Estimating morning and evening commute period O concentration in Taiwan using a fine spatial-temporal resolution ensemble mixed spatial model with Geo-AI technology.

Elevated levels of ground-level ozone (O) can have harmful effects on health. While previous studies have focused mainly on daily averages and daytime patterns, it's crucial to consider the effects of air pollution during daily commutes, as this can significantly contribute to overall exposure. This study is also the first to employ an ensemble mixed spatial model (EMSM) that integrates multiple machine learning algorithms and predictor variables selected using Shapley Additive exExplanations (SHAP) values to predict spatial-temporal fluctuations in O concentrations across the entire island of Taiwan.