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Int. J. Environ. Res. Public Health 2016, 13(2), 180; doi:10.3390/ijerph13020180

Comparison of Four Ground-Level PM2.5 Estimation Models Using PARASOL Aerosol Optical Depth Data from China

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
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Author to whom correspondence should be addressed.
Academic Editor: Kim Natasha Dirks
Received: 9 December 2015 / Revised: 19 January 2016 / Accepted: 25 January 2016 / Published: 30 January 2016
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Abstract

Satellite remote sensing is of considerable importance for estimating ground-level PM2.5 concentrations to support environmental agencies monitoring air quality. However, most current studies have focused mainly on the application of MODIS aerosol optical depth (AOD) to predict PM2.5 concentrations, while PARASOL AOD, which is sensitive to fine-mode aerosols over land surfaces, has received little attention. In this study, we compared a linear regression model, a quadratic regression model, a power regression model and a logarithmic regression model, which were developed using PARASOL level 2 AOD collected in China from 18 January 2013 to 10 October 2013. We obtained R (correlation coefficient) values of 0.64, 0.63, 0.62, and 0.57 for the four models when they were cross validated with the observed values. Furthermore, after all the data were classified into six levels according to the Air Quality Index (AQI), a low level of statistical significance between the four empirical models was found when the ground-level PM2.5 concentrations were greater than 75 μg/m3. The maximum R value was 0.44 (for the logarithmic regression model and the power model), and the minimum R value was 0.28 (for the logarithmic regression model and the power model) when the PM2.5 concentrations were less than 75 μg/m3. We also discussed uncertainty sources and possible improvements. View Full-Text
Keywords: PM2.5 concentrations; fine-mode aerosol; polarized remote sensing; air quality monitoring; empirical models PM2.5 concentrations; fine-mode aerosol; polarized remote sensing; air quality monitoring; empirical models
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Guo, H.; Cheng, T.; Gu, X.; Chen, H.; Wang, Y.; Zheng, F.; Xiang, K. Comparison of Four Ground-Level PM2.5 Estimation Models Using PARASOL Aerosol Optical Depth Data from China. Int. J. Environ. Res. Public Health 2016, 13, 180.

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