Estimating Ground-Level PM 2.5 in China Using Satellite Remote Sensing
State Key Laboratory of Pollution Control and Resource Reuse · Emory University · +1 more institution
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…
Citation impact
- FWCI
- 22.93
- Percentile
- 100%
- References
- 42
Authors
5- ZMZongwei MaCorresponding
State Key Laboratory of Pollution Control and Resource Reuse, Emory University, Nanjing University
- XHXuefei Hu
Emory University
- LHLei Huang
Nanjing University, State Key Laboratory of Pollution Control and Resource Reuse
- JBJun Bi
State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University
- YLYang Liu
Emory University
Topics & keywords
- Environmental science
- Satellite
- Mean squared error
- Meteorology
- Remote sensing
- Scale (ratio)
- Geographically Weighted Regression
- Geography