Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2011) (1950 - 2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA_; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2011-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude - 2013

DOE Data Explorer

Andres, R. J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, G. [Appalachain State University, Boone, NC (United States)

1996-01-01

The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

NATURAL VOLATILE ORGANIC COMPOUND EMISSION RATE ESTIMATES FOR U.S. WOODLAND LANDSCAPES

EPA Science Inventory

Volatile organic compound (VOC) emission rate factors are estimated for 49 tree genera based on a review of foliar emission rate measurements. oliar VOC emissions are grouped into three categories: isoprene, monoterpenes and other VOC'S. ypical emission rates at a leaf temperatur...

Regional Variability and Uncertainty of Electric Vehicle Life Cycle CO₂ Emissions across the United States.

PubMed

Tamayao, Mili-Ann M; Michalek, Jeremy J; Hendrickson, Chris; Azevedo, Inês M L

2015-07-21

We characterize regionally specific life cycle CO2 emissions per mile traveled for plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) across the United States under alternative assumptions for regional electricity emission factors, regional boundaries, and charging schemes. We find that estimates based on marginal vs average grid emission factors differ by as much as 50% (using National Electricity Reliability Commission (NERC) regional boundaries). Use of state boundaries versus NERC region boundaries results in estimates that differ by as much as 120% for the same location (using average emission factors). We argue that consumption-based marginal emission factors are conceptually appropriate for evaluating the emissions implications of policies that increase electric vehicle sales or use in a region. We also examine generation-based marginal emission factors to assess robustness. Using these two estimates of NERC region marginal emission factors, we find the following: (1) delayed charging (i.e., starting at midnight) leads to higher emissions in most cases due largely to increased coal in the marginal generation mix at night; (2) the Chevrolet Volt has higher expected life cycle emissions than the Toyota Prius hybrid electric vehicle (the most efficient U.S. gasoline vehicle) across the U.S. in nearly all scenarios; (3) the Nissan Leaf BEV has lower life cycle emissions than the Prius in the western U.S. and in Texas, but the Prius has lower emissions in the northern Midwest regardless of assumed charging scheme and marginal emissions estimation method; (4) in other regions the lowest emitting vehicle depends on charge timing and emission factor estimation assumptions.

Estimates of reservoir methane emissions based on a spatially balanced probabilistic-survey

EPA Science Inventory

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; h...

Estimating nitrogen oxides emissions at city scale in China with a nightlight remote sensing model.

PubMed

Jiang, Jianhui; Zhang, Jianying; Zhang, Yangwei; Zhang, Chunlong; Tian, Guangming

2016-02-15

Increasing nitrogen oxides (NOx) emissions over the fast developing regions have been of great concern due to their critical associations with the aggravated haze and climate change. However, little geographically specific data exists for estimating spatio-temporal trends of NOx emissions. In order to quantify the spatial and temporal variations of NOx emissions, a spatially explicit approach based on the continuous satellite observations of artificial nighttime stable lights (NSLs) from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) was developed to estimate NOx emissions from the largest emission source of fossil fuel combustion. The NSL based model was established with three types of data including satellite data of nighttime stable lights, geographical data of administrative boundaries, and provincial energy consumptions in China, where a significant growth of NOx emission has experienced during three policy stages corresponding to the 9th-11th)Five-Year Plan (FYP, 1995-2010). The estimated national NOx emissions increased by 8.2% per year during the study period, and the total annual NOx emissions in China estimated by the NSL-based model were approximately 4.1%-13.8% higher than the previous estimates. The spatio-temporal variations of NOx emissions at city scale were then evaluated by the Moran's I indices. The global Moran's I indices for measuring spatial agglomerations of China's NOx emission increased by 50.7% during 1995-2010. Although the inland cities have shown larger contribution to the emission growth than the more developed coastal cities since 2005, the High-High clusters of NOx emission located in Beijing-Tianjin-Hebei regions, the Yangtze River Delta, and the Pearl River Delta should still be the major focus of NOx mitigation. Our results indicate that the readily available DMSP/OLS nighttime stable lights based model could be an easily accessible and effective tool for achieving strategic decision making toward NOx reduction. Copyright © 2015 Elsevier B.V. All rights reserved.

Aircraft-Based Measurements of Point Source Methane Emissions in the Barnett Shale Basin.

PubMed

Lavoie, Tegan N; Shepson, Paul B; Cambaliza, Maria O L; Stirm, Brian H; Karion, Anna; Sweeney, Colm; Yacovitch, Tara I; Herndon, Scott C; Lan, Xin; Lyon, David

2015-07-07

We report measurements of methane (CH4) emission rates observed at eight different high-emitting point sources in the Barnett Shale, Texas, using aircraft-based methods performed as part of the Barnett Coordinated Campaign. We quantified CH4 emission rates from four gas processing plants, one compressor station, and three landfills during five flights conducted in October 2013. Results are compared to other aircraft- and surface-based measurements of the same facilities, and to estimates based on a national study of gathering and processing facilities emissions and 2013 annual average emissions reported to the U.S. EPA Greenhouse Gas Reporting Program (GHGRP). For the eight sources, CH4 emission measurements from the aircraft-based mass balance approach were a factor of 3.2-5.8 greater than the GHGRP-based estimates. Summed emissions totaled 7022 ± 2000 kg hr(-1), roughly 9% of the entire basin-wide CH4 emissions estimated from regional mass balance flights during the campaign. Emission measurements from five natural gas management facilities were 1.2-4.6 times larger than emissions based on the national study. Results from this study were used to represent "super-emitters" in a newly formulated Barnett Shale Inventory, demonstrating the importance of targeted sampling of "super-emitters" that may be missed by random sampling of a subset of the total.

Airborne measurements of isoprene and monoterpene emissions from southeastern U.S. forests.

PubMed

Yu, Haofei; Guenther, Alex; Gu, Dasa; Warneke, Carsten; Geron, Chris; Goldstein, Allen; Graus, Martin; Karl, Thomas; Kaser, Lisa; Misztal, Pawel; Yuan, Bin

2017-10-01

Isoprene and monoterpene emission rates are essential inputs for atmospheric chemistry models that simulate atmospheric oxidant and particle distributions. Process studies of the biochemical and physiological mechanisms controlling these emissions are advancing our understanding and the accuracy of model predictions but efforts to quantify regional emissions have been limited by a lack of constraints on regional distributions of ecosystem emission capacities. We used an airborne wavelet-based eddy covariance measurement technique to characterize isoprene and monoterpene fluxes with high spatial resolution during the 2013 SAS (Southeast Atmosphere Study) in the southeastern United States. The fluxes measured by direct eddy covariance were comparable to emissions independently estimated using an indirect inverse modeling approach. Isoprene emission factors based on the aircraft wavelet flux estimates for high isoprene chemotypes (e.g., oaks) were similar to the MEGAN2.1 biogenic emission model estimates for landscapes dominated by oaks. Aircraft flux measurement estimates for landscapes with fewer isoprene emitting trees (e.g., pine plantations), were about a factor of two lower than MEGAN2.1 model estimates. The tendency for high isoprene emitters in these landscapes to occur in the shaded understory, where light dependent isoprene emissions are diminished, may explain the lower than expected emissions. This result demonstrates the importance of accurately representing the vertical profile of isoprene emitting biomass in biogenic emission models. Airborne measurement-based emission factors for high monoterpene chemotypes agreed with MEGAN2.1 in landscapes dominated by pine (high monoterpene chemotype) trees but were more than a factor of three higher than model estimates for landscapes dominated by oak (relatively low monoterpene emitting) trees. This results suggests that unaccounted processes, such as floral emissions or light dependent monoterpene emissions, or vegetation other than high monoterpene emitting trees may be an important source of monoterpene emissions in those landscapes and should be identified and included in biogenic emission models. Copyright © 2017 Elsevier B.V. All rights reserved.

Airborne measurements of isoprene and monoterpene emissions from southeastern U.S. forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Haofei; Guenther, Alex; Gu, Dasa

Isoprene and monoterpene emission rates are essential inputs for atmospheric chemistry models that simulate atmospheric oxidant and particle distributions. Process studies of the biochemical and physiological mechanisms controlling these emissions are advancing our understanding and the accuracy of model predictions but efforts to quantify regional emissions have been limited by a lack of constraints on regional distributions of ecosystem emission capacities. We used an airborne wavelet-based eddy covariance measurement technique to characterize isoprene and monoterpene fluxes with high spatial resolution during the 2013 SAS (Southeast Atmosphere Study) in the southeastern United States. The fluxes measured by direct eddy covariance weremore » comparable to emissions independently estimated using an indirect inverse modeling approach. Isoprene emission factors based on the aircraft wavelet flux estimates for high isoprene chemotypes (e.g., oaks) were similar to the MEGAN2.1 biogenic emission model estimates for landscapes dominated by oaks. Aircraft flux measurement estimates for landscapes with fewer isoprene emitting trees (e.g., pine plantations), were about a factor of two lower than MEGAN2.1 model estimates. The tendency for high isoprene emitters in these landscapes to occur in the shaded understory, where light dependent isoprene emissions are diminished, may explain the lower than expected emissions. This result demonstrates the importance of accurately representing the vertical profile of isoprene emitting biomass in biogenic emission models. Airborne measurement-based emission factors for high monoterpene chemotypes agreed with MEGAN2.1 in landscapes dominated by pine (high monoterpene chemotype) trees but were more than a factor of three higher than model estimates for landscapes dominated by oak (relatively low monoterpene emitting) trees. This results suggests that unaccounted processes, such as floral emissions or light dependent monoterpene emissions, or vegetation other than high monoterpene emitting trees may be an important source of monoterpene emissions in those landscapes and should be identified and included in biogenic emission models.« less

An intercomparison of biogenic emissions estimates from BEIS2 and BIOME: Reconciling the differences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilkinson, J.G.; Emigh, R.A.; Pierce, T.E.

1996-12-31

Biogenic emissions play a critical role in urban and regional air quality. For instance, biogenic emissions contribute upwards of 76% of the daily hydrocarbon emissions in the Atlanta, Georgia airshed. The Biogenic Emissions Inventory System-Version 2.0 (BEIS2) and the Biogenic Model for Emissions (BIOME) are two models that compute biogenic emissions estimates. BEIS2 is a FORTRAN-based system, and BIOME is an ARC/INFO{reg_sign} - and SAS{reg_sign}-based system. Although the technical formulations of the models are similar, the models produce different biogenic emissions estimates for what appear to be essentially the same inputs. The goals of our study are the following: (1)more » Determine why BIOME and BEIS2 produce different emissions estimates; (2) Attempt to understand the impacts that the differences have on the emissions estimates; (3) Reconcile the differences where possible; and (4) Present a framework for the use of BEIS2 and BIOME. In this study, we used the Coastal Oxidant Assessment for Southeast Texas (COAST) biogenics data which were supplied to us courtesy of the Texas Natural Resource Conservation Commission (TNRCC), and we extracted the BEIS2 data for the same domain. We compared the emissions estimates of the two models using their respective data sets BIOME Using TNRCC data and BEIS2 using BEIS2 data.« less

Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

NASA Astrophysics Data System (ADS)

Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

2015-12-01

One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

Black carbon emissions in Russia: A critical review

NASA Astrophysics Data System (ADS)

Evans, Meredydd; Kholod, Nazar; Kuklinski, Teresa; Denysenko, Artur; Smith, Steven J.; Staniszewski, Aaron; Hao, Wei Min; Liu, Liang; Bond, Tami C.

2017-08-01

This study presents a comprehensive review of estimated black carbon (BC) emissions in Russia from a range of studies. Russia has an important role regarding BC emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data on Russia's associated petroleum gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 688 Gg in 2014, with an uncertainty range 401 Gg-1453 Gg, while OC emissions are 9224 Gg with uncertainty ranging between 5596 Gg and 14,736 Gg. Wildfires dominated and contributed about 83% of the total BC emissions: however, the effect on radiative forcing is mitigated in part by OC emissions. We also present an adjusted estimate of Arctic forcing from Russia's BC and OC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.

Comparison of two U.S. power-plant carbon dioxide emissions data sets

USGS Publications Warehouse

Ackerman, K.V.; Sundquist, E.T.

2008-01-01

Estimates of fossil-fuel CO2 emissions are needed to address a variety of climate-change mitigation concerns over a broad range of spatial and temporal scales. We compared two data sets that report power-plant CO 2 emissions in the conterminous U.S. for 2004, the most recent year reported in both data sets. The data sets were obtained from the Department of Energy's Energy Information Administration (EIA) and the Environmental Protection Agency's eGRID database. Conterminous U.S. total emissions computed from the data sets differed by 3.5% for total plant emissions (electricity plus useful thermal output) and 2.3% for electricity generation only. These differences are well within previous estimates of uncertainty in annual U.S. fossil-fuel emissions. However, the corresponding average absolute differences between estimates of emissions from individual power plants were much larger, 16.9% and 25.3%, respectively. By statistical analysis, we identified several potential sources of differences between EIA and eGRID estimates for individual plants. Estimates that are based partly or entirely on monitoring of stack gases (reported by eGRID only) differed significantly from estimates based on fuel consumption (as reported by EIA). Differences in accounting methods appear to explain differences in estimates for emissions from electricity generation from combined heat and power plants, and for total and electricity generation emissions from plants that burn nonconventional fuels (e.g., biomass). Our analysis suggests the need for care in utilizing emissions data from individual power plants, and the need for transparency in documenting the accounting and monitoring methods used to estimate emissions.

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751 - 2009) (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marlad, Greg [Appalachian State University, Boone, NC (USA)

2012-01-01

The annual, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1751-2009 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2012) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Increasing efficiency of CO2 uptake by combined land-ocean sink

NASA Astrophysics Data System (ADS)

van Marle, M.; van Wees, D.; Houghton, R. A.; Nassikas, A.; van der Werf, G.

2017-12-01

Carbon-climate feedbacks are one of the key uncertainties in predicting future climate change. Such a feedback could originate from carbon sinks losing their efficiency, for example due to saturation of the CO2 fertilization effect or ocean warming. An indirect approach to estimate how the combined land and ocean sink responds to climate change and growing fossil fuel emissions is based on assessing the trends in the airborne fraction of CO2 emissions from fossil fuel and land use change. One key limitation with this approach has been the large uncertainty in quantifying land use change emissions. We have re-assessed those emissions in a more data-driven approach by combining estimates coming from a bookkeeping model with visibility-based land use change emissions available for the Arc of Deforestation and Equatorial Asia, two key regions with large land use change emissions. The advantage of the visibility-based dataset is that the emissions are observation-based and this dataset provides more detailed information about interannual variability than previous estimates. Based on our estimates we provide evidence that land use and land cover change emissions have increased more rapidly than previously thought, implying that the airborne fraction has decreased since the start of CO2 measurements in 1959. This finding is surprising because it means that the combined land and ocean sink has become more efficient while the opposite is expected.

Improving Large-scale Biomass Burning Carbon Consumption and Emissions Estimates in the Former Soviet Union based on Fire Weather

NASA Astrophysics Data System (ADS)

Westberg, D. J.; Soja, A. J.; Tchebakova, N.; Parfenova, E. I.; Kukavskaya, E.; de Groot, B.; McRae, D.; Conard, S. G.; Stackhouse, P. W., Jr.

2012-12-01

Estimating the amount of biomass burned during fire events is challenging, particularly in remote and diverse regions, like those of the Former Soviet Union (FSU). Historically, we have typically assumed 25 tons of carbon per hectare (tC/ha) is emitted, however depending on the ecosystem and severity, biomass burning emissions can range from 2 to 75 tC/ha. Ecosystems in the FSU span from the tundra through the taiga to the forest-steppe, steppe and desserts and include the extensive West Siberian lowlands, permafrost-lain forests and agricultural lands. Excluding this landscape disparity results in inaccurate emissions estimates and incorrect assumptions in the transport of these emissions. In this work, we present emissions based on a hybrid ecosystem map and explicit estimates of fuel that consider the depth of burning based on the Canadian Forest Fire Weather Index System. Specifically, the ecosystem map is a fusion of satellite-based data, a detailed ecosystem map and Alexeyev and Birdsey carbon storage data, which is used to build carbon databases that include the forest overstory and understory, litter, peatlands and soil organic material for the FSU. We provide a range of potential carbon consumption estimates for low- to high-severity fires across the FSU that can be used with fire weather indices to more accurately estimate fire emissions. These data can be incorporated at ecoregion and administrative territory scales and are optimized for use in large-scale Chemical Transport Models. Additionally, paired with future climate scenarios and ecoregion cover, these carbon consumption data can be used to estimate potential emissions.

ESTIMATION OF THE RATE OF VOC EMISSIONS FROM SOLVENT-BASED INDOOR COATING MATERIALS BASED ON PRODUCT FORMULATION

EPA Science Inventory

Two computational methods are proposed for estimation of the emission rate of volatile organic compounds (VOCs) from solvent-based indoor coating materials based on the knowledge of product formulation. The first method utilizes two previously developed mass transfer models with ...

Vapor saturation and accumulation in magmas of the 1989-1990 eruption of Redoubt Volcano, Alaska

USGS Publications Warehouse

Gerlach, Terrance M.; Westrich, Henry R.; Casadevall, Thomas J.; Finnegan, David L.

1994-01-01

The 1989–1990 eruption of Redoubt Volcano, Alaska, provided an opportunity to compare petrologic estimates of SO2 and Cl emissions with estimates of SO2 emissions based on remote sensing data and estimates of Cl emissions based on plume sampling. In this study, we measure the sulfur and chlorine contents of melt inclusions and matrix glasses in the eruption products to determine petrologic estimates of SO2 and Cl emissions. We compare the results with emission estimates based on COSPEC and TOMS data for SO2 and data for Cl/SO2 in plume samples. For the explosive vent clearing period (December 14–22, 1989), the petrologic estimate for SO2 emission is 21,000 tons, or ~12% of a TOMS estimate of 175,000 tons. For the dome growth period (December 22, 1989 to mid-June 1990), the petrologic estimate for SO2 emission is 18,000 tons, or ~3% of COSPEC-based estimates of 572,000–680,000 tons. The petrologic estimates give a total SO2 emission of only 39,000 tons compared to an integrated TOMS/COSPEC emission estimate of ~1,000,000 tons for the whole eruption, including quiescent degassing after mid-June 1990. Petrologic estimates also appear to underestimate Cl emissions, but apparent HCl scavenging in the plume complicates Cl emission comparisons. Several potential sources of ‘excess sulfur’ often invoked to explain petrologic SO2 deficits are concluded to be unlikely for the 1989–1990 Redoubt eruption — e.g., breakdown of sulfides, breakdown of anhydrite, release of SO2 from a hydrothermal system, degassing of commingled infusions of basalt in the magma chamber, and syn-eruptive degassing of sulfur from melt present in non-erupted magma. Leakage and/or diffusion of sulfur from melt inclusions do not provide convincing explanations for the petrologic SO2 deficits either. The main cause of low petrologic estimates for SO2 is that melt inclusions do not represent the total sulfur content of the Redoubt magmas, which were vapor-saturated magmas carrying most of their sulfur in an accumulated vapor phase. Almost all the sulfur of the SO2 emissions was present prior to emission as accumulated magmatic vapor at 6–10 km depth in the magma that supplied the eruption; whole-rock normalized concentrations of gaseous excess S in these magmas remained at ~0.2 wt.% throughout the eruption, equivalent to ~0.7 vol.% at depth. Data for CO2 emissions during the eruption indicate that CO2 at whole-rock concentrations of ~0.6 wt.% in the erupted magma was a key factor in creating the vapor saturation and accumulation condition making a vapor phase source of excess sulfur possible at depth. When explosive volcanism involves magma with accumulated vapor, melt inclusions do not provide a sufficient basis for predicting SO2 emissions. Thus, petrologic estimates made for SO2 emissions during explosive eruptions of the past may be too low and may significantly underestimate impacts on climate and the chemistry of the atmosphere.

Black carbon emissions in Russia: A critical review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evans, Meredydd; Kholod, Nazar; Kuklinski, Teresa

Russia has a particularly important role regarding black carbon (BC) emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. This study presents a comprehensive review of BC estimates from a range of studies. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data on Russian associated petroleummore » gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 689 Gg in 2014, with an uncertainty range between (407-1,416), while OC emissions are 9,228 Gg (with uncertainty between 5,595 and 14,728). Wildfires dominated and contributed about 83% of the total BC emissions, however the effect on radiative forcing is mitigated by OC emissions. We also present an adjusted estimate of Arctic forcing from Russian OC and BC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.« less

Fire and deforestation dynamics in Amazonia (1973-2014).

PubMed

van Marle, Margreet J E; Field, Robert D; van der Werf, Guido R; Estrada de Wagt, Ivan A; Houghton, Richard A; Rizzo, Luciana V; Artaxo, Paulo; Tsigaridis, Kostas

2017-01-01

Consistent long-term estimates of fire emissions are important to understand the changing role of fire in the global carbon cycle and to assess the relative importance of humans and climate in shaping fire regimes. However, there is limited information on fire emissions from before the satellite era. We show that in the Amazon region, including the Arc of Deforestation and Bolivia, visibility observations derived from weather stations could explain 61% of the variability in satellite-based estimates of bottom-up fire emissions since 1997 and 42% of the variability in satellite-based estimates of total column carbon monoxide concentrations since 2001. This enabled us to reconstruct the fire history of this region since 1973 when visibility information became available. Our estimates indicate that until 1987 relatively few fires occurred in this region and that fire emissions increased rapidly over the 1990s. We found that this pattern agreed reasonably well with forest loss data sets, indicating that although natural fires may occur here, deforestation and degradation were the main cause of fires. Compared to fire emissions estimates based on Food and Agricultural Organization's Global Forest and Resources Assessment data, our estimates were substantially lower up to the 1990s, after which they were more in line. These visibility-based fire emissions data set can help constrain dynamic global vegetation models and atmospheric models with a better representation of the complex fire regime in this region.

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2007) (V. 2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy, and Economics Appalachian State University Boone, NC 28608-2131 USA

2010-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2013.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996) for years prior to 1990 and a variable population distribution for later years (Andres et al. 2016). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production). The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Reconciling divergent estimates of oil and gas methane emissions

PubMed Central

Zavala-Araiza, Daniel; Lyon, David R.; Alvarez, Ramón A.; Davis, Kenneth J.; Harriss, Robert; Herndon, Scott C.; Karion, Anna; Kort, Eric Adam; Lamb, Brian K.; Lan, Xin; Marchese, Anthony J.; Pacala, Stephen W.; Robinson, Allen L.; Shepson, Paul B.; Sweeney, Colm; Talbot, Robert; Townsend-Small, Amy; Yacovitch, Tara I.; Zimmerle, Daniel J.; Hamburg, Steven P.

2015-01-01

Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency’s Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%. PMID:26644584

Comparing facility-level methane emission rate estimates at natural gas gathering and boosting stations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vaughn, Timothy L.; Bell, Clay S.; Yacovitch, Tara I.

Coordinated dual-tracer, aircraft-based, and direct component-level measurements were made at midstream natural gas gathering and boosting stations in the Fayetteville shale (Arkansas, USA). On-site component-level measurements were combined with engineering estimates to generate comprehensive facility-level methane emission rate estimates ('study on-site estimates (SOE)') comparable to tracer and aircraft measurements. Combustion slip (unburned fuel entrained in compressor engine exhaust), which was calculated based on 111 recent measurements of representative compressor engines, accounts for an estimated 75% of cumulative SOEs at gathering stations included in comparisons. Measured methane emissions from regenerator vents on glycol dehydrator units were substantially larger than predicted bymore » modelling software; the contribution of dehydrator regenerator vents to the cumulative SOE would increase from 1% to 10% if based on direct measurements. Concurrent measurements at 14 normally-operating facilities show relative agreement between tracer and SOE, but indicate that tracer measurements estimate lower emissions (regression of tracer to SOE = 0.91 (95% CI = 0.83-0.99), R2 = 0.89). Tracer and SOE 95% confidence intervals overlap at 11/14 facilities. Contemporaneous measurements at six facilities suggest that aircraft measurements estimate higher emissions than SOE. Aircraft and study on-site estimate 95% confidence intervals overlap at 3/6 facilities. The average facility level emission rate (FLER) estimated by tracer measurements in this study is 17-73% higher than a prior national study by Marchese et al.« less

Comparing facility-level methane emission rate estimates at natural gas gathering and boosting stations

DOE PAGES

Vaughn, Timothy L.; Bell, Clay S.; Yacovitch, Tara I.; ...

2017-02-09

Coordinated dual-tracer, aircraft-based, and direct component-level measurements were made at midstream natural gas gathering and boosting stations in the Fayetteville shale (Arkansas, USA). On-site component-level measurements were combined with engineering estimates to generate comprehensive facility-level methane emission rate estimates ('study on-site estimates (SOE)') comparable to tracer and aircraft measurements. Combustion slip (unburned fuel entrained in compressor engine exhaust), which was calculated based on 111 recent measurements of representative compressor engines, accounts for an estimated 75% of cumulative SOEs at gathering stations included in comparisons. Measured methane emissions from regenerator vents on glycol dehydrator units were substantially larger than predicted bymore » modelling software; the contribution of dehydrator regenerator vents to the cumulative SOE would increase from 1% to 10% if based on direct measurements. Concurrent measurements at 14 normally-operating facilities show relative agreement between tracer and SOE, but indicate that tracer measurements estimate lower emissions (regression of tracer to SOE = 0.91 (95% CI = 0.83-0.99), R2 = 0.89). Tracer and SOE 95% confidence intervals overlap at 11/14 facilities. Contemporaneous measurements at six facilities suggest that aircraft measurements estimate higher emissions than SOE. Aircraft and study on-site estimate 95% confidence intervals overlap at 3/6 facilities. The average facility level emission rate (FLER) estimated by tracer measurements in this study is 17-73% higher than a prior national study by Marchese et al.« less

Comparison of emission estimates for non-CO2 greenhouse gases from livestock and poultry in Korea from 1990 to 2010.

PubMed

Paik, Chunhyun; Chung, Yongjoo; Kim, Hugon; Kim, Young Jin

2016-04-01

It has often been claimed that non-carbon dioxide greenhouse gases (NCGGs), such as methane, nitrous oxide and fluorinated greenhouse gases, are significant contributors to climate change. Here we nvestigate emission estimates of methane and nitrous oxide from livestock and poultry production, which is recognized as a major source of those NCGGs, in Korea over the period of 1990 through 2010. Based on the data on livestock and poultry populations, emission estimates of methane and nitrous oxide are first derived based on the Tier 1 approach. Then, the Tier 2 approach is adopted to obtain emission estimates of methane and nitrous oxide from cattle, which are known to be the largest sources of these NCGGs and account for about 70% of emissions from livestock and poultry in Korea. The result indicates that the Tier 2 estimates of methane and nitrous oxide emissions from enteric fermentation and manure management are significantly different from the Tier 1 estimates over the analysis period. © 2015 Japanese Society of Animal Science.

A statistical approach to determining the uncertainty in power-law model estimates of emissions based on time-dependent chamber concentration measurements

EPA Science Inventory

The use of models for estimating emissions from products beyond the timeframe of an emissions test is a means of managing the time and expenses associated with product emissions certification. This paper presents a discussion of (1) the impact of uncertainty in test chamber emiss...

Black carbon emissions in Russia: A critical review

DOE PAGES

Evans, Meredydd; Kholod, Nazar; Kuklinski, Teresa; ...

2017-05-18

Here, this study presents a comprehensive review of estimated black carbon (BC) emissions in Russia from a range of studies. Russia has an important role regarding BC emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data onmore » Russia's associated petroleum gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 688 Gg in 2014, with an uncertainty range 401 Gg-1453 Gg, while OC emissions are 9224 Gg with uncertainty ranging between 5596 Gg and 14,736 Gg. Wildfires dominated and contributed about 83% of the total BC emissions: however, the effect on radiative forcing is mitigated in part by OC emissions. We also present an adjusted estimate of Arctic forcing from Russia's BC and OC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.« less

Black carbon emissions in Russia: A critical review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evans, Meredydd; Kholod, Nazar; Kuklinski, Teresa

Here, this study presents a comprehensive review of estimated black carbon (BC) emissions in Russia from a range of studies. Russia has an important role regarding BC emissions given the extent of its territory above the Arctic Circle, where BC emissions have a particularly pronounced effect on the climate. We assess underlying methodologies and data sources for each major emissions source based on their level of detail, accuracy and extent to which they represent current conditions. We then present reference values for each major emissions source. In the case of flaring, the study presents new estimates drawing on data onmore » Russia's associated petroleum gas and the most recent satellite data on flaring. We also present estimates of organic carbon (OC) for each source, either based on the reference studies or from our own calculations. In addition, the study provides uncertainty estimates for each source. Total BC emissions are estimated at 688 Gg in 2014, with an uncertainty range 401 Gg-1453 Gg, while OC emissions are 9224 Gg with uncertainty ranging between 5596 Gg and 14,736 Gg. Wildfires dominated and contributed about 83% of the total BC emissions: however, the effect on radiative forcing is mitigated in part by OC emissions. We also present an adjusted estimate of Arctic forcing from Russia's BC and OC emissions. In recent years, Russia has pursued policies to reduce flaring and limit particulate emissions from on-road transport, both of which appear to significantly contribute to the lower emissions and forcing values found in this study.« less

How to estimate green house gas (GHG) emissions from an excavator by using CAT's performance chart

NASA Astrophysics Data System (ADS)

Hajji, Apif M.; Lewis, Michael P.

2017-09-01

Construction equipment activities are a major part of many infrastructure projects. This type of equipment typically releases large quantities of green house gas (GHG) emissions. GHG emissions may come from fuel consumption. Furthermore, equipment productivity affects the fuel consumption. Thus, an estimating tool based on the construction equipment productivity rate is able to accurately assess the GHG emissions resulted from the equipment activities. This paper proposes a methodology to estimate the environmental impact for a common construction activity. This paper delivers sensitivity analysis and a case study for an excavator based on trench excavation activity. The methodology delivered in this study can be applied to a stand-alone model, or a module that is integrated with other emissions estimators. The GHG emissions are highly correlated to diesel fuel use, which is approximately 10.15 kilograms (kg) of CO2 per gallon of diesel fuel. The results showed that the productivity rate model as the result from multiple regression analysis can be used as the basis for estimating GHG emissions, and also as the framework for developing emissions footprint and understanding the environmental impact from construction equipment activities introduction.

One decade of space-based isoprene emission estimates: Interannual variations and emission trends between 2005 and 2014

NASA Astrophysics Data System (ADS)

Bauwens, Maite; Stavrakou, Trissevgeni; Müller, Jean-François; De Smedt, Isabelle; Van Roozendael, Michel

2016-04-01

Isoprene is one of the most largely emitted hydrocarbons in the atmosphere, with global annual emissions estimated at about 500 Tg, but with large uncertainties (Arneth et al., 2011). Here we use the source inversion approach to derive top-down biogenic isoprene emission estimates for the period between 2005 and 2014 constrained by formaldehyde observations, a high-yield intermediate in the oxidation of isoprene in the atmosphere. Formaldehyde columns retrieved from the Ozone Monitoring Instrument (OMI) are used to constrain the IMAGESv2 global chemistry-transport model and its adjoint code (Stavrakou et al., 2009). The MEGAN-MOHYCAN isoprene emissions (Stavrakou et al., 2014) are used as bottom-up inventory in the model. The inversions are performed separately for each year of the study period, and monthly emissions are derived for every model grid cell. The inversion results are compared to independent isoprene emissions from GUESS-ES (Arneth et al., 2007) and MEGAN-MACC (Sinderalova et al., 2014) and to top-down fluxes based on GOME-2 formaldehyde columns (Bauwens et al., 2014; Stavrakou et al., 2015). The mean global annual OMI-based isoprene flux for the period 2005-2014 is estimated to be 270 Tg, with small interannual variation. This estimate is by 20% lower with regard to the a priori inventory on average, but on the regional scale strong emission updates are inferred. The OMI-based emissions are substantially lower than the MEGAN-MACC and the GUESS-ES inventory, but agree well with the isoprene fluxes constrained by GOME-2 formaldehyde columns. Strong emission reductions are derived over tropical regions. The seasonal pattern of isoprene emissions is generally well preserved after inversion and relatively consistent with other inventories, lending confidence to the MEGAN parameterization of the a priori inventory. In boreal regions the isoprene emission trend is positive and reinforced after inversion, whereas the inversion suggests negative trends in the rainforests of Equatorial Africa and South America. The top-down isoprene fluxes are available at a resolution of 0.5°x0.5° between 2005 and 2014 at the GlobEmission website (http://www.globemission.eu). References: Arneth, A., et al.: Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO 2-isoprene interaction, Atmos. Chem. Phys., 7(1), 31-53, 2007. Arneth, A., et al.: Global terrestrial isoprene emission models: sensitivity to variability in climate and vegetation, Atmos. Chem. Phys., 11(15), 8037-8052, 2011. Bauwens, M., et al.: Satellite-based isoprene emission estimates (2007-2012) from the GlobEmission project, in ACCENT-Plus Symposium 2013 Proceedings., 2014. Stavrakou, T., et al.: Isoprene emissions over Asia 1979 - 2012: impact of climate and land-use changes, Atmos. Chem. Phys., 14(9), 4587-4605, doi:10.5194/acp-14-4587-2014, 2014. Stavrakou, T., et al.: How consistent are top-down hydrocarbon emissions based on formaldehyde observations from GOME-2 and OMI?, Atmos. Chem. Phys., 15(20), 11861-11884, doi:10.5194/acp-15-11861-2015, 2015. Stavrakou, T., et al.: Evaluating the performance of pyrogenic and biogenic emission inventories against one decade of space-based formaldehyde columns, Atmos. Chem. Phys., 9(3), 1037-1060, doi:10.5194/acp-9-1037-2009, 2009.

SEASONAL NH3 EMISSION ESTIMATES FOR THE EASTERN UNITED STATES BASED ON AMMONIUM WET CONCENTRATIONS AND AN INVERSE MODELING METHOD

EPA Science Inventory

Significant uncertainty exists in the magnitude and variability of ammonia (NH3) emissions. NH3 emissions are needed as input for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3 emissions are estimated to come from agricultural ...

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

Estimating fire severity and carbon emissions over Australian tropical savannas based on passive microwave satellite observations

NASA Astrophysics Data System (ADS)

Chen, X.; Liu, Y.; Evans, J. P.; Parinussa, R.

2017-12-01

Carbon emissions from large-scale fire activity over the Australian tropical savannas have strong inter-annual variability, due mainly to variations in fuel accumulation in response to rainfall. We investigated the use of a recently developed satellite-based vegetation optical depth (VOD) dataset to estimate fire severity and carbon emission. VOD is sensitive to the dynamics of all aboveground vegetation and available nearly every two days. For areas burned during 2003 - 2010, we calculated the VOD change (ΔVOD) pre- and post-fire and the associated loss in above ground biomass carbon. Both results compare well with widely-accepted approaches: ΔVOD agreed well with the Normalized Burn Ratio change (ΔNBR) and carbon loss with modelled emissions from the Global Fire Emissions Database (GFED). We found that the ΔVOD and ΔNBR are generally linearly related. The Pearson correlation coefficients (R) between VOD- and GFED-based fire carbon emissions for monthly and annual total estimates are very high, 0.92 and 0.96 respectively. A key feature of fire carbon emissions is the strong inter-annual variation, ranging from 21.1 million tonnes in 2010 to 84.3 million tonnes in 2004. This study demonstrates that a reasonable estimate of fire carbon emissions can be achieved in a timely manner based on multiple satellite observations over the regions where the emissions are primarily from aboveground vegetation loss, which can be complementary to the currently used approaches.

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950-2008) (V. 2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2011-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2015)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA)

2015-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2010) (V. 2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2013-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2009) (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2012-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree latitude by One Degree Longitude (V. 2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA).

2013-01-01

The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Fire and deforestation dynamics in Amazonia (1973–2014)

PubMed Central

Field, Robert D.; van der Werf, Guido R.; Estrada de Wagt, Ivan A.; Houghton, Richard A.; Rizzo, Luciana V.; Artaxo, Paulo; Tsigaridis, Kostas

2017-01-01

Abstract Consistent long‐term estimates of fire emissions are important to understand the changing role of fire in the global carbon cycle and to assess the relative importance of humans and climate in shaping fire regimes. However, there is limited information on fire emissions from before the satellite era. We show that in the Amazon region, including the Arc of Deforestation and Bolivia, visibility observations derived from weather stations could explain 61% of the variability in satellite‐based estimates of bottom‐up fire emissions since 1997 and 42% of the variability in satellite‐based estimates of total column carbon monoxide concentrations since 2001. This enabled us to reconstruct the fire history of this region since 1973 when visibility information became available. Our estimates indicate that until 1987 relatively few fires occurred in this region and that fire emissions increased rapidly over the 1990s. We found that this pattern agreed reasonably well with forest loss data sets, indicating that although natural fires may occur here, deforestation and degradation were the main cause of fires. Compared to fire emissions estimates based on Food and Agricultural Organization's Global Forest and Resources Assessment data, our estimates were substantially lower up to the 1990s, after which they were more in line. These visibility‐based fire emissions data set can help constrain dynamic global vegetation models and atmospheric models with a better representation of the complex fire regime in this region. PMID:28286373

An evaluation of the uncertainties in biomass burning emissions

NASA Astrophysics Data System (ADS)

Yano, A.; Garcia Menendez, F.; Hu, Y.; Odman, M.

2012-12-01

The contribution of biomass burning emissions to the atmospheric loads of gases and aerosols can lead to major air quality problems and have significant climate impacts. Whether from wildfires, natural or human-induced, or controlled burns, biomass burning emissions are an important source of air pollutants regionally in certain parts of the world as well as globally. There are two common ways of estimating biomass burning emissions: by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels and their consumption amounts, and the progression of the fire, ground-based estimation is preferred. For controlled burns a.k.a. prescribed burns and wildfires in places where land management is practiced to a certain extent there is typically sufficient ground-based information for emissions estimation. However, for remote regions where no ground-based information is available on the size, intensity, or the spread of the fire, estimates based on satellite observations are preferred. For example, burn location, size and timing information can be obtained from satellite retrievals of thermal anomalies and fuel loading information can be obtained from satellite products of vegetation cover. In both cases, reasonable emission estimates for a variety of pollutants can be obtained by using emission factors (mass of pollutant released per unit mass of fuel consumed) derived from field or laboratory studies. Here, emissions from a controlled burn and a wildfire are estimated using both ground-based information and satellite observations. The controlled burn was conducted on 17 November 2009 near Santa Barbara, California over 80 ha of land covered with chaparral. An aircraft tracked the smoke plume and measured CO2, light scattering, as well as meteorological parameters during the burn (Akagi et al., 2011). The wildfire is from the summer of 2008 when tens of thousands hectares of wild land burned in Northern California causing unprecedented damage. NASA Aircraft commissioned for the ARCTAS campaign at the time flew over the fires and collected data detailing composition of gases and aerosols in the fire plumes (Singh et al., 2012). We model the fires using a newly developed system consisting of a plume rise and dispersion model specifically designed for wild-land fire plumes (Daysmoke; Achtemeier et al., 2011) coupled with a regional-scale chemistry-transport model (CMAQ). Wind fields generated by a weather prediction model (WRF) are adjusted locally to match the aircraft measurements of wind speed and direction. The fires are simulated using both ground-based and satellite-based estimates of emissions. Predicted concentrations of gases and aerosols are compared to corresponding aircraft measurements. Satellite retrievals of aerosol optical depth are also used in evaluating model predictions. The new modeling system along with the wind adjustments reduces several of the uncertainties inherent to regional-scale modeling of plume transport. This allows for a more reliable analysis of the uncertainties related to emissions. Uncertainties in the magnitudes and timings of emissions, and in plume injection heights with respect to boundary layer heights are investigated. Uncertainties associated with ground-based and satellite-based emissions estimation methods are compared to each other.

Impact of the Volkswagen emissions control defeat device on US public health

NASA Astrophysics Data System (ADS)

Barrett, Steven R. H.; Speth, Raymond L.; Eastham, Sebastian D.; Dedoussi, Irene C.; Ashok, Akshay; Malina, Robert; Keith, David W.

2015-11-01

The US Environmental Protection Agency (EPA) has alleged that Volkswagen Group of America (VW) violated the Clean Air Act (CAA) by developing and installing emissions control system ‘defeat devices’ (software) in model year 2009-2015 vehicles with 2.0 litre diesel engines. VW has admitted the inclusion of defeat devices. On-road emissions testing suggests that in-use NOx emissions for these vehicles are a factor of 10 to 40 above the EPA standard. In this paper we quantify the human health impacts and associated costs of the excess emissions. We propagate uncertainties throughout the analysis. A distribution function for excess emissions is estimated based on available in-use NOx emissions measurements. We then use vehicle sales data and the STEP vehicle fleet model to estimate vehicle distance traveled per year for the fleet. The excess NOx emissions are allocated on a 50 km grid using an EPA estimate of the light duty diesel vehicle NOx emissions distribution. We apply a GEOS-Chem adjoint-based rapid air pollution exposure model to produce estimates of particulate matter and ozone exposure due to the spatially resolved excess NOx emissions. A set of concentration-response functions is applied to estimate mortality and morbidity outcomes. Integrated over the sales period (2008-2015) we estimate that the excess emissions will cause 59 (95% CI: 10 to 150) early deaths in the US. When monetizing premature mortality using EPA-recommended data, we find a social cost of ˜450m over the sales period. For the current fleet, we estimate that a return to compliance for all affected vehicles by the end of 2016 will avert ˜130 early deaths and avoid ˜840m in social costs compared to a counterfactual case without recall.

Estimates of air emissions from asphalt storage tanks and truck loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trumbore, D.C.

1999-12-31

Title V of the 1990 Clean Air Act requires the accurate estimation of emissions from all US manufacturing processes, and places the burden of proof for that estimate on the process owner. This paper is published as a tool to assist in the estimation of air emission from hot asphalt storage tanks and asphalt truck loading operations. Data are presented on asphalt vapor pressure, vapor molecular weight, and the emission split between volatile organic compounds and particulate emissions that can be used with AP-42 calculation techniques to estimate air emissions from asphalt storage tanks and truck loading operations. Since currentmore » AP-42 techniques are not valid in asphalt tanks with active fume removal, a different technique for estimation of air emissions in those tanks, based on direct measurement of vapor space combustible gas content, is proposed. Likewise, since AP-42 does not address carbon monoxide or hydrogen sulfide emissions that are known to be present in asphalt operations, this paper proposes techniques for estimation of those emissions. Finally, data are presented on the effectiveness of fiber bed filters in reducing air emissions in asphalt operations.« less

Residual effects of fertilization history increase nitrous oxide emissions from zero-N controls:Implications for estimating fertilizer-induced emission factors

USDA-ARS?s Scientific Manuscript database

Agricultural N fertilization is the dominant driver of increasing atmospheric nitrous oxide (N2O) concentrations over the past half century, yet there is considerable uncertainty in estimates of N2O emissions from agriculture. Such estimates are typically based on the amount of N applied and a ferti...

Comparison of flexible fuel vehicle and life-cycle fuel consumption and emissions of selected pollutants and greenhouse gases for ethanol 85 versus gasoline.

PubMed

Zhai, Haibo; Frey, H Christopher; Rouphail, Nagui M; Gonçalves, Gonçalo A; Farias, Tiago L

2009-08-01

The objective of this research is to evaluate differences in fuel consumption and tailpipe emissions of flexible fuel vehicles (FFVs) operated on ethanol 85 (E85) versus gasoline. Theoretical ratios of fuel consumption and carbon dioxide (CO2) emissions for both fuels are estimated based on the same amount of energy released. Second-by-second fuel consumption and emissions from one FFV Ford Focus fueled with E85 and gasoline were measured under real-world traffic conditions in Lisbon, Portugal, using a portable emissions measurement system (PEMS). Cycle average dynamometer fuel consumption and emission test results for FFVs are available from the U.S. Department of Energy, and emissions certification test results for ethanol-fueled vehicles are available from the U.S. Environmental Protection Agency. On the basis of the PEMS data, vehicle-specific power (VSP)-based modal average fuel and emission rates for both fuels are estimated. For E85 versus gasoline, empirical ratios of fuel consumption and CO2 emissions agree within a margin of error to the theoretical expectations. Carbon monoxide (CO) emissions were found to be typically lower. From the PEMS data, nitric oxide (NO) emissions associated with some higher VSP modes are higher for E85. From the dynamometer and certification data, average hydrocarbon (HC) and nitrogen oxides (NOx) emission differences vary depending on the vehicle. The differences of average E85 versus gasoline emission rates for all vehicle models are -22% for CO, 12% for HC, and -8% for NOx emissions, which imply that replacing gasoline with E85 reduces CO emissions, may moderately decrease NOx tailpipe emissions, and may increase HC tailpipe emissions. On a fuel life cycle basis for corn-based ethanol versus gasoline, CO emissions are estimated to decrease by 18%. Life-cycle total and fossil CO2 emissions are estimated to decrease by 25 and 50%, respectively; however, life-cycle HC and NOx emissions are estimated to increase by 18 and 82%, respectively.

Estimating global nitrous oxide emissions by lichens and bryophytes with a process-based productivity model

NASA Astrophysics Data System (ADS)

Porada, Philipp; Pöschl, Ulrich; Kleidon, Axel; Beer, Christian; Weber, Bettina

2017-03-01

Nitrous oxide is a strong greenhouse gas and atmospheric ozone-depleting agent which is largely emitted by soils. Recently, lichens and bryophytes have also been shown to release significant amounts of nitrous oxide. This finding relies on ecosystem-scale estimates of net primary productivity of lichens and bryophytes, which are converted to nitrous oxide emissions by empirical relationships between productivity and respiration, as well as between respiration and nitrous oxide release. Here we obtain an alternative estimate of nitrous oxide emissions which is based on a global process-based non-vascular vegetation model of lichens and bryophytes. The model quantifies photosynthesis and respiration of lichens and bryophytes directly as a function of environmental conditions, such as light and temperature. Nitrous oxide emissions are then derived from simulated respiration assuming a fixed relationship between the two fluxes. This approach yields a global estimate of 0.27 (0.19-0.35) (Tg N2O) year-1 released by lichens and bryophytes. This is lower than previous estimates but corresponds to about 50 % of the atmospheric deposition of nitrous oxide into the oceans or 25 % of the atmospheric deposition on land. Uncertainty in our simulated estimate results from large variation in emission rates due to both physiological differences between species and spatial heterogeneity of climatic conditions. To constrain our predictions, combined online gas exchange measurements of respiration and nitrous oxide emissions may be helpful.

Estimating PM2.5-associated mortality increase in California due to the Volkswagen emission control defeat device

NASA Astrophysics Data System (ADS)

Wang, Tianyang; Jerrett, Michael; Sinsheimer, Peter; Zhu, Yifang

2016-11-01

The Volkswagen Group of America (VW) was found by the US Environmental Protection Agency (EPA) and the California Air Resources Board (CARB) to have installed "defeat devices" and emit more oxides of nitrogen (NOx) than permitted under current EPA standards. In this paper, we quantify the hidden NOx emissions from this so-called VW scandal and the resulting public health impacts in California. The NOx emissions are calculated based on VW road test data and the CARB Emission Factors (EMFAC) model. Cumulative hidden NOx emissions from 2009 to 2015 were estimated to be over 3500 tons. Adult mortality changes were estimated based on ambient fine particulate matter (PM2.5) change due to secondary nitrate formation and the related concentration-response functions. We estimated that hidden NOx emissions from 2009 to 2015 have resulted in a total of 12 PM2.5-associated adult mortality increases in California. Most of the mortality increase happened in metropolitan areas, due to their high population and vehicle density.

Direct Top-down Estimates of Biomass Burning CO Emissions Using TES and MOPITT Versus Bottom-up GFED Inventory

NASA Technical Reports Server (NTRS)

Pechony, Olga; Shindell, Drew T.; Faluvegi, Greg

2013-01-01

In this study, we utilize near-simultaneous observations from two sets of multiple satellite sensors to segregate Tropospheric Emission Spectrometer (TES) and Measurements of Pollution in the Troposphere (MOPITT) CO observations over active fire sources from those made over clear background. Hence, we obtain direct estimates of biomass burning CO emissions without invoking inverse modeling as in traditional top-down methods. We find considerable differences between Global Fire Emissions Database (GFED) versions 2.1 and 3.1 and satellite-based emission estimates in many regions. Both inventories appear to greatly underestimate South and Southeast Asia emissions, for example. On global scales, however, CO emissions in both inventories and in the MOPITT-based analysis agree reasonably well, with the largest bias (30%) found in the Northern Hemisphere spring. In the Southern Hemisphere, there is a one-month shift between the GFED and MOPITT-based fire emissions peak. Afternoon tropical fire emissions retrieved from TES are about two times higher than the morning MOPITT retrievals. This appears to be both a real difference due to the diurnal fire activity variations, and a bias due to the scarcity of TES data.

Estimating Agricultural Nitrous Oxide Emissions

USDA-ARS?s Scientific Manuscript database

Nitrous oxide emissions are highly variable in space and time and different methodologies have not agreed closely, especially at small scales. However, as scale increases, so does the agreement between estimates based on soil surface measurements (bottom up approach) and estimates derived from chang...

Quantifying atmospheric pollutant emissions from open biomass burning with multiple methods: a case study for Yangtze River Delta region, China

NASA Astrophysics Data System (ADS)

Yang, Y.; Zhao, Y.

2017-12-01

To understand the differences and their origins of emission inventories based on various methods for the source, emissions of PM10, PM2.5, OC, BC, CH4, VOCs, CO, CO2, NOX, SO2 and NH3 from open biomass burning (OBB) in Yangtze River Delta (YRD) are calculated for 2005-2012 using three (bottom-up, FRP-based and constraining) approaches. The inter-annual trends in emissions with FRP-based and constraining methods are similar with the fire counts in 2005-2012, while that with bottom-up method is different. For most years, emissions of all species estimated with constraining method are smaller than those with bottom-up method (except for VOCs), while they are larger than those with FRP-based (except for EC, CH4 and NH3). Such discrepancies result mainly from different masses of crop residues burned in the field (CRBF) estimated in the three methods. Among the three methods, the simulated concentrations from chemistry transport modeling with the constrained emissions are the closest to available observations, implying the result from constraining method is the best estimation for OBB emissions. CO emissions in the three methods are compared with other studies. Similar temporal variations were found for the constrained emissions, FRP-based emissions, GFASv1.0 and GFEDv4.1s, with the largest and the lowest emissions estimated for 2012 and 2006, respectively. The constrained CO emissions in this study are smaller than those in other studies based on bottom-up method and larger than those based on burned area and FRP derived from satellite. The contributions of OBB to two particulate pollution events in 2010 and 2012 are analyzed with the brute-force method. The average contribution of OBB to PM10 mass concentrations in June 8-14 2012 was estimated at 38.9% (74.8 μg m-3), larger than that in June 17-24, 2010 at 23.6 % (38.5 μg m-3). Influences of diurnal curves and meteorology on air pollution caused by OBB are also evaluated, and the results suggest that air pollution caused by OBB will become heavier if the meteorological conditions are unfavorable, and that more attention should be paid to the supervision in night. Quantified with the Monte-Carlo simulation, the uncertainties of OBB emissions with constraining method are significantly lower than those with bottom-up or FRP-based methods.

Estimation of Pre-industrial Nitrous Oxide Emission from the Terrestrial Biosphere

NASA Astrophysics Data System (ADS)

Xu, R.; Tian, H.; Lu, C.; Zhang, B.; Pan, S.; Yang, J.

2015-12-01

Nitrous oxide (N2O) is currently the third most important greenhouse gases (GHG) after methane (CH4) and carbon dioxide (CO2). Global N2O emission increased substantially primarily due to reactive nitrogen (N) enrichment through fossil fuel combustion, fertilizer production, and legume crop cultivation etc. In order to understand how climate system is perturbed by anthropogenic N2O emissions from the terrestrial biosphere, it is necessary to better estimate the pre-industrial N2O emissions. Previous estimations of natural N2O emissions from the terrestrial biosphere range from 3.3-9.0 Tg N2O-N yr-1. This large uncertainty in the estimation of pre-industrial N2O emissions from the terrestrial biosphere may be caused by uncertainty associated with key parameters such as maximum nitrification and denitrification rates, half-saturation coefficients of soil ammonium and nitrate, N fixation rate, and maximum N uptake rate. In addition to the large estimation range, previous studies did not provide an estimate on preindustrial N2O emissions at regional and biome levels. In this study, we applied a process-based coupled biogeochemical model to estimate the magnitude and spatial patterns of pre-industrial N2O fluxes at biome and continental scales as driven by multiple input data, including pre-industrial climate data, atmospheric CO2 concentration, N deposition, N fixation, and land cover types and distributions. Uncertainty associated with key parameters is also evaluated. Finally, we generate sector-based estimates of pre-industrial N2O emission, which provides a reference for assessing the climate forcing of anthropogenic N2O emission from the land biosphere.

Community-LINE Source Model (C-LINE) to estimate roadway emissions

EPA Pesticide Factsheets

C-LINE is a web-based model that estimates emissions and dispersion of toxic air pollutants for roadways in the U.S. This reduced-form air quality model examines what-if scenarios for changes in emissions such as traffic volume fleet mix and vehicle speed.

Crop moisture estimation over the southern Great Plains with dual polarization 1.66 centimeter passive microwave data from Nimbus 7

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.; Harder, P. H., II; Wilke, G. D.; Huebner, G. L., Jr.

1984-01-01

Moisture content of snow-free, unfrozen soil is inferred using passive microwave brightness temperatures from the scanning multichannel microwave radiometer (SMMR) on Nimbus-7. Investigation is restricted to the two polarizations of the 1.66 cm wavelength sensor. Passive microwave estimates of soil moisture are of two basic categories; those based upon soil emissivity and those based upon the polarization of soil emission. The two methods are compared and contrasted through the investigation of 54 potential functions of polarized brightness temperatures and, in some cases, ground-based temperature measurements. Of these indices, three are selected for the estimated emissivity, the difference between polarized brightness temperatures, and the normalized polarization difference. Each of these indices is about equally effective for monitoring soil moisture. Using an antecedent precipitation index (API) as ground control data, temporal and spatial analyses show that emissivity data consistently give slightly better soil moisture estimates than depolarization data. The difference, however, is not statistically significant. It is concluded that polarization data alone can provide estimates of soil moisture in areas where the emissivity cannot be inferred due to nonavailability of surface temperature data.

Comparison of models used for national agricultural ammonia emission inventories in Europe: Litter-based manure systems

NASA Astrophysics Data System (ADS)

Reidy, B.; Webb, J.; Misselbrook, T. H.; Menzi, H.; Luesink, H. H.; Hutchings, N. J.; Eurich-Menden, B.; Döhler, H.; Dämmgen, U.

Six N-flow models, used to calculate national ammonia (NH 3) emissions from agriculture in different European countries, were compared using standard data sets. Scenarios for litter-based systems were run separately for beef cattle and for broilers, with three different levels of model standardisation: (a) standardized inputs to all models (FF scenario); (b) standard N excretion, but national values for emission factors (EFs) (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario for beef cattle produced very similar estimates of total losses of total ammoniacal-N (TAN) (±6% of the mean total), but large differences in NH 3 emissions (±24% of the mean). These differences arose from the different approaches to TAN immobilization in litter, other N losses and mineralization in the models. As a result of those differences estimates of TAN available at spreading differed by a factor of almost 3. Results of the FF scenario for broilers produced a range of estimates of total changes in TAN (±9% of the mean total), and larger differences in the estimate of NH 3 emissions (±17% of the mean). The different approaches among the models to TAN immobilization, other N losses and mineralization, produced estimates of TAN available at spreading which differed by a factor of almost 1.7. The differences in estimates of NH 3 emissions decreased as estimates of immobilization and other N losses increased. Since immobilization and denitrification depend also on the C:N ratio in manure, there would be advantages to include C flows in mass-flow models. This would also provide an integrated model for the estimation of emissions of methane, non-methane VOCs and carbon dioxide. Estimation of these would also enable an estimate of mass loss, calculation of the N and TAN concentrations in litter-based manures and further validation of model outputs.

Life cycle inventory energy consumption and emissions for biodiesel versus petroleum diesel fueled construction vehicles.

PubMed

Pang, Shih-Hao; Frey, H Christopher; Rasdorf, William J

2009-08-15

Substitution of soy-based biodiesel fuels for petroleum diesel will alter life cycle emissions for construction vehicles. A life cycle inventory was used to estimate fuel cycle energy consumption and emissions of selected pollutants and greenhouse gases. Real-world measurements using a portable emission measurement system (PEMS) were made forfive backhoes, four front-end loaders, and six motor graders on both fuels from which fuel consumption and tailpipe emission factors of CO, HC, NO(x), and PM were estimated. Life cycle fossil energy reductions are estimated it 9% for B20 and 42% for B100 versus petroleum diesel based on the current national energy mix. Fuel cycle emissions will contribute a larger share of total life cycle emissions as new engines enter the in-use fleet. The average differences in life cycle emissions for B20 versus diesel are: 3.5% higher for NO(x); 11.8% lower for PM, 1.6% higher for HC, and 4.1% lower for CO. Local urban tailpipe emissions are estimated to be 24% lower for HC, 20% lower for CO, 17% lower for PM, and 0.9% lower for NO(x). Thus, there are environmental trade-offs such as for rural vs urban areas. The key sources of uncertainty in the B20 LCI are vehicle emission factors.

Discrepancies and Uncertainties in Bottom-up Gridded Inventories of Livestock Methane Emissions for the Contiguous United States

NASA Astrophysics Data System (ADS)

Randles, C. A.; Hristov, A. N.; Harper, M.; Meinen, R.; Day, R.; Lopes, J.; Ott, T.; Venkatesh, A.

2017-12-01

In this analysis we used a spatially-explicit, bottom-up approach, based on animal inventories, feed intake, and feed intake-based emission factors to estimate county-level enteric (cattle) and manure (cattle, swine, and poultry) livestock methane emissions for the contiguous United States. Combined enteric and manure emissions were highest for counties in California's Central Valley. Overall, this analysis yielded total livestock methane emissions (8,916 Gg/yr; lower and upper bounds of 6,423 and 11,840 Gg/yr, respectively) for 2012 that are comparable to the current USEPA estimates for 2012 (9,295 Gg/yr) and to estimates from the global gridded Emission Database for Global Atmospheric Research (EDGAR) inventory (8,728 Gg/yr), used previously in a number of top-down studies. However, the spatial distribution of emissions developed in this analysis differed significantly from that of EDGAR. As an example, methane emissions from livestock in Texas and California (highest contributors to the national total) in this study were 36% lesser and 100% greater, respectively, than estimates by EDGAR. Thespatial distribution of emissions in gridded inventories (e.g., EDGAR) likely strongly impacts the conclusions of top-down approaches that use them, especially in the source attribution of resulting (posterior) emissions, and hence conclusions from such studies should be interpreted with caution.

Revised spatially distributed global livestock emissions

NASA Astrophysics Data System (ADS)

Asrar, G.; Wolf, J.; West, T. O.

2015-12-01

Livestock play an important role in agricultural carbon cycling through consumption of biomass and emissions of methane. Quantification and spatial distribution of methane and carbon dioxide produced by livestock is needed to develop bottom-up estimates for carbon monitoring. These estimates serve as stand-alone international emissions estimates, as input to global emissions modeling, and as comparisons or constraints to flux estimates from atmospheric inversion models. Recent results for the US suggest that the 2006 IPCC default coefficients may underestimate livestock methane emissions. In this project, revised coefficients were calculated for cattle and swine in all global regions, based on reported changes in body mass, quality and quantity of feed, milk production, and management of living animals and manure for these regions. New estimates of livestock methane and carbon dioxide emissions were calculated using the revised coefficients and global livestock population data. Spatial distribution of population data and associated fluxes was conducted using the MODIS Land Cover Type 5, version 5.1 (i.e. MCD12Q1 data product), and a previously published downscaling algorithm for reconciling inventory and satellite-based land cover data at 0.05 degree resolution. Preliminary results for 2013 indicate greater emissions than those calculated using the IPCC 2006 coefficients. Global total enteric fermentation methane increased by 6%, while manure management methane increased by 38%, with variation among species and regions resulting in improved spatial distributions of livestock emissions. These new estimates of total livestock methane are comparable to other recently reported studies for the entire US and the State of California. These new regional/global estimates will improve the ability to reconcile top-down and bottom-up estimates of methane production as well as provide updated global estimates for use in development and evaluation of Earth system models.

Improved modelling of ship SO 2 emissions—a fuel-based approach

NASA Astrophysics Data System (ADS)

Endresen, Øyvind; Bakke, Joachim; Sørgård, Eirik; Flatlandsmo Berglen, Tore; Holmvang, Per

Significant variations are apparent between the various reported regional and global ship SO 2 emission inventories. Important parameters for SO 2 emission modelling are sulphur contents and marine fuel consumption. Since 1993, the global average sulphur content for heavy fuel has shown an overall downward trend, while the bunker sale has increased. We present an improved bottom up approach to estimate marine sulphur emissions from ship transportation, including the geographical distribution. More than 53,000 individual bunker samples are used to establish regionally and globally (volume) weighted average sulphur contents for heavy and distillate marine fuels. We find that the year 2002 sulphur content in heavy fuels varies regionally from 1.90% (South America) to 3.07% (Asia), with a globally weighted average of 2.68% sulphur. The calculated globally weighted average content for heavy fuels is found to be 5% higher than the average (arithmetic mean) sulphur content commonly used. The reason for this is likely that larger bunker stems are mainly of high-viscosity heavy fuel, which tends to have higher sulphur values compared to lower viscosity fuels. The uncertainties in SO 2 inventories are significantly reduced using our updated SO 2 emission factors (volume-weighted sulphur content). Regional marine bunker sales figures are combined with volume-weighted sulphur contents for each region to give a global SO 2 emission estimate in the range of 5.9-7.2 Tg (SO 2) for international marine transportation. Also taking into account the domestic sales, the total emissions from all ocean-going transportation is estimated to be 7.0-8.5 Tg (SO 2). Our estimate is significantly lower than recent global estimate reported by Corbett and Koehler [2003. Journal of Geophysical Research: Atmospheres 108] (6.49 Tg S or about 13.0 Tg SO 2). Endresen et al. [2004. Journal of Geophysical Research 109, D23302] claim that uncertainties in input data for the activity-based method will give too high emission estimates. We also indicate that this higher estimate will almost give doubling of regional emissions, compared to detailed movement-based estimates. The paper presents an alternative approach to estimate present overall SO 2 ship emissions with improved accuracy.

Estimating Biases for Regional Methane Fluxes using Co-emitted Tracers

NASA Astrophysics Data System (ADS)

Bambha, R.; Safta, C.; Michelsen, H. A.; Cui, X.; Jeong, S.; Fischer, M. L.

2017-12-01

Methane is a powerful greenhouse gas, and the development and improvement of emissions models rely on understanding the flux of methane released from anthropogenic sources relative to releases from other sources. Increasing production of shale oil and gas in the mid-latitudes and associated fugitive emissions are suspected to be a dominant contributor to the global methane increase. Landfills, sewage treatment, and other sources may be dominant sources in some parts of the U.S. Large discrepancies between emissions models present a great challenge to reconciling atmospheric measurements with inventory-based estimates for various emissions sectors. Current approaches for measuring regional emissions yield highly uncertain estimates because of the sparsity of measurement sites and the presence of multiple simultaneous sources. Satellites can provide wide spatial coverage at the expense of much lower measurement precision compared to ground-based instruments. Methods for effective assimilation of data from a variety of sources are critically needed to perform regional GHG attribution with existing measurements and to determine how to structure future measurement systems including satellites. We present a hierarchical Bayesian framework to estimate surface methane fluxes based on atmospheric concentration measurements and a Lagrangian transport model (Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport). Structural errors in the transport model are estimated with the help of co-emitted traces species with well defined decay rates. We conduct the analyses at regional scales that are based on similar geographical and meteorological conditions. For regions where data are informative, we further refine flux estimates by emissions sector and infer spatially and temporally varying biases parameterized as spectral random field representations.

Kalman-filtered compressive sensing for high resolution estimation of anthropogenic greenhouse gas emissions from sparse measurements.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, Jaideep; Lee, Jina; Lefantzi, Sophia

2013-09-01

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. The limited nature of the measured data leads to a severely-underdetermined estimation problem. If the estimation is performed at fine spatial resolutions, it can also be computationally expensive. In order to enable such estimations, advances are needed in the spatial representation of ffCO2 emissions, scalable inversion algorithms and the identification of observables to measure. To that end, we investigate parsimonious spatial parameterizations of ffCO2 emissions whichmore » can be used in atmospheric inversions. We devise and test three random field models, based on wavelets, Gaussian kernels and covariance structures derived from easily-observed proxies of human activity. In doing so, we constructed a novel inversion algorithm, based on compressive sensing and sparse reconstruction, to perform the estimation. We also address scalable ensemble Kalman filters as an inversion mechanism and quantify the impact of Gaussian assumptions inherent in them. We find that the assumption does not impact the estimates of mean ffCO2 source strengths appreciably, but a comparison with Markov chain Monte Carlo estimates show significant differences in the variance of the source strengths. Finally, we study if the very different spatial natures of biogenic and ffCO2 emissions can be used to estimate them, in a disaggregated fashion, solely from CO2 concentration measurements, without extra information from products of incomplete combustion e.g., CO. We find that this is possible during the winter months, though the errors can be as large as 50%.« less

40 CFR 63.1414 - Test methods and emission estimation equations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (D) Design analysis based on accepted chemical engineering principles, measurable process parameters.... Engineering assessment may be used to estimate organic HAP emissions from a batch emission episode only under... (d)(5) of this section; through engineering assessment, as defined in paragraph (d)(6)(ii) of this...

40 CFR 63.1414 - Test methods and emission estimation equations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... (D) Design analysis based on accepted chemical engineering principles, measurable process parameters.... Engineering assessment may be used to estimate organic HAP emissions from a batch emission episode only under... (d)(5) of this section; through engineering assessment, as defined in paragraph (d)(6)(ii) of this...

40 CFR 63.1414 - Test methods and emission estimation equations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (D) Design analysis based on accepted chemical engineering principles, measurable process parameters.... Engineering assessment may be used to estimate organic HAP emissions from a batch emission episode only under... (d)(5) of this section; through engineering assessment, as defined in paragraph (d)(6)(ii) of this...

SEASONAL NH 3 EMISSIONS FOR THE CONTINENTAL UNITED STATES: INVERSE MODEL ESTIMATION AND EVALUATION

EPA Science Inventory

An inverse modeling study has been conducted here to evaluate a prior estimate of seasonal ammonia (NH₃) emissions. The prior estimates were based on a previous inverse modeling study and two other bottom-up inventory studies. The results suggest that the prior estim...

Top-down Estimates of Isoprene Emissions in Australia Inferred from OMI Satellite Data.

NASA Astrophysics Data System (ADS)

Greenslade, J.; Fisher, J. A.; Surl, L.; Palmer, P. I.

2017-12-01

Australia is a global hotspot for biogenic isoprene emission factors predicted by process-based models such as the Model of Emissions of Gases and Aerosols from Nature (MEGAN). It is also prone to increasingly frequent temperature extremes that can drive episodically high emissions. Estimates of biogenic isoprene emissions from Australia are poorly constrained, with the frequently used MEGAN model overestimating emissions by a factor of 4-6 in some areas. Evaluating MEGAN and other models in Australia is difficult due to sparse measurements of emissions and their ensuing chemical products. In this talk, we will describe efforts to better quantify Australian isoprene emissions using top-down estimates based on formaldehyde (HCHO) observations from the OMI satellite instrument, combined with modelled isoprene to HCHO yields obtained from the GEOS-Chem chemical transport model. The OMI-based estimates are evaluated using in situ observations from field campaigns conducted in southeast Australia. We also investigate the impact on the inferred emission of horizontal resolution used for the yield calculations, particularly in regions on the boundary between low- and high-NOx chemistry. The prevalence of fire smoke plumes roughly halves the available satellite dataset over Australia for much of the year; however, seasonal averages remain robust. Preliminary results show that the top-down isoprene emissions are lower than MEGAN estimates by up to 90% in summer. The overestimates are greatest along the eastern coast, including areas surrounding Australia's major population centres in Sydney, Melbourne, and Brisbane. The coarse horizontal resolution of the model significantly affects the emissions estimates, as many biogenic emitting regions lie along narrow coastal stretches. Our results confirm previous findings that the MEGAN biogenic emission model is poorly calibrated for the Australian environment and suggests that chemical transport models driven by MEGAN are likely to overpredict ozone and secondary organic aerosols from biogenic sources in the Australian environment. Further measurements of biogenic gases are critical to improving biogenic emissions and follow-on chemical transport modelling, in this region. We hope to quantify this overestimation and its flow-on effects in future work.

Atmospheric particulate emissions from dry abrasive blasting using coal slag.

PubMed

Kura, Bhaskar; Kambham, Kalpalatha; Sangameswaran, Sivaramakrishnan; Potana, Sandhya

2006-08-01

Coal slag is one of the widely used abrasives in dry abrasive blasting. Atmospheric emissions from this process include particulate matter (PM) and heavy metals, such as chromium, lead, manganese, nickel. Quantities and characteristics of PM emissions depend on abrasive characteristics and process parameters. Emission factors are key inputs to estimate emissions. Experiments were conducted to study the effect of blast pressure, abrasive feed rate, and initial surface contamination on total PM (TPM) emission factors for coal slag. Rusted and painted mild steel surfaces were used as base plates. Blasting was carried out in an enclosed chamber, and PM was collected from an exhaust duct using U.S. Environment Protection Agency source sampling methods for stationary sources. Results showed that there is significant effect of blast pressure, feed rate, and surface contamination on TPM emissions. Mathematical equations were developed to estimate emission factors in terms of mass of emissions per unit mass of abrasive used, as well as mass of emissions per unit of surface area cleaned. These equations will help industries in estimating PM emissions based on blast pressure and abrasive feed rate. In addition, emissions can be reduced by choosing optimum operating conditions.

Comparing Top-down and Bottom-up Estimates of Methane Emissions across Multiple U.S. Basins Provides Insights into National Oil and Gas Emissions and Mitigation Strategies

NASA Astrophysics Data System (ADS)

Hamburg, S.; Alvarez, R.; Lyon, D. R.; Zavala-Araiza, D.

2016-12-01

Several recent studies quantified regional methane emissions in U.S. oil and gas (O&G) basins using top-down approaches such as airborne mass balance measurements. These studies apportioned total methane emissions to O&G based on hydrocarbon ratios or subtracting bottom-up estimates of other sources. In most studies, top-down estimates of O&G methane emissions exceeded bottom-up emission inventories. An exception is the Barnett Shale Coordinated Campaign, which found agreement between aircraft mass balance estimates and a custom emission inventory. Reconciliation of Barnett Shale O&G emissions depended on two key features: 1) matching the spatial domains of top-down and bottom-up estimates, and 2) accounting for fat-tail sources in site-level emission factors. We construct spatially explicit custom emission inventories for domains with top-down O&G emission estimates in eight major U.S. oil and gas production basins using a variety of data sources including a spatially-allocated U.S. EPA Greenhouse Gas Inventory, the EPA Greenhouse Gas Reporting Program, state emission inventories, and recently published measurement studies. A comparison of top-down and our bottom-up estimates of O&G emissions constrains the gap between these approaches and elucidates regional variability in production-normalized loss rates. A comparison of component-level and site-level emission estimates of production sites in the Barnett Shale region - where comprehensive activity data and emissions estimates are available - indicates that abnormal process conditions contribute about 20% of regional O&G emissions. Combining these two analyses provides insights into the relative importance of different equipment, processes, and malfunctions to emissions in each basin. These data allow us to estimate the U.S. O&G supply chain loss rate, recommend mitigation strategies to reduce emissions from existing infrastructure, and discuss how a similar approach can be applied internationally.

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

A Fuel-Based Assessment of On-Road and Off-Road Mobile Source Emission Trends

NASA Astrophysics Data System (ADS)

Dallmann, T. R.; Harley, R. A.

2009-12-01

Mobile sources contribute significantly to emissions of nitrogen oxides (NOx) and fine particulate matter (PM2.5) in the United States. These emissions lead to a variety of environmental concerns including adverse human health effects and climate change. In the electric power sector, sulfur dioxide (SO2) and NOx emissions from power plants are measured directly using continuous emission monitoring systems. In contrast for mobile sources, statistical models are used to estimate average emissions from a very large and diverse population of engines. Despite much effort aimed at improving them, mobile source emission inventories continue to have large associated uncertainties. Alternate methods are needed to help evaluate estimates of mobile source emissions and quantify and reduce the associated uncertainties. In this study, a fuel-based approach is used to estimate emissions from mobile sources, including on-road and off-road gasoline and diesel engines. In this approach, engine activity is measured by fuel consumed (in contrast EPA mobile source emission models are based on vehicle km of travel and total amount of engine work output for on-road and off-road engines, respectively). Fuel consumption is defined in this study based on highway fuel tax reports for on-road engines, and from surveys of fuel wholesalers who sell tax-exempt diesel fuel for use in various off-road sectors such as agriculture, construction, and mining. Over the decade-long time period (1996-2006) that is the focus of the present study, national sales of taxable gasoline and diesel fuel intended for on-road use increased by 15 and 43%, respectively. Diesel fuel use by off-road equipment increased by about 20% over the same time period. Growth in fuel consumption offset some of the reductions in pollutant emission factors that occurred during this period. This study relies on in-use measurements of mobile source emission factors, for example from roadside and tunnel studies, remote sensing, and plume capture experiments. Extensive in-use emissions data are available for NOx, especially for on-road engines. Measurements of exhaust PM2.5 emission factors are sparse in comparison. For NOx, there have been dramatic (factor of 2) decreases in emission factors for on-road gasoline engines between 1996 and 2006, due to use of improved catalytic converters on most engines. In contrast, diesel NOx emission factors decreased more gradually over the same time period. Exhaust PM2.5 emission factors appear to have decreased for most engine categories, but emission uncertainties are large for this pollutant. Pollutant emissions were estimated by combining fuel sales with emission factors expressed per unit of fuel burned. Diesel engines are the dominant mobile source of both NOx and PM2.5; the diesel contribution to NOx has increased over time as gasoline engine emissions have declined. Comparing fuel-based emission estimates with EPA’s national emission inventory led to the following conclusions: (1) total emissions of both NOx and PM2.5 estimated by two different methods were similar, (2) the distribution of source contributions to these totals differ significantly, with higher relative contributions coming from on-road diesel engines in this study compared to EPA.

Speed Profiles for Improvement of Maritime Emission Estimation.

PubMed

Yau, Pui Shan; Lee, Shun-Cheng; Ho, Kin Fai

2012-12-01

Maritime emissions play an important role in anthropogenic emissions, particularly for cities with busy ports such as Hong Kong. Ship emissions are strongly dependent on vessel speed, and thus accurate vessel speed is essential for maritime emission studies. In this study, we determined minute-by-minute high-resolution speed profiles of container ships on four major routes in Hong Kong waters using Automatic Identification System (AIS). The activity-based ship emissions of NO(x), CO, HC, CO(2), SO(2), and PM(10) were estimated using derived vessel speed profiles, and results were compared with those using the speed limits of control zones. Estimation using speed limits resulted in up to twofold overestimation of ship emissions. Compared with emissions estimated using the speed limits of control zones, emissions estimated using vessel speed profiles could provide results with up to 88% higher accuracy. Uncertainty analysis and sensitivity analysis of the model demonstrated the significance of improvement of vessel speed resolution. From spatial analysis, it is revealed that SO(2) and PM(10) emissions during maneuvering within 1 nautical mile from port were the highest. They contributed 7%-22% of SO(2) emissions and 8%-17% of PM(10) emissions of the entire voyage in Hong Kong.

Assessment of atmospheric mercury emissions in Finland

PubMed

Mukherjee; Melanen; Ekqvist; Verta

2000-10-02

This paper is part of the study of atmospheric emissions of heavy metals conducted by the Finnish Environment Institute in collaboration with the Technical Research Centre of Finland (VTT) under the umbrella of the Finnish Ministry of the Environment. The scope of our study is limited solely to anthropogenic mercury that is emitted directly to the atmosphere. This article addresses emission factors and trends of atmospheric mercury emissions during the 1990s and is based mainly on the database of the Finnish Environmental Administration. In addition, data based on the measurements taken by the VTT regarding emission factors have been used to estimate emissions of mercury from the incineration of waste. The study indicates that the total emission of mercury has decreased from 1140 kg in 1990 to 620 kg in 1997, while industrial and energy production have been on the increase simultaneously. The 45% emission reduction is due to improved gas cleaning equipment, process changes, automation, the installation of flue gas desulfurization process in coal-fired power plants and strict pollution control laws. In the past, some authors have estimated a higher mercury emission in Finland. In this study, it is also observed that there are no big changes in the quality of raw materials. Estimated emission factors can be of great help to management for estimating mercury emissions and also its risk assessment.

A simple mathematical method to estimate ammonia emission from in-house windrowing of poultry litter.

PubMed

Ro, Kyoung S; Szogi, Ariel A; Moore, Philip A

2018-05-12

In-house windrowing between flocks is an emerging sanitary management practice to partially disinfect the built-up litter in broiler houses. However, this practice may also increase ammonia (NH 3 ) emission from the litter due to the increase in litter temperature. The objectives of this study were to develop mathematical models to estimate NH 3 emission rates from broiler houses practicing in-house windrowing between flocks. Equations to estimate mass-transfer areas form different shapes windrowed litter (triangular, rectangular, and semi-cylindrical prisms) were developed. Using these equations, the heights of windrows yielding the smallest mass-transfer area were estimated. Smaller mass-transfer area is preferred as it reduces both emission rates and heat loss. The heights yielding the minimum mass-transfer area were 0.8 and 0.5 m for triangular and rectangular windrows, respectively. Only one height (0.6 m) was theoretically possible for semi-cylindrical windrows because the base and the height were not independent. Mass-transfer areas were integrated with published process-based mathematical models to estimate the total house NH 3 emission rates during in-house windrowing of poultry litter. The NH 3 emission rate change calculated from the integrated model compared well with the observed values except for the very high NH 3 initial emission rate from mechanically disturbing the litter to form the windrows. This approach can be used to conveniently estimate broiler house NH 3 emission rates during in-house windrowing between flocks by simply measuring litter temperatures.

Comparing emission rates derived from a model with a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

PubMed

Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne

2018-06-05

This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.

Fine particulate matter emissions inventories: comparisons of emissions estimates with observations from recent field programs.

PubMed

Simon, Heather; Allen, David T; Wittig, Ann E

2008-02-01

Emissions inventories of fine particulate matter (PM2.5) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM2.5 emissions were reviewed: on-road mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5-20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM2.s are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods.

Estimation of vehicular emissions using dynamic emission factors: A case study of Delhi, India

NASA Astrophysics Data System (ADS)

Mishra, Dhirendra; Goyal, P.

2014-12-01

The estimation of vehicular emissions depends mainly on the values of emission factors, which are used for the development of a comprehensive emission inventory of vehicles. In this study the variations of emission factors as well as the emission rates have been studied in Delhi. The implementation of compressed natural gas (CNG), in the diesel and petrol, public vehicles in the year 2001 has changed the complete air quality scenario of Delhi. The dynamic emission factors of criteria pollutants viz. carbon monoxide (CO), nitrogen oxide (NOx) and particulate matter (PM10) for all types of vehicles have been developed after, which are based on the several factors such as regulated emission limits, number of vehicle deterioration, vehicle increment, vehicle age etc. These emission factors are found to be decreased continuously throughout the study years 2003-2012. The International Vehicle Emissions (IVE) model is used to estimate the emissions of criteria pollutants by utilizing a dataset available from field observations at different traffic intersections in Delhi. Thus the vehicular emissions, based on dynamic emission factors have been estimated for the years 2003-2012, which are found to be comparable with the monitored concentrations at different locations in Delhi. It is noticed that the total emissions of CO, NOx, and PM10 are increased by 45.63%, 68.88% and 17.92%, respectively up to the year 2012 and the emissions of NOx and PM10 are grown continuously with an annual average growth rate of 5.4% and 1.7% respectively.

A refined 2010-based VOC emission inventory and its improvement on modeling regional ozone in the Pearl River Delta Region, China.

PubMed

Yin, Shasha; Zheng, Junyu; Lu, Qing; Yuan, Zibing; Huang, Zhijiong; Zhong, Liuju; Lin, Hui

2015-05-01

Accurate and gridded VOC emission inventories are important for improving regional air quality model performance. In this study, a four-level VOC emission source categorization system was proposed. A 2010-based gridded Pearl River Delta (PRD) regional VOC emission inventory was developed with more comprehensive source coverage, latest emission factors, and updated activity data. The total anthropogenic VOC emission was estimated to be about 117.4 × 10(4)t, in which on-road mobile source shared the largest contribution, followed by industrial solvent use and industrial processes sources. Among the industrial solvent use source, furniture manufacturing and shoemaking were major VOC emission contributors. The spatial surrogates of VOC emission were updated for major VOC sources such as industrial sectors and gas stations. Subsector-based temporal characteristics were investigated and their temporal variations were characterized. The impacts of updated VOC emission estimates and spatial surrogates were evaluated by modeling O₃ concentration in the PRD region in the July and October of 2010, respectively. The results indicated that both updated emission estimates and spatial allocations can effectively reduce model bias on O₃ simulation. Further efforts should be made on the refinement of source classification, comprehensive collection of activity data, and spatial-temporal surrogates in order to reduce uncertainty in emission inventory and improve model performance. Copyright © 2015 Elsevier B.V. All rights reserved.

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1950 - 2006) (V.2009)

DOE Data Explorer

Andres, R. J. [.; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Marland, Greg [Appalachian State University, Boone, North Carolina (USA)

2009-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2006.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (V. 2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, North Caroline (USA)

2012-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2009.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html Q10 for a description why emission totals based upon consumption differ from those based upon production).

Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana.

PubMed

Lamb, Brian K; Cambaliza, Maria O L; Davis, Kenneth J; Edburg, Steven L; Ferrara, Thomas W; Floerchinger, Cody; Heimburger, Alexie M F; Herndon, Scott; Lauvaux, Thomas; Lavoie, Tegan; Lyon, David R; Miles, Natasha; Prasad, Kuldeep R; Richardson, Scott; Roscioli, Joseph Robert; Salmon, Olivia E; Shepson, Paul B; Stirm, Brian H; Whetstone, James

2016-08-16

This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.

Measurement of fugitive volatile organic compound emissions from a petrochemical tank farm using open-path Fourier transform infrared spectrometry

NASA Astrophysics Data System (ADS)

Wu, Chang-Fu; Wu, Tzong-gang; Hashmonay, Ram A.; Chang, Shih-Ying; Wu, Yu-Syuan; Chao, Chun-Ping; Hsu, Cheng-Ping; Chase, Michael J.; Kagann, Robert H.

2014-01-01

Fugitive emission of air pollutants is conventionally estimated based on standard emission factors. The Vertical Radial Plume Mapping (VRPM) technique, as described in the US EPA OTM-10, is designed to measure emission flux by directly monitoring the concentration of the plume crossing a vertical plane downwind of the site of interest. This paper describes the evaluation results of implementing VRPM in a complex industrial setting (a petrochemical tank farm). The vertical plane was constructed from five retroreflectors and an open-path Fourier transform infrared spectrometer. The VRPM configuration was approximately 189.2 m in width × 30.7 m in height. In the accompanying tracer gas experiment, the bias of the VRPM estimate was less than 2% and its 95% confidence interval contained the true release rate. Emission estimates of the target VOCs (benzene, m-xylene, o-xylene, p-xylene, and toluene) ranged from 0.86 to 2.18 g s-1 during the 14-day field campaign, while estimates based on the standard emission factors were one order of magnitude lower, possibly leading to an underestimation of the impact of these fugitive emissions on air quality and human health. It was also demonstrated that a simplified 3-beam geometry (i.e., without one dimensional scanning lines) resulted in higher uncertainties in the emission estimates.

Estimating air chemical emissions from research activities using stack measurement data.

PubMed

Ballinger, Marcel Y; Duchsherer, Cheryl J; Woodruff, Rodger K; Larson, Timothy V

2013-03-01

Current methods of estimating air emissions from research and development (R&D) activities use a wide range of release fractions or emission factors with bases ranging from empirical to semi-empirical. Although considered conservative, the uncertainties and confidence levels of the existing methods have not been reported. Chemical emissions were estimated from sampling data taken from four research facilities over 10 years. The approach was to use a Monte Carlo technique to create distributions of annual emission estimates for target compounds detected in source test samples. Distributions were created for each year and building sampled for compounds with sufficient detection frequency to qualify for the analysis. The results using the Monte Carlo technique without applying a filter to remove negative emission values showed almost all distributions spanning zero, and 40% of the distributions having a negative mean. This indicates that emissions are so low as to be indistinguishable from building background. Application of a filter to allow only positive values in the distribution provided a more realistic value for emissions and increased the distribution mean by an average of 16%. Release fractions were calculated by dividing the emission estimates by a building chemical inventory quantity. Two variations were used for this quantity: chemical usage, and chemical usage plus one-half standing inventory. Filters were applied so that only release fraction values from zero to one were included in the resulting distributions. Release fractions had a wide range among chemicals and among data sets for different buildings and/or years for a given chemical. Regressions of release fractions to molecular weight and vapor pressure showed weak correlations. Similarly, regressions of mean emissions to chemical usage, chemical inventory, molecular weight, and vapor pressure also gave weak correlations. These results highlight the difficulties in estimating emissions from R&D facilities using chemical inventory data. Air emissions from research operations are difficult to estimate because of the changing nature of research processes and the small quantity and wide variety of chemicals used. Analysis of stack measurements taken over multiple facilities and a 10-year period using a Monte Carlo technique provided a method to quantify the low emissions and to estimate release fractions based on chemical inventories. The variation in release fractions did not correlate well with factors investigated, confirming the complexities in estimating R&D emissions.

Reconciling Top-Down and Bottom-Up Estimates of Oil and Gas Methane Emissions in the Barnett Shale

NASA Astrophysics Data System (ADS)

Hamburg, S.

2015-12-01

Top-down approaches that use aircraft, tower, or satellite-based measurements of well-mixed air to quantify regional methane emissions have typically estimated higher emissions from the natural gas supply chain when compared to bottom-up inventories. A coordinated research campaign in October 2013 used simultaneous top-down and bottom-up approaches to quantify total and fossil methane emissions in the Barnett Shale region of Texas. Research teams have published individual results including aircraft mass-balance estimates of regional emissions and a bottom-up, 25-county region spatially-resolved inventory. This work synthesizes data from the campaign to directly compare top-down and bottom-up estimates. A new analytical approach uses statistical estimators to integrate facility emission rate distributions from unbiased and targeted high emission site datasets, which more rigorously incorporates the fat-tail of skewed distributions to estimate regional emissions of well pads, compressor stations, and processing plants. The updated spatially-resolved inventory was used to estimate total and fossil methane emissions from spatial domains that match seven individual aircraft mass balance flights. Source apportionment of top-down emissions between fossil and biogenic methane was corroborated with two independent analyses of methane and ethane ratios. Reconciling top-down and bottom-up estimates of fossil methane emissions leads to more accurate assessment of natural gas supply chain emission rates and the relative contribution of high emission sites. These results increase our confidence in our understanding of the climate impacts of natural gas relative to more carbon-intensive fossil fuels and the potential effectiveness of mitigation strategies.

Methane emissions from the global oil and gas supply chain: recent advances and next steps

NASA Astrophysics Data System (ADS)

Zavala Araiza, D.; Herndon, S. C.; Roscioli, J. R.; Yacovitch, T. I.; Knighton, W. B.; Johnson, M.; Tyner, D. R.; Hamburg, S.

2017-12-01

A wide body of research has characterized methane emissions from the oil and gas system in the US. In contrast, empirical data is limited for other significant oil and gas producing regions across the world. As a consequence, measuring and characterizing methane emissions across global oil and gas operations will be crucial to the design of effective mitigation strategies. Several countries have announced pledges to reduce methane emissions from this system (e.g., North America, Climate and Clean Air Coalition [CCAC] ministers). In the case of Canada, the federal government recently announced regulations supporting a 40-45% reduction of methane emissions from the oil and gas production systems. For these regulations to be effective, it is critical to understand the current methane emission patterns. We present results from a coordinated multiscale (i.e., airborne-based, ground-based) measurement campaign in Alberta, Canada. We use empirically derived emission estimates to characterize site-level emissions and derive an emissions distribution. Our work shows that many major sources of emissions are unmeasured or underreported. Consistent with previous studies in the US, a small fraction of sites disproportionately account for the majority of emissions: roughly 20% of sites accounted for 75% of emissions. An independent airborne-based regional estimate was 40% lower than the ground-based regional estimate, but not statistically different. Finally, we summarize next steps as part of the CCAC Oil and Gas Methane Study: ongoing work that is targeting oil and gas sectors/production regions with limited empirical data on methane emissions. This work builds on the approach deployed in quantifying methane emissions from the oil and gas supply chain in the US, underscoring the commitment to transparency of the collected data, external review, deployment of multiple methodologies, and publication of results in peer-reviewed journals.

Data analysis in emission tomography using emission-count posteriors

NASA Astrophysics Data System (ADS)

Sitek, Arkadiusz

2012-11-01

A novel approach to the analysis of emission tomography data using the posterior probability of the number of emissions per voxel (emission count) conditioned on acquired tomographic data is explored. The posterior is derived from the prior and the Poisson likelihood of the emission-count data by marginalizing voxel activities. Based on emission-count posteriors, examples of Bayesian analysis including estimation and classification tasks in emission tomography are provided. The application of the method to computer simulations of 2D tomography is demonstrated. In particular, the minimum-mean-square-error point estimator of the emission count is demonstrated. The process of finding this estimator can be considered as a tomographic image reconstruction technique since the estimates of the number of emissions per voxel divided by voxel sensitivities and acquisition time are the estimates of the voxel activities. As an example of a classification task, a hypothesis stating that some region of interest (ROI) emitted at least or at most r-times the number of events in some other ROI is tested. The ROIs are specified by the user. The analysis described in this work provides new quantitative statistical measures that can be used in decision making in diagnostic imaging using emission tomography.

Emissions estimates of carbon tetrachloride for 1992-2014 in China.

PubMed

Bie, Pengju; Fang, Xuekun; Li, Zhifang; Wang, Ziyuan; Hu, Jianxin

2017-05-01

Discrepancies in emission estimates of carbon tetrachloride (CCl 4 , CTC), between bottom-up and top-down methods, have been shown since the 1990s at both the global and regional scale. This study estimates the emissions of China from 1992 to 2014 based on emission functions and aggregated activity information given reasonable uncertainties. The results show that emissions increase from 7.3 Gg/yr (5.6-9.1 Gg/yr at 95% confidential interval) to 14.0 (9.1-19.5) Gg/yr with a growth rate of 6.7 (1.9-11.4) %/yr during 1992-2002 and then decrease to a minimum of 4.3 (1.9-8.0) Gg/yr in 2011. More than 54% of the emissions during 1992-2009 are from the process agents sector. The estimates are comparable with those of other studies and those in this study based on observations during 2011-2014 using the interspecies correlation method. China's contribution to global emissions increases from 7.5% to 19.5% during 1992-2009, but the contribution is reduced to 9.9% and 8.0% in 2010 and 2011, respectively, indicating the effectiveness of compliance with the Montreal Protocol and its subsequent Amendments and Adjustments, whereby CTC emissions are phased-out. The results of this study are beneficial for narrowing the gap between bottom-up estimates and top-down emission calculations of CTC in China. Copyright © 2017 Elsevier Ltd. All rights reserved.

Global sulfur emissions from 1850 to 2000.

PubMed

Stern, David I

2005-01-01

The ASL database provides continuous time-series of sulfur emissions for most countries in the World from 1850 to 1990, but academic and official estimates for the 1990s either do not cover all years or countries. This paper develops continuous time series of sulfur emissions by country for the period 1850-2000 with a particular focus on developments in the 1990s. Global estimates for 1996-2000 are the first that are based on actual observed data. Raw estimates are obtained in two ways. For countries and years with existing published data I compile and integrate that data. Previously published data covers the majority of emissions and almost all countries have published emissions for at least 1995. For the remaining countries and for missing years for countries with some published data, I interpolate or extrapolate estimates using either an econometric emissions frontier model, an environmental Kuznets curve model, or a simple extrapolation, depending on the availability of data. Finally, I discuss the main movements in global and regional emissions in the 1990s and earlier decades and compare the results to other studies. Global emissions peaked in 1989 and declined rapidly thereafter. The locus of emissions shifted towards East and South Asia, but even this region peaked in 1996. My estimates for the 1990s show a much more rapid decline than other global studies, reflecting the view that technological progress in reducing sulfur based pollution has been rapid and is beginning to diffuse worldwide.

Global civil aviation black carbon emissions.

PubMed

Stettler, Marc E J; Boies, Adam M; Petzold, Andreas; Barrett, Steven R H

2013-09-17

Aircraft black carbon (BC) emissions contribute to climate forcing, but few estimates of BC emitted by aircraft at cruise exist. For the majority of aircraft engines the only BC-related measurement available is smoke number (SN)-a filter based optical method designed to measure near-ground plume visibility, not mass. While the first order approximation (FOA3) technique has been developed to estimate BC mass emissions normalized by fuel burn [EI(BC)] from SN, it is shown that it underestimates EI(BC) by >90% in 35% of directly measured cases (R(2) = -0.10). As there are no plans to measure BC emissions from all existing certified engines-which will be in service for several decades-it is necessary to estimate EI(BC) for existing aircraft on the ground and at cruise. An alternative method, called FOX, that is independent of the SN is developed to estimate BC emissions. Estimates of EI(BC) at ground level are significantly improved (R(2) = 0.68), whereas estimates at cruise are within 30% of measurements. Implementing this approach for global civil aviation estimated aircraft BC emissions are revised upward by a factor of ~3. Direct radiative forcing (RF) due to aviation BC emissions is estimated to be ~9.5 mW/m(2), equivalent to ~1/3 of the current RF due to aviation CO2 emissions.

Aerial photography based census of Adélie Penguin and its application in CH4 and N2O budget estimation in Victoria Land, Antarctic.

PubMed

He, Hong; Cheng, Xiao; Li, Xianglan; Zhu, Renbin; Hui, Fengming; Wu, Wenhui; Zhao, Tiancheng; Kang, Jing; Tang, Jianwu

2017-10-11

Penguin guano provides favorable conditions for production and emission of greenhouse gases (GHGs). Many studies have been conducted to determine the GHG fluxes from penguin colonies, however, at regional scale, there is still no accurate estimation of total GHG emissions. We used object-based image analysis (OBIA) method to estimate the Adélie penguin (Pygoscelis adeliae) population based on aerial photography data. A model was developed to estimate total GHG emission potential from Adélie penguin colonies during breeding seasons in 1983 and 2012, respectively. Results indicated that OBIA method was effective for extracting penguin information from aerial photographs. There were 17,120 and 21,183 Adélie penguin breeding pairs on Inexpressible Island in 1983 and 2012, respectively, with overall accuracy of the estimation of 76.8%. The main reasons for the increase in Adélie penguin populations were attributed to increase in temperature, sea ice and phytoplankton. The average estimated CH 4 and N 2 O emissions tended to be increasing during the period from 1983 to 2012 and CH 4 was the main GHG emitted from penguin colonies. Total global warming potential (GWP) of CH 4 and N 2 O emissions was 5303 kg CO 2 -eq in 1983 and 6561 kg CO 2 -eq in 2012, respectively.

Fossil-Fuel C02 Emissions Database and Exploration System

NASA Astrophysics Data System (ADS)

Krassovski, M.; Boden, T.

2012-04-01

Fossil-Fuel C02 Emissions Database and Exploration System Misha Krassovski and Tom Boden Carbon Dioxide Information Analysis Center Oak Ridge National Laboratory The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL) quantifies the release of carbon from fossil-fuel use and cement production each year at global, regional, and national spatial scales. These estimates are vital to climate change research given the strong evidence suggesting fossil-fuel emissions are responsible for unprecedented levels of carbon dioxide (CO2) in the atmosphere. The CDIAC fossil-fuel emissions time series are based largely on annual energy statistics published for all nations by the United Nations (UN). Publications containing historical energy statistics make it possible to estimate fossil-fuel CO2 emissions back to 1751 before the Industrial Revolution. From these core fossil-fuel CO2 emission time series, CDIAC has developed a number of additional data products to satisfy modeling needs and to address other questions aimed at improving our understanding of the global carbon cycle budget. For example, CDIAC also produces a time series of gridded fossil-fuel CO2 emission estimates and isotopic (e.g., C13) emissions estimates. The gridded data are generated using the methodology described in Andres et al. (2011) and provide monthly and annual estimates for 1751-2008 at 1° latitude by 1° longitude resolution. These gridded emission estimates are being used in the latest IPCC Scientific Assessment (AR4). Isotopic estimates are possible thanks to detailed information for individual nations regarding the carbon content of select fuels (e.g., the carbon signature of natural gas from Russia). CDIAC has recently developed a relational database to house these baseline emissions estimates and associated derived products and a web-based interface to help users worldwide query these data holdings. Users can identify, explore and download desired CDIAC fossil-fuel CO2 emissions data. This presentation introduces the architecture and design of the new relational database and web interface, summarizes the present state and functionality of the Fossil-Fuel CO2 Emissions Database and Exploration System, and highlights future plans for expansion of the relational database and interface.

Current sources of carbon tetrachloride (CCl4) in our atmosphere

NASA Astrophysics Data System (ADS)

Sherry, David; McCulloch, Archie; Liang, Qing; Reimann, Stefan; Newman, Paul A.

2018-02-01

Carbon tetrachloride (CCl4 or CTC) is an ozone-depleting substance whose emissive uses are controlled and practically banned by the Montreal Protocol (MP). Nevertheless, previous work estimated ongoing emissions of 35 Gg year-1 of CCl4 into the atmosphere from observation-based methods, in stark contrast to emissions estimates of 3 (0-8) Gg year-1 from reported numbers to UNEP under the MP. Here we combine information on sources from industrial production processes and legacy emissions from contaminated sites to provide an updated bottom-up estimate on current CTC global emissions of 15-25 Gg year-1. We now propose 13 Gg year-1 of global emissions from unreported non-feedstock emissions from chloromethane and perchloroethylene plants as the most significant CCl4 source. Additionally, 2 Gg year-1 are estimated as fugitive emissions from the usage of CTC as feedstock and possibly up to 10 Gg year-1 from legacy emissions and chlor-alkali plants.

A new method for estimating carbon dioxide emissions from transportation at fine spatial scales

PubMed Central

Shu, Yuqin; Reams, Margaret

2016-01-01

Detailed estimates of carbon dioxide (CO2) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO2 emission estimates from the county-level scale to a 1 km2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO2 emission values by county (i.e. parish) for the state of Louisiana into 1 km2 grids. The results reveal a more realistic spatial pattern of CO2 emission from transportation, which can be used to identify the emission ‘hot spots’. Of the four highest transportation-related CO2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches. PMID:26997973

A New Global Anthropogenic SO2 Emission Inventory for the Last Decade: A Mosaic of Satellite-derived and Bottom-up Emissions

NASA Astrophysics Data System (ADS)

Liu, F.; Joiner, J.; Choi, S.; Krotkov, N. A.; Li, C.; Fioletov, V. E.; McLinden, C. A.

2017-12-01

Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor have been used to detect emissions from large point sources using an innovative estimation technique. Emissions from about 500 sources have been quantified individually based on OMI observations, accounting for about a half of total reported anthropogenic SO2 emissions. We developed a new emission inventory, OMI-HTAP, by combining these OMI-based emission estimates and the conventional bottom-up inventory. OMI-HTAP includes OMI-based estimates for over 400 point sources and is gap-filled with the emission grid map of the latest available global bottom-up emission inventory (HTAP v2.2) for the rest of sources. We have evaluated the OMI-HTAP inventory by performing simulations with the Goddard Earth Observing System version 5 (GEOS-5) model. The GEOS-5 simulated SO2 concentrations driven by both the HTAP and the OMI-HTAP inventory were compared against in-situ and satellite measurements. Results show that the OMI-HTAP inventory improves the model agreement with observations, in particular over the US, India and the Middle East. Additionally, simulations with the OMI-HTAP inventory capture the major trends of anthropogenic SO2 emissions over the world and highlight the influence of missing sources in the bottom-up inventory.

Development of the Vista Methane Emissions Inventory for Southern California: A GIS-Based Approach for Mapping Methane Emissions

NASA Astrophysics Data System (ADS)

Carranza, V.; Frausto-Vicencio, I.; Rafiq, T.; Verhulst, K. R.; Hopkins, F. M.; Rao, P.; Duren, R. M.; Miller, C. E.

2016-12-01

Atmospheric methane (CH4) is the second most prevalent anthropogenic greenhouse gas. Improved estimates of CH4 emissions from cities is essential for carbon cycle science and climate mitigation efforts. Development of spatially-resolved carbon emissions data sets may offer significant advances in understanding and managing carbon emissions from cities. Urban CH4 emissions in particular require spatially resolved emission maps to help resolve uncertainties in the CH4 budget. This study presents a Geographic Information System (GIS)-based approach to mapping CH4 emissions using locations of infrastructure known to handle and emit methane. We constrain the spatial distribution of sources to the facility level for the major CH4 emitting sources in the South Coast Air Basin. GIS spatial modeling was combined with publicly available datasets to determine the distribution of potential CH4 sources. The datasets were processed and validated to ensure accuracy in the location of individual sources. This information was then used to develop the Vista emissions prior, which is a one-year long, spatially-resolved CH4 emissions estimate. Methane emissions were calculated and spatially allocated to produce 1 km x 1 km gridded CH4 emission map spanning the Los Angeles Basin. In future work, the Vista CH4 emissions prior will be compared with existing, coarser-resolution emissions estimates and will be evaluated in inverse modeling studies using atmospheric observations. The Vista CH4 emissions inventory presents the first detailed spatial maps of CH4 sources and emissions estimates in the Los Angeles Basin and is a critical step towards sectoral attribution of CH4 emissions at local to regional scales.

Towards a Novel Integrated Approach for Estimating Greenhouse Gas Emissions in Support of International Agreements

NASA Astrophysics Data System (ADS)

Reimann, S.; Vollmer, M. K.; Henne, S.; Brunner, D.; Emmenegger, L.; Manning, A.; Fraser, P. J.; Krummel, P. B.; Dunse, B. L.; DeCola, P.; Tarasova, O. A.

2016-12-01

In the recently adopted Paris Agreement the community of signatory states has agreed to limit the future global temperature increase between +1.5 °C and +2.0 °C, compared to pre-industrial times. To achieve this goal, emission reduction targets have been submitted by individual nations (called Intended Nationally Determined Contributions, INDCs). Inventories will be used for checking progress towards these envisaged goals. These inventories are calculated by combining information on specific activities (e.g. passenger cars, agriculture) with activity-related, typically IPCC-sanctioned, emission factors - the so-called bottom-up method. These calculated emissions are reported on an annual basis and are checked by external bodies by using the same method. A second independent method estimates emissions by translating greenhouse gas measurements made at regionally representative stations into regional/global emissions using meteorologically-based transport models. In recent years this so-called top-down approach has been substantially advanced into a powerful tool and emission estimates at the national/regional level have become possible. This method is already used in Switzerland, in the United Kingdom and in Australia to estimate greenhouse gas emissions and independently support the national bottom-up emission inventories within the UNFCCC framework. Examples of the comparison of the two independent methods will be presented and the added-value will be discussed. The World Meteorological Organization (WMO) and partner organizations are currently developing a plan to expand this top-down approach and to expand the globally representative GAW network of ground-based stations and remote-sensing platforms and integrate their information with atmospheric transport models. This Integrated Global Greenhouse Gas Information System (IG3IS) initiative will help nations to improve the accuracy of their country-based emissions inventories and their ability to evaluate the success of emission reductions strategies. This could foster trans-national collaboration on methodologies for estimation of emissions. Furthermore, more accurate emission knowledge will clarify the value of emission reduction efforts and could encourage countries to strengthen their reduction pledges.

A historical reconstruction of ships' fuel consumption and emissions

NASA Astrophysics Data System (ADS)

Endresen, Øyvind; Sørgârd, Eirik; Behrens, Hanna Lee; Brett, Per Olaf; Isaksen, Ivar S. A.

2007-06-01

Shipping activity has increased considerably over the last century and currently represents a significant contribution to the global emissions of pollutants and greenhouse gases. Despite this, information about the historical development of fuel consumption and emissions is generally limited, with little data published pre-1950 and large deviations reported for estimates covering the last 3 decades. To better understand the historical development in ship emissions and the uncertainties associated with the estimates, we present fuel-based CO2 and SO2 emission inventories from 1925 up to 2002 and activity-based estimates from 1970 up to 2000. The global CO2 emissions from ships in 1925 have been estimated to 229 Tg (CO2), growing to about 634 Tg (CO2) in 2002. The corresponding SO2 emissions are about 2.5 Tg (SO2) and 8.5 Tg (SO2), respectively. Our activity-based estimates of fuel consumption from 1970 to 2000, covering all oceangoing civil ships above or equal to 100 gross tonnage (GT), are lower compared to previous activity-based studies. We have applied a more detailed model approach, which includes variation in the demand for sea transport, as well as operational and technological changes of the past. This study concludes that the main reason for the large deviations found in reported inventories is the applied number of days at sea. Moreover, our modeling indicates that the ship size and the degree of utilization of the fleet, combined with the shift to diesel engines, have been the major factors determining yearly fuel consumption. Interestingly, the model results from around 1973 suggest that the fleet growth is not necessarily followed by increased fuel consumption, as technical and operational characteristics have changed. Results from this study indicate that reported sales over the last 3 decades seems not to be significantly underreported as previous simplified activity-based studies have suggested. The results confirm our previously reported modeling estimates for year 2000. Previous activity-based studies have not considered ships less than 100 GT (e.g., today some 1.3 million fishing vessels), and we suggest that this fleet could account for an important part of the total fuel consumption (˜10%).

A comparison of ground-based and aircraft-based methane emission flux estimates in a western oil and natural gas production basin

NASA Astrophysics Data System (ADS)

Snare, Dustin A.

Recent increases in oil and gas production from unconventional reservoirs has brought with it an increase of methane emissions. Estimating methane emissions from oil and gas production is complex due to differences in equipment designs, maintenance, and variable product composition. Site access to oil and gas production equipment can be difficult and time consuming, making remote assessment of emissions vital to understanding local point source emissions. This work presents measurements of methane leakage made from a new ground-based mobile laboratory and a research aircraft around oil and gas fields in the Upper Green River Basin (UGRB) of Wyoming in 2014. It was recently shown that the application of the Point Source Gaussian (PSG) method, utilizing atmospheric dispersion tables developed by US EPA (Appendix B), is an effective way to accurately measure methane flux from a ground-based location downwind of a source without the use of a tracer (Brantley et al., 2014). Aircraft measurements of methane enhancement regions downwind of oil and natural gas production and Planetary Boundary Layer observations are utilized to obtain a flux for the entire UGRB. Methane emissions are compared to volumes of natural gas produced to derive a leakage rate from production operations for individual production sites and basin-wide production. Ground-based flux estimates derive a leakage rate of 0.14 - 0.78 % (95 % confidence interval) per site with a mass-weighted average (MWA) of 0.20 % for all sites. Aircraft-based flux estimates derive a MWA leakage rate of 0.54 - 0.91 % for the UGRB.

Uncertainty in temperature response of current consumption-based emissions estimates

NASA Astrophysics Data System (ADS)

Karstensen, J.; Peters, G. P.; Andrew, R. M.

2015-05-01

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties along the entire causal chain. We estimate uncertainties in economic data, multi-pollutant emission statistics, and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. Based on our assumptions, which exclude correlations in the economic data, the uncertainty in the economic data appears to have a relatively small impact on uncertainty at the national level in comparison to emissions and metric uncertainty. Much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production-based emissions since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±10 to ±27 % using the Global Temperature Potential with a 50-year time horizon, with metric uncertainties dominating. National-level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top 10 emitting regions have a broad uncertainty range of ±9 to ±25 %, with metric and emission uncertainties contributing similarly. The absolute global temperature potential (AGTP) with a 50-year time horizon has much higher uncertainties, with considerable uncertainty overlap for regions and sectors, indicating that the ranking of countries is uncertain.

Uncertainty in temperature response of current consumption-based emissions estimates

NASA Astrophysics Data System (ADS)

Karstensen, J.; Peters, G. P.; Andrew, R. M.

2014-09-01

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties in the end results. We estimate uncertainties in economic data, multi-pollutant emission statistics and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. The economic data have a relatively small impact on uncertainty at the global and national level, while much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production based emissions, since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±9-±27% using the global temperature potential with a 50 year time horizon, with metric uncertainties dominating. National level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top 10 emitting regions have a broad uncertainty range of ±9-±25%, with metric and emissions uncertainties contributing similarly. The Absolute global temperature potential with a 50 year time horizon has much higher uncertainties, with considerable uncertainty overlap for regions and sectors, indicating that the ranking of countries is uncertain.

Improved rice residue burning emissions estimates: Accounting for practice-specific emission factors in air pollution assessments of Vietnam.

PubMed

Lasko, Kristofer; Vadrevu, Krishna

2018-05-01

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for PM 2.5 . We found significant differences in the resulting burning-practice specific emission factors, with 16.9 g kg -2 (±6.9) for pile burning and 8.8 g kg -2 (±3.5) for non-pile burning. We calculated burning-practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 Gg of PM 2.5 result from the pile burning method and 130 Gg result from non-pile burning method, with the most-likely current emission scenario of 150 Gg PM 2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 Gg PM 2.5 , which is only 44% of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18% of Vietnam's total PM 2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices. Copyright © 2018 Elsevier Ltd. All rights reserved.

In-use measurement of activity, energy use, and emissions of a plug-in hybrid electric vehicle.

PubMed

Graver, Brandon M; Frey, H Christopher; Choi, Hyung-Wook

2011-10-15

Plug-in hybrid electric vehicles (PHEVs) could reduce transportation air emissions and energy use. However, a method is needed for estimating on-road emissions of PHEVs. To develop a framework for quantifying microscale energy use and emissions (EU&E), measurements were conducted on a Toyota Prius retrofitted with a plug-in battery system on eight routes. Measurements were made using the following: (1) a data logger for the hybrid control system; (2) a portable emissions measurement system; and (3) a global positioning system with barometric altimeter. Trends in EU&E are estimated based on vehicle specific power. Energy economy is quantified based on gasoline consumed by the engine and grid energy consumed by the plug-in battery. Emissions from electricity consumption are estimated based on the power generation mix. Fuel use is approximately 30% lower during plug-in battery use. Grid emissions were higher for CO₂, NO(x), SO₂, and PM compared to tailpipe emissions but lower for CO and hydrocarbons. EU&E depends on engine and plug-in battery operation. The use of two energy sources must be addressed in characterizing fuel economy; overall energy economy is 11% lower if including grid energy use than accounting only for fuel consumption.

Speed Profiles for Improvement of Maritime Emission Estimation

PubMed Central

Yau, Pui Shan; Lee, Shun-Cheng; Ho, Kin Fai

2012-01-01

Abstract Maritime emissions play an important role in anthropogenic emissions, particularly for cities with busy ports such as Hong Kong. Ship emissions are strongly dependent on vessel speed, and thus accurate vessel speed is essential for maritime emission studies. In this study, we determined minute-by-minute high-resolution speed profiles of container ships on four major routes in Hong Kong waters using Automatic Identification System (AIS). The activity-based ship emissions of NOx, CO, HC, CO2, SO2, and PM10 were estimated using derived vessel speed profiles, and results were compared with those using the speed limits of control zones. Estimation using speed limits resulted in up to twofold overestimation of ship emissions. Compared with emissions estimated using the speed limits of control zones, emissions estimated using vessel speed profiles could provide results with up to 88% higher accuracy. Uncertainty analysis and sensitivity analysis of the model demonstrated the significance of improvement of vessel speed resolution. From spatial analysis, it is revealed that SO2 and PM10 emissions during maneuvering within 1 nautical mile from port were the highest. They contributed 7%–22% of SO2 emissions and 8%–17% of PM10 emissions of the entire voyage in Hong Kong. PMID:23236250

Greenhouse gas emissions from vegetation fires in Southern Africa.

PubMed

Scholes, R J

1995-01-01

Methane (CH4), carbon monoxide (CO), nitrogen oxides (NOx), volatile organic carbon, and aerosols emitted as a result of the deliberate or accidental burning of natural vegetation constitute a large component of the greenhouse gas emissions of many African countries, but the data needed for calculating these emissions by the IPCC methodology is sparse and subject to estimation errors. An improved procedure for estimating emissions from fires in southern Africa has been developed. The proposed procedure involves reclassifying existing vegetation maps into one of eleven broad, functional vegetation classes. Fuel loads are calculated within each 0.5 × 0.5° cell based on empirical relationships to climate data for each class. The fractional area of each class that burns is estimated by using daily low-resolution satellite fire detection, which is calibrated against a subsample of pre- and post-fire high-resolution satellite images. The emission factors that relate the quantity of gas released to the mass of fuel burned are based on recent field campaigns in Africa and are related to combustion efficiency, which is in turn related to the fuel mix. The emissions are summed over the 1989 fire season for Africa south of the equator. The estimated emissions from vegetation burning in the subcontinent are 0.5 Tg CH4, 14.9 Tg CO, 1.05 Tg NOx, and 1.08 Tg of particles smaller than 2.5µm. The 324 Tg CO2 emitted is expected to be reabsorbed in subsequent years. These estimates are smaller than previous estimates.

Verification of Agricultural Methane Emission Inventories

NASA Astrophysics Data System (ADS)

Desjardins, R. L.; Pattey, E.; Worth, D. E.; VanderZaag, A.; Mauder, M.; Srinivasan, R.; Worthy, D.; Sweeney, C.; Metzger, S.

2017-12-01

It is estimated that agriculture contributes more than 40% of anthropogenic methane (CH4) emissions in North America. However, these estimates, which are either based on the Intergovernmental Panel on Climate Change (IPCC) methodology or inverse modeling techniques, are poorly validated due to the challenges of separating interspersed CH4 sources within agroecosystems. A flux aircraft, instrumented with a fast-response Picarro CH4 analyzer for the eddy covariance (EC) technique and a sampling system for the relaxed eddy accumulation technique (REA), was flown at an altitude of about 150 m along several 20-km transects over an agricultural region in Eastern Canada. For all flight days, the top-down CH4 flux density measurements were compared to the footprint adjusted bottom-up estimates based on an IPCC Tier II methodology. Information on the animal population, land use type and atmospheric and surface variables were available for each transect. Top-down and bottom-up estimates of CH4 emissions were found to be poorly correlated, and wetlands were the most frequent confounding source of CH4; however, there were other sources such as waste treatment plants and biodigesters. Spatially resolved wavelet covariance estimates of CH4 emissions helped identify the contribution of wetlands to the overall CH4 flux, and the dependence of these emissions on temperature. When wetland contribution in the flux footprint was minimized, top-down and bottom-up estimates agreed to within measurement error. This research demonstrates that although existing aircraft-based technology can be used to verify regional ( 100 km2) agricultural CH4 emissions, it remains challenging due to diverse sources of CH4 present in many regions. The use of wavelet covariance to generate spatially-resolved flux estimates was found to be the best way to separate interspersed sources of CH4.

An estimation of vehicle kilometer traveled and on-road emissions using the traffic volume and travel speed on road links in Incheon City.

PubMed

Jung, Sungwoon; Kim, Jounghwa; Kim, Jeongsoo; Hong, Dahee; Park, Dongjoo

2017-04-01

The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.11 times greater than that of the applied traffic volumes because each VKT estimation method is different. Therefore, we had to define the inner VKT is moved VKT inner in urban to compare two values. Also, we focused on freight modes because these are discharged much air pollutant emissions. From analysis results, we found middle and large trucks registered in other regions traveled to target city in order to carry freight, target city has included many industrial and logistics areas. Freight is transferred through the harbors, large logistics centers, or via locations before being moved to the final destination. During this process, most freight is moved by middle and large trucks, and trailers rather than small trucks for freight import and export. Therefore, these trucks from other areas are inflow more than registered vehicles. Most emissions from diesel trucks had been overestimated in comparison to VKT from applied traffic volumes in target city. From these findings, VKT is essential based on traffic volume and travel speed on road links in order to estimate accurately the emissions of diesel trucks in target city. Our findings support the estimation of the effect of on-road emissions on urban air quality in Korea. Copyright © 2016. Published by Elsevier B.V.

A review of land-based greenhouse gas flux estimates in Indonesia

NASA Astrophysics Data System (ADS)

Austin, Kemen G.; Harris, Nancy L.; Wijaya, Arief; Murdiyarso, Daniel; Harvey, Tom; Stolle, Fred; Kasibhatla, Prasad S.

2018-05-01

This study examines underlying reasons for differences among land-based greenhouse gas flux estimates in Indonesia, where six national inventories reported average emissions of between 0.4 and 1.1 Gt CO2e yr‑1 over the 2000–2012 period. The large range among estimates is only somewhat smaller than Indonesia’s GHG mitigation commitment. To determine the reasons for these differences, we compared input data and estimation methods, including the definitions and assumptions used for setting accounting boundaries, including emitting activities, incorporating fluxes from various carbon pools, and handling legacy fluxes. We also tested the sensitivity of methodological differences by generating our own reference emissions estimate and iteratively modifying individual components of the inventory. We found that the largest changes stem from the inclusion of legacy GHG emissions due to peat drainage (which increased emissions by at least +94% compared to the reference), methane emissions due to peat fires (+35%), and GHG emissions from belowground biomass and necromass carbon pools (+61%), modifications to assumptions of the mass of fuel burnt in peat fire events (+88%), and accounting for regrowth following a deforestation event (‑31%). These differences cumulatively explain more than half of the observed difference among inventory estimates. Understanding the various approaches to emissions estimation, and how these influence the magnitude of component GHG fluxes, is an important first step towards reconciling GHG inventories. The Indonesian government’s success in achieving its mitigation goal will depend on its ability to measure progress and evaluate the effectiveness of abatement actions, for which reliable harmonized greenhouse gas inventories are an essential foundation.

[Estimation of average traffic emission factor based on synchronized incremental traffic flow and air pollutant concentration].

PubMed

Li, Run-Kui; Zhao, Tong; Li, Zhi-Peng; Ding, Wen-Jun; Cui, Xiao-Yong; Xu, Qun; Song, Xian-Feng

2014-04-01

On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.

New methodology for estimating biofuel consumption for cooking: Atmospheric emissions of black carbon and sulfur dioxide from India

NASA Astrophysics Data System (ADS)

Habib, Gazala; Venkataraman, Chandra; Shrivastava, Manish; Banerjee, Rangan; Stehr, J. W.; Dickerson, Russell R.

2004-09-01

The dominance of biofuel combustion emissions in the Indian region, and the inherently large uncertainty in biofuel use estimates based on cooking energy surveys, prompted the current work, which develops a new methodology for estimating biofuel consumption for cooking. This is based on food consumption statistics, and the specific energy for food cooking. Estimated biofuel consumption in India was 379 (247-584) Tg yr-1. New information on the user population of different biofuels was compiled at a state level, to derive the biofuel mix, which varied regionally and was 74:16:10%, respectively, of fuelwood, dung cake and crop waste, at a national level. Importantly, the uncertainty in biofuel use from quantitative error assessment using the new methodology is around 50%, giving a narrower bound than in previous works. From this new activity data and currently used black carbon emission factors, the black carbon (BC) emissions from biofuel combustion were estimated as 220 (65-760) Gg yr-1. The largest BC emissions were from fuelwood (75%), with lower contributions from dung cake (16%) and crop waste (9%). The uncertainty of 245% in the BC emissions estimate is now governed by the large spread in BC emission factors from biofuel combustion (122%), implying the need for reducing this uncertainty through measurements. Emission factors of SO2 from combustion of biofuels widely used in India were measured, and ranged 0.03-0.08 g kg-1 from combustion of two wood species, 0.05-0.20 g kg-1 from 10 crop waste types, and 0.88 g kg-1 from dung cake, significantly lower than currently used emission factors for wood and crop waste. Estimated SO2 emissions from biofuels of 75 (36-160) Gg yr-1 were about a factor of 3 lower than that in recent studies, with a large contribution from dung cake (73%), followed by fuelwood (21%) and crop waste (6%).

A bottom up approach to on-road CO2 emissions estimates: improved spatial accuracy and applications for regional planning.

PubMed

Gately, Conor K; Hutyra, Lucy R; Wing, Ian Sue; Brondfield, Max N

2013-03-05

On-road transportation is responsible for 28% of all U.S. fossil-fuel CO2 emissions. Mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories use spatial proxies such as population and road density to downscale national or state-level data. Such procedures introduce errors where the proxy variables and actual emissions are weakly correlated, and limit analysis of the relationship between emissions and demographic trends at local scales. We develop an on-road emission inventory product for Massachusetts-based on roadway-level traffic data obtained from the Highway Performance Monitoring System (HPMS). We provide annual estimates of on-road CO2 emissions at a 1 × 1 km grid scale for the years 1980 through 2008. We compared our results with on-road emissions estimates from the Emissions Database for Global Atmospheric Research (EDGAR), with the Vulcan Product, and with estimates derived from state fuel consumption statistics reported by the Federal Highway Administration (FHWA). Our model differs from FHWA estimates by less than 8.5% on average, and is within 5% of Vulcan estimates. We found that EDGAR estimates systematically exceed FHWA by an average of 22.8%. Panel regression analysis of per-mile CO2 emissions on population density at the town scale shows a statistically significant correlation that varies systematically in sign and magnitude as population density increases. Population density has a positive correlation with per-mile CO2 emissions for densities below 2000 persons km(-2), above which increasing density correlates negatively with per-mile emissions.

Historical emissions of carbonaceous aerosols from biomass and fossil fuel burning for the period 1870-2000

NASA Astrophysics Data System (ADS)

Ito, Akinori; Penner, Joyce E.

2005-06-01

Historical changes of black carbon (BC) and particulate organic matter (POM) emissions from biomass burning (BB) and fossil fuel (FF) burning are estimated from 1870 to 2000. A bottom-up inventory for open vegetation (OV) burning is scaled by a top-down estimate for the year 2000. Monthly and interannual variations are derived over the time period from 1979 to 2000 based on the TOMS satellite aerosol index (AI) and this global map. Prior to 1979, emissions are scaled to a CH4 emissions inventory based on land-use change. Biofuel (BF) emissions from a recent inventory for developing countries are scaled forward and backward in time using population statistics and crop production statistics. In developed countries, wood consumption data together with emission factors for cooking and heating practices are used for biofuel estimates. For fossil fuel use, we use fuel consumption data and specific emission factors for different fuel use categories to develop an inventory over 1950-2000, and emissions are scaled to a CO2 inventory prior to that time. Technology changes for emissions from the diesel transport sector are included. During the last decade of this time period, the BC and POM emissions from biomass burning (i.e., OV + BF) contribute a significant amount to the primary sources of BC and POM and are larger than those from FF. Thus 59% of the NH BC emissions and 90% of the NH POM emissions are from BB in 2000. Fossil fuel consumption technologies are needed prior to 1990 in order to improve estimates of fossil fuel emissions during the twentieth century. These results suggest that the aerosol emissions from biomass burning need to be represented realistically in climate change assessments. The estimated emissions are available on a 1° × 1° grid for global climate modeling studies of climate changes.

ESTIMATE OF GLOBAL METHANE EMISSIONS FROM LANDFILLS AND OPEN DUMPS

EPA Science Inventory

The report presents an empirical model to estimate global methane (CH4) emissions from landfills and open dumps based on EPA data from landfill gas (LFG) recovery projects. The EPA CH4 estimates for 1990 range between 19 and 40 teragrams (10 to the 12th power) per year (Tg/yr), w...

A Pilot Study to Evaluate California's Fossil Fuel CO2 Emissions Using Atmospheric Observations

NASA Astrophysics Data System (ADS)

Graven, H. D.; Fischer, M. L.; Lueker, T.; Guilderson, T.; Brophy, K. J.; Keeling, R. F.; Arnold, T.; Bambha, R.; Callahan, W.; Campbell, J. E.; Cui, X.; Frankenberg, C.; Hsu, Y.; Iraci, L. T.; Jeong, S.; Kim, J.; LaFranchi, B. W.; Lehman, S.; Manning, A.; Michelsen, H. A.; Miller, J. B.; Newman, S.; Paplawsky, B.; Parazoo, N.; Sloop, C.; Walker, S.; Whelan, M.; Wunch, D.

2016-12-01

Atmospheric CO2 concentration is influenced by human activities and by natural exchanges. Studies of CO2 fluxes using atmospheric CO2 measurements typically focus on natural exchanges and assume that CO2 emissions by fossil fuel combustion and cement production are well-known from inventory estimates. However, atmospheric observation-based or "top-down" studies could potentially provide independent methods for evaluating fossil fuel CO2 emissions, in support of policies to reduce greenhouse gas emissions and mitigate climate change. Observation-based estimates of fossil fuel-derived CO2 may also improve estimates of biospheric CO2 exchange, which could help to characterize carbon storage and climate change mitigation by terrestrial ecosystems. We have been developing a top-down framework for estimating fossil fuel CO2 emissions in California that uses atmospheric observations and modeling. California is implementing the "Global Warming Solutions Act of 2006" to reduce total greenhouse gas emissions to 1990 levels by 2020, and it has a diverse array of ecosystems that may serve as CO2 sources or sinks. We performed three month-long field campaigns in different seasons in 2014-15 to collect flask samples from a state-wide network of 10 towers. Using measurements of radiocarbon in CO2, we estimate the fossil fuel-derived CO2 present in the flask samples, relative to marine background air observed at coastal sites. Radiocarbon (14C) is not present in fossil fuel-derived CO2 because of radioactive decay over millions of years, so fossil fuel emissions cause a measurable decrease in the 14C/C ratio in atmospheric CO2. We compare the observations of fossil fuel-derived CO2 to simulations based on atmospheric modeling and published fossil fuel flux estimates, and adjust the fossil fuel flux estimates in a statistical inversion that takes account of several uncertainties. We will present the results of the top-down technique to estimate fossil fuel emissions for our field campaigns in California, and we will give an outlook for future development of the technique in California.

Emission estimates of selected volatile organic compounds from tropical savanna burning in northern Australia

NASA Astrophysics Data System (ADS)

Shirai, T.; Blake, D. R.; Meinardi, S.; Rowland, F. S.; Russell-Smith, J.; Edwards, A.; Kondo, Y.; Koike, M.; Kita, K.; Machida, T.; Takegawa, N.; Nishi, N.; Kawakami, S.; Ogawa, T.

2003-02-01

Here we present measurements of a range of carbon-based compounds: carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), nonmethane hydrocarbons (NMHCs), methyl halides, and dimethyl sulfide (DMS) emitted by Australian savanna fires studied as part of the Biomass Burning and Lightning Experiment (BIBLE) phase B aircraft campaign, which took place during the local late dry season (28 August to 13 September 1999). Significant enhancements of short-lived NMHCs were observed in the boundary layer (BL) over the region of intensive fires and indicate recent emissions for which the mean transport time was estimated to be about 9 hours. Emission ratios relative to CO were determined for 20 NMHCs, 3 methyl halides, DMS, and CH4 based on the BL enhancements in the source region. Tight correlations with CO were obtained for most of those compounds, indicating the homogeneity of the local savanna source. The emission ratios were in good agreement with some previous measurements of savanna fires for stable compounds but indicated the decay of emission ratios during transport for several reactive compounds. Based on the observed emission ratios, emission factors were derived and compared to previous studies. While emission factors (g species/kg dry mole) of CO2 varied little according to the vegetation types, those of CO and NMHCs varied significantly. Higher combustion efficiency and a lower emission factor for methane in this study, compared to forest fires, agreed well with results for savanna fires in other tropical regions. The amount of biomass burned was estimated by modeling methods using available satellite data, and showed that 1999 was an above average year for savanna burning. The gross emissions of the trace gases from Australian savanna fires were estimated.

Quantification of Shipping Emissions in the Eastern Mediterranean and Comparison with Satellite Observations

NASA Astrophysics Data System (ADS)

Kilic, A.; Unal, A.; Kindap, T.; Karaca, M.; Khan, M. N.

2010-12-01

Shipping is considered as one of the main emission sources worldwide. Recent studies suggest that, in the Mediterrenean, ship emissions are responsible for 10-50% of black carbon, 2-12% ozone in the surface layer and 5-20% for nitrogen dioxide atmospheric column burden (Marmer et al., 2009). It is, therefore, essential to have an accurate emissions estimation for ships. Marmara Sea, an inland sea connecting the Mediterrenean to the Black Sea, has significant marine activity. Marmara region, surrounding the Marmara Sea, has over 30 million population (including Istanbul megacity) with significant emission sources (e.g., on-road traffic, industry). Emission amounts from ships can be calculated based on two different methodologies, one is according to the total amount of bunker fuels for maritime transport sold which is called top down approach and the other is shipping activity-based bottom-up approach. The top-down estimation method is not suitable for calculations of shipping emissions in Turkey since fuel sales cannot be accurately obtained. Also, top-down approaches possibly have some errors, since data assumptions for the average engine power, engine operating hours and emission factors are the most important uncertain inputs. Previously, a few studies based on bottom-up aproach have been carried on about shipping emissions in Marmara Sea according to the shipping statistics belong to Istanbul and Canakkale Straits and port regions. These studies were mainly depending on very rough assumptions such as avearage ship speed, fixed ships routes, generalized engine types and average fuel consumptions. Deniz C. (2008) estimated shipping emissions in 2003, for Marmara Sea and Turkish Straits as 111,000 tons for NOx, 87,000 tons for SO2, 5,451,000 tons for CO2, 4762 tons for PM. Although- between 2003 and 2008- there is approximately 15% increase in number of ships passsing through Turkish Straits, this study shows that, shippings emissions for the same region are estimated to be more than 3 times of previous studies. In this study, Automatic Information System (AIS) records of marine vessels (having 1 minute temporal resolution) for over 10,000 ships operating at the study area (including Marmara Sea, Istanbul and Canakkale Straits and some parts of Black Sea and Aegian Sea) were obtained from Turkish Undersecretariat for Maritime Affairs for the period between August 2008 and August 2009. These records include the position of the ships, gross tonnage and ship types. Using energy based emission factors for each operation mode, minute-by-minute emissions were estimated. Annual emission totals for merchant ships were estimated as 605,000 tons for NOX; 495,000 tons for SO2; 25,600 tons for HC; 53,300 tons for PM and 29,630,000 tons for CO2. This paper presents the methodology and the findings of the emissions estimates for ships. The results will also be compared to satellite observations. For this purpose, CO measurements from MOPITT and SO2 measurements from OMI will be utilized.

Estimation of mercury emission from different sources to atmosphere in Chongqing, China.

PubMed

Wang, Dingyong; He, Lei; Wei, Shiqiang; Feng, Xinbin

2006-08-01

This investigation presents a first assessment of the contribution to the regional mercury budget from anthropogenic and natural sources in Chongqing, an important industrial region in southwest China. The emissions of mercury to atmosphere from anthropogenic sources in the region were estimated through indirect approaches, i.e. using commonly acceptable emission factors method, which based on annual process throughputs or consumption for these sources. The natural mercury emissions were estimated from selected natural sources by the dynamic flux chamber technique. The results indicated that the anthropogenic mercury emissions totaled approximately 8.85 tons (t), more than 50% of this total originated in coal combustion and 23.7% of this total emission in the industrial process (include cement production, metal smelting and chemical industry). The natural emissions represented approximately 17% of total emissions (1.78 t yr(-1)). The total mercury emission to atmosphere in Chongqing in 2001 was 10.63 t.

The activity-based methodology to assess ship emissions - A review.

PubMed

Nunes, R A O; Alvim-Ferraz, M C M; Martins, F G; Sousa, S I V

2017-12-01

Several studies tried to estimate atmospheric emissions with origin in the maritime sector, concluding that it contributed to the global anthropogenic emissions through the emission of pollutants that have a strong impact on hu' health and also on climate change. Thus, this paper aimed to review published studies since 2010 that used activity-based methodology to estimate ship emissions, to provide a summary of the available input data. After exclusions, 26 articles were analysed and the main information were scanned and registered, namely technical information about ships, ships activity and movement information, engines, fuels, load and emission factors. The larger part of studies calculating in-port ship emissions concluded that the majority was emitted during hotelling and most of the authors allocating emissions by ship type concluded that containerships were the main pollutant emitters. To obtain technical information about ships the combined use of data from Lloyd's Register of Shipping database with other sources such as port authority's databases, engine manufactures and ship-owners seemed the best approach. The use of AIS data has been growing in recent years and seems to be the best method to report activities and movements of ships. To predict ship powers the Hollenbach (1998) method which estimates propelling power as a function of instantaneous speed based on total resistance and use of load balancing schemes for multi-engine installations seemed to be the best practices for more accurate ship emission estimations. For emission factors improvement, new on-board measurement campaigns or studies should be undertaken. Regardless of the effort that has been performed in the last years to obtain more accurate shipping emission inventories, more precise input data (technical information about ships, engines, load and emission factors) should be obtained to improve the methodology to develop global and universally accepted emission inventories for an effective environmental policy plan. Copyright © 2017 Elsevier Ltd. All rights reserved.

Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

2009-12-01

The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

Methodology of Estimation of Methane Emissions from Coal Mines in Poland

NASA Astrophysics Data System (ADS)

Patyńska, Renata

2014-03-01

Based on a literature review concerning methane emissions in Poland, it was stated in 2009 that the National Greenhouse Inventory 2007 [13] was published. It was prepared firstly to meet Poland's obligations resulting from point 3.1 Decision no. 280/2004/WE of the European Parliament and of the Council of 11 February 2004, concerning a mechanism for monitoring community greenhouse gas emissions and for implementing the Kyoto Protocol and secondly, for the United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol. The National Greenhouse Inventory states that there are no detailed data concerning methane emissions in collieries in the Polish mining industry. That is why the methane emission in the methane coal mines of Górnośląskie Zagłębie Węglowe - GZW (Upper Silesian Coal Basin - USCB) in Poland was meticulously studied and evaluated. The applied methodology for estimating methane emission from the GZW coal mining system was used for the four basic sources of its emission. Methane emission during the mining and post-mining process. Such an approach resulted from the IPCC guidelines of 2006 [10]. Updating the proposed methods (IPCC2006) of estimating the methane emissions of hard coal mines (active and abandoned ones) in Poland, assumes that the methane emission factor (EF) is calculated based on methane coal mine output and actual values of absolute methane content. The result of verifying the method of estimating methane emission during the mining process for Polish coal mines is the equation of methane emission factor EF.

Estimate of Fuel Consumption and GHG Emission Impact from an Automated Mobility District

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuche; Young, Stanley; Qi, Xuewei

2015-10-19

This study estimates the range of fuel and emissions impact of an automated-vehicle (AV) based transit system that services campus-based developments, termed an automated mobility district (AMD). The study develops a framework to quantify the fuel consumption and greenhouse gas (GHG) emission impacts of a transit system comprised of AVs, taking into consideration average vehicle fleet composition, fuel consumption/GHG emission of vehicles within specific speed bins, and the average occupancy of passenger vehicles and transit vehicles. The framework is exercised using a previous mobility analysis of a personal rapid transit (PRT) system, a system which shares many attributes with envisionedmore » AV-based transit systems. Total fuel consumption and GHG emissions with and without an AMD are estimated, providing a range of potential system impacts on sustainability. The results of a previous case study based of a proposed implementation of PRT on the Kansas State University (KSU) campus in Manhattan, Kansas, serves as the basis to estimate personal miles traveled supplanted by an AMD at varying levels of service. The results show that an AMD has the potential to reduce total system fuel consumption and GHG emissions, but the amount is largely dependent on operating and ridership assumptions. The study points to the need to better understand ride-sharing scenarios and calls for future research on sustainability benefits of an AMD system at both vehicle and system levels.« less

Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

NASA Astrophysics Data System (ADS)

Bergamaschi, Peter; Karstens, Ute; Manning, Alistair J.; Saunois, Marielle; Tsuruta, Aki; Berchet, Antoine; Vermeulen, Alexander T.; Arnold, Tim; Janssens-Maenhout, Greet; Hammer, Samuel; Levin, Ingeborg; Schmidt, Martina; Ramonet, Michel; Lopez, Morgan; Lavric, Jost; Aalto, Tuula; Chen, Huilin; Feist, Dietrich G.; Gerbig, Christoph; Haszpra, László; Hermansen, Ove; Manca, Giovanni; Moncrieff, John; Meinhardt, Frank; Necki, Jaroslaw; Galkowski, Michal; O'Doherty, Simon; Paramonova, Nina; Scheeren, Hubertus A.; Steinbacher, Martin; Dlugokencky, Ed

2018-01-01

We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006-2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2-29.7) Tg CH4 yr-1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006-2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr-1 (2006) to 18.8 Tg CH4 yr-1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3-8.2) Tg CH4 yr-1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between -40 and 20 % at the aircraft profile sites in France, Hungary and Poland.

Estimation of carbon dioxide emissions per urban center link unit using data collected by the Advanced Traffic Information System in Daejeon, Korea

NASA Astrophysics Data System (ADS)

Ryu, B. Y.; Jung, H. J.; Bae, S. H.; Choi, C. U.

2013-12-01

CO2 emissions on roads in urban centers substantially affect global warming. It is important to quantify CO2 emissions in terms of the link unit in order to reduce these emissions on the roads. Therefore, in this study, we utilized real-time traffic data and attempted to develop a methodology for estimating CO2 emissions per link unit. Because of the recent development of the vehicle-to-infrastructure (V2I) communication technology, data from probe vehicles (PVs) can be collected and speed per link unit can be calculated. Among the existing emission calculation methodologies, mesoscale modeling, which is a representative modeling measurement technique, requires speed and traffic data per link unit. As it is not feasible to install fixed detectors at every link for traffic data collection, in this study, we developed a model for traffic volume estimation by utilizing the number of PVs that can be additionally collected when the PV data are collected. Multiple linear regression and an artificial neural network (ANN) were used for estimating the traffic volume. The independent variables and input data for each model are the number of PVs, travel time index (TTI), the number of lanes, and time slots. The result from the traffic volume estimate model shows that the mean absolute percentage error (MAPE) of the ANN is 18.67%, thus proving that it is more effective. The ANN-based traffic volume estimation served as the basis for the calculation of emissions per link unit. The daily average emissions for Daejeon, where this study was based, were 2210.19 ton/day. By vehicle type, passenger cars accounted for 71.28% of the total emissions. By road, Gyeryongro emitted 125.48 ton/day, accounting for 5.68% of the total emission, the highest percentage of all roads. In terms of emissions per kilometer, Hanbatdaero had the highest emission volume, with 7.26 ton/day/km on average. This study proves that real-time traffic data allow an emissions estimate in terms of the link unit. Furthermore, an analysis of CO2 emissions can support traffic management to make decisions related to the reduction of carbon emissions.

Economic Data and Models in a Greenhouse Gas Monitoring System (Invited)

NASA Astrophysics Data System (ADS)

Reilly, J. M.

2010-12-01

Under the Framework Convention for Climate Change a system of inventory reporting of greenhouse gas emissions has been developed (UNFCCC, 2010). The system is based on a bottom-up approach that identifies activities associated with emissions (e.g. coal burning, rice production), develops coefficients associated with each unit of the activity (ton of coal, hectare of rice), and then based on the level of the activity (total tons, hectares) arrives through multiplication at an estimate of annual emissions at a country level. Tier 1, 2, and 3 approaches vary in the level of detail taken into account in making estimates, in large part attempting to take account of variation in emissions coefficients based on experimental measurements that may not be representative of the countries actual activities (differences among rice fields, livestock, etc). Top-down approaches use direct measurements of concentrations of GHGs in the atmosphere and inverse methods and assimilated weather data to estimate emissions sources (e.g. Prinn, 2000). The statistical approaches used rely on known relationships, measurements, and estimates of error to reconcile different measurements to improve the estimate of interest—i.e. emissions. While inverse methods have typically relied on measurement of concentrations, economic data and relationships such as those used in bottom-up reporting could also be brought into the inverse calculations to reconcile estimates of anthropogenic emissions in national reports with those of natural emissions , of non-reporting countries, and of concentrations. For example, per unit emissions from coal, oil, or gas combustion are well constrained, and estimates of tons know reasonably well but with some uncertainty. Inverse methods may improve estimates of tons of fuel combusted but because they are relatively well known that information is likely to tightly constrain fossil emissions and thus improve the estimate of emissions from land use change which are more poorly known. If inverse methods are to be used for treaty verification, it would seem particularly important to incorporate economic data because so far treaties have covered emissions from "anthropogenic" emissions and there may not be a distinct physical signature to identify concentration changes related to legally defined anthropogenic sources from natural sources (e.g. emissions or uptake on managed forest land from a natural change in uptake of carbon on land or nitrous oxide emissions related to land management (inorganic or organic fertilizers) from N2O from natural cycles. There are many issues that would need to be resolved to effectively utilize economic activity data in inverse calculations. In particular, economic activity data often lacks spatial and temporal resolution as it is reported for political units (e.g. at the national level) and often only annually. However, given the potential gain these data could contribute to top down estimates it is worth further investigating their incorporation, and it may give impetus to efforts to create economic data sets with greater spatial and temporal resolution. Prinn, R.G., 2000: Measurement Equation for Trace Chemicals in Fluids and Solution of its Inverse, in Inverse Methods in Global Biogeochemical Cycles, Geophysical Monograph 114, American Geophysical Union. UNFCCC, 2010, National Reports at http://unfccc.int/national_reports/items/1408.php

The global distribution of ammonia emissions from seabird colonies

NASA Astrophysics Data System (ADS)

Riddick, S. N.; Dragosits, U.; Blackall, T. D.; Daunt, F.; Wanless, S.; Sutton, M. A.

2012-08-01

Seabird colonies represent a significant source of atmospheric ammonia (NH3) in remote maritime systems, producing a source of nitrogen that may encourage plant growth, alter terrestrial plant community composition and affect the surrounding marine ecosystem. To investigate seabird NH3 emissions on a global scale, we developed a contemporary seabird database including a total seabird population of 261 million breeding pairs. We used this in conjunction with a bioenergetics model to estimate the mass of nitrogen excreted by all seabirds at each breeding colony. The results combined with the findings of mid-latitude field studies of volatilization rates estimate the global distribution of NH3 emissions from seabird colonies on an annual basis. The largest uncertainty in our emission estimate concerns the potential temperature dependence of NH3 emission. To investigate this we calculated and compared temperature independent emission estimates with a maximum feasible temperature dependent emission, based on the thermodynamic dissociation and solubility equilibria. Using the temperature independent approach, we estimate global NH3 emissions from seabird colonies at 404 Gg NH3 per year. By comparison, since most seabirds are located in relatively cold circumpolar locations, the thermodynamically dependent estimate is 136 Gg NH3 per year. Actual global emissions are expected to be within these bounds, as other factors, such as non-linear interactions with water availability and surface infiltration, moderate the theoretical temperature response. Combining sources of error from temperature (±49%), seabird population estimates (±36%), variation in diet composition (±23%) and non-breeder attendance (±13%), gives a mid estimate with an overall uncertainty range of NH3 emission from seabird colonies of 270 [97-442] Gg NH3 per year. These emissions are environmentally relevant as they primarily occur as "hot-spots" in otherwise pristine environments with low anthropogenic emissions.

Lebanese household carbon footprint: Measurements, analysis and challenges

NASA Astrophysics Data System (ADS)

Nasr, Rawad; Tall, Ibrahim; Nachabe, Nour; Chaaban, Farid

2016-07-01

The main purpose of this paper is to estimate the carbon footprint of a typical Lebanese household, and compare the results with international standards and trends. The estimation of this footprint will reflect the impact of the daily Lebanese household activities on the environment in terms of carbon dioxide emissions. The method used in estimating the carbon emissions is based on gathering the primary footprints from various household activities. Another proposed method that provides more accurate results is the estimation of emissions based on secondary footprint, which reflects the total emissions not only from the regular activities but also from a lifecycle perspective. Practical and feasible solutions were proposed to help reduce the amount of C02 emissions per household. This would lead to a better air quality, money savings, greenhouse gases emissions reduction and would ensure the sustainability and prosperity of future generations. A detailed survey was conducted in which the questions were focused mainly on energy, food, and transportation issues. The fourteen questions were addressed to one hundred families in different Lebanese regions coming from different social and economic backgrounds. This diversity would constitute a reflective sample of the actual Lebanese society, allowing us to extrapolate the gathered results on a national level.

Using RAQMS Chemical Transport Model, Aircraft In-situ and Satellite Data to Verify Ground-based Biomass Burning Emissions from the Extreme Fire Event in Boreal Alaska 2004

NASA Astrophysics Data System (ADS)

Soja, A. J.; Pierce, R. B.; Al-Saadi, J. A.; Alvarado, E.; Sandberg, D. V.; Ottmar, R. D.; Kittaka, C.; McMillian, W. W.; Sachse, G. W.; Warner, J. X.; Szykman, J. J.

2006-12-01

Current climate change scenarios are predicted to result in increased biomass burning, particularly in boreal regions. Biomass burning events feedback to the climate system by altering albedo (affecting the energy balance) and by direct and indirect fire emissions. Additionally, fire emissions influence air quality and human health downwind of burning. Biomass burning emission estimates are difficult to quantify in near-real-time and accurate estimates are useful for large-scale chemical transport models, which could be used to warn the public of potential health risks and for climate modeling. In this talk, we describe a methodology to quantify emissions, validate those emission estimates, transport the emissions and verify the resultant CO plume 100's of kilometers from the fire events using aircraft in-situ and satellite data. First, we developed carbon consumption estimates that are specifically designed for near-real-time use in conjunction with satellite-derived fire data for regional- to global-chemical transport models. Large-scale carbon consumption estimates are derived for 10 ecozones across North America and each zone contains 3 classes of severity. The estimates range is from a low severity 3.11 t C ha-1 estimate from the Western Taiga Shield to a high severity 59.83 t C ha-1 estimate from the Boreal Cordillera. These estimates are validated using extensive supplementary ground-based Alaskan data. Then, the RAQMS chemical transport model ingests these data and transports CO from the Alaskan 2004 fires across North America, where results are compared with in-situ flight CO data measured during INTEX-A and satellite-based CO data (AIRS and MOPITT). Ground-based CO is 6 to 14 times greater than the typically modeled fire climatology. RAQMS often overestimates CO in the biomass plumes in comparison to satellite- derived CO data and we suspect this may be due to the satellite instruments low sensitivity to planetary boundary layer CO, which is prevalent in the near field plumes, and also the assumption of high-severity fires throughout the burning season. RAQMS underestimates biomass CO in comparison to in-situ CO data (146 out of 148 ascents and descents), and we suspect this may be due to RAQMS difficulty in defining narrow fire plumes due to the 1.4° x 1.4° resolution.

Annual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751 - 2008) (V. 2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Boden, T. A. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Marland, G. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.

2012-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2008.html) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Monthly Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude by One Degree Longitude

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.

2015-01-01

The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2011.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).

Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model Over the Northern sub-Saharan African Region

NASA Astrophysics Data System (ADS)

Wang, Jun; Yue, Yun; Wang, Yi; Ichoku, Charles; Ellison, Luke; Zeng, Jing

2018-01-01

Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar-orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub-Saharan African region. Simulations from WRF-Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30-50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope.

Estimates of Power Plant NOx Emissions and Lifetimes from OMI NO2 Satellite Retrievals

NASA Technical Reports Server (NTRS)

de Foy, Benjamin; Lu, Zifeng; Streets, David G.; Lamsal, Lok N.; Duncan, Bryan N.

2015-01-01

Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.

Mapping pan-Arctic CH4 emissions using an adjoint method by integrating process-based wetland and lake biogeochemical models and atmospheric CH4 concentrations

NASA Astrophysics Data System (ADS)

Tan, Z.; Zhuang, Q.; Henze, D. K.; Frankenberg, C.; Dlugokencky, E. J.; Sweeney, C.; Turner, A. J.

2015-12-01

Understanding CH4 emissions from wetlands and lakes are critical for the estimation of Arctic carbon balance under fast warming climatic conditions. To date, our knowledge about these two CH4 sources is almost solely built on the upscaling of discontinuous measurements in limited areas to the whole region. Many studies indicated that, the controls of CH4 emissions from wetlands and lakes including soil moisture, lake morphology and substrate content and quality are notoriously heterogeneous, thus the accuracy of those simple estimates could be questionable. Here we apply a high spatial resolution atmospheric inverse model (nested-grid GEOS-Chem Adjoint) over the Arctic by integrating SCIAMACHY and NOAA/ESRL CH4 measurements to constrain the CH4 emissions estimated with process-based wetland and lake biogeochemical models. Our modeling experiments using different wetland CH4 emission schemes and satellite and surface measurements show that the total amount of CH4 emitted from the Arctic wetlands is well constrained, but the spatial distribution of CH4 emissions is sensitive to priors. For CH4 emissions from lakes, our high-resolution inversion shows that the models overestimate CH4 emissions in Alaskan costal lowlands and East Siberian lowlands. Our study also indicates that the precision and coverage of measurements need to be improved to achieve more accurate high-resolution estimates.

U.S. ENVIRONMENTAL PROTECTION AGENCY'S LANDFILL GAS EMISSION MODEL (LANDGEM)

EPA Science Inventory

The paper discusses EPA's available software for estimating landfill gas emissions. This software is based on a first-order decomposition rate equation using empirical data from U.S. landfills. The software provides a relatively simple approach to estimating landfill gas emissi...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nurten Vardar; Zehra Yumurtaci

The major gaseous emissions (e.g. sulfur dioxide, nitrogen oxides, carbon dioxide, and carbon monoxide), some various organic emissions (e.g. benzene, toluene and xylenes) and some trace metals (e.g. arsenic, cobalt, chromium, manganese and nickel) generated from lignite-fired power plants in Turkey are estimated. The estimations are made separately for each one of the thirteen plants that produced electricity in 2007, because the lignite-fired thermal plants in Turkey are installed near the regions where the lignite is mined, and characteristics and composition of lignite used in each power plant are quite different from a region to another. Emission factors methodology ismore » used for the estimations. The emission factors obtained from well-known literature are then modified depending on local moisture content of lignite. Emission rates and specific emissions (per MWh) of the pollutants from the plants without electrostatic precipitators and flue-gas desulfurization systems are found to be higher than emissions from the plants having electrostatic precipitators and flue -gas desulfurization systems. Finally a projection for the future emissions due to lignite-based power plants is given. Predicted demand for the increasing generation capacity based on the lignite-fired thermal power plant, from 2008 to 2017 is around 30%. 39 refs., 13 figs., 10 tabs.« less

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

DOE PAGES

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.; ...

2017-11-24

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

Evaluation of mobile source emission trends in the United States

NASA Astrophysics Data System (ADS)

Dallmann, Timothy R.; Harley, Robert A.

2010-07-01

A fuel-based approach is used to estimate exhaust emissions of nitrogen oxides (NOx) and fine particulate matter (PM2.5) from mobile sources in the United States for the years 1996-2006. Source categories considered include on-road and off-road gasoline and diesel engines. Pollutant emissions for each mobile source category were estimated by combining fuel consumption with emission factors expressed per unit of fuel burned. Over the 10-year time period that is the focus of this study, sales of gasoline and diesel fuel intended for on-road use increased by 15 and 43%, respectively. Diesel fuel use by off-road equipment increased by ˜20% over the same time period. Growth in fuel consumption offset some of the reductions in pollutant emission factors that occurred during this period. For NOx, there have been dramatic (factor of 2) decreases in emission factors for on-road gasoline engines between 1996 and 2006. In contrast, diesel NOx emission factors decreased more gradually. Exhaust PM2.5 emission factors appear to have decreased for most engine categories, but emission uncertainties are large for this pollutant. Diesel engines appear to be the dominant mobile source of both NOx and PM2.5; the diesel share of total NOx has increased over time as gasoline engine emissions have declined. Comparing fuel-based emission estimates with U.S. Environmental Protection Agency's national emission inventory led to the following conclusions: (1) total emissions of NOx and PM2.5 estimated by two different methods were similar, (2) source contributions to these totals differ significantly, with higher relative contributions coming from on-road diesel engines in this study.

Top-down estimates of methane and nitrogen oxide emissions from shale gas production regions using aircraft measurements and a mesoscale Bayesian inversion system together with a flux ratio inversion technique

NASA Astrophysics Data System (ADS)

Cui, Y.; Brioude, J. F.; Angevine, W. M.; McKeen, S. A.; Henze, D. K.; Bousserez, N.; Liu, Z.; McDonald, B.; Peischl, J.; Ryerson, T. B.; Frost, G. J.; Trainer, M.

2016-12-01

Production of unconventional natural gas grew rapidly during the past ten years in the US which led to an increase in emissions of methane (CH4) and, depending on the shale region, nitrogen oxides (NOx). In terms of radiative forcing, CH4 is the second most important greenhouse gas after CO2. NOx is a precursor of ozone (O3) in the troposphere and nitrate particles, both of which are regulated by the US Clean Air Act. Emission estimates of CH4 and NOx from the shale regions are still highly uncertain. We present top-down estimates of CH4 and NOx surface fluxes from the Haynesville and Fayetteville shale production regions using aircraft data collected during the Southeast Nexus of Climate Change and Air Quality (SENEX) field campaign (June-July, 2013) and the Shale Oil and Natural Gas Nexus (SONGNEX) field campaign (March-May, 2015) within a mesoscale inversion framework. The inversion method is based on a mesoscale Bayesian inversion system using multiple transport models. EPA's 2011 National CH4 and NOx Emission Inventories are used as prior information to optimize CH4 and NOx emissions. Furthermore, the posterior CH4 emission estimates are used to constrain NOx emission estimates using a flux ratio inversion technique. Sensitivity of the posterior estimates to the use of off-diagonal terms in the error covariance matrices, the transport models, and prior estimates is discussed. Compared to the ground-based in-situ observations, the optimized CH4 and NOx inventories improve ground level CH4 and O3 concentrations calculated by the Weather Research and Forecasting mesoscale model coupled with chemistry (WRF-Chem).

Top-down Estimates of Greenhouse Gas Intensities and Emissions for Individual Oil Sands Facilities in Alberta Canada

NASA Astrophysics Data System (ADS)

Liggio, J.; Li, S. M.; Staebler, R. M.; Hayden, K. L.; Mittermeier, R. L.; McLaren, R.; Baray, S.; Darlington, A.; Worthy, D.; O'Brien, J.

2017-12-01

The oil sands (OS) region of Alberta contributes approximately 10% to Canada's overall anthropogenic greenhouse gas (GHG) emissions. Such emissions have traditionally been estimated through "bottom-up" methods which seek to account for all individual sources of GHGs within a given facility. However, it is recognized that bottom-up approaches for complex industrial facilities can be subject to uncertainties associated with incomplete or inaccurate emission factor and/or activity data. In order to quantify air pollutant emissions from oil sands activities an aircraft-based measurement campaign was performed in the summer of 2013. The aircraft measurements could also be used to quantify GHG emissions for comparison to the bottom up emissions estimates. Utilizing specific flight patterns, together with an emissions estimation algorithm and measurements of CO2 and methane, a "top-down" estimate of GHG intensities for several large surface mining operations was obtained. The results demonstrate that there is a wide variation in emissions intensities (≈80 - 220 kg CO2/barrel oil) across OS facilities, which in some cases agree with calculated intensities, and in other cases are larger than that estimated using industry reported GHG emission and oil production data. When translated to annual GHG emissions, the "top-down" approach results in a CO2 emission of approximately 41 Mega Tonnes (MT) CO2/year for the 4 OS facilities investigated, in contrast to the ≈26 MT CO2/year reported by industry. The results presented here highlight the importance of using "top-down" approaches as a complimentary method in evaluating GHG emissions from large industrial sources.

Analysis of uncertainties in the estimates of nitrous oxide and methane emissions in the UK's greenhouse gas inventory for agriculture

NASA Astrophysics Data System (ADS)

Milne, Alice E.; Glendining, Margaret J.; Bellamy, Pat; Misselbrook, Tom; Gilhespy, Sarah; Rivas Casado, Monica; Hulin, Adele; van Oijen, Marcel; Whitmore, Andrew P.

2014-01-01

The UK's greenhouse gas inventory for agriculture uses a model based on the IPCC Tier 1 and Tier 2 methods to estimate the emissions of methane and nitrous oxide from agriculture. The inventory calculations are disaggregated at country level (England, Wales, Scotland and Northern Ireland). Before now, no detailed assessment of the uncertainties in the estimates of emissions had been done. We used Monte Carlo simulation to do such an analysis. We collated information on the uncertainties of each of the model inputs. The uncertainties propagate through the model and result in uncertainties in the estimated emissions. Using a sensitivity analysis, we found that in England and Scotland the uncertainty in the emission factor for emissions from N inputs (EF1) affected uncertainty the most, but that in Wales and Northern Ireland, the emission factor for N leaching and runoff (EF5) had greater influence. We showed that if the uncertainty in any one of these emission factors is reduced by 50%, the uncertainty in emissions of nitrous oxide reduces by 10%. The uncertainty in the estimate for the emissions of methane emission factors for enteric fermentation in cows and sheep most affected the uncertainty in methane emissions. When inventories are disaggregated (as that for the UK is) correlation between separate instances of each emission factor will affect the uncertainty in emissions. As more countries move towards inventory models with disaggregation, it is important that the IPCC give firm guidance on this topic.

Uncertainties in Emissions In Emissions Inputs for Near-Road Assessments

EPA Science Inventory

Emissions, travel demand, and dispersion models are all needed to obtain temporally and spatially resolved pollutant concentrations. Current methodology combines these three models in a bottom-up approach based on hourly traffic and emissions estimates, and hourly dispersion conc...

Covariance specification and estimation to improve top-down Green House Gas emission estimates

NASA Astrophysics Data System (ADS)

Ghosh, S.; Lopez-Coto, I.; Prasad, K.; Whetstone, J. R.

2015-12-01

The National Institute of Standards and Technology (NIST) operates the North-East Corridor (NEC) project and the Indianapolis Flux Experiment (INFLUX) in order to develop measurement methods to quantify sources of Greenhouse Gas (GHG) emissions as well as their uncertainties in urban domains using a top down inversion method. Top down inversion updates prior knowledge using observations in a Bayesian way. One primary consideration in a Bayesian inversion framework is the covariance structure of (1) the emission prior residuals and (2) the observation residuals (i.e. the difference between observations and model predicted observations). These covariance matrices are respectively referred to as the prior covariance matrix and the model-data mismatch covariance matrix. It is known that the choice of these covariances can have large effect on estimates. The main objective of this work is to determine the impact of different covariance models on inversion estimates and their associated uncertainties in urban domains. We use a pseudo-data Bayesian inversion framework using footprints (i.e. sensitivities of tower measurements of GHGs to surface emissions) and emission priors (based on Hestia project to quantify fossil-fuel emissions) to estimate posterior emissions using different covariance schemes. The posterior emission estimates and uncertainties are compared to the hypothetical truth. We find that, if we correctly specify spatial variability and spatio-temporal variability in prior and model-data mismatch covariances respectively, then we can compute more accurate posterior estimates. We discuss few covariance models to introduce space-time interacting mismatches along with estimation of the involved parameters. We then compare several candidate prior spatial covariance models from the Matern covariance class and estimate their parameters with specified mismatches. We find that best-fitted prior covariances are not always best in recovering the truth. To achieve accuracy, we perform a sensitivity study to further tune covariance parameters. Finally, we introduce a shrinkage based sample covariance estimation technique for both prior and mismatch covariances. This technique allows us to achieve similar accuracy nonparametrically in a more efficient and automated way.

Estimation of Nitrous Oxide Emissions from US Grasslands.

PubMed

Mummey; Smith; Bluhm

2000-02-01

/ Nitrous oxide (N(2)O) emissions from temperate grasslands are poorly quantified and may be an important part of the atmospheric N(2)O budget. In this study N(2)O emissions were simulated for 1052 grassland sites in the United States using the NGAS model of Parton and others (1996) coupled with an organic matter decomposition model. N(2)O flux was calculated for each site using soil and land use data obtained from the National Resource Inventory (NRI) database and weather data obtained from NASA. The estimates were regionalized based upon temperature and moisture isotherms. Annual N(2)O emissions for each region were based on the grassland area of each region and the mean estimated annual N(2)O flux from NRI grassland sites in the region. The regional fluxes ranged from 0.18 to 1.02 kg N(2)O N/ha/yr with the mean flux for all regions being 0.28 kg N(2)O N/ha/yr. Even though fluxes from the western regions were relatively low, these regions made the largest contribution to total emissions due to their large grassland area. Total US grassland N(2)O emissions were estimated to be about 67 Gg N(2)O N/yr. Emissions from the Great Plains states, which contain the largest expanse of natural grassland in the United States, were estimated to average 0.24 kg N(2)O N/ha/yr. Using the annual flux estimate for the temperate Great Plains, we estimate that temperate grasslands worldwide may potentially produce 0.27 Tg N(2)O N/yr. Even though our estimate for global temperate grassland N(2)O emissions is less than published estimates for other major temperate and tropical biomes, our results indicate that temperate grasslands are a significant part of both United States and global atmospheric N(2)O budgets. This study demonstrates the utility of models for regional N(2)O flux estimation although additional data from carefully designed field studies is needed to further validate model results.

Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.

Improved Rice Residue Burning Emissions Estimates: Accounting for Practice-Specific Emission Factors in Air Pollution Assessments of Vietnam

NASA Technical Reports Server (NTRS)

Lasko, Kristofer; Vadrevu, Krishna

2018-01-01

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for Particulate Matter less than 2.5 microns (PM2.5). We found significant differences in the resulting burning-practice specific emission factors, with 16.9 grams per square kilogram (plus or minus 6.9) for pile burning and 8.8 grams per square kilogram (plus or minus 3.5) for non-pile burning. We calculated burning practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 gigagrams of PM2.5 result from the pile burning method and 130 gigagrams result from non-pile burning method, with the most-likely current emission scenario of 150 gigagrams PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 gigagrams PM2.5, which is only 44 percent of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18 percent of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

High-Resolution Spatially Gridded Biomass Burning Emissions Inventory In Asia

NASA Astrophysics Data System (ADS)

Vadrevu, K. P.; Lau, W. K.; da Silva, A.; Justice, C. O.

2012-12-01

Biomass burning is long recognized an important source of greenhouse gas (GHG) emissions (CO2, CO, CH4, H2, CH3Cl, NO, HCN, CH3CN, COS, etc) and aerosols. In the Asian region, the current estimates of greenhouse gas emissions and aerosols from biomass burning are severely constrained by the lack of reliable statistics on fire distribution and frequency, and the lack of accurate estimates of area burned, fuel load, etc. As a part of NASA funded interdisciplinary research project entitled "Effects of biomass burning on water cycle and climate in the monsoon Asia", we initially developed a high resolution spatially gridded emissions inventory from the biomass burning for Indo-Ganges region and then extended the inventory to the entire Asia. Active fires from MODIS as well as high resolution LANDSAT data have been used to fine-tune the MODIS burnt area products for estimating the emissions. Locally based emission factors were used to refine the gaseous emissions. The resulting emissions data has been gridded at 5-minute intervals. We also compared our emission estimates with the other emission products such as Global Fire Assimilation System (GFAS), Quick fire emissions database (QFED) and Global Fire Emissions Database (GFED). Our results revealed significant vegetation fires from Myanmar, India, Indonesia, China, Laos, Thailand, Cambodia and Vietnam. These seven countries accounted for 92.4% of all vegetation fires in the Asian region. Satellite-based vegetation fire analysis showed the highest fire occurrence in the closed to open shrub land category, (19%) followed by closed to open, broadleaved evergreen-semi deciduous forest (16%), rain fed croplands (17%), post flooded or irrigated croplands (12%), mosaic cropland vegetation (11%), mosaic vegetation/cropland (10%). Emission contribution from agricultural fires was significant, however, showed discrepancies due to low confidence in burnt areas and lack of crop specific emission factors. Further, our results suggest that FRP products underestimate emissions from agriculture fires compared to burnt area products. Details on uncertainties in emission estimates from biomass burning in Asia will also be presented.

Ventilation potential during the emissions survey in Toluca Valley, Mexico

NASA Astrophysics Data System (ADS)

Ruiz Angulo, A.; Peralta, O.; Jurado, O. E.; Ortinez, A.; Grutter de la Mora, M.; Rivera, C.; Gutierrez, W.; Gonzalez, E.

2017-12-01

During the late-spring early-summer measurements of emissions and pollutants were carried out during a survey campaign at four different locations within the Toluca Valley. The current emissions inventory typically estimates the generation of pollutants based on pre-estimated values representing an entire sector function of their activities. However, those factors are not always based direct measurements. The emissions from the Toluca Valley are rather large and they could affect the air quality of Mexico City Valley. The air masses interchange between those two valleys is not very well understood; however, based on the measurements obtained during the 3 months campaign we looked carefully at the daily variability of the wind finding a clear signal for mountain-valley breeze. The ventilation coefficient is estimated and the correlations with the concentrations at the 4 locations and in a far away station in Mexico City are addressed in this work. Finally, we discuss the implication of the ventilation capacity in air quality for the system of Valleys that include Mexico City.

Assessing global radiative forcing due to regional emissions of tropospheric ozone precursors: a step towards climate credit for ozone reductions

NASA Astrophysics Data System (ADS)

Mauzerall, D. L.; Naik, V.; Horowitz, L. W.; Schwarzkopf, D.; Ramaswamy, V.; Oppenheimer, M.

2005-05-01

Carbon dioxide emissions from fossil-fuel consumption are presented for the five Asian countries that are among the global leaders in anthropogenic carbon emissions: China (13% of global total), Japan (5% of global total), India (5% of global total), South Korea (2% of global total), and Indonesia (1% of global total). Together, these five countries represent over a quarter of the world's fossil-fuel based carbon emissions. Moreover, these countries are rapidly developing and energy demand has grown dramatically in the last two decades. A method is developed to estimate the spatial and seasonal flux of fossil-fuel consumption, thereby greatly improving the temporal and spatial resolution of anthropogenic carbon dioxide emissions. Currently, only national annual data for anthropogenic carbon emissions are available, and as such, no understanding of seasonal or sub-national patterns of emissions are possible. This methodology employs fuel distribution data from representative sectors of the fossil-fuel market to determine the temporal and spatial patterns of fuel consumption. These patterns of fuel consumption are then converted to patterns of carbon emissions. The annual total emissions estimates produced by this method are consistent to those maintained by the United Nations. Improved estimates of temporal and spatial resolution of the human based carbon emissions allows for better projections about future energy demands, carbon emissions, and ultimately the global carbon cycle.

FHWA infrastructure carbon estimator : final report and user’s guide.

DOT National Transportation Integrated Search

2014-09-01

This study developed a method of estimating energy and GHG emissions from construction and maintenance of transportation systems. Designed as a spreadsheet-based model for practitioners, FHWAs Infrastructure Carbon Estimator is based on data colle...

Historical evaluation of vehicle emission control in Guangzhou based on a multi-year emission inventory

NASA Astrophysics Data System (ADS)

Zhang, Shaojun; Wu, Ye; Liu, Huan; Wu, Xiaomeng; Zhou, Yu; Yao, Zhiliang; Fu, Lixin; He, Kebin; Hao, Jiming

2013-09-01

The Guangzhou government adopted many vehicle emission control policies and strategies during the five-year preparation (2005-2009) to host the 2010 Asian Games. This study established a multi-year emission inventory for vehicles in Guangzhou during 2005-2009 and estimated the uncertainty in total vehicle emissions by taking the assumed uncertainties in fleet-average emission factors and annual mileage into account. In 2009, the estimated total vehicle emissions in Guangzhou were 313 000 (242 000-387 000) tons of CO, 60 900 (54 000-70 200) tons of THC, 65 600 (56 800-74 100) tons of NOx and 2740 (2100-3400) tons of PM10. Vehicle emissions within the urban area of Guangzhou were estimated to be responsible for ˜40% of total gaseous pollutants and ˜25% of total PM10 in the entire city. Although vehicle use intensity increased rapidly in Guangzhou during 2005-2009, vehicle emissions were estimated to have been reduced by 12% for CO, 21% for THC and 20% for PM10 relative to those in 2005. NOx emissions were estimated to have remained almost constant during this period. Compared to the "without control" scenario, 19% (15%-23%) of CO, 20% (18%-23%) of THC, 9% (8%-10%) of NOx and 16% (12%-20%) of PM10 were estimated to have been mitigated from a combination of the implementation of Euro III standards for light-duty vehicles (LDVs) and heavy-duty diesel vehicles and improvement of fuel quality. This study also evaluated several enhanced vehicle emission control actions taken recently. For example, the enhanced I/M program for LDVs was estimated to reduce 11% (9%-14%) of CO, 9% (8%-10%) of THC and 2% (2%-3%) of NOx relative to total vehicle emissions in 2009. Total emission reductions by temporary traffic controls for the Asian Games were estimated equivalent to 9% (7%-11%) of CO, 9% (8%-10%) of THC, 5% (5%-6%) of NOx and 10% (8%-13%) of PM10 estimated total vehicle emissions in 2009. Those controls are essential to further vehicle emission mitigation in Guangzhou required by the new National Ambient Air Quality Standards.

Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty

DOE PAGES

Kim, Young-Min; Zhou, Ying; Gao, Yang; ...

2014-11-16

We report that the spatial pattern of the uncertainty in air pollution-related health impacts due to climate change has rarely been studied due to the lack of high-resolution model simulations, especially under the Representative Concentration Pathways (RCPs), the latest greenhouse gas emission pathways. We estimated future tropospheric ozone (O 3) and related excess mortality and evaluated the associated uncertainties in the continental United States under RCPs. Based on dynamically downscaled climate model simulations, we calculated changes in O 3 level at 12 km resolution between the future (2057 and 2059) and base years (2001–2004) under a low-to-medium emission scenario (RCP4.5)more » and a fossil fuel intensive emission scenario (RCP8.5). We then estimated the excess mortality attributable to changes in O 3. Finally, we analyzed the sensitivity of the excess mortality estimates to the input variables and the uncertainty in the excess mortality estimation using Monte Carlo simulations. O 3-related premature deaths in the continental U.S. were estimated to be 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O 3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally, excess mortality estimates attributable to the combined effect of climate and emission changes on O 3 as well as the associated uncertainties vary substantially in space and so do the most influential input variables. Spatially resolved data is crucial to develop effective community level mitigation and adaptation policy.« less

Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Young-Min; Zhou, Ying; Gao, Yang

We report that the spatial pattern of the uncertainty in air pollution-related health impacts due to climate change has rarely been studied due to the lack of high-resolution model simulations, especially under the Representative Concentration Pathways (RCPs), the latest greenhouse gas emission pathways. We estimated future tropospheric ozone (O 3) and related excess mortality and evaluated the associated uncertainties in the continental United States under RCPs. Based on dynamically downscaled climate model simulations, we calculated changes in O 3 level at 12 km resolution between the future (2057 and 2059) and base years (2001–2004) under a low-to-medium emission scenario (RCP4.5)more » and a fossil fuel intensive emission scenario (RCP8.5). We then estimated the excess mortality attributable to changes in O 3. Finally, we analyzed the sensitivity of the excess mortality estimates to the input variables and the uncertainty in the excess mortality estimation using Monte Carlo simulations. O 3-related premature deaths in the continental U.S. were estimated to be 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O 3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally, excess mortality estimates attributable to the combined effect of climate and emission changes on O 3 as well as the associated uncertainties vary substantially in space and so do the most influential input variables. Spatially resolved data is crucial to develop effective community level mitigation and adaptation policy.« less

Ground based mobile isotopic methane measurements in the Front Range, Colorado

NASA Astrophysics Data System (ADS)

Vaughn, B. H.; Rella, C.; Petron, G.; Sherwood, O.; Mielke-Maday, I.; Schwietzke, S.

2014-12-01

Increased development of unconventional oil and gas resources in North America has given rise to attempts to monitor and quantify fugitive emissions of methane from the industry. Emission estimates of methane from oil and gas basins can vary significantly from one study to another as well as from EPA or State estimates. New efforts are aimed at reconciling bottom-up, or inventory-based, emission estimates of methane with top-down estimates based on atmospheric measurements from aircraft, towers, mobile ground-based vehicles, and atmospheric models. Attributing airborne measurements of regional methane fluxes to specific sources is informed by ground-based measurements of methane. Stable isotopic measurements (δ13C) of methane help distinguish between emissions from the O&G industry, Confined Animal Feed Operations (CAFO), and landfills, but analytical challenges typically limit meaningful isotopic measurements to individual point sampling. We are developing a toolbox to use δ13CH4 measurements to assess the partitioning of methane emissions for regions with multiple methane sources. The method was applied to the Denver-Julesberg Basin. Here we present data from continuous isotopic measurements obtained over a wide geographic area by using MegaCore, a 1500 ft. tube that is constantly filled with sample air while driving, then subsequently analyzed at slower rates using cavity ring down spectroscopy (CRDS). Pressure, flow and calibration are tightly controlled allowing precise attribution of methane enhancements to their point of collection. Comparisons with point measurements are needed to confirm regional values and further constrain flux estimates and models. This effort was made in conjunction with several major field campaigns in the Colorado Front Range in July-August 2014, including FRAPPÉ (Front Range Air Pollution and Photochemistry Experiment), DISCOVER-AQ, and the Air Water Gas NSF Sustainability Research Network at the University of Colorado.

Airborne Quantification of Methane Emissions in the San Francisco Bay Area of California

NASA Astrophysics Data System (ADS)

Guha, A.; Newman, S.; Martien, P. T.; Young, A.; Hilken, H.; Faloona, I. C.; Conley, S.

2017-12-01

The Bay Area Air Quality Management District, the San Francisco Bay Area's air quality regulatory agency, has set a goal to reduce the region's greenhouse gas (GHG) emissions 80% below 1990 levels by 2050, consistent with the State of California's climate protection goal. The Air District maintains a regional GHG emissions inventory that includes emissions estimates and projections which influence the agency's programs and regulatory activities. The Air District is currently working to better characterize methane emissions in the GHG inventory through source-specific measurements, to resolve differences between top-down regional estimates (Fairley and Fischer, 2015; Jeong et al., 2016) and the bottom-up inventory. The Air District funded and participated in a study in Fall 2016 to quantify methane emissions from a variety of sources from an instrumented Mooney aircraft. This study included 40 hours of cylindrical vertical profile flights that combined methane and wind measurements to derive mass emission rates. Simultaneous measurements of ethane provided source-apportionment between fossil-based and biological methane sources. The facilities sampled included all five refineries in the region, five landfills, two dairy farms and three wastewater treatment plants. The calculated mass emission rates were compared to bottom-up rates generated by the Air District and to those from facility reports to the US EPA as part of the mandatory GHG reporting program. Carbon dioxide emission rates from refineries are found to be similar to bottom-up estimates for all sources, supporting the efficacy of the airborne measurement methodology. However, methane emission estimates from the airborne method showed significant differences for some source categories. For example, methane emission estimates based on airborne measurements were up to an order of magnitude higher for refineries, and up to five times higher for landfills compared to bottom-up methods, suggesting significant underestimation in the inventories and self-reported estimates. Future measurements over the same facilities will reveal if we have seasonal and process-dependent trends in emissions. This will provide a basis for rule making and for designing mitigation and control actions.

The Establishment of LTO Emission Inventory of Civil Aviation Airports Based on Big Data

NASA Astrophysics Data System (ADS)

Lu, Chengwei; Liu, Hefan; Song, Danlin; Yang, Xinyue; Tan, Qinwen; Hu, Xiang; Kang, Xue

2018-03-01

An estimation model on LTO emissions of civil aviation airports was developed in this paper, LTO big data was acquired by analysing the internet with Python, while the LTO emissions was dynamically calculated based on daily LTO data, an uncertainty analysis was conducted with Monte Carlo method. Through the model, the emission of LTO in Shuangliu International Airport was calculated, and the characteristics and temporal distribution of LTO in 2015 was analysed. Results indicates that compared with the traditional methods, the model established can calculate the LTO emissions from different types of airplanes more accurately. Based on the hourly LTO information of 302 valid days, it was obtained that the total number of LTO cycles in Chengdu Shuangliu International Airport was 274,645 and the annual amount of emission of SO2, NOx, VOCs, CO, PM10 and PM2.5 was estimated, and the uncertainty of the model was around 7% to 10% varies on pollutants.

Evaluation of new flux attribution methods for mapping N2O emissions at the landscape scale from EC measurements

NASA Astrophysics Data System (ADS)

Grossel, Agnes; Bureau, Jordan; Loubet, Benjamin; Laville, Patricia; Massad, Raia; Haas, Edwin; Butterbach-Bahl, Klaus; Guimbaud, Christophe; Hénault, Catherine

2017-04-01

The objective of this study was to develop and evaluate an attribution method based on a combination of Eddy Covariance (EC) and chamber measurements to map N2O emissions over a 3-km2 area of croplands and forests in France. During 2 months of spring 2015, N2O fluxes were measured (i) by EC at 15 m height and (ii) punctually with a mobile chamber at 16 places within 1-km of EC mast. The attribution method was based on coupling the EC measurements, information on footprints (Loubet et al., 20101) and emission ratios based on crops and fertilizations, calculated based on chamber measurements. The results were evaluated against an independent flux dataset measured by automatic chambers in a wheat field within the area. At the landscape scale, the method estimated a total emission of 114-271 kg N-N2O during the campaign. This new approach allowed estimating continuously N2O emission and better accounting for the spatial variability of N2O emission at the landscape scale.

A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2015-04-29

Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO 2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) andmore » fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO 2 (ffCO 2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO 2 emissions and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray, J.; Lee, J.; Yadav, V.

Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO 2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) andmore » fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO 2 (ffCO 2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO 2 emissions and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Considerable contribution of the Montreal Protocol to declining greenhouse gas emissions from the United States

NASA Astrophysics Data System (ADS)

Hu, Lei; Montzka, Stephen A.; Lehman, Scott J.; Godwin, David S.; Miller, Benjamin R.; Andrews, Arlyn E.; Thoning, Kirk; Miller, John B.; Sweeney, Colm; Siso, Caroline; Elkins, James W.; Hall, Bradley D.; Mondeel, Debra J.; Nance, David; Nehrkorn, Thomas; Mountain, Marikate; Fischer, Marc L.; Biraud, Sébastien C.; Chen, Huilin; Tans, Pieter P.

2017-08-01

Ozone depleting substances (ODSs) controlled by the Montreal Protocol are potent greenhouse gases (GHGs), as are their substitutes, the hydrofluorocarbons (HFCs). Here we provide for the first time a comprehensive estimate of U.S. emissions of ODSs and HFCs based on precise measurements in discrete air samples from across North America and in the remote atmosphere. Derived emissions show spatial and seasonal variations qualitatively consistent with known uses and largely confirm U.S. Environmental Protection Agency (EPA) national emissions inventories for most gases. The measurement-based results further indicate a substantial decline of ODS emissions from 2008 to 2014, equivalent to 50% of the CO2-equivalent decline in combined emissions of CO2 and all other long-lived GHGs inventoried by the EPA for the same period. Total estimated CO2-equivalent emissions of HFCs were comparable to the sum of ODS emissions in 2014, but can be expected to decline in the future in response to recent policy measures.

Residual Effects of Fertilization History Increase Nitrous Oxide Emissions from Zero-N Controls: Implications for Estimating Fertilizer-Induced Emission Factors.

PubMed

LaHue, Gabriel T; van Kessel, Chris; Linquist, Bruce A; Adviento-Borbe, Maria Arlene; Fonte, Steven J

2016-09-01

Agricultural N fertilization is the dominant driver of increasing atmospheric nitrous oxide (NO) concentrations over the past half-century, yet there is considerable uncertainty in estimates of NO emissions from agriculture. Such estimates are typically based on the amount of N applied and a fertilizer-induced emission factor (EF), which is calculated as the difference in emissions between a fertilized plot and a zero-N control plot divided by the amount of N applied. A fertilizer-induced EF of 1% is currently recognized by the Intergovernmental Panel on Climate Change (IPCC) based on several studies analyzing published field measurements of NO emissions. Although many zero-N control plots used in these measurements received historical N applications, the potential for a residual impact of these inputs on NO emissions has been largely ignored and remains poorly understood. To address this issue, we compared NO emissions under laboratory conditions from soils sampled within zero-N control plots that had historically received N inputs versus soils from plots that had no N inputs for 20 yr. Historical N fertilization of zero-N control plots increased initial NO emissions by roughly one order of magnitude on average relative to historically unfertilized control plots. Higher NO emissions were positively correlated with extractable N and potentially mineralizable N. This finding suggests that accounting for fertilization history may help reduce the uncertainty associated with the IPCC fertilizer-induced EF and more accurately estimate the contribution of fertilizer N to agricultural NO emissions, although further research to demonstrate this relationship in the field is needed. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Energy-Related Carbon Dioxide Emissions in U.S. Manufacturing

EIA Publications

2006-01-01

Based on the Manufacturing Energy Consumption Survey (MECS) conducted by the U.S. Department of Energy, Energy Information Administration (EIA), this paper presents historical energy-related carbon dioxide emission estimates for energy-intensive sub-sectors and 23 industries. Estimates are based on surveys of more than 15,000 manufacturing plants in 1991, 1994, 1998, and 2002. EIA is currently developing its collection of manufacturing data for 2006.

40 CFR 63.1414 - Test methods and emission estimation equations.

Code of Federal Regulations, 2014 CFR

2014-07-01

... (D) Design analysis based on accepted chemical engineering principles, measurable process parameters... paragraph (d)(5) of this section. Engineering assessment may be used to estimate organic HAP emissions from... defined in paragraph (d)(5) of this section; through engineering assessment, as defined in paragraph (d)(6...

40 CFR 63.1414 - Test methods and emission estimation equations.

Code of Federal Regulations, 2013 CFR

2013-07-01

... (D) Design analysis based on accepted chemical engineering principles, measurable process parameters... paragraph (d)(5) of this section. Engineering assessment may be used to estimate organic HAP emissions from... defined in paragraph (d)(5) of this section; through engineering assessment, as defined in paragraph (d)(6...

Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

EPA Science Inventory

We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

40 CFR 98.85 - Procedures for estimating missing data.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to determine combined process and combustion CO2 emissions, the missing data procedures in § 98.35 apply. (b) For CO2 process emissions from cement manufacturing facilities calculated according to § 98... best available estimate of the monthly clinker production based on information used for accounting...

PERFORMANCE AND COST OF MERCURY AND MULTIPOLLUTANT EMISSION CONTROL TECHNOLOGY APPLICATIONS ON ELECTRIC UTILITY BOILERS

EPA Science Inventory

The report presents estimates of the performance and cost of both powdered activated carbon (PAC) and multipollutant control technologies that may be useful in controlling mercury emissions. Based on currently available data, cost estimates for PAC injection range are 0.03-3.096 ...

Estimation of GHG Emissions from Water Reclamation Plants in Beijing.

PubMed

Fan, Yupeng; Bai, Yanying; Jiao, Wentao

  A procedure for estimating Greenhouse gas (GHG) emissions from a wastewater reclamation plant in Beijing was developed based on the process chain model. GHG emissions under two typical water reclamation treatment processes, the coagulation-sedimentation-filtration traditional process and advanced biological treatment process, were examined. The total on-site GHG emissions were estimated to be 0.0056 kg/m 3 and 0.6765 kg/m 3 respectively, while total off-site GHG emissions were estimated to be 0.3699 kg/m 3 and 0.4816 kg/m 3 . The overall GHG emissions were 0.3755 kg/m 3 under the type 1 treatment, which is much lower than that under the type 2 of 1.1581 kg/m 3 . Emissions from both processes were lower than that from the tap water production. Wastewater reclamation and reuse should be promoted as it not only saves the water resources but also can reduce the GHG emissions. Energy consumption was the most significant source of GHG emissions. Biogas recovery should be employed as it can significantly reduce the GHG emissions, especially under the type 2 treatment process. Considering the wastewater treatment and reclamation process as a whole, the type 2 treatment process has advantages in reducing the GHG emissions per unit of pollutant. This paper provides scientific basis for decision making.

Use of short-term breath measures to estimate daily methane production by cattle.

PubMed

Velazco, J I; Mayer, D G; Zimmerman, S; Hegarty, R S

2016-01-01

Methods to measure enteric methane (CH4) emissions from individual ruminants in their production environment are required to validate emission inventories and verify mitigation claims. Estimates of daily methane production (DMP) based on consolidated short-term emission measurements are developing, but method verification is required. Two cattle experiments were undertaken to test the hypothesis that DMP estimated by averaging multiple short-term breath measures of methane emission rate did not differ from DMP measured in respiration chambers (RC). Short-term emission rates were obtained from a GreenFeed Emissions Monitoring (GEM) unit, which measured emission rate while cattle consumed a dispensed supplement. In experiment 1 (Expt. 1), four non-lactating cattle (LW=518 kg) were adapted for 18 days then measured for six consecutive periods. Each period consisted of 2 days of ad libitum intake and GEM emission measurement followed by 1 day in the RC. A prototype GEM unit releasing water as an attractant (GEM water) was also evaluated in Expt. 1. Experiment 2 (Expt. 2) was a larger study based on similar design with 10 cattle (LW=365 kg), adapted for 21 days and GEM measurement was extended to 3 days in each of the six periods. In Expt. 1, there was no difference in DMP estimated by the GEM unit relative to the RC (209.7 v. 215.1 g CH(4)/day) and no difference between these methods in methane yield (MY, 22.7 v. 23.7 g CH(4)/kg of dry matter intake, DMI). In Expt. 2, the correlation between GEM and RC measures of DMP and MY were assessed using 95% confidence intervals, with no difference in DMP or MY between methods and high correlations between GEM and RC measures for DMP (r=0.85; 215 v. 198 g CH(4)/day SEM=3.0) and for MY (r=0.60; 23.8 v. 22.1 g CH(4)/kg DMI SEM=0.42). When data from both experiments was combined neither DMP nor MY differed between GEM- and RC-based measures (P>0.05). GEM water-based estimates of DMP and MY were lower than RC and GEM (P<0.05). Cattle accessed the GEM water unit with similar frequency to the GEM unit (2.8 v. 3.5 times/day, respectively) but eructation frequency was reduced from 1.31 times/min (GEM) to once every 2.6 min (GEM water). These studies confirm the hypothesis that DMP estimated by averaging multiple short-term breath measures of methane emission rate using GEM does not differ from measures of DMP obtained from RCs. Further, combining many short-term measures of methane production rate during supplement consumption provides an estimate of DMP, which can be usefully applied in estimating MY.

Preindustrial nitrous oxide emissions from the land biosphere estimated by using a global biogeochemistry model

NASA Astrophysics Data System (ADS)

Xu, Rongting; Tian, Hanqin; Lu, Chaoqun; Pan, Shufen; Chen, Jian; Yang, Jia; Zhang, Bowen

2017-07-01

To accurately assess how increased global nitrous oxide (N2O) emission has affected the climate system requires a robust estimation of the preindustrial N2O emissions since only the difference between current and preindustrial emissions represents net drivers of anthropogenic climate change. However, large uncertainty exists in previous estimates of preindustrial N2O emissions from the land biosphere, while preindustrial N2O emissions on the finer scales, such as regional, biome, or sector scales, have not been well quantified yet. In this study, we applied a process-based Dynamic Land Ecosystem Model (DLEM) to estimate the magnitude and spatial patterns of preindustrial N2O fluxes at the biome, continental, and global level as driven by multiple environmental factors. Uncertainties associated with key parameters were also evaluated. Our study indicates that the mean of the preindustrial N2O emission was approximately 6.20 Tg N yr-1, with an uncertainty range of 4.76 to 8.13 Tg N yr-1. The estimated N2O emission varied significantly at spatial and biome levels. South America, Africa, and Southern Asia accounted for 34.12, 23.85, and 18.93 %, respectively, together contributing 76.90 % of global total emission. The tropics were identified as the major source of N2O released into the atmosphere, accounting for 64.66 % of the total emission. Our multi-scale estimates provide a robust reference for assessing the climate forcing of anthropogenic N2O emission from the land biosphere

Accounting for climate and air quality damages in future U.S. electricity generation scenarios.

PubMed

Brown, Kristen E; Henze, Daven K; Milford, Jana B

2013-04-02

The EPA-MARKAL model of the U.S. electricity sector is used to examine how imposing emissions fees based on estimated health and environmental damages might change electricity generation. Fees are imposed on life-cycle emissions of SO(2), nitrogen oxides (NO(x)), particulate matter, and greenhouse gases (GHG) from 2015 through 2055. Changes in electricity production, fuel type, emissions controls, and emissions produced under various fees are examined. A shift in fuels used for electricity production results from $30/ton CO(2)-equivalent GHG fees or from criteria pollutant fees set at the higher-end of the range of published damage estimates, but not from criteria pollutant fees based on low or midrange damage estimates. With midrange criteria pollutant fees assessed, SO(2) and NOx emissions are lower than the business as usual case (by 52% and 10%, respectively), with larger differences in the western U.S. than in the eastern U.S. GHG emissions are not significantly impacted by midrange criteria pollutant fees alone; conversely, with only GHG fees, NO(x) emissions are reduced by up to 11%, yet SO(2) emissions are slightly higher than in the business as usual case. Therefore, fees on both GHG and criteria pollutants may be needed to achieve significant reductions in both sets of pollutants.

Estimating the agricultural fertilizer NH3 emission in China based on the bi-directional CMAQ model and an agro-ecosystem model

NASA Astrophysics Data System (ADS)

Wang, S.

2014-12-01

Atmospheric ammonia (NH3) plays an important role in fine particle formation. Accurate estimates of ammonia can reduce uncertainties in air quality modeling. China is one of the largest countries emitting ammonia with the majority of NH3 emissions coming from the agricultural practices, such as fertilizer applications and animal operations. The current ammonia emission estimates in China are mainly based on pre-defined emission factors. Thus, there are considerable uncertainties in estimating NH3 emissions, especially in time and space distribution. For example, fertilizer applications vary in the date of application and amount by geographical regions and crop types. In this study, the NH3 emission from the agricultural fertilizer use in China of 2011 was estimated online by an agricultural fertilizer modeling system coupling a regional air-quality model and an agro-ecosystem model, which contains three main components 1) the Environmental Policy Integrated Climate (EPIC) model, 2) the meso-scale meteorology Weather Research and Forecasting (WRF) model and 3) the CMAQ air quality model with bi-directional ammonia fluxes. The EPIC output information about daily fertilizer application and soil characteristics would be the input of the CMAQ model. In order to run EPIC model, much Chinese local information is collected and processed. For example, Crop land data are computed from the MODIS land use data at 500-m resolution and crop categories at Chinese county level; the fertilizer use rate for different fertilizer types, crops and provinces are obtained from Chinese statistic materials. The system takes into consideration many influencing factors on agriculture ammonia emission, including weather, the fertilizer application method, timing, amount, and rate for specific pastures and crops. The simulated fertilizer data is compared with the NH3 emissions and fertilizer application data from other sources. The results of CMAQ modeling are also discussed and analyzed with field measurements. The estimated agricultural fertilizer NH3 emission in this study is about 3Tg in 2011. The regions with the highest emission rates are located in the North China Plain. Monthly, the peak ammonia emissions occur in April to July.

Estimation of Energy Consumption and Greenhouse Gas Emissions considering Aging and Climate Change in Residential Sector

NASA Astrophysics Data System (ADS)

Lee, M.; Park, C.; Park, J. H.; Jung, T. Y.; Lee, D. K.

2015-12-01

The impacts of climate change, particularly that of rising temperatures, are being observed across the globe and are expected to further increase. To counter this phenomenon, numerous nations are focusing on the reduction of greenhouse gas (GHG) emissions. Because energy demand management is considered as a key factor in emissions reduction, it is necessary to estimate energy consumption and GHG emissions in relation to climate change. Further, because South Korea is the world's fastest nation to become aged, demographics have also become instrumental in the accurate estimation of energy demands and emissions. Therefore, the purpose of this study is to estimate energy consumption and GHG emissions in the residential sectors of South Korea with regard to climate change and aging to build more accurate strategies for energy demand management and emissions reduction goals. This study, which was stablished with 2010 and 2050 as the base and target years, respectively, was divided into a two-step process. The first step evaluated the effects of aging and climate change on energy demand, and the second estimated future energy use and GHG emissions through projected scenarios. First, aging characteristics and climate change factors were analyzed by using the logarithmic mean divisia index (LMDI) decomposition analysis and the application of historical data. In the analysis of changes in energy use, the effects of activity, structure, and intensity were considered; the degrees of contribution were derived from each effect in addition to their relations to energy demand. Second, two types of scenarios were stablished based on this analysis. The aging scenarios are business as usual and future characteristics scenarios, and were used in combination with Representative Concentration Pathway (RCP) 2.6 and 8.5. Finally, energy consumption and GHG emissions were estimated by using a combination of scenarios. The results of these scenarios show an increase in energy consumption and GHG emissions from 2010 to 2050. This growth is caused by increases in heating energy because the elderly generally spend more time at home, and cooling energy owing to rising temperatures. This study will be useful in the preparation of energy demand management policies and the establishment and attainability of GHG emissions reduction goals.

Industrial point source CO2 emission strength estimation with aircraft measurements and dispersion modelling.

PubMed

Carotenuto, Federico; Gualtieri, Giovanni; Miglietta, Franco; Riccio, Angelo; Toscano, Piero; Wohlfahrt, Georg; Gioli, Beniamino

2018-02-22

CO 2 remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO 2 emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO 2 industrial point source, located in Biganos, France. CO 2 density measurements were obtained by applying the mass balance method, while CO 2 emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.

Use of a land-use-based emissions inventory in delineating clean-air zones

Treesearch

Victor S. Fahrer; Howard A. Peters

1977-01-01

Use of a land-use-based emissions inventory from which air-pollution estimates can be projected was studied. First the methodology used to establish a land-use-based emission inventory is described. Then this inventory is used as input in a simple model that delineates clean air and buffer zones. The model is applied to the town of Burlington, Massachusetts....

The importance of carbon footprint estimation boundaries.

PubMed

Matthews, H Scott; Hendrickson, Chris T; Weber, Christopher L

2008-08-15

Because of increasing concern about global climate change and carbon emissions as a causal factor, many companies and organizations are pursuing "carbon footprint" projects to estimate their own contributions to global climate change. Protocol definitions from carbon registries help organizations analyze their footprints. The scope of these protocols varies but generally suggests estimating only direct emissions and emissions from purchased energy, with less focus on supply chain emissions. In contrast approaches based on comprehensive environmental life-cycle assessment methods are available to track total emissions across the entire supply chain, and experience suggests that following narrowly defined estimation protocols will generally lead to large underestimates of carbon emissions for providing products and services. Direct emissions from an industry are, on average, only 14% of the total supply chain carbon emissions (often called Tier 1 emissions), and direct emissions plus industry energy inputs are, on average, only 26% of the total supply chain emissions (often called Tier 1 and 2 emissions). Without a full knowledge of their footprints, firms will be unable to pursue the most cost-effective carbon mitigation strategies. We suggest that firms use the screening-level analysis described here to set the bounds of their footprinting strategy to ensure that they do not ignore large sources of environmental effects across their supply chains. Such information can help firms pursue carbon and environmental emission mitigation projects not only within their own plants but also across their supply chain.

Methane emission to the atmosphere from landfills in the Canary Islands

NASA Astrophysics Data System (ADS)

Hernández, Pedro A.; Asensio-Ramos, María; Rodríguez, Fátima; Alonso, Mar; García-Merino, Marta; Amonte, Cecilia; Melián, Gladys V.; Barrancos, José; Rodríguez-Delgado, Miguel A.; Hernández-Abad, Marta; Pérez, Erica; Alonso, Monica; Tassi, Franco; Raco, Brunella; Pérez, Nemesio M.

2017-04-01

Methane (CH4) is one of the most powerful greenhouse gases, and is increasing in the atmosphere by 0.6% each year (Intergovernmental Panel on Climate Change, IPCC, 2013). This gas is produced in landfills in large quantities following the anaerobic degradation of organic matter. The IPCC has estimated that more than 10% of the total anthropogenic emissions of CH4 are originated in landfills. Even after years of being no operative (closed), a significant amount of landfill gas could be released to the atmosphere through its surface as diffuse or fugitive degassing. Many landfills currently report their CH4 emissions to the atmosphere using model-based methods, which are based on the rate of production of CH4, the oxidation rate of CH4 and the amount of CH4 recovered (Bingemer and Crutzen, 1987). This approach often involves large uncertainties due to inaccuracies of input data and many assumptions in the estimation. In fact, the estimated CH4 emissions from landfills in the Canary Islands published by the Spanish National Emission and Pollutant Sources Registration (PRTR-Spain) seem to be overestimated due to the use of protocols and analytical methodologies based on mathematical models. For this reason, direct measurements to estimate CH4 emissions in landfills are essential to reduce this uncertainty. In order to estimate the CH4 emissions to the atmosphere from landfills in the Canary Islands 23 surveys have been performed since 1999. Each survey implies hundreds of CO2and CH4 efflux measurements covering the landfill surface area. Surface landfill CO2 efflux measurements were carried out at each sampling site by means of a portable non-dispersive infrared spectrophotometer (NDIR) model LICOR Li800 following the accumulation chamber method. Samples of landfill gases were taken in the gas accumulated in the chamber and CO2 and CH4 were analyzed using a double channel VARIAN 4900 micro-GC. The CH4 efflux measurent was computed combining CO2 efflux and CH4/CO2 ratio. To quantify the the diffuse or fugitive CO2 and CH4 emission, gas efflux contour maps were constructed using sequential Gaussian simulation (sGs) as interpolation method. Considering that (a) there are 5 controlled landfills in the Canary Islands, (b) the average area of the 23 studied cells is 0.17 km2 and (c) the mean value of the CH4 emission estimated for the studied cells range between 6.9 and 8.1 kt km-2 y-1, the estimated CH4 emission to the atmosphere from landfills in the Canary Islands showed a range of 7.0 - 7.8 kt y-1. On the contrary and for the same period of time, the PRTR-Spain estimates CH4 emission in the order of 10.3 - 14.9 kt y-1, nearly two times our estimated value. This result demonstrates the need to perform direct measurements to estimate the surface fugitive emission of CH4 from landfills. Bingemer, H. G., and P. J. Crutzen (1987). The production of methane from solid wastes, J. Geophys. Res. 92, 2182-2187

Satellite-derived methane hotspot emission estimates using a fast data-driven method

NASA Astrophysics Data System (ADS)

Buchwitz, Michael; Schneising, Oliver; Reuter, Maximilian; Heymann, Jens; Krautwurst, Sven; Bovensmann, Heinrich; Burrows, John P.; Boesch, Hartmut; Parker, Robert J.; Somkuti, Peter; Detmers, Rob G.; Hasekamp, Otto P.; Aben, Ilse; Butz, André; Frankenberg, Christian; Turner, Alexander J.

2017-05-01

Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. XCH4, can be used to quantify methane emissions. Maps of time-averaged satellite-derived XCH4 show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1σ uncertainties directly from maps of annually averaged satellite XCH4. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100 %) but also find that our method tends to underestimate emissions by typically about 40 %. To what extent these findings are model dependent needs to be assessed. We apply our method to an ensemble of satellite XCH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003-2014. We obtain annual emissions of four source areas: Four Corners in the south-western USA, the southern part of Central Valley, California, Azerbaijan, and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50 % higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 5-8 higher emissions compared to EDGAR, albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in EDGAR.

A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)

NASA Astrophysics Data System (ADS)

Bloom, A. Anthony; Bowman, Kevin W.; Lee, Meemong; Turner, Alexander J.; Schroeder, Ronny; Worden, John R.; Weidner, Richard; McDonald, Kyle C.; Jacob, Daniel J.

2017-06-01

Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemical transport models (WetCHARTs version 1.0). Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation reanalyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature dependence parameterizations for the period 2009-2010; an extended ensemble subset based solely on precipitation and the data-constrained terrestrial carbon cycle analysis is derived for the period 2001-2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare the model against surface measurements of atmospheric CH4; the model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and the wetland extent together account for more than 80 % of the dominant uncertainty in the timing, magnitude and seasonal variability in wetland CH4 emissions, although uncertainty in the temperature CH4 : C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty that is critical for top-down estimates of wetland CH4 fluxes. Specifically, our ensemble can provide enhanced information on the prior CH4 emission uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain the biogeochemical process controls of global wetland CH4 emissions.

The Dairy Greenhouse Gas Emission Model: Reference Manual

USDA-ARS?s Scientific Manuscript database

The Dairy Greenhouse Gas Model (DairyGHG) is a software tool for estimating the greenhouse gas emissions and carbon footprint of dairy production systems. A relatively simple process-based model is used to predict the primary greenhouse gas emissions, which include the net emission of carbon dioxide...

Greenhouse gases inventory and carbon balance of two dairy systems obtained from two methane-estimation methods.

PubMed

Cunha, C S; Lopes, N L; Veloso, C M; Jacovine, L A G; Tomich, T R; Pereira, L G R; Marcondes, M I

2016-11-15

The adoption of carbon inventories for dairy farms in tropical countries based on models developed from animals and diets of temperate climates is questionable. Thus, the objectives of this study were to estimate enteric methane (CH4) emissions through the SF6 tracer gas technique and through equations proposed by the Intergovernmental Panel on Climate Change (IPCC) Tier 2 and to calculate the inventory of greenhouse gas (GHG) emissions from two dairy systems. In addition, the carbon balance of these properties was estimated using enteric CH4 emissions obtained using both methodologies. In trial 1, the CH4 emissions were estimated from seven Holstein dairy cattle categories based on the SF6 tracer gas technique and on IPCC equations. The categories used in the study were prepubertal heifers (n=6); pubertal heifers (n=4); pregnant heifers (n=5); high-producing (n=6); medium-producing (n=5); low-producing (n=4) and dry cows (n=5). Enteric methane emission was higher for the category comprising prepubertal heifers when estimated by the equations proposed by the IPCC Tier 2. However, higher CH4 emissions were estimated by the SF6 technique in the categories including medium- and high-producing cows and dry cows. Pubertal heifers, pregnant heifers, and low-producing cows had equal CH4 emissions as estimated by both methods. In trial 2, two dairy farms were monitored for one year to identify all activities that contributed in any way to GHG emissions. The total emission from Farm 1 was 3.21t CO2e/animal/yr, of which 1.63t corresponded to enteric CH4. Farm 2 emitted 3.18t CO2e/animal/yr, with 1.70t of enteric CH4. IPCC estimations can underestimate CH4 emissions from some categories while overestimate others. However, considering the whole property, these discrepancies are offset and we would submit that the equations suggested by the IPCC properly estimate the total CH4 emission and carbon balance of the properties. Thus, the IPCC equations should be utilized with caution, and the herd composition should be analysed at the property level. When the carbon stock in pasture and other crops was considered, the carbon balance suggested that both farms are sustainable for GHG, by both methods. On the other hand, carbon balance without carbon stock, by both methods, suggests that farms emit more carbon than the system is capable of stock. Copyright © 2016 Elsevier B.V. All rights reserved.

Atmospheric Nitrogen Trifluoride: Optimized emission estimates using 2-D and 3-D Chemical Transport Models from 1973-2008

NASA Astrophysics Data System (ADS)

Ivy, D. J.; Rigby, M. L.; Prinn, R. G.; Muhle, J.; Weiss, R. F.

2009-12-01

We present optimized annual global emissions from 1973-2008 of nitrogen trifluoride (NF3), a powerful greenhouse gas which is not currently regulated by the Kyoto Protocol. In the past few decades, NF3 production has dramatically increased due to its usage in the semiconductor industry. Emissions were estimated through the 'pulse-method' discrete Kalman filter using both a simple, flexible 2-D 12-box model used in the Advanced Global Atmospheric Gases Experiment (AGAGE) network and the Model for Ozone and Related Tracers (MOZART v4.5), a full 3-D atmospheric chemistry model. No official audited reports of industrial NF3 emissions are available, and with limited information on production, a priori emissions were estimated using both a bottom-up and top-down approach with two different spatial patterns based on semiconductor perfluorocarbon (PFC) emissions from the Emission Database for Global Atmospheric Research (EDGAR v3.2) and Semiconductor Industry Association sales information. Both spatial patterns used in the models gave consistent results, showing the robustness of the estimated global emissions. Differences between estimates using the 2-D and 3-D models can be attributed to transport rates and resolution differences. Additionally, new NF3 industry production and market information is presented. Emission estimates from both the 2-D and 3-D models suggest that either the assumed industry release rate of NF3 or industry production information is still underestimated.

Estimates of reservoir methane emissions based on a spatially ...

EPA Pesticide Factsheets

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence

A High Resolution Technology-based Emissions Inventory for Nepal: Present and Future Scenario

NASA Astrophysics Data System (ADS)

Sadavarte, P.; Das, B.; Rupakheti, M.; Byanju, R.; Bhave, P.

2016-12-01

A comprehensive regional assessment of emission sources is a major hindrance for a complete understanding of the air quality and for designing appropriate mitigation solutions in Nepal, a landlocked country in foothills of the Himalaya. This study attempts, for the first time, to develop a fine resolution (1km × 1km) present day emission inventory of Nepal with a higher tier approach using our understanding of the currently used technologies, energy consumption used in various energy sectors and its resultant emissions. We estimate present-day emissions of aerosols (BC, OC and PM2.5), trace gases (SO2, CO, NOX and VOC) and greenhouse gases (CO2, N2O and CH4) from non-open burning sources (residential, industry, transport, commercial) and open-burning sources (agriculture and municipal solid waste burning) for the base year 2013. We used methodologies published in literatures, and both primary and secondary data to estimate energy production and consumption in each sector and its sub-sector and associated emissions. Local practices and activity rates are explicitly accounted for energy consumption and dispersed often under-documented emission sources like brick manufacturing, diesel generator sets, mining, stone crushing, solid waste burning and diesel use in farms are considered. Apart from pyrogenic source of CH4 emissions, methanogenic and enteric fermentation sources are also accounted. Region-specific and newly measured country-specific emission factors are used for emission estimates. Activity based proxies are used for spatial and temporal distribution of emissions. Preliminary results suggest that 80% of national energy consumption is in residential sector followed by industry (8%) and transport (7%). More than 90% of the residential energy is supplied by biofuel which needs immediate attention to reduce emissions. Further, the emissions would be compared with other contemporary studies, regional and global datasets and used in the model simulations to understand impacts of air pollution on health and climate in Kathmandu Valley and Nepal. Future emissions are being developed based on different possible growth scenarios and policy interventions to mitigate emissions.

Advancing Methods for Estimating Soil Nitrous Oxide Emissions by Incorporating Freeze-Thaw Cycles into a Tier 3 Model-Based Assessment

NASA Astrophysics Data System (ADS)

Ogle, S. M.; DelGrosso, S.; Parton, W. J.

2017-12-01

Soil nitrous oxide emissions from agricultural management are a key source of greenhouse gas emissions in many countries due to the widespread use of nitrogen fertilizers, manure amendments from livestock production, planting legumes and other practices that affect N dynamics in soils. In the United States, soil nitrous oxide emissions have ranged from 250 to 280 Tg CO2 equivalent from 1990 to 2015, with uncertainties around 20-30 percent. A Tier 3 method has been used to estimate the emissions with the DayCent ecosystem model. While the Tier 3 approach is considerably more accurate than IPCC Tier 1 methods, there is still the possibility of biases in emission estimates if there are processes and drivers that are not represented in the modeling framework. Furthermore, a key principle of IPCC guidance is that inventory compilers estimate emissions as accurately as possible. Freeze-thaw cycles and associated hot moments of nitrous oxide emissions are one of key drivers influencing emissions in colder climates, such as the cold temperate climates of the upper Midwest and New England regions of the United States. Freeze-thaw activity interacts with management practices that are increasing N availability in the plant-soil system, leading to greater nitrous oxide emissions during transition periods from winter to spring. Given the importance of this driver, the DayCent model has been revised to incorproate freeze-thaw cycles, and the results suggests that including this driver can significantly modify the emissions estimates in cold temperate climate regions. Consequently, future methodological development to improve estimation of nitrous oxide emissions from soils would benefit from incorporating freeze-thaw cycles into the modeling framework for national territories with a cold climate.

Development of a high temporal-spatial resolution vehicle emission inventory based on NRT traffic data and its impact on air pollution in Beijing - Part 1: Development and evaluation of vehicle emission inventory

NASA Astrophysics Data System (ADS)

Jing, B. Y.; Wu, L.; Mao, H. J.; Gong, S. L.; He, J. J.; Zou, C.; Song, G. H.; Li, X. Y.; Wu, Z.

2015-10-01

As the ownership of vehicles and frequency of utilization increase, vehicle emissions have become an important source of air pollution in Chinese cities. An accurate emission inventory for on-road vehicles is necessary for numerical air quality simulation and the assessment of implementation strategies. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near real time (NRT) traffic data on road segments to develop a high temporal-spatial resolution vehicle emission inventory (HTSVE) for the urban Beijing area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54 × 104, 42.51 × 104 and 2.13 × 104 and 0.41 × 104 Mg, respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Additionally, the on-road vehicle emission inventory model and control effect assessment system in Beijing, a vehicle emission inventory model, was established based on this study in a companion paper (He et al., 2015).

Development of probabilistic emission inventories of air toxics for Jacksonville, Florida, USA.

PubMed

Zhao, Yuchao; Frey, H Christopher

2004-11-01

Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum Likelihood Estimation (MLE) method or the Method of Matching Moments was used to fit parametric distributions. For data sets that contain nondetected measurements, a method based upon MLE was used for parameter estimation. To quantify the uncertainty in urban air toxic emission factors, parametric bootstrap simulation and empirical bootstrap simulation were applied to uncensored and censored data, respectively. The probabilistic emission inventories were developed based on the product of the uncertainties in the emission factors and in the activity factors. The uncertainties in the urban air toxics emission inventories range from as small as -25 to +30% for Hg to as large as -83 to +243% for As. The key sources of uncertainty in the emission inventory for each toxic are identified based upon sensitivity analysis. Typically, uncertainty in the inventory of a given pollutant can be attributed primarily to a small number of source categories. Priorities for improving the inventories and for refining the probabilistic analysis are discussed.

An AIS-based high-resolution ship emission inventory and its uncertainty in Pearl River Delta region, China.

PubMed

Li, Cheng; Yuan, Zibing; Ou, Jiamin; Fan, Xiaoli; Ye, Siqi; Xiao, Teng; Shi, Yuqi; Huang, Zhijiong; Ng, Simon K W; Zhong, Zhuangmin; Zheng, Junyu

2016-12-15

Ship emissions contribute significantly to air pollution and impose health risks to residents along the coastal area. By using the refined data from the Automatic Identification System (AIS), this study developed a highly resolved ship emission inventory for the Pearl River Delta (PRD) region, China, home to three of ten busiest ports in the world. The region-wide SO 2 , NO X , CO, PM 10 , PM 2.5 , and VOC emissions in 2013 were estimated to be 61,484, 103,717, 10,599, 7155, 6605, and 4195t, respectively. Ocean going vessels were the largest contributors of the total emissions, followed by coastal vessels and river vessels. In terms of ship type, container ship was the leading contributor, followed by conventional cargo ship, dry bulk carrier, fishing ship, and oil tanker. These five ship types accounted for >90% of total emissions. The spatial distributions of emissions revealed that the key emission hot spots all concentrated within the newly proposed emission control area (ECA) and ship emissions within ECA covered >80% of total ship emissions in the PRD, highlighting the importance of ECA in emissions reduction in the PRD. The uncertainties of emission estimates of pollutants were quantified, with lower bounds of -24.5% to -21.2% and upper bounds of 28.6% to 33.3% at 95% confidence intervals. The lower uncertainties in this study highlighted the powerfulness of AIS data in improving ship emission estimates. The AIS-based bottom-up methodology can be used for developing and upgrading ship emission inventory and formulating effective control measures on ship emissions in other port regions wherever possible. Copyright © 2016 Elsevier B.V. All rights reserved.

Rapid decline in carbon monoxide emissions and export from East Asia between years 2005 and 2016

NASA Astrophysics Data System (ADS)

Zheng, Bo; Chevallier, Frederic; Ciais, Philippe; Yin, Yi; Deeter, Merritt N.; Worden, Helen M.; Wang, Yilong; Zhang, Qiang; He, Kebin

2018-04-01

Measurements of Pollution in the Troposphere (MOPITT) satellite and ground-based carbon monoxide (CO) measurements both suggest a widespread downward trend in CO concentrations over East Asia during the period 2005–2016. This negative trend is inconsistent with global bottom-up inventories of CO emissions, which show a small increase or stable emissions in this region. We try to reconcile the observed CO trend with emission inventories using an atmospheric inversion of the MOPITT CO data that estimates emissions from primary sources, secondary production, and chemical sinks of CO. The atmospheric inversion indicates a ~ ‑2% yr‑1 decrease in emissions from primary sources in East Asia from 2005–2016. The decreasing emissions are mainly caused by source reductions in China. The regional MEIC inventory for China is the only bottom up estimate consistent with the inversion-diagnosed decrease of CO emissions. According to the MEIC data, decreasing CO emissions from four main sectors (iron and steel industries, residential sources, gasoline-powered vehicles, and construction materials industries) in China explain 76% of the inversion-based trend of East Asian CO emissions. This result suggests that global inventories underestimate the recent decrease of CO emission factors in China which occurred despite increasing consumption of carbon-based fuels, and is driven by rapid technological changes with improved combustion efficiency and emission control measures.

Directional Canopy Emissivity Estimation Based on Spectral Invariants

NASA Astrophysics Data System (ADS)

Guo, M.; Cao, B.; Ren, H.; Yongming, D.; Peng, J.; Fan, W.

2017-12-01

Land surface emissivity is a crucial parameter for estimating land surface temperature from remote sensing data and also plays an important role in the physical process of surface energy and water balance from local to global scales. To our knowledge, the emissivity varies with surface type and cover. As for the vegetation, its canopy emissivity is dependent on vegetation types, viewing zenith angle and structure that changes in different growing stages. Lots of previous studies have focused on the emissivity model, but few of them are analytic and suited to different canopy structures. In this paper, a new physical analytic model is proposed to estimate the directional emissivity of homogenous vegetation canopy based on spectral invariants. The initial model counts the directional absorption in six parts: the direct absorption of the canopy and the soil, the absorption of the canopy and soil after a single scattering and after multiple scattering within the canopy-soil system. In order to analytically estimate the emissivity, the pathways of photons absorbed in the canopy-soil system are traced using the re-collision probability in Fig.1. After sensitive analysis on the above six absorptions, the initial complicated model was further simplified as a fixed mathematic expression to estimate the directional emissivity for vegetation canopy. The model was compared with the 4SAIL model, FRA97 model, FRA02 model and DART model in Fig.2, and the results showed that the FRA02 model is significantly underestimated while the FRA97 model is a little underestimated, on basis of the new model. On the contrary, the emissivity difference between the new model with the 4SAIL model and DART model was found to be less than 0.002. In general, since the new model has the advantages of mathematic expression with accurate results and clear physical meaning, the model is promising to be extended to simulate the directional emissivity for the discrete canopy in further study.

2014 National Emissions Inventory (NEI) Plan

EPA Pesticide Factsheets

The NEI is prepared at least every three years by the U.S. EPA based primarily upon emissions estimates and emissions model inputs provided by State, Local and Tribal (SLT) air agencies, and supplemented by data developed by the EPA.

Assessing methane emission estimation methods based on atmospheric measurements from oil and gas production using LES simulations

NASA Astrophysics Data System (ADS)

Saide, P. E.; Steinhoff, D.; Kosovic, B.; Weil, J.; Smith, N.; Blewitt, D.; Delle Monache, L.

2017-12-01

There are a wide variety of methods that have been proposed and used to estimate methane emissions from oil and gas production by using air composition and meteorology observations in conjunction with dispersion models. Although there has been some verification of these methodologies using controlled releases and concurrent atmospheric measurements, it is difficult to assess the accuracy of these methods for more realistic scenarios considering factors such as terrain, emissions from multiple components within a well pad, and time-varying emissions representative of typical operations. In this work we use a large-eddy simulation (LES) to generate controlled but realistic synthetic observations, which can be used to test multiple source term estimation methods, also known as an Observing System Simulation Experiment (OSSE). The LES is based on idealized simulations of the Weather Research & Forecasting (WRF) model at 10 m horizontal grid-spacing covering an 8 km by 7 km domain with terrain representative of a region located in the Barnett shale. Well pads are setup in the domain following a realistic distribution and emissions are prescribed every second for the components of each well pad (e.g., chemical injection pump, pneumatics, compressor, tanks, and dehydrator) using a simulator driven by oil and gas production volume, composition and realistic operational conditions. The system is setup to allow assessments under different scenarios such as normal operations, during liquids unloading events, or during other prescribed operational upset events. Methane and meteorology model output are sampled following the specifications of the emission estimation methodologies and considering typical instrument uncertainties, resulting in realistic observations (see Figure 1). We will show the evaluation of several emission estimation methods including the EPA Other Test Method 33A and estimates using the EPA AERMOD regulatory model. We will also show source estimation results from advanced methods such as variational inverse modeling, and Bayesian inference and stochastic sampling techniques. Future directions including other types of observations, other hydrocarbons being considered, and assessment of additional emission estimation methods will be discussed.

Estimation of snow emissivity via assimilation of multi-frequency passive microwave data into an ensemble-based data assimilation system

NASA Astrophysics Data System (ADS)

Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.

2017-12-01

Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness temperatures at all frequencies (i.e., 1.4-, 18.7-, 36.5-, and 89-GHz) reduce the root-mean-square-error (RMSE) of snow emissivity at 1.4-, 18.7-, 36.5-, and 89-GHz (H-pol.) by 80%, 42%, 52%, 40%, respectively compared to the corresponding snow emissivity estimates from the open-loop model.

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

Greenhouse gas emissions from Australian open-cut coal mines: contribution from spontaneous combustion and low-temperature oxidation.

PubMed

Day, Stuart J; Carras, John N; Fry, Robyn; Williams, David J

2010-07-01

Spontaneous combustion and low-temperature oxidation of waste coal and other carbonaceous material at open-cut coal mines are potentially significant sources of greenhouse gas emissions. However, the magnitude of these emissions is largely unknown. In this study, emissions from spontaneous combustion and low-temperature oxidation were estimated for six Australian open-cut coal mines with annual coal production ranging from 1.7 to more than 16 Mt. Greenhouse emissions from all other sources at these mines were also estimated and compared to those from spontaneous combustion and low-temperature oxidation. In all cases, fugitive emission of methane was the largest source of greenhouse gas; however, in some mines, spontaneous combustion accounted for almost a third of all emissions. For one mine, it was estimated that emissions from spontaneous combustion were around 250,000 t CO(2)-e per annum. The contribution from low-temperature oxidation was generally less than about 1% of the total for all six mines. Estimating areas of spoil affected by spontaneous combustion by ground-based surveys was prone to under-report the area. Airborne infrared imaging appears to be a more reliable method.

Ammonia emission inventory for the state of Wyoming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirchstetter, Thomas W.; Maser, Colette R.; Brown, Nancy J.

2003-12-17

Ammonia (NH{sub 3}) is the only significant gaseous base in the atmosphere and it has a variety of impacts as an atmospheric pollutant, including the formation of secondary aerosol particles: ammonium sulfate and ammonium nitrate. NH{sub 3} preferentially forms ammonium sulfate; consequently ammonium nitrate aerosol formation may be limited by the availability of NH{sub 3}. Understanding the impact of emissions of oxides of sulfur and nitrogen on visibility, therefore, requires accurately determined ammonia emission inventories for use in air quality models, upon which regulatory and policy decisions increasingly depend. This report presents an emission inventory of NH{sub 3} for themore » state of Wyoming. The inventory is temporally and spatially resolved at the monthly and county level, and is comprised of emissions from individual sources in ten categories: livestock, fertilizer, domestic animals, wild animals, wildfires, soil, industry, mobile sources, humans, and publicly owned treatment works. The Wyoming NH{sub 3} inventory was developed using the Carnegie Mellon University (CMU) Ammonia Model as framework. Current Wyoming-specific activity data and emissions factors obtained from state agencies and published literature were assessed and used as inputs to the CMU Ammonia Model. Biogenic emissions from soils comprise about three-quarters of the Wyoming NH{sub 3} inventory, though emission factors from soils are highly uncertain. Published emission factors are scarce and based on limited measurements. In Wyoming, agricultural land, rangeland, and forests comprise 96% of the land area and essentially all of the estimated emissions from soils. Future research on emission rates of NH{sub 3} for these land categories may lead to a substantial change in the magnitude of soil emissions, a different inventory composition, and reduced uncertainty in the inventory. While many NH{sub 3} inventories include annual emissions, air quality modeling studies require finer temporal resolution. Published studies indicate higher emission rates from soils and animal wastes at higher temperatures, and temporal variation in fertilizer application. A recent inverse modeling study indicates temporal variation in regional NH{sub 3} emissions. Monthly allocation factors were derived to estimate monthly emissions from soils, livestock and wild animal waste based on annual emission estimates. Monthly resolution of NH{sub 3} emissions from fertilizers is based on fertilizer sales to farmers. Statewide NH{sub 3} emissions are highest in the late spring and early summer months.« less

Estimating Uncertainty in N2O Emissions from US Cropland Soils

USDA-ARS?s Scientific Manuscript database

A Monte Carlo analysis was combined with an empirically-based approach to quantify uncertainties in soil N2O emissions from US croplands estimated with the DAYCENT simulation model. Only a subset of croplands was simulated in the Monte Carlo analysis which was used to infer uncertainties across the ...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saide, Pablo E.; Peterson, David A.; de Silva, Arlindo

We couple airborne, ground-based, and satellite observations; conduct regional simulations; and develop and apply an inversion technique to constrain hourly smoke emissions from the Rim Fire, the third largest observed in California, USA. Emissions constrained with multiplatform data show notable nocturnal enhancements (sometimes over a factor of 20), correlate better with daily burned area data, and are a factor of 2–4 higher than a priori estimates, highlighting the need for improved characterization of diurnal profiles and day-to-day variability when modeling extreme fires. Constraining only with satellite data results in smaller enhancements mainly due to missing retrievals near the emissions source,more » suggesting that top-down emission estimates for these events could be underestimated and a multiplatform approach is required to resolve them. Predictions driven by emissions constrained with multiplatform data present significant variations in downwind air quality and in aerosol feedback on meteorology, emphasizing the need for improved emissions estimates during exceptional events.« less

Methane Emissions from Bangladesh: Bridging the Gap Between Ground-based and Space-borne Estimates

NASA Astrophysics Data System (ADS)

Peters, C.; Bennartz, R.; Hornberger, G. M.

2015-12-01

Gaining an understanding of methane (CH4) emission sources and atmospheric dispersion is an essential part of climate change research. Large-scale and global studies often rely on satellite observations of column CH4 mixing ratio whereas high-spatial resolution estimates rely on ground-based measurements. Extrapolation of ground-based measurements on, for example, rice paddies to broad region scales is highly uncertain because of spatio-temporal variability. We explore the use of ground-based river stage measurements and independent satellite observations of flooded area along with satellite measurements of CH4 mixing ratio to estimate the extent of methane emissions. Bangladesh, which comprises most of the Ganges Brahmaputra Meghna (GBM) delta, is a region of particular interest for studying spatio-temporal variation of methane emissions due to (1) broadscale rice cultivation and (2) seasonal flooding and atmospheric convection during the monsoon. Bangladesh and its deltaic landscape exhibit a broad range of environmental, economic, and social circumstances that are relevant to many nations in South and Southeast Asia. We explore the seasonal enhancement of CH4 in Bangladesh using passive remote sensing spectrometer CH4 products from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) and the Atmospheric Infrared Sounder (AIRS). The seasonal variation of CH4 is compared to independent estimates of seasonal flooding from water gauge stations and space-based passive microwave water-to-land fractions from the Tropical Rainfall Measuring Mission Microwave Imager (TRMM-TMI). Annual cycles in inundation (natural and anthropogenic) and atmospheric CH4 concentrations show highly correlated seasonal signals. NOAA's HYSPLIT model is used to determine atmospheric residence time of ground CH4 fluxes. Using the satellite observations, we can narrow the large uncertainty in extrapolation of ground-based CH4 emission estimates from rice paddies, allowing for country-wide upscaling of high spatial resolution data. This approach allows for better informed carbon cycling modeling for the GBM delta and is applicable to other regions.

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

PubMed

Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

2015-12-01

Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual. Copyright © 2015 Elsevier Ltd. All rights reserved.

A High-Speed Continuous Recording High Flow Gas Sampler for Measuring Methane Emissions from Pneumatic Devices at Oil and Natural Gas Production Facilities

NASA Astrophysics Data System (ADS)

Ferrara, T.; Howard, T. M.

2016-12-01

Studies attempting to reconcile facility level emission estimates of sources at oil and gas facilities with basin wide methane flux measurements have had limited success. Pneumatic devices are commonly used at oil and gas production facilities for process control or liquid pumping. These devices are powered by pressurized natural gas from the well, so they are known methane sources at these sites. Pneumatic devices are estimated to contribute 14% to 25% of the total greenhouse gas emissions (GHG) from production facilities. Measurements of pneumatic devices have shown that malfunctioning or poorly maintained control systems may be emitting significantly more methane than currently estimated. Emission inventories for these facilities use emission factors from EPA that are based on pneumatic device measurements made in the early 1990's. Recent studies of methane emissions from production facilities have attempted to measure emissions from pneumatic devices by several different methods. These methods have had limitations including alteration of the system being measured, the inability to distinguish between leaks and venting during normal operation, or insufficient response time to account of the time based emission events. We have developed a high speed recording high flow sampler that is capable of measuring the transient emissions from pneumatic devices. This sampler is based on the well-established high flow measurement technique used in oil and gas for quantifying component leak rates. In this paper we present the results of extensive laboratory controlled release testing. Additionally, test data from several field studies where this sampler has been used to measure pneumatic device emissions will be presented.

Assessment of on-road transportation demand and CO2 emissions for determination of air quality impacts from the Megacity of São Paulo

NASA Astrophysics Data System (ADS)

Perez-Martinez, P. J.; Miranda, R. M.; Andrade, M. D. F.

2017-12-01

In this manuscript we assess the capability of using mobility surveys and a high-scale assignment and emission model to study climate change and air quality impacts related to on-road transportation in the Megacity of São Paulo (MSP). Initially, we estimate CO2 emissions of light and heavy vehicles (LVs and HVs) at a spatial scale of 500m and temporal scale of an hour, using transport demand modeling. The estimates are based on origin and destination trip pairs and the height of the planetary boundary layer (PBL). These estimates, performed for the years 2007 and 2012, depend also on intermediate variables as dilution rates (D) and surface particulate-matter concentrations (PM). Secondly, we assess the changes in CO2 vehicle emissions from the MRSP over the period 2007-2012 (4% year-1). Consequently, CO2 emission inventories merge trip-based surveys, traffic assignments and road network database with air pollution monitoring data. Despite the difference of the methodologies, we use a road link bottom up vehicle activity based approach, the assessed emissions agree with the State's Emission Inventory. This paper shows that the CO2 emissions from LDVs and HDVs in the MSP in 2007 and 2012 were 8,477 and 10,075 tCeq day-1 (58% LVs and 42% HVs), respectively. CO2 emissions from vehicles show spatial patterns consistent with passenger and freight transport trips and road network assignments. Temporal profiles (diurnal, weekly and monthly) were estimated using traffic counts and congestion surrogates. The profiles were compared with average road-site (Western of MSP) and background (Jaraguá Peak) CO2 measurements available for 2014. On-road measurements showed one peak associated to the morning peak hour of vehicles (437±45 ppm) and another night peak (435±49 ppm) related to the low PBL (313 m) and D (329 m2 h-1). From on-road measurements, background values (414±2 ppm) were subtracted to estimate excess CO2 (12±8 ppm) directly attributed to vehicles. The inventory reflects the relationships between traffic patterns and emissions, and the developed methodology could be used to evaluate the impacts of forthcoming urban transport and emission control policies. In the future, our estimates will be verified with ground measurements of CO2 concentrations over a bigger monitoring network in the MSP.

A regional mass balance model based on total ammoniacal nitrogen for estimating ammonia emissions from beef cattle in Alberta Canada

NASA Astrophysics Data System (ADS)

Chai, Lilong; Kröbel, Roland; Janzen, H. Henry; Beauchemin, Karen A.; McGinn, Sean M.; Bittman, Shabtai; Atia, Atta; Edeogu, Ike; MacDonald, Douglas; Dong, Ruilan

2014-08-01

Animal feeding operations are primary contributors of anthropogenic ammonia (NH3) emissions in North America and Europe. Mathematical modeling of NH3 volatilization from each stage of livestock manure management allows comprehensive quantitative estimates of emission sources and nutrient losses. A regionally-specific mass balance model based on total ammoniacal nitrogen (TAN) content in animal manure was developed for estimating NH3 emissions from beef farming operations in western Canada. Total N excretion in urine and feces was estimated from animal diet composition, feed dry matter intake and N utilization for beef cattle categories and production stages. Mineralization of organic N, immobilization of TAN, nitrification, and denitrification of N compounds in manure, were incorporated into the model to account for quantities of TAN at each stage of manure handling. Ammonia emission factors were specified for different animal housing (feedlots, barns), grazing, manure storage (including composting and stockpiling) and land spreading (tilled and untilled land), and were modified for temperature. The model computed NH3 emissions from all beef cattle sub-classes including cows, calves, breeding bulls, steers for slaughter, and heifers for slaughter and replacement. Estimated NH3 emissions were about 1.11 × 105 Mg NH3 in Alberta in 2006, with a mean of 18.5 kg animal-1 yr-1 (15.2 kg NH3-N animal-1 yr-1) which is 23.5% of the annual N intake of beef cattle (64.7 kg animal-1 yr-1). The percentage of N intake volatilized as NH3-N was 50% for steers and heifers for slaughter, and between 11 and 14% for all other categories. Steers and heifers for slaughter were the two largest contributors (3.5 × 104 and 3.9 × 104 Mg, respectively) at 31.5 and 32.7% of total NH3 emissions because most growing animals were finished in feedlots. Animal housing and grazing contributed roughly 63% of the total NH3 emissions (feedlots, barns and pastures contributed 54.4, 0.2 and 8.1% of total emissions, respectively.). Manure storage (composting and stockpiling) and land spreading contributed 23 and 14% of the total emissions, respectively. Parameters from this TAN-based mass balance model will be incorporated into the HOLOS model - a farm-level greenhouse gas calculator.

Integrating internet GPS vehicle tracking data into a bottom-up vehicular emissions inventory and atmospheric simulation in South-East, Brazil

NASA Astrophysics Data System (ADS)

Ibarra Espinosa, S.; Ynoue, R.; Giannotti, M., , Dr

2017-12-01

It has been shown the importance of emissions inventories for air quality studies and environmental planning at local, regional (REAS), hemispheric (CLRTAP) and global (IPCC) scales. It has been shown also that vehicules are becoming the most important sources in urban centers. Several efforts has been made in order to model vehicular emissions to obtain more accurate emission factors based on Vehicular Specific Power (VPS) with IVE and MOVES based on VSP, MOBILE, VERSIT and COPERT based on average speed, or ARTEMIS and HBEFA based on traffic situations. However, little effort has been made to improve traffic activity data. In this study we are proposing using a novel approach to develop vehicular emissions inventory including point data from MAPLINK a company that feeds with traffic data to Google. This includes working and transforming massive amount of data to generate traffic flow and speeds. The region of study is the south east of Brazil including São Paulo metropolitan areas. To estimate vehicular emissions we are using the open source model VEIN available at https://CRAN.R-project.org/package=vein. We generated hourly traffic between 2010-04-21 and 2010-10-22, totalizing 145 hours. This data consists GPS readings from vehicles with assurance policy, applications and other sources. This type data presents spacial bias meaning that only a part of the vehicles are tracked. We corrected this bias using the calculated speed as proxy of traffic flow using measurements of traffic flow and speed per lane made in São Paulo. Then we calibrated the total traffic estimating Fuel Consumption with VEIN and comparing Fuel Sales for the region. We estimated the hourly vehicular emissions and produced emission maps and data-bases. In addition, we simulated atmospheric simulations using WRF-Chem to identify which inventory produces better agreement with air pollutant observations. New technologies and big data provides opportunities to improve vehicular emissions inventories.

Estimation of VOC emissions from produced-water treatment ponds in Uintah Basin oil and gas field using modeling techniques

NASA Astrophysics Data System (ADS)

Tran, H.; Mansfield, M. L.; Lyman, S. N.; O'Neil, T.; Jones, C. P.

2015-12-01

Emissions from produced-water treatment ponds are poorly characterized sources in oil and gas emission inventories that play a critical role in studying elevated winter ozone events in the Uintah Basin, Utah, U.S. Information gaps include un-quantified amounts and compositions of gases emitted from these facilities. The emitted gases are often known as volatile organic compounds (VOCs) which, beside nitrogen oxides (NOX), are major precursors for ozone formation in the near-surface layer. Field measurement campaigns using the flux-chamber technique have been performed to measure VOC emissions from a limited number of produced water ponds in the Uintah Basin of eastern Utah. Although the flux chamber provides accurate measurements at the point of sampling, it covers just a limited area of the ponds and is prone to altering environmental conditions (e.g., temperature, pressure). This fact raises the need to validate flux chamber measurements. In this study, we apply an inverse-dispersion modeling technique with evacuated canister sampling to validate the flux-chamber measurements. This modeling technique applies an initial and arbitrary emission rate to estimate pollutant concentrations at pre-defined receptors, and adjusts the emission rate until the estimated pollutant concentrations approximates measured concentrations at the receptors. The derived emission rates are then compared with flux-chamber measurements and differences are analyzed. Additionally, we investigate the applicability of the WATER9 wastewater emission model for the estimation of VOC emissions from produced-water ponds in the Uintah Basin. WATER9 estimates the emission of each gas based on properties of the gas, its concentration in the waste water, and the characteristics of the influent and treatment units. Results of VOC emission estimations using inverse-dispersion and WATER9 modeling techniques will be reported.

Atmospheric Sulfur Hexafluoride: Sources, Sinks and Greenhouse Warming

NASA Technical Reports Server (NTRS)

Sze, Nien Dak; Wang, Wei-Chyung; Shia, George; Goldman, Aaron; Murcray, Frank J.; Murcray, David G.; Rinsland, Curtis P.

1993-01-01

Model calculations using estimated reaction rates of sulfur hexafluoride (SF6) with OH and 0('D) indicate that the atmospheric lifetime due to these processes may be very long (25,000 years). An upper limit for the UV cross section would suggest a photolysis lifetime much longer than 1000 years. The possibility of other removal mechanisms are discussed. The estimated lifetimes are consistent with other estimated values based on recent laboratory measurements. There appears to be no known natural source of SF6. An estimate of the current production rate of SF6 is about 5 kt/yr. Based on historical emission rates, we calculated a present-day atmospheric concentrations for SF6 of about 2.5 parts per trillion by volume (pptv) and compared the results with available atmospheric measurements. It is difficult to estimate the atmospheric lifetime of SF6 based on mass balance of the emission rate and observed abundance. There are large uncertainties concerning what portion of the SF6 is released to the atmosphere. Even if the emission rate were precisely known, it would be difficult to distinguish among lifetimes longer than 100 years since the current abundance of SF6 is due to emission in the past three decades. More information on the measured trends over the past decade and observed vertical and latitudinal distributions of SF6 in the lower stratosphere will help to narrow the uncertainty in the lifetime. Based on laboratory-measured IR absorption cross section for SF6, we showed that SF6 is about 3 times more effective as a greenhouse gas compared to CFC 11 on a per molecule basis. However, its effect on atmospheric warming will be minimal because of its very small concentration. We estimated the future concentration of SF6 at 2010 to be 8 and 10 pptv based on two projected emission scenarios. The corresponding equilibrium warming of 0.0035 C and 0.0043 C is to be compared with the estimated warming due to CO2 increase of about 0.8 C in the same period.

The evaluation of stack metal emissions from hazardous waste incinerators: assessing human exposure through noninhalation pathways.

PubMed Central

Sedman, R M; Polisini, J M; Esparza, J R

1994-01-01

Potential public health effects associated with exposure to metal emissions from hazardous waste incinerators through noninhalation pathways were evaluated. Instead of relying on modeling the movement of toxicants through various environmental media, an approach based on estimating changes from baseline levels of exposure was employed. Changes in soil and water As, Cd, Hg, Pb, Cr, and Be concentrations that result from incinerator emissions were first determined. Estimates of changes in human exposure due to direct contact with shallow soil or the ingestion of surface water were then ascertained. Projected changes in dietary intakes of metals due to incinerator emissions were estimated based on changes from baseline dietary intakes that are monitored in U.S. Food and Drug Administration total diet studies. Changes from baseline intake were deemed to be proportional to the projected changes in soil or surface water metal concentrations. Human exposure to metals emitted from nine hazardous waste incinerators were then evaluated. Metal emissions from certain facilities resulted in tangible human exposure through noninhalation pathways. However, the analysis indicated that the deposition of metals from ambient air would result in substantially greater human exposure through noninhalation pathways than the emissions from most of the facilities. PMID:7925180

Model-based estimation with boundary side information or boundary regularization [cardiac emission CT].

PubMed

Chiao, P C; Rogers, W L; Fessler, J A; Clinthorne, N H; Hero, A O

1994-01-01

The authors have previously developed a model-based strategy for joint estimation of myocardial perfusion and boundaries using ECT (emission computed tomography). They have also reported difficulties with boundary estimation in low contrast and low count rate situations. Here they propose using boundary side information (obtainable from high resolution MRI and CT images) or boundary regularization to improve both perfusion and boundary estimation in these situations. To fuse boundary side information into the emission measurements, the authors formulate a joint log-likelihood function to include auxiliary boundary measurements as well as ECT projection measurements. In addition, they introduce registration parameters to align auxiliary boundary measurements with ECT measurements and jointly estimate these parameters with other parameters of interest from the composite measurements. In simulated PET O-15 water myocardial perfusion studies using a simplified model, the authors show that the joint estimation improves perfusion estimation performance and gives boundary alignment accuracy of <0.5 mm even at 0.2 million counts. They implement boundary regularization through formulating a penalized log-likelihood function. They also demonstrate in simulations that simultaneous regularization of the epicardial boundary and myocardial thickness gives comparable perfusion estimation accuracy with the use of boundary side information.

2017 National Emissions Inventory (NEI) Plan

EPA Pesticide Factsheets

The 2017 NEI Plan is prepared at least every three years by the U.S. EPA based primarily upon emissions estimates and emissions model inputs provided by State, Local and Tribal (SLT) air agencies, and supplemented by data developed by the EPA.

Evaluation of mobile emissions contributions to Mexico City's emissions inventory using on-road and cross-road emission measurements and ambient data

NASA Astrophysics Data System (ADS)

Zavala, M.; Herndon, S. C.; Wood, E. C.; Onasch, T. B.; Knighton, W. B.; Marr, L. C.; Kolb, C. E.; Molina, L. T.

2009-09-01

Mobile emissions represent a significant fraction of the total anthropogenic emissions burden in the Mexico City Metropolitan Area (MCMA) and, therefore, it is crucial to use top-down techniques informed by on-road exhaust measurements to evaluate and improve traditional bottom-up official emissions inventory (EI) for the city. We present the measurements of on-road fleet-average emission factors obtained using the Aerodyne mobile laboratory in the MCMA in March 2006 as part of the MILAGRO/MCMA-2006 field campaign. A comparison of our on-road emission measurements with those obtained in 2003 using essentially the same measurement techniques and analysis methods indicates that, in the three year span, NO emission factors remain within the measured variability ranges whereas emission factors of aldehydes and aromatics species were reduced for all sampled driving conditions. We use a top-down fuel-based approach to evaluate the mobile emissions from the gasoline fleet estimated in the bottom-up official 2006 MCMA mobile sources. Within the range of measurement uncertainties, we found probable slight overpredictions of mean EI estimates on the order of 20-28% for CO and 14-20% for NO. However, we identify a probable EI discrepancy of VOC mobile emissions between 1.4 and 1.9; although estimated benzene and toluene mobile emissions in the inventory seem to be well within the uncertainties of the corresponding emissions estimates. Aldehydes mobile emissions in the inventory, however, seem to be underpredicted by factors of 3 for HCHO and 2 for CH3CHO. Our on-road measurement-based estimate of annual emissions of organic mass from PM1 particles suggests a severe underprediction (larger than a factor of 4) of PM2.5 mobile emissions in the inventory. Analyses of ambient CO, NOx and CO/NOx concentration trends in the MCMA indicate that the early morning ambient CO/NOx ratio has decreased at a rate of about 1.9 ppm/ppm/year over the last two decades due to reductions in CO levels rather than by NOx. These trends, together with the analysis of fuel sales and fleet size, suggest that the relative contribution of diesel vehicles to overall NOx levels has increased over time in the city. Despite the impressive increase in the size of the vehicle fleet between 2000 and 2006, the early morning ambient concentrations of CO and NOx have not increased accordingly, probably due to the reported low removal rates of older vehicles, which do not have emissions control technologies, and partially due to the much lower emissions from newer gasoline vehicles. This indicates that an emission-based air quality improvement strategy targeting large reductions of emissions from mobile sources should be directed towards a significant increase of the removal rate of older, highly-polluting, vehicles.

Mercury emission estimates from fires: an initial inventory for the United States.

PubMed

Wiedinmyer, Christine; Friedli, Hans

2007-12-01

Recent studies have shown that emissions of mercury (Hg), a hazardous air pollutant, from fires can be significant. However, to date, these emissions have not been well-quantified for the entire United States. Daily emissions of Hg from fires in the lower 48 states of the United States (LOWER48) and in Alaska were estimated for 2002-2006 using a simple fire emissions model. Emission factors of Hg from fires in different ecosystems were compiled from published plume studies and from soil-based assessments. Annual averaged emissions of Hg from fires in the LOWER48 and Alaska were 44 (20-65) metric tons yr(-1), equivalent to approximately 30% of the U.S. EPA 2002 National Emissions Inventory for Hg. Alaska had the highest averaged monthly emissions of all states; however, the emissions have a high temporal variability. Emissions from forests dominate the inventory, suggesting that Hg emissions from agricultural fires are not significant on an annual basis. The uncertainty in the Hg emission factors due to limited data leads to an uncertainty in the emission estimates on the order of +/-50%. Research is still needed to better constrain Hg emission factors from fires, particularly in the eastern U.S. and for ecosystems other than forests.

Influence of updating global emission inventory of black carbon on evaluation of the climate and health impact

NASA Astrophysics Data System (ADS)

Wang, Rong; Tao, Shu; Balkanski, Yves; Ciais, Philippe

2013-04-01

Black carbon (BC) is an air component of particular concern in terms of air quality and climate change. Black carbon emissions are often estimated based on the fuel data and emission factors. However, large variations in emission factors reported in the literature have led to a high uncertainty in previous inventories. Here, we develop a new global 0.1°×0.1° BC emission inventory for 2007 with full uncertainty analysis based on updated source and emission factor databases. Two versions of LMDz-OR-INCA models, named as INCA and INCA-zA, are run to evaluate the new emission inventory. INCA is built up based on a regular grid system with a resolution of 1.27° in latitude and 2.50° in longitude, while INCA-zA is specially zoomed to 0.51°×0.66° (latitude×longitude) in Asia. By checking against field observations, we compare our inventory with ACCMIP, which is used by IPCC in the 5th assessment report, and also evaluate the influence of model resolutions. With the newly calculated BC air concentrations and the nested model, we estimate the direct radiative forcing of BC and the premature death and mortality rate induced by BC exposure with Asia emphasized. Global BC direct radiative forcing at TOA is estimated to be 0.41 W/m2 (0.2 - 0.8 as inter-quartile range), which is 17% higher than that derived from the inventory adopted by IPCC-AR5 (0.34 W/m2). The estimated premature deaths induced by inhalation exposure to anthropogenic BC (0.36 million in 2007) and the percentage of high risk population are higher than those previously estimated. Ninety percents of the global total anthropogenic PD occur in Asia with 0.18 and 0.08 million deaths in China and India, respectively.

Estimating the potential of energy saving and carbon emission mitigation of cassava-based fuel ethanol using life cycle assessment coupled with a biogeochemical process model.

PubMed

Jiang, Dong; Hao, Mengmeng; Fu, Jingying; Tian, Guangjin; Ding, Fangyu

2017-09-14

Global warming and increasing concentration of atmospheric greenhouse gas (GHG) have prompted considerable interest in the potential role of energy plant biomass. Cassava-based fuel ethanol is one of the most important bioenergy and has attracted much attention in both developed and developing countries. However, the development of cassava-based fuel ethanol is still faced with many uncertainties, including raw material supply, net energy potential, and carbon emission mitigation potential. Thus, an accurate estimation of these issues is urgently needed. This study provides an approach to estimate energy saving and carbon emission mitigation potentials of cassava-based fuel ethanol through LCA (life cycle assessment) coupled with a biogeochemical process model-GEPIC (GIS-based environmental policy integrated climate) model. The results indicate that the total potential of cassava yield on marginal land in China is 52.51 million t; the energy ratio value varies from 0.07 to 1.44, and the net energy surplus of cassava-based fuel ethanol in China is 92,920.58 million MJ. The total carbon emission mitigation from cassava-based fuel ethanol in China is 4593.89 million kgC. Guangxi, Guangdong, and Fujian are identified as target regions for large-scale development of cassava-based fuel ethanol industry. These results can provide an operational approach and fundamental data for scientific research and energy planning.

Estimating the potential of energy saving and carbon emission mitigation of cassava-based fuel ethanol using life cycle assessment coupled with a biogeochemical process model

NASA Astrophysics Data System (ADS)

Jiang, Dong; Hao, Mengmeng; Fu, Jingying; Tian, Guangjin; Ding, Fangyu

2017-09-01

Global warming and increasing concentration of atmospheric greenhouse gas (GHG) have prompted considerable interest in the potential role of energy plant biomass. Cassava-based fuel ethanol is one of the most important bioenergy and has attracted much attention in both developed and developing countries. However, the development of cassava-based fuel ethanol is still faced with many uncertainties, including raw material supply, net energy potential, and carbon emission mitigation potential. Thus, an accurate estimation of these issues is urgently needed. This study provides an approach to estimate energy saving and carbon emission mitigation potentials of cassava-based fuel ethanol through LCA (life cycle assessment) coupled with a biogeochemical process model—GEPIC (GIS-based environmental policy integrated climate) model. The results indicate that the total potential of cassava yield on marginal land in China is 52.51 million t; the energy ratio value varies from 0.07 to 1.44, and the net energy surplus of cassava-based fuel ethanol in China is 92,920.58 million MJ. The total carbon emission mitigation from cassava-based fuel ethanol in China is 4593.89 million kgC. Guangxi, Guangdong, and Fujian are identified as target regions for large-scale development of cassava-based fuel ethanol industry. These results can provide an operational approach and fundamental data for scientific research and energy planning.

Understanding Methane Emission from Natural Gas Activities Using Inverse Modeling Techniques

NASA Astrophysics Data System (ADS)

Abdioskouei, M.; Carmichael, G. R.

2015-12-01

Natural gas (NG) has been promoted as a bridge fuel that can smooth the transition from fossil fuels to zero carbon energy sources by having lower carbon dioxide emission and lower global warming impacts in comparison to other fossil fuels. However, the uncertainty around the estimations of methane emissions from NG systems can lead to underestimation of climate and environmental impacts of using NG as a replacement for coal. Accurate estimates of methane emissions from NG operations is crucial for evaluation of environmental impacts of NG extraction and at larger scale, adoption of NG as transitional fuel. However there is a great inconsistency within the current estimates. Forward simulation of methane from oil and gas operation sites for the US is carried out based on NEI-2011 using the WRF-Chem model. Simulated values are compared against measurements of observations from different platforms such as airborne (FRAPPÉ field campaign) and ground-based measurements (NOAA Earth System Research Laboratory). A novel inverse modeling technique is used in this work to improve the model fit to the observation values and to constrain methane emission from oil and gas extraction sites.

Historic Emissions from Deforestation and Forest Degradation in Mato Grosso, Brazil: 1. Source Data Uncertainties

NASA Technical Reports Server (NTRS)

Morton, Douglas C.; Sales, Marcio H.; Souza, Carlos M., Jr.; Griscom, Bronson

2011-01-01

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results: Deforestation estimates showed good agreement for multi-year trends of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by >20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C/ha, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions: Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

The Impact of Advanced Greenhouse Gas Measurement Science on Policy Goals and Research Strategies

NASA Astrophysics Data System (ADS)

Abrahams, L.; Clavin, C.; McKittrick, A.

2016-12-01

In support of the Paris agreement, accurate characterizations of U.S. greenhouse gas (GHG) emissions estimates have been area of increased scientific focus. Over the last several years, the scientific community has placed significant emphasis on understanding, quantifying, and reconciling measurement and modeling methods that characterize methane emissions from petroleum and natural gas sources. This work has prompted national policy discussions and led to the improvement of regional and national methane emissions estimates. Research campaigns focusing on reconciling atmospheric measurements ("top-down") and process-based emissions estimates ("bottom-up") have sought to identify where measurement technology advances could inform policy objectives. A clear next step is development and deployment of advanced detection capabilities that could aid U.S. emissions mitigation and verification goals. The breadth of policy-relevant outcomes associated with advances in GHG measurement science are demonstrated by recent improvements in the petroleum and natural gas sector emission estimates in the EPA Greenhouse Gas Inventory, ambitious efforts to apply inverse modeling results to inform or validate national GHG inventory, and outcomes from federal GHG measurement science technology development programs. In this work, we explore the variety of policy-relevant outcomes impacted by advances in GHG measurement science, with an emphasis on improving GHG inventory estimates, identifying emissions mitigation strategies, and informing technology development requirements.

Estimation and projection of nitrous oxide (N2O) emissions from anthropogenic sources in Taiwan.

PubMed

Tsai, Wen-Tien; Chyan, Jih-Ming

2006-03-01

Taiwan is a densely populated and developed country with more than 97% of energy consumption supplied by imported fuels. Greenhouse gas emissions are thus becoming significant environmental issues in the country. Using the Intergovernmental Panel on Climate Change (IPCC) recommended methodologies, anthropogenic emissions of nitrous oxide (N2O) in Taiwan during 2000-2003 were estimated to be around 41 thousand metric tons annually. About 87% of N2O emissions come from agriculture, 7% from the energy sector, 3% from industrial processes sector, 3% from waste sector. On the basis of N2O emissions in 2000, projections for the year 2010 show that emissions were estimated to decline by about 6% mainly due to agricultural changes in response to the entry of WTO in 2002. In contrast to projections for the year 2020, N2O emissions were projected to grow by about 17%. This is based on the reasonable scenario that a new adipic acid/nitric acid plant will be probably started after 2010.

Evaluation of On-Road Vehicle Emission Trends in the United States

NASA Astrophysics Data System (ADS)

Harley, R. A.; Dallmann, T. R.; Kirchstetter, T.

2010-12-01

Mobile sources contribute significantly to emissions of nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM2.5), and black carbon (BC). These emissions lead to a variety of environmental problems including air pollution and climate change. At present, national and state-level mobile source emission inventories are developed using statistical models to predict emissions from large and diverse populations of vehicles. Activity is measured by total vehicle-km traveled, and pollutant emission factors are predicted based on laboratory testing of individual vehicles. Despite efforts to improve mobile source emission inventories, they continue to have large associated uncertainties. Alternate methods, such as the fuel-based approach used here, are needed to evaluate estimates of mobile source emissions and to help reduce uncertainties. In this study we quantify U.S. national emissions of NOx, CO, PM2.5, and BC from on-road diesel and gasoline vehicles for the years 1990-2010, including effects of a weakened national economy on fuel sales and vehicle travel from 2008-10. Pollutant emissions are estimated by multiplying total amounts of fuel consumed with emission factors expressed per unit of fuel burned. Fuel consumption is used as a measure of vehicle activity, and is based on records of taxable fuel sales. Pollutant emission factors are derived from roadside and tunnel studies, remote sensing measurements, and individual vehicle exhaust plume capture experiments. Emission factors are updated with new results from a summer 2010 field study conducted at the Caldecott tunnel in the San Francisco Bay Area.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Dasa; Guenther, Alex B.; Shilling, John E.

Terrestrial vegetation emits vast quantities of volatile organic compounds (VOCs) to he atmosphere1-3, which influence oxidants and aerosols leading to complex feedbacks on air quality and climate4-6. Isoprene dominates global non-methane VOC emissions with tropical regions contributing ~80% of global isoprene emissions2. Isoprene emission rates vary over several orders of magnitude for different plant species, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft direct eddy covariance measurements over the pristine Amazon forest. We report isoprene emission rates that are 3 times higher thanmore » satellite top-down estimates and 35% higher than model predictions based on satellite land cover and vegetation specific emission factors (EFs). The results reveal strong correlations between observed isoprene emission rates and terrain elevations which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can explain a substantial degree of isoprene emission variability in tropical forests. Finally, we apply this approach over the central Amazon and use a model to demonstrate the impacts on regional air quality.« less

Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750-2015)

NASA Astrophysics Data System (ADS)

van Marle, Margreet J. E.; Kloster, Silvia; Magi, Brian I.; Marlon, Jennifer R.; Daniau, Anne-Laure; Field, Robert D.; Arneth, Almut; Forrest, Matthew; Hantson, Stijn; Kehrwald, Natalie M.; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stéphane; Yue, Chao; Kaiser, Johannes W.; van der Werf, Guido R.

2017-09-01

Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data have shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently, there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emission estimates back in time based on satellite data starting in 1997, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant, with 10-year averages varying between 1.8 and 2.3 Pg C yr-1. Carbon emissions increased only slightly over the full time period and peaked during the 1990s after which they decreased gradually. There is substantial uncertainty in these estimates, and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 % of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emission estimates are mostly suited for global analyses and will be used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.

Life cycle greenhouse gas emissions of sugar cane renewable jet fuel.

PubMed

Moreira, Marcelo; Gurgel, Angelo C; Seabra, Joaquim E A

2014-12-16

This study evaluated the life cycle GHG emissions of a renewable jet fuel produced from sugar cane in Brazil under a consequential approach. The analysis included the direct and indirect emissions associated with sugar cane production and fuel processing, distribution, and use for a projected 2020 scenario. The CA-GREET model was used as the basic analytical tool, while Land Use Change (LUC) emissions were estimated employing the GTAP-BIO-ADV and AEZ-EF models. Feedstock production and LUC impacts were evaluated as the main sources of emissions, respectively estimated as 14.6 and 12 g CO2eq/MJ of biofuel in the base case. However, the renewable jet fuel would strongly benefit from bagasse and trash-based cogeneration, which would enable a net life cycle emission of 8.5 g CO2eq/MJ of biofuel in the base case, whereas Monte Carlo results indicate 21 ± 11 g CO2eq/MJ. Besides the major influence of the electricity surplus, the sensitivity analysis showed that the cropland-pasture yield elasticity and the choice of the land use factor employed to sugar cane are relevant parameters for the biofuel life cycle performance. Uncertainties about these estimations exist, especially because the study relies on projected performances, and further studies about LUC are also needed to improve the knowledge about their contribution to the renewable jet fuel life cycle.

Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts

NASA Astrophysics Data System (ADS)

Brioude, J.; Angevine, W. M.; Ahmadov, R.; Kim, S.-W.; Evan, S.; McKeen, S. A.; Hsie, E.-Y.; Frost, G. J.; Neuman, J. A.; Pollack, I. B.; Peischl, J.; Ryerson, T. B.; Holloway, J.; Brown, S. S.; Nowak, J. B.; Roberts, J. M.; Wofsy, S. C.; Santoni, G. W.; Oda, T.; Trainer, M.

2013-04-01

We present top-down estimates of anthropogenic CO, NOx and CO2 surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May-June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NOx inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO2 inventory without prior knowledge of CO2 surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NOx fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% in LA County and by 37% in the South Coast Air Basin (SoCAB). NOx posterior emissions were lower by 32% in LA County and by 27% in the SoCAB. NOx posterior emissions were 40% lower on weekends relative to weekdays. The CO2 posterior estimates were 183 Tg yr-1 in SoCAB. A flight during ITCT (Intercontinental Transport and Chemical Transformation) in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NOx posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO2 emissions increased by 10% in LA County but decreased by 4% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NOx emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, a gridded CARB inventory and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, suggesting that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry simulations.

Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties

PubMed Central

2011-01-01

Background Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from credited mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008. Results Deforestation estimates showed good agreement for multi-year periods of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by > 20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C ha-1, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas. Conclusions Estimates of source data uncertainties are essential for REDD+. Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions. PMID:22208947

Variability of wildland fire emissions across the contiguous United States

Treesearch

YongQiang Liu

2004-01-01

This study analyzes spatial and temporal variability of emissions from wildland fires across the contiguous US. The emissions are estimates based on a recently constructed dataset of historical fire records collected by multiple US governlnental agencies. Both wildfire and prescribed fires have the highest emissions over the Pacific coastal states. Prescribed fire...

A high-resolution air pollutants emission inventory in 2013 for the Beijing-Tianjin-Hebei region, China

NASA Astrophysics Data System (ADS)

Qi, Ji; Zheng, Bo; Li, Meng; Yu, Fang; Chen, Chuchu; Liu, Fei; Zhou, Xiafei; Yuan, Jing; Zhang, Qiang; He, Kebin

2017-12-01

We developed a high-resolution Beijing-Tianjin-Hebei (BTH) regional air pollutants emission inventory for the year 2013. The inventory was established using a bottom-up approach based on facility-level activity data obtained from multiple data sources. The estimates from the BTH 2013 emission inventory show that the total emissions of SO2, NOX, PM2.5, PM10, CO, NMVOC, NH3, BC, and OC were 2,305, 2,686, 1,090, 1,494, 20,567, 2,207, 623, 160, and 254 Gg, respectively. The industry sector is the largest emissions source for SO2, NOX, PM2.5, PM10, CO, and NMVOC in the BTH region, contributing 72.6%, 43.7%, 59.6%, 64.7%, 60.3%, and 70.4% of the total emissions, respectively. Power plants contributed 11.8% and 23.3% of the total SO2 and NOX emissions, respectively. The transportation sector contributed 28.9% of the total NOX emissions. Emissions from the residential sector accounted for 31.3%, 21.5%, 46.6% and 71.7% of the total PM2.5, NMVOC, BC and OC emissions, respectively. In addition, more than 90% of the total NH3 emissions originate from the agriculture sector, with 44.2% from fertilizer use and 47.7% from livestock. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. Beijing, Tianjin, Shijiazhuang, Tangshan and Handan are the major contributors of air pollutants. The major NMVOC species in the BTH region are ethylene, acetylene, ethane and toluene. Ethylene is the biggest contributor in Tianjin and Hebei. The largest contributor in Beijing is toluene. There is relatively low uncertainty in SO2 and NOX emission estimates, medium uncertainty in PM2.5, PM10 and CO emission estimates, and high uncertainties in VOC, NH3, BC and OC emission estimates. The proposed policy recommendations, based on the BTH 2013 emission inventory, would be helpful to develop strategies for air pollution control.

Use of MODIS-Derived Fire Radiative Energy to Estimate Smoke Aerosol Emissions over Different Ecosystems

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.

2003-01-01

Biomass burning is the main source of smoke aerosols and certain trace gases in the atmosphere. However, estimates of the rates of biomass consumption and emission of aerosols and trace gases from fires have not attained adequate reliability thus far. Traditional methods for deriving emission rates employ the use of emission factors e(sub x), (in g of species x per kg of biomass burned), which are difficult to measure from satellites. In this era of environmental monitoring from space, fire characterization was not a major consideration in the design of the early satellite-borne remote sensing instruments, such as AVHRR. Therefore, although they are able to provide fire location information, they were not adequately sensitive to variations in fire strength or size, because their thermal bands used for fire detection saturated at the lower end of fire radiative temperature range. As such, hitherto, satellite-based emission estimates employ proxy techniques using satellite derived fire pixel counts (which do not express the fire strength or rate of biomass consumption) or burned areas (which can only be obtained after the fire is over). The MODIS sensor, recently launched into orbit aboard EOS Terra (1999) and Aqua (2002) satellites, have a much higher saturation level and can, not only detect the fire locations 4 times daily, but also measures the at-satellite fire radiative energy (which is a measure of the fire strength) based on its 4 micron channel temperature. Also, MODIS measures the optical thickness of smoke and other aerosols. Preliminary analysis shows appreciable correlation between the MODIS-derived rates of emission of fire radiative energy and smoke over different regions across the globe. These relationships hold great promise for deriving emission coefficients, which can be used for estimating smoke aerosol emissions from MODIS active fire products. This procedure has the potential to provide more accurate emission estimates in near real-time, providing opportunities for various disaster management applications such as alerts, evacuation and, smoke dispersion forecasting.

Virtual CO2 Emission Flows in the Global Electricity Trade Network.

PubMed

Qu, Shen; Li, Yun; Liang, Sai; Yuan, Jiahai; Xu, Ming

2018-06-05

Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO 2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.

Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China

NASA Astrophysics Data System (ADS)

Zhao, Y.; Nielsen, C. P.; Lei, Y.; McElroy, M. B.; Hao, J.

2010-11-01

The uncertainties of a national, bottom-up inventory of Chinese emissions of anthropogenic SO2, NOx, and particulate matter (PM) of different size classes and carbonaceous species are comprehensively quantified, for the first time, using Monte Carlo simulation. The inventory is structured by seven dominant sectors: coal-fired electric power, cement, iron and steel, other industry (boiler combustion), other industry (non-combustion processes), transportation, and residential. For each parameter related to emission factors or activity-level calculations, the uncertainties, represented as probability distributions, are either statistically fitted using results of domestic field tests or, when these are lacking, estimated based on foreign or other domestic data. The uncertainties (i.e., 95% confidence intervals around the central estimates) of Chinese emissions of SO2, NOx, total PM, PM10, PM2.5, black carbon (BC), and organic carbon (OC) in 2005 are estimated to be -14%~12%, -10%~36%, -10%~36%, -12%~42% -16%~52%, -23%~130%, and -37%~117%, respectively. Variations at activity levels (e.g., energy consumption or industrial production) are not the main source of emission uncertainties. Due to narrow classification of source types, large sample sizes, and relatively high data quality, the coal-fired power sector is estimated to have the smallest emission uncertainties for all species except BC and OC. Due to poorer source classifications and a wider range of estimated emission factors, considerable uncertainties of NOx and PM emissions from cement production and boiler combustion in other industries are found. The probability distributions of emission factors for biomass burning, the largest source of BC and OC, are fitted based on very limited domestic field measurements, and special caution should thus be taken interpreting these emission uncertainties. Although Monte Carlo simulation yields narrowed estimates of uncertainties compared to previous bottom-up emission studies, the results are not always consistent with those derived from satellite observations. The results thus represent an incremental research advance; while the analysis provides current estimates of uncertainty to researchers investigating Chinese and global atmospheric transport and chemistry, it also identifies specific needs in data collection and analysis to improve on them. Strengthened quantification of emissions of the included species and other, closely associated ones - notably CO2, generated largely by the same processes and thus subject to many of the same parameter uncertainties - is essential not only for science but for the design of policies to redress critical atmospheric environmental hazards at local, regional, and global scales.

Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China

NASA Astrophysics Data System (ADS)

Zhao, Y.; Nielsen, C. P.; Lei, Y.; McElroy, M. B.; Hao, J.

2011-03-01

The uncertainties of a national, bottom-up inventory of Chinese emissions of anthropogenic SO2, NOx, and particulate matter (PM) of different size classes and carbonaceous species are comprehensively quantified, for the first time, using Monte Carlo simulation. The inventory is structured by seven dominant sectors: coal-fired electric power, cement, iron and steel, other industry (boiler combustion), other industry (non-combustion processes), transportation, and residential. For each parameter related to emission factors or activity-level calculations, the uncertainties, represented as probability distributions, are either statistically fitted using results of domestic field tests or, when these are lacking, estimated based on foreign or other domestic data. The uncertainties (i.e., 95% confidence intervals around the central estimates) of Chinese emissions of SO2, NOx, total PM, PM10, PM2.5, black carbon (BC), and organic carbon (OC) in 2005 are estimated to be -14%~13%, -13%~37%, -11%~38%, -14%~45%, -17%~54%, -25%~136%, and -40%~121%, respectively. Variations at activity levels (e.g., energy consumption or industrial production) are not the main source of emission uncertainties. Due to narrow classification of source types, large sample sizes, and relatively high data quality, the coal-fired power sector is estimated to have the smallest emission uncertainties for all species except BC and OC. Due to poorer source classifications and a wider range of estimated emission factors, considerable uncertainties of NOx and PM emissions from cement production and boiler combustion in other industries are found. The probability distributions of emission factors for biomass burning, the largest source of BC and OC, are fitted based on very limited domestic field measurements, and special caution should thus be taken interpreting these emission uncertainties. Although Monte Carlo simulation yields narrowed estimates of uncertainties compared to previous bottom-up emission studies, the results are not always consistent with those derived from satellite observations. The results thus represent an incremental research advance; while the analysis provides current estimates of uncertainty to researchers investigating Chinese and global atmospheric transport and chemistry, it also identifies specific needs in data collection and analysis to improve on them. Strengthened quantification of emissions of the included species and other, closely associated ones - notably CO2, generated largely by the same processes and thus subject to many of the same parameter uncertainties - is essential not only for science but for the design of policies to redress critical atmospheric environmental hazards at local, regional, and global scales.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuche; Young, Stanley; Gonder, Jeff

This study estimates the range of fuel and emissions impact of an automated-vehicle (AV) based transit system that services campus-based developments, termed an automated mobility district (AMD). The study develops a framework to quantify the fuel consumption and greenhouse gas (GHG) emission impacts of a transit system comprised of AVs, taking into consideration average vehicle fleet composition, fuel consumption/GHG emission of vehicles within specific speed bins, and the average occupancy of passenger vehicles and transit vehicles. The framework is exercised using a previous mobility analysis of a personal rapid transit (PRT) system, a system which shares many attributes with envisionedmore » AV-based transit systems. Total fuel consumption and GHG emissions with and without an AMD are estimated, providing a range of potential system impacts on sustainability. The results of a previous case study based of a proposed implementation of PRT on the Kansas State University (KSU) campus in Manhattan, Kansas, serves as the basis to estimate personal miles traveled supplanted by an AMD at varying levels of service. The results show that an AMD has the potential to reduce total system fuel consumption and GHG emissions, but the amount is largely dependent on operating and ridership assumptions. The study points to the need to better understand ride-sharing scenarios and calls for future research on sustainability benefits of an AMD system at both vehicle and system levels.« less

"Peer Review: Nonroad (NR) Updates to Population Growth, Compression Ignition (CI) Criteria, Toxic Emission Factors and Speciation Profiles"

EPA Science Inventory

This report focuses on the methodology for estimating growth in NR engine populations as used in the MOVES201X-NONROAD emission inventory model. MOVES NR growth rates start with base year engine populations and estimate growth in the populations of NR engines, while applying cons...

Spatially-resolved aircraft-based quantification of methane emissions from the Fayetteville Shale Gas Play

NASA Astrophysics Data System (ADS)

Schwietzke, S.; Petron, G.; Conley, S. A.; Karion, A.; Tans, P. P.; Wolter, S.; King, C. W.; White, A. B.; Coleman, T.; Bianco, L.; Schnell, R. C.

2016-12-01

Confidence in basin scale oil and gas industry related methane (CH4) emission estimates hinges on an in-depth understanding, objective evaluation, and continued improvements of both top-down (e.g. aircraft measurement based) and bottom-up (e.g. emission inventories using facility- and/or component-level measurements) approaches. Systematic discrepancies of CH4 emission estimates between both approaches in the literature have highlighted research gaps. This paper is part of a more comprehensive study to expand and improve this reconciliation effort for a US dry shale gas play. This presentation will focus on refinements of the aircraft mass balance method to reduce the number of potential methodological biases (e.g. data and methodology). The refinements include (i) an in-depth exploration of the definition of upwind conditions and their impact on calculated downwind CH4 enhancements and total CH4 emissions, (ii) taking into account small but non-zero vertical and horizontal wind gradients in the boundary layer, and (iii) characterizing the spatial distribution of CH4 emissions in the study area using aircraft measurements. For the first time to our knowledge, we apply the aircraft mass balance method to calculate spatially resolved total CH4 emissions for 10 km x 60 km sub-regions within the study area. We identify higher-emitting sub-regions and localize repeating emission patterns as well as differences between days. The increased resolution of the top-down calculation will for the first time allow for an in-depth comparison with a spatially and temporally resolved bottom-up emission estimate based on measurements, concurrent activity data and other data sources.

Nitrogen trifluoride global emissions estimated from updated atmospheric measurements

PubMed Central

Arnold, Tim; Harth, Christina M.; Mühle, Jens; Manning, Alistair J.; Salameh, Peter K.; Kim, Jooil; Ivy, Diane J.; Steele, L. Paul; Petrenko, Vasilii V.; Severinghaus, Jeffrey P.; Baggenstos, Daniel; Weiss, Ray F.

2013-01-01

Nitrogen trifluoride (NF3) has potential to make a growing contribution to the Earth’s radiative budget; however, our understanding of its atmospheric burden and emission rates has been limited. Based on a revision of our previous calibration and using an expanded set of atmospheric measurements together with an atmospheric model and inverse method, we estimate that the global emissions of NF3 in 2011 were 1.18 ± 0.21 Gg⋅y−1, or ∼20 Tg CO2-eq⋅y−1 (carbon dioxide equivalent emissions based on a 100-y global warming potential of 16,600 for NF3). The 2011 global mean tropospheric dry air mole fraction was 0.86 ± 0.04 parts per trillion, resulting from an average emissions growth rate of 0.09 Gg⋅y−2 over the prior decade. In terms of CO2 equivalents, current NF3 emissions represent between 17% and 36% of the emissions of other long-lived fluorinated compounds from electronics manufacture. We also estimate that the emissions benefit of using NF3 over hexafluoroethane (C2F6) in electronics manufacture is significant—emissions of between 53 and 220 Tg CO2-eq⋅y−1 were avoided during 2011. Despite these savings, total NF3 emissions, currently ∼10% of production, are still significantly larger than expected assuming global implementation of ideal industrial practices. As such, there is a continuing need for improvements in NF3 emissions reduction strategies to keep pace with its increasing use and to slow its rising contribution to anthropogenic climate forcing. PMID:23341630

Assessment of Particle Pollution from Jetliners: from Smoke Visibility to Nanoparticle Counting.

PubMed

Durdina, Lukas; Brem, Benjamin T; Setyan, Ari; Siegerist, Frithjof; Rindlisbacher, Theo; Wang, Jing

2017-03-21

Aviation is a substantial and a fast growing emissions source. Besides greenhouse gases, aircraft engines emit black carbon (BC), a climate forcer and air pollutant. Aviation BC emissions have been regulated and estimated through exhaust smoke visibility (smoke number). Their impacts are poorly understood because emission inventories lack representative data. Here, we measured BC mass and number-based emissions of the most popular airliner's engines according to a new emission standard. We used a calibrated engine performance model to determine the emissions on the ground, at cruise altitude, and over entire flight missions. Compared to previous estimates, we found up to a factor of 4 less BC mass emitted from the standardized landing and takeoff cycle and up to a factor of 40 less during taxiing. However, the taxi phase accounted for up to 30% of the total BC number emissions. Depending on the fuel composition and flight distance, the mass and number-based emission indices (/kg fuel burned) were 6.2-14.7 mg and 2.8 × 10 14 - 8.7 × 10 14 , respectively. The BC mass emissions per passenger-km were similar to gasoline vehicles, but the number-based emissions were relatively higher, comparable to old diesel vehicles. This study provides representative data for models and will lead to more accurate assessments of environmental impacts of aviation.

On the Impact of Granularity of Space-Based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

NASA Technical Reports Server (NTRS)

Oda, Tomohiro; Lauvaux, Thomas; Lu, Dengsheng; Rao, Preeti; Miles, Natasha L.; Richardson, Scott J.; Gurney, Kevin R.

2017-01-01

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1x1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1x1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 3030 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand.

PubMed

Phairuang, Worradorn; Hata, Mitsuhiko; Furuuchi, Masami

2017-02-01

Annual and monthly-based emission inventories in northern, central and north-eastern provinces in Thailand, where agriculture and related agro-industries are very intensive, were estimated to evaluate the contribution of agricultural activity, including crop residue burning, forest fires and related agro-industries on air quality monitored in corresponding provinces. The monthly-based emission inventories of air pollutants, or, particulate matter (PM), NOx and SO 2 , for various agricultural crops were estimated based on information on the level of production of typical crops: rice, corn, sugarcane, cassava, soybeans and potatoes using emission factors and other parameters related to country-specific values taking into account crop type and the local residue burning period. The estimated monthly emission inventory was compared with air monitoring data obtained at monitoring stations operated by the Pollution Control Department, Thailand (PCD) for validating the estimated emission inventory. The agro-industry that has the greatest impact on the regions being evaluated, is the sugar processing industry, which uses sugarcane as a raw material and its residue as fuel for the boiler. The backward trajectory analysis of the air mass arriving at the PCD station was calculated to confirm this influence. For the provinces being evaluated which are located in the upper northern, lower northern and northeast in Thailand, agricultural activities and forest fires were shown to be closely correlated to the ambient PM concentration while their contribution to the production of gaseous pollutants is much less. Copyright © 2016. Published by Elsevier B.V.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2010-01-01

The 2010 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2007. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2007 were published earlier (Boden et al. 2010). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2013-01-01

The 2013 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2010. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2010 were published earlier (Boden et al. 2013). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2015)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2015-01-01

The 2015 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2011. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2011 were published earlier (Boden et al. 2015). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2011-01-01

The 2011 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2008. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2008 were published earlier (Boden et al. 2011). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2012-01-01

The 2012 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2009. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2009 were published earlier (Boden et al. 2012). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751-2006) (NDP-058.2009)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2009-01-01

The 2009 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2006. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2006 were published earlier (Boden et al. 2009). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2016)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2016-01-01

The 2016 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2013. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2013 were published earlier (Boden et al. 2016). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

A novel method for quantifying the greenhouse gas emissions of biofuels based on historical land use change

NASA Astrophysics Data System (ADS)

Liu, X.; Rhodes, J.; Clarens, A. F.

2012-12-01

Land use change (LUC) emissions have been at the center of an ongoing debate about how the carbon footprint of biofuels compare to petroleum-based fuels over their entire life cycle. The debate about LUC has important implications in the US, the EU, and other countries that are working to deploy biofuel policies, informed by life cycle assessment, that promote carbon emission reductions, among other things. LUC calculations often distinguish between direct land use change (DLUC), those that occur onsite, and indirect land use change (ILUC), those that result from market mechanisms leading to emissions that are either spatially or temporally removed from the agricultural activity. These designations are intended to capture the fundamental connection between agricultural production of biofuel feedstock and its physical effects on the land, but both DLUC and ILUC can be difficult to measure and apply broadly. ILUC estimates are especially challenging to quantify because they rely on global economic models to assess how much land would be brought into production in other countries as a consequence of biofuel feedstock cultivation. As a result, ILUC estimates inherently uncertain, are sensitive to complex assumptions, have limited transparency, and have precipitated sufficient controversy to delay development of coherent biofuel policies. To address these shortcomings of conventional LUC methodologies, we have developed a method for estimating land use change emissions that is based on historical emissions from a parcel of land. The method, which we call historical land use change (HLUC) can be readily quantified for any parcel of land in the world using open source datasets of historical emissions. HLUC is easy to use and is directly tied to the physical processes on land used for biofuel production. The emissions from the HLUC calculations are allocated between historical agricultural activity and proposed biofuel feedstock cultivation. This is compatible with existing life cycle assessment frameworks. HLUC does not represent a direct substitute for conventional ILUC estimates but rather an alternate approach for capturing LUC emissions overall. HLUC estimates for six biofuel producing countries: US (corn ethanol), Brazil (sugarcane ethanol), France (rapeseed biodiesel), Germany (rapeseed biodiesel), Indonesia (palm oil biodiesel), and Malaysia (palm oil biodiesel) were developed. The values are highly comparable to published ILUC values but the nature and magnitude of the uncertainty is lower and the estimates are more regionally variable. Important differences were found between government-derived LUC estimates and HLUC estimates in Brazil and South Asia, which suggest that HLUC could be a more equitable means for allocating emissions than existing approaches. Sensitivity analysis in terms of the spatial resolution of the data suggest that the open source data sets are adequate for obtaining reasonable estimates of HLUC with minimal effort. Alternative allocation scenarios could consider some of the climate dynamics, e.g., carbon degradation in the atmosphere, that would inform more sophisticated accounting. HLUC represents a more straightforward and less controversial policy tool for capturing the emissions associated for land use change and it could enable the advancement of coherent biofuel and climate policy instruments.

Assessing fire emissions from tropical savanna and forests of central Brazil

NASA Technical Reports Server (NTRS)

Riggan, Philip J.; Brass, James A.; Lockwood, Robert N.

1993-01-01

Wildfires in tropical forest and savanna are a strong source of trace gas and particulate emissions to the atmosphere, but estimates of the continental-scale impacts are limited by large uncertainties in the rates of fire occurrence and biomass combustion. Satellite-based remote sensing offers promise for characterizing fire physical properties and impacts on the environment, but currently available sensors saturate over high-radiance targets and provide only indications of regions and times at which fires are extensive and their areal rate of growing as recorded in ash layers. Here we describe an approach combining satellite- and aircraft-based remote sensing with in situ measurements of smoke to estimate emissions from central Brazil. These estimates will improve global accounting of radiation-absorbing gases and particulates that may be contributing to climate change and will provide strategic data for fire management.

Greenhouse gas emissions from the waste sector in Argentina in business-as-usual and mitigation scenarios.

PubMed

Santalla, Estela; Córdoba, Verónica; Blanco, Gabriel

2013-08-01

The objective of this work was the application of 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for the estimation of methane and nitrous oxide emissions from the waste sector in Argentina as a preliminary exercise for greenhouse gas (GHG) inventory development and to compare with previous inventories based on 1996 IPCC Guidelines. Emissions projections to 2030 were evaluated under two scenarios--business as usual (BAU), and mitigation--and the calculations were done by using the ad hoc developed IPCC software. According to local activity data, in the business-as-usual scenario, methane emissions from solid waste disposal will increase by 73% by 2030 with respect to the emissions of year 2000. In the mitigation scenario, based on the recorded trend of methane captured in landfills, a decrease of 50% from the BAU scenario should be achieved by 2030. In the BAU scenario, GHG emissions from domestic wastewater will increase 63% from 2000 to 2030. Methane emissions from industrial wastewater, calculated from activity data of dairy, swine, slaughterhouse, citric, sugar, and wine sectors, will increase by 58% from 2000 to 2030 while methane emissions from domestic will increase 74% in the same period. Results show that GHG emissions calculated from 2006 IPCC Guidelines resulted in lower levels than those reported in previous national inventories for solid waste disposal and domestic wastewater categories, while levels were 18% higher for industrial wastewater. The implementation of the 2006 IPCC Guidelines for National Greenhouse Inventories is now considering by the UNFCCC for non-Annex I countries in order to enhance the compilation of inventories based on comparable good practice methods. This work constitutes the first GHG emissions estimation from the waste sector of Argentina applying the 2006 IPCC Guidelines and the ad doc developed software. It will contribute to identifying the main differences between the models applied in the estimation of methane emissions on the key categories of waste emission sources and to comparing results with previous inventories based on 1996 IPCC Guidelines.

Comparison of different modeling approaches to better evaluate greenhouse gas emissions from whole wastewater treatment plants.

PubMed

Corominas, Lluís; Flores-Alsina, Xavier; Snip, Laura; Vanrolleghem, Peter A

2012-11-01

New tools are being developed to estimate greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs). There is a trend to move from empirical factors to simple comprehensive and more complex process-based models. Thus, the main objective of this study is to demonstrate the importance of using process-based dynamic models to better evaluate GHG emissions. This is tackled by defining a virtual case study based on the whole plant Benchmark Simulation Model Platform No. 2 (BSM2) and estimating GHG emissions using two approaches: (1) a combination of simple comprehensive models based on empirical assumptions and (2) a more sophisticated approach, which describes the mechanistic production of nitrous oxide (N(2) O) in the biological reactor (ASMN) and the generation of carbon dioxide (CO(2) ) and methane (CH(4) ) from the Anaerobic Digestion Model 1 (ADM1). Models already presented in literature are used, but modifications compared to the previously published ASMN model have been made. Also model interfaces between the ASMN and the ADM1 models have been developed. The results show that the use of the different approaches leads to significant differences in the N(2) O emissions (a factor of 3) but not in the CH(4) emissions (about 4%). Estimations of GHG emissions are also compared for steady-state and dynamic simulations. Averaged values for GHG emissions obtained with steady-state and dynamic simulations are rather similar. However, when looking at the dynamics of N(2) O emissions, large variability (3-6 ton CO(2) e day(-1) ) is observed due to changes in the influent wastewater C/N ratio and temperature which would not be captured by a steady-state analysis (4.4 ton CO(2) e day(-1) ). Finally, this study also shows the effect of changing the anaerobic digestion volume on the total GHG emissions. Decreasing the anaerobic digester volume resulted in a slight reduction in CH(4) emissions (about 5%), but significantly decreased N(2) O emissions in the water line (by 14%). Copyright © 2012 Wiley Periodicals, Inc.

USCG Pollution Abatement Program : A Preliminary Study of Vessel and Boat Exhaust Emissions

DOT National Transportation Integrated Search

1971-11-30

A preliminary study of exhaust emissions from Coast Guard vessels and boats indicates that the Coast Guard fleet is an insignificant contributor to air pollution on a national and regional basis. Based upon fuel usage data, emission estimates by vess...

Coupled carbon-nitrogen land surface modelling for UK agricultural landscapes using JULES and JULES-ECOSSE-FUN (JEF)

NASA Astrophysics Data System (ADS)

Comyn-Platt, Edward; Clark, Douglas; Blyth, Eleanor

2016-04-01

The UK is required to provide accurate estimates of the UK greenhouse gas (GHG; CO2, CH4 and N2O) emissions for the UNFCCC (United Nations Framework Convention on Climate Change). Process based land surface models (LSMs), such as the Joint UK Land Environment Simulator (JULES), attempt to provide such estimates based on environmental (e.g. land use and soil type) and meteorological conditions. The standard release of JULES focusses on the water and carbon cycles, however, it has long been suggested that a coupled carbon-nitrogen scheme could enhance simulations. This is of particular importance when estimating agricultural emission inventories where the carbon cycle is effectively managed via the human application of nitrogen based fertilizers. JULES-ECOSSE-FUN (JEF) links JULES with the Estimation of Carbon in Organic Soils - Sequestration and Emission (ECOSSE) model and the Fixation and Uptake of Nitrogen (FUN) model as a means of simulating C:N coupling. This work presents simulations from the standard release of JULES and the most recent incarnation of the JEF coupled system at the point and field scale. Various configurations of JULES and JEF were calibrated and fine-tuned based on comparisons with observations from three UK field campaigns (Crichton, Harwood Forest and Brattleby) specifically chosen to represent the managed vegetation types that cover the UK. The campaigns included flux tower and chamber measurements of CO2, CH4 and N2O amongst other meteorological parameters and records of land management such as application of fertilizer and harvest date at the agricultural sites. Based on the results of these comparisons, JULES and/or JEF will be used to provide simulations on the regional and national scales in order to provide improved estimates of the total UK emission inventory.

Regional Attribution of Ozone Production and Associated Radiative Forcing: a Step to Crediting NOx Emission Reductions

NASA Astrophysics Data System (ADS)

Naik, V.; Mauzerall, D. L.; Horowitz, L.; Schwarzkopf, D.; Ramaswamy, V.; Oppenheimer, M.

2004-12-01

The global distribution of tropospheric ozone (O3) depends on the location of emissions of its precursors in addition to chemical and dynamical factors. The global picture of O3 forcing is, therefore, a sum of regional forcings arising from emissions of precursors from different sources. The Kyoto Protocol does not include ozone as a greenhouse gas, and emission reductions of ozone precursors made under Kyoto or any similar agreement would presently receive no credit. In this study, we quantitatively estimate the contribution of emissions of nitrogen oxides (NOx), the primary limiting O3 precursor in the non-urban atmosphere, from specific countries and regions of the world to global O3 concentration distributions. We then estimate radiative forcing resulting from the regional perturbations of NOx emissions. This analysis is intended as an early step towards incorporating O3 into the Kyoto Protocol or any successor agreement. Under such a system countries could obtain credit for improvements in local air quality that result in reductions of O3 concentrations because of the associated reductions in radiative forcing. We use the global chemistry transport model, MOZART-2, to simulate the global O3 distribution for base year 1990 and perturbations to this distribution caused by a 10% percent reduction in the base emissions of NOx from the United States, Europe, East Asia, India, South America, and Africa. We calculate the radiative forcing for the simulated base and perturbed O3 distributions using the GFDL radiative transfer model. The difference between the radiative forcing from O3 for the base and perturbed distributions provides an estimate of the marginal radiative forcing from a region's emissions of NOx. We will present a quantitative analysis of the magnitude, spatial, and temporal distribution of radiative forcing resulting from marginal changes in the NOx emissions from each region.

Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality.

PubMed

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries' mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country's boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries' level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990-2010) to estimate the relationships between countries' level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country's level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure.

Airborne observations reveal elevational gradient in tropical forest isoprene emissions

DOE PAGES

Gu, Dasa; Guenther, Alex B.; Shilling, John E.; ...

2017-05-23

Terrestrial vegetation emits vast quantities of volatile organic compounds (VOCs) to he atmosphere1-3, which influence oxidants and aerosols leading to complex feedbacks on air quality and climate4-6. Isoprene dominates global non-methane VOC emissions with tropical regions contributing ~80% of global isoprene emissions2. Isoprene emission rates vary over several orders of magnitude for different plant species, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft direct eddy covariance measurements over the pristine Amazon forest. We report isoprene emission rates that are 3 times higher thanmore » satellite top-down estimates and 35% higher than model predictions based on satellite land cover and vegetation specific emission factors (EFs). The results reveal strong correlations between observed isoprene emission rates and terrain elevations which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can explain a substantial degree of isoprene emission variability in tropical forests. Finally, we apply this approach over the central Amazon and use a model to demonstrate the impacts on regional air quality.« less

Comparison of WindTrax and flux-gradient technique in determining PM10 emission rates from a beef cattle feedlot

USDA-ARS?s Scientific Manuscript database

Several emission estimation methods can be used to determine emission fluxes from ground-level area sources, including open-lot beef cattle feedlots. This research determined PM10 emission fluxes from a commercial cattle feedlot in Kansas using WindTrax, a backward Lagrangian stochastic-based atmosp...

QUANTIFICATION OF FUGITIVE REACTIVE ALKENE EMISSIONS FROM PETROCHEMICAL PLANTS WITH PERFLUOROCARBON TRACERS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

SENUM,G.I.; DIETZ,R.N.

2004-06-30

Recent studies demonstrate the impact of fugitive emissions of reactive alkenes on the atmospheric chemistry of the Houston Texas metropolitan area (1). Petrochemical plants located in and around the Houston area emit atmospheric alkenes, such as ethene, propene and 1,3-butadiene. The magnitude of emissions is a major uncertainty in assessing their effects. Even though the petrochemical industry reports that fugitive emissions of alkenes have been reduced to less than 0.1% of daily production, recent measurement data, obtained during the TexAQS 2000 experiment indicates that emissions are perhaps a factor of ten larger than estimated values. Industry figures for fugitive emissionsmore » are based on adding up estimated emission factors for every component in the plant to give a total estimated emission from the entire facility. The dramatic difference between estimated and measured rates indicates either that calculating emission fluxes by summing estimates for individual components is seriously flawed, possibly due to individual components leaking well beyond their estimated tolerances, that not all sources of emissions for a facility are being considered in emissions estimates, or that there are known sources of emissions that are not being reported. This experiment was designed to confirm estimates of reactive alkene emissions derived from analysis of the TexAQS 2000 data by releasing perfluorocarbon tracers (PFTs) at a known flux from a petrochemical plant and sampling both the perfluorocarbon tracer and reactive alkenes downwind using the Piper-Aztec research aircraft operated by Baylor University. PFTs have been extensively used to determine leaks in pipelines, air infiltration in buildings, and to characterize the transport and dispersion of air parcels in the atmosphere. Over 20 years of development by the Tracer Technology Center (TTC) has produced a range of analysis instruments, field samplers and PFT release equipment that have been successfully deployed in a large variety of experiments. PFTs are inert, nontoxic, noncombustible and nonreactive. Up to seven unique PFTs can be simultaneously released, sampled and analyzed and the technology is well suited for determining emission fluxes from large petrochemical facilities. The PFT experiment described here was designed to quantitate alkene emissions from a single petrochemical facility, but such experiments could be applied to other industrial sources or groups of sources in the Houston area.« less

Producing remote sensing-based emission estimates of prescribed burning in the contiguous United States for the U.S. Environmental Protection Agency 2011 National Emissions Inventory

NASA Astrophysics Data System (ADS)

McCarty, J. L.; Pouliot, G. A.; Soja, A. J.; Miller, M. E.; Rao, T.

2013-12-01

Prescribed fires in agricultural landscapes generally produce smaller burned areas than wildland fires but are important contributors to emissions impacting air quality and human health. Currently, there are a variety of available satellite-based estimates of crop residue burning, including the NOAA/NESDIS Hazard Mapping System (HMS) the Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE 2), the Moderate Resolution Imaging Spectroradiometer (MODIS) Official Burned Area Product (MCD45A1)), the MODIS Direct Broadcast Burned Area Product (MCD64A1) the MODIS Active Fire Product (MCD14ML), and a regionally-tuned 8-day cropland differenced Normalized Burn Ratio product for the contiguous U.S. The purpose of this NASA-funded research was to refine the regionally-tuned product utilizing higher spatial resolution crop type data from the USDA NASS Cropland Data Layer and burned area training data from field work and high resolution commercial satellite data to improve the U.S. Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The final product delivered to the EPA included a detailed database of 25 different atmospheric emissions at the county level, emission distributions by crop type and seasonality, and GIS data. The resulting emission databases were shared with the U.S. EPA and regional offices, the National Wildfire Coordinating Group (NWGC) Smoke Committee, and all 48 states in the contiguous U.S., with detailed error estimations for Wyoming and Indiana and detailed analyses of results for Florida, Minnesota, North Dakota, Oklahoma, and Oregon. This work also provided opportunities in discovering the different needs of federal and state partners, including the various geospatial abilities and platforms across the many users and how to incorporate expert air quality, policy, and land management knowledge into quantitative earth observation-based estimations of prescribed fire emissions. Finally, this work created direct communication paths between federal and state partners to the scientists creating the remote sensing-based products, further improving the geospatial products and understanding of air quality impacts of prescribed burning at the state, regional, and national scales.

Incorrect interpretation of carbon mass balance biases global vegetation fire emission estimates.

PubMed

Surawski, N C; Sullivan, A L; Roxburgh, S H; Meyer, C P Mick; Polglase, P J

2016-05-05

Vegetation fires are a complex phenomenon in the Earth system with many global impacts, including influences on global climate. Estimating carbon emissions from vegetation fires relies on a carbon mass balance technique that has evolved with two different interpretations. Databases of global vegetation fire emissions use an approach based on 'consumed biomass', which is an approximation to the biogeochemically correct 'burnt carbon' approach. Here we show that applying the 'consumed biomass' approach to global emissions from vegetation fires leads to annual overestimates of carbon emitted to the atmosphere by 4.0% or 100 Tg compared with the 'burnt carbon' approach. The required correction is significant and represents ∼9% of the net global forest carbon sink estimated annually. Vegetation fire emission studies should use the 'burnt carbon' approach to quantify and understand the role of this burnt carbon, which is not emitted to the atmosphere, as a sink enriched in carbon.

Global atmospheric emissions of polycyclic aromatic hydrocarbons from 1960 to 2008 and future predictions.

PubMed

Shen, Huizhong; Huang, Ye; Wang, Rong; Zhu, Dan; Li, Wei; Shen, Guofeng; Wang, Bin; Zhang, Yanyan; Chen, Yuanchen; Lu, Yan; Chen, Han; Li, Tongchao; Sun, Kang; Li, Bengang; Liu, Wenxin; Liu, Junfeng; Tao, Shu

2013-06-18

Global atmospheric emissions of 16 polycyclic aromatic hydrocarbons (PAHs) from 69 major sources were estimated for a period from 1960 to 2030. Regression models and a technology split method were used to estimate country and time specific emission factors, resulting in a new estimate of PAH emission factor variation among different countries and over time. PAH emissions in 2007 were spatially resolved to 0.1° × 0.1° grids based on a newly developed global high-resolution fuel combustion inventory (PKU-FUEL-2007). The global total annual atmospheric emission of 16 PAHs in 2007 was 504 Gg (331-818 Gg, as interquartile range), with residential/commercial biomass burning (60.5%), open-field biomass burning (agricultural waste burning, deforestation, and wildfire, 13.6%), and petroleum consumption by on-road motor vehicles (12.8%) as the major sources. South (87 Gg), East (111 Gg), and Southeast Asia (52 Gg) were the regions with the highest PAH emission densities, contributing half of the global total PAH emissions. Among the global total PAH emissions, 6.19% of the emissions were in the form of high molecular weight carcinogenic compounds and the percentage of the carcinogenic PAHs was higher in developing countries (6.22%) than in developed countries (5.73%), due to the differences in energy structures and the disparities of technology. The potential health impact of the PAH emissions was greatest in the parts of the world with high anthropogenic PAH emissions, because of the overlap of the high emissions and high population densities. Global total PAH emissions peaked at 592 Gg in 1995 and declined gradually to 499 Gg in 2008. Total PAH emissions from developed countries peaked at 122 Gg in the early 1970s and decreased to 38 Gg in 2008. Simulation of PAH emissions from 2009 to 2030 revealed that PAH emissions in developed and developing countries would decrease by 46-71% and 48-64%, respectively, based on the six IPCC SRES scenarios.

Global atmospheric emissions of polycyclic aromatic hydrocarbons from 1960 to 2008 and future predictions

PubMed Central

Shen, Huizhong; Huang, Ye; Wang, Rong; Zhu, Dan; Li, Wei; Shen, Guofeng; Wang, Bin; Zhang, Yanyan; Chen, Yuanchen; Lu, Yan; Chen, Han; Li, Tongchao; Sun, Kang; Li, Bengang; Liu, Wenxin; Liu, Junfeng; Tao, Shu

2013-01-01

Global atmospheric emissions of 16 polycyclic aromatic hydrocarbons (PAHs) from 69 major sources were estimated for a period from 1960 to 2030. Regression models and a technology split method were used to estimate country and time specific emission factors, resulting in a new estimate of PAH emission factor variation among different countries and over time. PAH emissions in 2007 were spatially resolved to 0.1°× 0.1° grids based on a newly developed global high-resolution fuel combustion inventory (PKU-FUEL-2007). The global total annual atmospheric emission of 16 PAHs in 2007 was 504 Gg (331-818 Gg, as interquartile range), with residential/commercial biomass burning (60.5%), open-field biomass burning (agricultural waste burning, deforestation, and wildfire, 13.6%), and petroleum consumption by on-road motor vehicles (12.8%) as the major sources. South (87 Gg), East (111 Gg), and Southeast Asia (52 Gg) were the regions with the highest PAH emission densities, contributing half of the global total PAH emissions. Among the global total PAH emissions, 6.19% of the emissions were in the form of high molecular weight carcinogenic compounds and the percentage of the carcinogenic PAHs was higher in developing countries (6.22%) than in developed countries (5.73%), due to the differences in energy structures and the disparities of technology. The potential health impact of the PAH emissions was greatest in the parts of the world with high anthropogenic PAH emissions, because of the overlap of the high emissions and high population densities. Global total PAH emissions peaked at 592 Gg in 1995 and declined gradually to 499 Gg in 2008. Total PAH emissions from developed countries peaked at 122 Gg in the early 1970s and decreased to 38 Gg in 2008. Simulation of PAH emissions from 2009 to 2030 revealed that PAH emissions in developed and developing countries would decrease by 46-71% and 48-64%, respectively, based on the six IPCC SRES scenarios. PMID:23659377

Quantification of uncertainty associated with United States high resolution fossil fuel CO2 emissions: updates, challenges and future plans

NASA Astrophysics Data System (ADS)

Gurney, K. R.; Chandrasekaran, V.; Mendoza, D. L.; Geethakumar, S.

2010-12-01

The Vulcan Project has estimated United States fossil fuel CO2 emissions at the hourly time scale and at spatial scales below the county level for the year 2002. Vulcan is built from a wide variety of observational data streams including regulated air pollutant emissions reporting, traffic monitoring, energy statistics, and US census data. In addition to these data sets, Vulcan relies on a series of modeling assumptions and constructs to interpolate in space, time and transform non-CO2 reporting into an estimate of CO2 combustion emissions. The recent version 2.0 of the Vulcan inventory has produced advances in a number of categories with particular emphasis on improved temporal structure. Onroad transportation emissions now avail of roughly 5000 automated traffic count monitors allowing for much improved diurnal and weekly time structure in our onroad transportation emissions. Though the inventory shows excellent agreement with independent national-level CO2 emissions estimates, uncertainty quantification has been a challenging task given the large number of data sources and numerous modeling assumptions. However, we have now accomplished a complete uncertainty estimate across all the Vulcan economic sectors and will present uncertainty estimates as a function of space, time, sector and fuel. We find that, like the underlying distribution of CO2 emissions themselves, the uncertainty is also strongly lognormal with high uncertainty associated with a relatively small number of locations. These locations typically are locations reliant upon coal combustion as the dominant CO2 source. We will also compare and contrast Vulcan fossil fuel CO2 emissions estimates against estimates built from DOE fuel-based surveys at the state level. We conclude that much of the difference between the Vulcan inventory and DOE statistics are not due to biased estimation but mechanistic differences in supply versus demand and combustion in space/time.

A refined method for the calculation of the Non-Methane Volatile Organic Compound emission estimate from Domestic Solvent Usage in Ireland from 1992 to 2014 - A case study for Ireland

NASA Astrophysics Data System (ADS)

Barry, Stephen; O'Regan, Bernadette

2016-08-01

This study describes a new methodology to calculate Non-Methane Volatile Organic Compounds from Domestic Solvent Use including Fungicides over the period 1992-2014. Improved emissions data compiled at a much more refined level can help policy-makers develop more effective policy's to address environmental issues. However, a number of problems were found when member states attempt to use national statistics for Domestic Solvent Use including Fungicides. For instance, EMEP/EEA (2013) provides no guidance regarding which activity data should be used, resulting in emission estimates being potentially inconsistent and un-comparable. Also, previous methods and emission factors described in the EMEP/EEA (2013) guidebook do not exactly match data collected by state agencies. This makes using national statistics difficult. In addition, EMEP/EEA (2013) use broader categories than necessary (e.g. Cosmetics Aerosol/Non Aerosol) to estimate emissions while activity data is available at a more refined level scale (e.g. Personal Cleaning Products, Hair Products, Cosmetics, Deodorants and Perfumes). This can make identifying the drivers of emissions unclear. This study builds upon Tzanidakis et al. (2012) whereby it provides a method for collecting activity data from state statistics, developed country specific emission factors based on a survey of 177 Irish products and importantly, used a new method to account for the volatility of organic compounds found in commonly available domestic solvent containing products. This is the first study to account for volatility based on the characteristics of organic compounds and therefore is considered a more accurate method of accounting for emissions from this emission source. The results of this study can also be used to provide a simple method for other member parties to account for the volatility of organic compounds using sectorial adjustment factors described here. For comparison purposes, emission estimates were calculated using the Tier 1 approach currently used in the emission inventory, using activity data and emission factors unadjusted for volatility and adjusted for volatility. The unadjusted estimate is useful, because it demonstrates the failure to properly account for volatility can produce significantly over-estimated emissions from the Domestic Solvent Usage sector. Unadjusted emissions were found to be 30% lower than the EMEP/EEA (2013) Tier 1 period in 2014. Emissions were found to reduce a further 20.9% when the volatility of the organic compounds was included. This new method shows that member parties may be significantly overestimating emissions from Domestic Solvent Use including pesticides and further work should include refining organic compound content and the sectorial adjustment factor of products.

COMPILATION AND ANALYSES OF EMISSIONS INVENTORIES FOR THE NOAA ATMOSPHERIC CHEMISTRY PROJECT. PROGRESS REPORT, AUGUST 1997.

DOE Office of Scientific and Technical Information (OSTI.GOV)

BENKOVITZ,C.M.

1997-09-01

Global inventories of anthropogenic emissions of oxides of nitrogen (NO{sub x}) for circa 1985 and 1990 and Non-Methane Volatile Organic Compounds (NMVOCs) for circa 1990 have been compiled by this project. Work on the inventories has been carried out under the umbrella of the Global Emissions Inventory Activity (GEIA) of the International Global Atmospheric Chemistry (IGAC) Program. The 1985 NO{sub x} inventory was compiled using default data sets of global emissions that were refined via the use of more detailed regional data sets; this inventory is being distributed to the scientific community at large as the GEIA Version 1A inventory.more » Global emissions of NO{sub x} for 1985 are estimated to be 21 Tg N y{sup -1}, with approximately 84% originating in the Northern Hemisphere. The 1990 inventories of NO{sub x} and NMVOCs were compiled using unified methodologies and data sets in collaboration with the Netherlands National Institute of Public Health and Environmental Protection (Rijksinstituut Voor Volksgezondheid en Milieuhygiene, RIVM) and the Division of Technology for Society of the Netherlands Organization for Applied Scientific Research, (IMW-TNO); these emissions will be used as the default estimates to be updated with more accurate regional data. The NMVOC inventory was gridded and speciated into 23 chemical categories. The resulting global emissions for 1990 are 31 Tg N yr{sup -1} for NO{sub x} and 173 Gg NMVOC yr{sup -1}. Emissions of NO{sub x} are highest in the populated and industrialized areas of eastern North America and across Europe, and in biomass burning areas of South America, Africa, and Asia. Emissions of NMVOCs are highest in biomass burning areas of South America, Africa, and Asia. The 1990 NO{sub x} emissions were gridded to 1{sup o} resolution using surrogate data, and were given seasonal, two-vertical-level resolution and speciated into NO and NO{sub 2} based on proportions derived from the 1985 GEIA Version 1B inventory. Global NMVOC emissions were given additional species resolution by allocating the 23 chemical categories to individual chemical species based on factors derived from the speciated emissions of NMVOCs in the U.S. from the U.S. EPA's 1990 Interim Inventory. Ongoing research activities for this project continue to address emissions of both NO{sub x} and NMVOCs. Future tasks include: (a) evaluation of more detailed regional emissions estimates and update of the default 1990 inventories with the appropriate estimates, (b) derivation of quantitative uncertainty estimates for the emission values, and (c) development of emissions estimates for 1995.« less

Intermediate Volatility Organic Compound Emissions from On-Road Diesel Vehicles: Chemical Composition, Emission Factors, and Estimated Secondary Organic Aerosol Production.

PubMed

Zhao, Yunliang; Nguyen, Ngoc T; Presto, Albert A; Hennigan, Christopher J; May, Andrew A; Robinson, Allen L

2015-10-06

Emissions of intermediate-volatility organic compounds (IVOCs) from five on-road diesel vehicles and one off-road diesel engine were characterized during dynamometer testing. The testing evaluated the effects of driving cycles, fuel composition and exhaust aftertreatment devices. On average, more than 90% of the IVOC emissions were not identified on a molecular basis, instead appearing as an unresolved complex mixture (UCM) during gas-chromatography mass-spectrometry analysis. Fuel-based emissions factors (EFs) of total IVOCs (speciated + unspeciated) depend strongly on aftertreatment technology and driving cycle. Total-IVOC emissions from vehicles equipped with catalyzed diesel particulate filters (DPF) are substantially lower (factor of 7 to 28, depending on driving cycle) than from vehicles without any exhaust aftertreatment. Total-IVOC emissions from creep and idle operations are substantially higher than emissions from high-speed operations. Although the magnitude of the total-IVOC emissions can vary widely, there is little variation in the IVOC composition across the set of tests. The new emissions data are combined with published yield data to investigate secondary organic aerosol (SOA) formation. SOA production from unspeciated IVOCs is estimated using surrogate compounds, which are assigned based on gas-chromatograph retention time and mass spectral signature of the IVOC UCM. IVOCs contribute the vast majority of the SOA formed from exhaust from on-road diesel vehicles. The estimated SOA production is greater than predictions by previous studies and substantially higher than primary organic aerosol. Catalyzed DPFs substantially reduce SOA formation potential of diesel exhaust, except at low speed operations.

Estimations of pollution emissions by the Moscow megapolis basing on in-situ measurements and optical remote sensing

NASA Astrophysics Data System (ADS)

Elansky, N.; Postylyakov, O.; Verevkin, Y.; Volobuev, L.; Ponomarev, N.

2017-11-01

By the present a large amount of data has been accumulated on direct measurements of the pollution and thermodynamic state of the atmosphere in the Moscow region, which was obtained at stations of Roshydromet, Mosecomonitoring, A.M.Obukhov Institute of Atmospheric Physics (OIAP), M.V. Lomonosov Moscow State University, NPO Typhoon, what allows estimating pollution emissions based on measurements and correcting existing emission inventories, which are evaluated mainly on indirect data connected with population density, fuel consumption, etc. Within the framework of the project, the whole volume of data on the concentration of ground contaminants CO, NOx, SO2, CH4, obtained at regularly operated Moscow Ecological Monitoring stations and at OIAP stations from 2005 to 2014, was systematized. Observation data on pollution concentrations are supplemented by measurements of their integral content in the atmospheric boundary layer, obtained by differential spectroscopy methods (MAX DOAS, ZDOAS) at stationary stations and by passing Moscow with DOAS-equipped car. The paper present preliminary estimates of pollution emissions in the Moscow region, obtained on the basis of the collected array of experimental data. The estimations of pollutant emissions from Moscow were obtained experimentally in a few ways: (1) on the basis of network observations of surface concentrations, (2) on the basis of measurements in the atmospheric layer 0-348 m at Ostankino TV tower, (3) on the basis of the integral pollutant (NO2) content in ABL obtained by DOAS technique from stationary stations, and (4) using a car with DOAS equipment traveling over the closed route around Moscow (for NO2). All experimental approaches yielded close values of pollution emissions for Moscow. Trends in emissions of CO, NOx, and CH4 are negative, and the trend of SO2 emission is positive from 2005 to 2014.

A New Black Hole Mass Estimate for Obscured Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Minezaki, Takeo; Matsushita, Kyoko

2015-04-01

We propose a new method for estimating the mass of a supermassive black hole, applicable to obscured active galactic nuclei (AGNs). This method estimates the black hole mass using the width of the narrow core of the neutral FeKα emission line in X-rays and the distance of its emitting region from the black hole based on the isotropic luminosity indicator via the luminosity scaling relation. Assuming the virial relation between the locations and the velocity widths of the neutral FeKα line core and the broad Hβ emission line, the luminosity scaling relation of the neutral FeKα line core emitting region is estimated. We find that the velocity width of the neutral FeKα line core falls between that of the broad Balmer emission lines and the corresponding value at the dust reverberation radius for most of the target AGNs. The black hole mass {{M}BH,FeKα } estimated with this method is then compared with other black hole mass estimates, such as the broad emission-line reverberation mass {{M}BH,rev} for type 1 AGNs, the mass {{M}BH,{{H2}O}} based on the H2O maser, and the single-epoch mass estimate {{M}BH,pol} based on the polarized broad Balmer lines for type 2 AGNs. We find that {{M}BH,FeKα } is consistent with {{M}BH,rev} and {{M}BH,pol}, and find that {{M}BH,FeKα } correlates well with {{M}BH,{{H2}O}}. These results suggest that {{M}BH,FeKα } is a potential indicator of the black hole mass for obscured AGNs. In contrast, {{M}BH,FeKα } is systematically larger than {{M}BH,{{H2}O}} by about a factor of 5, and the possible origins are discussed.

Assessing the Impact of Fires on Air Quality in the Southeastern U.S. with a Unified Prescribed Burning Database

NASA Astrophysics Data System (ADS)

Garcia Menendez, F.; Afrin, S.

2017-12-01

Prescribed fires are used extensively across the Southeastern United States and are a major source of air pollutant emissions in the region. These land management projects can adversely impact local and regional air quality. However, the emissions and air pollution impacts of prescribed fires remain largely uncertain. Satellite data, commonly used to estimate fire emissions, is often unable to detect the low-intensity, short-lived prescribed fires characteristic of the region. Additionally, existing ground-based prescribed burn records are incomplete, inconsistent and scattered. Here we present a new unified database of prescribed fire occurrence and characteristics developed from systemized digital burn permit records collected from public and private land management organizations in the Southeast. This bottom-up fire database is used to analyze the correlation between high PM2.5 concentrations measured by monitoring networks in southern states and prescribed fire occurrence at varying spatial and temporal scales. We show significant associations between ground-based records of prescribed fire activity and the observational air quality record at numerous sites by applying regression analysis and controlling confounding effects of meteorology. Furthermore, we demonstrate that the response of measured PM2.5 concentrations to prescribed fire estimates based on burning permits is significantly stronger than their response to satellite fire observations from MODIS (moderate-resolution imaging spectroradiometer) and geostationary satellites or prescribed fire emissions data in the National Emissions Inventory. These results show the importance of bottom-up smoke emissions estimates and reflect the need for improved ground-based fire data to advance air quality impacts assessments focused on prescribed burning.

Estimating emissions from the Indian transport sector with on-road fleet composition and traffic volume

NASA Astrophysics Data System (ADS)

Pandey, Apoorva; Venkataraman, Chandra

2014-12-01

Urbanization and rising household incomes in India have led to growing transport demand, particularly during 1990-2010. Emissions from transportation have been implicated in air quality and climate effects. In this work, emissions of particulate matter (PM2.5 or mass concentration of particles smaller than 2.5 um diameter), black carbon (BC) and organic carbon (OC), were estimated from the transport sector in India, using detailed technology divisions and regionally measured emission factors. Modes of transport addressed in this work include road transport, railways, shipping and aviation, but exclude off-road equipment like diesel machinery and tractors. For road transport, a vehicle fleet model was used, with parameters derived from vehicle sales, registration data, and surveyed age-profile. The fraction of extremely high emitting vehicles, or superemitters, which is highly uncertain, was assumed as 20%. Annual vehicle utilization estimates were based on regional surveys and user population. For railways, shipping and aviation, a top-down approach was applied, using nationally reported fuel consumption. Fuel use and emissions from on-road vehicles were disaggregated at the state level, with separate estimates for 30 cities in India. The on-road fleet was dominated by two-wheelers, followed by four-and three-wheelers, with new vehicles comprising the majority of the fleet for each vehicle type. A total of 276 (-156, 270) Gg/y PM2.5, 144 (-99, 207) Gg/y BC, and 95 (-64, 130) Gg/y OC emissions were estimated, with over 97% contribution from on-road transport. Largest emitters were identified as heavy duty diesel vehicles for PM2.5 and BC, but two-stroke vehicles and superemitters for OC. Old vehicles (pre-2005) contributed significantly more (∼70%) emissions, while their share in the vehicle fleet was smaller (∼45%). Emission estimates were sensitive to assumed superemitter fraction. Improvement of emission estimates requires on-road emission factor measurements for all vehicle types and a better understanding of vehicle utilization and superemitter fraction.

Volatile organic compound (VOC) emissions during malting and beer manufacture

NASA Astrophysics Data System (ADS)

Gibson, Nigel B.; Costigan, Gavin T.; Swannell, Richard P. J.; Woodfield, Michael J.

Estimates have been made of the amounts of volatile organic compounds (VOCs) released during different stages of beer manufacture. The estimates are based on recent measurements and plant specification data supplied by manufacturers. Data were obtained for three main manufacturing processes (malting, wort processing and fermentation) for three commercial beer types. Some data on the speciation of emitted compounds have been obtained. Based on these measurements, an estimate of the total unabated VOC emission. from the U.K. brewing industry was calculated as 3.5 kta -1, over 95% of which was generated during barley malting. This value does not include any correction for air pollution control.

Estimation of fire emissions from satellite-based measurements

NASA Astrophysics Data System (ADS)

Ichoku, C. M.; Kaufman, Y. J.

2004-12-01

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System (EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (Ce in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America or Australia, but about 50 percent lower than the value for Zambia in southern Africa.

Estimation of Fire Emissions from Satellite-Based Measurements

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.

2004-01-01

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (C(e), in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America, Western Europe, or Australia, but about 50% lower than the value for southern Africa.

Impact of Biogenic Emission Uncertainties on the Simulated Response of Ozone and Fine Particulate Matter to Anthropogenic Emission Reductions

PubMed Central

Hogrefe, Christian; Isukapalli, Sastry S.; Tang, Xiaogang; Georgopoulos, Panos G.; He, Shan; Zalewsky, Eric E.; Hao, Winston; Ku, Jia-Yeong; Key, Tonalee; Sistla, Gopal

2011-01-01

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1–0.25 μg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1–2% of the value of the annual PM2.5 NAAQS of 15 μg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions. PMID:21305893

Market-driven emissions from recovery of carbon dioxide gas.

PubMed

Supekar, Sarang D; Skerlos, Steven J

2014-12-16

This article uses a market-based allocation method in a consequential life cycle assessment (LCA) framework to estimate the environmental emissions created by recovering carbon dioxide (CO2). We find that 1 ton of CO2 recovered as a coproduct of chemicals manufacturing leads to additional greenhouse gas emissions of 147-210 kg CO2 eq , while consuming 160-248 kWh of electricity, 254-480 MJ of heat, and 1836-4027 kg of water. The ranges depend on the initial and final purity of the CO2, particularly because higher purity grades require additional processing steps such as distillation, as well as higher temperature and flow rate of regeneration as needed for activated carbon treatment and desiccant beds. Higher purity also reduces process efficiency due to increased yield losses from regeneration gas and distillation reflux. Mass- and revenue-based allocation methods used in attributional LCA estimate that recovering CO2 leads to 19 and 11 times the global warming impact estimated from a market-based allocation used in consequential LCA.

Downward Atmospheric Longwave Radiation in the City of Sao Paulo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barbaro, Eduardo W.; Oliveira, Amauri P.; Soares, Jacyra

2009-03-11

This work evaluates objectively the consistency and quality of a 9 year dataset based on 5 minute average values of downward longwave atmospheric (LW) emission, shortwave radiation, temperature and relative humidity. All these parameters were observed simultaneously and continuously from 1997 to 2006 in the IAG micrometeorological platform, located at the top of the IAG-USP building. The pyrgeometer dome emission effect was removed using neural network technique reducing the downward long wave atmospheric emission error to 3.5%. The comparison, between the monthly average values of LW emission observed in Sao Paulo and satellite estimates from SRB-NASA project, indicated a verymore » good agreement. Furthermore, this work investigates the performance of 10 empirical expressions to estimate the LW emission at the surface. The comparison between the models indicates that Brunt's one presents the better results, with smallest ''MBE,''''RMSE'' and biggest ''d'' index of agreement, therefore Brunt is the most indicated model to estimate LW emission under clear sky conditions in the city of Sao Paulo.« less

A new method for estimating greenhouse gases and ammonia emissions from livestock buildings

NASA Astrophysics Data System (ADS)

Barrancos, José; Briz, Susana; Nolasco, Dácil; Melián, Gladys; Padilla, Germán; Padrón, Eleazar; Fernández, Isabel; Pérez, Nemesio; Hernández, Pedro A.

2013-08-01

It is widely known that carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) are the main greenhouse gases contributing to global climate change. Emission factors for the aforementioned gases have been proposed in order to calculate the contribution of livestock farming to global climate change. However, these emission factors depend on many additional factors such as the housing system, environmental conditions, etc., which implies some uncertainties in their estimation. Therefore, works that aim at improving experimental calculation of these emissions are crucial to provide reliable estimates of the emissions produced by livestock. The purpose of this work was to apply a new methodology inspired by the accumulation chamber method to estimate emission rates from livestock buildings. The work was based on measuring the increase of gas emissions inside the livestock building by means of the remote sensing technique Open-Path FTIR (OP-FTIR). Previously to the measurements, livestock building cattle was confined outside of the building. Utilization of fan ventilation system favoured the homogenization of air inside the building. This experiment proved that evolution of CH4 and CO2 concentrations inside the livestock building behaved like an accumulation chamber unlike the N2O which did not show such behaviour. Results showed CH4, CO2 and NH3 emissions of 167 ± 54,700 ± 200 and 1.3 ± 0.2 kg head-1 year-1, respectively. One of the main parameters affecting the estimated emission factors is the type of animal feeding. Therefore, it is essential to investigate the influence of food composition on CH4 and CO2 emission in a relative larger number of operating cattle buildings since the methodology herein proposed is an easy and cheap tool to study livestock emission factors and their variability.

A spatial modeling framework to evaluate domestic biofuel-induced potential land use changed and emissions

USGS Publications Warehouse

Elliot, Joshua; Sharma, Bhavna; Best, Neil; Glotter, Michael; Dunn, Jennifer B.; Foster, Ian; Miguez, Fernando; Mueller, Steffen; Wang, Michael

2014-01-01

We present a novel bottom-up approach to estimate biofuel-induced land-use change (LUC) and resulting CO2 emissions in the U.S. from 2010 to 2022, based on a consistent methodology across four essential components: land availability, land suitability, LUC decision-making, and induced CO2 emissions. Using highresolution geospatial data and modeling, we construct probabilistic assessments of county-, state-, and national-level LUC and emissions for macroeconomic scenarios. We use the Cropland Data Layer and the Protected Areas Database to characterize availability of land for biofuel crop cultivation, and the CERES-Maize and BioCro biophysical crop growth models to estimate the suitability (yield potential) of available lands for biofuel crops. For LUC decisionmaking, we use a county-level stochastic partial-equilibrium modeling framework and consider five scenarios involving annual ethanol production scaling to 15, 22, and 29 BG, respectively, in 2022, with corn providing feedstock for the first 15 BG and the remainder coming from one of two dedicated energy crops. Finally, we derive high-resolution above-ground carbon factors from the National Biomass and Carbon Data set to estimate emissions from each LUC pathway. Based on these inputs, we obtain estimates for average total LUC emissions of 6.1, 2.2, 1.0, 2.2, and 2.4 gCO2e/MJ for Corn-15 Billion gallons (BG), Miscanthus × giganteus (MxG)-7 BG, Switchgrass (SG)-7 BG, MxG-14 BG, and SG-14 BG scenarios, respectively.

Estimates of increased black carbon emissions from electrostatic precipitators during powdered activated carbon injection for mercury emissions control.

PubMed

Clack, Herek L

2012-07-03

The behavior of mercury sorbents within electrostatic precipitators (ESPs) is not well-understood, despite a decade or more of full-scale testing. Recent laboratory results suggest that powdered activated carbon exhibits somewhat different collection behavior than fly ash in an ESP and particulate filters located at the outlet of ESPs have shown evidence of powdered activated carbon penetration during full-scale tests of sorbent injection for mercury emissions control. The present analysis considers a range of assumed differential ESP collection efficiencies for powdered activated carbon as compared to fly ash. Estimated emission rates of submicrometer powdered activated carbon are compared to estimated emission rates of particulate carbon on submicrometer fly ash, each corresponding to its respective collection efficiency. To the extent that any emitted powdered activated carbon exhibits size and optical characteristics similar to black carbon, such emissions could effectively constitute an increase in black carbon emissions from coal-based stationary power generation. The results reveal that even for the low injection rates associated with chemically impregnated carbons, submicrometer particulate carbon emissions can easily double if the submicrometer fraction of the native fly ash has a low carbon content. Increasing sorbent injection rates, larger collection efficiency differentials as compared to fly ash, and decreasing sorbent particle size all lead to increases in the estimated submicrometer particulate carbon emissions.

Global estimation of CO emissions using three sets of satellite data for burned area

NASA Astrophysics Data System (ADS)

Jain, Atul K.

Using three sets of satellite data for burned areas together with the tree cover imagery and a biogeochemical component of the Integrated Science Assessment Model (ISAM) the global emissions of CO and associated uncertainties are estimated for the year 2000. The available fuel load (AFL) is calculated using the ISAM biogeochemical model, which accounts for the aboveground and surface fuel removed by land clearing for croplands and pasturelands, as well as the influence on fuel load of various ecosystem processes (such as stomatal conductance, evapotranspiration, plant photosynthesis and respiration, litter production, and soil organic carbon decomposition) and important feedback mechanisms (such as climate and fertilization feedback mechanism). The ISAM estimated global total AFL in the year 2000 was about 687 Pg AFL. All forest ecosystems account for about 90% of the global total AFL. The estimated global CO emissions based on three global burned area satellite data sets (GLOBSCAR, GBA, and Global Fire Emissions Database version 2 (GFEDv2)) for the year 2000 ranges between 320 and 390 Tg CO. Emissions from open fires are highest in tropical Africa, primarily due to forest cutting and burning. The estimated overall uncertainty in global CO emission is about ±65%, with the highest uncertainty occurring in North Africa and Middle East region (±99%). The results of this study suggest that the uncertainties in the calculated emissions stem primarily from the area burned data.

Uncertainties of wild-land fires emission in AQMEII phase 2 case study

NASA Astrophysics Data System (ADS)

Soares, J.; Sofiev, M.; Hakkarainen, J.

2015-08-01

The paper discusses the main uncertainties of wild-land fire emission estimates used in the AQMEII-II case study. The wild-land fire emission of particulate matter for the summer fire season of 2010 in Eurasia was generated by the Integrated System for wild-land Fires (IS4FIRES). The emission calculation procedure included two steps: bottom-up emission compilation from radiative energy of individual fires observed by MODIS instrument on-board of Terra and Aqua satellites; and top-down calibration of emission factors based on the comparison between observations and modelled results. The approach inherits various uncertainties originating from imperfect information on fires, inaccuracies of the inverse problem solution, and simplifications in the fire description. These are analysed in regard to the Eurasian fires in 2010. It is concluded that the total emission is likely to be over-estimated by up to 50% with individual-fire emission accuracy likely to vary in a wide range. The first results of the new IS4FIRESv2 products and fire-resolving modelling are discussed in application to the 2010 events. It is shown that the new emission estimates have similar patterns but are lower than the IS4FIRESv1 values.

Arctic lakes are continuous methane sources to the atmosphere under warming conditions

NASA Astrophysics Data System (ADS)

Tan, Zeli; Zhuang, Qianlai

2015-05-01

Methane is the second most powerful carbon-based greenhouse gas in the atmosphere and its production in the natural environment through methanogenesis is positively correlated with temperature. Recent field studies showed that methane emissions from Arctic thermokarst lakes are significant and could increase by two- to four-fold due to global warming. But the estimates of this source are still poorly constrained. By using a process-based climate-sensitive lake biogeochemical model, we estimated that the total amount of methane emissions from Arctic lakes is 11.86 Tg yr-1, which is in the range of recent estimates of 7.1-17.3 Tg yr-1 and is on the same order of methane emissions from northern high-latitude wetlands. The methane emission rate varies spatially over high latitudes from 110.8 mg CH4 m-2 day-1 in Alaska to 12.7 mg CH4 m-2 day-1 in northern Europe. Under Representative Concentration Pathways (RCP) 2.6 and 8.5 future climate scenarios, methane emissions from Arctic lakes will increase by 10.3 and 16.2 Tg CH4 yr-1, respectively, by the end of the 21st century.

A process-based emission model for volatile organic compounds from silage sources on farms

USDA-ARS?s Scientific Manuscript database

Silage on dairy farms can emit large amounts of volatile organic compounds (VOCs), a precursor in the formation of tropospheric ozone. Because of the challenges associated with direct measurements, process-based modeling is another approach for estimating emissions of air pollutants from sources suc...

Revised methane emissions factors and spatially distributed annual carbon fluxes for global livestock.

PubMed

Wolf, Julie; Asrar, Ghassem R; West, Tristram O

2017-09-29

Livestock play an important role in carbon cycling through consumption of biomass and emissions of methane. Recent research suggests that existing bottom-up inventories of livestock methane emissions in the US, such as those made using 2006 IPCC Tier 1 livestock emissions factors, are too low. This may be due to outdated information used to develop these emissions factors. In this study, we update information for cattle and swine by region, based on reported recent changes in animal body mass, feed quality and quantity, milk productivity, and management of animals and manure. We then use this updated information to calculate new livestock methane emissions factors for enteric fermentation in cattle, and for manure management in cattle and swine. Using the new emissions factors, we estimate global livestock emissions of 119.1 ± 18.2 Tg methane in 2011; this quantity is 11% greater than that obtained using the IPCC 2006 emissions factors, encompassing an 8.4% increase in enteric fermentation methane, a 36.7% increase in manure management methane, and notable variability among regions and sources. For example, revised manure management methane emissions for 2011 in the US increased by 71.8%. For years through 2013, we present (a) annual livestock methane emissions, (b) complete annual livestock carbon budgets, including carbon dioxide emissions, and (c) spatial distributions of livestock methane and other carbon fluxes, downscaled to 0.05 × 0.05 degree resolution. Our revised bottom-up estimates of global livestock methane emissions are comparable to recently reported top-down global estimates for recent years, and account for a significant part of the increase in annual methane emissions since 2007. Our results suggest that livestock methane emissions, while not the dominant overall source of global methane emissions, may be a major contributor to the observed annual emissions increases over the 2000s to 2010s. Differences at regional and local scales may help distinguish livestock methane emissions from those of other sectors in future top-down studies. The revised estimates allow improved reconciliation of top-down and bottom-up estimates of methane emissions, will facilitate the development and evaluation of Earth system models, and provide consistent regional and global Tier 1 estimates for environmental assessments.

An Improved Approach to Estimate Methane Emissions from Coal Mining in China.

PubMed

Zhu, Tao; Bian, Wenjing; Zhang, Shuqing; Di, Pingkuan; Nie, Baisheng

2017-11-07

China, the largest coal producer in the world, is responsible for over 50% of the total global methane (CH 4 ) emissions from coal mining. However, the current emission inventory of CH4 from coal mining has large uncertainties because of the lack of localized emission factors (EFs). In this study, province-level CH4 EFs from coal mining in China were developed based on the data analysis of coal production and corresponding discharged CH4 emissions from 787 coal mines distributed in 25 provinces with different geological and operation conditions. Results show that the spatial distribution of CH 4 EFs is highly variable with values as high as 36 m3/t and as low as 0.74 m3/t. Based on newly developed CH 4 EFs and activity data, an inventory of the province-level CH4 emissions was built for 2005-2010. Results reveal that the total CH 4 emissions in China increased from 11.5 Tg in 2005 to 16.0 Tg in 2010. By constructing a gray forecasting model for CH 4 EFs and a regression model for activity, the province-level CH 4 emissions from coal mining in China are forecasted for the years of 2011-2020. The estimates are compared with other published inventories. Our results have a reasonable agreement with USEPA's inventory and are lower by a factor of 1-2 than those estimated using the IPCC default EFs. This study could help guide CH 4 mitigation policies and practices in China.

Geographic patterns of carbon dioxide emissions from fossil-fuel burning, hydraulic cement production, and gas flaring on a one degree by one degree grid cell basis: 1950 to 1990

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brenkert, A.L.; Andres, R.J.; Marland, G.

1997-03-01

Data sets of one degree latitude by one degree longitude carbon dioxide (CO{sub 2}) emissions in units of thousand metric tons of carbon (C) per year from anthropogenic sources have been produced for 1950, 1960, 1970, 1980 and 1990. Detailed geographic information on CO{sub 2} emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional and national annual estimates for 1950 through 1992 were published previously. Those national, annual CO{sub 2} emission estimates were based on statistics on fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well asmore » energy production, consumption and trade data, using the methods of Marland and Rotty. The national annual estimates were combined with gridded one-degree data on political units and 1984 human populations to create the new gridded CO{sub 2} emission data sets. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mix is uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in emissions over time are apparent for most areas.« less

ESTIMATE OF METHANE EMISSIONS FROM THE U.S. NATURAL GAS INDUSTRY

EPA Science Inventory

Global methane from the fossil fuel industries have been poorly quantified and, in many cases, emissions are not well-known even at the country level. Historically, methane emissions from the U.S. gas industry have been based on sparse data, incorrect assumptions, or both. As a r...

Inverse Estimation of California Methane Emissions and Their Uncertainties using FLEXPART-WRF

NASA Astrophysics Data System (ADS)

Cui, Y.; Brioude, J. F.; Angevine, W. M.; McKeen, S. A.; Peischl, J.; Nowak, J. B.; Henze, D. K.; Bousserez, N.; Fischer, M. L.; Jeong, S.; Liu, Z.; Michelsen, H. A.; Santoni, G.; Daube, B. C.; Kort, E. A.; Frost, G. J.; Ryerson, T. B.; Wofsy, S. C.; Trainer, M.

2015-12-01

Methane (CH4) has a large global warming potential and mediates global tropospheric chemistry. In California, CH4 emissions estimates derived from "top-down" methods based on atmospheric observations have been found to be greater than expected from "bottom-up" population-apportioned national and state inventories. Differences between bottom-up and top-down estimates suggest that the understanding of California's CH4 sources is incomplete, leading to uncertainty in the application of regulations to mitigate regional CH4 emissions. In this study, we use airborne measurements from the California research at the Nexus of Air Quality and Climate Change (CalNex) campaign in 2010 to estimate CH4 emissions in the South Coast Air Basin (SoCAB), which includes California's largest metropolitan area (Los Angeles), and in the Central Valley, California's main agricultural and livestock management area. Measurements from 12 daytime flights, prior information from national and regional official inventories (e.g. US EPA's National Emission Inventory, the California Air Resources Board inventories, the Liu et al. Hybrid Inventory, and the California Greenhouse Gas Emissions Measurement dataset), and the FLEXPART-WRF transport model are used in our mesoscale Bayesian inverse system. We compare our optimized posterior CH4 inventory to the prior bottom-up inventories in terms of total emissions (Mg CH4/hr) and the spatial distribution of the emissions (0.1 degree), and quantify uncertainties in our posterior estimates. Our inversions show that the oil and natural gas industry (extraction, processing and distribution) is the main source accounting for the gap between top-down and bottom-up inventories over the SoCAB, while dairy farms are the largest CH4 source in the Central Valley. CH4 emissions of dairy farms in the San Joaquin Valley and variations of CH4 emissions in the rice-growing regions of Sacramento Valley are quantified and discussed. We also estimate CO and NH3 surface fluxes and use their observed correlation with CH4 mixing ratio to further evaluate our CH4 total emission estimates, and understand the spatial distribution of CH4 emissions.

Estimation of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem in China using real-time remote sensing data

NASA Astrophysics Data System (ADS)

Li, M.; Huang, X.; Li, J.; Song, Y.

2012-04-01

Because of the high emission intensity and reactivity, biogenic volatile organic compounds (BVOCs) play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and limited meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in atmospheric chemical processes, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature) with MM5 (the Fifth-Generation Mesoscale Model) providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8) and seven monoterpene species (C10H16) in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer) data were introduced to update the land surface parameters and improve the simulation performance of MM5, and to modify the influence of leaf area index (LAI) and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value much lower than that given in global estimations but higher than the past estimations in China. Therein, the most important individual contributor was isoprene (9.36 Tg C), followed by α-pinene (1.24 Tg C yr-1) and β-pinene (0.84 Tg C yr-1). Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial-temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. On the other hand, Southeast China was the top-ranking contributor of monoterpenes, in which the dominant vegetation genera consist of evergreen coniferous forests (mainly Pinus massoniana). Temporally, BVOC emissions primarily occurred in July and August during periods of high temperatures, high solar radiation and dense plant cover, with daily emissions peaking at about 13:00~14:00 hours (Beijing Time, BJT) and reaching their lowest values at night. Additionally, emissions of volatile organic compounds (VOCs) of biogenic origin (14.7 Tg yr-1) were approximately one-third less than anthropogenic emissions (23.2 Tg yr-1) and showed distinct spatial distributions. We present a reasonable estimation of BVOC emissions, which provides important information for further exploration of the role of BVOCs in atmospheric processes.

Improved MEGAN predictions of biogenic isoprene in the contiguous United States

NASA Astrophysics Data System (ADS)

Wang, Peng; Schade, Gunnar; Estes, Mark; Ying, Qi

2017-01-01

Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions.

Modeling nitrous oxide emission from rivers: a global assessment.

PubMed

Hu, Minpeng; Chen, Dingjiang; Dahlgren, Randy A

2016-11-01

Estimates of global riverine nitrous oxide (N 2 O) emissions contain great uncertainty. We conducted a meta-analysis incorporating 169 observations from published literature to estimate global riverine N 2 O emission rates and emission factors. Riverine N 2 O flux was significantly correlated with NH 4 , NO 3 and DIN (NH 4  + NO 3 ) concentrations, loads and yields. The emission factors EF(a) (i.e., the ratio of N 2 O emission rate and DIN load) and EF(b) (i.e., the ratio of N 2 O and DIN concentrations) values were comparable and showed negative correlations with nitrogen concentration, load and yield and water discharge, but positive correlations with the dissolved organic carbon : DIN ratio. After individually evaluating 82 potential regression models based on EF(a) or EF(b) for global, temperate zone and subtropical zone datasets, a power function of DIN yield multiplied by watershed area was determined to provide the best fit between modeled and observed riverine N 2 O emission rates (EF(a): R 2  = 0.92 for both global and climatic zone models, n = 70; EF(b): R 2  = 0.91 for global model and R 2  = 0.90 for climatic zone models, n = 70). Using recent estimates of DIN loads for 6400 rivers, models estimated global riverine N 2 O emission rates of 29.6-35.3 (mean = 32.2) Gg N 2 O-N yr -1 and emission factors of 0.16-0.19% (mean = 0.17%). Global riverine N 2 O emission rates are forecasted to increase by 35%, 25%, 18% and 3% in 2050 compared to the 2000s under the Millennium Ecosystem Assessment's Global Orchestration, Order from Strength, Technogarden, and Adapting Mosaic scenarios, respectively. Previous studies may overestimate global riverine N 2 O emission rates (300-2100 Gg N 2 O-N yr -1 ) because they ignore declining emission factor values with increasing nitrogen levels and channel size, as well as neglect differences in emission factors corresponding to different nitrogen forms. Riverine N 2 O emission estimates will be further enhanced through refining emission factor estimates, extending measurements longitudinally along entire river networks and improving estimates of global riverine nitrogen loads. © 2016 John Wiley & Sons Ltd.

Regional landfills methane emission inventory in Malaysia.

PubMed

Abushammala, Mohammed F M; Noor Ezlin Ahmad Basri; Basri, Hassan; Ahmed Hussein El-Shafie; Kadhum, Abdul Amir H

2011-08-01

The decomposition of municipal solid waste (MSW) in landfills under anaerobic conditions produces landfill gas (LFG) containing approximately 50-60% methane (CH(4)) and 30-40% carbon dioxide (CO(2)) by volume. CH(4) has a global warming potential 21 times greater than CO(2); thus, it poses a serious environmental problem. As landfills are the main method for waste disposal in Malaysia, the major aim of this study was to estimate the total CH(4) emissions from landfills in all Malaysian regions and states for the year 2009 using the IPCC, 1996 first-order decay (FOD) model focusing on clean development mechanism (CDM) project applications to initiate emission reductions. Furthermore, the authors attempted to assess, in quantitative terms, the amount of CH(4) that would be emitted from landfills in the period from 1981-2024 using the IPCC 2006 FOD model. The total CH(4) emission using the IPCC 1996 model was estimated to be 318.8 Gg in 2009. The Northern region had the highest CH(4) emission inventory, with 128.8 Gg, whereas the Borneo region had the lowest, with 24.2 Gg. It was estimated that Pulau Penang state produced the highest CH(4) emission, 77.6 Gg, followed by the remaining states with emission values ranging from 38.5 to 1.5 Gg. Based on the IPCC 1996 FOD model, the total Malaysian CH( 4) emission was forecast to be 397.7 Gg by 2020. The IPCC 2006 FOD model estimated a 201 Gg CH(4) emission in 2009, and estimates ranged from 98 Gg in 1981 to 263 Gg in 2024.

Quantifying alkane emissions in the Eagle Ford Shale using boundary layer enhancement

NASA Astrophysics Data System (ADS)

Roest, Geoffrey; Schade, Gunnar

2017-09-01

The Eagle Ford Shale in southern Texas is home to a booming unconventional oil and gas industry, the climate and air quality impacts of which remain poorly quantified due to uncertain emission estimates. We used the atmospheric enhancement of alkanes from Texas Commission on Environmental Quality volatile organic compound monitors across the shale, in combination with back trajectory and dispersion modeling, to quantify C2-C4 alkane emissions for a region in southern Texas, including the core of the Eagle Ford, for a set of 68 days from July 2013 to December 2015. Emissions were partitioned into raw natural gas and liquid storage tank sources using gas and headspace composition data, respectively, and observed enhancement ratios. We also estimate methane emissions based on typical ethane-to-methane ratios in gaseous emissions. The median emission rate from raw natural gas sources in the shale, calculated as a percentage of the total produced natural gas in the upwind region, was 0.7 % with an interquartile range (IQR) of 0.5-1.3 %, below the US Environmental Protection Agency's (EPA) current estimates. However, storage tanks contributed 17 % of methane emissions, 55 % of ethane, 82 % percent of propane, 90 % of n-butane, and 83 % of isobutane emissions. The inclusion of liquid storage tank emissions results in a median emission rate of 1.0 % (IQR of 0.7-1.6 %) relative to produced natural gas, overlapping the current EPA estimate of roughly 1.6 %. We conclude that emissions from liquid storage tanks are likely a major source for the observed non-methane hydrocarbon enhancements in the Northern Hemisphere.

On the relationship between land surface infrared emissivity and soil moisture

NASA Astrophysics Data System (ADS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

2018-01-01

The relationship between surface infrared (IR) emissivity and soil moisture content has been investigated based on satellite measurements. Surface soil moisture content can be estimated by IR remote sensing, namely using the surface parameters of IR emissivity, temperature, vegetation coverage, and soil texture. It is possible to separate IR emissivity from other parameters affecting surface soil moisture estimation. The main objective of this paper is to examine the correlation between land surface IR emissivity and soil moisture. To this end, we have developed a simple yet effective scheme to estimate volumetric soil moisture (VSM) using IR land surface emissivity retrieved from satellite IR spectral radiance measurements, assuming those other parameters impacting the radiative transfer (e.g., temperature, vegetation coverage, and surface roughness) are known for an acceptable time and space reference location. This scheme is applied to a decade of global IR emissivity data retrieved from MetOp-A infrared atmospheric sounding interferometer measurements. The VSM estimated from these IR emissivity data (denoted as IR-VSM) is used to demonstrate its measurement-to-measurement variations. Representative 0.25-deg spatially-gridded monthly-mean IR-VSM global datasets are then assembled to compare with those routinely provided from satellite microwave (MW) multisensor measurements (denoted as MW-VSM), demonstrating VSM spatial variations as well as seasonal-cycles and interannual variability. Initial positive agreement is shown to exist between IR- and MW-VSM (i.e., R2 = 0.85). IR land surface emissivity contains surface water content information. So, when IR measurements are used to estimate soil moisture, this correlation produces results that correspond with those customarily achievable from MW measurements. A decade-long monthly-gridded emissivity atlas is used to estimate IR-VSM, to demonstrate its seasonal-cycle and interannual variation, which is spatially coherent and consistent with that from MW measurements, and, moreover, to achieve our objective of investigating the relationship between land surface IR emissivity and soil moisture.

An inverse method to estimate emission rates based on nonlinear least-squares-based ensemble four-dimensional variational data assimilation with local air concentration measurements.

PubMed

Geng, Xiaobing; Xie, Zhenghui; Zhang, Lijun; Xu, Mei; Jia, Binghao

2018-03-01

An inverse source estimation method is proposed to reconstruct emission rates using local air concentration sampling data. It involves the nonlinear least squares-based ensemble four-dimensional variational data assimilation (NLS-4DVar) algorithm and a transfer coefficient matrix (TCM) created using FLEXPART, a Lagrangian atmospheric dispersion model. The method was tested by twin experiments and experiments with actual Cs-137 concentrations measured around the Fukushima Daiichi Nuclear Power Plant (FDNPP). Emission rates can be reconstructed sequentially with the progression of a nuclear accident, which is important in the response to a nuclear emergency. With pseudo observations generated continuously, most of the emission rates were estimated accurately, except under conditions when the wind blew off land toward the sea and at extremely slow wind speeds near the FDNPP. Because of the long duration of accidents and variability in meteorological fields, monitoring networks composed of land stations only in a local area are unable to provide enough information to support an emergency response. The errors in the estimation compared to the real observations from the FDNPP nuclear accident stemmed from a shortage of observations, lack of data control, and an inadequate atmospheric dispersion model without improvement and appropriate meteorological data. The proposed method should be developed further to meet the requirements of a nuclear emergency response. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-resolution ammonia emissions inventories in Fujian, China, 2009-2015

NASA Astrophysics Data System (ADS)

Wu, Shui-Ping; Zhang, Yin-Ju; Schwab, James J.; Li, Yang-Fan; Liu, Yuan-Long; Yuan, Chung-Shin

2017-08-01

A high-resolution NH3 emission inventory was developed based on the corrected emission factors and county-level activity data. To provide model-ready emission input, the NH3 emission inventory was gridded for the modeling domain at 1 × 1 km resolution using source-based spatial surrogates and a GIS system. The best estimate of total NH3 emission for the province was 228.02 kt in 2015 with a percentage uncertainty of ±16.3%. Four major contributors were farmland ecosystem, livestock wastes, humans and waste treatment, which contributed 39.4%, 43.1%, 4.9%, and 4.2% of the total emissions, respectively. The averaged NH3 emission density for the whole region was 1.88 t km-2 yr-1 and the higher values were found in coastal areas with higher dense populations. The seasonal patterns, with higher emissions in summer, were consistent with the patterns of temperature and planting practices. From 2009 to 2015, annual NH3 emissions increased from 218.49 kt to 228.02 kt. All of these changes are insignificant compared to the estimated overall uncertainties in the analysis, but indicative of changes in the source categories over this period. Between 2009 and 2015, the largest changes occurred in human emissions and waste treatment plants, which were consistent with the process of rapid urbanization. Meanwhile, the decrease of emissions from pigs was slightly higher than the increased emissions from broilers and the increased emissions from meat goats and beef cattle due to the combine effects of increasingly stringent environmental requirements for pig farms and shift away from pork consumption to beef, chicken and mutton. The validity of the estimates was further evaluated using uncertainty analysis, comparison with previous studies, and correlation analysis between emission density and observed ground ammonia. The inventories reflect the changes in economic progress and environmental protection and can provide scientific basis for the establishment of effective PM2.5 control strategies.

Assessing the Gap Between Top-down and Bottom-up Measured Methane Emissions in Indianapolis, IN.

NASA Astrophysics Data System (ADS)

Prasad, K.; Lamb, B. K.; Cambaliza, M. O. L.; Shepson, P. B.; Stirm, B. H.; Salmon, O. E.; Lavoie, T. N.; Lauvaux, T.; Ferrara, T.; Howard, T.; Edburg, S. L.; Whetstone, J. R.

2014-12-01

Releases of methane (CH4) from the natural gas supply chain in the United States account for approximately 30% of the total US CH4 emissions. However, there continues to be large questions regarding the accuracy of current emission inventories for methane emissions from natural gas usage. In this paper, we describe results from top-down and bottom-up measurements of methane emissions from the large isolated city of Indianapolis. The top-down results are based on aircraft mass balance and tower based inverse modeling methods, while the bottom-up results are based on direct component sampling at metering and regulating stations, surface enclosure measurements of surveyed pipeline leaks, and tracer/modeling methods for other urban sources. Mobile mapping of methane urban concentrations was also used to identify significant sources and to show an urban-wide low level enhancement of methane levels. The residual difference between top-down and bottom-up measured emissions is large and cannot be fully explained in terms of the uncertainties in top-down and bottom-up emission measurements and estimates. Thus, the residual appears to be, at least partly, attributed to a significant wide-spread diffusive source. Analyses are included to estimate the size and nature of this diffusive source.

Particulate emissions calculations from fall tillage operations using point and remote sensors.

PubMed

Moore, Kori D; Wojcik, Michael D; Martin, Randal S; Marchant, Christian C; Bingham, Gail E; Pfeiffer, Richard L; Prueger, John H; Hatfield, Jerry L

2013-07-01

Soil preparation for agricultural crops produces aerosols that may significantly contribute to seasonal atmospheric particulate matter (PM). Efforts to reduce PM emissions from tillage through a variety of conservation management practices (CMPs) have been made, but the reductions from many of these practices have not been measured in the field. A study was conducted in California's San Joaquin Valley to quantify emissions reductions from fall tillage CMP. Emissions were measured from conventional tillage methods and from a "combined operations" CMP, which combines several implements to reduce tractor passes. Measurements were made of soil moisture, bulk density, meteorological profiles, filter-based total suspended PM (TSP), concentrations of PM with an equivalent aerodynamic diameter ≤10 μm (PM) and PM with an equivalent aerodynamic diameter ≤2.5 μm (PM), and aerosol size distribution. A mass-calibrated, scanning, three-wavelength light detection and ranging (LIDAR) procedure estimated PM through a series of algorithms. Emissions were calculated via inverse modeling with mass concentration measurements and applying a mass balance to LIDAR data. Inverse modeling emission estimates were higher, often with statistically significant differences. Derived PM emissions for conventional operations generally agree with literature values. Sampling irregularities with a few filter-based samples prevented calculation of a complete set of emissions through inverse modeling; however, the LIDAR-based emissions dataset was complete. The CMP control effectiveness was calculated based on LIDAR-derived emissions to be 29 ± 2%, 60 ± 1%, and 25 ± 1% for PM, PM, and TSP size fractions, respectively. Implementation of this CMP provides an effective method for the reduction of PM emissions. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Road traffic emission factors for heavy metals

NASA Astrophysics Data System (ADS)

Johansson, Christer; Norman, Michael; Burman, Lars

Quantifying the emissions and concentrations of heavy metals in urban air is a prerequisite for assessing their health effects. In this paper a combination of measurements and modelling is used to assess the contribution from road traffic emissions. Concentrations of particulate heavy metals in air were measured simultaneously during 1 year at a densely trafficked street and at an urban background site in Stockholm, Sweden. Annual mean concentrations of cadmium were 50 times lower than the EU directive and for nickel and arsenic concentrations were 10 and six times lower, respectively. More than a factor of two higher concentrations was in general observed at the street in comparison to roof levels indicating the strong influence from local road traffic emissions. The only compound with a significantly decreasing trend in the urban background was Pb with 9.1 ng m -3 in 1995/96 compared to 3.4 ng m -3 2003/04. This is likely due to decreased emissions from wear of brake linings and reduced emissions due to oil and coal combustion in central Europe. Total road traffic emission factors for heavy metals were estimated using parallel measurements of NOx concentrations and knowledge of NOx emission factors. In general, the emission factors for the street were higher than reported in road tunnel measurements. This could partly be due to different driving conditions, since especially for metals which are mainly emitted from brake wear, more stop and go driving in the street compared to in road tunnels is likely to increase emissions. Total emissions were compared with exhaust emissions, obtained from the COPERT model and brake wear emissions based on an earlier study in Stockholm. For Cu, Ni and Zn the sum of brake wear and exhaust emissions agreed very well with estimated total emission factors in this study. More than 90% of the road traffic emissions of Cu were due to brake wear. For Ni more than 80% is estimated to be due to exhaust emissions and for Zn around 40% of road traffic emissions are estimated to be due to exhaust emissions. Pb is also mainly due to exhaust emissions (90%); a fuel Pb content of only 0.5 mg L -1 would give similar emission factor as that based on the concentration increment at the street. This is the first study using simultaneous measurements of heavy metals at street and roof enabling calculations of emission factors using a tracer technique.

Sparse estimation of model-based diffuse thermal dust emission

NASA Astrophysics Data System (ADS)

Irfan, Melis O.; Bobin, Jérôme

2018-03-01

Component separation for the Planck High Frequency Instrument (HFI) data is primarily concerned with the estimation of thermal dust emission, which requires the separation of thermal dust from the cosmic infrared background (CIB). For that purpose, current estimation methods rely on filtering techniques to decouple thermal dust emission from CIB anisotropies, which tend to yield a smooth, low-resolution, estimation of the dust emission. In this paper, we present a new parameter estimation method, premise: Parameter Recovery Exploiting Model Informed Sparse Estimates. This method exploits the sparse nature of thermal dust emission to calculate all-sky maps of thermal dust temperature, spectral index, and optical depth at 353 GHz. premise is evaluated and validated on full-sky simulated data. We find the percentage difference between the premise results and the true values to be 2.8, 5.7, and 7.2 per cent at the 1σ level across the full sky for thermal dust temperature, spectral index, and optical depth at 353 GHz, respectively. A comparison between premise and a GNILC-like method over selected regions of our sky simulation reveals that both methods perform comparably within high signal-to-noise regions. However, outside of the Galactic plane, premise is seen to outperform the GNILC-like method with increasing success as the signal-to-noise ratio worsens.

Characterization of road freight transportation and its impact on the national emission inventory in China

NASA Astrophysics Data System (ADS)

Yang, X. F.; Liu, H.; Man, H. Y.; He, K. B.

2014-06-01

Mobile source emission inventories serve as critical input for atmospheric chemical transport models, which are used to simulate air quality and understand the role of mobile source emissions. The significance of mobile sources is even more important in China because the country has the largest vehicle population in the world, and that population continues to grow rapidly. Estimating emissions from diesel trucks is a critical work in mobile source emission inventories due to the importance and difficulties associated with estimating emissions from diesel trucks. Although diesel trucks are major contributors of nitrogen oxide (NOx) and primary particulate matter smaller than 2.5 μm (PM2.5), there are still more obstacles on the existing estimation of diesel truck emissions compared with that of cars; long-range freight transportation activities are complicated, and much of the basic data remain unclear. Most of existing inventories were based on local registration number. However, according to our research, a large number of trucks are conducting long-distance inter-city or inter province transportation. Instead of the local registration number based approach, a road emission intensity-based (REIB) approach is introduced in this research. To provide efficient data for the REIB approach, 1060 questionnaire responses and approximately 1.7 million valid seconds of onboard GPS monitoring data were collected. Both the questionnaire answers and GPS monitoring results indicated that the driving conditions on different types of road have significant impacts on the emission levels of freight trucks. We present estimated emissions of NOx and primary PM2.5 from diesel freight trucks for China in 2011. Using the REIB approach, the activity level and distribution data are obtained from the questionnaire answers. Emission factors are calculated with the International Vehicle Emission (IVE) model that interpolated local on-board measurement results in China according to the GPS monitoring data on different roads. Depending on the results in this research, the largest differences among the emission factors (in g km-1) on different roads exceed 70 and 50% for NOx and PM2.5, respectively. The differences were caused by different driving conditions that we monitored via GPS. The estimated NOx and PM2.5 emissions from diesel freight trucks in China were 5.0 (4.8-7.2) million t and 0.20 (0.17-0.22) million t, respectively, via the REIB approach in 2011. Another implication of this research is that different road infrastructure would have different impacts for NOx and PM2.5 emissions. A region with more inter-city freeways or national roads tends to have more NOx emissions, while urban streets play a more important role in primary PM2.5 emissions from freight trucks. Compared with former studies, which allocate emissions according to local truck registration number and neglect inter-region long distance transport trips, the REIB approach has advantages regarding the allocation of diesel truck emissions into the provinces. Furthermore, the different driving conditions on the different roads types are no longer overlooked with this approach.

Analysis of the vehicle fleet in the Kathmandu Valley for estimation of environment and climate co-benefits of technology intrusions

NASA Astrophysics Data System (ADS)

Shrestha, Shreejan Ram; Kim Oanh, Nguyen Thi; Xu, Quishi; Rupakheti, Maheswar; Lawrence, Mark G.

2013-12-01

Technologies and activities of the on-road traffic fleets, including bus, van, 3-wheeler, taxi and motorcycle (MC) in the Kathmandu Valley, Nepal, during 2010, were investigated with the aim to produce emission estimates, using the International Vehicle Emission (IVE) model, for the base year and for an optimistic technology scenario. The parking lot survey, GPS monitoring and video camera monitoring were conducted over four typical road types (arterial, highway, residential and outskirt roads). The average age of vehicles in the bus, van, 3-wheeler, taxi and MC fleet was 9, 8.7, 11, 9.5 and 4 years, respectively. There were some extremely old buses (over 40 years old) which had extremely high emission factors. Except for MCs that had a large share of Euro III technology (75%), other types of surveyed vehicles were at most Euro II or lower. The average vehicle kilometers traveled (VKT) for each vehicle type was estimated based on odometer readings which showed comparable results with the GPS survey. The emission factors (EFs) produced by the IVE model for the driving and meteorological conditions in Kathmandu were used to estimate emissions for the base case of 2010. EFs in Kathmandu were higher than other developing cities, especially for PM and NOx from the bus fleet. Diurnal variations of the emissions were consistent with the diurnal vehicle density. From the fleet in 2010, total emissions of the major pollutants, i.e., CO, VOC, NOx, PM, BC, and CO2, were 31, 7.7, 16, 4.7, 2.1, and 1554 Gg, respectively. If the entire fleet in the Kathmandu Valley would comply with Euro III then the emission would decrease, as compared to the base case, by 44% for toxic air pollutants (excluding CO2) and 31% for climate-forcers in terms of the 20-year horizon CO2-equivalent. Future surveys should include other vehicle types such as trucks, personal cars, and non-road vehicles. The EFs obtained for the Euro III scenario in Kathmandu were well above those in other parts of the World, hence strongly suggesting influences of the driving conditions, especially the low vehicle speeds, on the vehicle emission in the valley.

Global Top-Down Smoke-Aerosol Emissions Estimation Using Satellite Fire Radiative Power Measurements

NASA Technical Reports Server (NTRS)

Ichoku, C.; Ellison, L.

2014-01-01

Fire emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. We present the development of a global gridded (1 deg ×1 deg) emission coefficients (Ce) product for smoke total particulate matter (TPM) based on a top-down approach using coincident measurements of fire radiative power (FRP) and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from http://feer.gsfc. nasa.gov/, along with the corresponding 1-to-1 mapping of their quality assurance (QA) flags that will enable the Ce values to be filtered by quality for use in various applications. The regional averages of Ce values for different ecosystem types were found to be in the ranges of 16-21/gMJ-1 for savanna and grasslands, 15-32/gMJ-1 for tropical forest, 9-12/gMJ-1 for North American boreal forest, and 18- 26/MJ-1 for Russian boreal forest, croplands and natural vegetation. The FEER.v1 Ce product was multiplied by time-integrated FRP data to calculate regional smoke TPM emissions, which were compared with equivalent emissions products from three existing inventories. FEER.v1 showed higher and more reasonable smoke TPM estimates than two other emissions inventories that are based on bottom-up approaches and already reported in the literature to be too low, but portrayed an overall reasonable agreement with another top-down approach. This suggests that top-down approaches may hold better promise and need to be further developed to accelerate the reduction of uncertainty associated with fire emissions estimation in air-quality and climate research and applications. Results of the analysis of FEER.v1 data for 2004-2011 show that 65-85 Tg yr-1 of TPM is emitted globally from open biomass burning, with a generally decreasing trend over this short time period. The FEER.v1 Ce product is the first global gridded product in the family of "emission factors", that is based essentially on satellite measurements, and requires only direct satellite FRP measurements of an actively burning fire anywhere to evaluate its emission rate in near-real time, which is essential for operational activities, such as the monitoring and forecasting of smoke emission impacts on air quality.

Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts

NASA Astrophysics Data System (ADS)

Brioude, Jerome; Angevine, Wayne; Ahmadov, Ravan; Kim, Si Wan; Evan, Stephanie; McKeen, Stuart; Hsie, Eirh Yu; Frost, Greg; Neuman, Andy; Pollack, Ilana; Peischl, Jeff; Ryerson, Tom; Holloway, John; Brown, Steeve; Nowak, John; Roberts, Jim; Wofsy, Steeve; Santoni, Greg; Trainer, Michael

2013-04-01

We present top-down estimates of anthropogenic CO, NOx and CO2 surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May-June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NOx inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO2 inventory without prior knowledge of CO2 surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NOx fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% ± 6% in LA County and by 37% ± 10% in the South Coast Air Basin (SoCAB). NOx posterior emissions were lower by 32% ± 10% in LA County and by 27% ± 15% in the SoCAB. NOx posterior emissions were 40% lower on weekends relative to weekdays. The CO2 posterior estimates were 183 ± 18 Tg yr-1 in SoCAB. A flight during ITCT in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NOx posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO2 emissions increased by 10% ± 14% in LA County but decreased by 4% ± 10% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NOx emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, CARB 2010 and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, showing that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry forecasts.

Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts

NASA Astrophysics Data System (ADS)

Brioude, J.; Angevine, W. M.; Ahmadov, R.; Kim, S.-W.; Evan, S.; McKeen, S. A.; Hsie, E.-Y.; Frost, G. J.; Neuman, J. A.; Pollack, I. B.; Peischl, J.; Ryerson, T. B.; Holloway, J.; Brown, S. S.; Nowak, J. B.; Roberts, J. M.; Wofsy, S. C.; Santoni, G. W.; Trainer, M.

2012-12-01

We present top-down estimates of anthropogenic CO, NOx and CO2 surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May-June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NOx inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO2 inventory without prior knowledge of CO2 surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NOx fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% ± 6% in LA County and by 37% ± 10% in the South Coast Air Basin (SoCAB). NOx posterior emissions were lower by 32% ± 10% in LA County and by 27% ± 15% in the SoCAB. NOx posterior emissions were 40% lower on weekends relative to weekdays. The CO2 posterior estimates were 183 ± 18 Tg yr-1 in SoCAB. A flight during ITCT in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NOx posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO2 emissions increased by 10% ± 14% in LA County but decreased by 4% ± 10% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NOx emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, CARB 2010 and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, showing that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry forecasts.

Geographic Patterns of Carbon Dioxide Emissions from Fossil-Fuel Burning\\, Hydraulic Cement Production\\, and Gas Flaring on a One Degree by One Degree Grid Cell Basis: 1950 to 1990 (NDP:058) (Issued March, 1997)

DOE Data Explorer

Andres, R.J. [University of Alaska, Fairbanks, AK (United States); Marland, G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fung, I. [NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Matthews, E. [NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Brenkert, Antoinette L. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN

1997-01-01

This data package presents data sets recording 1° latitude by 1° longitude CO2 emissions in units of thousand metric tons of carbon per year from anthropogenic sources for 1950, 1960, 1970, 1980, and 1990. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1950 through 1992 were published previously. Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission data sets. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in emissions over time are apparent for most areas; for example, from 1980 and 1990, a 63% increase in CO2 emissions (based on 1980 emissions) occurred in mainland China and a 95% increase in India. However, actual decreases from 1980 to 1990 occurred in Western Europe: 30% in Sweden, 27% in France, and 23% in Belgium. Latitudinal summations of emissions show a slow southerly shift (in the Northern Hemisphere) in the bulk of emissions over time. The large increases, from 1950 to 1990, in China's and India's contributions to anthropogenic CO2 emissions compared to those by the United States are, for example, very apparent at the latitudinal band around 25.5° North.

[Estimation of VOC emission from forests in China based on the volume of tree species].

PubMed

Zhang, Gang-feng; Xie, Shao-dong

2009-10-15

Applying the volume data of dominant trees from statistics on the national forest resources, volatile organic compounds (VOC) emissions of each main tree species in China were estimated based on the light-temperature model put forward by Guenther. China's VOC emission inventory for forest was established, and the space-time and age-class distributions of VOC emission were analyzed. The results show that the total VOC emissions from forests in China are 8565.76 Gg, of which isoprene is 5689.38 Gg (66.42%), monoterpenes is 1343.95 Gg (15.69%), and other VOC is 1532.43 Gg (17.89%). VOC emissions have significant species variation. Quercus is the main species responsible for emission, contributing 45.22% of the total, followed by Picea and Pinus massoniana with 6.34% and 5.22%, respectively. Southwest and Northeast China are the major emission regions. In specific, Yunnan, Sichuan, Heilongjiang, Jilin and Shaanxi are the top five provinces producing the most VOC emissions from forests, and their contributions to the total are 15.09%, 12.58%, 10.35%, 7.49% and 7.37%, respectively. Emissions from these five provinces occupy more than half (52.88%) of the national emissions. Besides, VOC emissions show remarkable seasonal variation. Emissions in summer are the largest, accounting for 56.66% of the annual. Forests of different ages have different emission contribution. Half-mature forests play a key role and contribute 38.84% of the total emission from forests.

Emission factor of ammonia (NH3) from on-road vehicles in China: tunnel tests in urban Guangzhou

NASA Astrophysics Data System (ADS)

Liu, Tengyu; Wang, Xinming; Wang, Boguang; Ding, Xiang; Deng, Wei; Lü, Sujun; Zhang, Yanli

2014-05-01

Ammonia (NH3) is the primary alkaline gas in the atmosphere that contributes to formation of secondary particles. Emission of NH3 from vehicles, particularly gasoline powered light duty vehicles equipped with three-way catalysts, is regarded as an important source apart from emissions from animal wastes and soils, yet measured emission factors for motor vehicles are still not available in China, where traffic-related emission has become an increasingly important source of air pollutants in urban areas. Here we present our tunnel tests for NH3 from motor vehicles under ‘real world conditions’ in an urban roadway tunnel in Guangzhou, a central city in the Pearl River Delta (PRD) region in south China. By attributing all NH3 emissions in the tunnel to light-duty gasoline vehicles, we obtained a fuel-based emission rate of 2.92 ± 0.18 g L-1 and a mileage-based emission factor of 229.5 ± 14.1 mg km-1. These emission factors were much higher than those measured in the United States while measured NO x emission factors (7.17 ± 0.60 g L-1 or 0.56 ± 0.05 g km-1) were contrastingly near or lower than those previously estimated by MOBILE/PART5 or COPERT IV models. Based on the NH3 emission factors from this study, on-road vehicles accounted for 8.1% of NH3 emissions in the PRD region in 2006 instead of 2.5% as estimated in a previous study using emission factors taken from the Emission Inventory Improvement Program (EIIP) in the United States.

Emission measures derived from far ultraviolet spectra of T Tauri stars

NASA Astrophysics Data System (ADS)

Cram, L. E.; Giampapa, M. S.; Imhoff, C. L.

1980-06-01

Spectroscopic diagnostics based on UV emission line observations have been developed to study the solar chromosphere, transition region, and corona. The atmospheric properties that can be inferred from observations of total line intensities include the temperature, by identifying the ionic species present; the temperature distribution of the emission measure, from the absolute intensities; and the electron density of the source, from line intensity ratios sensitive to the electron density. In the present paper, the temperature distribution of the emission measure is estimated from observations of far UV emission line fluxes of the T Tauri stars, RW Aurigae and RU Lupi, made on the IUE. A crude estimate of the electron density of one star is obtained, using density-sensitive line ratios.

Health risk assessment of air emissions from a municipal solid waste incineration plant--a case study.

PubMed

Cangialosi, Federico; Intini, Gianluca; Liberti, Lorenzo; Notarnicola, Michele; Stellacci, Paolo

2008-01-01

A health risk assessment of long-term emissions of carcinogenic and non-carcinogenic air pollutants has been carried out for the municipal solid waste incinerator (MSWI) of the city of Taranto, Italy. Ground level air concentrations and soil deposition of carcinogenic (Polychlorinated Dibenzo-p-Dioxins/Furans and Cd) and non-carcinogenic (Pb and Hg) pollutants have been estimated using a well documented atmospheric dispersion model. Health risk values for air inhalation, dermal contact, soil and food ingestion have been calculated based on a combination of these concentrations and a matrix of environmental exposure factors. Exposure of the surrounding population has been addressed for different release scenarios based on four pollutants, four exposure pathways and two receptor groups (children and adults). Spatial risk distribution and cancer excess cases projected from plant emissions have been compared with background mortality records. Estimated results based on the MSWI emissions show: (1) individual risks well below maximum acceptable levels, (2) very small incremental cancer risk compared with background level.

Model simulations of cooking organic aerosol (COA) over the UK using estimates of emissions based on measurements at two sites in London

NASA Astrophysics Data System (ADS)

Ots, Riinu; Vieno, Massimo; Allan, James D.; Reis, Stefan; Nemitz, Eiko; Young, Dominique E.; Coe, Hugh; Di Marco, Chiara; Detournay, Anais; Mackenzie, Ian A.; Green, David C.; Heal, Mathew R.

2016-11-01

Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km × 5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person-1 day-1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January-February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (˜ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m-3 (˜ 20 % of total measured OA1) and between 0.5 and 0.7 µg m-3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m-3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.

Highlighting Uncertainty and Recommendations for Improvement of Black Carbon Biomass Fuel-Based Emission Inventories in the Indo-Gangetic Plain Region.

PubMed

Soneja, Sutyajeet I; Tielsch, James M; Khatry, Subarna K; Curriero, Frank C; Breysse, Patrick N

2016-03-01

Black carbon (BC) is a major contributor to hydrological cycle change and glacial retreat within the Indo-Gangetic Plain (IGP) and surrounding region. However, significant variability exists for estimates of BC regional concentration. Existing inventories within the IGP suffer from limited representation of rural sources, reliance on idealized point source estimates (e.g., utilization of emission factors or fuel-use estimates for cooking along with demographic information), and difficulty in distinguishing sources. Inventory development utilizes two approaches, termed top down and bottom up, which rely on various sources including transport models, emission factors, and remote sensing applications. Large discrepancies exist for BC source attribution throughout the IGP depending on the approach utilized. Cooking with biomass fuels, a major contributor to BC production has great source apportionment variability. Areas requiring attention tied to research of cookstove and biomass fuel use that have been recognized to improve emission inventory estimates include emission factors, particulate matter speciation, and better quantification of regional/economic sectors. However, limited attention has been given towards understanding ambient small-scale spatial variation of BC between cooking and non-cooking periods in low-resource environments. Understanding the indoor to outdoor relationship of BC emissions due to cooking at a local level is a top priority to improve emission inventories as many health and climate applications rely upon utilization of accurate emission inventories.

The 2014 National Emission Inventory for Rangeland Fires ...

EPA Pesticide Factsheets

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. One component of the biomass burning inventory, crop residue burning, has been poorly characterized in the National Emissions Inventory. In the 2011 NEI, Wildland fires, prescribed fires, and crop residue burning collectively were the largest source of PM2.5 This paper summarizes our 2014 NEI method to estimate crop residue burning emissions and grass/pasture burning emissions using remote sensing data and field information and literature-based, crop-specific emission factors. We will focus on both the post-harvest and pre-harvest burning that takes place with bluegrass, corn, cotton, rice, soybeans, sugarcane and wheat. Estimates for 2014 indicate that over the continental United States (CONUS), crop residue burning including all areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay produced 64,994 short tons of PM2.5. This estimate compares with the 2011 NEI and 2008 NEI as follows: 2008: 49,653 short tons and 2011: 141,184 short tons. Note that in the previous two NEI’s rangeland burning was not well-defined and so the comparison is not exact. In addition, the entire database used to estimate this sector of emissions is available on EPA’s Clearinghouse for Inventories and Emission Factors (CHIEF http://www3.epa.gov/ttn/chief/index.html The National Emissions Inventory is developed on

[Temporal and spatial distribution of anthropogenic ammonia emissions in China: 1994-2006].

PubMed

Dong, Wen-xuan; Xing, Jia; Wang, Shu-xiao

2010-07-01

Ammonia has both direct and indirect impacts on important environmental issues including acid deposition, regional fine particles and eutrophication. Estimation of anthropogenic ammonia emissions will provide valuable information for the pollution control of acid deposition and regional fine particle. Based on the provincial activity data on N-fertilizer application, livestock farming, N-fertilizer production and populations, this paper uses emission factor method to estimate China's atmospheric ammonia emissions, analyzes its historical trends and presents its geographical distributions from year 1994 to 2006. The national total atmospheric ammonia emissions are estimated to be 11.06 million tons (Mt) in 1994, which increase quickly to 16.07 Mt in 2006. Emissions from livestock farming, N-fertilizer application, N-fertilizer production and human excreta have increased from 4.47 Mt, 5.94 Mt, 0.09 Mt, and 0.59 Mt in 1994 to 6.61 Mt, 8.68 Mt, 0.14 Mt, 0.65 Mt respectively in 2006. Livestock farming and N-fertilizer application are the most important ammonia emission sources, which contributed 40.79 and 55.53 percent of total emissions respectively in 2006. In 2006, the average ammonia emission intensity is 1.67 t x km(-2) but there are large variations among atmospheric ammonia emissions from each province. Emissions from provinces including Henan, Shandong, Hebei, Sichuan and Jiangsu accounted for 40.82 percent of national emissions.

Final report for SERDP project RC-1648: new tools for estimating and managing local/regional air quality impacts of prescribed burns. University of California - Riverside

Treesearch

W. Miller; D. Weise; S. Mahalingam; M. Princevac; R. Yokelson; W. Hao; D. Cocker; H. Jung; G. Tonnesen; S. Urbanski; I. Burling; S. Hosseini; S. Akagi

2013-01-01

Gaseous and particulate emissions were measured for a variety of chaparral and Madrean oak woodland fuel types in a series of laboratory and field experiments in California and Arizona. Emissions were measured using state of the art ground-based and aircraft-based sampling systems. Emission factors were determined for many new chemical species for the fuels....

Estimated tetrachloroethylene (C2Cl4) emissions for 1992 2014 in China and a high resolution gridded emission in 2010

NASA Astrophysics Data System (ADS)

Bie, P.; Li, Z.; Hu, J.

2016-12-01

Estimated tetrachloroethylene (C2Cl4) emissions for 1992 2014 in China and a high resolution gridded emission in 2010 Pengju Bie1, Zhifang Li1, Jianxin Hu1,*1Collaborative Innovation Center for Regional Environmental Quality, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China *Corresponding author E-mail: jianxin@pku.edu.cnTel: 86-10-62756593 Fax: 86-10-62760755 Evaluating the contribution from tetrachloroethylene (C2Cl4, PCE) to stratospheric halogen loading requires the knowledge of the spatial and temporal variability of emissions, and thus the tropospheric degradation and removal. And the short atmospheric lifetime (90 days) leads to a large regional variability. This study estimated the emissions of China from 1992 to 2014, based on emission functions and aggregated information given reasonable uncertainties. Results show that the emissions increased from 5.3(3.8 7.0) Gg to 176.9(131.2 232.1) Gg with a moderate growth rate of 17.3%/yr during 1992 2014. More than 97.3% of emissions stemmed from solvents sector. Considering the GDP data availability and the comparable estimate to that of top-down method in 2010, we developed a gridded emission inventory on a 0.5°×0.5° latitude-longitude grid of this year. Due to the more advanced social-economic conditions and more intensive industrial establishment, greater PCE emissions were observed to originate from East China, especially for Jiangsu and Zhejiang provinces, and Beijing-Tianjin-Hebei region and Pearl River Delta (PRD) region.

Real-world emissions of in-use off-road vehicles in Mexico.

PubMed

Zavala, Miguel; Huertas, Jose Ignacio; Prato, Daniel; Jazcilevich, Aron; Aguilar, Andrés; Balam, Marco; Misra, Chandan; Molina, Luisa T

2017-09-01

Off-road vehicles used in construction and agricultural activities can contribute substantially to emissions of gaseous pollutants and can be a major source of submicrometer carbonaceous particles in many parts of the world. However, there have been relatively few efforts in quantifying the emission factors (EFs) and for estimating the potential emission reduction benefits using emission control technologies for these vehicles. This study characterized the black carbon (BC) component of particulate matter and NOx, CO, and CO 2 EFs of selected diesel-powered off-road mobile sources in Mexico under real-world operating conditions using on-board portable emissions measurements systems (PEMS). The vehicles sampled included two backhoes, one tractor, a crane, an excavator, two front loaders, two bulldozers, an air compressor, and a power generator used in the construction and agricultural activities. For a selected number of these vehicles the emissions were further characterized with wall-flow diesel particle filters (DPFs) and partial-flow DPFs (p-DPFs) installed. Fuel-based EFs presented less variability than time-based emission rates, particularly for the BC. Average baseline EFs in working conditions for BC, NOx, and CO ranged from 0.04 to 5.7, from 12.6 to 81.8, and from 7.9 to 285.7 g/kg-fuel, respectively, and a high dependency by operation mode and by vehicle type was observed. Measurement-base frequency distributions of EFs by operation mode are proposed as an alternative method for characterizing the variability of off-road vehicles emissions under real-world conditions. Mass-based reductions for black carbon EFs were substantially large (above 99%) when DPFs were installed and the vehicles were idling, and the reductions were moderate (in the 20-60% range) for p-DPFs in working operating conditions. The observed high variability in measured EFs also indicates the need for detailed vehicle operation data for accurately estimating emissions from off-road vehicles in emissions inventories. Measurements of off-road vehicles used in construction and agricultural activities in Mexico using on-board portable emissions measurements systems (PEMS) showed that these vehicles can be major sources of black carbon and NO X . Emission factors varied significantly under real-world operating conditions, suggesting the need for detailed vehicle operation data for accurately estimating emissions inventories. Tests conducted in a selected number of sampled vehicles indicated that diesel particle filters (DPFs) are an effective technology for control of diesel particulate emissions and can provide potentially large emissions reduction in Mexico if widely implemented.

Reconciling Basin-Scale Top-Down and Bottom-Up Methane Emission Measurements for Onshore Oil and Gas Development: Cooperative Research and Development Final Report, CRADA Number CRD-14-572

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heath, Garvin A.

The overall objective of the Research Partnership to Secure Energy for America (RPSEA)-funded research project is to develop independent estimates of methane emissions using top-down and bottom-up measurement approaches and then to compare the estimates, including consideration of uncertainty. Such approaches will be applied at two scales: basin and facility. At facility scale, multiple methods will be used to measure methane emissions of the whole facility (controlled dual tracer and single tracer releases, aircraft-based mass balance and Gaussian back-trajectory), which are considered top-down approaches. The bottom-up approach will sum emissions from identified point sources measured using appropriate source-level measurement techniquesmore » (e.g., high-flow meters). At basin scale, the top-down estimate will come from boundary layer airborne measurements upwind and downwind of the basin, using a regional mass balance model plus approaches to separate atmospheric methane emissions attributed to the oil and gas sector. The bottom-up estimate will result from statistical modeling (also known as scaling up) of measurements made at selected facilities, with gaps filled through measurements and other estimates based on other studies. The relative comparison of the bottom-up and top-down estimates made at both scales will help improve understanding of the accuracy of the tested measurement and modeling approaches. The subject of this CRADA is NREL's contribution to the overall project. This project resulted from winning a competitive solicitation no. RPSEA RFP2012UN001, proposal no. 12122-95, which is the basis for the overall project. This Joint Work Statement (JWS) details the contributions of NREL and Colorado School of Mines (CSM) in performance of the CRADA effort.« less

Dietary greenhouse gas emissions of meat-eaters, fish-eaters, vegetarians and vegans in the UK.

PubMed

Scarborough, Peter; Appleby, Paul N; Mizdrak, Anja; Briggs, Adam D M; Travis, Ruth C; Bradbury, Kathryn E; Key, Timothy J

The production of animal-based foods is associated with higher greenhouse gas (GHG) emissions than plant-based foods. The objective of this study was to estimate the difference in dietary GHG emissions between self-selected meat-eaters, fish-eaters, vegetarians and vegans in the UK. Subjects were participants in the EPIC-Oxford cohort study. The diets of 2,041 vegans, 15,751 vegetarians, 8,123 fish-eaters and 29,589 meat-eaters aged 20-79 were assessed using a validated food frequency questionnaire. Comparable GHG emissions parameters were developed for the underlying food codes using a dataset of GHG emissions for 94 food commodities in the UK, with a weighting for the global warming potential of each component gas. The average GHG emissions associated with a standard 2,000 kcal diet were estimated for all subjects. ANOVA was used to estimate average dietary GHG emissions by diet group adjusted for sex and age. The age-and-sex-adjusted mean (95 % confidence interval) GHG emissions in kilograms of carbon dioxide equivalents per day (kgCO 2 e/day) were 7.19 (7.16, 7.22) for high meat-eaters ( > = 100 g/d), 5.63 (5.61, 5.65) for medium meat-eaters (50-99 g/d), 4.67 (4.65, 4.70) for low meat-eaters ( < 50 g/d), 3.91 (3.88, 3.94) for fish-eaters, 3.81 (3.79, 3.83) for vegetarians and 2.89 (2.83, 2.94) for vegans. In conclusion, dietary GHG emissions in self-selected meat-eaters are approximately twice as high as those in vegans. It is likely that reductions in meat consumption would lead to reductions in dietary GHG emissions.

Space-based observations of megacity carbon dioxide

NASA Astrophysics Data System (ADS)

Kort, Eric A.; Frankenberg, Christian; Miller, Charles E.; Oda, Tom

2012-09-01

Urban areas now house more than half the world's population, and are estimated to contribute over 70% of global energy-related CO2 emissions. Many cities have emission reduction policies in place, but lack objective, observation-based methods for verifying their outcomes. Here we demonstrate the potential of satellite-borne instruments to provide accurate global monitoring of megacity CO2 emissions using GOSAT observations of column averaged CO2 dry air mole fraction (XCO2) collected over Los Angeles and Mumbai. By differencing observations over the megacity with those in nearby background, we observe robust, statistically significant XCO2 enhancements of 3.2 ± 1.5 ppm for Los Angeles and 2.4 ± 1.2 ppm for Mumbai, and find these enhancements can be exploited to track anthropogenic emission trends over time. We estimate that XCO2 changes as small as 0.7 ppm in Los Angeles, corresponding to a 22% change in emissions, could be detected with GOSAT at the 95% confidence level.

Agricultural soil greenhouse gas emissions: a review of national inventory methods.

PubMed

Lokupitiya, Erandathie; Paustian, Keith

2006-01-01

Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to submit national greenhouse gas (GHG) inventories, together with information on methods used in estimating their emissions. Currently agricultural activities contribute a significant portion (approximately 20%) of global anthropogenic GHG emissions, and agricultural soils have been identified as one of the main GHG source categories within the agricultural sector. However, compared to many other GHG sources, inventory methods for soils are relatively more complex and have been implemented only to varying degrees among member countries. This review summarizes and evaluates the methods used by Annex 1 countries in estimating CO2 and N2O emissions in agricultural soils. While most countries utilize the Intergovernmental Panel on Climate Change (IPCC) default methodology, several Annex 1 countries are developing more advanced methods that are tailored for specific country circumstances. Based on the latest national inventory reporting, about 56% of the Annex 1 countries use IPCC Tier 1 methods, about 26% use Tier 2 methods, and about 18% do not estimate or report N2O emissions from agricultural soils. More than 65% of the countries do not report CO2 emissions from the cultivation of mineral soils, organic soils, or liming, and only a handful of countries have used country-specific, Tier 3 methods. Tier 3 methods usually involve process-based models and detailed, geographically specific activity data. Such methods can provide more robust, accurate estimates of emissions and removals but require greater diligence in documentation, transparency, and uncertainty assessment to ensure comparability between countries. Availability of detailed, spatially explicit activity data is a major constraint to implementing higher tiered methods in many countries.

Estimating Lightning NOx Emissions for Regional Air Quality Modeling

NASA Astrophysics Data System (ADS)

Holloway, T.; Scotty, E.; Harkey, M.

2014-12-01

Lightning emissions have long been recognized as an important source of nitrogen oxides (NOx) on a global scale, and an essential emission component for global atmospheric chemistry models. However, only in recent years have regional air quality models incorporated lightning NOx emissions into simulations. The growth in regional modeling of lightning emissions has been driven in part by comparisons with satellite-derived estimates of column NO2, especially from the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. We present and evaluate a lightning inventory for the EPA Community Multiscale Air Quality (CMAQ) model. Our approach follows Koo et al. [2010] in the approach to spatially and temporally allocating a given total value based on cloud-top height and convective precipitation. However, we consider alternate total NOx emission values (which translate into alternate lightning emission factors) based on a review of the literature and performance evaluation against OMI NO2 for July 2007 conditions over the U.S. and parts of Canada and Mexico. The vertical distribution of lightning emissions follow a bimodal distribution from Allen et al. [2012] calculated over 27 vertical model layers. Total lightning NO emissions for July 2007 show the highest above-land emissions in Florida, southeastern Texas and southern Louisiana. Although agreement with OMI NO2 across the domain varied significantly depending on lightning NOx assumptions, agreement among the simulations at ground-based NO2 monitors from the EPA Air Quality System database showed no meaningful sensitivity to lightning NOx. Emissions are compared with prior studies, which find similar distribution patterns, but a wide range of calculated magnitudes.

Toward a Multi-City Framework for Urban GHG Estimation in the United States: Methods, Uncertainties, and Future Goals

NASA Astrophysics Data System (ADS)

Mueller, K. L.; Callahan, W.; Davis, K. J.; Dickerson, R. R.; Duren, R. M.; Gurney, K. R.; Karion, A.; Keeling, R. F.; Kim, J.; Lauvaux, T.; Miller, C. E.; Shepson, P. B.; Turnbull, J. C.; Weiss, R. F.; Whetstone, J. R.

2017-12-01

City and State governments are increasingly interested in mitigating greenhouse gas (GHG) emissions to improve sustainability within their jurisdictions. Estimation of urban GHG emissions remains an active research area with many sources of uncertainty. To support the effort of improving measurement of trace gas emissions in city environments, several federal agencies along with academic, research, and private entities have been working within a handful of domestic metropolitan areas to improve both (1) the assessment of GHG emissions accuracy using a variety of measurement technologies, and (2) the tools that can better assess GHG inventory data at urban mitigation scales based upon these measurements. The National Institute of Standards and Technology (NIST) activities have focused on three areas, or testbeds: Indianapolis (INFLUX experiment), Los Angeles (the LA Megacities project), and the Northeastern Corridor areas encompassing Washington and Baltimore (the NEC/BW GHG Measurements project). These cities represent diverse meteorological, terrain, demographic, and emissions characteristics having a broad range of complexities. To date this research has involved multiple measurement systems and integrated observing approaches, all aimed at advancing development of a robust, science-base upon which higher accuracy quantification approaches can rest. Progress toward such scientifically robust, widely-accepted emissions quantification methods will rely upon continuous performance assessment. Such assessment is challenged by the complexities of cities themselves (e.g., population, urban form) along with the many variables impacting a city's technological ability to estimate its GHG emissions (e.g., meteorology, density of observations). We present the different NIST testbeds and a proposal to initiate conceptual development of a reference framework supporting the comparison of multi-city GHG emissions estimates. Such a reference framework has potential to provide the basis for city governments to choose the measurements and methods that can quantify their GHG and related trace gas emissions at levels commensurate with their needs.

Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality

PubMed Central

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W.

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries’ mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country’s boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries’ level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990–2010) to estimate the relationships between countries’ level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country’s level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure. PMID:26642202

Nitrogen oxides emissions from thermal power plants in china: current status and future predictions.

PubMed

Tian, Hezhong; Liu, Kaiyun; Hao, Jiming; Wang, Yan; Gao, Jiajia; Qiu, Peipei; Zhu, Chuanyong

2013-10-01

Increasing emissions of nitrogen oxides (NOx) over the Chinese mainland have been of great concern due to their adverse impacts on regional air quality and public health. To explore and obtain the temporal and spatial characteristics of NOx emissions from thermal power plants in China, a unit-based method is developed. The method assesses NOx emissions based on detailed information on unit capacity, boiler and burner patterns, feed fuel types, emission control technologies, and geographical locations. The national total NOx emissions in 2010 are estimated at 7801.6 kt, of which 5495.8 kt is released from coal-fired power plant units of considerable size between 300 and 1000 MW. The top provincial emitter is Shandong where plants are densely concentrated. The average NOx-intensity is estimated at 2.28 g/kWh, markedly higher than that of developed countries, mainly owing to the inadequate application of high-efficiency denitrification devices such as selective catalytic reduction (SCR). Future NOx emissions are predicted by applying scenario analysis, indicating that a reduction of about 40% by the year 2020 can be achieved compared with emissions in 2010. These results suggest that NOx emissions from Chinese thermal power plants could be substantially mitigated within 10 years if reasonable control measures were implemented effectively.

Estimating the confidence bounds for projected ozone design values under different emissions control options

EPA Science Inventory

In current regulatory applications, regional air quality model is applied for a base year and a future year with reduced emissions using the same meteorological conditions. The base year design value is multiplied by the ratio of the average of the top 10 ozone concentrations fo...

[Study on the quantitative estimation method for VOCs emission from petrochemical storage tanks based on tanks 4.0.9d model].

PubMed

Li, Jing; Wang, Min-Yan; Zhang, Jian; He, Wan-Qing; Nie, Lei; Shao, Xia

2013-12-01

VOCs emission from petrochemical storage tanks is one of the important emission sources in the petrochemical industry. In order to find out the VOCs emission amount of petrochemical storage tanks, Tanks 4.0.9d model is utilized to calculate the VOCs emission from different kinds of storage tanks. VOCs emissions from a horizontal tank, a vertical fixed roof tank, an internal floating roof tank and an external floating roof tank were calculated as an example. The consideration of the site meteorological information, the sealing information, the tank content information and unit conversion by using Tanks 4.0.9d model in China was also discussed. Tanks 4.0.9d model can be used to estimate VOCs emissions from petrochemical storage tanks in China as a simple and highly accurate method.

Emissions of CH4 from natural gas production in the United States using aircraft-based observations (Invited)

NASA Astrophysics Data System (ADS)

Sweeney, C.; Ryerson, T. B.; Karion, A.; Peischl, J.; Petron, G.; Schnell, R. C.; Tsai, T.; Crosson, E.; Rella, C.; Trainer, M.; Frost, G. J.; Hardesty, R. M.; Montzka, S. A.; Dlugokencky, E. J.; Tans, P. P.

2013-12-01

New extraction technologies are making natural gas from shale and tight sand gas reservoirs in the United States (US) more accessible. As a result, the US has become the largest producer of natural gas in the world. This growth in natural gas production may result in increased leakage of methane, a potent greenhouse gas, offsetting the climate benefits of natural gas relative to other fossil fuels. Methane emissions from natural gas production are not well quantified because of the large variety of potential sources, the variability in production and operating practices, the uneven distribution of emitters, and a lack of verification of emission inventories with direct atmospheric measurements. Researchers at the NOAA Earth System Research Laboratory (ESRL) have used simple mass balance approaches to estimate emissions of CH4 from several natural gas and oil plays across the US. We will summarize the results of the available aircraft and ground-based atmospheric emissions estimates to better understand the spatial and temporal distribution of these emissions in the US.

Emissions of CH4 from natural gas production in the United States using aircraft-based observations

NASA Astrophysics Data System (ADS)

Sweeney, Colm; Karion, Anna; Petron, Gabrielle; Ryerson, Thomas; Peischl, Jeff; Trainer, Michael; Rella, Chris; Hardesty, Michael; Crosson, Eric; Montzka, Stephen; Tans, Pieter; Shepson, Paul; Kort, Eric

2014-05-01

New extraction technologies are making natural gas from shale and tight sand gas reservoirs in the United States (US) more accessible. As a result, the US has become the largest producer of natural gas in the world. This growth in natural gas production may result in increased leakage of methane, a potent greenhouse gas, offsetting the climate benefits of natural gas relative to other fossil fuels. Methane emissions from natural gas production are not well quantified because of the large variety of potential sources, the variability in production and operating practices, the uneven distribution of emitters, and a lack of verification of emission inventories with direct atmospheric measurements. Researchers at the NOAA Earth System Research Laboratory (ESRL) have used simple mass balance approaches in combination with isotopes and light alkanes to estimate emissions of CH4 from several natural gas and oil plays across the US. We will summarize the results of the available aircraft and ground-based atmospheric emissions estimates to better understand the spatial and temporal distribution of these emissions in the US.

Atmospheric Compensation and Surface Temperature and Emissivity Retrieval with LWIR Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Pieper, Michael

Accurate estimation or retrieval of surface emissivity spectra from long-wave infrared (LWIR) or Thermal Infrared (TIR) hyperspectral imaging data acquired by airborne or space-borne sensors is necessary for many scientific and defense applications. The at-aperture radiance measured by the sensor is a function of the ground emissivity and temperature, modified by the atmosphere. Thus the emissivity retrieval process consists of two interwoven steps: atmospheric compensation (AC) to retrieve the ground radiance from the measured at-aperture radiance and temperature-emissivity separation (TES) to separate the temperature and emissivity from the ground radiance. In-scene AC (ISAC) algorithms use blackbody-like materials in the scene, which have a linear relationship between their ground radiances and at-aperture radiances determined by the atmospheric transmission and upwelling radiance. Using a clear reference channel to estimate the ground radiance, a linear fitting of the at-aperture radiance and estimated ground radiance is done to estimate the atmospheric parameters. TES algorithms for hyperspectral imaging data assume that the emissivity spectra for solids are smooth compared to the sharp features added by the atmosphere. The ground temperature and emissivity are found by finding the temperature that provides the smoothest emissivity estimate. In this thesis we develop models to investigate the sensitivity of AC and TES to the basic assumptions enabling their performance. ISAC assumes that there are perfect blackbody pixels in a scene and that there is a clear channel, which is never the case. The developed ISAC model explains how the quality of blackbody-like pixels affect the shape of atmospheric estimates and the clear channel assumption affects their magnitude. Emissivity spectra for solids usually have some roughness. The TES model identifies four sources of error: the smoothing error of the emissivity spectrum, the emissivity error from using the incorrect temperature, and the errors caused by sensor noise and wavelength calibration. The ways these errors interact determines the overall TES performance. Since the AC and TES processes are interwoven, any errors in AC are transferred to TES and the final temperature and emissivity estimates. Combining the two models, shape errors caused by the blackbody assumption are transferred to the emissivity estimates, where magnitude errors from the clear channel assumption are compensated by TES temperature induced emissivity errors. The ability for the temperature induced error to compensate for such atmospheric errors makes it difficult to determine the correct atmospheric parameters for a scene. With these models we are able to determine the expected quality of estimated emissivity spectra based on the quality of blackbody-like materials on the ground, the emissivity of the materials being searched for, and the properties of the sensor. The quality of material emissivity spectra is a key factor in determining detection performance for a material in a scene.

Marginal Emissions Factors for Electricity Generation in the Midcontinent ISO.

PubMed

Thind, Maninder P S; Wilson, Elizabeth J; Azevedo, Inês L; Marshall, Julian D

2017-12-19

Environmental consequences of electricity generation are often determined using average emission factors. However, as different interventions are incrementally pursued in electricity systems, the resulting marginal change in emissions may differ from what one would predict based on system-average conditions. Here, we estimate average emission factors and marginal emission factors for CO 2 , SO 2 , and NO x from fossil and nonfossil generators in the Midcontinent Independent System Operator (MISO) region during years 2007-2016. We analyze multiple spatial scales (all MISO; each of the 11 MISO states; each utility; each generator) and use MISO data to characterize differences between the two emission factors (average; marginal). We also explore temporal trends in emissions factors by hour, day, month, and year, as well as the differences that arise from including only fossil generators versus total generation. We find, for example, that marginal emission factors are generally higher during late-night and early morning compared to afternoons. Overall, in MISO, average emission factors are generally higher than marginal estimates (typical difference: ∼20%). This means that the true environmental benefit of an energy efficiency program may be ∼20% smaller than anticipated if one were to use average emissions factors. Our analysis can usefully be extended to other regions to support effective near-term technical, policy and investment decisions based on marginal rather than only average emission factors.

Estimate of methane emissions from oil and gas operations in the Uintah Basin using airborne measurements and Lidar wind data

NASA Astrophysics Data System (ADS)

Karion, A.; Sweeney, C.; Petron, G.; Frost, G. J.; Trainer, M.; Brewer, A.; Hardesty, R.; Conley, S. A.; Wolter, S.; Newberger, T.; Kofler, J.; Tans, P. P.

2012-12-01

During a February 2012 campaign in the Uintah oil and gas basin in northeastern Utah, thirteen research flights were conducted in conjunction with a variety of ground-based measurements. Using aircraft-based high-resolution (0.5 Hz) observations of methane (CH4) and carbon dioxide (CO2), along with High-Resolution Doppler Lidar wind observations from a ground site in the basin, we have calculated the basin-wide CH4 flux on several days. Uncertainty estimates are calculated for each day and are generally large for all but one flight day. On one day, February 3, uncertainty on the estimate from a mass balance approach is better than 30% due to ideal meteorological conditions, including a well-mixed boundary layer and low wind variability both in time and altitude, as determined from the Lidar wind observations. This aircraft-based mass balance approach to flux estimates is a critical and valuable tool for estimating CH4 emissions from oil and gas basins.

An evaluation of the carbon balance technique for estimating emission factors and fuel consumption in forest fires

Treesearch

Nelson, Jr. Ralph M.

1982-01-01

Eighteen experimental fires were used to compare measured and calculated values for emission factors and fuel consumption to evaluate the carbon balance technique. The technique is based on a model for the emission factor of carbon dioxide, corrected for the production of other emissions, and which requires measurements of effluent concentrations and air volume in the...

Estimation of sulphur dioxide emission rate from a power plant based on the remote sensing measurement with an imaging-DOAS instrument

NASA Astrophysics Data System (ADS)

Chong, Jihyo; Kim, Young J.; Baek, Jongho; Lee, Hanlim

2016-10-01

Major anthropogenic sources of sulphur dioxide in the troposphere include point sources such as power plants and combustion-derived industrial sources. Spatially resolved remote sensing of atmospheric trace gases is desirable for better estimation and validation of emission from those sources. It has been reported that Imaging Differential Optical Absorption Spectroscopy (I-DOAS) technique can provide the spatially resolved two-dimensional distribution measurement of atmospheric trace gases. This study presents the results of I-DOAS observations of SO2 from a large power plant. The stack plume from the Taean coal-fired power plant was remotely sensed with an I-DOAS instrument. The slant column density (SCD) of SO2 was derived by data analysis of the absorption spectra of the scattered sunlight measured by an I-DOAS over the power plant stacks. Two-dimensional distribution of SO2 SCD was obtained over the viewing window of the I-DOAS instrument. The measured SCDs were converted to mixing ratios in order to estimate the rate of SO2 emission from each stack. The maximum mixing ratio of SO2 was measured to be 28.1 ppm with a SCD value of 4.15×1017 molecules/cm2. Based on the exit velocity of the plume from the stack, the emission rate of SO2 was estimated to be 22.54 g/s. Remote sensing of SO2 with an I-DOAS instrument can be very useful for independent estimation and validation of the emission rates from major point sources as well as area sources.

Assessment of riverine load of contaminants to European seas under policy implementation scenarios: an example with 3 pilot substances.

PubMed

Marinov, Dimitar; Pistocchi, Alberto; Trombetti, Marco; Bidoglio, Giovanni

2014-01-01

An evaluation of conventional emission scenarios is carried out targeting a possible impact of European Union (EU) policies on riverine loads to the European seas for 3 pilot pollutants: lindane, trifluralin, and perfluorooctane sulfonate (PFOS). The policy scenarios are investigated to the time horizon of year 2020 starting from chemical-specific reference conditions and considering different types of regulatory measures including business as usual (BAU), current trend (CT), partial implementation (PI), or complete ban (PI ban) of emissions. The scenario analyses show that the model-estimated lindane load of 745 t to European seas in 1995, based on the official emission data, would be reduced by 98.3% to approximately 12.5 t in 2005 (BAU scenario), 10 years after the start of the EU regulation of this chemical. The CT and PI ban scenarios indicate a reduction of sea loads of lindane in 2020 by 74% and 95%, respectively, when compared to the BAU estimate. For trifluralin, an annual load of approximately 61.7 t is estimated for the baseline year 2003 (BAU scenario), although the applied conservative assumptions related to pesticide use data availability in Europe. Under the PI (ban) scenario, assuming only small residual emissions of trifluralin, we estimate a sea loading of approximately 0.07 t/y. For PFOS, the total sea load from all European countries is estimated at approximately 5.8 t/y referred to 2007 (BAU scenario). Reducing the total load of PFOS below 1 t/y requires emissions to be reduced by 84%. The analysis of conventional scenarios or scenario typologies for emissions of contaminants using simple spatially explicit GIS-based models is suggested as a viable, affordable exercise that may support the assessment of implementation of policies and the identification or negotiation of emission reduction targets. © 2013 SETAC.

Greenhouse gas contribution of municipal solid waste collection: A case study in the city of Istanbul, Turkey.

PubMed

Korkut, Nafiz E; Yaman, Cevat; Küçükağa, Yusuf; Jaunich, Megan K; Demir, İbrahim

2018-02-01

This article estimates greenhouse gas emissions and global warming factors resulting from collection of municipal solid waste to the transfer stations or landfills in Istanbul for the year of 2015. The aim of this study is to quantify and compare diesel fuel consumption and estimate the greenhouse gas emissions and global warming factors associated with municipal solid waste collection of the 39 districts of Istanbul. Each district's greenhouse gas emissions resulting from the provision and combustion of diesel fuel was estimated by considering the number of collection trips and distances to municipal solid waste facilities. The estimated greenhouse gases and global warming factors for the districts varied from 61.2 to 2759.1 t CO 2 -eq and from 4.60 to 15.20 kg CO 2 -eq t -1 , respectively. The total greenhouse gas emission was estimated as 46.4E3 t CO 2 -eq. Lastly, the collection data from the districts was used to parameterise a collection model that can be used to estimate fuel consumption associated with municipal solid waste collection. This mechanistic model can then be used to predict future fuel consumption and greenhouse gas emissions associated with municipal solid waste collection based on projected population, waste generation, and distance to transfer stations and landfills. The greenhouse gas emissions can be reduced by decreasing the trip numbers and trip distances, building more transfer stations around the city, and making sure that the collection trucks are full in each trip.

Estimation of the local and long-range contributions to particulate matter levels using continuous measurements in a single urban background site

NASA Astrophysics Data System (ADS)

Diamantopoulou, Marianna; Skyllakou, Ksakousti; Pandis, Spyros N.

2016-06-01

The Particulate Matter Source Apportionment Technology (PSAT) algorithm is used together with PMCAMx, a regional chemical transport model, to develop a simple observation-based method (OBM) for the estimation of local and regional contributions of sources of primary and secondary pollutants in urban areas. We test the hypothesis that the minimum of the diurnal average concentration profile of the pollutant is a good estimate of the average contribution of long range transport levels. We use PMCAMx to generate "pseudo-observations" for four different European cities (Paris, London, Milan, and Dusseldorf) and PSAT to estimate the corresponding "true" local and regional contributions. The predictions of the proposed OBM are compared to the "true" values for different definitions of the source area. During winter, the estimates by the OBM for the local contributions to the concentrations of total PM2.5, primary pollutants, and sulfate are within 25% of the "true" contributions of the urban area sources. For secondary organic aerosol the OBM overestimates the importance of the local sources and it actually estimates the contributions of sources within 200 km from the receptor. During summer for primary pollutants and cities with low nearby emissions (ratio of emissions in an area extending 100 km from the city over local emissions lower than 10) the OBM estimates correspond to the city emissions within 25% or so. For cities with relatively high nearby emissions the OBM estimates correspond to emissions within 100 km from the receptor. For secondary PM2.5 components like sulfate and secondary organic aerosol the OBM's estimates correspond to sources within 200 km from the receptor. Finally, for total PM2.5 the OBM provides approximately the contribution of city emissions during the winter and the contribution of sources within 100 km from the receptor during the summer.

A high-resolution open biomass burning emission inventory based on statistical data and MODIS observations in mainland China

NASA Astrophysics Data System (ADS)

Xu, Y.; Fan, M.; Huang, Z.; Zheng, J.; Chen, L.

2017-12-01

Open biomass burning which has adverse effects on air quality and human health is an important source of gas and particulate matter (PM) in China. Current emission estimations of open biomass burning are generally based on single source (alternative to statistical data and satellite-derived data) and thus contain large uncertainty due to the limitation of data. In this study, to quantify the 2015-based amount of open biomass burning, we established a new estimation method for open biomass burning activity levels by combining the bottom-up statistical data and top-down MODIS observations. And three sub-category sources which used different activity data were considered. For open crop residue burning, the "best estimate" of activity data was obtained by averaging the statistical data from China statistical yearbooks and satellite observations from MODIS burned area product MCD64A1 weighted by their uncertainties. For the forest and grassland fires, their activity levels were represented by the combination of statistical data and MODIS active fire product MCD14ML. Using the fire radiative power (FRP) which is considered as a better indicator of active fire level as the spatial allocation surrogate, coarse gridded emissions were reallocated into 3km ×3km grids to get a high-resolution emission inventory. Our results showed that emissions of CO, NOx, SO2, NH3, VOCs, PM2.5, PM10, BC and OC in mainland China were 6607, 427, 84, 79, 1262, 1198, 1222, 159 and 686 Gg/yr, respectively. Among all provinces of China, Henan, Shandong and Heilongjiang were the top three contributors to the total emissions. In this study, the developed open biomass burning emission inventory with a high-resolution could support air quality modeling and policy-making for pollution control.

Evaluation of carbon emission reductions promoted by private driving restrictions based on automatic fare collection data in Beijing, China.

PubMed

Zhang, Wandi; Chen, Feng; Wang, Zijia; Huang, Jianling; Wang, Bo

2017-11-01

Public transportation automatic fare collection (AFC) systems are able to continuously record large amounts of passenger travel information, providing massive, low-cost data for research on regulations pertaining to public transport. These data can be used not only to analyze characteristics of passengers' trips but also to evaluate transport policies that promote a travel mode shift and emission reduction. In this study, models combining card, survey, and geographic information systems (GIS) data are established with a research focus on the private driving restriction policies being implemented in an ever-increasing number of cities. The study aims to evaluate the impact of these policies on the travel mode shift, as well as relevant carbon emission reductions. The private driving restriction policy implemented in Beijing is taken as an example. The impact of the restriction policy on the travel mode shift from cars to subways is analyzed through a model based on metro AFC data. The routing paths of these passengers are also analyzed based on the GIS method and on survey data, while associated carbon emission reductions are estimated. The analysis method used in this study can provide reference for the application of big data in evaluating transport policies. Motor vehicles have become the most prevalent source of emissions and subsequently air pollution within Chinese cities. The evaluation of the effects of driving restriction policies on the travel mode shift and vehicle emissions will be useful for other cities in the future. Transport big data, playing an important support role in estimating the travel mode shift and emission reduction considered, can help related departments to estimate the effects of traffic jam alleviation and environment improvement before the implementation of these restriction policies and provide a reference for relevant decisions.

An audit of the global carbon budget: identifying and reducing sources of uncertainty

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Tans, P. P.; Marland, G.; Stocker, B. D.

2012-12-01

Uncertainties in our carbon accounting practices may limit our ability to objectively verify emission reductions on regional scales. Furthermore uncertainties in the global C budget must be reduced to benchmark Earth System Models that incorporate carbon-climate interactions. Here we present an audit of the global C budget where we try to identify sources of uncertainty for major terms in the global C budget. The atmospheric growth rate of CO2 has increased significantly over the last 50 years, while the uncertainty in calculating the global atmospheric growth rate has been reduced from 0.4 ppm/yr to 0.2 ppm/yr (95% confidence). Although we have greatly reduced global CO2 growth rate uncertainties, there remain regions, such as the Southern Hemisphere, Tropics and Arctic, where changes in regional sources/sinks will remain difficult to detect without additional observations. Increases in fossil fuel (FF) emissions are the primary factor driving the increase in global CO2 growth rate; however, our confidence in FF emission estimates has actually gone down. Based on a comparison of multiple estimates, FF emissions have increased from 2.45 ± 0.12 PgC/yr in 1959 to 9.40 ± 0.66 PgC/yr in 2010. Major sources of increasing FF emission uncertainty are increased emissions from emerging economies, such as China and India, as well as subtle differences in accounting practices. Lastly, we evaluate emission estimates from Land Use Change (LUC). Although relative errors in emission estimates from LUC are quite high (2 sigma ~ 50%), LUC emissions have remained fairly constant in recent decades. We evaluate the three commonly used approaches to estimating LUC emissions- Bookkeeping, Satellite Imagery, and Model Simulations- to identify their main sources of error and their ability to detect net emissions from LUC.; Uncertainties in Fossil Fuel Emissions over the last 50 years.

From carbon sink to carbon source: extensive peat oxidation in insular Southeast Asia since 1990

NASA Astrophysics Data System (ADS)

Miettinen, Jukka; Hooijer, Aljosja; Vernimmen, Ronald; Liew, Soo Chin; Page, Susan E.

2017-02-01

Tropical peatlands of the western part of insular Southeast Asia have experienced extensive land cover changes since 1990. Typically involving drainage, these land cover changes have resulted in increased peat oxidation in the upper peat profile. In this paper we provide current (2015) and cumulative carbon emissions estimates since 1990 from peat oxidation in Peninsular Malaysia, Sumatra and Borneo, utilizing newly published peatland land cover information and the recently agreed Intergovernmental Panel on Climate Change (IPCC) peat oxidation emission values for tropical peatland areas. Our results highlight the change of one of the Earth’s most efficient long-term carbon sinks to a short-term emission source, with cumulative carbon emissions since 1990 estimated to have been in the order of 2.5 Gt C. Current (2015) levels of emissions are estimated at around 146 Mt C yr-1, with a range of 132-159 Mt C yr-1 depending on the selection of emissions factors for different land cover types. 44% (or 64 Mt C yr-1) of the emissions come from industrial plantations (mainly oil palm and Acacia pulpwood), followed by 34% (49 Mt C yr-1) of emissions from small-holder areas. Thus, altogether 78% of current peat oxidation emissions come from managed land cover types. Although based on the latest information, these estimates may still include considerable, yet currently unquantifiable, uncertainties (e.g. due to uncertainties in the extent of peatlands and drainage networks) which need to be focused on in future research. In comparison, fire induced carbon dioxide emissions over the past ten years for the entire equatorial Southeast Asia region have been estimated to average 122 Mt C yr-1 (www.globalfiredata.org/_index.html). The results emphasise that whilst reducing emissions from peat fires is important, urgent efforts are also needed to mitigate the constantly high level of emissions arising from peat drainage, regardless of fire occurrence.

Agricultural ammonia emissions in China: reconciling bottom-up and top-down estimates

NASA Astrophysics Data System (ADS)

Zhang, Lin; Chen, Youfan; Zhao, Yuanhong; Henze, Daven K.; Zhu, Liye; Song, Yu; Paulot, Fabien; Liu, Xuejun; Pan, Yuepeng; Lin, Yi; Huang, Binxiang

2018-01-01

Current estimates of agricultural ammonia (NH3) emissions in China differ by more than a factor of 2, hindering our understanding of their environmental consequences. Here we apply both bottom-up statistical and top-down inversion methods to quantify NH3 emissions from agriculture in China for the year 2008. We first assimilate satellite observations of NH3 column concentration from the Tropospheric Emission Spectrometer (TES) using the GEOS-Chem adjoint model to optimize Chinese anthropogenic NH3 emissions at the 1/2° × 2/3° horizontal resolution for March-October 2008. Optimized emissions show a strong summer peak, with emissions about 50 % higher in summer than spring and fall, which is underestimated in current bottom-up NH3 emission estimates. To reconcile the latter with the top-down results, we revisit the processes of agricultural NH3 emissions and develop an improved bottom-up inventory of Chinese NH3 emissions from fertilizer application and livestock waste at the 1/2° × 2/3° resolution. Our bottom-up emission inventory includes more detailed information on crop-specific fertilizer application practices and better accounts for meteorological modulation of NH3 emission factors in China. We find that annual anthropogenic NH3 emissions are 11.7 Tg for 2008, with 5.05 Tg from fertilizer application and 5.31 Tg from livestock waste. The two sources together account for 88 % of total anthropogenic NH3 emissions in China. Our bottom-up emission estimates also show a distinct seasonality peaking in summer, consistent with top-down results from the satellite-based inversion. Further evaluations using surface network measurements show that the model driven by our bottom-up emissions reproduces the observed spatial and seasonal variations of NH3 gas concentrations and ammonium (NH4+) wet deposition fluxes over China well, providing additional credibility to the improvements we have made to our agricultural NH3 emission inventory.

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

NASA Technical Reports Server (NTRS)

Oda, T.; Ott, L.; Lauvaux, T.; Feng, S.; Bun, R.; Roman, M.; Baker, D. F.; Pawson, S.

2017-01-01

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

Assessing uncertainties in gridded emissions: A case study for fossil fuel carbon dioxide (FFCO2) emission data

NASA Astrophysics Data System (ADS)

Oda, T.; Ott, L. E.; Lauvaux, T.; Feng, S.; Bun, R.; Roman, M. O.; Baker, D. F.; Pawson, S.

2017-12-01

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds that share emission sectors.

Implications of uncertainty on regional CO2 mitigation policies for the U.S. onroad sector based on a high-resolution emissions estimate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendoza, D.; Gurney, Kevin R.; Geethakumar, Sarath

2013-04-01

In this study we present onroad fossil fuel CO2 emissions estimated by the Vulcan Project, an effort quantifying fossil fuel CO2 emissions for the U.S. in high spatial and temporal resolution. This high-resolution data, aggregated at the state-level and classified in broad road and vehicle type categories, is compared to a commonly used national-average approach. We find that the use of national averages incurs state-level biases for road groupings that are almost twice as large as for vehicle groupings. The uncertainty for all groups exceeds the bias, and both quantities are positively correlated with total state emissions. States with themore » largest emissions totals are typically similar to one another in terms of emissions fraction distribution across road and vehicle groups, while smaller-emitting states have a wider range of variation in all groups. Errors in reduction estimates as large as ±60% corresponding to ±0.2 MtC are found for a national-average emissions mitigation strategy focused on a 10% emissions reduction from a single vehicle class, such as passenger gas vehicles or heavy diesel trucks. Recommendations are made for reducing CO2 emissions uncertainty by addressing its main drivers: VMT and fuel efficiency uncertainty.« less

Estimating Landscape Fire Particulate Matter (PM) Emissions over Southern Africa using MSG-SEVIRI Fire Radiative Power (FRP) and MODIS Aerosol Optical Thickness Observations

NASA Astrophysics Data System (ADS)

Mota, Bernardo; Wooster, Martin J.

2016-04-01

The approach to estimating landscape fire fuel consumption based on the remotely sensed fire radiative power (FRP) thermal energy release rate, as opposed to burned area, is now relatively widely used in studies of fire emissions, including operationally within the Copernicus Atmosphere Monitoring Service (CAMS). Nevertheless, there are still limitations to the approach, including uncertainties associated with using only the few daily overpasses typically provided by polar orbiting satellite systems, the conversion between FRP and smoke emissions, and the increased likelihood that the more frequent data from geostationary systems fails to detect the (probably highly numerous) smaller (i.e. low FRP) component of a regions fire regime. In this study, we address these limitations to directly estimate fire emissions of Particular Matter (PM; or smoke aerosols) by presenting an approach combining the "bottom-up" FRP observations available every 15 minutes across Africa from the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Radiative Product (FRP) processed at the EUMETSAT LSA SAF, and the "top-down" aerosol optical thickness (AOT) measures of the fire plumes themselves as measured by the Moderate-resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Terra (MOD04_L2) and Aqua (MYD04_L2) satellites. We determine PM emission coefficients that relate directly to FRP measures by combining these two datasets, and the use of the almost continuous geostationary FRP observations allows us to do this without recourse to (uncertain) data on wind speed at the (unknown) height of the matching plume. We also develop compensation factors to address the detection limitations of small/low intensity (low FRP) fires, and remove the need to estimate fuel consumption by going directly from FRP to PM emissions. We derive the smoke PM emissions coefficients per land cover class by comparing the total fire radiative energy (FRE) released from individual fires and the MODIS AOD seen in the corresponding plume. Analysis was performed for plumes extracted from 31 study sites covering 10,000km2each, during 10 consecutive days, for the 2011 southern Africa fire season. Compensation factors associated with undetected low FRP fires was based on extraction and application of frequency density function shape parameters, characterized by analyzing 4 years (2009-2013) of MSG-SEVIRI FRP data in 0.5o degree cells. Using the derived emission coefficients and compensation factors we estimate Total Particulate Matter (TPM) emissions for 2011 on a daily basis and 0.25o spatial resolution across southern Africa. Preliminary results show agreement between our derived emission coefficients and those of past studies following similar methods but with MODIS FRP data, and our annual TPM estimate is in reasonable agreement with those of other emission inventories based on burned area approaches. The proposed approach shows strong potential to be applied to other regions, and also to other geostationary satellite FRP products. Once the smoke emissions coefficients have been derived via comparison to the AOD data, the method requires only the FRP data, which is available at very high temporal frequency from geostationary orbit. Therefore our approach can provide near real time smoke emissions estimates which are essential for operational activities such as NRT smoke dispersion modeling and air quality forecasting.

GOSAT observations of anthropogenic emission of carbon dioxide and methane

NASA Astrophysics Data System (ADS)

Janardanan, Rajesh; Maksyutov, Shamil; Oda, Tomohiro; Saito, Makoto; Ito, Akihiko; Kaiser, Johannes W.; Ganshin, Alexander; Yoshida, Yukio; Yokota, Tatsuya; Matsunaga, Tsuneo

2017-04-01

Carbon dioxide (CO2) and methane (CH4) are the most important greenhouse gases in terms of radiative forcing. Human activities such as combustion of fossil fuel (for CO2), and gas leakage, animal agriculture, rice cultivation and landfill emissions (for CH4), are considered to be major sources of their emissions. Global emissions datasets usually depend on emission estimates reported by countries, which are seldom evaluated in an objective way. Here we present a method for delineating anthropogenic contributions to global atmospheric CO2 and CH4 (2009-2014) concentration fields using GOSAT observations of column-average dry air mole fractions (XCO2 and XCH4) and atmospheric transport model simulations using high-resolution emissions datasets (ODIAC for CO2 and EDGAR for CH4). The XCO2 and XCH4 concentration enhancements due to anthropogenic emissions are estimated at all GOSAT observation locations using the transport model simulation. We calculated threshold values to classify GOSAT observations into two categories: (1) data influenced by the anthropogenic sources and (2) those not influenced. We defined a clean background (averaged concentrations of GOSAT data that are free from contamination) in 10˚ ×10˚ regions over the globe and subtracted the background values from individual GOSAT observations. The anomalies (GOSAT observed values minus background values) were binned and compared to model-based anomalies over continental regions and selected countries. For CO2, we have found global and regional linear relationships between model and observed anomalies especially for Eurasia and North America. The analysis for East Asian region showed a systematic bias that is somewhat comparable in magnitude to the uncertainties in emission inventories in that region, which were reported by recent studies. In the case of CH4, we found a good match between inventory-based estimates and GOSAT observations for continental regions and large countries. The inventory-based estimate over North American region is biased which is in agreement with recent studies. Currently, our method is limited by the numbers of GOSAT observations available. If sufficient numbers of satellite observations are available from a instrument like GOSAT, our method could be a useful tool for monitoring greenhouse gas emissions using the regression slope between modeled and observed anomalies as a correction factor for nationally reported emissions.

Incorrect interpretation of carbon mass balance biases global vegetation fire emission estimates

PubMed Central

Surawski, N. C.; Sullivan, A. L.; Roxburgh, S. H.; Meyer, C.P. Mick; Polglase, P. J.

2016-01-01

Vegetation fires are a complex phenomenon in the Earth system with many global impacts, including influences on global climate. Estimating carbon emissions from vegetation fires relies on a carbon mass balance technique that has evolved with two different interpretations. Databases of global vegetation fire emissions use an approach based on ‘consumed biomass', which is an approximation to the biogeochemically correct ‘burnt carbon' approach. Here we show that applying the ‘consumed biomass' approach to global emissions from vegetation fires leads to annual overestimates of carbon emitted to the atmosphere by 4.0% or 100 Tg compared with the ‘burnt carbon' approach. The required correction is significant and represents ∼9% of the net global forest carbon sink estimated annually. Vegetation fire emission studies should use the ‘burnt carbon' approach to quantify and understand the role of this burnt carbon, which is not emitted to the atmosphere, as a sink enriched in carbon. PMID:27146785

Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways

DOE PAGES

Han, Jeongwoo; Tao, Ling; Wang, Michael

2017-01-24

To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. Here, this study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H 2more » options for STJ via catalytic conversion are investigated: external H 2 from natural gas (NG) steam methane reforming (SMR), in situ H 2, and H 2 from biomass gasification. Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce the WTWa GHG emissions by 28% with H 2 from NG SMR or 71% with H 2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO 2e/MJ than those estimated with an energy allocation method. Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.« less

Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Jeongwoo; Tao, Ling; Wang, Michael

To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. Here, this study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H 2more » options for STJ via catalytic conversion are investigated: external H 2 from natural gas (NG) steam methane reforming (SMR), in situ H 2, and H 2 from biomass gasification. Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce the WTWa GHG emissions by 28% with H 2 from NG SMR or 71% with H 2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO 2e/MJ than those estimated with an energy allocation method. Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.« less

Well-to-wake analysis of ethanol-to-jet and sugar-to-jet pathways.

PubMed

Han, Jeongwoo; Tao, Ling; Wang, Michael

2017-01-01

To reduce the environmental impacts of the aviation sector as air traffic grows steadily, the aviation industry has paid increasing attention to bio-based alternative jet fuels (AJFs), which may provide lower life-cycle petroleum consumption and greenhouse gas (GHG) emissions than petroleum jet fuel. This study presents well-to-wake (WTWa) results for four emerging AJFs: ethanol-to-jet (ETJ) from corn and corn stover, and sugar-to-jet (STJ) from corn stover via both biological and catalytic conversion. For the ETJ pathways, two plant designs were examined: integrated (processing corn or corn stover as feedstock) and distributed (processing ethanol as feedstock). Also, three H 2 options for STJ via catalytic conversion are investigated: external H 2 from natural gas (NG) steam methane reforming (SMR), in situ H 2 , and H 2 from biomass gasification. Results demonstrate that the feedstock is a key factor in the WTWa GHG emissions of ETJ: corn- and corn stover-based ETJ are estimated to produce WTWa GHG emissions that are 16 and 73%, respectively, less than those of petroleum jet. As for the STJ pathways, this study shows that STJ via biological conversion could generate WTWa GHG emissions 59% below those of petroleum jet. STJ via catalytic conversion could reduce the WTWa GHG emissions by 28% with H 2 from NG SMR or 71% with H 2 from biomass gasification than those of petroleum jet. This study also examines the impacts of co-product handling methods, and shows that the WTWa GHG emissions of corn stover-based ETJ, when estimated with a displacement method, are lower by 11 g CO 2 e/MJ than those estimated with an energy allocation method. Corn- and corn stover-based ETJ as well as corn stover-based STJ show potentials to reduce WTWa GHG emissions compared to petroleum jet. Particularly, WTWa GHG emissions of STJ via catalytic conversion depend highly on the hydrogen source. On the other hand, ETJ offers unique opportunities to exploit extensive existing corn ethanol plants and infrastructure, and to provide a boost to staggering ethanol demand, which is largely being used as gasoline blendstock.

An observationally constrained estimate of global dust aerosol optical depth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ridley, David A.; Heald, Colette L.; Kok, Jasper F.

Here, the role of mineral dust in climate and ecosystems has been largely quantified using global climate and chemistry model simulations of dust emission, transport, and deposition. However, differences between these model simulations are substantial, with estimates of global dust aerosol optical depth (AOD) that vary by over a factor of 5. Here we develop an observationally based estimate of the global dust AOD, using multiple satellite platforms, in situ AOD observations and four state-of-the-science global models over 2004–2008. We estimate that the global dust AOD at 550 nm is 0.030 ± 0.005 (1σ), higher than the AeroCom model medianmore » (0.023) and substantially narrowing the uncertainty. The methodology used provides regional, seasonal dust AOD and the associated statistical uncertainty for key dust regions around the globe with which model dust schemes can be evaluated. Exploring the regional and seasonal differences in dust AOD between our observationally based estimate and the four models in this study, we find that emissions in Africa are often overrepresented at the expense of Asian and Middle Eastern emissions and that dust removal appears to be too rapid in most models.« less

An observationally constrained estimate of global dust aerosol optical depth

DOE PAGES

Ridley, David A.; Heald, Colette L.; Kok, Jasper F.; ...

2016-12-06

Here, the role of mineral dust in climate and ecosystems has been largely quantified using global climate and chemistry model simulations of dust emission, transport, and deposition. However, differences between these model simulations are substantial, with estimates of global dust aerosol optical depth (AOD) that vary by over a factor of 5. Here we develop an observationally based estimate of the global dust AOD, using multiple satellite platforms, in situ AOD observations and four state-of-the-science global models over 2004–2008. We estimate that the global dust AOD at 550 nm is 0.030 ± 0.005 (1σ), higher than the AeroCom model medianmore » (0.023) and substantially narrowing the uncertainty. The methodology used provides regional, seasonal dust AOD and the associated statistical uncertainty for key dust regions around the globe with which model dust schemes can be evaluated. Exploring the regional and seasonal differences in dust AOD between our observationally based estimate and the four models in this study, we find that emissions in Africa are often overrepresented at the expense of Asian and Middle Eastern emissions and that dust removal appears to be too rapid in most models.« less

A new gridded on-road CO2 emissions inventory for the United States, 1980-2011

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.

2013-12-01

On-road transportation is responsible for 28% of all U.S. fossil fuel CO2 emissions. However, mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories have used spatial proxies such as population and road density to downscale national or state level data, which may introduce errors where the proxy variables and actual emissions are weakly correlated. We have developed a national on-road emissions inventory product based on roadway-level traffic data obtained from the Highway Performance Monitoring System. We produce annual estimates of on-road CO2 emissions at a 1km spatial resolution for the contiguous United States for the years 1980 through 2011. For the year 2011 we also produce an hourly emissions product at the 1km scale using hourly traffic volumes from hundreds of automated traffic counters across the country. National on-road emissions rose at roughly 2% per year from 1980 to 2006, with emissions peaking at 1.71 Tg CO2 in 2007. However, while national emissions have declined 6% since the peak, we observe considerable regional variation in emissions trends post-2007. While many states show stable or declining on-road emissions, several states and metropolitan areas in the Midwest, mountain west and south had emissions increases of 3-10% from 2008 to 2011. Our emissions estimates are consistent with state-reported totals of gasoline and diesel fuel consumption. This is in contrast to on-road CO2 emissions estimated by the Emissions Database of Global Atmospheric Research (EDGAR), which we show to be inconsistent in matching on-road emissions to published fuel consumption at the scale of U.S. states, due to the non-linear relationships between emissions and EDGAR's chosen spatial proxies at these scales. Since our emissions estimates were generated independent of population density and other demographic data, we were able to conduct a panel regression analysis to estimate the relationship between these variables and on-road CO2 at various spatial scales. In the case of Massachusetts we find a non-linear relationship between emissions and population density indicating that increasing density resulted in increased emissions when density is less than 2000 persons-km-2. These results highlight the value of using an emissions inventory with high spatial and temporal resolution. At coarser spatial scales, much of the variation in population density and on-road emissions between towns is lost due to aggregation. The high spatial resolution and broad temporal scope of our CO2 estimates provides a basis for analyses to support emissions monitoring, verification and mitigation policies at regional, state and local scale.

Global and regional emissions of HFC-125 (CHF2CF3) from in situ and air archive atmospheric observations at AGAGE and SOGE observatories

NASA Astrophysics Data System (ADS)

O'Doherty, S.; Cunnold, D. M.; Miller, B. R.; Mühle, J.; McCulloch, A.; Simmonds, P. G.; Manning, A. J.; Reimann, S.; Vollmer, M. K.; Greally, B. R.; Prinn, R. G.; Fraser, P. J.; Steele, L. P.; Krummel, P. B.; Dunse, B. L.; Porter, L. W.; Lunder, C. R.; Schmidbauer, N.; Hermansen, O.; Salameh, P. K.; Harth, C. M.; Wang, R. H. J.; Weiss, R. F.

2009-12-01

High-frequency, in situ observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and System for Observation of halogenated Greenhouse gases in Europe (SOGE) networks for the period 1998 to 2008, combined with archive flask measurements dating back to 1978, have been used to capture the rapid growth of HFC-125 (CHF2CF3) in the atmosphere. HFC-125 is the fifth most abundant HFC, and it currently makes the third largest contribution of the HFCs to atmospheric radiative forcing. At the beginning of 2008 the global average was 5.6 ppt in the lower troposphere and the growth rate was 16% yr-1. The extensive observations have been combined with a range of modeling techniques to derive global emission estimates in a top-down approach. It is estimated that 21 kt were emitted globally in 2007, and the emissions are estimated to have increased 15% yr-1 since 2000. These estimates agree within approximately 20% with values reported to the United Nations Framework Convention on Climate Change (UNFCCC) provided that estimated emissions from East Asia are included. Observations of regionally polluted air masses at individual AGAGE sites have been used to produce emission estimates for Europe (the EU-15 countries), the United States, and Australia. Comparisons between these top-down estimates and bottom-up estimates based on reports by individual countries to the UNFCCC show a range of approximately four in the differences. This process of independent verification of emissions, and an understanding of the differences, is vital for assessing the effectiveness of international treaties, such as the Kyoto Protocol.

Emission inventory estimation of an intercity bus terminal.

PubMed

Qiu, Zhaowen; Li, Xiaoxia; Hao, Yanzhao; Deng, Shunxi; Gao, H Oliver

2016-06-01

Intercity bus terminals are hotspots of air pollution due to concentrated activities of diesel buses. In order to evaluate the bus terminals' impact on air quality, it is necessary to estimate the associated mobile emission inventories. Since the vehicles' operating condition at the bus terminal varies significantly, conventional calculation of the emissions based on average emission factors suffers the loss of accuracy. In this study, we examined a typical intercity bus terminal-the Southern City Bus Station of Xi'an, China-using a multi-scale emission model-(US EPA's MOVES model)-to quantity the vehicle emission inventory. A representative operating cycle for buses within the station is constructed. The emission inventory was then estimated using detailed inputs including vehicle ages, operating speeds, operating schedules, and operating mode distribution, as well as meteorological data (temperature and humidity). Five functional areas (bus yard, platforms, disembarking area, bus travel routes within the station, and bus entrance/exit routes) at the terminal were identified, and the bus operation cycle was established using the micro-trip cycle construction method. Results of our case study showed that switching to compressed natural gas (CNG) from diesel fuel could reduce PM2.5 and CO emissions by 85.64 and 6.21 %, respectively, in the microenvironment of the bus terminal. When CNG is used, tail pipe exhaust PM2.5 emission is significantly reduced, even less than brake wear PM2.5. The estimated bus operating cycles can also offer researchers and policy makers important information for emission evaluation in the planning and design of any typical intercity bus terminals of a similar scale.

Satellite Mapping of Rain-Induced Nitric Oxide Emissions from Soils

NASA Technical Reports Server (NTRS)

Jaegle, L.; Martin, R. V.; Chance, K.; Steinberger, L.; Kurosu, T. P.; Jacob, D. J.; Modi, A. I.; Yoboue, V.; Sigha-Nkamdjou, L.; Galy-Lacaux, C.

2004-01-01

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to map the spatial and seasonal variations of NOx emissions over Africa during 2000. The GOME observations show not only enhanced tropospheric NO2 columns from biomass burning during the dry season but also comparable enhancements from soil emissions during the rainy season over the Sahel. These soil emissions occur in strong pulses lasting 1-3 weeks following the onset of rain, and affect 3 million sq km of semiarid sub-Saharan savanna. Surface observations of NO2 from the International Global Atmospheric Chemistry (IGAC)/Deposition of Biochemically Important Trace Species (DEBITS)/Africa (IDAF) network over West Africa provide further evidence for a strong role for microbial soil sources. By combining inverse modeling of GOME NO2 columns with space-based observations of fires, we estimate that soils contribute 3.3+/-1.8 TgN/year, similar to the biomass burning source (3.8+/-2.1 TgN/year), and thus account for 40% of surface NO(x) emissions over Africa. Extrapolating to all the tropics, we estimate a 7.3 TgN/year biogenic soil source, which is a factor of 2 larger compared to model-based inventories but agrees with observation-based inventories. These large soil NO(x) emissions are likely to significantly contribute to the ozone enhancement originating from tropical Africa.

HFC-134a Emissions in China: An Inventory for 1995-2030

NASA Astrophysics Data System (ADS)

Su, Shenshen; Fang, Xuekun; Wu, Jing; Li, Li; Hu, Jianxin; Han, Jiarui

2014-05-01

HFC-134a is the most important substitute of CFC-12 used in the mobile air-conditioner in China since 1995. The bottom-up method was used to estimate HFC-134a emissions in China, from 1995 to 2030, basing on updated automobile industry data and latest emission characters. From 1995, total HFC-134a emission has kept a high growth rate of nearly 60% per year, and reached 16,414.3 Mg (11,959.4-20,834.5 Mg) in 2010, which was equivalent to 23.5 Mt CO2-eq emissions. Furthermore, the emissions in China accounted for nearly half of total emissions of Non-AnnexI countries in 2008. As for provincial emissions in 2010, provinces with emission greater than 1,000 Mg are Guangdong, Shandong, Jiangsu and Beijing. Quantitative relationship between provincial HFC-134a emissions and GRP of the Tertiary Industry was used to estimate HFC-134a emissions at county level, and Hangzhou municipal district held the maximum emission intensity (4,605 Mg/10,000 km2). For HFC-134a, emissions calculated from the observations within 46 cities through Euler box model are in good agreement with the corresponding emissions estimated from the bottom-up method, verifying that the emission inventory at county level adequately describes the emission spatial pattern. For the future emissions of HFC-134a, projected emissions will reach 89,370.4 Mg (65,959.7- 114,068.2 Mg) in 2030 under the Business-as-usual (BAU) Scenario, but under the Alternative Scenario, a emission reduction potential of 88.6% of the projected BAU emissions would be obtained.

EVALUATION OF POLLUTION PREVENTION OPPORTUNITIES FOR MOLD RELEASE AGENTS

EPA Science Inventory

The report gives results of an assessment of the processes, materials, installation practices, and emission characteristics associated with the application of mold release agents (MRAs). Emissions were estimated based on available information on MRA composition and consumption. V...

Agriculture is a major source of NOx pollution in California

PubMed Central

Almaraz, Maya; Bai, Edith; Wang, Chao; Trousdell, Justin; Conley, Stephen; Faloona, Ian; Houlton, Benjamin Z.

2018-01-01

Nitrogen oxides (NOx = NO + NO2) are a primary component of air pollution—a leading cause of premature death in humans and biodiversity declines worldwide. Although regulatory policies in California have successfully limited transportation sources of NOx pollution, several of the United States’ worst–air quality districts remain in rural regions of the state. Site-based findings suggest that NOx emissions from California’s agricultural soils could contribute to air quality issues; however, a statewide estimate is hitherto lacking. We show that agricultural soils are a dominant source of NOx pollution in California, with especially high soil NOx emissions from the state’s Central Valley region. We base our conclusion on two independent approaches: (i) a bottom-up spatial model of soil NOx emissions and (ii) top-down airborne observations of atmospheric NOx concentrations over the San Joaquin Valley. These approaches point to a large, overlooked NOx source from cropland soil, which is estimated to increase the NOx budget by 20 to 51%. These estimates are consistent with previous studies of point-scale measurements of NOx emissions from the soil. Our results highlight opportunities to limit NOx emissions from agriculture by investing in management practices that will bring co-benefits to the economy, ecosystems, and human health in rural areas of California. PMID:29399630

Probabilistic location estimation of acoustic emission sources in isotropic plates with one sensor

NASA Astrophysics Data System (ADS)

Ebrahimkhanlou, Arvin; Salamone, Salvatore

2017-04-01

This paper presents a probabilistic acoustic emission (AE) source localization algorithm for isotropic plate structures. The proposed algorithm requires only one sensor and uniformly monitors the entire area of such plates without any blind zones. In addition, it takes a probabilistic approach and quantifies localization uncertainties. The algorithm combines a modal acoustic emission (MAE) and a reflection-based technique to obtain information pertaining to the location of AE sources. To estimate confidence contours for the location of sources, uncertainties are quantified and propagated through the two techniques. The approach was validated using standard pencil lead break (PLB) tests on an Aluminum plate. The results demonstrate that the proposed source localization algorithm successfully estimates confidence contours for the location of AE sources.

Rising critical emission of air pollutants from renewable biomass based cogeneration from the sugar industry in India

NASA Astrophysics Data System (ADS)

Sahu, S. K.; Ohara, T.; Beig, G.; Kurokawa, J.; Nagashima, T.

2015-09-01

In the recent past, the emerging India economy is highly dependent on conventional as well as renewable energy to deal with energy security. Keeping the potential of biomass and its plentiful availability, the Indian government has been encouraging various industrial sectors to generate their own energy from it. The Indian sugar industry has adopted and made impressive growth in bagasse (a renewable biomass, i.e. left after sugercane is crushed) based cogeneration power to fulfil their energy need, as well as to export a big chunk of energy to grid power. Like fossil fuel, bagasse combustion also generates various critical pollutants. This article provides the first ever estimation, current status and overview of magnitude of air pollutant emissions from rapidly growing bagasse based cogeneration technology in Indian sugar mills. The estimated emission from the world’s second largest sugar industry in India for particulate matter, NOX, SO2, CO and CO2 is estimated to be 444 ± 225 Gg yr-1, 188 ± 95 Gg yr-1, 43 ± 22 Gg yr-1, 463 ± 240 Gg yr-1 and 47.4 ± 9 Tg yr-1, respectively in 2014. The studies also analyze and identify potential hot spot regions across the country and explore the possible further potential growth for this sector. This first ever estimation not only improves the existing national emission inventory, but is also useful in chemical transport modeling studies, as well as for policy makers.

In-Use Emissions and Estimated Impacts of Traditional, Natural- and Forced-Draft Cookstoves in Rural Malawi

PubMed Central

2017-01-01

Emissions from traditional cooking practices in low- and middle-income countries have detrimental health and climate effects; cleaner-burning cookstoves may provide “co-benefits”. Here we assess this potential via in-home measurements of fuel-use and emissions and real-time optical properties of pollutants from traditional and alternative cookstoves in rural Malawi. Alternative cookstove models were distributed by existing initiatives and include a low-cost ceramic model, two forced-draft cookstoves (FDCS; Philips HD4012LS and ACE-1), and three institutional cookstoves. Among household cookstoves, emission factors (EF; g (kg wood)−1) were lowest for the Philips, with statistically significant reductions relative to baseline of 45% and 47% for fine particulate matter (PM2.5) and carbon monoxide (CO), respectively. The Philips was the only cookstove tested that showed significant reductions in elemental carbon (EC) emission rate. Estimated health and climate cobenefits of alternative cookstoves were smaller than predicted from laboratory tests due to the effects of real-world conditions including fuel variability and nonideal operation. For example, estimated daily PM intake and field-measurement-based global warming commitment (GWC) for the Philips FDCS were a factor of 8.6 and 2.8 times higher, respectively, than those based on lab measurements. In-field measurements provide an assessment of alternative cookstoves under real-world conditions and as such likely provide more realistic estimates of their potential health and climate benefits than laboratory tests. PMID:28060518

Aircraft-Based Estimate of Total Methane Emissions from the Barnett Shale Region.

PubMed

Karion, Anna; Sweeney, Colm; Kort, Eric A; Shepson, Paul B; Brewer, Alan; Cambaliza, Maria; Conley, Stephen A; Davis, Ken; Deng, Aijun; Hardesty, Mike; Herndon, Scott C; Lauvaux, Thomas; Lavoie, Tegan; Lyon, David; Newberger, Tim; Pétron, Gabrielle; Rella, Chris; Smith, Mackenzie; Wolter, Sonja; Yacovitch, Tara I; Tans, Pieter

2015-07-07

We present estimates of regional methane (CH4) emissions from oil and natural gas operations in the Barnett Shale, Texas, using airborne atmospheric measurements. Using a mass balance approach on eight different flight days in March and October 2013, the total CH4 emissions for the region are estimated to be 76 ± 13 × 10(3) kg hr(-1) (equivalent to 0.66 ± 0.11 Tg CH4 yr(-1); 95% confidence interval (CI)). We estimate that 60 ± 11 × 10(3) kg CH4 hr(-1) (95% CI) are emitted by natural gas and oil operations, including production, processing, and distribution in the urban areas of Dallas and Fort Worth. This estimate agrees with the U.S. Environmental Protection Agency (EPA) estimate for nationwide CH4 emissions from the natural gas sector when scaled by natural gas production, but it is higher than emissions reported by the EDGAR inventory or by industry to EPA's Greenhouse Gas Reporting Program. This study is the first to show consistency between mass balance results on so many different days and in two different seasons, enabling better quantification of the related uncertainty. The Barnett is one of the largest production basins in the United States, with 8% of total U.S. natural gas production, and thus, our results represent a crucial step toward determining the greenhouse gas footprint of U.S. onshore natural gas production.

An algorithm to estimate aircraft cruise black carbon emissions for use in developing a cruise emissions inventory.

PubMed

Peck, Jay; Oluwole, Oluwayemisi O; Wong, Hsi-Wu; Miake-Lye, Richard C

2013-03-01

To provide accurate input parameters to the large-scale global climate simulation models, an algorithm was developed to estimate the black carbon (BC) mass emission index for engines in the commercial fleet at cruise. Using a high-dimensional model representation (HDMR) global sensitivity analysis, relevant engine specification/operation parameters were ranked, and the most important parameters were selected. Simple algebraic formulas were then constructed based on those important parameters. The algorithm takes the cruise power (alternatively, fuel flow rate), altitude, and Mach number as inputs, and calculates BC emission index for a given engine/airframe combination using the engine property parameters, such as the smoke number, available in the International Civil Aviation Organization (ICAO) engine certification databank. The algorithm can be interfaced with state-of-the-art aircraft emissions inventory development tools, and will greatly improve the global climate simulations that currently use a single fleet average value for all airplanes. An algorithm to estimate the cruise condition black carbon emission index for commercial aircraft engines was developed. Using the ICAO certification data, the algorithm can evaluate the black carbon emission at given cruise altitude and speed.

Sensitivity of terrestrial N2O emission to atmospheric nitrogen deposition

NASA Astrophysics Data System (ADS)

Ito, A.; Sudo, K.; Nishina, K.; Ishijima, K.; Inatomi, M. I.

2015-12-01

Terrestrial N2O emission is generated from several nitrogen sources including biological fixation, agricultural fertilizer, and atmospheric deposition. There remain large uncertainties how much N2O is produced from atmospheric deposition. This is a crosscutting issue between global warming and atmospheric pollution. In this study, we assessed the sensitivity of global terrestrial N2O emission to atmospheric deposition, using a process-based model VISIT. In the model, N2O emission is estimated separately for nitrification and denitrfication with the NGAS parameterization. The global simulations were conducted from 1901 to 2014 at spatial resolution of 0.5 degree. Atmospheric deposition of ammonium, NOy, and organic nitrogen simulated by the atmospheric chemistry model CHASER from the pre-industrial time to the present was used. Annual total nitrogen deposition was estimated to increase from 27 Tg N in 1901 to 77 Tg N in 2014. The total N2O emission was also estimated to increase in the period, but it was largely attributable to the increased emission from croplands. We need further investigations for the N2O emission from natural soils, which may be nitrogen-limited.

Large CO 2 effluxes at night and during synoptic weather events significantly contribute to CO 2 emissions from a reservoir

DOE PAGES

Liu, Heping; Zhang, Qianyu; Katul, Gabriel G.; ...

2016-05-24

CO 2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collected during the day in fair weather throughout the course of a year. Direct measurements of eddy covariance CO 2 fluxes from a large inland water body (Ross Barnett reservoir, Mississippi, USA) show that CO 2 effluxes at night are approximately 70% greater than those during the day. At longer time scales, frequent synoptic weather eventsmore » associated with extratropical cyclones induce CO 2 flux pulses, resulting in further increase in annual CO 2 effluxes by 16%. Therefore, CO 2 emission rates from this reservoir, if these diel and synoptic processes are under-sampled, are likely to be underestimated by approximately 40%. Our results also indicate that the CO 2 emission rates from global inland waters reported in the literature, when based on indirect methods, are likely underestimated. Field samplings and indirect modeling frameworks that estimate CO 2 emissions should account for both daytime-nighttime efflux difference and enhanced emissions during synoptic weather events. Furthermore, the analysis here can guide carbon emission sampling to improve regional carbon estimates.« less

Large CO 2 effluxes at night and during synoptic weather events significantly contribute to CO 2 emissions from a reservoir

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Heping; Zhang, Qianyu; Katul, Gabriel G.

CO 2 emissions from inland waters are commonly determined by indirect methods that are based on the product of a gas transfer coefficient and the concentration gradient at the air water interface (e.g., wind-based gas transfer models). The measurements of concentration gradient are typically collected during the day in fair weather throughout the course of a year. Direct measurements of eddy covariance CO 2 fluxes from a large inland water body (Ross Barnett reservoir, Mississippi, USA) show that CO 2 effluxes at night are approximately 70% greater than those during the day. At longer time scales, frequent synoptic weather eventsmore » associated with extratropical cyclones induce CO 2 flux pulses, resulting in further increase in annual CO 2 effluxes by 16%. Therefore, CO 2 emission rates from this reservoir, if these diel and synoptic processes are under-sampled, are likely to be underestimated by approximately 40%. Our results also indicate that the CO 2 emission rates from global inland waters reported in the literature, when based on indirect methods, are likely underestimated. Field samplings and indirect modeling frameworks that estimate CO 2 emissions should account for both daytime-nighttime efflux difference and enhanced emissions during synoptic weather events. Furthermore, the analysis here can guide carbon emission sampling to improve regional carbon estimates.« less

Estimation of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem in China using real-time remote sensing data

NASA Astrophysics Data System (ADS)

Li, M.; Huang, X.; Li, J.; Song, Y.

2012-03-01

Because of the high emission rate and reactivity, biogenic volatile organic compounds (BVOCs) play a significant role in the terrestrial ecosystems, human health, secondary pollution, global climate change and the global carbon cycle. Past estimations of BVOC emissions in China were based on outdated algorithms and coarsely resolved meteorological data, and there have been significant inconsistences between the land surface parameters of dynamic models and those of BVOC estimation models, leading to large inaccuracies in the estimated results. To refine BVOC emission estimations for China and to further explore the role of BVOCs in the atmosphere, we used the latest algorithms of MEGAN (Model of Emissions of Gases and Aerosols from Nature), with MM5 (the Fifth-Generation Mesoscale Model) providing highly resolved meteorological data, to estimate the biogenic emissions of isoprene (C5H8) and seven monoterpene species (C10H16) in 2006. Real-time MODIS (Moderate Resolution Imaging Spectroradiometer) data were introduced to update the land surface parameters and to improve the simulation performance of MM5, and to determine the influence of leaf area index (LAI) and leaf age deviation from standard conditions. In this study, the annual BVOC emissions for the whole country totaled 12.97 Tg C, a relevant value compared with past studies. Therein, the most important individual contributor was isoprene (9.36 Tg C yr-1), followed by α-pinene (1.24 Tg C yr-1) and β-pinene (0.84 Tg C yr-1). Due to the considerable regional disparity in plant distributions and meteorological conditions across China, BVOC emissions presented significant spatial and temporal variations. Spatially, isoprene emission was concentrated in South China, which is covered by large areas of broadleaf forests and shrubs. While Southeast China was the top-ranking contributor of monoterpenes, in which the dominant vegetation genera consist of evergreen coniferous forests. Temporally, BVOC emissions primarily occurred in July and August, with daily emissions peaking at about 13:00∼14:00 h (Beijing Time, BJT). In this study, we present an improved estimation of BVOC emissions, which provides important information for further exploration of the role of BVOCs in atmospheric processes.

Estimation of the emission factors of PAHs by traffic with the model of atmospheric dispersion and deposition from heavy traffic road.

PubMed

Ozaki, N; Tokumitsu, H; Kojima, K; Kindaichi, T

2007-01-01

In order to consider the total atmospheric loadings of the PAHs (polycyclic aromatic hydrocarbons) from traffic activities, the emission factors of PAHs were estimated and from the obtained emission factors and vehicle transportation statistics, total atmospheric loadings were integrated and the loadings into the water body were estimated on a regional scale. The atmospheric concentration of PAHs was measured at the roadside of a road with heavy traffic in the Hiroshima area in Japan. The samplings were conducted in summer and winter. Atmospheric particulate matters (fine particle, 0.6-7 microm; coarse particle, over 7 microm) and their PAH concentration were measured. Also, four major emission sources (gasoline and diesel vehicle emissions, tire and asphalt debris) were assumed for vehicle transportation activities, the chemical mass balance method was applied and the source partitioning at the roadside was estimated. Furthermore, the dispersion of atmospheric particles from the vehicles was modelled and the emission factors of the sources were determined by the comparison to the chemical mass balance results. Based on emission factors derived from the modelling, an atmospheric dispersion model of nationwide scale (National Institute of Advanced Industrial Science and Technology - Atmospheric Dispersion Model for Exposure and Risk assessment) was applied, and the atmospheric concentration and loading to the ground were calculated for the Hiroshima Bay watershed area.

Au-nanocluster emission based glucose sensing.

PubMed

Hussain, A M P; Sarangi, S N; Kesarwani, J A; Sahu, S N

2011-11-15

Fabrication of a glucose biosensor based on Au-cluster emission quenching in the UV region is reported. The glucose biosensor is highly sensitive to β-d-glucose in 2.5-25.0mM range as confirmed from a linear calibration plot between Au-cluster colloid emission intensity as a function of β-d-glucose concentration. The interaction of β-d-glucose with l-cysteine capped Au cluster colloids has been confirmed from their Fourier transformed infrared spectroscopy (FTIR) measurements. It has been found that the biomolecules present in the serum such as ascorbic and uric acids, proteins and peptides do not interfere and affect in glucose estimation as confirmed from their absorption and fluorescence (FL) emission measurements. Practical utility of this sensor based on FL quenching method has been demonstrated by estimating the glucose level in human serum that includes diabetes and the data were found to be comparable or more accurate than those of the pathological data obtained from a local hospital. In addition, this biosensor is useful to detect glucose level over a wide range with sensor response time of the order of nano to picoseconds that is emission lifetime of Au clusters. Copyright © 2011 Elsevier B.V. All rights reserved.

Emission-factor uncertainties in maritime transport in the Strait of Gibraltar, Spain

NASA Astrophysics Data System (ADS)

Moreno-Gutiérrez, J.; Durán-Grados, V.; Uriondo, Z.; Ángel Llamas, J.

2012-08-01

A reliable and up-to-date maritime emission inventory is essential for atmospheric scientists quantifying the impact of shipping. The objective of this study is to estimate the atmospheric emissions of SO2, NOx, CO2 and PM10 by international merchant shipping in 2007 in the Strait of Gibraltar, Spain, including the Algeciras Bay by two methods. Two methods (both bottom-up) have been used in this study: 1. Establishing engine power-based emission factors (g kWh-1, EPA) or the mass of pollutant per work performed by the engine for each of the relevant components of the exhaust gas from diesel engines and power for each ship. 2. Establishing fuel-based emission factors (kg emitted/t of fuel) or mass of pollutant per mass of combusted fuel for each of the relevant components of the exhaust gas and a fuel-consumption inventory (IMO). In both methods, the means to estimate engine power and fuel-consumption inventories are the same. The exhaust from boilers and incinerators is regarded as a small contributor and excluded. In total, an estimated average of 1 389 111.05 t of CO2, 23 083.09 t of SO2, 32 005.63 t of NOx and 2972 t of PM10 were emitted from January 2007 until December 2007 by international and domestic shipping. The estimated total fuel consumption amounts to 437 405.84 t. The major differences between the estimates generated by the two methods are for NOx (16% in certain cases) and CO (up to 23%). A total difference for all compounds of 3038 t (approximately 2%) has been found between the two methods but it is not areasonable estimate of uncertainty. Therefore, the results for both methods may be considered acceptable because the actual uncontrolled deviations appear in the changes in emission factors that occur for a given engine with age. These deviations are often difficult to quantify and depend on individual shipboard service and maintenance routines. Emission factors for CO and NOx are not constant and depend on engine condition. For example, tests conducted by the authors of this paper demonstrate that when an engine operates under normal in-service conditions, the emissions are within limits. However, with a small fault in injection timing, the NOx emission exceeds the limits (30% higher value in some cases). A fault in the maintenance of the injection nozzles increases the CO emission (15% higher value in some cases).

Emission of polybrominated diphenyl ethers (PBDEs) in use of electric/electronic equipment and recycling of e-waste in Korea.

PubMed

Park, Jong-Eun; Kang, Young-Yeul; Kim, Woo-Il; Jeon, Tae-Wan; Shin, Sun-Kyoung; Jeong, Mi-Jeong; Kim, Jong-Guk

2014-02-01

The emission rates of polybrominated diphenyl ethers (PBDEs) from electric/electronic products during their use and disposal were estimated. E-wastes, including televisions and refrigerators, gathered at recycling centers were also analyzed to estimate their emissions. The average concentrations of PBDEs in TV rear covers produced before and after the year 2000 were 145,027 mg/kg and 14,049 mg/kg, respectively. The PBDEs concentration in TV front covers was lower than the concentration in TV rear covers. The concentration in the components of the refrigerator samples ranged from ND to 445 mg/kg. We estimated the atmospheric emissions of PBDEs based on the concentrations. The annual emissions from TV rear covers produced before 2000 were calculated to be approximately 162.1 kg and after 2000, the annual emissions were 18.7 kg. Refrigerators showed the lowest annual emissions of PBDEs (0.7 kg). The atmospheric concentrations were also measured to calculate emissions generated during the recycling process. The highest concentration was 16.86 ng/m(3) emitted from the TV sets during the dismantling process. The concentrations of PBDEs generated in the plastic processing field ranged from 2.05 to 5.43 ng/m(3) depending on the products, and ambient air in open-air yards showed concentrations in the range of 0.32 to 5.55 ng/m(3). Emission factors for the recycling process were calculated using the observed concentrations. The estimated emissions according to the emission factors ranged from 0.3×10(-1) to 90.3 kg/year for open-air yards and from 0.1×10(-1) to 292.7 kg/year for the dismantling and crushing processes of TV set, depending on the production year. © 2013 Elsevier B.V. All rights reserved.

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, Zeli; Zhuang, Qianlai; Henze, Daven K.

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range ofmore » 496.4–511.5 Tg yr −1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr −1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr −1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.« less

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

DOE PAGES

Tan, Zeli; Zhuang, Qianlai; Henze, Daven K.; ...

2016-10-12

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range ofmore » 496.4–511.5 Tg yr −1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr −1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr −1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.« less

Modelling coronal electron density and temperature profiles of the Active Region NOAA 11855

NASA Astrophysics Data System (ADS)

Rodríguez Gómez, J. M.; Antunes Vieira, L. E.; Dal Lago, A.; Palacios, J.; Balmaceda, L. A.; Stekel, T.

2017-10-01

The magnetic flux emergence can help understand the physical mechanism responsible for solar atmospheric phenomena. Emerging magnetic flux is frequently related to eruptive events, because when emerging they can reconnected with the ambient field and release magnetic energy. We will use a physic-based model to reconstruct the evolution of the solar emission based on the configuration of the photospheric magnetic field. The structure of the coronal magnetic field is estimated by employing force-free extrapolation NLFFF based on vector magnetic field products (SHARPS) observed by HMI instrument aboard SDO spacecraft from Sept. 29 (2013) to Oct. 07 (2013). The coronal plasma temperature and density are described and the emission is estimated using the CHIANTI atomic database 8.0. The performance of the our model is compared to the integrated emission from the AIA instrument aboard SDO spacecraft in the specific wavelengths 171Å and 304Å.

2004 Methane and Nitrous Oxide Emissions from Manure Management in South Africa

PubMed Central

Moeletsi, Mokhele Edmond; Tongwane, Mphethe Isaac

2015-01-01

Simple Summary Livestock manure management is one of the main sources of greenhouse gas (GHG) emissions in South Africa producing mainly methane and nitrous oxide. The emissions from this sub-category are dependent on how manure is stored. Liquid-stored manure predominantly produces methane while dry-based manure enhances mainly production of nitrous oxide. Intergovernmental Panel on Climate Change (IPCC) guidelines were utilized at different tier levels in estimating GHG emissions from manure management. The results show that methane emissions are relatively higher than nitrous oxide emissions with 3104 Gg and 2272 Gg respectively in carbon dioxide global warming equivalent. Abstract Manure management in livestock makes a significant contribution towards greenhouse gas emissions in the Agriculture; Forestry and Other Land Use category in South Africa. Methane and nitrous oxide emissions are prevalent in contrasting manure management systems; promoting anaerobic and aerobic conditions respectively. In this paper; both Tier 1 and modified Tier 2 approaches of the IPCC guidelines are utilized to estimate the emissions from South African livestock manure management. Activity data (animal population, animal weights, manure management systems, etc.) were sourced from various resources for estimation of both emissions factors and emissions of methane and nitrous oxide. The results show relatively high methane emissions factors from manure management for mature female dairy cattle (40.98 kg/year/animal), sows (25.23 kg/year/animal) and boars (25.23 kg/year/animal). Hence, contributions for pig farming and dairy cattle are the highest at 54.50 Gg and 32.01 Gg respectively, with total emissions of 134.97 Gg (3104 Gg CO2 Equivalent). Total nitrous oxide emissions are estimated at 7.10 Gg (2272 Gg CO2 Equivalent) and the three main contributors are commercial beef cattle; poultry and small-scale beef farming at 1.80 Gg; 1.72 Gg and 1.69 Gg respectively. Mitigation options from manure management must be taken with care due to divergent conducive requirements of methane and nitrous oxide emissions requirements. PMID:26479229

Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin

DOE PAGES

Cui, Yu Yan; Brioude, Jerome; McKeen, Stuart A.; ...

2015-07-28

Methane (CH 4) is the primary component of natural gas and has a larger global warming potential than CO 2. Some recent top-down studies based on observations showed CH 4 emissions in California's South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH 4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use themore » FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH 4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency's National Emission Inventory 2005, R 2 = 0.5). The emission estimates for CH 4 in the posterior, 46.3 ± 9.2 Mg CH 4/h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH 4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. Furthermore, we estimate that dairies contributed 5.9 ± 1.7 Mg CH 4/h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1 Mg CH 4/h in the SoCAB.« less

Delay correction model for estimating bus emissions at signalized intersections based on vehicle specific power distributions.

PubMed

Song, Guohua; Zhou, Xixi; Yu, Lei

2015-05-01

The intersection is one of the biggest emission points for buses and also the high exposure site for people. Several traffic performance indexes have been developed and widely used for intersection evaluations. However, few studies have focused on the relationship between these indexes and emissions at intersections. This paper intends to propose a model that relates emissions to the two commonly used measures of effectiveness (i.e. delay time and number of stops) by using bus activity data and emission data at intersections. First, with a large number of field instantaneous emission data and corresponding activity data collected by the Portable Emission Measurement System (PEMS), emission rates are derived for different vehicle specific power (VSP) bins. Then, 2002 sets of trajectory data, an equivalent of about 140,000 sets of second-by-second activity data, are obtained from Global Position Systems (GPSs)-equipped diesel buses in Beijing. The delay and the emission factors of each trajectory are estimated. Then, by using baseline emission factors for two types of intersections, e.g. the Arterial @ Arterial Intersection and the Arterial @ Collector, delay correction factors are calculated for the two types of intersections at different congestion levels. Finally, delay correction models are established for adjusting emission factors for each type of intersections and different numbers of stops. A comparative analysis between estimated and field emission factors demonstrates that the delay correction model is reliable. Copyright © 2015 Elsevier B.V. All rights reserved.

Emission factors of air toxics from semiconductor manufacturing in Korea.

PubMed

Eom, Yun-Sung; Hong, Ji-Hyung; Lee, Suk-Jo; Lee, Eun-Jung; Cha, Jun-Seok; Lee, Dae-Gyun; Bang, Sun-Ae

2006-11-01

The development of local, accurate emission factors is very important for the estimation of reliable national emissions and air quality management. For that, this study is performed for pollutants released to the atmosphere with source-specific emission tests from the semiconductor manufacturing industry. The semiconductor manufacturing industry is one of the major sources of air toxics or hazardous air pollutants (HAPs); thus, understanding the emission characteristics of the emission source is a very important factor in the development of a control strategy. However, in Korea, there is a general lack of information available on air emissions from the semiconductor industry. The major emission sources of air toxics examined from the semiconductor manufacturing industry were wet chemical stations, coating applications, gaseous operations, photolithography, and miscellaneous devices in the wafer fabrication and semiconductor packaging processes. In this study, analyses of emission characteristics, and the estimations of emission data and factors for air toxics, such as acids, bases, heavy metals, and volatile organic compounds from the semiconductor manufacturing process have been performed. The concentration of hydrogen chloride from the packaging process was the highest among all of the processes. In addition, the emission factor of total volatile organic compounds (TVOCs) for the packaging process was higher than that of the wafer fabrication process. Emission factors estimated in this study were compared with those of Taiwan for evaluation, and they were found to be of similar level in the case of TVOCs and fluorine compounds.

Comparison and evaluation of anthropogenic emissions of SO2 and NOx over China

NASA Astrophysics Data System (ADS)

Li, Meng; Klimont, Zbigniew; Zhang, Qiang; Martin, Randall V.; Zheng, Bo; Heyes, Chris; Cofala, Janusz; Zhang, Yuxuan; He, Kebin

2018-03-01

Bottom-up emission inventories provide primary understanding of sources of air pollution and essential input of chemical transport models. Focusing on SO2 and NOx, we conducted a comprehensive evaluation of two widely used anthropogenic emission inventories over China, ECLIPSE and MIX, to explore the potential sources of uncertainties and find clues to improve emission inventories. We first compared the activity rates and emission factors used in two inventories and investigated the reasons of differences and the impacts on emission estimates. We found that SO2 emission estimates are consistent between two inventories (with 1 % differences), while NOx emissions in ECLIPSE's estimates are 16 % lower than those of MIX. The FGD (flue-gas desulfurization) device penetration rate and removal efficiency, LNB (low-NOx burner) application rate and abatement efficiency in power plants, emission factors of industrial boilers and various vehicle types, and vehicle fleet need further verification. Diesel consumptions are quite uncertain in current inventories. Discrepancies at the sectorial and provincial levels are much higher than those of the national total. We then examined the impacts of different inventories on model performance by using the nested GEOS-Chem model. We finally derived top-down emissions by using the retrieved columns from the Ozone Monitoring Instrument (OMI) compared with the bottom-up estimates. High correlations were observed for SO2 between model results and OMI columns. For NOx, negative biases in bottom-up gridded emission inventories (-21 % for MIX, -39 % for ECLIPSE) were found compared to the satellite-based emissions. The emission trends from 2005 to 2010 estimated by two inventories were both consistent with satellite observations. The inventories appear to be fit for evaluation of the policies at an aggregated or national level; more work is needed in specific areas in order to improve the accuracy and robustness of outcomes at finer spatial and also technological levels. To our knowledge, this is the first work in which source comparisons detailed to technology-level parameters are made along with the remote sensing retrievals and chemical transport modeling. Through the comparison between bottom-up emission inventories and evaluation with top-down information, we identified potential directions for further improvement in inventory development.

Regional modeling of tropospheric NO2 vertical column density over East Asia during the period 2000-2010: comparison with multisatellite observations

NASA Astrophysics Data System (ADS)

Itahashi, S.; Uno, I.; Irie, H.; Kurokawa, J.-I.; Ohara, T.

2014-04-01

Satellite observations of the tropospheric NO2 vertical column density (VCD) are closely correlated to, and thus can be used to estimate, surface NOx emissions. In this study, the NO2 VCD simulated by a regional chemical transport model with emissions data from the updated Regional Emission inventory in ASia (REAS) version 2.1 were validated through comparison with multisatellite observations during the period 2000-2010. Rapid growth in NO2 VCD (~11% year-1) driven by the expansion of anthropogenic NOx emissions was identified above the central eastern China (CEC) region, except for the period during the economic downturn. In contrast, slightly decreasing trends (~2% year-1) were identified above Japan accompanied by a decline in anthropogenic emissions. To systematically compare the modeled NO2 VCD, we estimated sampling bias and the effect of applying the averaging kernel information, with particular focus on the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. Using the updated REAS, the modeled NO2 VCD reasonably reproduced annual trends observed by multisatellites, suggesting that the rate of increase of NOx emissions estimated by the updated REAS inventory would be robust. Province-scale revision of emissions above CEC is needed to further refine emission inventories. Based on the close linear relationship between modeled and observed NO2 VCD and anthropogenic NOx emissions, NOx emissions in 2009 and 2010, which were not covered by the updated REAS inventory, were estimated. NOx emissions from anthropogenic sources in China in 2009 and 2010 were determined to be 26.4 and 28.5 Tg year-1, respectively, indicating that NOx emissions increased more than twofold between 2000 and 2010. This increase reflected the strong growth of anthropogenic emissions in China following the rapid recovery from the economic downturn from late 2008 until mid-2009. Our method consists of simple estimations from satellite observations and provides results that are consistent with the most recent inventory of emissions data for China.

Estimating 20-year land-use change and derived CO2 emissions associated with crops, pasture and forestry in Brazil and each of its 27 states.

PubMed

Novaes, Renan M L; Pazianotto, Ricardo A A; Brandão, Miguel; Alves, Bruno J R; May, André; Folegatti-Matsuura, Marília I S

2017-09-01

Land-use change (LUC) in Brazil has important implications on global climate change, ecosystem services and biodiversity, and agricultural expansion plays a critical role in this process. Concerns over these issues have led to the need for estimating the magnitude and impacts associated with that, which are increasingly reported in the environmental assessment of products. Currently, there is an extensive debate on which methods are more appropriate for estimating LUC and related emissions and regionalized estimates are lacking for Brazil, which is a world leader in agricultural production (e.g. food, fibres and bioenergy). We developed a method for estimating scenarios of past 20-year LUC and derived CO 2 emission rates associated with 64 crops, pasture and forestry in Brazil as whole and in each of its 27 states, based on time-series statistics and in accordance with most used carbon-footprinting standards. The scenarios adopted provide a range between minimum and maximum rates of CO 2 emissions from LUC according to different possibilities of land-use transitions, which can have large impacts in the results. Specificities of Brazil, like multiple cropping and highly heterogeneous carbon stocks, are also addressed. The highest CO 2 emission rates are observed in the Amazon biome states and crops with the highest rates are those that have undergone expansion in this region. Some states and crops showing large agricultural areas have low emissions associated, especially in southern and eastern Brazil. Native carbon stocks and time of agricultural expansion are the most decisive factors to the patterns of emissions. Some implications on LUC estimation methods and standards and on agri-environmental policies are discussed. © 2017 John Wiley & Sons Ltd.

Estimation of refueling emissions based on theoretical model and effects of E10 fuel on refueling and evaporative emissions from gasoline cars.

PubMed

Yamada, Hiroyuki; Inomata, Satoshi; Tanimoto, Hiroshi; Hata, Hiroo; Tonokura, Kenichi

2018-05-01

The effects of Reid vapor pressure (RVP) on refueling emissions and the effects of ethanol 10% (E10) fuel on refueling and evaporative emissions were observed using six cars and seven fuels. The results indicated that refueling emissions can be reproduced by a simple theoretical model in which fuel vapor in the empty space in the tank is pushed out by the refueling process. In this model, the vapor pressures of fuels can be estimated by the Clausius-Clapeyron equation as a function of temperature. We also evaluated E10 fuel in terms of refueling and evaporative emissions, excluding the effect of contamination of ethanol in the canister. E10 fuel had no effect on the refueling emissions in cases without onboard refueling vapor recovery. E10 showed increased permeation emissions in evaporative emissions because of the high permeability of ethanol. And with E10 fuel, breakthrough emissions appeared earlier but broke through slower than normal fuel. Finally, canisters could store more fuel vapor with E10 fuel. Copyright © 2017 Elsevier B.V. All rights reserved.

Transport of Cs-137 from Boreal Biomass Burning in Summer of 2010

NASA Technical Reports Server (NTRS)

Strode, Sarah; Ott, Lesley; Nielsen, Eric; Pawson, Steven

2010-01-01

The summer of 2010 was a severe fire season in western Russia. Wildfires were detected in the Bryansk region, raising concerns that radionuclide contamination from the Chernobyl accident could be resuspended in the atmosphere. We simulate the transport of passive and particulate tracers of biomass burning from this region using the GEOS5 GOCART model driven by assimilated meteorology. Biomass burning emissions are based on MODIS fire detections. We validate the model against aerosol optical depth from MODIS. Using a range of estimates for Cs-137 emissions during wildfires, we estimate the downwind concentration and deposition of Cs-137 based on the emission ratios of Cs-137 to the simulated tracers. We discuss the sensitivity of our results to the location of the fires and the fraction of Cs-137 resuspended.

Determining Source Strength of Semivolatile Organic Compounds using Measured Concentrations in Indoor Dust

PubMed Central

Shin, Hyeong-Moo; McKone, Thomas E.; Nishioka, Marcia G.; Fallin, M. Daniele; Croen, Lisa A.; Hertz-Picciotto, Irva; Newschaffer, Craig J.; Bennett, Deborah H.

2014-01-01

Consumer products and building materials emit a number of semivolatile organic compounds (SVOCs) in the indoor environment. Because indoor SVOCs accumulate in dust, we explore the use of dust to determine source strength and report here on analysis of dust samples collected in 30 U.S. homes for six phthalates, four personal care product ingredients, and five flame retardants. We then use a fugacity-based indoor mass-balance model to estimate the whole house emission rates of SVOCs that would account for the measured dust concentrations. Di-2-ethylhexyl phthalate (DEHP) and di-iso-nonyl phthalate (DiNP) were the most abundant compounds in these dust samples. On the other hand, the estimated emission rate of diethyl phthalate (DEP) is the largest among phthalates, although its dust concentration is over two orders of magnitude smaller than DEHP and DiNP. The magnitude of the estimated emission rate that corresponds to the measured dust concentration is found to be inversely correlated with the vapor pressure of the compound, indicating that dust concentrations alone cannot be used to determine which compounds have the greatest emission rates. The combined dust-assay modeling approach shows promise for estimating indoor emission rates for SVOCs. PMID:24118221

General circulation model response to production-limited fossil fuel emission estimates.

NASA Astrophysics Data System (ADS)

Bowman, K. W.; Rutledge, D.; Miller, C.

2008-12-01

The differences in emissions scenarios used to drive IPCC climate projections are the largest sources of uncertainty in future temperature predictions. These estimates are critically dependent on oil, gas, and coal production where the extremal variations in fossil fuel production used in these scenarios is roughly 10:1 after 2100. The development of emission scenarios based on production-limited fossil fuel estimates, i.e., total fossil fuel reserves can be reliably predicted from cumulative production, offers the opportunity to significantly reduce this uncertainty. We present preliminary results of the response of the NASA GISS atmospheric general circulation model to input forcings constrained by production-limited cumulative future fossil-fuel CO2 emissions estimates that reach roughly 500 GtC by 2100, which is significantly lower than any of the IPCC emission scenarios. For climate projections performed from 1958 through 2400 and a climate sensitivity of 5C/2xCO2, the change in globally averaged annual mean temperature relative to fixed CO2 does not exceed 3C with most changes occurring at high latitudes. We find that from 2100-2400 other input forcings such as increased in N2O play an important role in maintaining increase surface temperatures.

Uncertainties of fluxes and 13C / 12C ratios of atmospheric reactive-gas emissions

NASA Astrophysics Data System (ADS)

Gromov, Sergey; Brenninkmeijer, Carl A. M.; Jöckel, Patrick

2017-07-01

We provide a comprehensive review of the proxy data on the 13C / 12C ratios and uncertainties of emissions of reactive carbonaceous compounds into the atmosphere, with a focus on CO sources. Based on an evaluated set-up of the EMAC model, we derive the isotope-resolved data set of its emission inventory for the 1997-2005 period. Additionally, we revisit the calculus required for the correct derivation of uncertainties associated with isotope ratios of emission fluxes. The resulting δ13C of overall surface CO emission in 2000 of -(25. 2 ± 0. 7) ‰ is in line with previous bottom-up estimates and is less uncertain by a factor of 2. In contrast to this, we find that uncertainties of the respective inverse modelling estimates may be substantially larger due to the correlated nature of their derivation. We reckon the δ13C values of surface emissions of higher hydrocarbons to be within -24 to -27 ‰ (uncertainty typically below ±1 ‰), with an exception of isoprene and methanol emissions being close to -30 and -60 ‰, respectively. The isotope signature of ethane surface emission coincides with earlier estimates, but integrates very different source inputs. δ13C values are reported relative to V-PDB.

Greenhouse gas emissions and carbon sequestration by agroforestry systems in southeastern Brazil.

PubMed

Torres, Carlos Moreira Miquelino Eleto; Jacovine, Laércio Antônio Gonçalves; Nolasco de Olivera Neto, Sílvio; Fraisse, Clyde William; Soares, Carlos Pedro Boechat; de Castro Neto, Fernando; Ferreira, Lino Roberto; Zanuncio, José Cola; Lemes, Pedro Guilherme

2017-12-01

Agrosilvopastoral and silvopastoral systems can increase carbon sequestration, offset greenhouse gas (GHG) emissions and reduce the carbon footprint generated by animal production. The objective of this study was to estimate GHG emissions, the tree and grass aboveground biomass production and carbon storage in different agrosilvopastoral and silvopastoral systems in southeastern Brazil. The number of trees required to offset these emissions were also estimated. The GHG emissions were calculated based on pre-farm (e.g. agrochemical production, storage, and transportation), and on-farm activities (e.g. fertilization and machinery operation). Aboveground tree grass biomass and carbon storage in all systems was estimated with allometric equations. GHG emissions from the agroforestry systems ranged from 2.81 to 7.98 t CO 2 e ha -1 . Carbon storage in the aboveground trees and grass biomass were 54.6, 11.4, 25.7 and 5.9 t C ha -1 , and 3.3, 3.6, 3.8 and 3.3 t C ha -1 for systems 1, 2, 3 and 4, respectively. The number of trees necessary to offset the emissions ranged from 17 to 44 trees ha -1 , which was lower than the total planted in the systems. Agroforestry systems sequester CO 2 from the atmosphere and can help the GHG emission-reduction policy of the Brazilian government.

Direct measurements show decreasing methane emissions from natural gas local distribution systems in the United States.

PubMed

Lamb, Brian K; Edburg, Steven L; Ferrara, Thomas W; Howard, Touché; Harrison, Matthew R; Kolb, Charles E; Townsend-Small, Amy; Dyck, Wesley; Possolo, Antonio; Whetstone, James R

2015-04-21

Fugitive losses from natural gas distribution systems are a significant source of anthropogenic methane. Here, we report on a national sampling program to measure methane emissions from 13 urban distribution systems across the U.S. Emission factors were derived from direct measurements at 230 underground pipeline leaks and 229 metering and regulating facilities using stratified random sampling. When these new emission factors are combined with estimates for customer meters, maintenance, and upsets, and current pipeline miles and numbers of facilities, the total estimate is 393 Gg/yr with a 95% upper confidence limit of 854 Gg/yr (0.10% to 0.22% of the methane delivered nationwide). This fraction includes emissions from city gates to the customer meter, but does not include other urban sources or those downstream of customer meters. The upper confidence limit accounts for the skewed distribution of measurements, where a few large emitters accounted for most of the emissions. This emission estimate is 36% to 70% less than the 2011 EPA inventory, (based largely on 1990s emission data), and reflects significant upgrades at metering and regulating stations, improvements in leak detection and maintenance activities, as well as potential effects from differences in methodologies between the two studies.

A Nonlinear Regression Model Estimating Single Source Concentrations of Primary and Secondarily Formed 2.5

EPA Science Inventory

Various approaches and tools exist to estimate local and regional PM_2.5 impacts from a single emissions source, ranging from simple screening techniques to Gaussian based dispersion models and complex grid-based Eulerian photochemical transport models. These approache...

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system.

PubMed

Sun, Kangfeng; Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai; Yang, Shichun

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small.

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system

PubMed Central

Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small. PMID:29408924

Municipal solid waste characterization and its assessment for potential methane generation: a case study.

PubMed

Mor, Suman; Ravindra, Khaiwal; De Visscher, Alex; Dahiya, R P; Chandra, A

2006-12-01

There has been a significant increase in municipal solid waste (MSW) generation in India during the last few decades and its management has become a major issue because the poor waste management practices affect the health and amenity of the cities. In the present study, various physico-chemical parameters of the MSW were analyzed to characterize the waste dumped at Gazipur landfill site in Delhi, India, which shows that it contains a high fraction of degradable organic components. The decomposition of organic components produces methane, a significant contributor to global warming. Based on the waste composition, waste age and the total amount dumped, a first-order decay model (FOD) was applied to estimate the methane generation potential of the Gazipur landfill site, which yields an estimate of 15.3 Gg/year. This value accounts to about 1-3% of existing Indian landfill methane emission estimates. Based on the investigation of Gazipur landfill, we estimate Indian landfill methane emissions at 1.25 Tg/year or 1.68 Tg/year of methane generation potential. These values are within the range of existing estimates. A comparison of FOD with a recently proposed triangular model was also performed and it shows that both models can be used for the estimation of methane generation. However, the decrease of the emission after closure is more gradual in the case of the first-order model, leading to larger gas production predictions after more than 10 years of closure. The regional and global implications of national landfill methane emission are also discussed.

Remotely sensed MODIS wetland components for assessing the variability of methane emissions in Indian tropical/subtropical wetlands

NASA Astrophysics Data System (ADS)

Bansal, Sangeeta; Katyal, Deeksha; Saluja, Ridhi; Chakraborty, Monojit; Garg, J. K.

2018-02-01

Temperature and area fluctuations in wetlands greatly influence its various physico-chemical characteristics, nutrients dynamic, rates of biomass generation and decomposition, floral and faunal composition which in turn influence methane (CH4) emission rates. In view of this, the present study attempts to up-scale point CH4 flux from the wetlands of Uttar Pradesh (UP) by modifying two-factor empirical process based CH4 emission model for tropical wetlands by incorporating MODIS derived wetland components viz. wetland areal extent and corresponding temperature factors (Ft). This study further focuses on the utility of remotely sensed temperature response of CH4 emission in terms of Ft. Ft is generated using MODIS land surface temperature products and provides an important semi-empirical input for up-scaling CH4 emissions in wetlands. Results reveal that annual mean Ft values for UP wetlands vary from 0.69 (2010-2011) to 0.71(2011-2012). The total estimated area-wise CH4 emissions from the wetlands of UP varies from 66.47 Gg yr-1with wetland areal extent and Ft value of 2564.04 km2 and 0.69 respectively in 2010-2011 to 88.39 Gg yr-1with wetland areal extent and Ft value of 2720.16 km2 and 0.71 respectively in 2011-2012. Temporal analysis of estimated CH4 emissions showed that in monsoon season estimated CH4 emissions are more sensitive to wetland areal extent while in summer season sensitivity of estimated CH4 emissions is chiefly controlled by augmented methanogenic activities at high wetland surface temperatures.

Super-emitters in natural gas infrastructure are caused by abnormal process conditions

NASA Astrophysics Data System (ADS)

Zavala-Araiza, Daniel; Alvarez, Ramón A.; Lyon, David R.; Allen, David T.; Marchese, Anthony J.; Zimmerle, Daniel J.; Hamburg, Steven P.

2017-01-01

Effectively mitigating methane emissions from the natural gas supply chain requires addressing the disproportionate influence of high-emitting sources. Here we use a Monte Carlo simulation to aggregate methane emissions from all components on natural gas production sites in the Barnett Shale production region (Texas). Our total emission estimates are two-thirds of those derived from independent site-based measurements. Although some high-emitting operations occur by design (condensate flashing and liquid unloadings), they occur more than an order of magnitude less frequently than required to explain the reported frequency at which high site-based emissions are observed. We conclude that the occurrence of abnormal process conditions (for example, malfunctions upstream of the point of emissions; equipment issues) cause additional emissions that explain the gap between component-based and site-based emissions. Such abnormal conditions can cause a substantial proportion of a site's gas production to be emitted to the atmosphere and are the defining attribute of super-emitting sites.

A sparse reconstruction method for the estimation of multiresolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2014-08-20

We present a sparse reconstruction scheme that can also be used to ensure non-negativity when fitting wavelet-based random field models to limited observations in non-rectangular geometries. The method is relevant when multiresolution fields are estimated using linear inverse problems. Examples include the estimation of emission fields for many anthropogenic pollutants using atmospheric inversion or hydraulic conductivity in aquifers from flow measurements. The scheme is based on three new developments. Firstly, we extend an existing sparse reconstruction method, Stagewise Orthogonal Matching Pursuit (StOMP), to incorporate prior information on the target field. Secondly, we develop an iterative method that uses StOMP tomore » impose non-negativity on the estimated field. Finally, we devise a method, based on compressive sensing, to limit the estimated field within an irregularly shaped domain. We demonstrate the method on the estimation of fossil-fuel CO 2 (ffCO 2) emissions in the lower 48 states of the US. The application uses a recently developed multiresolution random field model and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of two. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Comparison of Landfill Methane Oxidation Measured Using Stable Isotope Analysis and CO2/CH4 Fluxes Measured by the Eddy Covariance Method

NASA Astrophysics Data System (ADS)

Xu, L.; Chanton, J.; McDermitt, D. K.; Li, J.; Green, R. B.

2015-12-01

Methane plays a critical role in the radiation balance and chemistry of the atmosphere. Globally, landfill methane emission contributes about 10-19% of the anthropogenic methane burden into the atmosphere. In the United States, 18% of annual anthropogenic methane emissions come from landfills, which represent the third largest source of anthropogenic methane emissions, behind enteric fermentation and natural gas and oil production. One uncertainty in estimating landfill methane emissions is the fraction of methane oxidized when methane produced under anaerobic conditions passes through the cover soil. We developed a simple stoichiometric model to estimate methane oxidation fraction when the anaerobic CO2 / CH4 production ratio is known, or can be estimated. The model predicts a linear relationship between CO2 emission rates and CH4 emission rates, where the slope depends on anaerobic CO2 / CH4 production ratio and the fraction of methane oxidized, and the intercept depends on non-methane-dependent oxidation processes. The model was tested using carbon dioxide emission rates (fluxes) and methane emission rates (fluxes) measured using the eddy covariance method over a one year period at the Turkey Run landfill in Georgia, USA. The CO2 / CH4 production ratio was estimated by measuring CO2 and CH4 concentrations in air sampled under anaerobic conditions deep inside the landfill. We also used a mass balance approach to independently estimate fractional oxidation based on stable isotope measurements (δ13C of methane) of gas samples taken from deep inside the landfill and just above the landfill surface. Results from the two independent methods agree well. The model will be described and methane oxidation will be discussed in relation to wind direction, location at the landfill, and age of the deposited refuse.

Predicting emissions from oil and gas operations in the Uinta Basin, Utah.

PubMed

Wilkey, Jonathan; Kelly, Kerry; Jaramillo, Isabel Cristina; Spinti, Jennifer; Ring, Terry; Hogue, Michael; Pasqualini, Donatella

2016-05-01

In this study, emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin are predicted (with uncertainty estimates) from 2015-2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010-2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010-2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015-2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards. This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.

Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations

NASA Astrophysics Data System (ADS)

Dekker, Iris N.; Houweling, Sander; Aben, Ilse; Röckmann, Thomas; Krol, Maarten; Martínez-Alonso, Sara; Deeter, Merritt N.; Worden, Helen M.

2017-12-01

The growth of mega-cities leads to air quality problems directly affecting the citizens. Satellite measurements are becoming of higher quality and quantity, which leads to more accurate satellite retrievals of enhanced air pollutant concentrations over large cities. In this paper, we compare and discuss both an existing and a new method for estimating urban-scale trends in CO emissions using multi-year retrievals from the MOPITT satellite instrument. The first method is mainly based on satellite data, and has the advantage of fewer assumptions, but also comes with uncertainties and limitations as shown in this paper. To improve the reliability of urban-to-regional scale emission trend estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRF-Chem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. This method has the advantage over the existing method in that it allows both a trend analysis of CO concentrations and a quantification of CO emissions. Our analysis confirms that MOPITT is capable of detecting CO enhancements over Madrid, although significant differences remain between the yearly averaged model output and satellite measurements (R2 = 0.75) over the city. After optimization, we find Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006 compared with the EdgarV4.2 emission inventory. The MOPITT-derived emission adjustments lead to better agreement with the European emission inventory TNO-MAC-III for both years. This suggests that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MACC-III. However, our satellite and model based emission estimates have large uncertainties, around 20 % for 2002 and 50 % for 2006.

A first European scale multimedia fate modelling of BDE-209 from 1970 to 2020.

PubMed

Earnshaw, Mark R; Jones, Kevin C; Sweetman, Andy J

2015-01-01

The European Variant Berkeley Trent (EVn-BETR) multimedia fugacity model is used to test the validity of previously derived emission estimates and predict environmental concentrations of the main decabromodiphenyl ether congener, BDE-209. The results are presented here and compared with measured environmental data from the literature. Future multimedia concentration trends are predicted using three emission scenarios (Low, Realistic and High) in the dynamic unsteady state mode covering the period 1970-2020. The spatial and temporal distributions of emissions are evaluated. It is predicted that BDE-209 atmospheric concentrations peaked in 2004 and will decline to negligible levels by 2025. Freshwater concentrations should have peaked in 2011, one year after the emissions peak with sediment concentrations peaking in 2013. Predicted atmospheric concentrations are in good agreement with measured data for the Realistic (best estimate of emissions) and High (worst case scenario) emission scenarios. The Low emission scenario consistently underestimates measured data. The German unilateral ban on the use of DecaBDE in the textile industry is simulated in an additional scenario, the effects of which are mainly observed within Germany with only a small effect on the surrounding areas. Overall, the EVn-BTER model predicts atmospheric concentrations reasonably well, within a factor of 5 and 1.2 for the Realistic and High emission scenarios respectively, providing partial validation for the original emission estimate. Total mean MEC:PEC shows the High emission scenario predicts the best fit between air, freshwater and sediment data. An alternative spatial distribution of emissions is tested, based on higher consumption in EBFRIP member states, resulting in improved agreement between MECs and PECs in comparison with the Uniform spatial distribution based on population density. Despite good agreement between modelled and measured point data, more long-term monitoring datasets are needed to compare predicted trends in concentration to determine the rate of change of POPs within the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification and characterization of high methane-emitting abandoned oil and gas wells

PubMed Central

Kang, Mary; Christian, Shanna; Celia, Michael A.; Mauzerall, Denise L.; Bill, Markus; Miller, Alana R.; Chen, Yuheng; Conrad, Mark E.; Darrah, Thomas H.; Jackson, Robert B.

2016-01-01

Recent measurements of methane emissions from abandoned oil/gas wells show that these wells can be a substantial source of methane to the atmosphere, particularly from a small proportion of high-emitting wells. However, identifying high emitters remains a challenge. We couple 163 well measurements of methane flow rates; ethane, propane, and n-butane concentrations; isotopes of methane; and noble gas concentrations from 88 wells in Pennsylvania with synthesized data from historical documents, field investigations, and state databases. Using our databases, we (i) improve estimates of the number of abandoned wells in Pennsylvania; (ii) characterize key attributes that accompany high emitters, including depth, type, plugging status, and coal area designation; and (iii) estimate attribute-specific and overall methane emissions from abandoned wells. High emitters are best predicted as unplugged gas wells and plugged/vented gas wells in coal areas and appear to be unrelated to the presence of underground natural gas storage areas or unconventional oil/gas production. Repeat measurements over 2 years show that flow rates of high emitters are sustained through time. Our attribute-based methane emission data and our comprehensive estimate of 470,000–750,000 abandoned wells in Pennsylvania result in estimated state-wide emissions of 0.04–0.07 Mt (1012 g) CH4 per year. This estimate represents 5–8% of annual anthropogenic methane emissions in Pennsylvania. Our methodology combining new field measurements with data mining of previously unavailable well attributes and numbers of wells can be used to improve methane emission estimates and prioritize cost-effective mitigation strategies for Pennsylvania and beyond. PMID:27849603

Towards a measurement-based national verification system for GHG emissions: UK emission estimates of CO2 from the GAUGE experiment

NASA Astrophysics Data System (ADS)

Gonzi, Siegfried; Palmer, Paul; O'Doherty, Simon; Young, Dickon; Stanley, Kieran; Stavert, Ann; Grant, Aoife; Helfter, Carole; Mullinger, Neil; Nemitz, Eiko; Allen, Grant; Pitt, Joseph; Le Breton, Michael; Bösch, Hartmut; Sembhi, Harjinder; Sonderfeld, Hannah; Parker, Robert; Bauguitte, Stephane

2016-04-01

Robust quantification of emissions of greenhouse gases (GHG) is central to the success of ongoing international efforts to slow current emissions and mitigate future climate change. The Greenhouse gAs Uk and Global Emissions (GAUGE) project aims to quantify the magnitude and uncertainty of country-scale emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) using concentration measurements from a network of tall towers and mobile platforms (aircraft and ferry) distributed across the UK. The GAUGE measurement programme includes: (a) GHG measurements on a regular ferry route down the North Sea aimed at sampling UK outflow; (b) campaign deployment of the UK BAe-146 research aircraft to provide vertical profile measurements of GHG over and around the UK; (c) a high-density GHG measurement network over East Anglia that is primarily focused on the agricultural sector; and (d) regular measurements of CO2 and CH4 isotopologues used for GHG source attribution. We also use satellite observations from the Japanese Greenhouse gases Observing SATellite (GOSAT) to provide continental-scale constraints on GHG flux estimates. We present CO2 flux estimates for the UK inferred from GAUGE measurements using a nested, high-resolution (25 km) version of the GEOS-Chem global atmospheric chemistry and transport model and an ensemble Kalman filter. We will present our current best estimate for CO2 fluxes and a preliminary assessment of the efficacy of individual GAUGE data sources to spatially resolve CO2 flux estimates over the UK. We will also discuss how flux estimates inferred from the different models used within GAUGE can help to assess the role of transport model error and to determine an ensemble CO2 flux estimate for the UK.

First experiences with methods to measure ammonia emissions from naturally ventilated cattle buildings in the U.K.

NASA Astrophysics Data System (ADS)

Demmers, T. G. M.; Burgess, L. R.; Short, J. L.; Phillips, V. R.; Clark, J. A.; Wathes, C. M.

A method has been developed to measure the emission rate of ammonia from naturally ventilated U.K. livestock buildings. The method is based on measurements of ammonia concentration and estimates of the ventilation rate of the building by continuous release of carbon monoxide tracer within the building. The tracer concentration is measured at nine positions in openings around the perimeter of the building, as well as around a ring sampling line. Two criteria were evaluated to decide whether, at any given time, a given opening in the building acted as an air inlet or as an air outlet. Carbon monoxide concentration difference across an opening was found to be a better criterion than the temperature difference across the opening. Ammonia concentrations were measured continuously at the sampling points using a chemiluminescence analyser. The method was applied to a straw-bedded beef unit and to a slurry-based dairy unit. Both buildings were of space-boarded construction. Ventilation rates estimated by the ring line sample were consistently higher than by the perimeter samples. During calm weather, the ventilation estimates by both samples were similar (10-20 air changes h -1). However, during windy conditions (>5 m s -1) the ventilation rate was overestimated by the ring line sample (average 100 air changes h -1) compared to the perimeter samples (average 50 air changes h -1). The difference was caused by incomplete mixing of the tracer within the building. The ventilation rate estimated from the perimeter samples was used for the calculation of the emission rate. Preliminary estimates of the ammonia emission factor were 6.0 kg NH 3 (500 kg live-weight) -1 (190 d) -1 for the slurry-based dairy unit and 3.7 for the straw-bedded beef unit.

Global radioxenon emission inventory based on nuclear power reactor reports.

PubMed

Kalinowski, Martin B; Tuma, Matthias P

2009-01-01

Atmospheric radioactivity is monitored for the verification of the Comprehensive Nuclear-Test-Ban Treaty, with xenon isotopes 131mXe, 133Xe, 133mXe and 135Xe serving as important indicators of nuclear explosions. The treaty-relevant interpretation of atmospheric concentrations of radioxenon is enhanced by quantifying radioxenon emissions released from civilian facilities. This paper presents the first global radioxenon emission inventory for nuclear power plants, based on North American and European emission reports for the years 1995-2005. Estimations were made for all power plant sites for which emission data were unavailable. According to this inventory, a total of 1.3PBq of radioxenon isotopes are released by nuclear power plants as continuous or pulsed emissions in a generic year.

Estimates of CO2 from fires in the United States: implications for carbon management.

PubMed

Wiedinmyer, Christine; Neff, Jason C

2007-11-01

Fires emit significant amounts of CO2 to the atmosphere. These emissions, however, are highly variable in both space and time. Additionally, CO2 emissions estimates from fires are very uncertain. The combination of high spatial and temporal variability and substantial uncertainty associated with fire CO2 emissions can be problematic to efforts to develop remote sensing, monitoring, and inverse modeling techniques to quantify carbon fluxes at the continental scale. Policy and carbon management decisions based on atmospheric sampling/modeling techniques must account for the impact of fire CO2 emissions; a task that may prove very difficult for the foreseeable future. This paper addresses the variability of CO2 emissions from fires across the US, how these emissions compare to anthropogenic emissions of CO2 and Net Primary Productivity, and the potential implications for monitoring programs and policy development. Average annual CO2 emissions from fires in the lower 48 (LOWER48) states from 2002-2006 are estimated to be 213 (+/- 50 std. dev.) Tg CO2 yr-1 and 80 (+/- 89 std. dev.) Tg CO2 yr-1 in Alaska. These estimates have significant interannual and spatial variability. Needleleaf forests in the Southeastern US and the Western US are the dominant source regions for US fire CO2 emissions. Very high emission years typically coincide with droughts, and climatic variability is a major driver of the high interannual and spatial variation in fire emissions. The amount of CO2 emitted from fires in the US is equivalent to 4-6% of anthropogenic emissions at the continental scale and, at the state-level, fire emissions of CO2 can, in some cases, exceed annual emissions of CO2 from fossil fuel usage. The CO2 released from fires, overall, is a small fraction of the estimated average annual Net Primary Productivity and, unlike fossil fuel CO2 emissions, the pulsed emissions of CO2 during fires are partially counterbalanced by uptake of CO2 by regrowing vegetation in the decades following fire. Changes in fire severity and frequency can, however, lead to net changes in atmospheric CO2 and the short-term impacts of fire emissions on monitoring, modeling, and carbon management policy are substantial.

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

Impact of cutting meat intake on hidden greenhouse gas emissions in an import-reliant city

NASA Astrophysics Data System (ADS)

Yau, Y. Y.; Thibodeau, B.; Not, C.

2018-06-01

Greenhouse gas emissions embodied in trade is a growing concern for the international community. Multiple studies have highlighted drawbacks in the territorial and production-based accounting of greenhouse gas emissions because it neglects emissions from the consumption of goods in trade. This creates weak carbon leakage and complicates international agreements on emissions regulations. Therefore, we estimated consumption-based emissions using input-output analysis and life cycle assessment to calculate the greenhouse gas emissions hidden in meat and dairy products in Hong Kong, a city predominately reliant on imports. We found that emissions solely from meat and dairy consumption were higher than the city’s total greenhouse gas emissions using conventional production-based calculation. This implies that government reports underestimate more than half of the emissions, as 62% of emissions are embodied in international trade. The discrepancy emphasizes the need of transitioning climate targets and policy to consumption-based accounting. Furthermore, we have shown that dietary change from a meat-heavy diet to a diet in accordance with governmental nutrition guidelines could achieve a 67% reduction in livestock-related emissions, allowing Hong Kong to achieve the Paris Agreement targets for 2030. Consequently, we concluded that consumption-based accounting for greenhouse gas emissions is crucial to target the areas where emissions reduction is realistically achievable, especially for import-reliant cities like Hong Kong.

Validation of temporal and spatial consistency of facility- and speed-specific vehicle-specific power distributions for emission estimation: A case study in Beijing, China.

PubMed

Zhai, Zhiqiang; Song, Guohua; Lu, Hongyu; He, Weinan; Yu, Lei

2017-09-01

Vehicle-specific power (VSP) has been found to be highly correlated with vehicle emissions. It is used in many studies on emission modeling such as the MOVES (Motor Vehicle Emissions Simulator) model. The existing studies develop specific VSP distributions (or OpMode distribution in MOVES) for different road types and various average speeds to represent the vehicle operating modes on road. However, it is still not clear if the facility- and speed-specific VSP distributions are consistent temporally and spatially. For instance, is it necessary to update periodically the database of the VSP distributions in the emission model? Are the VSP distributions developed in the city central business district (CBD) area applicable to its suburb area? In this context, this study examined the temporal and spatial consistency of the facility- and speed-specific VSP distributions in Beijing. The VSP distributions in different years and in different areas are developed, based on real-world vehicle activity data. The root mean square error (RMSE) is employed to quantify the difference between the VSP distributions. The maximum differences of the VSP distributions between different years and between different areas are approximately 20% of that between different road types. The analysis of the carbon dioxide (CO 2 ) emission factor indicates that the temporal and spatial differences of the VSP distributions have no significant impact on vehicle emission estimation, with relative error of less than 3%. The temporal and spatial differences have no significant impact on the development of the facility- and speed-specific VSP distributions for the vehicle emission estimation. The database of the specific VSP distributions in the VSP-based emission models can maintain in terms of time. Thus, it is unnecessary to update the database regularly, and it is reliable to use the history vehicle activity data to forecast the emissions in the future. In one city, the areas with less data can still develop accurate VSP distributions based on better data from other areas.

Evaluation of speciated VOC emission factors for Air Force hush houses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, P.D.; Stevens, D.K.

1997-12-31

Data published in: ``Engine and Hush House Emissions from a TF30-P109 Jet Engine Tested at Cannon Air Force Base, NM`` by Radian Corporation and ``Aircraft Emissions. Characterization: TF41-A2, TF30-P103 , and TF30-P109 Engines`` by Battelle are reviewed and compared. Specifically CO, NO{sub x}, and VOC emission factors using EPA Method 19 are addressed, with comparisons between JP-4 and JP-8 jet fuels. CO and NO{sub x} emissions for JP-4 and JP-8 jet fuels were found to be essentially the same. VOC emission data exhibited high variability. Problems inherent in speciated VOC emission testing are discussed. A limiting of speciated VOC emissionmore » testing, with emission factor estimation based on fuel content is proposed.« less

Systematic Review of Life Cycle Greenhouse Gas Emissions from Geothermal Electricity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eberle, Annika; Heath, Garvin A.; Carpenter Petri, Alberta C.

The primary goal of this work was to assess the magnitude and variability of published life cycle greenhouse gas (GHG) emission estimates for three types of geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash, and HT binary. These technologies were chosen to align the results of this report with technologies modeled in National Renewable Energy Laboratory's (NREL's) Regional Energy Deployment Systems (ReEDs) model. Although we did gather and screen life cycle assessment (LCA) literature on hybrid systems, dry steam, and two geothermal heating technologies, we did not analyze published GHG emission estimates for these technologies. Inmore » our systematic literature review of the LCA literature, we screened studies in two stages based on a variety of criteria adapted from NREL's Life Cycle Assessment (LCA) Harmonization study (Heath and Mann 2012). Of the more than 180 geothermal studies identified, only 29 successfully passed both screening stages and only 26 of these included estimates of life cycle GHG emissions. We found that the median estimate of life cycle GHG emissions (in grams of carbon dioxide equivalent per kilowatt-hour generated [g CO2eq/kWh]) reported by these studies are 32.0, 47.0, and 11.3 for EGS binary, HT flash, and HT binary, respectively (Figure ES-1). We also found that the total life cycle GHG emissions are dominated by different stages of the life cycle for different technologies. For example, the GHG emissions from HT flash plants are dominated by the operations phase owing to the flash cycle being open loop whereby carbon dioxide entrained in the geothermal fluids is released to the atmosphere. This is in contrast to binary plants (using either EGS or HT resources), whose GHG emissions predominantly originate in the construction phase, owing to its closed-loop process design. Finally, by comparing this review's literature-derived range of HT flash GHG emissions to data from currently operating geothermal plants, we found that emissions from operational plants exhibit more variability and the median of emissions from operational plants is twice the median of operational emissions reported by LCAs. Further investigation is warranted to better understand the cause of differences between published LCAs and estimates from operational plants and to develop LCA analytical approaches that can yield estimates closer to actual emissions.« less

Analysis of Biogenic VOCs Emissions During the MAPS-Seoul Aircraft Field Campaign

NASA Astrophysics Data System (ADS)

Lee, Y.; Woo, J. H.; Kim, Y.; Bu, C.; Kim, J.; Kim, H. K.; Lee, M. H.; Eo, Y.

2016-12-01

The MAPS-Seoul (Megacity Air Pollution Studies-Seoul) aircraft mission was conducted in May - June 2016 to understand atmospheric environment over the South Korea. BVOCs emissions forecasting, along with other components, were conducted daily in support of the aircraft mission planning. The biogenic emissions as well as anthropogenic ones were very important factor to model and analyze atmospheric environment since more than 80% of global VOCs emission comes from biogenic sources. This also could be true for South Korea, since more than 70% of its land area are vegetated such as forest, cropland. For modeling-based BVOC emission estimation, geographical distribution of PFT (plant functional type) and LAI (Leaf Area Index) are considered as very important driving variables. Most of cases, PFTs and LAI were derived from the low-resolution satellite-based information which are not quite ideal for relatively small area like South Korea. In this study, we developed the more reliable Korean PFT and LAI cover derived from Korean landcover maps and modeled satellite images. The WRF-MEGAN modeling framework over South Korea for the period of May to June 2016 was used to estimate re-analysis BVOCs emission field. Analysis of different PFT and LAI inputs affected local and national biogenic emission estimations will be presented at site. Acknowledgements : This subject is supported by Korea Ministry of Environment as "Climate Change Correspondence Program". This work was supported by a grant from the National Institute of Environment Research (NIER), funded by the Ministry of Environment (MOE) of the Republic of Korea.

Agriculture-driven deforestation in the tropics from 1990-2015: emissions, trends and uncertainties

NASA Astrophysics Data System (ADS)

Carter, Sarah; Herold, Martin; Avitabile, Valerio; de Bruin, Sytze; De Sy, Veronique; Kooistra, Lammert; Rufino, Mariana C.

2018-01-01

Limited data exists on emissions from agriculture-driven deforestation, and available data are typically uncertain. In this paper, we provide comparable estimates of emissions from both all deforestation and agriculture-driven deforestation, with uncertainties for 91 countries across the tropics between 1990 and 2015. Uncertainties associated with input datasets (activity data and emissions factors) were used to combine the datasets, where most certain datasets contribute the most. This method utilizes all the input data, while minimizing the uncertainty of the emissions estimate. The uncertainty of input datasets was influenced by the quality of the data, the sample size (for sample-based datasets), and the extent to which the timeframe of the data matches the period of interest. Area of deforestation, and the agriculture-driver factor (extent to which agriculture drives deforestation), were the most uncertain components of the emissions estimates, thus improvement in the uncertainties related to these estimates will provide the greatest reductions in uncertainties of emissions estimates. Over the period of the study, Latin America had the highest proportion of deforestation driven by agriculture (78%), and Africa had the lowest (62%). Latin America had the highest emissions from agriculture-driven deforestation, and these peaked at 974 ± 148 Mt CO2 yr-1 in 2000-2005. Africa saw a continuous increase in emissions between 1990 and 2015 (from 154 ± 21-412 ± 75 Mt CO2 yr-1), so mitigation initiatives could be prioritized there. Uncertainties for emissions from agriculture-driven deforestation are ± 62.4% (average over 1990-2015), and uncertainties were highest in Asia and lowest in Latin America. Uncertainty information is crucial for transparency when reporting, and gives credibility to related mitigation initiatives. We demonstrate that uncertainty data can also be useful when combining multiple open datasets, so we recommend new data providers to include this information.

Modeling emission rates and exposures from outdoor cooking

NASA Astrophysics Data System (ADS)

Edwards, Rufus; Princevac, Marko; Weltman, Robert; Ghasemian, Masoud; Arora, Narendra K.; Bond, Tami

2017-09-01

Approximately 3 billion individuals rely on solid fuels for cooking globally. For a large portion of these - an estimated 533 million - cooking is outdoors, where emissions from cookstoves pose a health risk to both cooks and other household and village members. Models that estimate emissions rates from stoves in indoor environments that would meet WHO air quality guidelines (AQG), explicitly don't account for outdoor cooking. The objectives of this paper are to link health based exposure guidelines with emissions from outdoor cookstoves, using a Monte Carlo simulation of cooking times from Haryana India coupled with inverse Gaussian dispersion models. Mean emission rates for outdoor cooking that would result in incremental increases in personal exposure equivalent to the WHO AQG during a 24-h period were 126 ± 13 mg/min for cooking while squatting and 99 ± 10 mg/min while standing. Emission rates modeled for outdoor cooking are substantially higher than emission rates for indoor cooking to meet AQG, because the models estimate impact of emissions on personal exposure concentrations rather than microenvironment concentrations, and because the smoke disperses more readily outdoors compared to indoor environments. As a result, many more stoves including the best performing solid-fuel biomass stoves would meet AQG when cooking outdoors, but may also result in substantial localized neighborhood pollution depending on housing density. Inclusion of the neighborhood impact of pollution should be addressed more formally both in guidelines on emissions rates from stoves that would be protective of health, and also in wider health impact evaluation efforts and burden of disease estimates. Emissions guidelines should better represent the different contexts in which stoves are being used, especially because in these contexts the best performing solid fuel stoves have the potential to provide significant benefits.

Slowdown of N2O emissions from China's croplands

NASA Astrophysics Data System (ADS)

Zhou, F.; Shang, Z.; Ciais, P.; Piao, S.; Tian, H.; Saikawa, E.; Zaehle, S.; Del Grosso, S. J.; Galloway, J. N.

2016-12-01

To feed the increasing population, China has experienced a rapid agricultural development over past decades, accompanied by increased fertilizer consumptions in croplands, but the magnitude, trend, and causes of the associated nitrous oxide (N2O) emissions has remain unclear. The primary sources of this uncertainty are conflicting estimates of fertilizer consumption and emission factors, the latter being uncertain because of very few regional representativeness of the Nrate-flux relationships in China. Here we re-estimate China's N2O emissions from croplands using three different methods: flux upscaling technique, process-based models and atmospheric inversion, and also analyze the corresponding drivers using an attribution approach. The three methods produce similar estimates of N2O emissions in the range of 0.67 ± 0.08 to 0.62± 0.11 Tg nitrogen per year, which is 29% larger than the estimates by the Emission Database for Global Atmospheric Research (EDGAR) that is adopted by Intergovernmental Panel on Climate Change (IPCC) as the emission baseline and twofold larger than the latest Chinese national report submitted to the United Nations Framework Convention on Climate Change, but the revised trend slows down after 2005. Fertilizer N application per area is the dominant factor driving the increase in N2O emissions across most cropping regions from 1990 to 2004, but climate-induced change of emission factors has also controlled N2O flux from 2005 onwards. Our findings suggest that, as precipitation would increase in North China but decline in the South in future, EF will increasingly control China's agri. soil emissions of N2O, unless offset by larger reductions of fertilizer consumptions.

Modeled nitrous oxide emissions from corn fields in Iowa based on county level data

USDA-ARS?s Scientific Manuscript database

The US Corn Belt area has the capacity to generate high nitrous oxide (N2O) emissions due to medium to high annual precipitation, medium to heavy textured soils rich in organic matter, and high nitrogen (N) application rates. The purpose of this work was to estimate field N2O emissions from cornfiel...

A novel methodology to quantify nitrous oxide emissions from full-scale wastewater treatment systems with surface aerators.

PubMed

Ye, Liu; Ni, Bing-Jie; Law, Yingyu; Byers, Craig; Yuan, Zhiguo

2014-01-01

The quantification of nitrous oxide (N2O) emissions from open-surface wastewater treatment systems with surface aerators is difficult as emissions from the surface aerator zone cannot be easily captured by floating hoods. In this study, we propose and demonstrate a novel methodology to estimate N2O emissions from such systems through determination of the N2O transfer coefficient (kLa) induced by surface aerators based on oxygen balance for the entire system. The methodology is demonstrated through its application to a full-scale open oxidation ditch wastewater treatment plant with surface aerators. The estimated kLa profile based on a month-long measurement campaign for oxygen balance, intensive monitoring of dissolved N2O profiles along the oxidation ditch over a period of four days, together with mathematical modelling, enabled to determine the N2O emission factor from this treatment plant (0.52 ± 0.16%). Majority of the N2O emission was found to occur in the surface aerator zone, which would be missed if the gas hood method was applied alone. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact of policy on greenhouse gas emissions and economics of biodiesel production.

PubMed

Olivetti, Elsa; Gülşen, Ece; Malça, João; Castanheira, Erica; Freire, Fausto; Dias, Luis; Kirchain, Randolph

2014-07-01

As an alternative transportation fuel to petrodiesel, biodiesel has been promoted within national energy portfolio targets across the world. Early estimations of low lifecycle greenhouse gas (GHG) emissions of biodiesel were a driver behind extensive government support in the form of financial incentives for the industry. However, studies consistently report a high degree of uncertainty in these emissions estimates, raising questions concerning the carbon benefits of biodiesel. Furthermore, the implications of feedstock blending on GHG emissions uncertainty have not been explicitly addressed despite broad practice by the industry to meet fuel quality standards and to control costs. This work investigated the impact of feedstock blending on the characteristics of biodiesel by using a chance-constrained (CC) blend optimization method. The objective of the optimization is minimization of feedstock costs subject to fuel standards and emissions constraints. Results indicate that blending can be used to manage GHG emissions uncertainty characteristics of biodiesel, and to achieve cost reductions through feedstock diversification. Simulations suggest that emissions control policies that restrict the use of certain feedstocks based on their GHG estimates overlook blending practices and benefits, increasing the cost of biodiesel. In contrast, emissions control policies which recognize the multifeedstock nature of biodiesel provide producers with feedstock selection flexibility, enabling them to manage their blend portfolios cost effectively, potentially without compromising fuel quality or emissions reductions.

Time Resolved Temperature Measurement of Hypervelocity Impact Generated Plasma Using a Global Optimization Method

NASA Astrophysics Data System (ADS)

Hew, Y. M.; Linscott, I.; Close, S.

2015-12-01

Meteoroids and orbital debris, collectively referred to as hypervelocity impactors, travel between 7 and 72 km/s in free space. Upon their impact onto the spacecraft, the energy conversion from kinetic to ionization/vaporization occurs within a very brief timescale and results in a small and dense expanding plasma with a very strong optical flash. The radio frequency (RF) emission produced by this plasma can potentially lead to electrical anomalies within the spacecraft. In addition, space weather, such as solar activity and background plasma, can establish spacecraft conditions which can exaggerate the damages done by these impacts. During the impact, a very strong impact flash will be generated. Through the studying of this emission spectrum of the impact, we hope to study the impact generated gas cloud/plasma properties. The impact flash emitted from a ground-based hypervelocity impact test is long expected by many scientists to contain the characteristics of the impact generated plasma, such as plasma temperature and density. This paper presents a method for the time-resolved plasma temperature estimation using three-color visible band photometry data with a global pattern search optimization method. The equilibrium temperature of the plasma can be estimated using an optical model which accounts for both the line emission and continuum emission from the plasma. Using a global pattern search based optimizer, the model can isolate the contribution of the continuum emission versus the line emission from the plasma. The plasma temperature can thus be estimated. Prior to the optimization step, a Gaussian process is also applied to extract the optical emission signal out of the noisy background. The resultant temperature and line-to-continuum emission weighting factor are consistent with the spectrum of the impactor material and current literature.

Low-Computation Strategies for Extracting CO2 Emission Trends from Surface-Level Mixing Ratio Observations

NASA Astrophysics Data System (ADS)

Shusterman, A.; Kim, J.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

Global momentum is building for drastic, regulated reductions in greenhouse gas emissions over the coming decade. With this increasing regulation comes a clear need for increasingly sophisticated monitoring, reporting, and verification (MRV) strategies capable of enforcing and optimizing emissions-related policy, particularly as it applies to urban areas. Remote sensing and/or activity-based emission inventories can offer MRV insights for entire sectors or regions, but are not yet sophisticated enough to resolve unexpected trends in specific emitters. Urban surface monitors can offer the desired proximity to individual greenhouse gas sources, but due to the densely-packed nature of typical urban landscapes, surface observations are rarely representative of a single source. Most previous efforts to decompose these complex signals into their contributing emission processes have involved inverse atmospheric modeling techniques, which are computationally intensive and believed to depend heavily on poorly understood a priori estimates of error covariance. Here we present a number of transparent, low-computation approaches for extracting source-specific emissions estimates from signals with a variety of nearfield influences. Using observations from the first several years of the BErkeley Atmospheric CO2 Observation Network (BEACO2N), we demonstrate how to exploit strategic pairings of monitoring "nodes," anomalous wind conditions, and well-understood temporal variations to hone in on specific CO2 sources of interest. When evaluated against conventional, activity-based bottom-up emission inventories, these strategies are seen to generate quantitatively rigorous emission estimates. With continued application as the BEACO2N data set grows in time and space, these approaches offer a promising avenue for optimizing greenhouse gas mitigation strategies into the future.

Estimates and Predictions of Methane Emissions from Wastewater in China from 2000 to 2020

NASA Astrophysics Data System (ADS)

Du, Mingxi; Zhu, Qiuan; Wang, Xiaoge; Li, Peng; Yang, Bin; Chen, Huai; Wang, Meng; Zhou, Xiaolu; Peng, Changhui

2018-02-01

Methane accounts for 20% of the global warming caused by greenhouse gases, and wastewater is a major anthropogenic source of methane. Based on the Intergovernmental Panel on Climate Change greenhouse gas inventory guidelines and current research findings, we calculated the amount of methane emissions from 2000 to 2014 that originated from wastewater from different provinces in China. Methane emissions from wastewater increased from 1349.01 to 3430.03 Gg from 2000 to 2014, and the mean annual increase was 167.69 Gg. The methane emissions from industrial wastewater treated by wastewater treatment plants (EIt) accounted for the highest proportion of emissions. We also estimated the future trend of industrial wastewater methane emissions using the artificial neural network model. A comparison of the emissions for the years 2020, 2010, and 2000 showed an increasing trend in methane emissions in China and a spatial transition of industrial wastewater emissions from eastern and southern regions to central and southwestern regions and from coastal regions to inland regions. These changes were caused by changes in economics, demographics, and relevant policies.

New methodology for modeling annual-aircraft emissions at airports

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodmansey, B.G.; Patterson, J.G.

An as-accurate-as-possible estimation of total-aircraft emissions are an essential component of any environmental-impact assessment done for proposed expansions at major airports. To determine the amount of emissions generated by aircraft using present models it is necessary to know the emission characteristics of all engines that are on all planes using the airport. However, the published data base does not cover all engine types and, therefore, a new methodology is needed to assist in estimating annual emissions from aircraft at airports. Linear regression equations relating quantity of emissions to aircraft weight using a known-fleet mix are developed in this paper. Total-annualmore » emissions for CO, NO[sub x], NMHC, SO[sub x], CO[sub 2], and N[sub 2]O are tabulated for Toronto's international airport for 1990. The regression equations are statistically significant for all emissions except for NMHC from large jets and NO[sub x] and NMHC for piston-engine aircraft. This regression model is a relatively simple, fast, and inexpensive method of obtaining an annual-emission inventory for an airport.« less

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport.

PubMed

Zhou, Luxi; Baker, Kirk R; Napelenok, Sergey L; Pouliot, George; Elleman, Robert; O'Neill, Susan M; Urbanski, Shawn P; Wong, David C

2018-06-15

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment in the Pacific Northwest focused on cropland residue burning was used to evaluate model performance in capturing surface and aloft impacts from the burning events. The Community Multiscale Air Quality (CMAQ) model was used to simulate multiple crop residue burns with 2 km grid spacing using field-specific information and also more general assumptions traditionally used to support National Emission Inventory based assessments. Field study specific information, which includes area burned, fuel consumption, and combustion completeness, resulted in increased biomass consumption by 123 tons (60% increase) on average compared to consumption estimated with default methods in the National Emission Inventory (NEI) process. Buoyancy heat flux, a key parameter for model predicted fire plume rise, estimated from fuel loading obtained from field measurements can be 30% to 200% more than when estimated using default field information. The increased buoyancy heat flux resulted in higher plume rise by 30% to 80%. This evaluation indicates that the regulatory air quality modeling system can replicate intensity and transport (horizontal and vertical) features for crop residue burning in this region when region-specific information is used to inform emissions and plume rise calculations. Further, previous vertical emissions allocation treatment of putting all cropland residue burning in the surface layer does not compare well with measured plume structure and these types of burns should be modeled more similarly to prescribed fires such that plume rise is based on an estimate of buoyancy. Copyright © 2018 Elsevier B.V. All rights reserved.

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

Hypergolic oxidizer and fuel scrubber emissions

NASA Technical Reports Server (NTRS)

Parrish, Clyde F.; Barile, Ronald G.; Curran, Dan; Hodge, Tim; Lueck, Dale E.; Young, Rebecca C.

1995-01-01

Hypergolic fuels and oxidizer are emitted to the environment during fueling and deservicing shuttle and other spacecraft. Such emissions are difficult to measure due to the intermittent purge flow and to the presence of suspended scrubber liquor. A new method for emissions monitoring was introduced in a previous paper. This paper is a summary of the results of a one-year study of shuttle launch pads and orbiter processing facilities (OPF's) which proved that emissions can be determined from field scrubbers without direct measurement of vent flow rate and hypergol concentration. This new approach is based on the scrubber efficiency, which was measured during normal operations, and on the accumulated weight of hypergol captured in the scrubber liquor, which is part of the routine monitoring data of scrubber liquors. To validate this concept, three qualification tests were performed, logs were prepared for each of 16 hypergol scrubbers at KSC, the efficiencies of KSC scrubbers were measured during normal operations, and an estimate of the annual emissions was made based on the efficiencies and the propellant buildup data. The results have confirmed that the emissions from the KSC scrubbers can be monitored by measuring the buildup of hypergol propellant in the liquor, and then using the appropriate efficiency to calculate the emissions. There was good agreement between the calculated emissions based on outlet concentration and flow rate, and the emissions calculated from the propellant buildup and efficiency. The efficiencies of 12 KSC scrubbers, measured under actual servicing operations and special test conditions, were assumed to be valid for all subsequent operations until a significant change in hardware occurred. An estimate of the total emissions from 16 scrubbers for three years showed that 0.3 kg/yr of fuel and 234 kg/yr of oxidizer were emitted.

Indirect nitrous oxide emissions from streams within the US Corn Belt scale with stream order

PubMed Central

Turner, Peter A.; Griffis, Timothy J.; Lee, Xuhui; Baker, John M.; Venterea, Rodney T.; Wood, Jeffrey D.

2015-01-01

N2O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N2O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N2O emissions, implying that EFs may be biased low. Here, we measured N2O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N2O fluxes from headwater streams often exceeded 29 nmol N2O-N m−2⋅s−1 and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N2O emissions by 40%. We show that accounting for zero-order streams as potential N2O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5r underestimation explains the large differences observed between top-down and bottom-up emission estimates. PMID:26216994

Process-based Modeling of Ammonia Emission from Beef Cattle Feedyards with the Integrated Farm Systems Model.

PubMed

Waldrip, Heidi M; Rotz, C Alan; Hafner, Sasha D; Todd, Richard W; Cole, N Andy

2014-07-01

Ammonia (NH) volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N) and potentially leads to overfertilization and acidification of aquatic and terrestrial ecosystems. In addition, NH is involved in the formation of atmospheric fine particulate matter (PM), which can affect human health. Process-based models have been developed to estimate NH emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot beef cattle feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita NH emission rates were compared with emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations and were sensitive to variations in air temperature and dietary crude protein concentration. Predicted mean daily NH emission rates for the two feedyards had 71 to 81% agreement with observations. In addition, IFSM estimates of annual feedyard emissions were within 11 to 24% of observations, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can quantify average feedyard NH emissions, assist with emissions reporting, provide accurate information for legislators and policymakers, investigate methods to mitigate NH losses, and evaluate the effects of specific management practices on farm nutrient balances. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Optimizing Fukushima Emissions Through Pattern Matching and Genetic Algorithms

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Simpson, M. D.; Philip, C. S.; Baskett, R.

2017-12-01

Hazardous conditions during the Fukushima Daiichi nuclear power plant (NPP) accident hindered direct observations of the emissions of radioactive materials into the atmosphere. A wide range of emissions are estimated from bottom-up studies using reactor inventories and top-down approaches based on inverse modeling. We present a new inverse modeling estimate of cesium-137 emitted from the Fukushima NPP. Our estimate considers weather uncertainty through a large ensemble of Weather Research and Forecasting model simulations and uses the FLEXPART atmospheric dispersion model to transport and deposit cesium. The simulations are constrained by observations of the spatial distribution of cumulative cesium deposited on the surface of Japan through April 2, 2012. Multiple spatial metrics are used to quantify differences between observed and simulated deposition patterns. In order to match the observed pattern, we use a multi-objective genetic algorithm to optimize the time-varying emissions. We find that large differences with published bottom-up estimates are required to explain the observations. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

U.S. emissions of HFC-134a derived for 2008-2012 from an extensive flask-air sampling network

NASA Astrophysics Data System (ADS)

Hu, Lei; Montzka, Stephen A.; Miller, John B.; Andrews, Aryln E.; Lehman, Scott J.; Miller, Benjamin R.; Thoning, Kirk; Sweeney, Colm; Chen, Huilin; Godwin, David S.; Masarie, Kenneth; Bruhwiler, Lori; Fischer, Marc L.; Biraud, Sebastien C.; Torn, Margaret S.; Mountain, Marikate; Nehrkorn, Thomas; Eluszkiewicz, Janusz; Miller, Scot; Draxler, Roland R.; Stein, Ariel F.; Hall, Bradley D.; Elkins, James W.; Tans, Pieter P.

2015-01-01

national and regional emissions of HFC-134a are derived for 2008-2012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximum likelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr-1 for the contiguous U.S. during 2008-2012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12 km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 2008-2010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 10-20% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 20-50%.

How much do direct livestock emissions actually contribute to global warming?

PubMed

Reisinger, Andy; Clark, Harry

2018-04-01

Agriculture directly contributes about 10%-12% of current global anthropogenic greenhouse gas emissions, mostly from livestock. However, such percentage estimates are based on global warming potentials (GWPs), which do not measure the actual warming caused by emissions and ignore the fact that methane does not accumulate in the atmosphere in the same way as CO 2 . Here, we employ a simple carbon cycle-climate model, historical estimates and future projections of livestock emissions to infer the fraction of actual warming that is attributable to direct livestock non-CO 2 emissions now and in future, and to CO 2 from pasture conversions, without relying on GWPs. We find that direct livestock non-CO 2 emissions caused about 19% of the total modelled warming of 0.81°C from all anthropogenic sources in 2010. CO 2 from pasture conversions contributed at least another 0.03°C, bringing the warming directly attributable to livestock to 23% of the total warming in 2010. The significance of direct livestock emissions to future warming depends strongly on global actions to reduce emissions from other sectors. Direct non-CO 2 livestock emissions would contribute only about 5% of the warming in 2100 if emissions from other sectors increase unabated, but could constitute as much as 18% (0.27°C) of the warming in 2100 if global CO 2 emissions from other sectors are reduced to near or below zero by 2100, consistent with the goal of limiting warming to well below 2°C. These estimates constitute a lower bound since indirect emissions linked to livestock feed production and supply chains were not included. Our estimates demonstrate that expanding the mitigation potential and realizing substantial reductions of direct livestock non-CO 2 emissions through demand and supply side measures can make an important contribution to achieve the stringent mitigation goals set out in the Paris Agreement, including by increasing the carbon budget consistent with the 1.5°C goal. © 2017 John Wiley & Sons Ltd.

Estimation of Methane Emissions from Slurry Pits below Pig and Cattle Confinements

PubMed Central

Petersen, Søren O.; Olsen, Anne B.; Elsgaard, Lars; Triolo, Jin Mi; Sommer, Sven G.

2016-01-01

Quantifying in-house emissions of methane (CH4) from liquid manure (slurry) is difficult due to high background emissions from enteric processes, yet of great importance for correct estimation of CH4 emissions from manure management and effects of treatment technologies such as anaerobic digestion. In this study CH4 production rates were determined in 20 pig slurry and 11 cattle slurry samples collected beneath slatted floors on six representative farms; rates were determined within 24 h at temperatures close to the temperature in slurry pits at the time of collection. Methane production rates in pig and cattle slurry differed significantly at 0.030 and 0.011 kg CH4 kg-1 VS (volatile solids). Current estimates of CH4 emissions from pig and cattle manure management correspond to 0.032 and 0.015 kg CH4 kg-1, respectively, indicating that slurry pits under animal confinements are a significant source. Fractions of degradable volatile solids (VSd, kg kg-1 VS) were estimated using an aerobic biodegradability assay and total organic C analyses. The VSd in pig and cattle slurry averaged 0.51 and 0.33 kg kg-1 VS, and it was estimated that on average 43 and 28% of VSd in fresh excreta from pigs and cattle, respectively, had been lost at the time of sampling. An empirical model of CH4 emissions from slurry was reparameterised based on experimental results. A sensitivity analysis indicated that predicted CH4 emissions were highly sensitive to uncertainties in the value of lnA of the Arrhenius equation, but much less sensitive to uncertainties in VSd or slurry temperature. A model application indicated that losses of carbon in VS as CO2 may be much greater than losses as CH4. Implications of these results for the correct estimation of CH4 emissions from manure management, and for the mitigation potential of treatments such as anaerobic digestion, are discussed. PMID:27529692

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-08-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system, and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with instationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012, respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012, respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

NASA Astrophysics Data System (ADS)

Stieger, J.; Bamberger, I.; Buchmann, N.; Eugster, W.

2015-12-01

This study provides the first experimental validation of Swiss agricultural methane emission estimates at the farm scale. We measured CH4 concentrations at a Swiss farmstead during two intensive field campaigns in August 2011 and July 2012 to (1) quantify the source strength of livestock methane emissions using a tethered balloon system and (2) to validate inventory emission estimates via nocturnal boundary layer (NBL) budgets. Field measurements were performed at a distance of 150 m from the nearest farm buildings with a tethered balloon system in combination with gradient measurements at eight heights on a 10 m tower to better resolve the near-surface concentrations. Vertical profiles of air temperature, relative humidity, CH4 concentration, wind speed, and wind direction showed that the NBL was strongly influenced by local transport processes and by the valley wind system. Methane concentrations showed a pronounced time course, with highest concentrations in the second half of the night. NBL budget flux estimates were obtained via a time-space kriging approach. Main uncertainties of NBL budget flux estimates were associated with nonstationary atmospheric conditions and the estimate of the inversion height zi (top of volume integration). The mean NBL budget fluxes of 1.60 ± 0.31 μg CH4 m-2 s-1 (1.40 ± 0.50 and 1.66 ± 0.20 μg CH4 m-2 s-1 in 2011 and 2012 respectively) were in good agreement with local inventory estimates based on current livestock number and default emission factors, with 1.29 ± 0.47 and 1.74 ± 0.63 μg CH4 m-2 s-1 for 2011 and 2012 respectively. This indicates that emission factors used for the national inventory reports are adequate, and we conclude that the NBL budget approach is a useful tool to validate emission inventory estimates.

Estimation of exhaust emission from ocean-going vessels in Hong Kong.

PubMed

Yau, P S; Lee, S C; Corbett, James J; Wang, Chengfeng; Cheng, Y; Ho, K F

2012-08-01

As one of the busiest port in the world, ship emissions have become of great concern in Hong Kong. In this study, a detailed maritime emission inventory for ocean-going vessels (OGVs) in Hong Kong with the base year of 2007 was developed. The high-resolution vessel speed profiles determined using the Automatic Identification System (AIS) during 2009 were adopted for the speed data in the estimation. It was obtained that the total ship emissions from 37,150 voyages of OGVs in 2007 were 17,097, 8190, and 1035 tonnes accounting for 17%, 11%, and 16% of the total emissions of NO(x), SO(2), and PM(10), respectively. The contribution of ship emissions during transiting was 60-68% for three pollutants while the emissions during hotelling were responsible for the remaining portions. From the emission spatial allocation, the shipping route along the East Lamma Channel and the berthing location of the Kwai Chung and Tsing Yi Container Port comprised the regions with the highest emissions. The OGV emissions in Hong Kong contributed 0.07% NO(x), 0.05% SO(2), and 0.06% PM(10) out of the global total shipping emissions in 2007. Copyright © 2012 Elsevier B.V. All rights reserved.

High-Mileage Light-Duty Fleet Vehicle Emissions: Their Potentially Overlooked Importance.

PubMed

Bishop, Gary A; Stedman, Donald H; Burgard, Daniel A; Atkinson, Oscar

2016-05-17

State and local agencies in the United States use activity-based computer models to estimate mobile source emissions for inventories. These models generally assume that vehicle activity levels are uniform across all of the vehicle emission level classifications using the same age-adjusted travel fractions. Recent fuel-specific emission measurements from the SeaTac Airport, Los Angeles, and multi-year measurements in the Chicago area suggest that some high-mileage fleets are responsible for a disproportionate share of the fleet's emissions. Hybrid taxis at the airport show large increases in carbon monoxide, hydrocarbon, and oxide of nitrogen emissions in their fourth year when compared to similar vehicles from the general population. Ammonia emissions from the airport shuttle vans indicate that catalyst reduction capability begins to wane after 5-6 years, 3 times faster than is observed in the general population, indicating accelerated aging. In Chicago, the observed, on-road taxi fleet also had significantly higher emissions and an emissions share that was more than double their fleet representation. When compounded by their expected higher than average mileage accumulation, we estimate that these small fleets (<1% of total) may be overlooked as a significant emission source (>2-5% of fleet emissions).

A high-resolution emission inventory of primary pollutants for the Huabei region, China

NASA Astrophysics Data System (ADS)

Zhao, B.; Wang, P.; Ma, J. Z.; Zhu, S.; Pozzer, A.; Li, W.

2012-01-01

Huabei, located between 32° N and 42° N, is part of eastern China and includes administratively the Beijing and Tianjin Municipalities, Hebei and Shanxi Provinces, and Inner-Mongolia Autonomous Region. Over the past decades, the region has experienced dramatic changes in air quality and climate, and has become a major focus of environmental research in China. Here we present a new inventory of air pollutant emissions in Huabei for the year 2003 developed as part of the project Influence of Pollution on Aerosols and Cloud Microphysics in North China (IPAC-NC). Our estimates are based on data from the statistical yearbooks of the state, provinces and local districts, including major sectors and activities of power generation, industrial energy consumption, industrial processing, civil energy consumption, crop straw burning, oil and solvent evaporation, manure, and motor vehicles. The emission factors are selected from a variety of literature and those from local measurements in China are used whenever available. The estimated total emissions in the Huabei administrative region in 2003 are 4.73 Tg SO2, 2.72 Tg NOx (in equivalent NO2), 1.77 Tg VOC, 24.14 Tg CO, 2.03 Tg NH3, 4.57 Tg PM10, 2.42 Tg PM2.5, 0.21 Tg EC, and 0.46 Tg OC. For model convenience, we consider a larger Huabei region with Shandong, Henan and Liaoning Provinces included in our inventory. The estimated total emissions in the larger Huabei region in 2003 are: 9.55 Tg SO2, 5.27 Tg NOx (in equivalent NO2), 3.82 Tg VOC, 46.59 Tg CO, 5.36 Tg NH3, 10.74 Tg PM10, 5.62 Tg PM2.5, 0.41 Tg EC, and 0.99 Tg OC. The estimated emission rates are projected into grid cells at a horizontal resolution of 0.1° latitude by 0.1° longitude. Our gridded emission inventory consists of area sources, which are classified into industrial, civil, traffic, and straw burning sectors, and large industrial point sources, which include 345 sets of power plants, iron and steel plants, cement plants, and chemical plants. The estimated regional NO2 emissions are about 2-3% (administrative Huabei region) or 5% (larger Huabei region) of the global anthropogenic NO2 emissions. We compare our inventory (IPAC-NC) with the global emission inventory EDGAR-CIRCE and the Asian emission inventory INTEX-B. Except for a factor of 3 lower EC emission rate in comparison with INTEX-B, the biases of the total emissions of most primary air pollutants in Huabei estimated in our inventory, with respect to EDGAR-CIRCE and INTEX-B, generally range from -30% to +40%. Large differences up to a factor of 2-3 for local emissions in some areas (e.g. Beijing and Tianjin) are found. It is recommended that the inventories based on the activity rates and emission factors for each specific year should be applied in future modeling work related to the changes in air quality and atmospheric chemistry over this region.

Can we improve C IV-based single epoch black hole mass estimations?

NASA Astrophysics Data System (ADS)

Mejía-Restrepo, J. E.; Trakhtenbrot, B.; Lira, P.; Netzer, H.

2018-05-01

In large optical surveys at high redshifts (z > 2), the C IV broad emission line is the most practical alternative to estimate the mass (MBH) of active super-massive black holes (SMBHs). However, mass determinations obtained with this line are known to be highly uncertain. In this work we use the Sloan Digital Sky Survey Data Release 7 and 12 quasar catalogues to statistically test three alternative methods put forward in the literature to improve C IV-based MBH estimations. These methods are constructed from correlations between the ratio of the C IV line-width to the low ionization line-widths (Hα, Hβ and Mg II) and several other properties of rest-frame UV emission lines. Our analysis suggests that these correction methods are of limited applicability, mostly because all of them depend on correlations that are driven by the linewidth of the C IV profile itself and not by an interconnection between the linewidth of the C IV line with the linewidth of the low ionization lines. Our results show that optical C IV-based mass estimates at high redshift cannot be a proper replacement for estimates based on IR spectroscopy of low ionization lines like Hα, Hβ and Mg II.

Synthesis of urban greenhouse gas emission estimates from the Indianapolis Flux Experiment (INFLUX)

NASA Astrophysics Data System (ADS)

Turnbull, J. C.; Davis, K. J.; Deng, A.; Lauvaux, T.; Miles, N. L.; Richardson, S.; Sarmiento, D. P.; Wu, K.; Brewer, A.; Hardesty, R. M.; McKain, K.; Sweeney, C.; Gurney, K. R.; Liang, J.; O'Keeffe, D.; Patarasuk, R.; Cambaliza, M. O. L.; Harvey, R. M.; Heimburger, A. M. F.; Shepson, P. B.; Karion, A.; Lopez-Coto, I.; Prasad, K.; Whetstone, J. R.

2016-12-01

The Indianapolis Flux Experiment (INFLUX) is testing the boundaries of our ability to use atmospheric measurements to quantify urban greenhouse gas (GHG) emissions. The project brings together high-resolution (in both space and time) inventory assessments, a multi-year record of in situ CO2, CH4and CO from tower-based and aircraft-based atmospheric measurements along with a complementary suite of 35 trace gases and isotopes from flasks collected at the same sites, and atmospheric modelling. Together, these provide high-accuracy, high-resolution, continuous monitoring of emissions of GHGs from the city. Here we synthesize the results to date, and demonstrate broad agreement amongst city-wide emission rates determined from the various top-down and bottom-up methods. We highlight the areas where ongoing efforts are reducing uncertainties in the overall flux estimation, including accurate representation of atmospheric transport, partitioning of GHG source types and the influence of background atmospheric GHG mole fractions.

Modeling methane emissions from Arctic lakes under warming conditions

NASA Astrophysics Data System (ADS)

Zhuang, Qianlai; Tan, Zeli

2014-05-01

To investigate the response of methane emissions from arctic lakes, a process-based climate-sensitive lake methane model is developed. The processes of methane production, oxidation and transport are modeled within a one-dimensional water and sediment column. Dynamics of point-source ebullition seeps are explicitly modeled. The model was calibrated and verified using observational data in the region. The model was further used to estimate the lake methane emissions from the Arctic from 2002 to 2004. We estimate that the total amount of methane emissions is 24.9 Tg CH4 yr-1, which is consistent with a recent estimation of 24±10 Tg CH4 yr-1 and two-fold of methane emissions from natural wetlands in the north of 60 oN. The methane emission rate of lakes spatially varies over high latitudes from 170.5 mg CH4 m-2 day-1 in northern Siberia to only 10.1 mg CH4 m-2 day-1 in northern Europe. A projection assuming 2-7.5oC warming and 15-25% expansion of lake coverage shows that the total amount of methane emitted from Arctic lakes will increase to 29.8-35.6 Tg CH4 yr-1.

Wall Paint Exposure Assessment Model (WPEM)

EPA Pesticide Factsheets

WPEM uses mathematical models developed from small chamber data to estimate the emissions of chemicals from oil-based (alkyd) and latex wall paint which is then combined with detailed use, workload and occupancy data to estimate user exposure.

A 3-D model analysis of the slowdown and interannual variability in the methane growth rate from 1988 to 1997

NASA Astrophysics Data System (ADS)

Wang, James S.; Logan, Jennifer A.; McElroy, Michael B.; Duncan, Bryan N.; Megretskaia, Inna A.; Yantosca, Robert M.

2004-09-01

Methane has exhibited significant interannual variability with a slowdown in its growth rate beginning in the 1980s. We use a 3-D chemical transport model accounting for interannually varying emissions, transport, and sinks to analyze trends in CH4 from 1988 to 1997. Variations in CH4 sources were based on meteorological and country-level socioeconomic data. An inverse method was used to optimize the strengths of sources and sinks for a base year, 1994. We present a best-guess budget along with sensitivity tests. The analysis suggests that the sum of emissions from animals, fossil fuels, landfills, and wastewater estimated using Intergovernmental Panel on Climate Change default methodology is too high. Recent bottom-up estimates of the source from rice paddies appear to be too low. Previous top-down estimates of emissions from wetlands may be a factor of 2 higher than bottom-up estimates because of possible overestimates of OH. The model captures the general decrease in the CH4 growth rate observed from 1988 to 1997 and the anomalously low growth rates during 1992-1993. The slowdown in the growth rate is attributed to a combination of slower growth of sources and increases in OH. The economic downturn in the former Soviet Union and Eastern Europe made a significant contribution to the decrease in the growth rate of emissions. The 1992-1993 anomaly can be explained by fluctuations in wetland emissions and OH after the eruption of Mount Pinatubo. The results suggest that the recent slowdown of CH4 may be temporary.

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 22 2012-07-01 2012-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 21 2011-07-01 2011-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.305 - Procedures for estimating missing data.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 22 2013-07-01 2013-07-01 false Procedures for estimating missing data... Use § 98.305 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

40 CFR 98.455 - Procedures for estimating missing data.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 21 2014-07-01 2014-07-01 false Procedures for estimating missing data... § 98.455 Procedures for estimating missing data. A complete record of all measured parameters used in the GHG emissions calculations is required. Replace missing data, if needed, based on data from...

Isoprene emissions over Asia 1979-2012 : impact of climate and land use changes

NASA Astrophysics Data System (ADS)

Stavrakou, Trissevgeni; Müller, Jean-Francois; Bauwens, Maite; Guenther, Alex; De Smedt, Isabelle; Van Roozendael, Michel

2014-05-01

Due to the scarcity of observational contraints and the rapidly changing environment in East and Southeast Asia, isoprene emissions predicted by models are expected to bear substantial uncertainties. This study aims at improving upon current bottom-up estimates, and investigate the temporal evolution of isoprene fluxes in Asia over 1979-2012. For that, we use the MEGAN model and incorporate (i) changes in land use, including the rapid expansion of oil palms, (ii) meteorological variability, (iii) long-term changes in solar radiation constrained by surface network measurements, and (iv) recent experimental evidence that South Asian forests are much weaker isoprene emitters than previously assumed. These effects lead to a significant reduction of the total isoprene fluxes over the studied domain compared to the standard simulation. The bottom-up emissions are evaluated using satellite-based emission estimates derived from inverse modelling constrained by GOME-2/MetOp-A formaldehyde columns through 2007-2012. The top-down estimates support our assumptions and confirm the lower isoprene emission rate in tropical forests of Indonesia and Malaysia.

Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations

NASA Astrophysics Data System (ADS)

Di Giuseppe, Francesca; Rémy, Samuel; Pappenberger, Florian; Wetterhall, Fredrik

2018-04-01

The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.

Biomass Combustions and Burning Emissions Inferred from GOES Fire Radiative Power

NASA Astrophysics Data System (ADS)

Zhang, X.; Kondragunta, S.; Schmidt, C.

2007-12-01

Biomass burning significantly affects air quality and climate changes. Current estimates of burning emissions are rather imprecise and vary markedly with different methodologies. This paper investigates biomass burning consumption and emissions using GOES (Geostationary Operational Environmental Satellites) WF_ABBA (Wildfire Automated Biomass Burning Algorithm) fire product. In doing this, we establish a set of representatives in diurnal patterns of half-hourly GOES Fire Radiative Power (FRP) for various ecosystems. The representative patterns are used to fill the missed and poor observations of half hourly FRP in GOES fire data for individual fire pixels. The simulated FRP is directly applied to the calculation of the biomass combusted during fire activities. The FRP-based biomass combustion is evaluated using the estimates using a traditional model which integrates burned area, fuel loading, and combustion factor. In the traditional model calculation, we derive burned areas from GOES WF_ABBA fire size. Fuel loading includes three different types (1) MODIS Vegetation Property-based Fuel System (MVPFS), (2) National Dangerous Rating Systems (NFDRS), and (3) the Fuel Characteristic Classification System (FCCS). By comparing the biomass combustions across the Contiguous United States (CONUS) from 2003-2005, we conclude that FRP is an effective tool to estimate the biomass burning emissions. Finally, we examine the temporal and spatial patterns in biomass combustions and emissions (PM2.5, CO, NH3) across the CONUS.

Agriculture is a major source of NO x pollution in California.

PubMed

Almaraz, Maya; Bai, Edith; Wang, Chao; Trousdell, Justin; Conley, Stephen; Faloona, Ian; Houlton, Benjamin Z

2018-01-01

Nitrogen oxides (NO x = NO + NO 2 ) are a primary component of air pollution-a leading cause of premature death in humans and biodiversity declines worldwide. Although regulatory policies in California have successfully limited transportation sources of NO x pollution, several of the United States' worst-air quality districts remain in rural regions of the state. Site-based findings suggest that NO x emissions from California's agricultural soils could contribute to air quality issues; however, a statewide estimate is hitherto lacking. We show that agricultural soils are a dominant source of NO x pollution in California, with especially high soil NO x emissions from the state's Central Valley region. We base our conclusion on two independent approaches: (i) a bottom-up spatial model of soil NO x emissions and (ii) top-down airborne observations of atmospheric NO x concentrations over the San Joaquin Valley. These approaches point to a large, overlooked NO x source from cropland soil, which is estimated to increase the NO x budget by 20 to 51%. These estimates are consistent with previous studies of point-scale measurements of NO x emissions from the soil. Our results highlight opportunities to limit NO x emissions from agriculture by investing in management practices that will bring co-benefits to the economy, ecosystems, and human health in rural areas of California.

Challenges and opportunities in the design and construction of a GIS-based emission inventory infrastructure for the Niger Delta region of Nigeria.

PubMed

Fagbeja, Mofoluso A; Hill, Jennifer L; Chatterton, Tim J; Longhurst, James W S; Akpokodje, Joseph E; Agbaje, Ganiy I; Halilu, Shaba A

2017-03-01

Environmental monitoring in middle- and low-income countries is hampered by many factors which include enactment and enforcement of legislations; deficiencies in environmental data reporting and documentation; inconsistent, incomplete and unverifiable data; a lack of access to data; and technical expertise. This paper describes the processes undertaken and the major challenges encountered in the construction of the first Niger Delta Emission Inventory (NDEI) for criteria air pollutants and CO 2 released from the anthropogenic activities in the region. This study focused on using publicly available government and research data. The NDEI has been designed to provide a Geographic Information System-based component of an air quality and carbon management framework. The NDEI infrastructure was designed and constructed at 1-, 10- and 20-km grid resolutions for point, line and area sources using industry standard processes and emission factors derived from activities similar to those in the Niger Delta. Due to inadequate, incomplete, potentially inaccurate and unavailable data, the infrastructure was populated with data based on a series of best possible assumptions for key emission sources. This produces outputs with variable levels of certainty, which also highlights the critical challenges in the estimation of emissions from a developing country. However, the infrastructure is functional and has the ability to produce spatially resolved emission estimates.

CO Component Estimation Based on the Independent Component Analysis

NASA Astrophysics Data System (ADS)

Ichiki, Kiyotomo; Kaji, Ryohei; Yamamoto, Hiroaki; Takeuchi, Tsutomu T.; Fukui, Yasuo

2014-01-01

Fast Independent Component Analysis (FastICA) is a component separation algorithm based on the levels of non-Gaussianity. Here we apply FastICA to the component separation problem of the microwave background, including carbon monoxide (CO) line emissions that are found to contaminate the PLANCK High Frequency Instrument (HFI) data. Specifically, we prepare 100 GHz, 143 GHz, and 217 GHz mock microwave sky maps, which include galactic thermal dust, NANTEN CO line, and the cosmic microwave background (CMB) emissions, and then estimate the independent components based on the kurtosis. We find that FastICA can successfully estimate the CO component as the first independent component in our deflection algorithm because its distribution has the largest degree of non-Gaussianity among the components. Thus, FastICA can be a promising technique to extract CO-like components without prior assumptions about their distributions and frequency dependences.

CO component estimation based on the independent component analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ichiki, Kiyotomo; Kaji, Ryohei; Yamamoto, Hiroaki

2014-01-01

Fast Independent Component Analysis (FastICA) is a component separation algorithm based on the levels of non-Gaussianity. Here we apply FastICA to the component separation problem of the microwave background, including carbon monoxide (CO) line emissions that are found to contaminate the PLANCK High Frequency Instrument (HFI) data. Specifically, we prepare 100 GHz, 143 GHz, and 217 GHz mock microwave sky maps, which include galactic thermal dust, NANTEN CO line, and the cosmic microwave background (CMB) emissions, and then estimate the independent components based on the kurtosis. We find that FastICA can successfully estimate the CO component as the first independentmore » component in our deflection algorithm because its distribution has the largest degree of non-Gaussianity among the components. Thus, FastICA can be a promising technique to extract CO-like components without prior assumptions about their distributions and frequency dependences.« less

Emissions of carbon tetrachloride from Europe

NASA Astrophysics Data System (ADS)

Graziosi, Francesco; Arduini, Jgor; Bonasoni, Paolo; Furlani, Francesco; Giostra, Umberto; Manning, Alistair J.; McCulloch, Archie; O'Doherty, Simon; Simmonds, Peter G.; Reimann, Stefan; Vollmer, Martin K.; Maione, Michela

2016-10-01

Carbon tetrachloride (CCl4) is a long-lived radiatively active compound with the ability to destroy stratospheric ozone. Due to its inclusion in the Montreal Protocol on Substances that Deplete the Ozone Layer (MP), the last two decades have seen a sharp decrease in its large-scale emissive use with a consequent decline in its atmospheric mole fractions. However, the MP restrictions do not apply to the use of carbon tetrachloride as feedstock for the production of other chemicals, implying the risk of fugitive emissions from the industry sector. The occurrence of such unintended emissions is suggested by a significant discrepancy between global emissions as derived from reported production and feedstock usage (bottom-up emissions), and those based on atmospheric observations (top-down emissions). In order to better constrain the atmospheric budget of carbon tetrachloride, several studies based on a combination of atmospheric observations and inverse modelling have been conducted in recent years in various regions of the world. This study is focused on the European scale and based on long-term high-frequency observations at three European sites, combined with a Bayesian inversion methodology. We estimated that average European emissions for 2006-2014 were 2.2 (± 0.8) Gg yr-1, with an average decreasing trend of 6.9 % per year. Our analysis identified France as the main source of emissions over the whole study period, with an average contribution to total European emissions of approximately 26 %. The inversion was also able to allow the localisation of emission "hot spots" in the domain, with major source areas in southern France, central England (UK) and Benelux (Belgium, the Netherlands, Luxembourg), where most industrial-scale production of basic organic chemicals is located. According to our results, European emissions correspond, on average, to 4.0 % of global emissions for 2006-2012. Together with other regional studies, our results allow a better constraint of the global budget of carbon tetrachloride and a better quantification of the gap between top-down and bottom-up estimates.

Inverse modelling estimates of N2O surface emissions and stratospheric losses using a global dataset

NASA Astrophysics Data System (ADS)

Thompson, R. L.; Bousquet, P.; Chevallier, F.; Dlugokencky, E. J.; Vermeulen, A. T.; Aalto, T.; Haszpra, L.; Meinhardt, F.; O'Doherty, S.; Moncrieff, J. B.; Popa, M.; Steinbacher, M.; Jordan, A.; Schuck, T. J.; Brenninkmeijer, C. A.; Wofsy, S. C.; Kort, E. A.

2010-12-01

Nitrous oxide (N2O) levels have been steadily increasing in the atmosphere over the past few decades at a rate of approximately 0.3% per year. This trend is of major concern as N2O is both a long-lived Greenhouse Gas (GHG) and an Ozone Depleting Substance (ODS), as it is a precursor of NO and NO2, which catalytically destroy ozone in the stratosphere. Recently, N2O emissions have been recognised as the most important ODS emissions and are now of greater importance than emissions of CFC's. The growth in atmospheric N2O is predominantly due to the enhancement of surface emissions by human activities. Most notably, the intensification and proliferation of agriculture since the mid-19th century, which has been accompanied by the increased input of reactive nitrogen to soils and has resulted in significant perturbations to the natural N-cycle and emissions of N2O. There exist two approaches for estimating N2O emissions, the so-called 'bottom-up' and 'top-down' approaches. Top-down approaches, based on the inversion of atmospheric measurements, require an estimate of the loss of N2O via photolysis and oxidation in the stratosphere. Uncertainties in the loss magnitude contribute uncertainties of 15 to 20% to the global annual surface emissions, complicating direct comparisons between bottom-up and top-down estimates. In this study, we present a novel inversion framework for the simultaneous optimization of N2O surface emissions and the magnitude of the loss, which avoids errors in the emissions due to incorrect assumptions about the lifetime of N2O. We use a Bayesian inversion with a variational formulation (based on 4D-Var) in order to handle very large datasets. N2O fluxes are retrieved at 4-weekly resolution over a global domain with a spatial resolution of 3.75° x 2.5° longitude by latitude. The efficacy of the simultaneous optimization of emissions and losses is tested using a global synthetic dataset, which mimics the available atmospheric data. Lastly, using real atmospheric data from the networks of NOAA, AGAGE, and CHIOTTO, and additionally aircraft data from the CARIBIC and NOAA programmes and the START campaign, we infer N2O emissions for the years 2006 to 2008. We find large N2O emissions in the tropics, namely in tropical south-east Asia, America and Africa, with notable emissions also in Europe and south Asia.

Nitrous oxide emissions estimated with the Carbon Tracker Lagrange regional inversion framework suggest the North American source comes predominantly from agricultural regions

NASA Astrophysics Data System (ADS)

Nevison, C. D.; Andrews, A. E.; Thoning, K. W.; Saikawa, E.; Dlugokencky, E. J.; Sweeney, C.; Benmergui, J. S.

2016-12-01

The Carbon Tracker Lagrange (CTL) regional inversion framework is used to estimate North American nitrous oxide (N2O) emissions of 1.6 ± 0.4 Tg N/yr over 2008-2013. More than half of the North American emissions are estimated to come from the central agricultural belt, extending from southern Canada to Texas, and are strongest in spring and early summer, consistent with a nitrogen fertilizer-driven source. The estimated N2O flux from the Midwestern corn/soybean belt and the more northerly wheat belt corresponds to 5% of synthetic + organic N fertilizer applied to those regions. While earlier regional atmospheric inversion studies have suggested that global inventories such as EDGAR may be underestimating U.S. anthropogenic N2O emissions by a factor of 3 or more, our results, integrated over a full calendar year, are generally consistent with those inventories and with global inverse model results and budget constraints. The CTL framework is a Bayesian method based on footprints from the Stochastic Time-Inverted Lagrangian Transport (STILT) model applied to atmospheric N2O data from the National Oceanic and Atmospheric Administration (NOAA) Global Greenhouse Gas Reference Network, including surface, aircraft and tall tower platforms. The CTL inversion results are sensitive to the prescribed boundary condition or background value of N2O, which is estimated based on a new Empirical BackGround (EBG) product derived from STILT back trajectories applied to NOAA data. Analysis of the N2O EBG products suggests a significant, seasonally-varying influence on surface N2O data due to the stratospheric influx of N2O-depleted air. Figure 1. Posterior annual mean N2O emissions for 2010 estimated with the CTL regional inversion framework. The locations of NOAA surface and aircraft data used in the inversion are superimposed as black circles and grey triangles, respectively. Mobile surface sites are indicated with asterisks.

Plume Tracker: Interactive mapping of volcanic sulfur dioxide emissions with high-performance radiative transfer modeling

NASA Astrophysics Data System (ADS)

Realmuto, Vincent J.; Berk, Alexander

2016-11-01

We describe the development of Plume Tracker, an interactive toolkit for the analysis of multispectral thermal infrared observations of volcanic plumes and clouds. Plume Tracker is the successor to MAP_SO2, and together these flexible and comprehensive tools have enabled investigators to map sulfur dioxide (SO2) emissions from a number of volcanoes with TIR data from a variety of airborne and satellite instruments. Our objective for the development of Plume Tracker was to improve the computational performance of the retrieval procedures while retaining the accuracy of the retrievals. We have achieved a 300 × improvement in the benchmark performance of the retrieval procedures through the introduction of innovative data binning and signal reconstruction strategies, and improved the accuracy of the retrievals with a new method for evaluating the misfit between model and observed radiance spectra. We evaluated the accuracy of Plume Tracker retrievals with case studies based on MODIS and AIRS data acquired over Sarychev Peak Volcano, and ASTER data acquired over Kilauea and Turrialba Volcanoes. In the Sarychev Peak study, the AIRS-based estimate of total SO2 mass was 40% lower than the MODIS-based estimate. This result was consistent with a 45% reduction in the AIRS-based estimate of plume area relative to the corresponding MODIS-based estimate. In addition, we found that our AIRS-based estimate agreed with an independent estimate, based on a competing retrieval technique, within a margin of ± 20%. In the Kilauea study, the ASTER-based concentration estimates from 21 May 2012 were within ± 50% of concurrent ground-level concentration measurements. In the Turrialba study, the ASTER-based concentration estimates on 21 January 2012 were in exact agreement with SO2 concentrations measured at plume altitude on 1 February 2012.

How Accurate Are Infrared Luminosities from Monochromatic Photometric Extrapolation?

NASA Astrophysics Data System (ADS)

Lin, Zesen; Fang, Guanwen; Kong, Xu

2016-12-01

Template-based extrapolations from only one photometric band can be a cost-effective method to estimate the total infrared (IR) luminosities ({L}{IR}) of galaxies. By utilizing multi-wavelength data that covers across 0.35-500 μm in GOODS-North and GOODS-South fields, we investigate the accuracy of this monochromatic extrapolated {L}{IR} based on three IR spectral energy distribution (SED) templates out to z˜ 3.5. We find that the Chary & Elbaz template provides the best estimate of {L}{IR} in Herschel/Photodetector Array Camera and Spectrometer (PACS) bands, while the Dale & Helou template performs best in Herschel/Spectral and Photometric Imaging Receiver (SPIRE) bands. To estimate {L}{IR}, we suggest that extrapolations from the available longest wavelength PACS band based on the Chary & Elbaz template can be a good estimator. Moreover, if the PACS measurement is unavailable, extrapolations from SPIRE observations but based on the Dale & Helou template can also provide a statistically unbiased estimate for galaxies at z≲ 2. The emission with a rest-frame 10-100 μm range of IR SED can be well described by all three templates, but only the Dale & Helou template shows a nearly unbiased estimate of the emission of the rest-frame submillimeter part.

A Global Catalogue of Large SO2 Sources and Emissions Derived from the Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Fioletov, Vitali E.; McLinden, Chris A.; Krotkov, Nickolay; Li, Can; Joiner, Joanna; Theys, Nicolas; Carn, Simon; Moran, Mike D.

2016-01-01

Sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor processed with the new principal component analysis (PCA) algorithm were used to detect large point emission sources or clusters of sources. The total of 491 continuously emitting point sources releasing from about 30 kt yr(exp -1) to more than 4000 kt yr(exp -1) of SO2 per year have been identified and grouped by country and by primary source origin: volcanoes (76 sources); power plants (297); smelters (53); and sources related to the oil and gas industry (65). The sources were identified using different methods, including through OMI measurements themselves applied to a new emission detection algorithm, and their evolution during the 2005- 2014 period was traced by estimating annual emissions from each source. For volcanic sources, the study focused on continuous degassing, and emissions from explosive eruptions were excluded. Emissions from degassing volcanic sources were measured, many for the first time, and collectively they account for about 30% of total SO2 emissions estimated from OMI measurements, but that fraction has increased in recent years given that cumulative global emissions from power plants and smelters are declining while emissions from oil and gas industry remained nearly constant. Anthropogenic emissions from the USA declined by 80% over the 2005-2014 period as did emissions from western and central Europe, whereas emissions from India nearly doubled, and emissions from other large SO2-emitting regions (South Africa, Russia, Mexico, and the Middle East) remained fairly constant. In total, OMI-based estimates account for about a half of total reported anthropogenic SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr(exp -1) and not detected by OMI.

Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases

NASA Astrophysics Data System (ADS)

Arora, V. K.; Scinocca, J. F.; Boer, G. J.; Christian, J. R.; Denman, K. L.; Flato, G. M.; Kharin, V. V.; Lee, W. G.; Merryfield, W. J.

2011-03-01

The response of the second-generation Canadian earth system model (CanESM2) to historical (1850-2005) and future (2006-2100) natural and anthropogenic forcing is assessed using the newly-developed representative concentration pathways (RCPs) of greenhouse gases (GHGs) and aerosols. Allowable emissions required to achieve the future atmospheric CO2 concentration pathways, are reported for the RCP 2.6, 4.5 and 8.5 scenarios. For the historical 1850-2005 period, cumulative land plus ocean carbon uptake and, consequently, cumulative diagnosed emissions compare well with observation-based estimates. The simulated historical carbon uptake is somewhat weaker for the ocean and stronger for the land relative to their observation-based estimates. The simulated historical warming of 0.9°C compares well with the observation-based estimate of 0.76 ± 0.19°C. The RCP 2.6, 4.5 and 8.5 scenarios respectively yield warmings of 1.4, 2.3, and 4.9°C and cumulative diagnosed fossil fuel emissions of 182, 643 and 1617 Pg C over the 2006-2100 period. The simulated warming of 2.3°C over the 1850-2100 period in the RCP 2.6 scenario, with the lowest concentration of GHGs, is slightly larger than the 2°C warming target set to avoid dangerous climate change by the 2009 UN Copenhagen Accord. The results of this study suggest that limiting warming to roughly 2°C by the end of this century is unlikely since it requires an immediate ramp down of emissions followed by ongoing carbon sequestration in the second half of this century.

Mixture model based joint-MAP reconstruction of attenuation and activity maps in TOF-PET

NASA Astrophysics Data System (ADS)

Hemmati, H.; Kamali-Asl, A.; Ghafarian, P.; Ay, M. R.

2018-06-01

A challenge to have quantitative positron emission tomography (PET) images is to provide an accurate and patient-specific photon attenuation correction. In PET/MR scanners, the nature of MR signals and hardware limitations have led to a real challenge on the attenuation map extraction. Except for a constant factor, the activity and attenuation maps from emission data on TOF-PET system can be determined by the maximum likelihood reconstruction of attenuation and activity approach (MLAA) from emission data. The aim of the present study is to constrain the joint estimations of activity and attenuation approach for PET system using a mixture model prior based on the attenuation map histogram. This novel prior enforces non-negativity and its hyperparameters can be estimated using a mixture decomposition step from the current estimation of the attenuation map. The proposed method can also be helpful on the solving of scaling problem and is capable to assign the predefined regional attenuation coefficients with some degree of confidence to the attenuation map similar to segmentation-based attenuation correction approaches. The performance of the algorithm is studied with numerical and Monte Carlo simulations and a phantom experiment and was compared with MLAA algorithm with and without the smoothing prior. The results demonstrate that the proposed algorithm is capable of producing the cross-talk free activity and attenuation images from emission data. The proposed approach has potential to be a practical and competitive method for joint reconstruction of activity and attenuation maps from emission data on PET/MR and can be integrated on the other methods.

Implications of near-term coal power plant retirement for SO2 and NOX and life cycle GHG emissions.

PubMed

Venkatesh, Aranya; Jaramillo, Paulina; Griffin, W Michael; Matthews, H Scott

2012-09-18

Regulations monitoring SO(2), NO(X), mercury, and other metal emissions in the U.S. will likely result in coal plant retirement in the near-term. Life cycle assessment studies have previously estimated the environmental benefits of displacing coal with natural gas for electricity generation, by comparing systems that consist of individual natural gas and coal power plants. However, such system comparisons may not be appropriate to analyze impacts of coal plant retirement in existing power fleets. To meet this limitation, simplified economic dispatch models for PJM, MISO, and ERCOT regions are developed in this study to examine changes in regional power plant dispatch that occur when coal power plants are retired. These models estimate the order in which existing power plants are dispatched to meet electricity demand based on short-run marginal costs, with cheaper plants being dispatched first. Five scenarios of coal plant retirement are considered: retiring top CO(2) emitters, top NO(X) emitters, top SO(2) emitters, small and inefficient plants, and old and inefficient plants. Changes in fuel use, life cycle greenhouse gas emissions (including uncertainty), and SO(2) and NO(X) emissions are estimated. Life cycle GHG emissions were found to decrease by less than 4% in almost all scenarios modeled. In addition, changes in marginal damage costs due to SO(2), and NO(X) emissions are estimated using the county level marginal damage costs reported in the Air Pollution Emissions Experiments and Policy (APEEP) model, which are a proxy for measuring regional impacts of SO(2) and NO(X) emissions. Results suggest that location specific parameters should be considered within environmental policy frameworks targeting coal plant retirement, to account for regional variability in the benefits of reducing the impact of SO(2) and NO(X) emissions.

Biomechanical monitoring of healing bone based on acoustic emission technology.

PubMed

Hirasawa, Yasusuke; Takai, Shinro; Kim, Wook-Cheol; Takenaka, Nobuyuki; Yoshino, Nobuyuki; Watanabe, Yoshinobu

2002-09-01

Acoustic emission testing is a well-established method for assessment of the mechanical integrity of general construction projects. The purpose of the current study was to investigate the usefulness of acoustic emission technology in monitoring the yield strength of healing callus during external fixation. Thirty-five patients with 39 long bones treated with external fixation were evaluated for fracture healing by monitoring load for the initiation of acoustic emission signal (yield strength) under axial loading. The major criteria for functional bone union based on acoustic emission testing were (1) no acoustic emission signal on full weightbearing, and (2) a higher estimated strength than body weight. The yield strength monitored by acoustic emission testing increased with the time of healing. The external fixator could be removed safely and successfully in 97% of the patients. Thus, the acoustic emission method has good potential as a reliable method for monitoring the mechanical status of healing bone.

Sensitivity of CAM-Chem/DART MOPITT CO Assimilation Performance to the Choice of Ensemble System Configuration: A Case Study for Fires in the Amazon

NASA Astrophysics Data System (ADS)

Arellano, A. F., Jr.; Tang, W.

2017-12-01

Assimilating observational data of chemical constituents into a modeling system is a powerful approach in assessing changes in atmospheric composition and estimating associated emissions. However, the results of such chemical data assimilation (DA) experiments are largely subject to various key factors such as: a) a priori information, b) error specification and representation, and c) structural biases in the modeling system. Here we investigate the sensitivity of an ensemble-based data assimilation state and emission estimates to these key factors. We focus on investigating the assimilation performance of the Community Earth System Model (CESM)/CAM-Chem with the Data Assimilation Research Testbed (DART) in representing biomass burning plumes in the Amazonia during the 2008 fire season. We conduct the following ensemble DA MOPITT CO experiments: 1) use of monthly-average NCAR's FINN surface fire emissionss, 2) use of daily FINN surface fire emissions, 3) use of daily FINN emissions with climatological injection heights, and 4) use of perturbed FINN emission parameters to represent not only the uncertainties in combustion activity but also in combustion efficiency. We show key diagnostics of assimilation performance for these experiments and verify with available ground-based and aircraft-based measurements.

Evaluating measurements of carbon dioxide emissions using a precision source--A natural gas burner.

PubMed

Bryant, Rodney; Bundy, Matthew; Zong, Ruowen

2015-07-01

A natural gas burner has been used as a precise and accurate source for generating large quantities of carbon dioxide (CO2) to evaluate emissions measurements at near-industrial scale. Two methods for determining carbon dioxide emissions from stationary sources are considered here: predicting emissions based on fuel consumption measurements-predicted emissions measurements, and direct measurement of emissions quantities in the flue gas-direct emissions measurements. Uncertainty for the predicted emissions measurement was estimated at less than 1%. Uncertainty estimates for the direct emissions measurement of carbon dioxide were on the order of ±4%. The relative difference between the direct emissions measurements and the predicted emissions measurements was within the range of the measurement uncertainty, therefore demonstrating good agreement. The study demonstrates how independent methods are used to validate source emissions measurements, while also demonstrating how a fire research facility can be used as a precision test-bed to evaluate and improve carbon dioxide emissions measurements from stationary sources. Fossil-fuel-consuming stationary sources such as electric power plants and industrial facilities account for more than half of the CO2 emissions in the United States. Therefore, accurate emissions measurements from these sources are critical for evaluating efforts to reduce greenhouse gas emissions. This study demonstrates how a surrogate for a stationary source, a fire research facility, can be used to evaluate the accuracy of measurements of CO2 emissions.

Characterization of Methane Emission Sources Using Genetic Algorithms and Atmospheric Transport Modeling

NASA Astrophysics Data System (ADS)

Cao, Y.; Cervone, G.; Barkley, Z.; Lauvaux, T.; Deng, A.; Miles, N.; Richardson, S.

2016-12-01

Fugitive methane emission rates for the Marcellus shale area are estimated using a genetic algorithm that finds optimal weights to minimize the error between simulated and observed concentrations. The overall goal is to understand the relative contribution of methane due to Shale gas extraction. Methane sensors were installed on four towers located in northeastern Pennsylvania to measure atmospheric concentrations since May 2015. Inverse Lagrangian dispersion model runs are performed from each of these tower locations for each hour of 2015. Simulated methane concentrations at each of the four towers are computed by multiplying the resulting footprints from the atmospheric simulations by thousands of emission sources grouped into 11 classes. The emission sources were identified using GIS techniques, and include conventional and unconventional wells, different types of compressor stations, pipelines, landfills, farming and wetlands. Initial estimates for each source are calculated based on emission factors from EPA and few regional studies. A genetic algorithm is then used to identify optimal emission rates for the 11 classes of methane emissions and to explore extreme events and spatial and temporal structures in the emissions associated with natural gas activities.

Estimation of radionuclide (137Cs) emission rates from a nuclear power plant accident using the Lagrangian Particle Dispersion Model (LPDM).

PubMed

Park, Soon-Ung; Lee, In-Hye; Ju, Jae-Won; Joo, Seung Jin

2016-10-01

A methodology for the estimation of the emission rate of 137 Cs by the Lagrangian Particle Dispersion Model (LPDM) with the use of monitored 137 Cs concentrations around a nuclear power plant has been developed. This method has been employed with the MM5 meteorological model in the 600 km × 600 km model domain with the horizontal grid scale of 3 km × 3 km centered at the Fukushima nuclear power plant to estimate 137 Cs emission rate for the accidental period from 00 UTC 12 March to 00 UTC 6 April 2011. The Lagrangian Particles are released continuously with the rate of one particle per minute at the first level modelled, about 15 m above the power plant site. The presently developed method was able to simulate quite reasonably the estimated 137 Cs emission rate compared with other studies, suggesting the potential usefulness of the present method for the estimation of the emission rate from the accidental power plant without detailed inventories of reactors and fuel assemblies and spent fuels. The advantage of this method is not so complicated but can be applied only based on one-time forward LPDM simulation with monitored concentrations around the power plant, in contrast to other inverse models. It was also found that continuously monitored radionuclides concentrations from possibly many sites located in all directions around the power plant are required to get accurate continuous emission rates from the accident power plant. The current methodology can also be used to verify the previous version of radionuclides emissions used among other modeling groups for the cases of intermittent or discontinuous samplings. Copyright © 2016. Published by Elsevier Ltd.

Response Surface Model (RSM)-based Benefit Per Ton Estimates

EPA Pesticide Factsheets

The tables below are updated versions of the tables appearing in The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution (Fann, Fulcher and Hubbell 2009).

Estimating emissions from adhesives and sealants uses and manufacturing for environmental risk assessments.

PubMed

Tolls, Johannes; Gómez, Divina; Guhl, Walter; Funk, Torsten; Seger, Erich; Wind, Thorsten

2016-01-01

Regulation (EC) No 1907/2006 concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) requires that environmental exposure assessments be performed for all uses of dangerous substances that are marketed in the European Union in quantities above 10 tons per year. The quantification of emissions to the environment is a key step in this process. This publication describes the derivation of release factors and gives guidance for estimating use rates for quantifying the emissions from the manufacturing and application of adhesives and sealants. Release factors available for coatings and paints are read across to adhesives or sealants based on similarities between these 2 product groups with regard to chemical composition and to processing during manufacturing and application. The granular emission scenarios in these documents are mapped to the broad emission scenarios for adhesives or sealants. According to the mapping, the worst-case release factors for coatings or paints are identified and assigned to the adhesives or sealants scenarios. The resulting 10 specific environmental release categories (SPERCs) for adhesives and sealants are defined by differentiating between solvent and nonsolvent ingredients and between water-borne and solvent-borne or solvent-free products. These cover the vast majority of the production processes and uses and are more realistic than the 5 relevant emission estimation defaults provided in the REACH guidance. They are accompanied with adhesive or sealant consumption rates in the EU and with guidance for estimating conservative substance use rates at a generic level. The approach of combining conservative SPERC release factors with conservative estimates of substance rates is likely to yield emission estimates that tend to overpredict actual releases. Because this qualifies the approach for use in lower-tier environmental exposure assessment, the Association of the European Adhesive & Sealant Industry (FEICA) SPERCs are available in several exposure assessment tools that are used under REACH. Given the limited regional variation in the manufacturing and use processes of adhesives and sealants, the SPERCs may be applicable for emission estimation not only in the EU but also in other regions. © 2015 SETAC.

A Statistical Method for Estimating Missing GHG Emissions in Bottom-Up Inventories: The Case of Fossil Fuel Combustion in Industry in the Bogota Region, Colombia

NASA Astrophysics Data System (ADS)

Jimenez-Pizarro, R.; Rojas, A. M.; Pulido-Guio, A. D.

2012-12-01

The development of environmentally, socially and financially suitable greenhouse gas (GHG) mitigation portfolios requires detailed disaggregation of emissions by activity sector, preferably at the regional level. Bottom-up (BU) emission inventories are intrinsically disaggregated, but although detailed, they are frequently incomplete. Missing and erroneous activity data are rather common in emission inventories of GHG, criteria and toxic pollutants, even in developed countries. The fraction of missing and erroneous data can be rather large in developing country inventories. In addition, the cost and time for obtaining or correcting this information can be prohibitive or can delay the inventory development. This is particularly true for regional BU inventories in the developing world. Moreover, a rather common practice is to disregard or to arbitrarily impute low default activity or emission values to missing data, which typically leads to significant underestimation of the total emissions. Our investigation focuses on GHG emissions by fossil fuel combustion in industry in the Bogota Region, composed by Bogota and its adjacent, semi-rural area of influence, the Province of Cundinamarca. We found that the BU inventories for this sub-category substantially underestimate emissions when compared to top-down (TD) estimations based on sub-sector specific national fuel consumption data and regional energy intensities. Although both BU inventories have a substantial number of missing and evidently erroneous entries, i.e. information on fuel consumption per combustion unit per company, the validated energy use and emission data display clear and smooth frequency distributions, which can be adequately fitted to bimodal log-normal distributions. This is not unexpected as industrial plant sizes are typically log-normally distributed. Moreover, our statistical tests suggest that industrial sub-sectors, as classified by the International Standard Industrial Classification (ISIC), are also well represented by log-normal distributions. Using the validated data, we tested several missing data estimation procedures, including Montecarlo sampling of the real and fitted distributions, and a per ISIC estimation based on bootstrap-calculated mean values. These results will be presented and discussed in detail. Our results suggest that the accuracy of sub-sector BU emission inventories, particularly in developing regions, could be significantly improved if they are designed and carried out to be representative sub-samples (surveys) of the actual universe of emitters. A large fraction the missing data could be subsequently estimated by robust statistical procedures provided that most of the emitters were accounted by number and ISIC.

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

NASA Astrophysics Data System (ADS)

Thornhill, D. A.; Williams, A. E.; Onasch, T. B.; Wood, E.; Herndon, S. C.; Kolb, C. E.; Knighton, W. B.; Zavala, M.; Molina, L. T.; Marr, L. C.

2010-04-01

The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are found to be responsible for 97% of total vehicular emissions of CO, 22% of NOx, 95-97% of each aromatic species, 72-85% of each carbonyl species, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction.The resulting fuel-based estimates of emissions are lower than in the official inventory for CO and NOx and higher for VOCs. For NOx, the fuel-based estimates are lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory. While conclusions regarding the inventory should be interpreted with care because of the small sample size, 3.5 h of driving, the discrepancies with the official inventory agree with those reported in other studies.

Global methane emission estimates for 2000-2012 from CarbonTracker Europe-CH4 v1.0

NASA Astrophysics Data System (ADS)

Tsuruta, Aki; Aalto, Tuula; Backman, Leif; Hakkarainen, Janne; van der Laan-Luijkx, Ingrid T.; Krol, Maarten C.; Spahni, Renato; Houweling, Sander; Laine, Marko; Dlugokencky, Ed; Gomez-Pelaez, Angel J.; van der Schoot, Marcel; Langenfelds, Ray; Ellul, Raymond; Arduini, Jgor; Apadula, Francesco; Gerbig, Christoph; Feist, Dietrich G.; Kivi, Rigel; Yoshida, Yukio; Peters, Wouter

2017-03-01

We present a global distribution of surface methane (CH4) emission estimates for 2000-2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000-2012 are 516 ± 51 Tg CH4 yr-1, with an increase of 18 Tg CH4 yr-1 from 2000-2006 to 2007-2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( < 2 Tg CH4 yr-1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr-1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16-20 Tg CH4 yr-1). However, this study could not conclusively separate a small trend in biospheric emissions (-5 to +6.9 Tg CH4 yr-1) from the much larger trend in anthropogenic emissions (15-27 Tg CH4 yr-1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

Integrating pro-environmental behavior with transportation network modeling: User and system level strategies, implementation, and evaluation

NASA Astrophysics Data System (ADS)

Aziz, H. M. Abdul

Personal transport is a leading contributor to fossil fuel consumption and greenhouse (GHG) emissions in the U.S. The U.S. Energy Information Administration (EIA) reports that light-duty vehicles (LDV) are responsible for 61% of all transportation related energy consumption in 2012, which is equivalent to 8.4 million barrels of oil (fossil fuel) per day. The carbon content in fossil fuels is the primary source of GHG emissions that links to the challenge associated with climate change. Evidently, it is high time to develop actionable and innovative strategies to reduce fuel consumption and GHG emissions from the road transportation networks. This dissertation integrates the broader goal of minimizing energy and emissions into the transportation planning process using novel systems modeling approaches. This research aims to find, investigate, and evaluate strategies that minimize carbon-based fuel consumption and emissions for a transportation network. We propose user and system level strategies that can influence travel decisions and can reinforce pro-environmental attitudes of road users. Further, we develop strategies that system operators can implement to optimize traffic operations with emissions minimization goal. To complete the framework we develop an integrated traffic-emissions (EPA-MOVES) simulation framework that can assess the effectiveness of the strategies with computational efficiency and reasonable accuracy. The dissertation begins with exploring the trade-off between emissions and travel time in context of daily travel decisions and its heterogeneous nature. Data are collected from a web-based survey and the trade-off values indicating the average additional travel minutes a person is willing to consider for reducing a lb. of GHG emissions are estimated from random parameter models. Results indicate that different trade-off values for male and female groups. Further, participants from high-income households are found to have higher trade-off values compared with other groups. Next, we propose personal mobility carbon allowance (PMCA) scheme to reduce emissions from personal travel. PMCA is a market-based scheme that allocates carbon credits to users at no cost based on the emissions reduction goal of the system. Users can spend carbon credits for travel and a market place exists where users can buy or sell credits. This dissertation addresses two primary dimensions: the change in travel behavior of the users and the impact at network level in terms of travel time and emissions when PMCA is implemented. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Random parameter models are estimated to examine the impact of PMCA on short-term travel decisions. Further, to assess the impact at system level, a multi-class dynamic user equilibrium model is formulated that captures the travel behavior under PMCA scheme. The equivalent variational inequality problem is solved using projection method. Results indicate that PMCA scheme is able to reduce GHG emissions from transportation networks. Individuals with high value of travel time (VOTT) are less sensitive to PMCA scheme in context of work trips. High and medium income users are more likely to have non-work trips with lower carbon cost (higher travel time) to save carbon credits for work trips. Next, we focus on the strategies from the perspectives of system operators in transportation networks. Learning based signal control schemes are developed that can reduce emissions from signalized urban networks. The algorithms are implemented and tested in VISSIM micro simulator. Finally, an integrated emissions-traffic simulator framework is outlined that can be used to evaluate the effectiveness of the strategies. The integrated framework uses MOVES2010b as the emissions simulator. To estimate the emissions efficiently we propose a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the link driving schedules for MOVES2010b. Test results using the data from a five-intersection corridor show that HC-DTW technique can significantly reduce emissions estimation time without compromising the accuracy. The benefits are found to be most significant when the level of congestion variation is high. In addition to finding novel strategies for reducing emissions from transportation networks, this dissertation has broader impacts on behavior based energy policy design and transportation network modeling research. The trade-off values can be a useful indicator to identify which policies are most effective to reinforce pro-environmental travel choices. For instance, the model can estimate the distribution of trade-off between emissions and travel time, and provide insights on the effectiveness of policies for New York City if we are able to collect data to construct a representative sample. The probability of route choice decisions vary across population groups and trip contexts. The probability as a function of travel and demographic attributes can be used as behavior rules for agents in an agent-based traffic simulation. Finally, the dynamic user equilibrium based network model provides a general framework for energy policies such carbon tax, tradable permit, and emissions credits system.

Global and regional emissions estimates of 1,1-difluoroethane (HFC-152a, CH3CHF2) from in situ and air archive observations

NASA Astrophysics Data System (ADS)

Simmonds, P. G.; Rigby, M.; Manning, A. J.; Lunt, M. F.; O'Doherty, S.; Young, D.; McCulloch, A.; Fraser, P. J.; Henne, S.; Vollmer, M. K.; Reimann, S.; Wenger, A.; Mühle, J.; Harth, C. M.; Salameh, P. K.; Arnold, T.; Weiss, R. F.; Krummel, P. B.; Steele, L. P.; Dunse, B. L.; Miller, B. R.; Lunder, C. R.; Hermansen, O.; Schmidbauer, N.; Saito, T.; Yokouchi, Y.; Park, S.; Li, S.; Yao, B.; Zhou, L. X.; Arduini, J.; Maione, M.; Wang, R. H. J.; Prinn, R. G.

2015-08-01

High frequency, ground-based, in situ measurements from eleven globally-distributed sites covering 1994-2014, combined with measurements of archived air samples dating from 1978 onward and atmospheric transport models, have been used to estimate the growth of 1,1-difluoroethane (HFC-152a, CH3CHF2) mole fractions in the atmosphere and the global emissions required to derive the observed growth. HFC-152a is a significant greenhouse gas but since it does not contain chlorine or bromine, HFC-152a makes no direct contribution to the destruction of stratospheric ozone and is therefore used as a substitute for the ozone depleting chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs). HFC-152a has exhibited substantial atmospheric growth since the first measurements reaching a maximum annualised global growth rate of 0.81 ± 0.05 ppt yr-1 in 2006, implying a substantial increase in emissions up to 2006. However, since 2007, the annualised rate of growth has slowed to 0.38 ± 0.04 ppt yr-1 in 2010 with a further decline to an average rate of change in 2013-2014 of -0.06 ± 0.05 ppt yr-1. The average Northern Hemisphere (NH) mixing ratio in 1994 was 1.2 ppt rising to a mixing ratio of 10.2 ppt in December 2014. Average annual mixing ratios in the Southern Hemisphere (SH) in 1994 and 2014 were 0.34 and 4.4 ppt, respectively. We estimate global emissions of HFC-152a have risen from 7.3 ± 5.6 Gg yr-1 in 1994 to a maximum of 54.4 ± 17.1 Gg yr-1 in 2011, declining to 52.5 ± 20.1 Gg yr-1 in 2014 or 7.2 ± 2.8 Tg-CO2 eq yr-1. Analysis of mixing ratio enhancements above regional background atmospheric levels suggests substantial emissions from North America, Asia and Europe. Global HFC emissions (so called "bottom up" emissions) reported by the United Nations Framework Convention on Climate Change (UNFCCC) are based on cumulative national emission data reported to the UNFCCC, which in turn are based on national consumption data. There appears to be a significant underestimate of "bottom-up" global emissions of HFC-152a, possibly arising from largely underestimated USA emissions and undeclared Asian emissions.

Derivation of burn scar depths and estimation of carbon emissions with LIDAR in Indonesian peatlands

PubMed Central

Ballhorn, Uwe; Siegert, Florian; Mason, Mike; Limin, Suwido

2009-01-01

During the 1997/98 El Niño-induced drought peatland fires in Indonesia may have released 13–40% of the mean annual global carbon emissions from fossil fuels. One major unknown in current peatland emission estimations is how much peat is combusted by fire. Using a light detection and ranging data set acquired in Central Kalimantan, Borneo, in 2007, one year after the severe peatland fires of 2006, we determined an average burn scar depth of 0.33 ± 0.18 m. Based on this result and the burned area determined from satellite imagery, we estimate that within the 2.79 million hectare study area 49.15 ± 26.81 megatons of carbon were released during the 2006 El Niño episode. This represents 10–33% of all carbon emissions from transport for the European Community in the year 2006. These emissions, originating from a comparatively small area (approximately 13% of the Indonesian peatland area), underline the importance of peat fires in the context of green house gas emissions and global warming. In the past decade severe peat fires occurred during El Niño-induced droughts in 1997, 2002, 2004, 2006, and 2009. Currently, this important source of carbon emissions is not included in IPCC carbon accounting or in regional and global carbon emission models. Precise spatial measurements of peat combusted and potential avoided emissions in tropical peat swamp forests will also be required for future emission trading schemes in the framework of Reduced Emissions from Deforestation and Degradation in developing countries. PMID:19940252

Comparison of real-world and certification emission rates for light duty gasoline vehicles.

PubMed

Khan, Tanzila; Frey, H Christopher

2018-05-01

U.S. light duty vehicles are subject to the U.S. Environmental Protection Agency (EPA) emission standards. Emission compliance is determined by certification testing of selected emissions from representative vehicles on standard driving cycles using chassis dynamometers. Test results are also used in many emission inventories. The dynamometer based emission rates are adjusted to provide the certification levels (CL), which must be lower than the standards for compliance. Although standard driving cycles are based on specific observations of real-world driving, they are not necessarily real-world representative. A systematic comparison of the real-world emission rates of U.S. light duty gasoline vehicles (LDGVs) versus CL, and emission standards has not been previously reported. The purpose of this work is to compare regulatory limits (both CLs and emission standards) and the real-world emissions of LDGVs. The sensitivity of the comparisons to cold start emission was assessed. Portable Emission Measurement Systems (PEMS) were used to measure hot stabilized exhaust emissions of 122 LDGVs on a specified 110 mile test route. Cold start emissions were measured with PEMS for a selected vehicle sample of 32 vehicles. Emissions were measured for carbon dioxide (CO 2 ), carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides (NO x ). For each vehicle, a Vehicle Specific Power (VSP) modal emission rate model was developed. The VSP modal rates were weighted by the standard driving cycles and real-world driving cycles to estimate the respective cycle average emission rates (CAERs). Measured vehicles were matched with certification test vehicles for comparison. For systematic trends in comparison, vehicles were classified into four groups based on the Tier 1 and Tier 2 emission regulation, and the vehicle type such as passenger car and passenger truck. Depending on the cycle-pollutant and the vehicle groups, hot stabilized CAERs are on average either statistically significantly higher than or significantly not different from the CLs, with the exception of CO on the US06 cycle, for which real-world rates are lower than CLs. Compared to the emission standards, hot stabilized CAERs are on average significantly lower. However, comparisons of CAERs and standards are sensitive to cold start emissions. For some combinations of pollutants and vehicle groups, cold start inclusive CAERs are higher than the corresponding CLs and as high as the standards. The CLs, which are based on standard driving cycles, tend to underestimate real-world emission rates. Therefore, emission inventory estimates using certification test results are potentially underestimated. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying the uncertainties of China's emission inventory for industrial sources: From national to provincial and city scales

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhou, Yaduan; Qiu, Liping; Zhang, Jie

2017-09-01

A comprehensive uncertainty analysis was conducted on emission inventories for industrial sources at national (China), provincial (Jiangsu), and city (Nanjing) scales for 2012. Based on various methods and data sources, Monte-Carlo simulation was applied at sector level for national inventory, and at plant level (whenever possible) for provincial and city inventories. The uncertainties of national inventory were estimated at -17-37% (expressed as 95% confidence intervals, CIs), -21-35%, -19-34%, -29-40%, -22-47%, -21-54%, -33-84%, and -32-92% for SO2, NOX, CO, TSP (total suspended particles), PM10, PM2.5, black carbon (BC), and organic carbon (OC) emissions respectively for the whole country. At provincial and city levels, the uncertainties of corresponding pollutant emissions were estimated at -15-18%, -18-33%, -16-37%, -20-30%, -23-45%, -26-50%, -33-79%, and -33-71% for Jiangsu, and -17-22%, -10-33%, -23-75%, -19-36%, -23-41%, -28-48%, -45-82%, and -34-96% for Nanjing, respectively. Emission factors (or associated parameters) were identified as the biggest contributors to the uncertainties of emissions for most source categories except iron & steel production in the national inventory. Compared to national one, uncertainties of total emissions in the provincial and city-scale inventories were not significantly reduced for most species with an exception of SO2. For power and other industrial boilers, the uncertainties were reduced, and the plant-specific parameters played more important roles to the uncertainties. Much larger PM10 and PM2.5 emissions for Jiangsu were estimated in this provincial inventory than other studies, implying the big discrepancies on data sources of emission factors and activity data between local and national inventories. Although the uncertainty analysis of bottom-up emission inventories at national and local scales partly supported the ;top-down; estimates using observation and/or chemistry transport models, detailed investigations and field measurements were recommended for further improving the emission estimates and reducing the uncertainty of inventories at local and regional scales, for both industrial and other sectors.

Global assessment of the effect of climate change on ammonia emissions from seabirds

NASA Astrophysics Data System (ADS)

Riddick, Stuart N.; Dragosits, Ulrike; Blackall, Trevor D.; Tomlinson, Sam J.; Daunt, Francis; Wanless, Sarah; Hallsworth, Stephen; Braban, Christine F.; Tang, Y. Sim; Sutton, Mark A.

2018-07-01

Seabird colonies alter the biogeochemistry of nearby ecosystems, while the associated emissions of ammonia (NH3) may cause acidification and eutrophication of finely balanced biomes. To examine the possible effects of future climate change on the magnitude and distribution of seabird NH3 emissions globally, a global seabird database was used as input to the GUANO model, a dynamic mass-flow process-based model that simulates NH3 losses from seabird colonies at an hourly resolution in relation to environmental conditions. Ammonia emissions calculated by the GUANO model were in close agreement with measured NH3 emissions across a wide range of climates. For the year 2010, the total global seabird NH3 emission is estimated at 82 [37-127] Gg year-1. This is less than previously estimated using a simple temperature-dependent empirical model, mainly due to inclusion of nitrogen wash-off from colonies during precipitation events in the GUANO model. High precipitation, especially between 40° and 60° S, results in total emissions for the penguin species that are 82% smaller than previously estimated, while for species found in dry tropical areas, emissions are 83-133% larger. Application of temperature anomalies for several IPCC scenarios for 2099 in the GUANO model indicated a predicted net increase in global seabird NH3 emissions of 27% (B1 scenario) and 39% (A2 scenario), compared with the 2010 estimates. At individual colonies, the net change was the result of influences of temperature, precipitation and relative humidity change, with smaller effects of wind-speed changes. The largest increases in NH3 emissions (mean: 60% [486 to -50] increase; A2 scenario for 2099 compared with 2010) were found for colonies 40°S to 65°N, and may lead to increased plant growth and decreased biodiversity by eliminating nitrogen sensitive plant species. Only 7% of the seabird colonies assessed globally (mainly limited to the sub-polar Southern Ocean) were estimated to experience a reduction in NH3 emission (average: -18% [-50 to 0] reduction between 2010 and 2099, A2 scenario), where an increase in precipitation was found to more than offset the effect of rising temperatures.

Impact of freeway weaving segment design on light-duty vehicle exhaust emissions.

PubMed

Li, Qing; Qiao, Fengxiang; Yu, Lei; Chen, Shuyan; Li, Tiezhu

2018-06-01

In the United States, 26% of greenhouse gas emissions is emitted from the transportation sector; these emisssions meanwhile are accompanied by enormous toxic emissions to humans, such as carbon monoxide (CO), nitrogen oxides (NO x ), and hydrocarbon (HC), approximately 2.5% and 2.44% of a total exhaust emissions for a petrol and a diesel engine, respectively. These exhaust emissions are typically subject to vehicles' intermittent operations, such as hard acceleration and hard braking. In practice, drivers are inclined to operate intermittently while driving through a weaving segment, due to complex vehicle maneuvering for weaving. As a result, the exhaust emissions within a weaving segment ought to vary from those on a basic segment. However, existing emission models usually rely on vehicle operation information, and compute a generalized emission result, regardless of road configuration. This research proposes to explore the impacts of weaving segment configuration on vehicle emissions, identify important predictors for emission estimations, and develop a nonlinear normalized emission factor (NEF) model for weaving segments. An on-board emission test was conducted on 12 subjects on State Highway 288 in Houston, Texas. Vehicles' activity information, road conditions, and real-time exhaust emissions were collected by on-board diagnosis (OBD), a smartphone-based roughness app, and a portable emission measurement system (PEMS), respectively. Five feature selection algorithms were used to identify the important predictors for the response of NEF and the modeling algorithm. The predictive power of four algorithm-based emission models was tested by 10-fold cross-validation. Results showed that emissions are also susceptible to the type and length of a weaving segment. Bagged decision tree algorithm was chosen to develop a 50-grown-tree NEF model, which provided a validation error of 0.0051. The estimated NEFs are highly correlated with the observed NEFs in the training data set as well as in the validation data set, with the R values of 0.91 and 0.90, respectively. Existing emission models usually rely on vehicle operation information to compute a generalized emission result, regardless of road configuration. In practice, while driving through a weaving segment, drivers are inclined to perform erratic maneuvers, such as hard braking and hard acceleration due to the complex weaving maneuver required. As a result, the exhaust emissions within a weaving segment vary from those on a basic segment. This research proposes to involve road configuration, in terms of the type and length of a weaving segment, in constructing an emission nonlinear model, which significantly improves emission estimations at a microscopic level.

Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040

NASA Astrophysics Data System (ADS)

Li, Cheng; Borken-Kleefeld, Jens; Zheng, Junyu; Yuan, Zibing; Ou, Jiamin; Li, Yue; Wang, Yanlong; Xu, Yuanqian

2018-05-01

Ship emissions contribute significantly to air pollution and pose health risks to residents of coastal areas in China, but the current research remains incomplete and coarse due to data availability and inaccuracy in estimation methods. In this study, an integrated approach based on the Automatic Identification System (AIS) was developed to address this problem. This approach utilized detailed information from AIS and cargo turnover and the vessel calling number information and is thereby capable of quantifying sectoral contributions by fuel types and emissions from ports, rivers, coastal traffic and over-the-horizon ship traffic. Based upon the established methodology, ship emissions in China from 2004 to 2013 were estimated, and those to 2040 at 5-year intervals under different control scenarios were projected. Results showed that for the area within 200 nautical miles (Nm) of the Chinese coast, SO2, NOx, CO, PM10, PM2.5, hydrocarbon (HC), black carbon (BC) and organic carbon (OC) emissions in 2013 were 1010, 1443, 118, 107, 87, 67, 29 and 21 kt yr-1, respectively, which doubled over these 10 years. Ship sources contributed ˜ 10 % to the total SO2 and NOx emissions in the coastal provinces of China. Emissions from the proposed Domestic Emission Control Areas (DECAs) within 12 Nm constituted approximately 40 % of the all ship emissions along the Chinese coast, and this percentage would double when the DECA boundary is extended to 100 Nm. Ship emissions in ports accounted for about one-quarter of the total emissions within 200 Nm, within which nearly 80 % of the emissions were concentrated in the top 10 busiest ports of China. SO2 emissions could be reduced by 80 % in 2020 under a 0.5 % global sulfur cap policy. In comparison, a similar reduction of NOx emissions would require significant technological change and would likely take several decades. This study provides solid scientific support for ship emissions control policy making in China. It is suggested to investigate and monitor the emissions from the shipping sector in more detail in the future.

Relative changes in CO emissions over megacities based on observations from space

NASA Astrophysics Data System (ADS)

Pommier, Matthieu; McLinden, Chris A.; Deeter, Merritt

2013-07-01

Urban areas are large sources of several air pollutants, with carbon monoxide (CO) among the largest. Yet measurement from space of their CO emissions remains elusive due to its long lifetime. Here we introduce a new method of estimating relative changes in CO emissions over megacities. A new multichannel Measurements of Pollution in the Troposphere (MOPITT) CO data product, offering improved sensitivity to the boundary layer, is used to estimate this relative change over eight megacities: Moscow, Paris, Mexico, Tehran, Baghdad, Los Angeles, Sao Paulo, and Delhi. By combining MOPITT observations with wind information from a meteorological reanalysis, changes in the CO upwind-downwind difference are used as a proxy for changes in emissions. Most locations show a clear reduction in CO emission between 2000-2003 and 2004-2008, reaching -43% over Tehran and -47% over Baghdad. There is a contrasted agreement between these results and the MACCity and Emission Database for Global Atmospheric Research v4.2 inventories.

Are Emissions of Restricted Halocarbons in the USA and Canada Still Globally Significant?

NASA Astrophysics Data System (ADS)

Hurst, D. F.; Romashkin, P. A.; Hall, B. D.; Elkins, J. W.; Lin, J. C.; Gerbig, C.; Daube, B. C.; Wofsy, S. C.

2004-12-01

The global manufacture of halocarbons regulated by the Montreal Protocol has dropped substantially in response to the January 1, 1996, production phase-out deadline (1994 for halons) for developed (Article 5) countries like the United States and Canada. Contemporary emissions of these ozone-depleting substances (ODS) emanate from ongoing production in developing countries and releases of banked halocarbons world-wide. ODS emissions in developing nations can be appraised from reported production figures, but not so for developed nations where recent manufacture is negligible. Emissions in the United States and Canada are increasingly difficult to estimate because of limited information about bank sizes and release rates in the post-production era. In addition, regional- or national-scale emission estimates should no longer be derived wholly from localized measurements because of the potentially patchy spatial distributions of modern emissions. We estimate ODS emissions in the USA and Canada from >1000 simultaneous, in situ measurements each of CO and six restricted halocarbons (CFC-11, CFC-12, CFC-113, methyl chloroform, carbon tetrachloride, and halon-1211) in and above the planetary boundary layer during the 2003 CO2 Budget and Regional Airborne - North America (COBRA-NA 2003) study. The data obtained during 87 flight hours are geographically extensive (>30,000 km) including two 11,000 km flight circuits across both countries. More than 50 pollution "events" with statistically significant ODS:CO emission ratios were sampled, and for each event we have determined a flux footprint using the Stochastic Time-Inverted Lagrangian Transport (STILT) model. The model also calculates footprint-weighted average population densities and CO fluxes which we convert to footprint-weighted average ODS fluxes using the measured ODS:CO emission ratios. Statistically robust relationships between footprint-averaged ODS fluxes and population densities for several ODS indicate that population-based extrapolations of these relationships to national levels are warranted. Emission estimates for the USA and Canada in 2003 will be presented and compared to the magnitudes of global emissions.

Performance of the JULES land surface model for UK Biogenic VOC emissions

NASA Astrophysics Data System (ADS)

Hayman, Garry; Comyn-Platt, Edward; Vieno, Massimo; Langford, Ben

2017-04-01

Emissions of biogenic non-methane volatile organic compounds (NMVOCs) are important for air quality and tropospheric composition. Through their contribution to the production of tropospheric ozone and secondary organic aerosol (SOA), biogenic VOCs indirectly contribute to climate forcing and climate feedbacks [1]. Biogenic VOCs encompass a wide range of compounds and are produced by plants for growth, development, reproduction, defence and communication [2]. There are both biological and physico-chemical controls on emissions [3]. Only a few of the many biogenic VOCs are of wider interest and only two or three (isoprene and the monoterpenes, α- and β-pinene) are represented in chemical transport models. We use the Joint UK Land Environment Simulator (JULES), the UK community land surface model, to estimate biogenic VOC emission fluxes. JULES is a process-based model that describes the water, energy and carbon balances and includes temperature, moisture and carbon stores [4, 5]. JULES currently provides emission fluxes of the 4 largest groups of biogenic VOCs: isoprene, terpenes, methanol and acetone. The JULES isoprene scheme uses gross primary productivity (GPP), leaf internal carbon and the leaf temperature as a proxy for the electron requirement for isoprene synthesis [6]. In this study, we compare JULES biogenic VOC emission estimates of isoprene and terepenes with (a) flux measurements made at selected sites in the UK and Europe and (b) gridded estimates for the UK from the EMEP/EMEP4UK atmospheric chemical transport model [7, 8], using site-specific or EMEP4UK driving meteorological data, respectively. We compare the UK-scale emission estimates with literature estimates. We generally find good agreement in the comparisons but the estimates are sensitive to the choice of the base or reference emission potentials. References (1) Unger, 2014: Geophys. Res. Lett., 41, 8563, doi:10.1002/2014GL061616; (2) Laothawornkitkul et al., 2009: New Phytol., 183, 27, doi:10.1111/j.1469-8137.2009.02859.x; (3) Grote and Niinemets, 2008: Plant Biol., 10, 8, doi:10.1055/s-2007-964975; (4) Best et al., 2011: Geosci. Model Dev., 4, 677, doi:10.5194/gmd-4-677-2011; (5) Clark et al., 2011: Geosci. Model Dev., 4, 701, doi:10.5194/gmd-4-701-2011; (6) Pacifico et al., 2011: Atmos. Chem. Phys., 11, 4371, doi:10.5194/acp-11-4371-2011; [7] Simpson et al., 2012: Atmos. Chem. Phys., 12, 7825, doi: 10.5194/acp-12-7825-2012; [8] Vieno et al., 2016: Atmos. Chem. Phys., 16, 265, doi: 10.5194/acp-16-265-2016.

Confirmation of Elevated Methane Emissions in Utah's Uintah Basin With Ground-Based Observations and a High-Resolution Transport Model

NASA Astrophysics Data System (ADS)

Foster, C. S.; Crosman, E. T.; Holland, L.; Mallia, D. V.; Fasoli, B.; Bares, R.; Horel, J.; Lin, J. C.

2017-12-01

Large CH4 leak rates have been observed in the Uintah Basin of eastern Utah, an area with over 10,000 active and producing natural gas and oil wells. In this paper, we model CH4 concentrations at four sites in the Uintah Basin and compare the simulated results to in situ observations at these sites during two spring time periods in 2015 and 2016. These sites include a baseline location (Fruitland), two sites near oil wells (Roosevelt and Castlepeak), and a site near natural gas wells (Horsepool). To interpret these measurements and relate observed CH4 variations to emissions, we carried out atmospheric simulations using the Stochastic Time-Inverted Lagrangian Transport model driven by meteorological fields simulated by the Weather Research and Forecasting and High Resolution Rapid Refresh models. These simulations were combined with two different emission inventories: (1) aircraft-derived basin-wide emissions allocated spatially using oil and gas well locations, from the National Oceanic and Atmospheric Administration (NOAA), and (2) a bottom-up inventory for the entire U.S., from the Environmental Protection Agency (EPA). At both Horsepool and Castlepeak, the diurnal cycle of modeled CH4 concentrations was captured using NOAA emission estimates but was underestimated using the EPA inventory. These findings corroborate emission estimates from the NOAA inventory, based on daytime mass balance estimates, and provide additional support for a suggested leak rate from the Uintah Basin that is higher than most other regions with natural gas and oil development.