Real-Time Estimation of Satellite-Derived PM 2.5 Based on a Semi-Physical Geographically Weighted Regression Model

Tianhao Zhang, Gang Liu, Zhongmin Zhu, Wei Gong, Yuxi Ji and Yusi Huang
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Tianhao Zhang: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Gang Liu: Shanghai Institute of Satellite Engineering, Shanghai 201100, China
Zhongmin Zhu: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Wei Gong: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Yuxi Ji: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Yusi Huang: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

IJERPH, 2016, vol. 13, issue 10, 1-13

Abstract: The real-time estimation of ambient particulate matter with diameter no greater than 2.5 ?m (PM 2.5 ) is currently quite limited in China. A semi-physical geographically weighted regression (GWR) model was adopted to estimate PM 2.5 mass concentrations at national scale using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth product fused by the Dark Target (DT) and Deep Blue (DB) algorithms, combined with meteorological parameters. The fitting results could explain over 80% of the variability in the corresponding PM 2.5 mass concentrations, and the estimation tends to overestimate when measurement is low and tends to underestimate when measurement is high. Based on World Health Organization standards, results indicate that most regions in China suffered severe PM 2.5 pollution during winter. Seasonal average mass concentrations of PM 2.5 predicted by the model indicate that residential regions, namely Jing-Jin-Ji Region and Central China, were faced with challenge from fine particles. Moreover, estimation deviation caused primarily by the spatially uneven distribution of monitoring sites and the changes of elevation in a relatively small region has been discussed. In summary, real-time PM 2.5 was estimated effectively by the satellite-based semi-physical GWR model, and the results could provide reasonable references for assessing health impacts and offer guidance on air quality management in China.

Keywords: real-time estimation; national-scale PM 2.5; aerosol optical depth; fusion by DT and DB; semi-physical geographically weighted regression (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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