# Identification and Time Series Analysis of PM2.5 and O3 Associated Health Risk Prevention and Control Areas

## TL;DR

This study introduces a new method to identify air pollution control areas based on health risks, showing these areas have higher risk populations and more equitable risk distribution than government-defined regions.

## Contribution

A novel method for defining air pollution control areas using health risk metrics instead of pollutant concentrations.

## Key findings

- Prevention and control areas showed higher health risk populations for PM2.5 and O3 compared to government-defined key areas.
- Gini coefficients in prevention and control areas were lower, indicating more equitable health risk distribution.
- The method provides a more objective and health-focused approach to pollution zoning.

## Abstract

Air pollution of PM2.5 and O3 is a global health concern. Traditional approaches for identifying air pollution control areas mainly relied on pollutant concentrations, neglecting population distribution and exposure. This study proposes a method to divide these areas from a health risk perspective, comparing their objectivity and rationality with the government-defined key regions. The results show that for PM2.5, the health risk population and average risk rates in the prevention and control areas were 0.993 million (0.1286%), 1.030 million (0.1283%), and 1.023 million (0.1202%) in 2010, 2015, and 2020, significantly higher than in the key areas: 0.778 million (0.1252%), 0.834 million (0.1278%), and 0.825 million (0.1212%). Similarly, for O3, the figures in the prevention and control areas were 0.096 million (0.01228%), 0.095 million (0.01243%), and 0.110 million (0.01316%), also higher than in the key areas: 0.0757 million (0.01218%), 0.078 million (0.01189%), and 0.090 million (0.01315%). Additionally, the Gini coefficients for PM2.5, O3, and overall health risks in the prevention and control areas were lower (0.182, 0.203, 0.284) compared to those in the key areas (0.207, 0.216, 0.292). This study provides a method for defining air pollution control regions based on health risks, offering significant insights for pollution zoning and prevention strategies