Comparison of the Anthropogenic Emission Inventory for CMIP6 Models with a Country-Level Inventory over China and the Simulations of the Aerosol Properties

2022 ◽  
Vol 39 (1) ◽  
pp. 80-96
Author(s):  
Tianyi Fan ◽  
Xiaohong Liu ◽  
Chenglai Wu ◽  
Qiang Zhang ◽  
Chuanfeng Zhao ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Anthropogenic Emission ◽  
Country Level ◽  
Aerosol Properties

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).

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.

A Spatially and Temporally Disaggregated Anthropogenic Emission Inventory in the Southern Balkan Region

2007 ◽  
Vol 185 (1-4) ◽  
pp. 335-348 ◽  
Author(s):  
Anastasia Poupkou ◽  
Panagiotis Symeonidis ◽  
Ioannis Ziomas ◽  
Dimitrios Melas ◽  
Konstantinos Markakis
Keyword(s):  
Emission Inventory ◽  
Anthropogenic Emission ◽  
Balkan Region

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 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.

scholarly journals MIX: a mosaic Asian anthropogenic emission inventory for the MICS-Asia and the HTAP projects

2015 ◽  
Vol 15 (23) ◽  
pp. 34813-34869 ◽  
Author(s):  
M. Li ◽  
Q. Zhang ◽  
J. Kurokawa ◽  
J.-H. Woo ◽  
K. B. He ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Task Force ◽  
Anthropogenic Sources ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Comparison Study ◽  
China And India ◽  
Volatile Organic ◽  
Relative Change ◽  
Assignment Approach

Abstract. An anthropogenic emission inventory for Asia is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) projects by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 30 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best-available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. We estimate the total Asian emissions of ten species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.0 % for SO2, +19 % for NOx, +4 % for CO, +15 % for NMVOC, +2 % for NH3, −3 % for PM10, −2 % for PM2.5, +6 % for BC, +2 % for OC and +20 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

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