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This article presents an improved machine learning approach for predicting near-surface ozone concentrations in mainland China from 2010-2021. The hourly concentrations of near-surface ozone at state-operated observation stations (mostly located in urban areas) were obtained from the Ministry of Ecology and Environment website, and data from district- and county-level control stations (located in rural areas) were also collected for 2019. A total of 51 variables were selected as model predictors, including parameters from meteorology, chemistry, social and economic conditions, and geography.
