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Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model

Based on 0.01°×0.01° grid data of PM(2.5) annual concentration and statistical yearbook data for 11 cities in Hebei Province from 2000 to 2015, the temporal and spatial distribution characteristics of PM(2.5) in the study area are analysed, the level of intensive land use in the area is evaluated, a...

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Autores principales: Shao, Jingjing, Ge, Jingfeng, Feng, Xiaomiao, Zhao, Chaoran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500636/
https://www.ncbi.nlm.nih.gov/pubmed/32946497
http://dx.doi.org/10.1371/journal.pone.0238547
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author Shao, Jingjing
Ge, Jingfeng
Feng, Xiaomiao
Zhao, Chaoran
author_facet Shao, Jingjing
Ge, Jingfeng
Feng, Xiaomiao
Zhao, Chaoran
author_sort Shao, Jingjing
collection PubMed
description Based on 0.01°×0.01° grid data of PM(2.5) annual concentration and statistical yearbook data for 11 cities in Hebei Province from 2000 to 2015, the temporal and spatial distribution characteristics of PM(2.5) in the study area are analysed, the level of intensive land use in the area is evaluated, and decoupling theory and spatial regression are used to discuss the relationship between PM(2.5) concentration and intensive land use and the influence of intensive land use variables on PM(2.5) in Hebei Province. The results show that 1. In terms of time, the concentration of PM(2.5) in Hebei Province showed an overall upward trend from 2000 to 2015, with the highest in winter and the lowest in summer. The daily variations show double peaks at 8:00–10:00 and 21:00–0:00 and a single valley at 16:00–18:00. 2. In terms of space, the concentration of PM(2.5) in Hebei Province is high in the southeast and low in the northwest, and the pollution spillover initially decreases and then increases. 3. In the past 16 years, the level of intensive land use in Hebei Province has increased annually, but blind expansion still exists. 4. Decoupling theory and the spatial lag model show that land use intensity, land input level and land use structure are positively correlated with PM(2.5) concentration, land output benefit is negatively correlated with PM(2.5) concentration, and PM(2.5) concentration and land intensive use level have not yet been decoupled; thus, the relationship is not harmonious. This research can provide a scientific basis for reducing air pollution and promoting the development of urban land resources for intensive and sustainable development.
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spelling pubmed-75006362020-09-24 Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model Shao, Jingjing Ge, Jingfeng Feng, Xiaomiao Zhao, Chaoran PLoS One Research Article Based on 0.01°×0.01° grid data of PM(2.5) annual concentration and statistical yearbook data for 11 cities in Hebei Province from 2000 to 2015, the temporal and spatial distribution characteristics of PM(2.5) in the study area are analysed, the level of intensive land use in the area is evaluated, and decoupling theory and spatial regression are used to discuss the relationship between PM(2.5) concentration and intensive land use and the influence of intensive land use variables on PM(2.5) in Hebei Province. The results show that 1. In terms of time, the concentration of PM(2.5) in Hebei Province showed an overall upward trend from 2000 to 2015, with the highest in winter and the lowest in summer. The daily variations show double peaks at 8:00–10:00 and 21:00–0:00 and a single valley at 16:00–18:00. 2. In terms of space, the concentration of PM(2.5) in Hebei Province is high in the southeast and low in the northwest, and the pollution spillover initially decreases and then increases. 3. In the past 16 years, the level of intensive land use in Hebei Province has increased annually, but blind expansion still exists. 4. Decoupling theory and the spatial lag model show that land use intensity, land input level and land use structure are positively correlated with PM(2.5) concentration, land output benefit is negatively correlated with PM(2.5) concentration, and PM(2.5) concentration and land intensive use level have not yet been decoupled; thus, the relationship is not harmonious. This research can provide a scientific basis for reducing air pollution and promoting the development of urban land resources for intensive and sustainable development. Public Library of Science 2020-09-18 /pmc/articles/PMC7500636/ /pubmed/32946497 http://dx.doi.org/10.1371/journal.pone.0238547 Text en © 2020 Shao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shao, Jingjing
Ge, Jingfeng
Feng, Xiaomiao
Zhao, Chaoran
Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title_full Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title_fullStr Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title_full_unstemmed Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title_short Study on the relationship between PM(2.5) concentration and intensive land use in Hebei Province based on a spatial regression model
title_sort study on the relationship between pm(2.5) concentration and intensive land use in hebei province based on a spatial regression model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500636/
https://www.ncbi.nlm.nih.gov/pubmed/32946497
http://dx.doi.org/10.1371/journal.pone.0238547
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