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长江三角洲PM2.5质量浓度遥感估算与时空分布特征
摘要点击 3798  全文点击 1724  投稿时间:2015-02-26  修订日期:2015-04-15
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中文关键词  PM2.5  MODIS AOT  遥感  估算  时空分布  长江三角洲
英文关键词  PM2.5  MODIS AOT  remote sensing  evaluation  spatial and temporal variation  Yangtze Delta
作者单位E-mail
徐建辉 南京大学国际地球系统科学研究所, 南京 210093
滁州学院地理信息与旅游学院, 滁州 239000 
jianhuixu2003@126.com 
江洪 南京大学国际地球系统科学研究所, 南京 210093 jianghong_china@hotmail.com 
中文摘要
      卫星遥感反演气溶胶光学厚度(AOT)已被广泛地应用于地面PM2.5遥感监测. 为遥感监测长江三角洲地区PM2.5,利用2013年的MODIS/Terra AOT产品,考虑研究区36个空气质量监测站点的风速、温度、湿度和边界层高度等气象条件,构建了基于MODIS AOD产品估算PM2.5的模型. 利用17个空气质量监测站点数据对模型进行散点拟合验证,结果表明模型估算精度较高,春夏秋冬4个季节PM2.5质量浓度的模型估算值与地面监测值的相关系数R2值分别为0.45、0.50、0.58和0.52. 利用模型估算的长时间序列PM2.5时空分布数据进行时空变化特征分析,结果表明:1 2000~2013年研究区PM2.5质量浓度呈增长趋势,月均增长量为0.047μg ·m-3,最大值出现在2月,为(66.2±19.3)μg ·m-3,最小值出现在8月,为(22.6±5.9)μg ·m-3. 2研究区PM2.5质量浓度空间分布差异显著,南部低,北部高,高值主要出现在由上海、杭州和南京构成的三角形区域的城市群中,而低值主要出现在南部远离城市的森林区域. 结果表明基于MODIS/Terra AOT产品和地面观测气象数据估算PM2.5的多元线性回归模型能较好地应用于区域PM2.5监测.
英文摘要
      Satellite remote sensing retrieved aerosol optical thickness is widely used to monitor surface PM2.5 concentration. In order to monitor PM2.5 by remote sensing in the Yangtze delta, estimate model of PM2.5 concentration was constructed based on MODIS AOT, PM2.5 concentration data of the 36 ground air quality observation sites and meteorological data in 2013. Afterwards, the model estimated PM2.5 was validated by PM2.5 concentration data from the 17 ground air quality observation sites, and the results showed that the model estimation was higher. The correlation coefficient value of R2 between model estimation of PM2.5 concentration and the value of the ground monitoring of spring, summer, autumn and winter were 0.45, 0.50, 0.58 and 0.52, respectively. The variation characteristics of temporal and spatial was analyzed based on the long time PM2.5 data together with model estimated, and an increase trend of PM2.5 concentration was observed from 2000 to 2013, with the maximum concentration of PM2.5(66.2μg ·m-3±19.3 μg ·m-3) in February and minimum in December (22.6μg ·m-3±5.9 μg ·m-3). In addition, it was found that the distribution of PM2.5 concentration was of obvious features, displaying high value in south and low in north. Mass concentration of PM2.5 was peaked in the zone of urban agglomeration which was grouped to a delta-shaped region by Shanghai, Hangzhou and Nanjing, while the low value areas were in the forest away from city. The result suggested that MODIS AOT and meteorological data can be used to monitor regional PM2.5 by the established multi-linear regression model.

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