Mapping dust storm PM2.5 pollution risk using indicator kriging in northern Taiwan

  • Author(s): Hui-Chung Yeh, Yen-Chang Chen, and Chiang Wei
  • DOI: 10.3319/TAO.2019.11.07.01
  • Keywords: PM2.5 Indicator kriging Risk mapping
  • Citation: Yeh, H.-C., Y.-C. Chen, and C. Wei, 2020: Mapping dust storm PM2.5 pollution risk using indicator kriging in northern Taiwan. Terr. Atmos. Ocean. Sci., 31, 313-323, doi: 10.3319/TAO.2019.11.07.01
  • Mapping the PM2.5 of dust storm
  • Risk evaluation by indicator kriging
  • Provide a novel approach for health risk analysis
Abstract

For this study, dust storm data was collected on 24 - 25 March, 2012. This dust storm impacted the northern area of Taiwan for about two days, so our study was confined to the northern air quality region of Taiwan using indicator kriging for assessing the probability of exceeding the threhold concentration of PM2.5. Results showed that the highest levels of dust storm pollution in the study area were in the Zhongzheng District of Taipei City, with a concentration of 39.86 μg m-3. The lowest levels were 21.88 μg m-3, in Xinzhuang District, New Taipei City. Among the four administrative regions, variation was greatest in Taipei City, with concentrations between 22.74 and 39.86 μg m-3, and lowest in Keelung City, with concentrations between 23.97 and 27.56 μg m-3. We categorized pollution concentrations with probabilities greater than 0.7 into three categories to represent health risk hazards. Eighty-seven percent of areas were low risk, with PM2.5 concentrations above 25 μg m-3. Areas with PM2.5 concentrations greater than 30 μg m-3 were considered moderate risk areas, and comprised 1.2% of all area; this category appeared in the Zhongshan, Songshan, Datong, and Daan Districts of Taipei City and the Zhongli District of Taoyuan City. Concentrations greater than 35 μg m-3, labeled high risk areas, accounted for only 0.4% and were concentrated in the Zhongshan, Songshan, and Zhongli Districts of Taipei City. The methods used in this study and its results can be key references for future early warning and prevention of dust pollution by relevant authorities.

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