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Real‐time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan
Fine particulate matter (PM2.5) has gained increasing attention due to its adverse health effects to human. In Taiwan, it was conventionally monitored by large environmental monitoring stations of the Environmental Protection Administration. However, only a small number of 77 monitoring stations are currently established. Recently, a project using a large number of small devices, called AirBoxes, was launched in March 2016 to monitor PM2.5 concentrations. Although thousands of AirBoxes have been deployed across Taiwan to give a broader coverage, they are mostly located in big cities and their measurements are less accurate. In this paper, we apply a robust kriging method that provides a smoothly varied real‐time PM2.5 concentration map and its associated standard error map. In addition, we develop a novel spatio‐temporal control chart that monitors anomalous measurements by utilizing neighboring AirBox information. Our method automatically adapts to different neighboring structures at different AirBox locations without the need to specify a neighborhood range. The proposed method has abilities to detect potential emission sources, malfunctioned AirBoxes, and AirBoxes that are wrongly put indoors.
Real‐time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan
Fine particulate matter (PM2.5) has gained increasing attention due to its adverse health effects to human. In Taiwan, it was conventionally monitored by large environmental monitoring stations of the Environmental Protection Administration. However, only a small number of 77 monitoring stations are currently established. Recently, a project using a large number of small devices, called AirBoxes, was launched in March 2016 to monitor PM2.5 concentrations. Although thousands of AirBoxes have been deployed across Taiwan to give a broader coverage, they are mostly located in big cities and their measurements are less accurate. In this paper, we apply a robust kriging method that provides a smoothly varied real‐time PM2.5 concentration map and its associated standard error map. In addition, we develop a novel spatio‐temporal control chart that monitors anomalous measurements by utilizing neighboring AirBox information. Our method automatically adapts to different neighboring structures at different AirBox locations without the need to specify a neighborhood range. The proposed method has abilities to detect potential emission sources, malfunctioned AirBoxes, and AirBoxes that are wrongly put indoors.
Real‐time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan
Huang, G. (author) / Chen, L.‐J. (author) / Hwang, W.‐H. (author) / Tzeng, S. (author) / Huang, H.‐C. (author)
Environmetrics ; 29
2018-12-01
1 pages
Article (Journal)
Electronic Resource
English
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