Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area:: A comparison between MISR and MODIS
Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area:: A comparison between MISR and MODIS
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DOI：
10.1016/j.rse.2006.05.022
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发表时间：
2007-03-15
影响因子：
13.5
通讯作者：
Koutrakis, Petros
中科院分区：
文献类型：
--
作者：
Liu, Yang;Franklin, Meredith;Koutrakis, Petros
利用两种一般线性回归模型，比较了多角度成像光谱仪（MISR）和中分辨率成像光谱仪（MODIS）反演的气溶胶光学厚度（AOT）对密苏里州圣路易斯市及其周边地区地面PM2.5浓度的预测能力。这些模型包括从美国国家海洋和大气管理局（NOAA）的快速更新周期（RUC20）模型获得的气象参数作为协变量。MISR和MODIS AOT值都是PM2.5浓度的极显著预测因子。MISR和MODIS模式对地面PM2.5浓度的总体可预测性具有可比性。MISR模型对PM2.5浓度变异性的解释百分比（62%）略高于MODIS模型（51%），因此更适合。在整个数据范围内，MISR模型对PM2.5浓度的低估约为12%，而MODIS模型对PM2.5浓度的低估约为18%。这种低估主要发生在PM2.5浓度较高的两个模型中。两种模式的回归系数具有较强的可比性，表明MISR的预测精度较高，MODIS的空间覆盖范围较好，MISR与MODIS的AOT数据组合可能受益。MISR和MODIS气溶胶产品中新开发的粒径/形状指标并没有显著提高我们使用AOT测量预测PM2.5浓度的能力。最后，在当前的研究区域，使用每小时PM2.5浓度似乎并没有改善其与AOT的关系。(c) 2006爱思唯尔公司版权所有。
Using two general linear regression models, we compared the ability of the aerosol optical thickness (AOT) retrieved by the Multiangle Imaging SpectroRadiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) to predict ground-level PM2.5 concentrations in St. Louis, MO and its surrounding areas. The models included meteorological parameters obtained from the National Oceanic and Atmospheric Administration (NOAA)'s Rapid Update Cycle (RUC20) model as covariates. Both MISR and MODIS AOT values were highly significant predictors Of PM2.5 concentrations. The MISR and MODIS models have overall comparable predictability of ground-level PM2.5 concentrations. The MISR model explained a slightly greater percentage (62%) of the variability in PM2.5 concentrations than the MODIS model (51%), and thus was a better fit. Over the entire data range, the MISR model underpredicts PM2.5 concentrations by approximately 12%, whereas the MODIS model underpredicts PM2.5 concentrations by approximately 18%. This underestimation occurred primarily at higher PM2.5 concentrations in both models. The regression coefficients from two models were highly comparable, suggesting that combining MISR and MODIS AOT data might benefit from the higher predicting accuracy of MISR and the better spatial coverage of MODIS. The newly developed particle size/shape indicators in MISR and MODIS aerosol product did not significantly improve our ability to predict PM2.5 concentrations using AOT measurements. Finally, using hourly PM2.5 concentrations did not seem to improve its association with AOT for the current study region. (c) 2006 Elsevier Inc. All rights reserved.