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博士生郭阳洁的论文在INTERNATIONAL JOURNAL OF REMOTE SENSING刊出
发布时间:2015-01-04 17:00:51     发布者:yz     浏览次数:

标题:Satellite remote sensing of fine particulate matter (PM2.5) air quality over Beijing using MODIS作者:Guo, Yangjie; Feng, Nan; Christopher, Sundar A.; Kang, Ping; Zhan, F.Benjamin; Hong, Song

来源出版物:INTERNATIONAL JOURNAL OF REMOTE SENSING 卷:35 期:17 页:6522-6544 DOI:10.1080/01431161.2014.958245 出版年:2014

摘要:Fine particulate matter (aerodynamic diameters of less than 2.5 mu m, PM2.5) air pollution has become one of the major environmental challenges, causing severe environmental issues in urban visibility, climate, and public health. In this study, ground-level PM2.5 concentrations, air-quality categories (AQCs), and health risk categories (HRCs) over Beijing, China, have been estimated based on mid-visible column aerosol optical depth (AOD) measurements extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data on board both Terra and Aqua satellites. Our results indicate that the MODIS AOD retrievals at 550 nm (AOD(550)) match hourly aerosol robotic network (AERONET) measurements with correlation coefficients (r) of 0.950 for Terra and 0.895 for Aqua. The relationship between ground-level PM2.5 and MODIS AOD(550) from March 2012 to February 2013 showed correlation coefficients of 0.69, 0.60, and 0.73 for spring, summer, and autumn, respectively. The atmospheric boundary layer height and relative humidity (RH) adjustments improved the AOD-PM2.5 relationship in summer months. The estimates of daily average PM2.5 from satellite measurements were used to predict both AQCs and HRCs, which are well matched with observations. Satellite remote sensing of atmospheric aerosols continues to show great potential for estimating ground-level PM2.5 concentrations and can be further used to monitor the atmospheric environment in China.

入藏号:WOS:000345706300009

文献类型:Article

语种:English

扩展关键词:AEROSOL OPTICAL DEPTH; PARTICLE CONCENTRATIONS; TEMPORAL VARIATIONS; CHINA; AERONET; PRODUCTS; URBAN; MASS; VALIDATION; POLLUTION

通讯作者地址:Hong, Song; Wuhan Univ, Sch Resource & Environm Sci, Dept Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址:environmentalanalytics@gmail.com

地址:

[Guo, Yangjie; Kang, Ping; Hong, Song] Wuhan Univ, Sch Resource & Environm Sci, Dept Environm Sci, Wuhan 430079, Peoples R China.

[Guo, Yangjie; Feng, Nan; Christopher, Sundar A.] Univ Alabama, Dept Atmospher Sci, Huntsville, AL 35805 USA.

[Zhan, F. Benjamin; Hong, Song] Texas State Univ, Dept Geog, San Marcos, TX 78666 USA.

研究方向:Remote Sensing; Imaging Science & Photographic Technology

ISSN:0143-1161

eISSN:1366-5901

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