Sector-Based Top-Down Estimates of NO x , SO 2 , and CO Emissions in East Asia.

Top-down estimates using satellite data provide important information on the sources of air pollutants. We develop a sector-based 4D-Var framework based on the GEOS-Chem adjoint model to address the impacts of co-emissions and chemical interactions on top-down emission estimates. We apply OMI NO 2 , OMI SO 2 , and MOPITT CO observations to estimate NO x , SO 2 , and CO emissions in East Asia during 2005-2012. Posterior evaluations with surface measurements show reduced normalized mean bias (NMB) by 7% (NO 2 )-15% (SO 2 ) and normalized mean square error (NMSE) by 8% (SO 2 )-9% (NO 2 ) compared to a species-based inversion. This new inversion captures the peak years of Chinese SO 2 (2007) and NO x (2011) emissions and attributes their drivers to industry and energy activities. The CO peak in 2007 in China is driven by residential and industry emissions. In India, the inversion attributes NO x and SO 2 trends mostly to energy and CO trend to residential emissions.