https://scholars.lib.ntu.edu.tw/handle/123456789/373017
標題: | Identifying spatial mixture distributions of PM2.5 and PM10 in Taiwan during and after a dust storm | 作者: | Chu, Hone-Jay Yu, Hwa-Lung Kuo, Yi-Ming |
關鍵字: | Dust storm; Finite mixture distribution; Meteorological condition; Particulate matter; PM10; PM2.5; Sequential Gaussian simulation | 公開日期: | 2012 | 卷: | 54 | 起(迄)頁: | 728-737 | 來源出版物: | Atmospheric Environment | 摘要: | Atmospheric particulate matter (PM) exhibits a high correlation with public health. The mixture distributions of PM in Taiwan derive mainly from anthropogenic (industrial) and natural (rural) air pollutants. This study determines the mixture distribution of monthly PM2.5 and PM10 data of a dust storm occurred in Taiwan in March 2008 using a finite mixture distribution model (FMDM). The probabilities of a contaminated area are mapped using sequential Gaussian simulation (SGS) with the FMDM cut-off values of PM2.5 and PM10. Results show that PM2.5 and PM10 can be individually fitted using the FMDM. Using the SGS with FMDM cut-off values can delineate high and low concentration areas. Spatial patterns of PM2.5 and PM10 concentrations show seasonal variations caused by dust storms and meteorological conditions. The difference of the mixture distribution of high and low PM concentrations during the dust storm is significant. The area with high PM concentration is delineated in the industrial and urban areas of Taiwan (southwestern, west central, and northern Taiwan). This information can define the boundaries of the PM hotspot areas to control pollutants and reduce public exposure. © 2012 Elsevier Ltd. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84861576573&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/373017 |
DOI: | 10.1016/j.atmosenv.2012.01.022 | SDG/關鍵字: | Dust storm; Finite mixture distribution; Meteorological condition; Particulate Matter; PM10; PM2.5; Sequential Gaussian simulation; Mixtures; Storms; Particles (particulate matter); atmospheric pollution; correlation; dust storm; Gaussian method; industrial location; meteorology; particulate matter; pollution control; pollution exposure; probability; public health; seasonal variation; spatial distribution; urban pollution; urban region; article; atmosphere; atmospheric dispersion; dust; hurricane; kernel method; meteorological phenomena; particulate matter; priority journal; seasonal variation; spatial soil variability; Taiwan; urban area; Taiwan |
顯示於: | 生物環境系統工程學系 |
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