Sector-Based Top-Down Estimates of NO , SO, 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, OMI SO, and MOPITT CO observations to estimate NO , SO, and CO emissions in East Asia during 2005-2012.

SO Emission Estimates Using OMI SO Retrievals for 2005-2017.

SO column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO emissions. SO column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes.

Hybrid Mass Balance/4D-Var Joint Inversion of NO and SO Emissions in East Asia.

Accurate estimates of NO and SO emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005-2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO and NO can provide more accurate constraints on emissions than single-species inversions.