scholarly journals A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

2020 ◽  
Vol 12 (4) ◽  
pp. 3413-3442
Author(s):  
Erin E. McDuffie ◽  
Steven J. Smith ◽  
Patrick O'Rourke ◽  
Kushal Tibrewal ◽  
Chandra Venkataraman ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Data System ◽  
Atmospheric Pollutants ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Fuel Type ◽  
Road Transportation ◽  
International Shipping ◽  
Global Emission ◽  
Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5∘ × 0.5∘) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

scholarly journals A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): An application of the Community Emissions Data System (CEDS)

2020 ◽  
Author(s):  
Erin E. McDuffie ◽  
Steven J. Smith ◽  
Patrick O'Rourke ◽  
Kushal Tibrewal ◽  
Chandra Venkataraman ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Data System ◽  
Atmospheric Pollutants ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Fuel Type ◽  
Road Transportation ◽  
Activity Data ◽  
Global Emission ◽  
Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the fate and transport of atmospheric pollution, as well as the resulting impacts on the environment, human health, and society. Rapid changes in today’s society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel-type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx, CO, SO2, NH3, NMVOCs, BC, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture, energy generation, industrial processes, transportation (on-road and non-road), residential, commercial, and other sectors (RCO), waste, solvent use, and international-shipping) and four fuel categories (total coal, solid biofuel, and the sum of liquid fuels and natural gas combustion, plus remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes global gridded (0.5°×0.5°) emission fluxes with monthly time resolution for each compound, sector, and fuel-type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default calibration procedure, and modifications to the final procedures for emissions gridding and aggregation to retain sector and fuel-specific information. Relative to the previous CEDS data released for CMIP6 (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to-date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel-types across multiple source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors, as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), as well as emissions from waste. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture serving as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories, including uncertainties in the underlying activity data and sector- and region-specific emission factors. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS. The CEDSGBD-MAPS emission inventory dataset (both annual country-total and global gridded files) is publicly available and registered under: https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020).

Southeast Asian anthropogenic emission changes: An analysis from regional and global emission inventories

2020 ◽  
Author(s):  
Yun fat Lam ◽  
Shimul Roy ◽  
Ka Wing Chui
Keyword(s):  
Rural Areas ◽  
Industrial Sector ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Road Transportation ◽  
Global Emission ◽  
Transportation Sector ◽  
Emission Changes ◽  
Asean Countries ◽  
Average Contribution

<p>In ASEAN (Southeast Asia) countries, anthropogenic emissions have increased significantly over the last two decades from a variety of sources, including power and heating, industries, road-transportation, residential, and agricultural activities. In this study, we analyzed different emission inventories (i.e., MICS-Asia, REAS, EDGAR) to provide the integrated emissions for ASEAN during the period 2000-2010. The study found that anthropogenic emission contribution from ASEAN countries to the total Asian emission was notable during that period. For instance, from the MIX-Asian EI, our analysis shows that the average contribution was the highest from the transportation sector (34%), followed by residential (29%), power (24%), and industrial sector (14%), respectively in 2010. However, similar to the sector-specific emission contribution in 2000 in ASEAN countries, residential sector was the most significant contributor for CO (53%), PM10 (48%), PM2.5 (63%), BC (76%), OC (79%) in 2010, although it is in decreasing trend compared to other sectors. On the contrary, emission contribution of SO2 was the highest from the industrial sector (47%), followed by power (36%), while NOx and NMVOC were contributed mainly by transportation sector (55% and 45%, respectively). Spatially, the emission intensities of SO2, CO, NOx, NMVOC, PM10, PM2.5, BC, OC, and CO2 were high in the major urban cities of Thailand, Vietnam, Malaysia, Philippines, and Indonesia except CH4, N2O, and NH3, which were high in the rural areas of ASEAN countries.</p>

scholarly journals Updated national emission inventory and comparison with the Emissions Database for Global Atmospheric Research (EDGAR): case of Lebanon

2022 ◽  
Author(s):  
Anwar Al Shami ◽  
Elissar Al Aawar ◽  
Abdelkader Baayoun ◽  
Najat A. Saliba ◽  
Jonilda Kushta ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Model Performance ◽  
Atmospheric Modeling ◽  
Atmospheric Pollutants ◽  
Pollutant Emissions ◽  
Emission Inventories ◽  
Gaseous Species ◽  
Emission Standard ◽  
Activity Data ◽  
Atmospheric Research

AbstractPhysically based computational modeling is an effective tool for estimating and predicting the spatial distribution of pollutant concentrations in complex environments. A detailed and up-to-date emission inventory is one of the most important components of atmospheric modeling and a prerequisite for achieving high model performance. Lebanon lacks an accurate inventory of anthropogenic emission fluxes. In the absence of a clear emission standard and standardized activity datasets in Lebanon, this work serves to fill this gap by presenting the first national effort to develop a national emission inventory by exhaustively quantifying detailed multisector, multi-species pollutant emissions in Lebanon for atmospheric pollutants that are internationally monitored and regulated as relevant to air quality. Following the classification of the Emissions Database for Global Atmospheric Research (EDGAR), we present the methodology followed for each subsector based on its characteristics and types of fuels consumed. The estimated emissions encompass gaseous species (CO, NOx, SO2), and particulate matter (PM2.5 and PM10). We compare totals per sector obtained from the newly developed national inventory with the international EDGAR inventory and previously published emission inventories for the country for base year 2010 presenting current discrepancies and analyzing their causes. The observed discrepancies highlight the fact that emission inventories, especially for data-scarce settings, are highly sensitive to the activity data and their underlying assumptions, and to the methodology used to estimate the emissions.

scholarly journals Molecular hydrogen (H2) combustion emissions and their isotope (D/H) signatures from domestic heaters, diesel vehicle engines, waste incinerator plants, and biomass burning

2012 ◽  
Vol 12 (3) ◽  
pp. 6839-6875
Author(s):  
M. K. Vollmer ◽  
S. Walter ◽  
J. Mohn ◽  
M. Steinbacher ◽  
S. W. Bond ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Molecular Hydrogen ◽  
Fossil Fuel ◽  
Ambient Air ◽  
Waste Incinerator ◽  
Emission Inventories ◽  
Road Transportation ◽  
Global Emission ◽  
Combustion Emissions ◽  
Combustion Processes

Abstract. Molecular hydrogen (H2), its stable isotope signature (δD), and the key combustion parameters carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) were measured from various combustion processes. H2 in the exhaust of gas and oil-fired heaters and of waste incinerator plants was generally depleted compared to ambient intake air, while CO was significantly elevated. These findings contradict the often assumed co-occurring net H2 and CO emissions in combustion processes and suggest that previous H2 emissions from combustion may have been overestimated when scaled to CO emissions. For the heater exhausts, H2 and δD generally decrease with increasing fuel-to-air ratio, from ambient values of ∼0.5 ppm and +130‰ to 0.2 ppm and −206‰, respectively. These results are interpreted as a combination of an isotopically light H2 source from fossil fuel combustion and a D/H kinetic isotope fractionation of hydrogen in the advected ambient air during its partial removal during combustion. Diesel exhaust measurements from dynamometer test stand driving cycles show elevated H2 and CO emissions during cold-start and some acceleration phases. Their molar H2/CO ratios are <0.25, significantly smaller than those for gasoline combustion. Using H2/CO emission ratios, along with CO global emission inventories, we estimate global H2 emissions for 2000, 2005, and 2010. For road transportation (gasoline and diesel), we calculate 8.6 ± 2.1 Tg, 6.3 ± 1.5 Tg, and 4.1 ± 1.0 Tg, respectively, whereas the contribution from diesel vehicles has increased from 5% to 8% over this time. Other fossil fuel emissions are believed to be negligible but H2 emissions from coal combustion are unknown. For residential (domestic) emissions, which are likely dominated by biofuel combustion, emissions for the same years are estimated at 2.7 ± 0.7 Tg, 2.8 ± 0.7 Tg, and 3.0 ± 0.8 Tg, respectively. Our wood combustion measurements are combined with results from the literature to calculate biomass burning emissions. For these estimates, we propose a molar H2/CH4 ratio of 3.3, when using CH4 emission inventories. When using this approach, our resulting global biomass burning H2 emissions agree well with published results, suggesting that CH4 emissions may be a good proxy for H2 emissions.

scholarly journals Are contributions of emissions to ozone a matter of scale? – A study using MECO(n) (MESSy v2.50)

2019 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen
Keyword(s):  
Source Apportionment ◽  
Emission Inventory ◽  
Climate Model ◽  
Ground Level ◽  
Emission Sources ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Model Resolution ◽  
Ground Level Ozone ◽  
Transport Emissions

Abstract. Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air-quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a high spatial resolution, while studies focusing on climate related questions often use coarsely resolved global models. It is well known that simulated ozone concentrations depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated by source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study is a first attempt to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions diagnosed with a tagging method. The differences of the ozone contributions caused by these factors are compared with differences which arise due to different emission inventories. To do so we apply the MECO(n) model system which on-line couples a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (300 km resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolution. Averaged over Europe the simulated contributions of land transport emissions to ground-level ozone differ by 10 % at maximum. For other anthropogenic emission sources the differences are in the same order of magnitude, while the contribution of stratospheric ozone to ground level ozone differs by up to 30 % on average. This suggests that ozone contributions of anthropogenic emission sources averaged on continental scale are rather robust with respect to different models, model and emission inventory resolutions. On regional scale, however, we quantified differences of the contribution of land transport emissions to ozone of up to 20 %. Depending on the region the largest differences are either caused by inter model differences, or differences of the anthropogenic emission inventories. Clearly, the results strongly depend on the compared models and emission inventories and cannot necessarily be generalised, however we show how the inclusion of source apportionment methods can help in analysing inter-model differences.

scholarly journals Sectorial and regional uncertainty analysis of the contribution of anthropogenic emissions to regional and global PM<sub>2.5</sub> health impacts

2017 ◽  
Author(s):  
Monica Crippa ◽  
Greet Janssens-Maenhout ◽  
Diego Guizzardi ◽  
Rita Van Dingenen ◽  
Frank Dentener
Keyword(s):  
Power Generation ◽  
Air Quality ◽  
Human Health ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Health Impacts ◽  
Pollutant Emission ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Relative Contribution

Abstract. In this work we couple the HTAPv2.2 global air pollutant emission inventory with the global source receptor model TM5-FASST to evaluate the relative contribution of the major anthropogenic emission sources (power generation, industry, ground transport, residential, agriculture and international shipping) to air quality and human health in 2010. We focus on particulate matter (PM) concentrations because of the relative importance of PM2.5 emissions in populated areas and the proven cumulative negative effects on human health. We estimate that in 2010 regional annual averaged anthropogenic PM2.5 concentrations varied between ca. 1 and 40 μg/m3 depending on the region, with the highest concentrations observed in China and India, and lower concentrations in Europe and North America. The relative contribution of anthropogenic emission source sectors to PM2.5 concentrations varies between the regions. European PM pollution is mainly influenced by the agricultural and residential sectors, while the major contributing sectors to PM pollution in Asia and the emerging economies are the power generation, industrial and residential sectors. We also evaluate the emission sectors and emission regions in which pollution reduction measures would lead to the largest improvement on the overall air quality. We show that in order to improve air quality, regional policies should be implemented (e.g. in Europe) due to the transboundary features of PM pollution. In addition, we investigate emission inventory uncertainties and their propagation to PM2.5 concentrations, in order to identify the most effective strategies to be implemented at sector and regional level to improve emission inventories knowledge and air quality. We show that the uncertainty of PM concentrations depends not only on the uncertainty of local emission inventories but also on that of the surrounding regions. Finally, we propagate emission inventories uncertainty to PM concentrations and health impacts.

scholarly journals Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

2013 ◽  
Vol 13 (18) ◽  
pp. 9415-9438 ◽  
Author(s):  
E. V. Berezin ◽  
I. B. Konovalov ◽  
P. Ciais ◽  
A. Richter ◽  
S. Tao ◽  
...  
Keyword(s):  
Time Series ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Satellite Measurements ◽  
Top Down ◽  
Global Emission ◽  
Tropospheric No2 ◽  
Emission Changes ◽  
Emission Ratios

Abstract. Multiannual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect top-down annual estimates of CO2 emissions are derived from the satellite NO2 column measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry–transport model and the CO2-to-NOx emission ratios from the Emission Database for Global Atmospheric Research (EDGAR) global anthropogenic emission inventory and Regional Emission Inventory in Asia (REAS). Exponential trends in the normalized time series of annual emissions are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are best estimated to be in the range from 3.7 to 8.3 and from 11.0 to 13.2% per year, respectively, taking into account statistical uncertainties and differences between the CO2-to-NOx emission ratios from the EDGAR and REAS inventories. Comparison of our indirect top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by the EDGAR (version 4.2) and Global Carbon Project (GCP) glomal emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the global emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and indirect top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the global emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies that indicated probable large uncertainties in the energy production and other activity data for China from international energy statistics used as the input information in the global emission inventories. For the period from 2001 to 2008, some quantitative differences between the different kinds of estimates are found to be in the range of possible systematic uncertainties associated with our estimation method. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources collocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

scholarly journals Contribution and uncertainty of sectorial and regional emissions to regional and global PM<sub>2.5</sub> health impacts

2019 ◽  
Vol 19 (7) ◽  
pp. 5165-5186 ◽  
Author(s):  
Monica Crippa ◽  
Greet Janssens-Maenhout ◽  
Diego Guizzardi ◽  
Rita Van Dingenen ◽  
Frank Dentener
Keyword(s):  
Power Generation ◽  
Air Quality ◽  
Human Health ◽  
Emission Inventory ◽  
Health Impacts ◽  
Pollutant Emission ◽  
Emission Sources ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Premature Deaths

Abstract. In this work we couple the HTAP_v2.2 global air pollutant emission inventory with the global source receptor model TM5-FASST to evaluate the relative contributions of the major anthropogenic emission sources (power generation, industry, ground transport, residential, agriculture and international shipping) to air quality and human health in 2010. We focus on particulate matter (PM) concentrations because of the relative importance of PM2.5 emissions in populated areas and the well-documented cumulative negative effects on human health. We estimate that in 2010, depending on the region, annual averaged anthropogenic PM2.5 concentrations varied between ca. 1 and 40 µg m−3, with the highest concentrations observed in China and India, and lower concentrations in Europe and North America. The relative contribution of anthropogenic emission sources to PM2.5 concentrations varies between the regions. European PM pollution is mainly influenced by the agricultural and residential sectors, while the major contributing sectors to PM pollution in Asia and the emerging economies are the power generation, industrial and residential sectors. We also evaluate the emission sectors and emission regions in which pollution reduction measures would lead to the largest improvement on the overall air quality. We show that air quality improvements would require regional policies, in addition to local- and urban-scale measures, due to the transboundary features of PM pollution. We investigate emission inventory uncertainties and their propagation to PM2.5 concentrations, in order to identify the most effective strategies to be implemented at sector and regional level to improve emission inventories, knowledge and air quality modelling. We show that the uncertainty of PM concentrations depends not only on the uncertainty of local emission inventories, but also on that of the surrounding regions. Countries with high emission uncertainties are often impacted by the uncertainty of pollution coming from surrounding regions, highlighting the need for effective efforts in improving emissions not only within a region but also from extra-regional sources. Finally, we propagate emission inventory uncertainty to PM concentrations and health impacts. We estimate 2.1 million premature deaths per year with an uncertainty of more than 1 million premature deaths per year due to the uncertainty associated only with the emissions.

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