Assessment of State-of-the-Art Dust Emission Scheme in GEOS

NASA Technical Reports Server (NTRS)

Darmenov, Anton; Liu, Xiaohong; Prigent, Catherine

2017-01-01

The GEOS modeling system has been extended with state of the art parameterization of dust emissions based on the vertical flux formulation described in Kok et al 2014. The new dust scheme was coupled with the GOCART and MAM aerosol models. In the present study we compare dust emissions, aerosol optical depth (AOD) and radiative fluxes from GEOS experiments with the standard and new dust emissions. AOD from the model experiments are also compared with AERONET and satellite based data. Based on this comparative analysis we concluded that the new parameterization improves the GEOS capability to model dust aerosols originating from African sources, however it lead to overestimation of dust emissions from Asian and Arabian sources. Further regional tuning of key parameters controlling the threshold friction velocity may be required in order to achieve more definitive and uniform improvement in the dust modeling skill.

Development of database of real-world diesel vehicle emission factors for China.

PubMed

Shen, Xianbao; Yao, Zhiliang; Zhang, Qiang; Wagner, David Vance; Huo, Hong; Zhang, Yingzhi; Zheng, Bo; He, Kebin

2015-05-01

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models. Copyright © 2015. Published by Elsevier B.V.

A model of plant isoprene emission based on available reducing power captures responses to atmospheric CO₂.

PubMed

Morfopoulos, Catherine; Sperlich, Dominik; Peñuelas, Josep; Filella, Iolanda; Llusià, Joan; Medlyn, Belinda E; Niinemets, Ülo; Possell, Malcolm; Sun, Zhihong; Prentice, Iain Colin

2014-07-01

We present a unifying model for isoprene emission by photosynthesizing leaves based on the hypothesis that isoprene biosynthesis depends on a balance between the supply of photosynthetic reducing power and the demands of carbon fixation. We compared the predictions from our model, as well as from two other widely used models, with measurements of isoprene emission from leaves of Populus nigra and hybrid aspen (Populus tremula × P. tremuloides) in response to changes in leaf internal CO2 concentration (C(i)) and photosynthetic photon flux density (PPFD) under diverse ambient CO2 concentrations (C(a)). Our model reproduces the observed changes in isoprene emissions with C(i) and PPFD, and also reproduces the tendency for the fraction of fixed carbon allocated to isoprene to increase with increasing PPFD. It also provides a simple mechanism for the previously unexplained decrease in the quantum efficiency of isoprene emission with increasing C(a). Experimental and modelled results support our hypothesis. Our model can reproduce the key features of the observations and has the potential to improve process-based modelling of isoprene emissions by land vegetation at the ecosystem and global scales. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

NASA Astrophysics Data System (ADS)

Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo

2018-02-01

Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.

Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.

A Process-based, Climate-Sensitive Model to Derive Methane Emissions from Natural Wetlands: Application to 5 Wetland Sites, Sensitivity to Model Parameters and Climate

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin

1999-01-01

Methane emissions from natural wetlands constitutes the largest methane source at present and depends highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a 1-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a 1-dimensional soil column and the three different transport mechanisms diffusion, plant-mediated transport and ebullition are modeled explicitly. The model forcing consists of daily values of soil temperature, water table and Net Primary Productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at 5 wetland sites located in North America, Europe and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed, because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to climate variations.

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...

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....

Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

NASA Astrophysics Data System (ADS)

Qiu, Feng; Dai, Guang; Zhang, Ying

According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

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.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China.

PubMed

Pei, Ling-Ling; Li, Qin; Wang, Zheng-Xin

2018-03-08

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China's pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N )) model based on the nonlinear least square (NLS) method. The Gauss-Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N ) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N ) and the NLS-based TNGM (1, N ) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO₂ and dust, alongside GDP per capita in China during the period 1996-2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N ) model presents greater precision when forecasting WDPC, SO₂ emissions and dust emissions per capita, compared to the traditional GM (1, N ) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO₂ and dust reduce accordingly.

AN APPROACH TO A UNIFIED PROCESS-BASED REGIONAL EMISSION FLUX MODELING PLATFORM

EPA Science Inventory

The trend towards episodic modeling of environmentally-dependent emissions is increasing, with models available or under development for dust, ammonia, biogenic volatile organic compounds, soil nitrous oxide, pesticides, sea salt, and chloride, mercury, and wildfire emissions. T...

Top-down constraints of regional emissions for KORUS-AQ 2016 field campaign

NASA Astrophysics Data System (ADS)

Bae, M.; Yoo, C.; Kim, H. C.; Kim, B. U.; Kim, S.

2017-12-01

Accurate estimations of emission rates form local and international sources are essential in regional air quality simulations, especially in assessing the relative contributions from international emission sources. While bottom-up constructions of emission inventories provide detailed information on specific emission types, they are limited to cover regions with rapid change of anthropogenic emissions (e.g. China) or regions without enough socioeconomic information (e.g. North Korea). We utilized space-borne monitoring of major pollutant precursors to construct a realistic emission inputs for chemistry transport models during the KORUS-AQ 2016 field campaign. Base simulation was conducted using WRF, SMOKE, and CMAQ modeling frame using CREATE 2015 (Asian countries) and CAPSS 2013 (South Korea) emissions inventories. NOx, SO2 and VOC model emissions are adjusted using the column density comparisons ratios (between modeled and observed NO2, SO2 and HCHO column densities) and emission-to-density conversion ratio (from model). Brute force perturbation method was used to separate contributions from North Korea, China and South Korea for flight pathways during the field campaign. Backward-Tracking Model Analyzer (BMA), based on NOAA HYSPLIT trajectory and dispersion model, are also utilized to track histories of chemical processes and emission source apportionment. CMAQ simulations were conducted over East Asia (27-km) and over South and North Korea (9-km) during KORUS-AQ campaign (1st May to 10th June 2016).

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.

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

Delay-feedback control strategy for reducing CO2 emission of traffic flow system

NASA Astrophysics Data System (ADS)

Zhang, Li-Dong; Zhu, Wen-Xing

2015-06-01

To study the signal control strategy for reducing traffic emission theoretically, we first presented a kind of discrete traffic flow model with relative speed term based on traditional coupled map car-following model. In the model, the relative speed difference between two successive running cars is incorporated into following vehicle's acceleration running equation. Then we analyzed its stability condition with discrete control system stability theory. Third, we designed a delay-feedback controller to suppress traffic jam and decrease traffic emission based on modern controller theory. Last, numerical simulations are made to support our theoretical results, including the comparison of models' stability analysis, the influence of model type and signal control on CO2 emissions. The results show that the temporal behavior of our model is superior to other models, and the traffic signal controller has good effect on traffic jam suppression and traffic CO2 emission, which fully supports the theoretical conclusions.

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.

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.

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.

Development , Implementation and Evaluation of a Physics-Base Windblown Dust Emission Model

EPA Science Inventory

A physics-based windblown dust emission parametrization scheme is developed and implemented in the CMAQ modeling system. A distinct feature of the present model includes the incorporation of a newly developed, dynamic relation for the surface roughness length, which is important ...

[Spatial temporal differentiation of product-based and consumption-based CO2 emissions and balance in the Beijing-Tianjin-Hebei region: an economic input- output analysis].

PubMed

Wang, Hao; Chen, Cao-cao; Pan, Tao; Liu, Chun-lan; Chen, Long; Sun, Li

2014-09-01

Distinguishing product-based and consumption-based CO2 emissions in the open economic region is the basis for differentiating the emission responsibility, which is attracting increasing attention of decision-makers'attention. The spatial and temporal characteristics of product-based and consumption-based CO2 emissions, as well as carbon balance, in 1997, 2002 and 2007 of JING- JIN-JI region were analyzed by the Economic Input-Output-Life Cycle Assessment model. The results revealed that both the product- based and consumption-based CO2 emissions in the region have been increased by about 4% annually. The percentage of CO2 emissions embodied in trade was 30% -83% , to which the domestic trading added the most. The territorial and consumption-based CO2 emissions in Hebei province were the predominant emission in JING-JIN-JI region, and the increasing speed and emission intensity were stronger than those of Beijing and Tianjin. JING-JIN-JI region was a net inflow region of CO2 emissions, and parts of the emission responsibility were transferred. Beijing and Tianjin were the net importers of CO2 emissions, and Hebei was a net outflow area of CO2 emissions. The key CO2 emission departments in the region were concentrated, and the similarity was great. The inter-regional mechanisms could be set up for joint prevention and control work. - Production and distribution of electricity, gas and water and smelting and pressing of metals had the highest reliability on CO2 emissions, and took on the responsibility of other departments. The EIO-LCA model could be used to analyze the product-based and consumption-based CO2 emissions, which is helpful for the delicate management of regional CO2 emissions reduction and policies making, and stimulating the reduction cooperation at regional scale.

Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide

NASA Astrophysics Data System (ADS)

Jalkanen, J.-P.; Johansson, L.; Kukkonen, J.; Brink, A.; Kalli, J.; Stipa, T.

2011-08-01

A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NOx, SOx and CO2. This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions surrounding the Danish Straits.

Development of a modal emissions model using data from the Cooperative Industry/Government Exhaust Emission test program

DOT National Transportation Integrated Search

2003-06-22

The Environmental Protection Agencys (EPAs) recommended model, MOBILE5a, has been : used extensively to predict emission factors based on average speeds for each fleet type. : Because average speeds are not appropriate in modeling intersections...

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.

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...

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles.

PubMed

Tóth-Nagy, Csaba; Conley, John J; Jarrett, Ronald P; Clark, Nigel N

2006-07-01

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.

Effective pollutant emission heights for atmospheric transport modelling based on real-world information.

PubMed

Pregger, Thomas; Friedrich, Rainer

2009-02-01

Emission data needed as input for the operation of atmospheric models should not only be spatially and temporally resolved. Another important feature is the effective emission height which significantly influences modelled concentration values. Unfortunately this information, which is especially relevant for large point sources, is usually not available and simple assumptions are often used in atmospheric models. As a contribution to improve knowledge on emission heights this paper provides typical default values for the driving parameters stack height and flue gas temperature, velocity and flow rate for different industrial sources. The results were derived from an analysis of the probably most comprehensive database of real-world stack information existing in Europe based on German industrial data. A bottom-up calculation of effective emission heights applying equations used for Gaussian dispersion models shows significant differences depending on source and air pollutant and compared to approaches currently used for atmospheric transport modelling.

Hot emission model for mobile sources: application to the metropolitan region of the city of Santiago, Chile.

PubMed

Corvalán, Roberto M; Osses, Mauricio; Urrutia, Cristian M

2002-02-01

Depending on the final application, several methodologies for traffic emission estimation have been developed. Emission estimation based on total miles traveled or other average factors is a sufficient approach only for extended areas such as national or worldwide areas. For road emission control and strategies design, microscale analysis based on real-world emission estimations is often required. This involves actual driving behavior and emission factors of the local vehicle fleet under study. This paper reports on a microscale model for hot road emissions and its application to the metropolitan region of the city of Santiago, Chile. The methodology considers the street-by-street hot emission estimation with its temporal and spatial distribution. The input data come from experimental emission factors based on local driving patterns and traffic surveys of traffic flows for different vehicle categories. The methodology developed is able to estimate hourly hot road CO, total unburned hydrocarbons (THCs), particulate matter (PM), and NO(x) emissions for predefined day types and vehicle categories.

Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide

NASA Astrophysics Data System (ADS)

Jalkanen, J.-P.; Johansson, L.; Kukkonen, J.; Brink, A.; Kalli, J.; Stipa, T.

2012-03-01

A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few tens of metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NOx, SOx and CO2. This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. We have also compared the annually averaged emission values with those of the corresponding EMEP inventory, As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions of the Baltic Sea surrounding the Danish Straits.

The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China

PubMed Central

Pei, Ling-Ling; Li, Qin

2018-01-01

The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. PMID:29517985

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.

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing.

PubMed

Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo

2018-04-18

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

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

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.

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

Towards a climate-dependent paradigm of ammonia emission and deposition.

PubMed

Sutton, Mark A; Reis, Stefan; Riddick, Stuart N; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R; Tang, Y Sim; Braban, Christine F; Vieno, Massimo; Dore, Anthony J; Mitchell, Robert F; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D; Milford, Celia; Flechard, Chris R; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J; Pinder, Robert W; Bash, Jesse O; Walker, John T; Simpson, David; Horváth, László; Misselbrook, Tom H; Bleeker, Albert; Dentener, Frank; de Vries, Wim

2013-07-05

Existing descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.

The 1977 emissions inventory for southeastern Virginia. [environment model of air quality based on exhaust emission from urban areas

NASA Technical Reports Server (NTRS)

Brewer, D. A.; Remsberg, E. E.; Woodbury, G. E.; Quinn, L. C.

1979-01-01

Regional tropospheric air pollution modeling and data compilation to simulate the time variation of species concentrations in and around an urban area is discussed. The methods used to compile an emissions inventory are outlined. Emissions factors for vehicular travel in the urban area are presented along with an analysis of the emission gases. Emission sources other than vehicular including industrial wastes, residential solid waste disposal, aircraft emissions, and emissions from the railroads are investigated.

A New Search Paradigm for Correlated Neutrino Emission from Discrete GRBs using Antarctic Cherenkov Telescopes in the Swift Era

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

Stamatikos, Michael; Band, David L.; JCA/UMBC, Baltimore, MD 21250

2006-05-19

We describe the theoretical modeling and analysis techniques associated with a preliminary search for correlated neutrino emission from GRB980703a, which triggered the Burst and Transient Source Experiment (BATSE GRB trigger 6891), using archived data from the Antarctic Muon and Neutrino Detector Array (AMANDA-B10). Under the assumption of associated hadronic acceleration, the expected observed neutrino energy flux is directly derived, based upon confronting the fireball phenomenology with the discrete set of observed electromagnetic parameters of GRB980703a, gleaned from ground-based and satellite observations, for four models, corrected for oscillations. Models 1 and 2, based upon spectral analysis featuring a prompt photon energymore » fit to the Band function, utilize an observed spectroscopic redshift, for isotropic and anisotropic emission geometry, respectively. Model 3 is based upon averaged burst parameters, assuming isotropic emission. Model 4 based upon a Band fit, features an estimated redshift from the lag-luminosity relation, with isotropic emission. Consistent with our AMANDA-II analysis of GRB030329, which resulted in a flux upper limit of {approx} 0.150GeV /cm2/s for model 1, we find differences in excess of an order of magnitude in the response of AMANDA-B10, among the various models for GRB980703a. Implications for future searches in the era of Swift and IceCube are discussed.« less

Reported emissions of organic gases are not consistent with observations

PubMed Central

Henry, Ronald C.; Spiegelman, Clifford H.; Collins, John F.; Park, EunSug

1997-01-01

Regulatory agencies and photochemical models of ozone rely on self-reported industrial emission rates of organic gases. Incorrect self-reported emissions can severely impact on air quality models and regulatory decisions. We compared self-reported emissions of organic gases in Houston, Texas, to measurements at a receptor site near the Houston ship channel, a major petrochemical complex. We analyzed hourly observations of total nonmethane organic carbon and 54 hydrocarbon compounds from C-2 to C-9 for the period June through November, 1993. We were able to demonstrate severe inconsistencies between reported emissions and major sources as derived from the data using a multivariate receptor model. The composition and the location of the sources as deduced from the data are not consistent with the reported industrial emissions. On the other hand, our observationally based methods did correctly identify the location and composition of a relatively small nearby chemical plant. This paper provides strong empirical evidence that regulatory agencies and photochemical models are making predictions based on inaccurate industrial emissions. PMID:11038551

DEPENDENCE OF NITRIC OXIDE EMISSIONS ON VEHICLE LOAD: RESULTS FROM THE GTRP INSTRUMENTED VEHICLE PROGRAM

EPA Science Inventory

The presentation discussed the dependence of nitric oxide (NO) emissions on vehicle load, bases on results from an instrumented-vehicle program. The accuracy and feasibility of modal emissions models depend on algorithms to allocate vehicle emissions based on a vehicle operation...

A process-based inventory model for landfill CH4 emissions inclusive of seasonal soil microclimate and CH4 oxidation

USDA-ARS?s Scientific Manuscript database

We have developed and field-validated an annual inventory model for California landfill CH4 emissions that incorporates both site-specific soil properties and soil microclimate modeling coupled to 0.5o scale global climatic models. Based on 1-D diffusion, CALMIM (California Landfill Methane Inventor...

2011 Version 6.3 Technical Support Document

EPA Pesticide Factsheets

This TSD describes how the emission inventories were prepared for air quality modeling for the years 2011, 2017, and 2025 using the 2011, version 6.2 emissions modeling platform, which is based on the 2011 National Emissions Inventory, Version 3

2011 Version 6.2 Technical Support Document

EPA Pesticide Factsheets

This TSD describes how the emission inventories were prepared for air quality modeling for the years 2011, 2017, and 2025 using the 2011, version 6.2 emissions modeling platform, which is based on the 2011 National Emissions Inventory, Version 2.

2011 Version 6.1 Technical Support Document

EPA Pesticide Factsheets

This TSD describes how the emission inventories were prepared for air quality modeling for the years 2011, 2018, and 2025 using the 2011, version 6.1 emissions modeling platform, which is based on the 2011 National Emissions Inventory, Version 1.

2011 Version 6.0 Technical Support Document

EPA Pesticide Factsheets

This TSD describes how the emission inventories were prepared for air quality modeling for the years 2011, 2018, and 2025 using the 2011, version 6.0 emissions modeling platform, which is based on the 2011 National Emissions Inventory, Version 1

An original traffic additional emission model and numerical simulation on a signalized road

NASA Astrophysics Data System (ADS)

Zhu, Wen-Xing; Zhang, Jing-Yu

2017-02-01

Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.

Study on multimodal transport route under low carbon background

NASA Astrophysics Data System (ADS)

Liu, Lele; Liu, Jie

2018-06-01

Low-carbon environmental protection is the focus of attention around the world, scientists are constantly researching on production of carbon emissions and living carbon emissions. However, there is little literature about multimodal transportation based on carbon emission at home and abroad. Firstly, this paper introduces the theory of multimodal transportation, the multimodal transport models that didn't consider carbon emissions and consider carbon emissions are analyzed. On this basis, a multi-objective programming 0-1 programming model with minimum total transportation cost and minimum total carbon emission is proposed. The idea of weight is applied to Ideal point method for solving problem, multi-objective programming is transformed into a single objective function. The optimal solution of carbon emission to transportation cost under different weights is determined by a single objective function with variable weights. Based on the model and algorithm, an example is given and the results are analyzed.

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.

Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

NASA Astrophysics Data System (ADS)

Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

2013-12-01

Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

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

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 ...

Study on Influencing Factors of Carbon Emissions from Energy Consumption of Shandong Province of China from 1995 to 2012

PubMed Central

Song, Jiekun; Song, Qing; Zhang, Dong; Lu, Youyou; Luan, Long

2014-01-01

Carbon emissions from energy consumption of Shandong province from 1995 to 2012 are calculated. Three zero-residual decomposition models (LMDI, MRCI and Shapley value models) are introduced for decomposing carbon emissions. Based on the results, Kendall coordination coefficient method is employed for testing their compatibility, and an optimal weighted combination decomposition model is constructed for improving the objectivity of decomposition. STIRPAT model is applied to evaluate the impact of each factor on carbon emissions. The results show that, using 1995 as the base year, the cumulative effects of population, per capita GDP, energy consumption intensity, and energy consumption structure of Shandong province in 2012 are positive, while the cumulative effect of industrial structure is negative. Per capita GDP is the largest driver of the increasing carbon emissions and has a great impact on carbon emissions; energy consumption intensity is a weak driver and has certain impact on carbon emissions; population plays a weak driving role, but it has the most significant impact on carbon emissions; energy consumption structure is a weak driver of the increasing carbon emissions and has a weak impact on carbon emissions; industrial structure has played a weak inhibitory role, and its impact on carbon emissions is great. PMID:24977216

2007 Version 5.0 Technical Support Document

EPA Pesticide Factsheets

Preparation of Emissions Inventories for the Version 5.0, 2007 Emissions Modeling Platform describes how emissions based on the 2008 NEI, version 2 and were processed to represent the year 2007 in support of air quality modeling of the PM NAAQS.

CROSS-SPECIES DOSE EXTRAPOLATION FOR DIESEL EMISSIONS

EPA Science Inventory

Models for cross-species (rat to human) dose extrapolation of diesel emission were evaluated for purposes of establishing guidelines for human exposure to diesel emissions (DE) based on DE toxicological data obtained in rats. Ideally, a model for this extrapolation would provide...

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.

Low Emissions and Delay Optimization for an Isolated Signalized Intersection Based on Vehicular Trajectories

PubMed Central

2015-01-01

A traditional traffic signal control system is established based on vehicular delay, queue length, saturation and other indicators. However, due to the increasing severity of urban environmental pollution issues and the development of a resource-saving and environmentally friendly social philosophy, the development of low-carbon and energy-efficient urban transport is required. This paper first defines vehicular trajectories and the calculation of vehicular emissions based on VSP. Next, a regression analysis method is used to quantify the relationship between vehicular emissions and delay, and a traffic signal control model is established to reduce emissions and delay using the enumeration method combined with saturation constraints. Finally, one typical intersection of Changchun is selected to verify the model proposed in this paper; its performance efficiency is also compared using simulations in VISSIM. The results of this study show that the proposed model can significantly reduce vehicle delay and traffic emissions simultaneously. PMID:26720095

Low Emissions and Delay Optimization for an Isolated Signalized Intersection Based on Vehicular Trajectories.

PubMed

Lin, Ciyun; Gong, Bowen; Qu, Xin

2015-01-01

A traditional traffic signal control system is established based on vehicular delay, queue length, saturation and other indicators. However, due to the increasing severity of urban environmental pollution issues and the development of a resource-saving and environmentally friendly social philosophy, the development of low-carbon and energy-efficient urban transport is required. This paper first defines vehicular trajectories and the calculation of vehicular emissions based on VSP. Next, a regression analysis method is used to quantify the relationship between vehicular emissions and delay, and a traffic signal control model is established to reduce emissions and delay using the enumeration method combined with saturation constraints. Finally, one typical intersection of Changchun is selected to verify the model proposed in this paper; its performance efficiency is also compared using simulations in VISSIM. The results of this study show that the proposed model can significantly reduce vehicle delay and traffic emissions simultaneously.

A generalised model for traffic induced road dust emissions. Model description and evaluation

NASA Astrophysics Data System (ADS)

Berger, Janne; Denby, Bruce

2011-07-01

This paper concerns the development and evaluation of a new and generalised road dust emission model. Most of today's road dust emission models are based on local measurements and/or contain empirical emission factors that are specific for a given road environment. In this study, a more generalised road dust emission model is presented and evaluated. We have based the emissions on road, tyre and brake wear rates and used the mass balance concept to describe the build-up of road dust on the road surface and road shoulder. The model separates the emissions into a direct part and a resuspension part, and treats the road surface and road shoulder as two different sources. We tested the model under idealized conditions as well as on two datasets in and just outside of Oslo in Norway during the studded tyre season. We found that the model reproduced the observed increase in road dust emissions directly after drying of the road surface. The time scale for the build-up of road dust on the road surface is less than an hour for medium to heavy traffic density. The model performs well for temperatures above 0 °C and less well during colder periods. Since the model does not yet include salting as an additional mass source, underestimations are evident under dry periods with temperatures around 0 °C, under which salting occurs. The model overestimates the measured PM 10 (particulate matter less than 10 μm in diameter) concentrations under heavy precipitation events since the model does not take the amount of precipitation into account. There is a strong sensitivity of the modelled emissions to the road surface conditions and the current parameterisations of the effect of precipitation, runoff and evaporation seem inadequate.

Trends and Patterns in a New Time Series of Natural and Anthropogenic Methane Emissions, 1980-2000

NASA Astrophysics Data System (ADS)

Matthews, E.; Bruhwiler, L.; Themelis, N. J.

2007-12-01

We report on a new time series of methane (CH4) emissions from anthropogenic and natural sources developed for a multi-decadal methane modeling study (see following presentation by Bruhwiler et al.). The emission series extends from 1980 through the early 2000s with annual emissions for all countries has several features distinct from the source histories based on IPCC methods typically employed in modeling the global methane cycle. Fossil fuel emissions rely on 7 fuel-process emission combinations and minimize reliance on highly-uncertain emission factors. Emissions from ruminant animals employ regional profiles of bovine populations that account for the influence of variable age- and size-demographics on emissions and are ~15% lower than other estimates. Waste-related emissions are developed using an approach that avoids using of data-poor emission factors and accounts for impacts of recycling and thermal treatment of waste on diverting material from landfills and CH4 capture at landfill facilities. Emissions from irrigated rice use rice-harvest areas under 3 water-management systems and a new historical data set that analyzes multiple sources for trends in water management since 1980. A time series of emissions from natural wetlands was developed by applying a multiple-regression model derived from full process-based model of Walter with analyzed meteorology from the ERA-40 reanalysis.

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.

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.

A Dynamic Evaluation Of A Model And An Estimate Of The Air Quality And Regional Climate Impacts Of Enhanced Solar Power Generation

NASA Astrophysics Data System (ADS)

Millstein, D.; Brown, N. J.; Zhai, P.; Menon, S.

2012-12-01

We use the WRF/Chem model (Weather Research and Forecasting model with chemistry) and pollutant emissions based on the EPA National Emission Inventories from 2005 and 2008 to model regional climate and air quality over the continental United States. Additionally, 2030 emission scenarios are developed to investigate the effects of future enhancements to solar power generation. Modeling covered 6 summer and 6 winter weeks each year. We model feedback between aerosols and meteorology and thus capture direct and indirect aerosol effects. The grid resolution is 25 km and includes no nesting. Between 2005 and 2008 significant emission reductions were reported in the National Emission Inventory. The 2008 weekday emissions over the continental U.S. of SO2 and NO were reduced from 2005 values by 28% and 16%, respectively. Emission reductions of this magnitude are similar in scale to the potential emission reductions from various energy policy initiatives. By evaluating modeled and observed air quality changes from 2005 to 2008, we analyze how well the model represents the effects of historical emission changes. We also gain insight into how well the model might predict the effects of future emission changes. In addition to direct comparisons of model outputs to ground and satellite observations, we compare observed differences between 2005 and 2008 to corresponding modeled differences. Modeling was extended to future scenarios (2030) to simulate air quality and regional climate effects of large-scale adoption of solar power. The 2030-year was selected to allow time for development of solar generation infrastructure. The 2030 emission scenario was scaled, with separate factors for different economic sectors, from the 2008 National Emissions Inventory. The changes to emissions caused by the introduction of large-scale solar power (here assumed to be 10% of total energy generation) are based on results from a parallel project that used an electricity grid model applied over multiple regions across the country. The regional climate and air quality effects of future large-scale solar power adoption are analyzed in the context of uncertainty quantified by the dynamic evaluation of the historical (2005 and 2008) WRF/Chem simulations.

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

NASA Astrophysics Data System (ADS)

Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

2017-12-01

A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

Response of CH4 emissions to straw and biochar applications in double-rice cropping systems: Insights from observations and modeling.

PubMed

Chen, Dan; Wang, Cong; Shen, Jianlin; Li, Yong; Wu, Jinshui

2018-04-01

Paddy soil plays an essential role in contributing to the emission of methane (CH 4 ), a potent greenhouse gas, to the atmosphere. This study aimed to demonstrate the effects of straw incorporation and straw-derived biochar amendment on CH 4 emissions from double-rice cropping fields and to explore their potential mechanisms based on in-situ field measurements conducted for a period of three years (2012-2014) and model analysis. The results showed that the improved soil aeration due to biochar amendment resulted in low CH 4 emissions and that sufficient substrate carbon availability in straw amendment treatments caused high CH 4 emissions. The newly developed CH 4 emission module for the water and nitrogen management model (WNMM), a process-based biophysical model, performed well when simulating both daily CH 4 fluxes and the annual cumulative CH 4 emissions under straw incorporation and biochar amendment. Results of our study indicate that the model has a great potential for upscaling and could benefit mechanism analyses about the factors regulating CH 4 emissions. Application of biochar into paddy fields provides a great opportunity to reduce CH 4 emissions, and the decrease in CH 4 emissions following biochar amendment with repeated crop cycles would sustain for a prolonged period. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

A 100-3000 GHz model of thermal dust emission observed by Planck, DIRBE and IRAS

NASA Astrophysics Data System (ADS)

Meisner, Aaron M.; Finkbeiner, Douglas P.

2015-01-01

We apply the Finkbeiner et al. (1999) two-component thermal dust emission model to the Planck HFI maps. This parametrization of the far-infrared dust spectrum as the sum of two modified blackbodies serves as an important alternative to the commonly adopted single modified blackbody (MBB) dust emission model. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. (1999) based on FIRAS and DIRBE. We also derive full-sky 6.1' resolution maps of dust optical depth and temperature by fitting the two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100μm data. Because our two-component model matches the dust spectrum near its peak, accounts for the spectrum's flattening at millimeter wavelengths, and specifies dust temperature at 6.1' FWHM, our model provides reliable, high-resolution thermal dust emission foreground predictions from 100 to 3000 GHz. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration (2013) single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anistropy on small angular scales. We have recently released maps and associated software utilities for obtaining thermal dust emission and reddening predictions using our Planck-based two-component model.

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

NASA Astrophysics Data System (ADS)

Jeon, Wonbae; Choi, Yunsoo; Roy, Anirban; Pan, Shuai; Price, Daniel; Hwang, Mi-Kyoung; Kim, Kyu Rang; Oh, Inbo

2018-02-01

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor ( C e ), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated C e and meteorology played an important role in the calculation of oak pollen emissions. While C e was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based C e used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.

Studies for the Loss of Atomic and Molecular Species from Io

NASA Technical Reports Server (NTRS)

Smyth, William H.

1998-01-01

Updated neutral emission rates for electron impact excitation of atomic oxygen and sulfur based upon the Collisional Radiative Equilibrium (COREQ) model have been incorporated in the neutral cloud models. An empirical model for the Io plasma torus wake has also been added in the neutral cloud model to describe important enhancements in the neutral emission rates and lifetime rates in this spatial region. New insights into Io's atmosphere and its interaction with the plasma torus are discussed. These insights are based upon an initial comparison of simultaneous lo observations on October 14, 1997, for [0I] 6300 Angstrom emissions acquired by groundbased facilities and several ultraviolet emissions acquired by HST/STIS in the form of high-spatial- resolution images for atomic oxygen and sulfur.

Towards a climate-dependent paradigm of ammonia emission and deposition

PubMed Central

Sutton, Mark A.; Reis, Stefan; Riddick, Stuart N.; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R.; Tang, Y. Sim; Braban, Christine F.; Vieno, Massimo; Dore, Anthony J.; Mitchell, Robert F.; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D.; Milford, Celia; Flechard, Chris R.; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F.; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J.; Pinder, Robert W.; Bash, Jesse O.; Walker, John T.; Simpson, David; Horváth, László; Misselbrook, Tom H.; Bleeker, Albert; Dentener, Frank; de Vries, Wim

2013-01-01

Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100. PMID:23713128

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2 O emissions.

PubMed

Ehrhardt, Fiona; Soussana, Jean-François; Bellocchi, Gianni; Grace, Peter; McAuliffe, Russel; Recous, Sylvie; Sándor, Renáta; Smith, Pete; Snow, Val; de Antoni Migliorati, Massimiliano; Basso, Bruno; Bhatia, Arti; Brilli, Lorenzo; Doltra, Jordi; Dorich, Christopher D; Doro, Luca; Fitton, Nuala; Giacomini, Sandro J; Grant, Brian; Harrison, Matthew T; Jones, Stephanie K; Kirschbaum, Miko U F; Klumpp, Katja; Laville, Patricia; Léonard, Joël; Liebig, Mark; Lieffering, Mark; Martin, Raphaël; Massad, Raia S; Meier, Elizabeth; Merbold, Lutz; Moore, Andrew D; Myrgiotis, Vasileios; Newton, Paul; Pattey, Elizabeth; Rolinski, Susanne; Sharp, Joanna; Smith, Ward N; Wu, Lianhai; Zhang, Qing

2018-02-01

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed. © 2017 John Wiley & Sons Ltd.

Modeled and observed ozone sensitivity to mobile-source emissions in Mexico City

NASA Astrophysics Data System (ADS)

Zavala, M.; Lei, W.; Molina, M. J.; Molina, L. T.

2009-01-01

The emission characteristics of mobile sources in the Mexico City Metropolitan Area (MCMA) have changed significantly over the past few decades in response to emission control policies, advancements in vehicle technologies and improvements in fuel quality, among others. Along with these changes, concurrent non-linear changes in photochemical levels and criteria pollutants have been observed, providing a unique opportunity to understand the effects of perturbations of mobile emission levels on the photochemistry in the region using observational and modeling approaches. The observed historical trends of ozone (O3), carbon monoxide (CO) and nitrogen oxides (NOx) suggest that ozone production in the MCMA has changed from a low to a high VOC-sensitive regime over a period of 20 years. Comparison of the historical emission trends of CO, NOx and hydrocarbons derived from mobile-source emission studies in the MCMA from 1991 to 2006 with the trends of the concentrations of CO, NOx, and the CO/NOx ratio during peak traffic hours also indicates that fuel-based fleet average emission factors have significantly decreased for CO and VOCs during this period whereas NOx emission factors do not show any strong trend, effectively reducing the ambient VOC/NOx ratio. This study presents the results of model analyses on the sensitivity of the observed ozone levels to the estimated historical changes in its precursors. The model sensitivity analyses used a well-validated base case simulation of a high pollution episode in the MCMA with the mathematical Decoupled Direct Method (DDM) and the standard Brute Force Method (BFM) in the 3-D CAMx chemical transport model. The model reproduces adequately the observed historical trends and current photochemical levels. Comparison of the BFM and the DDM sensitivity techniques indicates that the model yields ozone values that increase linearly with NOx emission reductions and decrease linearly with VOC emission reductions only up to 30% from the base case. We further performed emissions perturbations from the gasoline fleet, diesel fleet, all mobile (gasoline plus diesel) and all emission sources (anthropogenic plus biogenic). The results suggest that although large ozone reductions obtained in the past were from changes in emissions from gasoline vehicles, currently significant benefits could be achieved with additional emission control policies directed to regulation of VOC emissions from diesel and area sources that are high emitters of alkenes, aromatics and aldehydes.

Modeled and observed ozone sensitivity to mobile-source emissions in Mexico City

NASA Astrophysics Data System (ADS)

Zavala, M.; Lei, W. F.; Molina, M. J.; Molina, L. T.

2008-08-01

The emission characteristics of mobile sources in the Mexico City Metropolitan Area (MCMA) have changed significantly over the past few decades in response to emission control policies, advancements in vehicle technologies and improvements in fuel quality, among others. Along with these changes, concurrent non-linear changes in photochemical levels and criteria pollutants have been observed, providing a unique opportunity to understand the effects of perturbations of mobile emission levels on the photochemistry in the region using observational and modeling approaches. The observed historical trends of ozone (O3), carbon monoxide (CO) and nitrogen oxides (NOx) suggest that ozone production in the MCMA has changed from a low to a high VOC-sensitive regime over a period of 20 years. Comparison of the historical emission trends of CO, NOx and hydrocarbons derived from mobile-source emission studies in the MCMA from 1991 to 2006 with the trends of the concentrations of CO, NOx, and the CO/NOx ratio during peak traffic hours also indicates that fuel-based fleet average emission factors have significantly decreased for CO and VOCs during this period whereas NOx emission factors do not show any strong trend, effectively reducing the ambient VOC/NOx ratio. This study presents the results of model analyses on the sensitivity of the observed ozone levels to the estimated historical changes in its precursors. The model sensitivity analyses used a well-validated base case simulation of a high pollution episode in the MCMA with the mathematical Decoupled Direct Method (DDM) and the standard Brute Force Method (BFM) in the 3-D CAMx chemical transport model. The model reproduces adequately the observed historical trends and current photochemical levels. Comparison of the BFM and the DDM sensitivity techniques indicates that the model yields ozone values that increase linearly with NOx emission reductions and decrease linearly with VOC emission reductions only up to 30% from the base case. We further performed emissions perturbations from the gasoline fleet, diesel fleet, all mobile (gasoline plus diesel) and all emission sources (anthropogenic plus biogenic). The results suggest that although large ozone reductions obtained in the past were from changes in emissions from gasoline vehicles, currently significant benefits could be achieved with additional emission control policies directed to regulation of VOC emissions from diesel and area sources that are high emitters of alkenes, aromatics and aldehydes.

Modeling the weekly cycle of NOx and CO emissions and their impacts on O3 in the Los Angeles-South Coast Air Basin during the CalNex 2010 field campaign

NASA Astrophysics Data System (ADS)

Kim, S.-W.; McDonald, B. C.; Baidar, S.; Brown, S. S.; Dube, B.; Ferrare, R. A.; Frost, G. J.; Harley, R. A.; Holloway, J. S.; Lee, H.-J.; McKeen, S. A.; Neuman, J. A.; Nowak, J. B.; Oetjen, H.; Ortega, I.; Pollack, I. B.; Roberts, J. M.; Ryerson, T. B.; Scarino, A. J.; Senff, C. J.; Thalman, R.; Trainer, M.; Volkamer, R.; Wagner, N.; Washenfelder, R. A.; Waxman, E.; Young, C. J.

2016-02-01

We developed a new nitrogen oxide (NOx) and carbon monoxide (CO) emission inventory for the Los Angeles-South Coast Air Basin (SoCAB) expanding the Fuel-based Inventory for motor-Vehicle Emissions and applied it in regional chemical transport modeling focused on the California Nexus of Air Quality and Climate Change (CalNex) 2010 field campaign. The weekday NOx emission over the SoCAB in 2010 is 620 t d-1, while the weekend emission is 410 t d-1. The NOx emission decrease on weekends is caused by reduced diesel truck activities. Weekday and weekend CO emissions over this region are similar: 2340 and 2180 t d-1, respectively. Previous studies reported large discrepancies between the airborne observations of NOx and CO mixing ratios and the model simulations for CalNex based on the available bottom-up emission inventories. Utilizing the newly developed emission inventory in this study, the simulated NOx and CO mixing ratios agree with the observations from the airborne and the ground-based in situ and remote sensing instruments during the field study. The simulations also reproduce the weekly cycles of these chemical species. Both the observations and the model simulations indicate that decreased NOx on weekends leads to enhanced photochemistry and increase of O3 and Ox (=O3 + NO2) in the basin. The emission inventory developed in this study can be extended to different years and other urban regions in the U.S. to study the long-term trends in O3 and its precursors with regional chemical transport models.

Determining the Uncertainties in Prescribed Burn Emissions Through Comparison of Satellite Estimates to Ground-based Estimates and Air Quality Model Evaluations in Southeastern US

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A. G.

2016-12-01

Prescribed burning is practiced throughout the US, and most widely in the Southeast, for the purpose of maintaining and improving the ecosystem, and reducing the wildfire risk. However, prescribed burn emissions contribute significantly to the of trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, prescribed burns can lead to major health and environmental problems. Air quality modeling efforts are under way to assess the impacts of prescribed burn emissions. Operational forecasts of the impacts are also emerging for use in dynamic management of air quality as well as the burns. Unfortunately, large uncertainties exist in the process of estimating prescribed burn emissions and these uncertainties limit the accuracy of the burn impact predictions. Prescribed burn emissions are estimated by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels, their consumption amounts, and the progression of the fire, ground-based estimates are more accurate. In the absence of such information satellites remain as the only reliable source for emission estimation. To determine the level of uncertainty in prescribed burn emissions, we compared estimates derived from a burn permit database and other ground-based information to the estimates by the Biomass Burning Emissions Product derived from a constellation of NOAA and NASA satellites. Using these emissions estimates we conducted simulations with the Community Multiscale Air Quality (CMAQ) model and predicted trace gas and particulate matter concentrations throughout the Southeast for two consecutive burn seasons (2015 and 2016). In this presentation, we will compare model predicted concentrations to measurements at monitoring stations and evaluate if the differences are commensurate with our emission uncertainty estimates. We will also investigate if spatial and temporal patterns in the differences reveal the sources of the uncertainty in the prescribed burn emission estimates.

Study of CNG/diesel dual fuel engine's emissions by means of RBF neural network.

PubMed

Liu, Zhen-tao; Fei, Shao-mei

2004-08-01

Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFEmain performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx, emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.

System-wide emissions implications of increased wind power penetration.

PubMed

Valentino, Lauren; Valenzuela, Viviana; Botterud, Audun; Zhou, Zhi; Conzelmann, Guenter

2012-04-03

This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

Impacts of prescribed fires on air quality over the Southeastern United States in spring based on modeling and ground/satellite measurements.

PubMed

Zeng, Tao; Wang, Yuhang; Yoshida, Yasuko; Tian, Di; Russell, Amistead G; Barnard, William R

2008-11-15

Prescribed burning is a large aerosol source in the southeastern United States. Its air quality impact is investigated using 3-D model simulations and analysis of ground and satellite observations. Fire emissions for 2002 are calculated based on a recently developed VISTAS emission inventory. March was selected for the investigation because it is the most active prescribed fire month. Inclusion of fire emissions significantly improved model performance. Model results show that prescribed fire emissions lead to approximately 50% enhancements of mean OC and EC concentrations in the Southeast and a daily increase of PM2.5 up to 25 microg m(-3), indicating that fire emissions can lead to PM2.5 nonattainment in affected regions. Surface enhancements of CO up to 200 ppbv are found. Fire count measurements from the moderate resolution imaging spectroradiometer (MODIS) onboard the NASA Terra satellite show large springtime burning in most states, which is consistent with the emission inventory. These measurements also indicate that the inventory may underestimate fire emissions in the summer.

A model for inventory of ammonia emissions from agriculture in the Netherlands

NASA Astrophysics Data System (ADS)

Velthof, G. L.; van Bruggen, C.; Groenestein, C. M.; de Haan, B. J.; Hoogeveen, M. W.; Huijsmans, J. F. M.

2012-01-01

Agriculture is the major source of ammonia (NH 3). Methodologies are needed to quantify national NH 3 emissions and to identify the most effective options to mitigate NH 3 emissions. Generally, NH 3 emissions from agriculture are quantified using a nitrogen (N) flow approach, in which the NH 3 emission is calculated from the N flows and NH 3 emission factors. Because of the direct dependency between NH 3 volatilization and Total Ammoniacal N (TAN; ammonium-N + N compounds readily broken down to ammonium) an approach based on TAN is preferred to calculate NH 3 emission instead of an approach based on total N. A TAN-based NH 3-inventory model was developed, called NEMA (National Emission Model for Ammonia). The total N excretion and the fraction of TAN in the excreted N are calculated from the feed composition and N digestibility of the components. TAN-based emission factors were derived or updated for housing systems, manure storage outside housing, manure application techniques, N fertilizer types, and grazing. The NEMA results show that the total NH 3 emission from agriculture in the Netherlands in 2009 was 88.8 Gg NH 3-N, of which 50% from housing, 37% from manure application, 9% from mineral N fertilizer, 3% from outside manure storage, and 1% from grazing. Cattle farming was the dominant source of NH 3 in the Netherlands (about 50% of the total NH 3 emission). The NH 3 emission expressed as percentage of the excreted N was 22% of the excreted N for poultry, 20% for pigs, 15% for cattle, and 12% for other livestock, which is mainly related to differences in emissions from housing systems. The calculated ammonia emission was most sensitive to changes in the fraction of TAN in the excreted manure and to the emission factor of manure application. From 2011, NEMA will be used as official methodology to calculate the national NH 3 emission from agriculture in the Netherlands.

A new proposal for greenhouse gas emissions responsibility allocation: best available technologies approach.

PubMed

Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo

2014-01-01

In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.

Global emissions of PM10 and PM2.5 from agricultural tillage and harvesting operations

NASA Astrophysics Data System (ADS)

Chen, W.; Tong, D.; Lee, P.

2014-12-01

Soil particles emitted during agricultural activities is a major recurring source contributing to atmospheric aerosol loading. Emission inventories of agricultural dust emissions have been compiled in several regions. These inventories, compiled based on historic survey and activity data, may reflect the current emission strengths that introduce large uncertainties when they are used to drive chemical transport models. In addition, there is no global emission inventory of agricultural dust emissions required to support global air quality and climate modeling. In this study, we present our recent efforts to develop a global emission inventory of PM10 and PM2.5 released from field tillage and harvesting operations using an emission factors-based approach. Both major crops (e.g., wheat and corn) and forage production were considered. For each crop or forage, information of crop area, crop calendar, farming activities and emission factors of specified operations were assembled. The key issue of inventory compilation is the choice of suitable emission factors for specified operations over different parts of the world. Through careful review of published emission factors, we modified the traditional emission factor-based model by multiplying correction coefficient factors to reflect the relationship between emission factors, soil texture, and climate conditions. Then, the temporal (i.e., monthly) and spatial (i.e., 0.5º resolution) distribution of agricultural PM10 and PM2.5 emissions from each and all operations were estimated for each crop or forage. Finally, the emissions from individual crops were aggregated to assemble a global inventory from agricultural operations. The inventory was verified by comparing the new data with the existing agricultural fugitive dust inventory in North America and Europe, as well as satellite observations of anthropogenic agricultural dust emissions.

Modelling the spatial distribution of ammonia emissions in the UK.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Vieno, M; Dore, A J; Misselbrook, T H; Tang, Y S; Sutton, M A

2008-08-01

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.

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.

Meteorological air quality forecasting using the WRF-Chem model during the LMOS2017 field campaign

NASA Astrophysics Data System (ADS)

Stanier, C. O.; Abdioskouei, M.; Carmichael, G. R.; Christiansen, M.; Sobhani, N.

2017-12-01

The Lake Michigan Ozone Study (LMOS 2017) occurred during May and June 2017 to address the high ozone episodes in coastal communities surrounding Lake Michigan. Aircraft, ship, mobile lab, and ground-based stations were used in this campaign to build an extensive dataset regarding ozone, its precursors, and particulate matter. The University of Iowa produced high-resolution (4x4 km2 horizontal resolution and 53 vertical levels) forecast products using the WRF-Chem modeling system in support of experimental planning during LMOS 2017. The base forecast system used WRF-Chem 3.6.1 and updated National Emission Inventory (NEI-2011v2). In the updated NEI-2011v2, we reduced the NOx emissions by 28% based on EPA's estimated NOx trends from 2011 to 2017. We ran another daily forecast (perturbed forecast) with 50% reduced NOx emission to capture the sensitivity of ozone to NOx emission and account for the impact of weekend emissions on ozone values. Preliminary in-field evaluation of model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. The model captured the variability of O3 well, but underpredicted peak ozone during high O3 episodes. In post-campaign WRF-Chem simulations, we investigated the sensitivity of the model to the hydrocarbon emission.

Changes in travel-related carbon emissions associated with modernization of services for patients with acute myocardial infarction: a case study.

PubMed

Zander, Alexis; Niggebrugge, Aphrodite; Pencheon, David; Lyratzopoulos, Georgios

2011-06-01

Little attention has been paid on the carbon footprint of different healthcare service models. We examined this question for service models for patients with acute ST elevation myocardial infarction (STEMI). We estimated carbon emissions associated with ambulance (patient) transport under a primary percutaneous coronary intervention (pPCI) care model based in tertiary centres, compared with historical emissions under a thrombolysis model based in general hospitals. We used geographical information on 41,449 hospitalizations, and published UK government fuel to carbon emissions conversion factors. The average ambulance journey required for transporting a STEMI patient to its closest care point was 13.0 km under the thrombolysis model and 42.2 km under the pPCI model, producing 3.46 and 11.2 kg of CO(2) emissions, respectively. Thus, introducing pPCI will more than triple ambulance journey associated carbon emissions (by a factor of 3.24). This ratio was robust to sensitivity analysis varying assumptions on conversion factor values; and the number of patients treated. Introducing pPCI to manage STEMI patients results in substantial carbon emissions increase. Environmental profiling of service modernization projects could motivate carbon control strategies, and care pathways design that will reduce patient transport need. Healthcare planners should consider the environmental legacy of quality improvement initiatives.

Update of NOx emission temporal profiles using CMAQ-HDDM

NASA Astrophysics Data System (ADS)

Bae, C.; Lee, J. B.; Kim, H. C.; Kim, B. U.; Kim, S.

2017-12-01

This study demonstrates the impact of revised temporal profiles of NOx emissions on air quality simulations in the Seoul Metropolitan Area (SMA), South Korea. Air pollutants such as ozone and nitrogen oxides can be harmful to the human body even with short-term exposure. Since most of air quality models use predefined temporal profiles which are often outdated or taken from different chemical environment, providing accurate temporal variation of emissions are challenging in prediction of correct local air quality. Considering secondary formation of pollutants are important in mega cities and temporal variations of emissions are not coincident with those of resultant concentrations, we utilized CMAQ-HDDM to link emissions and consequential concentrations from different time steps. Base simulations were conducted using WRF, SMOKE, and CMAQ modeling frame using CREATE 2015 and CAPSS 2013 emissions inventories for East Asia and South Korea, respectively. With current modeling system, modeled NOx concentrations underestimate 4% in the daytime (10-16 LST), but overestimate 30% in the nighttime during May to August 2015. Applying revised temporal profiles based on HDDM sensitivities, model performance was improved significantly. We conclude that the proposed temporal allocation method can be useful to reduce the model-observation discrepancies when the activity data for emission sources are difficult to obtain with a bottom-up approach.

Frequency and Angular Variations of Land Surface Microwave Emissivities: Can we Estimate SSM/T and AMSU Emissivities from SSM/I Emissivities?

NASA Technical Reports Server (NTRS)

Prigent, Catherine; Wigneron, Jean-Pierre; Rossow, William B.; Pardo-Carrion, Juan R.

1999-01-01

To retrieve temperature and humidity profiles from SSM/T and AMSU, it is important to quantify the contribution of the Earth surface emission. So far, no global estimates of the land surface emissivities are available at SSM/T and AMSU frequencies and scanning conditions. The land surface emissivities have been previously calculated for the globe from the SSM/I conical scanner between 19 and 85 GHz. To analyze the feasibility of deriving SSM/T and AMSU land surface emissivities from SSM/I emissivities, the spectral and angular variations of the emissivities are studied, with the help of ground-based measurements, models and satellite estimates. Up to 100 GHz, for snow and ice free areas, the SSM/T and AMSU emissivities can be derived with useful accuracy from the SSM/I emissivities- The emissivities can be linearly interpolated in frequency. Based on ground-based emissivity measurements of various surface types, a simple model is proposed to estimate SSM/T and AMSU emissivities for all zenith angles knowing only the emissivities for the vertical and horizontal polarizations at 53 deg zenith angle. The method is tested on the SSM/T-2 91.655 GHz channels. The mean difference between the SSM/T-2 and SSM/I-derived emissivities is less than or equal to 0.01 for all zenith angles with an r.m.s. difference of approx. = 0.02. Above 100 GHz, preliminary results are presented at 150 GHz, based on SSM/T-2 observations and are compared with the very few estimations available in the literature.

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...

Modelling carbonaceous aerosol from residential solid fuel burning with different assumptions for emissions

NASA Astrophysics Data System (ADS)

Ots, Riinu; Heal, Mathew R.; Young, Dominique E.; Williams, Leah R.; Allan, James D.; Nemitz, Eiko; Di Marco, Chiara; Detournay, Anais; Xu, Lu; Ng, Nga L.; Coe, Hugh; Herndon, Scott C.; Mackenzie, Ian A.; Green, David C.; Kuenen, Jeroen J. P.; Reis, Stefan; Vieno, Massimo

2018-04-01

Evidence is accumulating that emissions of primary particulate matter (PM) from residential wood and coal combustion in the UK may be underestimated and/or spatially misclassified. In this study, different assumptions for the spatial distribution and total emission of PM from solid fuel (wood and coal) burning in the UK were tested using an atmospheric chemical transport model. Modelled concentrations of the PM components were compared with measurements from aerosol mass spectrometers at four sites in central and Greater London (ClearfLo campaign, 2012), as well as with measurements from the UK black carbon network.The two main alternative emission scenarios modelled were Base4x and combRedist. For Base4x, officially reported PM2.5 from the residential and other non-industrial combustion source sector were increased by a factor of four. For the combRedist experiment, half of the baseline emissions from this same source were redistributed by residential population density to simulate the effect of allocating some emissions to the smoke control areas (that are assumed in the national inventory to have no emissions from this source). The Base4x scenario yielded better daily and hourly correlations with measurements than the combRedist scenario for year-long comparisons of the solid fuel organic aerosol (SFOA) component at the two London sites. However, the latter scenario better captured mean measured concentrations across all four sites. A third experiment, Redist - all emissions redistributed linearly to population density, is also presented as an indicator of the maximum concentrations an assumption like this could yield.The modelled elemental carbon (EC) concentrations derived from the combRedist experiments also compared well with seasonal average concentrations of black carbon observed across the network of UK sites. Together, the two model scenario simulations of SFOA and EC suggest both that residential solid fuel emissions may be higher than inventory estimates and that the spatial distribution of residential solid fuel burning emissions, particularly in smoke control areas, needs re-evaluation. The model results also suggest the assumed temporal profiles for residential emissions may require review to place greater emphasis on evening (including discretionary) solid fuel burning.

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.

Development of Future Scenario Emission Inventories for East Asia in Support of Multiple Modeling Studies

NASA Astrophysics Data System (ADS)

Kim, Y.; Woo, J. H.; Choi, K. C.; Lee, J. B.; Song, C. K.; Kim, S. K.; Hong, J.; Hong, S. C.; Zhang, Q.; Hong, C.; Tong, D.

2015-12-01

Future emission scenarios based on up-to-date regional socio-economic and control policy information were developed in support of climate-air quality integrated modeling research over East Asia. Two IPCC-participated Integrated Assessment Models(IAMs) were used to developed those scenario pathways. The two emission processing systems, KU-EPS and SMOKE-Asia, were used to convert these future scenario emissions to comprehensive chemical transport model-ready form. The NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment) served as the regional base-year emission inventory. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, CH4, N2O, SO2, NOx, CO, NMVOC, NH3, OC, BC, PM10, PM2.5, and mercury. Fast energy growth and aggressive penetration of the control measures make emissions projection very active for East Asia. Despite of more stringent air pollution control policies by the governments, however, air quality over the region seems not been improved as much - even worse in many cases. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are very high to effectively protect public health and ecosystems against ozone, fine particles, and other toxic pollutants in the air. After developing these long-term future emissions, therefore, we also tried to apply our future scenarios to develop the present emissions inventory for chemical weather forecasting and aircraft field campaign. On site, we will present; 1) the future scenario development framework and process methodologies, 2) initial development results of the future emission pathways, 3) present emission inventories from short-term projection, and 4) air quality modeling performance improvements over the region.

Nebular Continuum and Line Emission in Stellar Population Synthesis Models

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

Byler, Nell; Dalcanton, Julianne J.; Conroy, Charlie

Accounting for nebular emission when modeling galaxy spectral energy distributions (SEDs) is important, as both line and continuum emissions can contribute significantly to the total observed flux. In this work, we present a new nebular emission model integrated within the Flexible Stellar Population Synthesis code that computes the line and continuum emission for complex stellar populations using the photoionization code Cloudy. The self-consistent coupling of the nebular emission to the matched ionizing spectrum produces emission line intensities that correctly scale with the stellar population as a function of age and metallicity. This more complete model of galaxy SEDs will improvemore » estimates of global gas properties derived with diagnostic diagrams, star formation rates based on H α , and physical properties derived from broadband photometry. Our models agree well with results from other photoionization models and are able to reproduce observed emission from H ii regions and star-forming galaxies. Our models show improved agreement with the observed H ii regions in the Ne iii/O ii plane and show satisfactory agreement with He ii emission from z = 2 galaxies, when including rotating stellar models. Models including post-asymptotic giant branch stars are able to reproduce line ratios consistent with low-ionization emission regions. The models are integrated into current versions of FSPS and include self-consistent nebular emission predictions for MIST and Padova+Geneva evolutionary tracks.« less

A Physically based Model of the Ionizing Radiation from Active Galaxies for Photoionization Modeling

NASA Astrophysics Data System (ADS)

Thomas, A. D.; Groves, B. A.; Sutherland, R. S.; Dopita, M. A.; Kewley, L. J.; Jin, C.

2016-12-01

We present a simplified model of active galactic nucleus (AGN) continuum emission designed for photoionization modeling. The new model oxaf reproduces the diversity of spectral shapes that arise in physically based models. We identify and explain degeneracies in the effects of AGN parameters on model spectral shapes, with a focus on the complete degeneracy between the black hole mass and AGN luminosity. Our reparametrized model oxaf removes these degeneracies and accepts three parameters that directly describe the output spectral shape: the energy of the peak of the accretion disk emission {E}{peak}, the photon power-law index of the non-thermal emission Γ, and the proportion of the total flux that is emitted in the non-thermal component {p}{NT}. The parameter {E}{peak} is presented as a function of the black hole mass, AGN luminosity, and “coronal radius” of the optxagnf model upon which oxaf is based. We show that the soft X-ray excess does not significantly affect photoionization modeling predictions of strong emission lines in Seyfert narrow-line regions. Despite its simplicity, oxaf accounts for opacity effects where the accretion disk is ionized because it inherits the “color correction” of optxagnf. We use a grid of mappings photoionization models with oxaf ionizing spectra to demonstrate how predicted emission-line ratios on standard optical diagnostic diagrams are sensitive to each of the three oxaf parameters. The oxaf code is publicly available in the Astrophysics Source Code Library.

HEAVY-DUTY GREENHOUSE GAS EMISSIONS MODEL ...

EPA Pesticide Factsheets

Class 2b-8 vocational truck manufacturers and Class 7/8 tractor manufacturers would be subject to vehicle-based fuel economy and emission standards that would use a truck simulation model to evaluate the impact of the truck tires and/or tractor cab design on vehicle compliance with any new standards. The EPA has created a model called “GHG Emissions Model (GEM)”, which is specifically tailored to predict truck GHG emissions. As the model is designed for the express purpose of vehicle compliance demonstration, it is less configurable than similar commercial products and its only outputs are GHG emissions and fuel consumption. This approach gives a simple and compact tool for vehicle compliance without the overhead and costs of a more sophisticated model. Evaluation of both fuel consumption and CO2 emissions from heavy-duty highway vehicles through a whole-vehicle operation simulation model.

High-resolution simulation of link-level vehicle emissions and concentrations for air pollutants in a traffic-populated eastern Asian city

NASA Astrophysics Data System (ADS)

Zhang, Shaojun; Wu, Ye; Huang, Ruikun; Wang, Jiandong; Yan, Han; Zheng, Yali; Hao, Jiming

2016-08-01

Vehicle emissions containing air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in eastern Asia. A high-resolution emission inventory is a useful tool compared with traditional tools (e.g. registration data-based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macau, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multimodels. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays in 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macau. Second, based on a localized vehicle emission model (e.g. the emission factor model for the Beijing vehicle fleet - Macau, EMBEV-Macau), this study established a link-based vehicle emission inventory in Macau with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD (AMS/EPA Regulatory Model) model to map concentrations of CO and primary PM2.5 contributed by local vehicle emissions during weekdays in November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 26 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that the estimated CO2 emissions from gasoline vehicles agreed well with the statistical fuel consumption in Macau. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in eastern Asia.

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

NASA Astrophysics Data System (ADS)

Bonifacio, H. F.; Rotz, C. A.; Hafner, S. D.; Montes, F.; Cohen, M.; Mitloehner, F. M.

2017-03-01

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 such as those from dairy farms. A process-based model for predicting VOC emissions from silage was developed and incorporated into the Integrated Farm System Model (IFSM, v. 4.3), a whole-farm simulation of crop, dairy, and beef production systems. The performance of the IFSM silage VOC emission model was evaluated using ethanol and methanol emissions measured from conventional silage piles (CSP), silage bags (SB), total mixed rations (TMR), and loose corn silage (LCS) at a commercial dairy farm in central California. With transport coefficients for ethanol refined using experimental data from our previous studies, the model performed well in simulating ethanol emission from CSP, TMR, and LCS; its lower performance for SB could be attributed to possible changes in face conditions of SB after silage removal that are not represented in the current model. For methanol emission, lack of experimental data for refinement likely caused the underprediction for CSP and SB whereas the overprediction observed for TMR can be explained as uncertainty in measurements. Despite these limitations, the model is a valuable tool for comparing silage management options and evaluating their relative effects on the overall performance, economics, and environmental impacts of farm production. As a component of IFSM, the silage VOC emission model was used to simulate a representative dairy farm in central California. The simulation showed most silage VOC emissions were from feed lying in feed lanes and not from the exposed face of silage storages. This suggests that mitigation efforts, particularly in areas prone to ozone non-attainment status, should focus on reducing emissions during feeding. For the simulated dairy farm, a reduction of around 30% was found if cows were housed and fed in a barn rather than in an open lot, and 23% if feeds were delivered as four feedings per day rather than as one. Reducing the exposed face of storage can also be useful. Simulated use of silage bags resulted in 90% and 18% reductions in emissions from the storage face and whole farm, respectively.

Modeling Ozone in the Eastern U.S. using a Fuel-Based Mobile Source Emissions Inventory.

PubMed

McDonald, Brian C; McKeen, Stuart A; Cui, Yu Yan; Ahmadov, Ravan; Kim, Si-Wan; Frost, Gregory J; Pollack, Ilana B; Peischl, Jeff; Ryerson, Thomas B; Holloway, John S; Graus, Martin; Warneke, Carsten; Gilman, Jessica B; de Gouw, Joost A; Kaiser, Jennifer; Keutsch, Frank N; Hanisco, Thomas F; Wolfe, Glenn M; Trainer, Michael

2018-06-22

Recent studies suggest overestimates in current U.S. emission inventories of nitrogen oxides (NO x = NO + NO 2 ). Here, we expand a previously developed fuel-based inventory of motor-vehicle emissions (FIVE) to the continental U.S. for the year 2013, and evaluate our estimates of mobile source emissions with the U.S. Environmental Protection Agency's National Emissions Inventory (NEI) interpolated to 2013. We find that mobile source emissions of NO x and carbon monoxide (CO) in the NEI are higher than FIVE by 28% and 90%, respectively. Using a chemical transport model, we model mobile source emissions from FIVE, and find consistent levels of urban NO x and CO as measured during the Southeast Nexus (SENEX) Study in 2013. Lastly, we assess the sensitivity of ozone (O 3 ) over the Eastern U.S. to uncertainties in mobile source NO x emissions and biogenic volatile organic compound (VOC) emissions. The ground-level O 3 is sensitive to reductions in mobile source NO x emissions, most notably in the Southeastern U.S. and during O 3 exceedance events, under the revised standard proposed in 2015 (>70 ppb, 8 h maximum). This suggests that decreasing mobile source NO x emissions could help in meeting more stringent O 3 standards in the future.

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.

High-global warming potential F-gas emissions in California: comparison of ambient-based versus inventory-based emission estimates, and implications of refined estimates.

PubMed

Gallagher, Glenn; Zhan, Tao; Hsu, Ying-Kuang; Gupta, Pamela; Pederson, James; Croes, Bart; Blake, Donald R; Barletta, Barbara; Meinardi, Simone; Ashford, Paul; Vetter, Arnie; Saba, Sabine; Slim, Rayan; Palandre, Lionel; Clodic, Denis; Mathis, Pamela; Wagner, Mark; Forgie, Julia; Dwyer, Harry; Wolf, Katy

2014-01-21

To provide information for greenhouse gas reduction policies, the California Air Resources Board (CARB) inventories annual emissions of high-global-warming potential (GWP) fluorinated gases, the fastest growing sector of greenhouse gas (GHG) emissions globally. Baseline 2008 F-gas emissions estimates for selected chlorofluorocarbons (CFC-12), hydrochlorofluorocarbons (HCFC-22), and hydrofluorocarbons (HFC-134a) made with an inventory-based methodology were compared to emissions estimates made by ambient-based measurements. Significant discrepancies were found, with the inventory-based emissions methodology resulting in a systematic 42% under-estimation of CFC-12 emissions from older refrigeration equipment and older vehicles, and a systematic 114% overestimation of emissions for HFC-134a, a refrigerant substitute for phased-out CFCs. Initial, inventory-based estimates for all F-gas emissions had assumed that equipment is no longer in service once it reaches its average lifetime of use. Revised emission estimates using improved models for equipment age at end-of-life, inventories, and leak rates specific to California resulted in F-gas emissions estimates in closer agreement to ambient-based measurements. The discrepancies between inventory-based estimates and ambient-based measurements were reduced from -42% to -6% for CFC-12, and from +114% to +9% for HFC-134a.

Iterative Inverse Modeling for Reconciliation of Emission Inventories during the 2006 TexAQS Intensive Field Campaign

NASA Astrophysics Data System (ADS)

Xiao, X.; Cohan, D. S.

2009-12-01

Substantial uncertainties in current emission inventories have been detected by the Texas Air Quality Study 2006 (TexAQS 2006) intensive field program. These emission uncertainties have caused large inaccuracies in model simulations of air quality and its responses to management strategies. To improve the quantitative understanding of the temporal, spatial, and categorized distributions of primary pollutant emissions by utilizing the corresponding measurements collected during TexAQS 2006, we implemented both the recursive Kalman filter and a batch matrix inversion 4-D data assimilation (FDDA) method in an iterative inverse modeling framework of the CMAQ-DDM model. Equipped with the decoupled direct method, CMAQ-DDM enables simultaneous calculation of the sensitivity coefficients of pollutant concentrations to emissions to be used in the inversions. Primary pollutant concentrations measured by the multiple platforms (TCEQ ground-based, NOAA WP-3D aircraft and Ronald H. Brown vessel, and UH Moody Tower) during TexAQS 2006 have been integrated for the use in the inverse modeling. Firstly pseudo-data analyses have been conducted to assess the two methods, taking a coarse spatial resolution emission inventory as a case. Model base case concentrations of isoprene and ozone at arbitrarily selected ground grid cells were perturbed to generate pseudo measurements with different assumed Gaussian uncertainties expressed by 1-sigma standard deviations. Single-species inversions have been conducted with both methods for isoprene and NOx surface emissions from eight states in the Southeastern United States by using the pseudo measurements of isoprene and ozone, respectively. Utilization of ozone pseudo data to invert for NOx emissions serves only for the purpose of method assessment. Both the Kalman filter and FDDA methods show good performance in tuning arbitrarily shifted a priori emissions to the base case “true” values within 3-4 iterations even for the nonlinear responses of ozone to NOx emissions. While the Kalman filter has better performance under the situation of very large observational uncertainties, the batch matrix FDDA method is better suited for incorporating temporally and spatially irregular data such as those measured by NOAA aircraft and ship. After validating the methods with the pseudo data, the inverse technique is applied to improve emission estimates of NOx from different source sectors and regions in the Houston metropolitan area by using NOx measurements during TexAQS 2006. EPA NEI2005-based and Texas-specified Emission Inventories for 2006 are used as the a priori emission estimates before optimization. The inversion results will be presented and discussed. Future work will conduct inverse modeling for additional species, and then perform a multi-species inversion for emissions consistency and reconciliation with secondary pollutants such as ozone.

[Emission Factors of Vehicle Exhaust in Beijing].

PubMed

Fan, Shou-bin; Tian, Ling-di; Zhang, Dong-xu; Qu, Song

2015-07-01

Based on the investigation of basic data such as vehicle type composition, driving conditions, ambient temperature and oil quality, etc., emission factors of vehicle exhaust pollutants including carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC) and particulate matter(PM) were calculated using COPERT IV model. Emission factors of typical gasoline passenger cars and diesel trucks were measured using on-board measurement system on actual road. The measured and modeled emission factors were compared and the results showed that: the measured emission factors of CO, NOx and HC were 0. 96, 0. 64 and 4. 89 times of the modeled data for passenger cars conforming to the national IV emission standard. For the light, medium and heavy diesel trucks conforming to the national III emission standard, the measured data of CO emission factors were 1.61, 1. 07 and 1.76 times of the modeled data, respectively, the measured data of NOx emission factors were 1. 04, 1. 21 and 1. 18 times of the modeled data, and the measured data of HC emission factors were 3. 75, 1. 84 and 1. 47 times of the modeled data, while the model data of PM emission factors were 1. 31, 3. 42 and 6. 42 times of the measured data, respectively.

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.

40 CFR 600.208-12 - Calculation of FTP-based and HFET-based fuel economy and carbon-related exhaust emission values...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Calculation of FTP-based and HFET-based fuel economy and carbon-related exhaust emission values for a model type. 600.208-12 Section 600.208-12 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR...

SVR-based prediction of carbon emissions from energy consumption in Henan Province

NASA Astrophysics Data System (ADS)

Gou, Guohua

2018-02-01

This paper analyzes the advantage of support vector regression (SVR) in the prediction of carbon emission and establishes the SVR-based carbon emission prediction model. The model is established using the data of Henan’s carbon emissions and influence factors from the 1991 to 2016 to train and test and then predict the carbon emissions from 2017 to 2021. The results show that: from the perspective of carbon emission from energy consumption, it raised 224.876 million tons of carbon dioxide from 1991 to 2016, and the predicted increment from 2017 to 2021 is 30.5563million tons with an average annual growth rate at 3%. From the perspective of growth rate among the six factors related to carbon emissions it is proved that population urbanization rate per capital GDP and energy consumption per unit of GDP influences the growth rate of carbon emissions less than the proportion of secondary industry and coal consumption ratio of carbon. Finally some suggestions are proposed for the carbon emission reduction of Henan Province.

Evaluation of the effect of accounting method, IPCC v. LCA, on grass-based and confinement dairy systems' greenhouse gas emissions.

PubMed

O'Brien, D; Shalloo, L; Patton, J; Buckley, F; Grainger, C; Wallace, M

2012-09-01

Life cycle assessment (LCA) and the Intergovernmental Panel on Climate Change (IPCC) guideline methodology, which are the principal greenhouse gas (GHG) quantification methods, were evaluated in this study using a dairy farm GHG model. The model was applied to estimate GHG emissions from two contrasting dairy systems: a seasonal calving pasture-based dairy farm and a total confinement dairy system. Data used to quantify emissions from these systems originated from a research study carried out over a 1-year period in Ireland. The genetic merit of cows modelled was similar for both systems. Total mixed ration was fed in the Confinement system, whereas grazed grass was mainly fed in the grass-based system. GHG emissions from these systems were quantified per unit of product and area. The results of both methods showed that the dairy system that emitted the lowest GHG emissions per unit area did not necessarily emit the lowest GHG emissions possible for a given level of product. Consequently, a recommendation from this study is that GHG emissions be evaluated per unit of product given the growing affluent human population and increasing demand for dairy products. The IPCC and LCA methods ranked dairy systems' GHG emissions differently. For instance, the IPCC method quantified that the Confinement system reduced GHG emissions per unit of product by 8% compared with the grass-based system, but the LCA approach calculated that the Confinement system increased emissions by 16% when off-farm emissions associated with primary dairy production were included. Thus, GHG emissions should be quantified using approaches that quantify the total GHG emissions associated with the production system, so as to determine whether the dairy system was causing emissions displacement. The IPCC and LCA methods were also used in this study to simulate, through a dairy farm GHG model, what effect management changes within both production systems have on GHG emissions. The findings suggest that single changes have a small mitigating effect on GHG emissions (<5%), except for strategies used to control emissions from manure storage in the Confinement system (14% to 24%). However, when several management strategies were combined, GHG emissions per unit of product could be reduced significantly (15% to 30%). The LCA method was identified as the preferred approach to assess the effect of management changes on GHG emissions, but the analysis indicated that further standardisation of the approach is needed given the sensitivity of the approach to allocation decisions regarding milk and meat.

Comparison of emission factors for road traffic from a tunnel study (Gubrist tunnel, Switzerland) and from emission modeling

NASA Astrophysics Data System (ADS)

John, Christian; Friedrich, Rainer; Staehelin, Johannes; Schläpfer, Kurt; Stahel, Werner A.

The emission factors of NO x, VOC and CO of a road tunnel study performed in September 1993 in the Gubrist tunnel, close to Zürich (Switzerland) are compared with results of emission calculations based on recent results of dynamometric test measurements. The emission calculations are carried out with a traffic emission model taking into account the detailed composition of the vehicle fleet in the tunnel, the average speed and the gradient of the road and the special aerodynamics in a tunnel. With the exception of NO x emission factors for heavy duty vehicles no evidence for a discrepancy between the results of the tunnel study and the emission modeling was found. The measured emission factors of individual hydrocarbons of light duty vehicles were in good agreement with the expectations for most components.

Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data.

PubMed

Wang, Shaojian; Fang, Chuanglin; Li, Guangdong

2015-01-01

This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China's CO2 emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995-2011 into consideration. The results indicated that CO2 emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO2 emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO2 emissions. Conversely, energy intensity was identified as having a negative influence on CO2 emissions. In addition, the significance of the relationship between CO2 emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO2 emissions.

Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data

PubMed Central

Wang, Shaojian

2015-01-01

This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China’s CO2 emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995–2011 into consideration. The results indicated that CO2 emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO2 emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO2 emissions. Conversely, energy intensity was identified as having a negative influence on CO2 emissions. In addition, the significance of the relationship between CO2 emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO2 emissions. PMID:26397373

Environmental assessment of biofuel pathways in Ile de France based on ecosystem modeling.

PubMed

Gabrielle, Benoît; Gagnaire, Nathalie; Massad, Raia Silvia; Dufossé, Karine; Bessou, Cécile

2014-01-01

The objective of the work reported here was to reduce the uncertainty on the greenhouse gas balances of biofuels using agro-ecosystem modeling at a high resolution over the Ile-de-France region in Northern France. The emissions simulated during the feedstock production stage were input to a life-cycle assessment of candidate biofuel pathways: bioethanol from wheat, sugar-beet and miscanthus, and biodiesel from oilseed rape. Compared to the widely-used methodology based on fixed emission factors, ecosystem modeling lead to 55-70% lower estimates for N2O emissions, emphasizing the importance of regional factors. The life-cycle GHG emissions of first-generation biofuels were 50-70% lower than fossil-based equivalents, and 85% lower for cellulosic ethanol. When including indirect land-use change effects, GHG savings became marginal for biodiesel and wheat ethanol, but were positive due to direct effects for cellulosic ethanol. Copyright © 2013 Elsevier Ltd. All rights reserved.

Transport and radiative impacts of atmospheric pollen using online, observation-based emissions

NASA Astrophysics Data System (ADS)

Wozniak, M. C.; Steiner, A. L.; Solmon, F.; Li, Y.

2015-12-01

Atmospheric pollen emitted from trees and grasses exhibits both a high temporal variability and a highly localized spatial distribution that has been difficult to quantify in the atmosphere. Pollen's radiative impact is also not quantified because it is neglected in climate modeling studies. Here we couple an online, meteorological active pollen emissions model guided by observations of airborne pollen to understand the role of pollen in the atmosphere. We use existing pollen counts from 2003-2008 across the continental U.S. in conjunction with a tree database and historical meteorological data to create an observation-based phenological model that produces accurately scaled and timed emissions. These emissions are emitted and transported within the regional climate model (RegCM4) and the direct radiative effect is calculated. Additionally, we simulate the rupture of coarse pollen grains into finer particles by adding a second size mode for pollen emissions, which contributes to the shortwave radiative forcing and also has an indirect effect on climate.

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.

Reduction of CO2 emission by INCAM model in Malaysia biomass power plants during the year 2016.

PubMed

Amin, Nor Aishah Saidina; Talebian-Kiakalaieh, Amin

2018-03-01

As the world's second largest palm oil producer and exporter, Malaysia could capitalize on its oil palm biomass waste for power generation. The emission factors from this renewable energy source are far lower than that of fossil fuels. This study applies an integrated carbon accounting and mitigation (INCAM) model to calculate the amount of CO 2 emissions from two biomass thermal power plants. The CO 2 emissions released from biomass plants utilizing empty fruit bunch (EFB) and palm oil mill effluent (POME), as alternative fuels for powering steam and gas turbines, were determined using the INCAM model. Each section emitting CO 2 in the power plant, known as the carbon accounting center (CAC), was measured for its carbon profile (CP) and carbon index (CI). The carbon performance indicator (CPI) included electricity, fuel and water consumption, solid waste and waste-water generation. The carbon emission index (CEI) and carbon emission profile (CEP), based on the total monthly carbon production, were determined across the CPI. Various innovative strategies resulted in a 20%-90% reduction of CO 2 emissions. The implementation of reduction strategies significantly reduced the CO 2 emission levels. Based on the model, utilization of EFB and POME in the facilities could significantly reduce the CO 2 emissions and increase the potential for waste to energy initiatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance limitations of temperature-emissivity separation techniques in long-wave infrared hyperspectral imaging applications

NASA Astrophysics Data System (ADS)

Pieper, Michael; Manolakis, Dimitris; Truslow, Eric; Cooley, Thomas; Brueggeman, Michael; Jacobson, John; Weisner, Andrew

2017-08-01

Accurate estimation or retrieval of surface emissivity from long-wave infrared or thermal infrared (TIR) hyperspectral imaging data acquired by airborne or spaceborne sensors is necessary for many scientific and defense applications. This process consists of two interwoven steps: atmospheric compensation and temperature-emissivity separation (TES). The most widely used TES algorithms for hyperspectral imaging data assume that the emissivity spectra for solids are smooth compared to the atmospheric transmission function. We develop a model to explain and evaluate the performance of TES algorithms using a smoothing approach. Based on this model, we identify three 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. For each TES smoothing technique, we analyze the bias and variability of the temperature errors, which translate to emissivity errors. The performance model explains how the errors interact to generate temperature errors. Since we assume exact knowledge of the atmosphere, the presented results provide an upper bound on the performance of TES algorithms based on the smoothness assumption.

Assessment of China's virtual air pollution transport embodied in trade by a consumption-based emission inventory

NASA Astrophysics Data System (ADS)

Zhao, H. Y.; Zhang, Q.; Davis, S. J.; Guan, D.; Liu, Z.; Huo, H.; Lin, J. T.; Liu, W. D.; He, K. B.

2014-10-01

High anthropogenic emissions from China have resulted in serious air pollution, and it has attracted considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated, however, understanding the mechanisms how the pollutants were transferred through economic and trade activities remains challenge. In this work, we assessed China's virtual air pollutant transport embodied in trade, by using consumption-based accounting approach. We first constructed a consumption-based emission inventory for China's four key air pollutants (primary PM2.5, sulfur dioxide (SO2), nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC)) in 2007, based on the bottom-up sectoral emission inventory concerning their production activities - a production-based inventory. We used a multiregional input-output (MRIO) model to integrate the sectoral production-based emissions and the associated economic and trade activities, and finally obtained consumption-based inventory. Unlike the production-based inventory, the consumption-based inventory tracked emissions throughout the supply chain related to the consumption of goods and services and hereby identified the emission flows followed the supply chains. From consumption-based perspective, emissions were significantly redistributed among provinces due to interprovincial trade. Large amount of emissions were embodied in the net imports of east regions from northern and central regions; these were determined by differences in the regional economic status and environmental policies. We also calculated the emissions embodied in exported and imported goods and services. It is found that 15-23% of China's pollutant emissions were related to exports for foreign consumption; that proportion was much higher for central and export-oriented coastal regions. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers in national agreements to encourage efficiency improvement in the supply chain and optimizing consumption structure internationally. The consumption-based air pollutants emission inventory developed in this work can be further used to attribute pollution to different economic activities and final demand types with the aid of air quality models.

Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine.

PubMed

Silitonga, Arridina Susan; Hassan, Masjuki Haji; Ong, Hwai Chyuan; Kusumo, Fitranto

2017-11-01

The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machine (KELM) model is developed in this study using MATLAB software in order to predict the performance, combustion and emission characteristics of the engine. To acquire the data for training and testing the KELM model, the engine speed was selected as the input parameter, whereas the performance, exhaust emissions and combustion characteristics were chosen as the output parameters of the KELM model. The performance, emissions and combustion characteristics predicted by the KELM model were validated by comparing the predicted data with the experimental data. The results show that the coefficient of determination of the parameters is within a range of 0.9805-0.9991 for both the KELM model and the experimental data. The mean absolute percentage error is within a range of 0.1259-2.3838. This study shows that KELM modelling is a useful technique in biodiesel production since it facilitates scientists and researchers to predict the performance, exhaust emissions and combustion characteristics of internal combustion engines with high accuracy.

Temporal characteristics of atmospheric ammonia and nitrogen dioxide over China based on emission data, satellite observations and atmospheric transport modeling since 1980

NASA Astrophysics Data System (ADS)

Liu, Lei; Zhang, Xiuying; Xu, Wen; Liu, Xuejun; Li, Yi; Lu, Xuehe; Zhang, Yuehan; Zhang, Wuting

2017-08-01

China is experiencing intense air pollution caused in large part by anthropogenic emissions of reactive nitrogen (Nr). Atmospheric ammonia (NH3) and nitrogen dioxide (NO2) are the most important precursors for Nr compounds (including N2O5, HNO3, HONO and particulate NO3- and NH4+) in the atmosphere. Understanding the changes in NH3 and NO2 has important implications for the regulation of anthropogenic Nr emissions and is a requirement for assessing the consequence of environmental impacts. We conducted the temporal trend analysis of atmospheric NH3 and NO2 on a national scale since 1980 based on emission data (during 1980-2010), satellite observation (for NH3 since 2008 and for NO2 since 2005) and atmospheric chemistry transport modeling (during 2008-2015).Based on the emission data, during 1980-2010, significant continuous increasing trends in both NH3 and NOx were observed in REAS (Regional Emission inventory in Asia, for NH3 0.17 and for NOx 0.16 kg N ha-1 yr-2) and EDGAR (Emissions Database for Global Atmospheric Research, for NH3 0.24 and for NOx 0.17 kg N ha-1 yr-2) over China. Based on the satellite data and atmospheric chemistry transport model (CTM) MOZART-4 (Model for Ozone and Related chemical Tracers, version 4), the NO2 columns over China increased significantly from 2005 to 2011 and then decreased significantly from 2011 to 2015; the satellite-retrieved NH3 columns from 2008 to 2014 increased at a rate of 2.37 % yr-1. The decrease in NO2 columns since 2011 may result from more stringent strategies taken to control NOx emissions during the 12th Five Year Plan, while no control policy has focused on NH3 emissions. Our findings provided an overall insight into the temporal trends of both NO2 and NH3 since 1980 based on emission data, satellite observations and atmospheric transport modeling. These findings can provide a scientific background for policy makers that are attempting to control atmospheric pollution in China. Moreover, the multiple datasets used in this study have implications for estimating long-term Nr deposition datasets to assess its impact on soil, forest, water and greenhouse balance.

Development and Application of a Life Cycle-Based Model to Evaluate Greenhouse Gas Emissions of Oil Sands Upgrading Technologies.

PubMed

Pacheco, Diana M; Bergerson, Joule A; Alvarez-Majmutov, Anton; Chen, Jinwen; MacLean, Heather L

2016-12-20

A life cycle-based model, OSTUM (Oil Sands Technologies for Upgrading Model), which evaluates the energy intensity and greenhouse gas (GHG) emissions of current oil sands upgrading technologies, is developed. Upgrading converts oil sands bitumen into high quality synthetic crude oil (SCO), a refinery feedstock. OSTUM's novel attributes include the following: the breadth of technologies and upgrading operations options that can be analyzed, energy intensity and GHG emissions being estimated at the process unit level, it not being dependent on a proprietary process simulator, and use of publicly available data. OSTUM is applied to a hypothetical, but realistic, upgrading operation based on delayed coking, the most common upgrading technology, resulting in emissions of 328 kg CO 2 e/m 3 SCO. The primary contributor to upgrading emissions (45%) is the use of natural gas for hydrogen production through steam methane reforming, followed by the use of natural gas as fuel in the rest of the process units' heaters (39%). OSTUM's results are in agreement with those of a process simulation model developed by CanmetENERGY, other literature, and confidential data of a commercial upgrading operation. For the application of the model, emissions are found to be most sensitive to the amount of natural gas utilized as feedstock by the steam methane reformer. OSTUM is capable of evaluating the impact of different technologies, feedstock qualities, operating conditions, and fuel mixes on upgrading emissions, and its life cycle perspective allows easy incorporation of results into well-to-wheel analyses.

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.

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.

Emissions from prescribed burning of agricultural fields in the Pacific Northwest

Treesearch

A. L. Holder; B. K. Gullett; S. P. Urbanski; R. Elleman; S. O' Neill; D. Tabor; W. Mitchell; K. R. Baker

2017-01-01

Prescribed burns of winter wheat stubble and Kentucky bluegrass fields in northern Idaho and eastern Washington states (U.S.A.) were sampled using ground-, aerostat-, airplane-, and laboratory-based measurement platforms to determine emission factors, compare methods, and provide a current and comprehensive set of emissions data for air quality models, climate models,...

Impact of ship emissions on air pollution and AOD over North Atlantic and European Arctic

NASA Astrophysics Data System (ADS)

Kaminski, Jacek W.; Struzewska, Joanna; Jefimow, Maciej; Durka, Pawel

2016-04-01

The iAREA project is combined of experimental and theoretical research in order to contribute to the new knowledge on the impact of absorbing aerosols on the climate system in the European Arctic (http://www.igf.fuw.edu.pl/iAREA). A tropospheric chemistry model GEM-AQ (Global Environmental Multiscale Air Quality) was used as a computational tool. The core of the model is based on a weather prediction model with environmental processes (chemistry and aerosols) implanted on-line and are interactive (i.e. providing feedback of chemistry on radiation and dynamics). The numerical grid covered the Euro-Atlantic region with the resolution of 50 km. Emissions developed by NILU in the ECLIPSE project was used (Klimont et al., 2013). The model was run for two 1-year scenarios. 2014 was chosen as a base year for simulations and analysis. Scenarios include a base run with most up-to-date emissions and a run without maritime emissions. The analysis will focus on the contribution of maritime emissions on levels of particulate matter and gaseous pollutants over the European Arctic, North Atlantic and coastal areas. The annual variability will be assessed based on monthly mean near-surface concentration fields. Analysis of shipping transport on near-surface air pollution over the Euro-Atlantic region will be assessed for ozone, NO2, SO2, CO, PM10, PM2.5. Also, a contribution of ship emissions to AOD will be analysed.

Integrating Measurement Based New Knowledge on Wildland Fire Emissions and Chemistry into the AIRPACT Air Quality Forecasting for the Pacific Northwest

NASA Astrophysics Data System (ADS)

Nergui, T.; Lee, Y.; Chung, S. H.; Lamb, B. K.; Yokelson, R. J.; Barsanti, K.

2017-12-01

A number of chamber and field measurements have shown that atmospheric organic aerosols and their precursors produced from wildfires are significantly underestimated in the emission inventories used for air quality models for various applications such as regulatory strategy development, impact assessments of air pollutants, and air quality forecasting for public health. The AIRPACT real-time air quality forecasting system consistently underestimates surface level fine particulate matter (PM2.5) concentrations in the summer at both urban and rural locations in the Pacific Northwest, primarily result of errors in organic particulate matter. In this work, we implement updated chemical speciation and emission factors based on FLAME-IV (Fourth Fire Lab at Missoula Experiment) and other measurements in the Blue-Sky fire emission model and the SMOKE emission preprocessor; and modified parameters for the secondary organic aerosol (SOA) module in CMAQ chemical transport model of the AIRPACT modeling system. Simulation results from CMAQ version 5.2 which has a better treatment for anthropogenic SOA formation (as a base case) and modified parameterization used for fire emissions and chemistry in the model (fire-soa case) are evaluated against airborne measurements downwind of the Big Windy Complex Fire and the Colockum Tarps Fire, both of which occurred in the Pacific Northwest in summer 2013. Using the observed aerosol chemical composition and mass loadings for organics, nitrate, sulfate, ammonium, and chloride from aircraft measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), we assess how new knowledge gained from wildfire measurements improve model predictions for SOA and its contribution to the total mass of PM2.5 concentrations.

Understanding Emissions in East Asia - The KORUS 2015 Emissions Inventory

NASA Astrophysics Data System (ADS)

Woo, J. H.; Kim, Y.; Park, R.; Choi, Y.; Simpson, I. J.; Emmons, L. K.; Streets, D. G.

2017-12-01

The air quality over Northeast Asia have been deteriorated for decades due to high population and energy use in the region. Despite of more stringent air pollution control policies by the governments, air quality over the region seems not been improved as much - even worse sometimes. The needs of more scientific understanding of inter-relationship among emissions, transport, chemistry over the region are much higher to effectively protect public health and ecosystems. Two aircraft filed campaigns targeting year 2016, MAPS-Seoul and KORUS-AQ, have been organized to study the air quality of over Korea and East Asia relating to chemical evolution, emission inventories, trans-boundary contribution, and satellite application. We developed a new East-Asia emissions inventory, named KORUS2015, based on NIER/KU-CREATE (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment), in support of the filed campaigns. For anthropogenic emissions, it has 54 fuel classes, 201 sub-sectors and 13 pollutants, including CO2, SO2, NOx, CO, NMVOC, NH3, PM10, and PM2.5. Since the KORUS2015 emissions framework was developed using the integrated climate and air quality assessment modeling framework (i.e. GAINS) and is fully connected with the comprehensive emission processing/modeling systems (i.e. SMOKE, KU-EPS, and MEGAN), it can be effectively used to support atmospheric field campaigns for science and policy. During the field campaigns, we are providing modeling emissions inventory to participating air quality models, such as CMAQ, WRF-Chem, CAMx, GEOS-Chem, MOZART, for forecasting and post-analysis modes. Based on initial assessment of those results, we are improving our emissions, such as VOC speciation, biogenic VOCs modeling. From the 2nditeration between emissions and modeling/measurement, further analysis results will be presented at the conference. Acknowledgements : This subject is supported by Korea Ministry of Environment as "Climate Change Correspondence Program." This work was supported under the framework of national strategy project on fine particulate matters by Ministry of Science, ICT and Future Planning.

[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.

[Decomposition model of energy-related carbon emissions in tertiary industry for China].

PubMed

Lu, Yuan-Qing; Shi, Jun

2012-07-01

Tertiary industry has been developed in recent years. And it is very important to find the factors influenced the energy-related carbon emissions in tertiary industry. A decomposition model of energy-related carbon emissions for China is set up by adopting logarithmic mean weight Divisia method based on the identity of carbon emissions. The model is adopted to analyze the influence of energy structure, energy efficiency, tertiary industry structure and economic output to energy-related carbon emissions in China from 2000 to 2009. Results show that the contribution rate of economic output and energy structure to energy-related carbon emissions increases year by year. Either is the contribution rate of energy efficiency or the tertiary industry restraining to energy-related carbon emissions. However, the restrain effect is weakening.

A model for the relation between stimulus frequency and spontaneous otoacoustic emissions in lizard papillae.

PubMed

Wit, Hero P; van Dijk, Pim; Manley, Geoffrey A

2012-11-01

Spontaneous otoacoustic emissions (SOAEs) and stimulus frequency otoacoustic emissions (SFOAEs) have been described from lizard ears. Although there are several models for these systems, none has modeled the characteristics of both of these types of otoacoustic emissions based upon their being derived from hair cells as active oscillators. Data from the ears of two lizard species, one lacking a tectorial membrane and one with a chain of tectorial sallets, as described by Bergevin et al. ["Coupled, active oscillators and lizard otoacoustic emissions," AIP Conf. Proc. 1403, 453 (2008)], are modeled as an array of coupled self-sustained oscillators. The model, originally developed by Vilfan and Duke ["Frequency clustering in spontaneous otoacoustic emissions from a lizard's ear," Biophys. J. 95, 4622-4630 (2008)], well describes both the amplitude and phase characteristics of SFOAEs and the relation between SFOAEs and SOAEs.

Modeling and measurement of microwave emission and backscattering from bare soil surfaces

NASA Technical Reports Server (NTRS)

Saatchi, S.; Wegmuller, U.

1992-01-01

A multifrequency ground-based radiometer-scatterometer system working at frequencies between 3.0 GHz and 11.0 GHz has been used to study the effect of soil moisture and roughness on microwave emission and backscattering. The freezing and thawing effect of the soil surface and the changes of the surface roughness due to rain and erosion are reported. To analyze the combined active and passive data, a scattering model based on physical optics approximation for the low frequency and geometrical optics approximation for high frequency has been developed. The model is used to calculate the bistatic scattering coefficients from the surface. By considering the conservation of energy, the result has been integrated over a hemisphere above the surface to calculate the emissivity. The backscattering and emission model has been coupled with the observed data in order to extract soil moisture and surface roughness.

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.

Radiative transfer model for aerosols in infrared wavelengths for passive remote sensing applications.

PubMed

Ben-David, Avishai; Embury, Janon F; Davidson, Charles E

2006-09-10

A comprehensive analytical radiative transfer model for isothermal aerosols and vapors for passive infrared remote sensing applications (ground-based and airborne sensors) has been developed. The theoretical model illustrates the qualitative difference between an aerosol cloud and a chemical vapor cloud. The model is based on two and two/four stream approximations and includes thermal emission-absorption by the aerosols; scattering of diffused sky radiances incident from all sides on the aerosols (downwelling, upwelling, left, and right); and scattering of aerosol thermal emission. The model uses moderate resolution transmittance ambient atmospheric radiances as boundary conditions and provides analytical expressions for the information on the aerosol cloud that is contained in remote sensing measurements by using thermal contrasts between the aerosols and diffused sky radiances. Simulated measurements of a ground-based sensor viewing Bacillus subtilis var. niger bioaerosols and kaolin aerosols are given and discussed to illustrate the differences between a vapor-only model (i.e., only emission-absorption effects) and a complete model that adds aerosol scattering effects.

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 ...

Prediction models for CO2 emission in Malaysia using best subsets regression and multi-linear regression

NASA Astrophysics Data System (ADS)

Tan, C. H.; Matjafri, M. Z.; Lim, H. S.

2015-10-01

This paper presents the prediction models which analyze and compute the CO2 emission in Malaysia. Each prediction model for CO2 emission will be analyzed based on three main groups which is transportation, electricity and heat production as well as residential buildings and commercial and public services. The prediction models were generated using data obtained from World Bank Open Data. Best subset method will be used to remove irrelevant data and followed by multi linear regression to produce the prediction models. From the results, high R-square (prediction) value was obtained and this implies that the models are reliable to predict the CO2 emission by using specific data. In addition, the CO2 emissions from these three groups are forecasted using trend analysis plots for observation purpose.

Top-Down CO Emissions Based On IASI Observations and Hemispheric Constraints on OH Levels

NASA Astrophysics Data System (ADS)

Müller, J.-F.; Stavrakou, T.; Bauwens, M.; George, M.; Hurtmans, D.; Coheur, P.-F.; Clerbaux, C.; Sweeney, C.

2018-02-01

Assessments of carbon monoxide emissions through inverse modeling are dependent on the modeled abundance of the hydroxyl radical (OH) which controls both the primary sink of CO and its photochemical source through hydrocarbon oxidation. However, most chemistry transport models (CTMs) fall short of reproducing constraints on hemispherically averaged OH levels derived from methylchloroform (MCF) observations. Here we construct five different OH fields compatible with MCF-based analyses, and we prescribe those fields in a global CTM to infer CO fluxes based on Infrared Atmospheric Sounding Interferometer (IASI) CO columns. Each OH field leads to a different set of optimized emissions. Comparisons with independent data (surface, ground-based remotely sensed, aircraft) indicate that the inversion adopting the lowest average OH level in the Northern Hemisphere (7.8 × 105 molec cm-3, ˜18% lower than the best estimate based on MCF measurements) provides the best overall agreement with all tested observation data sets.

Modelisation 0D/1D des emissions de particules de suie dans les turbines a gaz aeronautiques

NASA Astrophysics Data System (ADS)

Bisson, Jeremie

Because of more stringent regulations of aircraft particle emissions as well as strong uncertainties about their formation and their effects on the atmosphere, a better understanding of particle microphysical mechanisms and their interactions with the engine components is required. This thesis focuses on the development of a 0D/1D combustion model with soot production in an aeronautical gas turbine. A major objective of this study is to assess the quality of soot particle emission predictions for different flight configurations. The model should eventually allow performing parametric studies on current or future engines with a minimal computation time. The model represents the combustor as well as turbines and nozzle with a chemical reactor network (CRN) that is coupled with a detailed combustion chemistry for kerosene (Jet A-1) and a soot particle dynamics model using the method of moments. The CRN was applied to the CFM56-2C1 engine during flight configurations of the LTO cycle (Landing-Take-Off) as in the APEX-1 study on aircraft particle emissions. The model was mainly validated on gas turbine thermodynamic data and pollutant concentrations (H2O, COX, NOx, SOX) which were measured in the same study. Once the first validation completed, the model was subsequently used for the computation of mass and number-based emissions indices of the soot particulate population and average diameter. Overall, the model is representative of the thermodynamic conditions and succeeds in predicting the emissions of major pollutants, particularly at high power. Concerning soot particulate emissions, the model's ability to predict simultaneously the emission indices as well as mean diameter has been partially validated. Indeed, the mass emission indices have remained higher than experimental results particularly at high power. These differences on particulate emission index may be the result of uncertainties on thermodynamic parameters of the CRN and mass air flow distribution in the combustion chamber. The analysis of the number-based emission index profile along the CRN also highlights the need to review the nucleation model that has been used and to consider in the future the implementation of a particle aggregation mechanism.

Microcomputer pollution model for civilian airports and Air Force bases. Model description

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

Segal, H.M.; Hamilton, P.L.

1988-08-01

This is one of three reports describing the Emissions and Dispersion Modeling System (EDMS). EDMS is a complex source emissions/dispersion model for use at civilian airports and Air Force bases. It operates in both a refined and a screening mode and is programmed for an IBM-XT (or compatible) computer. This report--MODEL DESCRIPTION--provides the technical description of the model. It first identifies the key design features of both the emissions (EMISSMOD) and dispersion (GIMM) portions of EDMS. It then describes the type of meteorological information the dispersion model can accept and identifies the manner in which it preprocesses National Climatic Centermore » (NCC) data prior to a refined-model run. The report presents the results of running EDMS on a number of different microcomputers and compares EDMS results with those of comparable models. The appendices elaborate on the information noted above and list the source code.« less

Future Sulfur Dioxide Emissions

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

Smith, Steven J.; Pitcher, Hugh M.; Wigley, Tom M.

2005-12-01

The importance of sulfur dioxide emissions for climate change is now established, although substantial uncertainties remain. This paper presents projections for future sulfur dioxide emissions using the MiniCAM integrated assessment model. A new income-based parameterization for future sulfur dioxide emissions controls is developed based on purchasing power parity (PPP) income estimates and historical trends related to the implementation of sulfur emissions limitations. This parameterization is then used to produce sulfur dioxide emissions trajectories for the set of scenarios developed for the Special Report on Emission Scenarios (SRES). We use the SRES methodology to produce harmonized SRES scenarios using the latestmore » version of the MiniCAM model. The implications, and requirements, for IA modeling of sulfur dioxide emissions are discussed. We find that sulfur emissions eventually decline over the next century under a wide set of assumptions. These emission reductions result from a combination of emission controls, the adoption of advanced electric technologies, and a shift away from the direct end use of coal with increasing income levels. Only under a scenario where incomes in developing regions increase slowly do global emission levels remain at close to present levels over the next century. Under a climate policy that limits emissions of carbon dioxide, sulfur dioxide emissions fall in a relatively narrow range. In all cases, the relative climatic effect of sulfur dioxide emissions decreases dramatically to a point where sulfur dioxide is only a minor component of climate forcing by the end of the century. Ecological effects of sulfur dioxide, however, could be significant in some developing regions for many decades to come.« less

Construction of a quartz spherical analyzer: application to high-resolution analysis of the Ni Kα emission spectrum

DOE PAGES

Honnicke, Marcelo Goncalves; Bianco, Leonardo M.; Ceppi, Sergio A.; ...

2016-08-10

The construction and characterization of a focusing X-ray spherical analyzer based on α-quartz 4more » $$\\overline{4}$$04 are presented. For this study, the performance of the analyzer was demonstrated by applying it to a high-resolution X-ray spectroscopy study of theKα 1,2emission spectrum of Ni. An analytical representation based on physical grounds was assumed to model the shape of the X-ray emission lines. Satellite structures assigned to 3dspectator hole transitions were resolved and determined as well as their relative contribution to the emission spectrum. The present results on 1s -13d -1shake probabilities support a recently proposed calculation framework based on a multi-configuration atomic model.« less

Construction of a quartz spherical analyzer: application to high-resolution analysis of the Ni Kα emission spectrum

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

Honnicke, Marcelo Goncalves; Bianco, Leonardo M.; Ceppi, Sergio A.

The construction and characterization of a focusing X-ray spherical analyzer based on α-quartz 4more » $$\\overline{4}$$04 are presented. For this study, the performance of the analyzer was demonstrated by applying it to a high-resolution X-ray spectroscopy study of theKα 1,2emission spectrum of Ni. An analytical representation based on physical grounds was assumed to model the shape of the X-ray emission lines. Satellite structures assigned to 3dspectator hole transitions were resolved and determined as well as their relative contribution to the emission spectrum. The present results on 1s -13d -1shake probabilities support a recently proposed calculation framework based on a multi-configuration atomic model.« less

Construction of a quartz spherical analyzer: application to high-resolution analysis of the Ni K α emission spectrum

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

Honnicke, Marcelo Goncalves; Bianco, Leonardo M.; Ceppi, Sergio A.

The construction and characterization of a focusing X-ray spherical analyzer based on α-quartz 4more » $$\\bar{4}$$04 are presented. The performance of the analyzer was demonstrated by applying it to a high-resolution X-ray spectroscopy study of theKα 1,2emission spectrum of Ni. An analytical representation based on physical grounds was assumed to model the shape of the X-ray emission lines. Satellite structures assigned to 3dspectator hole transitions were resolved and determined as well as their relative contribution to the emission spectrum. The present results on 1s -13d -1shake probabilities support a recently proposed calculation framework based on a multi-configuration atomic model.« less

Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.

PubMed

Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

2016-12-01

This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China.

A Prototype Physical Database for Passive Microwave Retrievals of Precipitation over the US Southern Great Plains

NASA Technical Reports Server (NTRS)

Ringerud, S.; Kummerow, C. D.; Peters-Lidard, C. D.

2015-01-01

An accurate understanding of the instantaneous, dynamic land surface emissivity is necessary for a physically based, multi-channel passive microwave precipitation retrieval scheme over land. In an effort to assess the feasibility of the physical approach for land surfaces, a semi-empirical emissivity model is applied for calculation of the surface component in a test area of the US Southern Great Plains. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are utilized along with coincident brightness temperatures (Tbs) from the TRMM Microwave Imager (TMI), and cloud-resolving model profiles. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled top of the atmosphere Tbs show correlations to observations of 0.9, biases of 1K or less, root-mean-square errors on the order of 5K, and improved agreement over the use of climatological emissivity values. The synthesis of these models and data sets leads to the creation of a simple prototype Tb database that includes both dynamic surface and atmospheric information physically consistent with the land surface model, emissivity model, and atmospheric information.

Time-Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Kuo, Chaincy; Feldman, Daniel R.; Huang, Xianglei; Flanner, Mark; Yang, Ping; Chen, Xiuhong

2018-01-01

Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.

Analysis of consistency of global net land-use change carbon emission scenario using offline vegetation model and earth system model

NASA Astrophysics Data System (ADS)

Kato, E.; Kawamiya, M.

2010-12-01

For CMIP5 experiments, emissions scenarios data sets for climate models are prepared as Representative Concentration Pathways (RCPs) by the Integrated Assessment Models (IAMs). IAMs also have depicted regional land-use scenarios based on the socioeconomic assumption of the future scenarios of RCPs. In the land-use harmonization project, gridded land-use transition data has been constructed from the regional IAMs future land-use scenarios which smoothly connects historical reconstructions of land-use based on HYDE 3 data and FAO wood harvest data. In this study, using the gridded transition land-use scenario data, global net CO2 emission from land-use change for each RCPs scenarios is evaluated with a offline version of terrestrial biogeochemical model, VISIT (Vegetation Integrative SImulation Tool), utilizing a protocol to estimate carbon emission from deforested biomass considering delayed decomposition of product pools, and regrowth absorption from the secondary lands with abandoned agricultural lands. From the model output, effect of CO2 fertilization and land-use scenario itself on the emission is assessed to see the consistency of the scenarios. In addition, to see the effect of climate change and the climate-carbon feedback on terrestrial ecosystems, net land-use change CO2 emission is also evaluated with an earth system model, MIROC-ESM incorporating a DGVM with land-use change component. In the simulations with earth system model, RCP 6.0 scenario has been evaluated by model runs with and without land-use change forcing.

Spatiotemporal comparison of highly-resolved emissions and concentrations of carbon dioxide and criteria pollutants in Salt Lake City, Utah for health and policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Fasoli, B.; Bares, R.; o'Keefe, D.; Song, T.; Huang, J.; Horel, J.; Crosman, E.; Ehleringer, J. R.

2015-12-01

This study addresses the need for robust highly-resolved emissions and concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are dependent on proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present emissions inventories and modeled concentrations for CO2 and CAPs: carbon monoxide (CO), lead (Pb), nitrogen oxides (NOx), particulate matter (PM2.5 and PM10), and sulfur oxides (SOx) for Salt Lake County, Utah. We compare the resulting concentrations against stationary and mobile measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at an hourly, building and road link resolution as well as hourly gridded emissions with a 0.002o x 0.002o spatial resolution. Two methods for deriving criteria pollutant emission inventories were compared. One was constructed using methods similar to Hestia but downscales total emissions based on the 2011 National Emissions Inventory (NEI). The other used Emission Modeling Clearinghouse spatial and temporal surrogates to downscale the NEI data from annual and county-level resolution to hourly and 0.002o x 0.002o grid cells. The gridded emissions from both criteria pollutant methods were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The CALPUFF dispersion model was used to transport emissions and estimate air pollutant concentrations at an hourly 0.002o x 0.002o resolution. The resulting concentrations were spatially compared in the same manner as the emissions. Modeled results were compared against stationary measurements and from equipment mounted atop a light rail car in the Salt Lake City area. The comparison between both approaches to emissions estimation and resulting concentrations highlights spatial locations and hours of high variability and uncertainty.

Evaluation of NOx Emissions and Modeling

NASA Astrophysics Data System (ADS)

Henderson, B. H.; Simon, H. A.; Timin, B.; Dolwick, P. D.; Owen, R. C.; Eyth, A.; Foley, K.; Toro, C.; Baker, K. R.

2017-12-01

Studies focusing on ambient measurements of NOy have concluded that NOx emissions are overestimated and some have attributed the error to the onroad mobile sector. We investigate this conclusion to identify the cause of observed bias. First, we compare DISCOVER-AQ Baltimore ambient measurements to fine-scale modeling with NOy tagged by sector. Sector-based relationships with bias are present, but these are sensitive to simulated vertical mixing. This is evident both in sensitivity to mixing parameterization and the seasonal patterns of bias. We also evaluate observation-based indicators, like CO:NOy ratios, that are commonly used to diagnose emissions inventories. Second, we examine the sensitivity of predicted NOx and NOy to temporal allocation of emissions. We investigate alternative temporal allocations for EGUs without CEMS, on-road mobile, and several non-road categories. These results show some location-specific sensitivity and will lead to some improved temporal allocations. Third, near-road studies have inherently fewer confounding variables, and have been examined for more direct evaluation of emissions and dispersion models. From 2008-2011, the EPA and FHWA conducted near-road studies in Las Vegas and Detroit. These measurements are used to more directly evaluate the emissions and dispersion using site-specific traffic data. In addition, the site-specific emissions are being compared to the emissions used in larger-scale photochemical modeling to identify key discrepancies. These efforts are part of a larger coordinated effort by EPA scientist to ensure the highest quality in emissions and model processes. We look forward to sharing the state of these analyses and expected updates.

Land-use change and greenhouse gas emissions from corn and cellulosic ethanol

PubMed Central

2013-01-01

Background The greenhouse gas (GHG) emissions that may accompany land-use change (LUC) from increased biofuel feedstock production are a source of debate in the discussion of drawbacks and advantages of biofuels. Estimates of LUC GHG emissions focus mainly on corn ethanol and vary widely. Increasing the understanding of LUC GHG impacts associated with both corn and cellulosic ethanol will inform the on-going debate concerning their magnitudes and sources of variability. Results In our study, we estimate LUC GHG emissions for ethanol from four feedstocks: corn, corn stover, switchgrass, and miscanthus. We use new computable general equilibrium (CGE) results for worldwide LUC. U.S. domestic carbon emission factors are from state-level modelling with a surrogate CENTURY model and U.S. Forest Service data. This paper investigates the effect of several key domestic lands carbon content modelling parameters on LUC GHG emissions. International carbon emission factors are from the Woods Hole Research Center. LUC GHG emissions are calculated from these LUCs and carbon content data with Argonne National Laboratory’s Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) model. Our results indicate that miscanthus and corn ethanol have the lowest (−10 g CO2e/MJ) and highest (7.6 g CO2e/MJ) LUC GHG emissions under base case modelling assumptions. The results for corn ethanol are lower than corresponding results from previous studies. Switchgrass ethanol base case results (2.8 g CO2e/MJ) were the most influenced by assumptions regarding converted forestlands and the fate of carbon in harvested wood products. They are greater than miscanthus LUC GHG emissions because switchgrass is a lower-yielding crop. Finally, LUC GHG emissions for corn stover are essentially negligible and insensitive to changes in model assumptions. Conclusions This research provides new insight into the influence of key carbon content modelling variables on LUC GHG emissions associated with the four bioethanol pathways we examined. Our results indicate that LUC GHG emissions may have a smaller contribution to the overall biofuel life cycle than previously thought. Additionally, they highlight the need for future advances in LUC GHG emissions estimation including improvements to CGE models and aboveground and belowground carbon content data. PMID:23575438

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

NASA Technical Reports Server (NTRS)

Diehl, T. L.; Mian, Chin; Bond, T. C.; Carn, S. A.; Duncan, B. N.; Krotkov, N. A.; Streets, D. G.

2007-01-01

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthopogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ATSR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

NASA Technical Reports Server (NTRS)

Diehl, Thomas L.; Chin, Mian; Bond, Tami C.; Carn, SImon A.; Duncan, Bryan N.; Krotkov, Nickolay A.; Streets, David G.

2006-01-01

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthropogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ASTR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Constraining a complex biogeochemical model for CO2 and N2O emission simulations from various land uses by model-data fusion

NASA Astrophysics Data System (ADS)

Houska, Tobias; Kraus, David; Kiese, Ralf; Breuer, Lutz

2017-07-01

This study presents the results of a combined measurement and modelling strategy to analyse N2O and CO2 emissions from adjacent arable land, forest and grassland sites in Hesse, Germany. The measured emissions reveal seasonal patterns and management effects, including fertilizer application, tillage, harvest and grazing. The measured annual N2O fluxes are 4.5, 0.4 and 0.1 kg N ha-1 a-1, and the CO2 fluxes are 20.0, 12.2 and 3.0 t C ha-1 a-1 for the arable land, grassland and forest sites, respectively. An innovative model-data fusion concept based on a multicriteria evaluation (soil moisture at different depths, yield, CO2 and N2O emissions) is used to rigorously test the LandscapeDNDC biogeochemical model. The model is run in a Latin-hypercube-based uncertainty analysis framework to constrain model parameter uncertainty and derive behavioural model runs. The results indicate that the model is generally capable of predicting trace gas emissions, as evaluated with RMSE as the objective function. The model shows a reasonable performance in simulating the ecosystem C and N balances. The model-data fusion concept helps to detect remaining model errors, such as missing (e.g. freeze-thaw cycling) or incomplete model processes (e.g. respiration rates after harvest). This concept further elucidates the identification of missing model input sources (e.g. the uptake of N through shallow groundwater on grassland during the vegetation period) and uncertainty in the measured validation data (e.g. forest N2O emissions in winter months). Guidance is provided to improve the model structure and field measurements to further advance landscape-scale model predictions.

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.

Assessment and Optimization of the Accuracy of an Aircraft-Based Technique Used to Quantify Greenhouse Gas Emission Rates from Point Sources

NASA Astrophysics Data System (ADS)

Shepson, P. B.; Lavoie, T. N.; Kerlo, A. E.; Stirm, B. H.

2016-12-01

Understanding the contribution of anthropogenic activities to atmospheric greenhouse gas concentrations requires an accurate characterization of emission sources. Previously, we have reported the use of a novel aircraft-based mass balance measurement technique to quantify greenhouse gas emission rates from point and area sources, however, the accuracy of this approach has not been evaluated to date. Here, an assessment of method accuracy and precision was performed by conducting a series of six aircraft-based mass balance experiments at a power plant in southern Indiana and comparing the calculated CO2 emission rates to the reported hourly emission measurements made by continuous emissions monitoring systems (CEMS) installed directly in the exhaust stacks at the facility. For all flights, CO2 emissions were quantified before CEMS data were released online to ensure unbiased analysis. Additionally, we assess the uncertainties introduced to the final emission rate caused by our analysis method, which employs a statistical kriging model to interpolate and extrapolate the CO2 fluxes across the flight transects from the ground to the top of the boundary layer. Subsequently, using the results from these flights combined with the known emissions reported by the CEMS, we perform an inter-model comparison of alternative kriging methods to evaluate the performance of the kriging approach.

Space based inverse modeling of seasonal variations of anthropogenic and natural emissions of nitrogen oxides over China and effects of uncertainties in model meteorology and chemistry

NASA Astrophysics Data System (ADS)

Lin, J.

2011-12-01

Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry, surface air quality and climatic forcing. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, which can be estimated inversely from satellite remote sensing of the vertical column densities (VCDs) of nitrogen dioxide (NO2) in the troposphere. Based on VCDs of NO2 retrieved from OMI, a novel approach is developed in this study to separate anthropogenic emissions of NOx from natural sources over East China for 2006. It exploits the fact that anthropogenic and natural emissions vary with seasons with distinctive patterns. The global chemical transport model (CTM) GEOS-Chem is used to establish the relationship between VCDs of NO2 and emissions of NOx for individual sources. Derived soil emissions are compared to results from a newly developed bottom-up approach. Effects of uncertainties in model meteorology and chemistry over China, an important source of errors in the emission inversion, are evaluated systematically for the first time. Meteorological measurements from space and the ground are used to analyze errors in meteorological parameters driving the CTM.

Multiple regression analysis in modelling of carbon dioxide emissions by energy consumption use in Malaysia

NASA Astrophysics Data System (ADS)

Keat, Sim Chong; Chun, Beh Boon; San, Lim Hwee; Jafri, Mohd Zubir Mat

2015-04-01

Climate change due to carbon dioxide (CO2) emissions is one of the most complex challenges threatening our planet. This issue considered as a great and international concern that primary attributed from different fossil fuels. In this paper, regression model is used for analyzing the causal relationship among CO2 emissions based on the energy consumption in Malaysia using time series data for the period of 1980-2010. The equations were developed using regression model based on the eight major sources that contribute to the CO2 emissions such as non energy, Liquefied Petroleum Gas (LPG), diesel, kerosene, refinery gas, Aviation Turbine Fuel (ATF) and Aviation Gasoline (AV Gas), fuel oil and motor petrol. The related data partly used for predict the regression model (1980-2000) and partly used for validate the regression model (2001-2010). The results of the prediction model with the measured data showed a high correlation coefficient (R2=0.9544), indicating the model's accuracy and efficiency. These results are accurate and can be used in early warning of the population to comply with air quality standards.

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

NASA Astrophysics Data System (ADS)

Wang, Lina; Jayaratne, Rohan; Heuff, Darlene; Morawska, Lidia

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

Exhaust Emission Rates for Heavy-Duty On road Vehicles in MOVES201X

EPA Science Inventory

Updated running exhaust gaseous emission rates (THC, CO, NOx, CO2) for heavy-duty diesel trucks model year 2010 and later based on portable emission measurements from the manufacturer-run, heavy-duty in-use testing (HDIUT) program. Updated cold start emission rates and soak adjus...

Dynamic Evaluation of Regional Air Quality Model's Response to Emission Reductions in the Presence of Uncertain Emission Inventories

EPA Science Inventory

A method is presented and applied for evaluating an air quality model’s changes in pollutant concentrations stemming from changes in emissions while explicitly accounting for the uncertainties in the base emission inventory. Specifically, the Community Multiscale Air Quality (CMA...

Model study of greenline dayglow emission under geomagnetic storm conditions.

NASA Astrophysics Data System (ADS)

Singh, V.; Bag, T.; Sunil Krishna, M. V.

2016-12-01

A comprehensive model is developed to study the influences of geomagnetic storms on greenline (557.7 nm) dayglow emission during the solar active and solar quiet conditions in thermosphere. This study is based on a photochemical model which is developed using the latest reaction rate coefficients, quantum yields and collisional cross-sections obtained from the experimental observations and empirical models. This study is for a low latitude station Tirunelveli (8.7N,77.8E), India. The volume emission rate (VER) has been calculated using the densities and temperature from NRLMSISE-00 and IRI-2012 models. The modeled VER shows a positive correlation with the Dst index, and a negative correlation with the number densities of O, O2, and N2. The VER calculated at the peak emission altitude shows depletion during the main phase of the storm. The peak emission altitude doesn't show any appreciable variation during storm period. On the other hand, the peak emission altitude shows an upward movement with the increase in F10.7 solar index.

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.

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.

A microphysically-based approach to modeling emissivity and albedo of the martian seasonal caps

USGS Publications Warehouse

Eluszkiewicz, J.; Moncet, J.-L.; Titus, T.N.; Hansen, G.B.

2005-01-01

A new model of albedo and emissivity of the martian seasonal caps represented as porous CO2 slabs containing spherical voids and dust particles is described. In the model, a radiative transfer model is coupled with a microphysical model in order to link changes in albedo and emissivity to changes in porosity caused by ice metamorphism. The coupled model is capable of reproducing temporal changes in the spectra of the caps taken by the Thermal Emission Spectrometer onboard the Mars Global Surveyor and it can be used as the forward model in the retrievals of the caps' physical properties (porosity, dust abundance, void and dust grain size) from the spectra. Preliminary results from such inversion studies are presented. ?? 2004 Elsevier Inc. All rights reserved.

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.

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.

40 CFR 600.208-12 - Calculation of FTP-based and HFET-based fuel economy and carbon-related exhaust emission values...

Code of Federal Regulations, 2011 CFR

2011-07-01

... emission data from tests conducted on these vehicle configuration(s) at high altitude to calculate the fuel... values from the tests performed using alcohol or natural gas test fuel. (b) For each model type, as..., highway, and combined fuel economy and carbon-related exhaust emission values from the tests performed...

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.

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.

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.

Modeling spatial patterns of link-based PM2.5 emissions and subsequent human exposure in a large canadian metropolitan area

NASA Astrophysics Data System (ADS)

Requia, Weeberb J.; Dalumpines, Ron; Adams, Matthew D.; Arain, Altaf; Ferguson, Mark; Koutrakis, Petros

2017-06-01

Understanding the relationship between mobile source emissions and subsequent human exposure is crucial for emissions control. Determining this relationship over space is fundamental to improve the accuracy and precision of public policies. In this study, we evaluated the spatial patterns of link-based PM2.5 emissions and subsequent human exposure in a large Canadian metropolitan area - the Greater Toronto and Hamilton Area (GTHA). This study was performed in three stages. First, we estimated vehicle emissions using transportation models and emission simulators. Then we evaluated human exposure to PM2.5 emissions using the Intake fraction (iF) approach. Finally, we applied geostatistical methods to assess spatial patterns of vehicle emissions and subsequent human exposure based on three prospective goals: i) classification of emissions (Global Moran's I test), ii) level of emission exposure (Getis-Ord General G test), and; iii) location of emissions (Anselin Local Moran's I). Our results showed that passenger vehicles accounted for the highest total amount of PM2.5 emissions, representing 57% emissions from all vehicles. Examining only the emissions from passenger vehicles, on average, each person in the GTHA inhales 2.58 × 10-3 ppm per day. Accounting the emissions from buses and trucks, on average each person inhales 0.12 × 10-3 and 1.91 × 10-3 ppm per day, respectively. For both PM2.5 emissions and human exposure using iF approach, our analysis showed Moran's Index greater than 0 for all vehicle categories, suggesting the presence of significant clusters (p-value <0.01) in the region. Our study indicates that air pollution control policy must be developed for the whole region, because of the spatial distribution of housing and businesses centers and inter-connectivity of transportation networks across the region, where a policy cannot simply be based on a municipal or other boundaries.

High temporal resolution modelling of environmentally-dependent seabird ammonia emissions: Description and testing of the GUANO model

NASA Astrophysics Data System (ADS)

Riddick, S. N.; Blackall, T. D.; Dragosits, U.; Tang, Y. S.; Moring, A.; Daunt, F.; Wanless, S.; Hamer, K. C.; Sutton, M. A.

2017-07-01

Many studies in recent years have highlighted the ecological implications of adding reactive nitrogen (Nr) to terrestrial ecosystems. Seabird colonies represent a situation with concentrated sources of Nr, through excreted and accumulated guano, often occurring in otherwise nutrient-poor areas. To date, there has been little attention given to modelling N flows in this context, and particularly to quantifying the relationship between ammonia (NH3) emissions and meteorology. This paper presents a dynamic mass-flow model (GUANO) that simulates temporal variations in NH3 emissions from seabird guano. While the focus is on NH3 emissions, the model necessarily also treats the interaction with wash-off as far as this affects NH3. The model is validated using NH3 emissions measurements from seabird colonies across a range of climates, from sub-polar to tropical. In simulations for hourly time-resolved data, the model is able to capture the observed dependence of NH3 emission on environmental variables. With temperature and wind speed having the greatest effects on emission for the cases considered. In comparison with empirical data, the percentage of excreted nitrogen that volatilizes as NH3 is found to range from 2% to 67% (based on measurements), with the GUANO model providing a range of 2%-82%. The model provides a tool that can be used to investigate the meteorological dependence of NH3 emissions from seabird guano and provides a starting point to refine models of NH3 emissions from other sources.

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.

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.

Predicting Future-Year Ozone Concentrations: Integrated Observational-Modeling Approach for Probabilistic Evaluation of the Efficacy of Emission Control strategies

EPA Science Inventory

Regional-scale air quality models are being used to demonstrate attainment of the ozone air quality standard. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological ...

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...

A mass transfer model of ethanol emission from thin layers of corn silage

USDA-ARS?s Scientific Manuscript database

A mass transfer model of ethanol emission from thin layers of corn silage was developed and validated. The model was developed based on data from wind tunnel experiments conducted at different temperatures and air velocities. Multiple regression analysis was used to derive an equation that related t...

DYNAMIC EVALUATION OF REGIONAL AIR QUALITY MODELS: ASSESSING CHANGES TO O 3 STEMMING FROM CHANGES IN EMISSIONS AND METEOROLOGY

EPA Science Inventory

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...

Comparison of AERMOD and WindTrax dispersion models in determining PM10 emission rates from beef cattle feedlots

USDA-ARS?s Scientific Manuscript database

Reverse dispersion modeling has been used to determine air emission fluxes from ground-level area sources, including open-lot beef cattle feedlots. This research compared AERMOD, a Gaussian-based and currently the U.S. Environmental Protection Agency (EPA) preferred regulatory dispersion model, and ...

A linear programming model to optimize diets in environmental policy scenarios.

PubMed

Moraes, L E; Wilen, J E; Robinson, P H; Fadel, J G

2012-03-01

The objective was to develop a linear programming model to formulate diets for dairy cattle when environmental policies are present and to examine effects of these policies on diet formulation and dairy cattle nitrogen and mineral excretions as well as methane emissions. The model was developed as a minimum cost diet model. Two types of environmental policies were examined: a tax and a constraint on methane emissions. A tax was incorporated to simulate a greenhouse gas emissions tax policy, and prices of carbon credits in the current carbon markets were attributed to the methane production variable. Three independent runs were made, using carbon dioxide equivalent prices of $5, $17, and $250/t. A constraint was incorporated into the model to simulate the second type of environmental policy, reducing methane emissions by predetermined amounts. The linear programming formulation of this second alternative enabled the calculation of marginal costs of reducing methane emissions. Methane emission and manure production by dairy cows were calculated according to published equations, and nitrogen and mineral excretions were calculated by mass conservation laws. Results were compared with respect to the values generated by a base least-cost model. Current prices of the carbon credit market did not appear onerous enough to have a substantive incentive effect in reducing methane emissions and altering diet costs of our hypothetical dairy herd. However, when emissions of methane were assumed to be reduced by 5, 10, and 13.5% from the base model, total diet costs increased by 5, 19.1, and 48.5%, respectively. Either these increased costs would be passed onto the consumer or dairy producers would go out of business. Nitrogen and potassium excretions were increased by 16.5 and 16.7% with a 13.5% reduction in methane emissions from the base model. Imposing methane restrictions would further increase the demand for grains and other human-edible crops, which is not a progressive solution for an industry trying to be sustainable. However, these results might depend on the constraints and inputs used in our model (e.g., feed prices), and more extensive analyses are required before they are used in policy development. The model structure was able to incorporate effects of environmental policies in diet formulation and it can assist dairy producers in meeting limits set by these policies. The model can also assist policy makers examining the effects of policies on the dairy production system. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Testing a high resolution CO2 and CO emission inventory against atmospheric observations in Salt Lake City, Utah for policy applications

NASA Astrophysics Data System (ADS)

Mendoza, D. L.; Lin, J. C.; Mitchell, L.; Gurney, K. R.; Patarasuk, R.; Mallia, D. V.; Fasoli, B.; Bares, R.; Catharine, D.; O'Keeffe, D.; Song, Y.; Huang, J.; Horel, J.; Crosman, E.; Hoch, S.; Ehleringer, J. R.

2016-12-01

We address the need for robust highly-resolved emissions and trace gas concentration data required for planning purposes and policy development aimed at managing pollutant sources. Adverse health effects resulting from urban pollution exposure are the result of proximity to emission sources and atmospheric mixing, necessitating models with high spatial and temporal resolution. As urban emission sources co-emit carbon dioxide (CO2) and criteria air pollutants (CAPs), efforts to reduce specific pollutants would synergistically reduce others. We present a contemporary (2010-2015) emissions inventory and modeled CO2 and carbon monoxide (CO) concentrations for Salt Lake County, Utah. We compare emissions transported by a dispersion model against stationary measurement data and present a systematic quantification of uncertainties. The emissions inventory for CO2 is based on the Hestia emissions data inventory that resolves emissions at hourly, building and road-link resolutions, as well as on an hourly gridded scale. The emissions were scaled using annual Energy Information Administration (EIA) fuel consumption data. We derived a CO emissions inventory using methods similar to Hestia, downscaling total county emissions from the 2011 Environmental Protection Agency's (EPA) National Emissions Inventory (NEI). The gridded CO emissions were compared against the Hestia CO2 gridded data to characterize spatial similarities and differences between them. Correlations were calculated at multiple scales of aggregation. The Stochastic Time-Inverted Lagrangian Trasport (STILT) dispersion model was used to transport emissions and estimate pollutant concentrations at an hourly resolution. Modeled results were compared against stationary measurements in the Salt Lake County area. This comparison highlights spatial locations and hours of high variability and uncertainty. Sensitivity to biological fluxes as well as to specific economic sectors was tested by varying their contributions to modeled concentrations and calibrating their emissions.

Contribution of milk production to global greenhouse gas emissions. An estimation based on typical farms.

PubMed

Hagemann, Martin; Ndambi, Asaah; Hemme, Torsten; Latacz-Lohmann, Uwe

2012-02-01

Studies on the contribution of milk production to global greenhouse gas (GHG) emissions are rare (FAO 2010) and often based on crude data which do not appropriately reflect the heterogeneity of farming systems. This article estimates GHG emissions from milk production in different dairy regions of the world based on a harmonised farm data and assesses the contribution of milk production to global GHG emissions. The methodology comprises three elements: (1) the International Farm Comparison Network (IFCN) concept of typical farms and the related globally standardised dairy model farms representing 45 dairy regions in 38 countries; (2) a partial life cycle assessment model for estimating GHG emissions of the typical dairy farms; and (3) standard regression analysis to estimate GHG emissions from milk production in countries for which no typical farms are available in the IFCN database. Across the 117 typical farms in the 38 countries analysed, the average emission rate is 1.50 kg CO(2) equivalents (CO(2)-eq.)/kg milk. The contribution of milk production to the global anthropogenic emissions is estimated at 1.3 Gt CO(2)-eq./year, accounting for 2.65% of total global anthropogenic emissions (49 Gt; IPCC, Synthesis Report for Policy Maker, Valencia, Spain, 2007). We emphasise that our estimates of the contribution of milk production to global GHG emissions are subject to uncertainty. Part of the uncertainty stems from the choice of the appropriate methods for estimating emissions at the level of the individual animal.

Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models.

PubMed

Hristov, A N; Kebreab, E; Niu, M; Oh, J; Bannink, A; Bayat, A R; Boland, T B; Brito, A F; Casper, D P; Crompton, L A; Dijkstra, J; Eugène, M; Garnsworthy, P C; Haque, N; Hellwing, A L F; Huhtanen, P; Kreuzer, M; Kuhla, B; Lund, P; Madsen, J; Martin, C; Moate, P J; Muetzel, S; Muñoz, C; Peiren, N; Powell, J M; Reynolds, C K; Schwarm, A; Shingfield, K J; Storlien, T M; Weisbjerg, M R; Yáñez-Ruiz, D R; Yu, Z

2018-04-18

Ruminant production systems are important contributors to anthropogenic methane (CH 4 ) emissions, but there are large uncertainties in national and global livestock CH 4 inventories. Sources of uncertainty in enteric CH 4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH 4 emission factors. There is also significant uncertainty associated with enteric CH 4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF 6 ) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH 4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH 4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH 4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH 4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH 4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH 4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Speciation and Toxic Emissions from On road Vehicles, and Particulate Matter Emissions from Light-Duty Gasoline Vehicles in MOVES201X

EPA Science Inventory

Updated methane, non-methane organic gas, and volatile organic compound calculations based on speciation data. Updated speciation and toxic emission rates for new model year 2010 and later heavy-duty diesel engines. Updated particulate matter emission rates for 2004 and later mod...

Full-sky, High-resolution Maps of Interstellar Dust

NASA Astrophysics Data System (ADS)

Meisner, Aaron Michael

We present full-sky, high-resolution maps of interstellar dust based on data from the Wide-field Infrared Survey Explorer (WISE) and Planck missions. We describe our custom processing of the entire WISE 12 micron All-Sky imaging data set, and present the resulting 15 arcsecond resolution, full-sky map of diffuse Galactic dust emission, free of compact sources and other contaminating artifacts. Our derived 12 micron dust map offers angular resolution far superior to that of all other existing full-sky, infrared dust emission maps, revealing a wealth of small-scale filamentary structure. We also apply the Finkbeiner et al. (1999) two-component thermal dust emission model to the Planck HFI maps. We derive full-sky 6.1 arcminute resolution maps of dust optical depth and temperature by fitting this two-component model to Planck 217-857 GHz along with DIRBE/IRAS 100 micron data. In doing so, we obtain the first ever full-sky 100-3000 GHz Planck-based thermal dust emission model, as well as a dust temperature correction with ~10 times enhanced angular resolution relative to DIRBE-based temperature maps. Analyzing the joint Planck/DIRBE dust spectrum, we show that two-component models provide a better fit to the 100-3000 GHz emission than do single-MBB models, though by a lesser margin than found by Finkbeiner et al. (1999) based on FIRAS and DIRBE. We find that, in diffuse sky regions, our two-component 100-217 GHz predictions are on average accurate to within 2.2%, while extrapolating the Planck Collaboration (2013) single-MBB model systematically underpredicts emission by 18.8% at 100 GHz, 12.6% at 143 GHz and 7.9% at 217 GHz. We calibrate our two-component optical depth to reddening, and compare with reddening estimates based on stellar spectra. We find the dominant systematic problems in our temperature/reddening maps to be zodiacal light on large angular scales and the cosmic infrared background anisotropy on small angular scales. Future work will focus on combining our WISE 12 micron dust map and Planck dust model to create a next-generation, full-sky dust extinction map with angular resolution several times better than Schlegel et al. (1998).

Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

2012-12-01

Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite retrievals. Evaluation results are assessed against recommended criteria and peer studies in the literature. Further analysis is conducted, based upon these assessments, to discover likely errors in model inputs and potential deficiencies in the model itself. Correlations as well as differences in input errors and model deficiencies revealed by ground-level measurements versus satellite observations are discussed. Additionally, sensitivity analyses are employed to investigate errors in emission-rate estimates using either ground-level measurements or satellite retrievals, and the results are compared against each other considering observational uncertainties. Recommendations are made for how to effectively utilize satellite retrievals in regulatory air quality modeling.

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.

Fundamental mass transfer modeling of emission of volatile organic compounds from building materials

NASA Astrophysics Data System (ADS)

Bodalal, Awad Saad

In this study, a mass transfer theory based model is presented for characterizing the VOC emissions from building materials. A 3-D diffusion model is developed to describe the emissions of volatile organic compounds (VOCs) from individual sources. Then the formulation is extended to include the emissions from composite sources (system comprising an assemblage of individual sources). The key parameters for the model (The diffusion coefficient of the VOC in the source material D, and the equilibrium partition coefficient k e) were determined independently (model parameters are determined without the use of chamber emission data). This procedure eliminated to a large extent the need for emission testing using environmental chambers, which is costly, time consuming, and may be subject to confounding sink effects. An experimental method is developed and implemented to measure directly the internal diffusion (D) and partition coefficients ( ke). The use of the method is illustrated for three types of VOC's: (i) Aliphatic Hydrocarbons, (ii) Aromatic Hydrocarbons and ( iii) Aldehydes, through typical dry building materials (carpet, plywood, particleboard, vinyl floor tile, gypsum board, sub-floor tile and OSB). Then correlations for predicting D and ke based solely on commonly available properties such as molecular weight and vapour pressure were proposed for each product and type of VOC. These correlations can be used to estimate the D and ke when direct measurement data are not available, and thus facilitate the prediction of VOC emissions from the building materials using mass transfer theory. The VOC emissions from a sub-floor material (made of the recycled automobile tires), and a particleboard are measured and predicted. Finally, a mathematical model to predict the diffusion coefficient through complex sources (floor adhesive) as a function of time was developed. Then this model (for diffusion coefficient in complex sources) was used to predict the emission rate from material system (namely, substrate//glue//vinyl tile).

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

NASA Astrophysics Data System (ADS)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.

Implementation of the MEGAN (v2.1) biogenic emission model in the ECHAM6-HAMMOZ chemistry climate model

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; Stanelle, Tanja; Schröder, Sabine; Siegenthaler, Colombe; Taraborrelli, Domenico; Schultz, Martin G.

2017-02-01

A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the reference simulation is 634 Tg C yr-1 (simulation period 2000-2012). Isoprene is the main contributor to the average emission total, accounting for 66 % (417 Tg C yr-1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %), and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated with tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional biogenic volatile organic compound (BVOC) emissions of the reference simulation were compared to previous published experiment results with MEGAN. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained here are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of MEGAN. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about -9 %, but reaches +75 % for α-pinene when switching from global emission factor maps to PFT-specific emission factor distributions. The highest sensitivity of isoprene emissions is calculated when considering soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has an impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.

Evaluation of Biogenic and Fire Emissions in a Global Chemistry Model with NOMADSS, DC3 and SEAC4RS observations

NASA Astrophysics Data System (ADS)

Emmons, L. K.; Wiedinmyer, C.; Park, M.; Kaser, L.; Apel, E. C.; Guenther, A. B.

2014-12-01

Numerous measurements of compounds produced by biogenic and fire emissions were made during several recent field campaigns in the southeast United States, providing a unique data set for emissions and chemical model evaluation. The NCAR Community Atmosphere Model with Chemistry (CAM-chem) is coupled to the Community Land Model (CLM), which includes the biogenic emissions model MEGAN-v2.1, allowing for online calculation of emissions from vegetation for 150 compounds. Simulations of CAM-chem for summers 2012 and 2013 are evaluated with the aircraft and ground-based observations from DC3, NOMADSS and SEAC4RS. Comparison of directly emitted biogenic species, such as isoprene, terpenes, methanol and acetone, are used to evaluate the MEGAN emissions. Evaluation of oxidation products, including methyl vinyl ketone (MVK), methacrolein, formaldehyde, and other oxygenated VOCs are used to test the model chemistry mechanism. In addition, several biomass burning inventories are used in the model, including FINN, QFED, and FLAMBE, and are compared for their impact on atmospheric composition and ozone production, and evaluated with the aircraft observations.

An objective decision model of power grid environmental protection based on environmental influence index and energy-saving and emission-reducing index

NASA Astrophysics Data System (ADS)

Feng, Jun-shu; Jin, Yan-ming; Hao, Wei-hua

2017-01-01

Based on modelling the environmental influence index of power transmission and transformation project and energy-saving and emission-reducing index of source-grid-load of power system, this paper establishes an objective decision model of power grid environmental protection, with constraints of power grid environmental protection objectives being legal and economical, and considering both positive and negative influences of grid on the environmental in all-life grid cycle. This model can be used to guide the programming work of power grid environmental protection. A numerical simulation of Jiangsu province’s power grid environmental protection objective decision model has been operated, and the results shows that the maximum goal of energy-saving and emission-reducing benefits would be reached firstly as investment increasing, and then the minimum goal of environmental influence.

Validation of smoke plume rise models using ground based lidar

Treesearch

Cyle E. Wold; Shawn Urbanski; Vladimir Kovalev; Alexander Petkov; Wei Min Hao

2010-01-01

Biomass fires can significantly degrade regional air quality. Plume rise height is one of the critical factors determining the impact of fire emissions on air quality. Plume rise models are used to prescribe the vertical distribution of fire emissions which are critical input for smoke dispersion and air quality models. The poor state of model evaluation is due in...

Why models struggle to capture Arctic Haze: the underestimated role of gas flaring and domestic combustion emissions

NASA Astrophysics Data System (ADS)

Stohl, A.; Klimont, Z.; Eckhardt, S.; Kupiainen, K.

2013-04-01

Arctic Haze is a seasonal phenomenon with high concentrations of accumulation-mode aerosols occurring in the Arctic in winter and early spring. Chemistry transport models and climate chemistry models struggle to reproduce this phenomenon, and this has recently prompted changes in aerosol removal schemes to remedy the modeling problems. In this paper, we show that shortcomings in current emission data sets are at least as important. We perform a 3 yr model simulation of black carbon (BC) with the Lagrangian particle dispersion model FLEXPART. The model is driven with a new emission data set which includes emissions from gas flaring. While gas flaring is estimated to contribute less than 3% of global BC emissions in this data set, flaring dominates the estimated BC emissions in the Arctic (north of 66° N). Putting these emissions into our model, we find that flaring contributes 42% to the annual mean BC surface concentrations in the Arctic. In March, flaring even accounts for 52% of all Arctic BC near the surface. Most of the flaring BC remains close to the surface in the Arctic, so that the flaring contribution to BC in the middle and upper troposphere is small. Another important factor determining simulated BC concentrations is the seasonal variation of BC emissions from domestic combustion. We have calculated daily domestic combustion emissions using the heating degree day (HDD) concept based on ambient air temperature and compare results from model simulations using emissions with daily, monthly and annual time resolution. In January, the Arctic-mean surface concentrations of BC due to domestic combustion emissions are 150% higher when using daily emissions than when using annually constant emissions. While there are concentration reductions in summer, they are smaller than the winter increases, leading to a systematic increase of annual mean Arctic BC surface concentrations due to domestic combustion by 68% when using daily emissions. A large part (93%) of this systematic increase can be captured also when using monthly emissions; the increase is compensated by a decreased BC burden at lower latitudes. In a comparison with BC measurements at six Arctic stations, we find that using daily-varying domestic combustion emissions and introducing gas flaring emissions leads to large improvements of the simulated Arctic BC, both in terms of mean concentration levels and simulated seasonality. Case studies based on BC and carbon monoxide (CO) measurements from the Zeppelin observatory appear to confirm flaring as an important BC source that can produce pollution plumes in the Arctic with a high BC/CO enhancement ratio, as expected for this source type. Our results suggest that it may not be "vertical transport that is too strong or scavenging rates that are too low" and "opposite biases in these processes" in the Arctic and elsewhere in current aerosol models, as suggested in a recent review article (Bond et al., 2013), but missing emission sources and lacking time resolution of the emission data that are causing opposite model biases in simulated BC concentrations in the Arctic and in the mid-latitudes.

Thermal history regulates methylbutenol basal emission rate in Pinus ponderosa.

PubMed

Gray, Dennis W; Goldstein, Allen H; Lerdau, Manuel T

2006-07-01

Methylbutenol (MBO) is a 5-carbon alcohol that is emitted by many pines in western North America, which may have important impacts on the tropospheric chemistry of this region. In this study, we document seasonal changes in basal MBO emission rates and test several models predicting these changes based on thermal history. These models represent extensions of the ISO G93 model that add a correction factor C(basal), allowing MBO basal emission rates to change as a function of thermal history. These models also allow the calculation of a new emission parameter E(standard30), which represents the inherent capacity of a plant to produce MBO, independent of current or past environmental conditions. Most single-component models exhibited large departures in early and late season, and predicted day-to-day changes in basal emission rate with temporal offsets of up to 3 d relative to measured basal emission rates. Adding a second variable describing thermal history at a longer time scale improved early and late season model performance while retaining the day-to-day performance of the parent single-component model. Out of the models tested, the T(amb),T(max7) model exhibited the best combination of day-to-day and seasonal predictions of basal MBO emission rates.

New Approach in Modelling Indonesian Peat Fire Emission

NASA Astrophysics Data System (ADS)

Putra, E. I.; Cochrane, M. A.; Saharjo, B.; Yokelson, R. J.; Stockwell, C.; Vetrita, Y.; Zhang, X.; Hagen, S. C.; Nurhayati, A. D.; Graham, L.

2017-12-01

Peat fires are a serious problem for Indonesia, producing devastating environmental effects and making the country the 3rd largest emitter of CO2. Extensive fires ravaged vast areas of peatlands in Sumatra, Kalimantan and Papua during the pronounced El-Nino of 2015, causing international concern when the resultant haze blanketed Indonesia and neighboring countries, severely impacting the health of millions of people. Our recent unprecedented in-situ studies of aerosol and gas emissions from 35 peat fires of varying depths near Palangka Raya, Central Kalimantan have documented the range and variability of emissions from these major fires. We strongly suggest revisions to previously recommended IPPC's emission factors (EFs) from peat fires, notably: CO2 (-8%), CH4 (-55%), NH3 (-86%), and CO (+39%). Our findings clearly showed that Indonesian carbon equivalent measurements (100 years) might have been 19% less than what current IPCC emission factors indicate. The results also demonstrate the toxic air quality in the area with HCN, which is almost only emitted by biomass burning, accounting for 0.28% and the carcinogenic compound formaldehyde 0.04% of emissions. However, considerable variation in emissions may exist between peat fires of different Indonesian peat formations, illustrating the need for additional regional field emissions measurements for parameterizing peatland emissions models for all of Indonesia's major peatland areas. Through the continuous mutual research collaboration between the Indonesian and USA scientists, we will implement our standardized field-based analyses of fuels, hydrology, peat burning characteristics and fire emissions to characterize the three major Indonesian peatland formations across four study provinces (Central Kalimantan, Riau, Jambi and West Papua). We will provide spatial and temporal drivers of the modeled emissions and validate them at a national level using biomass burning emissions estimations derived from Visible/Infrared Imager and Radiometer Suite (VIIRS). Multiple LiDAR datasets (2014, 2011, 2007) for Kalimantan will be used to quantify model accuracy, and new work will be undertaken to quantify uncertainty in our most recent LiDAR-based digital terrain model (DTM), further improving assessments of modelling errors.

Research on Bifurcation and Chaos in a Dynamic Mixed Game System with Oligopolies Under Carbon Emission Constraint

NASA Astrophysics Data System (ADS)

Ma, Junhai; Yang, Wenhui; Lou, Wandong

This paper establishes an oligopolistic game model under the carbon emission reduction constraint and investigates its complex characteristics like bifurcation and chaos. Two oligopolistic manufacturers comprise three mixed game models, aiming to explore the variation in the status of operating system as per the upgrading of benchmark reward-penalty mechanism. Firstly, we set up these basic models that are respectively distinguished with carbon emission quantity and study these models using different game methods. Then, we concentrate on one typical game model to further study the dynamic complexity of variations in the system status, through 2D bifurcation diagrams and 4D parameter adjustment features based on the bounded rationality scheme for price, and the adaptive scheme for carbon emission. The results show that the carbon emission constraint has significant influence on the status variation of two-oligopolistic game operating systems no matter whether it is stable or chaotic. Besides, the new carbon emission regulation meets government supervision target and achieves the goal of being environment friendly by motivating the system to operate with lower carbon emission.

Methane emissions from floodplains in the Amazon Basin: towards a process-based model for global applications

NASA Astrophysics Data System (ADS)

Ringeval, B.; Houweling, S.; van Bodegom, P. M.; Spahni, R.; van Beek, R.; Joos, F.; Röckmann, T.

2013-10-01

Tropical wetlands are estimated to represent about 50% of the natural wetland emissions and explain a large fraction of the observed CH4 variability on time scales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This study documents the first regional-scale, process-based model of CH4 emissions from tropical floodplains. The LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially-explicit hydrology model PCR-GLOBWB. We introduced new Plant Functional Types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote sensing datasets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX simulated CH4 flux densities are in reasonable agreement with observations at the field scale but with a~tendency to overestimate the flux observed at specific sites. In addition, the model did not reproduce between-site variations or between-year variations within a site. Unfortunately, site informations are too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr-1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin modulated emissions by about 20%. Correcting the LPX simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the seasonality in CH4 emissions. The Inter Annual Variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is account for, but still remains lower than in most of WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results stress the need for more research to constrain floodplain CH4 emissions and their temporal variability.

Spectral Neugebauer-based color halftone prediction model accounting for paper fluorescence.

PubMed

Hersch, Roger David

2014-08-20

We present a spectral model for predicting the fluorescent emission and the total reflectance of color halftones printed on optically brightened paper. By relying on extended Neugebauer models, the proposed model accounts for the attenuation by the ink halftones of both the incident exciting light in the UV wavelength range and the emerging fluorescent emission in the visible wavelength range. The total reflectance is predicted by adding the predicted fluorescent emission relative to the incident light and the pure reflectance predicted with an ink-spreading enhanced Yule-Nielsen modified Neugebauer reflectance prediction model. The predicted fluorescent emission spectrum as a function of the amounts of cyan, magenta, and yellow inks is very accurate. It can be useful to paper and ink manufacturers who would like to study in detail the contribution of the fluorescent brighteners and the attenuation of the fluorescent emission by ink halftones.

Competition between the compound and the pre-compound emission processes in α-induced reactions at near astrophysical energy to well above it

NASA Astrophysics Data System (ADS)

Sharma, Manoj Kumar; Sharma, Vijay Raj; Yadav, Abhiskek; Singh, Pushpendra P.; Singh, B. P.; Prasad, R.

2016-04-01

The study of pre-compound emission in α-induced reactions, particularly at the low incident energies, is of considerable interest as the pre-compound emission is more likely to occur at higher energies. With a view to study the competition between the compound and the pre-compound emission processes in α-induced reactions at different energies and with different targets, a systematics for neutron emission channels in targets 51V, 55Mn, 93Nb, 121, 123Sb and 141Pr at energy ranging from astrophysical interest to well above it, has been developed. The off-line γ-ray-spectrometry based activation technique has been adopted to measure the excitation functions. The experimental excitation functions have been analysed within the framework of the compound nucleus mechanism based on the Weisskopf-Ewing model and the pre-compound emission calculations based on the geometry dependent hybrid model. The analysis of the data shows that experimental excitation functions could be reproduced only when the pre-compound emission, simulated theoretically, is taken into account. The strength of pre-compound emission process for each system has been obtained by deducing the pre-compound fraction. Analysis of data indicates that in α-induced reactions, the pre-compound emission process plays an important role, particularly at the low incident energies, where the pure compound nucleus process is likely to dominate.

DEVELOPMENT OF A MODEL FOR REAL TIME CO CONCENTRATIONS NEAR ROADWAYS

EPA Science Inventory

Although emission standards for mobile sources continue to be tightened, tailpipe emissions in urban areas continue to be a major source of human exposure to air toxics. Current human exposure models using simplified assumptions based on fixed air monitoring stations and region...

A global gas flaring black carbon emission rate dataset from 1994 to 2012

PubMed Central

Huang, Kan; Fu, Joshua S.

2016-01-01

Global flaring of associated petroleum gas is a potential emission source of particulate matters (PM) and could be notable in some specific regions that are in urgent need of mitigation. PM emitted from gas flaring is mainly in the form of black carbon (BC), which is a strong short-lived climate forcer. However, BC from gas flaring has been neglected in most global/regional emission inventories and is rarely considered in climate modeling. Here we present a global gas flaring BC emission rate dataset for the period 1994–2012 in a machine-readable format. We develop a region-dependent gas flaring BC emission factor database based on the chemical compositions of associated petroleum gas at various oil fields. Gas flaring BC emission rates are estimated using this emission factor database and flaring volumes retrieved from satellite imagery. Evaluation using a chemical transport model suggests that consideration of gas flaring emissions can improve model performance. This dataset will benefit and inform a broad range of research topics, e.g., carbon budget, air quality/climate modeling, and environmental/human exposure. PMID:27874852

A global gas flaring black carbon emission rate dataset from 1994 to 2012

NASA Astrophysics Data System (ADS)

Huang, Kan; Fu, Joshua S.

2016-11-01

Global flaring of associated petroleum gas is a potential emission source of particulate matters (PM) and could be notable in some specific regions that are in urgent need of mitigation. PM emitted from gas flaring is mainly in the form of black carbon (BC), which is a strong short-lived climate forcer. However, BC from gas flaring has been neglected in most global/regional emission inventories and is rarely considered in climate modeling. Here we present a global gas flaring BC emission rate dataset for the period 1994-2012 in a machine-readable format. We develop a region-dependent gas flaring BC emission factor database based on the chemical compositions of associated petroleum gas at various oil fields. Gas flaring BC emission rates are estimated using this emission factor database and flaring volumes retrieved from satellite imagery. Evaluation using a chemical transport model suggests that consideration of gas flaring emissions can improve model performance. This dataset will benefit and inform a broad range of research topics, e.g., carbon budget, air quality/climate modeling, and environmental/human exposure.

LOW EMISSION AND HIGH EFFICIENCY RESIDENTIAL PELLET-FIRED HEATERS

EPA Science Inventory

The paper gives results of air emissions testing and efficiency testing on new commercially available under-feed and top-feed residential heaters burning hardwood- and softwood-based pellets. The results were compared with data from earlier models. Reductions in air emissions w...

DEVELOPMENT OF THE MODEL OF GALACTIC INTERSTELLAR EMISSION FOR STANDARD POINT-SOURCE ANALYSIS OF FERMI LARGE AREA TELESCOPE DATA

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

Acero, F.; Ballet, J.; Ackermann, M.

2016-04-01

Most of the celestial γ rays detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope originate from the interstellar medium when energetic cosmic rays interact with interstellar nucleons and photons. Conventional point-source and extended-source studies rely on the modeling of this diffuse emission for accurate characterization. Here, we describe the development of the Galactic Interstellar Emission Model (GIEM), which is the standard adopted by the LAT Collaboration and is publicly available. This model is based on a linear combination of maps for interstellar gas column density in Galactocentric annuli and for the inverse-Compton emission producedmore » in the Galaxy. In the GIEM, we also include large-scale structures like Loop I and the Fermi bubbles. The measured gas emissivity spectra confirm that the cosmic-ray proton density decreases with Galactocentric distance beyond 5 kpc from the Galactic Center. The measurements also suggest a softening of the proton spectrum with Galactocentric distance. We observe that the Fermi bubbles have boundaries with a shape similar to a catenary at latitudes below 20° and we observe an enhanced emission toward their base extending in the north and south Galactic directions and located within ∼4° of the Galactic Center.« less

Development of the Model of Galactic Interstellar Emission for Standard Point-Source Analysis of Fermi Large Area Telescope Data

NASA Technical Reports Server (NTRS)

Acero, F.; Ackermann, M.; Ajello, M.; Albert, A.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bellazzini, R.; Brandt, T. J.;

Seasonal Variation and Ecosystem Dependence of Emission Factors for Selected Trace Gases and PM2.5 for Southern African Savanna Fires

NASA Technical Reports Server (NTRS)

Korontzi, S.; Ward, D. E.; Susott, R. A.; Yokelson, R. J.; Justice, C. O.; Hobbs, P. V.; Smithwick, E. A. H.; Hao, W. M.

2003-01-01

In this paper we present the first early dry season (early June-early August) emission factor measurements for carbon dioxide (CO2), carbon monoxide (CO), methane (Ca), nonmethane hydrocarbons (NMHC), and particulates with a diameter less than 2.5 microns (pM2.5) for southern African grassland and woodland fires. Seasonal emission factors for grassland fires correlate linearly with the proportion of green grass, used as a surrogate for the fuel moisture content, and are higher for products of incomplete combustion in the early part of the dry season compared with later in the dry season. Models of emission factors for NMHC and PM(sub 2.5) versus modified combustion efficiency (MCE) are statistically different in grassland compared with woodland ecosystems. We compare predictions based on the integration of emissions factors from this study, from the southern African Fire-Atmosphere Research Initiative 1992 (SAFARI-92), and from SAFARI-2000 with those based on the smaller set of ecosystem-specific emission factors to estimate the effects of using regional-average rather than ecosystem-specific emission factors. We also test the validity of using the SAFARI-92 models for emission factors versus MCE to predict the early dry season emission factors measured in this study. The comparison indicates that the largest discrepancies occur at the low end (0.907) and high end (0.972) of MCE values measured in this study. Finally, we combine our models of MCE versus proportion of green grass for grassland fires with emission factors versus MCE for selected oxygenated volatile organic compounds measured in the SAFARI-2000 campaign to derive the first seasonal emission factors for these compounds. The results of this study demonstrate that seasonal variations in savanna fire emissions are important and should be considered in modeling emissions at regional to continental scales.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

NASA Astrophysics Data System (ADS)

Ringeval, B.; Houweling, S.; van Bodegom, P. M.; Spahni, R.; van Beek, R.; Joos, F.; Röckmann, T.

2014-03-01

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial-interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr-1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

util_2comp: Planck-based two-component dust model utilities

NASA Astrophysics Data System (ADS)

Meisner, Aaron

2014-11-01

The util_2comp software utilities generate predictions of far-infrared Galactic dust emission and reddening based on a two-component dust emission model fit to Planck HFI, DIRBE and IRAS data from 100 GHz to 3000 GHz. These predictions and the associated dust temperature map have angular resolution of 6.1 arcminutes and are available over the entire sky. Implementations in IDL and Python are included.

Estimation of ambient BVOC emissions using remote sensing techniques

NASA Astrophysics Data System (ADS)

Nichol, Janet; Wong, Man Sing

2011-06-01

The contribution of Biogenic Volatile Organic Compounds (BVOCs) to local air quality modelling is often ignored due to the difficulty of obtaining accurate spatial estimates of emissions. Yet their role in the formation of secondary aerosols and photochemical smog is thought to be significant, especially in hot tropical cities such as Hong Kong, which are situated downwind from dense forests. This paper evaluates Guenther et al.'s [Guenther, A., Hewitt, C.N., Erickson, D., Fall, R., Geron, C., Graedel, T.E., Harley, P., Klinger, L., Lerdau, M., McKay, W.A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmerman, P., 1995. A global model of natural volatile organic compound emissions. Journal of Geophysical Research 100, 8873-8892] global model of BVOC emissions, for application at a spatially detailed level to Hong Kong's tropical forested landscape using high resolution remote sensing and ground data. The emission estimates are based on a landscape approach which assigns emission rates directly to ecosystem types not to individual species, since unlike in temperate regions where one or two single species may dominate over large regions, Hong Kong's vegetation is extremely diverse with up to 300 different species in one hectare. The resulting BVOC emission maps are suitable for direct input to regional and local air quality models giving 10 m raster output on an hourly basis over the whole of the Hong Kong territory, an area of 1100 km 2. Due to the spatially detailed mapping of isoprene emissions over the study area, it was possible to validate the model output using field data collected at a precise time and place by replicating those conditions in the model. The field measurement of emissions used for validating the model was based on a canister sampling technique, undertaken under different climatic conditions for Hong Kong's main ecosystem types in both urban and rural areas. The model-derived BVOC flux distributions appeared to be consistent with the field observations, indicating the robustness of the landscape modelling approach when applied to tropical forests at detailed level, as well as the promising role of remote sensing in BVOC mapping.

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.

Research on the Direct Carbon Emission Forecast of CHINA'S Provincial Residents Based on Neural Network

NASA Astrophysics Data System (ADS)

Zhang, T.; Zhou, B.; Zhou, S.; Yan, W.

2018-04-01

Global climate change, which mainly effected by human carbon emissions, would affect the regional economic, natural ecological environment, social development and food security in the near future. It's particularly important to make accurate predictions of carbon emissions based on current carbon emissions. This paper accounted out the direct consumption of carbon emissions data from 1995 to 2014 about 30 provinces (the data of Tibet, Hong Kong, Macao and Taiwan is missing) and the whole of China. And it selected the optimal models from BP, RBF and Elman neural network for direct carbon emission prediction, what aim was to select the optimal prediction method and explore the possibility of reaching the peak of residents direct carbon emissions of China in 2030. Research shows that: 1) Residents' direct carbon emissions per capita of all provinces showed an upward trend in 20 years. 2) The accuracy of the prediction results by Elman neural network model is higher than others and more suitable for carbon emission data projections. 3) With the situation of residents' direct carbon emissions free development, the direct carbon emissions will show a fast to slow upward trend in the next few years and began to flatten after 2020, and the direct carbon emissions of per capita will reach the peak in 2032. This is also confirmed that China is expected to reach its peak in carbon emissions by 2030 in theory.

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

2013-08-01

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport. Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3 emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOx differed among the emissions that were obtained from the different disaggregation methods. In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventories.

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.

Physical characterization of the fine particle emissions from commercial aircraft engines during the Aircraft Particle Emissions Experiment (APEX) 1 to 3

EPA Science Inventory

The f1me particulate matter (PM) emissions from nine commercial aircraft engine models were determined by plume sampling during the three field campaigns of the Aircraft Particle Emissions Experiment (APEX). Ground-based measurements were made primarily at 30 m behind the engine ...

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%).

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

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

Meng, L.; Paudel, R.; Hess, P. G. M.

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

DOE PAGES

Meng, L.; Paudel, R.; Hess, P. G. M.; ...

2015-07-03

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which themore » atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.« less

Modeling methane and nitrous oxide emissions from direct-seeded rice systems

NASA Astrophysics Data System (ADS)

Simmonds, Maegen B.; Li, Changsheng; Lee, Juhwan; Six, Johan; van Kessel, Chris; Linquist, Bruce A.

2015-10-01

Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scale of management and policy making. However, the accuracy of these models in simulating CH4 and N2O emissions in direct-seeded rice systems under various management practices remains a question. We empirically evaluated the denitrification-decomposition model for estimating CH4 and N2O fluxes in California rice systems. Five and nine site-year combinations were used for calibration and validation, respectively. The model was parameterized for two cultivars, M206 and Koshihikari, and able to simulate 30% and 78% of the variation in measured yields, respectively. Overall, modeled and observed seasonal CH4 emissions were similar (R2 = 0.85), but there was poor correspondence in fallow period CH4 emissions and in seasonal and fallow period N2O emissions. Furthermore, management effects on seasonal CH4 emissions were highly variable and not well represented by the model (0.2-465% absolute relative deviation). Specifically, simulated CH4 emissions were oversensitive to fertilizer N rate but lacked sensitivity to the type of seeding system (dry seeding versus water seeding) and prior fallow period straw management. Additionally, N2O emissions were oversensitive to fertilizer N rate and field drainage. Sensitivity analysis showed that CH4 emissions were highly sensitive to changes in the root to total plant biomass ratio, suggesting that it is a significant source of model uncertainty. These findings have implications for model-directed field research that could improve model representation of paddy soils for application at larger spatial scales.

Evaluation of transportation/air quality model improvements based on TOTEMS on-road driving style and tailpipe emissions data.

DOT National Transportation Integrated Search

2014-06-01

In June 2012, the Environmental Protection Agency (EPA) released the Operating Mode : Distribution Generator (OMDG) a tool for developing an operating mode distribution as an input : to the Motor Vehicle Emissions Simulator model (MOVES). The t...

HEAVY-DUTY GREENHOUSE GAS EMISSIONS MODEL (GEM)

EPA Science Inventory

Class 2b-8 vocational truck manufacturers and Class 7/8 tractor manufacturers would be subject to vehicle-based fuel economy and emission standards that would use a truck simulation model to evaluate the impact of the truck tires and/or tractor cab design on vehicle compliance wi...

Quantifying the sources of ozone, fine particulate matter, and regional haze in the Southeastern United States.

PubMed

Odman, M Talat; Hu, Yongtao; Russell, Armistead G; Hanedar, Asude; Boylan, James W; Brewer, Patricia F

2009-07-01

A detailed sensitivity analysis was conducted to quantify the contributions of various emission sources to ozone (O3), fine particulate matter (PM2.5), and regional haze in the Southeastern United States. O3 and particulate matter (PM) levels were estimated using the Community Multiscale Air Quality (CMAQ) modeling system and light extinction values were calculated from modeled PM concentrations. First, the base case was established using the emission projections for the year 2009. Then, in each model run, SO2, primary carbon (PC), NH3, NO(x) or VOC emissions from a particular source category in a certain geographic area were reduced by 30% and the responses were determined by calculating the difference between the results of the reduced emission case and the base case. The sensitivity of summertime O3 to VOC emissions is small in the Southeast and ground-level NO(x) controls are generally more beneficial than elevated NO(x) controls (per unit mass of emissions reduced). SO2 emission reduction is the most beneficial control strategy in reducing summertime PM2.5 levels and improving visibility in the Southeast and electric generating utilities are the single largest source of SO2. Controlling PC emissions can be very effective locally, especially in winter. Reducing NH3 emissions is an effective strategy to reduce wintertime ammonium nitrate (NO3NH4) levels and improve visibility; NO(x) emissions reductions are not as effective. The results presented here will help the development of specific emission control strategies for future attainment of the National Ambient Air Quality Standards in the region.

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.

Areas of Anomalous Surface Temperature in Archuleta County, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Archuleta County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma

Areas of Anomalous Surface Temperature in Dolores County, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Dolores County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma

Areas of Anomalous Surface Temperature in Chaffee County, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Chaffee County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma

Areas of Anomalous Surface Temperature in Garfield County, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Garfield County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

Areas of Anomalous Surface Temperature in Routt County, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Routt County identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies). Note: 'o' is used in this description to represent lowercase sigma.

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.

A GIS-BASED MODAL MODEL OF AUTOMOBILE EXHAUST EMISSIONS

EPA Science Inventory

The report presents progress toward the development of a computer tool called MEASURE, the Mobile Emission Assessment System for Urban and Regional Evaluation. The tool works toward a goal of providing researchers and planners with a way to assess new mobile emission mitigation s...

Isoprene emission response to drought and the impact on global atmospheric chemistry

NASA Astrophysics Data System (ADS)

Jiang, Xiaoyan; Guenther, Alex; Potosnak, Mark; Geron, Chris; Seco, Roger; Karl, Thomas; Kim, Saewung; Gu, Lianhong; Pallardy, Stephen

2018-06-01

Biogenic isoprene emissions play a very important role in atmospheric chemistry. These emissions are strongly dependent on various environmental conditions, such as temperature, solar radiation, plant water stress, ambient ozone and CO2 concentrations, and soil moisture. Current biogenic emission models (i.e., Model of Emissions of Gases and Aerosols from Nature, MEGAN) can simulate emission responses to some of the major driving variables, such as short-term variations in temperature and solar radiation, but the other factors are either missing or poorly represented. In this paper, we propose a new modelling approach that considers the physiological effects of drought stress on plant photosynthesis and isoprene emissions for use in the MEGAN3 biogenic emission model. We test the MEGAN3 approach by integrating the algorithm into the existing MEGAN2.1 biogenic emission model framework embedded into the global Community Land Model of the Community Earth System Model (CLM4.5/CESM1.2). Single-point simulations are compared against available field measurements at the Missouri Ozarks AmeriFlux (MOFLUX) field site. The modelling results show that the MEGAN3 approach of using of a photosynthesis parameter (Vcmax) and soil wetness factor (βt) to determine the drought activity factor leads to better simulated isoprene emissions in non-drought and drought periods. The global simulation with the MEGAN3 approach predicts a 17% reduction in global annual isoprene emissions, in comparison to the value predicted using the default CLM4.5/MEGAN2.1 without any drought effect. This reduction leads to changes in surface ozone and oxidants in the areas where the reduction of isoprene emissions is observed. Based on the results presented in this study, we conclude that it is important to simulate the drought-induced response of biogenic isoprene emission accurately in the coupled Earth System model.

Improving dust emission characterization in dust models using dynamic high-resolution geomorphic erodibility map

NASA Astrophysics Data System (ADS)

Parajuli, S. P.; Yang, Z.; Kocurek, G.

2013-12-01

Dust is known to affect the earth radiation budget, biogeochemical cycle, precipitation, human health and visibility. Despite the increased research effort, dust emission modeling remains challenging because dust emission is affected by complex geomorphological processes. Existing dust models overestimate dust emission and rely on tuning and a static erodibility factor in order to make simulated results comparable to remote sensing and ground-based observations. In most of current models, dust emission is expressed in terms of threshold friction speed, which ultimately depends mainly upon the percentage clay content and soil moisture. Unfortunately, due to the unavailability of accurate and high resolution input data of the clay content and soil moisture, estimated threshold friction speed commonly does not represent the variability in field condition. In this work, we attempt to improve dust emission characterization by developing a high resolution geomorphic map of the Middle East and North Africa (MENA), which is responsible for more than 50% of global dust emission. We develop this geomorphic map by visually examining high resolution satellite images obtained from Google Earth Pro and ESRI base map. Albeit subjective, our technique is more reliable compared to automatic image classification technique because we incorporate knowledge of geological/geographical setting in identifying dust sources. We hypothesize that the erodibility is unique for different geomorphic landforms and that it can be quantified by the correlation between observed wind speed and satellite retrieved aerosol optical depth (AOD). We classify the study area into several key geomorphological categories with respect to their dust emission potential. Then we quantify their dust emission potential using the correlation between observed wind speed and satellite retrieved AOD. The dynamic, high-resolution geomorphic erodibility map thus prepared will help to reduce the uncertainty in current dust models associated with poor characterization of dust sources. The baseline dust scheme used in this study is the Dust Entrainment and Deposition (DEAD) model, which is also a component of the community land model (CLM). Proposed improvements in the dust emission representation will help to better understand the accurate effect of dust on climate processes.

Mercury emission and dispersion models from soils contaminated by cinnabar mining and metallurgy.

PubMed

Llanos, Willians; Kocman, David; Higueras, Pablo; Horvat, Milena

2011-12-01

The laboratory flux measurement system (LFMS) and dispersion models were used to investigate the kinetics of mercury emission flux (MEF) from contaminated soils. Representative soil samples with respect to total Hg concentration (26-9770 μg g(-1)) surrounding a decommissioned mercury-mining area (Las Cuevas Mine), and a former mercury smelter (Cerco Metalúrgico de Almadenejos), in the Almadén mercury mining district (South Central Spain), were collected. Altogether, 14 samples were analyzed to determine the variation in mercury emission flux (MEF) versus distance from the sources, regulating two major environmental parameters comprising soil temperature and solar radiation. In addition, the fraction of the water-soluble mercury in these samples was determined in order to assess how MEF from soil is related to the mercury in the aqueous soil phase. Measured MEFs ranged from less than 140 to over 10,000 ng m(-2) h(-1), with the highest emissions from contaminated soils adjacent to point sources. A significant decrease of MEF was then observed with increasing distance from these sites. Strong positive effects of both temperature and solar radiation on MEF was observed. Moreover, MEF was found to occur more easily in soils with higher proportions of soluble mercury compared to soils where cinnabar prevails. Based on the calculated Hg emission rates and with the support of geographical information system (GIS) tools and ISC AERMOD software, dispersion models for atmospheric mercury were implemented. In this way, the gaseous mercury plume generated by the soil-originated emissions at different seasons was modeled. Modeling efforts revealed that much higher emissions and larger mercury plumes are generated in dry and warm periods (summer), while the plume is smaller and associated with lower concentrations of atmospheric mercury during colder periods with higher wind activity (fall). Based on the calculated emissions and the model implementation, yearly emissions from the "Cerco Metalúrgico de Almadenejos" decommissioned metallurgical precinct were estimated at 16.4 kg Hg y(-1), with significant differences between seasons.

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.

Implications of overestimated anthropogenic CO2 emissions on East Asian and global land CO2 flux inversion

NASA Astrophysics Data System (ADS)

Saeki, Tazu; Patra, Prabir K.

2017-12-01

Measurement and modelling of regional or country-level carbon dioxide (CO2) fluxes are becoming critical for verification of the greenhouse gases emission control. One of the commonly adopted approaches is inverse modelling, where CO2 fluxes (emission: positive flux, sink: negative flux) from the terrestrial ecosystems are estimated by combining atmospheric CO2 measurements with atmospheric transport models. The inverse models assume anthropogenic emissions are known, and thus the uncertainties in the emissions introduce systematic bias in estimation of the terrestrial (residual) fluxes by inverse modelling. Here we show that the CO2 sink increase, estimated by the inverse model, over East Asia (China, Japan, Korea and Mongolia), by about 0.26 PgC year-1 (1 Pg = 1012 g) during 2001-2010, is likely to be an artifact of the anthropogenic CO2 emissions increasing too quickly in China by 1.41 PgC year-1. Independent results from methane (CH4) inversion suggested about 41% lower rate of East Asian CH4 emission increase during 2002-2012. We apply a scaling factor of 0.59, based on CH4 inversion, to the rate of anthropogenic CO2 emission increase since the anthropogenic emissions of both CO2 and CH4 increase linearly in the emission inventory. We find no systematic increase in land CO2 uptake over East Asia during 1993-2010 or 2000-2009 when scaled anthropogenic CO2 emissions are used, and that there is a need of higher emission increase rate for 2010-2012 compared to those calculated by the inventory methods. High bias in anthropogenic CO2 emissions leads to stronger land sinks in global land-ocean flux partitioning in our inverse model. The corrected anthropogenic CO2 emissions also produce measurable reductions in the rate of global land CO2 sink increase post-2002, leading to a better agreement with the terrestrial biospheric model simulations that include CO2-fertilization and climate effects.

Assembling a biogenic hydrocarbon emissions inventory for the SCOS97-NARSTO modeling domain

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

Benjamin, M.T.; Winer, A.M.; Karlik, J.

1998-12-31

To assist in developing ozone control strategies for Southern California, the California Air Resources Board is developing a biogenic hydrocarbon (BHC) emissions inventory model for the SCOS97-NARSTO domain. The basis for this bottom-up model is SCOS97-NARSTO-specific landuse and landcover maps, leafmass constants, and BHC emission rates. In urban areas, landuse maps developed by the Southern California Association of Governments, San Diego Association of Governments, and other local governments are used while in natural areas, landcover and plant community databases produced by the GAP Analysis Project (GAP) are employed. Plant identities and canopy volumes for species in each landuse and landcovermore » category are based on the most recent botanical field survey data. Where possible, experimentally determined leafmass constant and BHC emission rate measurements reported in the literature are used or, for those species where experimental data are not available, values are assigned based on taxonomic methods. A geographic information system is being used to integrate these databases, as well as the most recent environmental correction algorithms and canopy shading factors, to produce a spatially- and temporally-resolved BHC emission inventory suitable for input into the Urban Airshed Model.« less

Ammonia emission model for whole farm evaluation of dairy production systems.

PubMed

Rotz, C Alan; Montes, Felipe; Hafner, Sasha D; Heber, Albert J; Grant, Richard H

2014-07-01

Ammonia (NH) emissions vary considerably among farms as influenced by climate and management. Because emission measurement is difficult and expensive, process-based models provide an alternative for estimating whole farm emissions. A model that simulates the processes of NH formation, speciation, aqueous-gas partitioning, and mass transfer was developed and incorporated in a whole farm simulation model (the Integrated Farm System Model). Farm sources included manure on the floor of the housing facility, manure in storage (if used), field-applied manure, and deposits on pasture (if grazing is used). In a comprehensive evaluation of the model, simulated daily, seasonal, and annual emissions compared well with data measured over 2 yr for five free stall barns and two manure storages on dairy farms in the eastern United States. In a further comparison with published data, simulated and measured barn emissions were similar over differing barn designs, protein feeding levels, and seasons of the year. Simulated emissions from manure storage were also highly correlated with published emission data across locations, seasons, and different storage covers. For field applied manure, the range in simulated annual emissions normally bounded reported mean values for different manure dry matter contents and application methods. Emissions from pastures measured in northern Europe across seasons and fertilization levels were also represented well by the model. After this evaluation, simulations of a representative dairy farm in Pennsylvania illustrated the effects of animal housing and manure management on whole farm emissions and their interactions with greenhouse gas emissions, nitrate leaching, production costs, and farm profitability. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Modeling Modern Methane Emissions from Natural Wetlands. 2; Interannual Variations 1982-1993

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin; Mattews, Elaine; Hansen, James E. (Technical Monitor)

2001-01-01

A global run of a process-based methane model [Walter et al., this issue] is performed using high-frequency atmospheric forcing fields from ECMWF reanalyses of the period from 1982 to 1993. We calculate global annual methane emissions to be 260 Tg/ yr. 25% of methane emissions originate from wetlands north of 30 deg. N. Only 60% of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands, the seasonality of simulated and observed methane emissions agrees well. The effects of sub-grid scale variations in model parameters and input data are examined. Modeled methane emissions show high regional, seasonal and interannual variability. Seasonal cycles of methane emissions are dominated by temperature in high latitude wetlands, and by changes in the water table in tropical wetlands. Sensitivity tests show that +/- 1 C changes in temperature lead to +/- 20 % changes in methane emissions from wetlands. Uniform changes of +/- 20% in precipitation alter methane emissions by about +/- 18%. Limitations in the model are analyzed. Simulated interannual variations in methane emissions from wetlands are compared to observed atmospheric growth rate anomalies. Our model simulation results suggest that contributions from other sources than wetlands and/or the sinks are more important in the tropics than north-of 30 deg. N. In higher northern latitudes, it seems that a large part, of the observed interannual variations can be explained by variations in wetland emissions. Our results also suggest that reduced wetland emissions played an important role in the observed negative methane growth rate anomaly in 1992.

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

PubMed Central

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

PubMed

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments

NASA Astrophysics Data System (ADS)

Diehl, T.; Heil, A.; Chin, M.; Pan, X.; Streets, D.; Schultz, M.; Kinne, S.

2012-09-01

Two historical emission inventories of black carbon (BC), primary organic carbon (OC), and SO2 emissions from land-based anthropogenic sources, ocean-going vessels, air traffic, biomass burning, and volcanoes are presented and discussed for the period 1980-2010. These gridded inventories are provided to the internationally coordinated AeroCom Phase II multi-model hindcast experiments. The horizontal resolution is 0.5°×0.5° and 1.0°×1.0°, while the temporal resolution varies from daily for volcanoes to monthly for biomass burning and aircraft emissions, and annual averages for land-based and ship emissions. One inventory is based on inter-annually varying activity rates of land-based anthropogenic emissions and shows strong variability within a decade, while the other one is derived from interpolation between decadal endpoints and thus exhibits linear trends within a decade. Both datasets capture the major trends of decreasing anthropogenic emissions over the USA and Western Europe since 1980, a sharp decrease around 1990 over Eastern Europe and the former USSR, and a steep increase after 2000 over East and South Asia. The inventory differences for the combined anthropogenic and biomass burning emissions in the year 2005 are 34% for BC, 46% for OC, and 13% for SO2. They vary strongly depending on species, year and region, from about 10% to 40% in most cases, but in some cases the inventories differ by 100% or more. Differences in emissions from wild-land fires are caused only by different choices of the emission factors for years after 1996 which vary by a factor of about 1 to 2 for OC depending on region, and by a combination of emission factors and the amount of dry mass burned for years up to 1996. Volcanic SO2 emissions, which are only provided in one inventory, include emissions from explosive, effusive, and quiescent degassing events for 1167 volcanoes.

Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

NASA Astrophysics Data System (ADS)

Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Shichkin, A. V.; Tyagunov, A. G.; Medvedev, A. N.

2017-06-01

Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: projections under current legislation

NASA Astrophysics Data System (ADS)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Gsella, A.; Amann, M.

2013-08-01

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement during recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality data base that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale - 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport, regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

Request for Correction of Information Concerning the U.S. Environmental Protection Agency's EPAct/V2/E-89 Fuel Effects Study and Motor Vehicle Emissions Simulator Model (MOVES2014) Docket ID Nos. EPA420-R-13-002, FRL-9917-26-OAR

EPA Pesticide Factsheets

Petition for the US EPA to correct information concerning motor vehicle fiel emissions represented in the Motor Vehicle Emissions Simulator model (MOVES2014) and the EPAct/V2/E-89 fuel effects study (EPAct study)1 on which it is based

Atmospheric mercury footprints of nations.

PubMed

Liang, Sai; Wang, Yafei; Cinnirella, Sergio; Pirrone, Nicola

2015-03-17

The Minamata Convention was established to protect humans and the natural environment from the adverse effects of mercury emissions. A cogent assessment of mercury emissions is required to help implement the Minamata Convention. Here, we use an environmentally extended multi-regional input-output model to calculate atmospheric mercury footprints of nations based on upstream production (meaning direct emissions from the production activities of a nation), downstream production (meaning both direct and indirect emissions caused by the production activities of a nation), and consumption (meaning both direct and indirect emissions caused by final consumption of goods and services in a nation). Results show that nations function differently within global supply chains. Developed nations usually have larger consumption-based emissions than up- and downstream production-based emissions. India, South Korea, and Taiwan have larger downstream production-based emissions than their upstream production- and consumption-based emissions. Developed nations (e.g., United States, Japan, and Germany) are in part responsible for mercury emissions of developing nations (e.g., China, India, and Indonesia). Our findings indicate that global mercury abatement should focus on multiple stages of global supply chains. We propose three initiatives for global mercury abatement, comprising the establishment of mercury control technologies of upstream producers, productivity improvement of downstream producers, and behavior optimization of final consumers.

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.

Near-Field Characterization of Methane Emission Variability from a Compressor Station Using a Model Aircraft.

PubMed

Nathan, Brian J; Golston, Levi M; O'Brien, Anthony S; Ross, Kevin; Harrison, William A; Tao, Lei; Lary, David J; Johnson, Derek R; Covington, April N; Clark, Nigel N; Zondlo, Mark A

2015-07-07

A model aircraft equipped with a custom laser-based, open-path methane sensor was deployed around a natural gas compressor station to quantify the methane leak rate and its variability at a compressor station in the Barnett Shale. The open-path, laser-based sensor provides fast (10 Hz) and precise (0.1 ppmv) measurements of methane in a compact package while the remote control aircraft provides nimble and safe operation around a local source. Emission rates were measured from 22 flights over a one-week period. Mean emission rates of 14 ± 8 g CH4 s(-1) (7.4 ± 4.2 g CH4 s(-1) median) from the station were observed or approximately 0.02% of the station throughput. Significant variability in emission rates (0.3-73 g CH4 s(-1) range) was observed on time scales of hours to days, and plumes showed high spatial variability in the horizontal and vertical dimensions. Given the high spatiotemporal variability of emissions, individual measurements taken over short durations and from ground-based platforms should be used with caution when examining compressor station emissions. More generally, our results demonstrate the unique advantages and challenges of platforms like small unmanned aerial vehicles for quantifying local emission sources to the atmosphere.

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.

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.

Two Model-Based Methods for Policy Analyses of Fine Particulate Matter Control in China: Source Apportionment and Source Sensitivity

NASA Astrophysics Data System (ADS)

Li, X.; Zhang, Y.; Zheng, B.; Zhang, Q.; He, K.

2013-12-01

Anthropogenic emissions have been controlled in recent years in China to mitigate fine particulate matter (PM2.5) pollution. Recent studies show that sulfate dioxide (SO2)-only control cannot reduce total PM2.5 levels efficiently. Other species such as nitrogen oxide, ammonia, black carbon, and organic carbon may be equally important during particular seasons. Furthermore, each species is emitted from several anthropogenic sectors (e.g., industry, power plant, transportation, residential and agriculture). On the other hand, contribution of one emission sector to PM2.5 represents contributions of all species in this sector. In this work, two model-based methods are used to identify the most influential emission sectors and areas to PM2.5. The first method is the source apportionment (SA) based on the Particulate Source Apportionment Technology (PSAT) available in the Comprehensive Air Quality Model with extensions (CAMx) driven by meteorological predictions of the Weather Research and Forecast (WRF) model. The second method is the source sensitivity (SS) based on an adjoint integration technique (AIT) available in the GEOS-Chem model. The SA method attributes simulated PM2.5 concentrations to each emission group, while the SS method calculates their sensitivity to each emission group, accounting for the non-linear relationship between PM2.5 and its precursors. Despite their differences, the complementary nature of the two methods enables a complete analysis of source-receptor relationships to support emission control policies. Our objectives are to quantify the contributions of each emission group/area to PM2.5 in the receptor areas and to intercompare results from the two methods to gain a comprehensive understanding of the role of emission sources in PM2.5 formation. The results will be compared in terms of the magnitudes and rankings of SS or SA of emitted species and emission groups/areas. GEOS-Chem with AIT is applied over East Asia at a horizontal grid resolution of 0.5° (Lat) × 0.67° (Lon). WRF/CAMx with PSAT is applied to nested grids: 36-km × 36-km over China and 12-km × 12-km over northern China. These simulations are performed for 2006 and 2011. Beijing and northern Hebei are selected as representative receptor areas. Simulated surface concentrations by both models are evaluated with available observations in China. Focusing on inorganic aerosols (sulfate, nitrate and ammonium), preliminary SS results from GEOS-Chem/AIT at Beijing identify the top three major emission sectors to be agriculture, residential, and transportation in winter and agriculture, industry and power plant in summer. The top four source areas are northern Hebei, local, Neimenggu, and Liaoning in winter and northern Hebei, local, Shandong, and southern Hebei in summer. The synthesis of SS and SA for influential emission groups or areas from this work will provide a quantitative basis for emission control strategy development and policy making for PM2.5 control in China.

ARCADE 2 Observations of Galactic Radio Emission

NASA Technical Reports Server (NTRS)

Kogut, A.; Fixsen, D. J.; Levin, S. M.; Limon, M.; Lubin, P. M.; Mirel, P.; Seiffert, M.; Singal, J.; Villela, T.; Wollack, E.;

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.

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.

Modeling multi-scale aerosol dynamics and micro-environmental air quality near a large highway intersection using the CTAG model.

PubMed

Wang, Yan Jason; Nguyen, Monica T; Steffens, Jonathan T; Tong, Zheming; Wang, Yungang; Hopke, Philip K; Zhang, K Max

2013-01-15

A new methodology, referred to as the multi-scale structure, integrates "tailpipe-to-road" (i.e., on-road domain) and "road-to-ambient" (i.e., near-road domain) simulations to elucidate the environmental impacts of particulate emissions from traffic sources. The multi-scale structure is implemented in the CTAG model to 1) generate process-based on-road emission rates of ultrafine particles (UFPs) by explicitly simulating the effects of exhaust properties, traffic conditions, and meteorological conditions and 2) to characterize the impacts of traffic-related emissions on micro-environmental air quality near a highway intersection in Rochester, NY. The performance of CTAG, evaluated against with the field measurements, shows adequate agreement in capturing the dispersion of carbon monoxide (CO) and the number concentrations of UFPs in the near road micro-environment. As a proof-of-concept case study, we also apply CTAG to separate the relative impacts of the shutdown of a large coal-fired power plant (CFPP) and the adoption of the ultra-low-sulfur diesel (ULSD) on UFP concentrations in the intersection micro-environment. Although CTAG is still computationally expensive compared to the widely-used parameterized dispersion models, it has the potential to advance our capability to predict the impacts of UFP emissions and spatial/temporal variations of air pollutants in complex environments. Furthermore, for the on-road simulations, CTAG can serve as a process-based emission model; Combining the on-road and near-road simulations, CTAG becomes a "plume-in-grid" model for mobile emissions. The processed emission profiles can potentially improve regional air quality and climate predictions accordingly. Copyright © 2012 Elsevier B.V. All rights reserved.

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

The Hestia Project: High Spatial Resolution Fossil Fuel Carbon Dioxide Emissions Quantification at Hourly Scale in Indianapolis, USA

NASA Astrophysics Data System (ADS)

Zhou, Y.; Gurney, K. R.

2009-12-01

In order to advance the scientific understanding of carbon exchange with the land surface and contribute to sound, quantitatively-based U.S. climate change policy interests, quantification of greenhouse gases emissions drivers at fine spatial and temporal scales is essential. Quantification of fossil fuel CO2 emissions, the primary greenhouse gases, has become a key component to cost-effective CO2 emissions mitigation options and a carbon trading system. Called the ‘Hestia Project’, this pilot study generated CO2 emissions down to high spatial resolution and hourly scale for the greater Indianapolis region in the USA through the use of air quality and traffic monitoring data, remote sensing, GIS, and building energy modeling. The CO2 emissions were constructed from three data source categories: area, point, and mobile. For the area source emissions, we developed an energy consumption model using DOE/EIA survey data on building characteristics and energy consumption. With the Vulcan Project’s county-level CO2 emissions and simulated building energy consumption, we quantified the CO2 emissions for each individual building by allocating Vulcan emissions to roughly 50,000 structures in Indianapolis. The temporal pattern of CO2 emissions in each individual building was developed based on temporal patterns of energy consumption. The point sources emissions were derived from the EPA National Emissions Inventory data and effluent monitoring of electricity producing facilities. The mobile source CO2 emissions were estimated at the month/county scale using the Mobile6 combustion model and the National Mobile Inventory Model database. The month/county scale mobile source CO2 emissions were downscaled to the “native” spatial resolution of road segments every hour using a GIS road atlas and traffic monitoring data. The result is shown in Figure 1. The resulting urban-scale inventory can serve as a baseline of current CO2 emissions and should be of immediate use to city environmental managers and regional industry as they plan emission mitigation options and project future emission trends. The results obtained here will also be a useful comparison to atmospheric CO2 monitoring efforts from the top-down. Figure 1. Location of the study area, the building level and mobile CO2 emissions, and an enlarged example neighborhood

40 CFR 1042.104 - Exhaust emission standards for Category 3 engines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... for other testing. (2) NOX standards apply based on the engine's model year and maximum in-use engine... Engines (g/kW-hr) Emission standards Model year Maximum in-use engine speed Less than130 RPM 130-2000RPM a... Tier 1 NOX standards apply as specified in 40 CFR part 94 for engines originally manufactured in model...

40 CFR 1042.104 - Exhaust emission standards for Category 3 engines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... for other testing. (2) NOX standards apply based on the engine's model year and maximum in-use engine... Engines (g/kW-hr) Emission standards Model year Maximum in-use engine speed Less than130 RPM 130-2000RPM a... Tier 1 NOX standards apply as specified in 40 CFR part 94 for engines originally manufactured in model...

40 CFR 1042.104 - Exhaust emission standards for Category 3 engines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... for other testing. (2) NOX standards apply based on the engine's model year and maximum in-use engine... Engines (g/kW-hr) Emission standards Model year Maximum in-use engine speed Less than130 RPM 130-2000RPM a... standards apply as specified in 40 CFR part 94 for engines originally manufactured in model years 2004...

40 CFR 1042.104 - Exhaust emission standards for Category 3 engines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... for other testing. (2) NOX standards apply based on the engine's model year and maximum in-use engine... Engines (g/kW-hr) Emission standards Model year Maximum in-use engine speed Less than130 RPM 130-2000RPM a... standards apply as specified in 40 CFR part 94 for engines originally manufactured in model years 2004...

40 CFR 1042.104 - Exhaust emission standards for Category 3 engines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... for other testing. (2) NOX standards apply based on the engine's model year and maximum in-use engine... Engines (g/kW-hr) Emission standards Model year Maximum in-use engine speed Less than130 RPM 130-2000RPM a... Tier 1 NOX standards apply as specified in 40 CFR part 94 for engines originally manufactured in model...

Emission of hydrogen sulfide (H2S) at a waterfall in a sewer: study of main factors affecting H2S emission and modeling approaches.

PubMed

Jung, Daniel; Hatrait, Laetitia; Gouello, Julien; Ponthieux, Arnaud; Parez, Vincent; Renner, Christophe

2017-11-01

Hydrogen sulfide (H 2 S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H 2 S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H 2 S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H 2 S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H 2 S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H 2 S·h -1 . Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

Canadian Whole-Farm Model Holos - Development, Stakeholder Involvement, and Model Application

NASA Astrophysics Data System (ADS)

Kroebel, R.; Janzen, H.; Beauchemin, K. A.

2017-12-01

Agriculture and Agri-Food Canada's Holos model, based mostly on emission factors, aims to explore the effect of management on Canadian whole-farm greenhouse gas emissions. The model includes 27 commonly grown annual and perennial crops, summer fallow, grassland, and 8 types of tree plantings, along with beef, dairy, sheep, swine and other livestock or poultry operations. Model outputs encompass net emissions of CO2, CH4, and N2O (in CO2 equivalents), calculated for various farm components. Where possible, algorithms are drawn from peer-reviewed publications. For consistency, Holos is aligned with the Canadian sustainability indicator and national greenhouse gas inventory objectives. Although primarily an exploratory tool for research, the model's design makes it accessible and instructive also to agricultural producers, educators, and policy makers. Model development, therefore, proceeds iteratively, with extensive stakeholder feedback from training sessions or annual workshops. To make the model accessible to diverse users, the team developed a multi-layered interface, with general farming scenarios for general use, but giving access to detailed coefficients and assumptions to researchers. The model relies on extensive climate, soil, and agronomic databases to populate regionally-applicable default values thereby minimizing keyboard entries. In an initial application, the model was used to assess greenhouse gas emissions from the Canadian beef production system; it showed that enteric methane accounted for 63% of total GHG emissions and that 84% of emissions originated from the cow-calf herd. The model further showed that GHG emission intensity per kg beef, nationally, declined by 14% from 1981 to 2011, owing to gains in production efficiency. Holos is now being used to consider further potential advances through improved rations or other management options. We are now aiming to expand into questions of grazing management, and are developing a novel carbon modelling approach based on the ICBM model. Also under development are sub-models to predict ammonia volatilization and water budgets. Development of Holos is expected to continue, forging an interactive link between ongoing research and the interests of stakeholders in an ever-changing agricultural environment.

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.

Potential for Woody Bioenergy Crops Grown on Marginal Lands in the US Midwest to Reduce Carbon Emissions

NASA Astrophysics Data System (ADS)

Sahajpal, R.; Hurtt, G. C.; Fisk, J. P.; Izaurralde, R. C.; Zhang, X.

2012-12-01

While cellulosic biofuels are widely considered to be a low carbon energy source for the future, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting US energy and food needs without exacerbating environmental harm. To assess the carbon emission reduction potential of cellulosic biofuels, we need to identify lands that are initially not storing large quantities of carbon in soil and vegetation but are capable of producing abundant biomass with limited management inputs, and accurately model forest production rates and associated input requirements. Here we present modeled results for carbon emission reduction potential and cellulosic ethanol production of woody bioenergy crops replacing existing native prairie vegetation grown on marginal lands in the US Midwest. Marginal lands are selected based on soil properties describing use limitation, and are extracted from the SSURGO (Soil Survey Geographic) database. Yield estimates for existing native prairie vegetation on marginal lands modeled using the process-based field-scale model EPIC (Environmental Policy Integrated Climate) amount to ~ 6.7±2.0 Mg ha-1. To model woody bioenergy crops, the individual-based terrestrial ecosystem model ED (Ecosystem Demography) is initialized with the soil organic carbon stocks estimated at the end of the EPIC simulation. Four woody bioenergy crops: willow, southern pine, eucalyptus and poplar are parameterized in ED. Sensitivity analysis of model parameters and drivers is conducted to explore the range of carbon emission reduction possible with variation in woody bioenergy crop types, spatial and temporal resolution. We hypothesize that growing cellulosic crops on these marginal lands can provide significant water quality, biodiversity and GHG emissions mitigation benefits, without accruing additional carbon costs from the displacement of food and feed production.

Seasonal variation of polycyclic aromatic hydrocarbons (PAHs) emissions in China.

PubMed

Zhang, Yanxu; Tao, Shu

2008-12-01

A regression model based on the provincial energy consumption data was developed to calculate the monthly proportions of residential energy consumption compared to the total year volume. This model was also validated by comparing with some survey and statistical data. With this model, a PAHs emission inventory with seasonal variation was developed. The seasonal variations of different sources in different regions of China and the spatial distribution of the major sources in different seasons were also achieved. The PAHs emissions were larger in the winter than in the summer, with a difference of about 1.3-folds between the months with the largest and the smallest emissions. Residential solid fuel combustion dominated the pattern of seasonal variation with the winter-time emissions as much as 1.6 times as that in the summer, while the emissions from wild fires and open fire straw burning was mainly concentrated during the spring and summer.

Modelling the time-variant dietary exposure of PCBs in China over the period 1930 to 2100.

PubMed

Zhao, Shizhen; Breivik, Knut; Jones, Kevin C; Sweetman, Andrew J

2018-06-06

This study aimed for the first time to reconstruct historical exposure profiles for PCBs to the Chinese population, by examining the combined effect of changing temporal emissions and dietary transition. A long-term (1930-2100) dynamic simulation of human exposure using realistic emission scenarios, including primary emissions, unintentional emissions and emissions from e-waste, combined with dietary transition trends was conducted by a multimedia fate model (BETR-Global) linked to a bioaccumulation model (ACC-HUMAN). The model predicted an approximate 30-year delay of peak body burden for PCB-153 in a 30-year-old Chinese female, compared to their European counterpart. This was mainly attributed to a combination of change in diet and divergent emission patterns in China. A fish-based diet was predicted to result in up to 8 times higher body burden than a vegetable-based diet (2010-2100). During the production period, a worst-case scenario assuming only consumption of imported food from a region with more extensive production and usage of PCBs would result in up to 4 times higher body burden compared to consumption of only locally produced food. However, such differences gradually diminished after cessation of production. Therefore, emission reductions in China alone may not be sufficient to protect human health for PCB-like chemicals, particularly during the period of mass production. The results from this study illustrate that human exposure is also likely to be dictated by inflows of PCBs via the environment, waste and food.

Modelling the emissions from ships in ports and their impact on air quality in the metropolitan area of Hamburg

NASA Astrophysics Data System (ADS)

Ramacher, Martin; Karl, Matthias; Aulinger, Armin; Bieser, Johannes; Matthias, Volker; Quante, Markus

2016-04-01

Exhaust emissions from shipping contribute significantly to the anthropogenic burden of air pollutants such as nitrogen oxides (NOX) and particulate matter (PM). Ships emit not only when sailing on open sea, but also when approaching harbors, during port manoeuvers and at berth to produce electricity and heat for the ship's operations. This affects the population of harbor cities because long-term exposure to PM and NOX has significant effects on human health. The European Union has therefore has set air quality standards for air pollutants. Many port cities have problems meeting these standards. The port of Hamburg with around 10.000 ship calls per year is Germany's largest seaport and Europe's second largest container port. Air quality standard reporting in Hamburg has revealed problems in meeting limits for NO2 and PM10. The amount and contribution of port related ship emissions (38% for NOx and 17% for PM10) to the overall emissions in the metropolitan area in 2005 [BSU Hamburg (2012): Luftreinhalteplan für Hamburg. 1. Fortschreibung 2012] has been modelled with a bottom up approach by using statistical data of ship activities in the harbor, technical vessel information and specific emission algorithms [GAUSS (2008): Quantifizierung von gasförmigen Emissionen durch Maschinenanlagen der Seeschiffart an der deutschen Küste]. However, knowledge about the spatial distribution of the harbor ship emissions over the city area is crucial when it comes to air quality standards and policy decisions to protect human health. Hence, this model study examines the spatial distribution of harbor ship emissions (NOX, PM10) and their deposition in the Hamburg metropolitan area. The transport and chemical transformation of atmospheric pollutants is calculated with the well-established chemistry transport model TAPM (The Air Pollution Model). TAPM is a three-dimensional coupled prognostic meteorological and air pollution model with a condensed chemistry scheme including photochemistry. The model was applied to the Hamburg metropolitan area with a setup of 30 x 30 grid cells of 1 km² each and 30 vertical grid levels from 10 to 8,000 m, for a time period of one year. Emission inventories for traffic, industry, households and ships in 2013 were generated. To investigate the dispersion of ship emissions to air pollution two different model runs for 2013 were performed; one model run including land-based emissions and the ship emissions and a model run just including the land-based emissions. The modelling results were evaluated with air quality data from the monitoring station network of Hamburg (luft.hamburg.de). The results are presented in form of spatial distribution maps for the Hamburg metropolitan area highlighting the pollutants (PM and NOX) originating from harbor residential ships.

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.

Biodiversity matters in feedbacks between climate change and air quality: a study using an individual-based model.

PubMed

Wang, Bin; Shuman, Jacquelyn; Shugart, Herman H; Lerdau, Manuel T

2018-03-30

Air quality is closely associated with climate change via the biosphere because plants release large quantities of volatile organic compounds (VOC) that mediate both gaseous pollutants and aerosol dynamics. Earlier studies, which considered only leaf physiology and simply scale up from leaf-level enhancements of emissions, suggest that climate warming enhances whole forest VOC emissions, and these increased VOC emissions aggravate ozone pollution and secondary organic aerosol formation. Using an individual-based forest VOC emissions model, UVAFME-VOC, that simulates system-level emissions by explicitly simulating forest community dynamics to the individual tree level, ecological competition among the individuals of differing size and age, and radiative transfer and leaf function through the canopy, we find that climate warming only sometimes stimulates isoprene emissions (the single largest source of non-methane hydrocarbon) in a southeastern U.S. forest. These complex patterns result from the combination of higher temperatures' stimulating emissions at the leaf level but decreasing the abundance of isoprene-emitting taxa at the community level by causing a decline in the abundance of isoprene-emitting species (Quercus spp.). This ecological effect eventually outweighs the physiological one, thus reducing overall emissions. Such reduced emissions have far-reaching implications for the climate-air-quality relationships that have been established on the paradigm of warming-enhancement VOC emissions from vegetation. This local scale modeling study suggests that community ecology rather than only individual physiology should be integrated into future studies of biosphere-climate-chemistry interactions. © 2018 by the Ecological Society of America.

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.

Modeling 13.3nm Fe XXIII Flare Emissions Using the GOES-R EXIS Instrument

NASA Astrophysics Data System (ADS)

Rook, H.; Thiemann, E.

2017-12-01

The solar EUV spectrum is dominated by atomic transitions in ionized atoms in the solar atmosphere. As solar flares evolve, plasma temperatures and densities change, influencing abundances of various ions, changing intensities of different EUV wavelengths observed from the sun. Quantifying solar flare spectral irradiance is important for constraining models of Earth's atmosphere, improving communications quality, and controlling satellite navigation. However, high time cadence measurements of flare irradiance across the entire EUV spectrum were not available prior to the launch of SDO. The EVE MEGS-A instrument aboard SDO collected 0.1nm EUV spectrum data from 2010 until 2014, when the instrument failed. No current or future instrument is capable of similar high resolution and time cadence EUV observation. This necessitates a full EUV spectrum model to study EUV phenomena at Earth. It has been recently demonstrated that one hot flare EUV line, such as the 13.3nm Fe XXIII line, can be used to model cooler flare EUV line emissions, filling the role of MEGS-A. Since unblended measurements of Fe XXIII are typically unavailable, a proxy for the Fe XXIII line must be found. In this study, we construct two models of this line, first using the GOES 0.1-0.8nm soft x-ray (SXR) channel as the Fe XXIII proxy, and second using a physics-based model dependent on GOES emission measure and temperature data. We determine that the more sophisticated physics-based model shows better agreement with Fe XXIII measurements, although the simple proxy model also performs well. We also conclude that the high correlation between Fe XXIII emissions and the GOES 0.1-0.8nm band is because both emissions tend to peak near the GOES emission measure peak despite large differences in their contribution functions.

Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions

NASA Astrophysics Data System (ADS)

Stohl, A.; Klimont, Z.; Eckhardt, S.; Kupiainen, K.; Shevchenko, V. P.; Kopeikin, V. M.; Novigatsky, A. N.

2013-09-01

Arctic haze is a seasonal phenomenon with high concentrations of accumulation-mode aerosols occurring in the Arctic in winter and early spring. Chemistry transport models and climate chemistry models struggle to reproduce this phenomenon, and this has recently prompted changes in aerosol removal schemes to remedy the modeling problems. In this paper, we show that shortcomings in current emission data sets are at least as important. We perform a 3 yr model simulation of black carbon (BC) with the Lagrangian particle dispersion model FLEXPART. The model is driven with a new emission data set ("ECLIPSE emissions") which includes emissions from gas flaring. While gas flaring is estimated to contribute less than 3% of global BC emissions in this data set, flaring dominates the estimated BC emissions in the Arctic (north of 66° N). Putting these emissions into our model, we find that flaring contributes 42% to the annual mean BC surface concentrations in the Arctic. In March, flaring even accounts for 52% of all Arctic BC near the surface. Most of the flaring BC remains close to the surface in the Arctic, so that the flaring contribution to BC in the middle and upper troposphere is small. Another important factor determining simulated BC concentrations is the seasonal variation of BC emissions from residential combustion (often also called domestic combustion, which is used synonymously in this paper). We have calculated daily residential combustion emissions using the heating degree day (HDD) concept based on ambient air temperature and compare results from model simulations using emissions with daily, monthly and annual time resolution. In January, the Arctic-mean surface concentrations of BC due to residential combustion emissions are 150% higher when using daily emissions than when using annually constant emissions. While there are concentration reductions in summer, they are smaller than the winter increases, leading to a systematic increase of annual mean Arctic BC surface concentrations due to residential combustion by 68% when using daily emissions. A large part (93%) of this systematic increase can be captured also when using monthly emissions; the increase is compensated by a decreased BC burden at lower latitudes. In a comparison with BC measurements at six Arctic stations, we find that using daily-varying residential combustion emissions and introducing gas flaring emissions leads to large improvements of the simulated Arctic BC, both in terms of mean concentration levels and simulated seasonality. Case studies based on BC and carbon monoxide (CO) measurements from the Zeppelin observatory appear to confirm flaring as an important BC source that can produce pollution plumes in the Arctic with a high BC / CO enhancement ratio, as expected for this source type. BC measurements taken during a research ship cruise in the White, Barents and Kara seas north of the region with strong flaring emissions reveal very high concentrations of the order of 200-400 ng m-3. The model underestimates these concentrations substantially, which indicates that the flaring emissions (and probably also other emissions in northern Siberia) are rather under- than overestimated in our emission data set. Our results suggest that it may not be "vertical transport that is too strong or scavenging rates that are too low" and "opposite biases in these processes" in the Arctic and elsewhere in current aerosol models, as suggested in a recent review article (Bond et al., Bounding the role of black carbon in the climate system: a scientific assessment, J. Geophys. Res., 2013), but missing emission sources and lacking time resolution of the emission data that are causing opposite model biases in simulated BC concentrations in the Arctic and in the mid-latitudes.

Comparison of process-based models to quantify nutrient flows and greenhouse gas emissions of milk production

USDA-ARS?s Scientific Manuscript database

Assessing and improving the sustainability of dairy production systems is essential to secure future food production. This requires a holistic approach that reveals trade-offs between emissions of the different greenhouse gases (GHG) and nutrient-based pollutants and ensures that interactions betwee...

Historical gaseous and primary aerosol emissions in the United States from 1990-2010

EPA Science Inventory

An accurate description of emissions is crucial for model simulations to reproduce and interpret observed phenomena over extended time periods. In this study, we used an approach based on activity data to develop a consistent series of spatially resolved emissions in the United S...

Modeling Modern Methane Emissions from Natural Wetlands. 1; Model Description and Results

NASA Technical Reports Server (NTRS)

Walter, Bernadette P.; Heimann, Martin; Matthews, Elaine

2001-01-01

Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane­ hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.

Assessing the Impact of Oil and Natural Gas Activities on Regional Air Quality in the Colorado Northern Front Range using WRF-Chem

NASA Astrophysics Data System (ADS)

Abdioskouei, M.; Carmichael, G. R.

2017-12-01

Recent increases in the Natural Gas (NG) production through hydraulic fracturing have questioned the climate benefit of switching from coal-fired to natural gas-fired power plants. Higher than expected levels of methane, VOCs, and NOx have been observed in areas close to oil and NG (OnG) operation facilities. High uncertainty in the OnG emission inventories and methane budget challenge the assessment of OnG impact on air quality and climate and consequently development of effective mitigation policies and control regulations. In this work, we focus on reducing the uncertainties around the OnG emissions by using high resolution (4x4 km2) WRF-Chem simulations coupled with detailed observation from the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ 2014) field campaign. First, we identified the optimal WRF-Chem configurations in the NFR area. We compared the performance of local and non-local Planetary Boundary Layer (PBL) schemes in predicting the PBL height and vertical mixing in the domain. We evaluated the impact of different meteorological and chemical initial and boundary conditions on the model performance. Next, simulations based on optimal configurations were used to assess the performance of the emission inventory (NEI-2011v2). To evaluate the impact of OnG emission on regional air quality and performance of NEI-2011 we tested the sensitivity of the model to the OnG emission. Comparison between simulated values and ground-based and airborne measurements shows a low bias of OnG emission in NEI-2011. Finally, inverse modeling techniques based on emission sensitivity simulations are being used to optimal scaling the OnG emission from the NEI-2011.

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

PubMed

Zhao, Xin; Han, Meng; Ding, Lili; Calin, Adrian Cantemir

2018-01-01

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.

CO bandhead emission of massive young stellar objects: determining disc properties

NASA Astrophysics Data System (ADS)

Ilee, J. D.; Wheelwright, H. E.; Oudmaijer, R. D.; de Wit, W. J.; Maud, L. T.; Hoare, M. G.; Lumsden, S. L.; Moore, T. J. T.; Urquhart, J. S.; Mottram, J. C.

2013-03-01

Massive stars play an important role in many areas of astrophysics, but numerous details regarding their formation remain unclear. In this paper we present and analyse high-resolution (R ˜ 30 000) near-infrared 2.3 μm spectra of 20 massive young stellar objects (MYSOs) from the Red MSX Source (RMS) data base, in the largest such study of CO first overtone bandhead emission to date. We fit the emission under the assumption it originates from a circumstellar disc in Keplerian rotation. We explore three approaches to modelling the physical conditions within the disc - a disc heated mainly via irradiation from the central star, a disc heated mainly via viscosity, and a disc in which the temperature and density are described analytically. We find that the models described by heating mechanisms are inappropriate because they do not provide good fits to the CO emission spectra. We therefore restrict our analysis to the analytic model, and obtain good fits to all objects that possess sufficiently strong CO emission, suggesting circumstellar discs are the source of this emission. On average, the temperature and density structure of the discs correspond to geometrically thin discs, spread across a wide range of inclinations. Essentially all the discs are located within the dust sublimation radius, providing strong evidence that the CO emission originates close to the central protostar, on astronomical unit scales. In addition, we show that the objects in our sample appear no different to the general population of MYSOs in the RMS data base, based on their near- and mid-infrared colours. The combination of observations of a large sample of MYSOs with CO bandhead emission and our detailed modelling provide compelling evidence of the presence of small-scale gaseous discs around such objects, supporting the scenario in which massive stars form via disc accretion.

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.

Dust Emission Modeling Incorporating Land Cover Parameterizations in the Chihuahuan Desert and Dissemination of Data Suites

NASA Astrophysics Data System (ADS)

Olgin, J. G.; Pennington, D. D.; Webb, N.

2017-12-01

A variety of models have been developed to better understand dust emissions - from initial erosive event to entrainment to transport through the atmosphere. Many of these models have been used to analyze dust emissions by representing atmospheric and surface variables, such as wind and soil moisture respectively, in a numerical model to determine the resulting dust emissions. Pertinent to modeling these variables, there are three important factors influencing emissions: 1) Friction velocity threshold based on wind interactions with dust, 2) horizontal flux (saltation) of dust and 3) vertical dust flux. While all of the existing models incorporate these processes, additional improvements are needed to yield results reflective of recorded data of dust events. Our investigation focuses on explicitly identifying specific land cover (LC) elements unique to the Chihuahan desert that contribute to aerodynamic roughness length (Zo); a main component to dust emission and key to provide results more representative of known dust events in semi-arid regions. These elements will be formulated into computer model inputs by conducting analysis (e.g. geostatistics) on field and satellite data to ascertain core LC characteristics responsible for affecting wind velocities (e.g. wind shadowing effects), which are conducive to dust emissions. This inputs will be used in a modified program using the Weather and Research Forecast model (WRF) to replicate previously recorded dust events. Results from this study will be presented here.

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.

Evaluation of lead concentration by one-box type multimedia model in Lake Biwa-Yodo River basin of Japan.

PubMed

Kondo, Akira; Yamamoto, Megumi; Inoue, Yoshio; Ariyadasa, B H A K T

2013-07-01

A one box type multimedia model was developed and applied for Lake Biwa-Yodo River basin in Japan to assess the distribution of lead in the environment. This model is based on mass balance and includes four environmental media; the atmosphere, the soil, the water body, and the sediment. The mass balance of lead is represented by the summation of mass transfer flux at equilibrium, emission flux, advection flux, and deposition flux or sedimentation flux. In the case of metallic compounds, dissolution rate and exchange equilibrium have also been taken into consideration. Pollutant Release and Transfer Registry (PRTR) in Japan was used as one of the major data source for this study. The emission of lead in Lake Biwa-Yodo River basin is calculated based on five sources of registered emission in PRTR, unregistered emission in PRTR, incinerators, leaded gasoline, and landfills. In this study, we estimated lead emission from 1957 to 2007 to observe the temporal accumulation of lead. Calculated lead concentrations were compared with the measured/observed concentrations. It was found out that the model could closely predict lead concentration in the soil and the water body. The concentration in the atmosphere was underestimated by the calculated concentrations. The reason was attributed to the underestimation of the amount of lead emission from incinerators. Copyright © 2013 Elsevier Ltd. All rights reserved.

Areas of Anomalous Surface Temperature in Alamosa and Saguache Counties, Colorado, as Identified from ASTER Thermal Data

DOE Data Explorer

Khalid Hussein

2012-02-01

This layer contains areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled very warm surface exposures (thermal anomalies) Note: 'o' is used in this description to represent lowercase sigma.

Non-Linear Relationship between Economic Growth and CO2 Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models

PubMed Central

Wang, Zheng-Xin; Hao, Peng; Yao, Pei-Yi

2017-01-01

The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO2 emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO2 emissions is significantly higher than those of GDPpc and Es on per capita CO2 emissions. PMID:29236083

Non-Linear Relationship between Economic Growth and CO₂ Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models.

PubMed

Wang, Zheng-Xin; Hao, Peng; Yao, Pei-Yi

2017-12-13

The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO₂ emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO₂ emissions is significantly higher than those of GDPpc and Es on per capita CO₂ emissions.

Factors affecting regional per-capita carbon emissions in China based on an LMDI factor decomposition model.

PubMed

Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang

2013-01-01

China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.

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.

On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations

NASA Astrophysics Data System (ADS)

Stein, O.; Schultz, M. G.; Bouarar, I.; Clark, H.; Huijnen, V.; Gaudel, A.; George, M.; Clerbaux, C.

2014-09-01

Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.

Nitrogen gas emissions and nitrate leaching dynamics under different tillage practices based on data synthesis and process-based modeling

NASA Astrophysics Data System (ADS)

Huang, Y.; Ren, W.; Tao, B.; Zhu, X.

2017-12-01

Nitrogen losses from the agroecosystems have been of great concern to global changes due to the effects on global warming and water pollution in the form of nitrogen gas emissions (e.g., N2O) and mineral nitrogen leaching (e.g., NO3-), respectively. Conservation tillage, particularly no-tillage (NT), may enhance soil carbon sequestration, soil aggregation and moisture; therefore it has the potential of promoting N2O emissions and reducing NO3- leaching, comparing with conventional tillage (CT). However, associated processes are significantly affected by various factors, such as soil properties, climate, and crop types. How tillage management practices affect nitrogen transformations and fluxes is still far from clear, with inconsistent even opposite results from previous studies. To fill this knowledge gap, we quantitatively investigated gaseous and leaching nitrogen losses from NT and CT agroecosystems based on data synthesis and an improved process-based agroecosystem model. Our preliminary results suggest that NT management is more efficient in reducing NO3- leaching, and meanwhile it simultaneously increases N2O emissions by approximately 10% compared with CT. The effects of NT on N2O emissions and NO3- leaching are highly influenced by the placement of nitrogen fertilizer and are more pronounced in humid climate conditions. The effect of crop types is a less dominant factor in determining N2O and NO3- losses. Both our data synthesis and process-based modeling suggest that the enhanced carbon sequestration capacity from NT could be largely compromised by relevant NT-induced increases in N2O emissions. This study provides the comprehensive quantitative assessment of NT on the nitrogen emissions and leaching in agroecosystems. It provides scientific information for identifying proper management practices for ensuring food security and minimizing the adverse environmental impacts. The results also underscore the importance of suitable nitrogen management in the NT agroecosystems for climate adaptation and mitigation.

Effects of crop management, soil type, and climate on N2O emissions from Austrian Soils

NASA Astrophysics Data System (ADS)

Zechmeister-Boltenstern, Sophie; Sigmund, Elisabeth; Kasper, Martina; Kitzler, Barbara; Haas, Edwin; Wandl, Michael; Strauss, Peter; Poetzelsberger, Elisabeth; Dersch, Georg; Winiwarter, Wilfried; Amon, Barbara

2015-04-01

Within the project FarmClim ("Farming for a better climate") we assessed recent N2O emissions from two selected regions in Austria. Our aim was to deepen the understanding of Austrian N2O fluxes regarding region specific properties. Currently, N2O emissions are estimated with the IPCC default emission factor which only considers the amount of N-input as an influencing factor for N2O emissions. We evaluated the IPCC default emission factor for its validity under spatially distinct environmental conditions. For this two regions for modeling with LandscapeDNDC have been identified in this project. The benefit of using LandscapeDNDC is the detailed illustration of microbial processes in the soil. Required input data to run the model included daily climate data, vegetation properties, soil characteristics and land management. The analysis of present agricultural practices was basis for assessing the hot spots and hot moments of nitrogen emissions on a regional scale. During our work with LandscapeDNDC we were able to adapt specific model algorithms to Austrian agricultural conditions. The model revealed a strong dependency of N2O emissions on soil type. We could estimate how strongly soil texture affects N2O emissions. Based on detailed soil maps with high spatial resolution we calculated region specific contribution to N2O emissions. Accordingly we differentiated regions with deviating gas fluxes compared to the predictions by the IPCC inventory methodology. Taking region specific management practices into account (tillage, irrigation, residuals) calculation of crop rotation (fallow, catch crop, winter wheat, barley, winter barley, sugar beet, corn, potato, onion and rapeseed) resulted in N2O emissions differing by a factor of 30 depending on preceding crop and climate. A maximum of 2% of N fertilizer input was emitted as N2O. Residual N in the soil was a major factor stimulating N2O emissions. Interannual variability was affected by varying N-deposition even in case of constant management practices. High temporal resolution of model outputs enabled us to identify hot moments of N-turnover and total N2O emissions according to extreme weather events. We analysed how strongly these event based emissions, which are not accounted for by classical inventories, affect emission factors. The evaluation of the IPCC default emission factor for its validity under spatially distinct environmental conditions revealed which environmental conditions are responsible for major deviations of actual emissions from the theoretical values. Scrutinizing these conditions can help to improve climate reporting and greenhouse gas mitigation measures.

Constraining Modern and Historic Mercury Emissions From Gold Mining

NASA Astrophysics Data System (ADS)

Strode, S. A.; Jaeglé, L.; Selin, N. E.; Sunderland, E.

2007-12-01

Mercury emissions from both historic gold and silver mining and modern small-scale gold mining are highly uncertain. Historic mercury emissions can affect the modern atmosphere through reemission from land and ocean, and quantifying mercury emissions from historic gold and silver mining can help constrain modern mining sources. While estimates of mercury emissions during historic gold rushes exceed modern anthropogenic mercury emissions in North America, sediment records in many regions do not show a strong gold rush signal. We use the GEOS-Chem chemical transport model to determine the spatial footprint of mercury emissions from mining and compare model runs from gold rush periods to sediment and ice core records of historic mercury deposition. Based on records of gold and silver production, we include mercury emissions from North and South American mining of 1900 Mg/year in 1880, compared to modern global anthropogenic emissions of 3400 Mg/year. Including this large mining source in GEOS-Chem leads to an overestimate of the modeled 1880 to preindustrial enhancement ratio compared to the sediment core record. We conduct sensitivity studies to constrain the level of mercury emissions from modern and historic mining that is consistent with the deposition records for different regions.

Modeling and simulation of a beam emission spectroscopy diagnostic for the ITER prototype neutral beam injector.

PubMed

Barbisan, M; Zaniol, B; Pasqualotto, R

2014-11-01

A test facility for the development of the neutral beam injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H(-)/D(-) ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance of the two prototypes. In particular, beam emission spectroscopy will measure the uniformity and the divergence of the fast particles beam exiting the ion source and travelling through the beam line components. This type of measurement is based on the collection of the Hα/Dα emission resulting from the interaction of the energetic particles with the background gas. A numerical model has been developed to simulate the spectrum of the collected emissions in order to design this diagnostic and to study its performance. The paper describes the model at the base of the simulations and presents the modeled Hα spectra in the case of MITICA experiment.

Biogenic Emission Inventories: Scaling Local Biogenic Measurements to Regions

NASA Astrophysics Data System (ADS)

Lamb, B.; Pressley, S.; Westberg, H.; Guenther, A.

2002-12-01

Biogenic Hydrocarbons, such as isoprene, are important trace gas species that are naturally emitted by vegetation and that affect the oxidative capacity of the atmosphere. Biogenic emissions are regulated by many environmental variables; the most important variables are thought to be temperature and light. Long-term isoprene flux measurements are useful for verifying existing canopy models and exploring other correlations between isoprene fluxes and environmental parameters. Biogenic Emission Models, such as BEIS (Biogenic Emission Inventory System) rely on above canopy environmental parameters and below canopy scaling factors to estimate canopy scale biogenic hydrocarbon fluxes. Other models, which are more complex, are coupled micrometeorological and physiological modules that provide feedback mechanisms present in a canopy environment. These types of models can predict biogenic emissions well, however, the required input is extensive, and for regional applications, they can be cumbersome. This paper presents analyses based on long-term isoprene flux measurements that have been collected since 1999 at the AmeriFlux site located at the University of Michigan Biological Station (UMBS) as part of the Program for Research on Oxidants: PHotochemistry, Emissions, and Transport (PROPHET). The goals of this research were to explore a potential relationship between the surface energy budget (primarily sensible heat flux) and isoprene emissions. Our hypothesis is that the surface energy flux is a better model parameter for isoprene emissions at the canopy scale than temperature and light levels, and the link to the surface energy budget will provide a significant improvement in isoprene emission models. Preliminary results indicate a significant correlation between daily isoprene emissions and sensible heat fluxes for a predominantly aspen/oak stand located in northern Michigan. Since surface energy budgets are an integral part of mesoscale meteorological models, this could potentially be a useful tool for including biogenic emissions into regional atmospheric models. Comparison of measured isoprene fluxes with current BEIS estimates will also be shown as an example of where emission inventories currently stand.

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.

Engineering light emission of two-dimensional materials in both the weak and strong coupling regimes

NASA Astrophysics Data System (ADS)

Brotons-Gisbert, Mauro; Martínez-Pastor, Juan P.; Ballesteros, Guillem C.; Gerardot, Brian D.; Sánchez-Royo, Juan F.

2018-01-01

Two-dimensional (2D) materials have promising applications in optoelectronics, photonics, and quantum technologies. However, their intrinsically low light absorption limits their performance, and potential devices must be accurately engineered for optimal operation. Here, we apply a transfer matrix-based source-term method to optimize light absorption and emission in 2D materials and related devices in weak and strong coupling regimes. The implemented analytical model accurately accounts for experimental results reported for representative 2D materials such as graphene and MoS2. The model has been extended to propose structures to optimize light emission by exciton recombination in MoS2 single layers, light extraction from arbitrarily oriented dipole monolayers, and single-photon emission in 2D materials. Also, it has been successfully applied to retrieve exciton-cavity interaction parameters from MoS2 microcavity experiments. The present model appears as a powerful and versatile tool for the design of new optoelectronic devices based on 2D semiconductors such as quantum light sources and polariton lasers.

Application of Gauss's law space-charge limited emission model in iterative particle tracking method

NASA Astrophysics Data System (ADS)

Altsybeyev, V. V.; Ponomarev, V. A.

2016-11-01

The particle tracking method with a so-called gun iteration for modeling the space charge is discussed in the following paper. We suggest to apply the emission model based on the Gauss's law for the calculation of the space charge limited current density distribution using considered method. Based on the presented emission model we have developed a numerical algorithm for this calculations. This approach allows us to perform accurate and low time consumpting numerical simulations for different vacuum sources with the curved emitting surfaces and also in the presence of additional physical effects such as bipolar flows and backscattered electrons. The results of the simulations of the cylindrical diode and diode with elliptical emitter with the use of axysimmetric coordinates are presented. The high efficiency and accuracy of the suggested approach are confirmed by the obtained results and comparisons with the analytical solutions.

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...

Quantifying the Global Nitrous Oxide Emissions Using a Trait-based Biogeochemistry Model

NASA Astrophysics Data System (ADS)

Zhuang, Q.; Yu, T.

2017-12-01

Nitrogen is an essential element for the global biogeochemical cycle. It is a key nutrient for organisms and N compounds including nitrous oxide significantly influence the global climate. The activities of bacteria and archaea are responsible for the nitrification and denitrification in a wide variety of environments, so microbes play an important role in the nitrogen cycle in soils. To date, most existing process-based models treated nitrification and denitrification as chemical reactions driven by soil physical variables including soil temperature and moisture. In general, the effect of microbes on N cycling has not been modeled in sufficient details. Soil organic carbon also affects the N cycle because it supplies energy to microbes. In my study, a trait-based biogeochemistry model quantifying N2O emissions from the terrestrial ecosystems is developed based on an extant process-based model TEM (Terrestrial Ecosystem Model). Specifically, the improvement to TEM includes: 1) Incorporating the N fixation process to account for the inflow of N from the atmosphere to biosphere; 2) Implementing the effects of microbial dynamics on nitrification process; 3) fully considering the effects of carbon cycling on N nitrogen cycling following the principles of stoichiometry of carbon and nitrogen in soils, plants, and microbes. The difference between simulations with and without the consideration of bacterial activity lies between 5% 25% based on climate conditions and vegetation types. The trait based module allows a more detailed estimation of global N2O emissions.

Modeling greenhouse gas emissions from dairy farms.

PubMed

Rotz, C Alan

2017-11-15

Dairy farms have been identified as an important source of greenhouse gas emissions. Within the farm, important emissions include enteric CH 4 from the animals, CH 4 and N 2 O from manure in housing facilities during long-term storage and during field application, and N 2 O from nitrification and denitrification processes in the soil used to produce feed crops and pasture. Models using a wide range in level of detail have been developed to represent or predict these emissions. They include constant emission factors, variable process-related emission factors, empirical or statistical models, mechanistic process simulations, and life cycle assessment. To fully represent farm emissions, models representing the various emission sources must be integrated to capture the combined effects and interactions of all important components. Farm models have been developed using relationships across the full scale of detail, from constant emission factors to detailed mechanistic simulations. Simpler models, based upon emission factors and empirical relationships, tend to provide better tools for decision support, whereas more complex farm simulations provide better tools for research and education. To look beyond the farm boundaries, life cycle assessment provides an environmental accounting tool for quantifying and evaluating emissions over the full cycle, from producing the resources used on the farm through processing, distribution, consumption, and waste handling of the milk and dairy products produced. Models are useful for improving our understanding of farm processes and their interacting effects on greenhouse gas emissions. Through better understanding, they assist in the development and evaluation of mitigation strategies for reducing emissions and improving overall sustainability of dairy farms. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Investigation of CO, C2H6 and aerosols over Eastern Canada during BORTAS 2011 using ground-based and satellite-based observations and model simulations

NASA Astrophysics Data System (ADS)

Griffin, Debora; Franklin, Jonathan; Parrington, Mark; Whaley, Cynthia; Hopper, Jason; Lesins, Glen; Tereszchuk, Keith; Walker, Kaley A.; Drummond, James R.; Palmer, Paul; Strong, Kimberly; Duck, Thomas J.; Abboud, Ihab; Dan, Lin; O'Neill, Norm; Clerbaux, Cathy; Coheur, Pierre; Bernath, Peter F.; Hyer, Edward; Kliever, Jenny

2013-04-01

We present the results of total column measurements of CO and C2H6 and aerosol optical depth (AOD) during the Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS-B) campaign over Eastern Canada. Ground-based observations, using Fourier transform spectrometers (FTSs) and sun photometers, were carried out in July and August 2011. They were taken in Halifax, Nova Scotia, which is an ideal location to monitor the outflow of boreal fires from North America, and in Toronto, Ontario. Measurements of enhanced fine mode AOD were highly correlated with enhancements in coincident trace gas (CO and C2H6) observations between 19 and 21 July 2011, which is typical for a smoke plume event. In this study, we will focus on the identification of the origin and the transport of this smoke plume. We use back-trajectories calculated by the Canadian Meteorological Centre (CMC) as well as FLEXPART forward-trajectories to demonstrate that the enhanced CO, C2H6 and fine mode AOD seen near Halifax and Toronto did originate from forest fires in Northwestern Ontario, that occurred between 17 and 19 July 2011. In addition, total column measurements of CO from the satellite-borne Infrared Atmospheric Sounding Interferometer (IASI) have been used to trace the smoke plume and to confirm the origin of the CO enhancement. Furthermore, the emission ratio (ERC2H6-CO) and the emission factor (EFC2H6) of C2H6 (with respect to the CO emission) were estimated from these ground-based observations. The C2H6 emission results from boreal fires in Northwestern Ontario agree well with C2H6 emission measurements from other boreal regions, and are relatively high compared to other geographical regions. The ground-based CO and C2H6 observations were compared with output from the 3-D global chemical transport model GEOS-Chem, using the inventory of the Fire Locating And Monitoring of Burning Emissions (FLAMBE). Good agreement was found for the magnitude of the enhancement of the total columns of CO between the measured and modelled results; however, a small shift in time of approximately 6 h of the arrival of the plume over Halifax is apparent between the results. The modeled C2H6 columns are systematically lower than the observations from the ground-based FTSs. It is possible that this difference between the model output and observations is due to the extra-tropical (rather than specific boreal) fire emission ratio used in the GEOS-Chem simulation, which seems to underestimate the C2H6 emission, derived from the presented ground-based observations. This suggests that a finer categorization of extra-tropical biomass burning is necessary and should be considered in future model simulations.

Monthly and spatially resolved black carbon emission inventory of India: uncertainty analysis

NASA Astrophysics Data System (ADS)

Paliwal, Umed; Sharma, Mukesh; Burkhart, John F.

2016-10-01

Black carbon (BC) emissions from India for the year 2011 are estimated to be 901.11 ± 151.56 Gg yr-1 based on a new ground-up, GIS-based inventory. The grid-based, spatially resolved emission inventory includes, in addition to conventional sources, emissions from kerosene lamps, forest fires, diesel-powered irrigation pumps and electricity generators at mobile towers. The emissions have been estimated at district level and were spatially distributed onto grids at a resolution of 40 × 40 km2. The uncertainty in emissions has been estimated using a Monte Carlo simulation by considering the variability in activity data and emission factors. Monthly variation of BC emissions has also been estimated to account for the seasonal variability. To the total BC emissions, domestic fuels contributed most significantly (47 %), followed by industry (22 %), transport (17 %), open burning (12 %) and others (2 %). The spatial and seasonal resolution of the inventory will be useful for modeling BC transport in the atmosphere for air quality, global warming and other process-level studies that require greater temporal resolution than traditional inventories.

Understanding high wintertime ozone pollution events in an oil- and natural gas-producing region of the western US

NASA Astrophysics Data System (ADS)

Ahmadov, R.; McKeen, S.; Trainer, M.; Banta, R.; Brewer, A.; Brown, S.; Edwards, P. M.; de Gouw, J. A.; Frost, G. J.; Gilman, J.; Helmig, D.; Johnson, B.; Karion, A.; Koss, A.; Langford, A.; Lerner, B.; Olson, J.; Oltmans, S.; Peischl, J.; Pétron, G.; Pichugina, Y.; Roberts, J. M.; Ryerson, T.; Schnell, R.; Senff, C.; Sweeney, C.; Thompson, C.; Veres, P. R.; Warneke, C.; Wild, R.; Williams, E. J.; Yuan, B.; Zamora, R.

2015-01-01

Recent increases in oil and natural gas (NG) production throughout the western US have come with scientific and public interest in emission rates, air quality and climate impacts related to this industry. This study uses a regional-scale air quality model (WRF-Chem) to simulate high ozone (O3) episodes during the winter of 2013 over the Uinta Basin (UB) in northeastern Utah, which is densely populated by thousands of oil and NG wells. The high-resolution meteorological simulations are able qualitatively to reproduce the wintertime cold pool conditions that occurred in 2013, allowing the model to reproduce the observed multi-day buildup of atmospheric pollutants and the accompanying rapid photochemical ozone formation in the UB. Two different emission scenarios for the oil and NG sector were employed in this study. The first emission scenario (bottom-up) was based on the US Environmental Protection Agency (EPA) National Emission Inventory (NEI) (2011, version 1) for the oil and NG sector for the UB. The second emission scenario (top-down) was based on estimates of methane (CH4) emissions derived from in situ aircraft measurements and a regression analysis for multiple species relative to CH4 concentration measurements in the UB. Evaluation of the model results shows greater underestimates of CH4 and other volatile organic compounds (VOCs) in the simulation with the NEI-2011 inventory than in the case when the top-down emission scenario was used. Unlike VOCs, the NEI-2011 inventory significantly overestimates the emissions of nitrogen oxides (NOx), while the top-down emission scenario results in a moderate negative bias. The model simulation using the top-down emission case captures the buildup and afternoon peaks observed during high O3 episodes. In contrast, the simulation using the bottom-up inventory is not able to reproduce any of the observed high O3 concentrations in the UB. Simple emission reduction scenarios show that O3 production is VOC sensitive and NOx insensitive within the UB. The model results show a disproportionate contribution of aromatic VOCs to O3 formation relative to all other VOC emissions. The model analysis reveals that the major factors driving high wintertime O3 in the UB are shallow boundary layers with light winds, high emissions of VOCs from oil and NG operations compared to NOx emissions, enhancement of photolysis fluxes and reduction of O3 loss from deposition due to snow cover.

Characterization of in-use light-duty gasoline vehicle emissions by remote sensing in Beijing: impact of recent control measures.

PubMed

Zhou, Yu; Fu, Lixin; Cheng, Linglin

2007-09-01

China's national government and Beijing city authorities have adopted additional control measures to reduce the negative impact of vehicle emissions on Beijing's air quality. An evaluation of the effectiveness of these measures may provide guidance for future vehicle emission control strategy development. In-use emissions from light-duty gasoline vehicles (LDGVs) were investigated at five sites in Beijing with remote sensing instrumentation. Distance-based mass emission factors were derived with fuel consumption modeled on real world data. The results show that the recently implemented aggressive control strategies are significantly reducing the emissions of on-road vehicles. Older vehicles are contributing substantially to the total fleet emissions. An earlier program to retrofit pre-Euro cars with three-way catalysts produced little emission reduction. The impact of model year and driving conditions on the average mass emission factors indicates that the durability of vehicles emission controls may be inadequate in Beijing.

Effect of water and heat transport processes on methane emissions from paddy soils: a process-based model analysis

NASA Astrophysics Data System (ADS)

Rizzo, Anacleto; Boano, Fulvio; Revelli, Roberto; Ridolfi, Luca

2013-04-01

High CH4 fluxes are emitted from paddy fields worldwide and represent a considerable issue for the rice production eco-sustainability. Water and heat transport fluxes are known to strongly influence biogeochemical cycles in wetland environments, and therefore also CH4 emissions from paddy soils. Water percolation affects the dynamics of many compounds (e.g. DOC, O2) influencing CH4 fate. On the other hand, heat fluxes strongly influence CH4 production in submerged rice crops, and lowering ponding water temperature (LPWT) can reduce microbial activities and consequently decrease CH4 emissions. Moreover, as long as the optimal temperature range for rice growth is maintained, LPWT can lower CH4 emissions without rice yield limitation. Hence, a process-based model is proposed and applied to investigate the role of water flow on CH4 emissions, and to analyse the efficiency of LPWT as mitigation strategy for CH4 production and release. The process-based model relies on a system of partial differential mass balance equations to describe the vertical dynamics of the chemical compounds leading to CH4 production. Many physico-chemical processes and features characteristic of paddy soil are included: paddy soil stratigraphy; spatio-temporal variations of plant-root compartment; water and heat transport; SOC decomposition; heterotrophic reactions in both aerobic and anaerobic conditions; root radial oxygen loss; root solute uptake; DOC root exudation; plant-mediated, ebullition, and diffusion gas exchange pathways. LPWT is included as a temperature shift subtracted directly to the ponding water temperature. Model results confirm the importance of water flow on CH4 emission, since simulations that do not include water fluxes show a considerable overestimation of CH4 emissions due to a different DOC spatio-temporal dynamics. Particularly, when water fluxes are not modeled the overestimation can reach 67 % of the total CH4 emission over the whole growing season. Moreover, model results also suggest that roots influence CH4 dynamics principally due to their solute uptake, while root effect on advective flow plays a minor role. In addition, the analysis of CH4 transport fluxes show the limiting effect of upward dispersive transport fluxes on the downward CH4 percolation. Finally, LPWT is confirmed to be a valid mitigation strategy for CH4 emissions from paddy soils, since the reduction of CH4 emission reach about -50 % with a LPWT equal to only 2°C over the whole growing season.

Full uncertainty quantification of N2O and NO emissions using the biogeochemical model LandscapeDNDC on site and regional scale

NASA Astrophysics Data System (ADS)

Haas, Edwin; Santabarbara, Ignacio; Kiese, Ralf; Butterbach-Bahl, Klaus

2017-04-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional / national scale and are outlined as the most advanced methodology (Tier 3) in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems and are thus thought to be widely applicable at various conditions and spatial scales. Process based modelling requires high spatial resolution input data on soil properties, climate drivers and management information. The acceptance of model based inventory calculations depends on the assessment of the inventory's uncertainty (model, input data and parameter induced uncertainties). In this study we fully quantify the uncertainty in modelling soil N2O and NO emissions from arable, grassland and forest soils using the biogeochemical model LandscapeDNDC. We address model induced uncertainty (MU) by contrasting two different soil biogeochemistry modules within LandscapeDNDC. The parameter induced uncertainty (PU) was assessed by using joint parameter distributions for key parameters describing microbial C and N turnover processes as obtained by different Bayesian calibration studies for each model configuration. Input data induced uncertainty (DU) was addressed by Bayesian calibration of soil properties, climate drivers and agricultural management practices data. For the MU, DU and PU we performed several hundred simulations each to contribute to the individual uncertainty assessment. For the overall uncertainty quantification we assessed the model prediction probability, followed by sampled sets of input datasets and parameter distributions. Statistical analysis of the simulation results have been used to quantify the overall full uncertainty of the modelling approach. With this study we can contrast the variation in model results to the different sources of uncertainties for each ecosystem. Further we have been able to perform a fully uncertainty analysis for modelling N2O and NO emissions from arable, grassland and forest soils necessary for the comprehensibility of modelling results. We have applied the methodology to a regional inventory to assess the overall modelling uncertainty for a regional N2O and NO emissions inventory for the state of Saxony, Germany.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Characteristics of Biogenic VOCs Emission and its High-Resolution Emission Inventory in China

NASA Astrophysics Data System (ADS)

Li, L.; Li, Y.; Xie, S.

2017-12-01

Biogenic volatile organic compounds (BVOCs), with high emission and reactivity, can have substantial impacts on the haze and photochemical pollution. It is essential to establish an accurate high-resolution BVOC emission inventory in China for air quality simulation and decision making. Firstly, a semi-static enclosure technique is developed for the field measurements of BVOC emission rates from 50 plant species in China. Using the GC-MS/FID system, 103 VOC species for each plant species are measured. Based on the field measurements in our study and the reported emission rates at home and abroad, a methodology for determining the emission categories of BVOCs is developed using statistical analysis. The isoprene and monoterpene emission rates of 192 plant species/genera in China are determined based on the above emission categories. Secondly, a new vegetation classification with 82 plant functional types (PFTs) is developed based on the most detailed and latest vegetation investigations, China's official statistical data and Vegetation Atlas of China (1:1,000,000). The leaf biomass is estimated based on provincial vegetation volume and production with biomass-apportion models. The WRF model is used to determine meteorological variables at a high spatio-temporal resolution. Using MEAGNv2.1 and the determined emission rates in our study, the high-resolution emission inventories of isoprene, 37 monoterpene species, 32 sesquiterpene species, and other VOCs (OVOCs) from 82 PFTs in China for 1981-2013 are established. The total annual BVOC emissions in 2013 are 55.88 Tg, including 33.87 Tg isoprene, 6.36 Tg monoterpene, 1.29 Tg sesquiterpene, and 14.37 Tg OVOCs. The distribution of isoprene emission fluxes is consistent with the distribution of broadleaf trees, especially tree species with high or higher emission potential. During 1981-2013, China's BVOC emissions have increased by 47.48% at an average rate of 1.80% yr-1. Emissions of isoprene have the largest enhancement, with an average rate of 3.10% yr-1. The increasing BVOC emissions largely originate from the enhanced forest volume and crop production. But the influence of meteorology cannot be ignored. Our study will be very significant for understanding the BVOC emission characteristics and improving the accuracy of air quality simulation in China.

Modeling uncertainties for tropospheric nitrogen dioxide columns affecting satellite-based inverse modeling of nitrogen oxides emissions

NASA Astrophysics Data System (ADS)

Lin, J.-T.; Liu, Z.; Zhang, Q.; Liu, H.; Mao, J.; Zhuang, G.

2012-12-01

Errors in chemical transport models (CTMs) interpreting the relation between space-retrieved tropospheric column densities of nitrogen dioxide (NO2) and emissions of nitrogen oxides (NOx) have important consequences on the inverse modeling. They are however difficult to quantify due to lack of adequate in situ measurements, particularly over China and other developing countries. This study proposes an alternate approach for model evaluation over East China, by analyzing the sensitivity of modeled NO2 columns to errors in meteorological and chemical parameters/processes important to the nitrogen abundance. As a demonstration, it evaluates the nested version of GEOS-Chem driven by the GEOS-5 meteorology and the INTEX-B anthropogenic emissions and used with retrievals from the Ozone Monitoring Instrument (OMI) to constrain emissions of NOx. The CTM has been used extensively for such applications. Errors are examined for a comprehensive set of meteorological and chemical parameters using measurements and/or uncertainty analysis based on current knowledge. Results are exploited then for sensitivity simulations perturbing the respective parameters, as the basis of the following post-model linearized and localized first-order modification. It is found that the model meteorology likely contains errors of various magnitudes in cloud optical depth, air temperature, water vapor, boundary layer height and many other parameters. Model errors also exist in gaseous and heterogeneous reactions, aerosol optical properties and emissions of non-nitrogen species affecting the nitrogen chemistry. Modifications accounting for quantified errors in 10 selected parameters increase the NO2 columns in most areas with an average positive impact of 18% in July and 8% in January, the most important factor being modified uptake of the hydroperoxyl radical (HO2) on aerosols. This suggests a possible systematic model bias such that the top-down emissions will be overestimated by the same magnitude if the model is used for emission inversion without corrections. The modifications however cannot eliminate the large model underestimates in cities and other extremely polluted areas (particularly in the north) as compared to satellite retrievals, likely pointing to underestimates of the a priori emission inventory in these places with important implications for understanding of atmospheric chemistry and air quality. Note that these modifications are simplified and should be interpreted with caution for error apportionment.

Hard X-ray emission from accretion shocks around galaxy clusters

NASA Astrophysics Data System (ADS)

Kushnir, Doron; Waxman, Eli

2010-02-01

We show that the hard X-ray (HXR) emission observed from several galaxy clusters is consistent with a simple model, in which the nonthermal emission is produced by inverse Compton scattering of cosmic microwave background photons by electrons accelerated in cluster accretion shocks: The dependence of HXR surface brightness on cluster temperature is consistent with that predicted by the model, and the observed HXR luminosity is consistent with the fraction of shock thermal energy deposited in relativistic electrons being lesssim0.1. Alternative models, where the HXR emission is predicted to be correlated with the cluster thermal emission, are disfavored by the data. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed.

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.

How consistent are top-down hydrocarbon emissions based on formaldehyde observations from GOME-2 and OMI?

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

Stavrakou, T.; Muller, J. F.; Bauwens, M.

2015-10-26

The vertical columns of formaldehyde (HCHO) retrieved from two satellite instruments, the Global Ozone Monitoring Instrument-2 (GOME-2) on Metop-A and the Ozone Monitoring Instrument (OMI) on Aura, are used to constrain global emissions of HCHO precursors from open fires, vegetation and human activities in the year 2010. To this end, the emissions are varied and optimized using the ad-joint model technique in the IMAGESv2 global CTM (chem-ical transport model) on a monthly basis and at the model res-olution. Given the different local overpass times of GOME- 2 (09:30 LT) and OMI (13:30 LT), the simulated diurnal cy-cle of HCHO columnsmore » is investigated and evaluated against ground-based optical measurements at seven sites in Europe, China and Africa. The modeled diurnal cycle exhibits large variability, reflecting competition between photochemistry and emission variations, with noon or early afternoon max-ima at remote locations (oceans) and in regions dominated by anthropogenic emissions, late afternoon or evening max-ima over fire scenes, and midday minima in isoprene-rich re-gions. The agreement between simulated and ground-based columns is generally better in summer (with a clear after-noon maximum at mid-latitude sites) than in winter, and the annually averaged ratio of afternoon to morning columns is slightly higher in the model (1.126) than in the ground-based measurements (1.043).The anthropogenic VOC (volatile organic compound) sources are found to be weakly constrained by the inversions on the global scale, mainly owing to their generally minor contribution to the HCHO columns, except over strongly pol-luted regions, like China. The OMI-based inversion yields total flux estimates over China close to the bottom-up inven-tory (24.6 vs. 25.5 TgVOC yr -1 in the a priori) with, how-ever, pronounced increases in the northeast of China and re-ductions in the south. Lower fluxes are estimated based on GOME-2 HCHO columns (20.6 TgVOC yr -1), in particular over the northeast, likely reflecting mismatches between the observed and the modeled diurnal cycle in this region.« less

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.

Model study of the ship emissions impact on the air quality in the Adriatic/Ionian area

NASA Astrophysics Data System (ADS)

Karagiannidis, Athanasios; Poupkou, Anastasia; Liora, Natalia; Dimopoulos, Spiros; Giannaros, Christos; Melas, Dimitrios; Argiriou, Athanassios

2015-04-01

The increase of the ship traffic for touristic and commercial purposes is one of the EU Blue Growth targets. The Adriatic/Ionian is one of the sea-basin strategic areas for this target. The purpose of the study is the examination of the impact of the ship emissions on the gaseous and particulate pollutants concentrations in the Adriatic/Ionian area for which the current scientific knowledge is limited. The impact is simulated over a domain covering the Central and Eastern Mediterranean in 10 km resolution during a summer period (July) and a winter period (January) of the year 2012. The modeling system used consists of the photochemical model CAMx off line coupled with the meteorological model WRF. The zero-out modeling method is implemented involving CAMx simulations performed while including and omitting the ship emission data. The simulations are based on the European scale anthropogenic emission inventory of The Netherlands Organisation (TNO) for the reference year 2009. Natural emissions (NMVOCs from the vegetation, sea salt, wind-blown dust), estimated with the use of the Natural Emission MOdel (NEMO) developed by the Aristotle University of Thessaloniki, are accounted for in the photochemical model runs. The spatial distribution of the resulting differences in the gaseous and particulate pollutant concentration fields for both emission scenarios are presented and discussed, providing an estimation of the contribution of ship emissions on the determination of the air quality in the Adriatic/Ionian countries

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.

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.

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.

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.

Modelling methane emissions from natural wetlands by development and application of the TRIPLEX-GHG model

USGS Publications Warehouse

Zhu, Qing; Liu, Jinxun; Peng, C.; Chen, H.; Fang, X.; Jiang, H.; Yang, G.; Zhu, D.; Wang, W.; Zhou, X.

2014-01-01

A new process-based model TRIPLEX-GHG was developed based on the Integrated Biosphere Simulator (IBIS), coupled with a new methane (CH4) biogeochemistry module (incorporating CH4 production, oxidation, and transportation processes) and a water table module to investigate CH4 emission processes and dynamics that occur in natural wetlands. Sensitivity analysis indicates that the most sensitive parameters to evaluate CH4 emission processes from wetlands are r (defined as the CH4 to CO2 release ratio) and Q10 in the CH4 production process. These two parameters were subsequently calibrated to data obtained from 19 sites collected from approximately 35 studies across different wetlands globally. Being heterogeneously spatially distributed, r ranged from 0.1 to 0.7 with a mean value of 0.23, and the Q10 for CH4 production ranged from 1.6 to 4.5 with a mean value of 2.48. The model performed well when simulating magnitude and capturing temporal patterns in CH4 emissions from natural wetlands. Results suggest that the model is able to be applied to different wetlands under varying conditions and is also applicable for global-scale simulations.

Temporalization of Electric Generation Emissions for Improved Representation of Peak Air Quality Episodes

NASA Astrophysics Data System (ADS)

Farkas, C. M.; Moeller, M.; Carlton, A. G.

2013-12-01

Photochemical transport models routinely under predict peak air quality events. This deficiency may be due, in part, to inadequate temporalization of emissions from the electric generating sector. The National Emissions Inventory (NEI) reports emissions from Electric Generating Units (EGUs) by either Continuous Emission Monitors (CEMs) that report hourly values or as an annual total. The Sparse Matrix Operator Kernel Emissions preprocessor (SMOKE), used to prepare emissions data for modeling with the CMAQ air quality model, allocates annual emission totals throughout the year using specific monthly, weekly, and hourly weights according to standard classification code (SCC) and location. This approach represents average diurnal and seasonal patterns of electricity generation but does not capture spikes in emissions due to episodic use as with peaking units or due to extreme weather events. In this project we use a combination of state air quality permits, CEM data, and EPA emission factors to more accurately temporalize emissions of NOx, SO2 and particulate matter (PM) during the extensive heat wave of July and August 2006. Two CMAQ simulations are conducted; the first with the base NEI emissions and the second with improved temporalization, more representative of actual emissions during the heat wave. Predictions from both simulations are evaluated with O3 and PM measurement data from EPA's National Air Monitoring Stations (NAMS) and State and Local Air Monitoring Stations (SLAMS) during the heat wave, for which ambient concentrations of criteria pollutants were often above NAAQS. During periods of increased photochemistry and high pollutant concentrations, it is critical that emissions are most accurately represented in air quality models.

Upscaling NZ-DNDC using a regression based meta-model to estimate direct N2O emissions from New Zealand grazed pastures.

PubMed

Giltrap, Donna L; Ausseil, Anne-Gaëlle E

2016-01-01

The availability of detailed input data frequently limits the application of process-based models at large scale. In this study, we produced simplified meta-models of the simulated nitrous oxide (N2O) emission factors (EF) using NZ-DNDC. Monte Carlo simulations were performed and the results investigated using multiple regression analysis to produce simplified meta-models of EF. These meta-models were then used to estimate direct N2O emissions from grazed pastures in New Zealand. New Zealand EF maps were generated using the meta-models with data from national scale soil maps. Direct emissions of N2O from grazed pasture were calculated by multiplying the EF map with a nitrogen (N) input map. Three meta-models were considered. Model 1 included only the soil organic carbon in the top 30cm (SOC30), Model 2 also included a clay content factor, and Model 3 added the interaction between SOC30 and clay. The median annual national direct N2O emissions from grazed pastures estimated using each model (assuming model errors were purely random) were: 9.6GgN (Model 1), 13.6GgN (Model 2), and 11.9GgN (Model 3). These values corresponded to an average EF of 0.53%, 0.75% and 0.63% respectively, while the corresponding average EF using New Zealand national inventory values was 0.67%. If the model error can be assumed to be independent for each pixel then the 95% confidence interval for the N2O emissions was of the order of ±0.4-0.7%, which is much lower than existing methods. However, spatial correlations in the model errors could invalidate this assumption. Under the extreme assumption that the model error for each pixel was identical the 95% confidence interval was approximately ±100-200%. Therefore further work is needed to assess the degree of spatial correlation in the model errors. Copyright © 2015 Elsevier B.V. All rights reserved.

An integrated approach for estimation of methane emissions from wetlands and lakes in high latitude regions

NASA Astrophysics Data System (ADS)

Chiu, C.; Bowling, L. C.; Podest, E.; Bohn, T. J.; Lettenmaier, D. P.; Schroeder, R.; McDonald, K. C.

2009-04-01

In recent years, there has been increasing evidence of significant alteration in the extent of lakes and wetlands in high latitude regions due in part to thawing permafrost, as well as other changes governing surface and subsurface hydrology. Methane is a 23 times more efficient greenhouse gas than carbon dioxide; changes in surface water extent, and the associated subsurface anaerobic conditions, are important controls on methane emissions in high latitude regions. Methane emissions from wetlands vary substantially in both time and space, and are influenced by plant growth, soil organic matter decomposition, methanogenesis, and methane oxidation controlled by soil temperature, water table level and net primary productivity (NPP). The understanding of spatial and temporal heterogeneity of surface saturation, thermal regime and carbon substrate in northern Eurasian wetlands from point measurements are limited. In order to better estimate the magnitude and variability of methane emissions from northern lakes and wetlands, we present an integrated assessment approach based on remote sensing image classification, land surface modeling and process-based ecosystem modeling. Wetlands classifications based on L-band JERS-1 SAR (100m) and ALOS PALSAR (~30m) are used together with topographic information to parameterize a lake and wetland algorithm in the Variable Infiltration Capacity (VIC) land surface model at 25 km resolution. The enhanced VIC algorithm allows subsurface moisture exchange between surface water and wetlands and includes a sub-grid parameterization of water table position within the wetland area using a generalized topographic index. Average methane emissions are simulated by using the Walter and Heimann methane emission model based on temporally and spatially varying soil temperature, net primary productivity and water table generated from the modified VIC model. Our five preliminary study areas include the Z. Dvina, Upper Volga, Yeloguy, Syum, and Chaya river basins. The temporally-variable inundation extent simulated by the VIC model is compared to 25 km resolution inundation products developed from combined QuikSCAT, AMSR-E and MODIS data sets covering the time period from 2002 onward. The seasonal variation in methane emissions associated with sub-grid variability in water table extent is explored between 1948 and 2006. This work was carried out at Purdue University, at the University of Washington, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the NASA.

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.

First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Souri, Amir H.; Choi, Yunsoo; Pan, Shuai; Curci, Gabriele; Nowlan, Caroline R.; Janz, Scott J.; Kowalewski, Matthew G.; Liu, Junjie; Herman, Jay R.; Weinheimer, Andrew J.

2018-03-01

A number of satellite-based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high-quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NOx emissions in the Houston-Galveston-Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO2 profiles from a high-resolution regional model (1 × 1 km2) constrained by P-3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and (iii) high-resolution surface albedo constrained by ground-based spectrometers. We characterize errors in the GCAS NO2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 1015 molecules cm-2. On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2-50% reduction in polluted areas, partly counterbalancing the well-documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top-down emissions.

Development of the Model of Galactic Interstellar Emission for Standard Point-Source Analysis of Fermi Large Area Telescope Data

DOE PAGES

Acero, F.

2016-04-22

Most of the celestial γ rays detected by the Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope originate from the interstellar medium when energetic cosmic rays interact with interstellar nucleons and photons. Conventional point and extended source studies rely on the modeling of this diffuse emission for accurate characterization. We describe here the development of the Galactic Interstellar Emission Model (GIEM) that is the standard adopted by the LAT Collaboration and is publicly available. The model is based on a linear combination of maps for interstellar gas column density in Galactocentric annuli and for the inverse Compton emissionmore » produced in the Galaxy. We also include in the GIEM large-scale structures like Loop I and the Fermi bubbles. The measured gas emissivity spectra con rm that the cosmic-ray proton density decreases with Galactocentric distance beyond 5 kpc from the Galactic Center. The measurements also suggest a softening of the proton spectrum with Galactocentric distance. We observe that the Fermi bubbles have boundaries with a shape similar to a catenary at latitudes below 20° and we observe an enhanced emission toward their base extending in the North and South Galactic direction and located within ~4° of the Galactic Center.« less

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...

77 FR 6627 - National Emission Standards for Hazardous Air Pollutant Emissions: Hard and Decorative Chromium...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-08

... electroplating and anodizing facilities and proposes revisions to the NESHAP based on those reviews. This action...; and email address: [email protected] . For specific information regarding the risk modeling... based on our technology review? B. What are the results of the risk assessment? C. What are our proposed...

A comparison of emission calculations using different modeled indicators with 1-year online measurements.

PubMed

Lengers, Bernd; Schiefler, Inga; Büscher, Wolfgang

2013-12-01

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm's characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow(-1) year(-1)) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow(-1) year(-1) (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between -6.4% and 10.5%), compared with findings from the literature.

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

Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: projections under current legislation

NASA Astrophysics Data System (ADS)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Gsella, A.; Amann, M.

2014-01-01

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

Can dust emission mechanisms be determined from field measurements?

NASA Astrophysics Data System (ADS)

Klose, Martina; Webb, Nicholas; Gill, Thomas E.; Van Pelt, Scott; Okin, Gregory

2017-04-01

Field observations are needed to develop and test theories on dust emission for use in dust modeling systems. The dust emission mechanism (aerodynamic entrainment, saltation bombardment, aggregate disintegration) as well as the amount and particle-size distribution of emitted dust may vary under sediment supply- and transport-limited conditions. This variability, which is caused by heterogeneity of the surface and the atmosphere, cannot be fully captured in either field measurements or models. However, uncertainty in dust emission modeling can be reduced through more detailed observational data on the dust emission mechanism itself. To date, most measurements do not provide enough information to allow for a determination of the mechanisms leading to dust emission and often focus on a small variety of soil and atmospheric settings. Additionally, data sets are often not directly comparable due to different measurement setups. As a consequence, the calibration of dust emission schemes has so far relied on a selective set of observations, which leads to an idealization of the emission process in models and thus affects dust budget estimates. Here, we will present results of a study which aims to decipher the dust emission mechanism from field measurements as an input for future model development. Detailed field measurements are conducted, which allow for a comparison of dust emission for different surface and atmospheric conditions. Measurements include monitoring of the surface, loose erodible material, transported sediment, and meteorological data, and are conducted in different environmental settings in the southwestern United States. Based on the field measurements, a method is developed to differentiate between the different dust emission mechanisms.

Spatial variability of intake fractions for Canadian emission scenarios: a comparison between three resolution scales.

PubMed

Manneh, Rima; Margni, Manuele; Deschênes, Louise

2010-06-01

Spatially differentiated intake fractions (iFs) linked to Canadian emissions of toxic organic chemicals were developed using the multimedia and multipathways fate and exposure model IMPACT 2002. The fate and exposure of chemicals released to the Canadian environment were modeled with a single regional mass-balance model and three models that provided multiple mass-balance regions within Canada. These three models were based on the Canadian subwatersheds (172 zones), ecozones (15 zones), and provinces (13 zones). Releases of 32 organic chemicals into water and air were considered. This was done in order to (i) assess and compare the spatial variability of iFs within and across the three levels of regionalization and (ii) compare the spatial iFs to nonspatial ones. Results showed that iFs calculated using the subwatershed resolution presented a higher spatial variability (up to 10 orders of magnitude for emissions into water) than the ones based on the ecozones and provinces, implying that higher spatial resolution could potentially reduce uncertainty in iFs and, therefore, increase the discriminating power when assessing and comparing toxic releases for known emission locations. Results also indicated that, for an unknown emission location, a model with high spatial resolution such as the subwatershed model could significantly improve the accuracy of a generic iF. Population weighted iFs span up to 3 orders of magnitude compared to nonspatial iFs calculated by the one-box model. Less significant differences were observed when comparing spatial versus nonspatial iFs from the ecozones and provinces, respectively.

The blue skies in Beijing during APEC 2014: A quantitative assessment of emission control efficiency and meteorological influence

NASA Astrophysics Data System (ADS)

Liu, Hongli; He, Jing; Guo, Jianping; Miao, Yucong; Yin, Jinfang; Wang, Yuan; Xu, Hui; Liu, Huan; Yan, Yan; Li, Yuan; Zhai, Panmao

2017-10-01

Most previous studies attributed the alleviation of aerosol pollution to either emission control measures or favorable meteorological conditions. However, our understanding of their quantitative contribution is far from complete. In this study, based on model simulation using the CMA (China Meteorological Administration) Unified Atmospheric Chemistry Environment for aerosols (CUACE/Aero), in combination with simultaneous ground-based hourly PM2.5 observations, we aim to quantify the relative contributions of the emission control measures and meteorology to the blue-skies seen in Beijing during the Asia-Pacific Economic Cooperation (APEC) summit held in November of 2014. A series of model simulations have been performed over Beijing-Tianjin-Hebei (BTH) region by implementing nine different emission control schemes. To investigate the relative contributions of the emission control measures and meteorology, the study period has been divided into five episodes. Overall, the CUACE/Aero model can reasonably well reproduce the temporal and spatial evolution of PM2.5 during APEC 2014, although the model performance varies by different time periods and regions of interest. Model results show the emission control measures on average reduced the PM2.5 concentration by 41.3% in urban areas of Beijing and 39.7% in Huairou district, respectively, indicating emission control plays a significant role for the blue skies observed. Among all the emission control measures under investigation, local emission control in Beijing contributed the largest to the reduction of PM2.5 concentrations with a reduction of 35.5% in urban area of Beijing and 34.8% in Huairou, in contrast with the vehicle emission control in Hebei that contributed the least with a reduction of less than 1%. The emission control efficiency in five episodes has been assessed quantitatively, which falls in the range of 36.2%-41.2% in urban area of Beijing and 34.9%-40.7% in Huairou, indicative of no significant episode and geographic dependence in the emission control efficiency. The emission control measures and meteorology, however, alternated to dominate the absolute reduction of PM2.5 concentrations. When the weather conditions are unfavorable, emission control measures outperformed meteorology with a reduction of 55.3-59.4 μg/m3 in urban area of Beijing and 32.5-33 μg/m3 in Huairou. Conversely, when the northwesterly winds prevailed, meteorology tends to outweigh the role of emission control in accounting for the drop of PM2.5. The atmospheric dilution conditions are determined through the model calculation of the mass inflow of PM2.5 per unit volume near the surface. Our findings have significant implications for effective planning and implementation of emission control measures.

First-principles calculations of orientation dependence of Si thermal oxidation based on Si emission model

NASA Astrophysics Data System (ADS)

Nagura, Takuya; Kawachi, Shingo; Chokawa, Kenta; Shirakawa, Hiroki; Araidai, Masaaki; Kageshima, Hiroyuki; Endoh, Tetsuo; Shiraishi, Kenji

2018-04-01

It is expected that the off-state leakage current of MOSFETs can be reduced by employing vertical body channel MOSFETs (V-MOSFETs). However, in fabricating these devices, the structure of the Si pillars sometimes cannot be maintained during oxidation, since Si atoms sometimes disappear from the Si/oxide interface (Si missing). Thus, in this study, we used first-principles calculations based on the density functional theory, and investigated the Si emission behavior at the various interfaces on the basis of the Si emission model including its atomistic structure and dependence on Si crystal orientation. The results show that the order in which Si atoms are more likely to be emitted during thermal oxidation is (111) > (110) > (310) > (100). Moreover, the emission of Si atoms is enhanced as the compressive strain increases. Therefore, the emission of Si atoms occurs more easily in V-MOSFETs than in planar MOSFETs. To reduce Si missing in V-MOSFETs, oxidation processes that induce less strain, such as wet or pyrogenic oxidation, are necessary.

Satellite-based observations of tsunami-induced mesosphere airglow perturbations

NASA Astrophysics Data System (ADS)

Yang, Yu-Ming; Verkhoglyadova, Olga; Mlynczak, Martin G.; Mannucci, Anthony J.; Meng, Xing; Langley, Richard B.; Hunt, Linda A.

2017-01-01

Tsunami-induced airglow emission perturbations were retrieved by using space-based measurements made by the Sounding of the Atmosphere using Broad-band Emission Radiometry (SABER) instrument on board the Thermosphere-Ionosphere-Mesosphere Energetics Dynamics spacecraft. At and after the time of the Tohoku-Oki earthquake on 11 March 2011, and the Chile earthquake on 16 September 2015, the spacecraft was performing scans over the Pacific Ocean. Significant ( 10% relative to the ambient emission profiles) and coherent nighttime airglow perturbations were observed in the mesosphere following Sounding of the Atmosphere using Broad-band Emission Radiometry limb scans intercepting tsunami-induced atmospheric gravity waves. Simulations of emission variations are consistent with the physical characteristics of the disturbances at the locations of the corresponding SABER scans. Airglow observations and model simulations suggest that atmospheric neutral density and temperature perturbations can lead to the observed amplitude variations and multipeak structures in the emission profiles. This is the first time that airglow emission rate perturbations associated with tsunamis have been detected with space-based measurements.

Source attribution and quantification of benzene event emissions in a Houston ship channel community based on real-time mobile monitoring of ambient air.

PubMed

Olaguer, Eduardo P; Erickson, Matthew H; Wijesinghe, Asanga; Neish, Bradley S

2016-02-01

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppbv in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km(2) model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2-6. Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.

Assessment of methods for methyl iodide emission reduction and pest control using a simulation model

NASA Astrophysics Data System (ADS)

Luo, Lifang; Ashworth, Daniel J.; Šimunek, Jirka; Xuan, Richeng; Yates, Scott R.

2013-02-01

The increasing registration of the fumigant methyl iodide within the USA has led to more concerns about its toxicity to workers and bystanders. Emission mitigation strategies are needed to protect the public and environmental health while providing effective pest control. The effectiveness of various methods on emissions reduction and pest control was assessed using a process-based mathematical model in this study. Firstly, comparisons between the simulated and laboratory measured emission fluxes and cumulative emissions were made for methyl iodide (MeI) under four emission reduction treatments: 1) control, 2) using soil with high organic matter content (HOM), 3) being covered by virtually impermeable film (VIF), and 4) irrigating soil surface following fumigation (Irrigation). Then the model was extended to simulate a broader range of emission reduction strategies for MeI, including 5) being covered by high density polyethylene (HDPE), 6) increasing injection depth from 30 cm to 46 cm (Deep), 7) HDPE + Deep, 8) adding a reagent at soil surface (Reagent), 9) Reagent + Irrigation, and 10) Reagent + HDPE. Furthermore, the survivability of three types of soil-borne pests (citrus nematodes [Tylenchulus semipenetrans], barnyard seeds [Echinochloa crus-galli], fungi [Fusarium oxysporum]) was also estimated for each scenario. Overall, the trend of the measured emission fluxes as well as total emission were reasonably reproduced by the model for treatments 1 through 4. Based on the numerical simulation, the ranking of effectiveness in total emission reduction was VIF (82.4%) > Reagent + HDPE (73.2%) > Reagent + Irrigation (43.0%) > Reagent (23.5%) > Deep + HDPE (19.3%) > HOM (17.6%) > Deep (13.0%) > Irrigation (11.9%) > HDPE (5.8%). The order for pest control efficacy suggests, VIF had the highest pest control efficacy, followed by Deep + HDPE, Irrigation, Reagent + Irrigation, HDPE, Deep, Reagent + HDPE, Reagent, and HOM. Therefore, VIF is the optimal method disregarding the cost of the film since it maximizes efficacy while minimizing volatility losses. Otherwise, the integrated methods such as Deep + HDPE and Reagent + Irrigation, are recommended.

Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems.

PubMed

Del Prado, A; Crosson, P; Olesen, J E; Rotz, C A

2013-06-01

The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

NASA Astrophysics Data System (ADS)

Nita, Gelu M.; Viall, Nicholeen M.; Klimchuk, James A.; Loukitcheva, Maria A.; Gary, Dale E.; Kuznetsov, Alexey A.; Fleishman, Gregory D.

2018-01-01

The study of time-dependent solar active region (AR) morphology and its relation to eruptive events requires analysis of imaging data obtained in multiple wavelength domains with differing spatial and time resolution, ideally in combination with 3D physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tool, GX_Simulator, previously developed for modeling microwave and X-ray emission from flaring loops, to allow it to simulate quiescent emission from solar ARs. The framework includes new tools for building the atmospheric model and enhanced routines for calculating emission that include new wavelengths. In this paper, we use our upgraded tool to model and analyze an AR and compare the synthetic emission maps with observations. We conclude that the modeled magneto-thermal structure is a reasonably good approximation of the real one.

Acoustic emission based damage localization in composites structures using Bayesian identification

NASA Astrophysics Data System (ADS)

Kundu, A.; Eaton, M. J.; Al-Jumali, S.; Sikdar, S.; Pullin, R.

2017-05-01

Acoustic emission based damage detection in composite structures is based on detection of ultra high frequency packets of acoustic waves emitted from damage sources (such as fibre breakage, fatigue fracture, amongst others) with a network of distributed sensors. This non-destructive monitoring scheme requires solving an inverse problem where the measured signals are linked back to the location of the source. This in turn enables rapid deployment of mitigative measures. The presence of significant amount of uncertainty associated with the operating conditions and measurements makes the problem of damage identification quite challenging. The uncertainties stem from the fact that the measured signals are affected by the irregular geometries, manufacturing imprecision, imperfect boundary conditions, existing damages/structural degradation, amongst others. This work aims to tackle these uncertainties within a framework of automated probabilistic damage detection. The method trains a probabilistic model of the parametrized input and output model of the acoustic emission system with experimental data to give probabilistic descriptors of damage locations. A response surface modelling the acoustic emission as a function of parametrized damage signals collected from sensors would be calibrated with a training dataset using Bayesian inference. This is used to deduce damage locations in the online monitoring phase. During online monitoring, the spatially correlated time data is utilized in conjunction with the calibrated acoustic emissions model to infer the probabilistic description of the acoustic emission source within a hierarchical Bayesian inference framework. The methodology is tested on a composite structure consisting of carbon fibre panel with stiffeners and damage source behaviour has been experimentally simulated using standard H-N sources. The methodology presented in this study would be applicable in the current form to structural damage detection under varying operational loads and would be investigated in future studies.

Effects of Advanced Fuel Injection Strategies on DI Diesel Emissions

DTIC Science & Technology

2001-06-19

Skeletal mechanism for NO chemistry in Diesel engines ," SAE Paper 981450. 2) Duffy, K. P. and Mellor, A. M. (1998), "jadf;lkajdf," SAE Paper. 3) Lavoie...pressure for this zone are the start of combustion, stoichiometric flame temperature (Tý.,) and pressure. The NO chemistry is based on a skeletal mechanism ...emissions from a 2.2L high speed direct injection (HSDI) Diesel engine [2]. Model Formulation for Single Injections: The model is based on the assumption

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

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.

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.

Changes in the carbon footprint of Japanese households in an aging society.

PubMed

Shigetomi, Yosuke; Nansai, Keisuke; Kagawa, Shigemi; Tohno, Susumu

2014-06-03

As the aging and low birthrate trends continue in Japan, and as changes in the working population and consumption patterns occur, new factors are expected to have an impact on consumption-based greenhouse gas (GHG) emissions. We present the impacts of changes in the composition of Japanese households on GHG emission structures using current (2005) consumption-based accounting on the commodity sectors that are expected to require priority efforts for reducing emissions in 2035. This is done using the Global Link Input-Output model (GLIO) and domestic household consumption data and assuming that recent detailed consumption expenditures based on the Social Accounting Matrix (SAM) will continue into the future. The results show that consumption-based GHG emissions derived from Japanese household consumption in 2035 are estimated to be 1061 Mt-CO2eq (4.2% lower than in 2005). This study can be used to reveal more information and as a resource in developing policies to more meticulously and efficiently reduce emissions based on emission and import rates for each domestic and overseas commodity supply chain.

Impacts of Energy Sector Emissions on PM2.5 Air Quality in Northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Kiesewetter, G.; Heyes, C.; Holloway, T.

2015-12-01

India experiences high concentrations of fine particulate matter (PM2.5), and several Indian cities currently rank among the world's most polluted cities. With ongoing urbanization and a growing economy, emissions from different energy sectors remain major contributors to air pollution in India. Emission sectors impact ambient air quality differently due to spatial distribution (typical urban vs. typical rural sources) as well as source height characteristics (low-level vs. high stack sources). This study aims to assess the impacts of emissions from three distinct energy sectors—transportation, domestic, and electricity—on ambient PM2.5­­ in northern India using an advanced air quality analysis framework based on the U.S. EPA Community Multi-Scale Air Quality (CMAQ) model. Present air quality conditions are simulated using 2010 emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model. Modeled PM2.5 concentrations are compared with satellite observations of aerosol optical depth (AOD) from the Moderate Imaging Spectroradiometer (MODIS) for 2010. Energy sector emissions impacts on future (2030) PM2.5 are evaluated with three sensitivity simulations, assuming maximum feasible reduction technologies for either transportation, domestic, or electricity sectors. These simulations are compared with a business as usual 2030 simulation to assess relative sectoral impacts spatially and temporally. CMAQ is modeled at 12km by 12km and include biogenic emissions from the Community Land Model coupled with the Model of Emissions of Gases and Aerosols in Nature (CLM-MEGAN), biomass burning emissions from the Global Fires Emissions Database (GFED), and ERA-Interim meteorology generated with the Weather Research and Forecasting (WRF) model for 2010 to quantify the impact of modified anthropogenic emissions on ambient PM2.5 concentrations. Energy sector emissions analysis supports decision-making to improve future air quality and public health in India.

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions--Application of system dynamics modeling for the case of Latvia.

PubMed

Dace, Elina; Muizniece, Indra; Blumberga, Andra; Kaczala, Fabio

2015-09-15

European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to "neutralize" the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. Copyright © 2015 Elsevier B.V. All rights reserved.

A GIS model-based assessment of the environmental distribution of gamma-hexachlorocyclohexane in European soils and waters.

PubMed

Vizcaíno, P; Pistocchi, A

2010-10-01

The MAPPE GIS based multimedia model is used to produce a quantitative description of the behaviour of gamma-hexachlorocyclohexane (gamma-HCH) in Europe, with emphasis on continental surface waters. The model is found to reasonably reproduce gamma-HCH distributions and variations along the years in atmosphere and soil; for continental surface waters, concentrations were reasonably well predicted for year 1995, when lindane was still used in agriculture, while for 2005, assuming severe restrictions in use, yields to substantial underestimation. Much better results were yielded when same mode of release as in 1995 was considered, supporting the conjecture that for gamma-HCH, emission data rather that model structure and parameterization can be responsible for wrong estimation of concentrations. Future research should be directed to improve the quality of emission data. Joint interpretation of monitoring and modelling results, highlights that lindane emissions in Europe, despite the marked decreasing trend, persist beyond the provisions of existing legislation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

40 CFR 1037.520 - Modeling CO2 emissions to show compliance.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) AIR POLLUTION CONTROLS CONTROL OF EMISSIONS FROM NEW HEAVY-DUTY MOTOR VEHICLES Test and Modeling..., expressed in m2 and rounded to two decimal places. Where we allow you to group multiple configurations... bin based on the drag area bin of an equivalent high-roof tractor. If the high-roof tractor is in Bin...

Field measurements and modeling to resolve m2 to km2 CH4 emissions for a complex urban source: An Indiana landfill study

USDA-ARS?s Scientific Manuscript database

Large uncertainties for landfill CH4 emissions due to spatial and temporal variabilities remain unresolved by short-term field campaigns and historic GHG inventory models. Using four field methods (aircraft-based mass balance, tracer correlation, vertical radial plume mapping, and static chambers) ...

Modeling impacts of management on carbon sequestration and trace gas emissions in forested wetland ecosystems

Treesearch

Changsheng Li; Jianbo Cui

2004-01-01

A process- based model, Wetland-DNDC, was modified to enhance its capacity to predict the impacts of management practices on carbon sequestration in and trace gas emissions from forested wetland ecosystems. The modifications included parameterization of management practices fe.g., forest harvest, chopping, burning, water management, fertilization, and tree planting),...

Observations of the 10-micron natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Espenak, F.; Deming, D.; Jennings, D.; Kostiuk, T.; Mumma, M.; Zipoy, D.

1983-01-01

Observations of the total flux and center to limb dependence of the nonthermal emission occurring in the cores of the 9.4 and 10.4 micrometers CO2 bands on Mars are compared to a theoretical model based on this mechanism. The model successfully reproduces the observed center to limb dependence of this emission, to within the limits imposed by the spatial resolution of the observations of Mars and Venus. The observed flux from Mars agrees closely with the prediction of the model; the flux observed from Venus is 74 percent of the flux predicted by the model. This emission is used to obtain the kinetic temperatures of the Martian and Venusian mesospheres. For Mars near 70 km altitude, a rotational temperature analysis using five lines gives T = 135 + or - 20 K. The frequency width of the emission is also analyzed to derive a temperature of 126 + or - 6 K. In the case of the Venusian mesosphere near 109 km, the frequency width of the emission gives T = 204 + or - 10 K.

Observations of the 10 micrometer natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Espenak, F.; Jennings, D.; Kostiuk, T.; Mumma, M. J.

1983-01-01

Observations of the total flux and center to limb dependence of the nonthermal emission occurring in the cores of the 9.4 and 10.4 micrometers CO2 bands on Mars are compared to a theoretical model based on this mechanism. The model successfully reproduces the observed center to limb dependence of this emission, to within the limits imposed by the spatial resolution of the observations of Mars and Venus. The observed flux from Mars agrees closely with the prediction of the model; the flux observed from Venus is 74% of the flux predicted by the model. This emission is used to obtain the kinetic temperatures of the Martian and Venusian mesospheres. For Mars near 70 km altitude, a rotational temperature analysis using five lines gives T = 135 + or - 20 K. The frequency width of the emission is also analyzed to derive a temperature of 126 + or - 6 K. In the case of the Venusian mesosphere near 109 km, the frequency width of the emission gives T = 204 + or - 10 K.

The emission function of ground-based light sources: State of the art and research challenges

NASA Astrophysics Data System (ADS)

Solano Lamphar, Héctor Antonio

2018-05-01

To understand the night sky radiance generated by the light emissions of urbanised areas, different researchers are currently proposing various theoretical approaches. The distribution of the radiant intensity as a function of the zenith angle is one of the most unknown properties on modelling skyglow. This is due to the collective effects of the artificial radiation emitted from the ground-based light sources. The emission function is a key property in characterising the sky brightness under arbitrary conditions, therefore it is required by modellers, environmental engineers, urban planners, light pollution researchers, and experimentalists who study the diffuse light of the night sky. As a matter of course, the emission function considers the public lighting system, which is in fact the main generator of the skyglow. Still, another class of light-emitting devices are gaining importance since their overuse and the urban sprawl of recent years. This paper will address the importance of the emission function in modelling skyglow and the factors involved in its characterization. On this subject, the author's intention is to organise, integrate, and evaluate previously published research in order to state the progress of current research toward clarifying this topic.

[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.

What could have caused pre-industrial biomass burning emissions to exceed current rates?

NASA Astrophysics Data System (ADS)

van der Werf, G. R.; Peters, W.; van Leeuwen, T. T.; Giglio, L.

2012-08-01

Recent studies based on trace gas mixing ratios in ice cores and charcoal data indicate that biomass burning emissions over the past millennium exceeded contemporary emissions by up to a factor of 4 for certain time periods. This is surprising because various sources of biomass burning are linked with population density, which has increased over the past centuries. Here we have analyzed how emissions from several biomass burning sources could have fluctuated to yield emissions that are in correspondence with recent results based on ice core mixing ratios of carbon monoxide (CO) and its isotopic signature measured at South Pole station (SPO). Based on estimates of contemporary fire emissions and the TM5 chemical transport model, we found that CO mixing ratios at SPO are more sensitive to emissions from South America and Australia than from Africa, and are relatively insensitive to emissions from the Northern Hemisphere. We then explored how various biomass burning sources may have varied over the past centuries and what the resulting emissions and corresponding CO mixing ratio at SPO would be, using population density variations to reconstruct sources driven by humans (e.g. fuelwood burning) and a new model to relate savanna emissions to changes in fire return times. We found that to match the observed ice core CO data all savannas in the Southern Hemisphere had to burn annually, or bi-annually in combination with deforestation and slash and burn agriculture matching current levels despite much lower population densities and lack of machinery to aid the deforestation process. While possible, these scenarios are unlikely and in conflict with current literature. However, we do show the large potential for increased emissions from savannas in a pre-industrial world. This is mainly because in the past, fuel beds were probably less fragmented compared to the current situation; we show that the majority of savannas have not burned in the past 10 yr, even in Africa which is considered "the burning continent". Our new modelling results, together with existing literature, indicate that no definitive conclusions can be drawn about unprecedentedly high or low biomass burning rates from current data analyses.

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.

Comparison of CMAQ Modeling Study with Discover-AQ 2014 Aircraft Measurements over Colorado

NASA Astrophysics Data System (ADS)

Tang, Y.; Pan, L.; Lee, P.; Tong, D.; Kim, H. C.; Artz, R. S.

2014-12-01

NASA and NCAR jointly led a recent multiple platform-based (space, air and ground) measurement intensive to study air quality and to validate satellite data. The Discover-AQ/FRAPPE field experiment took place along the Colorado Front Range in July and August, 2014. The air quality modeling team of the NOAA Air Resources Laboratory was one of the three teams that provided real-time air quality forecasting for the campaign. The U.S. EPA Community Multi-scale Air Quality (CMAQ) Model was used with emission inventories based on the data set used by the NOAA National Air Quality Forecasting Capacity (NAQFC). By analyzing the forecast results calculated using aircraft measurements, it was found that CO emissions tended to be overestimated, while ethane emissions were underestimated. Biogenic VOCs were also underpredicted. Due to their relatively high altitude, ozone concentrations in Denver and the surrounding areas are affected by both local emissions and transported ozone. The modeled ozone was highly dependent on the meteorological predictions over this region. The complex terrain over the Rocky Mountains also contributed to the model uncertainty. This study discussed the causes of model biases, the forecast performance under different meteorology, and results from using different model grid resolutions. Several data assimilation techniques were further tested to improve the "post-analysis" performance of the modeling system for the period.

A simulation model for methane emissions from landfills with interaction of vegetation and cover soil.

PubMed

Bian, Rongxing; Xin, Danhui; Chai, Xiaoli

2018-01-01

Global climate change and ecological problems brought about by greenhouse gas effect have become a severe threat to humanity in the 21st century. Vegetation plays an important role in methane (CH 4 ) transport, oxidation and emissions from municipal solid waste (MSW) landfills as it modifies the physical and chemical properties of the cover soil, and transports CH 4 to the atmosphere directly via their conduits, which are mainly aerenchymatous structures. In this study, a novel 2-D simulation CH 4 emission model was established, based on an interactive mechanism of cover soil and vegetation, to model CH 4 transport, oxidation and emissions in landfill cover soil. Results of the simulation model showed that the distribution of CH 4 concentration and emission fluxes displayed a significant difference between vegetated and non-vegetated areas. CH 4 emission flux was 1-2 orders of magnitude higher than bare areas in simulation conditions. Vegetation play a negative role in CH 4 emissions from landfill cover soil due to the strong CH 4 transport capacity even though vegetation also promotes CH 4 oxidation via changing properties of cover soil and emitting O 2 via root system. The model will be proposed to allow decision makers to reconsider the actual CH 4 emission from vegetated and non-vegetated covered landfills. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Archuleta County

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, San Miguel County, Colorado

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Fremont County, Colorado

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Routt County, Colorado

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled"warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Alamosa and Saguache Counties, Colorado

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Surface Temperature Anomalies Derived from Night Time ASTER Data Corrected for Solar and Topographic Effects, Dolores County

DOE Data Explorer

Khalid Hussein

2012-02-01

This map shows areas of anomalous surface temperature in Alamosa and Saguache Counties identified from ASTER thermal data and spatial based insolation model. The temperature is calculated using the Emissivity Normalization Algorithm that separate temperature from emissivity. The incoming solar radiation was calculated using spatial based insolation model developed by Fu and Rich (1999). Then the temperature due to solar radiation was calculated using emissivity derived from ASTER data. The residual temperature, i.e. temperature due to solar radiation subtracted from ASTER temperature was used to identify thermally anomalous areas. Areas that had temperature greater than 2o were considered ASTER modeled "very warm modeled surface temperature" are shown in red on the map. Areas that had temperatures between 1o and 2o were considered ASTER modeled "warm modeled surface temperature" are shown in yellow on the map. This map also includes the locations of shallow temperature survey points, locations of springs or wells with favorable geochemistry, faults, transmission lines, and areas of modeled basement weakness "fairways." Note: 'o' is used in this description to represent lowercase sigma.

Size distribution and concentrations of heavy metals in atmospheric aerosols originating from industrial emissions as predicted by the HYSPLIT model

NASA Astrophysics Data System (ADS)

Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.

2013-06-01

This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (<0.33, 0.66, 1.3, 2.5, 5, 14, 17, and >17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.

Time trend of polycyclic aromatic hydrocarbon emission factors from motor vehicles

NASA Astrophysics Data System (ADS)

Tao, Shu; Shen, Huizhong; Wang, Rong; Sun, Kang

2010-05-01

Motor vehicle is an important emission source of polycyclic aromatic hydrocarbons (PAHs) and this is particularly true in urban areas. Motor vehicle emission factors (EFs) for individual PAH compound reported in the literature varied for 4 to 5 orders of magnitude, leading to high uncertainty in emission estimation. In this study, the major factors affecting EFs were investigated and characterized by regression models. Based on the model developed, a motor vehicle PAH emission inventory at country level was developed. It was found that country and model year are the most important factors affecting EFs for PAHs. The influence of the two factors can be quantified by a single parameter of per capita gross domestic production (purchasing power parity), which was used as the independent variables of the regression models. The models developed using randomly selected 80% of measurements and tested with the remained data accounted for 28 to 48% of the variations in EFs for PAHs measured in 16 countries over 50 years. The regression coefficients of the EF prediction models were molecular weight dependent. Motor vehicle emission of PAHs from individual countries in the world in 1985, 1995, 2005, 2015, and 2025 were calculated and the global emission of total PAHs were 470, 390, and 430 Gg in 1985, 1995, and 2005 and will be 290 and 130 Gg in 2015 and 2025, respectively. The emission is currently passing its peak and will decrease due to significant decrease in China and other developing countries.

Effects of Changing Emissions on Ozone and Particulates in the Northeastern United States

NASA Astrophysics Data System (ADS)

Frost, G. J.; McKeen, S.; Trainer, M.; Ryerson, T.; Holloway, J.; Brock, C.; Middlebrook, A.; Wollny, A.; Matthew, B.; Williams, E.; Lerner, B.; Fortin, T.; Sueper, D.; Parrish, D.; Fehsenfeld, F.; Peckham, S.; Grell, G.; Peltier, R.; Weber, R.; Quinn, P.; Bates, T.

2004-12-01

Emissions of nitrogen oxides (NOx) from electric power generation have decreased in recent years due to changes in burner technology and fuels used. Mobile NOx emissions assessments are less certain, since they must account for increases in vehicle miles traveled, changes in the proportion of diesel and gasoline vehicles, and more stringent controls on engines and fuels. The impact of these complicated emission changes on a particular region's air quality must be diagnosed by a combination of observation and model simulation. The New England Air Quality Study - Intercontinental Transport and Chemical Transformation 2004 (NEAQS-ITCT 2004) program provides an opportunity to test the effects of changes in emissions of NOx and other precursors on air quality in the northeastern United States. An array of ground, marine, and airborne observation platforms deployed during the study offer checks on emission inventories and air quality model simulations, like those of the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem). Retrospective WRF-Chem runs are carried out with two EPA inventories, one compiled for base year 1999 and an update for 2004 incorporating projected and known changes in emissions during the past 5 years. Differences in model predictions of ozone, particulates, and other tracers using the two inventories are investigated. The inventories themselves and the model simulations are compared with the extensive observations available during NEAQS-ITCT 2004. Preliminary insights regarding the sensitivity of the model to NOx emission changes are discussed.

The Another Assimilation System for WRF-Chem (AAS4WRF): a new mass-conserving emissions pre-processor for WRF-Chem regional modelling

NASA Astrophysics Data System (ADS)

Vara Vela, A. L.; Muñoz, A.; Lomas, A., Sr.; González, C. M.; Calderon, M. G.; Andrade, M. D. F.

2017-12-01

The Weather Research and Forecasting with Chemistry (WRF-Chem) community model have been widely used for the study of pollutants transport, formation of secondary pollutants, as well as for the assessment of air quality policies implementation. A key factor to improve the WRF-Chem air quality simulations over urban areas is the representation of anthropogenic emission sources. There are several tools that are available to assist users in creating their own emissions based on global emissions information (e.g. anthro_emiss, prep_chem_src); however, there is no single tool that will construct local emissions input datasets for any particular domain at this time. Because the official emissions pre-processor (emiss_v03) is designed to work with domains located over North America, this work presents the Another Assimilation System for WRF-Chem (AAS4WRF), a ncl based mass-conserving emissions pre-processor designed to create WRF-Chem ready emissions files from local inventories on a lat/lon projection. AAS4WRF is appropriate to scale emission rates from both surface and elevated sources, providing the users an alternative way to assimilate their emissions to WRF-Chem. Since it was successfully tested for the first time for the city of Lima, Peru in 2014 (managed by SENAMHI, the National Weather Service of the country), several studies on air quality modelling have applied this utility to convert their emissions to those required for WRF-Chem. Two case studies performed in the metropolitan areas of Sao Paulo and Manizales in Brazil and Colombia, respectively, are here presented in order to analyse the influence of using local or global emission inventories in the representation of regulated air pollutants such as O3 and PM2.5. Although AAS4WRF works with local emissions information at the moment, further work is being conducted to make it compatible with global/regional emissions data file format. The tool is freely available upon request to the corresponding author.

Managing CO{sub 2} emissions in Nigeria

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

Obioh, I.B.; Oluwole, A.F.; Akeredolu, F.A.

The energy resources in Nigeria are nearly equally divided between fossil fuels and biofuels. The increasing pressure on them, following expected increased population growth, may lead to substantial emissions of carbon into the atmosphere. Additionally agricultural and forestry management practices in vogue are those related to savannah burning and rotational bush fallow systems, which have been clearly implicated as important sources of CO{sub 2} and trace gases. An integrated model for the prediction of future CO{sub 2} emissions based on fossil fuels and biomass fuels requirements, rates of deforestation and other land-use indices is presented. This is further based onmore » trends in population and economic growth up to the year 2025, with a base year in 1988. A coupled carbon cycle-climate model based on the contribution of CO{sub 2} and other trace gases is established from the proportions of integrated global warming effects for a 20-year averaging time using the product of global warming potential (GWP) and total emissions. An energy-technology inventory approach to optimal resources management is used as a tool for establishing the future scope of reducing the CO{sub 2} emissions through improved fossil fuel energy efficiencies. Scenarios for reduction based on gradual to swift shifts from biomass to fossil and renewable fuels are presented together with expected policy options required to effect them.« less

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.

Latitudinal gradient of nitrous oxide: inferring source distribution from global measurements and model

NASA Astrophysics Data System (ADS)

Ishijima, K.; Kort, E. A.; Crotwell, A. M.; Dlugokencky, E. J.; Patra, P. K.; Tans, P. P.; Wofsy, S. C.

2010-12-01

Nitrous oxide (N2O) plays major role in the earth’s climate system through global warming and stratospheric ozone depletion. Recent observations from the HIPPO (Hiaper Pole to Pole Observations) campaign suggest enhanced N2O concentrations in lower and middle troposphere over tropical latitudes. However, the Atmospheric general circulation model-based Chemistry Transport model (ACTM) failed to simulate such features as in the measured N2O. We confirmed no systematic differences in ACTM and HIPPO latitudinal gradients exist for other long-lived species in the troposphere, e.g., sulfur hexafluoride (SF6), methane (CH4) and carbon dioxide (CO2). Further, we use measurements of all species from discrete samples collected at Earth's surface from NOAA/ESRL's global cooperative air sampling network to identify potential deficiencies in N2O simulations alone, which is unlikely to be arising from model transport error. We find that ACTM simulation is successfully capturing the increase in N2O by ~2 ppb from 30S to 30N, but always overestimate for the latitudes north of 30N. The latitudinal distributions of N2O emissions from all-anthropogenic, natural soil and ocean show the largest anthropogenic emission at 45-60N, which is based on the emission database developed in the 1990s. A net decrease in N2O emission in the mid-/high latitude region might have occurred in the past couple of years or earlier emission inventories overestimated the northern high latitude N2O emission.

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

Cost-effectiveness analysis of policy instruments for greenhouse gas emission mitigation in the agricultural sector.

PubMed

Bakam, Innocent; Balana, Bedru Babulo; Matthews, Robin

2012-12-15

Market-based policy instruments to reduce greenhouse gas (GHG) emissions are generally considered more appropriate than command and control tools. However, the omission of transaction costs from policy evaluations and decision-making processes may result in inefficiency in public resource allocation and sub-optimal policy choices and outcomes. This paper aims to assess the relative cost-effectiveness of market-based GHG mitigation policy instruments in the agricultural sector by incorporating transaction costs. Assuming that farmers' responses to mitigation policies are economically rationale, an individual-based model is developed to study the relative performances of an emission tax, a nitrogen fertilizer tax, and a carbon trading scheme using farm data from the Scottish farm account survey (FAS) and emissions and transaction cost data from literature metadata survey. Model simulations show that none of the three schemes could be considered the most cost effective in all circumstances. The cost effectiveness depends both on the tax rate and the amount of free permits allocated to farmers. However, the emissions trading scheme appears to outperform both other policies in realistic scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Cost-effectiveness of reducing sulfur emissions from ships.

PubMed

Wang, Chengfeng; Corbett, James J; Winebrake, James J

2007-12-15

We model cost-effectiveness of control strategies for reducing SO2 emissions from U.S. foreign commerce ships traveling in existing European or hypothetical U.S. West Coast SO(x) Emission Control Areas (SECAs) under international maritime regulations. Variation among marginal costs of control for individual ships choosing between fuel-switching and aftertreatment reveals cost-saving potential of economic incentive instruments. Compared to regulations prescribing low sulfur fuels, a performance-based policy can save up to $260 million for these ships with 80% more emission reductions than required because least-cost options on some individual ships outperform standards. Optimal simulation of a market-based SO2 control policy for approximately 4,700 U.S. foreign commerce ships traveling in the SECAs in 2002 shows that SECA emissions control targets can be achieved by scrubbing exhaust gas of one out of ten ships with annual savings up to $480 million over performance-based policy. A market-based policy could save the fleet approximately $63 million annually under our best-estimate scenario. Spatial evaluation of ship emissions reductions shows that market-based instruments can reduce more SO2 closer to land while being more cost-effective for the fleet. Results suggest that combining performance requirements with market-based instruments can most effectively control SO2 emissions from ships.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

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

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Picard, Ghislain; Brucker, Ludovic; Roy, Alexandre; DuPont, FLorent; Champollion, Nicolas; Morin, Samuel

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer).

Research on PM2.5 emission reduction path of China ‘s electric power industry based on DEA model

NASA Astrophysics Data System (ADS)

Jin, Yanming; Yang, Fan; Liu, Jun

2018-02-01

Based on the theory of data envelopment analysis, this study constructs the environmental performance evaluation model of the power industry, analyzes the performance of development of clean energy, the implementation of electricity replacement, and the development of coal-fired energy-saving and emission-reducing measures. Put forward technology path to reduce emission in the future. The results show that (1) improving the proportion of coal for power generation, speeding up the replacement of electricity is the key to solve the haze in China. (2) With the photovoltaic and other new energy power generation costs gradually reduced and less limit from thermal energy, by final of “thirteenth five-years plan”, the economy of clean energy will surpass thermal energy-saving emission reduction. (3) After 2025, the economy of the electricity replacement will be able to show.

Methane, carbon dioxide, and nitrous oxide emissions from septic tank systems.

PubMed

Diaz-Valbuena, Libia R; Leverenz, Harold L; Cappa, Christopher D; Tchobanoglous, George; Horwath, William R; Darby, Jeannie L

2011-04-01

Emissions of CH4, CO2, and N2O from conventional septic tank systems are known to occur, but there is a dearth of information as to the extent. Mass emission rates of CH4, CO2, and N2O, as measured with a modified flux chamber approach in eight septic tank systems, were determined to be 11, 33.3, and 0.005 g capita(-1) day(-1), respectively, in this research. Existing greenhouse gas (GHG) emission models based on BOD (biochemical oxygen demand) loading have estimated methane emissions to be as high as 27.1 g CH4 capita(-1) day(-1), more than twice the value measured in our study, and concluded that septic tanks are potentially significant sources of GHGs due to the large number of systems currently in use. Based on the measured CH4 emission value, a revised CH4 conversion factor of 0.22 (compared to 0.5) for use in the emissions models is suggested. Emission rates of CH4, CO2, and N2O were also determined from measurements of gas concentrations and flow rates in the septic vent system and were found to be 10.7, 335, and 0.2 g capita(-1)day(-1), respectively. The excellent agreement in the CH4 emission rates between the flux chamber and the vent values indicates the dominant CH4 source is the septic tank.

Middle East emissions of VOCs estimated using OMI HCHO observations and the MAGRITTE regional model

NASA Astrophysics Data System (ADS)

Müller, Jean-Francois; Stavrakou, Trisevgeni; Bauwens, Maite; De Smedt, Isabelle; Van Roozendael, Michel

2017-04-01

Air quality in the Middle East has considerably deteriorated in the last decades. In particular tropospheric ozone reaches very high levels during summer due to the combination of high solar irradiances with often very high and rapidly evolving anthropogenic emissions of NOx and VOCs associated to oil/gas exploitation and fast urbanisation. In addition, high biogenic VOC emissions are expected in non-desert areas, in particular during summer due to scorching temperatures and high solar irradiances. Both anthropogenic and biogenic VOC emissions are poorly known, however, due to near-absence of experimental constraints on emission factors for local vegetation and industrial and extraction processes. Furthermore, the dependence of emissions on environmental conditions (e.g. soil moisture in the case of biogenic isoprene emissions) is only very crudely parameterized in emission models. Here we use spaceborne (OMI) observations of formaldehyde, a known product of anthropogenic and biogenic VOC oxidation, as constraint in an inversion framework built on a regional model, MAGRITTE (Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace Gas Emissions). MAGRITTE is run at 0.5x0.5 degree resolution, with lateral boundary conditions provided by the global CTM IMAGESv2 (Bauwens et al., 2016). The global and regional models share essentially the same chemistry and physical parameterizations. Emission inversion with MAGRITTE is performed using an adjoint-based iterative procedure, similar to previous inversions using IMAGES. Biogenic VOC emissions are calculated using MEGAN (Muller et al., 2008; Stavrakou et al., 2015), whereas the HTAPv2 emission dataset is used for anthropogenic emissions, with several adjustments for oil/gas exploitation and traffic emissions. The OMI data are regridded onto the model resolution and averaged seasonally in order to reduce noise. Preliminary results indicate that biogenic isoprene emissions are a major VOC source in summertime throughout the "Fertile Crescent" from the Nile Valley to Iraq. Anthropogenic emissions from many large cities (e.g. Bagdad and Cairo) as well as from known oil extraction/refining/handling sites are well detected, while other cities (such as Riyadh) are elusive.

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.

Evaluating environmental modeling and sampling data with biomarker data to identify sources and routes of exposure

NASA Astrophysics Data System (ADS)

Shin, Hyeong-Moo; McKone, Thomas E.; Bennett, Deborah H.

2013-04-01

Exposure to environmental chemicals results from multiple sources, environmental media, and exposure routes. Ideally, modeled exposures should be compared to biomonitoring data. This study compares the magnitude and variation of modeled polycyclic aromatic hydrocarbons (PAHs) exposures resulting from emissions to outdoor and indoor air and estimated exposure inferred from biomarker levels. Outdoor emissions result in both inhalation and food-based exposures. We modeled PAH intake doses using U.S. EPA's 2002 National Air Toxics Assessment (NATA) county-level emissions data for outdoor inhalation, the CalTOX model for food ingestion (based on NATA emissions), and indoor air concentrations from field studies for indoor inhalation. We then compared the modeled intake with the measured urine levels of hydroxy-PAH metabolites from the 2001-2002 National Health and Nutrition Examination Survey (NHANES) survey as quantifiable human intake of PAH parent-compounds. Lognormal probability plots of modeled intakes and estimated intakes inferred from biomarkers suggest that a primary route of exposure to naphthalene, fluorene, and phenanthrene for the U.S. population is likely inhalation from indoor sources. For benzo(a)pyrene, the predominant exposure route is likely from food ingestion resulting from multi-pathway transport and bioaccumulation due to outdoor emissions. Multiple routes of exposure are important for pyrene. We also considered the sensitivity of the predicted exposure to the proportion of the total naphthalene production volume emitted to the indoor environment. The comparison of PAH biomarkers with exposure variability estimated from models and sample data for various exposure pathways supports that both indoor and outdoor models are needed to capture the sources and routes of exposure to environmental contaminants.

Emirates Mars Ultraviolet Spectrometer's (EMUS) Prediction of Oxygen OI 135.6 nm and CO 4PG Emissions in the Martian Atmosphere

NASA Astrophysics Data System (ADS)

Almatroushi, H. R.; Lootah, F. H.; Deighan, J.; Fillingim, M. O.; Jain, S.; Bougher, S. W.; England, S.; Schneider, N. M.

2017-12-01

This research focuses on developing empirical and theoretical models for OI 135.6 nm and CO 4PG band system FUV dayglow emissions in the Martian thermosphere as predicted to be seen from the Emirates Mars Ultraviolet Spectrometer (EMUS), one of the three scientific instruments aboard the Emirates Mars Mission (EMM) to be launched in 2020. These models will aid in simulating accurate disk radiances which will be utilized as an input to an EMUS instrument simulator. The developed zonally averaged empirical models are based on FUV data from the IUVS instrument onboard the MAVEN mission, while the theoretical models are based on a basic Chapman profile. The models calculate the brightness (B) of those emissions taking into consideration observation geometry parameters such as emission angle (EA), solar zenith angle (SZA) and planet distance from the sun (Ds). Specifically, the empirical models takes a general form of Bn=A*cos(SZA)n/cos(EA)m , where Bn is the normalized brightness value of an emission feature, and A, n, and m are positive constant values. The model form shows that the brightness has a positive correlation with EA and a negative correlation with SZA. A comparison of both models are explained in this research while examining full Mars and half Mars disk images generated using geometry code specially developed for the EMUS instrument. Sensitivity analyses have also been conducted for the theoretical modeling to observe the contributions of electron impact on atomic oxygen and CO2 to the brightness of OI 135.6nm, in addition to the effect of electron temperature on the CO2± dissociative recombination contribution to the CO 4PG band system.

Carbon dioxide emission prediction using support vector machine

NASA Astrophysics Data System (ADS)

Saleh, Chairul; Rachman Dzakiyullah, Nur; Bayu Nugroho, Jonathan

2016-02-01

In this paper, the SVM model was proposed for predict expenditure of carbon (CO2) emission. The energy consumption such as electrical energy and burning coal is input variable that affect directly increasing of CO2 emissions were conducted to built the model. Our objective is to monitor the CO2 emission based on the electrical energy and burning coal used from the production process. The data electrical energy and burning coal used were obtained from Alcohol Industry in order to training and testing the models. It divided by cross-validation technique into 90% of training data and 10% of testing data. To find the optimal parameters of SVM model was used the trial and error approach on the experiment by adjusting C parameters and Epsilon. The result shows that the SVM model has an optimal parameter on C parameters 0.1 and 0 Epsilon. To measure the error of the model by using Root Mean Square Error (RMSE) with error value as 0.004. The smallest error of the model represents more accurately prediction. As a practice, this paper was contributing for an executive manager in making the effective decision for the business operation were monitoring expenditure of CO2 emission.

Environmental assessment of biofuel chains based on ecosystem modelling, including land-use change effects

NASA Astrophysics Data System (ADS)

Gabrielle, B.; Gagnaire, N.; Massad, R.; Prieur, V.; Python, Y.

2012-04-01

The potential greenhouse gas (GHG) savings resulting from the displacement of fossil energy sources by bioenergy mostly hinges on the uncertainty on the magnitude of nitrous oxide (N2O) emissions from arable soils occuring during feedstock production. These emissions are broadly related to fertilizer nitrogen input rates, but largely controlled by soil and climate factors which makes their estimation highly uncertain. Here, we set out to improve estimates of N2O emissions from bioenergy feedstocks by using ecosystem models and measurements and modeling of atmospheric N2O in the greater Paris (France) area. Ground fluxes were measured in two locations to assess the effect of soil type and management, crop type (including lignocellulosics such as triticale, switchgrass and miscanthus), and climate on N2O emission rates and dynamics. High-resolution maps of N2O emissions were generated over the Ile-de-France region (around Paris) with two ecosystem models using geographical databases on soils, weather data, land-use and crop management. The models were tested against ground flux measurements and the emission maps were fed into the atmospheric chemistry-transport model CHIMERE. The maps were tested by comparing the CHIMERE simulations with time series of N2O concentrations measured at various heights above the ground in two locations in 2007. The emissions of N2O, as integrated over the region, were used in a life-cycle assessment of representative biofuel pathways: bioethanol from wheat and sugar-beet (1st generation), and miscanthus (2nd generation chain); bio-diesel from oilseed rape. Effects related to direct and indirect land-use changes (in particular on soil carbon stocks) were also included in the assessment based on various land-use scenarios and literature references. The potential deployment of miscanthus was simulated by assuming it would be grown on the current sugar-beet growing area in Ile-de-France, or by converting land currently under permanent fallow. Compared to the standard methodology currently used in LCA, based on fixed emissions for N2O, the use of model-derived estimates leads to a 10 to 40% reduction in the overall life-cycle GHG emissions of biofuels. This emphasizes the importance of regional factors in the relationship between agricultural inputs and emissions (altogether with biomass yields) in the outcome of LCAs. When excluding indirect land-use change effects (iLUC), 1st generation pathways enabled GHG savings ranging from 50 to 73% compared to fossile-derived equivalents, while this figure reached 88% for 2nd generation bioethanol from miscanthus. Including iLUC reduced the savings to less than 5% for bio-diesel from rapeseed, 10 to 45% for 1st generation bioethanol and to 60% for miscanthus. These figures apply to the year 2007 and should be extended to a larger number of years, but the magnitude of N2O emissions was similar between 2007, 2008 and 2009 over the Ile de France region.

LandscapeDNDC used to model nitrous oxide emissions from soils under an oak forest in southern England

NASA Astrophysics Data System (ADS)

Cade, Shirley; Clemitshaw, Kevin; Lowry, David; Yamulki, Sirwan; Casella, Eric; Molina, Saul; Haas, Edwin; Kiese, Ralf

2013-04-01

Nitrous oxide (N2O) is an important greenhouse gas, having a global warming potential of approximately 300 times that of carbon dioxide (CO2), and plays a significant role in depleting stratospheric ozone. Its principal source is microbial activity in soils and waters. Measured values of N2O emissions from soils show high temporal dynamics and a large range as a result of inter-related physico-chemical factors affecting the microbial processes, thus making predictions difficult. Emissions often occur in pulses following re-wetting, frost-thaw or management events such as N-fertilization, which further complicates predictions. Process-based models have been developed to help understand this emission variability and as potential tools for IPCC Tier 3 reporting on national emission inventories. Forests are promoted as sinks for CO2 and can be used as renewable sources of energy or longer term CO2 storage if timber is used in products such as in construction and furniture, provided appropriate replanting takes place. It is important that the effect of any changes in forest management and land use as a result of a desire to reduce CO2 emissions does not increase N2O emissions from forest soils, which are still poorly understood, compared to agricultural soils. LandscapeDNDC (Haas et al 2012) has been developed as a process-oriented model, based on the biogeochemical model, DNDC (Li et al, 1992), in order to simulate biosphere-atmosphere-hydrosphere exchanges at site and regional scales. It can model the carbon and nitrogen turnover and associated greenhouse gas (GHG) emissions of forest, agricultural and grassland ecosystems, and allows modelling of impacts of regional land use change over time. This study uses data (including forest growth, GHG emissions and soil moisture) from an oak forest, known as the Straits Enclosure, at Alice Holt in Hampshire, where extensive measurements have been made by Forest Research since 1995. It involves validation of the site scale model and internal parameters of LandscapeDNDC for use with an oak forest in SE England and as a result facilitates the broadening of its application. Modelled N2O soil emissions are compared with measurements from soil chambers in the forest. HAAS, E., KLATT, S., FRÖHLICH, A., KRAFT, P., WERNER, C., KIESE, R., GROTE, R., BREUER, L. and BUTTERBACH-BAHL, K., 2012. LandscapeDNDC: a process model for simulation of biosphere-atmosphere-hydrosphere exchange processes at site and regional scale. Landscape Ecology, , pp. 1-22. LI, C., FROLKING, S. and FROLKING, T.A., 1992. A model of nitrous oxide evolution from soil driven by rainfall events: 1. Model structure and sensitivity. J.Geophys.Res, 97(D9), pp. 9759-9776.

Global time trends in PAH emissions from motor vehicles

PubMed Central

Shen, Huizhong; Tao, Shu; Wang, Rong; Wang, Bin; Shen, Guofeng; Li, Wei; Su, Shenshen; Huang, Ye; Wang, Xilong; Liu, Wenxin; Li, Bengang; Sun, Kang

2013-01-01

Emission from motor vehicles is the most important source of polycyclic aromatic hydrocarbons (PAHs) in urban areas. Emission factors of individual PAHs for motor vehicles reported in the literature varied 4 to 5 orders of magnitude, leading to high uncertainty in emission inventory. In this study, key factors affecting emission factors of PAHs (EFPAH) for motor vehicles were evaluated quantitatively based on thousands of EFPAH measured in 16 countries for over 50 years. The result was used to develop a global emission inventory of PAHs from motor vehicles. It was found that country and vehicle model year are the most important factors affecting EFPAH, which can be quantified using a monovariate regression model with per capita gross domestic production (purchasing power parity) as a sole independent variable. On average, 29% of variation in log-transformed EFPAH could be explained by the model, which was equivalent to 90% reduction in overall uncertainty on arithmetic scale. The model was used to predict EFPAH and subsequently PAH emissions from motor vehicles for various countries in the world during a period from 1971 to 2030. It was estimated that the global emission reached its peak value of approximate 101 Gg in 1978 and decreased afterwards due to emission control in developed countries. The annual emission picked up again since 1990 owing to accelerated energy consumption in China and other developing countries. With more and more rigid control measures taken in the developing world, global emission of PAHs is currently passing its second peak. It was predicted that the emission would decrease from 77 Gg in 2010 to 42 Gg in 2030. PMID:24198716

Consumption-based Total Suspended Particulate Matter Emissions in Jing-Jin-Ji Area of China

NASA Astrophysics Data System (ADS)

Yang, S.; Chen, S.; Chen, B.

2014-12-01

The highly-industrialized regions in China have been facing a serious problem of haze mainly consisted of total suspended particulate matter (TSPM), which has attracted great attention from the public since it directly impairs human health and clinically increases the risks of various respiratory and pulmonary diseases. In this paper, we set up a multi-regional input-output (MRIO) model to analyze the transferring routes of TSPM emissions between regions through trades. TSPM emission from particulate source regions and sectors are identified by analyzing the embodied TSPM flows through monetary flow and carbon footprint. The track of TSPM from origin to end via consumption activities are also revealed by tracing the product supply chain associated with the TSPM emissions. Beijing-Tianjin-Hebei (Jing-Jin-Ji) as the most industrialized area of China is selected for a case study. The result shows that over 70% of TSPM emissions associated with goods consumed in Beijing and Tianjin occurred outside of their own administrative boundaries, implying that Beijing and Tianjin are net embodied TSPM importers. Meanwhile, 63% of the total TSPM emissions in Hebei Province are resulted from the outside demand, indicating Hebei is a net exporter. In addition, nearly half of TSPM emissions are the by-products related to electricity and heating supply and non-metal mineral products in Jing-Jin-Ji Area. Based on the model results, we provided new insights into establishing systemic strategies and identifying mitigation priorities to stem TSPM emissions in China. Keywords: total suspended particulate matter (TSPM); urban ecosystem modeling; multi-regional input-output (MRIO); China

Predicting gaseous emissions from small-scale combustion of agricultural biomass fuels.

PubMed

Fournel, S; Marcos, B; Godbout, S; Heitz, M

2015-03-01

A prediction model of gaseous emissions (CO, CO2, NOx, SO2 and HCl) from small-scale combustion of agricultural biomass fuels was developed in order to rapidly assess their potential to be burned in accordance to current environmental threshold values. The model was established based on calculation of thermodynamic equilibrium of reactive multicomponent systems using Gibbs free energy minimization. Since this method has been widely used to estimate the composition of the syngas from wood gasification, the model was first validated by comparing its prediction results with those of similar models from the literature. The model was then used to evaluate the main gas emissions from the combustion of four dedicated energy crops (short-rotation willow, reed canary grass, switchgrass and miscanthus) previously burned in a 29-kW boiler. The prediction values revealed good agreement with the experimental results. The model was particularly effective in estimating the influence of harvest season on SO2 emissions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Contribution of ship emissions to the concentration and deposition of air pollutants in Europe

NASA Astrophysics Data System (ADS)

Aksoyoglu, Sebnem; Baltensperger, Urs; Prévôt, André S. H.

2016-02-01

Emissions from the marine transport sector are one of the least-regulated anthropogenic emission sources and contribute significantly to air pollution. Although strict limits were introduced recently for the maximum sulfur content in marine fuels in the SECAs (sulfur emission control areas) and in EU ports, sulfur emissions outside the SECAs and emissions of other components in all European maritime areas have continued to increase in the last two decades. We have used the air quality model CAMx (Comprehensive Air Quality Model with Extensions) with and without ship emissions for the year 2006 to determine the effects of international shipping on the annual as well as seasonal concentrations of ozone, primary and secondary components of PM2.5, and the dry and wet deposition of nitrogen and sulfur compounds in Europe. The largest changes in pollutant concentrations due to ship emissions were predicted for summer. Concentrations of particulate sulfate increased due to ship emissions in the Mediterranean (up to 60 %), the English Channel and the North Sea (30-35 %), while increases in particulate nitrate levels were found especially in the north, around the Benelux area (20 %), where there were high NH3 land-based emissions. Our model results showed that not only are the atmospheric concentrations of pollutants affected by ship emissions, but also depositions of nitrogen and sulfur compounds increase significantly along the shipping routes. NOx emissions from the ships, especially in the English Channel and the North Sea, cause a decrease in the dry deposition of reduced nitrogen at source regions by moving it from the gas phase to the particle phase which then contributes to an increase in the wet deposition at coastal areas with higher precipitation. In the western Mediterranean region, on the other hand, model results show an increase in the deposition of oxidized nitrogen (mostly HNO3) due to the ship traffic. Dry deposition of SO2 seems to be significant along the shipping routes, whereas sulfate wet deposition occurs mainly along the Scandinavian and Adriatic coasts. The results presented in this paper suggest that evolution of NOx emissions from ships and land-based NH3 emissions will play a significant role in future European air quality.

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

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.

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.

The air quality and regional climate effects of widespread solar power generation under a changing regulatory environment

NASA Astrophysics Data System (ADS)

Millstein, D.; Zhai, P.; Menon, S.

2011-12-01

Over the past decade significant reductions of NOx and SOx emissions from coal burning power plants in the U.S. have been achieved due to regulatory action and substitution of new generation towards natural gas and wind power. Low natural gas prices, ever decreasing solar generation costs, and proposed regulatory changes, such as to the Cross State Air Pollution Rule, promise further long-run coal power plant emission reductions. Reduced power plant emissions have the potential to affect ozone and particulate air quality and influence regional climate through aerosol cloud interactions and visibility effects. Here we investigate, on a national scale, the effects on future (~2030) air quality and regional climate of power plant emission regulations in contrast to and combination with policies designed to aggressively promote solar electricity generation. A sophisticated, economic and engineering based, hourly power generation dispatch model is developed to explore the integration of significant solar generation resources (>10% on an energy basis) at various regions across the county, providing detailed estimates of substitution of solar generation for fossil fuel generation resources. Future air pollutant emissions from all sectors of the economy are scaled based on the U.S. Environmental Protection Agency's National Emission Inventory to account for activity changes based on population and economic projections derived from county level U.S. Census data and the Energy Information Administration's Annual Energy Outlook. Further adjustments are made for technological and regulatory changes applicable within various sectors, for example, emission intensity adjustments to on-road diesel trucking due to exhaust treatment and improved engine design. The future year 2030 is selected for the emissions scenarios to allow for the development of significant solar generation resources. A regional climate and air quality model (Weather Research and Forecasting, WRF model) is used to investigate the effects of the various solar generation scenarios given emissions projections that account for changing regulatory environment, economic and population growth, and technological change. The results will help to quantify the potential air quality benefits of promotion of solar electricity generation in regions containing high penetration of coal-fired power generation. Note current national solar incentives that are based only on solar generation capacity. Further investigation of changes to regional climate due to emission reductions of aerosols and relevant precursors will provide insight into the environmental effects that may occur if solar power generation becomes widespread.

Policy design and performance of emissions trading markets: an adaptive agent-based analysis.

PubMed

Bing, Zhang; Qinqin, Yu; Jun, Bi

2010-08-01

Emissions trading is considered to be a cost-effective environmental economic instrument for pollution control. However, the pilot emissions trading programs in China have failed to bring remarkable success in the campaign for pollution control. The policy design of an emissions trading program is found to have a decisive impact on its performance. In this study, an artificial market for sulfur dioxide (SO2) emissions trading applying the agent-based model was constructed. The performance of the Jiangsu SO2 emissions trading market under different policy design scenario was also examined. Results show that the market efficiency of emissions trading is significantly affected by policy design and existing policies. China's coal-electricity price system is the principal factor influencing the performance of the SO2 emissions trading market. Transaction costs would also reduce market efficiency. In addition, current-level emissions discharge fee/tax and banking mechanisms do not distinctly affect policy performance. Thus, applying emissions trading in emission control in China should consider policy design and interaction with other existing policies.

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 emission module for ICON-ART 2.0: implementation and simulations of acetone

NASA Astrophysics Data System (ADS)

Weimer, Michael; Schröter, Jennifer; Eckstein, Johannes; Deetz, Konrad; Neumaier, Marco; Fischbeck, Garlich; Hu, Lu; Millet, Dylan B.; Rieger, Daniel; Vogel, Heike; Vogel, Bernhard; Reddmann, Thomas; Kirner, Oliver; Ruhnke, Roland; Braesicke, Peter

2017-06-01

We present a recently developed emission module for the ICON (ICOsahedral Non-hydrostatic)-ART (Aerosols and Reactive Trace gases) modelling framework. The emission module processes external flux data sets and increments the tracer volume mixing ratios in the boundary layer accordingly. The performance of the emission module is illustrated with simulations of acetone, using a simplified chemical depletion mechanism based on a reaction with OH and photolysis only. In our model setup, we calculate a tropospheric acetone lifetime of 33 days, which is in good agreement with the literature. We compare our results with ground-based as well as with airborne IAGOS-CARIBIC measurements in the upper troposphere and lowermost stratosphere (UTLS) in terms of phase and amplitude of the annual cycle. In all our ICON-ART simulations the general seasonal variability is well represented but uncertainties remain concerning the magnitude of the acetone mixing ratio in the UTLS region. In addition, the module for online calculations of biogenic emissions (MEGAN2.1) is implemented in ICON-ART and can replace the offline biogenic emission data sets. In a sensitivity study we show how different parametrisations of the leaf area index (LAI) change the emission fluxes calculated by MEGAN2.1 and demonstrate the importance of an adequate treatment of the LAI within MEGAN2.1. We conclude that the emission module performs well with offline and online emission fluxes and allows the simulation of the annual cycles of emissions-dominated substances.

Modeling and simulation of a beam emission spectroscopy diagnostic for the ITER prototype neutral beam injector

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

Barbisan, M., E-mail: marco.barbisan@igi.cnr.it; Zaniol, B.; Pasqualotto, R.

2014-11-15

A test facility for the development of the neutral beam injection system for ITER is under construction at Consorzio RFX. It will host two experiments: SPIDER, a 100 keV H{sup −}/D{sup −} ion RF source, and MITICA, a prototype of the full performance ITER injector (1 MV, 17 MW beam). A set of diagnostics will monitor the operation and allow to optimize the performance of the two prototypes. In particular, beam emission spectroscopy will measure the uniformity and the divergence of the fast particles beam exiting the ion source and travelling through the beam line components. This type of measurementmore » is based on the collection of the H{sub α}/D{sub α} emission resulting from the interaction of the energetic particles with the background gas. A numerical model has been developed to simulate the spectrum of the collected emissions in order to design this diagnostic and to study its performance. The paper describes the model at the base of the simulations and presents the modeled H{sub α} spectra in the case of MITICA experiment.« less

Two-component Thermal Dust Emission Model: Application to the Planck HFI Maps

NASA Astrophysics Data System (ADS)

Meisner, Aaron M.; Finkbeiner, Douglas P.

2014-06-01

We present full-sky, 6.1 arcminute resolution maps of dust optical depth and temperature derived by fitting the Finkbeiner et al. (1999) two-component dust emission model to the Planck HFI and IRAS 100 micron maps. This parametrization of the far infrared thermal dust SED as the sum of two modified blackbodies serves as an important alternative to the commonly adopted single modified blackbody dust emission model. We expect our Planck-based maps of dust temperature and optical depth to form the basis for a next-generation, high-resolution extinction map which will additionally incorporate small-scale detail from WISE imaging.

Identification and elucidation of anthropogenic source contribution in PM10 pollutant: Insight gain from dispersion and receptor models.

PubMed

Roy, Debananda; Singh, Gurdeep; Yadav, Pankaj

2016-10-01

Source apportionment study of PM 10 (Particulate Matter) in a critically polluted area of Jharia coalfield, India has been carried out using Dispersion model, Principle Component Analysis (PCA) and Chemical Mass Balance (CMB) techniques. Dispersion model Atmospheric Dispersion Model (AERMOD) was introduced to simplify the complexity of sources in Jharia coalfield. PCA and CMB analysis indicates that monitoring stations near the mining area were mainly affected by the emission from open coal mining and its associated activities such as coal transportation, loading and unloading of coal. Mine fire emission also contributed a considerable amount of particulate matters in monitoring stations. Locations in the city area were mostly affected by vehicular, Liquid Petroleum Gas (LPG) & Diesel Generator (DG) set emissions, residential, and commercial activities. The experimental data sampling and their analysis could aid understanding how dispersion based model technique along with receptor model based concept can be strategically used for quantitative analysis of Natural and Anthropogenic sources of PM 10 . Copyright © 2016. Published by Elsevier B.V.

The generation of amplified spontaneous emission in high-power CPA laser systems.

PubMed

Keppler, Sebastian; Sävert, Alexander; Körner, Jörg; Hornung, Marco; Liebetrau, Hartmut; Hein, Joachim; Kaluza, Malte Christoph

2016-03-01

An analytical model is presented describing the temporal intensity contrast determined by amplified spontaneous emission in high-intensity laser systems which are based on the principle of chirped pulse amplification. The model describes both the generation and the amplification of the amplified spontaneous emission for each type of laser amplifier. This model is applied to different solid state laser materials which can support the amplification of pulse durations ≤350 fs . The results are compared to intensity and fluence thresholds, e.g. determined by damage thresholds of a certain target material to be used in high-intensity applications. This allows determining if additional means for contrast improvement, e.g. plasma mirrors, are required for a certain type of laser system and application. Using this model, the requirements for an optimized high-contrast front-end design are derived regarding the necessary contrast improvement and the amplified "clean" output energy for a desired focussed peak intensity. Finally, the model is compared to measurements at three different high-intensity laser systems based on Ti:Sapphire and Yb:glass. These measurements show an excellent agreement with the model.

Diffusion-controlled reference material for VOC emissions testing: proof of concept.

PubMed

Cox, S S; Liu, Z; Little, J C; Howard-Reed, C; Nabinger, S J; Persily, A

2010-10-01

Because of concerns about indoor air quality, there is growing awareness of the need to reduce the rate at which indoor materials and products emit volatile organic compounds (VOCs). To meet consumer demand for low emitting products, manufacturers are increasingly submitting materials to independent laboratories for emissions testing. However, the same product tested by different laboratories can result in very different emissions profiles because of a general lack of test validation procedures. There is a need for a reference material that can be used as a known emissions source and that will have the same emission rate when tested by different laboratories under the same conditions. A reference material was created by loading toluene into a polymethyl pentene film. A fundamental emissions model was used to predict the toluene emissions profile. Measured VOC emissions profiles using small-chamber emissions tests compared reasonably well to the emissions profile predicted using the emissions model, demonstrating the feasibility of the proposed approach to create a diffusion-controlled reference material. To calibrate emissions test chambers and improve the reproducibility of VOC emission measurements among different laboratories, a reference material has been created using a polymer film loaded with a representative VOC. Initial results show that the film's VOC emission profile measured in a conventional test chamber compares well to predictions based on independently determined material/chemical properties and a fundamental emissions model. The use of such reference materials has the potential to build consensus and confidence in emissions testing as well as 'level the playing field' for product testing laboratories and manufacturers.

Comparison of Greenhouse Gas Emissions between Two Dairy Farm Systems (Conventional vs. Organic Management) in New Hampshire Using the Manure DNDC Biogeochemical Model

NASA Astrophysics Data System (ADS)

Dorich, C.; Contosta, A.; Li, C.; Brito, A.; Varner, R. K.

2013-12-01

Agriculture contributes 20 to 25 % of the total anthropogenic greenhouse gas (GHG) emissions globally. These agricultural emissions are primarily in the form of methane (CH4) and nitrous oxide (N2O) with these GHG accounting for roughly 40 and 80 % of the total anthropogenic emissions of CH4 and N2O, respectively. Due to varied management and the complexities of agricultural ecosystems, it is difficult to estimate these CH4 and N2O emissions. The IPCC emission factors can be used to yield rough estimates of CH4 and N2O emissions but they are often based on limited data. Accurate modeling validated by measurements is needed in order to identify potential mitigation areas, reduce GHG emissions from agriculture, and improve sustainability of farming practices. The biogeochemical model Manure DNDC was validated using measurements from two dairy farms in New Hampshire, USA in order to quantify GHG emissions under different management systems. One organic and one conventional dairy farm operated by the University of New Hampshire's Agriculture Experiment Station were utilized as the study sites for validation of Manure DNDC. Compilation of management records started in 2011 to provide model inputs. Model results were then compared to field collected samples of soil carbon and nitrogen, above-ground biomass, and GHG fluxes. Fluxes were measured in crop, animal, housing, and waste management sites on the farms in order to examine the entire farm ecosystem and test the validity of the model. Fluxes were measured by static flux chambers, with enteric fermentation measurements being conducted by the SF6 tracer test as well as a new method called Greenfeeder. Our preliminary GHG flux analysis suggests higher emissions than predicted by IPCC emission factors and equations. Results suggest that emissions from manure management is a key concern at the conventional dairy farm while bedded housing at the organic dairy produced large quantities of GHG.

Indirect estimation of emission factors for phosphate surface mining using air dispersion modeling.

PubMed

Tartakovsky, Dmitry; Stern, Eli; Broday, David M

2016-06-15

To date, phosphate surface mining suffers from lack of reliable emission factors. Due to complete absence of data to derive emissions factors, we developed a methodology for estimating them indirectly by studying a range of possible emission factors for surface phosphate mining operations and comparing AERMOD calculated concentrations to concentrations measured around the mine. We applied this approach for the Khneifiss phosphate mine, Syria, and the Al-Hassa and Al-Abyad phosphate mines, Jordan. The work accounts for numerous model unknowns and parameter uncertainties by applying prudent assumptions concerning the parameter values. Our results suggest that the net mining operations (bulldozing, grading and dragline) contribute rather little to ambient TSP concentrations in comparison to phosphate processing and transport. Based on our results, the common practice of deriving the emission rates for phosphate mining operations from the US EPA emission factors for surface coal mining or from the default emission factor of the EEA seems to be reasonable. Yet, since multiple factors affect dispersion from surface phosphate mines, a range of emission factors, rather than only a single value, was found to satisfy the model performance. Copyright © 2016 Elsevier B.V. All rights reserved.

HST FGS1R Results On the Association Between Binary Wolf-Rayet Stars and Non-Thermal Radio Emission

NASA Astrophysics Data System (ADS)

Wallace, D. J.; Gies, D. R.; Nelan, E.; Leitherer, C.

2000-12-01

Two separate models have been proposed to explain the non-thermal emission detected in some Wolf-Rayet (WR) stars. In models based on single WR stars, this emission is proposed to arise via synchrotron radiative processes in the outer (intrinsically unstable) WR wind (e.g. White & Chen 1995). In models based on WR + O systems, this non-thermal radio emission is suggested to arise from the WR wind colliding with the wind of a companion (e.g. Williams et al. 1990). In order to be observed, the colliding winds region is believed to occur in wide binaries where the interaction zone is outside the WR radio photosphere (≈30 AU based on spherically symmetric uniform wind models). HST FGS1R observations of 9 non-thermal and 9, as a control group, purely thermal radio emitting stars attempted to verify the theory that this non-thermal emission is always a result of binary interactions. If the binary model is correct, then most or all of our non-thermal targets should have companions with projected separations of 0.01″

Emission factors of SO2, NOx and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling

NASA Astrophysics Data System (ADS)

Beecken, J.; Mellqvist, J.; Salo, K.; Ekholm, J.; Jalkanen, J.-P.; Johansson, L.; Litvinenko, V.; Volodin, K.; Frank-Kamenetsky, D. A.

2015-05-01

Emission factors of SO2, NOx and size-distributed particle numbers were measured for approximately 300 different ships in the Gulf of Finland and Neva Bay area during two campaigns in August/September 2011 and June/July 2012. The measurements were carried out from a harbor vessel and from an Mi-8 helicopter downwind of passing ships. Other measurements were carried out from shore sites near the island of Kronstadt and along the Neva River in the urban area of Saint Petersburg. Most ships were running at reduced speed (10 kn), i.e., not at their optimal load. Vessels for domestic and international shipping were monitored. It was seen that the distribution of the SO2 emission factors is bi-modal, with averages of 4.6 and 18.2 gSO2 kgfuel-1 for the lower and the higher mode, respectively. The emission factors show compliance with the 1% fuel sulfur content Sulfur Emission Control Areas (SECA) limit for 90% of the vessels in 2011 and 97% in 2012. The distribution of the NOx emission factor is mono-modal, with an average of 58 gNOx kgfuel-1. The corresponding emission related to the generated power yields an average of 12.1 gNOx kWh-1. The distribution of the emission factors for particulate number shows that nearly 90% of all particles in the 5.6 nm to 10 μm size range were below 70 nm in diameter. The distribution of the corresponding emission factors for the mass indicates two separated main modes, one for particles between 30 and 300 nm and the other for above 2 μm. The average particle emission factors were found to be in the range from 0.7 to 2.7 × 1016 particles kgfuel-1 and 0.2 to 3.4 gPM kgfuel-1, respectively. The NOx and particulate emissions are comparable with other studies. The measured emission factors were compared, for individual ships, to modeled ones using the Ship Traffic Emission Assessment Model (STEAM) of the Finnish Meteorological Institute. A reasonably good agreement for gaseous sulfur and nitrogen emissions can be seen for ships in international traffic, but significant deviations are found for inland vessels. Regarding particulate mass, the values of the modeled data are about 2-3 times higher than the measured results, which probably reflects the assumptions made in the modeled fuel sulfur content. The sulfur contents in the fuel retrieved from the measurements were lower than the previously used assumptions by the City of Saint Petersburg when carrying out atmospheric modeling, and using these measurements it was possible to better assess the impact of shipping on air quality.

GOSAT Observations of Anthropogenic Emission of Carbon Dioxide and Methane

NASA Astrophysics Data System (ADS)

Janardanan Achari, R.; Maksyutov, S. S.; Oda, T.; Saito, M.; W Kaiser, J.; Ganshin, A.; Matsunaga, T.; Yoshida, Y.; Yokota, T.

2016-12-01

Carbon dioxide (CO2) and methane (CH4) are the most important greenhouse gases in terms of radiative forcing. Anthropogenic activities such as combustion of fossil fuel (for CO2) and gas leakage, animal agriculture, rice cultivation and landfill emissions (CH4), are considered to be major sources of those emissions. Still, emission data usually depend on national emission reports, which are seldom evaluated independently. Here we present a method for delineating anthropogenic contribution to global atmospheric CO2 (2009-2014) and CH4 (2009-2012) fields using GOSAT observations of column-average dry air mole fractions (XCO2 and XCH4) and atmospheric transport model simulations using high-resolution emission inventories. The CO2 and CH4 concentration enhancement due to anthropogenic activities, are estimated with the transport model at all GOSAT observation locations using high-resolution emission inventories (ODIAC for CO2 and EDGAR for CH4). Based on this estimate, using a threshold value, the observations are classified into two categories: data influenced by the anthropogenic sources and those not including them. To extract concentration enhancements due to the anthropogenic emissions, we define a clean background (the averaged values for the data free from contamination) in 10°×10° regions over the globe and are subtracted from the individual observational data including the anthropogenic contamination. Thus the anomalies contain contributions from anthropogenic sources. These anomalies are binned and analyzed for continental scale regions and 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 comparable in magnitude to the reported uncertainties in emission inventories in that region. In the case of CH4, we also found a good match between inventory-based estimates and GOSAT observations for continental regions and large countries. In ideal case, the regression slope between modeled and observed anomalies can be a correction factor for the emission inventory. If sufficient number of satellite observations is available, this method will be a useful tool for monitoring greenhouse gas emissions.

A unifying conceptual model for the environmental responses of isoprene emissions from plants.

PubMed

Morfopoulos, Catherine; Prentice, Iain C; Keenan, Trevor F; Friedlingstein, Pierre; Medlyn, Belinda E; Peñuelas, Josep; Possell, Malcolm

2013-11-01

Isoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle. A simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed. The model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity. A simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission.

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.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

NASA Astrophysics Data System (ADS)

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; Church, Sarah E.; Wechsler, Risa H.

2017-09-01

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN-halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for our fiducial model, which is based on current understanding of the galaxy-halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

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

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small for ourmore » fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

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

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

On Estimation of Contamination from Hydrogen Cyanide in Carbon Monoxide Line-intensity Mapping

DOE PAGES

Chung, Dongwoo T.; Li, Tony Y.; Viero, Marco P.; ...

2017-08-31

Here, line-intensity mapping surveys probe large-scale structure through spatial variations in molecular line emission from a population of unresolved cosmological sources. Future such surveys of carbon monoxide line emission, specifically the CO(1-0) line, face potential contamination from a disjointed population of sources emitting in a hydrogen cyanide emission line, HCN(1-0). This paper explores the potential range of the strength of HCN emission and its effect on the CO auto power spectrum, using simulations with an empirical model of the CO/HCN–halo connection. We find that effects on the observed CO power spectrum depend on modeling assumptions but are very small formore » our fiducial model, which is based on current understanding of the galaxy–halo connection. Given the fiducial model, we expect the bias in overall CO detection significance due to HCN to be less than 1%.« less

Emission Inventory Development and Application Based On an Atmospheric Emission Source Priority Control Classification Technology Method, a Case Study in the Middle Reaches of Yangtze River Urban Agglomerations, China

NASA Astrophysics Data System (ADS)

Sun, X.; Cheng, S.

2017-12-01

This paper presents the first attempt to investigate the emission source control of the Middle Reaches of Yangtze River Urban Agglomerations (MRYRUA), one of the national urban agglomerations in China. An emission inventory of the MRYRUA was the first time to be developed as inputs to the CAMx model based on county-level activity data obtained by full-coverage investigation and source-based spatial surrogates. The emission inventory was proved to be acceptable owing to the atmospheric modeling verification. A classification technology method for atmospheric pollution source priority control was the first time to be introduced and applied in the MRYRUA for the evaluation of the emission sources control on the region-scale and city-scale. MICAPS (Meteorological Information comprehensive Analysis and Processing System) was applied for the regional meteorological condition and sensitivity analysis. The results demonstrated that the emission sources in the Hefei-center Urban Agglomerations contributed biggest on the mean PM2.5 concentrations of the MRYRUA and should be taken the priority to control. The emission sources in the Ma'anshan city, Xiangtan city, Hefei city and Wuhan city were the bigger contributors on the mean PM2.5 concentrations of the MRYRUA among the cities and should be taken the priority to control. In addition, the cities along the Yangtze River and the tributary should be given the special attention for the regional air quality target attainments. This study provide a valuable preference for policy makers to develop effective air pollution control strategies.

Biosolid stockpiles are a significant point source for greenhouse gas emissions.

PubMed

Majumder, Ramaprasad; Livesley, Stephen J; Gregory, David; Arndt, Stefan K

2014-10-01

The wastewater treatment process generates large amounts of sewage sludge that are dried and then often stored in biosolid stockpiles in treatment plants. Because the biosolids are rich in decomposable organic matter they could be a significant source for greenhouse gas (GHG) emissions, yet there are no direct measurements of GHG from stockpiles. We therefore measured the direct emissions of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) on a monthly basis from three different age classes of biosolid stockpiles at the Western Treatment Plant (WTP), Melbourne, Australia, from December 2009 to November 2011 using manual static chambers. All biosolid stockpiles were a significant point source for CH4 and N2O emissions. The youngest biosolids (<1 year old) had the greatest CH4 and N2O emissions of 60.2 kg of CO2-e per Mg of biosolid per year. Stockpiles that were between 1 and 3 years old emitted less overall GHG (∼29 kg CO2-e Mg(-1) yr(-1)) and the oldest stockpiles emitted the least GHG (∼10 kg CO2-e Mg(-1) yr(-1)). Methane emissions were negligible in all stockpiles but the relative contribution of N2O and CO2 changed with stockpile age. The youngest stockpile emitted two thirds of the GHG emission as N2O, while the 1-3 year old stockpile emitted an equal amount of N2O and CO2 and in the oldest stockpile CO2 emissions dominated. We did not detect any seasonal variability of GHG emissions and did not observe a correlation between GHG flux and environmental variables such as biosolid temperature, moisture content or nitrate and ammonium concentration. We also modeled CH4 emissions based on a first order decay model and the model based estimated annual CH4 emissions were higher as compared to the direct field based estimated annual CH4 emissions. Our results indicate that labile organic material in stockpiles is decomposed over time and that nitrogen decomposition processes lead to significant N2O emissions. Carbon decomposition favors CO2 over CH4 production probably because of aerobic stockpile conditions or CH4 oxidation in the outer stockpile layers. Although the GHG emission rate decreased with biosolid age, managers of biosolid stockpiles should assess alternate storage or uses for biosolids to avoid nutrient losses and GHG emissions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of a process-based model for assessing the methane budgets of global terrestrial ecosystems and evaluation of uncertainty

NASA Astrophysics Data System (ADS)

Ito, A.; Inatomi, M.

2012-02-01

We assessed the global terrestrial budget of methane (CH4) by using a process-based biogeochemical model (VISIT) and inventory data for components of the budget that were not included in the model. Emissions from wetlands, paddy fields, biomass burning, and plants, as well as oxidative consumption by upland soils, were simulated by the model. Emissions from ruminant livestock and termites were evaluated by using an inventory approach. These CH4 flows were estimated for each of the model's 0.5° × 0.5° grid cells from 1901 to 2009, while accounting for atmospheric composition, meteorological factors, and land-use changes. Estimation uncertainties were examined through ensemble simulations using different parameterization schemes and input data (e.g., different wetland maps and emission factors). From 1996 to 2005, the average global terrestrial CH4 budget was estimated on the basis of 1152 simulations, and terrestrial ecosystems were found to be a net source of 308.3 ± 20.7 Tg CH4 yr-1. Wetland and livestock ruminant emissions were the primary sources. The results of our simulations indicate that sources and sinks are distributed highly heterogeneously over the Earth's land surface. Seasonal and interannual variability in the terrestrial budget was also assessed. The trend of increasing net emission from terrestrial sources and its relationship with temperature variability imply that terrestrial CH4 feedbacks will play an increasingly important role as a result of future climatic change.

Estimation of GHG emissions in Egypt up to the year 2020

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

ElMahgary, Y.; Abdel-Fattah, A.I.; Shama, M.A.

1994-09-01

Within the frame of UNEP's project on the Methodologies of Determining the Costs of Abatement of GHG Emissions, a case study on Egypt was undertaken by VTT (Technical Research Centre of Finland) in cooperation with the Egyptian Environment Authority Agency (EEAA). Both the bottom-up or engineering models and the top-down or the macroeconomic models were used. In the bottom-up approach, the economic sectors were divided into seven groups: petroleum industry, power generation, heavy industry, light industry, residential and commercial sector, transport and agriculture and domestic wastes. First, a comprehensive inventory for the year 1990 was prepared for all the GHGmore » emissions mainly, but not exclusively, from energy sources. This included CO[sub 2], CH[sub 4] and N[sub 2]O. A base scenario of economic and energy growth of Egypt for business-as-usual alternative was fixed using the results of several optimization processes undertaken earlier by the National Committee of Egypt. GHG emissions of the different sources in this base scenario were then determined using LEAP model and spread sheets.« less

[Estimation of the effect derived from wind erosion of soil and dust emission in Tianjin suburbs on the central district based on WEPS model].

PubMed

Chen, Li; Han, Ting-Ting; Li, Tao; Ji, Ya-Qin; Bai, Zhi-Peng; Wang, Bin

2012-07-01

Due to the lack of a prediction model for current wind erosion in China and the slow development for such models, this study aims to predict the wind erosion of soil and the dust emission and develop a prediction model for wind erosion in Tianjin by investigating the structure, parameter systems and the relationships among the parameter systems of the prediction models for wind erosion in typical areas, using the U.S. wind erosion prediction system (WEPS) as reference. Based on the remote sensing technique and the test data, a parameter system was established for the prediction model of wind erosion and dust emission, and a model was developed that was suitable for the prediction of wind erosion and dust emission in Tianjin. Tianjin was divided into 11 080 blocks with a resolution of 1 x 1 km2, among which 7 778 dust emitting blocks were selected. The parameters of the blocks were localized, including longitude, latitude, elevation and direction, etc.. The database files of blocks were localized, including wind file, climate file, soil file and management file. The weps. run file was edited. Based on Microsoft Visualstudio 2008, secondary development was done using C + + language, and the dust fluxes of 7 778 blocks were estimated, including creep and saltation fluxes, suspension fluxes and PM10 fluxes. Based on the parameters of wind tunnel experiments in Inner Mongolia, the soil measurement data and climate data in suburbs of Tianjin, the wind erosion module, wind erosion fluxes, dust emission release modulus and dust release fluxes were calculated for the four seasons and the whole year in suburbs of Tianjin. In 2009, the total creep and saltation fluxes, suspension fluxes and PM10 fluxes in the suburbs of Tianjin were 2.54 x 10(6) t, 1.25 x 10(7) t and 9.04 x 10(5) t, respectively, among which, the parts pointing to the central district were 5.61 x 10(5) t, 2.89 x 10(6) t and 2.03 x 10(5) t, respectively.

The Impact of a Potential Shale Gas Development in Germany and the United Kingdom on Local and Regional Air Quality

NASA Astrophysics Data System (ADS)

Weger, L.; Lupascu, A.; Cremonese, L.; Butler, T. M.

2017-12-01

Numerous countries in Europe that possess domestic shale gas reserves are considering exploiting this unconventional gas resource as part of their energy transition agenda. While natural gas generates less CO2 emissions upon combustion compared to coal or oil, making it attractive as a bridge in the transition from fossil fuels to renewables, production of shale gas leads to emissions of CH4 and air pollutants such as NOx, VOCs and PM. These gases in turn influence the climate as well as air quality. In this study, we investigate the impact of a potential shale gas development in Germany and the United Kingdom on local and regional air quality. This work builds on our previous study in which we constructed emissions scenarios based on shale gas utilization in these counties. In order to explore the influence of shale gas production on air quality, we investigate emissions predicted from our shale gas scenarios with the Weather Research and Forecasting model with chemistry (WRF-Chem) model. In order to do this, we first design a model set-up over Europe and evaluate its performance for the meteorological and chemical parameters. Subsequently we add shale gas emissions fluxes based on the scenarios over the area of the grid in which the shale gas activities are predicted to occur. Finally, we model these emissions and analyze the impact on air quality on both a local and regional scale. The aims of this work are to predict the range of adverse effects on air quality, highlight the importance of emissions control strategies in reducing air pollution, to promote further discussion, and to provide policy makers with information for decision making on a potential shale gas development in the two study countries.

Urban Form Energy Use and Emissions in China: Preliminary Findings and Model Proof of Concept

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

Aden, Nathaniel; Qin, Yining; Fridley, David

Urbanization is reshaping China's economy, society, and energy system. Between 1990 and 2008 China added more than 300 million new urban residents, bringing the total urbanization rate to 46%. The ongoing population shift is spurring energy demand for new construction, as well as additional residential use with the replacement of rural biomass by urban commercial energy services. This project developed a modeling tool to quantify the full energy consequences of a particular form of urban residential development in order to identify energy- and carbon-efficient modes of neighborhood-level development and help mitigate resource and environmental implications of swelling cities. LBNL developedmore » an integrated modeling tool that combines process-based lifecycle assessment with agent-based building operational energy use, personal transport, and consumption modeling. The lifecycle assessment approach was used to quantify energy and carbon emissions embodied in building materials production, construction, maintenance, and demolition. To provide more comprehensive analysis, LBNL developed an agent-based model as described below. The model was applied to LuJing, a residential development in Jinan, Shandong Province, to provide a case study and model proof of concept. This study produced results data that are unique by virtue of their scale, scope and type. Whereas most existing literature focuses on building-, city-, or national-level analysis, this study covers multi-building neighborhood-scale development. Likewise, while most existing studies focus exclusively on building operational energy use, this study also includes embodied energy related to personal consumption and buildings. Within the boundaries of this analysis, food is the single largest category of the building energy footprint, accounting for 23% of the total. On a policy level, the LCA approach can be useful for quantifying the energy and environmental benefits of longer average building lifespans. In addition to prospective analysis for standards and certification, urban form modeling can also be useful in calculating or verifying ex post facto, bottom-up carbon emissions inventories. Emissions inventories provide a benchmark for evaluating future outcomes and scenarios as well as an empirical basis for valuing low-carbon technologies. By highlighting the embodied energy and emissions of building materials, the LCA approach can also be used to identify the most intensive aspects of industrial production and the supply chain. The agent based modeling aspect of the model can be useful for understanding how policy incentives can impact individual behavior and the aggregate effects thereof. The most useful elaboration of the urban form assessment model would be to further generalize it for comparative analysis. Scenario analysis could be used for benchmarking and identification of policy priorities. If the model is to be used for inventories, it is important to disaggregate the energy use data for more accurate emissions modeling. Depending on the policy integration of the model, it may be useful to incorporate occupancy data for per-capita results. On the question of density and efficiency, it may also be useful to integrate a more explicit spatial scaling mechanism for modeling neighborhood and city-level energy use and emissions, i.e. to account for scaling effects in public infrastructure and transportation.« less

Parameter-induced uncertainty quantification of a regional N2O and NO3 inventory using the biogeochemical model LandscapeDNDC

NASA Astrophysics Data System (ADS)

Haas, Edwin; Klatt, Steffen; Kraus, David; Werner, Christian; Ruiz, Ignacio Santa Barbara; Kiese, Ralf; Butterbach-Bahl, Klaus

2014-05-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional and national scales and are outlined as the most advanced methodology (Tier 3) for national emission inventory in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems like arable land and grasslands and are thus thought to be widely applicable at various spatial and temporal scales. The high complexity of ecosystem processes mirrored by such models requires a large number of model parameters. Many of those parameters are lumped parameters describing simultaneously the effect of environmental drivers on e.g. microbial community activity and individual processes. Thus, the precise quantification of true parameter states is often difficult or even impossible. As a result model uncertainty is not solely originating from input uncertainty but also subject to parameter-induced uncertainty. In this study we quantify regional parameter-induced model uncertainty on nitrous oxide (N2O) emissions and nitrate (NO3) leaching from arable soils of Saxony (Germany) using the biogeochemical model LandscapeDNDC. For this we calculate a regional inventory using a joint parameter distribution for key parameters describing microbial C and N turnover processes as obtained by a Bayesian calibration study. We representatively sampled 400 different parameter vectors from the discrete joint parameter distribution comprising approximately 400,000 parameter combinations and used these to calculate 400 individual realizations of the regional inventory. The spatial domain (represented by 4042 polygons) is set up with spatially explicit soil and climate information and a region-typical 3-year crop rotation consisting of winter wheat, rape- seed, and winter barley. Average N2O emission from arable soils in the state of Saxony across all 400 realizations was 1.43 ± 1.25 [kg N / ha] with a median value of 1.05 [kg N / ha]. Using the default IPCC emission factor approach (Tier 1) for direct emissions reveal a higher average N2O emission of 1.51 [kg N / ha] due to fertilizer use. In the regional uncertainty quantification the 20% likelihood range for N2O emissions is 0.79 - 1.37 [kg N / ha] (50% likelihood: 0.46 - 2.05 [kg N / ha]; 90% likelihood: 0.11 - 4.03 [kg N / ha]). Respective quantities were calculated for nitrate leaching. The method has proven its applicability to quantify parameter-induced uncertainty of simulated regional greenhouse gas emission and nitrate leaching inventories using process based biogeochemical models.

Understanding high wintertime ozone pollution events in an oil and natural gas producing region of the western US

NASA Astrophysics Data System (ADS)

Ahmadov, R.; McKeen, S.; Trainer, M.; Banta, R.; Brewer, A.; Brown, S.; Edwards, P. M.; de Gouw, J. A.; Frost, G. J.; Gilman, J.; Helmig, D.; Johnson, B.; Karion, A.; Koss, A.; Langford, A.; Lerner, B.; Olson, J.; Oltmans, S.; Peischl, J.; Pétron, G.; Pichugina, Y.; Roberts, J. M.; Ryerson, T.; Schnell, R.; Senff, C.; Sweeney, C.; Thompson, C.; Veres, P.; Warneke, C.; Wild, R.; Williams, E. J.; Yuan, B.; Zamora, R.

2014-08-01

Recent increases in oil and natural gas (NG) production throughout the western US have come with scientific and public interest in emission rates, air quality and climate impacts related to this industry. This study uses a regional scale air quality model WRF-Chem to simulate high ozone (O3) episodes during the winter of 2013 over the Uinta Basin (UB) in northeastern Utah, which is densely populated by thousands of oil and NG wells. The high resolution meteorological simulations are able to qualitatively reproduce the wintertime cold pool conditions that occurred in 2013, allowing the model to reproduce the observed multi-day buildup of atmospheric pollutants and accompanying rapid photochemical ozone formation in the UB. Two different emission scenarios for the oil and NG sector were employed in this study. The first emission scenario (bottom-up) was based on the US EPA National Emission Inventory (NEI) (2011, version 1) for the oil and NG sector for the UB. The second emission scenario (top-down) was based on the previously derived estimates of methane (CH4) emissions and a regression analysis for multiple species relative to CH4 concentration measurements in the UB. WRF-Chem simulations using the two emission data sets resulted in significant differences for concentrations of most gas-phase species. Evaluation of the model results shows greater underestimates of CH4 and other volatile organic compounds (VOCs) in the simulation with the NEI-2011 inventory than the case when the top-down emission scenario was used. Unlike VOCs, the NEI-2011 inventory significantly overestimates the emissions of nitrogen oxides (NOx), while the top-down emission scenario results in a moderate negative bias. Comparison of simulations using the two emission data sets reveals that the top-down case captures the high O3 episodes. In contrast, the simulation case using the bottom-up inventory is not able to reproduce any of the observed high O3 concentrations in the UB. A sensitivity analysis reveals that the major factors driving high wintertime O3 in the UB are shallow boundary layers with light winds, high emissions of VOCs from oil and NG operations compared to NOx emissions, enhancement of photolysis fluxes and reduction of O3 loss from deposition due to snow cover. Simple emission reduction scenarios show that the UB O3 production is VOC sensitive and NOx insensitive. The model results show a disproportionate contribution of aromatic VOCs to O3 formation relative to all other VOC emissions. We also present modeling results for winter of 2012, when high O3 levels were not observed in the UB. The air quality model together with the top-down emission framework presented here may help to address the emerging science and policy related questions surrounding the environmental impact of oil and NG drilling in western US.

Satellite measurements of SO2 emission and dispersion during the 2008-2009 eruption of Halema‘uma‘u, Kilauea

NASA Astrophysics Data System (ADS)

Carn, S. A.; Sutton, A. J.; Elias, T.; Patrick, M. R.; Owen, R. C.; Wu, S.

2009-12-01

Satellite remote sensing is providing unique constraints on sulfur dioxide (SO2) emissions associated with the ongoing eruption of Halema‘uma‘u (HMM), and daily observations of volcanic plume dispersion. We use synoptic SO2 measurements by the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite to chart the fluctuation in SO2 emissions and plume dispersion. Prior to the onset of degassing from HMM, OMI detected SO2 emissions from the east rift Pu‘u ‘O‘o vent; the average daily SO2 burden measured between Sept 6, 2004 and Feb 29, 2008 was 0.7 kilotons (kt) ±1 (1σ). The additional SO2 production from HMM caused total SO2 burdens in the composite Kilauea plume to increase notably in March-April 2008, and a daily average SO2 burden of ~4 kt ±4 (1σ) was measured by OMI between Mar 1, 2008 and Jul 31, 2009 (all burdens are preliminary and assume a SO2 plume altitude of 3 km). A total of ~2 Megatons of SO2 was measured by OMI in the Kilauea emissions between March 2008 and July 2009. The increased SO2 emissions provide an excellent opportunity to compare ground-based ultraviolet (UV) spectrometer and space-based UV OMI measurements of SO2 output, and test algorithms for derivation of emission rates from satellite data. Kilauea data analyzed to date show that trends in ground-based SO2 emission rates and OMI SO2 burdens are in qualitative agreement but differ in magnitude. Plume altitude is a critical factor in satellite SO2 retrievals, and interpretation of the Kilauea observations is complicated by the presence of two SO2 plumes (from HMM and Pu‘u ‘O‘o) within the OMI field-of-view. In order to constrain plume heights and SO2 lifetimes, we use plume simulations generated by the FLEXPART particle dispersion model and compare the model output with OMI SO2 observations. We validate the model-generated plume altitudes using vertical aerosol profiles derived from the CALIPSO space-borne lidar instrument. Gaussian plume models parameterized using visual observations of the HMM plume injection height further constrain near-source plume dispersion and downwind evolution. Refinement of SO2 altitude provides improved constraints on SO2 burdens in observed plumes. A more rigorous approach to deriving source emission strengths from satellite observations is an inverse modeling scheme incorporating measurements and models. Using Kilauea as a case study, we plan to develop such a scheme using OMI data, FLEXPART simulations and atmospheric chemistry and transport modeling using the GEOS-Chem model. Modeling of plume dispersion and chemistry will also provide estimates of SO2 and acid aerosol concentrations for potential use in air quality and health hazard assessments in Hawaii.

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...

40 CFR 600.208-12 - Calculation of FTP-based and HFET-based fuel economy, CO2 emissions, and carbon-related exhaust...

Code of Federal Regulations, 2014 CFR

2014-07-01

..., and carbon-related exhaust emissions from the tests performed using gasoline or diesel test fuel. (ii... from the tests performed using alcohol or natural gas test fuel. (b) For each model type, as determined... from the tests performed using gasoline or diesel test fuel. (ii) Calculate the city, highway, and...

40 CFR 600.208-12 - Calculation of FTP-based and HFET-based fuel economy, CO2 emissions, and carbon-related exhaust...

Code of Federal Regulations, 2012 CFR

2012-07-01

..., and carbon-related exhaust emissions from the tests performed using gasoline or diesel test fuel. (ii... from the tests performed using alcohol or natural gas test fuel. (b) For each model type, as determined... from the tests performed using gasoline or diesel test fuel. (ii) Calculate the city, highway, and...

40 CFR 600.208-12 - Calculation of FTP-based and HFET-based fuel economy, CO2 emissions, and carbon-related exhaust...

Code of Federal Regulations, 2013 CFR

2013-07-01

..., and carbon-related exhaust emissions from the tests performed using gasoline or diesel test fuel. (ii... from the tests performed using alcohol or natural gas test fuel. (b) For each model type, as determined... from the tests performed using gasoline or diesel test fuel. (ii) Calculate the city, highway, and...

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.

OCO-2 and GOSAT observations of anthropogenic emissions of carbon dioxide.

NASA Astrophysics Data System (ADS)

Maksyutov, S. S.; Yadav, V.; Eldering, A.; Janardanan Achari, R.; Saito, M.; Oda, T.

2017-12-01

We apply high resolution transport modeling with Lagrangian transport model Flexpart to analyze CO2 emission signatures in the total column XCO2 observed by OCO-2 and GOSAT satellites in 2014-2016. To reduce computational load for transport modeling, the OCO-2 observations are aggregated into 1 second averages prepared separately for two groups (left and right) made of simultaneously measured eight OCO-2 observations (footprints). Each group has surface footprint size close to 0.1 degree. The spatial distribution of CO2 concentrations, resulting from anthropogenic emissions, are estimated with the transport model for all GOSAT and OCO-2 observation locations using high-resolution emission inventory (ODIAC) and biospheric exchange simulated with VISIT model at 0.1 degree resolution. Based on this estimate, using a threshold value of 0.1 ppm, the observations are classified into two categories: data contaminated by the anthropogenic sources and those not including this contamination. To extract concentration enhancements due to the anthropogenic emissions, we define a clean background (the averaged values for the data free from contamination by anthropogenic emissions) in 10° by 10° regions over the globe that are subtracted from the observational data including anthropogenic contamination. These anomalies are binned and analyzed to see a match between observed and simulated enhancements. For both OCO-2 and GOSAT, we found linear relations between model and observed anomalies. Similar to the earlier findings made with GOSAT; enhancements observed by OCO-2 match the simulated ones with a regression slope close to unity. Even after aggregation of OCO-2 data into groups of up to 12 individual soundings, the number of enhanced XCO2 observations by OCO-2 is 15 and 25 times larger than that of GOSAT in each 0.1 ppm bin, in the range of simulated enhancements between 0.1 and 2 ppm. The result confirms high potential of using OCO-2 observations for analyzing anthropogenic emission signatures. We also prepare higher resolution simulation of the CO2 transport with emissions based on ODIAC inventory to match the resolution of the OCO-2 observations, that reduces smear introduced by aggregating individual observations used in the current approach.

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.

Comparing the greenhouse gas emissions from three alternative waste combustion concepts.

PubMed

Vainikka, Pasi; Tsupari, Eemeli; Sipilä, Kai; Hupa, Mikko

2012-03-01

Three alternative condensing mode power and combined heat and power (CHP) waste-to-energy concepts were compared in terms of their impacts on the greenhouse gas (GHG) emissions from a heat and power generation system. The concepts included (i) grate, (ii) bubbling fluidised bed (BFB) and (iii) circulating fluidised bed (CFB) combustion of waste. The BFB and CFB take advantage of advanced combustion technology which enabled them to reach electric efficiency up to 35% and 41% in condensing mode, respectively, whereas 28% (based on the lower heating value) was applied for the grate fired unit. A simple energy system model was applied in calculating the GHG emissions in different scenarios where coal or natural gas was substituted in power generation and mix of fuel oil and natural gas in heat generation by waste combustion. Landfilling and waste transportation were not considered in the model. GHG emissions were reduced significantly in all of the considered scenarios where the waste combustion concepts substituted coal based power generation. With the exception of condensing mode grate incinerator the different waste combustion scenarios resulted approximately in 1 Mton of fossil CO(2)-eq. emission reduction per 1 Mton of municipal solid waste (MSW) incinerated. When natural gas based power generation was substituted by electricity from the waste combustion significant GHG emission reductions were not achieved. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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.

Modelling terrestrial nitrous oxide emissions and implications for climate feedback.

PubMed

Xu-Ri; Prentice, I Colin; Spahni, Renato; Niu, Hai Shan

2012-10-01

Ecosystem nitrous oxide (N2O) emissions respond to changes in climate and CO2 concentration as well as anthropogenic nitrogen (N) enhancements. Here, we aimed to quantify the responses of natural ecosystem N2O emissions to multiple environmental drivers using a process-based global vegetation model (DyN-LPJ). We checked that modelled annual N2O emissions from nonagricultural ecosystems could reproduce field measurements worldwide, and experimentally observed responses to step changes in environmental factors. We then simulated global N2O emissions throughout the 20th century and analysed the effects of environmental changes. The model reproduced well the global pattern of N2O emissions and the observed responses of N cycle components to changes in environmental factors. Simulated 20th century global decadal-average soil emissions were c. 8.2-9.5 Tg N yr(-1) (or 8.3-10.3 Tg N yr(-1) with N deposition). Warming and N deposition contributed 0.85±0.41 and 0.80±0.14 Tg N yr(-1), respectively, to an overall upward trend. Rising CO2 also contributed, in part, through a positive interaction with warming. The modelled temperature dependence of N2O emission (c. 1 Tg N yr(-1) K(-1)) implies a positive climate feedback which, over the lifetime of N2O (114 yr), could become as important as the climate-carbon cycle feedback caused by soil CO2 release. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

2005 v4.1 Technical Support Document

EPA Pesticide Factsheets

Preparation of Emission Inventories for the Version 4.1, 2005-based Platform describes how emissions from the 2005 NEI, version 2 and were processed for air quality modeling in support of the Boiler MACT and the Mercury and Air Toxics Standards.

THE 1985 NAPAP EMISSIONS INVENTORY: DEVELOPMENT OF SPECIES ALLOCATION FACTORS

EPA Science Inventory

The report describes the methodologies and data bases used to develop species allocation factors and data processing software used to develop the 1985 National Acid Precipitation Assessment Program (NAPAP) Modelers' Emissions Inventory (Version 2). Species allocation factors were...

Evaluation of modeling NO2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

NASA Astrophysics Data System (ADS)

Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

2018-03-01

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope = 0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope = 1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

Evaluation of Modeling NO2 Concentrations Driven by Satellite-Derived and Bottom-Up Emission Inventories Using In-Situ Measurements Over China

NASA Technical Reports Server (NTRS)

Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

2018-01-01

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slopeD0.74 and 0.64 for the daily mean and daytime only) and the MIX (slopeD1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40% higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0% on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15% in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

A new physically-based windblown dust emission ...

EPA Pesticide Factsheets

Dust has significant impacts on weather and climate, air quality and visibility, and human health; therefore, it is important to include a windblown dust emission module in atmospheric and air quality models. In this presentation, we summarize our efforts in development of a physics-based windblown dust emission scheme and its implementation in the CMAQ modeling system. The new model incorporates the effect of the surface wind speed, soil texture, soil moisture, and surface roughness in a physically sound manner. Specifically, a newly developed dynamic relation for the surface roughness length in this model is believed to adequately represent the physics of the surface processes involved in the dust generation. Furthermore, careful attention is paid in integrating the new windblown dust module within the CMAQ to ensure that the required input parameters are correctly configured. The new model is evaluated for the case studies including the continental United States and the Northern hemisphere, and is shown to be able to capture the occurrence of the dust outbreak and the level of the soil concentration. We discuss the uncertainties and limitations of the model and briefly describe our path forward for further improvements. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based

Year-round simulated methane emissions from a permafrost ecosystem in Northeast Siberia

NASA Astrophysics Data System (ADS)

Castro-Morales, Karel; Kleinen, Thomas; Kaiser, Sonja; Zaehle, Sönke; Kittler, Fanny; Kwon, Min Jung; Beer, Christian; Göckede, Mathias

2018-05-01

Wetlands of northern high latitudes are ecosystems highly vulnerable to climate change. Some degradation effects include soil hydrologic changes due to permafrost thaw, formation of deeper active layers, and rising topsoil temperatures that accelerate the degradation of permafrost carbon and increase in CO2 and CH4 emissions. In this work we present 2 years of modeled year-round CH4 emissions into the atmosphere from a Northeast Siberian region in the Russian Far East. We use a revisited version of the process-based JSBACH-methane model that includes four CH4 transport pathways: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. The gas is emitted through wetlands represented by grid cell inundated areas simulated with a TOPMODEL approach. The magnitude of the summertime modeled CH4 emissions is comparable to ground-based CH4 fluxes measured with the eddy covariance technique and flux chambers in the same area of study, whereas wintertime modeled values are underestimated by 1 order of magnitude. In an annual balance, the most important mechanism for transport of methane into the atmosphere is through plants (61 %). This is followed by ebullition ( ˜ 35 %), while summertime molecular diffusion is negligible (0.02 %) compared to the diffusion through the snow during winter ( ˜ 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model will facilitate a more process-oriented land surface scheme and better simulate CH4 emissions under climate change. This is especially necessary at regional scales in Arctic ecosystems influenced by permafrost thaw.

Comparing mass balance and adjoint methods for inverse modeling of nitrogen dioxide columns for global nitrogen oxide emissions

NASA Astrophysics Data System (ADS)

Cooper, Matthew; Martin, Randall V.; Padmanabhan, Akhila; Henze, Daven K.

2017-04-01

Satellite observations offer information applicable to top-down constraints on emission inventories through inverse modeling. Here we compare two methods of inverse modeling for emissions of nitrogen oxides (NOx) from nitrogen dioxide (NO2) columns using the GEOS-Chem chemical transport model and its adjoint. We treat the adjoint-based 4D-Var modeling approach for estimating top-down emissions as a benchmark against which to evaluate variations on the mass balance method. We use synthetic NO2 columns generated from known NOx emissions to serve as "truth." We find that error in mass balance inversions can be reduced by up to a factor of 2 with an iterative process that uses finite difference calculations of the local sensitivity of NO2 columns to a change in emissions. In a simplified experiment to recover local emission perturbations, horizontal smearing effects due to NOx transport are better resolved by the adjoint approach than by mass balance. For more complex emission changes, or at finer resolution, the iterative finite difference mass balance and adjoint methods produce similar global top-down inventories when inverting hourly synthetic observations, both reducing the a priori error by factors of 3-4. Inversions of simulated satellite observations from low Earth and geostationary orbits also indicate that both the mass balance and adjoint inversions produce similar results, reducing a priori error by a factor of 3. As the iterative finite difference mass balance method provides similar accuracy as the adjoint method, it offers the prospect of accurately estimating top-down NOx emissions using models that do not have an adjoint.

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.

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.

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%.

Examining drivers of the emissions embodied in trade

PubMed Central

Wu, Leying; Wang, Zheng

2017-01-01

Emissions embodied in provincial trade (EEPT) have important effects on provinces’ responsibilities for carbon emission reductions. Based on a multi-regional input-output model, we calculated EEPT for China’s 30 provinces in 2002, 2007 and 2010, and we attempted to determine the drivers of EEPT. The results showed that, during this period, the ratio of EEPT to production-based emissions increased over time, reaching 40.24% in 2010. In consideration of its important role in carbon emissions, we analyzed the factors attributable to EEPT through structure decomposition analysis. The decomposition results showed that final demand and carbon emission intensity were two major factors in EEPT, while the final demand in other provinces and the carbon emission intensity in the local province were major factors for Emissions embodied in provincial exports and the final demand in the local province and the carbon emission intensity in other provinces were major factors for Emissions embodied in provincial imports. Regarding the differences among the EEPT of different provinces, changes in the structure of trade were the primary reason. PMID:28426769

Io: Escape and ionization of atmospheric gases

NASA Technical Reports Server (NTRS)

Smyth, W. H.

1981-01-01

Models for the Io oxygen clouds were improved to calculate the two dimensional sky plane intensity of the 1304 A emission and the 880 A emission of atomic oxygen, in addition to the 6300 A emission intensity. These three wavelength emissions are those for which observational measurements have been performed by ground based, rocket, Earth orbiting satellite and Voyager spacecraft instruments. Comparison of model results and observations suggests that an oxygen flux from Io of about 3 billion atoms sq cm sec is required for agreement. Quantitative analysis of the Io sodium cloud has focused upon the initial tasks of acquiring and preliminary evaluation of new sodium cloud and Io plasma torus data.

Testing CMAQ chemistry sensitivities in base case and emissions control runs at SEARCH and SOS99 surface sites in the southeastern US

NASA Astrophysics Data System (ADS)

Arnold, J. R.; Dennis, Robin L.

CMAQ was run to simulate urban and regional tropospheric conditions in the southeastern US over 14 days in July 1999 at 32, 8 and 2 km grid spacings. Runs were made with either of two older mechanisms, Carbon Bond IV (CB4) and the Regional Acid Deposition Model, version 2 (RADM2), and with the more recent and complete California Statewide Air Pollution Research Center, version 1999 mechanism (SAPRC99) in a sensitivity matrix with a full emissions base case and separate 50% control scenarios for emissions of nitrogen oxides (NO X) and volatile organic compounds (VOC). Results from the base case were compared to observations at the Southeastern Aerosol Research and Characterization Study (SEARCH) site at Jefferson Street in Atlanta, GA (JST) and the Southern Oxidant Study (SOS) Cornelia Fort Airpark (CFA) site downwind of Nashville, TN. In the base case, SAPRC99 predicted more ozone (O 3) than CB4 or RADM2 almost every hour and especially for afternoon maxima at both JST and CFA. Performance of the 8 km models at JST was better than that of the 32 km ones for all chemistries, reducing the 1 h peak bias by as much as 30 percentage points; at CFA only the RADM2 8 km model improved. The 2 km solutions did not show improved performance over the 8 km ones at either site, with normalized 1 h bias in the peak O 3 ranging from 21% at CFA to 43% at JST. In the emissions control cases, SAPRC99 was generally more responsive than CB4 and RADM2 to NO X and VOC controls, excepting hours at JST with predicted increased O 3 from NO X control. Differential sensitivity to chemical mechanism varied by more than ±10% for NO X control at JST and CFA, and in a similar range for VOC control at JST. VOC control at the more strongly NO X- limited urban CFA site produced a differential sensitivity response of <5%. However, even when differential sensitivities in control cases were small, neither their sign nor their magnitude could be reliably determined from model performance in the full emissions case, meaning that the degree of O 3 response to a change in chemical mechanism can differ substantially with the level of precursor emissions. Hence we conclude that properly understanding the effects of changes in a model's chemical mechanism always requires emissions control cases as part of model sensitivity analysis.

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Pierce, R. Bradley; Jo, Duseong S.; Park, Rokjin J.; Flemming, Johannes; Emmons, Louisa K.; Bowman, Kevin W.; Henze, Daven K.; Davila, Yanko; Sudo, Kengo; Eiof Jonson, Jan; Tronstad Lund, Marianne; Janssens-Maenhout, Greet; Dentener, Frank J.; Keating, Terry J.; Oetjen, Hilke; Payne, Vivienne H.

2017-05-01

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O3) can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (< 10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100 % emission reduction) source contribution obtained from linearly scaling the North American mean O3 sensitivities to a 20 % reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O3 sensitivities to the 20 % EAS emission perturbations are ˜ 8 % (May-June 2010)/˜ 11 % (2010 annual) lower than those estimated by eight global models, and the multi-model ensemble estimates are higher than the HTAP1 reported 2001 conditions. GEOS-Chem sensitivities indicate that the EAS anthropogenic NOx emissions matter more than the other EAS O3 precursors to the North American O3, qualitatively consistent with previous adjoint sensitivity calculations. In addition to the analyses on large spatial-temporal scales relative to the HTAP1, we also show results on subcontinental and event scales that are more relevant to the US air quality management. The EAS pollution impacts are weaker during observed O3 exceedances than on all days in most US regions except over some high-terrain western US rural/remote areas. Satellite O3 (TES, JPL-IASI, and AIRS) and carbon monoxide (TES and AIRS) products, along with surface measurements and model calculations, show that during certain episodes stratospheric O3 intrusions and the transported EAS pollution influenced O3 in the western and the eastern US differently. Free-running (i.e., without chemical data assimilation) global models underpredicted the transported background O3 during these episodes, posing difficulties for STEM to accurately simulate the surface O3 and its source contribution. Although we effectively improved the modeled O3 by incorporating satellite O3 (OMI and MLS) and evaluated the quality of the HTAP2 emission inventory with the Royal Netherlands Meteorological Institute-Ozone Monitoring Instrument (KNMI-OMI) nitrogen dioxide, using observations to evaluate and improve O3 source attribution still remains to be further explored.

Impact of intercontinental pollution transport on North American ozone air pollution: an HTAP phase 2 multi-model study.

PubMed

Huang, Min; Carmichael, Gregory R; Pierce, R Bradley; Jo, Duseong S; Park, Rokjin J; Flemming, Johannes; Emmons, Louisa K; Bowman, Kevin W; Henze, Daven K; Davila, Yanko; Sudo, Kengo; Jonson, Jan Eiof; Lund, Marianne Tronstad; Janssens-Maenhout, Greet; Dentener, Frank J; Keating, Terry J; Oetjen, Hilke; Payne, Vivienne H

2017-05-08

The recent update on the US National Ambient Air Quality Standards (NAAQS) of the ground-level ozone (O 3 / can benefit from a better understanding of its source contributions in different US regions during recent years. In the Hemispheric Transport of Air Pollution experiment phase 1 (HTAP1), various global models were used to determine the O 3 source-receptor (SR) relationships among three continents in the Northern Hemisphere in 2001. In support of the HTAP phase 2 (HTAP2) experiment that studies more recent years and involves higher-resolution global models and regional models' participation, we conduct a number of regional-scale Sulfur Transport and dEposition Model (STEM) air quality base and sensitivity simulations over North America during May-June 2010. STEM's top and lateral chemical boundary conditions were downscaled from three global chemical transport models' (i.e., GEOS-Chem, RAQMS, and ECMWF C-IFS) base and sensitivity simulations in which the East Asian (EAS) anthropogenic emissions were reduced by 20 %. The mean differences between STEM surface O 3 sensitivities to the emission changes and its corresponding boundary condition model's are smaller than those among its boundary condition models, in terms of the regional/period-mean (<10 %) and the spatial distributions. An additional STEM simulation was performed in which the boundary conditions were downscaled from a RAQMS (Realtime Air Quality Modeling System) simulation without EAS anthropogenic emissions. The scalability of O 3 sensitivities to the size of the emission perturbation is spatially varying, and the full (i.e., based on a 100% emission reduction) source contribution obtained from linearly scaling the North American mean O 3 sensitivities to a 20% reduction in the EAS anthropogenic emissions may be underestimated by at least 10 %. The three boundary condition models' mean O 3 sensitivities to the 20% EAS emission perturbations are ~8% (May-June 2010)/~11% (2010 annual) lower than those estimated by eight global models, and the multi-model ensemble estimates are higher than the HTAP1 reported 2001 conditions. GEOS-Chem sensitivities indicate that the EAS anthropogenic NO x emissions matter more than the other EAS O 3 precursors to the North American O 3 , qualitatively consistent with previous adjoint sensitivity calculations. In addition to the analyses on large spatial-temporal scales relative to the HTAP1, we also show results on subcontinental and event scales that are more relevant to the US air quality management. The EAS pollution impacts are weaker during observed O 3 exceedances than on all days in most US regions except over some high-terrain western US rural/remote areas. Satellite O 3 (TES, JPL-IASI, and AIRS) and carbon monoxide (TES and AIRS) products, along with surface measurements and model calculations, show that during certain episodes stratospheric O 3 intrusions and the transported EAS pollution influenced O 3 in the western and the eastern US differently. Free-running (i.e., without chemical data assimilation) global models underpredicted the transported background O 3 during these episodes, posing difficulties for STEM to accurately simulate the surface O 3 and its source contribution. Although we effectively improved the modeled O 3 by incorporating satellite O 3 (OMI and MLS) and evaluated the quality of the HTAP2 emission inventory with the Royal Netherlands Meteorological Institute-Ozone Monitoring Instrument (KNMI-OMI) nitrogen dioxide, using observations to evaluate and improve O 3 source attribution still remains to be further explored.

Emissions reduction scenarios in the Argentinean Energy Sector

DOE PAGES

Di Sbroiavacca, Nicolás; Nadal, Gustavo; Lallana, Francisco; ...

2016-04-14

Here in this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO 2 emission savings of the energy sector in Argentina over the 2010-2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic costmore » of 22.8 billion US$(2005) to 2050 is expected, resulting in a 16% reduction in GHG emissions compared to a business-as-usual scenario. These measures also bring economic co-benefits, such as a reduction of energy imports improving the balance of trade. A Low CO 2 price scenario in LEAP results in the replacement of coal by nuclear and wind energy in electricity expansion. A High CO 2 price leverages additional investments in hydropower. An emission cap scenario (2050 emissions 20% lower than 2010 emissions) is feasible by including such measures as CCS and Bio CCS, but at a significant cost. By way of cross-model comparison with the TIAM-ECN and GCAM global integrated assessment models, significant variation in projected emissions reductions in the carbon price scenarios was observed, which illustrates the inherent uncertainties associated with such long-term projections. These models predict approximately 37% and 94% reductions under the High CO 2 price scenario, respectively. By comparison, the LEAP model, using an approach based on the assessment of a limited set of mitigation options, predicts a 11.3% reduction under the ‘high’ carbon tax. The main reasons for this difference are differences in assumptions about technology cost and availability, CO 2 storage capacity, and the ability to import bioenergy. In terms of technology pathways, the models agree that fossil fuels, in particular natural gas, will remain an important part of the electricity mix in the core baseline scenario. Finally, according to the models there is agreement that the introduction of a carbon price will lead to a decline in absolute and relative shares of aggregate fossil fuel generation. However, predictions vary as to the extent to which coal, nuclear and renewable energy play a role.« less

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Picard, Ghislain; Roy, Alexandre; Dupont, Florent; Fily, Michel; Royer, Alain

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer), and is available at http:lgge.osug.frpicarddmrtml.

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.

Simplifiying global biogeochemistry models to evaluate methane emissions

NASA Astrophysics Data System (ADS)

Gerber, S.; Alonso-Contes, C.

2017-12-01

Process-based models are important tools to quantify wetland methane emissions, particularly also under climate change scenarios, evaluating these models is often cumbersome as they are embedded in larger land-surface models where fluctuating water table and the carbon cycle (including new readily decomposable plant material) are predicted variables. Here, we build on these large scale models but instead of modeling water table and plant productivity we provide values as boundary conditions. In contrast, aerobic and anaerobic decomposition, as well as soil column transport of oxygen and methane are predicted by the model. Because of these simplifications, the model has the potential to be more readily adaptable to the analysis of field-scale data. Here we determine the sensitivity of the model to specific setups, parameter choices, and to boundary conditions in order to determine set-up needs and inform what critical auxiliary variables need to be measured in order to better predict field-scale methane emissions from wetland soils. To that end we performed a global sensitivity analysis that also considers non-linear interactions between processes. The global sensitivity analysis revealed, not surprisingly, that water table dynamics (both mean level and amplitude of fluctuations), and the rate of the carbon cycle (i.e. net primary productivity) are critical determinants of methane emissions. The depth-scale where most of the potential decomposition occurs also affects methane emissions. Different transport mechanisms are compensating each other to some degree: If plant conduits are constrained, methane emissions by diffusive flux and ebullition compensate to some degree, however annual emissions are higher when plants help to bypass methanotrophs in temporally unsaturated upper layers. Finally, while oxygen consumption by plant roots help creating anoxic conditions it has little effect on overall methane emission. Our initial sensitivity analysis helps guiding further model development and improvement. However, an important goal for our model is to use it in field settings as a tool to deconvolve the different processes that contribute to the net transfer of methane from soils to atmosphere.

A shift in emission time profiles of fossil fuel combustion due to energy transitions impacts source receptor matrices for air quality.

PubMed

Hendriks, Carlijn; Kuenen, Jeroen; Kranenburg, Richard; Scholz, Yvonne; Schaap, Martijn

2015-03-01

Effective air pollution and short-lived climate forcer mitigation strategies can only be designed when the effect of emission reductions on pollutant concentrations and health and ecosystem impacts are quantified. Within integrated assessment modeling source-receptor relationships (SRRs) based on chemistry transport modeling are used to this end. Currently, these SRRs are made using invariant emission time profiles. The LOTOS-EUROS model equipped with a source attribution module was used to test this assumption for renewable energy scenarios. Renewable energy availability and thereby fossil fuel back up are strongly dependent on meteorological conditions. We have used the spatially and temporally explicit energy model REMix to derive time profiles for backup power generation. These time profiles were used in LOTOS-EUROS to investigate the effect of emission timing on air pollutant concentrations and SRRs. It is found that the effectiveness of emission reduction in the power sector is significantly lower when accounting for the shift in the way emissions are divided over the year and the correlation of emissions with synoptic situations. The source receptor relationships also changed significantly. This effect was found for both primary and secondary pollutants. Our results indicate that emission timing deserves explicit attention when assessing the impacts of system changes on air quality and climate forcing from short lived substances.

Long-path measurements of pollutants and micrometeorology over Highway 401 in Toronto

NASA Astrophysics Data System (ADS)

You, Yuan; Staebler, Ralf M.; Moussa, Samar G.; Su, Yushan; Munoz, Tony; Stroud, Craig; Zhang, Junhua; Moran, Michael D.

2017-11-01

Traffic emissions contribute significantly to urban air pollution. Measurements were conducted over Highway 401 in Toronto, Canada, with a long-path Fourier transform infrared (FTIR) spectrometer combined with a suite of micrometeorological instruments to identify and quantify a range of air pollutants. Results were compared with simultaneous in situ observations at a roadside monitoring station, and with output from a special version of the operational Canadian air quality forecast model (GEM-MACH). Elevated mixing ratios of ammonia (0-23 ppb) were observed, of which 76 % were associated with traffic emissions. Hydrogen cyanide was identified at mixing ratios between 0 and 4 ppb. Using a simple dispersion model, an integrated emission factor of on average 2.6 g km-1 carbon monoxide was calculated for this defined section of Highway 401, which agreed well with estimates based on vehicular emission factors and observed traffic volumes. Based on the same dispersion calculations, vehicular average emission factors of 0.04, 0.36, and 0.15 g km-1 were calculated for ammonia, nitrogen oxide, and methanol, respectively.

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.

Simulations of aerosol constituents and their sources of origin over Indo-Gangetic plain (IGP) to Himalayan foothills: a new perspective of GCM estimates

NASA Astrophysics Data System (ADS)

Kumar, B. D.; Verma, S.; Wang, R.; Boucher, O.

2016-12-01

In the present study, we evaluated aerosol constituents of the model using the measurements during premonsoon over Indo-Gangetic plain (IGP) to Himalayan foothills. Aerosol transport simulations were carried out in general circulation model (GCM) of Laboratoire de M ´et ´eorologie Dynamique (LMD-GCM) with three set of emissions including Indian emissions in GCM-Indemiss, global emissions in GCM coupled with aerosol interactive chemistry (GCM-INCA-I), and the global emissions with updated BC emission inventory over Asia in GCM-INCA-II. Among three models, GCM-indemiss reproduced measured single scattering albedo (SSA) at 670 nm with a relative bias of 5%. However, the estimated 30-50% of the measured aerosol optical depth (AOD) at 550 nm and 20-60% of the measured surface concentration of aerosol constituents (e.g. black carbon (BC), organic carbon (OC), and sulfate) at most of the times over the study period. Inability of model to reproduce observed AOD changes was attributed to the paucity of emissions represented in the model. Design of retrieval simulations using existing GCM-indemiss estimates was further carried out. Retrieval simulations have produced better results, which showed constituent surface concentration in the vicinity of the measurements with normalized mean bias (NMB) of <30%. Scatter analysis between surface and elevated contribution of region's emissions showed anthropogenic emissions from the IGP on anthropogenic days and the north west India (NWI) on anthropogenic with dust days influence aerosols over northern India (NI). Our analysis showed BC emissions from base inventory for the corresponding grids of source region influencing NI were lower by 200% compared to that of modified scenario. These emissions will further be implemented in an atmospheric GCM to evaluate their performance validating with measurements data.

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.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

PubMed

Treat, Claire C; Bloom, A Anthony; Marushchak, Maija E

2018-03-22

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH 4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH 4 emissions, we synthesized nongrowing season and annual CH 4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m 2 in bogs to 5.2 g/m 2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m -2  year -1 in tundra bogs to 78 g m -2  year -1 in temperate marshes. Uplands varied from CH 4 sinks to CH 4 sources with a median annual flux of 0.0 ± 0.2 g m -2  year -1 . The measured fraction of annual CH 4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH 4 emissions. Using this constraint, the modeled nongrowing season wetland CH 4 flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH 4 flux was 37 ± 7 Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH 4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate. © 2018 John Wiley & Sons Ltd.

Emission factors of SO2, NOx and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling

NASA Astrophysics Data System (ADS)

Beecken, J.; Mellqvist, J.; Salo, K.; Ekholm, J.; Jalkanen, J.-P.; Johansson, L.; Litvinenko, V.; Volodin, K.; Frank-Kamenetsky, D. A.

2014-10-01

Emission factors of SO2, NOx and size distributed particle numbers were measured for approximately 300 different ships in the Gulf of Finland and Neva Bay area during two campaigns in August/September 2011 and June/July 2012. The measurements were carried out from a harbor vessel and from an MI-8 helicopter downwind of passing ships. Other measurements were carried out from shore sites near the island of Kronstadt and along the river Neva in the city area of Saint Petersburg. Most ships were running at reduced speed (10 knots), i.e. not at their optimal load. Vessels for domestic and international shipping were monitored. It was seen that the distribution of the SO2 emission factors is bi-modal with averages of 4.6 gSO2 kgfuel-1 and 18.2 gSO2 kgfuel-1 for the lower and the higher mode, respectively. The emission factors show compliance with the 1% fuel sulfur content SECA limit for 90% of the vessels in 2011 and 97% in 2012. The distribution of the NOx emission factor is mono-modal with an average of 58 gNOx kgfuel-1. The corresponding emission related to the generated power yields an average of 12.1 gNOx kWh-1. The distribution of the emission factors for particulate number shows that nearly 90% of all particles in the 5.6 nm to 10 μm size range were below 70 nm in diameter. The distribution of the corresponding emission factors for the mass indicates two separated main modes, one for particles between 30 and 300 nm the other above 2 μm. The average particle emission factors were found to be in the range from 0.7 to 2.7 × 1016 particles kgfuel-1 and 0.2 to 3.4 gPM kgfuel-1, respectively. The NOx and particulate emissions are comparable with other studies. The measured emission factors were compared, for individual ships, to modeled ones using the Ship Traffic Emission Assessment Model (STEAM) of the Finnish Meteorological Institute. A reasonably good agreement for gaseous sulfur and nitrogen emissions can be seen for ships in international traffic, but significant deviations are found for inland vessels. Considering particulate mass, the modeled data is about two to three times above the measured results, which probably reflects the assumptions made in the modeled fuel sulfur content. The sulfur contents in the fuel retrieved from the measurements were lower than the previously used assumptions by the city of Saint Petersburg when carrying out atmospheric modeling and using these measurements it was possible to better assess the impact of shipping on air quality.

Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

NASA Astrophysics Data System (ADS)

Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

2017-08-01

Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.

A hybrid model describing ion induced kinetic electron emission

NASA Astrophysics Data System (ADS)

Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.

2015-06-01

We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.

Impact of a nitrogen emission control area (NECA) for ship traffic on the future air quality in the Baltic Sea region

NASA Astrophysics Data System (ADS)

Karl, Matthias; Geyer, Beate; Bieser, Johannes; Matthias, Volker; Quante, Markus; Jalkanen, Jukka-Pekka; Johansson, Lasse; Fridell, Erik

2017-04-01

Deposition of nitrogen compounds originating from shipping activities contribute to eutrophication of the Baltic Sea and coastal areas in the Baltic Sea region. Emissions of nitrogen oxides (NOx) from shipping on the Baltic Sea are comparable to the combined land-based emissions of NOx from Finland and Sweden and have been relatively stable over the last decade. However, expected future growth of maritime transport will result in higher fuel consumption and, if not compensated by increased transport efficiency or other measures, lead to higher total emissions of NOx from shipping. For the Baltic Sea a nitrogen emission control area (NECA) will become effective in 2021 - permitting only new built ships that are compliant with stringent Tier III emission limits - with the target of reducing NOx-emissions. In order to study the effect of implementing a Baltic Sea NECA-2021 on air quality and nitrogen deposition two future scenarios were designed; one with implementation of a NECA for the Baltic Sea starting in 2021 and another with no NECA implemented. The same increase of ship traffic was assumed for both future scenarios. Since complete fleet renewal with low NOx-emitting engines is not expected until 20-30 years after the NECA entry date, year 2040 was chosen as future scenario year. The Community Multiscale Air Quality (CMAQ) model was used to simulate the current and future air quality situation. The nested simulation runs with CMAQ were performed on a horizontal resolution of 4 km × 4 km for the entire Baltic Sea region. The meteorological year 2012 was chosen for the simulation of the current and future air quality situation since the 2m-temperature and precipitation anomalies of 2012 are closely aligned to the 2004-2014 decadal average over Baltic Proper. High-resolution meteorology obtained from COSMO-CLM was used for the regional simulations. Ship emissions were generated with the Ship Traffic Emission Assessment Model (STEAM) by the Finnish Meteorological Institute (FMI) using the Automatic Identification System (AIS) network data to allocate ship positions. Gridded land-based emissions were taken from the SMOKE-EU model which is based on the official EMEP data. Future land-based emissions were reduced in accordance with current legislation. Model simulations for the current situation show that shipping emissions are the main contributor to ambient NO2 concentrations over the Baltic Sea. Shipping emissions are responsible for 40-70 % of the particulate nitrate concentrations during the summer months. Relative contribution of shipping emissions to monthly total nitrogen deposition, as a sum of oxidized and reduced nitrogen compounds, was highest in summer, with up to 60 % in the northern part of the Baltic Proper, while it was on average 10 % for other parts of the Baltic Sea. With the NECA in the Baltic Sea in effect from 2021, the reduction of reactive nitrogen concentrations and deposition in the Baltic Sea region compared to a scenario without Tier III regulations is significant.

Fuel treatment effects on tree-based forest carbon storage and emissions under modeled wildfire scenarios

Treesearch

M. Hurteau; M. North

2009-01-01

Forests are viewed as a potential sink for carbon (C) that might otherwise contribute to climate change. It is unclear, however, how to manage forests with frequent fire regimes to maximize C storage while reducing C emissions from prescribed burns or wildfire. We modeled the effects of eight different fuel treatments on treebased C storage and release over a century,...

Global time trends in PAH emissions from motor vehicles

NASA Astrophysics Data System (ADS)

Shen, Huizhong; Tao, Shu; Wang, Rong; Wang, Bin; Shen, Guofeng; Li, Wei; Su, Shenshen; Huang, Ye; Wang, Xilong; Liu, Wenxin; Li, Bengang; Sun, Kang

2011-04-01

Emission from motor vehicles is the most important source of polycyclic aromatic hydrocarbons (PAHs) in urban areas. Emission factors of individual PAHs for motor vehicles reported in the literature varied 4 to 5 orders of magnitude, leading to high uncertainty in emission inventory. In this study, key factors affecting emission factors of PAHs (EF PAH) for motor vehicles were evaluated quantitatively based on thousands of EF PAH measured in 16 countries for over 50 years. The result was used to develop a global emission inventory of PAHs from motor vehicles. It was found that country and vehicle model year are the most important factors affecting EF PAH, which can be quantified using a monovariate regression model with per capita gross domestic production (purchasing power parity) as a sole independent variable. On average, 29% of variation in log-transformed EF PAH could be explained by the model, which was equivalent to 90% reduction in overall uncertainty on arithmetic scale. The model was used to predict EF PAH and subsequently PAH emissions from motor vehicles for various countries in the world during a period from 1971 to 2030. It was estimated that the global emission reached its peak value of approximate 101 Gg in 1978 and decreased afterwards due to emission control in developed countries. The annual emission picked up again since 1990 owing to accelerated energy consumption in China and other developing countries. With more and more rigid control measures taken in the developing world, global emission of PAHs is currently passing its second peak. It was predicted that the emission would decrease from 77 Gg in 2010 to 42 Gg in 2030.

Modeling the trade-off between diet costs and methane emissions: A goal programming approach.

PubMed

Moraes, L E; Fadel, J G; Castillo, A R; Casper, D P; Tricarico, J M; Kebreab, E

2015-08-01

Enteric methane emission is a major greenhouse gas from livestock production systems worldwide. Dietary manipulation may be an effective emission-reduction tool; however, the associated costs may preclude its use as a mitigation strategy. Several studies have identified dietary manipulation strategies for the mitigation of emissions, but studies examining the costs of reducing methane by manipulating diets are scarce. Furthermore, the trade-off between increase in dietary costs and reduction in methane emissions has only been determined for a limited number of production scenarios. The objective of this study was to develop an optimization framework for the joint minimization of dietary costs and methane emissions based on the identification of a set of feasible solutions for various levels of trade-off between emissions and costs. Such a set of solutions was created by the specification of a systematic grid of goal programming weights, enabling the decision maker to choose the solution that achieves the desired trade-off level. Moreover, the model enables the calculation of emission-mitigation costs imputing a trading value for methane emissions. Emission imputed costs can be used in emission-unit trading schemes, such as cap-and-trade policy designs. An application of the model using data from lactating cows from dairies in the California Central Valley is presented to illustrate the use of model-generated results in the identification of optimal diets when reducing emissions. The optimization framework is flexible and can be adapted to jointly minimize diet costs and other potential environmental impacts (e.g., nitrogen excretion). It is also flexible so that dietary costs, feed nutrient composition, and animal nutrient requirements can be altered to accommodate various production systems. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

COLLISION-INDUCED MAGNETIC RECONNECTION AND A UNIFIED INTERPRETATION OF POLARIZATION PROPERTIES OF GRBs AND BLAZARS

DOE PAGES

Deng; Zhang; Zhang; ...

2016-04-11

The jet composition and energy dissipation mechanism of gamma-ray bursts (GRBs) and blazars are fundamental questions that remain not fully understood. One plausible model is to interpret the γ-ray emission of GRBs and optical emission of blazars as synchrotron radiation of electrons accelerated from the collision-induced magnetic dissipation regions in Poynting-flux-dominated jets. The polarization observation is an important and independent information to test this model. Based on our recent 3D relativistic MHD simulations of collision-induced magnetic dissipation of magnetically dominated blobs, here we perform calculations of the polarization properties of the emission in the dissipation region and apply the resultsmore » to model the polarization observational data of GRB prompt emission and blazar optical emission. In this article, we show that the same numerical model with different input parameters can reproduce well the observational data of both GRBs and blazars, especially the 90° polarization angle (PA) change in GRB 100826A and the 180° PA swing in blazar 3C279. This supports a unified model for GRB and blazar jets, suggesting that collision-induced magnetic reconnection is a common physical mechanism to power the relativistic jet emission from events with very different black hole masses.« less

Constraining the 2012-2014 growing season Alaskan methane budget using CARVE aircraft measurements

NASA Astrophysics Data System (ADS)

Hartery, S.; Chang, R. Y. W.; Commane, R.; Lindaas, J.; Miller, S. M.; Wofsy, S. C.; Karion, A.; Sweeney, C.; Miller, C. E.; Dinardo, S. J.; Steiner, N.; McDonald, K. C.; Watts, J. D.; Zona, D.; Oechel, W. C.; Kimball, J. S.; Henderson, J.; Mountain, M. E.

2015-12-01

Soil in northen latitudes contains rich carbon stores which have been historically preserved via permafrost within the soil bed; however, recent surface warming in these regions is allowing deeper soil layers to thaw, influencing the net carbon exchange from these areas. Due to the extreme nature of its climate, these eco-regions remain poorly understood by most global models. In this study we analyze methane fluxes from Alaska using in situ aircraft observations from the 2012-2014 Carbon in Arctic Reservoir Vulnerability Experiment (CARVE). These observations are coupled with an atmospheric particle transport model which quantitatively links surface emissions to atmospheric observations to make regional methane emission estimates. The results of this study are two-fold. First, the inter-annual variability of the methane emissions was found to be <1 Tg over the area of interest and is largely influenced by the length of time the deep soil remains unfrozen. Second, the resulting methane flux estimates and mean soil parameters were used to develop an empirical emissions model to help spatially and temporally constrain the methane exchange at the Alaskan soil surface. The empirical emissions model will provide a basis for exploring the sensitivity of methane emissions to subsurface soil temperature, soil moisture, organic carbon content, and other parameters commonly used in process-based models.

CO2 acclimation impacts leaf isoprene emissions: evidence from past to future CO2 levels

NASA Astrophysics Data System (ADS)

de Boer, Hugo; van der Laan, Annick; Dekker, Stefan; Holzinger, Rupert

2017-04-01

Isoprene is emitted by many plant species as a side-product of photosynthesis. Once in the atmosphere, isoprene exhibits climate forcing through various feedback mechanisms. In order to quantify the climate feedbacks of biogenic isoprene emission it is crucial to establish how isoprene emissions are effected by plant acclimation to rising atmospheric CO2 levels. A promising development for modelling CO2-induced changes in isoprene emissions is the Leaf-Energetic-Status model (referred to as LES-model hereafter, see Harrison et al., 2013 and Morfopoulos et al., 2014). This model simulates isoprene emissions based on the hypothesis that isoprene biosynthesis depends on the imbalance between the photosynthetic electron supply of reducing power and the electron demands of carbon fixation. The energetic imbalance is critically related to the photosynthetic electron transport capacity (Jmax) and the maximum carboxylation capacity of Rubisco (Vcmax). Here we compare predictions of the LES-model with observed isoprene emission responses of Quercus robur (pedunculate oak) specimen that acclimated to CO2 growth conditions representative of the last glacial, the present and the end of this century (200, 400 and 800 ppm, respectively) for two growing seasons. These plants were grown in walk-in growth chambers with tight control of light, temperature, humidity and CO2 concentrations. Photosynthetic biochemical parameters Vcmax and Jmax were determined with a Licor LI-6400XT photosynthesis system. The relationship between photosynthesis and isoprene emissions was measured by coupling the photosynthesis system with a Proton-Transfer Reaction Time-of-Flight Mass Spectrometer. Our empirical results support the LES-model and show that the fractional allocation of carbon to isoprene biosynthesis is reduced in response to both short-term and long-term CO2 increases. In the short term, an increase in CO2 stimulates photosynthesis through an increase in the leaf interior CO2 concentration and marginally decreases isoprene production owing to an increase in the electron demand for carbon fixation. In the long-term, acclimation to rising CO2 growth conditions leads to down regulation of both Jmax and Vcmax, which modulates the stimulating effect of rising CO2 on photosynthesis. This CO2 effect is most pronounced between sub-ambient to present CO2. Our results highlight that the LES-model provides a suitable theoretical framework to model changes in leaf isoprene emissions related to biochemical acclimation to rising CO2. References Harrison, S. P. et al: Volatile isoprenoid emissions from plastid to planet, New Phytol., 197(1), 49-57, 2013. Morfopoulos, C. et al: A model of plant isoprene emission based on available reducing power captures responses to atmospheric CO2, New Phytol., 203(1), 125-139, 2014.

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.

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

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).

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.

Modeling diffuse phosphorus emissions to assist in best management practice designing

NASA Astrophysics Data System (ADS)

Kovacs, Adam; Zessner, Matthias; Honti, Mark; Clement, Adrienne

2010-05-01

A diffuse emission modeling tool has been developed, which is appropriate to support decision-making in watershed management. The PhosFate (Phosphorus Fate) tool allows planning best management practices (BMPs) in catchments and simulating their possible impacts on the phosphorus (P) loads. PhosFate is a simple fate model to calculate diffuse P emissions and their transport within a catchment. The model is a semi-empirical, catchment scale, distributed parameter and long-term (annual) average model. It has two main parts: (a) the emission and (b) the transport model. The main input data of the model are digital maps (elevation, soil types and landuse categories), statistical data (crop yields, animal numbers, fertilizer amounts and precipitation distribution) and point information (precipitation, meteorology, soil humus content, point source emissions and reservoir data). The emission model calculates the diffuse P emissions at their source. It computes the basic elements of the hydrology as well as the soil loss. The model determines the accumulated P surplus of the topsoil and distinguishes the dissolved and the particulate P forms. Emissions are calculated according to the different pathways (surface runoff, erosion and leaching). The main outputs are the spatial distribution (cell values) of the runoff components, the soil loss and the P emissions within the catchment. The transport model joins the independent cells based on the flow tree and it follows the further fate of emitted P from each cell to the catchment outlets. Surface runoff and P fluxes are accumulated along the tree and the field and in-stream retention of the particulate forms are computed. In case of base flow and subsurface P loads only the channel transport is taken into account due to the less known hydrogeological conditions. During the channel transport, point sources and reservoirs are also considered. Main results of the transport algorithm are the discharge, dissolved and sediment-bounded P load values at any arbitrary point within the catchment. Finally, a simple design procedure has been built up to plan BMPs in the catchments and simulate their possible impacts on diffuse P fluxes as well as calculate their approximately costs. Both source and transport controlling measures have been involved into the planning procedure. The model also allows examining the impacts of alterations of fertilizer application, point source emissions as well as the climate change on the river loads. Besides this, a simple optimization algorithm has been developed to select the most effective source areas (real hot spots), which should be targeted by the interventions. The fate model performed well in Hungarian pilot catchments. Using the calibrated and validated model, different management scenarios were worked out and their effects and costs evaluated and compared to each other. The results show that the approach is suitable to effectively design BMP measures at local scale. Combinative application of the source and transport controlling BMPs can result in high P reduction efficiency. Optimization of the interventions can remarkably reduce the area demand of the necessary BMPs, consequently the establishment costs can be decreased. The model can be coupled with a larger scale catchment model to form a "screening and planning" modeling system.

Effects of endogenous factors on regional land-use carbon emissions based on the Grossman decomposition model: a case study of Zhejiang Province, China.

PubMed

Wu, Cifang; Li, Guan; Yue, Wenze; Lu, Rucheng; Lu, Zhangwei; You, Heyuan

2015-02-01

The impact of land-use change on greenhouse gas emissions has become a core issue in current studies on global change and carbon cycle. However, a comprehensive evaluation of the effects of land-use changes on carbon emissions is very necessary. This paper attempted to apply the Grossman decomposition model to estimate the scale, structural, and management effects of land-use carbon emissions based on final energy consumption by establishing the relationship between the types of land use and carbon emissions in energy consumption. It was shown that land-use carbon emissions increase from 169.5624 million tons in 2000 to 637.0984 million tons in 2010, with an annual average growth rate of 14.15%. Meanwhile, land-use carbon intensity increased from 17.59 t/ha in 2000 to 64.42 t/ha in 2010, with an average annual growth rate of 13.86%. The results indicated that rapid industrialization and urbanization in Zhejiang Province promptly increased urban land and industrial land, which consequently affected land-use extensive emissions. The structural and management effects did not mitigate land-use carbon emissions. By contrast, both factors evidently affected the growth of carbon emissions because of the rigid demands of energy-intensive land-use types and the absence of land management. Results called for the policy implications of optimizing land-use structures and strengthening land-use management.

Effects of Endogenous Factors on Regional Land-Use Carbon Emissions Based on the Grossman Decomposition Model: A Case Study of Zhejiang Province, China

NASA Astrophysics Data System (ADS)

Wu, Cifang; Li, Guan; Yue, Wenze; Lu, Rucheng; Lu, Zhangwei; You, Heyuan

2015-02-01

The impact of land-use change on greenhouse gas emissions has become a core issue in current studies on global change and carbon cycle. However, a comprehensive evaluation of the effects of land-use changes on carbon emissions is very necessary. This paper attempted to apply the Grossman decomposition model to estimate the scale, structural, and management effects of land-use carbon emissions based on final energy consumption by establishing the relationship between the types of land use and carbon emissions in energy consumption. It was shown that land-use carbon emissions increase from 169.5624 million tons in 2000 to 637.0984 million tons in 2010, with an annual average growth rate of 14.15 %. Meanwhile, land-use carbon intensity increased from 17.59 t/ha in 2000 to 64.42 t/ha in 2010, with an average annual growth rate of 13.86 %. The results indicated that rapid industrialization and urbanization in Zhejiang Province promptly increased urban land and industrial land, which consequently affected land-use extensive emissions. The structural and management effects did not mitigate land-use carbon emissions. By contrast, both factors evidently affected the growth of carbon emissions because of the rigid demands of energy-intensive land-use types and the absence of land management. Results called for the policy implications of optimizing land-use structures and strengthening land-use management.

Correction of Measured Taxicab Exhaust Emission Data Based on Cmem Modle

NASA Astrophysics Data System (ADS)

Li, Q.; Jia, T.

2017-09-01

Carbon dioxide emissions from urban road traffic mainly come from automobile exhaust. However, the carbon dioxide emissions obtained by the instruments are unreliable due to time delay error. In order to improve the reliability of data, we propose a method to correct the measured vehicles' carbon dioxide emissions from instrument based on the CMEM model. Firstly, the synthetic time series of carbon dioxide emissions are simulated by CMEM model and GPS velocity data. Then, taking the simulation data as the control group, the time delay error of the measured carbon dioxide emissions can be estimated by the asynchronous correlation analysis, and the outliers can be automatically identified and corrected using the principle of DTW algorithm. Taking the taxi trajectory data of Wuhan as an example, the results show that (1) the correlation coefficient between the measured data and the control group data can be improved from 0.52 to 0.59 by mitigating the systematic time delay error. Furthermore, by adjusting the outliers which account for 4.73 % of the total data, the correlation coefficient can raise to 0.63, which suggests strong correlation. The construction of low carbon traffic has become the focus of the local government. In order to respond to the slogan of energy saving and emission reduction, the distribution of carbon emissions from motor vehicle exhaust emission was studied. So our corrected data can be used to make further air quality analysis.

Effect of severe geomagnetic disturbances on the atomic oxygen airglow emissions

NASA Astrophysics Data System (ADS)

Sunil Krishna, M.; Bag, T.

2013-12-01

The atomic oxygen greenline (557.7nm) and redline emission (630.0 nm) are the most readily observed and prominent lines in the nightglow. These emissions can be used as precursors for a variety of physical and chemical processes that occur in the upper mesosphere and lower thermosphere. There are a multitude of effects of space weather on the Earth's atmosphere. The decay of ring current is a very important parameter which can induce variation in the densities of few important species in the atmosphere which are of airglow interest. The connection of variation of airglow emissions with the extreme space weather conditions is not very well established. In the present study, severe geomagnetic storms and their effect on the airglow emissions such as 557.7 nm and 630.0 nm emissions is studied. This study is primarily based on photochemical models with the necessary input obtained from a combination of experimental observations and empirical models. We have tried to understand the effect of severe space weather conditions on few very important airglow emissions in terms of volume emission rates, change in the peak emission height. Based on the variation an attempt has been made to understand the cause of the variation and further to link the variations in the ring current to the airglow chemistry. The study presents the results of calculations performed for the most severe geomagnetic storms occurred over the recent past because of variety of causes on Sun.

Analysis of Emission Effects Related to Drivers' Compliance Rates for Cooperative Vehicle-Infrastructure System at Signalized Intersections.

PubMed

Liao, Ruohua; Chen, Xumei; Yu, Lei; Sun, Xiaofei

2018-01-12

Unknown remaining time of signal phase at a signalized intersection generally results in extra accelerations and decelerations that increase variations of operating conditions and thus emissions. A cooperative vehicle-infrastructure system can reduce unnecessary speed changes by establishing communications between vehicles and the signal infrastructure. However, the environmental benefits largely depend on drivers' compliance behaviors. To quantify the effects of drivers' compliance rates on emissions, this study applied VISSIM 5.20 (Planung Transport Verkehr AG, Karlsruhe, Germany) to develop a simulation model for a signalized intersection, in which light duty vehicles were equipped with a cooperative vehicle-infrastructure system. A vehicle-specific power (VSP)-based model was used to estimate emissions. Based on simulation data, the effects of different compliance rates on VSP distributions, emission factors, and total emissions were analyzed. The results show the higher compliance rate decreases the proportion of VSP bin = 0, which means that the frequencies of braking and idling were lower and light duty vehicles ran more smoothly at the intersection if more light duty vehicles complied with the cooperative vehicle-infrastructure system, and emission factors for light duty vehicles decreased significantly as the compliance rate increased. The case study shows higher total emission reductions were observed with higher compliance rate for all of CO₂, NO x , HC, and CO emissions. CO₂ was reduced most significantly, decreased by 16% and 22% with compliance rates of 0.3 and 0.7, respectively.