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首页> 外文期刊>International journal of remote sensing >Correlation between the spatio-temporal distributions of aerosols, sulphur dioxide, and formaldehyde using MODIS and SCIAMACHY satellite data for China
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Correlation between the spatio-temporal distributions of aerosols, sulphur dioxide, and formaldehyde using MODIS and SCIAMACHY satellite data for China

机译:利用MODIS和SCIAMACHY中国卫星数据,气溶胶,二氧化硫和甲醛的时空分布之间的相关性

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摘要

The spatial and temporal relationship between fine-mode aerosol optical depth (AOD) observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) and tropospheric columns of SO2 and formaldehyde (HCHO) from the Scanning Imaging Absorption Chartography (SCIAMACHY) are used to infer information on the variability of sulphate aerosol, which is a major determinant of fine-mode AOD (AOD(f)) in east China. When averaging the satellite data over specific regions of China and for longer time periods (from 2005 to 2011), we find obvious similar trends between AOD(f) and SO2, HCHO columns for southern and eastern China. The results of satellite observations show the high spatial and temporal correlation between AOD(f) and SO2 over the Yangtze River Delta (R-2), the Pearl River Delta (R-3), and the Chongqing-Chengdu region (R4), with the coefficients of determination (R-2) of 0.376, 0.438, and 0.837, respectively. These regions are performing with the huge amount of anthropogenic SO2 emissions by traffic, industry, and domestic heating. The trend is consistent with fine-mode aerosol and SO2 appearing in summer because AOD(f) is often correlated with enhanced HCHO concentrations, reflecting the importance of secondary aerosol formation over industrialized regions in that season. Over the North China Plain, distinct maximum values of AOD(f) and HCHO were observed and the minimum value for SO2 was observed in summer. The decrease in the mean SO2 column was 35.5%, which has been attributed to the strict security measures by the government during the 2008 Olympic Games period while there was a decrease of 46% in AOD(f) at the same time. As sulphate aerosol occurs seasonally in the North China Plain, the strong correlation between anomalies of AOD(f) and SO2 can be used to estimate and analyse the distribution of sulphate aerosol. Singular value decomposition (SVD) analysis showed the same variation between AOD(f) and SO2 over eastern China and Sichuan Province, and a distinct negative value of SVD variables over comparably industrialized regions in southern and eastern China and Sichuan Province. The results for SO4 from the Model for Ozone and Related chemical Tracers model for southern and eastern China and the Sichuan regions suggest much stronger sulphate contributions to aerosol formation than for other areas of China. We propose that the SVD variables between AOD(f) and SO2, which can be inferred from the satellite data, can be used as indicators for regional pollution control.
机译:中分辨率成像光谱仪(MODIS)观测到的精细模式气溶胶光学深度(AOD)与来自扫描成像吸收图谱(SCIAMACHY)的SO2和甲醛(HCHO)的对流层柱之间的时空关系可用于推断有关硫酸盐气溶胶的变异性,这是中国东部精细模式AOD(AOD(f))的主要决定因素。在对中国特定地区和较长时间段(2005年至2011年)的卫星数据进行平均时,我们发现中国南部和东部的AOD(f)与SO2,HCHO柱之间存在明显相似的趋势。卫星观测结果表明,长江三角洲(R-2),珠江三角洲(R-3)和重庆-成都地区(R4)的AOD(f)与SO2之间存在高度的时空相关性,测定系数(R-2)分别为0.376、0.438和0.837。这些地区的交通,工业和家庭取暖产生了大量的人为SO2排放。该趋势与夏季出现的精细模式气溶胶和二氧化硫相吻合,因为AOD(f)通常与HCHO浓度升高有关,反映了该季节工业化地区二次气溶胶形成的重要性。在华北平原,夏季观测到明显的AOD(f)和HCHO最大值,而SO2的最小值则观测到。平均SO2列下降了35.5%,这归因于政府在2008年奥运会期间采取了严格的安全措施,而AOD(f)下降了46%。由于华北平原地区的硫酸盐气溶胶呈季节性变化,因此可以利用AOD(f)和SO2异常之间的强相关性来估算和分析硫酸盐气溶胶的分布。奇异值分解(SVD)分析显示,华东和四川省的AOD(f)和SO2之间存在相同的变化,而华南和华东与四川省的相当工业化地区的SVD变量具有明显的负值。来自中国南部和东部以及四川地区的臭氧模型和相关化学示踪剂模型中的SO4结果表明,硫酸盐对气溶胶形成的贡献要比中国其他地区强得多。我们建议可以根据卫星数据推断出AOD(f)和SO2之间的SVD变量,将其用作区域污染控制的指标。

著录项

  • 来源
    《International journal of remote sensing》 |2015年第16期|3961-3978|共18页
  • 作者单位

    Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210093, Jiangsu, Peoples R China|Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China|Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China;

    Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210093, Jiangsu, Peoples R China|Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China;

    Natl Satellite Meteorol Ctr, Div Remote Sensing Data Applicat, Beijing 100081, Peoples R China;

    Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210093, Jiangsu, Peoples R China|Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China;

    Zhejiang A&F Univ, Zhejiang Prov Key Lab Carbon Cycling Forest Ecosy, Linan 311300, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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