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Real-time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan
Journal article   Peer reviewed

Real-time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan

G. Huang, L.-J. Chen, W.-H. Hwang, S. Tzeng and H.-C. Huang
Environmetrics, Vol.29(8), e2537
12/2018

Abstract

control chart fine particulate matter kriging multiresolution spline basis functions robust regression robust variogram estimation spatial prediction Statistics and Probability,Ecological Modeling
Fine particulate matter (PM 2.5 ) 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 PM 2.5 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 PM 2.5 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.

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