Assessment of PM_2.5-related health effects: A comparative study using multiple methods and multi-source data in China

Area of Science:

• Environmental Health
• Epidemiology
• Public Health Policy

Background:

• Particulate matter (PM2.5) pollution poses a severe threat to public health in China, leading to substantial mortality and economic burdens.
• Accurate spatial assessment of PM2.5-related losses is critical for effective air pollution control strategies.

Purpose of the Study:

• To assess the health effects and economic costs associated with PM2.5 exposure across 338 Chinese cities.
• To identify priority regions for PM2.5 pollution control interventions.

Main Methods:

• Utilized online monitoring data and the PM2.5 Hindcast Database (PHD) for PM2.5 exposure assessment.
• Applied the integrated exposure risk function and non-linear power law (NLP) function to estimate health outcomes.
• Validated data sources and employed Z statistics for accuracy assessment.

Main Results:

• PM2.5 exposure was linked to significant national-level deaths from stroke, ischemic heart disease, COPD, and lung cancer.
• Estimated national economic cost of PM2.5 pollution in 2016 was approximately US$80.25 billion.
• Monitoring data and PHD showed no significant difference (p=0.66), confirming data reliability.

Conclusions:

• The NLP function and monitoring data provide accurate assessments of PM2.5-related health effects.
• Beijing, Chongqing, and Tianjin are identified as priority areas for PM2.5 control to achieve substantial health benefits.
• Findings support improved accuracy in PM2.5 health impact assessments in China.