Abstract
A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.
Highlights
In recent decades, Asia has become increasingly populous, and its economies have grown rapidly, to the extent that East Asia has become the largest emission region in the world due to this large population and the increased energy use caused by its economic growth
We found that the ECLIPSE model produced values that were the closest to CREATE; this was not unexpected, as both Sustaininabvielintyto2r0i2e0s, 1w2,e7r9e30based on the GAINS model, had the same source categories and used the same19 of 26 emissions factors, with the exceptions of China, N
We found that CREATE NOx emission estimates were 11–37% lower than those from the other inventories, exhibiting the lowest values
Summary
Asia has become increasingly populous, and its economies have grown rapidly, to the extent that East Asia has become the largest emission region in the world due to this large population and the increased energy use caused by its economic growth. From the perspective of the global atmospheric environment, Asia is a critical source of air pollution, and this has become a more serious issue here than in other regions—and lately has begun to receive international attention [1,2,3] This problem can be resolved through long-term joint efforts and adoption of best practices, and this approach needs to be supported by objective and scientific data. Systematic tracking of air pollution sources and emissions data organization forms the most effective basis for understanding air pollution processes and deriving policy solutions. This includes collating pollutant emissions by region, sector, and fuel-type, within a comprehensive anthropogenic emissions inventory. The second method is advantageous because it provides better total emissions estimates for developed countries/regions; it can be limited by the amount of fundamental information needed to estimate emissions
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