Jiayi Huang
ABSTRACT
Air pollution is a serious urban problem that threatens human health. Therefore, fine-grained pollution events detection has become a concerned issue for environmental management. Algorithms in previous studies identify pollution events as uptrend intervals at hour level. However, a significant part of pollution events caused by traffic and industry can be brief but frequent, which may be neglected under traditional coarse-grained detection. In this paper, we propose a fine-grained analysis of air pollution pattern based on minute-level event detection. Over the real-world deployment in Foshan, these events are analyzed according to their geographical contexts and temporal features. Results show insightful findings and this case study provides a practical reference for government inspection and pollution control.
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