Abstract
Despite the implementation of multiple nationwide air pollution control policies over the past decade, China continues to face significant public health challenges, and there remains a lack of systematic quantitative assessment of the health impacts resulting from emission changes. To evaluate the effectiveness of these policies, we developed a large-scale XGBoost-based framework to isolate PM2.5 and O3 concentrations attributable solely to emission-related changes by eliminating meteorological influences. We analyzed the trends of emission-related pollutant concentrations during two key policy phases: the Action Plan on Air Pollution Prevention and Control (2013-2017) and the Blue Sky Protection Campaign (2018-2023). Results revealed a substantial reduction in PM2.5 concentrations during 2013-2017, with eastern China experiencing an average annual decrease of 4.20 μg/m3 and the Beijing-Tianjin-Hebei region showing the most rapid decline at 5.55 μg/m3 per year. Nationally, the average annual reduction was 2.38 μg/m3. However, during 2018-2023, the rate of decline slowed, and central China emerged as a new PM2.5 pollution hotspot. Conversely, O3 concentrations increased significantly nationwide from 2013 to 2017. Although a decreasing trend in O3 has been observed since 2018, urban agglomerations experienced slower improvements than surrounding regions, suggesting continued concern over O3 pollution in densely populated areas. Health impact assessments revealed a dual trend. While PM2.5-attributable mortality declined significantly (e.g., by ∼17% in BTH and ∼31% in the Pearl River Delta), O3-attributable deaths rose sharply, with increases of 78% in BTH and 68% in the FWP. Although PM2.5 reductions still yield greater overall health benefits, the health burden of O3 is approaching that of PM2.5 in major city clusters, underscoring the urgent need for integrated, multi-pollutant control strategies.
| Original language | English |
|---|---|
| Article number | 122240 |
| Number of pages | 11 |
| Journal | Atmospheric Environment |
| Volume | 383 |
| Early online date | 20 Jul 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 20 Jul 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
User-Defined Keywords
- Machine learning
- O3
- PM2.5
- meteorological normalization
- Meteorological normalization
- PM
- O
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