Exploratory study for estimating atmospheric low level particle pollution based on vertical integrated optical measurements

被引:10
作者
Yahi, Houda [1 ,2 ]
Santer, Richard [1 ]
Weill, Alain [3 ]
Crepon, Michel [2 ]
Thiria, Sylvie [2 ]
机构
[1] ULCO, F-62930 Wimereux, France
[2] LOCEAN, UMR 7159, Paris, France
[3] LATMOS, UMR 8190, Guyancourt 78, France
关键词
Weather types; Unsupervised classification; Aerosols; Atmospheric particulate matter (PM10); Aerosol Optical Thickness (AOT); WEATHER REGIMES; NORTH-ATLANTIC; AERONET; NETWORK; EVENTS;
D O I
10.1016/j.atmosenv.2010.11.047
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We present a method for retrieving atmospheric particulate matter (PM10) from sun-sky photometer measurements (AOT). As PM10 is a "surface parameter" and AOT is an "integrated parameters", we first determined whether a "functional relationship" linking these two quantities exists. Since these two parameters strongly depend on atmospheric structures and meteorological variables, we classified the meteorological situations in terms of weather types by using a neuronal classifier (Self organizing Map). For each weather type, we found that a relationship between AOT and PM10 can be established. We applied this approach to the Lille region (France) for the summer 2007 and then extended to a five summer period (summers of the years 2003-2007) in order to increase the statistical confidence of the PM10 retrieval from AOT measurements. The good performances of the method led us to envisage the possibility of deriving the PM10 from satellite observations. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3891 / 3902
页数:12
相关论文
共 23 条
  • [11] Kohonen T., 2001, SELF ORG MAPS, V3rd ed, DOI 10.1007/978-3-642-56927-2
  • [12] Kohonen T., 2001, SELF ORG ASS MEMORY
  • [13] Automatic neural classification of ocean colour reflectance spectra at the top of the atmosphere with introduction of expert knowledge
    Niang, A
    Gross, L
    Thiria, S
    Badran, F
    Moulin, C
    [J]. REMOTE SENSING OF ENVIRONMENT, 2003, 86 (02) : 257 - 271
  • [14] NOORDIJK H, 2003, CORRECTING AIR POLLU
  • [15] NOORDIJK H, 2002, CORRECTING AIR POLLU
  • [16] OSRODKA L, 2007, APPL DATA MINING FOR
  • [17] CONTINUOUS PM-10 MEASUREMENTS USING THE TAPERED ELEMENT OSCILLATING MICROBALANCE
    PATASHNICK, H
    RUPPRECHT, EG
    [J]. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 1991, 41 (08): : 1079 - 1083
  • [18] Retrieving of particulate matter from optical measurements: A semiparametric approach
    Pelletier, B.
    Santer, R.
    Vidot, J.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2007, 112 (D6)
  • [19] Assessment of vertically-resolved PM10 from mobile lidar observations
    Raut, J. -C.
    Chazette, P.
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (21) : 8617 - 8638
  • [20] Exploring the relation between aerosol optical depth and PM2.5 at Cabauw, the Netherlands
    Schaap, M.
    Apituley, A.
    Timmermans, R. M. A.
    Koelemeijer, R. B. A.
    de Leeuw, G.
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (03) : 909 - 925