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Prediction of local particle pollution level based on artificial neural network

Xiong, J., Yao, R. and Li, B. (2019) Prediction of local particle pollution level based on artificial neural network. In: CLIMA 2019 Congress, 26-29 May 2019, Bucharest, Romania, https://doi.org/10.1051/e3sconf/201911102031. (E3S Web of Conferences Volume 111, 02031)

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To link to this item DOI: 10.1051/e3sconf/201911102031

Abstract/Summary

Citizens eager to know the local pollution level to prevent from air pollution. The real-time measurement for everywhere is a very expensive way, a statistical model based on artificial neural network is applied in this research. This model can estimate particle pollution level with some influencing factors, including background pollution level, weather conditions, urban morphology and local pollution sources. The monitoring from regulatory monitoring sites is considered as the background level. The field measurements of 20 locations are conducted to feed the output layer of ANN model. The average relative error of prediction compared with measurement is 9.24% for PM10 and 18.90% for PM2.5.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of the Built Environment > Construction Management and Engineering > Innovative and Sustainable Technologies
ID Code:90162
Publisher:EDP Sciences

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