A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method

Abstract To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to Ch...

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Autores principales:	Xiaoling Ren, Zhenfu Luo, Shuyu Qin, Xinqian Shu, Yuanyuan Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cd2bb779b73a401ebe42850079ced7b5
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spelling	oai:doaj.org-article:cd2bb779b73a401ebe42850079ced7b52021-12-05T12:13:58ZA new method for evaluating air quality using an ideal grey close function cluster correlation analysis method10.1038/s41598-021-02880-12045-2322https://doaj.org/article/cd2bb779b73a401ebe42850079ced7b52021-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02880-1https://doaj.org/toc/2045-2322Abstract To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to China’s air quality standard, SO2, NO2, PM10, PM2.5 and O3 are selected as evaluation indexes to perform the evaluation. The results show that the air quality in this region in 2018 can be divided into three classifications, among which the relatively poor air quality in March, April and May is the first classification, the better air quality in August and September is the third classification, and the air quality in other months falls under the second classification. Correlation analysis is used to qualitatively determine that these three classifications correspond to first-level air quality in China’s air quality standard, and the correlation degree, which is the distance between the three classifications and the first-level air quality, is quantitatively determined. Specifically, the correlation degrees of the first-classification, second-classification and third-classification of air quality are 0.674, 0.697 and 0.71, respectively. The research results indicate potential directions and objectives for air quality management to achieve scientific management.Xiaoling RenZhenfu LuoShuyu QinXinqian ShuYuanyuan ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaoling Ren Zhenfu Luo Shuyu Qin Xinqian Shu Yuanyuan Zhang A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
description	Abstract To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to China’s air quality standard, SO2, NO2, PM10, PM2.5 and O3 are selected as evaluation indexes to perform the evaluation. The results show that the air quality in this region in 2018 can be divided into three classifications, among which the relatively poor air quality in March, April and May is the first classification, the better air quality in August and September is the third classification, and the air quality in other months falls under the second classification. Correlation analysis is used to qualitatively determine that these three classifications correspond to first-level air quality in China’s air quality standard, and the correlation degree, which is the distance between the three classifications and the first-level air quality, is quantitatively determined. Specifically, the correlation degrees of the first-classification, second-classification and third-classification of air quality are 0.674, 0.697 and 0.71, respectively. The research results indicate potential directions and objectives for air quality management to achieve scientific management.
format	article
author	Xiaoling Ren Zhenfu Luo Shuyu Qin Xinqian Shu Yuanyuan Zhang
author_facet	Xiaoling Ren Zhenfu Luo Shuyu Qin Xinqian Shu Yuanyuan Zhang
author_sort	Xiaoling Ren
title	A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
title_short	A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
title_full	A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
title_fullStr	A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
title_full_unstemmed	A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
title_sort	new method for evaluating air quality using an ideal grey close function cluster correlation analysis method
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/cd2bb779b73a401ebe42850079ced7b5
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A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method

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