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Estimating Ground-Level PM_(2.5) in China Using Satellite Remote Sensing

机译：利用卫星遥感估算中国的地面PM_（2.5）

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摘要

Estimating ground-level PM_(2.5) from satellite-derived aerosol optical depth (AOD) using a spatial statistical model is a promising new method to evaluate the spatial and temporal characteristics of PM_(2.5) exposure in a large geographic region. However, studies outside North America have been limited due to the lack of ground PM_(2.5) measurements to calibrate the model. Taking advantage of the newly established national monitoring network, we developed a national-scale geographically weighted regression (GWR) model to estimate daily PM_(2.5) concentrations in China with fused satellite AOD as the primary predictor. The results showed that the meteorological and land use information can greatly improve model performance. The overall cross-validation (CV) R~2 is 0.64 and root mean squared prediction error (RMSE) is 32.98 μg/m~3. The mean prediction error (MPE) of the predicted annual PM_(2.5) is 8.28 μg/m~3 . Our predicted annual PM_(2.5) concentrations indicated that over 96% of the Chinese population lives in areas that exceed the Chinese National Ambient Air Quality Standard (CNAAQS) Level 2 standard. Our results also confirmed satellite-derived AOD in conjunction with meteorological fields and land use information can be successfully applied to extend the ground PM_(2.5) monitoring network in China.
机译：使用空间统计模型从卫星衍生的气溶胶光学深度（AOD）估算地面PM_（2.5）是一种有前途的新方法，用于评估大地理区域PM_（2.5）暴露的时空特征。但是，由于缺乏用于校准模型的地面PM_（2.5）测量值，北美以外的研究受到了限制。利用新建立的国家监测网络，我们开发了国家规模的地理加权回归（GWR）模型，以融合卫星AOD作为主要预测因子来估算中国的日PM_（2.5）浓度。结果表明，气象和土地利用信息可以大大提高模型性能。总体交叉验证（CV）R〜2为0.64，均方根预测误差（RMSE）为32.98μg/ m〜3。预测的年度PM_（2.5）的平均预测误差（MPE）为8.28μg/ m〜3。我们预测的PM_（2.5）年度浓度表明，超过96％的中国人口居住在超过中国国家环境空气质量标准（CNAAQS）2级标准的地区。我们的结果还证实，结合气象领域的卫星衍生AOD和土地使用信息可以成功地应用于扩展中国地面PM_（2.5）监测网络。

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  • 来源
    《Environmental Science & Technology》 |2014年第13期|7436-7444|共9页
  • 作者

    Zongwei Ma; Xuefei Hu; Lei Huang; Jun Bi; Yang Liu;

  • 作者单位

    State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China,Department of Environmental Health, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, Georgia 30322, United States;

    Department of Environmental Health, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, Georgia 30322, United States;

    State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China;

    State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China;

    Department of Environmental Health, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, Georgia 30322, United States;

  • 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);
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