Prediction of local particle pollution level based on artificial neural network

Xiong, J., Yao, R. ORCID: https://orcid.org/0000-0003-4269-7224 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. doi: 10.1051/e3sconf/201911102031 (E3S Web of Conferences Volume 111, 02031)

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)
URI	https://reading-clone.eprints-hosting.org/id/eprint/90162
Identification Number/DOI	10.1051/e3sconf/201911102031
Refereed	Yes
Divisions	Science > School of the Built Environment > Energy and Environmental Engineering group
Publisher	EDP Sciences
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