Grey Correlation Analysis of Haze Impact Factor PM2.5

In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to...

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Autores principales:	Jiayi Xu, Zhixin Liu, Lirong Yin, Yan Liu, Jiawei Tian, Yang Gu, Wenfeng Zheng, Bo Yang, Shan Liu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	haze local climate PM2.5 grey correlation analysis Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/c2430c79d3c44904aba5d1b0f57a55cf
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id	oai:doaj.org-article:c2430c79d3c44904aba5d1b0f57a55cf
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spelling	oai:doaj.org-article:c2430c79d3c44904aba5d1b0f57a55cf2021-11-25T16:45:45ZGrey Correlation Analysis of Haze Impact Factor PM2.510.3390/atmos121115132073-4433https://doaj.org/article/c2430c79d3c44904aba5d1b0f57a55cf2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4433/12/11/1513https://doaj.org/toc/2073-4433In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to study the correlation between haze weather and local climate. First, we select Beijing, China and its surrounding areas (East longitude 115°20′11″–117°40′35″, North latitude 39°21′11″–41°7′51″) as the study area. We collected data from meteorological stations in Beijing and Xianghe from March 2014 to February 2015, and analyzed the meteorological parameters through correlation analysis and a grey correlation model. We study the correlation between the six influencing factors of temperature, dew point, humidity, wind speed, air pressure and visibility and PM2.5, so as to analyze the correlation between haze weather and local climate more comprehensively. The results show that the influence of each index on PM2.5 in descending order is air pressure, wind speed, humidity, dew point, temperature and visibility. The qualitative analysis results confirm each other. Among them, air pressure (correlation 0.771) has the greatest impact on haze weather, and visibility (correlation 0.511) is the weakest.Jiayi XuZhixin LiuLirong YinYan LiuJiawei TianYang GuWenfeng ZhengBo YangShan LiuMDPI AGarticlehazelocal climatePM2.5grey correlation analysisMeteorology. ClimatologyQC851-999ENAtmosphere, Vol 12, Iss 1513, p 1513 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	haze local climate PM2.5 grey correlation analysis Meteorology. Climatology QC851-999
spellingShingle	haze local climate PM2.5 grey correlation analysis Meteorology. Climatology QC851-999 Jiayi Xu Zhixin Liu Lirong Yin Yan Liu Jiawei Tian Yang Gu Wenfeng Zheng Bo Yang Shan Liu Grey Correlation Analysis of Haze Impact Factor PM2.5
description	In recent years, frequent severe haze weather has formed in China, including some of the most populated areas. We found that these smog-prone areas are often relatively a “local climate” and aim to explore this series of scientific problems. This paper uses remote sensing and data mining methods to study the correlation between haze weather and local climate. First, we select Beijing, China and its surrounding areas (East longitude 115°20′11″–117°40′35″, North latitude 39°21′11″–41°7′51″) as the study area. We collected data from meteorological stations in Beijing and Xianghe from March 2014 to February 2015, and analyzed the meteorological parameters through correlation analysis and a grey correlation model. We study the correlation between the six influencing factors of temperature, dew point, humidity, wind speed, air pressure and visibility and PM2.5, so as to analyze the correlation between haze weather and local climate more comprehensively. The results show that the influence of each index on PM2.5 in descending order is air pressure, wind speed, humidity, dew point, temperature and visibility. The qualitative analysis results confirm each other. Among them, air pressure (correlation 0.771) has the greatest impact on haze weather, and visibility (correlation 0.511) is the weakest.
format	article
author	Jiayi Xu Zhixin Liu Lirong Yin Yan Liu Jiawei Tian Yang Gu Wenfeng Zheng Bo Yang Shan Liu
author_facet	Jiayi Xu Zhixin Liu Lirong Yin Yan Liu Jiawei Tian Yang Gu Wenfeng Zheng Bo Yang Shan Liu
author_sort	Jiayi Xu
title	Grey Correlation Analysis of Haze Impact Factor PM2.5
title_short	Grey Correlation Analysis of Haze Impact Factor PM2.5
title_full	Grey Correlation Analysis of Haze Impact Factor PM2.5
title_fullStr	Grey Correlation Analysis of Haze Impact Factor PM2.5
title_full_unstemmed	Grey Correlation Analysis of Haze Impact Factor PM2.5
title_sort	grey correlation analysis of haze impact factor pm2.5
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/c2430c79d3c44904aba5d1b0f57a55cf
work_keys_str_mv	AT jiayixu greycorrelationanalysisofhazeimpactfactorpm25 AT zhixinliu greycorrelationanalysisofhazeimpactfactorpm25 AT lirongyin greycorrelationanalysisofhazeimpactfactorpm25 AT yanliu greycorrelationanalysisofhazeimpactfactorpm25 AT jiaweitian greycorrelationanalysisofhazeimpactfactorpm25 AT yanggu greycorrelationanalysisofhazeimpactfactorpm25 AT wenfengzheng greycorrelationanalysisofhazeimpactfactorpm25 AT boyang greycorrelationanalysisofhazeimpactfactorpm25 AT shanliu greycorrelationanalysisofhazeimpactfactorpm25
_version_	1718413041568055296

Grey Correlation Analysis of Haze Impact Factor PM2.5

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