[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.

Emission rates of regulated pollutants from on-road heavy-duty diesel vehicles

NASA Astrophysics Data System (ADS)

Shah, Sandip D.; Johnson, Kent C.; Wayne Miller, J.; Cocker, David R.

Emissions from heavy-duty diesel (HDD) vehicles are affected by many factors. Changes in engine technology, operating mode, fuel properties, vehicle speed and ambient conditions can have significant effects on emission rates of regulated species. This paper presents the results of on-road emissions testing of 11 HDD vehicles (model years 1996-2000) over the ARB Four Phase driving schedule and the urban dynamometer driving schedule (UDDS). Emission rates were found to be highly dependent on vehicle operating mode. Per mile NO x emission rates for vehicle operation at low speeds, in simulated congested traffic, were three times higher per mile emissions then while cruising on the freeway. Comparisons of NO x emission factors to EMFAC baseline emission factors were within 5-40% for vehicles of various model years tested over the UDDS. A comparison of NO x emission factors for a weighted average of the ARB four phase driving schedule yielded values within 17-57% of EMFAC values. Generally, particulate matter (PM) emission rates were lower than EMFAC values.

On-road particulate emission measurement

NASA Astrophysics Data System (ADS)

Mazzoleni, Claudio

Particulate matter (PM) suspended in the atmosphere has harmful health effects, contributes to visibility impairment, and affects atmospheric radiative transfer, thereby contributing to global change. Vehicles contribute substantially to the ambient PM concentration in urban areas, yet the fraction of ambient PM originating from vehicle emissions is poorly characterized because suitable measurement methods have not been available. This dissertation describes the development and the use of a new vehicle emission remote sensing system (VERSS) for the on-road measurement of PM emission factors for vehicles. The PM VERSS measures PM by ultraviolet backscattering and transmission. PM backscattering and transmission mass efficiencies have been calculated from Mie theory based on an homogeneous spherical model for gasoline particles and on a two-layers, spherical model for diesel particles. The VERSS was used in a large-scale study in Las Vegas, NV. A commercial gaseous VERSS was used for the measurement of gaseous emission factors (i.e., carbon monoxide, hydrocarbons, and nitrogen oxide). Speed and acceleration were also measured for each vehicle. A video image of each vehicle's rear license plate was acquired and license plate numbers were matched with the Clark County department of motor vehicle database to retrieve vehicle information such as model year, vehicle weight category and engine ignition type. PM VERSS has precisely estimated PM fleet average emission factors and clearly shown the dependence of PM emission factors on vehicle model year. Under mostly hot-stabilized operation, diesel vehicle PM emission factors are about 25 times higher than those of gasoline vehicles. Furthermore, the fleet frequency distributions of PM emission factors are highly skewed, meaning that most of the fleet emission factor is accounted for by a small portion of the fleet. The PM VERSS can measure PM emission factors for these high emitting vehicles on an individual basis. PM emission factors measured during this study are comparable to results of previous studies. Gaseous emissions in Las Vegas are similar to those in other urban areas in the United States. For individual vehicles, the pollutants do not correlate well with each other, however averaged data clearly show functional relationships.

Real-time emissions from construction equipment compared with model predictions.

PubMed

Heidari, Bardia; Marr, Linsey C

2015-02-01

The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO), nitrogen oxides (NOx), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases.

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Modeling long-term carbon residue in the ocean-atmosphere system following large CO2 emissions

NASA Astrophysics Data System (ADS)

Towles, N. J.; Olson, P.; Gnanadesikan, A.

2013-12-01

We use the LOSCAR carbon cycle model (Zeebe et al., 2009; Zeebe, 2012) to calculate the residual carbon in the ocean and atmosphere following large CO2 emissions. We consider the system response to CO2 emissions ranging from 100 to 20000 PgC, and emission durations from 100 yr to 100 kyr, subject to a wide range of system parameters such as the strengths of silicate weathering and the oceanic biological carbon pump. We define the carbon gain factor as the ratio of residual carbon in the ocean-atmosphere to the total emitted carbon. For moderate sized emissions shorter than about 50 kyr, we find that the carbon gain factor grows during the emission and peaks at about 1.7, primarily due to the erosion of carbonate marine sediments. In contrast, for longer emissions, the carbon gain factor peaks at a smaller value, and for very large emissions (more than 5000 PgC), the gain factor decreases with emission size due to carbonate sediment exhaustion. This gain factor is sensitive to model parameters such as low latitude efficiency of the biological pump. The timescale for removal of the residual carbon (reducing the carbon gain factor to zero) depends strongly on the assumed sensitivity of silicate weathering to atmospheric pCO2, and ranges from less than one million years to several million years.

Quantifying Uncertainty in Daily Temporal Variations of Atmospheric NH3 Emissions Following Application of Chemical Fertilizers

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2014-12-01

Improving modeling predictions of atmospheric particulate matter and deposition of reactive nitrogen requires representative emission inventories of precursor species, such as ammonia (NH3). Anthropogenic NH3 is primarily emitted to the atmosphere from agricultural sources (80-90%) with dominant contributions (56%) from chemical fertilizer usage (CFU) in regions like Midwest USA. Local crop management practices vary spatially and temporally, which influence regional air quality. To model the impact of CFU, NH3 emission inputs to chemical transport models are obtained from the National Emission Inventory (NEI). NH3 emissions from CFU are typically estimated by combining annual fertilizer sales data with emission factors. The Sparse Matrix Operator Kernel Emissions (SMOKE) model is used to disaggregate annual emissions to hourly scale using temporal factors. These factors are estimated by apportioning emissions within each crop season in proportion to the nitrogen applied and time-averaged to the hourly scale. Such approach does not reflect influence of CFU for different crops and local weather and soil conditions. This study provides an alternate approach for estimating temporal factors for NH3 emissions. The DeNitrification DeComposition (DNDC) model was used to estimate daily variations in NH3 emissions from CFU at 14 Central Illinois locations for 2002-2011. Weather, crop and soil data were provided as inputs. A method was developed to estimate site level CFU by combining planting and harvesting dates, nitrogen management and fertilizer sales data. DNDC results indicated that annual NH3 emissions were within ±15% of SMOKE estimates. Daily modeled emissions across 10 years followed similar distributions but varied in magnitudes within ±20%. Individual emission peaks on days after CFU were 2.5-8 times greater as compared to existing estimates from SMOKE. By identifying the episodic nature of NH3 emissions from CFU, this study is expected to provide improvements in predicting atmospheric particulate matter concentrations and deposition of reactive nitrogen.

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.

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/).

Modeling particulate matter emissions during mineral loading process under weak wind simulation.

PubMed

Zhang, Xiaochun; Chen, Weiping; Ma, Chun; Zhan, Shuifen

2013-04-01

The quantification of particulate matter emissions from mineral handling is an important problem for the quantification of global emissions on industrial sites. Mineral particulate matter emissions could adversely impact environmental quality in mining regions, transport regions, and even on a global scale. Mineral loading is an important process contributing to mineral particulate matter emissions, especially under weak wind conditions. Mathematical models are effective ways to evaluate particulate matter emissions during the mineral loading process. The currently used empirical models based on the form of a power function do not predict particulate matter emissions accurately under weak wind conditions. At low particulate matter emissions, the models overestimated, and at high particulate matter emissions, the models underestimated emission factors. We conducted wind tunnel experiments to evaluate the particulate matter emission factors for the mineral loading process. A new approach based on the mathematical form of a logistical function was developed and tested. It provided a realistic depiction of the particulate matter emissions during the mineral loading process, accounting for fractions of fine mineral particles, dropping height, and wind velocity. Copyright © 2013 Elsevier B.V. All rights reserved.

Uncertainties of isoprene emissions in the MEGAN model estimated for a coniferous and broad-leaved mixed forest in Southern China

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

Situ, S.; Wang, Xuemei; Guenther, Alex B.

2014-12-01

Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as highmore » as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.« less

Chamber study of PCB emissions from caulking materials and light ballasts.

PubMed

Liu, Xiaoyu; Guo, Zhishi; Krebs, Kenneth A; Stinson, Rayford A; Nardin, Joshua A; Pope, Robert H; Roache, Nancy F

2015-10-01

The emissions of polychlorinated biphenyl (PCB) congeners from thirteen caulk samples were tested in a micro-chamber system. Twelve samples were from PCB-contaminated buildings and one was prepared in the laboratory. Nineteen light ballasts collected from buildings that represent 13 different models from five manufacturers were tested in 53-L environmental chambers. The rates of PCB congener emissions from caulking materials and light ballasts were determined. Several factors that may have affected the emission rates were evaluated. The experimentally determined emission factors showed that, for a given PCB congener, there is a linear correlation between the emission factor and the concentration of the PCB congener in the source. Furthermore, the test results showed that an excellent log-linear correlation exists between the normalized emission factor and the vapor pressure (coefficient of determination, r(2)⩾0.8846). The PCB congener emissions from ballasts at or near room temperature were relatively low with or without electrical load. However, the PCB congener emission rates increased significantly as the temperature increased. The results of this research provide new data and models for ranking the primary sources of PCBs and supports the development and refinement of exposure assessment models for PCBs. Published by Elsevier Ltd.

Canopy Level Emissions of 2-methyl-3-buten-2-ol ...

EPA Pesticide Factsheets

Emissions of biogenic volatile organic compounds (BVOC) observed during 2007 from a Pinus taeda experimental plantation in Central North Carolina are compared with model estimates from MEGAN 2.1. Relaxed Eddy Accumulation (REA) estimates of 2-methyl-3-buten-2-ol (MBO) fluxes are a factor of 3-4 higher than model estimates. MEGAN2.1 monoterpene emission estimates were approximately a factor of two higher than REA flux measurements. MEGAN2.1 β-caryophyllene emission estimates were within 60% of growing season REA flux estimates, but were several times higher than REA fluxes during cooler, dormant season periods. The sum of other sesquiterpene emissions estimated by MEGAN2.1 was several times higher than REA estimates throughout the year. Model components are examined to understand these discrepancies. Summertime LAI (and therefore foliar biomass) is a factor of two higher than assumed in MEGAN for the Pinus taeda default. Increasing the canopy mean MBO emission factor from 0.35 to 1.0 mg m-2 hr-1 also reduces MEGAN2.1 vs flux differences. This increase is within current emission factor uncertainties. The algorithm within MEGAN which adjusts isoprene emission estimates as a function of the previous 24 hour’s temperatures and light seems to also improve seasonal MEGAN MBO correlation with REA fluxes. Including the effects of the previous 240 hours, however, seems to degrade temporal model correlation with fluxes. This paper describes an emission inventory and mod

Effects of improved spatial and temporal modeling of on-road vehicle emissions.

PubMed

Lindhjem, Christian E; Pollack, Alison K; DenBleyker, Allison; Shaw, Stephanie L

2012-04-01

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.

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.

Analysis of particulate emissions from tropical biomass burning using a global aerosol model and long-term surface observations

NASA Astrophysics Data System (ADS)

Reddington, Carly L.; Spracklen, Dominick V.; Artaxo, Paulo; Ridley, David A.; Rizzo, Luciana V.; Arana, Andrea

2016-09-01

We use the GLOMAP global aerosol model evaluated against observations of surface particulate matter (PM2.5) and aerosol optical depth (AOD) to better understand the impacts of biomass burning on tropical aerosol over the period 2003 to 2011. Previous studies report a large underestimation of AOD over regions impacted by tropical biomass burning, scaling particulate emissions from fire by up to a factor of 6 to enable the models to simulate observed AOD. To explore the uncertainty in emissions we use three satellite-derived fire emission datasets (GFED3, GFAS1 and FINN1). In these datasets the tropics account for 66-84 % of global particulate emissions from fire. With all emission datasets GLOMAP underestimates dry season PM2.5 concentrations in regions of high fire activity in South America and underestimates AOD over South America, Africa and Southeast Asia. When we assume an upper estimate of aerosol hygroscopicity, underestimation of AOD over tropical regions impacted by biomass burning is reduced relative to previous studies. Where coincident observations of surface PM2.5 and AOD are available we find a greater model underestimation of AOD than PM2.5, even when we assume an upper estimate of aerosol hygroscopicity. Increasing particulate emissions to improve simulation of AOD can therefore lead to overestimation of surface PM2.5 concentrations. We find that scaling FINN1 emissions by a factor of 1.5 prevents underestimation of AOD and surface PM2.5 in most tropical locations except Africa. GFAS1 requires emission scaling factor of 3.4 in most locations with the exception of equatorial Asia where a scaling factor of 1.5 is adequate. Scaling GFED3 emissions by a factor of 1.5 is sufficient in active deforestation regions of South America and equatorial Asia, but a larger scaling factor is required elsewhere. The model with GFED3 emissions poorly simulates observed seasonal variability in surface PM2.5 and AOD in regions where small fires dominate, providing independent evidence that GFED3 underestimates particulate emissions from small fires. Seasonal variability in both PM2.5 and AOD is better simulated by the model using FINN1 emissions. Detailed observations of aerosol properties over biomass burning regions are required to better constrain particulate emissions from fires.

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.

Contributions of wood smoke and vehicle emissions to ambient concentrations of volatile organic compounds and particulate matter during the Yakima wintertime nitrate study

NASA Astrophysics Data System (ADS)

VanderSchelden, Graham; de Foy, Benjamin; Herring, Courtney; Kaspari, Susan; VanReken, Tim; Jobson, Bertram

2017-02-01

A multiple linear regression (MLR) chemical mass balance model was applied to data collected during an air quality field experiment in Yakima, WA, during January 2013 to determine the relative contribution of residential wood combustion (RWC) and vehicle emissions to ambient pollutant levels. Acetonitrile was used as a chemical tracer for wood burning and nitrogen oxides (NOx) as a chemical tracer for mobile sources. RWC was found to be a substantial source of gas phase air toxics in wintertime. The MLR model found RWC primarily responsible for emissions of formaldehyde (73%), acetaldehyde (69%), and black carbon (55%) and mobile sources primarily responsible for emissions of carbon monoxide (CO; 83%), toluene (81%), C2-alkylbenzenes (81%), and benzene (64%). When compared with the Environmental Protection Agency's 2011 winter emission inventory, the MLR results suggest that the contribution of RWC to CO emissions was underestimated in the inventory by a factor of 2. Emission ratios to NOx from the MLR model agreed to within 25% with wintertime emission ratios predicted from the Motor Vehicle Emissions Simulator (MOVES) 2010b emission model for Yakima County for all pollutants modeled except for CO, C2-alkylbenzenes, and black carbon. The MLR model results suggest that MOVES was overpredicting mobile source emissions of CO relative to NOx by a factor of 1.33 and black carbon relative to NOx by about a factor of 3.

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.

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

Seasonal and interannual variations in CO and BC emissions from open biomass burning in Southern Africa during 1998-2005

NASA Astrophysics Data System (ADS)

Ito, Akinori; Ito, Akihiko; Akimoto, Hajime

2007-06-01

We estimate the emissions of carbon monoxide (CO) and black carbon (BC) from open vegetation fires in the Southern Hemisphere Africa from 1998 to 2005 using satellite information in conjunction with a biogeochemical model. Monthly burned areas at a 0.5-degree resolution are estimated from the Visible InfraRed Scanner (VIRS) fire count product and the MODerate resolution Imaging Spectroradiometer (MODIS) burned area data set associated with the MODIS tree cover imagery in grasslands and woodlands. The monthly fuel load distributions are derived from a 0.5-degree terrestrial carbon cycle model in conjunction with satellite data. The monthly maps of combustion factors and emission factors are estimated using empirical models that predict the effects of fuel conditions on these factors in grasslands and woodlands. Our annually averaged effective CO and BC emissions per area burned are 27 g CO m-2 and 0.17 g BC m-2 which are consistent with the products of fuel consumption and emission factors typically measured in southern Africa. The CO and BC emissions from open vegetation burning in southern Africa range from 45 Tg CO yr-1 and 0.26 Tg BC yr-1 for 2002 to 75 Tg CO yr-1 and 0.42 Tg BC yr-1 for 1998. The monthly averaged burned areas from VIRS fire counts peak earlier than modeled CO emissions. This characteristic delay between burned areas and emissions is mainly explained by significant changes in combustion factors for woodlands in our model. Consequently, the peaks in CO and BC emissions from our bottom-up approach are identical to those from previous top-down estimates using the Measurement Of the Pollution In The Troposphere (MOPITT) and the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data.

Source apportionment of VOCs in the Los Angeles area using positive matrix factorization

NASA Astrophysics Data System (ADS)

Brown, Steven G.; Frankel, Anna; Hafner, Hilary R.

Eight 3-h speciated hydrocarbon measurements were collected daily by the South Coast Air Quality Management District (SCAQMD) as part of the Photochemical Assessment Monitoring Stations (PAMS) program during the summers of 2001-03 at two sites in the Los Angeles air basin, Azusa and Hawthorne. Over 30 hydrocarbons from over 500 samples at Azusa and 600 samples at Hawthorne were subsequently analyzed using the multivariate receptor model positive matrix factorization (PMF). At Azusa and Hawthorne, five and six factors were identified, respectively, with a good comparison between predicted and measured mass. At Azusa, evaporative emissions (a median of 31% of the total mass), motor vehicle exhaust (22%), liquid/unburned gasoline (27%), coatings (17%), and biogenic emissions (3%) factors were identified. Factors identified at Hawthorne were evaporative emissions (a median of 34% of the total mass), motor vehicle exhaust (24%), industrial process losses (15%), natural gas (13%), liquid/unburned gasoline (13%), and biogenic emissions (1%). Together, the median contribution from mobile source-related factors (exhaust, evaporative emissions, and liquid/unburned gasoline) was 80% and 71% at Azusa and Hawthorne, respectively, similar to previous source apportionment results using the chemical mass balance (CMB) model. There is a difference in the distribution among mobile source factors compared to the CMB work, with an increase in the contribution from evaporative emissions, though the cause (changes in emissions or differences between models) is unknown.

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.

Comparison of the predictions of two road dust emission models with the measurements of a mobile van

NASA Astrophysics Data System (ADS)

Kauhaniemi, M.; Stojiljkovic, A.; Pirjola, L.; Karppinen, A.; Härkönen, J.; Kupiainen, K.; Kangas, L.; Aarnio, M. A.; Omstedt, G.; Denby, B. R.; Kukkonen, J.

2014-02-01

The predictions of two road dust suspension emission models were compared with the on-site mobile measurements of suspension emission factors. Such a quantitative comparison has not previously been reported in the reviewed literature. The models used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and the Swedish-Finnish FORE model (Forecasting Of Road dust Emissions). These models describe particulate matter generated by the wear of road surface due to traction control methods and processes that control the suspension of road dust particles into the air. An experimental measurement campaign was conducted using a mobile laboratory called SNIFFER, along two selected road segments in central Helsinki in 2007 and 2008. The suspended PM10 concentration was measured behind the left rear tyre and the street background PM10 concentration in front of the van. Both models reproduced the measured seasonal variation of suspension emission factors fairly well during both years at both measurement sites. However, both models substantially under-predicted the measured emission values. The results indicate that road dust emission models can be directly compared with mobile measurements; however, more extensive and versatile measurement campaigns will be needed in the future.

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.

PubMed

Ryan, Nicole A; Johnson, Jeremiah X; Keoleian, Gregory A

2016-09-06

Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.

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.

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.

Modelling site-specific N2O emission factors from Austrian agricultural soils for targeted mitigation measures (NitroAustria)

NASA Astrophysics Data System (ADS)

Amon, Barbara; Zechmeister-Boltenstern, Sophie; Kasper, Martina; Foldal, Cecilie; Schiefer, Jasmin; Kitzler, Barbara; Schwarzl, Bettina; Zethner, Gerhard; Anderl, Michael; Sedy, Katrin; Gaugitsch, Helmut; Dersch, Georg; Baumgarten, Andreas; Haas, Edwin; Kiese, Ralf

2016-04-01

Results from a previous project "FarmClim" highlight that the IPCC default emission factor is not able to reflect region specific N2O emissions from Austrian arable soils. The methodology is limited in identifying hot spots and hot moments of N2O emissions. When estimations are based on default emission factors no recommendations can be given on optimisation measures that would lead to a reduction of soil N2O emissions. The better the knowledge is about Nitrogen and Carbon budgets in Austrian agricultural managed soils the better the situation can be reflected in the Austrian GHG emission inventory calculations. Therefore national and regionally modelled emission factors should improve the evidence for national deviation from the IPCC default emission factors and reduce the uncertainties. The overall aim of NitroAustria is to identify the drivers for N2O emissions on a regional basis taking different soil types, climate, and agricultural management into account. We use the LandscapeDNDC model to update the N2O emission factors for N fertilizer and animal manure applied to soils. Key regions in Austria were selected and region specific N2O emissions calculated. The model runs at sub-daily time steps and uses data such as maximum and minimum air temperature, precipitation, radiation, and wind speed as meteorological drivers. Further input data are used to reflect agricultural management practices, e.g., planting/harvesting, tillage, fertilizer application, irrigation and information on soil and vegetation properties for site characterization and model initialization. While at site scale, arable management data (crop cultivation, rotations, timings etc.) is obtained by experimental data from field trials or observations, at regional scale such data need to be generated using region specific proxy data such as land use and management statistics, crop cultivations and yields, crop rotations, fertilizer sales, manure resulting from livestock units etc. The farming community can only profit from NitroAustria, if model developments and results are integrated into the national emission inventory. Trade-offs between different greenhouse gas emissions and other nitrogen losses have to be discussed. The derivation of suitable mitigation options by optimization of common and evaluation of potential management practices for current and future climatic conditions is crucial to minimize threats to the environment while ensuring the long-term productivity and sustainability of agro-ecosystems. From the results gained in NitroAustria we will be able to show potential environmental impacts and propose measures for a policy framework towards climate friendly farming.

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...

[Measurement model of carbon emission from forest fire: a review].

PubMed

Hu, Hai-Qing; Wei, Shu-Jing; Jin, Sen; Sun, Long

2012-05-01

Forest fire is the main disturbance factor for forest ecosystem, and an important pathway of the decrease of vegetation- and soil carbon storage. Large amount of carbonaceous gases in forest fire can release into atmosphere, giving remarkable impacts on the atmospheric carbon balance and global climate change. To scientifically and effectively measure the carbonaceous gases emission from forest fire is of importance in understanding the significance of forest fire in the carbon balance and climate change. This paper reviewed the research progress in the measurement model of carbon emission from forest fire, which covered three critical issues, i. e., measurement methods of forest fire-induced total carbon emission and carbonaceous gases emission, affecting factors and measurement parameters of measurement model, and cause analysis of the uncertainty in the measurement of the carbon emissions. Three path selections to improve the quantitative measurement of the carbon emissions were proposed, i. e., using high resolution remote sensing data and improving algorithm and estimation accuracy of burned area in combining with effective fuel measurement model to improve the accuracy of the estimated fuel load, using high resolution remote sensing images combined with indoor controlled environment experiments, field measurements, and field ground surveys to determine the combustion efficiency, and combining indoor controlled environment experiments with field air sampling to determine the emission factors and emission ratio.

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.

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

Greenberg, Jim; Penuelas, J.; Guenther, Alex B.

To survey landscape-scale fluxes of biogenic gases, a100-meterTeflon tube was attached to a tethered balloon as a sampling inlet for a fast response Proton Transfer Reaction Mass Spectrometer (PTRMS). Along with meteorological instruments deployed on the tethered balloon and at 3-mand outputs from a regional weather model, these observations were used to estimate landscape scale biogenic volatile organic compound fluxes with two micrometeorological techniques: mixed layer variance and surface layer gradients. This highly mobile sampling system was deployed at four field sites near Barcelona to estimate landscape-scale BVOC emission factors in a relatively short period (3 weeks). The two micrometeorologicalmore » techniques agreed within the uncertainty of the flux measurements at all four sites even though the locations had considerable heterogeneity in species distribution and complex terrain. The observed fluxes were significantly different than emissions predicted with an emission model using site-specific emission factors and land-cover characteristics. Considering the wide range in reported BVOC emission factors of VOCs for individual vegetation species (more than an order of magnitude), this flux estimation technique is useful for constraining BVOC emission factors used as model inputs.« less

Modeling greenhouse gas emissions from dairy farms

USDA-ARS?s Scientific Manuscript database

Evaluation and mitigation of greenhouse gas emissions from dairy farms requires a comprehensive approach that integrates the impacts and interactions of all important sources and sinks. This approach requires some form of modeling. Types of models commonly used include empirical emission factors, pr...

Chamber study of PCBemissions from caulking materials and ...

EPA Pesticide Factsheets

The emissions of polychlorinated biphenyl (PCB) congeners from 13 caulk samples were tested in a micro-chamber system. Twelve samples were from PCB-contaminated buildings and one was prepared in the laboratory. Nineteen light ballasts collected from buildings that represent 13 different models from five manufacturers were tested in 53-liter environmental chambers. The rates of PCB congener emissions from caulking materials and light ballasts were determined. Several factors that may have affected the emission rates were evaluated. The experimentally determined emission factors showed that, for a given PCB congener, there is a linear correlation between the emission factor and the concentration of the PCB congener in the source. Furthermore, the test results showed that an excellent log-linear correlation exists between the normalized emission factor and the vapor pressure (coefficient of determination, r2 ≥0.8846). The PCB congener emissions from ballasts at or near room temperature were relatively low with or without electrical load. However, the PCB congener emission rates increased significantly as the temperature increased. The results of this research provide new data and models for ranking the primary sources of PCBs and supports the development and refinement of exposure assessment models for PCBs. This study supplemented and complemented the field measurements in buildings conducted by U.S. EPA National Exposure Research Laboratory by providing a bette

New global fire emission estimates and evaluation of volatile organic compounds

Treesearch

C. Wiedinmyer; L. K. Emmons; S. K. Akagi; R. J. Yokelson; J. J. Orlando; J. A. Al-Saadi; A. J. Soja

2010-01-01

A daily, high-resolution, global fire emissions model has been built to estimate emissions from open burning for air quality modeling applications: The Fire INventory from NCAR (FINN version 1). The model framework uses daily fire detections from the MODIS instruments and updated emission factors, specifically for speciated non-methane organic compounds (NMOC). Global...

Odor and chemical emissions from dairy and swine facilities: Part 1 - project overview and collection methods

USDA-ARS?s Scientific Manuscript database

Livestock facilities have received numerous criticisms due to their emissions of odorous air and chemicals. Hence, there is a significant need for odor emission factors and identification of principle odorous chemicals. Odor emission factors are used as inputs to odor setback models, while chemica...

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...

Comparison of the predictions of two road dust emission models with the measurements of a mobile van

NASA Astrophysics Data System (ADS)

Kauhaniemi, M.; Stojiljkovic, A.; Pirjola, L.; Karppinen, A.; Härkönen, J.; Kupiainen, K.; Kangas, L.; Aarnio, M. A.; Omstedt, G.; Denby, B. R.; Kukkonen, J.

2014-09-01

The predictions of two road dust suspension emission models were compared with the on-site mobile measurements of suspension emission factors. Such a quantitative comparison has not previously been reported in the reviewed literature. The models used were the Nordic collaboration model NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and the Swedish-Finnish FORE model (Forecasting Of Road dust Emissions). These models describe particulate matter generated by the wear of road surface due to traction control methods and processes that control the suspension of road dust particles into the air. An experimental measurement campaign was conducted using a mobile laboratory called SNIFFER, along two selected road segments in central Helsinki in 2007 and 2008. The suspended PM10 concentration was measured behind the left rear tyre and the street background PM10 concentration in front of the van. Both models reproduced the measured seasonal variation of suspension emission factors fairly well during both years at both measurement sites. However, both models substantially under-predicted the measured emission values. The article illustrates the challenges in conducting road suspension measurements in densely trafficked urban conditions, and the numerous requirements for input data that are needed for accurately applying road suspension emission models.

Low modeled ozone production suggests underestimation of precursor emissions (especially NOx) in Europe

NASA Astrophysics Data System (ADS)

Oikonomakis, Emmanouil; Aksoyoglu, Sebnem; Ciarelli, Giancarlo; Baltensperger, Urs; Prévôt, André Stephan Henry

2018-02-01

High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone-temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10-20 ppb and overestimates the lower ones (< 40 ppb) by 5-15 ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone-temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, four scenarios were tested: (i) increased volatile organic compound (VOC) emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased nitrogen oxide (NOx) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased traffic-only NOx emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NOx emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone-temperature correlation is also better when NOx emissions are doubled. In the Benelux area, however, the third scenario (where both NOx and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NOx emissions by a factor of 4 gave very similar results to the doubling of all NOx emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NOx emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 °C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NOx) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.

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.

Evaluation of green house gas emissions models.

DOT National Transportation Integrated Search

2014-11-01

The objective of the project is to evaluate the GHG emissions models used by transportation agencies and industry leaders. Factors in the vehicle : operating environment that may affect modal emissions, such as, external conditions, : vehicle fleet c...

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

Research on impacts of population-related factors on carbon emissions in Beijing from 1984 to 2012

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

Yang, Yayun; Zhao, Tao; Wang, Yanan, E-mail: wyn3615@126.com

Carbon emissions related to population factors have aroused great attention around the world. A multitude of literature mainly focused on single demographic impacts on environmental issues at the national level, and comprehensive studies concerning population-related factors at a city level are rare. This paper employed STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model incorporating PLS (Partial least squares) regression method to examine the influence of population-related factors on carbon emissions in Beijing from 1984 to 2012. Empirically results manifest that urbanization is the paramount driver. Changes in population age structure have significantly positive impacts on carbon emissions,more » and shrinking young population, continuous expansion of working age population and aging population will keep on increasing environmental pressures. Meanwhile, shrinking household size and expanding floating population boost the discharge of carbon emissions. Besides, per capita consumption is an important contributor of carbon emissions, while industry energy intensity is the main inhibitory factor. Based upon these findings and the specific circumstances of Beijing, policies such as promoting clean and renewable energy, improving population quality and advocating low carbon lifestyles should be enhanced to achieve targeted emissions reductions. - Highlights: • We employed the STIRPAT model to identify population-related factors of carbon emissions in Beijing. • Urbanization is the paramount driver of carbon emissions. • Changes in population age structure exert significantly positive impacts on carbon emissions. • Shrinking household size, expanding floating population and improving consumption level increase carbon emissions. • Industry energy intensity decreases carbon emissions.« less

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR CO FOR PREDICTING REAL-TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's (EPA) National Exposure Research Laboratory (NERL) has initiated a project to improve the methodology for modeling human exposure to motor vehicle emission. The overall project goal is to develop improved methods for modeling...

Road vehicle emission factors development: A review

NASA Astrophysics Data System (ADS)

Franco, Vicente; Kousoulidou, Marina; Muntean, Marilena; Ntziachristos, Leonidas; Hausberger, Stefan; Dilara, Panagiota

2013-05-01

Pollutant emissions need to be accurately estimated to ensure that air quality plans are designed and implemented appropriately. Emission factors (EFs) are empirical functional relations between pollutant emissions and the activity that causes them. In this review article, the techniques used to measure road vehicle emissions are examined in relation to the development of EFs found in emission models used to produce emission inventories. The emission measurement techniques covered include those most widely used for road vehicle emissions data collection, namely chassis and engine dynamometer measurements, remote sensing, road tunnel studies and portable emission measurements systems (PEMS). The main advantages and disadvantages of each method with regards to emissions modelling are presented. A review of the ways in which EFs may be derived from test data is also performed, with a clear distinction between data obtained under controlled conditions (engine and chassis dynamometer measurements using standard driving cycles) and measurements under real-world operation.

Description and History of the MOBILE Highway Vehicle Emission Factor Model

EPA Pesticide Factsheets

MOBILE is an EPA model for estimating pollution from highway vehicles. It has been superseded by the Motor Vehicle Emission Simulator (MOVES). MOBILE calculates emissions of hydrocarbons (HC), oxides of nitrogen (NOx) and carbon monoxide (CO).

DEVELOPMENT OF REAL-TIME SITE-SPECIFIC MICROSCALE EMISSION FACTOR MODEL FOR THE ASSESSMENT OF HUMAN EXPOSURE TO MOTOR VEHICLE EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's (EPA) National Expsoure Research Laboratory (NERL) has initiated a project to improve the methodology for modeling urban-scale human exposure to mobile source emissions. The modeling project has started by considering the nee...

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) FOR PREDICTING REAL-TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source t...

SENSITIVITY ANALYSIS AND EVALUATION OF MICROFACO: A MICROSCALE MOTOR VEHICLE EMISSION FACTOR MODEL FOR CO EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source t...

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR CO (MICROFACCO) FOR PREDICTING REAL-TIME VEHICLE EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source t...

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) FOR PREDICTING REAL-TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project is to develop improved methods for modeling the source through...

Determining size-specific emission factors for environmental tobacco smoke particles

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

Klepeis, Neil E.; Apte, Michael G.; Gundel, Lara A.

Because size is a major controlling factor for indoor airborne particle behavior, human particle exposure assessments will benefit from improved knowledge of size-specific particle emissions. We report a method of inferring size-specific mass emission factors for indoor sources that makes use of an indoor aerosol dynamics model, measured particle concentration time series data, and an optimization routine. This approach provides--in addition to estimates of the emissions size distribution and integrated emission factors--estimates of deposition rate, an enhanced understanding of particle dynamics, and information about model performance. We applied the method to size-specific environmental tobacco smoke (ETS) particle concentrations measured everymore » minute with an 8-channel optical particle counter (PMS-LASAIR; 0.1-2+ micrometer diameters) and every 10 or 30 min with a 34-channel differential mobility particle sizer (TSI-DMPS; 0.01-1+ micrometer diameters) after a single cigarette or cigar was machine-smoked inside a low air-exchange-rate 20 m{sup 3} chamber. The aerosol dynamics model provided good fits to observed concentrations when using optimized values of mass emission rate and deposition rate for each particle size range as input. Small discrepancies observed in the first 1-2 hours after smoking are likely due to the effect of particle evaporation, a process neglected by the model. Size-specific ETS particle emission factors were fit with log-normal distributions, yielding an average mass median diameter of 0.2 micrometers and an average geometric standard deviation of 2.3 with no systematic differences between cigars and cigarettes. The equivalent total particle emission rate, obtained integrating each size distribution, was 0.2-0.7 mg/min for cigars and 0.7-0.9 mg/min for cigarettes.« less

Toxic volatile organic compounds in environmental tobacco smoke: Emission factors for modeling exposures of California populations

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

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air contaminants in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including, 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosamines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were alsomore » determined for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors ({mu}g/cigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were Generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

Toxic Volatile Organic Compounds in Environmental Tobacco Smoke:Emission Factors for Modeling Exposures of California Populations

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

Daisey, J.M.; Mahanama, K.R.R.; Hodgson, A.T.

The primary objective of this study was to measure emission factors for selected toxic air in environmental tobacco smoke (ETS) using a room-sized environmental chamber. The emissions of 23 volatile organic compounds (VOCs), including 1,3-butadiene, three aldehydes and two vapor-phase N-nitrosarnines were determined for six commercial brands of cigarettes and reference cigarette 1R4F. The commercial brands were selected to represent 62.5% of the cigarettes smoked in California. For each brand, three cigarettes were machine smoked in the chamber. The experiments were conducted over four hours to investigate the effects of aging. Emission factors of the target compounds were also determinedmore » for sidestream smoke (SS). For almost all target compounds, the ETS emission factors were significantly higher than the corresponding SS values probably due to less favorable combustion conditions and wall losses in the SS apparatus. Where valid comparisons could be made, the ETS emission factors were generally in good agreement with the literature. Therefore, the ETS emission factors, rather than the SS values, are recommended for use in models to estimate population exposures from this source. The variabilities in the emission factors (pgkigarette) of the selected toxic air contaminants among brands, expressed as coefficients of variation, were 16 to 29%. Therefore, emissions among brands were generally similar. Differences among brands were related to the smoked lengths of the cigarettes and the masses of consumed tobacco. Mentholation and whether a cigarette was classified as light or regular did not significantly affect emissions. Aging was determined not to be a significant factor for the target compounds. There were, however, deposition losses of the less volatile compounds to chamber surfaces.« less

Black Carbon Concentration from Worldwide Aerosol Robotic Network (AERONET) Measurements

NASA Technical Reports Server (NTRS)

Schuster, Gregory L.; Dubovik, Oleg; Holben, Brent N.; Clothiaux, Eugene E.

2006-01-01

The carbon emissions inventories used to initialize transport models and general circulation models are highly parameterized, and created on the basis of multiple sparse datasets (such as fuel use inventories and emission factors). The resulting inventories are uncertain by at least a factor of 2, and this uncertainty is carried forward to the model output. [Bond et al., 1998, Bond et al., 2004, Cooke et al., 1999, Streets et al., 2001] Worldwide black carbon concentration measurements are needed to assess the efficacy of the carbon emissions inventory and transport model output on a continuous basis.

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.

Combustion efficiency and emission factors for wildfire-season fires in mixed conifer forests of the northern Rocky Mountains, US

Treesearch

S. P. Urbanski

2013-01-01

In the US, wildfires and prescribed burning present significant challenges to air regulatory agencies attempting to achieve and maintain compliance with air quality regulations. Fire emission factors (EF) are essential input for the emission models used to develop wildland fire emission inventories. Most previous studies quantifying wildland fire EF of temperate...

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.

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...

Sensitivity analyses of factors influencing CMAQ performance for fine particulate nitrate.

PubMed

Shimadera, Hikari; Hayami, Hiroshi; Chatani, Satoru; Morino, Yu; Mori, Yasuaki; Morikawa, Tazuko; Yamaji, Kazuyo; Ohara, Toshimasa

2014-04-01

Improvement of air quality models is required so that they can be utilized to design effective control strategies for fine particulate matter (PM2.5). The Community Multiscale Air Quality modeling system was applied to the Greater Tokyo Area of Japan in winter 2010 and summer 2011. The model results were compared with observed concentrations of PM2.5 sulfate (SO4(2-)), nitrate (NO3(-)) and ammonium, and gaseous nitric acid (HNO3) and ammonia (NH3). The model approximately reproduced PM2.5 SO4(2-) concentration, but clearly overestimated PM2.5 NO3(-) concentration, which was attributed to overestimation of production of ammonium nitrate (NH4NO3). This study conducted sensitivity analyses of factors associated with the model performance for PM2.5 NO3(-) concentration, including temperature and relative humidity, emission of nitrogen oxides, seasonal variation of NH3 emission, HNO3 and NH3 dry deposition velocities, and heterogeneous reaction probability of dinitrogen pentoxide. Change in NH3 emission directly affected NH3 concentration, and substantially affected NH4NO3 concentration. Higher dry deposition velocities of HNO3 and NH3 led to substantial reductions of concentrations of the gaseous species and NH4NO3. Because uncertainties in NH3 emission and dry deposition processes are probably large, these processes may be key factors for improvement of the model performance for PM2.5 NO3(-). The Community Multiscale Air Quality modeling system clearly overestimated the concentration of fine particulate nitrate in the Greater Tokyo Area of Japan, which was attributed to overestimation of production of ammonium nitrate. Sensitivity analyses were conducted for factors associated with the model performance for nitrate. Ammonia emission and dry deposition of nitric acid and ammonia may be key factors for improvement of the model performance.

78 FR 33726 - Approval and Promulgation of Implementation Plans; Kentucky: Kentucky Portion of Cincinnati...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-05

... projections models, as well as changes to future vehicle mix assumptions, that influence the emission... methodology that may occur in the future such as updated socioeconomic data, new models, and other factors... updated mobile emissions model, the Motor Vehicle Emissions Simulator (also known as MOVES2010a), and to...

Seasonal and Interannual Variations in BC Emissions From Open Biomass Burning in Southern Africa From 1998 to 2005

NASA Astrophysics Data System (ADS)

Ito, A.; Akimoto, H.

2006-12-01

We estimate the emissions of black carbon (BC) from open vegetation fires in southern hemisphere Africa from 1998 to 2005 using satellite information in conjunction with a biogeochemical model. Monthly burned areas at a 0.5-degree resolution are estimated from the Visible and Infrared Scanner (VIRS) fire count product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area data set associated with the MODIS tree cover imagery in grasslands and woodlands. The monthly fuel load distribution is derived from a 0.5- degree terrestrial carbon cycle model in conjunction with satellite data. The monthly maps of combustion factor and emission factor are estimated using empirical models that predict the effects of fuel conditions on these factors in grasslands and woodlands. Our annual averaged BC emitted per unit area burned is 0.17 g BC m-2 which is consistent with the product of fuel consumption and emission factor typically measured in southern Africa. The BC emissions from open vegetation burning in southern Africa ranged from 0.26 Tg BC yr-1 for 2002 to 0.42 Tg BC yr-1 for 1998. The peak in BC emissions is identical to that from previous top-down estimate using the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data. The sum of monthly emissions during the burning season in 2000 is in good agreement between our estimate (0.38 Tg) and previous estimate constrained by numerical model and measurements (0.47 Tg).

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.

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

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

PubMed

Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model

NASA Technical Reports Server (NTRS)

Petrenko, Mariya; Kahn, Ralph; Chin, Mian; Limbacher, James

2017-01-01

Simulations of biomass burning (BB) emissions in global chemistry and aerosol transport models depend on external inventories, which provide location and strength of burning aerosol sources. Our previous work (Petrenko et al., 2012) shows that satellite snapshots of aerosol optical depth (AOD) near the emitted smoke plume can be used to constrain model-simulated AOD, and effectively, the assumed source strength. We now refine the satellite-snapshot method and investigate applying simple multiplicative emission correction factors for the widely used Global Fire Emission Database version 3 (GFEDv3) emission inventory can achieve regional-scale consistency between MODIS AOD snapshots and the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The model and satellite AOD are compared over a set of more than 900 BB cases observed by the MODIS instrument during the 2004, and 2006-2008 biomass burning seasons. The AOD comparison presented here shows that regional discrepancies between the model and satellite are diverse around the globe yet quite consistent within most ecosystems. Additional analysis of including small fire emission correction shows the complimentary nature of correcting for source strength and adding missing sources, and also indicates that in some regions other factors may be significant in explaining model-satellite discrepancies. This work sets the stage for a larger intercomparison within the Aerosol Inter-comparisons between Observations and Models (AeroCom) multi-model biomass burning experiment. We discuss here some of the other possible factors affecting the remaining discrepancies between model simulations and observations, but await comparisons with other AeroCom models to draw further conclusions.

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.

Studying the Impacts of Environmental Factors and Agricultural Management on Methane Emissions from Rice Paddies Using a Land Surface Model

NASA Astrophysics Data System (ADS)

Lin, T. S.; Gahlot, S.; Shu, S.; Jain, A. K.; Kheshgi, H. S.

2017-12-01

Continued growth in population is projected to drive increased future demand for rice and the methane emissions associated with its production. However, observational studies of methane emissions from rice have reported seemingly conflicting results and do not all support this projection. In this study we couple an ecophysiological process-based rice paddy module and a methane emission module with a land surface model, Integrated Science Assessment Model (ISAM), to study the impacts of various environmental factors and agricultural management practices on rice production and methane emissions from rice fields. This coupled modeling framework accounts for dynamic rice growth processes with adaptation of photosynthesis, rice-specific phenology, biomass accumulation, leaf area development and structures responses to water, temperature, light and nutrient stresses. The coupled model is calibrated and validated with observations from various rice cultivation fields. We find that the differing results of observational studies can be caused by the interactions of environmental factors, including climate, atmospheric CO2 concentration, and N deposition, and agricultural management practices, such as irrigation and N fertilizer applications, with rice production at spatial and temporal scales.

Gaining ground in the modeling of land-use change greenhouse gas emissions associated with biofuel production

NASA Astrophysics Data System (ADS)

Dunn, J.; Mueller, S.; Kwon, H.; Wang, M.; Wander, M.

2012-12-01

Land-use change (LUC) resulting from biofuel feedstock production and the associated greenhouse gas (GHG) emissions are a hotly-debated aspect of biofuels. Certainly, LUC GHG emissions are one of the most uncertain elements in life cycle analyses (LCA) of biofuels. To estimate LUC GHG emissions, two sets of data are necessary. First, information on the amount and type of land that is converted to biofuel feedstock production is required. These data are typically generated through application of computable general equilibrium (CGE) models such as Purdue University's Global Trade Analysis Project (GTAP) model. Second, soil carbon content data for the affected land types is essential. Recently, Argonne National Laboratory's Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) has been updated with CGE modeling results that estimate the amount and type of LUC world-wide from production of ethanol from corn, corn stover, miscanthus, and switchgrass (Mueller et al. 2012). Moreover, we have developed state-specific carbon content data, determined through modeling with CENTURY, for the two most dominant soil types in the conterminous 48 U.S. states (Kwon et al. 2012) to enable finer-resolution results for domestic LUC GHG emissions for these ethanol production scenarios. Of the feedstocks examined, CCLUB estimates that LUC GHG emissions are highest for corn ethanol (9.1 g CO2e/MJ ethanol) and lowest for miscanthus (-12 g CO2e/MJ ethanol). We will present key observations from CCLUB results incorporated into Argonne National Laboratory's Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model, which is a LCA tool for transportation fuels and advanced vehicle technologies. We will discuss selected issues in this modeling, including the sensitivity of domestic soil carbon emission factors to modeling parameters and assumptions about the fate of harvested wood products. Further, we will discuss efforts to update CCLUB with county-level soil carbon emission factors and updated international soil carbon emission factors. Finally, we will examine data needs for improved LUC GHG calculations in both the modeling of land conversion and soil carbon content. Kwon, H. Y., Wander, M. M., Mueller, S., Dunn, J. B. "Modeling state-level soil carbon emission factors under various scenarios for direct land use change associated with United States biofuel feedstock production." Biomass and Bioenergy. Under Review. Mueller, S., Dunn, J. B., Wang, M. "Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) Users' Manual and Technical Documentation." May 2012. ANL/ESD/12-5. Available at http://greet.es.anl.gov/publication-cclub-manual.

[Real world instantaneous emission simulation for light-duty diesel vehicle].

PubMed

Huang, Cheng; Chen, Chang-Hong; Dai, Pu; Li, Li; Huang, Hai-Ying; Cheng, Zhen; Jia, Ji-Hong

2008-10-01

Core architecture and input parameters of CMEM model were introduced to simulation the second by second vehicle emission rate on real world by taking a light-duty diesel car as a case. On-board test data by a portable emission measurement system were then used to validate the simulation results. Test emission factors of CO, THC, NO(x) and CO2 were respectively 0.81, 0.61, 2.09, and 193 g x km(-1), while calculated emission factors were 0.75, 0.47, 2.47, and 212 g x km(-1). The correlation coefficients reached 0.69, 0.69, 0.75, and 0.72. Simulated instantaneous emissions of the light duty diesel vehicle by CMEM model were strongly coherent with the transient driving cycle. By analysis, CO, THC, NO(x), and CO2 emissions would be reduced by 50%, 47%, 45%, and 44% after improving the traffic situation at the intersection. The result indicated that it is necessary and feasible to simulate the instantaneous emissions of mixed vehicle fleet in some typical traffic areas by the micro-scale vehicle emission model.

Integral emission factors for methane determined using urban flux measurements and local-scale inverse models

NASA Astrophysics Data System (ADS)

Christen, Andreas; Johnson, Mark; Molodovskaya, Marina; Ketler, Rick; Nesic, Zoran; Crawford, Ben; Giometto, Marco; van der Laan, Mike

2013-04-01

The most important long-lived greenhouse gas (LLGHG) emitted during combustion of fuels is carbon dioxide (CO2), however also traces of the LLGHGs methane (CH4) and nitrous oxide (N2O) are released, the quantities of which depend largely on the conditions of the combustion process. Emission factors determine the mass of LLGHGs emitted per energy used (or kilometre driven for cars) and are key inputs for bottom-up emission modelling. Emission factors for CH4 are typically determined in the laboratory or on a test stand for a given combustion system using a small number of samples (vehicles, furnaces), yet associated with larger uncertainties when scaled to entire fleets. We propose an alternative, different approach - Can integrated emission factors be independently determined using direct micrometeorological flux measurements over an urban surface? If so, do emission factors determined from flux measurements (top-down) agree with up-scaled emission factors of relevant combustion systems (heating, vehicles) in the source area of the flux measurement? Direct flux measurements of CH4 were carried out between February and May, 2012 over a relatively densely populated, urban surface in Vancouver, Canada by means of eddy covariance (EC). The EC-system consisted of an ultrasonic anemometer (CSAT-3, Campbell Scientific Inc.) and two open-path infrared gas analyzers (Li7500 and Li7700, Licor Inc.) on a tower at 30m above the surface. The source area of the EC system is characterised by a relative homogeneous morphometry (5.3m average building height), but spatially and temporally varying emission sources, including two major intersecting arterial roads (70.000 cars drive through the 50% source area per day) and seasonal heating in predominantly single-family houses (natural gas). An inverse dispersion model (turbulent source area model), validated against large eddy simulations (LES) of the urban roughness sublayer, allows the determination of the spatial area that contributes to each measurement interval (30 min), which varies with wind direction and stability. A detailed geographic information system of the urban surface combined with traffic counts and building energy models makes it possible to statistically relate fluxes to vehicle density (km driven) and buildings (gas heated volume) - and ultimately quantify the contribution of space heating, transport sector and fugitive emissions to the total emitted CH4 from an urban environment. The measured fluxes of CH4 over the selected urban environment averaged to 22.8 mg CH4 m-2 day-1 during the study period. Compared with the simultaneously measured CO2 emissions, the contribution of CH4, however, accounts for only about 3% of the total LLGHG emissions from this particular urban surface. Traffic contributed 8.8 mg CH4 m-2 day-1, equivalent to 39% of the total CH4 flux. The determined emission factor for the typical fleet composition is 0.062 g CH4 per km driven which is higher than upscaled fleet emission factors (EPA) by a factor of two. This discrepancy can be partially explained through the slower city traffic with frequent idling (traffic congestion), fleet composition and cold starts. Emissions of CH4 by domestic space heating (55% of the total CH4 flux or 12.7 mg CH4 m-2 day-1) are also higher than estimated from upscaled emission factors. There is no evidence of substantial unknown sources such as soil processes, combustion of wood, and leakages from gas distribution pipes (residual: 6% or 1.3 mg CH4 m-2 day-1). The presented study is among the first direct measurements of CH4 emissions over an urban surface and demonstrates that flux measurements of greenhouse gases can be used to determine sources and emission factors in complex urban situations.

Attribution of changes in global wetland methane emissions from pre-industrial to present using CLM4.5-BGC

DOE PAGES

Paudel, Rajendra; Mahowald, Natalie M.; Hess, Peter G. M.; ...

2016-03-10

An understanding of potential factors controlling methane emissions from natural wetlands is important to accurately project future atmospheric methane concentrations. Here, we examine the relative contributions of climatic and environmental factors, such as precipitation, temperature, atmospheric CO 2 concentration, nitrogen deposition, wetland inundation extent, and land-use and land-cover change, on changes in wetland methane emissions from preindustrial to present day (i.e., 1850-2005). We apply a mechanistic methane biogeochemical model integrated in the Community Land Model version 4.5 (CLM4.5), the land component of the Community Earth System Model. The methane model explicitly simulates methane production, oxidation, ebullition, transport through aerenchyma ofmore » plants, and aqueous and gaseous diffusion. We conduct a suite of model simulations from 1850 to 2005, with all changes in environmental factors included, and sensitivity studies isolating each factor. Globally, we estimate that preindustrial methane emissions were higher by 10% than present-day emissions from natural wetlands, with emissions changes from preindustrial to the present of +15%, -41%, and -11% for the high latitudes, temperate regions, and tropics, respectively. The most important change is due to the estimated change in wetland extent, due to the conversion of wetland areas to drylands by humans. This effect alone leads to higher preindustrial global methane fluxes by 33% relative to the present, with the largest change in temperate regions (+80%). These increases were partially offset by lower preindustrial emissions due to lower CO 2 levels (10%), shifts in precipitation (7%), lower nitrogen deposition (3%), and changes in land-use and land-cover (2%). Cooler temperatures in the preindustrial regions resulted in our simulations in an increase in global methane emissions of 6% relative to present day. Much of the sensitivity to these perturbations is mediated in the model by changes in methane substrate production and the areal extent of wetlands. The detrended interannual variability of high-latitude methane emissions is explained by the variation in substrate production and wetland inundation extent, whereas the tropical emission variability is explained by both of those variables and precipitation.« less

Attribution of changes in global wetland methane emissions from pre-industrial to present using CLM4.5-BGC

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

Paudel, Rajendra; Mahowald, Natalie M.; Hess, Peter G. M.

An understanding of potential factors controlling methane emissions from natural wetlands is important to accurately project future atmospheric methane concentrations. Here, we examine the relative contributions of climatic and environmental factors, such as precipitation, temperature, atmospheric CO 2 concentration, nitrogen deposition, wetland inundation extent, and land-use and land-cover change, on changes in wetland methane emissions from preindustrial to present day (i.e., 1850-2005). We apply a mechanistic methane biogeochemical model integrated in the Community Land Model version 4.5 (CLM4.5), the land component of the Community Earth System Model. The methane model explicitly simulates methane production, oxidation, ebullition, transport through aerenchyma ofmore » plants, and aqueous and gaseous diffusion. We conduct a suite of model simulations from 1850 to 2005, with all changes in environmental factors included, and sensitivity studies isolating each factor. Globally, we estimate that preindustrial methane emissions were higher by 10% than present-day emissions from natural wetlands, with emissions changes from preindustrial to the present of +15%, -41%, and -11% for the high latitudes, temperate regions, and tropics, respectively. The most important change is due to the estimated change in wetland extent, due to the conversion of wetland areas to drylands by humans. This effect alone leads to higher preindustrial global methane fluxes by 33% relative to the present, with the largest change in temperate regions (+80%). These increases were partially offset by lower preindustrial emissions due to lower CO 2 levels (10%), shifts in precipitation (7%), lower nitrogen deposition (3%), and changes in land-use and land-cover (2%). Cooler temperatures in the preindustrial regions resulted in our simulations in an increase in global methane emissions of 6% relative to present day. Much of the sensitivity to these perturbations is mediated in the model by changes in methane substrate production and the areal extent of wetlands. The detrended interannual variability of high-latitude methane emissions is explained by the variation in substrate production and wetland inundation extent, whereas the tropical emission variability is explained by both of those variables and precipitation.« less

NOx emissions from Euro IV busses with SCR systems associated with urban, suburban and freeway driving patterns.

PubMed

Fu, Mingliang; Ge, Yunshan; Wang, Xin; Tan, Jianwei; Yu, Linxiao; Liang, Bin

2013-05-01

NOx and particulate matter (PM) emissions from heavy-duty diesel vehicles (HDVs) have become the most important sources of pollutants affecting urban air quality in China. In recent years, a series of emission control strategies and diesel engine polices have been introduced that require advanced emission control technology. China and Europe mostly have used Selective Catalytic Reduction (SCR) with urea to meet the Euro IV diesel engine emission standard. In this study, two Euro IV busses with SCR were tested by using potable emission measurement system (PEMS) to assess NOx emissions associated with urban, suburban and freeway driving patterns. The results indicated that with the SCR system, the urea injection time for the entire driving period increased with higher vehicle speed. For freeway driving, the urea injection time covered 71%-83% of the driving period; the NOx emission factors from freeway driving were lower than those associated with urban and suburban driving. Unfortunately, the NOx emission factors were 2.6-2.8-, 2.3-2.7- and 2.2-2.3-fold higher than the Euro IV standard limits for urban, suburban and freeway driving, respectively; NOx emission factors (in g/km and g/(kW·h)) from the original vehicles (without SCR) were higher than their corresponding vehicles with SCR for suburban and freeway driving. Compared with the IVE model results, the measured NOx emission factors were 1.60-1.16-, 1.77-1.27-, 2.49-2.44-fold higher than the NOx predicted by the IVE model for urban and suburban driving, respectively. Thus, an adjustment of emission factors is needed to improve the estimation of Euro IV vehicle emissions in China. Copyright © 2013 Elsevier B.V. All rights reserved.

A methodology for calculating transport emissions in cities with limited traffic data: Case study of diesel particulates and black carbon emissions in Murmansk.

PubMed

Kholod, N; Evans, M; Gusev, E; Yu, S; Malyshev, V; Tretyakova, S; Barinov, A

2016-03-15

This paper presents a methodology for calculating exhaust emissions from on-road transport in cities with low-quality traffic data and outdated vehicle registries. The methodology consists of data collection approaches and emission calculation methods. For data collection, the paper suggests using video survey and parking lot survey methods developed for the International Vehicular Emissions model. Additional sources of information include data from the largest transportation companies, vehicle inspection stations, and official vehicle registries. The paper suggests using the European Computer Programme to Calculate Emissions from Road Transport (COPERT) 4 model to calculate emissions, especially in countries that implemented European emissions standards. If available, the local emission factors should be used instead of the default COPERT emission factors. The paper also suggests additional steps in the methodology to calculate emissions only from diesel vehicles. We applied this methodology to calculate black carbon emissions from diesel on-road vehicles in Murmansk, Russia. The results from Murmansk show that diesel vehicles emitted 11.7 tons of black carbon in 2014. The main factors determining the level of emissions are the structure of the vehicle fleet and the level of vehicle emission controls. Vehicles without controls emit about 55% of black carbon emissions. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling carbon emissions from urban traffic system using mobile monitoring.

PubMed

Sun, Daniel Jian; Zhang, Ying; Xue, Rui; Zhang, Yi

2017-12-01

Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO 2 and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO 2 and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Size resolved ultrafine particles emission model--a continues size distribution approach.

PubMed

Nikolova, Irina; Janssen, Stijn; Vrancken, Karl; Vos, Peter; Mishra, Vinit; Berghmans, Patrick

2011-08-15

A new parameterization for size resolved ultrafine particles (UFP) traffic emissions is proposed based on the results of PARTICULATES project (Samaras et al., 2005). It includes the emission factors from the Emission Inventory Guidebook (2006) (total number of particles, #/km/veh), the shape of the corresponding particle size distribution given in PARTICULATES and data for the traffic activity. The output of the model UFPEM (UltraFine Particle Emission Model) is a sum of continuous distributions of ultrafine particles emissions per vehicle type (passenger cars and heavy duty vehicles), fuel (petrol and diesel) and average speed representative for urban, rural and highway driving. The results from the parameterization are compared with measured total number of ultrafine particles and size distributions in a tunnel in Antwerp (Belgium). The measured UFP concentration over the entire campaign shows a close relation to the traffic activity. The modelled concentration is found to be lower than the measured in the campaign. The average emission factor from the measurement is 4.29E+14 #/km/veh whereas the calculated is around 30% lower. A comparison of emission factors with literature is done as well and in overall a good agreement is found. For the size distributions it is found that the measured distributions consist of three modes--Nucleation, Aitken and accumulation and most of the ultrafine particles belong to the Nucleation and the Aitken modes. The modelled Aitken mode (peak around 0.04-0.05 μm) is found in a good agreement both as amplitude of the peak and the number of particles whereas the modelled Nucleation mode is shifted to smaller diameters and the peak is much lower that the observed. Time scale analysis shows that at 300 m in the tunnel coagulation and deposition are slow and therefore neglected. The UFPEM emission model can be used as a source term in dispersion models. Copyright © 2011 Elsevier B.V. All rights reserved.

A framework for modeling in-use deterioration of light-duty vehicle emissions using MOBILE6

DOT National Transportation Integrated Search

2000-09-01

The Mobile Source Emission Factor Model used to estimate the inventory of exhaust and evaporative emissions from on-road motor vehicles is currently being revised by the U.S. Environmental Protection Agency. The framework used in calculating basic ex...

Road traffic emission factors for heavy metals

NASA Astrophysics Data System (ADS)

Johansson, Christer; Norman, Michael; Burman, Lars

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

Study on highway transportation greenhouse effect external cost estimation in China

NASA Astrophysics Data System (ADS)

Chu, Chunchao; Pan, Fengming

2017-03-01

This paper focuses on estimating highway transportation greenhouse gas emission volume and greenhouse gas external cost in China. At first, composition and characteristics of greenhouse gases were analysed about highway transportation emissions. Secondly, an improved model of emission volume was presented on basis of highway transportation energy consumption, which may be calculated by virtue of main affecting factors such as the annual average operation miles of each type of the motor vehicles and the unit consumption level. the model of emission volume was constructed which considered not only the availability of energy consumption statistics of highway transportation but also the greenhouse gas emission factors of various fuel types issued by IPCC. Finally, the external cost estimation model was established about highway transportation greenhouse gas emission which combined emission volume with the unit external cost of CO2 emissions. An example was executed to confirm presented model which ranged from 2011 to 2015 Year in China. The calculated result shows that the highway transportation total emission volume and greenhouse gas external cost are growing up, but the unit turnover external cost is steadily declining. On the whole overall, the situation is still grim about highway transportation greenhouse gas emission, and the green transportation strategy should be put into effect as soon as possible.

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.

Greenhouse gas emissions from dairy manure management: a review of field-based studies.

PubMed

Owen, Justine J; Silver, Whendee L

2015-02-01

Livestock manure management accounts for almost 10% of greenhouse gas emissions from agriculture globally, and contributes an equal proportion to the US methane emission inventory. Current emissions inventories use emissions factors determined from small-scale laboratory experiments that have not been compared to field-scale measurements. We compiled published data on field-scale measurements of greenhouse gas emissions from working and research dairies and compared these to rates predicted by the IPCC Tier 2 modeling approach. Anaerobic lagoons were the largest source of methane (368 ± 193 kg CH4 hd(-1) yr(-1)), more than three times that from enteric fermentation (~120 kg CH4 hd(-1) yr(-1)). Corrals and solid manure piles were large sources of nitrous oxide (1.5 ± 0.8 and 1.1 ± 0.7 kg N2O hd(-1) yr(-1), respectively). Nitrous oxide emissions from anaerobic lagoons (0.9 ± 0.5 kg N2O hd(-1) yr(-1)) and barns (10 ± 6 kg N2O hd(-1) yr(-1)) were unexpectedly large. Modeled methane emissions underestimated field measurement means for most manure management practices. Modeled nitrous oxide emissions underestimated field measurement means for anaerobic lagoons and manure piles, but overestimated emissions from slurry storage. Revised emissions factors nearly doubled slurry CH4 emissions for Europe and increased N2O emissions from solid piles and lagoons in the United States by an order of magnitude. Our results suggest that current greenhouse gas emission factors generally underestimate emissions from dairy manure and highlight liquid manure systems as promising target areas for greenhouse gas mitigation. © 2014 John Wiley & Sons Ltd.

Spontaneous emission in semiconductor laser amplifiers

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

Arnaud, J.; Coste, F.; Fesqueet, J.

1985-06-01

In a mode matched configuration, spontaneous emission in semiconductor laser amplifiers is enhanced by a factor which is larger than unity but which is significantly smaller than the K-factor calculated by Petermann. Using thin-slab model, we find that in typical situations, the factor is about K/2.

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) FOR PREDICTING REAL TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

Health risk evaluation needs precise measurement and modeling of human exposures in microenvironments to support review of current air quality standards. The particulate matter emissions from motor vehicles are a major component of human exposures in urban microenvironments. Cu...

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.

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.

Characterization of air pollutant concentrations, fleet emission factors, and dispersion near a North Carolina interstate freeway across two seasons

NASA Astrophysics Data System (ADS)

Saha, Provat K.; Khlystov, Andrey; Snyder, Michelle G.; Grieshop, Andrew P.

2018-03-01

We present field measurement data and modeling of multiple traffic-related air pollutants during two seasons at a site adjoining Interstate 40, near Durham, North Carolina. We analyze spatial-temporal and seasonal trends and fleet-average pollutant emission factors and use our data to evaluate a line source dispersion model. Month-long measurement campaigns were performed in summer 2015 and winter 2016. Data were collected at a fixed near-road site located within 10 m from the highway edge, an upwind background site and, under favorable meteorological conditions, along downwind perpendicular transects. Measurements included the size distribution, chemical composition, and volatility of submicron particles, black carbon (BC), nitrogen oxides (NOx), meteorological conditions and traffic activity data. Results show strong seasonal and diurnal differences in spatial distribution of traffic sourced pollutants. A strong signature of vehicle emissions was observed within 100-150 m from the highway edge with significantly higher concentrations during morning. Substantially higher concentrations and less-sharp near-road gradients were observed in winter for many species. Season-specific fleet-average fuel-based emission factors for NO, NOx, BC, and particle number (PN) were derived based on up- and down-wind roadside measurements. The campaign-average NOx and PN emission factors were 20% and 300% higher in winter than summer, respectively. These results suggest that the combined effect of higher emissions and their slower downwind dispersion in winter dictate the observed higher downwind concentrations and wider highway influence zone in winter for several species. Finally, measurements of traffic data, emission factors, and pollutant concentrations were integrated to evaluate a line source dispersion model (R-LINE). The dispersion model captured the general trends in the spatial and temporal patterns in near-road concentrations. However, there was a tendency for the model to under-predict concentrations near the road in the mornings and over-predict concentrations in the evenings.

Seasonal and diel variations of ammonia and methane emissions from a naturally ventilated dairy building and the associated factors influencing emissions.

PubMed

Saha, C K; Ammon, C; Berg, W; Fiedler, M; Loebsin, C; Sanftleben, P; Brunsch, R; Amon, T

2014-01-15

Understanding seasonal and diel variations of ammonia (NH3) and methane (CH4) emissions from a naturally ventilated dairy (NVD) building may lead to develop successful control strategies for reducing emissions throughout the year. The main objective of this study was to quantify seasonal and diel variations of NH3 and CH4 emissions together with associated factors influencing emissions. Measurements were carried out with identical experimental set-up to cover three winter, spring and summer seasons, and two autumn seasons in the years 2010, 2011, and 2012. The data from 2010 and 2011 were used for developing emission prediction models and the data from 2012 were used for model validation. The results showed that NH3 emission varied seasonally following outside temperature whereas CH4 emission did not show clear seasonal trend. Diel variation of CH4 emission was less pronounced than NH3. The average NH3 and CH4 emissions between 6a.m. and 6p.m. were 66% and 33% higher than the average NH3 and CH4 emissions between 6p.m. and 6a.m., respectively for all seasons. The significant relationships (P<0.0001) between NH3 and influencing factors were found including outside temperature, humidity, wind speed and direction, hour of the day and day of the year. The significant effect (P<0.0001) of climate factors, hours of the day and days of the year on CH4 emission might be directly related to activities of the cows. © 2013.

On-road heavy-duty diesel particulate matter emissions modeled using chassis dynamometer data.

PubMed

Kear, Tom; Niemeier, D A

2006-12-15

This study presents a model, derived from chassis dynamometer test data, for factors (operational correction factors, or OCFs) that correct (g/mi) heavy-duty diesel particle emission rates measured on standard test cycles for real-world conditions. Using a random effects mixed regression model with data from 531 tests of 34 heavy-duty vehicles from the Coordinating Research Council's E55/E59 research project, we specify a model with covariates that characterize high power transient driving, time spent idling, and average speed. Gram per mile particle emissions rates were negatively correlated with high power transient driving, average speed, and time idling. The new model is capable of predicting relative changes in g/mi on-road heavy-duty diesel particle emission rates for real-world driving conditions that are not reflected in the driving cycles used to test heavy-duty vehicles.

Estimation of vegetative mercury emissions in China.

PubMed

Quan, Jiannong; Zhang, Xiaoshan; Shim, Shang Gyoo

2008-01-01

Vegetative mercury emissions were estimated within the framework of Biogenic Emission Inventory System (BEIS3 V3.11). In this estimation, the 19 categories of U.S. Geological Survey landcover data were incorporated to generate the vegetation-specific mercury emissions in a 81-km Lambert Conformal model grid covering the total Chinese continent. The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for forest, agriculture and water, or assumed for other land fields without available flux data. Annual simulations using the MM5 data were performed to investigate the seasonal emission variation. From the sensitivity analysis using two sets of emission factors, the vegetative mercury emissions in China domain were estimated to range from a lower limit of 79 x 10(3) kg/year to an upper limit of 177 x 10(3) kg/year. The modeled vegetative emissions were mainly generated from the eastern and southern China. Using the estimated data, it is shown that mercury emissions from vegetation are comparable to that from anthropogenic sources during summer. However, the vegetative emissions decrease greatly during winter, leaving anthropogenic sources as the major sources of emission.

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

EPA Pesticide Factsheets

The uploaded data consists of the BRACE Na aerosol observations paired with CMAQ model output, the updated model's parameterization of sea salt aerosol emission size distribution, and the model's parameterization of the sea salt emission factor as a function of sea surface temperature. This dataset is associated with the following publication:Gantt , B., J. Kelly , and J. Bash. Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 8: 3733-3746, (2015).

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

NASA Astrophysics Data System (ADS)

Mishra, Dhirendra; Goyal, P.

2014-12-01

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

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.

How to address data gaps in life cycle inventories: a case study on estimating CO2 emissions from coal-fired electricity plants on a global scale.

PubMed

Steinmann, Zoran J N; Venkatesh, Aranya; Hauck, Mara; Schipper, Aafke M; Karuppiah, Ramkumar; Laurenzi, Ian J; Huijbregts, Mark A J

2014-05-06

One of the major challenges in life cycle assessment (LCA) is the availability and quality of data used to develop models and to make appropriate recommendations. Approximations and assumptions are often made if appropriate data are not readily available. However, these proxies may introduce uncertainty into the results. A regression model framework may be employed to assess missing data in LCAs of products and processes. In this study, we develop such a regression-based framework to estimate CO2 emission factors associated with coal power plants in the absence of reported data. Our framework hypothesizes that emissions from coal power plants can be explained by plant-specific factors (predictors) that include steam pressure, total capacity, plant age, fuel type, and gross domestic product (GDP) per capita of the resident nations of those plants. Using reported emission data for 444 plants worldwide, plant level CO2 emission factors were fitted to the selected predictors by a multiple linear regression model and a local linear regression model. The validated models were then applied to 764 coal power plants worldwide, for which no reported data were available. Cumulatively, available reported data and our predictions together account for 74% of the total world's coal-fired power generation capacity.

CARBON MONOXIDE EMISSIONS FROM ROAD DRIVING: EVIDENCE OF EMISSIONS DUE TO POWER ENRICHMENT

EPA Science Inventory

The paper examines one aspect of motor vehicle emissions behavior; i.e. emissions due to engine power enrichment, a factor not well represented in existing models. Database reflecting 46 instrumented vehicles was used to analyze the importance of enrichment emissions to overall v...

Particle and gas emissions from a simulated coal-burning household fire pit.

PubMed

Tian, Linwei; Lucas, Donald; Fischer, Susan L; Lee, S C; Hammond, S Katharine; Koshland, Catherine P

2008-04-01

An open fire was assembled with firebricks to simulate the household fire pit used in rural China, and 15 different coals from this area were burned to measure the gaseous and particulate emissions. Particle size distribution was studied with a microorifice uniform-deposit impactor (MOUDI). Over 90% of the particulate mass was attributed to sub-micrometer particles. The carbon balance method was used to calculate the emission factors. Emission factors for four pollutants (particulate matter, CO2, total hydrocarbons, and NOx) were 2-4 times higherfor bituminous coals than for anthracites. In past inventories of carbonaceous emissions used for climate modeling, these two types of coal were not treated separately. The dramatic emission factor difference between the two types of coal warrants attention in the future development of emission inventories.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

NASA Technical Reports Server (NTRS)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

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

Apportionment of NMHC tailpipe vs non-tailpipe emissions in the Fort McHenry and Tuscarora mountain tunnels

NASA Astrophysics Data System (ADS)

Gertler, Alan W.; Fujita, Eric M.; Pierson, William R.; Wittorff, David N.

Measurements of on-road emissions of non-methane hydrocarbons (NMHCs) were made in the Fort McHenry Tunnel (Baltimore) and Tuscarora Mountain Tunnel (Pennsylvania) during the summer of 1992. Measurements were made during 11 one-hour periods in the Fort McHenry Tunnel and during 11 one-hour periods in the Tuscarora Mountain Tunnel. The observed light-duty fleets were quite new, with a median model year of approximately 1989. Speciated NMHC values were obtained from analyses of canister and Tenax samples, and light-duty speciated emission factors were calculated for the two tunnels. Fuel samples were collected in the area around the tunnels for use in constructing headspace and liquid fuel profiles for the chemical mass balance (CMB) receptor model. Profiles of tailpipe emissions were obtained from the literature. The CMB was used to apportion tailpipe from non-tailpipe emissions. Non-tailpipe sources were found to constitute approximately 15% of the light-duty NMHC emissions. The Federal automotive emission-rate models, MOBILE4.1 and MOBILE5, underpredicted non-tailpipe emissions, assigning approximately 9% and 6.5%, respectively, to non-tailpipe sources. In terms of total absolute emissions, MOBILE5 predictions were approximately a factor of 2 greater than MOBILE4.1 predictions. Both MOBILE4.1 and MOBILE5 underestimated the NMHC emissions in the Fort McHenry Tunnel and overpredicted the NMHC emissions in the Tuscarora Mountain Tunnel. In all cases, the MOBILE models underestimated the absolute value of the non-tailpipe emissions. The ability of the MOBILE models to account for observed emissions when conditions are more variable than those studies in the Fort McHenry and Tuscarora Mountain tunnels is still an open question.

Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units

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

Cai, H.; Wang, M.; Elgowainy, A.

Greenhouse gas (CO{sub 2}, CH{sub 4} and N{sub 2}O, hereinafter GHG) and criteria air pollutant (CO, NO{sub x}, VOC, PM{sub 10}, PM{sub 2.5} and SO{sub x}, hereinafter CAP) emission factors for various types of power plants burning various fuels with different technologies are important upstream parameters for estimating life-cycle emissions associated with alternative vehicle/fuel systems in the transportation sector, especially electric vehicles. The emission factors are typically expressed in grams of GHG or CAP per kWh of electricity generated by a specific power generation technology. This document describes our approach for updating and expanding GHG and CAP emission factors inmore » the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model developed at Argonne National Laboratory (see Wang 1999 and the GREET website at http://greet.es.anl.gov/main) for various power generation technologies. These GHG and CAP emissions are used to estimate the impact of electricity use by stationary and transportation applications on their fuel-cycle emissions. The electricity generation mixes and the fuel shares attributable to various combustion technologies at the national, regional and state levels are also updated in this document. The energy conversion efficiencies of electric generating units (EGUs) by fuel type and combustion technology are calculated on the basis of the lower heating values of each fuel, to be consistent with the basis used in GREET for transportation fuels. On the basis of the updated GHG and CAP emission factors and energy efficiencies of EGUs, the probability distribution functions (PDFs), which are functions that describe the relative likelihood for the emission factors and energy efficiencies as random variables to take on a given value by the integral of their own probability distributions, are updated using best-fit statistical curves to characterize the uncertainties associated with GHG and CAP emissions in life-cycle modeling with GREET.« less

Application of the denitrification-decomposition model to predict carbon dioxide emissions under alternative straw retention methods.

PubMed

Chen, Can; Chen, Deli; Pan, Jianjun; Lam, Shu Kee

2013-01-01

Straw retention has been shown to reduce carbon dioxide (CO2) emission from agricultural soils. But it remains a big challenge for models to effectively predict CO2 emission fluxes under different straw retention methods. We used maize season data in the Griffith region, Australia, to test whether the denitrification-decomposition (DNDC) model could simulate annual CO2 emission. We also identified driving factors of CO2 emission by correlation analysis and path analysis. We show that the DNDC model was able to simulate CO2 emission under alternative straw retention scenarios. The correlation coefficients between simulated and observed daily values for treatments of straw burn and straw incorporation were 0.74 and 0.82, respectively, in the straw retention period and 0.72 and 0.83, respectively, in the crop growth period. The results also show that simulated values of annual CO2 emission for straw burn and straw incorporation were 3.45 t C ha(-1) y(-1) and 2.13 t C ha(-1) y(-1), respectively. In addition the DNDC model was found to be more suitable in simulating CO2 mission fluxes under straw incorporation. Finally the standard multiple regression describing the relationship between CO2 emissions and factors found that soil mean temperature (SMT), daily mean temperature (T mean), and water-filled pore space (WFPS) were significant.

Application of the Denitrification-Decomposition Model to Predict Carbon Dioxide Emissions under Alternative Straw Retention Methods

PubMed Central

Chen, Deli; Pan, Jianjun; Lam, Shu Kee

2013-01-01

Straw retention has been shown to reduce carbon dioxide (CO2) emission from agricultural soils. But it remains a big challenge for models to effectively predict CO2 emission fluxes under different straw retention methods. We used maize season data in the Griffith region, Australia, to test whether the denitrification-decomposition (DNDC) model could simulate annual CO2 emission. We also identified driving factors of CO2 emission by correlation analysis and path analysis. We show that the DNDC model was able to simulate CO2 emission under alternative straw retention scenarios. The correlation coefficients between simulated and observed daily values for treatments of straw burn and straw incorporation were 0.74 and 0.82, respectively, in the straw retention period and 0.72 and 0.83, respectively, in the crop growth period. The results also show that simulated values of annual CO2 emission for straw burn and straw incorporation were 3.45 t C ha−1 y−1 and 2.13 t C ha−1 y−1, respectively. In addition the DNDC model was found to be more suitable in simulating CO2 mission fluxes under straw incorporation. Finally the standard multiple regression describing the relationship between CO2 emissions and factors found that soil mean temperature (SMT), daily mean temperature (T mean), and water-filled pore space (WFPS) were significant. PMID:24453915

Effect of mid-term drought on Quercus pubescens BVOCs' emission seasonality and their dependency on light and/or temperature

NASA Astrophysics Data System (ADS)

Saunier, Amélie; Ormeño, Elena; Boissard, Christophe; Wortham, Henri; Temime-Roussel, Brice; Lecareux, Caroline; Armengaud, Alexandre; Fernandez, Catherine

2017-06-01

Biogenic volatile organic compounds (BVOCs) emitted by plants represent a large source of carbon compounds released into the atmosphere, where they account for precursors of tropospheric ozone and secondary organic aerosols. Being directly involved in air pollution and indirectly in climate change, understanding what factors drive BVOC emissions is a prerequisite for modeling their emissions and predict air pollution. The main algorithms currently used to model BVOC emissions are mainly light and/or temperature dependent. Additional factors such as seasonality and drought also influence isoprene emissions, especially in the Mediterranean region, which is characterized by a rather long drought period in summer. These factors are increasingly included in models but only for the principal studied BVOC, namely isoprene, but there are still some discrepancies in estimations of emissions. In this study, the main BVOCs emitted by Quercus pubescens - isoprene, methanol, acetone, acetaldehyde, formaldehyde, MACR, MVK and ISOPOOH (these three last compounds detected under the same m/z) - were monitored with a PTR-ToF-MS over an entire seasonal cycle during both in situ natural and amplified drought, which is expected with climate change. Amplified drought impacted all studied BVOCs by reducing emissions in spring and summer while increasing emissions in autumn. All six BVOCs monitored showed daytime light and temperature dependencies while three BVOCs (methanol, acetone and formaldehyde) also showed emissions during the night despite the absence of light under constant temperature. Moreover, methanol and acetaldehyde burst in the early morning and formaldehyde deposition and uptake were also punctually observed, which were not assessed by the classical temperature and light models.

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.

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.

Airborne and ground-based measurements of the trace gases and particles emitted from prescribed fires in the United States

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

Burling, Ian; Yokelson, Robert J.; Akagi, Sheryl

2011-12-07

We measured the emission factors for 19 trace gas species and particulate matter (PM2.5) from 14 prescribed fires in chaparral and oak savanna in the southwestern US, as well as pine forest understory in the southeastern US and Sierra Nevada mountains of California. These are likely the most extensive emission factor field measurements for temperate biomass burning to date and the only published emission factors for temperate oak savanna fuels. This study helps close the gap in emissions data available for temperate zone fires relative to tropical biomass burning. We present the first field measurements of the biomass burning emissionsmore » of glycolaldehyde, a possible precursor for aqueous phase secondary organic aerosol formation. We also measured the emissions of phenol, another aqueous phase secondary organic aerosol precursor. Our data confirm previous suggestions that urban deposition can impact the NOx emission factors and thus subsequent plume chemistry. For two fires, we measured the emissions in the convective smoke plume from our airborne platform at the same time the unlofted residual smoldering combustion emissions were measured with our ground-based platform after the flame front passed through. The smoke from residual smoldering combustion was characterized by emission factors for hydrocarbon and oxygenated organic species that were up to ten times higher than in the lofted plume, including significant 1,3-butadiene and isoprene concentrations which were not observed in the lofted plume. This should be considered in modeling the air quality impacts of smoke that disperses at ground level, and we show that the normally-ignored unlofted emissions can also significantly impact estimates of total emissions. Preliminary evidence of large emissions of monoterpenes was seen in the residual smoldering spectra, but we have not yet quantified these emissions. These data should lead to an improved capacity to model the impacts of biomass burning in similar ecosystems.« less

Development and review of Euro 5 passenger car emission factors based on experimental results over various driving cycles.

PubMed

Fontaras, Georgios; Franco, Vicente; Dilara, Panagiota; Martini, Giorgio; Manfredi, Urbano

2014-01-15

The emissions of CO2 and regulated pollutants (NOx, HC, CO, PM) of thirteen Euro 5 compliant passenger cars (seven gasoline, six Diesel) were measured on a chassis dynamometer. The vehicles were driven repeatedly over the European type-approval driving cycle (NEDC) and the more dynamic WMTC and CADC driving cycles. Distance-specific emission factors were derived for each pollutant and sub-cycle, and these were subsequently compared to the corresponding emission factors provided by the reference European models used for vehicle emission inventory compilation (COPERT and HBEFA) and put in context with the applicable European emission limits. The measured emissions stayed below the legal emission limits when the type-approval cycle (NEDC) was used. Over the more dynamic cycles (considered more representative of real-world driving) the emissions were consistently higher but in most cases remained below the type-approval limit. The high NOx emissions of Diesel vehicles under real-world driving conditions remain the main cause for environmental concern regarding the emission profile of Euro 5 passenger cars. Measured emissions of NOx exceeded the type-approval limits (up to 5 times in extreme cases) and presented significantly increased average values (0.35 g/km for urban driving and 0.56 g/km for motorway driving). The comparison with the reference models showed good correlation in all cases, a positive finding considering the importance of these tools in emission monitoring and policy-making processes. © 2013. Published by Elsevier B.V. All rights reserved.

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.

Simulating N2O emissions under different tillage systems of irrigated corn using RZ-Shaw model

USDA-ARS?s Scientific Manuscript database

Nitrous oxide (N2O) is potent greenhouse gas (GHG) and agriculture is a global source of N2O emissions from soil fertility management. Yet emissions vary by agronomic practices and environmental factors that govern soil moisture and temperature. Ecosystem models are important tools to estimate N2O e...

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,...

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.

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

NASA Technical Reports Server (NTRS)

Tang, Wei; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-01-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D. S.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-11-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Inverse modeling of Texas NOx emissions using space-based and ground-based NO2 observations

NASA Astrophysics Data System (ADS)

Tang, W.; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-07-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Fast and optimized methodology to generate road traffic emission inventories and their uncertainties

NASA Astrophysics Data System (ADS)

Blond, N.; Ho, B. Q.; Clappier, A.

2012-04-01

Road traffic emissions are one of the main sources of air pollution in the cities. They are also the main sources of uncertainties in the air quality numerical models used to forecast and define abatement strategies. Until now, the available models for generating road traffic emission always required a big effort, money and time. This inhibits decisions to preserve air quality, especially in developing countries where road traffic emissions are changing very fast. In this research, we developed a new model designed to fast produce road traffic emission inventories. This model, called EMISENS, combines the well-known top-down and bottom-up approaches to force them to be coherent. A Monte Carlo methodology is included for computing emission uncertainties and the uncertainty rate due to each input parameters. This paper presents the EMISENS model and a demonstration of its capabilities through an application over Strasbourg region (Alsace), France. Same input data as collected for Circul'air model (using bottom-up approach) which has been applied for many years to forecast and study air pollution by the Alsatian air quality agency, ASPA, are used to evaluate the impact of several simplifications that a user could operate . These experiments give the possibility to review older methodologies and evaluate EMISENS results when few input data are available to produce emission inventories, as in developing countries and assumptions need to be done. We show that same average fraction of mileage driven with a cold engine can be used for all the cells of the study domain and one emission factor could replace both cold and hot emission factors.

Arrhenius equation for modeling feedyard ammonia emissions using temperature and diet crude protein.

PubMed

Todd, Richard W; Cole, N Andy; Waldrip, Heidi M; Aiken, Robert M

2013-01-01

Temperature controls many processes of NH volatilization. For example, urea hydrolysis is an enzymatically catalyzed reaction described by the Arrhenius equation. Diet crude protein (CP) controls NH emission by affecting N excretion. Our objectives were to use the Arrhenius equation to model NH emissions from beef cattle () feedyards and test predictions against observed emissions. Per capita NH emission rate (PCER), air temperature (), and CP were measured for 2 yr at two Texas Panhandle feedyards. Data were fitted to analogs of the Arrhenius equation: PCER = () and PCER = (,CP). The models were applied at a third feedyard to predict NH emissions and compare predicted to measured emissions. Predicted mean NH emissions were within -9 and 2% of observed emissions for the () and (T,CP) models, respectively. Annual emission factors calculated from models underestimated annual NH emission by 11% [() model] or overestimated emission by 8% [(,CP) model]. When from a regional weather station and three classes of CP drove the models, the () model overpredicted annual NH emission of the low CP class by 14% and underpredicted emissions of the optimum and high CP classes by 1 and 39%, respectively. The (,CP) model underpredicted NH emissions by 15, 4, and 23% for low, optimum, and high CP classes, respectively. Ammonia emission was successfully modeled using only, but including CP improved predictions. The empirical () and (,CP) models can successfully model NH emissions in the Texas Panhandle. Researchers are encouraged to test the models in other regions where high-quality NH emissions data are available. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

The ABAG biogenic emissions inventory project

NASA Technical Reports Server (NTRS)

Carson-Henry, C. (Editor)

1982-01-01

The ability to identify the role of biogenic hydrocarbon emissions in contributing to overall ozone production in the Bay Area, and to identify the significance of that role, were investigated in a joint project of the Association of Bay Area Governments (ABAG) and NASA/Ames Research Center. Ozone, which is produced when nitrogen oxides and hydrocarbons combine in the presence of sunlight, is a primary factor in air quality planning. In investigating the role of biogenic emissions, this project employed a pre-existing land cover classification to define areal extent of land cover types. Emission factors were then derived for those cover types. The land cover data and emission factors were integrated into an existing geographic information system, where they were combined to form a Biogenic Hydrocarbon Emissions Inventory. The emissions inventory information was then integrated into an existing photochemical dispersion model.

Improved Model of Isoprene Emissions in Africa using Ozone Monitoring Instrument (OMI) Satellite Observations of Formaldehyde: Implications for Oxidants and Particulate Matter

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

Marais, E. A.; Jacob, D.; Guenther, Alex B.

We use a 2005-2009 record of isoprene emissions over Africa derived from OMI satellite observations of formaldehyde (HCHO) to better understand the factors controlling isoprene emission on the scale of the continent and evaluate the impact of isoprene emissions on atmospheric composition in Africa. OMI-derived isoprene emissions show large seasonality over savannas driven by temperature and leaf area index (LAI), and much weaker seasonality over equatorial forests driven by temperature. The commonly used MEGAN (version 2.1) global 31 isoprene emission model reproduces this seasonality but is biased high, particularly for 32 equatorial forests, when compared to OMI and relaxed-eddy accumulationmore » measurements. 33 Isoprene emissions in MEGAN are computed as the product of an emission factor Eo, LAI, and 34 activity factors dependent on environmental variables. We use the OMI-derived emissions to 35 provide improved estimates of Eo that are in good agreement with direct leaf measurements from 36 field campaigns (r = 0.55, bias = -19%). The largest downward corrections to MEGAN Eo values are for equatorial forests and semi-arid environments, and this is consistent with latitudinal transects of isoprene over West Africa from the AMMA aircraft campaign. Total emission of isoprene in Africa is estimated to be 77 Tg C a-1, compared to 104 Tg C a-1 in MEGAN. Simulations with the GEOS-Chem oxidant-aerosol model suggest that isoprene emissions increase mean surface ozone in West Africa by up to 8 ppbv, and particulate matter by up to 1.5 42 μg m-3, due to coupling with anthropogenic influences.« less

Highly-controlled, reproducible measurements of aerosol emissions from African biomass combustion

NASA Astrophysics Data System (ADS)

Haslett, Sophie; Thomas, J. Chris; Morgan, William; Hadden, Rory; Liu, Dantong; Allan, James; Williams, Paul; Sekou, Keïta; Liousse, Catherine; Coe, Hugh

2017-04-01

Particulate emissions from biomass burning can alter the atmosphere's radiative balance and cause significant harm to human health. However, the relationship between these emissions and fundamental combustion processes is, to date, poorly characterised. In atmospheric models, aerosol emissions are represented by emission factors based on mass loss, which are averaged over an entire combustion event for each particulate species. This approach, however, masks huge variability in emissions during different phases of the combustion period. Laboratory tests have shown that even small changes to the burning environment can lead to huge variation in observed aerosol emission factors (Akagi et al., 2011). In order to address this gap in understanding, in this study, small wood samples sourced from Côte D'Ivoire were burned in a highly-controlled laboratory environment. The shape and mass of samples, available airflow and surrounding heat were carefully regulated. Organic aerosol and refractory black carbon emissions were measured in real-time using an Aerosol Mass Spectrometer and a Single Particle Soot Photometer, respectively. Both of these instruments are used regularly to measure aerosol concentrations in the field. This methodology produced remarkably repeatable results, allowing three different phases of combustion to be identified by their emissions. Black carbon was emitted predominantly during flaming combustion; organic aerosols were emitted during pyrolysis before ignition and from smouldering-dominated behaviour near the end of combustion. During the flaming period, there was a strong correlation between the emission of black carbon and the rate of mass loss, which suggests there is value in employing a mass-based emission factor for this species. However, very little correlation was seen between organic aerosol and mass loss throughout the tests. As such, results here suggest that emission factors averaged over an entire combustion event are unlikely to be useful for organic aerosol emissions. The two different phases producing organic aerosol, pyrolysis and smouldering, were observed to have different mass spectra. In previous ambient experiments, two organic factors with very comparable signatures to these have been identified using positive matrix factorisation (Young et al., 2015). As such, it is postulated that these ambient organic factors are likely associated with the two combustion phases identified here. References: Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D. and Wennberg, P. O., Emission factors for open and domestic biomass burning for use in atmospheric models. Atmos. Chem. Phys., 11, 4039-4072 (2011) Young, D. E., Allan, J. D., Williams, P. I., Green, D. C., Harrison, R. M., Yin, J., Flynn, M. J., Gallagher, M. W., Coe, H., Investigating a two-component model of solid fuel organic aerosol in London: processes, PM1 contribution, and seasonality. Atmos. Chem. Phys, 15, 2429-2443 (2015)

Greenhouse gas emission curves for advanced biofuel supply chains

NASA Astrophysics Data System (ADS)

Daioglou, Vassilis; Doelman, Jonathan C.; Stehfest, Elke; Müller, Christoph; Wicke, Birka; Faaij, Andre; van Vuuren, Detlef P.

2017-12-01

Most climate change mitigation scenarios that are consistent with the 1.5-2 °C target rely on a large-scale contribution from biomass, including advanced (second-generation) biofuels. However, land-based biofuel production has been associated with substantial land-use change emissions. Previous studies show a wide range of emission factors, often hiding the influence of spatial heterogeneity. Here we introduce a spatially explicit method for assessing the supply of advanced biofuels at different emission factors and present the results as emission curves. Dedicated crops grown on grasslands, savannahs and abandoned agricultural lands could provide 30 EJBiofuel yr-1 with emission factors less than 40 kg of CO2-equivalent (CO2e) emissions per GJBiofuel (for an 85-year time horizon). This increases to 100 EJBiofuel yr-1 for emission factors less than 60 kgCO2e GJBiofuel-1. While these results are uncertain and depend on model assumptions (including time horizon, spatial resolution, technology assumptions and so on), emission curves improve our understanding of the relationship between biofuel supply and its potential contribution to climate change mitigation while accounting for spatial heterogeneity.

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.

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.

The influencing factors of CO2 emission intensity of Chinese agriculture from 1997 to 2014.

PubMed

Long, Xingle; Luo, Yusen; Wu, Chao; Zhang, Jijian

2018-05-01

In China, agriculture produces the greatest chemical oxygen demand (COD) emissions in wastewater and the most methane (CH 4 ) emissions. It is imperative that agricultural pollution in China be reduced. This study investigated the influencing factors of the CO 2 emission intensity of Chinese agriculture from 1997 to 2014. We analyzed the influencing factors of the CO 2 emission intensity through the first-stage least-square regression. We also analyzed determinants of innovation through the second-stage least-square regression. We found that innovation negatively affected the CO 2 emission intensity in the model of the nation. FDI positively affected innovation in China. It is important to enhance indigenous innovation for green agriculture through labor training and collaboration between agriculture and academia.

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

PubMed

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

2012-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Assessing the long-range transport of PAH to a sub-Arctic site using positive matrix factorization and potential source contribution function

NASA Astrophysics Data System (ADS)

Sofowote, Uwayemi M.; Hung, Hayley; Rastogi, Ankit K.; Westgate, John N.; Deluca, Patrick F.; Su, Yushan; McCarry, Brian E.

2011-02-01

Gas-phase and particle-phase atmospheric samples collected in a sparsely populated sub-Arctic environment in the Yukon Territory, Canada were analyzed for a wide range of organic pollutants including polycyclic aromatic hydrocarbons (PAH). Receptor modeling using positive matrix factorization (PMF) was applied to a PAH data set from samples collected between August 2007 and December 2008 to afford four factors. These factors were designated as fossil fuel combustion emissions, particle-phase wood combustion emissions, gas-phase wood combustion emissions, and unburned petroleum/petrogenic emissions. The multiple linear regression-derived average contributions of these factors to the total PAH concentrations were 14% for fossil fuel combustion, 6% for particle-phase wood combustion emissions, 46% for gas-phase wood combustion emissions and 34% for petrogenic emissions. When the total PAH concentrations (defined as the sum of twenty-two PAH) and the PMF-modeled PAH concentrations set were compared, the correlation was excellent ( R2 = 0.97). Ten-day back trajectories starting at four different heights were used in a potential source contribution function analysis (PSCF) to assess the potential source regions of these PAH factors. Mapping the computed PSCF values for the four PMF factors revealed different source regions in the northern hemisphere for each PMF factor. Atmospheric transport of PAH occurred from both relatively short and long distances with both continental (North American) and trans-oceanic (Asian) sources contributing significantly to the total PAH. This study provides evidence of the transport of fossil fuel and wood combustion emissions from Asia, continental North America and northern Europe to sub-Arctic Canada (and by extension to the Canadian Arctic) primarily during cooler (fall-winter) months. This study demonstrates for the first time that the combined PMF-PSCF methodology can be used to identify geographically-disperse PAH source contributors on a hemispherical scale.

Emissions of N2O and NO from fertilized fields: Summary of available measurement data

NASA Astrophysics Data System (ADS)

Bouwman, A. F.; Boumans, L. J. M.; Batjes, N. H.

2002-12-01

Information from 846 N2O emission measurements in agricultural fields and 99 measurements for NO emissions was summarized to assess the influence of various factors regulating emissions from mineral soils. The data indicate that there is a strong increase of both N2O and NO emissions accompanying N application rates, and soils with high organic-C content show higher emissions than less fertile soils. A fine soil texture, restricted drainage, and neutral to slightly acidic conditions favor N2O emission, while (though not significant) a good soil drainage, coarse texture, and neutral soil reaction favor NO emission. Fertilizer type and crop type are important factors for N2O but not for NO, while the fertilizer application mode has a significant influence on NO only. Regarding the measurements, longer measurement periods yield more of the fertilization effect on N2O and NO emissions, and intensive measurements (≥1 per day) yield lower emissions than less intensive measurements (2-3 per week). The available data can be used to develop simple models based on the major regulating factors which describe the spatial variability of emissions of N2O and NO with less uncertainty than emission factor approaches based on country N inputs, as currently used in national emission inventories.

Understanding the origins of uncertainty in landscape-scale variations of emissions of nitrous oxide

NASA Astrophysics Data System (ADS)

Milne, Alice; Haskard, Kathy; Webster, Colin; Truan, Imogen; Goulding, Keith

2014-05-01

Nitrous oxide is a potent greenhouse gas which is over 300 times more radiatively effective than carbon dioxide. In the UK, the agricultural sector is estimated to be responsible for over 80% of nitrous oxide emissions, with these emissions resulting from livestock and farmers adding nitrogen fertilizer to soils. For the purposes of reporting emissions to the IPCC, the estimates are calculated using simple models whereby readily-available national or international statistics are combined with IPCC default emission factors. The IPCC emission factor for direct emissions of nitrous oxide from soils has a very large uncertainty. This is primarily because the variability of nitrous oxide emissions in space is large and this results in uncertainty that may be regarded as sample noise. To both reduce uncertainty through improved modelling, and to communicate an understanding of this uncertainty, we must understand the origins of the variation. We analysed data on nitrous oxide emission rate and some other soil properties collected from a 7.5-km transect across contrasting land uses and parent materials in eastern England. We investigated the scale-dependence and spatial uniformity of the correlations between soil properties and emission rates from farm to landscape scale using wavelet analysis. The analysis revealed a complex pattern of scale-dependence. Emission rates were strongly correlated with a process-specific function of the water-filled pore space at the coarsest scale and nitrate at intermediate and coarsest scales. We also found significant correlations between pH and emission rates at the intermediate scales. The wavelet analysis showed that these correlations were not spatially uniform and that at certain scales changes in parent material coincided with significant changes in correlation. Our results indicate that, at the landscape scale, nitrate content and water-filled pore space are key soil properties for predicting nitrous oxide emissions and should therefore be incorporated into process models and emission factors for inventory calculations.

An emission inventory of livestock-related bioaerosols for Lower Saxony, Germany

NASA Astrophysics Data System (ADS)

Seedorf, Jens

Detailed livestock-related emission inventories are now available for gases but not for bioaerosols, which are emitted in significant amounts and in varying compositions. In view of the environmental importance of bioaerosols, a model for their calculation is proposed here. The basic formula multiplies emission factors by the number of farm animals, but the model is extended by a factor which considers provisionally the influence of production cycles of various types of livestock on the estimated emissions. Despite several uncertainty factors, emissions factors are calculated for dust (inhalable, respirable), endotoxins (inhalable, respirable) and microorganisms (total mesophilic bacteria, Enterobacteriaceae, fungi) from ventilated livestock buildings. The calculation model and the emission factors are the basis for a simple geographical information system designed to display the calculated emission potencies of livestock-related bioaerosols for the year 1999 in the 46 districts and autonomous cities in Lower Saxony, Germany. The three highest emissions of inhalable dust were determined for the three animal-dense districts of Grafschaft Bentheim (485.3 kg a -1 km -2), Cloppenburg (648.8 kg a -1 km -2) and Vechta (1203.4 kg a -1 km -2). On the other hand, the lowest bioaerosol emissions were found for the cities of Salzgitter (9.6 kg a -1 km -2), Braunschweig (10.6 kg a -1 km -2) and Wolfenbüttel (12.2 kg a -1 km -2) due to their more urban, non-agricultural setting. With the aid of the agricultural census data, the percentages of temporal emission variations were assessed between 1996 and 1999, and found to have changed distinctly due to fluctuations in animal numbers in the districts. The following changes were noted in the three districts with the greatest increase or decrease of emitted particulate matter from 1996 to 1999: more inhalable dust was emitted in the rural districts of Stade (+9.6%), Cloppenburg (+14.9%) and Emsland (+18.2%), while there were clear declines in Oldenburg City (-24.1%), the district Helmstedt (-15.1%) and Braunschweig City (-14.4%).

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.

Towards a climate-dependent paradigm of ammonia emission and deposition

EPA Science Inventory

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 ...

Historical anthropogenic and biofuel burning emissions of carbon monoxide, 1850-2000

NASA Astrophysics Data System (ADS)

Liu, L.; Zarzycki, C. M.; Winijkul, E.; Bond, T. C.

2011-12-01

Liang Liu, Colin Zarzycki, Ekbordin Winijkul, Tami C. Bond Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA Carbon monoxide (CO) plays an important role in atmospheric chemistry by acting as the primary sink of the most important atmospheric oxidizer, hydroxyl radicals (OH), and participating in the cycle of tropospheric ozone. CO can also provide constraints on model prediction of black carbon (BC) and vice versa due to their common sources of incomplete combustion. A well developed historical emission inventory of CO would serve the purpose of various global atmospheric models over the historical record. Only a few attempts have been made to represent the time dependence of CO emissions. In this study, we present the first technology based global historical trend of anthropogenic and biofuel emissions of CO from 1850 to 2000. The essential components of a bottom-up emission inventory are technology divisions, fuel consumptions for each technology, and emission factors for each combination of fuel and technology. Previous research done by Bond et al., [2007] has provided this study with technology breakdowns for different combinations of fuel and usage and the time trends of fuel-use for each specific technology in activities that contribute to BC emissions. This work reconstructs the fuel-use trend of the brick and cement industries which were not included in the historical BC emission inventory but play an important role in CO emission. Emission factors are developed for past and present CO emitters. Fuel consumption and emission factors are then combined to estimate global CO emissions at the country level. Uncertainty analysis in activity data, technology splits, and emission factors are performed. The developed historical CO emission trend is compared with the historical BC emission trend to provide more insight into the relationship of the two pollutants.

[Research on carbon reduction potential of electric vehicles for low-carbon transportation and its influencing factors].

PubMed

Shi, Xiao-Qing; Li, Xiao-Nuo; Yang, Jian-Xin

2013-01-01

Transportation is the key industry of urban energy consumption and carbon emissions. The transformation of conventional gasoline vehicles to new energy vehicles is an important initiative to realize the goal of developing low-carbon city through energy saving and emissions reduction, while electric vehicles (EV) will play an important role in this transition due to their advantage in energy saving and lower carbon emissions. After reviewing the existing researches on energy saving and emissions reduction of electric vehicles, this paper analyzed the factors affecting carbon emissions reduction. Combining with electric vehicles promotion program in Beijing, the paper analyzed carbon emissions and reduction potential of electric vehicles in six scenarios using the optimized energy consumption related carbon emissions model from the perspective of fuel life cycle. The scenarios included power energy structure, fuel type (energy consumption per 100 km), car type (CO2 emission factor of fuel), urban traffic conditions (speed), coal-power technologies and battery type (weight, energy efficiency). The results showed that the optimized model was able to estimate carbon emissions caused by fuel consumption more reasonably; electric vehicles had an obvious restrictive carbon reduction potential with the fluctuation of 57%-81.2% in the analysis of six influencing factors, while power energy structure and coal-power technologies play decisive roles in life-cycle carbon emissions of electric vehicles with the reduction potential of 78.1% and 81.2%, respectively. Finally, some optimized measures were proposed to reduce transport energy consumption and carbon emissions during electric vehicles promotion including improving energy structure and coal technology, popularizing energy saving technologies and electric vehicles, accelerating the battery R&D and so on. The research provides scientific basis and methods for the policy development for the transition of new energy vehicles in low-carbon transport.

Consideration of Real World Factors Influencing Greenhouse Gas Emissions in ALPHA

EPA Science Inventory

Discuss a variety of factors that influence the simulated fuel economy and GHG emissions that are often overlooked and updates made to ALPHA based on actual benchmarking data observed across a range of vehicles and transmissions. ALPHA model calibration is also examined, focusin...

Source apportionment of stack emissions from research and development facilities using positive matrix factorization

NASA Astrophysics Data System (ADS)

Ballinger, Marcel Y.; Larson, Timothy V.

2014-12-01

Research and development (R&D) facility emissions are difficult to characterize due to their variable processes, changing nature of research, and large number of chemicals. Positive matrix factorization (PMF) was applied to volatile organic compound (VOC) concentrations measured in the main exhaust stacks of four different R&D buildings to identify the number and composition of major contributing sources. PMF identified between 9 and 11 source-related factors contributing to stack emissions, depending on the building. Similar factors between buildings were major contributors to trichloroethylene (TCE), acetone, and ethanol emissions; other factors had similar profiles for two or more buildings but not all four. At least one factor for each building was identified that contained a broad mix of many species and constraints were used in PMF to modify the factors to resemble more closely the off-shift concentration profiles. PMF accepted the constraints with little decrease in model fit.

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.

Air pollution and health risks due to vehicle traffic.

PubMed

Zhang, Kai; Batterman, Stuart

2013-04-15

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed-volume relationship, the California Line Source Dispersion Model, an empirical NO2-NOx relationship, estimated travel time changes during congestion, and concentration-response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, "U" shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2-NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. Copyright © 2013 Elsevier B.V. All rights reserved.

Air pollution and health risks due to vehicle traffic

PubMed Central

Zhang, Kai; Batterman, Stuart

2014-01-01

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed–volume relationship, the California Line Source Dispersion Model, an empirical NO2–NOx relationship, estimated travel time changes during congestion, and concentration–response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, “U” shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2–NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. PMID:23500830

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.

Source apportionment vs. emission inventories of non-methane hydrocarbons (NMHC) in an urban area of the Middle East: local and global perspectives

NASA Astrophysics Data System (ADS)

Salameh, T.; Sauvage, S.; Afif, C.; Borbon, A.; Locoge, N.

2015-10-01

We applied the Positive Matrix Factorization model to two large datasets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt % respectively in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The national road transport inventory shows lowest emissions than the ones from PMF but with a reasonable difference lower than 50 %. Global inventories show higher discrepancies with lower emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is a strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector. Highlights: - PMF model was applied to identify major NMHC sources and their seasonal variation. - Gasoline evaporation accounts for more than 40 % both in winter and in summer. - NMHC urban emissions are dominated by traffic related sources in both seasons. - Agreement with the emission inventory regarding the relative contribution of the on-road mobile source but disagreement in terms of emission quantities suggesting an underestimation of the inventories.

Real-time emission factor measurements of isocyanic acid from light duty gasoline vehicles.

PubMed

Brady, James M; Crisp, Timia A; Collier, Sonya; Kuwayama, Toshihiro; Forestieri, Sara D; Perraud, Véronique; Zhang, Qi; Kleeman, Michael J; Cappa, Christopher D; Bertram, Timothy H

2014-10-07

Exposure to gas-phase isocyanic acid (HNCO) has been previously shown to be associated with the development of atherosclerosis, cataracts and rheumatoid arthritis. As such, accurate emission inventories for HNCO are critical for modeling the spatial and temporal distribution of HNCO on a regional and global scale. To date, HNCO emission rates from light duty gasoline vehicles, operated under driving conditions, have not been determined. Here, we present the first measurements of real-time emission factors of isocyanic acid from a fleet of eight light duty gasoline-powered vehicles (LDGVs) tested on a chassis dynamometer using the Unified Driving Cycle (UC) at the California Air Resources Board (CARB) Haagen-Smit test facility, all of which were equipped with three-way catalytic converters. HNCO emissions were observed from all vehicles, in contrast to the idealized laboratory measurements. We report the tested fleet averaged HNCO emission factors, which depend strongly on the phase of the drive cycle; ranging from 0.46 ± 0.13 mg kg fuel(-1) during engine start to 1.70 ± 1.77 mg kg fuel(-1) during hard acceleration after the engine and catalytic converter were warm. The tested eight-car fleet average fuel based HNCO emission factor was 0.91 ± 0.58 mg kg fuel(-1), within the range previously estimated for light duty diesel-powered vehicles (0.21-3.96 mg kg fuel(-1)). Our results suggest that HNCO emissions from LDGVs represent a significant emission source in urban areas that should be accounted for in global and regional models.

[Driving forces of carbon emission from energy consumption in China old industrial cities: a case study of Shenyang City, Northeast China].

PubMed

Ren, Wan-Xia; Geng, Yong; Xue, Bing

2012-10-01

To quantitatively analyze the effects of anthropogenic factors on regional environmental quality is a hot topic in the field of sustainable development research. Taking the typical old industrial city Shenyang in Northeast China as a case, and by using the IPCC method for calculating carbon emission from energy consumption, this paper estimated the carbon emission from energy consumption in the city in 1978-2009, and a time series analysis on the anthropogenic factors driving this carbon emission was made by the STIRPAT model based upon Kaya equation and ridge regression. In 1978-2009, the carbon emission in the city had a slow increase first, slow decrease then, and a rapid increase thereafter. The total carbon emission in 2009 was 4.6 times of that in 1978. Population growth was the main factor driving the growth of the emission, and there existed an equal-proportional variation between the population growth and the carbon emission growth. Urbanization was another main driving factor followed by population growth, and the per capita GDP was positively correlated with the carbon emission. Kuznets curve did not exist for the relationship between economic development and carbon emission in Shenyang. Energy source intensity reduction (representing technology improvement) was the main factor driving the reduction of the total carbon emission.

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.

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.

Factors Affecting Regional Per-Capita Carbon Emissions in China Based on an LMDI Factor Decomposition Model

PubMed Central

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. PMID:24353753

Near-road air pollutant concentrations of CO and PM 2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

NASA Astrophysics Data System (ADS)

Zhang, Kai; Batterman, Stuart

2010-05-01

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM 2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM 2.5 showed that GAM emission estimates were much higher (by 4-5 times) than the dispersion model results, and that the traffic-PM 2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM 2.5 concentrations, a likely result of underestimating PM 2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.

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.

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.

Evaluating near highway air pollutant levels and estimating emission factors: Case study of Tehran, Iran.

PubMed

Nayeb Yazdi, Mohammad; Delavarrafiee, Maryam; Arhami, Mohammad

2015-12-15

A field sampling campaign was implemented to evaluate the variation in air pollutants levels near a highway in Tehran, Iran (Hemmat highway). The field measurements were used to estimate road link-based emission factors for average vehicle fleet. These factors were compared with results of an in tunnel measurement campaign (in Resalat tunnel). Roadside and in-tunnel measurements of carbon monoxide (CO) and size-fractionated particulate matter (PM) were conducted during the field campaign. The concentration gradient diagrams showed exponential decay, which represented a substantial decay, more than 50-80%, in air pollutants level in a distance between 100 and 150meters (m) of the highway. The changes in particle size distribution by distancing from highway were also captured and evaluated. The results showed particle size distribution shifted to larger size particles by distancing from highway. The empirical emission factors were obtained by using the roadside and in tunnel measurements with a hypothetical box model, floating machine model, CALINE4, CT-EMFAC or COPERT. Average CO emission factors were estimated to be in a range of 4 to 12g/km, and those of PM10 were 0.1 to 0.2g/km, depending on traffic conditions. Variations of these emission factors under real working condition with speeds were determined. Copyright © 2015 Elsevier B.V. All rights reserved.

Atmospheric pollution reduction effect and regional predicament: An empirical analysis based on the Chinese provincial NOx emissions.

PubMed

Ding, Lei; Liu, Chao; Chen, Kunlun; Huang, Yalin; Diao, Beidi

2017-07-01

Atmospheric pollution emissions have become a matter of public concern in recent years. However, most of the existing researches on NOx pollution are from the natural science and technology perspective, few studies have been conducted from an economic point, and regional differences have not been given adequate attention. This paper adopts provincial panel data from 2006 to 2013 and the LMDI model to analyze the key driving factors and regional dilemmas of NOx emissions. The results show that significant regional disparities still exit on NO x emissions and its reduction effect 27 provinces didn't accomplish their corresponding reduction targets. Economic development factor is the dominating driving factor of NO x emissions during the study period, while energy efficiency and technology improvement factors offset total NO x emissions in the majority of provinces. In addition, the industrial structure factor plays a more significant role in reducing the NO x emissions after 2011. Therefore, the government should consider all these factors as well as regional heterogeneity in developing appropriate pollution mitigating policies. It's necessary to change NOx emissions control attitude from original key areas control to divided-zone control, not only attaches great importance to the reduction of the original key areas, but also emphasizes the new potential hotspots with high NO x emissions. Copyright © 2017 Elsevier Ltd. All rights reserved.

40 CFR 98.343 - Calculating GHG emissions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... potential (metric tons CH4/metric ton waste) = MCF × DOC × DOCF × F × 16/12. MCF = Methane correction factor... = Methane emissions from the landfill in the reporting year (metric tons CH4). GCH 4 = Modeled methane...). Emissions = Methane emissions from the landfill in the reporting year (metric tons CH4). R = Quantity of...

[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 New Direct Coupled Regional-scale Meteorology and Chemistry Model

NASA Astrophysics Data System (ADS)

Li, J.; Hsu, S.; Liu, T.; Chiang, C.; Chang, J.

2007-12-01

WRF/Chem was first developed in the US and generously made available to the international research community a short time ago. Starting from this, many groups have contributed new components and subroutines to this model. Based on WRF/Chem, a new online integrated model system named WRF/ChemT was established in Taiwan. It is significantly different from WRF/Chem in the following important aspects. For an online model, all chemical species emission must be direct coupled to WRF meteorology. All publicly available versions of WRF/Chem do not have this fundamental coupling. For these WRF/Chem models all emission data must first be preprocessed by SMOKE or other emission models driven by MM5 or WRF meteorologies in offline manner. WRF/ChemT has a self-consistent online emission process. We replaced the old emission driver with NCU driver, the plume rise of point sources and biogenic VOCs emission are calculated online. So that meteorology model, emission model and chemistry transport model are coupled directly in WRF/ChemT. Cloud impact on actinic flux should be consistent with WRF cloud-aerosol submodel used, not just moisture parameterization. Photolysis rates in WRF/ChemT are self consistent in every sub modules. New dry deposition routines were developed including addition of a vertical mixing scheme named the Asymmetrical Convective Model (ACM) which is used in CMAQ. The advantage of using ACM submodel had been demonstrated in earlier studies. Computational inefficiency has been a lingering problem for WRF/Chem. We have worked on this aspect of WRF/Chem development and by using a new chemical solver and also reorganizing the operator splitting computational algorithm we have made significant computational speed gain. WRF/chemT is about a factor of 4 faster in the chemistry solver and a factor of 2 faster in chemical species transport. When added together it is about a factor of 2 faster than WRF/Chem(version 2.1.2), i. e. gas-phase chemistry and meteorology are now equally fast. WRF/ChemT was evaluated and applied in regional air quality research in Taiwan. The comparison with WRF/Chem and selected current applications will be discussed in this report.

Projections of emissions from burning of biomass foruse in studies of global climate and atmospheric chemistry

Treesearch

Darold E. Ward; Weimin Hao

1991-01-01

Emissions of trace gases and particulate matter from burning of biomass are generally factored into global climate models. Models for improving the estimates of the global annual release of emissions from biomass fires are presented. Estimates of total biomass consumed on a global basis range from 2 to 10 Pg (1 petagram = 1015 g) per year. New...

Directional infrared temperature and emissivity of vegetation: Measurements and models

NASA Technical Reports Server (NTRS)

Norman, J. M.; Castello, S.; Balick, L. K.

1994-01-01

Directional thermal radiance from vegetation depends on many factors, including the architecture of the plant canopy, thermal irradiance, emissivity of the foliage and soil, view angle, slope, and the kinetic temperature distribution within the vegetation-soil system. A one dimensional model, which includes the influence of topography, indicates that thermal emissivity of vegetation canopies may remain constant with view angle, or emissivity may increase or decrease as view angle from nadir increases. Typically, variations of emissivity with view angle are less than 0.01. As view angle increases away from nadir, directional infrared canopy temperature usually decreases but may remain nearly constant or even increase. Variations in directional temperature with view angle may be 5C or more. Model predictions of directional emissivity are compared with field measurements in corn canopies and over a bare soil using a method that requires two infrared thermometers, one sensitive to the 8 to 14 micrometer wavelength band and a second to the 14 to 22 micrometer band. After correction for CO2 absorption by the atmosphere, a directional canopy emissivity can be obtained as a function of view angle in the 8 to 14 micrometer band to an accuracy of about 0.005. Modeled and measured canopy emissivities for corn varied slightly with view angle (0.990 at nadir and 0.982 at 75 deg view zenith angle) and did not appear to vary significantly with view angle for the bare soil. Canopy emissivity is generally nearer to unity than leaf emissivity may vary by 0.02 with wavelength even though leaf emissivity. High spectral resolution, canopy thermal emissivity may vary by 0.02 with wavelength even though leaf emissivity may vary by 0.07. The one dimensional model provides reasonably accurate predictions of infrared temperature and can be used to study the dependence of infrared temperature on various plant, soil, and environmental factors.

The spontaneous emission factor for lasers with gain induced waveguiding

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

Newstein, M.

1984-11-01

The expression for the spontaneous emission factor for lasers with gain induced waveguiding has a factor K, called by Petermann ''the astigmatism parameter.'' This factor has been invoked to explain spectral and dynamic characteristics of this class of lasers. We contend that the widely accepted form of the K factor is based on a derivation which is not appropriate for the typical laser situation where the spontaneous emission factor is much smaller than unity. An alternative derivation is presented which leads to a different form for the K factor. The new expression predicts much smaller values under conditions where themore » previous theory gave values large compared to unity. Petermann's form for the K factor is shown to be relevant to large gain linear amplifiers where the power is amplified spontaneous emission noise. The expression for the power output has Petermann's value of K as a factor. The difference in the two situations is that in the laser oscillator the typical atom of interest couples a small portion of its incoherent spontaneous emission into the dominant mode, whereas in the amplifier only the atoms at the input end are important as sources and their output is converted to a greater degree into the dominant mode through the propagation process. In this analysis the authors use a classical model of radiating point dipoles in a continuous medium characterized by a complex permittivity. Since uncritical use of this model will lead to infinite radiation resistance they address the problem of its self-consistency.« less

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...

Effect of ambient temperature on species lumping for total organic gases in gasoline exhaust emissions

NASA Astrophysics Data System (ADS)

Roy, Anirban; Choi, Yunsoo

2017-03-01

Volatile organic compound (VOCs) emissions from sources often need to be compressed or "lumped" into species classes for use in emissions inventories intended for air quality modeling. This needs to be done to ensure computational efficiency. The lumped profiles are usually reported for one value of ambient temperature. However, temperature-specific detailed profiles have been constructed in the recent past - the current study investigates how the lumping of species from those profiles into different atmospheric chemistry mechanisms is affected by temperature, considering three temperatures (-18 °C, -7 °C and 24 °C). The mechanisms considered differed on the assumptions used for lumping: CB05 (carbon bond type), SAPRC (ozone formation potential) and RACM2 (molecular surrogate and reactivity weighting). In this space, four sub-mechanisms for SAPRC were considered. Scaling factors were developed for each lumped model species and mechanism in terms of moles of lumped species per unit mass. Species which showed a direct one-to-one mapping (SAPRC/RACM2) reported scaling factors that were unchanged across mechanisms. However, CB05 showed different trends since one compound often is mapped onto multiple model species, out of which the paraffinic double bond (PAR) is predominant. Temperature-dependent parameterizations for emission factors pertaining to each lumped species class and mechanism were developed as part of the study. Here, the same kind of model species showed varying lumping parameters across the different mechanisms. These differences could be attributed to differing approaches in lumping. The scaling factors and temperature-dependent parameterizations could be used to update emissions inventories such as MOVES or SMOKE for use in chemical transport modeling.

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.

Energy consumption and CO{sub 2} emissions in Iran, 2025

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

Mirzaei, Maryam

Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO{sub 2} emissions. A system dynamic model was developed in this study to model the energy consumption and CO{sub 2} emission trends for Iran over 2000–2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO{sub 2} emissions in 2025 will reach 985more » million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO{sub 2} emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO{sub 2} emission outlines. - Highlights: • Creation of an energy consumption model using system dynamics. • The effect of different policies on energy consumption and emission reductions. • An ascending trend for the environmental costs caused by CO{sub 2} emissions is observed. • An urgent need for energy saving and emission reductions in Iran.« less

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

Temporal Considerations of Carbon Sequestration in LCA

Treesearch

James Salazar; Richard Bergman

2013-01-01

Accounting for carbon sequestration in LCA illustrates the limitations of a single global warming characterization factor. Typical cradle-to-grave LCA models all emissions from end-of-life processes and then characterizes these flows by IPCC GWP (100-yr) factors. A novel method estimates climate change impact by characterizing annual emissions with the IPCC GHG forcing...

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

NOx Emission Reduction and its Effects on Ozone during the 2008 Olympic Games

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

Yang, Qing; Wang, Yuhang; Zhao, Chun

2011-07-15

We applied a daily-assimilated inversion method to estimate NOx (NO+NO2) emissions for June-September 2007 and 2008 on the basis of the Aura Ozone Monitoring Instrument (OMI) observations of nitrogen dioxide (NO2) and model simulations using the Regional chEmistry and trAnsport Model (REAM). Over urban Beijing, rural Beijing, and the Huabei Plain, OMI column NO2 reductions are approximately 45%, 33%, and 14%, respectively, while the corresponding anthropogenic NOx emission reductions are only 28%, 24%, and 6%, during the full emission control period (July 20 – Sep 20, 2008). The emission reduction began in early July and was in full force bymore » July 20, corresponding to the scheduled implementation of emission controls over Beijing. The emissions did not appear to recover after the emission control period. Meteorological change from summer 2007 to 2008 is the main factor contributing to the column NO2 decreases not accounted for by the emission reduction. Model simulations suggest that the effect of emission reduction on ozone concentrations over Beijing is relatively minor using a standard VOC emission inventory in China. With an adjustment of the model emissions to reflect in situ observations of VOCs in Beijing, the model simulation suggests a larger effect of the emission reduction.« less

Global atmospheric emissions and transport of polycyclic aromatic hydrocarbons: Evaluation of modeling and transboundary pollution

NASA Astrophysics Data System (ADS)

Shen, Huizhong; Tao, Shu

2014-05-01

Global atmospheric emissions of 16 polycyclic aromatic hydrocarbons (PAHs) from 69 major sources were estimated for a period from 1960 to 2030. Regression models and a technology split method were used to estimated country and time specific emission factors, resulting in a new estimate of PAH emission factor variation among different countries and over time. PAH emissions in 2007 were spatially resolved to 0.1° × 0.1° grids based on a newly developed global high-resolution fuel combustion inventory (PKU-FUEL-2007). MOZART-4 (The Model for Ozone and Related Chemical Tracers, version 4) was applied to simulate the global tropospheric transport of Benzo(a)pyrene, one of the high molecular weight carcinogenic PAHs, at a horizontal resolution of 1.875° (longitude) × 1.8947° (latitude). The reaction with OH radical, gas/particle partitioning, wet deposition, dry deposition, and dynamic soil/ocean-air exchange of PAHs were considered. The simulation was validated by observations at both background and non-background sites, including Alert site in Canadian High Arctic, EMEP sites in Europe, and other 254 urban/rural sites reported from literatures. Key factors effecting long-range transport of BaP were addressed, and transboundary pollution was discussed.

Towards an understanding of the link between environmental emissions and human body burdens of PCBs using CoZMoMAN.

PubMed

Breivik, Knut; Czub, Gertje; McLachlan, Michael S; Wania, Frank

2010-01-01

Different factors affect how organic contaminants released into the environment over time distribute and accumulate, enter various food-chains, and potentially cause toxic effects in wildlife and humans. A sound chemical risk assessment thus requires the determination of the quantitative relationship between emissions and human exposure. This study aimed to assess the extent of the quantitative and mechanistic understanding of the link between environmental emissions and human body burdens for polychlorinated biphenyls (PCBs) in the western part of the Baltic Sea drainage basin and to identify any remaining knowledge gaps. An integrated, non-steady state model calculating human body burden from environmental emissions (CoZMoMAN) was created by linking the multi-compartment environmental fate model CoZMo-POP 2 with the human food chain bioaccumulation model ACC-HUMAN. CoZMoMAN predicted concentrations of seven PCB congeners in 11 key model compartments to typically within a factor of 2 to 4 of measured values, although larger discrepancies are noted for soils and humans. We conclude that whereas the most important processes which link emissions of PCBs to human body burdens are quite well understood in this region, some critical knowledge gaps related to the time trend of historical emissions remain to be addressed.

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

PubMed

Wiedinmyer, Christine; Friedli, Hans

2007-12-01

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

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.

Clearinghouse for Inventories and Emissions Factors

EPA Pesticide Factsheets

Emissions inventories, modeling, and monitoring are the basis for understanding, controlling and tracking stationary sources of air pollution. This technical site provides access to tools and data to support those efforts.

Particulate-phase mercury emissions from biomass burning ...

EPA Pesticide Factsheets

Mercury (Hg) emissions from biomass burning (BB) are an important source of atmospheric Hg and a major factor driving the interannual variation of Hg concentrations in the troposphere. The greatest fraction of Hg from BB is released in the form of elemental Hg (Hg0(g)). However, little is known about the fraction of Hg bound to particulate matter (HgP) released from BB, and the factors controlling this fraction are also uncertain. In light of the aims of the Minamata Convention to reduce intentional Hg use and emissions from anthropogenic activities, the relative importance of Hg emissions from BB will have an increasing impact on Hg deposition fluxes. Hg speciation is one of the most important factors determining the redistribution of Hg in the atmosphere and the geographical distribution of Hg deposition. Using the latest version of the Global Fire Emissions Database (GFEDv4.1s) and the global Hg chemistry transport model, ECHMERIT, the impact of Hg speciation in BB emissions, and the factors which influence speciation, on Hg deposition have been investigated for the year 2013. The role of other uncertainties related to physical and chemical atmospheric processes involving Hg and the influence of model parametrisations were also investigated, since their interactions with Hg speciation are complex. The comparison with atmospheric HgP concentrations observed at two remote sites, Amsterdam Island (AMD) and Manaus (MAN), in the Amazon showed a significant improve

An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

PubMed

Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

2017-04-15

This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

The Origin of the Prompt Emission for Short GRB 170817A: Photosphere Emission or Synchrotron Emission?

NASA Astrophysics Data System (ADS)

Meng, Yan-Zhi; Geng, Jin-Jun; Zhang, Bin-Bin; Wei, Jun-Jie; Xiao, Di; Liu, Liang-Duan; Gao, He; Wu, Xue-Feng; Liang, En-Wei; Huang, Yong-Feng; Dai, Zi-Gao; Zhang, Bing

2018-06-01

The first gravitational-wave event from the merger of a binary neutron star system (GW170817) was detected recently. The associated short gamma-ray burst (GRB 170817A) has a low isotropic luminosity (∼1047 erg s‑1) and a peak energy E p ∼ 145 keV during the initial main emission between ‑0.3 and 0.4 s. The origin of this short GRB is still under debate, but a plausible interpretation is that it is due to the off-axis emission from a structured jet. We consider two possibilities. First, since the best-fit spectral model for the main pulse of GRB 170817A is a cutoff power law with a hard low-energy photon index (α =-{0.62}-0.54+0.49), we consider an off-axis photosphere model. We develop a theory of photosphere emission in a structured jet and find that such a model can reproduce a low-energy photon index that is softer than a blackbody through enhancing high-latitude emission. The model can naturally account for the observed spectrum. The best-fit Lorentz factor along the line of sight is ∼20, which demands that there is a significant delay between the merger and jet launching. Alternatively, we consider that the emission is produced via synchrotron radiation in an optically thin region in an expanding jet with decreasing magnetic fields. This model does not require a delay of jet launching but demands a larger bulk Lorentz factor along the line of sight. We perform Markov Chain Monte Carlo fitting to the data within the framework of both models and obtain good fitting results in both cases.

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

NASA Astrophysics Data System (ADS)

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

2009-12-01

The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are responsible for 97% of mobile source emissions of CO, 22% of NOx, 95-97% of aromatics, 72-85% of carbonyls, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction. Nevertheless, the fuel-based inventory suggests that mobile source emissions of CO and NOx are overstated in the official inventory while emissions of VOCs may be understated. For NOx, the fuel-based inventory is lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory.

Quantifying Uncertainties in N2O Emission Due to N Fertilizer Application in Cultivated Areas

PubMed Central

Philibert, Aurore; Loyce, Chantal; Makowski, David

2012-01-01

Nitrous oxide (N2O) is a greenhouse gas with a global warming potential approximately 298 times greater than that of CO2. In 2006, the Intergovernmental Panel on Climate Change (IPCC) estimated N2O emission due to synthetic and organic nitrogen (N) fertilization at 1% of applied N. We investigated the uncertainty on this estimated value, by fitting 13 different models to a published dataset including 985 N2O measurements. These models were characterized by (i) the presence or absence of the explanatory variable “applied N”, (ii) the function relating N2O emission to applied N (exponential or linear function), (iii) fixed or random background (i.e. in the absence of N application) N2O emission and (iv) fixed or random applied N effect. We calculated ranges of uncertainty on N2O emissions from a subset of these models, and compared them with the uncertainty ranges currently used in the IPCC-Tier 1 method. The exponential models outperformed the linear models, and models including one or two random effects outperformed those including fixed effects only. The use of an exponential function rather than a linear function has an important practical consequence: the emission factor is not constant and increases as a function of applied N. Emission factors estimated using the exponential function were lower than 1% when the amount of N applied was below 160 kg N ha−1. Our uncertainty analysis shows that the uncertainty range currently used by the IPCC-Tier 1 method could be reduced. PMID:23226430

APPLICATION OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) TO CALCULATE VEHICLE GENERATED CONTRIBUTION PM 2.5 EMISSIONS

EPA Science Inventory

The United States Environmental Protection Agency's (EPA) National Exposure Research Laboratory is developing improved methods for modeling the source through the air pathway to human exposure in significant microenvironments of exposure. As a part of this project, we develope...

Strategies for enhanced deammonification performance and reduced nitrous oxide emissions.

PubMed

Leix, Carmen; Drewes, Jörg E; Ye, Liu; Koch, Konrad

2017-07-01

Deammonification's performance and associated nitrous oxide emissions (N 2 O) depend on operational conditions. While studies have investigated factors for high performances and low emissions separately, this study investigated optimizing deammonification performance while simultaneously reducing N 2 O emissions. Using a design of experiment (DoE) method, two models were developed for the prediction of the nitrogen removal rate and N 2 O emissions during single-stage deammonification considering three operational factors (i.e., pH value, feeding and aeration strategy). The emission factor varied between 0.7±0.5% and 4.1±1.2% at different DoE-conditions. The nitrogen removal rate was predicted to be maximized at settings of pH 7.46, intermittent feeding and aeration. Conversely, emissions were predicted to be minimized at the design edges at pH 7.80, single feeding, and continuous aeration. Results suggested a weak positive correlation between the nitrogen removal rate and N 2 O emissions, thus, a single optimizing operational set-point for maximized performance and minimized emissions did not exist. Copyright © 2017 Elsevier Ltd. All rights reserved.

Toxicological assessment of particulate emissions from the exhaust of old and new model heavy- and light-duty vehicles.

DOT National Transportation Integrated Search

2011-06-01

The primary objective of this project is to develop an improved understanding of the factors affecting the toxicology of particulate exhaust emissions. Diesel particulate matter is a known carcinogen, and particulate exhaust emissions from both light...

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.

Evaluating the Bulk Lorentz Factors of Outflow Material: Lessons Learned from the Extremely Energetic Outburst GRB 160625B

NASA Astrophysics Data System (ADS)

Wang, Yuan-Zhu; Wang, Hao; Zhang, Shuai; Liang, Yun-Feng; Jin, Zhi-Ping; He, Hao-Ning; Liao, Neng-Hui; Fan, Yi-Zhong; Wei, Da-Ming

2017-02-01

GRB 160625B is an extremely bright outburst with well-monitored afterglow emission. The geometry-corrected energy is high, up to ˜5.2 × 1052 erg or even ˜8 × 1052 erg, rendering it the most energetic GRB prompt emission recorded so far. We analyzed the time-resolved spectra of the prompt emission and found that in some intervals there were likely thermal-radiation components and the high energy emission was characterized by significant cutoff. The bulk Lorentz factors of the outflow material are estimated accordingly. We found out that the Lorentz factors derived in the thermal-radiation model are consistent with the luminosity-Lorentz factor correlation found in other bursts, as well as in GRB 090902B for the time-resolved thermal-radiation components, while the spectral cutoff model yields much lower Lorentz factors that are in tension with the constraints set by the electron pair Compton scattering process. We then suggest that these spectral cutoffs are more likely related to the particle acceleration process and that one should be careful in estimating the Lorentz factors if the spectrum cuts at a rather low energy (e.g., ˜tens of MeV). The nature of the central engine has also been discussed, and a stellar-mass black hole is favored.

Study of Opacity Effects on Emission Lines at EXTRAP T2R RFP

NASA Astrophysics Data System (ADS)

Stancalie, Viorica; Rachlew, Elisabeth

We have investigated the influence of opacity on hydrogen (H-α and Ly-β) and Li-like oxygen emission lines from the EXTRAP T2R reversed field pinch. We used the Atomic Data Analysis System (AzDAS) based on the escape factor approximation for radiative transfer to calculate metastable and excited population densities via a collisional-radiative model. Population escape factor, emergent escape factor and modified line profiles are plotted vs. optical depth. The simulated emission line ratios in the density/temperature plane are in good agreement with experimental data for electron density and temperature measurements.

Continuous odour measurement from fattening pig units

NASA Astrophysics Data System (ADS)

Romain, Anne-Claude; Nicolas, Jacques; Cobut, Pierre; Delva, Julien; Nicks, Baudouin; Philippe, François-Xavier

2013-10-01

A study in experimental slatted-system fattening pig units was conducted with the aim of estimating the odour emission factor (in ou s.pig-1), which can subsequently be used in dispersion models to assess the odour annoyance zone. Dynamic olfactometry measurements carried out at different development stages of pigs showed a logical trend of the mean assessed odour emission factor with the pig mass. However, the variation within the same mass class was much larger than variation between classes. Possible causes of such variation were identified as the evolution of ventilation rate during the day and the circadian rhythm of pig. To be able to monitor continuously the daily variation of the odour, an electronic nose was used with suitable regression model calibrated against olfactometric measurements. After appropriate validation check, the electronic nose proved to be convenient, as a complementary tool to dynamic olfactometry, to record the daily variation of the odour emission factor in the pig barn. It was demonstrated that, in the controlled conditions of the experimental pens, the daily variation of the odour emission rate could be mainly attributed to the sole influence of the circadian rhythm of pig. As a consequence, determining a representative odour emission factor in a real case cannot be based on a snapshot odour sampling.

UK emissions of the greenhouse gas nitrous oxide

PubMed Central

Skiba, U.; Jones, S. K.; Dragosits, U.; Drewer, J.; Fowler, D.; Rees, R. M.; Pappa, V. A.; Cardenas, L.; Chadwick, D.; Yamulki, S.; Manning, A. J.

2012-01-01

Signatories of the Kyoto Protocol are obliged to submit annual accounts of their anthropogenic greenhouse gas emissions, which include nitrous oxide (N2O). Emissions from the sectors industry (3.8 Gg), energy (14.4 Gg), agriculture (86.8 Gg), wastewater (4.4 Gg), land use, land-use change and forestry (2.1 Gg) can be calculated by multiplying activity data (i.e. amount of fertilizer applied, animal numbers) with simple emission factors (Tier 1 approach), which are generally applied across wide geographical regions. The agricultural sector is the largest anthropogenic source of N2O in many countries and responsible for 75 per cent of UK N2O emissions. Microbial N2O production in nitrogen-fertilized soils (27.6 Gg), nitrogen-enriched waters (24.2 Gg) and manure storage systems (6.4 Gg) dominate agricultural emission budgets. For the agricultural sector, the Tier 1 emission factor approach is too simplistic to reflect local variations in climate, ecosystems and management, and is unable to take into account some of the mitigation strategies applied. This paper reviews deviations of observed emissions from those calculated using the simple emission factor approach for all anthropogenic sectors, briefly discusses the need to adopt specific emission factors that reflect regional variability in climate, soil type and management, and explains how bottom-up emission inventories can be verified by top-down modelling. PMID:22451103

Emission factor for atmospheric ammonia from a typical municipal wastewater treatment plant in South China.

PubMed

Zhang, Chunlin; Geng, Xuesong; Wang, Hao; Zhou, Lei; Wang, Boguang

2017-01-01

Atmospheric ammonia (NH 3 ), a common alkaline gas found in air, plays a significant role in atmospheric chemistry, such as in the formation of secondary particles. However, large uncertainties remain in the estimation of ammonia emissions from nonagricultural sources, such as wastewater treatment plants (WWTPs). In this study, the ammonia emission factors from a large WWTP utilizing three typical biological treatment techniques to process wastewater in South China were calculated using the US EPA's WATER9 model with three years of raw sewage measurements and information about the facility. The individual emission factors calculated were 0.15 ± 0.03, 0.24 ± 0.05, 0.29 ± 0.06, and 0.25 ± 0.05 g NH 3  m -3 sewage for the adsorption-biodegradation activated sludge treatment process, the UNITANK process (an upgrade of the sequencing batch reactor activated sludge treatment process), and two slightly different anaerobic-anoxic-oxic treatment processes, respectively. The overall emission factor of the WWTP was 0.24 ± 0.06 g NH 3 m -3 sewage. The pH of the wastewater influent is likely an important factor affecting ammonia emissions, because higher emission factors existed at higher pH values. Based on the ammonia emission factor generated in this study, sewage treatment accounted for approximately 4% of the ammonia emissions for the urban area of South China's Pearl River Delta (PRD) in 2006, which is much less than the value of 34% estimated in previous studies. To reduce the large uncertainty in the estimation of ammonia emissions in China, more field measurements are required. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Particulate Matter Emissions for Fires in the Palmetto-Gallberry Fuel Type

Treesearch

Darold E. Ward

1983-01-01

Fire management specialists in the southeastern United States needing guides for predicting or assessing particulate matter emission factors, emission rates, and heat release rate can use the models presented in this paper for making these predictions as a function of flame length in the palmetto-gallberry fuel type.

Modeling the effect of heat fluxes on ammonia and nitrous oxide emissions from an anaerobic swine waste treatment lagoon using artificial neural network

USDA-ARS?s Scientific Manuscript database

Understanding factors that affect ammonia and nitrous emissions from anaerobic swine waste treatment lagoons or any animal waste receptacles is a necessary first step in deploying potential remediation options. In this study, we examined the various meteorological factors (i.e., air temperatures, s...

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Modeling indoor air pollution from cookstove emissions in developing countries using a Monte Carlo single-box model

NASA Astrophysics Data System (ADS)

Johnson, Michael; Lam, Nick; Brant, Simone; Gray, Christen; Pennise, David

2011-06-01

A simple Monte Carlo single-box model is presented as a first approach toward examining the relationship between emissions of pollutants from fuel/cookstove combinations and the resulting indoor air pollution (IAP) concentrations. The model combines stove emission rates with expected distributions of kitchen volumes and air exchange rates in the developing country context to produce a distribution of IAP concentration estimates. The resulting distribution can be used to predict the likelihood that IAP concentrations will meet air quality guidelines, including those recommended by the World Health Organization (WHO) for fine particulate matter (PM2.5) and carbon monoxide (CO). The model can also be used in reverse to estimate the probability that specific emission factors will result in meeting air quality guidelines. The modeled distributions of indoor PM2.5 concentration estimated that only 4% of homes using fuelwood in a rocket-style cookstove, even under idealized conditions, would meet the WHO Interim-1 annual PM2.5 guideline of 35 μg m-3. According to the model, the PM2.5 emissions that would be required for even 50% of homes to meet this guideline (0.055 g MJ-delivered-1) are lower than those for an advanced gasifier fan stove, while emissions levels similar to liquefied petroleum gas (0.018 g MJ-delivered-1) would be required for 90% of homes to meet the guideline. Although the predicted distribution of PM concentrations (median = 1320 μg m-3) from inputs for traditional wood stoves was within the range of reported values for India (108-3522 μg m-3), the model likely overestimates IAP concentrations. Direct comparison with simultaneously measured emissions rates and indoor concentrations of CO indicated the model overestimated IAP concentrations resulting from charcoal and kerosene emissions in Kenyan kitchens by 3 and 8 times respectively, although it underestimated the CO concentrations resulting from wood-burning cookstoves in India by approximately one half. The potential overestimation of IAP concentrations is thought to stem from the model's assumption that all stove emissions enter the room and are completely mixed. Future versions of the model may be improved by incorporating these factors into the model, as well as more comprehensive and representative data on stove emissions performance, daily cooking energy requirements, and kitchen characteristics.

Evaluations of in-use emission factors from off-road construction equipment

NASA Astrophysics Data System (ADS)

Cao, Tanfeng; Durbin, Thomas D.; Russell, Robert L.; Cocker, David R.; Scora, George; Maldonado, Hector; Johnson, Kent C.

2016-12-01

Gaseous and particle emissions from construction engines contribute an important fraction of the total air pollutants released into the atmosphere and are gaining increasing regulatory attention. Robust quantification of nitrogen oxides (NOx) and particulate matter (PM) emissions are necessary to inventory the contribution of construction equipment to atmospheric loadings. Theses emission inventories require emissions factors from construction equipment as a function of equipment type and modes of operation. While the development of portable emissions measurement systems (PEMS) has led to increased studies of construction equipment emissions, emissions data are still much more limited than for on-road vehicles. The goal of this research program was to obtain accurate in-use emissions data from a test fleet of newer construction equipment (model year 2002 or later) using a Code of Federal Requirements (CFR) compliant PEMS system. In-use emission measurements were made from twenty-seven pieces of construction equipment, which included four backhoes, six wheel loaders, four excavators, two scrapers (one with two engines), six bulldozers, and four graders. The engines ranged in model year from 2003 to 2012, in rated horsepower (hp) from 92 to 540 hp, and in hours of operation from 24 to 17,149 h. This is the largest study of off-road equipment emissions using 40 CFR part 1065 compliant PEMS equipment for all regulated gaseous and particulate emissions.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

NASA Astrophysics Data System (ADS)

Travis, K.; Jacob, D.; Fisher, J. A.; Kim, S.; Marais, E. A.; Zhu, L.; Yu, K.; Miller, C. E.; Yantosca, R.; Payer Sulprizio, M.; Thompson, A. M.; Wennberg, P. O.; Crounse, J.; St Clair, J. M.; Cohen, R. C.; Laughner, J.; Dibb, J. E.; Hall, S. R.; Ullmann, K.; Wolfe, G.; Pollack, I. B.; Peischl, J.; Neuman, J. A.; Zhou, X.

2016-12-01

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx = NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO­x from the US Environmental Protection Agency (EPA) is too high in the Southeast and nationally by a factor of 2. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Upper tropospheric NO2 from lightning makes a large contribution to the satellite observations that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This may be caused by excessively dry conditions in the model, representing another factor important in the simulation of surface ozone.

Comparison and evaluation of anthropogenic emissions of SO2 and NOx over China

NASA Astrophysics Data System (ADS)

Li, Meng; Klimont, Zbigniew; Zhang, Qiang; Martin, Randall V.; Zheng, Bo; Heyes, Chris; Cofala, Janusz; Zhang, Yuxuan; He, Kebin

2018-03-01

Bottom-up emission inventories provide primary understanding of sources of air pollution and essential input of chemical transport models. Focusing on SO2 and NOx, we conducted a comprehensive evaluation of two widely used anthropogenic emission inventories over China, ECLIPSE and MIX, to explore the potential sources of uncertainties and find clues to improve emission inventories. We first compared the activity rates and emission factors used in two inventories and investigated the reasons of differences and the impacts on emission estimates. We found that SO2 emission estimates are consistent between two inventories (with 1 % differences), while NOx emissions in ECLIPSE's estimates are 16 % lower than those of MIX. The FGD (flue-gas desulfurization) device penetration rate and removal efficiency, LNB (low-NOx burner) application rate and abatement efficiency in power plants, emission factors of industrial boilers and various vehicle types, and vehicle fleet need further verification. Diesel consumptions are quite uncertain in current inventories. Discrepancies at the sectorial and provincial levels are much higher than those of the national total. We then examined the impacts of different inventories on model performance by using the nested GEOS-Chem model. We finally derived top-down emissions by using the retrieved columns from the Ozone Monitoring Instrument (OMI) compared with the bottom-up estimates. High correlations were observed for SO2 between model results and OMI columns. For NOx, negative biases in bottom-up gridded emission inventories (-21 % for MIX, -39 % for ECLIPSE) were found compared to the satellite-based emissions. The emission trends from 2005 to 2010 estimated by two inventories were both consistent with satellite observations. The inventories appear to be fit for evaluation of the policies at an aggregated or national level; more work is needed in specific areas in order to improve the accuracy and robustness of outcomes at finer spatial and also technological levels. To our knowledge, this is the first work in which source comparisons detailed to technology-level parameters are made along with the remote sensing retrievals and chemical transport modeling. Through the comparison between bottom-up emission inventories and evaluation with top-down information, we identified potential directions for further improvement in inventory development.

Evaluating EDGARv4.tox2 speciated mercury emissions ex-post scenarios and their impacts on modelled global and regional wet deposition patterns

NASA Astrophysics Data System (ADS)

Muntean, Marilena; Janssens-Maenhout, Greet; Song, Shaojie; Giang, Amanda; Selin, Noelle E.; Zhong, Hui; Zhao, Yu; Olivier, Jos G. J.; Guizzardi, Diego; Crippa, Monica; Schaaf, Edwin; Dentener, Frank

2018-07-01

Speciated mercury gridded emissions inventories together with chemical transport models and concentration measurements are essential when investigating both the effectiveness of mitigation measures and the mercury cycle in the environment. Since different mercury species have contrasting behaviour in the atmosphere, their proportion in anthropogenic emissions could determine the spatial impacts. In this study, the time series from 1970 to 2012 of the EDGARv4.tox2 global mercury emissions inventory are described; the total global mercury emission in 2010 is 1772 tonnes. Global grid-maps with geospatial distribution of mercury emissions at a 0.1° × 0.1° resolution are provided for each year. Compared to the previous tox1 version, tox2 provides updates for more recent years and improved emissions in particular for agricultural waste burning, power generation and artisanal and small-scale gold mining (ASGM) sectors. We have also developed three retrospective emissions scenarios based on different hypotheses related to the proportion of mercury species in the total mercury emissions for each activity sector; improvements in emissions speciation are seen when using information primarily from field measurements. We evaluated them using the GEOS-Chem 3-D mercury model in order to explore the influence of speciation shifts, to reactive mercury forms in particular, on regional wet deposition patterns. The reference scenario S1 (EDGARv4.tox2_S1) uses speciation factors from the Arctic Monitoring and Assessment Programme (AMAP); scenario S2 ("EPA_power") uses factors from EPA's Information Collection Request (ICR); and scenario S3 ("Asia_filedM") factors from recent scientific publications. In the reference scenario, the sum of reactive mercury emissions (Hg-P and Hg2+) accounted for 25.3% of the total global emissions; the regions/countries that have shares of reactive mercury emissions higher than 6% in total global reactive mercury are China+ (30.9%), India+ (12.5%) and the United States (9.9%). In 2010, the variations of reactive mercury emissions amongst the different scenarios are in the range of -19.3 t/yr (China+) to 4.4 t/yr (OECD_Europe). However, at the sector level, the variation could be different, e.g., for the iron and steel industry in China reaches 15.4 t/yr. Model evaluation at the global level shows a variation of approximately ±10% in wet deposition for the three emissions scenarios. An evaluation of the impact of mercury speciation within nested grid sensitivity simulations is performed for the United States and modelled wet deposition fluxes are compared with measurements. These studies show that using the S2 and S3 emissions of reactive mercury, can improve wet deposition estimates near sources.

Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

NASA Astrophysics Data System (ADS)

Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

2017-12-01

The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability of different reactive N emissions (NO, HONO, N2O) with soil temperature, moisture and N inputs.

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.

Contact Us About Clearinghouse for Inventories and Emissions Factors

EPA Pesticide Factsheets

Emissions inventories, modeling, and monitoring are the basis for understanding, controlling and tracking stationary sources of air pollution. This technical site provides access to tools and data to support those efforts.

Light-curve modelling constraints on the obliquities and aspect angles of the young Fermi pulsars

NASA Astrophysics Data System (ADS)

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; Johnson, T. J.; Caraveo, P. A.; Kerr, M.; Gonthier, P. L.

2015-03-01

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed γ-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity α and of the line of sight angle ζ, yielding estimates of the radiation beaming factor and radiated luminosity. Using different γ-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit γ-ray light curves for 76 young or middle-aged pulsars and we jointly fit their γ-ray plus radio light curves when possible. We find that a joint radio plus γ-ray fit strategy is important to obtain (α,ζ) estimates that can explain simultaneously detectable radio and γ-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (α,ζ) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the γ-ray only fit leads to underestimated α or ζ when the solution is found to the left or to the right of the main α-ζ plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favoured in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived γ-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between γ-ray luminosity and spin-down power is consistent with a square root dependence. The γ-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction. Appendices are available in electronic form at http://www.aanda.org

Light-curve modelling constraints on the obliquities and aspect angles of the young Fermi pulsars

DOE PAGES

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; ...

2015-02-10

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed γ-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity α and of the line of sight angle ζ, yielding estimates of the radiation beaming factor and radiated luminosity. Using different γ-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit γ-ray light curves formore » 76 young or middle-aged pulsars and we jointly fit their γ-ray plus radio light curves when possible. We find that a joint radio plus γ-ray fit strategy is important to obtain (α,ζ) estimates that can explain simultaneously detectable radio and γ-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (α,ζ) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the γ-ray only fit leads to underestimated α or ζ when the solution is found to the left or to the right of the main α-ζ plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favoured in explaining the observations. We find no apparent evolution of α on a time scale of 106 years. For all emission geometries our derived γ-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between γ-ray luminosity and spin-down power is consistent with a square root dependence. The γ-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. Furthermore, the relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.« less

Light-Curve Modelling Constraints on the Obliquities and Aspect Angles of the Young Fermi Pulsars

NASA Technical Reports Server (NTRS)

Pierbattista, M.; Harding, A. K.; Grenier, I. A.; Johnson, T. J.; Caraveo, P. A.; Kerr, M.; Gonthier, P. L.

2015-01-01

In more than four years of observation the Large Area Telescope on board the Fermi satellite has identified pulsed gamma-ray emission from more than 80 young or middle-aged pulsars, in most cases providing light curves with high statistics. Fitting the observed profiles with geometrical models can provide estimates of the magnetic obliquity alpha and of the line of sight angle zeta, yielding estimates of the radiation beaming factor and radiated luminosity. Using different gamma-ray emission geometries (Polar Cap, Slot Gap, Outer Gap, One Pole Caustic) and core plus cone geometries for the radio emission, we fit gamma-ray light curves for 76 young or middle-aged pulsars and we jointly fit their gamma-ray plus radio light curves when possible. We find that a joint radio plus gamma-ray fit strategy is important to obtain (alpha, zeta) estimates that can explain simultaneously detectable radio and gamma-ray emission: when the radio emission is available, the inclusion of the radio light curve in the fit leads to important changes in the (alpha, gamma) solutions. The most pronounced changes are observed for Outer Gap and One Pole Caustic models for which the gamma-ray only fit leads to underestimated alpha or zeta when the solution is found to the left or to the right of the main alpha-zeta plane diagonal respectively. The intermediate-to-high altitude magnetosphere models, Slot Gap, Outer Gap, and One pole Caustic, are favored in explaining the observations. We find no apparent evolution of a on a time scale of 106 years. For all emission geometries our derived gamma-ray beaming factors are generally less than one and do not significantly evolve with the spin-down power. A more pronounced beaming factor vs. spin-down power correlation is observed for Slot Gap model and radio-quiet pulsars and for the Outer Gap model and radio-loud pulsars. The beaming factor distributions exhibit a large dispersion that is less pronounced for the Slot Gap case and that decreases from radio-quiet to radio-loud solutions. For all models, the correlation between gamma-ray luminosity and spin-down power is consistent with a square root dependence. The gamma-ray luminosities obtained by using the beaming factors estimated in the framework of each model do not exceed the spin-down power. This suggests that assuming a beaming factor of one for all objects, as done in other studies, likely overestimates the real values. The data show a relation between the pulsar spectral characteristics and the width of the accelerator gap. The relation obtained in the case of the Slot Gap model is consistent with the theoretical prediction.

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

NASA Technical Reports Server (NTRS)

Zhang, Feng; Wang, Jun; Ichoku, Charles; Hyer, Edward J.; Yang, Zhifeng; Ge, Cui; Su, Shenjian; Zhang, Xiaoyang; Kondragunta, Shobha; Kaiser, Johannes W.;

Population and Activity of On-road Vehicles in MOVES2014 ...

EPA Pesticide Factsheets

This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, lawnmowers, etc.) mobile sources. The national default activity information in MOVES2014 provides a reasonable basis for estimating national emissions. However, the uncertainties and variability in the default data contribute to the uncertainty in the resulting emission estimates. Properly characterizing emissions from the on-road vehicle subset requires a detailed understanding of the cars and trucks that make up the vehicle fleet and their patterns of operation. The MOVES model calculates emission inventories by multiplying emission rates by the appropriate emission-related activity, applying correction (adjustment) factors as needed to simulate specific situations, and then adding up the emissions from all sources (populations) and regions. This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, law

Variability and uncertainty in life cycle assessment models for greenhouse gas emissions from Canadian oil sands production.

PubMed

Brandt, Adam R

2012-01-17

Because of interest in greenhouse gas (GHG) emissions from transportation fuels production, a number of recent life cycle assessment (LCA) studies have calculated GHG emissions from oil sands extraction, upgrading, and refining pathways. The results from these studies vary considerably. This paper reviews factors affecting energy consumption and GHG emissions from oil sands extraction. It then uses publicly available data to analyze the assumptions made in the LCA models to better understand the causes of variability in emissions estimates. It is found that the variation in oil sands GHG estimates is due to a variety of causes. In approximate order of importance, these are scope of modeling and choice of projects analyzed (e.g., specific projects vs industry averages); differences in assumed energy intensities of extraction and upgrading; differences in the fuel mix assumptions; treatment of secondary noncombustion emissions sources, such as venting, flaring, and fugitive emissions; and treatment of ecological emissions sources, such as land-use change-associated emissions. The GHGenius model is recommended as the LCA model that is most congruent with reported industry average data. GHGenius also has the most comprehensive system boundaries. Last, remaining uncertainties and future research needs are discussed.

Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region

PubMed Central

Oikawa, P. Y.; Ge, C.; Wang, J.; Eberwein, J. R.; Liang, L. L.; Allsman, L. A.; Grantz, D. A.; Jenerette, G. D.

2015-01-01

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality. PMID:26556236

Aviation NOx-induced CH4 effect: Fixed mixing ratio boundary conditions versus flux boundary conditions

NASA Astrophysics Data System (ADS)

Khodayari, Arezoo; Olsen, Seth C.; Wuebbles, Donald J.; Phoenix, Daniel B.

2015-07-01

Atmospheric chemistry-climate models are often used to calculate the effect of aviation NOx emissions on atmospheric ozone (O3) and methane (CH4). Due to the long (∼10 yr) atmospheric lifetime of methane, model simulations must be run for long time periods, typically for more than 40 simulation years, to reach steady-state if using CH4 emission fluxes. Because of the computational expense of such long runs, studies have traditionally used specified CH4 mixing ratio lower boundary conditions (BCs) and then applied a simple parameterization based on the change in CH4 lifetime between the control and NOx-perturbed simulations to estimate the change in CH4 concentration induced by NOx emissions. In this parameterization a feedback factor (typically a value of 1.4) is used to account for the feedback of CH4 concentrations on its lifetime. Modeling studies comparing simulations using CH4 surface fluxes and fixed mixing ratio BCs are used to examine the validity of this parameterization. The latest version of the Community Earth System Model (CESM), with the CAM5 atmospheric model, was used for this study. Aviation NOx emissions for 2006 were obtained from the AEDT (Aviation Environmental Design Tool) global commercial aircraft emissions. Results show a 31.4 ppb change in CH4 concentration when estimated using the parameterization and a 1.4 feedback factor, and a 28.9 ppb change when the concentration was directly calculated in the CH4 flux simulations. The model calculated value for CH4 feedback on its own lifetime agrees well with the 1.4 feedback factor. Systematic comparisons between the separate runs indicated that the parameterization technique overestimates the CH4 concentration by 8.6%. Therefore, it is concluded that the estimation technique is good to within ∼10% and decreases the computational requirements in our simulations by nearly a factor of 8.

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

GHG emission factors developed for the recycling and composting of municipal waste in South African municipalities

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

Friedrich, Elena, E-mail: Friedriche@ukzn.ac.za; Trois, Cristina

2013-11-15

Highlights: • GHG emission factors for local recycling of municipal waste are presented. • GHG emission factors for two composting technologies for garden waste are included. • Local GHG emission factors were compared to international ones and discussed. • Uncertainties and limitations are presented and areas for new research highlighted. - Abstract: GHG (greenhouse gas) emission factors for waste management are increasingly used, but such factors are very scarce for developing countries. This paper shows how such factors have been developed for the recycling of glass, metals (Al and Fe), plastics and paper from municipal solid waste, as well asmore » for the composting of garden refuse in South Africa. The emission factors developed for the different recyclables in the country show savings varying from −290 kg CO{sub 2} e (glass) to −19 111 kg CO{sub 2} e (metals – Al) per tonne of recyclable. They also show that there is variability, with energy intensive materials like metals having higher GHG savings in South Africa as compared to other countries. This underlines the interrelation of the waste management system of a country/region with other systems, in particular with energy generation, which in South Africa, is heavily reliant on coal. This study also shows that composting of garden waste is a net GHG emitter, releasing 172 and 186 kg CO{sub 2} e per tonne of wet garden waste for aerated dome composting and turned windrow composting, respectively. The paper concludes that these emission factors are facilitating GHG emissions modelling for waste management in South Africa and enabling local municipalities to identify best practice in this regard.« less

Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables.

PubMed

Chen, Wenhui; Lei, Yalin

2017-02-01

Identifying the impact path on factors of CO 2 emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO 2 emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO 2 emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO 2 emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO 2 emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO 2 emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO 2 emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO 2 emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.

Emissions from prescribed burning of agricultural fields in the Pacific Northwest

NASA Astrophysics Data System (ADS)

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

2017-10-01

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, and emission inventories. Batch measurements of PM2.5, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated dibenzodioxins/dibenzofurans (PCDDs/PCDFs), and continuous measurements of black carbon (BC), particle mass by size, CO, CO2, CH4, and aerosol characteristics were taken at ground level, on an aerostat-lofted instrument package, and from an airplane. Biomass samples gathered from the field were burned in a laboratory combustion facility for comparison with these ground and aerial field measurements. Emission factors for PM2.5, organic carbon (OC), CH4, and CO measured in the field study platforms were typically higher than those measured in the laboratory combustion facility. Field data for Kentucky bluegrass suggest that biomass residue loading is directly proportional to the PM2.5 emission factor; no such relationship was found with the limited wheat data. CO2 and BC emissions were higher in laboratory burn tests than in the field, reflecting greater carbon oxidation and flaming combustion conditions. These distinctions between field and laboratory results can be explained by measurements of the modified combustion efficiency (MCE). Higher MCEs were recorded in the laboratory burns than from the airplane platform. These MCE/emission factor trends are supported by 1-2 min grab samples from the ground and aerostat platforms. Emission factors measured here are similar to other studies measuring comparable fuels, pollutants, and combustion conditions. The size distribution of refractory BC (rBC) was single modal with a log-normal shape, which was consistent among fuel types when normalized by total rBC mass. The field and laboratory measurements of the Angstrom exponent (α) and single scattering albedo (ω) exhibit a strong decreasing trend with increasing MCEs in the range of 0.9-0.99. Field measurements of α and ω were consistently higher than laboratory burns, which is likely due to less complete combustion. When VOC emissions are compared with MCE, the results are consistent for both fuel types: emission factors increase as MCE decreases.

Methods for Analysis of Urban Energy Systems: A New York City Case Study

NASA Astrophysics Data System (ADS)

Howard, Bianca

This dissertation describes methods developed for analysis of the New York City energy system. The analysis specifically aims to consider the built environment and its' impacts on greenhouse gas (GHG) emissions. Several contributions to the urban energy systems literature were made. First, estimates of annual energy intensities of the New York building stock were derived using a statistical analysis that leveraged energy consumption and tax assessor data collected by the Office of the Mayor. These estimates provided the basis for an assessment of the spatial distribution of building energy consumption. The energy consumption estimates were then leveraged to estimate the potential for combined heat and power (CHP) systems in New York City at both the building and microgrid scales. In aggregate, given the 2009 non-baseload GHG emissions factors for electricity production, these systems could reduce citywide GHG emissions by 10%. The operational characteristics of CHP systems were explored further considering different prime movers, climates, and GHG emissions factors. A combination of mixed integer linear programing and controlled random search algorithms were the methods used to determine the optimal capacity and operating strategies for the CHP systems under the various scenarios. Lastly a multi-regional unit commitment model of electricity and GHG emissions production for New York State was developed using data collected from several publicly available sources. The model was used to estimate average and marginal GHG emissions factors for New York State and New York City. The analysis found that marginal GHG emissions factors could reduce by 30% to 370 g CO2e/kWh in the next 10 years.

Direct Nitrous Oxide Emissions From Tropical And Sub-Tropical Agricultural Systems - A Review And Modelling Of Emission Factors.

PubMed

Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B; Brentrup, Frank; Stirling, Clare; Hillier, Jon

2017-03-10

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N 2 O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N 2 O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N 2 O-N emissions to estimate tropic-specific annual N 2 O emission factors (N 2 O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N 2 O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N 2 O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central &South America. Our annual N 2 O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N 2 O-EFs as a function of applied N. Our findings highlight that in reporting annual N 2 O emissions and estimating N 2 O-EFs, particular attention should be paid in modelling the effect of study length on response of N 2 O.

Direct Nitrous Oxide Emissions From Tropical And Sub-Tropical Agricultural Systems - A Review And Modelling Of Emission Factors

PubMed Central

Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B.; Brentrup, Frank; Stirling, Clare; Hillier, Jon

2017-01-01

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O. PMID:28281637

Direct Nitrous Oxide Emissions From Tropical And Sub-Tropical Agricultural Systems - A Review And Modelling Of Emission Factors

NASA Astrophysics Data System (ADS)

Albanito, Fabrizio; Lebender, Ulrike; Cornulier, Thomas; Sapkota, Tek B.; Brentrup, Frank; Stirling, Clare; Hillier, Jon

2017-03-01

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O.

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

Zhu Qin, E-mail: zhuqin@fudan.edu.cn; Peng Xizhe, E-mail: xzpeng@fudan.edu.cn

This study examines the impacts of population size, population structure, and consumption level on carbon emissions in China from 1978 to 2008. To this end, we expanded the stochastic impacts by regression on population, affluence, and technology model and used the ridge regression method, which overcomes the negative influences of multicollinearity among independent variables under acceptable bias. Results reveal that changes in consumption level and population structure were the major impact factors, not changes in population size. Consumption level and carbon emissions were highly correlated. In terms of population structure, urbanization, population age, and household size had distinct effects onmore » carbon emissions. Urbanization increased carbon emissions, while the effect of age acted primarily through the expansion of the labor force and consequent overall economic growth. Shrinking household size increased residential consumption, resulting in higher carbon emissions. Households, rather than individuals, are a more reasonable explanation for the demographic impact on carbon emissions. Potential social policies for low carbon development are also discussed. - Highlights: Black-Right-Pointing-Pointer We examine the impacts of population change on carbon emissions in China. Black-Right-Pointing-Pointer We expand the STIRPAT model by containing population structure factors in the model. Black-Right-Pointing-Pointer The population structure includes age structure, urbanization level, and household size. Black-Right-Pointing-Pointer The ridge regression method is used to estimate the model with multicollinearity. Black-Right-Pointing-Pointer The population structure plays a more important role compared with the population size.« less

Application of a combined measurement and modeling method to quantify windblown dust emissions from the exposed playa at Mono Lake, California.

PubMed

Ono, Duane; Kiddoo, Phill; Howard, Christopher; Davis, Guy; Richmond, Kenneth

2011-10-01

Particulate matter < or =10 microm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 microg/m3 (slope = 0.89, R2 = 0.77).

Air pollution response to changing weather and power plant emissions in the eastern United States

NASA Astrophysics Data System (ADS)

Bloomer, Bryan Jaye

Air pollution in the eastern United States causes human sickness and death as well as damage to crops and materials. NOX emission reduction is observed to improve air quality. Effectively reducing pollution in the future requires understanding the connections between smog, precursor emissions, weather, and climate change. Numerical models predict global warming will exacerbate smog over the next 50 years. My analysis of 21 years of CASTNET observations quantifies a climate change penalty. I calculate, for data collected prior to 2002, a climate penalty factor of ˜3.3 ppb O3/°C across the power plant dominated receptor regions in the rural, eastern U.S. Recent reductions in NOX emissions decreased the climate penalty factor to ˜2.2 ppb O3/°C. Prior to 1995, power plant emissions of CO2, SO2, and NOX were estimated with fuel sampling and analysis methods. Currently, emissions are measured with continuous monitoring equipment (CEMS) installed directly in stacks. My comparison of the two methods show CO 2 and SO2 emissions are ˜5% lower when inferred from fuel sampling; greater differences are found for NOX emissions. CEMS are the method of choice for emission inventories and commodity trading and should be the standard against which other methods are evaluated for global greenhouse gas trading policies. I used CEMS data and applied chemistry transport modeling to evaluate improvements in air quality observed by aircraft during the North American electrical blackout of 2003. An air quality model produced substantial reductions in O3, but not as much as observed. The study highlights weaknesses in the model as commonly used for evaluating a single day event and suggests areas for further investigation. A new analysis and visualization method quantifies local-daily to hemispheric-seasonal scale relationships between weather and air pollution, confirming improved air quality despite increasing temperatures across the eastern U.S. Climate penalty factors indicate amplified smog formation in areas of the world with rising temperatures and increasing emissions. Tools developed in this dissertation provide data for model evaluation and methods for establishing air quality standards with an adequate margin of safety for cleaning the air and protecting the public's health in a world with changing climate.

Maximum warming occurs about one decade after a carbon dioxide emission

NASA Astrophysics Data System (ADS)

Ricke, Katharine L.; Caldeira, Ken

2014-12-01

It is known that carbon dioxide emissions cause the Earth to warm, but no previous study has focused on examining how long it takes to reach maximum warming following a particular CO2 emission. Using conjoined results of carbon-cycle and physical-climate model intercomparison projects (Taylor et al 2012, Joos et al 2013), we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6-30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. If uncertainty in any one factor is reduced to zero without reducing uncertainty in the other factors, the majority of overall uncertainty remains. Thus, narrowing uncertainty in century-scale warming depends on narrowing uncertainty in all contributing factors. Our results indicate that benefit from avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While such avoidance could be expected to benefit future generations, there is potential for emissions avoidance to provide substantial benefit to current generations.

Characterization of Gas-Phase Organics Using Proton Transfer Reaction Time-of-Flight Mass Spectrometry: Residential Coal Combustion.

PubMed

Klein, Felix; Pieber, Simone M; Ni, Haiyan; Stefenelli, Giulia; Bertrand, Amelie; Kilic, Dogushan; Pospisilova, Veronika; Temime-Roussel, Brice; Marchand, Nicolas; El Haddad, Imad; Slowik, Jay G; Baltensperger, Urs; Cao, Junji; Huang, Ru-Jin; Prévôt, André S H

2018-03-06

Residential coal combustion is a significant contributor to particulate urban air pollution in Chinese mega cities and some regions in Europe. While the particulate emission factors and the chemical characteristics of the organic and inorganic aerosol from coal combustion have been extensively studied, the chemical composition and nonmethane organic gas (NMOG) emission factors from residential coal combustion are mostly unknown. We conducted 23 individual burns in a traditional Chinese stove used for heating and cooking using five different coals with Chinese origins, characterizing the NMOG emissions using a proton transfer reaction time-of-flight mass spectrometer. The measured emission factors range from 1.5 to 14.1 g/kg coal for bituminous coals and are below 0.1 g/kg coal for anthracite coals. The emission factors from the bituminous coals are mostly influenced by the time until the coal is fully ignited. The emissions from the bituminous coals are dominated by aromatic and oxygenated aromatic compounds with a significant contribution of hydrocarbons. The results of this study can help to improve urban air pollution modeling in China and Eastern Europe and can be used to constrain a coal burning factor in ambient gas phase positive matrix factorization studies.

Microscale traffic simulation and emission estimation in a heavily trafficked roundabout in Madrid (Spain).

PubMed

Quaassdorff, Christina; Borge, Rafael; Pérez, Javier; Lumbreras, Julio; de la Paz, David; de Andrés, Juan Manuel

2016-10-01

This paper presents the evaluation of emissions from vehicle operations in a domain of 300m×300m covering a complex urban roundabout with high traffic density in Madrid. Micro-level simulation was successfully applied to estimate the emissions on a scale of meters. Two programs were used: i) VISSIM to simulate the traffic on the square and to compute velocity-time profiles; and ii) VERSIT+micro through ENVIVER that uses VISSIM outputs to compute the related emissions at vehicle level. Data collection was achieved by a measurement campaign obtaining empirical data of vehicle flows and traffic intensities. Twelve simulations of different traffic situations (scenarios) were conducted, representing different hours from several days in a week and the corresponding NOX and PM10 emissions were estimated. The results show a general reduction on average speeds for higher intensities due to braking-acceleration patterns that contribute to increase the average emission factor and, therefore, the total emissions in the domain, especially on weekdays. The emissions are clearly related to traffic volume, although maximum emission scenario does not correspond to the highest traffic intensity due to congestion and variations in fleet composition throughout the day. These results evidence the potential that local measures aimed at alleviating congestion may have in urban areas to reduce emissions. In general, scenario-averaged emission factors estimated with the VISSIM-VERSIT+micro modelling system fitted well those from the average-speed model COPERT, used as a preliminary validation of the results. The largest deviations between these two models occur in those scenarios with more congestion. The design and resolution of the microscale modelling system allow to reflect the impact of actual traffic conditions on driving patterns and related emissions, making it useful for the design of mitigation measures for specific traffic hot-spots. Copyright © 2016 Elsevier B.V. All rights reserved.

A flare event of the long-period RS Canum Venaticorum system IM Pegasi

NASA Technical Reports Server (NTRS)

Buzasi, Derek L.; Ramsey, Lawrence W.; Huenemoerder, David P.

1987-01-01

The characteristics of a flare event detected on the long-period RS CVn system IM Pegasi are reported. The low-resolution spectrum show enhancements of up to a factor of five in some emission lines. All of the ultraviolet emission lines normally visible are enhanced significantly more than the normal 30 rotational modulation. Emission fluxes of both the quiescent and flare event are used to construct models of the density and temperature variation with height. These models reveal a downward shift of the transition region during the flare. Scaled models of the quiet and flaring solar outer atmosphere are used to estimate the filling factor of the flare event at about 30 percent of the stellar surface. The pattern of line enhancements in the flare is the same as a previous event in Lambda Andromeda observed previously.

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

NASA Astrophysics Data System (ADS)

Storm, Emma; Weniger, Christoph; Calore, Francesca

2017-08-01

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (gtrsim 105) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |l|<90o and |b|<20o, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

A two-step combination of top-down and bottom-up fire emission estimates at regional and global scales: strengths and main uncertainties

NASA Astrophysics Data System (ADS)

Sofiev, Mikhail; Soares, Joana; Kouznetsov, Rostislav; Vira, Julius; Prank, Marje

2016-04-01

Top-down emission estimation via inverse dispersion modelling is used for various problems, where bottom-up approaches are difficult or highly uncertain. One of such areas is the estimation of emission from wild-land fires. In combination with dispersion modelling, satellite and/or in-situ observations can, in principle, be used to efficiently constrain the emission values. This is the main strength of the approach: the a-priori values of the emission factors (based on laboratory studies) are refined for real-life situations using the inverse-modelling technique. However, the approach also has major uncertainties, which are illustrated here with a few examples of the Integrated System for wild-land Fires (IS4FIRES). IS4FIRES generates the smoke emission and injection profile from MODIS and SEVIRI active-fire radiative energy observations. The emission calculation includes two steps: (i) initial top-down calibration of emission factors via inverse dispersion problem solution that is made once using training dataset from the past, (ii) application of the obtained emission coefficients to individual-fire radiative energy observations, thus leading to bottom-up emission compilation. For such a procedure, the major classes of uncertainties include: (i) imperfect information on fires, (ii) simplifications in the fire description, (iii) inaccuracies in the smoke observations and modelling, (iv) inaccuracies of the inverse problem solution. Using examples of the fire seasons 2010 in Russia, 2012 in Eurasia, 2007 in Australia, etc, it is pointed out that the top-down system calibration performed for a limited number of comparatively moderate cases (often the best-observed ones) may lead to errors in application to extreme events. For instance, the total emission of 2010 Russian fires is likely to be over-estimated by up to 50% if the calibration is based on the season 2006 and fire description is simplified. Longer calibration period and more sophisticated parameterization (including the smoke injection model and distinguishing all relevant vegetation types) can improve the predictions. The other significant parameter, so far weakly addressed in fire emission inventories, is the size spectrum of the emitted aerosols. Direct size-resolving measurements showed, for instance, that smoke from smouldering fires has smaller particles as compares with smoke from flaming fires. Due to dependence of the smoke optical thickness on the size distribution, such variability can lead to significant changes in the top-down calibration step. Experiments with IS4FIRES-SILAM system manifested up to a factor of two difference in AOD, depending on the assumption on particle spectrum.

Verifying the UK agricultural N2O emission inventory with tall tower measurements

NASA Astrophysics Data System (ADS)

Carnell, E. J.; Meneguz, E.; Skiba, U. M.; Misselbrook, T. H.; Cardenas, L. M.; Arnold, T.; Manning, A.; Dragosits, U.

2016-12-01

Nitrous oxide (N2O) is a key greenhouse gas (GHG), with a global warming potential 300 times greater than that of CO2. N2O is emitted from a variety of sources, predominantly from agriculture. Annual UK emission estimates are reported, to comply with government commitments under the United Nations Framework Convention on Climate Change (UNFCCC). The UK N2O inventory follows internationally agreed protocols and emission estimates are derived by applying emission factors to estimates of (anthropogenic) emission sources. This approach is useful for comparing anthropogenic emissions from different countries, but does not capture regional differences and inter-annual variability associated with environmental factors (such as climate and soils) and agricultural management. In recent years, the UK inventory approach has been refined to include regional information into its emissions estimates, in an attempt to reduce uncertainty. This study attempts to assess the difference between current published inventory methodology (default IPCC methodology) and an alternative approach, which incorporates the latest thinking, using data from recent work. For 2013, emission estimates made using the alternative approach were 30 % lower than those made using default IPCC methodology, due to the use of lower emission factors suggested by recent projects (Defra projects: AC0116, AC0213 and MinNO). The 2013 emissions estimates were disaggregated on a monthly basis using agricultural management (e.g. sowing dates), climate data and soil properties. The temporally disaggregated emission maps were used as input to the Met Office atmospheric dispersion model NAME, for comparison with measured N2O concentrations, at three observation stations (Tacolneston, E. England; Ridge Hill, W. England; Mace Head, W. Ireland) in the UK DECC network (Deriving Emissions linked to Climate Change). The Mace Head site, situated on the west coast of Ireland, was used to establish baseline concentrations. The trends in the modelled data were found to correspond with the observational data trends, with concentration peaks coinciding with periods of land spreading of manures and fertiliser application. The model run using the default IPCC methodology was found to correspond with the observed data more closely than the alternative approach.

Verifying the UK N_{2}O emission inventory with tall tower measurements

NASA Astrophysics Data System (ADS)

Carnell, Ed; Meneguz, Elena; Skiba, Ute; Misselbrook, Tom; Cardenas, Laura; Arnold, Tim; Manning, Alistair; Dragosits, Ulli

2016-04-01

Nitrous oxide (N2O) is a key greenhouse gas (GHG), with a global warming potential ˜300 times greater than that of CO2. N2O is emitted from a variety of sources, predominantly from agriculture. Annual UK emission estimates are reported, to comply with government commitments under the United Nations Framework Convention on Climate Change (UNFCCC). The UK N2O inventory follows internationally agreed protocols and emission estimates are derived by applying emission factors to estimates of (anthropogenic) emission sources. This approach is useful for comparing anthropogenic emissions from different countries, but does not capture regional differences and inter-annual variability associated with environmental factors (such as climate and soils) and agricultural management. In recent years, the UK inventory approach has been refined to include regional information into its emissions estimates (e.g. agricultural management data), in an attempt to reduce uncertainty. This study attempts to assess the difference between current published inventory methodology (default IPCC methodology) and a revised approach, which incorporates the latest thinking, using data from recent work. For 2013, emission estimates made using the revised approach were 30 % lower than those made using default IPCC methodology, due to the use of lower emission factors suggested by recent projects (www.ghgplatform.org.uk, Defra projects: AC0116, AC0213 and MinNO). The 2013 emissions estimates were disaggregated on a monthly basis using agricultural management (e.g. sowing dates), climate data and soil properties. The temporally disaggregated emission maps were used as input to the Met Office atmospheric dispersion model NAME, for comparison with measured N2O concentrations, at three observation stations (Tacolneston, E England; Ridge Hill, W England; Mace Head, W Ireland) in the UK DECC network (Deriving Emissions linked to Climate Change). The Mace Head site, situated on the west coast of Ireland, was used to establish baseline concentrations. The trends in the modelled data were found to fit with the observational data trends, with concentration peaks coinciding with periods of fertiliser application and land spreading of manures. The model run using the 'experimental' approach was found to give a closer agreement with the observed data.

Emission factors for open and domestic biomass burning for use in atmospheric models

Treesearch

S. K. Akagi; R. J. Yokelson; C. Wiedinmyer; M. J. Alvarado; J. S. Reid; T. Karl; J. D. Crounse; P. O. Wennberg

2010-01-01

Biomass burning (BB) is the second largest source of trace gases and the largest source of primary fine carbonaceous particles in the global troposphere. Many recent BB studies have provided new emission factor (EF) measurements. This is especially 5 true for non methane organic compounds (NMOC), which influence secondary organic aerosol (SOA) and ozone formation. New...

Emissions databases for polycyclic aromatic compounds in the Canadian Athabasca oil sands region - development using current knowledge and evaluation with passive sampling and air dispersion modelling data

NASA Astrophysics Data System (ADS)

Qiu, Xin; Cheng, Irene; Yang, Fuquan; Horb, Erin; Zhang, Leiming; Harner, Tom

2018-03-01

Two speciated and spatially resolved emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada-Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes (DBTs), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model-measurement agreement in the total PAH concentrations and for most PAH species concentrations compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emissions estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.

Improved model of isoprene emissions in Africa using Ozone Monitoring Instrument (OMI) satellite observations of formaldehyde: implications for oxidants and particulate matter

EPA Science Inventory

We use a 2005–2009 record of isoprene emissions over Africa derived from Ozone Monitoring Instrument (OMI) satellite observations of formaldehyde (HCHO) to better understand the factors controlling isoprene emission in the continent and evaluate the impact on atmospheric co...

Energy consumption and CO2 emissions in Iran, 2025.

PubMed

Mirzaei, Maryam; Bekri, Mahmoud

2017-04-01

Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO 2 emissions. A system dynamic model was developed in this study to model the energy consumption and CO 2 emission trends for Iran over 2000-2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO 2 emissions in 2025 will reach 985million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO 2 emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO 2 emission outlines. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting emissions from oil and gas operations in the Uinta Basin, Utah.

PubMed

Wilkey, Jonathan; Kelly, Kerry; Jaramillo, Isabel Cristina; Spinti, Jennifer; Ring, Terry; Hogue, Michael; Pasqualini, Donatella

2016-05-01

In this study, emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin are predicted (with uncertainty estimates) from 2015-2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010-2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010-2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015-2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards. This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.

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.

A technology-based mass emission factors of gases and aerosol precursor and spatial distribution of emissions from on-road transport sector in India

NASA Astrophysics Data System (ADS)

Prakash, Jai; Habib, Gazala

2018-05-01

This study presents a new emission estimate of gaseous pollutants including CO, CO2, and NOX from on-road transport sector of India for the base year 2013. For the first time, a detailed vintage-wise on-road measured emission factors used for reducing uncertainties in emission estimates. The consumptions of diesel, gasoline, and compressed natural gas (CNG) were also estimated at the national level and disaggregated at the state level. The national average use of diesel, gasoline, and CNG and their 95% confidence interval estimated as 52 (39-66), 24 (18-30), and 1.6 (1.2-2.0) MTy-1 for the year 2013. The CO, CO2, and NOX emissions were estimated as 7349 (3220-11477) Gg y-1, 261 (179-343) Tg y-1, and 4052 (2127-5977) Gg y-1, respectively from on-road transport sector for the year 2013. New vehicles registered after 2005 emit 70-80% of national level CO2, and NOX, while rest 20-30% were emitted by old vehicles registered before 2005. Old and new vehicles both equally contributed to CO emissions. Superemitters accounted for 14% of total traffic volume, but they were responsible for 17-57% of total CO2, CO and NOX emissions. The uncertainties in emission estimates were reduced to 48-56% compared to previous estimates (62-136%). The comparison with recent studies for nationwide emission estimates from 4-wheelers indicated that use of emission factors from dynamometer studies can underestimate the emissions by 32-92% for various pollutants, while an overestimation by 20-82% was seen with the use of emission model derived emission factors. Similarly for Delhi city recent CO and NOx emission estimates for 4-wheelers based on emission factors reported from dynamometer studies were 23-89% lower than present work. The present work revealed the need for representative vintage wise emission factor database development from on-road measurement and the more comprehensive assessment of activity data through survey.

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.

Maximum warming occurs about one decade after carbon dioxide emission

NASA Astrophysics Data System (ADS)

Ricke, K.; Caldeira, K.

2014-12-01

There has been a long tradition of estimating the amount of climate change that would result from various carbon dioxide emission or concentration scenarios but there has been relatively little quantitative analysis of how long it takes to feel the consequences of an individual carbon dioxide emission. Using conjoined results of recent carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6 to 30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. To characterize the carbon cycle uncertainty associated with the global temperature response to a carbon dioxide emission today, we use fits to the time series of carbon dioxide concentrations from a CO2-impulse response function model intercomparison project's 15 ensemble members (1). To characterize both the uncertainty in climate sensitivity and in the thermal inertia of the climate system, we use fits to the time series of global temperature change from the Coupled Model Intercomparison Project phase 5 (CMIP5; 2) abrupt4xco2 experiment's 20 ensemble's members separating the effects of each uncertainty factors using one of two simple physical models for each CMIP5 climate model. This yields 6,000 possible combinations of these three factors using a standard convolution integral approach. Our results indicate that benefits of avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While the relevant time lags imposed by the climate system are substantially shorter than a human lifetime, they are substantially longer than the typical political election cycle, making the delay and its associated uncertainties both economically and politically significant. References: 1. Joos F et al. (2013) Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos Chem Phys 13:2793-2825. 2. Taylor KE, Stouffer RJ, Meehl GA (2011) An Overview of CMIP5 and the Experiment Design. Bull Am Meteorol Soc 93:485-498.

Short-term landfill methane emissions dependency on wind.

PubMed

Delkash, Madjid; Zhou, Bowen; Han, Byunghyun; Chow, Fotini K; Rella, Chris W; Imhoff, Paul T

2016-09-01

Short-term (2-10h) variations of whole-landfill methane emissions have been observed in recent field studies using the tracer dilution method for emissions measurement. To investigate the cause of these variations, the tracer dilution method is applied using 1-min emissions measurements at Sandtown Landfill (Delaware, USA) for a 2-h measurement period. An atmospheric dispersion model is developed for this field test site, which is the first application of such modeling to evaluate atmospheric effects on gas plume transport from landfills. The model is used to examine three possible causes of observed temporal emissions variability: temporal variability of surface wind speed affecting whole landfill emissions, spatial variability of emissions due to local wind speed variations, and misaligned tracer gas release and methane emissions locations. At this site, atmospheric modeling indicates that variation in tracer dilution method emissions measurements may be caused by whole-landfill emissions variation with wind speed. Field data collected over the time period of the atmospheric model simulations corroborate this result: methane emissions are correlated with wind speed on the landfill surface with R(2)=0.51 for data 2.5m above ground, or R(2)=0.55 using data 85m above ground, with emissions increasing by up to a factor of 2 for an approximately 30% increase in wind speed. Although the atmospheric modeling and field test are conducted at a single landfill, the results suggest that wind-induced emissions may affect tracer dilution method emissions measurements at other landfills. Copyright © 2016 Elsevier Ltd. 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.

Improving emissions inventories in Mexico through systematic analysis of model performance along C-130 and DC-8 flight tracks during MILAGRO

NASA Astrophysics Data System (ADS)

Mena-Carrasco, M.; Carmichael, G. R.; Campbell, J. E.; Tang, Y.; Chai, T.

2007-05-01

During the MILAGRO campaign in March 2006 the University of Iowa provided regional air quality forecasting for scientific flight planning for the C-130 and DC-8. Model performance showed positive bias of ozone prediction (~15ppbv), associated to overpredictions in precursor concentrations (~2.15 ppbv NOy and ~1ppmv ARO1). Model bias showed a distinct geographical pattern in which the higher values were in and near Mexico City. Newer runs in which NOx and VOC emissions were decreased improved ozone prediction, decreasing bias and increasing model correlation, at the same time reducing regional bias over Mexico. This work will evaluate model performance using the newly published Mexico National Emissions Inventory, and the introduction of data assimilation to recover emissions scaling factors to optimize model performance. Finally the results of sensitivity runs showing the regional impact of Mexico City emissions on ozone concentrations will be shown, along with the influence of Mexico City aerosol concentrations on regional photochemistry.

Top-down quantification of NOx emissions from traffic in an urban area using a high-resolution regional atmospheric chemistry model

NASA Astrophysics Data System (ADS)

Kuik, Friderike; Kerschbaumer, Andreas; Lauer, Axel; Lupascu, Aurelia; von Schneidemesser, Erika; Butler, Tim M.

2018-06-01

With NO2 limit values being frequently exceeded in European cities, complying with the European air quality regulations still poses a problem for many cities. Traffic is typically a major source of NOx emissions in urban areas. High-resolution chemistry transport modelling can help to assess the impact of high urban NOx emissions on air quality inside and outside of urban areas. However, many modelling studies report an underestimation of modelled NOx and NO2 compared with observations. Part of this model bias has been attributed to an underestimation of NOx emissions, particularly in urban areas. This is consistent with recent measurement studies quantifying underestimations of urban NOx emissions by current emission inventories, identifying the largest discrepancies when the contribution of traffic NOx emissions is high. This study applies a high-resolution chemistry transport model in combination with ambient measurements in order to assess the potential underestimation of traffic NOx emissions in a frequently used emission inventory. The emission inventory is based on officially reported values and the Berlin-Brandenburg area in Germany is used as a case study. The WRF-Chem model is used at a 3 km × 3 km horizontal resolution, simulating the whole year of 2014. The emission data are downscaled from an original resolution of ca. 7 km × 7 km to a resolution of 1 km × 1 km. An in-depth model evaluation including spectral decomposition of observed and modelled time series and error apportionment suggests that an underestimation in traffic emissions is likely one of the main causes of the bias in modelled NO2 concentrations in the urban background, where NO2 concentrations are underestimated by ca. 8 µg m-3 (-30 %) on average over the whole year. Furthermore, a diurnal cycle of the bias in modelled NO2 suggests that a more realistic treatment of the diurnal cycle of traffic emissions might be needed. Model problems in simulating the correct mixing in the urban planetary boundary layer probably play an important role in contributing to the model bias, particularly in summer. Also taking into account this and other possible sources of model bias, a correction factor for traffic NOx emissions of ca. 3 is estimated for weekday daytime traffic emissions in the core urban area, which corresponds to an overall underestimation of traffic NOx emissions in the core urban area of ca. 50 %. Sensitivity simulations for the months of January and July using the calculated correction factor show that the weekday model bias can be improved from -8.8 µg m-3 (-26 %) to -5.4 µg m-3 (-16 %) in January on average in the urban background, and -10.3 µg m-3 (-46 %) to -7.6 µg m-3 (-34 %) in July. In addition, the negative bias of weekday NO2 concentrations downwind of the city in the rural and suburban background can be reduced from -3.4 µg m-3 (-12 %) to -1.2 µg m-3 (-4 %) in January and from -3.0 µg m-3 (-22 %) to -1.9 µg m-3 (-14 %) in July. The results and their consistency with findings from other studies suggest that more research is needed in order to more accurately understand the spatial and temporal variability in real-world NOx emissions from traffic, and apply this understanding to the inventories used in high-resolution chemical transport models.

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.

The Study of Biogenetic Organic Compound Emissions and Ozone in a Subtropical Bamboo Forest

NASA Astrophysics Data System (ADS)

Bai, Jianhui; Guenther, Alex; Turnipseed, Andrew; Duhl, Tiffany; Duhl, Nanhao; van der A, Ronald; Yu, Shuquan; Wang, Bin

2016-08-01

Emissions of Biogenic Volatile Organic compounds (BVOCs), Photosynthetically Active Radiation (PAR), and meteorological parameters were measured in some ecosystems in China. A Relaxed Eddy Accumulation system and an enclosure technique were used to measure BVOC emissions. Obvious diurnal and seasonal variations of BVOC emissions were found. Empirical models of BVOC emissions were developed, the estimated BVOC emissions were in agreement with observations. BVOC emissions in growing seasons in the Inner Mongolia grassland, Chnagbai Mountain temperate forest, LinAn subtropical bamboo forest were estimated. The emission factors of these ecosystems were calculated.

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

PubMed

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

2015-05-01

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

A Consideration on Service Business Model for Saving Energy and Reduction of CO2 Emissions Using Inverters

NASA Astrophysics Data System (ADS)

Kosaka, Michitaka; Yabutani, Takashi

This paper considers the effectiveness of service business approach for reducing CO2 emission. “HDRIVE” is a service business using inverters to reduce energy consumption of motor drive. The business model of this service is changed for finding new opportunities of CO2 emission reduction by combining various factors such as financial service or long-term service contract. Risk analysis of this business model is very important for giving stable services to users for long term. HDRIVE business model is found to be suitable for this objective. This service can be applied to the industries such as chemical or steel industry effectively, where CO2 emission is very large, and has the possibility of creating new business considering CDM or trading CO2 emission right. The effectiveness of this approach is demonstrated through several examples in real business.

Integrated model for assessing the cost and CO2 emission (IMACC) for sustainable structural design in ready-mix concrete.

PubMed

Hong, Taehoon; Ji, Changyoon; Park, Hyoseon

2012-07-30

Cost has traditionally been considered the most important factor in the decision-making process. Recently, along with the consistent interest in environmental problems, environmental impact has also become a key factor. Accordingly, there is a need to develop a method that simultaneously reflects the cost and environmental impact in the decision-making process. This study proposed an integrated model for assessing the cost and CO(2) emission (IMACC) at the same time. IMACC is a model that assesses the cost and CO(2) emission of the various structural-design alternatives proposed in the structural-design process. To develop the IMACC, a standard on assessing the cost and CO(2) emission generated in the construction stage was proposed, along with the CO(2) emission factors in the structural materials, based on such materials' strengths. Moreover, using the economic and environmental scores that signify the cost and CO(2) emission reduction ratios, respectively, a method of selecting the best design alternative was proposed. To verify the applicability of IMACC, practical application was carried out. Structural designs were assessed, each of which used 21, 24, 27, and 30 MPa ready-mix concrete (RMC). The use of IMACC makes it easy to verify what the best design is. Results show the one that used 27 MPa RMC was the best design. Therefore, the proposed IMACC can be used as a tool for supporting the decision-making process in selecting the best design alternative. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ethylene glycol emissions from on-road vehicles: implications for aqueous phase secondary organic aerosol formation

NASA Astrophysics Data System (ADS)

Wood, E. C.; Knighton, W. B.; Fortner, E.; Herndon, S. C.; Onasch, T. B.; Franklin, J.; Harley, R. A.; Gentner, D. R.; Goldstein, A. H.

2012-12-01

Ethylene glycol (HOCH2CH2OH), used as an engine coolant for most on-road vehicles, is an intermediate volatility organic compound (IVOC) with a high Henry's Law Coefficient (kH > 10,000 M atm-1) . Oxidation of ethylene glycol, especially in the atmospheric aqueous phase (clouds, fog, wet aerosol), can lead to the formation of glycolaldehyde, oxalic acid, and ultimately secondary organic aerosol. We present measurements of unexpectedly high ethylene glycol emissions in the Caldecott Tunnel near San Francisco (Summer 2010) and the Washburn Tunnel near Houston (Spring 2009). Ethylene glycol was detected using a proton-transfer reaction mass spectrometer (PTR-MS) at m/z = 45, which is usually interpreted as acetaldehyde. Although not necessarily a tailpipe emission, effective fuel-based emission factors are calculated using the carbon balance method and range from 50 to 400 mg ethylene glycol per kg fuel. Total US and global emissions are estimated using these emission factors and fuel consumption rates and are compared to previous model estimates of ethylene glycol emissions (e.g., the Regional Atmospheric Chemistry Model). Compared to biogenically emitted isoprene, ethylene glycol is likely a minor source of glycolaldehyde globally, but may contribute significantly to glycolaldehyde, oxalate and SOA formation in areas dominated by urban emissions.

Application of GPS data for benefits of air quality assessment and fleet management

NASA Astrophysics Data System (ADS)

Hao, Song; Fat Lam, Yun; Cheong Ying, Chi; Chan, Ka Lok

2017-04-01

In the modern digitizedsociety, traffic data can be easily collected for use in roadway development, urban planning and vehicle emission. These data are then further parameterized to support traffic simulation and roadside emission calculations. With the commercialization of AGPS/GPS technology, GPS data are widely utilized to study habit and travelling behaviors. GPS on franchised buses can provide not only positioning information for fleet management but also raw data to analyze traffic situations. In HK, franchised buses account for 6% of RSP and 20% of NOx emissions among the whole vehicle fleet. Being the most heavily means of public transport, the setting up of bus travelling trajectories and service frequency always raise concern from citizens. On this basis, there is an increasing interest and as well as to design and realize an effective cost benefit fleet management strategy. In this study, data collection analysis is carried out on all bus routes (i.e. 112) in Shatin district, one of the 18 districts in Hong Kong. The GPS/AGPS data through Esri ArcGIS investigate the potential benefit of GPS data in different emission scenarios (such as engine type over whole bus fleet). Building on the emission factors from EMFC-HK model, we accounted for factors like travelling distance, idling time, occupancy rate, service frequency, tire and break emissions. Through the simple emission developed model we demonstrate how GPS are data are utilized to assess bus fleet emissions. Further amelioration on the results involve tuning the model with field measurement so as to assess district level emission change after fleet optimization.

Ammonia emissions from a grazed field estimated by miniDOAS measurements and inverse dispersion modelling

NASA Astrophysics Data System (ADS)

Bell, Michael; Flechard, Chris; Fauvel, Yannick; Häni, Christoph; Sintermann, Jörg; Jocher, Markus; Menzi, Harald; Hensen, Arjan; Neftel, Albrecht

2017-05-01

Ammonia (NH3) fluxes were estimated from a field being grazed by dairy cattle during spring by applying a backward Lagrangian stochastic model (bLS) model combined with horizontal concentration gradients measured across the field. Continuous concentration measurements at field boundaries were made by open-path miniDOAS (differential optical absorption spectroscopy) instruments while the cattle were present and for 6 subsequent days. The deposition of emitted NH3 to clean patches on the field was also simulated, allowing both net and gross emission estimates, where the dry deposition velocity (vd) was predicted by a canopy resistance (Rc) model developed from local NH3 flux and meteorological measurements. Estimated emissions peaked during grazing and decreased after the cattle had left the field, while control on emissions was observed from covariance with temperature, wind speed and humidity and wetness measurements made on the field, revealing a diurnal emission profile. Large concentration differences were observed between downwind receptors, due to spatially heterogeneous emission patterns. This was likely caused by uneven cattle distribution and a low grazing density, where hotspots of emissions would arise as the cattle grouped in certain areas, such as around the water trough. The spatial complexity was accounted for by separating the model source area into sub-sections and optimising individual source area coefficients to measured concentrations. The background concentration was the greatest source of uncertainty, and based on a sensitivity/uncertainty analysis the overall uncertainty associated with derived emission factors from this study is at least 30-40 %.Emission factors can be expressed as 6 ± 2 g NH3 cow-1 day-1, or 9 ± 3 % of excreted urine-N emitted as NH3, when deposition is not simulated and 7 ± 2 g NH3 cow-1 day-1, or 10 ± 3 % of excreted urine-N emitted as NH3, when deposition is included in the gross emission model. The results suggest that around 14 ± 4 % of emitted NH3 was deposited to patches within the field that were not affected by urine or dung.

Russia's black carbon emissions: focus on diesel sources

NASA Astrophysics Data System (ADS)

Kholod, Nazar; Evans, Meredydd; Kuklinski, Teresa

2016-09-01

Black carbon (BC) is a significant climate forcer with a particularly pronounced forcing effect in polar regions such as the Russian Arctic. Diesel combustion is a major global source of BC emissions, accounting for 25-30 % of all BC emissions. While the demand for diesel is growing in Russia, the country's diesel emissions are poorly understood. This paper presents a detailed inventory of Russian BC emissions from diesel sources. Drawing on a complete Russian vehicle registry with detailed information about vehicle types and emission standards, this paper analyzes BC emissions from diesel on-road vehicles. We use the COPERT emission model (COmputer Programme to calculate Emissions from Road Transport) with Russia-specific emission factors for all types of on-road vehicles. On-road diesel vehicles emitted 21 Gg of BC in 2014: heavy-duty trucks account for 60 % of the on-road BC emissions, while cars represent only 5 % (light commercial vehicles and buses account for the remainder). Using Russian activity data and fuel-based emission factors, the paper also presents BC emissions from diesel locomotives and ships, off-road engines in industry, construction and agriculture, and generators. The study also factors in the role of superemitters in BC emissions from diesel on-road vehicles and off-road sources. The total emissions from diesel sources in Russia are estimated to be 49 Gg of BC and 17 Gg of organic carbon (OC) in 2014. Off-road diesel sources emitted 58 % of all diesel BC in Russia.

Russia's black carbon emissions: focus on diesel sources

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

Kholod, Nazar; Evans, Meredydd; Kuklinski, Teresa

Black carbon (BC) is a significant climate forcer with a particularly pronounced forcing effect in polar regions such as the Russian Arctic. Diesel combustion is a major global source of BC emissions, accounting for 25–30% of all BC emissions. While the demand for diesel is growing in Russia, the country's diesel emissions are poorly understood. This paper presents a detailed inventory of Russian BC emissions from diesel sources. Drawing on a complete Russian vehicle registry with detailed information about vehicle types and emission standards, this paper analyzes BC emissions from diesel on-road vehicles. We use the COPERT emission model (COmputermore » Programme to calculate Emissions from Road Transport) with Russia-specific emission factors for all types of on-road vehicles. On-road diesel vehicles emitted 21 Gg of BC in 2014: heavy-duty trucks account for 60% of the on-road BC emissions, while cars represent only 5% (light commercial vehicles and buses account for the remainder). Using Russian activity data and fuel-based emission factors, the paper also presents BC emissions from diesel locomotives and ships, off-road engines in industry, construction and agriculture, and generators. The study also factors in the role of superemitters in BC emissions from diesel on-road vehicles and off-road sources. The total emissions from diesel sources in Russia are estimated to be 49 Gg of BC and 17 Gg of organic carbon (OC) in 2014. Off-road diesel sources emitted 58% of all diesel BC in Russia.« less

The impacts of reactive terpene emissions from plants on air quality in Las Vegas, Nevada

NASA Astrophysics Data System (ADS)

Papiez, Maria R.; Potosnak, Mark J.; Goliff, Wendy S.; Guenther, Alex B.; Matsunaga, Sou N.; Stockwell, William R.

A three-part study was conducted to quantify the impact of landscaped vegetation on air quality in a rapidly expanding urban area in the arid southeastern United States. The study combines in situ, plant-level measurements, a spatial emissions inventory, and a photochemical box model. Maximum plant-level basal emission rates were moderate: 18.1 μgC gdw -1 h -1 ( Washingtonia spp., palms) for isoprene and 9.56 μgC gdw -1 h -1 ( Fraxinus velutina, Arizona ash) for monoterpenes. Sesquiterpene emission rates were low for plant species selected in this study, with no measurement exceeding 0.1 μgC gdw -1 h -1. The high ambient temperatures combined with moderate plant-level emission factors resulted in landscape emission factors that were low (250-640 μgC m -2 h -1) compared to more mesic environments (e.g., the southeastern United States). The Regional Atmospheric Chemistry Mechanism (RACM) was modified to include a new reaction pathway for ocimene. Using measured concentrations of anthropogenic hydrocarbons and other reactive air pollutants (NO x, ozone), the box model employing the RACM mechanism revealed that these modest emissions could have a significant impact on air quality. For a suburban location that was downwind of the urban core (high NO x; low anthropogenic hydrocarbons), biogenic terpenes increased time-dependent ozone production rates by a factor of 50. Our study demonstrates that low-biomass density landscapes emit sufficient biogenic terpenes to have a significant impact on regional air quality.

PCDD/F emissions from light-duty diesel vehicles operated under highway conditions and a diesel-engine based power generator.

PubMed

Rey, M D; Font, R; Aracil, I

2014-08-15

PCDD/F emissions from three light-duty diesel vehicles--two vans and a passenger car--have been measured in on-road conditions. We propose a new methodology for small vehicles: a sample of exhaust gas is collected by means of equipment based on United States Environmental Protection Agency (U.S. EPA) method 23 A for stationary stack emissions. The concentrations of O2, CO, CO2, NO, NO2 and SO2 have also been measured. Six tests were carried out at 90-100 km/h on a route 100 km long. Two additional tests were done during the first 10 min and the following 60 min of the run to assess the effect of the engine temperature on PCDD/F emissions. The emission factors obtained for the vans varied from 1800 to 8400 pg I-TEQ/Nm(3) for a 2004 model year van and 490-580 pg I-TEQ/Nm(3) for a 2006 model year van. Regarding the passenger car, one run was done in the presence of a catalyst and another without, obtaining emission factors (330-880 pg I-TEQ/Nm(3)) comparable to those of the modern van. Two other tests were carried out on a power generator leading to emission factors ranging from 31 to 78 pg I-TEQ/Nm(3). All the results are discussed and compared with literature. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatiotemporal variability of biogenic terpenoid emissions in Pearl River Delta, China, with high-resolution land-cover and meteorological data

NASA Astrophysics Data System (ADS)

Wang, Xuemei; Situ, Shuping; Guenther, Alex; Chen, Fei; Wu, Zhiyong; Xia, Beicheng; Wang, Tijian

2011-04-01

This study intended to provide 4-km gridded, hourly, year-long, regional estimates of terpenoid emissions in the Pearl River Delta (PRD), China. It combined Thematic Mapper images and local-survey data to characterize plant functional types, and used observed emission potential of biogenic volatile organic compounds (BVOC) from local plant species and high-resolution meteorological outputs from the MM5 model to constrain the MEGAN BVOC-emission model. The estimated annual emissions for isoprene, monoterpene and sesquiterpene are 95.55 × 106 kg C, 117.35 × 106 kg C and 9.77 × 106 kg C, respectively. The results show strong variabilities of terpenoid emissions spanning diurnal and seasonal time scales, which are mainly distributed in the remote areas (with more vegetation and less economic development) in PRD. Using MODIS PFTs data reduced terpenoid emissions by 27% in remote areas. Using MEGAN-model default emission factors led to a 24% increase in BVOC emission. The model errors of temperature and radiation in MM5 output were used to assess impacts of uncertainties in meteorological forcing on emissions: increasing (decreasing) temperature and downward shortwave radiation produces more (less) terpenoid emissions for July and January. Strong temporal variability of terpenoid emissions leads to enhanced ozone formation during midday in rural areas where the anthropogenic VOC emissions are limited.

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

HEMCO v1.0: A Versatile, ESMF-Compliant Component for Calculating Emissions in Atmospheric Models

NASA Technical Reports Server (NTRS)

Keller, C. A.; Long, M. S.; Yantosca, R. M.; Da Silva, A. M.; Pawson, S.; Jacob, D. J.

2014-01-01

We describe the Harvard-NASA Emission Component version 1.0 (HEMCO), a stand-alone software component for computing emissions in global atmospheric models. HEMCO determines emissions from different sources, regions, and species on a user-defined grid and can combine, overlay, and update a set of data inventories and scale factors, as specified by the user through the HEMCO configuration file. New emission inventories at any spatial and temporal resolution are readily added to HEMCO and can be accessed by the user without any preprocessing of the data files or modification of the source code. Emissions that depend on dynamic source types and local environmental variables such as wind speed or surface temperature are calculated in separate HEMCO extensions. HEMCO is fully compliant with the Earth System Modeling Framework (ESMF) environment. It is highly portable and can be deployed in a new model environment with only few adjustments at the top-level interface. So far, we have implemented HEMCO in the NASA Goddard Earth Observing System (GEOS-5) Earth system model (ESM) and in the GEOS-Chem chemical transport model (CTM). By providing a widely applicable framework for specifying constituent emissions, HEMCO is designed to ease sensitivity studies and model comparisons, as well as inverse modeling in which emissions are adjusted iteratively. The HEMCO code, extensions, and the full set of emissions data files used in GEOS-Chem are available at http: //wiki.geos-chem.org/HEMCO.

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Major, David C.; Yu, Winston H.; Alam, Mozaharul; Hussain, Sk. Ghulam; Khan, Abu Saleh; Hassan, Ahmadul; Al Hossain, Bhuiya Md. Tamim; Goldberg, Richard; Horton, Radley M.;

Modeling atmospheric sulfur over the Northern Hemisphere during the Aerosol Characterization Experiment 2 experimental period

NASA Astrophysics Data System (ADS)

Benkovitz, Carmen M.; Schwartz, Stephen E.; Jensen, Michael P.; Miller, Mark A.; Easter, R. C.; Bates, Timothy S.

2004-11-01

A high-resolution (1° × 1°, 27 vertical levels) Eulerian chemical transport and transformation model for sulfate, SO2, and related species driven by analyzed forecast meteorological data has been run for the Northern Hemisphere for June-July 1997 and extensively evaluated with observational data, mainly from air quality and precipitation chemistry networks. For ˜5000 evaluations, 50% of the modeled sulfate 24-hour mixing ratios were within a factor of 1.85 of the observations; 50% of ˜328 concurrent subgrid observations were within a factor of 1.33. Much greater subgrid variation for 24-hour SO2 mixing ratios (50% of ˜3552 observations were within a factor of 2.32) reflects high variability of this primary species; for ˜12600 evaluations, 50% of modeled mixing ratios were within a factor of 2.54 of the observations. These results indicate that a substantial fraction of the modeled and observed differences is due to subgrid variation and/or measurement error. Sulfate mixing ratios are identified by source type (biogenic, volcanic, and anthropogenic) and production mechanism (primary and by gas-phase and aqueous-phase oxidation). Examination of key diagnostics showed substantial variation for the different types of sulfur, e.g., SO2 aqueous-phase oxidation rates of 29-102% d-1 and sulfate residence times of 4-9 days. Volcanic emissions contributed 10% of the sulfate burden and 6% of emissions, because the elevated release allows large fractional conversion of SO2 and long residence time. Biogenic SO2 was generally at lower concentrations than H2O2, resulting in efficient aqueous-phase oxidation; this source type contributed 13% of emissions but only 5% of sulfate burden. Anthropogenic sources were the dominant contributors to sulfur emissions (80%) and sulfate burden (84%).

Hybrid-Electric Passenger Car Carbon Dioxide and Fuel Consumption Benefits Based on Real-World Driving.

PubMed

Holmén, Britt A; Sentoff, Karen M

2015-08-18

Hybrid-electric vehicles (HEVs) have lower fuel consumption and carbon dioxide (CO2) emissions than conventional vehicles (CVs), on average, based on laboratory tests, but there is a paucity of real-world, on-road HEV emissions and performance data needed to assess energy use and emissions associated with real-world driving, including the effects of road grade. This need is especially great as the electrification of the passenger vehicle fleet (from HEVs to PHEVs to BEVs) increases in response to climate and energy concerns. We compared tailpipe CO2 emissions and fuel consumption of an HEV passenger car to a CV of the same make and model during real-world, on-the-road network driving to quantify the in-use benefit of one popular full HEV technology. Using vehicle specific power (VSP) assignments that account for measured road grade, the mean CV/HEV ratios of CO2 tailpipe emissions or fuel consumption defined the corresponding HEV "benefit" factor for each VSP class (1 kW/ton resolution). Averaging over all VSP classes for driving in all seasons, including temperatures from -13 to +35 °C in relatively steep (-13.2 to +11.5% grade), hilly terrain, mean (±SD) CO2 emission benefit factors were 4.5 ± 3.6, 2.5 ± 1.7, and 1.4 ± 0.5 for city, exurban/suburban arterial and highway driving, respectively. Benefit factor magnitude corresponded to the frequency of electric-drive-only (EDO) operation, which was modeled as a logarithmic function of VSP. A combined model explained 95% of the variance in HEV benefit for city, 75% for arterial and 57% for highway driving. Benefit factors consistently exceeded 2 for VSP classes with greater than 50% EDO (i.e., only city and arterial driving). The reported HEV benefits account for real-world road grade that is often neglected in regulatory emissions and fuel economy tests. Fuel use HEV benefit factors were 1.3 and 2 for the regulatory highway (HWFET) and city (FTP) cycles, respectively, 18% and 31% higher than the EPA adjusted fuel economy values. This study establishes the significant need for high-resolution vehicle activity and road grade data in transportation data sets to accurately forecast future petroleum and GHG emissions savings from hybridization of the passenger vehicle fleet.

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

PubMed

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

2017-09-29

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

Characterization of emission factors related to source activity for trichloroethylene degreasing and chrome plating processes.

PubMed

Wadden, R A; Hawkins, J L; Scheff, P A; Franke, J E

1991-09-01

A study at an automotive parts fabrication plant evaluated four metal surface treatment processes during production conditions. The evaluation provides examples of how to estimate process emission factors from activity and air concentration data. The processes were open tank and enclosed tank degreasing with trichloroethylene (TCE), chromium conversion coating, and chromium electroplating. Area concentrations of TCE and chromium (Cr) were monitored for 1-hr periods at three distances from each process. Source activities at each process were recorded during each sampling interval. Emission rates were determined by applying appropriate mass balance models to the concentration patterns around each source. The emission factors obtained from regression analysis of the emission rate and activity data were 16.9 g TCE/basket of parts for the open-top degreaser; 1.0 g TCE/1000 parts for the enclosed degreaser; 1.48-1.64 mg Cr/1000 parts processed in the hot CrO3/HNO3 tank for the chrome conversion coating; and 5.35-9.17 mg Cr/rack of parts for chrome electroplating. The factors were also used to determine the efficiency of collection for the local exhaust systems serving each process. Although the number of observations were limited, these factors may be useful for providing initial estimates of emissions from similar processes in other settings.

Emission factors of black carbon and co-pollutants from diesel vehicles in Mexico City

NASA Astrophysics Data System (ADS)

Zavala, Miguel; Molina, Luisa T.; Yacovitch, Tara I.; Fortner, Edward C.; Roscioli, Joseph R.; Floerchinger, Cody; Herndon, Scott C.; Kolb, Charles E.; Knighton, Walter B.; Paramo, Victor Hugo; Zirath, Sergio; Mejía, José Antonio; Jazcilevich, Aron

2017-12-01

Diesel-powered vehicles are intensively used in urban areas for transporting goods and people but can substantially contribute to high emissions of black carbon (BC), organic carbon (OC), and other gaseous pollutants. Strategies aimed at controlling mobile emissions sources thus have the potential to improve air quality and help mitigate the impacts of air pollutants on climate, ecosystems, and human health. However, in developing countries there are limited data on the BC and OC emission characteristics of diesel-powered vehicles, and thus there are large uncertainties in the estimation of the emission contributions from these sources. We measured BC, OC, and other inorganic components of fine particulate matter (PM), as well as carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), ethane, acetylene, benzene, toluene, and C2-benzenes under real-world driving conditions for 20 diesel-powered vehicles encompassing multiple emission level technologies in Mexico City with the chasing technique using the Aerodyne mobile laboratory. Average BC emission factors ranged from 0.41-2.48 g kg-1 of fuel depending on vehicle type. The vehicles were also simultaneously measured using the cross-road remote sensing technique to obtain the emission factors of nitrogen oxide (NO), CO, total hydrocarbons, and fine PM, thus allowing for the intercomparison of the results from the two techniques. There is overall good agreement between the two techniques and both can identify high and low emitters, but substantial differences were found in some of the vehicles, probably due to the ability of the chasing technique to capture a larger diversity of driving conditions in comparison to the remote sensing technique. A comparison of the results with the US EPA MOVES2014b model showed that the model underestimates CO, OC, and selected VOC species, whereas there is better agreement for NOx and BC. Larger OC / BC ratios were found in comparison to ratios measured in California using the same technique, further demonstrating the need for using locally obtained diesel-powered vehicle emission factor database in developing countries in order to reduce the uncertainty in the emissions estimates and to improve the evaluation of the effectiveness of emissions reduction measures.

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

The uncertainties in the global budget of carbon monoxide (CO) are assessed to explain causes for the long-standing issue of Northern Hemispheric wintertime underestimation of CO concentrations in global models. With a series of MOZART sensitivity simulations for the year 2008, the impacts from changing a variety of surface sources and sinks were analyzed. The model results were evaluated with monthly averages of surface station observations from the global CO monitoring network as well as with total columns observed from satellites and with vertical profiles from measurements on passenger aircraft. Our basic simulation using MACCity anthropogenic emissions underestimated Northern Hemispheric near-surface CO concentrations on average by more than 20 ppb from December to April with the largest bias over Europe of up to 75 ppb in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOC) is not able to reduce the annual course of the model bias and yields too high concentrations over the Southern Hemisphere. Raising global annual anthropogenic emissions results in overestimations of surface concentrations in most regions all-year-round. Instead, our results indicate that anthropogenic emissions in the MACCity inventory are too low for the industrialized countries during winter and spring. Thus we found it necessary to adjust emissions seasonally with regionally varying scaling factors. Moreover, exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes reduced the boreal winter dry deposition fluxes and could partly correct for the model bias. When combining the modified dry deposition scheme with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively) we were able to optimize the match to surface observations and to reduce the model bias significantly with respect to the satellite and aircraft observations. A reason for the apparent underestimation of emissions may be an exaggerated downward trend in the RCP8.5 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 exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations. Finally, underestimated emissions from anthropogenic VOCs can also account for a small part of the missing CO concentrations.

Current from a nano-gap hyperbolic diode using shape-factors: Theory

NASA Astrophysics Data System (ADS)

Jensen, Kevin L.; Shiffler, Donald A.; Peckerar, Martin; Harris, John R.; Petillo, John J.

2017-08-01

Quantum tunneling by field emission from nanoscale features or sharp field emission structures for which the anode-cathode gap is nanometers in scale ("nano diodes") experience strong deviations from the planar image charge lowered tunneling barrier used in the Murphy and Good formulation of the Fowler-Nordheim equation. These deviations alter the prediction of total current from a curved surface. Modifications to the emission barrier are modeled using a hyperbolic (prolate spheroidal) geometry to determine the trajectories along which the Gamow factor in a WKB-like treatment is undertaken; a quadratic equivalent potential is determined, and a method of shape factors is used to evaluate the corrected total current from a protrusion or wedge geometry.

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.

SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

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

Storm, Emma; Weniger, Christoph; Calore, Francesca, E-mail: e.m.storm@uva.nl, E-mail: c.weniger@uva.nl, E-mail: francesca.calore@lapth.cnrs.fr

We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that aremore » motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.« less

Understanding High Wintertime Ozone Events over an Oil and Natural Gas Production Region from Air Quality Model Perspective

NASA Astrophysics Data System (ADS)

Ahmadov, R.; McKeen, S. A.; Trainer, M.; Banta, R. M.; Brown, S. S.; Edwards, P. M.; Frost, G. J.; Gilman, J.; Helmig, D.; Johnson, B.; Karion, A.; Koss, A.; Lerner, B. M.; Oltmans, S. J.; Roberts, J. M.; Schnell, R. C.; Veres, P. R.; Warneke, C.; Williams, E. J.; Wild, R. J.; Yuan, B.; Zamora, R. J.; Petron, G.; De Gouw, J. A.; Peischl, J.

2014-12-01

The huge increase in production of oil and natural gas has been associated with high wintertime ozone events over some parts of the western US. The Uinta Basin, UT, where oil and natural gas production is abundant experienced high ozone concentrations in winters of recent years, when cold stagnant weather conditions were prevalent. It has been very challenging for conventional air quality models to accurately simulate such wintertime ozone pollution cases. Here, a regional air quality model study was successfully conducted for the Uinta Basin by using the WRF-Chem model. For this purpose a new emission dataset for the region's oil/gas sector was built based on atmospheric in-situ measurements made during 2012 and 2013 field campaigns in the Uinta Basin. The WRF-Chem model demonstrates that the major factors driving high ozone in the Uinta Basin in winter are shallow boundary layers with light winds, high emissions of volatile organic compounds (VOC) compared to nitrogen oxides emissions from the oil and natural gas industry, enhancement of photolysis rates and reduction of O3 dry deposition due to snow cover. We present multiple sensitivity simulations to quantify the contribution of various factors driving high ozone over the Uinta Basin. The emission perturbation simulations show that the photochemical conditions in the Basin during winter of 2013 were VOC sensitive, which suggests that targeting VOC emissions would be most beneficial for regulatory purposes. Shortcomings of the emissions within the most recent US EPA (NEI-2011, version 1) inventory are also discussed.

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.

Prompt Emission of GRB 121217A from Gamma-Rays to the Near-Infrared

NASA Technical Reports Server (NTRS)

Elliott, J.; Yu, H.-F.; Schmidl, S.; Greiner, J.; Gruber, D.; Oates, S.; Kobayashi, S.; Zhang, B.; Cummings, J. R.; Filgas, R.;

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.

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.

Evaluation of Contrail Reduction Strategies Based on Environmental and Operational Costs

NASA Technical Reports Server (NTRS)

Chen, Neil Y.; Sridhar, Banavar; Ng, Hok K.; Li, Jinhua

2013-01-01

This paper evaluates a set of contrail reduction strategies based on environmental and operational costs. A linear climate model was first used to convert climate effects of carbon dioxide emissions and aircraft contrails to changes in Absolute Global Temperature Potential, a metric that measures the mean surface temperature change due to aircraft emissions and persistent contrail formations. The concept of social cost of carbon and the carbon auction price from recent California's cap-and-trade system were then used to relate the carbon dioxide emissions and contrail formations to an environmental cost index. The strategy for contrail reduction is based on minimizing contrail formations by altering the aircraft's cruising altitude. The strategy uses a user-defined factor to trade off between contrail reduction and additional fuel burn and carbon dioxide emissions. A higher value of tradeoff factor results in more contrail reduction but also more fuel burn and carbon emissions. The strategy is considered favorable when the net environmental cost benefit exceeds the operational cost. The results show how the net environmental benefit varies with different decision-making time-horizon and different carbon cost. The cost models provide a guidance to select the trade-off factor that will result in the most net environmental benefit.

Aerosol emissions from prescribed fires in the United States: A synthesis of laboratory and aircraft measurements

NASA Astrophysics Data System (ADS)

May, A. A.; McMeeking, G. R.; Lee, T.; Taylor, J. W.; Craven, J. S.; Burling, I.; Sullivan, A. P.; Akagi, S.; Collett, J. L.; Flynn, M.; Coe, H.; Urbanski, S. P.; Seinfeld, J. H.; Yokelson, R. J.; Kreidenweis, S. M.

2014-10-01

Aerosol emissions from prescribed fires can affect air quality on regional scales. Accurate representation of these emissions in models requires information regarding the amount and composition of the emitted species. We measured a suite of submicron particulate matter species in young plumes emitted from prescribed fires (chaparral and montane ecosystems in California; coastal plain ecosystem in South Carolina) and from open burning of over 15 individual plant species in the laboratory. We report emission ratios and emission factors for refractory black carbon (rBC) and submicron nonrefractory aerosol and compare field and laboratory measurements to assess the representativeness of our laboratory-measured emissions. Laboratory measurements of organic aerosol (OA) emission factors for some fires were an order of magnitude higher than those derived from any of our aircraft observations; these are likely due to higher-fuel moisture contents, lower modified combustion efficiencies, and less dilution compared to field studies. Nonrefractory inorganic aerosol emissions depended more strongly on fuel type and fuel composition than on combustion conditions. Laboratory and field measurements for rBC were in good agreement when differences in modified combustion efficiency were considered; however, rBC emission factors measured both from aircraft and in the laboratory during the present study using the Single Particle Soot Photometer were generally higher than values previously reported in the literature, which have been based largely on filter measurements. Although natural variability may account for some of these differences, an increase in the BC emission factors incorporated within emission inventories may be required, pending additional field measurements for a wider variety of fires.

Source apportionment vs. emission inventories of non-methane hydrocarbons (NMHC) in an urban area of the Middle East: local and global perspectives

NASA Astrophysics Data System (ADS)

Salameh, Thérèse; Sauvage, Stéphane; Afif, Charbel; Borbon, Agnès; Locoge, Nadine

2016-03-01

We applied the positive matrix factorization model to two large data sets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC (non-methane hydrocarbons) sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt %, respectively, in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The PMF analysis finds reasonable differences on emission rates, of 20-39 % higher than the national road transport inventory. However, global inventories (ACCMIP, EDGAR, MACCity) underestimate the emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC (volatile organic compounds) anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector.

Towards an inventory of methane emissions from manure management that is responsive to changes on Canadian farms

NASA Astrophysics Data System (ADS)

VanderZaag, A. C.; MacDonald, J. D.; Evans, L.; Vergé, X. P. C.; Desjardins, R. L.

2013-09-01

Methane emissions from manure management represent an important mitigation opportunity, yet emission quantification methods remain crude and do not contain adequate detail to capture changes in agricultural practices that may influence emissions. Using the Canadian emission inventory methodology as an example, this letter explores three key aspects for improving emission quantification: (i) obtaining emission measurements to improve and validate emission model estimates, (ii) obtaining more useful activity data, and (iii) developing a methane emission model that uses the available farm management activity data. In Canada, national surveys to collect manure management data have been inconsistent and not designed to provide quantitative data. Thus, the inventory has not been able to accurately capture changes in management systems even between manure stored as solid versus liquid. To address this, we re-analyzed four farm management surveys from the past decade and quantified the significant change in manure management which can be linked to the annual agricultural survey to create a continuous time series. In the dairy industry of one province, for example, the percentage of manure stored as liquid increased by 300% between 1991 and 2006, which greatly affects the methane emission estimates. Methane emissions are greatest from liquid manure, but vary by an order of magnitude depending on how the liquid manure is managed. Even if more complete activity data are collected on manure storage systems, default Intergovernmental Panel on Climate Change (IPCC) guidance does not adequately capture the impacts of management decisions to reflect variation among farms and regions in inventory calculations. We propose a model that stays within the IPCC framework but would be more responsive to farm management by generating a matrix of methane conversion factors (MCFs) that account for key factors known to affect methane emissions: temperature, retention time and inoculum. This MCF matrix would be populated using a mechanistic emission model verified with on-farm emission measurements. Implementation of these MCF values will require re-analysis of farm surveys to quantify liquid manure emptying frequency and timing, and will rely on the continued collection of this activity data in the future. For model development and validation, emission measurement campaigns will be needed on representative farms over at least one full year, or manure management cycle (whichever is longer). The proposed approach described in this letter is long-term, but is required to establish baseline data for emissions from manure management systems. With these improvements, the manure management emission inventory will become more responsive to the changing practices on Canadian livestock farms.

Novel method for on-road emission factor measurements using a plume capture trailer.

PubMed

Morawska, L; Ristovski, Z D; Johnson, G R; Jayaratne, E R; Mengersen, K

2007-01-15

The method outlined provides for emission factor measurements to be made for unmodified vehicles driving under real world conditions at minimal cost. The method consists of a plume capture trailer towed behind a test vehicle. The trailer collects a sample of the naturally diluted plume in a 200 L conductive bag and this is delivered immediately to a mobile laboratory for subsequent analysis of particulate and gaseous emissions. The method offers low test turnaround times with the potential to complete much larger numbers of emission factor measurements than have been possible using dynamometer testing. Samples can be collected at distances up to 3 m from the exhaust pipe allowing investigation of early dilution processes. Particle size distribution measurements, as well as particle number and mass emission factor measurements, based on naturally diluted plumes are presented. A dilution profile relating the plume dilution ratio to distance from the vehicle tail pipe for a diesel passenger vehicle is also presented. Such profiles are an essential input for new mechanistic roadway air quality 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.

Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles

NASA Astrophysics Data System (ADS)

Abu-Allaban, Mahmoud; Gillies, John A.; Gertler, Alan W.; Clayton, Russ; Proffitt, David

Intensive mass and chemical measurements were performed at roadside locations in Reno, Nevada, and Durham/Research Triangle Park), North Carolina to derive tailpipe, resuspended road dust, and brake-wear emission factors from in-use vehicles. Continuous particulate matter (PM) data were utilized to derive total emission factors while integrated PM data were used to attribute the calculated emission factors to different mechanisms using chemical mass balance receptor modeling and scanning electron microscopy techniques. Resuspended road dust and tailpipe emissions were found to be the dominant mechanisms that contribute significantly to the total PM 10 and PM 2.5 emission factors, respectively. Small contributions from brake-wear were observed at locations where strong braking occurs, but no tire-wear was seen at any sampling location. PM 10 emission rates from light-duty spark ignition (LDSI) vehicles ranged from 40 to 780 mg/km, 10 to 70 mg/km, and 0 to 80 mg/km per vehicle for road dust, tailpipe, and brake-wear, respectively. PM 10 emission rates from heavy-duty vehicles ranged from 230 to 7800 mg/km, 60 to 570 mg/km, and 0 to 610 mg/km per vehicle for road dust, tailpipe, and brake-wear, respectively. PM 2.5 emission rates from LDSI vehicles ranged from 2 to 25 mg/km, 10 to 50 mg/km, and 0 to 5 mg/km per vehicle for road dust, tailpipe, and brake-wear, respectively. PM 2.5 emission rates from heavy-duty vehicles ranged from 15 to 300 mg/km, 60 to 480 mg/km, and 0 to 15 mg/km per vehicle for road dust, tailpipe, and brake-wear, respectively.

Mechanistic modeling of thermo-hydrological processes and microbial interactions at pore to profile scales resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-04-01

The sensitivity of the Earth's polar regions to raising global temperatures is reflected in rapidly changing hydrological processes with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and the stimulation of other soil-borne GHG emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and a host of other environmental factors. Soil structural elements such as aggregates and layering and hydration status affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hotspots or hot-layers). We developed a mechanistic individual based model to quantify microbial activity dynamics within soil pore networks considering, hydration, temperature, transport processes and enzymatic activity associated with methane production in soil. The model was the upscaled from single aggregates (or hotspots) to quantifying emissions from soil profiles in which freezing/thawing processes provide macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged parts of the profile) for resolving methane production and oxidation rates. Methane transport pathways through soil by diffusion and ebullition of bubbles vary with hydration dynamics and affect emission patterns. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability, enzyme activity, PH) on long term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Evaluating the Bulk Lorentz Factors of Outflow Material: Lessons Learned from the Extremely Energetic Outburst GRB 160625B

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

Wang, Yuan-Zhu; Wang, Hao; Zhang, Shuai

2017-02-10

GRB 160625B is an extremely bright outburst with well-monitored afterglow emission. The geometry-corrected energy is high, up to ∼5.2 × 10{sup 52} erg or even ∼8 × 10{sup 52} erg, rendering it the most energetic GRB prompt emission recorded so far. We analyzed the time-resolved spectra of the prompt emission and found that in some intervals there were likely thermal-radiation components and the high energy emission was characterized by significant cutoff. The bulk Lorentz factors of the outflow material are estimated accordingly. We found out that the Lorentz factors derived in the thermal-radiation model are consistent with the luminosity-Lorentz factormore » correlation found in other bursts, as well as in GRB 090902B for the time-resolved thermal-radiation components, while the spectral cutoff model yields much lower Lorentz factors that are in tension with the constraints set by the electron pair Compton scattering process. We then suggest that these spectral cutoffs are more likely related to the particle acceleration process and that one should be careful in estimating the Lorentz factors if the spectrum cuts at a rather low energy (e.g., ∼tens of MeV). The nature of the central engine has also been discussed, and a stellar-mass black hole is favored.« less

Application of positive matrix factorization to on-road measurements for source apportionment of diesel- and gasoline-powered vehicle emissions in Mexico City

NASA Astrophysics Data System (ADS)

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

2010-04-01

The goal of this research is to quantify diesel- and gasoline-powered motor vehicle emissions within the Mexico City Metropolitan Area (MCMA) using on-road measurements captured by a mobile laboratory combined with positive matrix factorization (PMF) receptor modeling. During the MCMA-2006 ground-based component of the MILAGRO field campaign, the Aerodyne Mobile Laboratory (AML) measured many gaseous and particulate pollutants, including carbon dioxide, carbon monoxide (CO), nitrogen oxides (NOx), benzene, toluene, alkylated aromatics, formaldehyde, acetaldehyde, acetone, ammonia, particle number, fine particulate mass (PM2.5), and black carbon (BC). These serve as inputs to the receptor model, which is able to resolve three factors corresponding to gasoline engine exhaust, diesel engine exhaust, and the urban background. Using the source profiles, we calculate fuel-based emission factors for each type of exhaust. The MCMA's gasoline-powered vehicles are considerably dirtier, on average, than those in the US with respect to CO and aldehydes. Its diesel-powered vehicles have similar emission factors of NOx and higher emission factors of aldehydes, particle number, and BC. In the fleet sampled during AML driving, gasoline-powered vehicles are found to be responsible for 97% of total vehicular emissions of CO, 22% of NOx, 95-97% of each aromatic species, 72-85% of each carbonyl species, 74% of ammonia, negligible amounts of particle number, 26% of PM2.5, and 2% of BC; diesel-powered vehicles account for the balance. Because the mobile lab spent 17% of its time waiting at stoplights, the results may overemphasize idling conditions, possibly resulting in an underestimate of NOx and overestimate of CO emissions. On the other hand, estimates of the inventory that do not correctly account for emissions during idling are likely to produce bias in the opposite direction.The resulting fuel-based estimates of emissions are lower than in the official inventory for CO and NOx and higher for VOCs. For NOx, the fuel-based estimates are lower for gasoline-powered vehicles but higher for diesel-powered ones compared to the official inventory. While conclusions regarding the inventory should be interpreted with care because of the small sample size, 3.5 h of driving, the discrepancies with the official inventory agree with those reported in other studies.

Making fate and exposure models for freshwater ecotoxicity in life cycle assessment suitable for organic acids and bases.

PubMed

van Zelm, Rosalie; Stam, Gea; Huijbregts, Mark A J; van de Meent, Dik

2013-01-01

Freshwater fate and exposure factors were determined for organic acids and bases, making use of the knowledge on electrical interaction of ionizing chemicals and their sorption to particles. The fate factor represents the residence time in the environment whereas exposure factors equal the dissolved fraction of a chemical. Multimedia fate, exposure, and effect model USES-LCA was updated to take into account the influence of ionization, based upon the acid dissociation constant (pK(a)) of a chemical, and the environmental pH. Freshwater fate (FF) and exposure (XF) factors were determined for 415 acids and 496 bases emitted to freshwater, air, and soil. The relevance of taking account of the degree of ionization of chemicals was tested by determining the ratio (R) of the new vs. fate and exposure factors determined with USES-LCA suitable for neutral chemicals only. Our results show that the majority of freshwater fate and exposure factors of chemicals that are largely ionized in the environment are larger with the ionics model compared to the factors determined with the neutrals model version. R(FF) ranged from 2.4×10(-1) to 1.6×10(1) for freshwater emissions, from 1.2×10(-2) to 2.0×10(4) for soil emissions and from 5.8×10(-2) to 6.0×10(3) for air emissions, and R(XF) from 5.3×10(-1) to 2.2×10(1). Prediction of changed solid-water partitioning, implying a change in runoff and in removal via sedimentation, and prediction of negligible air-water partition coefficient, leading to negligible volatilization were the main contributors to the changes in freshwater fate factors. Copyright © 2012 Elsevier Ltd. All rights reserved.

A prescribed fire emission factors database for land management and air quality applications

Treesearch

E. Lincoln; WeiMin Hao; S. Baker; R. J. Yokelson; I. R. Burling; Shawn Urbanski; W. Miller; D. R. Weise; T. J. Johnson

2010-01-01

Prescribed fire is a significant emissions source in the U.S. and that needs to be adequately characterized in atmospheric transport/chemistry models. In addition, the Clean Air Act, its amendments, and air quality regulations require that prescribed fire managers estimate the quantity of emissions that a prescribed fire will produce. Several published papers contain a...

Comparison of biomass burning inventories processed by GEOS-Chem and ACCESS2.0 with total column and satellite data in Australia.

NASA Astrophysics Data System (ADS)

Desservettaz, M.; Fisher, J. A.; Jones, N. B.; Bukosa, B.; Greenslade, J.; Luhar, A.; Woodhouse, M.; Griffith, D. W. T.; Velazco, V. A.

2016-12-01

Australia contributes approximately 6% of global biomass burning CO2 emissions, mostly from savanna type fires. This estimate comes from biomass burning inventories that use emission factors derived from field campaigns performed outside Australia. The relevance of these emission factors to the Australian environment has not previously been evaluated and therefore needs to be tested. Here we compare predictions from the chemical transport model GEOS-Chem and the global chemistry-climate model ACCESS-UKCA run using different biomass burning inventories to total column measurements of CO, C2H6 and HCHO, in order to identify the most representative inventory for Australian fire emissions. The measurements come from the Network for Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) solar remote sensing Fourier transform spectrometers and satellite measurements from IASI and OMI over Australia. We evaluate three inventories: the Global Fire Emission Database version 4 - GFED4 (Giglio et al. 2013), the Fire Inventory from NCAR - FINN (Wiedinmyer et al. 2011), the Quick Fire Emission Database - QFED from NASA and the MACCity emission inventory (from the MACC/CityZEN EU projects; Angiola et al. 2010). From this evaluation we aim to give recommendations for the most appropriate inventory to use for different Australian environments. We also plan to examine any significant concentration variations arising from the differences between the two model setups.

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.

The National Emissions Inventory Significantly Overestimates NOx Emissions: Analysis of CMAQ and in situ observations from DISCOVER-AQ

NASA Astrophysics Data System (ADS)

Anderson, D. C.; Dickerson, R. R.; Loughner, C.

2013-12-01

NOx and CO not only adversely impact human health, but they, along with associated VOCs, are also important precursors for O3 formation. While ambient NOx and CO concentrations have decreased dramatically over the past 10-20 years, O3 has remained a more recalcitrant problem, particularly in the Baltimore/Washington region. Reduction of O3 production requires that emissions inventories, such as the National Emissions Inventory (NEI), accurately capture total emissions of CO and NOx while also correctly apportioning them among different sectors. Previous evaluations of the NEI paint different pictures of its accuracy, with assertions that it overestimates either one or both of CO and NOx from anywhere between 25 percent to a factor of 2. These conflicting claims warrant further investigation. In this study, measurements of NOx and CO taken aboard the NOAA P3B airplane during the 2011 DISCOVER-AQ field campaign were used to determine the NOx/CO emissions ratio at 6 locations in the Washington/Baltimore region. An average molar emissions ratio of 12.8 × 1.2 CO/NOx was found by calculating the change in CO over the change in NOx from vertical concentration profiles in the planetary boundary layer. Ratios showed little variation with location. Observed values were approximately a factor of 1.35 - 1.75 times greater than that predicted by the annual, countywide emissions ratio from the 2008 NEI. When compared to a temporalized, gridded version of the inventory processed by SMOKE, ratio observations were greater than that predicted by inventories by up to a factor of 2. Comparison of the in situ measurements and remotely sensed observations from MOPITT of CO to the Community Multiscale Air Quality (CMAQ) model agree within 10-35 percent, with the model higher on average. Measurements of NOy by two separate analytical techniques, on the other hand, show that CMAQ consistently and significantly overestimates NOy concentrations. Combined with the CO observations, this indicates that the NEI overestimates NOx emissions by approximately a factor of 2. Comparison of the temporalized NEI to continuous monitoring of NOx emissions from point sources shows that, on average, agreement between observations and the NEI were within 5 percent. In a region where the NEI estimates on-road emissions can account for 50-75 percent of total NOx, the most likely source of error in the NOx inventory is in the on-road sector. Assumptions about the lifetime and efficacy of catalytic converters in the MOVES model should be investigated as a possible source of this error.

Carbon loss and greenhouse gas emission from extreme fire events occurred in Sardinia, Italy

NASA Astrophysics Data System (ADS)

Bacciu, V. M.; Salis, M.; Pellizzaro, G.; Arca, B.; Duce, P.; Spano, D.

2011-12-01

It is widely recognized that biomass burning is a significant driver of CO2 cycling and a source of greenhouse gases, aerosol particles, and other chemically reactive atmospheric gases. The large amounts of carbon that fires release into the atmosphere could approach levels of anthropogenic carbon emissions, especially in years of extreme fire activity. CO2 emissions from 2007 forest fires in Greece were in the range of 4.5 Mt, representing about the 4% of the total annual CO2 emissions of that country (http://effis.jrc.it/). Barbosa et al. (2006) reported a similar percentage of fire emissions to total emissions of CO2 in Portugal during the extreme fire seasons of 2003 and 2005. Currently, inventory methods for biomass burning emission use the equation first proposed by Seiler and Crutzen (1980), taking into account the area burned, the amount of biomass burned, and the emission factors associated with each specific chemical species. However, several errors and uncertainties can affect the emission assessment, due to the estimate consistency of the various parameters involved in the equation, including flaming and smoldering combustion periods, appropriate fuel load evaluations and gaseous emission factors for different fuel fractions and fire types. In this context, model approaching can contribute to better appraise fuel consumption and the resultant emissions. In addition, more comprehensive and accurate data inputs would be of valuable help for predicting and quantifying the source and the composition of fire emissions. The purpose of this work is to explore the impacts of extreme fire events occurred in Sardinia Island (Italy) using an integrated approach combining modelling fire emissions, field observations and remotely-sensed data. In order to achieve realistic fire emission estimates, we used the FOFEM model, due to the necessity to use a consistent modeling methodology across source categories, the input required, and its ability to estimate flaming and smoldering emissions. FOFEM input fuel load data were surveyed to represent those combusted, and fuel availability was obtained from supervised classification of remotely-sensed images. Data relative to fire perimeters, fire weather data, and fire behaviour were gathered by the Sardinian Forestry Corps (CFVA). Consumptions and emissions for each fuel types were estimated through FOFEM. Finally, all the data were assembled into a Geographical Information System (GIS) to facilitate manipulation and display of the data. The results showed the crucial role of appropriate fuel, fire, and weather data and maps to attain reasonable simulations of fuel consumption and smoke emissions. Carbon emission estimates are sensitive to pre-fire fuel loads, so the method used to establish initial fuel conditions is crucial. The FOFEM outputs and the derived smoke emission maps are useful for several applications including emissions inventories, air quality management plans, and emission source models coupled with dispersion models and decision support systems.

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods.

PubMed

Sofowote, Uwayemi M; McCarry, Brian E; Marvin, Christopher H

2008-08-15

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.

Building a Multivariable Linear Regression Model of On-road Traffic for Creation of High Resolution Emission Inventories

NASA Astrophysics Data System (ADS)

Powell, James Eckhardt

Emissions inventories are an important tool, often built by governments, and used to manage emissions. To build an inventory of urban CO2 emissions and other fossil fuel combustion products in the urban atmosphere, an inventory of on-road traffic is required. In particular, a high resolution inventory is necessary to capture the local characteristics of transport emissions. These emissions vary widely due to the local nature of the fleet, fuel, and roads. Here we show a new model of ADT for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 7,767 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway traffic count data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. An EPA-supplied emissions factor was used to estimate transportation CO2 emissions, which is compared to several other estimates for the city's CO2 footprint.

Global emission of black carbon from motor vehicles from 1960 to 2006.

PubMed

Wang, Rong; Tao, Shu; Shen, Huizhong; Wang, Xilong; Li, Bengang; Shen, Guofeng; Wang, Bin; Li, Wei; Liu, Xiaopeng; Huang, Ye; Zhang, Yanyan; Lu, Yan; Ouyang, Huiling

2012-01-17

Black carbon (BC) is a key short-lived climate change forcer. Motor vehicles are important sources of BC in the environment. BC emission factors (EF(BC)), defined as BC emitted per mass of fuel consumed, are critical in the development of BC emission inventories for motor vehicles. However, measured EF(BC) for motor vehicles vary in orders of magnitude, which is one of the major sources of uncertainty in the estimation of emissions. In this study, the main factors affecting EF(BC) for motor vehicles were investigated based on 385 measured EF(BC) collected from the literature. It was found that EF(BC) for motor vehicles of a given year in a particular country can be predicted using gross domestic product per capita (GDP(c)), temperature, and the year a country's GDP(c) reached 3000 USD (Y(3000)). GDP(c) represents technical progress in terms of emission control, while Y(3000) suggest the technical transfer from developed to developing countries. For global BC emission calculations, 87 and 64% of the variation can be eliminated for diesel and gasoline vehicles by using this model. In addition to a reduction in uncertainty, the model can be used to develop a global on-road vehicle BC emission inventory with spatial and temporal resolution.

Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion

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

Mena, Francisco; Bond, Tami C.; Riemer, Nicole

Residential biofuel combustion is an important source of aerosols and gases in the atmosphere. The change in cloud characteristics due to biofuel burning aerosols is uncertain, in part, due to the uncertainty in the added number of cloud condensation nuclei (CCN) from biofuel burning. We provide estimates of the CCN activity of biofuel burning aerosols by explicitly modeling plume dynamics (coagulation, condensation, chemical reactions, and dilution) in a young biofuel burning plume from emission until plume exit, defined here as the condition when the plume reaches ambient temperature and specific humidity through entrainment. We found that aerosol-scale dynamics affect CCNmore » activity only during the first few seconds of evolution, after which the CCN efficiency reaches a constant value. Homogenizing factors in a plume are co-emission of semi-volatile organic compounds (SVOCs) or emission at small particle sizes; SVOC co-emission can be the main factor determining plume-exit CCN for hydrophobic or small particles. Coagulation limits emission of CCN to about 10 16 per kilogram of fuel. Depending on emission factor, particle size, and composition, some of these particles may not activate at low supersaturation ( s sat). Hygroscopic Aitken-mode particles can contribute to CCN through self-coagulation but have a small effect on the CCN activity of accumulation-mode particles, regardless of composition differences. Simple models (monodisperse coagulation and average hygroscopicity) can be used to estimate plume-exit CCN within about 20 % if particles are unimodal and have homogeneous composition, or when particles are emitted in the Aitken mode even if they are not homogeneous. On the other hand, if externally mixed particles are emitted in the accumulation mode without SVOCs, an average hygroscopicity overestimates emitted CCN by up to a factor of 2. This work has identified conditions under which particle populations become more homogeneous during plume processes. This homogenizing effect requires the components to be truly co-emitted, rather than sequentially emitted.« less

Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion

NASA Astrophysics Data System (ADS)

Mena, Francisco; Bond, Tami C.; Riemer, Nicole

2017-08-01

Residential biofuel combustion is an important source of aerosols and gases in the atmosphere. The change in cloud characteristics due to biofuel burning aerosols is uncertain, in part, due to the uncertainty in the added number of cloud condensation nuclei (CCN) from biofuel burning. We provide estimates of the CCN activity of biofuel burning aerosols by explicitly modeling plume dynamics (coagulation, condensation, chemical reactions, and dilution) in a young biofuel burning plume from emission until plume exit, defined here as the condition when the plume reaches ambient temperature and specific humidity through entrainment. We found that aerosol-scale dynamics affect CCN activity only during the first few seconds of evolution, after which the CCN efficiency reaches a constant value. Homogenizing factors in a plume are co-emission of semi-volatile organic compounds (SVOCs) or emission at small particle sizes; SVOC co-emission can be the main factor determining plume-exit CCN for hydrophobic or small particles. Coagulation limits emission of CCN to about 1016 per kilogram of fuel. Depending on emission factor, particle size, and composition, some of these particles may not activate at low supersaturation (ssat). Hygroscopic Aitken-mode particles can contribute to CCN through self-coagulation but have a small effect on the CCN activity of accumulation-mode particles, regardless of composition differences. Simple models (monodisperse coagulation and average hygroscopicity) can be used to estimate plume-exit CCN within about 20 % if particles are unimodal and have homogeneous composition, or when particles are emitted in the Aitken mode even if they are not homogeneous. On the other hand, if externally mixed particles are emitted in the accumulation mode without SVOCs, an average hygroscopicity overestimates emitted CCN by up to a factor of 2. This work has identified conditions under which particle populations become more homogeneous during plume processes. This homogenizing effect requires the components to be truly co-emitted, rather than sequentially emitted.

Plume-exit modeling to determine cloud condensation nuclei activity of aerosols from residential biofuel combustion

DOE PAGES

Mena, Francisco; Bond, Tami C.; Riemer, Nicole

2017-08-07

Residential biofuel combustion is an important source of aerosols and gases in the atmosphere. The change in cloud characteristics due to biofuel burning aerosols is uncertain, in part, due to the uncertainty in the added number of cloud condensation nuclei (CCN) from biofuel burning. We provide estimates of the CCN activity of biofuel burning aerosols by explicitly modeling plume dynamics (coagulation, condensation, chemical reactions, and dilution) in a young biofuel burning plume from emission until plume exit, defined here as the condition when the plume reaches ambient temperature and specific humidity through entrainment. We found that aerosol-scale dynamics affect CCNmore » activity only during the first few seconds of evolution, after which the CCN efficiency reaches a constant value. Homogenizing factors in a plume are co-emission of semi-volatile organic compounds (SVOCs) or emission at small particle sizes; SVOC co-emission can be the main factor determining plume-exit CCN for hydrophobic or small particles. Coagulation limits emission of CCN to about 10 16 per kilogram of fuel. Depending on emission factor, particle size, and composition, some of these particles may not activate at low supersaturation ( s sat). Hygroscopic Aitken-mode particles can contribute to CCN through self-coagulation but have a small effect on the CCN activity of accumulation-mode particles, regardless of composition differences. Simple models (monodisperse coagulation and average hygroscopicity) can be used to estimate plume-exit CCN within about 20 % if particles are unimodal and have homogeneous composition, or when particles are emitted in the Aitken mode even if they are not homogeneous. On the other hand, if externally mixed particles are emitted in the accumulation mode without SVOCs, an average hygroscopicity overestimates emitted CCN by up to a factor of 2. This work has identified conditions under which particle populations become more homogeneous during plume processes. This homogenizing effect requires the components to be truly co-emitted, rather than sequentially emitted.« less

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.

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.

Identification of the driving factors' influences on regional energy-related carbon emissions in China based on geographical detector method.

PubMed

Zhang, Xinlin; Zhao, Yuan

2018-04-01

To investigate the influences of different factors on spatial heterogeneity of regional carbon emissions, we firstly studied the spatial-temporal dynamics of regional energy-related carbon emissions using global Moran's I and Getis-Ord Gi and applied geographical detector model to explain the spatial heterogeneity of regional carbon emissions. Some conclusions were drawn. Regional carbon emissions showed significant global and local spatial autocorrelation. The carbon emissions were greater in eastern and northern regions than in western and southern regions. Fixed assets investment and economic output had been the main contributing factors over the study period, and economic output had been decreasing its influence. Industrial structure's influence showed a decrease trend and became smaller in 2015. The results of the interaction detections in 2015 can be divided into two types: enhance and nonlinear, and enhance and bivariate. The interactive influences between technological level and fixed assets investment, economic output and technological level, population size and technological level, and economic output and economic development were greater than others. Some policy recommendations were proposed.

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.

The Impact of a Potential Shale Gas Development in Germany and the United Kingdom on Pollutant and Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Weger, L.; Cremonese, L.; Bartels, M. P.; Butler, T. M.

2016-12-01

Several European countries with domestic shale gas reserves are considering extracting this natural gas resource to complement their energy transition agenda. Natural gas, which produces lower CO2 emissions upon combustion compared to coal or oil, has the potential to serve as a bridge in the transition from fossil fuels to renewables. However, the generation of shale gas leads to emissions of CH4 and pollutants such as PM, NOx and VOCs, which in turn impact climate as well as local and regional air quality. In this study, we explore the impact of a potential shale gas development in Europe, specifically in Germany and the United Kingdom, on emissions of greenhouse gases and pollutants. In order to investigate the effect on emissions, we first estimate a range of wells drilled per year and production volume for the two countries under examination based on available geological information and on regional infrastructural and economic limitations. Subsequently we assign activity data and emissions factors to the well development, gas production and processing stages of shale gas generation to enable emissions quantification. We then define emissions scenarios to explore different storylines of potential shale gas development, including low emissions (high level of regulation), high emissions (low level of regulation) and middle emissions scenarios, which influence fleet make-up, emission factor and activity data choices for emissions quantification. The aim of this work is to highlight important variables and their ranges, to promote discussion and communication of potential impacts, and to construct possible visions for a future shale gas development in the two study countries. In a follow-up study, the impact of pollutant emissions from these scenarios on air quality will be explored using the Weather Research and Forecasting model with chemistry (WRF-Chem) model.

Impact of traffic intensity and pavement aggregate size on road dust particles loading

NASA Astrophysics Data System (ADS)

Amato, F.; Pandolfi, M.; Alastuey, A.; Lozano, A.; Contreras González, J.; Querol, X.

2013-10-01

Road dust emissions severely hamper PM10 urban air quality and their burden is expected to increase relatively to primary motor exhaust emissions. Beside the large influence of climate and meteorology, the emission potential varies widely also from one road to another due to numerous factors such as traffic conditions, pavement type and external sources. Nevertheless none of these factors is sufficiently known for a reliable description in emission modelling and for decision making in air quality management. In this study we carried out intensive road dust measurement campaigns in South Spain, with the aim of investigating the relationship between emission potential (i.e. road dust load) and traffic intensity, pavement aggregate size and distance from braking zones. Results indicate that, while no impact from braking activity can be drawn on the bulk road dust mass, an increase in traffic intensity or mean pavement aggregate size clearly reduce the single vehicle emission potential.

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

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

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

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.

Impact of increased vehicle emissions on the ozone concentrations around beach areas in summer using air quality modeling system

NASA Astrophysics Data System (ADS)

Song, S.; Kim, Y.; Shon, Z.; Kang, Y.; Jeong, J.

2012-12-01

The impact of pollutant emissions by the huge amount of road traffic around beaches on the ozone (O3) concentrations in the surrounding regions were evaluated using a numerical modeling approach during the beach opening period (BOP) (July to August). This analysis was performed based on two simulation conditions: 1) with mobile emissions during the BOP (i.e. BOP case); and 2) during the normal period (i.e. NOR case). On-road mobile emissions were estimated from the emission factors, vehicle kilometers traveled, and deterioration factors at several roads close to beaches in Busan, Korea during a 4-day observation period (29 and 31 July and 1 and 3 August) of the BOP in 2010. The emission data was then applied to the 3-D chemical transport model (i.e. the WRF-CMAQ modeling system). A process analysis (PA) was also used to assess the contributions of the individual physical and chemical processes to the production or loss of O3 in the study area. The model study suggested the possibility that road traffic emissions near the beach area can have a direct impact on the O3 concentrations in the source regions as well as their surrounding/downwind regions. The maximum negative impact of mobile emissions on the O3 concentrations between the BOP and NOR cases was predicted near the beach areas: by -4 ppb during the day due to the high NOx emissions with the high NOx/VOC ratio and -8 ppb during the late evening due to the fast titration of O3 by NO. The PA showed that the rate of O3 destruction due to the road traffic emissions around the beach areas decreased by -2.3 (weekend, 31 July) and -5.5 ppb h-1 (weekday, 3 August) during the day. Acknowledgments: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant CATER_2012-6140. This work was also funded by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0021141).

Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models

NASA Astrophysics Data System (ADS)

Heo, Jongbae; Dulger, Muaz; Olson, Michael R.; McGinnis, Jerome E.; Shelton, Brandon R.; Matsunaga, Aiko; Sioutas, Constantinos; Schauer, James J.

2013-07-01

Four hundred fine particulate matter (PM2.5) samples collected over a 1-year period at two sites in the Los Angeles Basin were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and organic molecular markers. The results were used in a Positive Matrix Factorization (PMF) receptor model to obtain daily, monthly and annual average source contributions to PM2.5 OC. Results of the PMF model showed similar source categories with comparable year-long contributions to PM2.5 OC across the sites. Five source categories providing reasonably stable profiles were identified: mobile, wood smoke, primary biogenic, and two types of secondary organic carbon (SOC) (i.e., anthropogenic and biogenic emissions). Total primary emission factors and total SOC factors contributed approximately 60% and 40%, respectively, to the annual-average OC concentrations. Primary sources showed strong seasonal patterns with high winter peaks and low summer peaks, while SOC showed a reverse pattern with highs in the spring and summer in the region. Interestingly, smoke from forest fires which occurred episodically in California during the summer and fall of 2009 was identified and combined with the primary biogenic source as one distinct factor to the OC budget. The PMF resolved factors were further investigated and compared to a chemical mass balance (CMB) model and a second multi-variant receptor model (UNMIX) using molecular markers considered in the PMF. Good agreement between the source contribution from mobile sources and biomass burning for three models were obtained, providing additional weight of evidence that these source apportionment techniques are sufficiently accurate for policy development. However, the CMB model did not quantify primary biogenic emissions, which were included in other sources with the SOC. Both multivariate receptor models, the PMF and the UNMIX, were unable to separate source contributions from diesel and gasoline engines.

Soil pH as the chief modifier for regional nitrous oxide emissions: New evidence and implications for global estimates and mitigation.

PubMed

Wang, Yajing; Guo, Jingheng; Vogt, Rolf David; Mulder, Jan; Wang, Jingguo; Zhang, Xiaoshan

2018-02-01

Nitrous oxide (N 2 O) is a greenhouse gas that also plays the primary role in stratospheric ozone depletion. The use of nitrogen fertilizers is known as the major reason for atmospheric N 2 O increase. Empirical bottom-up models therefore estimate agricultural N 2 O inventories using N loading as the sole predictor, disregarding the regional heterogeneities in soil inherent response to external N loading. Several environmental factors have been found to influence the response in soil N 2 O emission to N fertilization, but their interdependence and relative importance have not been addressed properly. Here, we show that soil pH is the chief factor explaining regional disparities in N 2 O emission, using a global meta-analysis of 1,104 field measurements. The emission factor (EF) of N 2 O increases significantly (p < .001) with soil pH decrease. The default EF value of 1.0%, according to IPCC (Intergovernmental Panel on Climate Change) for agricultural soils, occurs at soil pH 6.76. Moreover, changes in EF with N fertilization (i.e. ΔEF) is also negatively correlated (p < .001) with soil pH. This indicates that N 2 O emission in acidic soils is more sensitive to changing N fertilization than that in alkaline soils. Incorporating our findings into bottom-up models has significant consequences for regional and global N 2 O emission inventories and reconciling them with those from top-down models. Moreover, our results allow region-specific development of tailor-made N 2 O mitigation measures in agriculture. © 2017 John Wiley & Sons Ltd.

An inventory of nitrous oxide emissions from agriculture in the UK using the IPCC methodology: emission estimate, uncertainty and sensitivity analysis

NASA Astrophysics Data System (ADS)

Brown, L.; Armstrong Brown, S.; Jarvis, S. C.; Syed, B.; Goulding, K. W. T.; Phillips, V. R.; Sneath, R. W.; Pain, B. F.

Nitrous oxide emission from UK agriculture was estimated, using the IPCC default values of all emission factors and parameters, to be 87 Gg N 2O-N in both 1990 and 1995. This estimate was shown, however, to have an overall uncertainty of 62%. The largest component of the emission (54%) was from the direct (soil) sector. Two of the three emission factors applied within the soil sector, EF1 (direct emission from soil) and EF3 PRP (emission from pasture range and paddock) were amongst the most influential on the total estimate, producing a ±31 and +11% to -17% change in emissions, respectively, when varied through the IPCC range from the default value. The indirect sector (from leached N and deposited ammonia) contributed 29% of the total emission, and had the largest uncertainty (126%). The factors determining the fraction of N leached (Frac LEACH) and emissions from it (EF5), were the two most influential. These parameters are poorly specified and there is great potential to improve the emission estimate for this component. Use of mathematical models (NCYCLE and SUNDIAL) to predict Frac LEACH suggested that the IPCC default value for this parameter may be too high for most situations in the UK. Comparison with other UK-derived inventories suggests that the IPCC methodology may overestimate emission. Although the IPCC approach includes additional components to the other inventories (most notably emission from indirect sources), estimates for the common components (i.e. fertiliser and animals), and emission factors used, are higher than those of other inventories. Whilst it is recognised that the IPCC approach is generalised in order to allow widespread applicability, sufficient data are available to specify at least two of the most influential parameters, i.e. EF1 and Frac LEACH, more accurately, and so provide an improved estimate of nitrous oxide emissions from UK agriculture.

Exploring the impact of determining factors behind CO2 emissions in China: A CGE appraisal.

PubMed

Xiao, Bowen; Niu, Dongxiao; Wu, Han

2017-03-01

Along with the arrival of the post-Kyoto Protocol era, the Chinese government faces ever greater pressure to reduce greenhouse gases (GHGs). Hence, this paper aims to discuss the drivers of carbon dioxide (CO 2 ) emissions and their impact on society as a whole. First, we analyzed the background and overall situations of CO 2 emissions in China. Then, we reviewed previous studies to explore the determinants behind China's CO 2 emissions. It is widely acknowledged that energy efficiency, energy mix, and economy structure are three key factors contributing to CO 2 emissions. To explore the impacts of those three factors on the economy and CO 2 emissions, we established a computable general equilibrium (CGE) model. The following results were found: (1) The decline of a secondary industry can cause an emission reduction effect, but this is at the expense of the gross domestic product (GDP), whereas the development of a tertiary industry can boost the economy and help to reduce CO 2 emissions. (2) Cutting coal consumption can contribute significantly to emission reduction, which is accompanied by a great loss in the whole economy. (3) Although the energy efficiency improvement plays a positive role in promoting economic development, a backfire effect can weaken the effects of emission reduction and energy savings. Copyright © 2016 Elsevier B.V. All rights reserved.

Uncertainties in global aerosols and climate effects due to biofuel emissions

NASA Astrophysics Data System (ADS)

Kodros, J. K.; Scott, C. E.; Farina, S. C.; Lee, Y. H.; L'Orange, C.; Volckens, J.; Pierce, J. R.

2015-04-01

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing-state, and model nucleation and background SOA. We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include: amount, composition, size and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (internal, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from -0.02 to +0.06 W m-2 across all simulation/mixing state combinations with regional effects in source regions ranging from -0.2 to +1.2 W m-2. The global-mean cloud-albedo aerosol indirect effect ranges from +0.01 to -0.02 W m-2 with regional effects in source regions ranging from -1.0 to -0.05 W m-2. The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse-gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on: (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.

Uncertainties in global aerosols and climate effects due to biofuel emissions

NASA Astrophysics Data System (ADS)

Kodros, J. K.; Scott, C. E.; Farina, S. C.; Lee, Y. H.; L'Orange, C.; Volckens, J.; Pierce, J. R.

2015-08-01

Aerosol emissions from biofuel combustion impact both health and climate; however, while reducing emissions through improvements to combustion technologies will improve health, the net effect on climate is largely unconstrained. In this study, we examine sensitivities in global aerosol concentration, direct radiative climate effect, and cloud-albedo aerosol indirect climate effect to uncertainties in biofuel emission factors, optical mixing state, and model nucleation and background secondary organic aerosol (SOA). We use the Goddard Earth Observing System global chemical-transport model (GEOS-Chem) with TwO Moment Aerosol Sectional (TOMAS) microphysics. The emission factors include amount, composition, size, and hygroscopicity, as well as optical mixing-state properties. We also evaluate emissions from domestic coal use, which is not biofuel but is also frequently emitted from homes. We estimate the direct radiative effect assuming different mixing states (homogeneous, core-shell, and external) with and without absorptive organic aerosol (brown carbon). We find the global-mean direct radiative effect of biofuel emissions ranges from -0.02 to +0.06 W m-2 across all simulation/mixing-state combinations with regional effects in source regions ranging from -0.2 to +0.8 W m-2. The global-mean cloud-albedo aerosol indirect effect (AIE) ranges from +0.01 to -0.02 W m-2 with regional effects in source regions ranging from -1.0 to -0.05 W m-2. The direct radiative effect is strongly dependent on uncertainties in emissions mass, composition, emissions aerosol size distributions, and assumed optical mixing state, while the indirect effect is dependent on the emissions mass, emissions aerosol size distribution, and the choice of model nucleation and secondary organic aerosol schemes. The sign and magnitude of these effects have a strong regional dependence. We conclude that the climate effects of biofuel aerosols are largely unconstrained, and the overall sign of the aerosol effects is unclear due to uncertainties in model inputs. This uncertainty limits our ability to introduce mitigation strategies aimed at reducing biofuel black carbon emissions in order to counter warming effects from greenhouse gases. To better understand the climate impact of particle emissions from biofuel combustion, we recommend field/laboratory measurements to narrow constraints on (1) emissions mass, (2) emission size distribution, (3) mixing state, and (4) ratio of black carbon to organic aerosol.

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.

Gridded anthropogenic emissions inventory and atmospheric transport of carbonyl sulfide in the U.S.

NASA Astrophysics Data System (ADS)

Zumkehr, Andrew; Hilton, Timothy W.; Whelan, Mary; Smith, Steve; Campbell, J. Elliott

2017-02-01

Carbonyl sulfide (COS or OCS), the most abundant sulfur-containing gas in the troposphere, has recently emerged as a potentially important atmospheric tracer for the carbon cycle. Atmospheric inverse modeling studies may be able to use existing tower, airborne, and satellite observations of COS to infer information about photosynthesis. However, such analysis relies on gridded anthropogenic COS source estimates that are largely based on industry activity data from over three decades ago. Here we use updated emission factor data and industry activity data to develop a gridded inventory with a 0.1° resolution for the U.S. domain. The inventory includes the primary anthropogenic COS sources including direct emissions from the coal and aluminum industries as well as indirect sources from industrial carbon disulfide emissions. Compared to the previously published inventory, we found that the total anthropogenic source (direct and indirect) is 47% smaller. Using this new gridded inventory to drive the Sulfur Transport and Deposition Model/Weather Research and Forecasting atmospheric transport model, we found that the anthropogenic contribution to COS variation in the troposphere is small relative to the biosphere influence, which is encouraging for carbon cycle applications in this region. Additional anthropogenic sectors with highly uncertain emission factors require further field measurements.

Measurement and prediction of enteric methane emission

NASA Astrophysics Data System (ADS)

Sejian, Veerasamy; Lal, Rattan; Lakritz, Jeffrey; Ezeji, Thaddeus

2011-01-01

The greenhouse gas (GHG) emissions from the agricultural sector account for about 25.5% of total global anthropogenic emission. While CO2 receives the most attention as a factor relative to global warming, CH4, N2O and chlorofluorocarbons (CFCs) also cause significant radiative forcing. With the relative global warming potential of 25 compared with CO2, CH4 is one of the most important GHGs. This article reviews the prediction models, estimation methodology and strategies for reducing enteric CH4 emissions. Emission of CH4 in ruminants differs among developed and developing countries, depending on factors like animal species, breed, pH of rumen fluid, ratio of acetate:propionate, methanogen population, composition of diet and amount of concentrate fed. Among the ruminant animals, cattle contribute the most towards the greenhouse effect through methane emission followed by sheep, goats and buffalos, respectively. The estimated CH4 emission rate per cattle, buffaloe, sheep and goat in developed countries are 150.7, 137, 21.9 and 13.7 (g/animal/day) respectively. However, the estimated rates in developing countries are significantly lower at 95.9 and 13.7 (g/animal/day) per cattle and sheep, respectively. There exists a strong interest in developing new and improving the existing CH4 prediction models to identify mitigation strategies for reducing the overall CH4 emissions. A synthesis of the available literature suggests that the mechanistic models are superior to empirical models in accurately predicting the CH4 emission from dairy farms. The latest development in prediction model is the integrated farm system model which is a process-based whole-farm simulation technique. Several techniques are used to quantify enteric CH4 emissions starting from whole animal chambers to sulfur hexafluoride (SF6) tracer techniques. The latest technology developed to estimate CH4 more accurately is the micrometeorological mass difference technique. Because the conditions under which animals are managed vary greatly by country, CH4 emissions reduction strategies must be tailored to country-specific circumstances. Strategies that are cost effective, improve productivity, and have limited potential negative effects on livestock production hold a greater chance of being adopted by producers. It is also important to evaluate CH4 mitigation strategies in terms of the total GHG budget and to consider the economics of various strategies. Although reductions in GHG emissions from livestock industries are seen as high priorities, strategies for reducing emissions should not reduce the economic viability of enterprises.

Fugitive dust emissions from paved road travel in the Lake Tahoe basin.

PubMed

Zhu, Dongzi; Kuhns, Hampden D; Brown, Scott; Gillies, John A; Etyemezian, Vicken; Gertler, Alan W

2009-10-01

The clarity of water in Lake Tahoe has declined substantially over the past 40 yr. Causes of the degradation include nitrogen and phosphorous fertilization of the lake waters and increasing amounts of inorganic fine sediment that can scatter light. Atmospheric deposition is a major source of fine sediment. A year-round monitoring study of road dust emissions around the lake was completed in 2007 using the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) system developed at the Desert Research Institute (DRI). Results of this study found that, compared with the summer season, road dust emissions increased by a factor of 5 in winter, on average, and about a factor of 10 when traction control material was applied to the roads after snow events. For winter and summer, road dust emission factors (grams coarse particulate matter [PM10] per vehicle kilometer traveled [g/vkt]) showed a decreasing trend with the travel speed of the road. The highest emission factors were observed on very low traffic volume roads on the west side of the lake. These roads were composed of either a 3/8-in. gravel material or had degraded asphalt. The principle factors influencing road dust emissions in the basin are season, vehicle speed (or road type), road condition, road grade, and proximity to other high-emitting roads. Combined with a traffic volume model, an analysis of the total emissions from the road sections surveyed indicated that urban areas (in particular South Lake Tahoe) had the highest emitting roads in the basin.

Effect of temperature and humidity on formaldehyde emissions in temporary housing units.

PubMed

Parthasarathy, Srinandini; Maddalena, Randy L; Russell, Marion L; Apte, Michael G

2011-06-01

The effect of temperature and humidity on formaldehyde emissions from samples collected from temporary housing units (THUs) was studied. The THUs were supplied by the U.S. Federal Emergency Management Administration (FEMA) to families that lost their homes in Louisiana and Mississippi during the Hurricane Katrina and Rita disasters. On the basis of a previous study, four of the composite wood surface materials that dominated contributions to indoor formaldehyde were selected to analyze the effects of temperature and humidity on the emission factors. Humidity equilibration experiments were carried out on two of the samples to determine how long the samples take to equilibrate with the surrounding environmental conditions. Small chamber experiments were then conducted to measure emission factors for the four surface materials at various temperature and humidity conditions. The samples were analyzed for formaldehyde via high-performance liquid chromatography. The experiments showed that increases in temperature or humidity contributed to an increase in emission factors. A linear regression model was built using the natural log of the percent relative humidity (RH) and inverse of temperature (in K) as independent variables and the natural log of emission factors as the dependent variable. The coefficients for the inverse of temperature and log RH with log emission factor were found to be statistically significant for all of the samples at the 95% confidence level. This study should assist in retrospectively estimating indoor formaldehyde exposure of occupants of THUs.

Factor analysis of submicron particle size distributions near a major United States-Canada trade bridge.

PubMed

Ogulei, David; Hopke, Philip K; Ferro, Andrea R; Jaques, Peter A

2007-02-01

A factor analytic model has been applied to resolve and apportion particles based on submicron particle size distributions downwind of a United States-Canada bridge in Buffalo, NY. The sites chosen for this study were located at gradually increasing distances downwind of the bridge complex. Seven independent factors were resolved, including four factors that were common to all of the five sites considered. The common factors were generally characterized by the existence of two or more number and surface area modes. The seven factors resolved were identified as follows: fresh tail-pipe diesel exhaust, local/street diesel traffic, aged/evolved diesel particles, spark-ignition gasoline emissions, background urban emissions, heavy-duty diesel agglomerates, and secondary/transported material. Submicron (<0.5 microm) and ultrafine (<0.1 microm) particle emissions downwind of the bridge were dominated by commercial diesel truck emissions. Thus, this study obtained size distinction between fresh versus aged vehicle exhaust and spark-ignition versus diesel emissions based on the measured high time-resolution particle number concentrations. Because this study mainly used particles <300 nm in diameter, some sources that would usually exhibit number modes >100 nm were not resolved. Also, the resolved profiles suggested that the major number mode for fresh tailpipe diesel exhaust might exist below the detection limit of the spectrometer used. The average particle number contributions from the resolved factors were highest closest to the bridge.

Identification of biased sectors in emission data using a combination of chemical transport model and receptor model

NASA Astrophysics Data System (ADS)

Uranishi, Katsushige; Ikemori, Fumikazu; Nakatsubo, Ryohei; Shimadera, Hikari; Kondo, Akira; Kikutani, Yuki; Asano, Katsuyoshi; Sugata, Seiji

2017-10-01

This study presented a comparison approach with multiple source apportionment methods to identify which sectors of emission data have large biases. The source apportionment methods for the comparison approach included both receptor and chemical transport models, which are widely used to quantify the impacts of emission sources on fine particulate matter of less than 2.5 μm in diameter (PM2.5). We used daily chemical component concentration data in the year 2013, including data for water-soluble ions, elements, and carbonaceous species of PM2.5 at 11 sites in the Kinki-Tokai district in Japan in order to apply the Positive Matrix Factorization (PMF) model for the source apportionment. Seven PMF factors of PM2.5 were identified with the temporal and spatial variation patterns and also retained features of the sites. These factors comprised two types of secondary sulfate, road transportation, heavy oil combustion by ships, biomass burning, secondary nitrate, and soil and industrial dust, accounting for 46%, 17%, 7%, 14%, 13%, and 3% of the PM2.5, respectively. The multiple-site data enabled a comprehensive identification of the PM2.5 sources. For the same period, source contributions were estimated by air quality simulations using the Community Multiscale Air Quality model (CMAQ) with the brute-force method (BFM) for four source categories. Both models provided consistent results for the following three of the four source categories: secondary sulfates, road transportation, and heavy oil combustion sources. For these three target categories, the models' agreement was supported by the small differences and high correlations between the CMAQ/BFM- and PMF-estimated source contributions to the concentrations of PM2.5, SO42-, and EC. In contrast, contributions of the biomass burning sources apportioned by CMAQ/BFM were much lower than and little correlated with those captured by the PMF model, indicating large uncertainties in the biomass burning emissions used in the CMAQ simulations. Thus, this comparison approach using the two antithetical models enables us to identify which sectors of emission data have large biases for improvement of future air quality simulations.

An overview of particulate emissions from residential biomass combustion

NASA Astrophysics Data System (ADS)

Vicente, E. D.; Alves, C. A.

2018-01-01

Residential biomass burning has been pointed out as one of the largest sources of fine particles in the global troposphere with serious impacts on air quality, climate and human health. Quantitative estimations of the contribution of this source to the atmospheric particulate matter levels are hard to obtain, because emission factors vary greatly with wood type, combustion equipment and operating conditions. Updated information should improve not only regional and global biomass burning emission inventories, but also the input for atmospheric models. In this work, an extensive tabulation of particulate matter emission factors obtained worldwide is presented and critically evaluated. Existing quantifications and the suitability of specific organic markers to assign the input of residential biomass combustion to the ambient carbonaceous aerosol are also discussed. Based on these organic markers or other tracers, estimates of the contribution of this sector to observed particulate levels by receptor models for different regions around the world are compiled. Key areas requiring future research are highlighted and briefly discussed.

The seed factor: how a combination of four observables can unveil the location of blazar GeV emission.

NASA Astrophysics Data System (ADS)

Harvey, Adam; Georganopoulos, Markos; Meyer, Eileen

2018-01-01

We present here a method for constraining the emission location of γ-rays in powerful, lined blazars (i.e., flat spectrum radio quasars (FSRQs)). We develop a diagnostic criteria, which we term the seed factor, to differentiate between γ-ray emission due to external Compton (EC) scattering in the broad line region (BLR) and the molecular torus (MT). The seed factor is determined entirely by four observable quantities; the synchrotron and inverse Compton (IC) peak frequencies, and the respective peak luminosities. It may thus be possible to use the seed factor to constrain the emission location in a model-independent way.We also present preliminary results of our analysis regarding the seed factor in quasi-simultaneous multi-wavelength SEDs from the Fermi LAT Bright AGN Sample (LBAS), historical data from the ASDC SED Builder of FSRQs in the the Monitoring Of Jets in Active galactic nuclei with VLBA Experiments (MOJAVE) sample, and quasi-simultaneous multi-wavelength SEDs from the Dynamic SEDs of southern blazars (DSSB) sample.

Greenhouse gas contribution of municipal solid waste collection: A case study in the city of Istanbul, Turkey.

PubMed

Korkut, Nafiz E; Yaman, Cevat; Küçükağa, Yusuf; Jaunich, Megan K; Demir, İbrahim

2018-02-01

This article estimates greenhouse gas emissions and global warming factors resulting from collection of municipal solid waste to the transfer stations or landfills in Istanbul for the year of 2015. The aim of this study is to quantify and compare diesel fuel consumption and estimate the greenhouse gas emissions and global warming factors associated with municipal solid waste collection of the 39 districts of Istanbul. Each district's greenhouse gas emissions resulting from the provision and combustion of diesel fuel was estimated by considering the number of collection trips and distances to municipal solid waste facilities. The estimated greenhouse gases and global warming factors for the districts varied from 61.2 to 2759.1 t CO 2 -eq and from 4.60 to 15.20 kg CO 2 -eq t -1 , respectively. The total greenhouse gas emission was estimated as 46.4E3 t CO 2 -eq. Lastly, the collection data from the districts was used to parameterise a collection model that can be used to estimate fuel consumption associated with municipal solid waste collection. This mechanistic model can then be used to predict future fuel consumption and greenhouse gas emissions associated with municipal solid waste collection based on projected population, waste generation, and distance to transfer stations and landfills. The greenhouse gas emissions can be reduced by decreasing the trip numbers and trip distances, building more transfer stations around the city, and making sure that the collection trucks are full in each trip.

Comparison of Field Measurements to Methane Emissions ...

EPA Pesticide Factsheets

Due to both technical and economic limitations, estimates of methane emissions from landfills rely primarily on models. While models are easy to implement, there is uncertainty due to the use of parameters that are difficult to validate. The objective of this research was to compare modeled emissions using several greenhouse gas (GHG) emissions reporting protocols including: (1) Intergovernmental Panel on Climate Change (IPCC); (2) U.S. Environmental Protection Agency Greenhouse Gas Reporting Program (EPA GHGRP); (3) California Air Resources Board (CARB); (4) Solid Waste Industry for Climate Solutions (SWICS); and (5) an industry model from the Dutch waste company Afvalzorg, with measured data collected over 3 calendar years from a young landfill with no gas collection system. By working with whole landfill measurements of fugitive methane emissions and methane oxidation, the collection efficiency could be set to zero, thus eliminating one source of parameter uncertainty. The models consistently overestimated annual methane emissions by a factor ranging from 4 – 32.Varying input parameters over reasonable ranges reduced this range to 1.3 - 8. Waste age at the studied landfill was less than four years and the results suggest the need for measurements at additional landfills to evaluate the accuracy of the tested models to young landfills. This is a submission to a peer reviewed journal. The paper discusses landfill emission measurements and models for a new la

Integration of biogenic emissions in environmental fate, transport, and exposure systems

NASA Astrophysics Data System (ADS)

Efstathiou, Christos I.

Biogenic emissions make a significant contribution to the levels of aeroallergens and secondary air pollutants such as ozone. Understanding major factors contributing to allergic airway diseases requires accurate characterization of emissions and transport/transformation of biogenic emissions. However, biogenic emission estimates are laden with large uncertainties. Furthermore, the current biogenic emission estimation models use low-resolution data for estimating land use, vegetation biomass and VOC emissions. Furthermore, there are currently no established methods for estimating bioaerosol emissions over continental or regional scale, which can impact the ambient levels of pollent that have synergestic effects with other gaseous pollutants. In the first part of the thesis, an detailed review of different approaches and available databases for estimating biogenic emissions was conducted, and multiple geodatabases and satellite imagery were used in a consistent manner to improve the estimates of biogenic emissions over the continental United States. These emissions represent more realistic, higher resolution estimates of biogenic emissions (including those of highly reactive species such as isoprene). The impact of these emissions on tropospheric ozone levels was studied at a regional scale through the application of the USEPA's Community Multiscale Air Quality (CMAQ) model. Minor, but significant differences in the levels of ambient ozone were observed. In the second part of the thesis, an algorithm for estimating emissions of pollen particles from major allergenic tree and plant families in the United States was developed, extending the approach for modeling biogenic gas emissions in the Biogenic Emission Inventory System (BEIS). A spatio-temporal vegetation map was constructed from different remote sensing sources and local surveys, and was coupled with a meteorological model to develop pollen emissions rates. This model overcomes limitations posed by the lack of temporally resolved dynamic vegetation mapping in traditional pollen emission estimation methods. The pollen emissions model was applied to study the pollen emissions for North East US at 12 km resolution for comparison with ground level tree pollen data. A pollen transport model that simulates complex dispersion and deposition was developed through modifications to the USEPA's Community Multiscale Air Quality (CMAQ) model. The peak pollen emission predictions were within a day of peak pollen counts measured, thus corroborating independent model verification. Furthermore, the peak predicted pollen concentration estimates were within two days of the peak measured pollen counts, thus providing independent corroboration. The models for emissions and dispersion allow data-independent estimation of pollen levels, and provide an important component in assessing exposures of populations to pollen, especially under different climate change scenarios.

Are emissions of black carbon from gasoline vehicles underestimated? Insights from near and on-road measurements.

PubMed

Liggio, John; Gordon, Mark; Smallwood, Gregory; Li, Shao-Meng; Stroud, Craig; Staebler, Ralf; Lu, Gang; Lee, Patrick; Taylor, Brett; Brook, Jeffrey R

2012-05-01

Measurements of black carbon (BC) with a high-sensitivity laser-induced incandescence (HS-LII) instrument and a single particle soot photometer (SP2) were conducted upwind, downwind, and while driving on a highway dominated by gasoline vehicles. The results are used with concurrent CO(2) measurements to derive fuel-based BC emission factors for real-world average fleet and heavy-duty diesel vehicles separately. The derived emission factors from both instruments are compared, and a low SP2 bias (relative to the HS-LII) is found to be caused by a BC mass mode diameter less than 75 nm, that is most prominent with the gasoline fleet but is not present in the heavy-duty diesel vehicle exhaust on the highway. Results from both the LII and the SP2 demonstrate that the BC emission factors from gasoline vehicles are at least a factor of 2 higher than previous North American measurements, and a factor of 9 higher than currently used emission inventories in Canada, derived with the MOBILE 6.2C model. Conversely, the measured BC emission factor for heavy-duty diesel vehicles is in reasonable agreement with previous measurements. The results suggest that greater attention must be paid to black carbon from gasoline engines to obtain a full understanding of the impact of black carbon on air quality and climate and to devise appropriate mitigation strategies. © 2012 American Chemical Society

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.

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.

Analysis of Emission Effects Related to Drivers’ Compliance Rates for Cooperative Vehicle-Infrastructure System at Signalized Intersections

PubMed Central

Liao, Ruohua; Yu, Lei; Sun, Xiaofei

2018-01-01

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, NOx, HC, and CO emissions. CO2 was reduced most significantly, decreased by 16% and 22% with compliance rates of 0.3 and 0.7, respectively. PMID:29329214

Prompt gamma-ray emission of GRB 170817A associated to GW 170817: A consistent picture

NASA Astrophysics Data System (ADS)

Ziaeepour, Houri

2018-05-01

The short GRB 170817A associated to the first detection of gravitation waves from a Binary Neutron Star (BNS) merger was in many ways unusual. Possible explanations are emission from a cocoon or cocoon break out, off-axis view of a structured or uniform jet, and on-axis ultra-relativistic jet with reduced density and Lorentz factor. Here we use a phenomenological model of shock evolution and synchrotron/self-Compton emission to simulate the prompt emission of GRB 170817A and to test above proposals. We find that synchrotron emission from a mildly relativistic cocoon with a Lorentz factor of 2-3, as considered in the literature, generates a too soft, too long, and too bright prompt emission. Off-axis view of an structured jet with a Lorentz factor of about 10 can reproduce observations, but needs a very efficient transfer of kinetic energy to electrons in internal shocks, which is disfavored by particle in cell simulations. We also comment on cocoon breakout as a mechanism for generation of the prompt gamma-ray. A relativistic jet with a Lorentz factor of about 100 and a density lower than typical short GRBs seems to be the most plausible model and we conclude that GRB 170817A was intrinsically faint. Based on this result and findings of relativistic magnetohydrodynamics simulations of BNS merger in the literature we discuss physical and astronomical conditions, which may lead to such faint short GRBs. We identify small mass difference of progenitor neutron stars, their old age and reduced magnetic field, and anti-alignment of spin-orbit angular momentum induced by environmental gravitational disturbances during the lifetime of the BNS as causes for the faintness of GRB 170817A. We predict that BNS mergers at lower redshifts generate on average fainter GRBs.

Observational and modeling constraints on global anthropogenic enrichment of mercury.

PubMed

Amos, Helen M; Sonke, Jeroen E; Obrist, Daniel; Robins, Nicholas; Hagan, Nicole; Horowitz, Hannah M; Mason, Robert P; Witt, Melanie; Hedgecock, Ian M; Corbitt, Elizabeth S; Sunderland, Elsie M

2015-04-07

Centuries of anthropogenic releases have resulted in a global legacy of mercury (Hg) contamination. Here we use a global model to quantify the impact of uncertainty in Hg atmospheric emissions and cycling on anthropogenic enrichment and discuss implications for future Hg levels. The plausibility of sensitivity simulations is evaluated against multiple independent lines of observation, including natural archives and direct measurements of present-day environmental Hg concentrations. It has been previously reported that pre-industrial enrichment recorded in sediment and peat disagree by more than a factor of 10. We find this difference is largely erroneous and caused by comparing peat and sediment against different reference time periods. After correcting this inconsistency, median enrichment in Hg accumulation since pre-industrial 1760 to 1880 is a factor of 4.3 for peat and 3.0 for sediment. Pre-industrial accumulation in peat and sediment is a factor of ∼ 5 greater than the precolonial era (3000 BC to 1550 AD). Model scenarios that omit atmospheric emissions of Hg from early mining are inconsistent with observational constraints on the present-day atmospheric, oceanic, and soil Hg reservoirs, as well as the magnitude of enrichment in archives. Future reductions in anthropogenic emissions will initiate a decline in atmospheric concentrations within 1 year, but stabilization of subsurface and deep ocean Hg levels requires aggressive controls. These findings are robust to the ranges of uncertainty in past emissions and Hg cycling.

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.

The Story of Ever Diminishing Vehicle Tailpipe Emissions as Observed in the Chicago, Illinois Area.

PubMed

Bishop, Gary A; Haugen, Molly J

2018-05-15

The University of Denver has collected on-road fuel specific vehicle emissions measurements in the Chicago area since 1989. This nearly 30 year record illustrates the large reductions in light-duty vehicle tailpipe emissions and the remarkable improvements in emissions control durability to maintain low emissions over increasing periods of time. Since 1989 fuel specific carbon monoxide (CO) emissions have been reduced by an order of magnitude and hydrocarbon (HC) emissions by more than a factor of 20. Nitric oxide (NO) emissions have only been collected since 1997 but have seen reductions of 79%. This has increased the skewness of the emissions distribution where the 2016 fleet's 99th percentile contributes ∼3 times more of the 1990 total for CO and HC emissions. There are signs that these reductions may be leveling out as the emissions durability of Tier 2 vehicles in use today has almost eliminated the emissions reduction benefit of fleet turnover. Since 1997, the average age of the Chicago on-road fleet has increased 2 model years and the percentage of passenger vehicles has dropped from 71 to 52% of the fleet. Emissions are now so well controlled that the influence of driving mode has been completely eliminated as a factor for fuel specific CO and NO emissions.

Black carbon and polycyclic aromatic hydrocarbon emissions from vehicles in the United States-Mexico border region: pilot study.

PubMed

Kelly, Kerry; Wagner, David; Lighty, JoAnn; Quintero Núñez, Margarito; Vazquez, F Adrian; Collins, Kimberly; Barud-Zubillaga, Alberto

2006-03-01

The investigators developed a system to measure black carbon (BC) and particle-bound polycyclic aromatic hydrocarbon (PAH) emission factors during roadside sampling in four cities along the United States-Mexico border, Calexico/Mexicali and El Paso/Juarez. The measurement system included a photoacoustic analyzer for BC, a photoelectric aerosol sensor for particle-bound PAHs, and a carbon dioxide (CO2) analyzer. When a vehicle with measurable emissions passed the system probe, corresponding BC, PAH, and CO2 peaks were evident, and a fuel-based emission factor was estimated. A picture of each vehicle was also recorded with a digital camera. The advantage of this system, compared with other roadside methods, is the direct measurement of particulate matter components and limited interference from roadside dust. The study revealed some interesting trends: Mexican buses and all medium-duty trucks were more frequently identified as high emitters of BC and PAH than heavy-duty trucks or passenger vehicles. In addition, because of the high daily mileage of buses, they are good candidates for additional study. Mexican trucks and buses had higher average emission factors compared with U.S. trucks and buses, but the differences were not statistically significant. Few passenger vehicles had measurable BC and PAH emissions, although the highest emission factor came from an older model passenger vehicle licensed in Baja California.

Revealing driving factors of China's PM2.5 pollution

NASA Astrophysics Data System (ADS)

Zheng, Y.; Zhao, H.; Zhang, Q.; Geng, G.; Tong, D.; Peng, L.; He, K.

2017-12-01

China's rapid economic development and intensive energy consumption are deteriorating the air quality significantly. Understanding the key driving factors behind China's growing emissions of air pollutants and the accompanying PM2.5 pollution is critical for the development of China's clean air policies and also provides insight into how other emerging economies may develop a clear sky future. Here we reveal the socioeconomic drivers of the variations of China's PM2.5 concentrations during 2002-2012 by using an interdisciplinary framework that integrates an emission inventory model, an index decomposition analysis model, and a regional air quality model. The decomposition results demostrate that the improvements in emission efficiency and energy efficiency failed to offset the increased emissions of both primary PM2.5 and gaseous PM2.5 precursors (including SO2 NOx, and volatile organic compounds) triggered by the surging economic growth during 2002-2012. During the same time, the effects of energy structure, production structure and population growth were relatively less significant to all pollutants, which indicates the potential of large emission abatements through energy structure and production structure adjustment. Sensitivity simulations by the air quality model based on the provincial decomposition results also show that the economic growth have outpaced efficiency improvements in the increments of PM2.5 concentrations during the study years. As China continues to develop rapidly, future policies should promote further improvements in efficiency and accelerate the adjustments toward clean energy and production structures, which are critical for reducing China's emissions and alleviating the severe PM2.5 pollution.

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.

An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting

NASA Astrophysics Data System (ADS)

Sofiev, M.; Vankevich, R.; Lotjonen, M.; Prank, M.; Petukhov, V.; Ermakova, T.; Koskinen, J.; Kukkonen, J.

2009-09-01

This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4-5.5.2006, 15.8-25.8.2006 and in August 2008). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available ground-based observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate non-linear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is expected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire-originated concentrations of aerosols (PM2.5, PM10, sulphates and nitrates) and AOD, as predicted by the SILAM model were mainly within a factor of 2-3 compared with the observations. The main challenges of the FAS improvement include refining of the emission factors globally, determination of the types of fires (smouldering vs flaming), evaluation of the injection heights of the plumes, and predicting the temporal evolution of fires.

Intermediate Volatility Organic Compound Emissions from On-Road Gasoline Vehicles and Small Off-Road Gasoline Engines.

PubMed

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

2016-04-19

Dynamometer experiments were conducted to characterize the intermediate volatility organic compound (IVOC) emissions from a fleet of on-road gasoline vehicles and small off-road gasoline engines. IVOCs were quantified through gas chromatography/mass spectrometry analysis of adsorbent samples collected from a constant volume sampler. The dominant fraction (>80%, on average) of IVOCs could not be resolved on a molecular level. These unspeciated IVOCs were quantified as two chemical classes (unspeciated branched alkanes and cyclic compounds) in 11 retention-time-based bins. IVOC emission factors (mg kg-fuel(-1)) from on-road vehicles varied widely from vehicle to vehicle, but showed a general trend of lower emissions for newer vehicles that met more stringent emission standards. IVOC emission factors for 2-stroke off-road engines were substantially higher than 4-stroke off-road engines and on-road vehicles. Despite large variations in the magnitude of emissions, the IVOC volatility distribution and chemical characteristics were consistent across all tests and IVOC emissions were strongly correlated with nonmethane hydrocarbons (NMHCs), primary organic aerosol and speciated IVOCs. Although IVOC emissions only correspond to approximately 4% of NMHC emissions from on-road vehicles over the cold-start unified cycle, they are estimated to produce as much or more SOA than single-ring aromatics. Our results clearly demonstrate that IVOCs from gasoline engines are an important class of SOA precursors and provide observational constraints on IVOC emission factors and chemical composition to facilitate their inclusion into atmospheric chemistry models.

Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker Amundsen from the Polar 6 aircraft platform

NASA Astrophysics Data System (ADS)

Aliabadi, Amir A.; Thomas, Jennie L.; Herber, Andreas B.; Staebler, Ralf M.; Leaitch, W. Richard; Schulz, Hannes; Law, Kathy S.; Marelle, Louis; Burkart, Julia; Willis, Megan D.; Bozem, Heiko; Hoor, Peter M.; Köllner, Franziska; Schneider, Johannes; Levasseur, Maurice; Abbatt, Jonathan P. D.

2016-06-01

Decreasing sea ice and increasing marine navigability in northern latitudes have changed Arctic ship traffic patterns in recent years and are predicted to increase annual ship traffic in the Arctic in the future. Development of effective regulations to manage environmental impacts of shipping requires an understanding of ship emissions and atmospheric processing in the Arctic environment. As part of the summer 2014 NETCARE (Network on Climate and Aerosols) campaign, the plume dispersion and gas and particle emission factors of effluents originating from the Canadian Coast Guard icebreaker Amundsen operating near Resolute Bay, NU, Canada, were investigated. The Amundsen burned distillate fuel with 1.5 wt % sulfur. Emissions were studied via plume intercepts using the Polar 6 aircraft measurements, an analytical plume dispersion model, and using the FLEXPART-WRF Lagrangian particle dispersion model. The first plume intercept by the research aircraft was carried out on 19 July 2014 during the operation of the Amundsen in the open water. The second and third plume intercepts were carried out on 20 and 21 July 2014 when the Amundsen had reached the ice edge and operated under ice-breaking conditions. Typical of Arctic marine navigation, the engine load was low compared to cruising conditions for all of the plume intercepts. The measured species included mixing ratios of CO2, NOx, CO, SO2, particle number concentration (CN), refractory black carbon (rBC), and cloud condensation nuclei (CCN). The results were compared to similar experimental studies in mid-latitudes. Plume expansion rates (γ) were calculated using the analytical model and found to be γ = 0.75 ± 0.81, 0.93 ± 0.37, and 1.19 ± 0.39 for plumes 1, 2, and 3, respectively. These rates were smaller than prior studies conducted at mid-latitudes, likely due to polar boundary layer dynamics, including reduced turbulent mixing compared to mid-latitudes. All emission factors were in agreement with prior observations at low engine loads in mid-latitudes. Ice-breaking increased the NOx emission factor from EFNOx = 43.1 ± 15.2 to 71.6 ± 9.68 and 71.4 ± 4.14 g kg-diesel-1 for plumes 1, 2, and 3, likely due to changes in combustion temperatures. The CO emission factor was EFCO = 137 ± 120, 12.5 ± 3.70 and 8.13 ± 1.34 g kg-diesel-1 for plumes 1, 2, and 3. The rBC emission factor was EFrBC = 0.202 ± 0.052 and 0.202 ± 0.125 g kg-diesel-1 for plumes 1 and 2. The CN emission factor was reduced while ice-breaking from EFCN = 2.41 ± 0.47 to 0.45 ± 0.082 and 0.507 ± 0.037 × 1016 kg-diesel-1 for plumes 1, 2, and 3. At 0.6 % supersaturation, the CCN emission factor was comparable to observations in mid-latitudes at low engine loads with EFCCN = 3.03 ± 0.933, 1.39 ± 0.319, and 0.650 ± 0.136 × 1014 kg-diesel-1 for plumes 1, 2, and 3.

Specific model for the estimation of methane emission from municipal solid waste landfills in India.

PubMed

Kumar, Sunil; Nimchuk, Nick; Kumar, Rakesh; Zietsman, Josias; Ramani, Tara; Spiegelman, Clifford; Kenney, Megan

2016-09-01

The landfill gas (LFG) model is a tool for measuring methane (CH4) generation rates and total CH4 emissions from a particular landfill. These models also have various applications including the sizing of the LFG collection system, evaluating the benefits of gas recovery projects, and measuring and controlling gaseous emissions. This research paper describes the development of a landfill model designed specifically for Indian climatic conditions and the landfill's waste characteristics. CH4, carbon dioxide (CO2), oxygen (O2) and temperature were considered as the prime factor for the development of this model. The developed model was validated for three landfill sites in India: Shillong, Kolkata, and Jaipur. The autocorrelation coefficient for the model was 0.915, while the R(2) value was 0.429. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of modern radiative transfer tools to model laboratory quartz emissivity

NASA Astrophysics Data System (ADS)

Pitman, Karly M.; Wolff, Michael J.; Clayton, Geoffrey C.

2005-08-01

Planetary remote sensing of regolith surfaces requires use of theoretical models for interpretation of constituent grain physical properties. In this work, we review and critically evaluate past efforts to strengthen numerical radiative transfer (RT) models with comparison to a trusted set of nadir incidence laboratory quartz emissivity spectra. By first establishing a baseline statistical metric to rate successful model-laboratory emissivity spectral fits, we assess the efficacy of hybrid computational solutions (Mie theory + numerically exact RT algorithm) to calculate theoretical emissivity values for micron-sized α-quartz particles in the thermal infrared (2000-200 cm-1) wave number range. We show that Mie theory, a widely used but poor approximation to irregular grain shape, fails to produce the single scattering albedo and asymmetry parameter needed to arrive at the desired laboratory emissivity values. Through simple numerical experiments, we show that corrections to single scattering albedo and asymmetry parameter values generated via Mie theory become more necessary with increasing grain size. We directly compare the performance of diffraction subtraction and static structure factor corrections to the single scattering albedo, asymmetry parameter, and emissivity for dense packing of grains. Through these sensitivity studies, we provide evidence that, assuming RT methods work well given sufficiently well-quantified inputs, assumptions about the scatterer itself constitute the most crucial aspect of modeling emissivity values.

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate.

PubMed

Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim

2011-06-01

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach. Published by Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Discrepancies between modeled and observed nocturnal isoprene in an urban environment and the possible causes: A case study in Houston

NASA Astrophysics Data System (ADS)

Diao, Lijun; Choi, Yunsoo; Czader, Beata; Li, Xiangshang; Pan, Shuai; Roy, Anirban; Souri, Amir Hossein; Estes, Mark; Jeon, Wonbae

2016-11-01

Air quality simulations were conducted using the Community Multiscale Air Quality (CMAQ) model for nocturnal isoprene in September 2013 using the United States Environmental Protection Agency's (EPA's) National Emissions Inventory of 2011 (NEI, 2011). The results were evaluated against measurements collected at eight Texas Commission on Environmental Quality (TCEQ) Automated Gas Chromatographs (AutoGCs) monitoring stations. The comparisons demonstrated two distinctive behaviors: overestimation before midnight (20:00-23:00 p.m. local time) versus underestimation after midnight (00:00-06:00 a.m.). Analyses identify the uncertainties in nitrate radical (NO3) concentration and vertical mixing as the possible minor factors contributing to the underestimation, and the underestimated wind speed as the major factor contributing to the overestimation. Further analysis links isoprene underestimation to the uncertainties in the nocturnal isoprene anthropogenic emissions in the NEI (2011) over industrial areas in Houston. This can be substantiated by the fact that the observed nighttime isoprene concentrations increased when the wind direction veered back from southeast to northeast, placing the stations downwind of industrial facilities. A sensitivity run with adjusted anthropogenic isoprene emissions in the later part of the night (i.e., the emissions were multiplied by the hourly underestimation factors ranging from 3.81 to 14.82) yielded closer isoprene predictions after midnight with slightly improved model mean (0.15 to 0.20 ppb), mean error (- 0.10 to - 0.04 ppb), mean absolute error (0.18 to 0.15 ppb), root mean squared error (RMSE, 0.27 to 0.25 ppb), and index of agreement (IOA, 0.66 to 0.68). The insignificant improvement was likely due to the uncertainties in the location of the high-peaked anthropogenic emissions. The impacts of the nighttime-adjusted isoprene emissions on the isoprene oxidation products, organic nitrate and ozone, were found to be minimal. This study, however, shows that more in-situ surface nighttime measurement data is critical to constrain the underestimated nocturnal isoprene emissions in Houston.

Models to predict emissions of health-damaging pollutants and global warming contributions of residential fuel/stove combinations in China.

PubMed

Edwards, Rufus D; Smith, Kirk R; Zhang, Junfeng; Ma, Yuqing

2003-01-01

Residential energy use in developing countries has traditionally been associated with combustion devices of poor energy efficiency, which have been shown to produce substantial health-damaging pollution, contributing significantly to the global burden of disease, and greenhouse gas (GHG) emissions. Precision of these estimates in China has been hampered by limited data on stove use and fuel consumption in residences. In addition limited information is available on variability of emissions of pollutants from different stove/fuel combinations in typical use, as measurement of emission factors requires measurement of multiple chemical species in complex burn cycle tests. Such measurements are too costly and time consuming for application in conjunction with national surveys. Emissions of most of the major health-damaging pollutants (HDP) and many of the gases that contribute to GHG emissions from cooking stoves are the result of the significant portion of fuel carbon that is diverted to products of incomplete combustion (PIC) as a result of poor combustion efficiencies. The approximately linear increase in emissions of PIC with decreasing combustion efficiencies allows development of linear models to predict emissions of GHG and HDP intrinsically linked to CO2 and PIC production, and ultimately allows the prediction of global warming contributions from residential stove emissions. A comprehensive emissions database of three burn cycles of 23 typical fuel/stove combinations tested in a simulated village house in China has been used to develop models to predict emissions of HDP and global warming commitment (GWC) from cooking stoves in China, that rely on simple survey information on stove and fuel use that may be incorporated into national surveys. Stepwise regression models predicted 66% of the variance in global warming commitment (CO2, CO, CH4, NOx, TNMHC) per 1 MJ delivered energy due to emissions from these stoves if survey information on fuel type was available. Subsequently if stove type is known, stepwise regression models predicted 73% of the variance. Integrated assessment of policies to change stove or fuel type requires that implications for environmental impacts, energy efficiency, global warming and human exposures to HDP emissions can be evaluated. Frequently, this involves measurement of TSP or CO as the major HDPs. Incorporation of this information into models to predict GWC predicted 79% and 78% of the variance respectively. Clearly, however, the complexity of making multiple measurements in conjunction with a national survey would be both expensive and time consuming. Thus, models to predict HDP using simple survey information, and with measurement of either CO/CO2 or TSP/CO2 to predict emission factors for the other HDP have been derived. Stepwise regression models predicted 65% of the variance in emissions of total suspended particulate as grams of carbon (TSPC) per 1 MJ delivered if survey information on fuel and stove type was available and 74% if the CO/CO2 ratio was measured. Similarly stepwise regression models predicted 76% of the variance in COC emissions per MJ delivered with survey information on stove and fuel type and 85% if the TSPC/CO2 ratio was measured. Ultimately, with international agreements on emissions trading frameworks, similar models based on extensive databases of the fate of fuel carbon during combustion from representative household stoves would provide a mechanism for computing greenhouse credits in the residential sector as part of clean development mechanism frameworks and monitoring compliance to control regimes.

Modeling of pesticide emissions from agricultural ecosystems

NASA Astrophysics Data System (ADS)

Li, Rong

2012-04-01

Pesticides are applied to crops and soils to improve agricultural yields, but the use of pesticides has become highly regulated because of concerns about their adverse effects on human health and environment. Estimating pesticide emission rates from soils and crops is a key component for risk assessment for pesticide registration, identification of pesticide sources to the contamination of sensitive ecosystems, and appreciation of transport and fate of pesticides in the environment. Pesticide emission rates involve processes occurring in the soil, in the atmosphere, and on vegetation surfaces and are highly dependent on soil texture, agricultural practices, and meteorology, which vary significantly with location and/or time. To take all these factors into account for simulating pesticide emissions from large agricultural ecosystems, this study coupled a comprehensive meteorological model with a dynamic pesticide emission model. The combined model calculates hourly emission rates from both emission sources: current applications and soil residues resulting from historical use. The coupled modeling system is used to compute a gridded (36 × 36 km) hourly toxaphene emission inventory for North America for the year 2000 using a published U.S. toxaphene residue inventory and a Mexican toxaphene residue inventory developed using its historical application rates and a cropland inventory. To my knowledge, this is the first such hourly toxaphene emission inventory for North America. Results show that modeled emission rates have strong diurnal and seasonal variations at a given location and over the entire domain. The simulated total toxaphene emission from contaminated agricultural soils in North America in 2000 was about 255 t, which compares reasonably well to a published annual estimate. Most emissions occur in spring and summer, with domain-wide emission rates in April, May and, June of 36, 51, and 35 t/month, respectively. The spatial distribution of emissions depends on the distribution of toxaphene soil residues, and high emission rates coincide with heavily contaminated areas.

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.

Assessing air quality and climate impacts of future ground freight choice in United States

NASA Astrophysics Data System (ADS)

Liu, L.; Bond, T. C.; Smith, S.; Lee, B.; Ouyang, Y.; Hwang, T.; Barkan, C.; Lee, S.; Daenzer, K.

2013-12-01

The demand for freight transportation has continued to increase due to the growth of domestic and international trade. Emissions from ground freight (truck and railways) account for around 7% of the greenhouse gas emissions, 4% of the primary particulate matter emission and 25% of the NOx emissions in the U.S. Freight railways are generally more fuel efficient than trucks and cause less congestion. Freight demand and emissions are affected by many factors, including economic activity, the spatial distribution of demand, freight modal choice and routing decision, and the technology used in each modal type. This work links these four critical aspects of freight emission system to project the spatial distribution of emissions and pollutant concentration from ground freight transport in the U.S. between 2010 and 2050. Macroeconomic scenarios are used to forecast economic activities. Future spatial structure of employment and commodity demand in major metropolitan areas are estimated using spatial models and a shift-share model, respectively. Freight flow concentration and congestion patterns in inter-regional transportation networks are predicted from a four-step freight demand forecasting model. An asymptotic vehicle routing model is also developed to estimate delivery ton-miles for intra-regional freight shipment in metropolitan areas. Projected freight activities are then converted into impacts on air quality and climate. CO2 emissions are determined using a simple model of freight activity and fuel efficiency, and compared with the projected CO2 emissions from the Second Generation Model. Emissions of air pollutants including PM, NOx and CO are calculated with a vehicle fleet model SPEW-Trend, which incorporates the dynamic change of technologies. Emissions are projected under three economic scenarios to represent different plausible futures. Pollutant concentrations are then estimated using tagged chemical tracers in an atmospheric model with the emissions serving as input.

The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010

NASA Astrophysics Data System (ADS)

Parrington, M.; Palmer, P. I.; Henze, D. K.; Tarasick, D. W.; Hyer, E. J.; Owen, R. C.; Helmig, D.; Clerbaux, C.; Bowman, K. W.; Deeter, M. N.; Barratt, E. M.; Coheur, P.-F.; Hurtmans, D.; Jiang, Z.; George, M.; Worden, J. R.

2012-02-01

We have analysed the sensitivity of the tropospheric ozone distribution over North America and the North Atlantic to boreal biomass burning emissions during the summer of 2010 using the GEOS-Chem 3-D global tropospheric chemical transport model and observations from in situ and satellite instruments. We show that the model ozone distribution is consistent with observations from the Pico Mountain Observatory in the Azores, ozonesondes across Canada, and the Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Instrument (IASI) satellite instruments. Mean biases between the model and observed ozone mixing ratio in the free troposphere were less than 10 ppbv. We used the adjoint of GEOS-Chem to show the model ozone distribution in the free troposphere over Maritime Canada is largely sensitive to NOx emissions from biomass burning sources in Central Canada, lightning sources in the central US, and anthropogenic sources in the eastern US and south-eastern Canada. We also used the adjoint of GEOS-Chem to evaluate the Fire Locating And Monitoring of Burning Emissions (FLAMBE) inventory through assimilation of CO observations from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. The CO inversion showed that, on average, the FLAMBE emissions needed to be reduced to 89% of their original values, with scaling factors ranging from 12% to 102%, to fit the MOPITT observations in the boreal regions. Applying the CO scaling factors to all species emitted from boreal biomass burning sources led to a decrease of the model tropospheric distributions of CO, PAN, and NOx by as much as -20 ppbv, -50 pptv, and -20 pptv respectively. The modification of the biomass burning emission estimates reduced the model ozone distribution by approximately -3 ppbv (-8%) and on average improved the agreement of the model ozone distribution compared to the observations throughout the free troposphere, reducing the mean model bias from 5.5 to 4.0 ppbv for the Pico Mountain Observatory, 3.0 to 0.9 ppbv for ozonesondes, 2.0 to 0.9 ppbv for TES, and 2.8 to 1.4 ppbv for IASI.

Carbon Calculator for Land Use Change from Biofuels Production (CCLUB). Users' manual and technical documentation.

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

Mueller, S; Dunn, JB; Wang, M

2012-06-07

The Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) calculates carbon emissions from land use change (LUC) for four different ethanol production pathways including corn grain ethanol and cellulosic ethanol from corn stover, miscanthus, and switchgrass. This document discusses the version of CCLUB released May 31, 2012 which includes corn, as did the previous CCLUB version, and three cellulosic feedstocks: corn stover, miscanthus, and switchgrass. CCLUB calculations are based upon two data sets: land change areas and above- and below-ground carbon content. Table 1 identifies where these data are stored and used within the CCLUB model, which ismore » built in MS Excel. Land change area data is from Purdue University's Global Trade Analysis Project (GTAP) model, a computable general equilibrium (CGE) economic model. Section 2 describes the GTAP data CCLUB uses and how these data were modified to reflect shrubland transitions. Feedstock- and spatially-explicit below-ground carbon content data for the United States were generated with a surrogate model for CENTURY's soil organic carbon sub-model (Kwon and Hudson 2010) as described in Section 3. CENTURY is a soil organic matter model developed by Parton et al. (1987). The previous CCLUB version used more coarse domestic carbon emission factors. Above-ground non-soil carbon content data for forest ecosystems was sourced from the USDA/NCIAS Carbon Online Estimator (COLE) as explained in Section 4. We discuss emission factors used for calculation of international greenhouse gas (GHG) emissions in Section 5. Temporal issues associated with modeling LUC emissions are the topic of Section 6. Finally, in Section 7 we provide a step-by-step guide to using CCLUB and obtaining results.« less

Sensitivity Analysis Reveals Critical Factors that Affect Wetland Methane Emissions using Soil Biogeochemistry Model

NASA Astrophysics Data System (ADS)

Alonso-Contes, C.; Gerber, S.; Bliznyuk, N.; Duerr, I.

2017-12-01

Wetlands contribute approximately 20 to 40 % to global sources of methane emissions. We build a Methane model for tropical and subtropical forests, that allows inundated conditions, following the approaches used in more complex global biogeochemical emission models (LPJWhyMe and CLM4Me). The model was designed to replace model formulations with field and remotely sensed collected data for 2 essential drivers: plant productivity and hydrology. This allows us to directly focus on the central processes of methane production, consumption and transport. One of our long term goals is to make the model available to a scientists interested in including methane modeling in their location of study. Sensitivity analysis results help in focusing field data collection efforts. Here, we present results from a pilot global sensitivity analysis of the model order to determine which parameters and processes contribute most to the model's uncertainty of methane emissions. Results show that parameters related to water table behavior, carbon input (in form of plant productivity) and rooting depth affect simulated methane emissions the most. Current efforts include to perform the sensitivity analysis again on methane emissions outputs from an updated model that incorporates a soil heat flux routine and to determine the extent by which the soil temperature parameters affect CH4 emissions. Currently we are conducting field collection of data during Summer 2017 for comparison among 3 different landscapes located in the Ordway-Swisher Biological Station in Melrose, FL. We are collecting soil moisture and CH4 emission data from 4 different wetland types. Having data from 4 wetland types allows for calibration of the model to diverse soil, water and vegetation characteristics.

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.

Assessing Potential Air Pollutant Emissions from Agricultural Feedstock Production using MOVES

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

Eberle, Annika; Warner, Ethan; Zhang, Yi Min

Biomass feedstock production is expected to grow as demand for biofuels and bioenergy increases. The change in air pollutant emissions that may result from large-scale biomass supply has implications for local air quality and human health. We developed spatially explicit emissions inventories for corn grain and six cellulosic feedstocks through the extension of the National Renewable Energy Laboratory's Feedstock Production Emissions to Air Model (FPEAM). These inventories include emissions of seven pollutants (nitrogen oxides, ammonia, volatile organic compounds, particulate matter, sulfur oxides, and carbon monoxide) generated from biomass establishment, maintenance, harvest, transportation, and biofuel preprocessing activities. By integrating the EPA'smore » MOtor Vehicle Emissions Simulator (MOVES) into FPEAM, we created a scalable framework to execute county-level runs of the MOVES-Onroad model for representative counties (i.e., those counties with the largest amount of cellulosic feedstock production in each state) on a national scale. We used these results to estimate emissions from the on-road transportation of biomass and combined them with county-level runs of the MOVES-Nonroad model to estimate emissions from agricultural equipment. We also incorporated documented emission factors to estimate emissions from chemical application and the operation of drying equipment for feedstock processing, and used methods developed by the EPA and the California Air Resources Board to estimate fugitive dust emissions. The model developed here could be applied to custom equipment budgets and is extensible to accommodate additional feedstocks and pollutants. Future work will also extend this model to analyze spatial boundaries beyond the county-scale (e.g., regional or sub-county levels).« less

Agricultural ammonia emissions in China: reconciling bottom-up and top-down estimates

NASA Astrophysics Data System (ADS)

Zhang, Lin; Chen, Youfan; Zhao, Yuanhong; Henze, Daven K.; Zhu, Liye; Song, Yu; Paulot, Fabien; Liu, Xuejun; Pan, Yuepeng; Lin, Yi; Huang, Binxiang

2018-01-01

Current estimates of agricultural ammonia (NH3) emissions in China differ by more than a factor of 2, hindering our understanding of their environmental consequences. Here we apply both bottom-up statistical and top-down inversion methods to quantify NH3 emissions from agriculture in China for the year 2008. We first assimilate satellite observations of NH3 column concentration from the Tropospheric Emission Spectrometer (TES) using the GEOS-Chem adjoint model to optimize Chinese anthropogenic NH3 emissions at the 1/2° × 2/3° horizontal resolution for March-October 2008. Optimized emissions show a strong summer peak, with emissions about 50 % higher in summer than spring and fall, which is underestimated in current bottom-up NH3 emission estimates. To reconcile the latter with the top-down results, we revisit the processes of agricultural NH3 emissions and develop an improved bottom-up inventory of Chinese NH3 emissions from fertilizer application and livestock waste at the 1/2° × 2/3° resolution. Our bottom-up emission inventory includes more detailed information on crop-specific fertilizer application practices and better accounts for meteorological modulation of NH3 emission factors in China. We find that annual anthropogenic NH3 emissions are 11.7 Tg for 2008, with 5.05 Tg from fertilizer application and 5.31 Tg from livestock waste. The two sources together account for 88 % of total anthropogenic NH3 emissions in China. Our bottom-up emission estimates also show a distinct seasonality peaking in summer, consistent with top-down results from the satellite-based inversion. Further evaluations using surface network measurements show that the model driven by our bottom-up emissions reproduces the observed spatial and seasonal variations of NH3 gas concentrations and ammonium (NH4+) wet deposition fluxes over China well, providing additional credibility to the improvements we have made to our agricultural NH3 emission inventory.

Comparison of APSIM and DNDC simulations of nitrogen transformations and N2O emissions.

PubMed

Vogeler, I; Giltrap, D; Cichota, R

2013-11-01

Various models have been developed to better understand nitrogen (N) cycling in soils, which is governed by a complex interaction of physical, chemical and biological factors. Two process-based models, the Agricultural Production Systems sIMulator (APSIM) and DeNitrification DeComposition (DNDC), were used to simulate nitrification, denitrification and nitrous oxide (N2O) emissions from soils following N input from either fertiliser or excreta deposition. The effect of environmental conditions on N transformations as simulated by the two different models was compared. Temperature had a larger effect in APSIM on nitrification, whereas in DNDC, water content produced a larger response. In contrast, simulated denitrification showed a larger response to temperature and also organic carbon content in DNDC. And while denitrification in DNDC is triggered by rainfall ≥5mm/h, in APSIM, the driving factor is soil water content, with a trigger point at water content at field capacity. The two models also showed different responses to N load, with nearly linearly increasing N2O emission rates with N load simulated by DNDC, and a lower rate by APSIM. Increasing rainfall intensity decreased APSIM-simulated N2O emissions but increased those simulated by DNDC. Copyright © 2012 Elsevier B.V. All rights reserved.

Investigating the Impact of Marine Ship Emissions on Regional Air Quality using OMI Satellite NO2 Observations and the CMAQ Model

NASA Astrophysics Data System (ADS)

Ring, A.; Canty, T. P.; He, H.; Vinciguerra, T.; Lamsal, L. N.; Dickerson, R. R.; Salawitch, R. J.; Cohen, M.; Montgomery, L. N.; Dreessen, J.

2015-12-01

Commercial marine vessels (CMVs) emit significant amounts of NOx, an ozone precursor, which may contribute to negative health consequences for people living in areas near shipping lanes. In coastal US states, many metropolitan areas such as Baltimore and New York City are located near ports with CMVs. Many studies estimate that ships account for ~15-30% of the global anthropogenic NOx emissions. EPA developed emissions inventories are widely used by states to construct model scenarios for testing air quality attainment strategies. Currently, CMV emissions are generated by simply applying growth factors to aggregated emissions data from much earlier years. Satellite retrievals from the Ozone Monitoring Instrument (OMI) have been successfully used to improve the veracity of marine emissions by incorporating observational data from the inventory year. In this study we use OMI NO2 observations and Community Multiscale Air Quality (CMAQ) model outputs to improve the EPA marine emission estimates for the Mid-Atlantic region. Back trajectories from the NOAA Air Resources Laboratory HYSPLIT model are used to identify days with minimal continental influence on OMI tropospheric column NO2 over shipping lanes. We perform sensitivity analyses to quantify the impact of marine emissions on air quality and suggest strategies to better meet the EPA mandated ozone standard.

Observation of Solar Wind Charge Exchange Emission from Exospheric Material in and Outside Earth's Magnetosheath

NASA Technical Reports Server (NTRS)

Snowden, S. L.; Collier, M. R.; Cravens, T.; Kuntz, K. D.; Lepri, S. T.; Robertson, I.; Tomas, L.

2008-01-01

A long XMM-Newton exposure is used to observe solar wind charge exchange (SWCX) emission from exospheric material in and outside Earth s magnetosheath. The light curve of the O VII (0.5-0.62 keV) band is compared with a model for the expected emission, and while the emission is faint and the light curve has considerable scatter, the correlation is significant to better than 99.9%. This result demonstrates the validity of the geocoronal SWCX emission model for predicting a contribution to astrophysical observations to a scale factor of order unity (1.36). The results also demonstrate the potential utility of using X-ray observations to study global phenomena of the magnetosheath which currently are only investigated using in situ measurements.

Spatial analysis of toxic emissions in LCA: a sub-continental nested USEtox model with freshwater archetypes.

PubMed

Kounina, Anna; Margni, Manuele; Shaked, Shanna; Bulle, Cécile; Jolliet, Olivier

2014-08-01

This paper develops continent-specific factors for the USEtox model and analyses the accuracy of different model architectures, spatial scales and archetypes in evaluating toxic impacts, with a focus on freshwater pathways. Inter-continental variation is analysed by comparing chemical fate and intake fractions between sub-continental zones of two life cycle impact assessment models: (1) the nested USEtox model parameterized with sub-continental zones and (2) the spatially differentiated IMPACTWorld model with 17 interconnected sub-continental regions. Substance residence time in water varies by up to two orders of magnitude among the 17 zones assessed with IMPACTWorld and USEtox, and intake fraction varies by up to three orders of magnitude. Despite this variation, the nested USEtox model succeeds in mimicking the results of the spatially differentiated model, with the exception of very persistent volatile pollutants that can be transported to polar regions. Intra-continental variation is analysed by comparing fate and intake fractions modelled with the a-spatial (one box) IMPACT Europe continental model vs. the spatially differentiated version of the same model. Results show that the one box model might overestimate chemical fate and characterisation factors for freshwater eco-toxicity of persistent pollutants by up to three orders of magnitude for point source emissions. Subdividing Europe into three archetypes, based on freshwater residence time (how long it takes water to reach the sea), improves the prediction of fate and intake fractions for point source emissions, bringing them within a factor five compared to the spatial model. We demonstrated that a sub-continental nested model such as USEtox, with continent-specific parameterization complemented with freshwater archetypes, can thus represent inter- and intra-continental spatial variations, whilst minimizing model complexity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model

NASA Astrophysics Data System (ADS)

Petrenko, Mariya; Kahn, Ralph; Chin, Mian; Limbacher, James

2017-10-01

Simulations of biomass burning (BB) emissions in global chemistry and aerosol transport models depend on external inventories, which provide location and strength for BB aerosol sources. Our previous work shows that to first order, satellite snapshots of aerosol optical depth (AOD) near the emitted smoke plume can be used to constrain model-simulated AOD, and effectively, the smoke source strength. We now refine the satellite-snapshot method and investigate where applying simple multiplicative emission adjustment factors alone to the widely used Global Fire Emission Database version 3 emission inventory can achieve regional-scale consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) AOD snapshots and the Goddard Chemistry Aerosol Radiation and Transport model. The model and satellite AOD are compared globally, over a set of BB cases observed by the MODIS instrument during the 2004, and 2006-2008 biomass burning seasons. Regional discrepancies between the model and satellite are diverse around the globe yet quite consistent within most ecosystems. We refine our approach to address physically based limitations of our earlier work (1) by expanding the number of fire cases from 124 to almost 900, (2) by using scaled reanalysis-model simulations to fill missing AOD retrievals in the MODIS observations, (3) by distinguishing the BB components of the total aerosol load from background aerosol in the near-source regions, and (4) by including emissions from fires too small to be identified explicitly in the satellite observations. The small-fire emission adjustment shows the complimentary nature of correcting for source strength and adding geographically distinct missing sources. Our analysis indicates that the method works best for fire cases where the BB fraction of total AOD is high, primarily evergreen or deciduous forests. In heavily polluted or agricultural burning regions, where smoke and background AOD values tend to be comparable, this approach encounters large uncertainties, and in some regions, other model- or measurement-related factors might contribute significantly to model-satellite discrepancies. This work sets the stage for a larger study within the Aerosol Comparison between Observations and Models (AeroCOM) multimodel biomass burning experiment. By comparing multiple model results using the refined technique presented here, we aim to separate BB inventory from model-specific contributions to the remaining discrepancies.

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.

Site specific diel methane emission mechanisms in landfills: A field validated process based on vegetation and climate factors.

PubMed

Xin, Danhui; Hao, Yongxia; Shimaoka, Takayuki; Nakayama, Hirofumi; Chai, Xiaoli

2016-11-01

Diel methane emission fluxes from a landfill that was covered by vegetation were investigated to reveal the methane emission mechanisms based on the interaction of vegetation characteristics and climate factors. The methane emissions showed large variation between daytime and nighttime, and the trend of methane emissions exhibited clear bimodal patterns from both Setaria viridis- and Neyraudia reynaudiana-covered areas. Plants play an important role in methane transportation as well as methane oxidation. The notable decrease in methane emissions after plants were cut suggests that methane transportation via plants is the primary way of methane emissions in the vegetated areas of landfill. Within plants, the methane emission fluxes were enhanced due to a convection mechanism. Given that the methane emission flux is highly correlated with the solar radiation during daytime, the convection mechanism could be attributed to the increase in solar radiation. Whereas the methane emission flux is affected by a combined impact of the wind speed and pedosphere characteristics during nighttime. An improved understanding of the methane emission mechanisms in vegetated landfills is expected to develop a reliable model for landfill methane emissions and to attenuate greenhouse gas emissions from landfills. Copyright © 2016 Elsevier Ltd. All rights reserved.

Speed estimation for air quality analysis.

DOT National Transportation Integrated Search

2005-05-01

Average speed is an essential input to the air quality analysis model MOBILE6 for emission factor calculation. Traditionally, speed is obtained from travel demand models. However, such models are not usually calibrated to speeds. Furthermore, for rur...

Evaluation of MEGAN predicted biogenic isoprene emissions at urban locations in Southeast Texas

NASA Astrophysics Data System (ADS)

Kota, Sri Harsha; Schade, Gunnar; Estes, Mark; Boyer, Doug; Ying, Qi

2015-06-01

Summertime isoprene emissions in the Houston area predicted by the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1 during the 2006 TexAQS study were evaluated using a source-oriented Community Multiscale Air Quality (CMAQ) Model. Predicted daytime isoprene concentrations at nine surface sites operated by the Texas Commission of Environmental Quality (TCEQ) were significantly higher than local observations when biogenic emissions dominate the total isoprene concentrations, with mean normalized bias (MNB) ranges from 2.0 to 7.7 and mean normalized error (MNE) ranges from 2.2 to 7.7. Predicted upper air isoprene and its first generation oxidation products of methacrolein (MACR) and methyl vinyl ketone (MVK) were also significantly higher (MNB = 8.6, MNE = 9.1) than observations made onboard of NOAA's WP-3 airplane, which flew over the urban area. Over-prediction of isoprene and its oxidation products both at the surface and the upper air strongly suggests that biogenic isoprene emissions in the Houston area are significantly overestimated. Reducing the emission rates by approximately 3/4 was necessary to reduce the error between predictions and observations. Comparison of gridded leaf area index (LAI), plant functional type (PFT) and gridded isoprene emission factor (EF) used in MEGAN modeling with estimates of the same factors from a field survey north of downtown Houston showed that the isoprene over-prediction is likely caused by the combined effects of a large overestimation of the gridded EF in urban Houston and an underestimation of urban LAI. Nevertheless, predicted ozone concentrations in this region were not significantly affected by the isoprene over-predictions, while predicted isoprene SOA and total SOA concentrations can be higher by as much as 50% and 13% using the higher isoprene emission rates, respectively.

Revised (Mixed-Effects) Estimation for Forest Burning Emissions of Gases and Smoke, Fire/Emission Factor Typologies, and Potential Remote Sensing Classification of Types for Use in Ozone and Absorbing-Carbon Simulation

NASA Astrophysics Data System (ADS)

Chatfield, R. B.; Segal-Rosenhaimer, M.

2014-12-01

We summarize recent progress (a) in correcting biomass burning emissions factors deduced from airborne sampling of forest fire plumes, (b) in understanding the variability in reactivity of the fresh plumes sampled in ARCTAS (2008), DC3 (2012), and SEAC4RS (2013) airborne missions, and (c) in a consequent search for remotely sensed quantities that help classify forest-fire plumes. Particle properties, chemical speciation, and smoke radiative properties are related and mutually informative, as pictures below suggest (slopes of lines of same color are similar). (a) Mixed-effects (random-effects) statistical modeling provides estimates of both emission factors and a reasonable description of carbon-burned simultaneously. Different fire plumes will have very different contributions to volatile organic carbon reactivity; this may help explain differences of free NOx(both gas- and particle-phase), and also of ozone production, that have been noted for forest-fire plumes in California. Our evalualations check or correct emission factors based on sequential measurements (e.g., the Normalized Ratio Enhancement and similar methods). We stress the dangers of methods relying on emission-ratios to CO. (b) This work confirms and extends many reports of great situational variability in emissions factors. VOCs vary in OH reactivity and NOx-binding. Reasons for variability are not only fuel composition, fuel condition, etc, but are confused somewhat by rapid transformation and mixing of emissions. We use "unmixing" (distinct from mixed-effects) statistics and compare briefly to approaches like neural nets. We focus on one particularly intense fire the notorious Yosemite Rim Fire of 2013. In some samples, NOx activity was not so surpressed by binding into nitrates as in other fires. While our fire-typing is evolving and subject to debate, the carbon-burned Δ(CO2+CO) estimates that arise from mixed effects models, free of confusion by background-CO2 variation, should provide a solid base for discussion. (c) We report progress using promising links we find between emissions-related "fire types" and promising features deducible from remote observations of plumes, e.g., single scatter albedo, Ångström exponent of scattering, Ångström exponent of absorption, (CO column density)/(aerosol optical depth).

Revised (Mixed-Effects) Estimation for Forest Burning Emissions of Gases and Smoke, Fire/Emission Factor Typology, and Potential Remote Sensing Classification of Types for Ozone and Black-Carbon Simulation

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Segal Rozenhaimer, M.

2014-01-01

We summarize recent progress (a) in correcting biomass burning emissions factors deduced from airborne sampling of forest fire plumes, (b) in understanding the variability in reactivity of the fresh plumes sampled in ARCTAS (2008), DC3 (2012), and SEAC4RS (2013) airborne missions, and (c) in a consequent search for remotely sensed quantities that help classify forest-fire plumes. Particle properties, chemical speciation, and smoke radiative properties are related and mutually informative, as pictures below suggest (slopes of lines of same color are similar). (a) Mixed-effects (random-effects) statistical modeling provides estimates of both emission factors and a reasonable description of carbon-burned simultaneously. Different fire plumes will have very different contributions to volatile organic carbon reactivity; this may help explain differences of free NOx(both gas- and particle-phase), and also of ozone production, that have been noted for forest-fire plumes in California. Our evaluations check or correct emission factors based on sequential measurements (e.g., the Normalized Ratio Enhancement and similar methods). We stress the dangers of methods relying on emission-ratios to CO. (b) This work confirms and extends many reports of great situational variability in emissions factors. VOCs vary in OH reactivity and NOx-binding. Reasons for variability are not only fuel composition, fuel condition, etc., but are confused somewhat by rapid transformation and mixing of emissions. We use "unmixing" (distinct from mixed-effects) statistics and compare briefly to approaches like neural nets. We focus on one particularly intense fire the notorious Yosemite Rim Fire of 2013. In some samples, NOx activity was not so suppressed by binding into nitrates as in other fires. While our fire-typing is evolving and subject to debate, the carbon-burned delta(CO2+CO) estimates that arise from mixed effects models, free of confusion by background-CO2 variation, should provide a solid base for discussion. (c) We report progress using promising links we find between emissions-related "fire types" and promising features deducible from remote observations of plumes, e.g., single scatter albedo, Angstrom exponent of scattering, Angstrom exponent of absorption, (CO column density)/(aerosol optical depth).

Atomic and molecular emissions in the middle ultraviolet dayglow

NASA Astrophysics Data System (ADS)

Bucsela, Eric J.; Cleary, David D.; Dymond, Kenneth F.; McCoy, Robert P.

1998-12-01

Dayglow spectra in the middle ultraviolet, obtained during a sounding rocket flight from White Sands Missile Range in 1992, have been analyzed to determine the altitude distributions of thermospheric atomic and molecular species and to address a number of problems related to airglow excitation mechanisms. Among the atomic and molecular profiles retrieved are the N2 second positive, N2 Vegard-Kaplan and NO gamma band systems, and the OI 297.2 nm, OII 247.0 nm, and NII 214.3 nm emissions. A self-consistent study of the emission profiles was conducted by comparing observed intensities with one another and to forward models. Model photoelectron and photon fluxes were generated by the field line interhemispheric plasma model (FLIP) and two solar flux models. Neutral densities were obtained from mass-spectrometer/incoherent scatter (MSIS)-90. The results from the data analysis suggest that the major species' densities are within 40% of MSIS values. Evidence for the accuracy of the modeled densities and fluxes is seen in the close agreement between the calculated and observed intensities of the N2 second positive emission. Analysis of the OI 297.2 nm emission shows that the reaction N2(A)+O is the dominant source of O(1S) in the daytime thermosphere. The data imply that the vibrationally averaged yield of O(1S) from the reaction is 0.43+/-0.12, which is smaller than the laboratory value measured for the N2(A,v'=0) level. The cause of a disagreement between model and data for the Vegard-Kaplan emission is unclear, but the discrepancy can be eliminated if the N2(A)+O quenching coefficient or the A state lifetime is increased by a factor between 2 and 4. The observed intensity of OII 247.0 nm is greater than expected by a factor of 2, implying possible inadequacies in the EUVAC and/or EUV91 solar models used in the analysis.

Thermochemical Modeling and Experimental Validation of Wood Pyrolysis Occurring During Pre-ignition Combustion

NASA Astrophysics Data System (ADS)

Fawaz, M.; Lautenberger, C.; Bond, T. C.

2017-12-01

The use of wood as a solid fuel for cooking and heating is associated with high particle emission which largely contribute to the dispersion of particulate matter (PM) in the atmosphere. The majority of those particles are released during the "pre-ignition" phase, i.e., before flaming of the wood occurs. In this work, we investigate the factors that influence the emission of PM during pre-ignition and lead to high particle emission to the atmosphere. During this combustion phase, at elevated temperature, pyrolysis is responsible for wood degradation and the production of gaseous materials that travel and exit the wood. We model the thermal degradation using Gpyro, an open source finite volume method numerical model to simulate heat, mass, and momentum transfer in the wood. In our analysis, we study factors that vary during combustion and that influence emission of PM: wood sample size and boundary conditions. In a fire the boundary conditions represent the thermal energy a piece of wood receives from the surrounding in the form of heat flux. We find that heat transfer is the limiting process governing the production and transport of gas from the wood, and that the amount of emitted PM is dependent on the size of the wood. The dependence of heat transfer from the boundaries on PM emission becomes more important with increasing wood log size. The model shows that a small log of wood (6cm by 2cm) emits close values of total mass of gas at low and high heat fluxes. For a large log of wood (20cm by 5cm) the total mass of gas emitted increases by 30% between low and high heat flux. We validate the model results with a controlled-temperature reactor that accommodates centimeter scale wood samples. The size of the wood used, indicates the abundance of wood in the region where wood is used a solid fuel. Understanding those factors will allow for defining conditions that result in reducing particle emissions during combustion.

Estimation of wind erosion from construction of a railway in arid northwest China

USDA-ARS?s Scientific Manuscript database

A state-of-the-art wind erosion simulation model, the Wind Erosion Prediction System and the United States Environmental Protection Agency’s AP-42 emission factors formula, were combined together to evaluate wind-blown dust emissions from various construction units from a railway construction projec...

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

Treesearch

C. Wiedinmyer; S. K. Akagi; R. J. Yokelson; L. K. Emmons; J. A. Al-Saadi; J. J. Orlando; A. J. Soja

2010-01-01

The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km resolution, global estimates of the trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural fires, and prescribed burning and does not include 5 biofuel use and trash burning. Emission factors used in the calculations have been updated with recent data,...

Estimating NOx emissions and surface concentrations at high spatial resolution using OMI

NASA Astrophysics Data System (ADS)

Goldberg, D. L.; Lamsal, L. N.; Loughner, C.; Swartz, W. H.; Saide, P. E.; Carmichael, G. R.; Henze, D. K.; Lu, Z.; Streets, D. G.

2017-12-01

In many instances, NOx emissions are not measured at the source. In these cases, remote sensing techniques are extremely useful in quantifying NOx emissions. Using an exponential modified Gaussian (EMG) fitting of oversampled Ozone Monitoring Instrument (OMI) NO2 data, we estimate NOx emissions and lifetimes in regions where these emissions are uncertain. This work also presents a new high-resolution OMI NO2 dataset derived from the NASA retrieval that can be used to estimate surface level concentrations in the eastern United States and South Korea. To better estimate vertical profile shape factors, we use high-resolution model simulations (Community Multi-scale Air Quality (CMAQ) and WRF-Chem) constrained by in situ aircraft observations to re-calculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime. The correlation between our satellite product and ground NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in new product, r2 = 0.39 in operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to re-calculate vertical column data in areas with large spatial heterogeneities in NOx emissions. The methodologies developed in this work can be applied to other world regions and other satellite data sets to produce high-quality region-specific emissions estimates.

Empirical Research on Decoupling Relationship between Energy-Related Carbon Emission and Economic Growth in Guangdong Province Based on Extended Kaya Identity

PubMed Central

Wang, Wenxiu; Huang, Ningsheng; Zhao, Daiqing

2014-01-01

The decoupling elasticity decomposition quantitative model of energy-related carbon emission in Guangdong is established based on the extended Kaya identity and Tapio decoupling model for the first time, to explore the decoupling relationship and its internal mechanism between energy-related carbon emission and economic growth in Guangdong. Main results are as follows. (1) Total production energy-related carbon emissions in Guangdong increase from 4128 × 104 tC in 1995 to 14396 × 104 tC in 2011. Decoupling elasticity values of energy-related carbon emission and economic growth increase from 0.53 in 1996 to 0.85 in 2011, and its decoupling state turns from weak decoupling in 1996–2004 to expansive coupling in 2005–2011. (2) Land economic output and energy intensity are the first inhibiting factor and the first promoting factor to energy-related carbon emission decoupling from economic growth, respectively. The development speeds of land urbanization and population urbanization, especially land urbanization, play decisive roles in the change of total decoupling elasticity values. (3) Guangdong can realize decoupling of energy-related carbon emission from economic growth effectively by adjusting the energy mix and industrial structure, coordinating the development speed of land urbanization and population urbanization effectively, and strengthening the construction of carbon sink. PMID:24782666

Empirical research on decoupling relationship between energy-related carbon emission and economic growth in Guangdong province based on extended Kaya identity.

PubMed

Wang, Wenxiu; Kuang, Yaoqiu; Huang, Ningsheng; Zhao, Daiqing

2014-01-01

The decoupling elasticity decomposition quantitative model of energy-related carbon emission in Guangdong is established based on the extended Kaya identity and Tapio decoupling model for the first time, to explore the decoupling relationship and its internal mechanism between energy-related carbon emission and economic growth in Guangdong. Main results are as follows. (1) Total production energy-related carbon emissions in Guangdong increase from 4128 × 10⁴ tC in 1995 to 14396 × 10⁴ tC in 2011. Decoupling elasticity values of energy-related carbon emission and economic growth increase from 0.53 in 1996 to 0.85 in 2011, and its decoupling state turns from weak decoupling in 1996-2004 to expansive coupling in 2005-2011. (2) Land economic output and energy intensity are the first inhibiting factor and the first promoting factor to energy-related carbon emission decoupling from economic growth, respectively. The development speeds of land urbanization and population urbanization, especially land urbanization, play decisive roles in the change of total decoupling elasticity values. (3) Guangdong can realize decoupling of energy-related carbon emission from economic growth effectively by adjusting the energy mix and industrial structure, coordinating the development speed of land urbanization and population urbanization effectively, and strengthening the construction of carbon sink.

Design of a hybrid emissivity domestic electric oven

NASA Astrophysics Data System (ADS)

Isik, Ozgur; Onbasioglu, Seyhan Uygur

2017-10-01

In this study, the radiative properties of the surfaces of an electric oven were investigated. Using experimental data related to an oven-like enclosure, a novel combination of surface properties was developed. Three different surface emissivity combinations were analysed experimentally: low-emissivity, high emissivity (black-coated), and hybrid emissivity. The term "hybrid emissivity design" here corresponds to an enclosure with some high emissive and some low-emissive surfaces. The experiments were carried out according to the EN 50304 standard. When a brick (load) was placed in the enclosure, the view factors between its surfaces were calculated with the Monte Carlo method. These and the measured surface temperatures were then used to calculate the radiative heat fluxes on the surfaces of the load. The three different models were compared with respect to energy consumption and baking time. The hybrid model performed best, with the highest radiative heat transfer between the surfaces of the enclosure and the load and minimum heat loss from the cavity. Thus, it was the most efficient model with the lowest energy consumption and the shortest baking time. The recent European Union regulation regarding the energy labelling of domestic ovens was used.

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.

Field test of available methods to measure remotely SO2 and NOx emissions from ships

NASA Astrophysics Data System (ADS)

Balzani Lööv, J. M.; Alfoldy, B.; Beecken, J.; Berg, N.; Berkhout, A. J. C.; Duyzer, J.; Gast, L. F. L.; Hjorth, J.; Jalkanen, J.-P.; Lagler, F.; Mellqvist, J.; Prata, F.; van der Hoff, G. R.; Westrate, H.; Swart, D. P. J.; Borowiak, A.

2013-11-01

Methods for the determination of ship fuel sulphur content and NOx emission factors from remote measurements have been compared in the harbour of Rotterdam and compared to direct stack emission measurements on the ferry Stena Hollandica. The methods were selected based on a review of the available literature on ship emission measurements. They were either optical (LIDAR, DOAS, UV camera), combined with model based estimates of fuel consumption, or based on the so called "sniffer" principle, where SO2 or NOx emission factors are determined from simultaneous measurement of the increase of CO2 and SO2 or NOx concentrations in the plume of the ship compared to the background. The measurements were performed from stations at land, from a boat, and from a helicopter. Mobile measurement platforms were found to have important advantages compared to the landbased ones because they allow to optimize the sampling conditions and to sample from ships on the open sea. Although optical methods can provide reliable results, it was found that at the state of the art, the "sniffer" approach is the most convenient technique for determining both SO2 and NOx emission factors remotely. The average random error on the determination of SO2 emission factors comparing two identical instrumental set-ups was 6%. However, it was found that apparently minor differences in the instrumental characteristics, such as response time, could cause significant differences between the emission factors determined. Direct stack measurements showed that about 14% of the fuel sulphur content was not emitted as SO2. This was supported by the remote measurements and is in agreement with the results of other field studies.

Field test of available methods to measure remotely SOx and NOx emissions from ships

NASA Astrophysics Data System (ADS)

Balzani Lööv, J. M.; Alfoldy, B.; Gast, L. F. L.; Hjorth, J.; Lagler, F.; Mellqvist, J.; Beecken, J.; Berg, N.; Duyzer, J.; Westrate, H.; Swart, D. P. J.; Berkhout, A. J. C.; Jalkanen, J.-P.; Prata, A. J.; van der Hoff, G. R.; Borowiak, A.

2014-08-01

Methods for the determination of ship fuel sulphur content and NOx emission factors based on remote measurements have been compared in the harbour of Rotterdam and compared to direct stack emission measurements on the ferry Stena Hollandica. The methods were selected based on a review of the available literature on ship emission measurements. They were either optical (LIDAR, Differential Optical Absorption Spectroscopy (DOAS), UV camera), combined with model-based estimates of fuel consumption, or based on the so called "sniffer" principle, where SO2 or NOx emission factors are determined from simultaneous measurement of the increase of CO2 and SO2 or NOx concentrations in the plume of the ship compared to the background. The measurements were performed from stations at land, from a boat and from a helicopter. Mobile measurement platforms were found to have important advantages compared to the land-based ones because they allow optimizing the sampling conditions and sampling from ships on the open sea. Although optical methods can provide reliable results it was found that at the state of the art level, the "sniffer" approach is the most convenient technique for determining both SO2 and NOx emission factors remotely. The average random error on the determination of SO2 emission factors comparing two identical instrumental set-ups was 6%. However, it was found that apparently minor differences in the instrumental characteristics, such as response time, could cause significant differences between the emission factors determined. Direct stack measurements showed that about 14% of the fuel sulphur content was not emitted as SO2. This was supported by the remote measurements and is in agreement with the results of other field studies.

Air quality assessment of benzo(a)pyrene from asphalt plant operation.

PubMed

Gibson, Nigel; Stewart, Robert; Rankin, Erika

2012-01-01

A study has been carried out to assess the contribution of Polycyclic Aromatic Hydrocarbons (PAHs) from asphalt plant operation, utilising Benzo(a)pyrene (BaP) as a marker for PAHs, to the background air concentration around asphalt plants in the UK. The purpose behind this assessment was to determine whether the use of published BaP emission factors based on the US Environmental Protection Agency (EPA) methodology is appropriate in the context of the UK, especially as the EPA methodology does not give BaP emission factors for all activities. The study also aimed to improve the overall understanding of BaP emissions from asphalt plants in the UK, and determine whether site location and operation is likely to influence the contribution of PAHs to ambient air quality. In order to establish whether the use of US EPA emissions factors is appropriate, the study has compared the BaP emissions measured and calculated emissions rates from two UK sites with those estimated using US EPA emission factors. A dispersion modelling exercise was carried out to show the BaP contribution to ambient air around each site. This study showed that, as the US EPA methodology does not provide factors for all emission sources on asphalt plants, their use may give rise to over- or under-estimations, particularly where sources of BaP are temperature dependent. However, the contribution of both the estimated and measured BaP concentrations to environmental concentration were low, averaging about 0.05 ng m(-3) at the boundary of the sites, which is well below the UK BaP assessment threshold of 0.25 ng m(-3). Therefore, BaP concentrations, and hence PAH concentrations, from similar asphalt plant operations are unlikely to contribute negatively to ambient air quality.

Observation of Solar Wind Charge Exchange Emission From Exospheric Material in and Outside Earth's Magnetosheath 2008 September 25

NASA Technical Reports Server (NTRS)

Snowden, S. L.; Collier, M. R.; Cravens, T.; Kuntz, K. D.; Lepri, S. T.; Robertson, I.; Tomas, L.

2009-01-01

A long XMM-Newton exposure is used to observe solar wind charge exchange (SWCX) emission from exospheric material in and outside Earth's magnetosheath. The light curve of the O vii (0.5-0.62 keV) band is compared with a model for the expected emission, and while the emission is faint and the light curve has considerable scatter, the correlation is significant to better than 99.9%. This result demonstrates the validity of the geocoronal SWCX emission model for predicting a contribution to astrophysical observations to a scale factor of order unity (1.5). In addition, an average value of the SWCX O vii emission from the magnetosheath over the observation of 2.6 +/- 0.5 LU is derived. The results also demonstrate the potential utility of using X-ray observations to study global phenomena of the magnetosheath which currently are only investigated using in situ measurements.

Assessing the Accuracy of the Tracer Dilution Method with Atmospheric Dispersion Modeling

NASA Astrophysics Data System (ADS)

Taylor, D.; Delkash, M.; Chow, F. K.; Imhoff, P. T.

2015-12-01

Landfill methane emissions are difficult to estimate due to limited observations and data uncertainty. The mobile tracer dilution method is a widely used and cost-effective approach for predicting landfill methane emissions. The method uses a tracer gas released on the surface of the landfill and measures the concentrations of both methane and the tracer gas downwind. Mobile measurements are conducted with a gas analyzer mounted on a vehicle to capture transects of both gas plumes. The idea behind the method is that if the measurements are performed far enough downwind, the methane plume from the large area source of the landfill and the tracer plume from a small number of point sources will be sufficiently well-mixed to behave similarly, and the ratio between the concentrations will be a good estimate of the ratio between the two emissions rates. The mobile tracer dilution method is sensitive to different factors of the setup such as placement of the tracer release locations and distance from the landfill to the downwind measurements, which have not been thoroughly examined. In this study, numerical modeling is used as an alternative to field measurements to study the sensitivity of the tracer dilution method and provide estimates of measurement accuracy. Using topography and wind conditions for an actual landfill, a landfill emissions rate is prescribed in the model and compared against the emissions rate predicted by application of the tracer dilution method. Two different methane emissions scenarios are simulated: homogeneous emissions over the entire surface of the landfill, and heterogeneous emissions with a hot spot containing 80% of the total emissions where the daily cover area is located. Numerical modeling of the tracer dilution method is a useful tool for evaluating the method without having the expense and labor commitment of multiple field campaigns. Factors tested include number of tracers, distance between tracers, distance from landfill to transect path, and location of tracers with respect to the hot spot. Results show that location of the tracers relative to the hot spot of highest landfill emissions makes the largest difference in accuracy of the tracer dilution method.

ATMOSPHERIC AEROSOL SOURCE-RECEPTOR RELATIONSHIPS: THE ROLE OF COAL-FIRED POWER PLANTS

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-04-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of September 2004 through February 2005. Significant progress was made this project period on the analysis of ambient data, source apportionment, and deterministic modeling activities. The major experimental achievement this project period was the characterization of the mercury and fine particle emissions from two modern, large, commercial pulverized coal boilers. This testing completes the field work component of the Source Characterization Activity. This report highlights results from mercury emission measurements made using a dilution sampler. The measurements clearly indicate that mercury is beingmore » transformed from an oxidized to an elemental state within the dilution. However, wall effects are significant making it difficult to determine whether or not these changes occur in the gas phase or due to some interaction with the sampler walls. This report also presents results from an analysis that uses spherical aluminum silicate (SAS) particles as a marker for primary PM{sub 2.5} emitted from coal combustion. Primary emissions from coal combustion contribute only a small fraction of the PM{sub 2.5} mass (less than 1.5% in the summer and less than 3% in the winter) at the Pittsburgh site. Ambient SAS concentrations also appear to be reasonably spatially homogeneous. Finally, SAS emission factors measured at pilot-scale are consistent with measurements made at full-scale. This report also presents results from applying the Unmix and PMF models to estimate the contribution of different sources to the PM{sub 2.5} mass concentrations in Pittsburgh using aerosol composition information. Comparison of the two models shows similar source composition and contribution for five factors: crustal material, nitrate, an Fe, Mn, and Zn factor, specialty steel production, and a cadmium factor. PMF found several additional factors. Comparison between source contributions for the similar factors shows reasonable agreement between the two models. The sulfate factor shows the highest contribution to local PM{sub 2.5} with an annual average contribution of approximately 28% (from PMF). The nitrate, crustal material, and primary OC and EC factors also show significant contributions on the order of 10-14%. The sulfate factor is affected by photochemistry and therefore shows maximum values in summer.« less

GHG emission factors developed for the collection, transport and landfilling of municipal waste in South African municipalities

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

Friedrich, Elena, E-mail: Friedriche@ukzn.ac.za; Trois, Cristina

2013-04-15

Highlights: ► An average GHG emission factor for the collection and transport of municipal solid waste in South Africa is calculated. ► A range of GHG emission factors for different types of landfills (including dumps) in South Africa are calculated. ► These factors are compared internationally and their implications for South Africa and developing countries are discussed . ► Areas for new research are highlighted. - Abstract: Greenhouse gas (GHG) emission factors are used with increased frequency for the accounting and reporting of GHG from waste management. However, these factors have been calculated for developed countries of the Northern Hemispheremore » and are lacking for developing countries. This paper shows how such factors have been developed for the collection, transport and landfilling of municipal waste in South Africa. As such it presents a model on how international results and methodology can be adapted and used to calculate country-specific GHG emission factors from waste. For the collection and transport of municipal waste in South Africa, the average diesel consumption is around 5 dm{sup 3} (litres) per tonne of wet waste and the associated GHG emissions are about 15 kg CO{sub 2} equivalents (CO{sub 2} e). Depending on the type of landfill, the GHG emissions from the landfilling of waste have been calculated to range from −145 to 1016 kg CO{sub 2} e per tonne of wet waste, when taking into account carbon storage, and from 441 to 2532 kg CO{sub 2} e per tonne of wet waste, when carbon storage is left out. The highest emission factor per unit of wet waste is for landfill sites without landfill gas collection and these are the dominant waste disposal facilities in South Africa. However, cash strapped municipalities in Africa and the developing world will not be able to significantly upgrade these sites and reduce their GHG burdens if there is no equivalent replacement of the Clean Development Mechanism (CDM) resulting from the Kyoto agreement. Other low cost avenues need to be investigated to suit local conditions, in particular landfill covers which enhance methane oxidation.« less

The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010

NASA Astrophysics Data System (ADS)

Parrington, M.; Palmer, P. I.; Henze, D. K.; Tarasick, D. W.; Hyer, E. J.; Owen, R. C.; Helmig, D.; Clerbaux, C.; Bowman, K. W.; Deeter, M. N.; Barratt, E. M.; Coheur, P.-F.; Hurtmans, D.; George, M.; Worden, J. R.

2011-09-01

We analyse the tropospheric ozone distribution over North America and the North Atlantic to boreal biomass burning emissions during the summer of 2010 using the GEOS-Chem 3-D global tropospheric chemical transport model, and observations from in situ and satellite instruments. In comparison to observations from the PICO-NARE observatory in the Azores, ozonesondes across Canada, and the Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Instrument (IASI) satellite instruments, the model ozone distribution is shown to be in reasonable agreement with mean biases less than 10 ppbv. We use the adjoint of GEOS-Chem to show the model ozone distribution in the free troposphere over Maritime Canada is largely sensitive to NOx emissions from biomass burning sources in Central Canada, lightning sources in the central US, and anthropogenic sources in eastern US and south-eastern Canada. We also use the adjoint of GEOS-Chem to evaluate the Fire Locating And Monitoring of Burning Emissions (FLAMBE) inventory through assimilation of CO observations from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. The CO inversion showed that, on average the FLAMBE emissions needed to be reduced to 89 % of their original values, with scaling factors ranging from 12 % to 102 %, to fit the MOPITT observations in the boreal regions. Applying the CO scaling factors to all species emitted from boreal biomass burning sources led to a decrease of the model tropospheric distributions of CO, PAN, and NOx by as much as -20 ppbv, -50 ppbv, and -20 ppbv respectively. The impact of optimizing the biomass burning emissions was to reduce the model ozone distribution by approximately -3 ppbv (-8 %) and on average improved the agreement of the model ozone distribution compared to the observations throughout the free troposphere reducing the mean model bias from 5.5 to 4.0 ppbv for the PICO-NARE observatory, 3.0 to 0.9 ppbv for ozonesondes, 2.0 to 0.9 ppbv for TES, and 2.8 to 1.4 ppbv for IASI.

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

PubMed

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

2017-11-07

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

A {sup 13}CO Detection in a Brightest Cluster Galaxy

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

Vantyghem, A. N.; McNamara, B. R.; Hogan, M. T.

We present ALMA Cycle 4 observations of CO(1-0), CO(3-2), and {sup 13}CO(3-2) line emission in the brightest cluster galaxy (BCG) of RXJ0821+0752. This is one of the first detections of {sup 13}CO line emission in a galaxy cluster. Half of the CO(3-2) line emission originates from two clumps of molecular gas that are spatially offset from the galactic center. These clumps are surrounded by diffuse emission that extends 8 kpc in length. The detected {sup 13}CO emission is confined entirely to the two bright clumps, with any emission outside of this region lying below our detection threshold. Two distinct velocitymore » components with similar integrated fluxes are detected in the {sup 12}CO spectra. The narrower component (60 km s{sup −1} FWHM) is consistent in both velocity centroid and linewidth with {sup 13}CO(3-2) emission, while the broader (130–160 km s{sup −1}), slightly blueshifted wing has no associated {sup 13}CO(3-2) emission. A simple local thermodynamic model indicates that the {sup 13}CO emission traces 2.1 × 10{sup 9} M {sub ⊙} of molecular gas. Isolating the {sup 12}CO velocity component that accompanies the {sup 13}CO emission yields a CO-to-H{sub 2} conversion factor of α {sub CO} = 2.3 M {sub ⊙} (K km s{sup −1}){sup −1}, which is a factor of two lower than the Galactic value. Adopting the Galactic CO-to-H{sub 2} conversion factor in BCGs may therefore overestimate their molecular gas masses by a factor of two. This is within the object-to-object scatter from extragalactic sources, so calibrations in a larger sample of clusters are necessary in order to confirm a sub-Galactic conversion factor.« less

A new approach to modeling aerosol effects on East Asian climate: Parametric uncertainties associated with emissions, cloud microphysics, and their interactions: AEROSOL EFFECTS ON EAST ASIAN CLIMATE

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

Yan, Huiping; Qian, Yun; Zhao, Chun

2015-09-09

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. Themore » relative importance of cloud-microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC and dust, respectively, in East Asia.« less

Development of WRF-CO2 4DVAR Data Assimilation System

NASA Astrophysics Data System (ADS)

Zheng, T.; French, N. H. F.

2016-12-01

Four dimensional variational (4DVar) assimilation systems have been widely used for CO2 inverse modeling at global scale. At regional scale, however, 4DVar assimilation systems have been lacking. At present, most regional CO2 inverse models use Lagrangian particle backward trajectory tools to compute influence function in an analytical/synthesis framework. To provide a 4DVar based alternative, we developed WRF-CO2 4DVAR based on Weather Research and Forecasting (WRF), its chemistry extension (WRF-Chem), and its data assimilation system (WRFDA/WRFPLUS). Different from WRFDA, WRF-CO2 4DVAR does not optimize meteorology initial condition, instead it solves for the optimized CO2 surface fluxes (sources/sink) constrained by atmospheric CO2 observations. Based on WRFPLUS, we developed tangent linear and adjoint code for CO2 emission, advection, vertical mixing in boundary layer, and convective transport. Furthermore, we implemented an incremental algorithm to solve for optimized CO2 emission scaling factors by iteratively minimizing the cost function in a Bayes framework. The model sensitivity (of atmospheric CO2 with respect to emission scaling factor) calculated by tangent linear and adjoint model agrees well with that calculated by finite difference, indicating the validity of the newly developed code. The effectiveness of WRF-CO2 4DVar for inverse modeling is tested using forward-model generated pseudo-observation data in two experiments: first-guess CO2 fluxes has a 50% overestimation in the first case and 50% underestimation in the second. In both cases, WRF-CO2 4DVar reduces cost function to less than 10-4 of its initial values in less than 20 iterations and successfully recovers the true values of emission scaling factors. We expect future applications of WRF-CO2 4DVar with satellite observations will provide insights for CO2 regional inverse modeling, including the impacts of model transport error in vertical mixing.

Variations in embodied energy and carbon emission intensities of construction materials

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

Wan Omar, Wan-Mohd-Sabki; School of Environmental Engineering, Universiti Malaysia Perlis, 02600 Arau, Perlis; Doh, Jeung-Hwan, E-mail: j.doh@griffith.edu.au

2014-11-15

Identification of parameter variation allows us to conduct more detailed life cycle assessment (LCA) of energy and carbon emission material over their lifecycle. Previous research studies have demonstrated that hybrid LCA (HLCA) can generally overcome the problems of incompleteness and accuracy of embodied energy (EE) and carbon (EC) emission assessment. Unfortunately, the current interpretation and quantification procedure has not been extensively and empirically studied in a qualitative manner, especially in hybridising between the process LCA and I-O LCA. To determine this weakness, this study empirically demonstrates the changes in EE and EC intensities caused by variations to key parameters inmore » material production. Using Australia and Malaysia as a case study, the results are compared with previous hybrid models to identify key parameters and issues. The parameters considered in this study are technological changes, energy tariffs, primary energy factors, disaggregation constant, emission factors, and material price fluctuation. It was found that changes in technological efficiency, energy tariffs and material prices caused significant variations in the model. Finally, the comparison of hybrid models revealed that non-energy intensive materials greatly influence the variations due to high indirect energy and carbon emission in upstream boundary of material production, and as such, any decision related to these materials should be considered carefully. - Highlights: • We investigate the EE and EC intensity variation in Australia and Malaysia. • The influences of parameter variations on hybrid LCA model were evaluated. • Key significant contribution to the EE and EC intensity variation were identified. • High indirect EE and EC content caused significant variation in hybrid LCA models. • Non-energy intensive material caused variation between hybrid LCA models.« less

Emissions from international shipping: 2. Impact of future technologies on scenarios until 2050

NASA Astrophysics Data System (ADS)

Eyring, V.; KöHler, H. W.; Lauer, A.; Lemper, B.

2005-09-01

In this study the today's fleet-average emission factors of the most important ship exhausts are used to calculate emission scenarios for the future. To develop plausible future technology scenarios, first upcoming regulations and compliance with future regulations through technological improvements are discussed. We present geographically resolved emission inventory scenarios until 2050, based on a mid-term prognosis for 2020 and a long-term prognosis for 2050. The scenarios are based on some very strict assumptions on future ship traffic demands and technological improvements. The four future ship traffic demand scenarios are mainly determined by the economic growth, which follows the IPCC SRES storylines. The resulting fuel consumption is projected through extrapolations of historical trends in economic growth, total seaborne trade and number of ships, as well as the average installed power per ship. For the future technology scenarios we assume a diesel-only fleet in 2020 resulting in fuel consumption between 382 and 409 million metric tons (Mt). For 2050 one technology scenario assumes that 25% of the fuel consumed by a diesel-only fleet can be saved by applying future alternative propulsion plants, resulting in a fuel consumption that varies between 402 and 543 Mt. The other scenario is a business-as-usual scenario for a diesel-only fleet even in 2050 and gives an estimate between 536 and 725 Mt. Dependent on how rapid technology improvements for diesel engines are introduced, possible technology reduction factors are applied to the today's fleet-average emission factors of all important species to estimate future ship emissions. Combining the four traffic demand scenarios with the four technology scenarios, our results suggest emissions between 8.8 and 25.0 Tg (NO2) in 2020, and between 3.1 to 38.8 Tg (NO2) in 2050. The development of forecast scenarios for CO2, NOx, SOx, CO, hydrocarbons, and particulate matter is driven by the requirements for global model studies of the effects of these emissions on the chemical composition of the atmosphere and on climate. The developed scenarios are suitable for use as input for chemical transport models (CTMs) and coupled chemistry-climate models (CCMs).

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.

Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

NASA Astrophysics Data System (ADS)

Christian, Kenneth E.; Brune, William H.; Mao, Jingqiu; Ren, Xinrong

2018-02-01

Making sense of modeled atmospheric composition requires not only comparison to in situ measurements but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3), hydroxyl radical (OH), and hydroperoxyl radical (HO2) mixing ratios, and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA Intercontinental Chemical Transport Experiment (INTEX) campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally overpredicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

Modeling the impact of solid noise barriers on near road air ...

EPA Pesticide Factsheets

Studies based on field measurements, wind tunnel experiments, and controlled tracer gas releases indicate that solid, roadside noise barriers can lead to reductions in downwind near-road air pollutant concentrations. A tracer gas study showed that a solid barrier reduced pollutant concentrations as much as 80% next to the barrier relative to an open area under unstable meteorological conditions, which corresponds to typical daytime conditions when residents living or children going to school near roadways are most likely to be exposed to traffic emissions. The data from this tracer gas study and a wind tunnel simulation were used to develop a model to describe dispersion of traffic emissions near a highway in the presence of a solid noise barrier. The model is used to interpret real-world data collected during a field study conducted in a complex urban environment next to a large highway in Phoenix, Arizona, USA. We show that the analysis of the data with the model yields useful information on the emission factors and the mitigation impact of the barrier on near-road air quality. The estimated emission factors for the four species, ultrafine particles, CO, NO2, and black carbon, are consistent with data cited in the literature. The results suggest that the model accounted for reductions in pollutant concentrations from a 4.5 m high noise barrier, ranging from 40% next to the barrier to 10% at 300 m from the barrier. Highlights • Developed a dispersion model a

Towards national-scale greenhouse gas emissions evaluation with robust uncertainty estimates

NASA Astrophysics Data System (ADS)

Rigby, Matthew; Swallow, Ben; Lunt, Mark; Manning, Alistair; Ganesan, Anita; Stavert, Ann; Stanley, Kieran; O'Doherty, Simon

2016-04-01

Through the Deriving Emissions related to Climate Change (DECC) network and the Greenhouse gAs Uk and Global Emissions (GAUGE) programme, the UK's greenhouse gases are now monitored by instruments mounted on telecommunications towers and churches, on a ferry that performs regular transects of the North Sea, on-board a research aircraft and from space. When combined with information from high-resolution chemical transport models such as the Met Office Numerical Atmospheric dispersion Modelling Environment (NAME), these measurements are allowing us to evaluate emissions more accurately than has previously been possible. However, it has long been appreciated that current methods for quantifying fluxes using atmospheric data suffer from uncertainties, primarily relating to the chemical transport model, that have been largely ignored to date. Here, we use novel model reduction techniques for quantifying the influence of a set of potential systematic model errors on the outcome of a national-scale inversion. This new technique has been incorporated into a hierarchical Bayesian framework, which can be shown to reduce the influence of subjective choices on the outcome of inverse modelling studies. Using estimates of the UK's methane emissions derived from DECC and GAUGE tall-tower measurements as a case study, we will show that such model systematic errors have the potential to significantly increase the uncertainty on national-scale emissions estimates. Therefore, we conclude that these factors must be incorporated in national emissions evaluation efforts, if they are to be credible.

The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN

NASA Astrophysics Data System (ADS)

Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.

2012-01-01

Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.

Preoperative predictive model of cervical lymph node metastasis combining fluorine-18 fluorodeoxyglucose positron-emission tomography/computerized tomography findings and clinical factors in patients with oral or oropharyngeal squamous cell carcinoma.

PubMed

Mochizuki, Yumi; Omura, Ken; Nakamura, Shin; Harada, Hiroyuki; Shibuya, Hitoshi; Kurabayashi, Toru

2012-02-01

This study aimed to construct a preoperative predictive model of cervical lymph node metastasis using fluorine-18 fluorodeoxyglucose positron-emission tomography/computerized tomography ((18)F-FDG PET/CT) findings in patients with oral or oropharyngeal squamous cell carcinoma (SCC). Forty-nine such patients undergoing preoperative (18)F-FDG PET/CT and neck dissection or lymph node biopsy were enrolled. Retrospective comparisons with spatial correlation between PET/CT and the anatomical sites based on histopathological examinations of surgical specimens were performed. We calculated a logistic regression model, including the SUVmax-related variable. When using the optimal cutoff point criterion of probabilities calculated from the model that included either clinical factors and delayed-phase SUVmax ≥0.087 or clinical factors and maximum standardized uptake (SUV) increasing rate (SUV-IR) ≥ 0.100, it significantly increased the sensitivity, specificity, and accuracy (87.5%, 65.7%, and 75.2%, respectively). The use of predictive models that include clinical factors and delayed-phase SUVmax and SUV-IR improve preoperative nodal diagnosis. Copyright © 2012 Elsevier Inc. All rights reserved.

THE KINEMATICS AND IONIZATION OF NUCLEAR GAS CLOUDS IN CENTAURUS A

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

Bicknell, Geoffrey V.; Sutherland, Ralph S.; Neumayer, Nadine, E-mail: Geoff.Bicknell@anu.edu.au, E-mail: Ralph.Sutherland@anu.edu.au, E-mail: nadine.neumayer@universe-cluster.de

2013-03-20

Neumayer et al. established the existence of a blueshifted cloud in the core of Centaurus A, within a few parsecs of the nucleus and close to the radio jet. We propose that the cloud has been impacted by the jet, and that it is in the foreground of the jet, accounting for its blueshifted emission on the southern side of the nucleus. We consider both shock excitation and photoionization models for the excitation of the cloud. Shock models do not account for the [Si VI] and [Ca VIII] emission line fluxes. However, X-ray observations indicate a source of ionizing photonsmore » in the core of Centaurus A; photoionization by the inferred flux incident on the cloud can account for the fluxes in these lines relative to Brackett-{gamma}. The power-law slope of the ionizing continuum matches that inferred from synchrotron models of the X-rays. The logarithm of the ionization parameter is -1.9, typical of that in Seyfert galaxies and consistent with the value proposed for dusty ionized plasmas. The model cloud density depends upon the Lorentz factor of the blazar and the inclination of our line of sight to the jet axis. For acute inclinations, the inferred density is consistent with expected cloud densities. However, for moderate inclinations of the jet to the line of sight, high Lorentz factors imply cloud densities in excess of 10{sup 5} cm{sup -3} and very low filling factors, suggesting that models of the gamma-ray emission should incorporate jet Lorentz factors {approx}< 5.« less

A hadronic origin for ultra-high-frequency-peaked BL Lac objects

NASA Astrophysics Data System (ADS)

Cerruti, M.; Zech, A.; Boisson, C.; Inoue, S.

2015-03-01

Current Cherenkov telescopes have identified a population of ultra-high-frequency peaked BL Lac objects (UHBLs), also known as extreme blazars, that exhibit exceptionally hard TeV spectra, including 1ES 0229+200, 1ES 0347-121, RGB J0710+591, 1ES 1101-232, and 1ES 1218+304. Although one-zone synchrotron-self-Compton (SSC) models have been generally successful in interpreting the high-energy emission observed in other BL Lac objects, they are problematic for UHBLs, necessitating very large Doppler factors and/or extremely high minimum Lorentz factors of the emitting leptonic population. In this context, we have investigated alternative scenarios where hadronic emission processes are important, using a newly developed (lepto-)hadronic numerical code to systematically explore the physical parameters of the emission region that reproduces the observed spectra while avoiding the extreme values encountered in pure SSC models. Assuming a fixed Doppler factor δ = 30, two principal parameter regimes are identified, where the high-energy emission is due to: (1) proton-synchrotron radiation, with magnetic fields B ˜ 1-100 G and maximum proton energies Ep; max ≲ 1019 eV; and (2) synchrotron emission from p-γ-induced cascades as well as SSC emission from primary leptons, with B ˜ 0.1-1 G and Ep; max ≲ 1017 eV. This can be realized with plausible, sub-Eddington values for the total (kinetic plus magnetic) power of the emitting plasma, in contrast to hadronic interpretations for other blazar classes that often warrant highly super-Eddington values.

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

PubMed

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

2016-03-01

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

Mercury emissions from biomass burning in China.

PubMed

Huang, Xin; Li, Mengmeng; Friedli, Hans R; Song, Yu; Chang, Di; Zhu, Lei

2011-11-01

Biomass burning covers open fires (forest and grassland fires, crop residue burning in fields, etc.) and biofuel combustion (crop residues and wood, etc., used as fuel). As a large agricultural country, China may produce large quantities of mercury emissions from biomass burning. A new mercury emission inventory in China is needed because previous studies reflected outdated biomass burning with coarse resolution. Moreover, these studies often adopted the emission factors (mass of emitted species per mass of biomass burned) measured in North America. In this study, the mercury emissions from biomass burning in China (excluding small islands in the South China Sea) were estimated, using recently measured mercury concentrations in various biomes in China as emission factors. Emissions from crop residues and fuelwood were estimated based on annual reports distributed by provincial government. Emissions from forest and grassland fires were calculated by combining moderate resolution imaging spectroradiometer (MODIS) burned area product with combustion efficiency (ratio of fuel consumption to total available fuels) considering fuel moisture. The average annual emission from biomass burning was 27 (range from 15.1 to 39.9) Mg/year. This inventory has high spatial resolution (1 km) and covers a long period (2000-2007), making it useful for air quality modeling.

Gas- and particle-phase primary emissions from in-use, on-road gasoline and diesel vehicles

NASA Astrophysics Data System (ADS)

May, Andrew A.; Nguyen, Ngoc T.; Presto, Albert A.; Gordon, Timothy D.; Lipsky, Eric M.; Karve, Mrunmayi; Gutierrez, Alváro; Robertson, William H.; Zhang, Mang; Brandow, Christopher; Chang, Oliver; Chen, Shiyan; Cicero-Fernandez, Pablo; Dinkins, Lyman; Fuentes, Mark; Huang, Shiou-Mei; Ling, Richard; Long, Jeff; Maddox, Christine; Massetti, John; McCauley, Eileen; Miguel, Antonio; Na, Kwangsam; Ong, Richard; Pang, Yanbo; Rieger, Paul; Sax, Todd; Truong, Tin; Vo, Thu; Chattopadhyay, Sulekha; Maldonado, Hector; Maricq, M. Matti; Robinson, Allen L.

2014-05-01

Tailpipe emissions from sixty-four unique light-duty gasoline vehicles (LDGVs) spanning model years 1987-2012, two medium-duty diesel vehicles and three heavy-duty diesel vehicles with varying levels of aftertreatment were characterized at the California Air Resources Board Haagen-Smit and Heavy-Duty Engine Testing Laboratories. Each vehicle was tested on a chassis dynamometer using a constant volume sampler, commercial fuels and standard duty cycles. Measurements included regulated pollutants such as carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particulate matter (PM). Off-line analyses were performed to speciate gas- and particle-phase emissions. The data were used to investigate trends in emissions with vehicle age and to quantify the effects of different aftertreatment technologies on diesel vehicle emissions (e.g., with and without a diesel particulate filter). On average, newer LDGVs that met the most recent emissions standards had substantially lower emissions of regulated gaseous pollutants (CO, THC and NOx) than older vehicles. For example, THC emissions from the median LDGV that met the LEV2 standard was roughly a factor of 10 lower than the median pre-LEV vehicle; there were also substantial reductions in NOx (factor of ∼100) and CO (factor of ∼10) emissions from pre-LEV to LEV2 vehicles. However, reductions in LDGV PM mass emissions were much more modest. For example, PM emission from the median LEV2 vehicle was only a factor of three lower than the median pre-LEV vehicle, mainly due to the reductions in organic carbon emissions. In addition, LEV1 and LEV2 LDGVs had similar PM emissions. Catalyzed diesel particulate filters reduced CO, THC and PM emissions from HDDVs by one to two orders of magnitude. Comprehensive organic speciation was performed to quantify priority air toxic emissions and to estimate the secondary organic aerosol (SOA) formation potential. The data suggest that the SOA production from cold-start LDGVs exhaust will likely exceed primary PM emissions from LDGVs and could potentially exceed SOA formation from on-road diesel vehicles.

Development of a life-cycle fugitive methane emissions model utilizing device level emissions and activity factors

NASA Astrophysics Data System (ADS)

Englander, J.; Brandt, A. R.

2017-12-01

There has been numerous studies in quantifying the scale of fugitive emissions from across the natural gas value chain. These studies have typically focused on either specific types of equipment (such as valves) or on a single part of the life-cycle of natural gas production (such as gathering stations).1,2 However it has been demonstrated that average emissions factors are not sufficient for representing leaks in the natural gas system.3 In this work, we develop a robust estimate of fugitive emissions rates by incorporating all publicly available studies done at the component up to the process level. From these known studies, we create a database of leaks with normalized nomenclature from which leak estimates can be drawn from actual leak observations. From this database, and parameterized by meta-data such as location, scale of study, or placement in the life-cycle, we construct stochastic emissions factors specific for each process unit. This will be an integrated tool as part of the Oil production greenhouse gas estimator (OPGEE) as well as the Fugitive Emissions Abatement Simulation Toolkit (FEAST) models to enhances their treatment of venting and fugitive emissions, and will be flexible to include user provided data and input parameters.4,51. Thoma, ED et al. Assessment of Uinta Basin Oil and Natural Gas Well Pad Pneumatic Controller Emissions. J. Environ. Prot. 2017. 2. Marchese, AJ et al. Methane Emissions from United States Natural Gas Gathering and Processing. ES&T 2015. doi:10.1021/acs.est.5b02275 3. Brandt, AR et al. Methane Leaks from Natural Gas Systems Follow Extreme Distributions. ES&T 2016. doi:10.1021/acs.est.6b04303 4. El-Houjeiri, HM et al. An open-source LCA tool estimating greenhouse gas emissions from crude oil production using field characteristics. ES&T 2013. doi: 10.1021/es304570m 5. Kemp, CE et al. Comparing Natural Gas Leakage Detection Technologies Using an Open-Source `Virtual Gas Field' Simulator. ES&T 2016. doi:10.1021/acs.est.5b06068

Measuring Greenhouse Gas Emissions and Sinks Across California Land Cover

NASA Astrophysics Data System (ADS)

Fischer, M. L.

2017-12-01

Significant reductions in greenhouse gas (GHG) emissions are needed to limit rising planetary temperatures that will otherwise limit Earth's capacity to support life, introducing geopolitical instability. To help mitigate this threat, California has legislated landmark reductions in state-level greenhouse gas (GHG) emissions that set an example for broader action. Beginning with relatively assured reduction of current emissions to 1990 levels by 2020, future goals are much more challenging with 40% and 80% reductions below 1990 emissions by 2030 and 2050, respectively. While the majority of the reductions must focus on fossil fuels, inventory estimates of non-CO2 GHG emissions (i.e., CH4, N2O, and industrial compounds) constitute 15% of the total, suggesting reductions are required across multiple land use sectors. However, recent atmospheric inversion studies show methane and nitrous oxide (CH4 & N2O) emissions exceed current inventory estimates by factors of 1.2-1.8 and 1.6-2.6 (at 95% confidence), respectively, perhaps constituting up to 30% of State total emissions. The discrepancy is likely because current bottom-up models used for inventories do not accurately capture important management or biophysical factors. In the near term, process level experiments and sector-specific inversions are being planned to quantify the factors controlling non-CO2 GHG emissions for several of the dominant emission sectors. For biosphere carbon, California forests lands, which also depend on the combination of management, climate, and weather, lost above ground carbon from 2001-2010, and may be expected to lose soil and root carbon as a longer-term result. Here, it is important to identify and apply the best principles in forestry and agriculture to increase carbon stocks in depleted forest and agricultural areas, focusing on approaches that provide resilience to future climate and weather variations. Taken together, improved atmospheric, plant, and soil observations, together with empirical and/or process-level models should be developed to quantify current trajectories of both biological CO2 exchange and non-CO2 GHG emissions, identify knowledge gaps, and guide mitigation policies.

High-resolution inversion of OMI formaldehyde columns to quantify isoprene emission on ecosystem-relevant scales: application to the southeast US

NASA Astrophysics Data System (ADS)

Kaiser, Jennifer; Jacob, Daniel J.; Zhu, Lei; Travis, Katherine R.; Fisher, Jenny A.; González Abad, Gonzalo; Zhang, Lin; Zhang, Xuesong; Fried, Alan; Crounse, John D.; St. Clair, Jason M.; Wisthaler, Armin

2018-04-01

Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Bottom-up isoprene emission inventories used in atmospheric models are based on limited vegetation information and uncertain land cover data, leading to potentially large errors. Satellite observations of atmospheric formaldehyde (HCHO), a high-yield isoprene oxidation product, provide top-down information to evaluate isoprene emission inventories through inverse analyses. Past inverse analyses have however been hampered by uncertainty in the HCHO satellite data, uncertainty in the time- and NOx-dependent yield of HCHO from isoprene oxidation, and coarse resolution of the atmospheric models used for the inversion. Here we demonstrate the ability to use HCHO satellite data from OMI in a high-resolution inversion to constrain isoprene emissions on ecosystem-relevant scales. The inversion uses the adjoint of the GEOS-Chem chemical transport model at 0.25° × 0.3125° horizontal resolution to interpret observations over the southeast US in August-September 2013. It takes advantage of concurrent NASA SEAC4RS aircraft observations of isoprene and its oxidation products including HCHO to validate the OMI HCHO data over the region, test the GEOS-Chem isoprene oxidation mechanism and NOx environment, and independently evaluate the inversion. This evaluation shows in particular that local model errors in NOx concentrations propagate to biases in inferring isoprene emissions from HCHO data. It is thus essential to correct model NOx biases, which was done here using SEAC4RS observations but can be done more generally using satellite NO2 data concurrently with HCHO. We find in our inversion that isoprene emissions from the widely used MEGAN v2.1 inventory are biased high over the southeast US by 40 % on average, although the broad-scale distributions are correct including maximum emissions in Arkansas/Louisiana and high base emission factors in the oak-covered Ozarks of southeast Missouri. A particularly large discrepancy is in the Edwards Plateau of central Texas where MEGAN v2.1 is too high by a factor of 3, possibly reflecting errors in land cover. The lower isoprene emissions inferred from our inversion, when implemented into GEOS-Chem, decrease surface ozone over the southeast US by 1-3 ppb and decrease the isoprene contribution to organic aerosol from 40 to 20 %.

Characterization factors for thermal pollution in freshwater aquatic environments.

PubMed

Verones, Francesca; Hanafiah, Marlia Mohd; Pfister, Stephan; Huijbregts, Mark A J; Pelletier, Gregory J; Koehler, Annette

2010-12-15

To date the impact of thermal emissions has not been addressed in life cycle assessment despite the narrow thermal tolerance of most aquatic species. A method to derive characterization factors for the impact of cooling water discharges on aquatic ecosystems was developed which uses space and time explicit integration of fate and effects of water temperature changes. The fate factor is calculated with a 1-dimensional steady-state model and reflects the residence time of heat emissions in the river. The effect factor specifies the loss of species diversity per unit of temperature increase and is based on a species sensitivity distribution of temperature tolerance intervals for various aquatic species. As an example, time explicit characterization factors were calculated for the cooling water discharge of a nuclear power plant in Switzerland, quantifying the impact on aquatic ecosystems of the rivers Aare and Rhine. The relative importance of the impact of these cooling water discharges was compared with other impacts in life cycle assessment. We found that thermal emissions are relevant for aquatic ecosystems compared to other stressors, such as chemicals and nutrients. For the case of nuclear electricity investigated, thermal emissions contribute between 3% and over 90% to Ecosystem Quality damage.

Variability in Light-Duty Gasoline Vehicle Emission Factors from Trip-Based Real-World Measurements.

PubMed

Liu, Bin; Frey, H Christopher

2015-10-20

Using data obtained with portable emissions measurements systems (PEMS) on multiple routes for 100 gasoline vehicles, including passenger cars (PCs), passenger trucks (PTs), and hybrid electric vehicles (HEVs), variability in tailpipe emission rates was evaluated. Tier 2 emission standards are shown to be effective in lowering NOx, CO, and HC emission rates. Although PTs are larger, heavier vehicles that consume more fuel and produce more CO2 emissions, they do not necessarily produce more emissions of regulated pollutants compared to PCs. HEVs have very low emission rates compared to tier 2 vehicles under real-world driving. Emission factors vary with cycle average speed and road type, reflecting the combined impact of traffic control and traffic congestion. Compared to the slowest average speed and most congested cycles, optimal emission rates could be 50% lower for CO2, as much as 70% lower for NOx, 40% lower for CO, and 50% lower for HC. There is very high correlation among vehicles when comparing driving cycles. This has implications for how many cycles are needed to conduct comparisons between vehicles, such as when comparing fuels or technologies. Concordance between empirical and predicted emission rates using the U.S. Environmental Protection Agency's MOVES model was also assessed.

Heating with Biomass in the United Kingdom: Lessons from New Zealand

NASA Astrophysics Data System (ADS)

Mitchell, E. J. S.; Coulson, G.; Butt, E. W.; Forster, P. M.; Jones, J. M.; Williams, A.

2017-03-01

In this study we review the current status of residential solid fuel (RSF) use in the UK and compare it with New Zealand, which has had severe wintertime air quality issues for many years that is directly attributable to domestic wood burning in heating stoves. Results showed that RSF contributed to more than 40 μg m-3 PM10 and 10 μg m-3 BC in some suburban locations of New Zealand in 2006, with significant air quality and climate impacts. Models predict RSF consumption in New Zealand to decrease slightly from 7 PJ to 6 PJ between 1990 and 2030, whereas consumption in the UK increases by a factor of 14. Emissions are highest from heating stoves and fireplaces, and their calculated contribution to radiative forcing in the UK increases by 23% between 2010 and 2030, with black carbon accounting for more than three quarters of the total warming effect. By 2030, the residential sector accounts for 44% of total BC emissions in the UK and far exceeds emissions from the traffic sector. Finally, a unique bottom-up emissions inventory was produced for both countries using the latest national survey and census data for the year 2013/14. Fuel- and technology-specific emissions factors were compared between multiple inventories including GAINS, the IPCC, the EMEP/EEA and the NAEI. In the UK, it was found that wood consumption in stoves was within 30% of the GAINS inventory, but consumption in fireplaces was substantially higher and fossil fuel consumption is more than twice the GAINS estimate. As a result, emissions were generally a factor of 2-3 higher for biomass and 2-6 higher for coal. In New Zealand, coal and lignite consumption in stoves is within 24% of the GAINS inventory estimate, but wood consumption is more than 7 times the GAINS estimate. As a result, emissions were generally a factor of 1-2 higher for coal and several times higher for wood. The results of this study indicate that emissions from residential heating stoves and fireplaces may be underestimated in climate models. Emissions are increasing rapidly in the UK which may result in severe wintertime air quality reductions, as seen in New Zealand, and contribute to climate warming unless controls are implemented such as the Ecodesign emissions limits.

B Stars with and without emission lines, parts 1 and 2

NASA Technical Reports Server (NTRS)

Underhill, A. (Editor); Doazan, V. (Editor)

1982-01-01

The spectra for B stars for which emission lines occur not on the main sequence, but only among the supergiants, and those B stars for which the presence of emission in H ahlpa is considered to be a significant factor in delineating atmospheric structure are examined. The development of models that are compatible with all known facts about a star and with the laws of physics is also discussed.

40 CFR Table 5 to Subpart Mmmm of... - Model Rule-Toxic Equivalency Factors

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 7 2013-07-01 2013-07-01 false Model Rule-Toxic Equivalency Factors 5 Table 5 to Subpart MMMM of Part 60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge...

40 CFR Table 5 to Subpart Mmmm of... - Model Rule-Toxic Equivalency Factors

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 7 2014-07-01 2014-07-01 false Model Rule-Toxic Equivalency Factors 5 Table 5 to Subpart MMMM of Part 60 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines and Compliance Times for Existing Sewage Sludge...

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

New and Revised Emissions Factors for Flares and New Emissions Factors for Certain Refinery Process Units and Determination for No Changes to VOC Emissions Factors for Tanks and Wastewater Treatment Systems

EPA Pesticide Factsheets

New and Revised Emission Factors for Flares and New Emission Factors for Certain Refinery Process Units and Determination for No Changes to VOC Emission Factors for Tanks and Wastewater Treatment Systems

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

Devereux, Nick, E-mail: devereux@erau.edu

Prior imaging of the lenticular galaxy, NGC 3998, with the Hubble Space Telescope revealed a small, highly inclined, nuclear ionized gas disk, the kinematics of which indicate the presence of a 270 million solar mass black hole. Plausible kinematic models are used to constrain the size of the broad emission line region (BELR) in NGC 3998 by modeling the shape of the broad H{alpha}, H{beta}, and H{gamma} emission line profiles. The analysis indicates that the BELR is large with an outer radius {approx}7 pc, regardless of whether the kinematic model is represented by an accretion disk or a spherically symmetricmore » inflow. The electron temperature in the BELR is {<=} 28,800 K consistent with photoionization by the active galactic nucleus (AGN). Indeed, the AGN is able to sustain the ionization of the BELR, albeit with a high covering factor ranging between 20% and 100% depending on the spectral energy distribution adopted for the AGN. The high covering factor favors a spherical distribution for the gas as opposed to a thin disk. If the gas density is {>=}7 x 10{sup 3} cm{sup -3} as indicated by the broad forbidden [S II] emission line ratio, then interpreting the broad H{alpha} emission line in terms of a steady state spherically symmetric inflow leads to a rate {<=} 6.5 x 10{sup -2} M{sub sun} yr{sup -1} which exceeds the inflow requirement to explain the X-ray luminosity in terms of a radiatively inefficient inflow by a factor of {<=}18.« less

Space Telescope Imaging Spectrograph Spectroscopy of the Central 14 pc OF NGC 3998: Evidence for an Inflow

NASA Astrophysics Data System (ADS)

Devereux, Nick

2011-02-01

Prior imaging of the lenticular galaxy, NGC 3998, with the Hubble Space Telescope revealed a small, highly inclined, nuclear ionized gas disk, the kinematics of which indicate the presence of a 270 million solar mass black hole. Plausible kinematic models are used to constrain the size of the broad emission line region (BELR) in NGC 3998 by modeling the shape of the broad Hα, Hβ, and Hγ emission line profiles. The analysis indicates that the BELR is large with an outer radius ~7 pc, regardless of whether the kinematic model is represented by an accretion disk or a spherically symmetric inflow. The electron temperature in the BELR is <= 28,800 K consistent with photoionization by the active galactic nucleus (AGN). Indeed, the AGN is able to sustain the ionization of the BELR, albeit with a high covering factor ranging between 20% and 100% depending on the spectral energy distribution adopted for the AGN. The high covering factor favors a spherical distribution for the gas as opposed to a thin disk. If the gas density is >=7 × 103 cm-3 as indicated by the broad forbidden [S II] emission line ratio, then interpreting the broad Hα emission line in terms of a steady state spherically symmetric inflow leads to a rate <= 6.5 × 10-2 M sun yr-1 which exceeds the inflow requirement to explain the X-ray luminosity in terms of a radiatively inefficient inflow by a factor of <=18.

Modeling and simulation for the field emission of carbon nanotubes array

NASA Astrophysics Data System (ADS)

Wang, X. Q.; Wang, M.; Ge, H. L.; Chen, Q.; Xu, Y. B.

2005-12-01

To optimize the field emission of the infinite carbon nanotubes (CNTs) array on a planar cathode surface, the numerical simulation for the behavior of field emission with finite difference method was proposed. By solving the Laplace equation with computer, the influence of the intertube distance, the anode-cathode distance and the opened/capped CNT on the field emission of CNTs array were taken into account, and the results could accord well with the experiments. The simulated results proved that the field enhancement factor of individual CNT is largest, but the emission current density is little. Due to the enhanced screening of the electric field, the enhancement factor of CNTs array decreases with decreasing the intertube distance. From the simulation the field emission can be optimized when the intertube distance is close to the tube height. The anode-cathode distance hardly influences the field enhancement factor of CNTs array, but can low the threshold voltage by decreasing the anode-cathode distance. Finally, the distribution of potential of the capped CNTs array and the opened CNTs array was simulated, which the results showed that the distribution of potential can be influenced to some extent by the anode-cathode distance, especially at the apex of the capped CNTs array and the brim of the opened CNTs array. The opened CNTs array has larger field enhancement factor and can emit more current than the capped one.

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

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.

APPLICATION OF PSCF TO PMF-MODELED SOURCES OF PM2.5 IN RIVERSIDE USING 1-HR AVERAGED DATA

EPA Science Inventory

Data from semi-continuous instruments employed during a sampling campaign in Riverside, CA in July-August 2005 was used in a PMF2 analysis and sixteen sources were identified. Factors attributed to being primarily from local automobile emissions, local diesel emissions, wood comb...

Particulate-phase mercury emissions from biomass burning and impact on resulting deposition: a modelling assessment

EPA Science Inventory

Mercury (Hg) emissions from biomass burning (BB) are an important source of atmospheric Hg and a major factor driving the interannual variation of Hg concentrations in the troposphere. The greatest fraction of Hg from BB is released in the form of elemental Hg (Hg0(g)). However, ...

VALIDATION OF A METHOD FOR ESTIMATING POLLUTION EMISSION RATES FROM AREA SOURCES USING OPEN-PATH FTIR SEPCTROSCOPY AND DISPERSION MODELING TECHNIQUES

EPA Science Inventory

The paper describes a methodology developed to estimate emissions factors for a variety of different area sources in a rapid, accurate, and cost effective manner. he methodology involves using an open-path Fourier transform infrared (FTIR) spectrometer to measure concentrations o...

Isoprene emissions over Asia 1979-2012: impact of climate and land use changes

NASA Astrophysics Data System (ADS)

Stavrakou, T.; Müller, J.-F.; Bauwens, M.; De Smedt, I.; Van Roozendael, M.; Guenther, A.; Wild, M.; Xia, X.

2013-11-01

Due to the scarcity of observational constraints and the rapidly changing environment in East and Southeast Asia, isoprene emissions predicted by models are expected to bear substantial uncertainties. The aim of this study is to improve upon the existing bottom-up estimates, and investigate the temporal evolution of the fluxes in Asia over 1979-2012. To this purpose, we calculate the hourly emissions at 0.5° × 0.5° resolution using the MEGAN-MOHYCAN model driven by ECMWF ERA-Interim climatology. This study incorporates (i) changes in land use, including the rapid expansion of oil palms, (ii) meteorological variability according to ERA-Interim, (iii) long-term changes in solar radiation (dimming/brightening) constrained by surface network radiation measurements, and (iv) recent experimental evidence that South Asian tropical forests are much weaker isoprene emitters than previously assumed, and on the other hand, that oil palms hold a strong isoprene emission capacity. These effects lead to a significant lowering (factor of two) in the total isoprene fluxes over the studied domain, and to emission reductions reaching a~factor of 3.5 in Southeast Asia. The bottom-up annual isoprene emissions for 2005 are estimated at 7.0, 4.8, 8.3, 2.9 Tg in China, India, Indonesia and Malaysia, respectively. Changes in temperature and solar radiation are the major drivers of the interannual variability and trend in the emissions. An annual positive flux trend of 0.2% and 0.52% is found in Asia and China, respectively, through the entire period, related to positive trend in temperature and solar radiation. The impact of oil palm expansion in Indonesia and Malaysia is to enhance the trends over that region, e.g. from 1.17% to 1.5% in 1979-2005 in Malaysia. A negative emission trend is derived in India (-0.4%), owing to the negative trend in solar radiation data associated to the strong dimming effect likely due to increasing aerosol loadings. The bottom-up emissions are evaluated using top-down isoprene emission estimates derived from inverse modelling constrained by GOME-2/MetOp-A formaldehyde columns through 2007-2012. The satellite-based estimates appear to support our assumptions, and confirm the lower emission rate in tropical forests of Indonesia and Malaysia. Additional flux measurements are clearly needed to better characterize the spatial variability of emission factors. Finally, a decreasing trend in the top-down Chinese emissions inferred after 2007, is in line with the cooling episode recorded in China after that year, thus suggesting that the satellite HCHO columns are able to capture climate-induced changes in emissions.

Flying into the future: aviation emissions scenarios to 2050.

PubMed

Owen, Bethan; Lee, David S; Lim, Ling

2010-04-01

This study describes the methodology and results for calculating future global aviation emissions of carbon dioxide and oxides of nitrogen from air traffic under four of the IPCC/SRES (Intergovernmental Panel on Climate Change/Special Report on Emissions Scenarios) marker scenarios: A1B, A2, B1, and B2. In addition, a mitigation scenario has been calculated for the B1 scenario, requiring rapid and significant technology development and transition. A global model of aircraft movements and emissions (FAST) was used to calculate fuel use and emissions to 2050 with a further outlook to 2100. The aviation emission scenarios presented are designed to interpret the SRES and have been developed to aid in the quantification of the climate change impacts of aviation. Demand projections are made for each scenario, determined by SRES economic growth factors and the SRES storylines. Technology trends are examined in detail and developed for each scenario providing plausible projections for fuel efficiency and emissions control technology appropriate to the individual SRES storylines. The technology trends that are applied are calculated from bottom-up inventory calculations and industry technology trends and targets. Future emissions of carbon dioxide are projected to grow between 2000 and 2050 by a factor in the range of 2.0 and 3.6 depending on the scenario. Emissions of oxides of nitrogen associated with aviation over the same period are projected to grow by between a factor of 1.2 and 2.7.

Secondary organic aerosol formation exceeds primary particulate matter emissions for light-duty gasoline vehicles

NASA Astrophysics Data System (ADS)

Gordon, T. D.; Presto, A. A.; May, A. A.; Nguyen, N. T.; Lipsky, E. M.; Donahue, N. M.; Gutierrez, A.; Zhang, M.; Maddox, C.; Rieger, P.; Chattopadhyay, S.; Maldonado, H.; Maricq, M. M.; Robinson, A. L.

2014-05-01

The effects of photochemical aging on emissions from 15 light-duty gasoline vehicles were investigated using a smog chamber to probe the critical link between the tailpipe and ambient atmosphere. The vehicles were recruited from the California in-use fleet; they represent a wide range of model years (1987 to 2011), vehicle types and emission control technologies. Each vehicle was tested on a chassis dynamometer using the unified cycle. Dilute emissions were sampled into a portable smog chamber and then photochemically aged under urban-like conditions. For every vehicle, substantial secondary organic aerosol (SOA) formation occurred during cold-start tests, with the emissions from some vehicles generating as much as 6 times the amount of SOA as primary particulate matter (PM) after 3 h of oxidation inside the chamber at typical atmospheric oxidant levels (and 5 times the amount of SOA as primary PM after 5 × 106 molecules cm-3 h of OH exposure). Therefore, the contribution of light-duty gasoline vehicle exhaust to ambient PM levels is likely dominated by secondary PM production (SOA and nitrate). Emissions from hot-start tests formed about a factor of 3-7 less SOA than cold-start tests. Therefore, catalyst warm-up appears to be an important factor in controlling SOA precursor emissions. The mass of SOA generated by photooxidizing exhaust from newer (LEV2) vehicles was a factor of 3 lower than that formed from exhaust emitted by older (pre-LEV) vehicles, despite much larger reductions (a factor of 11-15) in nonmethane organic gas emissions. These data suggest that a complex and nonlinear relationship exists between organic gas emissions and SOA formation, which is not surprising since SOA precursors are only one component of the exhaust. Except for the oldest (pre-LEV) vehicles, the SOA production could not be fully explained by the measured oxidation of speciated (traditional) SOA precursors. Over the timescale of these experiments, the mixture of organic vapors emitted by newer vehicles appears to be more efficient (higher yielding) in producing SOA than the emissions from older vehicles. About 30% of the nonmethane organic gas emissions from the newer (LEV1 and LEV2) vehicles could not be speciated, and the majority of the SOA formed from these vehicles appears to be associated with these unspeciated organics. By comparing this study with a companion study of diesel trucks, we conclude that both primary PM emissions and SOA production for light-duty gasoline vehicles are much greater than for late-model (2007 and later) on-road heavy-duty diesel trucks.

SOA Formation Potential of Emissions from Soil and Leaf Litter

NASA Astrophysics Data System (ADS)

Faiola, C. L.; Vanderschelden, G. S.; Wen, M.; Cobos, D. R.; Jobson, B. T.; VanReken, T. M.

2013-12-01

In the United States, emissions of volatile organic compounds (VOCs) from natural sources exceed all anthropogenic sources combined. VOCs participate in oxidative chemistry in the atmosphere and impact the concentrations of ozone and particulate material. The formation of secondary organic aerosol (SOA) is particularly complex and is frequently underestimated using state-of-the-art modeling techniques. We present findings that suggest emissions of important SOA precursors from soil and leaf litter are higher than current inventories would suggest, particularly under conditions typical of Fall and Spring. Soil and leaf litter samples were collected at Big Meadow Creek from the University of Idaho Experimental Forest. The dominant tree species in this area of the forest are ponderosa pine, Douglas-fir, and western larch. Samples were transported to the laboratory and housed within a 0.9 cubic meter Teflon dynamic chamber where VOC emissions were continuously monitored with a GC-FID-MS and PTR-MS. Aerosol was generated from soil and leaf litter emissions by pumping the emissions into a 7 cubic meter Teflon aerosol growth chamber where they were oxidized with ozone in the absence of light. The evolution of particle microphysical and chemical characteristics was monitored over the following eight hours. Particle size distribution and chemical composition were measured with a SMPS and HR-ToF-AMS respectively. Monoterpenes dominated the emission profile with emission rates up to 283 micrograms carbon per meter squared per hour. The dominant monoterpenes emitted were beta-pinene, alpha-pinene, and delta-3-carene in descending order. The composition of the SOA produced was similar to biogenic SOA formed from oxidation of ponderosa pine emissions and alpha-pinene. Measured soil/litter monoterpene emission rates were compared with modeled canopy emissions. Results suggest that during fall and spring when tree emissions are lower, monoterpene emissions within forests may be dominated by soil/litter emissions--soil/litter monoterpene emissions in spring could contribute up to 63% of total forest emissions. If this is the case, a significant portion of total forest monoterpene emission rates would be controlled by factors that affect soil/litter emissions rather than factors that affect plant emissions.

Modeling of meteorology, chemistry and aerosol for the 2017 Utah Winter Fine Particle Study

NASA Astrophysics Data System (ADS)

McKeen, S. A.; Angevine, W. M.; McDonald, B.; Ahmadov, R.; Franchin, A.; Middlebrook, A. M.; Fibiger, D. L.; McDuffie, E. E.; Womack, C.; Brown, S. S.; Moravek, A.; Murphy, J. G.; Trainer, M.

2017-12-01

The Utah Winter Fine Particle Study (UWFPS-17) field project took place during January and February of 2017 within the populated region of the Great Salt Lake, Utah. The study focused on understanding the meteorology and chemistry associated with high particulate matter (PM) levels often observed near Salt Lake City during stable wintertime conditions. Detailed composition and meteorological observations were taken from the NOAA Twin-Otter aircraft and several surface sites during the study period, and extremely high aerosol conditions were encountered for two cold-pool episodes occurring in the last 2 weeks of January. A clear understanding of the photochemical and aerosol processes leading to these high PM events is still lacking. Here we present high spatiotemporal resolution simulations of meteorology, PM and chemistry over Utah from January 13 to February 1, 2017 using the WRF/Chem photochemical model. Correctly characterizing the meteorology is difficult due to the complex terrain and shallow inversion layers. We discuss the approach and limitations of the simulated meteorology, and evaluate low-level pollutant mixing using vertical profiles from missed airport approaches by the NOAA Twin-Otter performed routinely during each flight. Full photochemical simulations are calculated using NOx, ammonia and VOC emissions from the U.S. EPA NEI-2011 emissions inventory. Comparisons of the observed vertical column amounts of NOx, ammonia, aerosol nitrate and ammonium with model results shows the inventory estimates for ammonia emissions are low by a factor of four and NOx emissions are low by nearly a factor of two. The partitioning of both nitrate and NH3 between gas and particle phase depends strongly on the NH3 and NOx emissions to the model and calculated NOx to nitrate conversion rates. These rates are underestimated by gas-phase chemistry alone, even though surface snow albedo increases photolysis rates by nearly a factor of two. Several additional conversion mechanisms are added and evaluated in the model, including: heterogeneous nitrate to aerosol formation, catalytic conversion of NO2 to HONO and HNO3 at the snow surface, and direct HONO emissions from vehicles. Each mechanism contributes to the model matching observed NOx and total nitrate levels within 25% for median statistics over the study period.

Simulation of nitrous oxide emissions at field scale using the SPACSYS model

PubMed Central

Wu, L.; Rees, R.M.; Tarsitano, D.; Zhang, Xubo; Jones, S.K.; Whitmore, A.P.

2015-01-01

Nitrous oxide emitted to the atmosphere via the soil processes of nitrification and denitrification plays an important role in the greenhouse gas balance of the atmosphere and is involved in the destruction of stratospheric ozone. These processes are controlled by biological, physical and chemical factors such as growth and activity of microbes, nitrogen availability, soil temperature and water availability. A comprehensive understanding of these processes embodied in an appropriate model can help develop agricultural mitigation strategies to reduce greenhouse gas emissions, and help with estimating emissions at landscape and regional scales. A detailed module to describe the denitrification and nitrification processes and nitrogenous gas emissions was incorporated into the SPACSYS model to replace an earlier module that used a simplified first-order equation to estimate denitrification and was unable to distinguish the emissions of individual nitrogenous gases. A dataset derived from a Scottish grassland experiment in silage production was used to validate soil moisture in the top 10 cm soil, cut biomass, nitrogen offtake and N2O emissions. The comparison between the simulated and observed data suggested that the new module can provide a good representation of these processes and improve prediction of N2O emissions. The model provides an opportunity to estimate gaseous N emissions under a wide range of management scenarios in agriculture, and synthesises our understanding of the interaction and regulation of the processes. PMID:26026411

Trends in multi-pollutant emissions from a technology-linked inventory for India: I. Industry and transport sectors

NASA Astrophysics Data System (ADS)

Sadavarte, Pankaj; Venkataraman, Chandra

2014-12-01

Emissions estimation, for research and regulatory applications including reporting to international conventions, needs treatment of detailed technology divisions and high-emitting technologies. Here we estimate Indian emissions, for 1996-2015, of aerosol constituents (PM2.5, BC and OC) and precursor gas SO2, ozone precursors (CO, NOx, NMVOC and CH4) and greenhouse gases (CO2 and N2O), using a common fuel consumption database and consistent assumptions. Six source categories and 45 technologies/activities in the industry and transport sectors were used for estimating emissions for 2010. Mean emission factors, developed at the source-category level, were used with corresponding fuel consumption data, available for 1996-2011, projected to 2015. New activities were included to account for fugitive emissions of NMVOC from chemical and petrochemical industries. Dynamic emission factors, reflecting changes in technology-mix and emission regulations, were developed for thermal power plants and on-road transport vehicles. Modeled emission factors were used for gaseous pollutants for on-road vehicles. Emissions of 2.4 (0.6-7.5) Tg y-1 PM2.5, 0.23 (0.1-0.7) Tg y-1 BC, 0.15 (0.04-0.5) Tg y-1 OC, 7.3 (6-10) Tg y-1 SO2, 19 (7.5-33) Tg y-1 CO, 1.5 (0.1-9) Tg y-1 CH4, 4.3 (2-9) Tg y-1 NMVOC, 5.6 (1.7-15.9) Tg y-1 NOx, 1750 (1397-2231) Tg y-1 CO2 and 0.13 (0.05-0.3) Tg y-1 N2O were estimated for 2015. Significant emissions of aerosols and their precursors were from coal use in thermal power and industry (PM2.5 and SO2), and on-road diesel vehicles (BC), especially superemitters. Emissions of ozone precursors were largely from thermal power plants (NOx), on-road gasoline vehicles (CO and NMVOC) and fugitive emissions from mining (CH4). Highly uncertain default emission factors were the principal contributors to uncertainties in emission estimates, indicating the need for region specific measurements.

Temporal Arctic longwave surface emissivity feedbacks in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Kuo, C.; Feldman, D.; Huang, X.; Flanner, M.; Yang, P.; Chen, X.

2017-12-01

We have investigated how the inclusion of realistic and consistent surface emissivity in both land-surface and atmospheric components of the CESM coupled-climate model affects a wide range of climate variables. We did this by replacing the unit emissivity values in RRTMG_LW for water, fine-grained snow, and desert scenes with spectral emissivity values, and by replacing broadband emissivity values in surface components with the Planck-curve weighted counterparts. We find that this harmonized treatment of surface emissivity within CESM can be important for reducing high-latitude temperature biases. We also find that short-term effects of atmospheric dynamics and spectral information need to be considered to understand radiative effects in higher detail, and are possible with radiative kernels computed for every grid and time point for the entire model integration period. We find that conventional climatological feedback calculations indicate that sea-ice emissivity feedback is positive in sign, but that the radiative effects of the difference in emissivity between frozen and unfrozen surfaces exhibit seasonal dependence. Furthermore, this seasonality itself exhibits meridional asymmetry due to differences in sea-ice response to climate forcing between the Arctic and the Antarctic. In the Arctic, this seasonal, temporally higher order analysis exhibits increasing outgoing surface emissivity radiative response in a warming climate. While the sea-ice emissivity feedback and seasonal sea-ice emissivity radiative response amplitudes are a few percent of surface albedo feedbacks, the feedback analysis methods outlined in this work demonstrate that spatially and temporally localized feedback analysis can give insight into the mechanisms at work on those scales which differ in amplitude and sign from conventional climatological analyses. We note that the inclusion of this realistic physics leads to improved agreement between CESM model results and Arctic surface temperatures and sea-ice trends. This reduction of persistent high-latitude model biases suggests that the current unrealistic representation of surface emissivity in model component radiation routines may be an important contributing factor to cold-pole biases.

Early X-Ray Flares in GRBs

NASA Astrophysics Data System (ADS)

Ruffini, R.; Wang, Y.; Aimuratov, Y.; Barres de Almeida, U.; Becerra, L.; Bianco, C. L.; Chen, Y. C.; Karlica, M.; Kovacevic, M.; Li, L.; Melon Fuksman, J. D.; Moradi, R.; Muccino, M.; Penacchioni, A. V.; Pisani, G. B.; Primorac, D.; Rueda, J. A.; Shakeri, S.; Vereshchagin, G. V.; Xue, S.-S.

2018-01-01

We analyze the early X-ray flares in the GRB “flare–plateau–afterglow” (FPA) phase observed by Swift-XRT. The FPA occurs only in one of the seven GRB subclasses: the binary-driven hypernovae (BdHNe). This subclass consists of long GRBs with a carbon–oxygen core and a neutron star (NS) binary companion as progenitors. The hypercritical accretion of the supernova (SN) ejecta onto the NS can lead to the gravitational collapse of the NS into a black hole. Consequently, one can observe a GRB emission with isotropic energy {E}{iso}≳ {10}52 erg, as well as the associated GeV emission and the FPA phase. Previous work had shown that gamma-ray spikes in the prompt emission occur at ∼ {10}15{--}{10}17 cm with Lorentz Gamma factors {{Γ }}∼ {10}2{--}{10}3. Using a novel data analysis, we show that the time of occurrence, duration, luminosity, and total energy of the X-ray flares correlate with E iso. A crucial feature is the observation of thermal emission in the X-ray flares that we show occurs at radii ∼1012 cm with {{Γ }}≲ 4. These model-independent observations cannot be explained by the “fireball” model, which postulates synchrotron and inverse-Compton radiation from a single ultrarelativistic jetted emission extending from the prompt to the late afterglow and GeV emission phases. We show that in BdHNe a collision between the GRB and the SN ejecta occurs at ≃1010 cm, reaching transparency at ∼1012 cm with {{Γ }}≲ 4. The agreement between the thermal emission observations and these theoretically derived values validates our model and opens the possibility of testing each BdHN episode with the corresponding Lorentz Gamma factor.

Future shifts in African air quality and the resulting impacts on human health and climate: Design of efficient mitigation strategies.

NASA Astrophysics Data System (ADS)

Lacey, F.; Marais, E. A.; Wiedinmyer, C.; Coffey, E.; Pfotenhauer, D.; Henze, D. K.; Evans, M. J.; Hannigan, M.; Morris, E.; Davila, Y.; Mesenbring, E. C.

2017-12-01

Population in Africa is currently projected to double by 2050, which will have significant impacts on anthropogenic emissions and in turn the ambient air quality, especially near population centers. Recent research has also shown that the emissions factors used for global inventories are misrepresented when compared to field measurements in Africa, which leads to inaccuracies in the magnitude and spatial distribution of emissions throughout the continent. As the population in Africa increases, the combination of anthropogenic and biogenic emissions in many regions will lead to changes in atmospheric pollutant concentrations, including particulate matter (PM2.5) and ozone. Combining updated emissions estimates created using measured emissions factors reported from field studies in Africa with the Community Earth System Model (CESM2) improves predictions of the present day ambient air quality; validated based on available observations from field measurements and satellite data. We use these tools to quantify the impacts of anthropogenic emissions on both climate and human health, shown here as estimated premature deaths from chronic exposure to pollutants. Sensitivities derived from model source attribution calculations using the GEOS-Chem adjoint model are then used to examine the impacts of changes in population distribution and shifts in technology moving to the mid-21st century. With these results, we are able to identify efficient mitigation pathways that target specific regions and anthropogenic activities. These targeted control measures include shifts from traditional to modern cooking technologies, as well as other sector-specific interventions that represent feasible adoptions in Africa over the next several decades. This work provides a potential roadmap towards improved air quality to both government and non-governmental organizations as Africa transitions through this period of rapid growth.

An empirical model to predict road dust emissions based on pavement and traffic characteristics.

PubMed

Padoan, Elio; Ajmone-Marsan, Franco; Querol, Xavier; Amato, Fulvio

2018-06-01

The relative impact of non-exhaust sources (i.e. road dust, tire wear, road wear and brake wear particles) on urban air quality is increasing. Among them, road dust resuspension has generally the highest impact on PM concentrations but its spatio-temporal variability has been rarely studied and modeled. Some recent studies attempted to observe and describe the time-variability but, as it is driven by traffic and meteorology, uncertainty remains on the seasonality of emissions. The knowledge gap on spatial variability is much wider, as several factors have been pointed out as responsible for road dust build-up: pavement characteristics, traffic intensity and speed, fleet composition, proximity to traffic lights, but also the presence of external sources. However, no parameterization is available as a function of these variables. We investigated mobile road dust smaller than 10 μm (MF10) in two cities with different climatic and traffic conditions (Barcelona and Turin), to explore MF10 seasonal variability and the relationship between MF10 and site characteristics (pavement macrotexture, traffic intensity and proximity to braking zone). Moreover, we provide the first estimates of emission factors in the Po Valley both in summer and winter conditions. Our results showed a good inverse relationship between MF10 and macro-texture, traffic intensity and distance from the nearest braking zone. We also found a clear seasonal effect of road dust emissions, with higher emission in summer, likely due to the lower pavement moisture. These results allowed building a simple empirical mode, predicting maximal dust loadings and, consequently, emission potential, based on the aforementioned data. This model will need to be scaled for meteorological effect, using methods accounting for weather and pavement moisture. This can significantly improve bottom-up emission inventory for spatial allocation of emissions and air quality management, to select those roads with higher emissions for mitigation measures. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Novel Approach for Determining Source-Receptor Relationships of Aerosols in Model Simulations

NASA Astrophysics Data System (ADS)

Ma, P.; Gattiker, J.; Liu, X.; Rasch, P. J.

2013-12-01

The climate modeling community usually performs sensitivity studies in the 'one-factor-at-a-time' fashion. However, owing to the a-priori unknown complexity and nonlinearity of the climate system and simulation response, it is computationally expensive to systematically identify the cause-and-effect of multiple factors in climate models. In this study, we use a Gaussian Process emulator, based on a small number of Community Atmosphere Model Version 5.1 (CAM5) simulations (constrained by meteorological reanalyses) using a Latin Hypercube experimental design, to demonstrate that it is possible to characterize model behavior accurately and very efficiently without any modifications to the model itself. We use the emulator to characterize the source-receptor relationships of black carbon (BC), focusing specifically on describing the constituent burden and surface deposition rates from emissions in various regions. Our results show that the emulator is capable of quantifying the contribution of aerosol burden and surface deposition from different source regions, finding that most of current Arctic BC comes from remote sources. We also demonstrate that the sensitivity of the BC burdens to emission perturbations differs for various source regions. For example, the emission growth in Africa where dry convections are strong results in a moderate increase of BC burden over the globe while the same emission growth in the Arctic leads to a significant increase of local BC burdens and surface deposition rates. These results provide insights into the dynamical, physical, and chemical processes of the climate model, and the conclusions may have policy implications for making cost-effective global and regional pollution management strategies.

Weekly agricultural emissions and ambient concentrations of ammonia: Validation of an emission inventory

NASA Astrophysics Data System (ADS)

Bittman, Shabtai; Jones, Keith; Vingarzan, Roxanne; Hunt, Derek E.; Sheppard, Steve C.; Tait, John; So, Rita; Zhao, Johanna

2015-07-01

Weekly inventories for emissions of agricultural ammonia were calculated for 139 4 × 4 km grid cells over 52 weeks in the intensely farmed Lower Fraser Valley, BC. The grid cells were located both inside and outside an area that had been depopulated of poultry due to an outbreak of Avian Influenza prior to the start of the study. During the study period, ambient ammonia concentrations were measured hourly at two locations outside the cull area and one location inside the cull area. Large emission differences between grid cells and differences in temporal variation between cells were related to farming practices and meteorological factors such as temperature and rainfall. Weekly average ambient concentrations at the three sampling locations were significantly correlated with estimates of weekly emissions for many of the grid cells in the study area. Inside the cull area, ambient concentrations during the cull (week 1) were 37% of the concentrations after the cull (week 52), while outside the cull there was almost no difference between week 1 and week 52, suggesting that in normal (non-cull) conditions, about 60% of the ambient ammonia was due to poultry farms. Estimated emissions in weeks 1 and 52 for grid cells affected by the cull indicated that over 90% of the emissions came from poultry. The discrepancy in difference between week 1 and 52 for emissions and ambient concentrations could be due to atmospheric factors like transport, atmospheric reactions, dispersion or deposition; to errors in the inventory including farming data, emission factors; and omission of some non-poultry emission sources. Overall the study supports the ammonia emission inventory estimates. Detailed emission data helps in modeling ammonia in the atmosphere and is useful for developing abatement policy.

Use and uncertainty evaluation of a process-based model for assessing the methane budgets of global terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Ito, A.; Inatomi, M.

2011-07-01

We assessed the global terrestrial budget of methane (CH4) using a process-based biogeochemical model (VISIT) and inventory data. Emissions from wetlands, paddy fields, biomass burning, and plants, and oxidative consumption by upland soils, were simulated by the model. Emissions from livestock ruminants and termites were evaluated by 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 576 simulations, and terrestrial ecosystems were found to be a net source of 320.4 ± 18.9 Tg CH4 yr-1. Wetland and 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 assessed. The trend of increasing net 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.

Consideration of Real World Factors Influencing Greenhouse ...

EPA Pesticide Factsheets

Discuss a variety of factors that influence the simulated fuel economy and GHG emissions that are often overlooked and updates made to ALPHA based on actual benchmarking data observed across a range of vehicles and transmissions. ALPHA model calibration is also examined, focusing on developing generic calibrations for driver behavior, transmission gear selection and torque converter lockup. In addition, show the derivation of correction factors needed to estimate cold start emission results. To provide an overview of the ALPHA tool with additional focus on recent updates by presenting the approach for validating and calibrating ALPHA to match particular vehicles in a general sense, then by looking at the individual losses, and calibration factors likely to influence fuel economy.

Life cycle assessment of potential biojet fuel production in the United States.

PubMed

Agusdinata, Datu B; Zhao, Fu; Ileleji, Klein; DeLaurentis, Dan

2011-11-01

The objective of this paper is to reveal to what degree biobased jet fuels (biojet) can reduce greenhouse gas (GHG) emissions from the U.S. aviation sector. A model of the supply and demand chain of biojet involving farmers, biorefineries, airlines, and policymakers is developed by considering factors that drive the decisions of actors (i.e., decision-makers and stakeholders) in the life cycle stages. Two kinds of feedstock are considered: oil-producing feedstock (i.e., camelina and algae) and lignocellulosic biomass (i.e., corn stover, switchgrass, and short rotation woody crops). By factoring in farmer/feedstock producer and biorefinery profitability requirements and risk attitudes, land availability and suitability, as well as a time delay and technological learning factor, a more realistic estimate of the level of biojet supply and emissions reduction can be developed under different oil price assumptions. Factors that drive biojet GHG emissions and unit production costs from each feedstock are identified and quantified. Overall, this study finds that at likely adoption rates biojet alone would not be sufficient to achieve the aviation emissions reduction target. In 2050, under high oil price scenario assumption, GHG emissions can be reduced to a level ranging from 55 to 92%, with a median value of 74%, compared to the 2005 baseline level.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Space-based retrieval of NO2 over biomass burning regions: quantifying and reducing uncertainties

NASA Astrophysics Data System (ADS)

Bousserez, N.

2014-10-01

The accuracy of space-based nitrogen dioxide (NO2) retrievals from solar backscatter radiances critically depends on a priori knowledge of the vertical profiles of NO2 and aerosol optical properties. This information is used to calculate an air mass factor (AMF), which accounts for atmospheric scattering and is used to convert the measured line-of-sight "slant" columns into vertical columns. In this study we investigate the impact of biomass burning emissions on the AMF in order to quantify NO2 retrieval errors in the Ozone Monitoring Instrument (OMI) products over these sources. Sensitivity analyses are conducted using the Linearized Discrete Ordinate Radiative Transfer (LIDORT) model. The NO2 and aerosol profiles are obtained from a 3-D chemistry-transport model (GEOS-Chem), which uses the Fire Locating and Monitoring of Burning Emissions (FLAMBE) daily biomass burning emission inventory. Aircraft in situ data collected during two field campaigns, the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) and the Dust and Biomass-burning Experiment (DABEX), are used to evaluate the modeled aerosol optical properties and NO2 profiles over Canadian boreal fires and West African savanna fires, respectively. Over both domains, the effect of biomass burning emissions on the AMF through the modified NO2 shape factor can be as high as -60%. A sensitivity analysis also revealed that the effect of aerosol and shape factor perturbations on the AMF is very sensitive to surface reflectance and clouds. As an illustration, the aerosol correction can range from -20 to +100% for different surface reflectances, while the shape factor correction varies from -70 to -20%. Although previous studies have shown that in clear-sky conditions the effect of aerosols on the AMF was in part implicitly accounted for by the modified cloud parameters, here it is suggested that when clouds are present above a surface layer of scattering aerosols, an explicit aerosol correction would be beneficial to the NO2 retrieval. Finally, a new method that uses slant column information to correct for shape-factor-related AMF error over NOx emission sources is proposed, with possible application to near-real-time OMI retrievals.

An operational system for the assimilation of satellite information on wild-land fires for the needs of air quality modelling and forecasting

NASA Astrophysics Data System (ADS)

Sofiev, M.; Vankevich, R.; Lanne, M.; Prank, M.; Petukhov, V.; Ermakova, T.; Kukkonen, J.

2009-03-01

This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and the short-term forecasting of the atmospheric composition and air quality. Two treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes is described. The method does not contain a complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are comparatively uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that have been derived from the analysis of several fire episodes in Europe (28 April-5 May 2006, 15-25 August 2006, August 2008 etc.). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available independent observations of aerosol concentrations and optical thickness for the regions where fire smoke was dominant in comparison with contributions of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use an intermediate scaling was assumed. Despite significant difference between the TA and FRP products, an accurate non-linear fitting between the approaches was found. The agreement was comparatively weak only for small fires where the accuracy of both products is low. The re-analysis and forecasting applications of the Fire Assimilation System (FAS) showed that both TA and FRP products are suitable for evaluation of the emission fluxes from the wild-land fires. The concentrations of aerosols predicted by the regional dispersion modelling system SILAM appear within a factor of 2-3 from observations. The main areas of improvement include further refining the emission factors over the globe, explicit determination and appropriate treatment of the type of fires, evaluation of the injection height of the plumes and predicting the fire temporal evolution.

A Bulk Comptonization Model for the Prompt GRB Emission and its Relation to the Fermi GRB Spectra

NASA Technical Reports Server (NTRS)

Kazanas, Demosthenes

2010-01-01

We present a model in which the GRB prompt emission at E E(sub peak) is due to bulk Comptonization by the relativistic blast wave motion of either its own synchrotron photons of ambient photons of the stellar configuration that gave birth to the GRB. The bulk Comptonization process then induces the production of relativistic electrons of Lorentz factor equal to that of the blast wave through interactions with its ambient protons. The inverse compton emission of these electrons produces a power law component that extends to multi GeV energies in good agreement with the LAT GRB observations.

Atmospheric Aerosol Source-Receptor Relationships: The Role of Coal-Fired Power Plants

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

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-12-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of March 2005 through August 2005. Significant progress was made this project period on the source characterization, source apportionment, and deterministic modeling activities. This report highlights new data on road dust, vegetative detritus and motor vehicle emissions. For example, the results show significant differences in the composition in urban and rural road dust. A comparison of the organic of the fine particulate matter in the tunnel with the ambient provides clear evidence of the significant contribution of vehicle emissions to ambient PM. Themore » source profiles developed from this work are being used by the source-receptor modeling activities. The report presents results on the spatial distribution of PMF-factors. The results can be grouped into three different categories: regional sources, local sources, or potentially both regional and local sources. Examples of the regional sources are the sulfate and selenium PMF-factors which most likely-represent coal fired power plants. Examples of local sources are the specialty steel and lead factors. There is reasonable correspondence between these apportionments and data from the EPA TRI and AIRS emission inventories. Detailed comparisons between PMCAMx predictions and measurements by the STN and IMPROVE measurements in the Eastern US are presented. Comparisons were made for the major aerosol components and PM{sub 2.5} mass in July 2001, October 2001, January 2002, and April 2002. The results are encouraging with average fraction biases for most species less than 0.25. The improvement of the model performance during the last two years was mainly due to the comparison of the model predictions with the continuous measurements in the Pittsburgh Supersite. Major improvements have included the descriptions: of ammonia emissions (CMU inventory), night time nitrate chemistry, EC emissions and their diurnal variation, and nitric acid dry removal.« less

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.

Characterization of Methane Emission Sources Using Genetic Algorithms and Atmospheric Transport Modeling

NASA Astrophysics Data System (ADS)

Cao, Y.; Cervone, G.; Barkley, Z.; Lauvaux, T.; Deng, A.; Miles, N.; Richardson, S.

2016-12-01

Fugitive methane emission rates for the Marcellus shale area are estimated using a genetic algorithm that finds optimal weights to minimize the error between simulated and observed concentrations. The overall goal is to understand the relative contribution of methane due to Shale gas extraction. Methane sensors were installed on four towers located in northeastern Pennsylvania to measure atmospheric concentrations since May 2015. Inverse Lagrangian dispersion model runs are performed from each of these tower locations for each hour of 2015. Simulated methane concentrations at each of the four towers are computed by multiplying the resulting footprints from the atmospheric simulations by thousands of emission sources grouped into 11 classes. The emission sources were identified using GIS techniques, and include conventional and unconventional wells, different types of compressor stations, pipelines, landfills, farming and wetlands. Initial estimates for each source are calculated based on emission factors from EPA and few regional studies. A genetic algorithm is then used to identify optimal emission rates for the 11 classes of methane emissions and to explore extreme events and spatial and temporal structures in the emissions associated with natural gas activities.

Understanding Differences in the Body Burden–Age Relationships of Bioaccumulating Contaminants Based on Population Cross Sections versus Individuals

PubMed Central

Quinn, Cristina L.

2012-01-01

Background: Body burdens of persistent bioaccumulative contaminants estimated from the cross-sectional biomonitoring of human populations are often plotted against age. Such relationships have previously been assumed to reflect the role of age in bioaccumulation. Objectives: We used a mechanistic modeling approach to reproduce concentration-versus-age relationships and investigate factors that influence them. Method: CoZMoMAN is an environmental fate and human food chain bioaccumulation model that estimates time trends in human body burdens in response to time-variant environmental emissions. Trends of polychlorinated biphenyl (PCB) congener 153 concentrations versus age for population cross sections were estimated using simulated longitudinal data for individual women born at different times. The model was also used to probe the influence of partitioning and degradation properties, length of emissions, and model assumptions regarding lipid content and liver metabolism on concentration–age trends of bioaccumulative and persistent contaminants. Results: Body burden–age relationships for population cross sections and individuals over time are not equivalent. The time lapse between the peak in emissions and sample collection for biomonitoring is the most influential factor controlling the shape of concentration–age trends for chemicals with human metabolic half-lives longer than 1 year. Differences in observed concentration–age trends for PCBs and polybrominated diphenyl ethers are consistent with differences in emission time trends and human metabolic half-lives. Conclusions: Bioaccumulation does not monotonically increase with age. Our model suggests that the main predictors of cross-sectional body burden trends with age are the amount of time elapsed after peak emissions and the human metabolic and environmental degradation rates. PMID:22472302

Characterization factors for global warming in life cycle assessment based on damages to humans and ecosystems.

PubMed

De Schryver, An M; Brakkee, Karin W; Goedkoop, Mark J; Huijbregts, Mark A J

2009-03-15

Human and ecosystem health damage due to greenhouse gas (GHG) emissions is generally poorly quantified in the life cycle assessment of products, preventing an integrated comparison of the importance of GHGs with other stressor types, such as ozone depletion and acidifying emissions. In this study, we derived new characterization factors for 63 GHGs that quantify the impact of an emission change on human and ecosystem health damage. For human health damage, the Disability Adjusted Life Years (DALYs) per unit emission related to malaria, diarrhea, malnutrition, drowning, and cardiovascular diseases were quantified. For ecosystem health damage, the Potentially Disappeared Fraction (PDF) over space and time of various species groups, including plants, butterflies, birds, and mammals, per unit emission was calculated. The influence of value choices in the modeling procedure was analyzed by defining three coherent scenarios, based on Cultural theory perspectives. It was found that the characterization factor for human health damage by carbon dioxide (CO2) ranges from 1.1 x 10(-2) to 1.8 x 10(+1) DALY per kton of emission, while the characterization factor for ecosystem damage by CO2 ranges from 5.4 x 10(-2) to 1.2 x 10(+1) disappeared fraction of species over space and time ((km2 x year)/kton), depending on the scenario chosen. The characterization factor of a GHG can change up to 4 orders of magnitude, depending on the scenario. The scenario-specific differences are mainly explained by the choice for a specific time horizon and stresses the importance of dealing with value choices in the life cycle impact assessment of GHG emissions.

Impacts of potential CO2-reduction policies on air quality in the United States.

PubMed

Trail, Marcus A; Tsimpidi, Alexandra P; Liu, Peng; Tsigaridis, Kostas; Hu, Yongtao; Rudokas, Jason R; Miller, Paul J; Nenes, Athanasios; Russell, Armistead G

2015-04-21

Impacts of emissions changes from four potential U.S. CO2 emission reduction policies on 2050 air quality are analyzed using the community multiscale air quality model (CMAQ). Future meteorology was downscaled from the Goddard Institute for Space Studies (GISS) ModelE General Circulation Model (GCM) to the regional scale using the Weather Research Forecasting (WRF) model. We use emissions growth factors from the EPAUS9r MARKAL model to project emissions inventories for two climate tax scenarios, a combined transportation and energy scenario, a biomass energy scenario and a reference case. Implementation of a relatively aggressive carbon tax leads to improved PM2.5 air quality compared to the reference case as incentives increase for facilities to install flue-gas desulfurization (FGD) and carbon capture and sequestration (CCS) technologies. However, less capital is available to install NOX reduction technologies, resulting in an O3 increase. A policy aimed at reducing CO2 from the transportation sector and electricity production sectors leads to reduced emissions of mobile source NOX, thus reducing O3. Over most of the U.S., this scenario leads to reduced PM2.5 concentrations. However, increased primary PM2.5 emissions associated with fuel switching in the residential and industrial sectors leads to increased organic matter (OM) and PM2.5 in some cities.

Improve regional distribution and source apportionment of PM2.5 trace elements in China using inventory-observation constrained emission factors.

PubMed

Ying, Qi; Feng, Miao; Song, Danlin; Wu, Li; Hu, Jianlin; Zhang, Hongliang; Kleeman, Michael J; Li, Xinghua

2018-05-15

Contributions to 15 trace elements in airborne particulate matter with aerodynamic diameters <2.5μm (PM 2.5 ) in China from five major source sectors (industrial sources, residential sources, transportation, power generation and windblown dust) were determined using a source-oriented Community Multiscale Air Quality (CMAQ) model. Using emission factors in the composite speciation profiles from US EPA's SPECIATE database for the five sources leads to relatively poor model performance at an urban site in Beijing. Improved predictions of the trace elements are obtained by using adjusted emission factors derived from a robust multilinear regression of the CMAQ predicted primary source contributions and observation at the urban site. Good correlations between predictions and observations are obtained for most elements studied with R>0.5, except for crustal elements Al, Si and Ca, particularly in spring. Predicted annual and seasonal average concentrations of Mn, Fe, Zn and Pb in Nanjing and Chengdu are also consistently improved using the adjusted emission factors. Annual average concentration of Fe is as high as 2.0μgm -3 with large contributions from power generation and transportation. Annual average concentration of Pb reaches 300-500ngm -3 in vast areas, mainly from residential activities, transportation and power generation. The impact of high concentrations of Fe on secondary sulfate formation and Pb on human health should be evaluated carefully in future studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the impact of solid noise barriers on near road air quality

NASA Astrophysics Data System (ADS)

Venkatram, Akula; Isakov, Vlad; Deshmukh, Parikshit; Baldauf, Richard

2016-09-01

Studies based on field measurements, wind tunnel experiments, and controlled tracer gas releases indicate that solid, roadside noise barriers can lead to reductions in downwind near-road air pollutant concentrations. A tracer gas study showed that a solid barrier reduced pollutant concentrations as much as 80% next to the barrier relative to an open area under unstable meteorological conditions, which corresponds to typical daytime conditions when residents living or children going to school near roadways are most likely to be exposed to traffic emissions. The data from this tracer gas study and a wind tunnel simulation were used to develop a model to describe dispersion of traffic emissions near a highway in the presence of a solid noise barrier. The model is used to interpret real-world data collected during a field study conducted in a complex urban environment next to a large highway in Phoenix, Arizona, USA. We show that the analysis of the data with the model yields useful information on the emission factors and the mitigation impact of the barrier on near-road air quality. The estimated emission factors for the four species, ultrafine particles, CO, NO2, and black carbon, are consistent with data cited in the literature. The results suggest that the model accounted for reductions in pollutant concentrations from a 4.5 m high noise barrier, ranging from 40% next to the barrier to 10% at 300 m from the barrier.

EMISSION FACTORS FOR IRON FOUNDRIES - CRITERIA AND TOXIC POLLUTANTS

EPA Science Inventory

The report lists criteria and toxic pollutant emission factors or sources commonly found in gray and ductile iron foundries. Emission factors are identified for process source and process fugitive emissions. he emission factors, representing uncontrolled emissions, may be used to...

Selection of emission factor standards for estimating emissions from diesel construction equipment in building construction in the Australian context.

PubMed

Zhang, Guomin; Sandanayake, Malindu; Setunge, Sujeeva; Li, Chunqing; Fang, Jun

2017-02-01

Emissions from equipment usage and transportation at the construction stage are classified as the direct emissions which include both greenhouse gas (GHG) and non-GHG emissions due to partial combustion of fuel. Unavailability of a reliable and complete inventory restricts an accurate emission evaluation on construction work. The study attempts to review emission factor standards readily available worldwide for estimating emissions from construction equipment. Emission factors published by United States Environmental Protection Agency (US EPA), Australian National Greenhouse Accounts (AUS NGA), Intergovernmental Panel on Climate Change (IPCC) and European Environmental Agency (EEA) are critically reviewed to identify their strengths and weaknesses. A selection process based on the availability and applicability is then developed to help identify the most suitable emission factor standards for estimating emissions from construction equipment in the Australian context. A case study indicates that a fuel based emission factor is more suitable for GHG emission estimation and a time based emission factor is more appropriate for estimation of non-GHG emissions. However, the selection of emission factor standards also depends on factors like the place of analysis (country of origin), data availability and the scope of analysis. Therefore, suitable modifications and assumptions should be incorporated in order to represent these factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Singularities in x-ray spectra of metals

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

Mahan, G.D.

1987-08-01

The x-ray spectroscopies discussed are absorption, emission, and photoemission. The singularities show up in each of them in a different manner. In absorption and emission they show up as power law singularities at the thresholds frequencies. This review will emphasize two themes. First a simple model is proposed to describe this phenomena, which is now called the MND model after MAHAN-NOZIERES-DeDOMINICIS. Exact analytical solutions are now available for this model for the three spectroscopies discussed above. These analytical models can be evaluated numerically in a simple way. The second theme of this review is that great care must be usedmore » when comparing the theory to experiment. A number of factors influence the edge shapes in x-ray spectroscopy. The edge singularities play an important role, and are observed in many matals. Quantitative fits of the theory to experiment require the consideration of other factors. 51 refs.« less

Airborne observations reveal elevational gradient in tropical forest isoprene emissions

DOE PAGES

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

2017-05-23

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

Effects of Different Vegetation Zones on CH4 and N2O Emissions in Coastal Wetlands: A Model Case Study

PubMed Central

Liu, Yuhong; Wang, Lixin; Bao, Shumei; Liu, Huamin; Yu, Junbao; Wang, Yu; Shao, Hongbo; Ouyang, Yan; An, Shuqing

2014-01-01

The coastal wetland ecosystems are important in the global carbon and nitrogen cycle and global climate change. For higher fragility of coastal wetlands induced by human activities, the roles of coastal wetland ecosystems in CH4 and N2O emissions are becoming more important. This study used a DNDC model to simulate current and future CH4 and N2O emissions of coastal wetlands in four sites along the latitude in China. The simulation results showed that different vegetation zones, including bare beach, Spartina beach, and Phragmites beach, produced different emissions of CH4 and N2O in the same latitude region. Correlation analysis indicated that vegetation types, water level, temperature, and soil organic carbon content are the main factors affecting emissions of CH4 and N2O in coastal wetlands. PMID:24892044

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

Parworth, Caroline; Tilp, Alison; Fast, Jerome

In this study the long-term trends of non-refractory submicrometer aerosol (NR-PM1) composition and mass concentration measured by an Aerosol Chemical Speciation Monitor (ACSM) at the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site are discussed. NR-PM1 data was recorded at ~30 min intervals over a period of 19 months between November 2010 and June 2012. Positive Matrix Factorization (PMF) was performed on the measured organic mass spectral matrix using a rolling window technique to derive factors associated with distinct sources, evolution processes, and physiochemical properties. The rolling window approach also allows us to capture the dynamic variations ofmore » the chemical properties in the organic aerosol (OA) factors over time. Three OA factors were obtained including two oxygenated OA (OOA) factors, differing in degrees of oxidation, and a biomass burning OA (BBOA) factor. Back trajectory analyses were performed to investigate possible sources of major NR-PM1 species at the SGP site. Organics dominated NR-PM1 mass concentration for the majority of the study with the exception of winter, when ammonium nitrate increases due to transport of precursor species from surrounding urban and agricultural areas and also due to cooler temperatures. Sulfate mass concentrations have little seasonal variation with mixed regional and local sources. In the spring BBOA emissions increase and are mainly associated with local fires. Isoprene and carbon monoxide emission rates were obtained by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the 2011 U.S. National Emissions Inventory to represent the spatial distribution of biogenic and anthropogenic sources, respectively. The combined spatial distribution of isoprene emissions and air mass trajectories suggest that biogenic emissions from the southeast contribute to SOA formation at the SGP site during the summer.« less

Assessment of impact of unaccounted emission on ambient concentration using DEHM and AERMOD in combination with WRF

NASA Astrophysics Data System (ADS)

Kumar, Awkash; Patil, Rashmi S.; Dikshit, Anil Kumar; Kumar, Rakesh; Brandt, Jørgen; Hertel, Ole

2016-10-01

The accuracy of the results from an air quality model is governed by the quality of emission and meteorological data inputs in most of the cases. In the present study, two air quality models were applied for inverse modelling to determine the particulate matter emission strengths of urban and regional sources in and around Mumbai in India. The study takes outset in an existing emission inventory for Total Suspended Particulate Matter (TSPM). Since it is known that the available TSPM inventory is uncertain and incomplete, this study will aim for qualifying this inventory through an inverse modelling exercise. For use as input to the air quality models in this study, onsite meteorological data has been generated using the Weather Research Forecasting (WRF) model. The regional background concentration from regional sources is transported in the atmosphere from outside of the study domain. The regional background concentrations of particulate matter were obtained from model calculations with the Danish Eulerian Hemisphere Model (DEHM) for regional sources. The regional background concentrations obtained from DEHM were then used as boundary concentrations in AERMOD calculations of the contribution from local urban sources. The results from the AERMOD calculations were subsequently compared with observed concentrations and emission correction factors obtained by best fit of the model results to the observed concentrations. The study showed that emissions had to be up-scaled by between 14 and 55% in order to fit the observed concentrations; this is of course when assuming that the DEHM model describes the background concentration level of the right magnitude.

The advantage of calculating emission reduction with local emission factor in South Sumatera region

NASA Astrophysics Data System (ADS)

Buchari, Erika

2017-11-01

Green House Gases (GHG) which have different Global Warming Potential, usually expressed in CO2 equivalent. German has succeeded in emission reduction of CO2 in year 1990s, while Japan since 2001 increased load factor of public transports. Indonesia National Medium Term Development Plan, 2015-2019, has set up the target of minimum 26% and maximum 41% National Emission Reduction in 2019. Intergovernmental Panel on Climate Change (IPCC), defined three types of accuracy in counting emission of GHG, as tier 1, tier 2, and tier 3. In tier 1, calculation is based on fuel used and average emission (default), which is obtained from statistical data. While in tier 2, calculation is based fuel used and local emission factors. Tier 3 is more accurate from those in tier 1 and 2, and the calculation is based on fuel used from modelling method or from direct measurement. This paper is aimed to evaluate the calculation with tier 2 and tier 3 in South Sumatera region. In 2012, Regional Action Plan for Greenhouse Gases of South Sumatera for 2020 is about 6,569,000 ton per year and with tier 3 is about without mitigation and 6,229,858.468 ton per year. It was found that the calculation in tier 3 is more accurate in terms of fuel used of variation vehicles so that the actions of mitigation can be planned more realistically.

Development of Hot Exhaust Emission Factors for Iranian-Made Euro-2 Certified Light-Duty Vehicles.

PubMed

Banitalebi, Ehsan; Hosseini, Vahid

2016-01-05

Emission factors (EFs) are fundamental, necessary data for air pollution research and scenario implementation. With the vision of generating national EFs of the Iranian transportation system, a portable emission measurement system (PEMS) was used to develop the basic EFs for a statistically significant sample of Iranian gasoline-fueled privately owned light duty vehicles (LDVs) operated in Tehran. A smaller sample size of the same fleet was examined by chassis dynamometer (CD) bag emission measurement tests to quantify the systematic differences between the PEMS and CD methods. The selected fleet was tested over four different routes of uphill highways, flat highways, uphill urban streets, and flat urban streets. Real driving emissions (RDEs) and fuel consumption (FC) rates were calculated by weighted averaging of the results from each route. The activity of the fleet over each route type was assumed as a weighting factor. The activity data were obtained from a Tehran traffic model. The RDEs of the selected fleet were considerably higher than the certified emission levels of all vehicles. Differences between Tehran real driving cycles and the New European Driving Cycle (NEDC) was attributed to the lower loading of NEDC. A table of EFs based on RDEs was developed for the sample fleet.

Isoprene and monoterpene emissions in south-east Australia: comparison of a multi-layer canopy model with MEGAN and with atmospheric observations

NASA Astrophysics Data System (ADS)

Emmerson, Kathryn M.; Cope, Martin E.; Galbally, Ian E.; Lee, Sunhee; Nelson, Peter F.

2018-05-01

One of the key challenges in atmospheric chemistry is to reduce the uncertainty of biogenic volatile organic compound (BVOC) emission estimates from vegetation to the atmosphere. In Australia, eucalypt trees are a primary source of biogenic emissions, but their contribution to Australian air sheds is poorly quantified. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has performed poorly against Australian isoprene and monoterpene observations. Finding reasons for the MEGAN discrepancies and strengthening our understanding of biogenic emissions in this region is our focus. We compare MEGAN to the locally produced Australian Biogenic Canopy and Grass Emissions Model (ABCGEM), to identify the uncertainties associated with the emission estimates and the data requirements necessary to improve isoprene and monoterpene emissions estimates for the application of MEGAN in Australia. Previously unpublished, ABCGEM is applied as an online biogenic emissions inventory to model BVOCs in the air shed overlaying Sydney, Australia. The two models use the same meteorological inputs and chemical mechanism, but independent inputs of leaf area index (LAI), plant functional type (PFT) and emission factors. We find that LAI, a proxy for leaf biomass, has a small role in spatial, temporal and inter-model biogenic emission variability, particularly in urban areas for ABCGEM. After removing LAI as the source of the differences, we found large differences in the emission activity function for monoterpenes. In MEGAN monoterpenes are partially light dependent, reducing their dependence on temperature. In ABCGEM monoterpenes are not light dependent, meaning they continue to be emitted at high rates during hot summer days, and at night. When the light dependence of monoterpenes is switched off in MEGAN, night-time emissions increase by 90-100 % improving the comparison with observations, suggesting the possibility that monoterpenes emitted from Australian vegetation may not be as light dependent as vegetation globally. Targeted measurements of emissions from in situ Australian vegetation, particularly of the light dependence issue are critical to improving MEGAN for one of the world's major biogenic emitting regions.

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

EPA Science Inventory

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

CONSTRAINTS ON THE SYNCHROTRON EMISSION MECHANISM IN GAMMA-RAY BURSTS

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

Beniamini, Paz; Piran, Tsvi, E-mail: paz.beniamini@mail.huji.ac.il, E-mail: tsvi.piran@mail.huji.ac.il

2013-05-20

We reexamine the general synchrotron model for gamma-ray bursts' (GRBs') prompt emission and determine the regime in the parameter phase space in which it is viable. We characterize a typical GRB pulse in terms of its peak energy, peak flux, and duration and use the latest Fermi observations to constrain the high-energy part of the spectrum. We solve for the intrinsic parameters at the emission region and find the possible parameter phase space for synchrotron emission. Our approach is general and it does not depend on a specific energy dissipation mechanism. Reasonable synchrotron solutions are found with energy ratios ofmore » 10{sup -4} < {epsilon}{sub B}/{epsilon}{sub e} < 10, bulk Lorentz factor values of 300 < {Gamma} < 3000, typical electrons' Lorentz factor values of 3 Multiplication-Sign 10{sup 3} < {gamma}{sub e} < 10{sup 5}, and emission radii of the order 10{sup 15} cm < R < 10{sup 17} cm. Most remarkable among those are the rather large values of the emission radius and the electron's Lorentz factor. We find that soft (with peak energy less than 100 keV) but luminous (isotropic luminosity of 1.5 Multiplication-Sign 10{sup 53}) pulses are inefficient. This may explain the lack of strong soft bursts. In cases when most of the energy is carried out by the kinetic energy of the flow, such as in the internal shocks, the synchrotron solution requires that only a small fraction of the electrons are accelerated to relativistic velocities by the shocks. We show that future observations of very high energy photons from GRBs by CTA could possibly determine all parameters of the synchrotron model or rule it out altogether.« less

Modeling investigation of controlling factors in the increasing ratio of nitrate to non-seasalt sulfate in precipitation over Japan

NASA Astrophysics Data System (ADS)

Itahashi, Syuichi; Uno, Itsushi; Hayami, Hiroshi; Fujita, Shin-ichi

2014-08-01

Anthropogenic emissions in East Asia have been increasing during the three decades since 1980, as the population of East Asia has grown and the economies in East Asian countries have expanded. This has been particularly true in China, where NOx emissions have been rising continuously. However, because of fuel-gas desulfurization systems introduced as part of China’s 11th Five-Year Plan (2006-2010), SO2 emissions in China reached a peak in 2005-2006 and have declined since then. These drastic changes in emission levels of acidifying species are likely to have caused substantial changes in the precipitation chemistry. The absolute concentration of compounds in precipitation is inherently linked to precipitation amount; therefore, we use the ratio of nitrate (NO) to non-seasalt sulfate (nss-SO2-) concentration in precipitation as an index for evaluating acidification, which we call Ratio. In this study, we analyzed the long-term behavior of Ratio in precipitation over the Japanese archipelago during 2000-2011 and estimated the factors responsible for changes in Ratio in precipitation by using a model simulation. This analysis showed that Ratio was relatively constant at 0.5-0.6 between 2000 and 2005, and subsequently increased to 0.6-0.7 between 2006 and 2011. These changes in Ratio corresponded remarkably well to the changes of NOx/SO2 emissions ratio in China; this correspondence suggests that anthropogenic emissions from China were responsible for most of the change in precipitation chemistry over Japan. Sensitivity analysis elucidated that the increase in NOx emissions and the decrease in SO2 emissions contributed equally to the increases in Ratio. Considering both emission changes in China enables to capture the observed increasing trend of Ratio in Japan.

Mechanistic modeling of microbial interactions at pore to profile scale resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-05-01

The sensitivity of polar regions to raising global temperatures is reflected in rapidly changing hydrological processes associated with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and stimulation of other soil-borne greenhouse gas emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and other environmental factors. Soil structural elements such as aggregates and layering affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hot spots). We developed a mechanistic individual-based model to quantify microbial activity dynamics in soil pore networks considering transport processes and enzymatic activity associated with methane production in soil. The model was upscaled from single aggregates to the soil profile where freezing/thawing provides macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged profile) for resolving methane production and oxidation rates. Methane transport pathways by diffusion and ebullition of bubbles vary with hydration dynamics. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability and enzyme activity) on long-term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

Evolution of the US energy system and related emissions under varying social and technological development paradigms: Plausible scenarios for use in robust decision making.

PubMed

Brown, Kristen E; Hottle, Troy Alan; Bandyopadhyay, Rubenka; Babaee, Samaneh; Dodder, Rebecca Susanne; Kaplan, Pervin Ozge; Lenox, Carol; Loughlin, Dan

2018-06-21

The energy system is the primary source of air pollution. Thus, evolution of the energy system into the future will affect society's ability to maintain air quality. Anticipating this evolution is difficult because of inherent uncertainty in predicting future energy demand, fuel use, and technology adoption. We apply Scenario Planning to address this uncertainty, developing four very different visions of the future. Stakeholder engagement suggested technological progress and social attitudes toward the environment are critical and uncertain factors for determining future emissions. Combining transformative and static assumptions about these factors yields a matrix of four scenarios that encompass a wide range of outcomes. We implement these scenarios in the U.S. EPA MARKAL model. Results suggest that both shifting attitudes and technology transformation may lead to emission reductions relative to present, even without additional policies. Emission caps, such as the Cross State Air Pollution Rule, are most effective at protecting against future emission increases. An important outcome of this work is the scenario implementation approach, which uses technology-specific discount rates to encourage scenario-specific technology and fuel choices. End-use energy demands are modified to approximate societal changes. This implementation allows the model to respond to perturbations in manners consistent with each scenario.

Gridded anthropogenic emissions inventory and atmospheric transport of carbonyl sulfide in the U.S.: U.S. Anthropogenic COS Source and Transport

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

Zumkehr, Andrew; Hilton, Timothy W.; Whelan, Mary

Carbonyl sulfide (COS or OCS), the most abundant sulfur containing gas in the troposphere, has recently emerged as a potentially important atmospheric tracer for the carbon cycle. Atmospheric inverse modeling studies may be able to use existing tower, airborne, and satellite observations of COS to infer information about photosynthesis. However, such analysis relies on gridded anthropogenic COS source estimates that are largely based on industry activity data from over three decades ago. Here we use updated emission factor data and industry activity data to develop a gridded inventory with a 0.1 degree resolution for the U.S. domain. The inventory includesmore » the primary anthropogenic COS sources including direct emissions from the coal and aluminum industries as well as indirect sources from industrial carbon disulfide emissions. Compared to the previously published inventory, we found that the total anthropogenic source (direct and indirect) is 47% smaller. Using this new gridded inventory to drive the STEM/WRF atmospheric transport model, we found that the anthropogenic contribution to COS variation in the troposphere is small relative to the biosphere influence, which is encouraging of carbon cycle applications in this region. Additional anthropogenic sectors with highly uncertain emission factors require further field measurements.« less

Vehicular pollution modeling using the operational street pollution model (OSPM) for Chembur, Mumbai (India).

PubMed

Kumar, Awkash; Ketzel, Matthias; Patil, Rashmi S; Dikshit, Anil Kumar; Hertel, Ole

2016-06-01

Megacities in India such as Mumbai and Delhi are among the most polluted places in the world. In the present study, the widely used operational street pollution model (OSPM) is applied for assessing pollutant loads in the street canyons of Chembur, a suburban area just outside Mumbai city. Chembur is both industrialized and highly congested with vehicles. There are six major street canyons in this area, for which modeling has been carried out for NOx and particulate matter (PM). The vehicle emission factors for Indian cities have been developed by Automotive Research Association of India (ARAI) for PM, not specifically for PM10 or PM2.5. The model has been applied for 4 days of winter season and for the whole year to see the difference of effect of meteorology. The urban background concentrations have been obtained from an air quality monitoring station. Results have been compared with measured concentrations from the routine monitoring performed in Mumbai. NOx emissions originate mainly from vehicles which are ground-level sources and are emitting close to where people live. Therefore, those emissions are highly relevant. The modeled NOx concentration compared satisfactorily with observed data. However, this was not the case for PM, most likely because the emission inventory did not contain emission terms due to resuspended particulate matter.

Screening level risk assessment model for chemical fate and effects in the environment.

PubMed

Arnot, Jon A; Mackay, Don; Webster, Eva; Southwood, Jeanette M

2006-04-01

A screening level risk assessment model is developed and described to assess and prioritize chemicals by estimating environmental fate and transport, bioaccumulation, and exposure to humans and wildlife for a unit emission rate. The most sensitive risk endpoint is identified and a critical emission rate is then calculated as a result of that endpoint being reached. Finally, this estimated critical emission rate is compared with the estimated actual emission rate as a risk assessment factor. This "back-tracking" process avoids the use of highly uncertain emission rate data as model input. The application of the model is demonstrated in detail for three diverse chemicals and in less detail for a group of 70 chemicals drawn from the Canadian Domestic Substances List. The simple Level II and the more complex Level III fate calculations are used to "bin" substances into categories of similar probable risk. The essential role of the model is to synthesize information on chemical and environmental properties within a consistent mass balance framework to yield an overall estimate of screening level risk with respect to the defined endpoint. The approach may be useful to identify and prioritize those chemicals of commerce that are of greatest potential concern and require more comprehensive modeling and monitoring evaluations in actual regional environments and food webs.

VOC emissions from residential combustion of Southern and mid-European woods

NASA Astrophysics Data System (ADS)

Evtyugina, Margarita; Alves, Célia; Calvo, Ana; Nunes, Teresa; Tarelho, Luís; Duarte, Márcio; Prozil, Sónia O.; Evtuguin, Dmitry V.; Pio, Casimiro

2014-02-01

Emissions of trace gases (carbon dioxide (CO2), carbon monoxide (CO), total hydrocarbons (THC)), and volatile organic compounds (VOCs) from combustion of European beech, Pyrenean oak and black poplar in a domestic woodstove and fireplace were studied. These woods are widely used as biofuel in residential combustion in Southern and mid-European countries. VOCs in the flue gases were collected in Tedlar bags, concentrated in sorbent tubes and analysed by thermal desorption-gas chromatography-flame ionisation detection (GC-FID). CO2 emissions ranged from 1415 ± 136 to 1879 ± 29 g kg-1 (dry basis). The highest emission factors for CO and THC, 115.8 ± 11.7 and 95.6 24.7 ± 6.3 g kg-1 (dry basis), respectively, were obtained during the combustion of black poplar in the fireplace. European beech presented the lowest CO and THC emission factors for both burning appliances. Significant differences in emissions of VOCs were observed among wood species burnt and combustion devices. In general the highest emission factors were obtained from the combustion of Pyrenean oak in the woodstove. Among the VOCs identified, benzene and related compounds were always the most abundant group, followed by oxygenated compounds and aliphatic hydrocarbons. The amount and the composition of emitted VOCs were strongly affected by the wood composition, the type of burning device and operating conditions. Emission data obtained in this work are useful for modelling the impact of residential wood combustion on air quality and tropospheric ozone formation.

Atmospheric Ammonia Over China: Emission Estimates And Impact On Air Quality

NASA Astrophysics Data System (ADS)

Zhang, L.; Chen, Y.; Zhao, Y.; Henze, D. K.

2016-12-01

Ammonia (NH3) in the atmosphere is an important precursor of aerosols, and its deposition through wet and dry processes can cause adverse effects on ecosystems. The ammonia emissions over China are particularly large due to intensive agricultural activities, yet our current estimates of Chinese ammonia emissions and associated consequences on air quality are subject to large errors. We use the GEOS-Chem chemical transport model and its adjoint model to better quantify this issue. The TES satellite observations of ammonia concentrations and surface measurements of wet deposition fluxes are assimilated into the model to constrain the ammonia emissions over China. Optimized emissions show a strong seasonal variability with emissions in summer a factor of 3 higher than winter. This is consistent with an improved bottom-up estimate of Chinese ammonia emissions from fertilizer use by using more practical fertilizer application rates for different crop types. We further use the GEOS-Chem adjoint at 0.25x0.3125 degree resolution to examine the sources contributing to the PM2.5 air pollution over North China. We show that wintertime PM2.5 over Beijing is largely contributed by residential and industrial sources, and ammonia emissions from agriculture activities. PM2.5 concentrations over North China are particularly sensitive to emissions of ammonia and nitrogen oxides, reflecting strong formation of aerosol nitrate in the cold seasons.

Simulation of nitrous oxide effluxes, crop yields and soil physical properties using the LandscapeDNDC model in managed ecosystem

NASA Astrophysics Data System (ADS)

Nyckowiak, Jedrzej; Lesny, Jacek; Haas, Edwin; Juszczak, Radoslaw; Kiese, Ralf; Butterbach-Bahl, Klaus; Olejnik, Janusz

2014-05-01

Modeling of nitrous oxide emissions from soil is very complex. Many different biological and chemical processes take place in soils which determine the amount of emitted nitrous oxide. Additionaly, biogeochemical models contain many detailed factors which may determine fluxes and other simulated variables. We used the LandscapeDNDC model in order to simulate N2O emissions, crop yields and soil physical properties from mineral cultivated soils in Poland. Nitrous oxide emissions from soils were modeled for fields with winter wheat, winter rye, spring barley, triticale, potatoes and alfalfa crops. Simulations were carried out for the plots of the Brody arable experimental station of Poznan University of Life Science in western Poland and covered the period 2003 - 2012. The model accuracy and its efficiency was determined by comparing simulations result with measurements of nitrous oxide emissions (measured with static chambers) from about 40 field campaigns. N2O emissions are strongly dependent on temperature and soil water content, hence we compared also simulated soil temperature at 10cm depth and soil water content at the same depth with the daily measured values of these driving variables. We compared also simulated yield quantities for each individual experimental plots with yield quantities which were measured in the period 2003-2012. We conclude that the LandscapeDNDC model is capable to simulate soil N2O emissions, crop yields and physical properties of soil with satisfactorily good accuracy and efficiency.

Idle emissions from heavy-duty diesel and natural gas vehicles at high altitude.

PubMed

McCormick, R L; Graboski, M S; Alleman, T L; Yanowitz, J

2000-11-01

Idle emissions of total hydrocarbon (THC), CO, NOx, and particulate matter (PM) were measured from 24 heavy-duty diesel-fueled (12 trucks and 12 buses) and 4 heavy-duty compressed natural gas (CNG)-fueled vehicles. The volatile organic fraction (VOF) of PM and aldehyde emissions were also measured for many of the diesel vehicles. Experiments were conducted at 1609 m above sea level using a full exhaust flow dilution tunnel method identical to that used for heavy-duty engine Federal Test Procedure (FTP) testing. Diesel trucks averaged 0.170 g/min THC, 1.183 g/min CO, 1.416 g/min NOx, and 0.030 g/min PM. Diesel buses averaged 0.137 g/min THC, 1.326 g/min CO, 2.015 g/min NOx, and 0.048 g/min PM. Results are compared to idle emission factors from the MOBILE5 and PART5 inventory models. The models significantly (45-75%) overestimate emissions of THC and CO in comparison with results measured from the fleet of vehicles examined in this study. Measured NOx emissions were significantly higher (30-100%) than model predictions. For the pre-1999 (pre-consent decree) truck engines examined in this study, idle NOx emissions increased with model year with a linear fit (r2 = 0.6). PART5 nationwide fleet average emissions are within 1 order of magnitude of emissions for the group of vehicles tested in this study. Aldehyde emissions for bus idling averaged 6 mg/min. The VOF averaged 19% of total PM for buses and 49% for trucks. CNG vehicle idle emissions averaged 1.435 g/min for THC, 1.119 g/min for CO, 0.267 g/min for NOx, and 0.003 g/min for PM. The g/min PM emissions are only a small fraction of g/min PM emissions during vehicle driving. However, idle emissions of NOx, CO, and THC are significant in comparison with driving emissions.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Impacts of Climate Change on Forest Isoprene Emission: Diversity Matters

NASA Astrophysics Data System (ADS)

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

2016-12-01

Many abiotic and biotic factors influence volatile organic compound (VOC) production and emission by plants; for example, climate warming is widely projected to enhance VOC emissions by stimulating their biosynthesis. The species-dependent nature of VOC production by plants indicates that changes in species abundances may play an important role in determining VOC production and emission at the ecosystem scale. To date, however, the role of species abundances in affecting VOC emissions has not been well studied. We examine the role of forest systems as sources of VOC's in terms of how species diversity and abundance influence isoprene emission under climate warming by using an individual-based forest VOC emission model—UVAFME-VOC 1.0—that can explicitly simulate forest compositional and structural change and VOC production/emission at the individual and canopy scales. We simulate isoprene emissions under two warming scenarios (warming by 2 and 4 °C) for temperate deciduous forests of the southeastern United States, where the dominant isoprene-emitting species are oaks (Quercus). The simulations show that, contrary to previous expectations, a warming by 2 °C does not affect isoprene emissions, while a further warming by 4 °C causes a large reduction of isoprene emissions. Interestingly, climate warming can directly enhance isoprene emission and simultaneously indirectly reduce it by lowering the abundance of isoprene-emitting species. Under gradual continuous warming, the indirect effect outweighs the direct effect, thus reducing overall forest isoprene emission. This modelling study shows that climate warming does not necessarily stimulate ecosystem VOC emissions and, more generally, that ecosystem diversity and composition can play a significant role in determining vegetation VOC emission capacity. Future earth system models and climate-chemistry models should better represent species diversity in projecting climate-air quality feedbacks and making management policy recommendations.

Comparative Evaluation of Five Fire Emissions Datasets Using the GEOS-5 Model

NASA Astrophysics Data System (ADS)

Ichoku, C. M.; Pan, X.; Chin, M.; Bian, H.; Darmenov, A.; Ellison, L.; Kucsera, T. L.; da Silva, A. M., Jr.; Petrenko, M. M.; Wang, J.; Ge, C.; Wiedinmyer, C.

2017-12-01

Wildfires and other types of biomass burning affect most vegetated parts of the globe, contributing 40% of the annual global atmospheric loading of carbonaceous aerosols, as well as significant amounts of numerous trace gases, such as carbon dioxide, carbon monoxide, and methane. Many of these smoke constituents affect the air quality and/or the climate system directly or through their interactions with solar radiation and cloud properties. However, fire emissions are poorly constrained in global and regional models, resulting in high levels of uncertainty in understanding their real impacts. With the advent of satellite remote sensing of fires and burned areas in the last couple of decades, a number of fire emissions products have become available for use in relevant research and applications. In this study, we evaluated five global biomass burning emissions datasets, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) GFEDv4s (Global Fire Emissions Database version 4 with small fires); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0); (4) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); and (5) Fire INventory from NCAR (FINN) version 1.5. Overall, the spatial patterns of biomass burning emissions from these inventories are similar, although the magnitudes of the emissions can be noticeably different. The inventories derived using top-down approaches (QFEDv2.4 and FEERv1) are larger than those based on bottom-up approaches. For example, global organic carbon (OC) emissions in 2008 are: QFEDv2.4 (51.93 Tg), FEERv1 (28.48 Tg), FINN v1.5 (19.48 Tg), GFEDv3.1 (15.65 Tg) and GFEDv4s (13.76 Tg); representing a factor of 3.7 difference between the largest and the least. We also used all five biomass-burning emissions datasets to conduct aerosol simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5), and compared the resulting aerosol optical depth (AOD) output to the corresponding retrievals from MODIS and AERONET. Simulated AOD based on all five emissions inventories show significant underestimation in biomass burning dominated regions. Attributions of possible factors responsible for the differences among the inventories were further explored in Southern Africa and South America, two of the major biomass burning regions of the world.

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.

Search for C II Emission on Cosmological Scales at Redshift Z ˜ 2.6

NASA Astrophysics Data System (ADS)

Pullen, Anthony R.; Serra, Paolo; Chang, Tzu-Ching; Doré, Olivier; Ho, Shirley

2018-05-01

We present a search for Cii emission over cosmological scales at high-redshifts. The Cii line is a prime candidate to be a tracer of star formation over large-scale structure since it is one of the brightest emission lines from galaxies. Redshifted Cii emission appears in the submillimeter regime, meaning it could potentially be present in the higher frequency intensity data from the Planck satellite used to measure the cosmic infrared background (CIB). We search for Cii emission over redshifts z = 2 - 3.2 in the Planck 545 GHz intensity map by cross-correlating the 3 highest frequency Planck maps with spectroscopic quasars and CMASS galaxies from the Sloan Digital Sky Survey III (SDSS-III), which we then use to jointly fit for Cii intensity, CIB parameters, and thermal Sunyaev-Zeldovich (SZ) emission. We report a measurement of an anomalous emission I_ν =6.6^{+5.0}_{-4.8}× 10^4Jy/sr at 95% confidence, which could be explained by Cii emission, favoring collisional excitation models of Cii emission that tend to be more optimistic than models based on Cii luminosity scaling relations from local measurements; however, a comparison of Bayesian information criteria reveal that this model and the CIB & SZ only model are equally plausible. Thus, more sensitive measurements will be needed to confirm the existence of large-scale Cii emission at high redshifts. Finally, we forecast that intensity maps from Planck cross-correlated with quasars from the Dark Energy Spectroscopic Instrument (DESI) would increase our sensitivity to Cii emission by a factor of 5, while the proposed Primordial Inflation Explorer (PIXIE) could increase the sensitivity further.

Documentation for the Waste Reduction Model (WARM)

EPA Pesticide Factsheets

This page describes the WARM documentation files and provides links to all documentation files associated with EPA’s Waste Reduction Model (WARM). The page includes a brief summary of the chapters documenting the greenhouse gas emission and energy factors.

NONROAD2008a Installation and Updates

EPA Pesticide Factsheets

NONROAD2008 is the overall set of modeling files including the core model, default data files, graphical user interface (GUI), and reporting utility. NONROAD2008a is essentially the same, but with one correction to the NOx emission factor data file.

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Andreae, Meinrat O.

2016-01-01

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Andreae, Meinrat O.

2015-01-01

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha-x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China

NASA Astrophysics Data System (ADS)

Xiong, Chuanhe; Yang, Degang; Xia, Fuqiang; Huo, Jinwei

2016-11-01

Xinjiang’s agricultural carbon emissions showed three stages of change, i.e., continued to rise, declined and continued to rise, during 1991-2014. The agriculture belonged to the “low emissions and high efficiency” agriculture category, with a lower agricultural carbon emission intensity. By using the logarithmic mean divisia index decomposition method, agricultural carbon emissions were decomposed into an efficiency factor, a structure factor, an economy factor, and a labour factor. We divided the study period into five stages based on the changes in efficiency factor and economy factor. Xinjiang showed different agricultural carbon emission characteristics at different stages. The degree of impact on agricultural carbon emissions at these stages depended on the combined effect of planting-animal husbandry carbon intensity and agricultural labour productivity. The economy factor was the critical factor to promote the increase in agricultural carbon emissions, while the main inhibiting factor for agricultural carbon emissions was the efficiency factor. The labour factor became more and more obvious in increasing agricultural carbon emissions. Finally, we discuss policy recommendations in terms of the main factors, including the development of agricultural science and technology (S&T), the establishment of three major mechanisms and transfer of rural labour in ethnic areas.

Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China

PubMed Central

Xiong, Chuanhe; Yang, Degang; Xia, Fuqiang; Huo, Jinwei

2016-01-01

Xinjiang’s agricultural carbon emissions showed three stages of change, i.e., continued to rise, declined and continued to rise, during 1991–2014. The agriculture belonged to the “low emissions and high efficiency” agriculture category, with a lower agricultural carbon emission intensity. By using the logarithmic mean divisia index decomposition method, agricultural carbon emissions were decomposed into an efficiency factor, a structure factor, an economy factor, and a labour factor. We divided the study period into five stages based on the changes in efficiency factor and economy factor. Xinjiang showed different agricultural carbon emission characteristics at different stages. The degree of impact on agricultural carbon emissions at these stages depended on the combined effect of planting-animal husbandry carbon intensity and agricultural labour productivity. The economy factor was the critical factor to promote the increase in agricultural carbon emissions, while the main inhibiting factor for agricultural carbon emissions was the efficiency factor. The labour factor became more and more obvious in increasing agricultural carbon emissions. Finally, we discuss policy recommendations in terms of the main factors, including the development of agricultural science and technology (S&T), the establishment of three major mechanisms and transfer of rural labour in ethnic areas. PMID:27830739

Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China.

PubMed

Xiong, Chuanhe; Yang, Degang; Xia, Fuqiang; Huo, Jinwei

2016-11-10

Xinjiang's agricultural carbon emissions showed three stages of change, i.e., continued to rise, declined and continued to rise, during 1991-2014. The agriculture belonged to the "low emissions and high efficiency" agriculture category, with a lower agricultural carbon emission intensity. By using the logarithmic mean divisia index decomposition method, agricultural carbon emissions were decomposed into an efficiency factor, a structure factor, an economy factor, and a labour factor. We divided the study period into five stages based on the changes in efficiency factor and economy factor. Xinjiang showed different agricultural carbon emission characteristics at different stages. The degree of impact on agricultural carbon emissions at these stages depended on the combined effect of planting-animal husbandry carbon intensity and agricultural labour productivity. The economy factor was the critical factor to promote the increase in agricultural carbon emissions, while the main inhibiting factor for agricultural carbon emissions was the efficiency factor. The labour factor became more and more obvious in increasing agricultural carbon emissions. Finally, we discuss policy recommendations in terms of the main factors, including the development of agricultural science and technology (S&T), the establishment of three major mechanisms and transfer of rural labour in ethnic areas.

Soil nitric oxide emissions from terrestrial ecosystems in China: a synthesis of modeling and measurements

PubMed Central

Huang, Yong; Li, Dejun

2014-01-01

Soils are among the major sources of atmospheric nitric oxide (NO), which play a crucial role in atmospheric chemistry. Here we systematically synthesized the modeling studies and field measurements and presented a novel soil NO emission inventory of terrestrial ecosystems in China. The previously modeled inventories ranged from 480 to 1375 and from 242.8 to 550 Gg N yr−1 for all lands and croplands, respectively. Nevertheless, all the previous modeling studies were conducted based on very few measurements from China. According to the current synthesis of field measurements, most soil NO emission measurements were conducted at croplands, while the measurements were only conducted at two sites for forest and grassland. The median NO flux was 3.2 ng N m−2 s−1 with a fertilizer induced emission factor (FIE) of 0.04% for rice fields, and was 7.1 ng N m−2 s−1 with an FIE of 0.67% for uplands. A novel NO emission inventory of 1226.33 (ranging from 588.24 to 2132.05) Gg N yr−1 was estimated for China's terrestrial ecosystems, which was about 18% of anthropogenic emissions. More field measurements should be conducted to cover more biomes and obtain more representative data in order to well constrain soil NO emission inventory of China. PMID:25490942

Estimated Emissions from the Prime-Movers of Unconventional Natural Gas Well Development Using Recently Collected In-Use Data in the United States.

PubMed

Johnson, Derek; Heltzel, Robert; Nix, Andrew; Darzi, Mahdi; Oliver, Dakota

2018-05-01

Natural gas from shale plays dominates new production and growth. However, unconventional well development is an energy intensive process. The prime movers, which include over-the-road service trucks, horizontal drilling rigs, and hydraulic fracturing pumps, are predominately powered by diesel engines that impact air quality. Instead of relying on certification data or outdated emission factors, this model uses new in-use emissions and activity data combined with historical literature to develop a national emissions inventory. For the diesel only case, hydraulic fracturing engines produced the most NO x emissions, while drilling engines produced the most CO emissions, and truck engines produced the most THC emissions. By implementing dual-fuel and dedicated natural gas engines, total fuel energy consumed, CO 2 , CO, THC, and CH 4 emissions would increase, while NO x emissions, diesel fuel consumption, and fuel costs would decrease. Dedicated natural gas engines offered significant reductions in NO x emissions. Additional scenarios examined extreme cases of full fleet conversions. While deep market penetrations could reduce fuel costs, both technologies could significantly increase CH 4 emissions. While this model is based on a small sample size of engine configurations, data were collected during real in-use activity and is representative of real world activity.

Evaluation of a Mobile Phone for Aircraft GPS Interference

NASA Technical Reports Server (NTRS)

Nguyen, Truong X.

2004-01-01

Measurements of spurious emissions from a mobile phone are conducted in a reverberation chamber for the Global Positioning System (GPS) radio frequency band. This phone model was previously determined to have caused interference to several aircraft GPS receivers. Interference path loss (IPL) factors are applied to the emission data, and the outcome compared against GPS receiver susceptibility. The resulting negative safety margins indicate there are risks to aircraft GPS systems. The maximum emission level from the phone is also shown to be comparable with some laptop computer's emissions, implying that laptop computers can provide similar risks to aircraft GPS receivers.

Radiation of partially ionized atomic hydrogen

NASA Technical Reports Server (NTRS)

Soon, W. H.; Kunc, J. A.

1990-01-01

A nonlinear collisional-radiative model for determination of production of electrons, positive and negative ions, excited atoms, and spectral and continuum line intensities in stationary partially ionized atomic hydrogen is presented. Transport of radiation is included by coupling the rate equations for production of the electrons, ions, and excited atoms with the radiation escape factors, which are not constant but depend on plasma conditions. It is found that the contribution of the negative ion emission to the total continuum emission can be important. Comparison of the calculated total continuum emission coefficient, including the negative ion emission, is in good agreement with experimental results.