Abstract

Abstract. Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from space provide valuable information to estimate emissions of nitrogen oxides (NOx) inversely. Accurate emission attribution to individual sources, important both for understanding the global biogeochemical cycling of nitrogen and for emission control, remains difficult. This study presents a regression-based multi-step inversion approach to estimate emissions of NOx from anthropogenic, lightning and soil sources individually for 2006 over East China on a 0.25° long × 0.25° lat grid, employing the DOMINO product version 2 retrieved from the Ozone Monitoring Instrument. The inversion is done gridbox by gridbox to derive the respective emissions, taking advantage of differences in seasonality between anthropogenic and natural sources. Lightning and soil emissions are combined together for any given gridbox due to their similar seasonality; and their different spatial distributions are used implicitly for source separation to some extent. The nested GEOS-Chem model for East Asia is used to simulate the seasonal variations of different emission sources and impacts on VCDs of NO2 for the inversion purpose. Sensitivity tests are conducted to evaluate key assumptions embedded in the inversion process. The inverse estimate suggests annual budgets of about 7.1 TgN (±39%), 0.21 TgN (±61%), and 0.38 TgN (±65%) for the a posteriori anthropogenic, lightning and soil emissions, respectively, about 18–23% higher than the respective a priori values. The enhancements in anthropogenic emissions are largest in cities and areas with extensive use of coal, particularly in the north in winter, as evident on the high-resolution grid. Derived soil emissions are consistent with recent bottom-up estimates. They are less than 6% of anthropogenic emissions annually, increasing to about 13% for July. Derived lightning emissions are about 3% of anthropogenic emissions annually and about 10% in July. Overall, anthropogenic emissions are found to be the dominant source of NOx over East China with important implications for nitrogen control.

Highlights

  • Nitrogen oxides (NOx ≡ nitric oxide (NO) + NO2) are important constituents in the troposphere affecting the formation of ozone and aerosols with significant consequences on air quality, climate forcing and acid deposition

  • This study presents a new method to inversely derive emissions of nitrogen oxides (NOx) for 2006 over East China (101.25◦ E– 126.25◦ E, 19◦–46◦ N; see Fig. 1) from anthropogenic, lightning and soil sources individually based on satellite retrievals of NO2 columns and simulations of the global chemical transport model (CTM) GEOS-Chem

  • A regression-based multi-step inversion approach is proposed to estimate emissions of NOx from anthropogenic, lightning and soil sources for 2006 over East China on a 0.25◦ long × 0.25◦ lat grid. It exploits information on vertical column densities (VCDs) of tropospheric NO2 retrieved from the Ozone Monitoring Instrument (OMI) instrument by KNMI

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Summary

Introduction

Nitrogen oxides (NOx ≡ NO + NO2) are important constituents in the troposphere affecting the formation of ozone and aerosols with significant consequences on air quality, climate forcing and acid deposition. Wang et al (2007) suggested that soil emissions over East China amounted to 0.85 TgN per year for 1997–2000, differing significantly from other inverse estimates This study presents a new method to inversely derive emissions of NOx for 2006 over East China (101.25◦ E– 126.25◦ E, 19◦–46◦ N; see Fig. 1) from anthropogenic, lightning and soil sources individually based on satellite retrievals of NO2 columns and simulations of the global chemical transport model (CTM) GEOS-Chem.

VCDs of NO2 retrieved from OMI
Descriptions of model simulations
Total errors in a priori emissions
Comparison between simulated and retrieved VCDs of NO2
Method
A weighted multivariate linear regression analysis for each gridbox
A multi-step inversion process beyond the regression analysis
VCDs of NO2 predicted from the inversion process
Top-down emissions
Improved GEOS-Chem simulations using the top-down emissions
Sensitivity of emission inversion to embedded assumptions
Total errors in the top-down emission budgets over East China
A posteriori emissions
Comparison with previous estimates
Comparison with previous satellite-derived soil emission estimates
Comparison with recent bottom-up estimates for soil emissions
Findings
Conclusions
Full Text
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