Estimating spatial variability of ground-level PM2.5 based on a satellite-derived aerosol optical depth product: Fuzhou, China
Estimating spatial variability of ground-level PM2.5 based on a satellite-derived aerosol optical depth product: Fuzhou, China
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DOI：
10.1016/j.apr.2018.05.007
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发表时间：
2018-11
影响因子：
4.5
通讯作者：
Lijuan Yang;Hanqiu Xu;Zhifan Jin
中科院分区：
文献类型：
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作者：
Lijuan Yang;Hanqiu Xu;Zhifan Jin
估算城市地区PM2.5暴露量对人类健康具有重要意义。卫星遥感为PM2.5浓度的空间复盖率反演提供了有效手段。利用福州市政府2014年建立的监测网络，建立了一个线性混合效应模型，将来自MODIS的气溶胶光学厚度（AOD）测量值（空间分辨率：3 km）和来自GEOS-FP气象场的气象数据作为预测因子，对福州市地面PM2. 5浓度进行了逐日估算。采用10倍交叉验证方法来检查混合效应模型的性能。交叉验证得出混合效应模型的aR 2值为0.72，均方根误差值为9.2 μg/m3。混合效应模型估算的PM2. 5月/季平均值与现场实测值具有较高的相关性。结果还揭示了研究区域PM2.5分布的空间差异，即，城市中心的浓度较高，郊区和农村地区的浓度较低。结果表明，利用MODIS 3 km气溶胶光学厚度和气象资料建立的混合效应模型可以有效地估算福州地区PM2. 5浓度。
Estimating exposure to PM2.5within urban areas has important implications for human health. Satellite remote sensing provides an effective means to retrieve spatial coverage of PM2.5concentrations. Using the monitoring network established by the local government in 2014, this study developed a linear mixed effects model that integrates aerosol optical depth (AOD) measurements (spatial resolution: 3 km) from MODIS and meteorological data from GEOS-FP meteorological fields as predictors to derive daily estimations of ground-level PM2.5concentrations in Fuzhou (SE China). A 10-fold cross validation method was employed to examine the performance of the mixed effects model. The cross validation yielded aR2value of 0.72, and a root mean square error value of 9.2 μg/m3for the mixed effects model. Furthermore, the monthly/seasonal average PM2.5estimated by the mixed effects model was highly correlated with those of in situ measurements. The results also revealed the spatial differences in the PM2.5distribution across the study area, i.e., higher concentrations in the urban center and lower values in suburban to rural areas. The results suggest that the mixed effects model using MODIS 3 km AOD together with meteorological data could be effective for the estimation of PM2.5concentrations in the Fuzhou area.