Abstract. Following a continuous increase in the surface ozone (O3) level from 2013 to
2019, the overall summertime O3 concentrations 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 (relative to 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 due to the unexpected
surface O3 enhancements. We first use the XGBoost machine learning
method to correct the GEOS-Chem model–measurement O3 discrepancy
over the SCB. The relative contributions of meteorology and anthropogenic
emission changes to the unexpected surface O3 enhancements are then
quantified with a 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 mortalities are estimated. The results show
that changes in anthropogenic emissions caused a 0.9 ± 0.1 ppbv
O3 reduction, whereas changes in meteorology caused an 11.1 ± 0.7 ppbv
O3 increase in May–June 2020 relative to 2019. The meteorology-induced surface
O3 increase is mainly attributed to an increase in temperature and decreases in precipitation, specific humidity, and cloud fractions over
the SCB and surrounding regions in May–June 2020 relative to 2019. These changes in
meteorology combined with the complex basin effect enhance biogenic
emissions of volatile organic compounds (VOCs) and nitrogen oxides
(NOx), speed up O3 chemical production, and inhibit the
ventilation of O3 and its precursors; therefore, they 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 relative to 2019.