Attribution of Air Quality Benefits to Clean Winter Heating Polices in China: Combining Machine Learning with Causal Inference

Heating is a major source of air pollution. To improve air quality, a range of clean heating polices were implemented in China over the past decade. Here, we evaluated the impacts of winter heating and clean heating polices on air quality in China using a novel, observation-based causal inference approach. During 2015-2021, winter heating causally increased annual PM2.5, daily maximum 8-h average O3, and SO2 by 4.6, 2.5, and 2.3 mu g m-3, respectively. From 2015 to 2021, the impacts of winter heating on PM2.5 in Beijing and surrounding cities (i.e., 2 + 26 cities) decreased by 5.9 mu g m-3 (41.3%), whereas that in other northern cities only decreased by 1.2 mu g m-3 (12.9%). This demonstrates the effectiveness of stricter clean heating policies on PM2.5 in 2 + 26 cities. Overall, clean heating policies caused the annual PM2.5 in mainland China to reduce by 1.9 mu g m-3 from 2015 to 2021, potentially avoiding 23,556 premature deaths in 2021.

Automated summary

Heating, particularly during winter, has contributed significantly to air pollution in China. However, the implementation of clean heating policies over the past decade has led to improvements in air quality. A study using observation-based causal inference found that winter heating has caused an increase in PM2.5, O3, and SO2 levels. The effectiveness of stricter clean heating policies on reducing PM2.5 was observed in Beijing and surrounding cities.