Abstract

In recent years, with the significant decline in fine particulate matter (PM2.5) concentrations, ozone (O3) has emerged as a major composite air pollutant during the warm season in China, attracting increasing attention due to its associated health burden and economic costs. This study focuses on Tianjin, using ozone monitoring data from 2017 to 2023 combined with health statistics to assess the health impacts and economic losses attributable to ozone pollution. First, ozone exposure indicators and compliance criteria were constructed based on national air quality standards, and the interannual variation and spatial differences of O3 levels were analyzed at both citywide and district scales. Second, multiple machine learning classification models, including logistic regression, decision tree, k-nearest neighbors, and gradient boosting, were developed using ozone and meteorological variables to predict the occurrence risks of five diseases: cardiovascular diseases, respiratory diseases, hand-foot-and-mouth disease (HFMD), influenza, and dengue fever. Finally, excess cases were estimated using health impact functions, and the associated economic losses were quantified by combining the value of a statistical life (VSL) with cost-of-illness and willingness-to-pay (WTP) approaches. The results showed that the annual evaluation value of ozone in Tianjin, defined as the 90th percentile of the daily maximum 8 h average O3 concentration, exhibited a pattern of initially increasing, then decreasing, and subsequently rebounding. It peaked at 201 µg/m3 in 2018, declined to a minimum of 164 µg/m3 in 2021, and rebounded to 188 µg/m3 in 2023. Machine-learning results indicated that the logistic regression model showed relatively stable overall performance across predictions of different diseases, while the gradient boosting tree model also achieved high accuracy in predicting certain infectious diseases. Overall, ozone pollution exhibits significant heterogeneous effects across different disease types, and the associated health-related economic losses show stage-wise fluctuations in response to pollution levels. Based on these findings, it is recommended to implement refined control measures during periods of high ozone exceedance and in key regions, while strengthening protection for vulnerable populations such as the elderly, children, and patients with respiratory diseases, in order to achieve synergistic improvements in air quality management and public health outcomes.

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