An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM<sub>2.5</sub>-Bound Carbonaceous Compositions and Water-Soluble Ionic Species

An Application of Artificial Neural Network to Evaluate the Influence of Weather Conditions on the Variation of PM<sub>2.5</sub>-Bound Carbonaceous Compositions and Water-Soluble Ionic Species

Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source a...

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Bibliographic Details
Main Authors:	Siwatt Pongpiachan, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Yu Li, Li Xing, Guohui Li, Yongming Han, Junji Cao, Ronald C. Macatangay, Saran Poshyachinda, Aekkapol Aekakkararungroj, Muhammad Zaffar Hashmi
Format:	Article
Language:	English
Published:	MDPI AG 2022-06-01
Series:	Atmosphere
Subjects:	principal component analysis artificial neural networks PM<sub>2.5</sub> hotspots carbonaceous compositions water-soluble ionic species
Online Access:	https://www.mdpi.com/2073-4433/13/7/1042

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