Effects of Elevated Ozone Exposure on Regional Meteorology and Air Quality in China Through Ozone‐Vegetation Coupling

Abstract Ozone is a phytotoxic pollutant that could damage the vegetation growth and lead to complicated impacts on air quality through meteorological and biogeochemical feedbacks. This study implements a semi‐empirical parameterization regarding the impacts of ozone exposure on photosynthesis rate and stomatal resistance into the Noah‐Multi‐parameterization (Noah‐MP) dynamic vegetation module of Weather Research and Forecasting with Chemistry (WRF/Chem) model. The gaseous dry deposition and biogenic emission algorithms are also coupled with Noah‐MP to enable the ozone‐vegetation coupling. This model reproduces the near‐surface meteorology, air pollutants and vegetation physiology in China, with a spatial correlation coefficient more than 0.9 and normalized mean bias from −0.19 to 0.42. The optimized model also improves the simulations of vegetation physiology (e.g., a reduction of model error by 18%–32%) and ozone dry deposition velocity. The elevated ozone damages plant photosynthesis, and decreases the national gross primary productivity (−28.85%) and leaf area index (−17.41%). The plant transpiration and surface heat flux, as well as air temperature (e.g., up to +0.16°C in summer) and other associated meteorological variables are also altered, finally contributing to 0.49 μg m −3 increase of surface ozone. Otherwise, the suppressed vegetation LAI and biogenic emissions, as well as the lower dry deposition velocity in response to the ozone‐vegetation coupling contribute to the remaining ozone changes by −1.07 μg m −3 and 1.18 μg m −3 , jointly constituting the complicated ozone‐vegetation feedbacks on air quality. Our results highlight the necessity of including the ozone‐vegetation coupling in models for reliable prediction of regional climate and air quality.