基于卫星遥感与地统计结合的PM2.5估算方法研究

项目名称： 基于卫星遥感与地统计结合的PM2.5估算方法研究

项目编号： No.41601472

项目类型： 青年科学基金项目

立项/批准年度： 2017

项目学科： 天文学、地球科学

项目作者： 李荣

作者单位： 中国科学院大气物理研究所

项目金额： 14万元

中文摘要： 细颗粒物（PM2.5）污染已成为我国政府和社会关注的重大环境问题。与站点观测相比，卫星遥感在监测PM2.5的时空分布、点源及传输路径方面具有较大优势，但通常获取的为整层气溶胶光学厚度 (AOD)，与地面PM2.5关系受气溶胶垂直分布、气象条件等影响很大。准确的AOD-PM2.5关系是遥感估算PM2.5的关键，但目前针对我国重污染特征和站点分布的研究较少，且缺乏AOD缺失影响的定量评估与补充手段。本项目针对我国PM2.5遥感估算偏差问题与地基站点增加的背景，定量评估PM2.5急剧变化、AOD缺失等因素对遥感估算的影响，基于混合效应与地理加权回归二阶段模型分别考虑AOD-PM2.5关系的时间和空间变化，建立基于时空特征的PM2.5遥感估算模型；针对AOD缺失限制，发展空间统计插值方法，比较卫星遥感与地统计在不同空间尺度适用性；探讨遥感与地统计插值的结合方法，初步实现PM2.5时空连续估算。

中文关键词： 可见光-近红外遥感；可吸入颗粒物；大气污染；公共卫生与健康；霾

英文摘要： The fine particle pollution has been an important environmental problem in China. Compare with the ground-based observations, satellite remote sensing has advantages in monitoring spatial variation, point sources, and transport of PM2.5. However, aerosol optical depth is columnar extinction of the whole aerosol layers, the correlation of which with PM2.5 is impacted by several factors such as vertical distribution, meteorological conditions. Therefore, accurate AOD-PM2.5 relationship is the key step of PM2.5 estimation. So far, there are few studies concerning the special background in China as well as lack of AOD values. Considering the high deviation of PM2.5 estimation and increasing ground sites in China, we intend to evaluate the influence of large variations of PM2.5, lack of AOD on accuracy of the results, and develop a two-stage model of mixing effect and geographically weighted regression to take temporal and spatial variations of AOD-PM2.5 into account. Spatial interpolation is used according to the problems of AOD unavailable. Applicability of remote sensing and interpolation is different scales is compared. The combination of remote sensing and spatial interpolation is investigated to realize PM2.5 estimation that is continuous in temporal and spatial scales.

英文关键词： visible and near-infrared remote sensing ;inhalable particle ;air pollution ;public health ;haze