Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015–2021

Abstract

Surface ozone (O3) concentrations in China have increased largely in the past decade. An accurate understanding of O3 pollution evolution is critical for making effective regulatory policies. Here we integrate data- and process-based models to explore the drivers of the observed summertime surface O3 change in the North China Plain (NCP) over 2015–2021. The data-based model by the deep learning (DL) suggests the reverse of meteorological contributions to the observed O3 change, i.e., 0.14 ppb/y in 2015–2019 and −1.74 ppb/y in 2019–2021. This is mainly resulted from the reversed changes in meteorological variables in surface air temperature and relative humidity. The simulations from a global chemical transport model, GEOS-Chem, also support those results, i.e., the meteorological contribution to O3 changes are 0.26 ppb/y in 2015–2019 and −0.74 ppb/y in 2019–2021. Furthermore, our analysis exhibits possible weakened anthropogenic contributions to surface O3 rise, for example, 1.53 and 0.54 ppb/y by DL in 2015–2019 and 2019–2021, respectively. Similarly, GEOS-Chem simulations suggest an accelerated decrease in surface O3 concentrations driven by the decline in nitrogen dioxide (NO2) concentrations, i.e., approximately 0.4 and 1.2 ppb in 2015–2019 and 2019–2021, respectively. The combined effects of meteorological and anthropogenic contributions led to a significant decrease in surface O3 concentrations by −1.20 ppb/y in 2019–2021. The findings in this work offer valuable insights to mitigate O3 pollution in China.