Estimating ground-level PM10 in a Chinese city by combining satellite data, meteorological information and a land use regression model
2016
Meng, Xia | Fu, Qingyan | Ma, Zongwei | Chen, Li | Zou, Bin | Zhang, Yan | Xue, Wenbo | Wang, Jinnan | Wang, Dongfang | Kan, Haidong | Liu, Yang
Development of exposure assessment model is the key component for epidemiological studies concerning air pollution, but the evidence from China is limited. Therefore, a linear mixed effects (LME) model was established in this study in a Chinese metropolis by incorporating aerosol optical depth (AOD), meteorological information and the land use regression (LUR) model to predict ground PM10 levels on high spatiotemporal resolution. The cross validation (CV) R² and the RMSE of the LME model were 0.87 and 19.2 μg/m³, respectively. The relative prediction error (RPE) of daily and annual mean predicted PM10 concentrations were 19.1% and 7.5%, respectively. This study was the first attempt in China to estimate both short-term and long-term variation of PM10 levels with high spatial resolution in a Chinese metropolis with the LME model. The results suggested that the LME model could provide exposure assessment for short-term and long-term epidemiological studies in China.
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