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A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and sat...

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Detalles Bibliográficos
Autores principales: Zhao, Shen, Dong, Guanpeng, Xu, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013981/
https://www.ncbi.nlm.nih.gov/pubmed/31963735
http://dx.doi.org/10.3390/ijerph17020629
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author Zhao, Shen
Dong, Guanpeng
Xu, Yong
author_facet Zhao, Shen
Dong, Guanpeng
Xu, Yong
author_sort Zhao, Shen
collection PubMed
description Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and satellite data being used in social and environmental studies, fine spatial- and temporal-resolution measures of urban expansion and environmental quality are increasingly available. This, in turn, offers great opportunities to uncover the potential environmental impacts of fast urban expansion. This paper investigated the relationship between urban expansion and pollutant emissions in the Fujian province of China by building a Bayesian spatio-temporal autoregressive model. It drew upon recently compiled pollutant emission data with fine spatio-temporal resolution, long temporal coverage, and multiple sources of remote sensing data. Our results suggest that there was a significant relationship between urban expansion and pollution emission intensity—urban expansion significantly elevated the PM(2.5) and NO(x) emissions intensity in Fujian province during 1995–2015. This finding was robust to different measures of urban expansion and retained after controlling for potential confounding effects. The temporal evolution of pollutant emissions, net of covariate effects, presented a fluctuation pattern rather than a consistent trend of increasing or decreasing. Spatial variability of the pollutant emissions intensity among counties was, however, decreasing steadily with time.
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spelling pubmed-70139812020-03-09 A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province Zhao, Shen Dong, Guanpeng Xu, Yong Int J Environ Res Public Health Article Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and satellite data being used in social and environmental studies, fine spatial- and temporal-resolution measures of urban expansion and environmental quality are increasingly available. This, in turn, offers great opportunities to uncover the potential environmental impacts of fast urban expansion. This paper investigated the relationship between urban expansion and pollutant emissions in the Fujian province of China by building a Bayesian spatio-temporal autoregressive model. It drew upon recently compiled pollutant emission data with fine spatio-temporal resolution, long temporal coverage, and multiple sources of remote sensing data. Our results suggest that there was a significant relationship between urban expansion and pollution emission intensity—urban expansion significantly elevated the PM(2.5) and NO(x) emissions intensity in Fujian province during 1995–2015. This finding was robust to different measures of urban expansion and retained after controlling for potential confounding effects. The temporal evolution of pollutant emissions, net of covariate effects, presented a fluctuation pattern rather than a consistent trend of increasing or decreasing. Spatial variability of the pollutant emissions intensity among counties was, however, decreasing steadily with time. MDPI 2020-01-18 2020-01 /pmc/articles/PMC7013981/ /pubmed/31963735 http://dx.doi.org/10.3390/ijerph17020629 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Shen
Dong, Guanpeng
Xu, Yong
A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title_full A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title_fullStr A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title_full_unstemmed A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title_short A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province
title_sort dynamic spatio-temporal analysis of urban expansion and pollutant emissions in fujian province
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013981/
https://www.ncbi.nlm.nih.gov/pubmed/31963735
http://dx.doi.org/10.3390/ijerph17020629
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