Urban-rural patterns and driving factors of particulate matter pollution decrease in eastern China

Abstract. Understanding the urban-rural patterns and driving drivers behind the recent decrease in particulate matter (PM) pollution across eastern China is essential for assessing the efficacy of environmental policies and ensuring equitable health co-benefits. By employing an interpretable, end-to-end machine learning framework integrating satellite observations, meteorological factors, and auxiliary datasets, this study reveals changes in urban and rural PM pollution and the underlying drivers. During the period 2015–2023, the average decrease rates of PM10 and PM2.5 in eastern China were −4.02 ± 1.29 and −2.41 ± 0.91 µg m−3 yr−1, respectively. The rate of decrease in urban areas was higher than that in rural areas, which played a dominant role in PM reduction. Significant reductions in PM concentrations were observed in urban core areas, suburbs, towns and regions with high agricultural pressure. The interpretability analysis showed that temperature and interannual variability were the main drivers of PM pollution reduction. However, only interannual variability showed a significant decreasing trend in its effect on PM pollution, while other driving factors showed periodic variations. Furthermore, there were differences in the drivers of PM reduction between urban and rural areas, particularly with interannual variability in particular contributing to PM pollution reduction in urban areas, but having a lesser impact in most rural areas. This study reveals the urban-rural patterns of PM pollution reduction in eastern China, and highlights the need for differentiated air pollution control strategies in urban and rural areas.