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Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies

With the increase in global environmental pollution, it is important to understand the concentration characteristics and correlations with other pollutants of atmospheric particulate matter as affected by relevant policies. The data presented in this paper were obtained at monitoring stations in Xi’...

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Detalles Bibliográficos
Autores principales: Song, Hong, Dong, Yuhang, Yang, Jiayu, Zhang, Xin, Nie, Xingxin, Fan, Yuesheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858673/
https://www.ncbi.nlm.nih.gov/pubmed/36673805
http://dx.doi.org/10.3390/ijerph20021051
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author Song, Hong
Dong, Yuhang
Yang, Jiayu
Zhang, Xin
Nie, Xingxin
Fan, Yuesheng
author_facet Song, Hong
Dong, Yuhang
Yang, Jiayu
Zhang, Xin
Nie, Xingxin
Fan, Yuesheng
author_sort Song, Hong
collection PubMed
description With the increase in global environmental pollution, it is important to understand the concentration characteristics and correlations with other pollutants of atmospheric particulate matter as affected by relevant policies. The data presented in this paper were obtained at monitoring stations in Xi’an, China, in the years from 2016 to 2020, and the spatial distribution characteristics of the mass and quantity concentrations of particulate matter in the atmosphere, as well as its correlation with other pollutants, were analyzed in depth. The results showed that the annual average concentrations of PM(10) and PM(2.5) decreased year by year from 2016 to 2020. The annual concentrations of PM(2.5) decreased by 20.3 μg/m(3), and the annual concentrations of PM(10) decreased by 47.3 μg/m(3). The days with concentrations of PM(10) exceeding the standards decreased by 82 days, with a decrease of 66.7%. The days with concentrations of PM(2.5) exceeding the standards decreased by 40 days, with a decrease of 35.4%. The concentration values of PM(10) and PM(2.5) were roughly consistent with the monthly and daily trends. The change in monthly concentrations was U-shaped, and the change in daily concentrations showed a double-peak behavior. The highest concentrations of particulate matter appeared at about 8:00~9:00 am and 11:00 pm, and they were greatly affected by human activity. The proportion of particles of 0~1.0 μm decreased by 1.94%, and the proportion of particles of 0~2.5 μm decreased by 2.00% from 2016 to 2020. A multivariate linear regression model to calculate the concentrations of the pollutants was established. This study provides a reference for the comprehensive analysis and control of air pollutants in Xi’an and even worldwide.
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spelling pubmed-98586732023-01-21 Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies Song, Hong Dong, Yuhang Yang, Jiayu Zhang, Xin Nie, Xingxin Fan, Yuesheng Int J Environ Res Public Health Article With the increase in global environmental pollution, it is important to understand the concentration characteristics and correlations with other pollutants of atmospheric particulate matter as affected by relevant policies. The data presented in this paper were obtained at monitoring stations in Xi’an, China, in the years from 2016 to 2020, and the spatial distribution characteristics of the mass and quantity concentrations of particulate matter in the atmosphere, as well as its correlation with other pollutants, were analyzed in depth. The results showed that the annual average concentrations of PM(10) and PM(2.5) decreased year by year from 2016 to 2020. The annual concentrations of PM(2.5) decreased by 20.3 μg/m(3), and the annual concentrations of PM(10) decreased by 47.3 μg/m(3). The days with concentrations of PM(10) exceeding the standards decreased by 82 days, with a decrease of 66.7%. The days with concentrations of PM(2.5) exceeding the standards decreased by 40 days, with a decrease of 35.4%. The concentration values of PM(10) and PM(2.5) were roughly consistent with the monthly and daily trends. The change in monthly concentrations was U-shaped, and the change in daily concentrations showed a double-peak behavior. The highest concentrations of particulate matter appeared at about 8:00~9:00 am and 11:00 pm, and they were greatly affected by human activity. The proportion of particles of 0~1.0 μm decreased by 1.94%, and the proportion of particles of 0~2.5 μm decreased by 2.00% from 2016 to 2020. A multivariate linear regression model to calculate the concentrations of the pollutants was established. This study provides a reference for the comprehensive analysis and control of air pollutants in Xi’an and even worldwide. MDPI 2023-01-06 /pmc/articles/PMC9858673/ /pubmed/36673805 http://dx.doi.org/10.3390/ijerph20021051 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Song, Hong
Dong, Yuhang
Yang, Jiayu
Zhang, Xin
Nie, Xingxin
Fan, Yuesheng
Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title_full Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title_fullStr Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title_full_unstemmed Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title_short Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies
title_sort concentration characteristics and correlations with other pollutants of atmospheric particulate matter as affected by relevant policies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9858673/
https://www.ncbi.nlm.nih.gov/pubmed/36673805
http://dx.doi.org/10.3390/ijerph20021051
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