京津冀地区污染过程的气溶胶遥感反演Study of aerosol retrieval using remote sensing data during air pollution events over Jing-Jin-Ji area
王晶杰;李琦;冯逍;朱亚杰;
摘要(Abstract):
针对地面监测站覆盖范围有限且成本高的不足,该文采用遥感卫星与地面站点数据相结合的方式,利用简化的气溶胶反演算法反演京津冀地区2013年秋、冬季节两次污染过程的气溶胶光学厚度,分辨率为500m。以气溶胶自动观测网在北京站点的监测数据作为简化的气溶胶反演算法的输入参数,分析气溶胶光学厚度与气溶胶自动观测网对应地面站点的相关性;将所反演气溶胶光学厚度与京津冀地区空气质量监测站点的细颗粒物浓度24h均值进行相关性分析,发现除近海城市外,相关性均较高。结果表明,简化的气溶胶反演算法适用于区域污染过程中的气溶胶光学厚度反演,反演精度高,对空气质量具有较好的监测能力。
关键词(KeyWords): 京津冀地区;简化的气溶胶反演算法;气溶胶光学厚度;细颗粒物
基金项目(Foundation):
作者(Authors): 王晶杰;李琦;冯逍;朱亚杰;
DOI: 10.16251/j.cnki.1009-2307.2015.02.015
参考文献(References):
- [1]Aiimoto H.Global Air Quality and Pollution[J].Science,2003(302):1716-1719.
- [2]Ramanathan V,Crutzen P J,KIEHL J T,et al.Aerosols,Climate,and the Hydrological Cycle[J].Science,2001(294):2119-2124.
- [3]Layshock J,Simonich S M,Anderson K A.Effect of Dibenzopyrene Measurement on Assessing Air Quality in Beijing Air and Possible Implications for Human Health[J].Journal of Environmental Monitoring,2012(12):2290-2298.
- [4]Kaufman Y J,Tanre D,Gordon H R,et al.Passive Remote Sensing of Tropospheric Aerosol and Atmosphericcorrection for the Aerosol Effect[J].Journal of Geophysical Research,,1997,102(D14):16815-16830.
- [5]Hsu N C,Tsay S C,King M D.Aerosol Properties over Bright-reflecting Source Regions[C]//IEEE Transactions on Geoscience and Remote Sensing,2004,42(3):557-569.
- [6]Tanre D,Deschanps P Y,Devaux C,et al.Estimation of Sahran Aerosol Optical Depth from Blurring Effects in Thematic Mapper Data[J].Journal of Geophysical Research,1988,93(D12):15955-15964.
- [7]Diner D J,Martonchik J V,Kahn R A,et al.Using Angular and Spectral Shape Similarity Constraints to Improve Misr Aerosol and Surface Retrievals over Land[J].Remote Sensing of Environment,2005(94):155-171.
- [8]Deuze J L,Breon F M,Devaux C,et al.Remote Sensing of Aerosols over Land Surfaces from Polder-adeos–1Polarized Measurements[J].Journal of Geophysical Research,2001,106(D5):4913-4926.
- [9]Bilal M,Nichol J E,Bleiweiss M P,et al.A Simplified High Resolution Modis Aerosol Retrieval Algorithm(SARA)for Use over Mixed Surfaces[J].Remote Sensing of Environment,2013(136):135-145.
- [10]Bilal M,Nichol J E,Chan P W.Validation and Accuracy Assessment of a Simplified Aerosol Retrieval Algorithm(SARA)over Beijing under Low and High Aerosol Loadings and Dust Storms[J].Remote Sensing of Environment,2014(153):50-60.
- [11]Mattoo S,Munchak L A,LEVY R C,et al.The Collection 6 MODIS Aerosol Products over Land and Ocean[J].Atmospheric Measurement Techniques,2013(6):2989-3034.
- [12]Munchak L A,Levy R C,Mattoo S,et al.Modis 3Km Aerosol Product:Applications over Land in an Urban/Suburban Region[J].Atmos.meas.tech.,2013(6):1747-1759.
- [13]李成才,毛节泰,刘启汉.利用MODIS资料遥感香港地区高分辨率气溶胶光学厚度[J].大气科学,2005(3):335-342.
- [14]Chylek P B G.The Effect of Spatial Resolution on Satellite AOD Retrieval[C]//IEEE Transactions on Geoscience and Remote Sensing,2005,43(9):1984-1990.
- [15]王跃思,姚利,王莉莉,等.2013年元月我国中东部地区强霾污染成因分析[J].中国科学:地球科学,2014,44(1):15-26.
- [16]徐祥德,施晓晖,张胜军,等.北京及周边城市群落气溶胶影响域及其相关气候效应[J].科学通报,2005(22):2522-2530.
- [17]李成才,毛节泰,刘启汉,等.利用MODIS研究中国东部地区气溶胶光学厚度的分布和季节变化特征[J].科学通报,2003(19):2094-2100.
- [18]陈好,顾行发,程天海,等.中国地区气溶胶类型特性分析[J].遥感学报,2013(6):1559-1571.
- [19]Tanre D,Remer L A,Kaufman Y J,et al.Operational Remote Sensing of Tropospheric Aerosol over Land from Eos Moderate Resolution Imaging Spectroradiometer[J].Journal of Geophysical Research,1997,102(D14):17051-17067.
- [20]ngstrM A.The Parameters of Atmospheric Turbidity[J].Tellus,1964,16(1):64-75.
- [21]Xin J Y,Zhang Q,Wang L L,et al.The Empirical Relationship between the PM2.5 Concentration and Aerosol Optical Depth over the Background of North China from 2009to 2011[J].Atmospheric Research,2014(138):179-188.
- [22]于兴娜,李新妹,登增然登,等.北京雾霾天气期间气溶胶光学特性[J].环境科学,2012(4):1057-1062.
- [23]Beckerman B S,Jerrett M,Serre M,et al.A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM2.5in the Contiguous United States[J].Environmental Science&Technology,2013(47):7233-7241.
- [24]Donkelaar A V,Martin R V,Park R J.Estimating Ground-level PM2.5Using Aerosol Optical Depth Determined from Satellite Remote Sensing[J].Journal of Geophysical Research,2006,111(D21):1-10.
- [25]Tian J,Chen D M.A Semi-empirical Model for Predicting Hourly Ground-level Fine Particulate Matter(PM2.5)Concentration in Southern Ontario from Satellite Remote Sensing and Ground-based Meteorological Measurements[J].Remote Sensing of Environment,2010(114):221-229.