Quantitative Assessment of Relationship between Population Exposure to PM 2.5 and Socio-Economic Factors at Multiple Spatial Scales over Mainland China.

Analyzing the association between fine particulate matter (PM _2.5 ) pollution and socio-economic factors has become a major concern in public health. Since traditional analysis methods (such as correlation analysis and geographically weighted regression) cannot provide a full assessment of this relationship, the quantile regression method was applied to overcome such a limitation at different spatial scales in this study. The results indicated that merely 3% of the population and 2% of the Gross Domestic Product (GDP) occurred under an annually mean value of 35 μg/m³ in mainland China, and the highest population exposure to PM _2.5 was located in a lesser-known city named Dazhou in 2014. The analysis results at three spatial scales (grid-level, county-level, and city-level) demonstrated that the grid-level was the optimal spatial scale for analysis of socio-economic effects on exposure due to its tiny uncertainty, and the population exposure to PM _2.5 was positively related to GDP. An apparent upward trend of population exposure to PM _2.5 emerged at the 80th percentile GDP. For a 10 thousand yuan rise in GDP, population exposure to PM _2.5 increases by 1.05 person/km² at the 80th percentile, and 1.88 person/km ² at the 95th percentile, respectively.
Competing Interests: The authors declare no conflict of interest.