Back to Search Start Over

Estimating ground-level PM2.5 in China using satellite remote sensing.

Authors :
Ma Z
Hu X
Huang L
Bi J
Liu Y
Source :
Environmental science & technology [Environ Sci Technol] 2014 Jul 01; Vol. 48 (13), pp. 7436-44. Date of Electronic Publication: 2014 Jun 13.
Publication Year :
2014

Abstract

Estimating ground-level PM2.5 from satellite-derived aerosol optical depth (AOD) using a spatial statistical model is a promising new method to evaluate the spatial and temporal characteristics of PM2.5 exposure in a large geographic region. However, studies outside North America have been limited due to the lack of ground PM2.5 measurements to calibrate the model. Taking advantage of the newly established national monitoring network, we developed a national-scale geographically weighted regression (GWR) model to estimate daily PM2.5 concentrations in China with fused satellite AOD as the primary predictor. The results showed that the meteorological and land use information can greatly improve model performance. The overall cross-validation (CV) R(2) is 0.64 and root mean squared prediction error (RMSE) is 32.98 μg/m(3). The mean prediction error (MPE) of the predicted annual PM2.5 is 8.28 μg/m(3). Our predicted annual PM2.5 concentrations indicated that over 96% of the Chinese population lives in areas that exceed the Chinese National Ambient Air Quality Standard (CNAAQS) Level 2 standard. Our results also confirmed satellite-derived AOD in conjunction with meteorological fields and land use information can be successfully applied to extend the ground PM2.5 monitoring network in China.

Details

Language :
English
ISSN :
1520-5851
Volume :
48
Issue :
13
Database :
MEDLINE
Journal :
Environmental science & technology
Publication Type :
Academic Journal
Accession number :
24901806
Full Text :
https://doi.org/10.1021/es5009399