Abstract

Abstract. Satellite observations of the tropospheric NO2 vertical column density (VCD) are closely correlated to, and thus can be used to estimate, surface NOx emissions. In this study, the NO2 VCD simulated by a regional chemical transport model with emissions data from the updated Regional Emission inventory in ASia (REAS) version 2.1 were validated through comparison with multisatellite observations during the period 2000–2010. Rapid growth in NO2 VCD (~11% year−1) driven by the expansion of anthropogenic NOx emissions was identified above the central eastern China (CEC) region, except for the period during the economic downturn. In contrast, slightly decreasing trends (~2% year−1) were identified above Japan accompanied by a decline in anthropogenic emissions. To systematically compare the modeled NO2 VCD, we estimated sampling bias and the effect of applying the averaging kernel information, with particular focus on the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. Using the updated REAS, the modeled NO2 VCD reasonably reproduced annual trends observed by multisatellites, suggesting that the rate of increase of NOx emissions estimated by the updated REAS inventory would be robust. Province-scale revision of emissions above CEC is needed to further refine emission inventories. Based on the close linear relationship between modeled and observed NO2 VCD and anthropogenic NOx emissions, NOx emissions in 2009 and 2010, which were not covered by the updated REAS inventory, were estimated. NOx emissions from anthropogenic sources in China in 2009 and 2010 were determined to be 26.4 and 28.5 Tg year−1, respectively, indicating that NOx emissions increased more than twofold between 2000 and 2010. This increase reflected the strong growth of anthropogenic emissions in China following the rapid recovery from the economic downturn from late 2008 until mid-2009. Our method consists of simple estimations from satellite observations and provides results that are consistent with the most recent inventory of emissions data for China.

Highlights

  • Nitrogen oxides (NOx = NO + NO2) emitted from anthropogenic sources and natural sources play key roles in tropospheric chemistry, with important implications for air quality and climate change

  • This study investigated tropospheric NO2 vertical column density (VCD) over East Asia from 2000 to 2010 based on a combined analysis of CMAQ model simulations with an updated Regional Emission inventory in ASia (REAS) emission inventory and multisatellite observations (GOME, SCIAMACHY, Global Ozone Monitoring Experiment (GOME)-2, and Ozone Monitoring Instrument (OMI))

  • Rapid growth (∼ 11 % year−1) in tropospheric NO2 VCD along with expanding anthropogenic emissions was identified above the central eastern China (CEC) region in both model results and satellite observations

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Summary

Introduction

A systematic analysis of NO2 VCD measured by GOME and simulated by a regional chemical transport model with anthropogenic emissions data from the Regional Emission inventory in ASia (REAS) version 1.1 (Ohara et al, 2007) revealed that a bottom-up emission inventory underestimates the rapid growth in NOx emissions from China, especially from 1998 to 2000 (Uno et al, 2007). Tropospheric NO2 VCD over East Asia was simulated using a regional chemical transport model with the updated REAS inventory version 2.1, and observations by four satellites (GOME, SCIAMACHY, GOME-2, and OMI) were combined and analyzed. On the basis of the clear linear relationships between modeled and observed NO2 VCD and anthropogenic NOx emissions, simplified inverse estimations for 2009 and 2010, which were not covered by the updated REAS inventory, were proposed and compared with the latest emission inventories in China. The inverse estimation approach provides necessary information about the recent status of emissions over East Asia

Model description
Satellite observation data
Tropospheric NO2 column trends
Inverse estimation of anthropogenic NOx emissions
Findings
Conclusions
Full Text
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