Global High-Resolution Emission Inventories from Combustion Sources

A series efforts have been made to reduce uncertainty of emission inventories from combustion sources. The inventories developed are highly resolved spatially (0.1 degree), temporally (monthly or daily), and sectorically (over 60 combustion sources). Sub-national, instead of national fuel data are used to reduce spatial bias due to uneven distribution of per person energy consumption within large countries. Space-for-time substitution method was developed to model the dependence of residential energy consumptions on a series of meteorological and socioeconomic conditions. The regression models were used to project temporal variation of energy consumption, subsequently emissions of greenhouse gases and air pollutants. The models can also be used to downscale spatial distribution of residential emissions. By using this approach, global emission inventories of black carbon, polycyclic aromatic hydrocarbons, mercury, TSP, PM10, and PM2.5 have been established. The inventories were used to potential health impact assessment, atmospheric transport and long-range transport modeling, as well as exposure and health impact modeling.