Elucidating contributions of meteorology and emissions to O 3 variations in coastal city of China during 2019-2022: Insights from VOCs sources

Elucidating the meteorology and emissions contribution of O variation is a crucial issue for implementing effective measures for O pollution control. We quantified the impacts of meteorology and emissions on O variability during spring and autumn from 2019 to 2022, using multi-year continuous observations. A machine learning (ML)-based de-weathering model revealed that meteorology accounted for a greater proportion of O variability (71.9% in spring and 57.4% in autumn) compared to emissions (28.1% and 42.6%, respectively). In spring, relative humidity (RH, 22.8%) and wind speed (WS, 13.7%) were key drivers, contributing to O decreases and increases, respectively. During autumn, temperature (T, 10.8%) and surface solar radiation (SSR, 9.45%) were the dominant factors, both contributing to O production. We assessed the O formation sensitivity based on VOCs emissions sources and evaluated the importance of emission by O production rate (P(O )) calculated from box model and the positive matrix factorization (PMF) model. Vehicle emissions and solvent use were identified as the major contributors to O formation from 2019 to 2022 and reducing them would be beneficial for O pollution control. This study elucidates the relative roles of meteorological conditions and anthropogenic emissions in O variability and key insights for formulating future O control policies.