Satellite measurements of aerosol optical depth and carbon monoxide and comparison with ground data

被引:7
作者
Lalitaporn, Pichnaree [1 ]
Mekaumnuaychai, Tipvadee [1 ]
机构
[1] Kasetsart Univ, Fac Engn, Dept Environm Engn, Bangkok 10900, Thailand
关键词
Aerosol optical depth (AOD); CO; MODIS; MOPITT; Particulate matter; Thailand; IMAGING SPECTRORADIOMETER MODIS; LEVEL PM2.5 CONCENTRATIONS; PARTICULATE MATTER PM2.5; LONG-TERM ANALYSIS; AIR-QUALITY; CHIANG-MAI; CO EMISSIONS; POLLUTION; THAILAND; BIOMASS;
D O I
10.1007/s10661-020-08346-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Satellite data of aerosol optical depths (AODs) from the moderate resolution imaging spectroradiometer (MODIS) and carbon monoxide (CO) columns from the measurements of pollution in the troposphere (MOPITT) were collected for the study in Northern Thailand. Comparative analyses were conducted of MODIS (Terra and Aqua) AODs with ground particulate matter with diameter below 10 microns (PM10) concentrations and MOPITT CO surface/total columns with ground CO concentrations for 2014-2017. Temporal variations in both the satellite and ground datasets were in good agreement. High levels of air pollutants were common during March-April. The annual analysis of both satellite and ground datasets revealed the highest levels of air pollutants in 2016 and the lowest levels in 2017. The AODs and PM10 concentrations were at higher levels in the morning than in the afternoon. The comparison between satellite products showed that AODs correlated better with the CO total columns than the CO surface columns. The regression analysis presented better performance of Aqua AODs-PM10 than Terra AODs-PM10 with correlation coefficients (r) of 0.72-0.83 and 0.57-0.79, respectively. Ground CO concentrations correlated better with MOPITT CO surface columns (r = 0.65-0.73) than with CO total columns (r = 0.56-0.72). The r values of satellite and ground datasets were greatest when the analysis was restricted to November-March (dry weather periods with possible low mixing height (MH)). Overall, the results suggested that the relationships between satellite and ground data can be used to develop predictive models for ground PM10 and CO in northern Thailand, particularly during air pollution episodes located where ground monitoring stations are limited.
引用
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页数:19
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