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

Authors :: Qu Z
Henze DK
Worden HM
Jiang Z
Gaubert B
Theys N
Wang W
Source :: Geophysical research letters [Geophys Res Lett] 2022 Jan 28; Vol. 49 (2), pp. e2021GL096009. Date of Electronic Publication: 2022 Jan 20.
Publication Year :: 2022
Abstract: 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 <subscript>2</subscript> , OMI SO <subscript>2</subscript> , and MOPITT CO observations to estimate NO <subscript> x </subscript> , SO <subscript>2</subscript> , and CO emissions in East Asia during 2005-2012. Posterior evaluations with surface measurements show reduced normalized mean bias (NMB) by 7% (NO <subscript>2</subscript> )-15% (SO <subscript>2</subscript> ) and normalized mean square error (NMSE) by 8% (SO <subscript>2</subscript> )-9% (NO <subscript>2</subscript> ) compared to a species-based inversion. This new inversion captures the peak years of Chinese SO <subscript>2</subscript> (2007) and NO <subscript> x </subscript> (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 <subscript> x </subscript> and SO <subscript>2</subscript> trends mostly to energy and CO trend to residential emissions.<br /> (© 2022. The Authors.)