國家衛生研究院 NHRI:Item 3990099045/9708

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Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/9708

Title:	Estimating PM 2.5 concentration with MODIS for 2013 petrochemical industrial accident
Authors:	Chen, HH;Shih, PTY;Chiang, PH;Yu, PH;Tsou, HC;Yeh, HL
Contributors:	Division of Health Services and Preventive Medicine
Abstract:	The concentration of PM 2.5 (Particulate Matter) is an important indicator of air condition. By 2014, there are 73 PM 2.5 monitoring stations established by the Environmental Protection Administration (EPA) in Taiwan. Based on the location and role in the further application, these stations could be classified into six types, namely, general stations, industrial stations, traffic stations, background stations, park stations and others. While the ground stations provide continuous and high precision in-situ observations, satellite borne remote sensing technique could provide a vast area coverage but with limited time epoch information. Among a number of satellite image sensors, MODIS provides a standard scientific product, MOD04, for AOD (Aerosol Optical Depth, AOD) measurement. With MOD04, PM 2.5 concentration could be estimated with correlation and regression to in-situ measurements. This study utilized the 73 EPA ground stations for an incidence occurred on Feb. 14, 2013 and Mar. 5, 2014 in the sixth naphtha cracker of Formosa Plastic Group. The result shows that the correlation index R2 between AOD and PM 2.5 is 0.50. While the AOD measurements derived from satellite images offer a way for estimating PM 2.5 concentration, further improvement in the modeling and data processing is required for reducing the uncertainty.
Date:	2015-10
Relation:	Asian Conference on Remote Sensing (ACRS) Proceedings 2015. 2015 Oct:Meeting Abstract 317.
Link to:	http://acrs2015.ccgeo.info/proceedings/WEP2-16.pdf
Cited Times(Scopus):	http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84964049222
Appears in Collections:	[Po-Huang Chiang] Conference Papers/Meeting Abstract

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