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The empirical correlations between PM2.5, PM10 and AOD in the Beijing metropolitan region and the PM2.5, PM10 distributions retrieved by MODIS

机译:北京都市圈PM2.5,PM10和AOD与MODIS提取的PM2.5,PM10分布之间的经验相关性

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摘要

We observed PM2.5, PM10 concentration, aerosol optical depth (AOD), and Angstrom exponents (alpha) in three typical stations, the Beijing city, the Xianghe suburban and the Xinglong background station in the Beijing metropolitan region, from 2009 to 2010, synchronously. The annual means of PM2.5 (PM10) were 62 +/- 45 (130 +/- 88) mu g m(-3) and 79 +/- 61 (142 +/- 96) mu g m(-3) in the city and suburban region, which were much higher than the regional background (PM2.5: 36 +/- 29 mu g m(-3)). The annual means of AOD were 0.53 +/- 0.47 and 0.54 +/- 0.46 and 0.24 +/- 0.22 in the city, suburban and the background region, respectively. The annual means of Angstrom exponents were 1.11 +/- 0.31, 1.09 +/- 0.31 and 1.02 +/- 0.31 in three typical stations. Meanwhile, the rates of PM2.5 accounting for PM10 were 44%-54% and 46%-70% in the city and suburban region during four seasons. The pollution of fine particulate was more serious in winter than other seasons. The linear regression functions of PM2.5 (y) and ground-observed AOD (x) were similarly with high correlation coefficient in the three typical areas, which were y = 74x + 18 (R-2 = 0.58, N = 337, in the City), y = 80x + 25 (R-2 = 0.55, N = 306, in the suburban) and y = 87x + 9 (R-2 = 0.64, N = 350, in the background). The functions of PM10 (y) and ground-observed AOD (x) were y = 112x + 57 (R-2 = 0.54, N = 337, in the city) and y = 114x + 68 (R-2 = 0.47, N = 304, in the suburban). But the functions had large differences in four seasons. The correlations between PM2.5, PM10 and MODIS AOD were similar with the correlations between PM2.5, PM10 and the ground-observed AOD. With MODIS C6 AOD, the distributions of PM2.5 and PM10 concentration were retrieved by the seasonal functions. The absolute retrieval errors of seasonal PM2.5 distribution were less than 5 mu g m(-3) in the pollutant city and suburb, and less than 7 mu g m(-3) in the clean background. (C) 2016 Elsevier Ltd. All rights reserved.
机译:我们从2009年至2010年在北京市区,香河郊区和兴隆背景站这三个典型站点观测了PM2.5,PM10浓度,气溶胶光学深度(AOD)和埃指数(alpha),同步地。 PM2.5(PM10)的年平均值为62 +/- 45(130 +/- 88)μgm(-3)和79 +/- 61(142 +/- 96)μgm(-3)。城市和郊区,远高于区域背景(PM2.5:36 +/- 29μgm(-3))。在城市,郊区和背景地区,AOD的年平均值分别为0.53 +/- 0.47和0.54 +/- 0.46和0.24 +/- 0.22。在三个典型站点中,埃斯特朗指数的年平均值为1.11 +/- 0.31、1.09 +/- 0.31和1.02 +/- 0.31。同时,在四个季节中,城市和郊区的PM2.5占PM10的比率分别为44%-54%和46%-70%。冬季细颗粒物的污染比其他季节更为严重。在三个典型区域中,y = 74x + 18(R-2 = 0.58,N = 337 in)在三个典型区域中PM2.5(y)和地面观测的AOD(x)的线性回归函数相似,具有高相关系数。城市),y = 80x + 25(在郊区,R-2 = 0.55,N = 306),y = 87x + 9(在背景中,R-2 = 0.64,N = 350)。 PM10(y)和地面观测到的AOD(x)的函数分别为y = 112x + 57(城市中R-2 = 0.54,N = 337)和y = 114x + 68(R-2 = 0.47,N = 304,在郊区)。但是四个季节的功能差异很大。 PM2.5,PM10和MODIS AOD之间的相关性与PM2.5,PM10和地面观测到的AOD之间的相关性相似。使用MODIS C6 AOD,可通过季节函数获取PM2.5和PM10浓度的分布。在污染城市和郊区,季节性PM2.5分布的绝对取回误差小于5μg m(-3),而在干净的背景中小于7μg m(-3)。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Environmental Pollution》 |2016年第9期|350-360|共11页
  • 作者单位

    Lanzhou Univ, Key Lab Arid Climat Change & Reducing Disaster Ga, Coll Atmospher Sci, Lanzhou 730000, Peoples R China|Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China;

    Chengdu Univ Informat Technol, Plateau Atmosphere & Environm Key Lab Sichuan Pro, Chengdu, Peoples R China|Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China;

    Lanzhou Univ, Key Lab Arid Climat Change & Reducing Disaster Ga, Coll Atmospher Sci, Lanzhou 730000, Peoples R China;

    Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    PM2.5; PM10; AOD; MODIS; The Beijing metropolitan region;

    机译:PM2.5;PM10;AOD;MODIS;北京都会区;
  • 入库时间 2022-08-17 13:26:51

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