Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation

Abstract Rapid urbanization is causing serious PM2.5 (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM2.5 concentrations have not been thoroughly studied. In this study...

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Autores principales:	Nan Zhang, Hong Huang, Xiaoli Duan, Jinlong Zhao, Boni Su
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cfdde88ffa574549b1c550d9ef0f1b2e
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spelling	oai:doaj.org-article:cfdde88ffa574549b1c550d9ef0f1b2e2021-12-02T11:40:15ZQuantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation10.1038/s41598-018-27771-w2045-2322https://doaj.org/article/cfdde88ffa574549b1c550d9ef0f1b2e2018-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-27771-whttps://doaj.org/toc/2045-2322Abstract Rapid urbanization is causing serious PM2.5 (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM2.5 concentrations have not been thoroughly studied. In this study, we obtained a regression formula for PM2.5 concentration based on more than 1 million PM2.5 recorded values and data from meteorology, industrial production, energy production, agriculture, and transportation for 31 provinces of mainland China between January 2013 and May 2017. We used stepwise regression to process 49 factors that influence PM2.5 concentration, and obtained the 10 primary influencing factors. Data of PM2.5 concentration and 10 factors from June to December, 2017 was used to verify the robustness of the model. Excluding meteorological factors, production of natural gas, industrial boilers, and ore production have the highest association with PM2.5 concentration, while nuclear power generation is the most positive factor in decreasing PM2.5 concentration. Tianjin, Beijing, and Hebei provinces are the most vulnerable to high PM2.5 concentrations caused by industrial production, energy production, agriculture, and transportation (IEAT).Nan ZhangHong HuangXiaoli DuanJinlong ZhaoBoni SuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-9 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nan Zhang Hong Huang Xiaoli Duan Jinlong Zhao Boni Su Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
description	Abstract Rapid urbanization is causing serious PM2.5 (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM2.5 concentrations have not been thoroughly studied. In this study, we obtained a regression formula for PM2.5 concentration based on more than 1 million PM2.5 recorded values and data from meteorology, industrial production, energy production, agriculture, and transportation for 31 provinces of mainland China between January 2013 and May 2017. We used stepwise regression to process 49 factors that influence PM2.5 concentration, and obtained the 10 primary influencing factors. Data of PM2.5 concentration and 10 factors from June to December, 2017 was used to verify the robustness of the model. Excluding meteorological factors, production of natural gas, industrial boilers, and ore production have the highest association with PM2.5 concentration, while nuclear power generation is the most positive factor in decreasing PM2.5 concentration. Tianjin, Beijing, and Hebei provinces are the most vulnerable to high PM2.5 concentrations caused by industrial production, energy production, agriculture, and transportation (IEAT).
format	article
author	Nan Zhang Hong Huang Xiaoli Duan Jinlong Zhao Boni Su
author_facet	Nan Zhang Hong Huang Xiaoli Duan Jinlong Zhao Boni Su
author_sort	Nan Zhang
title	Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
title_short	Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
title_full	Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
title_fullStr	Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
title_full_unstemmed	Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation
title_sort	quantitative association analysis between pm2.5 concentration and factors on industry, energy, agriculture, and transportation
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/cfdde88ffa574549b1c550d9ef0f1b2e
work_keys_str_mv	AT nanzhang quantitativeassociationanalysisbetweenpm25concentrationandfactorsonindustryenergyagricultureandtransportation AT honghuang quantitativeassociationanalysisbetweenpm25concentrationandfactorsonindustryenergyagricultureandtransportation AT xiaoliduan quantitativeassociationanalysisbetweenpm25concentrationandfactorsonindustryenergyagricultureandtransportation AT jinlongzhao quantitativeassociationanalysisbetweenpm25concentrationandfactorsonindustryenergyagricultureandtransportation AT bonisu quantitativeassociationanalysisbetweenpm25concentrationandfactorsonindustryenergyagricultureandtransportation
_version_	1718395672064950272

Quantitative association analysis between PM2.5 concentration and factors on industry, energy, agriculture, and transportation

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