Particulate Matter Pollution and Population Exposure Assessment over Mainland China in 2010 with Remote Sensing
AbstractThe public is increasingly concerned about particulate matter pollution caused by respirable suspended particles (PM10) and fine particles (PM2.5). In this paper, PM10 and PM2.5 concentration are estimated with remote sensing and individual air quality indexes of PM10 and PM2.5 (IPM10 and IPM2.5) over mainland China in 2010 are calculated. We find that China suffered more serious PM2.5 than PM10 pollution in 2010, and they presented a spatial differentiation. Consequently, a particulate-based air quality index (PAQI) based on a weighting method is proposed to provide a more objective assessment of the particulate pollution. The study demonstrates that, in 2010, most of mainland China faced a lightly polluted situation in PAQI case; there were three areas obviously under moderate pollution (Hubei, Sichuan-Chongqing border region and Ningxia-Inner Mongolia border region). Simultaneously, two indicators are calculated with the combination of population density gridded data to reveal Chinese population exposure to PM2.5. Comparing per capita PM2.5 concentration with population-weighted PM2.5 concentration, the former shows that the high-level regions are distributed in Guangdong, Shanghai, and Tianjin, while the latter are in Hebei, Chongqing, and Shandong. By comparison, the results demonstrate that population-weighted PM2.5 concentration is more in line with the actual situation.
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Yao, L.; Lu, N. Particulate Matter Pollution and Population Exposure Assessment over Mainland China in 2010 with Remote Sensing. Int. J. Environ. Res. Public Health 2014, 11, 5241-5250.
Yao L, Lu N. Particulate Matter Pollution and Population Exposure Assessment over Mainland China in 2010 with Remote Sensing. International Journal of Environmental Research and Public Health. 2014; 11(5):5241-5250.Chicago/Turabian Style
Yao, Ling; Lu, Ning. 2014. "Particulate Matter Pollution and Population Exposure Assessment over Mainland China in 2010 with Remote Sensing." Int. J. Environ. Res. Public Health 11, no. 5: 5241-5250.