Preprints
https://doi.org/10.5194/acp-2021-664
https://doi.org/10.5194/acp-2021-664

  20 Sep 2021

20 Sep 2021

Review status: this preprint is currently under review for the journal ACP.

The drivers and health risks of the unexpected surface ozone enhancements over the Sichuan basin, China in 2020

Youwen Sun1,2, Hao Yin1,2, Xiao Lu3, Justus Notholt4, Mathias Palm4, Cheng Liu2, Yuan Tian5, and Bo Zheng6 Youwen Sun et al.
  • 1Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
  • 2Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei, 230026, China
  • 3School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, 519082, China
  • 4University of Bremen, Institute of Environmental Physics, P. O. Box 330440, 28334 Bremen, Germany
  • 5Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
  • 6Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China

Abstract. After a continuous increase in surface ozone (O3) level from 2013 to 2019, the overall summertime O3 concentration across China showed a significant reduction in 2020. In contrast to this overall reduction in surface O3 across China, unexpected surface O3 enhancements of 10.2 ± 0.8 ppbv (23.4 %) were observed in May–June 2020 vs. 2019 over the Sichuan basin (SCB), China. In this study, we use high resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method and the exposure−response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements. We first use the XGBoost machine learning method to correct the GEOS-Chem model-to-measurement O3 discrepancy over the SCB. The relative contributions of meteorology and anthropogenic emissions changes to the unexpected surface O3 enhancements are then quantified with the combination of GEOS-Chem and XGBoost models. In order to assess the health risks caused by the unexpected O3 enhancements over the SCB, total premature death mortalities are estimated. The results show that changes in anthropogenic emissions caused 0.9 ± 0.1 ppbv of O3 reduction and changes in meteorology caused 11.1 ± 0.7 ppbv of O3 increase in May–June 2020 vs. 2019. The meteorology-induced surface O3 increase is mainly attributed to significant increases in temperature and downward potential vorticity, and decreases in precipitation, specific humidity and cloud fractions over the SCB and surrounding regions in May–June 2020 vs. 2019. These changes in meteorology combined with the complex basin effect enhance downward transport of O3 from upper troposphere, enhance biogenic emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx), speed up O3 chemical production, and inhabit the ventilation of O3 and its precursors, and therefore account for the surface O3 enhancements over the SCB. The total premature mortality due to the unexpected surface O3 enhancements over the SCB has increased by 89.8 % in May–June 2020 vs. 2019.

Youwen Sun et al.

Status: open (until 01 Nov 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'use of potential vorticity', Heini Wernli, 23 Sep 2021 reply
  • RC1: 'Comment on acp-2021-664', Anonymous Referee #1, 28 Sep 2021 reply
  • RC2: 'Comment on acp-2021-664', Anonymous Referee #2, 15 Oct 2021 reply

Youwen Sun et al.

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Short summary
This study uses high resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method and the exposure−response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. The unexpected O3 enhancements over the SCB were induced by meteorology and have caused dramatically high health risks.
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