Sector-Based Top-Down Estimates of NO x , SO2, and CO Emissions in East Asia

Zhen Qu; Daven K Henze; Helen M Worden; Zhe Jiang; Benjamin Gaubert; Nicolas Theys; Wei Wang

doi:10.1029/2021GL096009

Sector-Based Top-Down Estimates of NO _x , SO₂, and CO Emissions in East Asia

Geophys Res Lett. 2022 Jan 28;49(2):e2021GL096009. doi: 10.1029/2021GL096009. Epub 2022 Jan 20.

Authors

Zhen Qu^{1

2}, Daven K Henze¹, Helen M Worden³, Zhe Jiang⁴, Benjamin Gaubert³, Nicolas Theys⁵, Wei Wang⁶

Affiliations

¹ Department of Mechanical Engineering University of Colorado Boulder Boulder CO USA.
² School of Engineering and Applied Science Harvard University Cambridge MA USA.
³ Atmospheric Chemistry Observations and Modeling National Center for Atmospheric Research Boulder CO USA.
⁴ School of Earth and Space Sciences University of Science and Technology of China Hefei China.
⁵ Belgian Institute for Space Aeronomy (BIRA-IASB) Brussels Belgium.
⁶ China National Environmental Monitoring Center Beijing China.

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 NO₂, OMI SO₂, and MOPITT CO observations to estimate NO _x , SO₂, and CO emissions in East Asia during 2005-2012. Posterior evaluations with surface measurements show reduced normalized mean bias (NMB) by 7% (NO₂)-15% (SO₂) and normalized mean square error (NMSE) by 8% (SO₂)-9% (NO₂) compared to a species-based inversion. This new inversion captures the peak years of Chinese SO₂ (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 SO₂ trends mostly to energy and CO trend to residential emissions.