Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data

[摘要] Ozone (O 3 ) is a secondary pollutant in the atmosphere formed byphotochemical reactions that endangers human health and ecosystems. O 3 has aggravated in Asia in recent decades and will vary in the future. Inthis study, to quantify the impacts of future climate change on O 3 pollution, near-surface O 3 concentrations over Asia in 2020–2100 areprojected using a machine learning (ML) method along with multi-source data.The ML model is trained with combined O 3 data from a globalatmospheric chemical transport model and real-time observations. The MLmodel is then used to estimate future O 3 with meteorological fieldsfrom multi-model simulations under various climate scenarios. Thenear-surface O 3 concentrations are projected to increase by 5 %–20 %over South China, Southeast Asia, and South India and less than 10 % overNorth China and the Gangetic Plains under the high-forcing scenarios in the lastdecade of 21st century, compared to the first decade of 2020–2100. TheO 3 increases are primarily owing to the favorable meteorologicalconditions for O 3 photochemical formation in most Asian regions. Wealso find that the summertime O 3 pollution over eastern China willexpand from North China to South China and extend into the cold season in awarmer future. Our results demonstrate the important role of a climate changepenalty on Asian O 3 in the future, which provides implications forenvironmental and climate strategies of adaptation and mitigation.

[学科分类] 医学（综合）