Long-term PM_2.5 pollution over China: Identification of PM_2.5 pollution hotspots and source contributions

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Public Health

Background:

• Fine particulate matter (PM2.5) poses a significant air quality challenge in China.
• Limited ground-based monitoring hinders long-term air pollution impact assessments.

Purpose of the Study:

• To develop and validate a long-term (2001-2020) PM2.5 dataset for China.
• To identify PM2.5 pollution hotspots and analyze trends and sources across China.

Main Methods:

• Utilized Geographically Weighted Regression (GWR) with updated global estimates (V5. GL.02) for monthly PM2.5.
• Validated GWR data against ground-based measurements (2014-2020) achieving high correlation (r=0.95).
• Employed the potential source contribution function (PSCF) to identify pollution sources.

Main Results:

• Identified major PM2.5 hotspots in central China, North China Plain, northwest, and Sichuan Basin.
• Winter pollution was most severe, with PM2.5 levels significantly exceeding WHO and Chinese air quality standards.
• PM2.5 concentrations increased from 2001-2012 and decreased significantly from 2013-2020 due to control policies.

Conclusions:

• China's air quality is primarily influenced by local PM2.5 emissions.
• Air pollution control policies have led to substantial PM2.5 reductions in recent years.
• The validated long-term PM2.5 dataset provides a valuable resource for future air quality research.