New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables
New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables
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DOI：
10.4209/aaqr.2016.03.0097
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发表时间：
2017-02-01
影响因子：
4
通讯作者：
Spak, Scott N.
中科院分区：
文献类型：
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作者：
Bilal, Muhammad;Nichol, Janet E.;Spak, Scott N.
细颗粒物（PM2.5）是严重呼吸系统和心血管疾病的罪魁祸首，近年来引起了全世界的关注，但基于点的地面监测站不足以了解PM2.5在复杂城市表面上的空间分布。本文提出了一种利用卫星气溶胶光学深度（AOD）和气象变量组合预测PM2.5的新方法。利用中分辨率成像光谱辐射计（MODIS） Collection 6 （C006）气溶胶产品的AOD、mod043k Dark-Target (DT) （3 km）、MOD04 DT （10 km）和MOD04 Deep-Blue (DB) （10 km）空间分辨率，以及简化气溶胶检索算法（SARA） （500 m分辨率）对香港和珠三角工业化地区进行了分析。500 m SARA AOD与PM2.5浓度的相关性（R = 0.72）高于MODIS C6 3 km DT AOD （R = 0.60）、10 km DT AOD （R = 0.61）和10 km DB AOD （R = 0.51）。利用SARA AOD和表面压力（996 ~ 1010 hPa）的分组，建立SARA分组模型（[PM2.5] = 110.5 [AOD] + 12.56）。该模型具有相关性好、斜率准确、截距小、误差小的特点，能较准确地反映城市500m分辨率下PM2.5的空间分布。总体而言，SARA初始化模式的预测能力远好于先前在香港和东亚地区报道的模式，这表明应用气象特定经验模式并结合边界层高度在卫星AOD反演的PM2.5业务预测中具有潜在价值。
Fine particulate matter (PM2.5) has recently gained attention worldwide as being responsible for severe respiratory and cardiovascular diseases, but point based ground monitoring stations are inadequate for understanding the spatial distribution of PM2.5 over complex urban surfaces. In this study, a new approach is introduced for prediction of PM2.5 which uses satellite aerosol optical depth (AOD) and binning of meteorological variables. AOD from the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) aerosol products, MOD04_ 3k Dark-Target (DT) at 3 km, MOD04 DT at 10 km, and MOD04 Deep-Blue (DB) at 10 km spatial resolution, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m resolution were obtained for Hong Kong and the industrialized Pearl River Delta (PRD) region. The SARA AOD at 500 m alone achieved a higher correlation (R = 0.72) with PM2.5 concentrations than the MODIS C6 DT AOD at 3 km (R = 0.60), the DT AOD at 10 km (R = 0.61), and the DB AOD at 10 km (R = 0.51). The SARA binning model ([PM2.5] = 110.5 [AOD] + 12.56) was developed using SARA AOD and binning of surface pressure (996-1010 hPa). This model exhibits good correlation, accurate slope, low intercept, low errors, and accurately represents the spatial distribution of PM2.5 at 500 m resolution over urban areas. Overall, the prediction power of the SARA binning model is much better than for previous models reported for Hong Kong and East Asia, and indicates the potential value of applying meteorologically-specific empirical models and incorporating boundary layer height in operational PM2.5 forecasting from satellite AOD retrievals.