Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach

Although China’s total industrial wastewater discharge (IWD) has shown a downward trend in recent years, it is still at a relatively high level. Based on the panel data gathered from 30 Chinese provinces from 2000 to 2017, this study attempts to investigate the spatial characteristics and influentia...

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Autores principales:	Yan Bu, Erda Wang, Ziyu Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Industrial wastewater discharge Spatial autocorrelation test Spatial econometric approach China Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/4487a4cc70fd4aa1995450aad669a310
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spelling	oai:doaj.org-article:4487a4cc70fd4aa1995450aad669a3102021-12-01T04:39:17ZEvaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach1470-160X10.1016/j.ecolind.2020.107219https://doaj.org/article/4487a4cc70fd4aa1995450aad669a3102021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20311584https://doaj.org/toc/1470-160XAlthough China’s total industrial wastewater discharge (IWD) has shown a downward trend in recent years, it is still at a relatively high level. Based on the panel data gathered from 30 Chinese provinces from 2000 to 2017, this study attempts to investigate the spatial characteristics and influential factors which could potentially pose primary contribution to the IWD. Specifically, the spatial autocorrelation test is used to depict the spatial characteristics of IWD. All statistical test results seem to support that using the spatial Durbin model (SDM) with spatial and time period fixed effects could be properly utilized in assessing over the factors of being considered of affecting the IWD. Those assumed factors involve with economic development, population growth, industrial structure, intensity of environmental governance and the level of technological innovation. The results show that the provincial industrial wastewater effluents exhibit a significant spatial autocorrelation as well as agglomeration characteristics. The relationship between IWD and GDP shows up an inverted U-shape, suggesting a typical dynamic of the Environmental Kuznets Curve (EKC). Perhaps, due to a lagging effect, the government’s investments in IWD governance at the current stage is somehow positively correlated with the volume of IWD while technological innovation and industrial structure are negatively correlated with IWD, and yet it appears no connection between population growth and IWD. Furthermore, the estimated direct and indirect effects indicate that economic development, technological innovation, and environmental governance intensity all impose negative spatial spillover effects on IWD. However, it seems to present a significant positive spatial spillover effect being exerted by the industrial structure. Accordingly, we put forward the general measures and specific measures to address China’s IWD problems.Yan BuErda WangZiyu JiangElsevierarticleIndustrial wastewater dischargeSpatial autocorrelation testSpatial econometric approachChinaEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107219- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Industrial wastewater discharge Spatial autocorrelation test Spatial econometric approach China Ecology QH540-549.5
spellingShingle	Industrial wastewater discharge Spatial autocorrelation test Spatial econometric approach China Ecology QH540-549.5 Yan Bu Erda Wang Ziyu Jiang Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
description	Although China’s total industrial wastewater discharge (IWD) has shown a downward trend in recent years, it is still at a relatively high level. Based on the panel data gathered from 30 Chinese provinces from 2000 to 2017, this study attempts to investigate the spatial characteristics and influential factors which could potentially pose primary contribution to the IWD. Specifically, the spatial autocorrelation test is used to depict the spatial characteristics of IWD. All statistical test results seem to support that using the spatial Durbin model (SDM) with spatial and time period fixed effects could be properly utilized in assessing over the factors of being considered of affecting the IWD. Those assumed factors involve with economic development, population growth, industrial structure, intensity of environmental governance and the level of technological innovation. The results show that the provincial industrial wastewater effluents exhibit a significant spatial autocorrelation as well as agglomeration characteristics. The relationship between IWD and GDP shows up an inverted U-shape, suggesting a typical dynamic of the Environmental Kuznets Curve (EKC). Perhaps, due to a lagging effect, the government’s investments in IWD governance at the current stage is somehow positively correlated with the volume of IWD while technological innovation and industrial structure are negatively correlated with IWD, and yet it appears no connection between population growth and IWD. Furthermore, the estimated direct and indirect effects indicate that economic development, technological innovation, and environmental governance intensity all impose negative spatial spillover effects on IWD. However, it seems to present a significant positive spatial spillover effect being exerted by the industrial structure. Accordingly, we put forward the general measures and specific measures to address China’s IWD problems.
format	article
author	Yan Bu Erda Wang Ziyu Jiang
author_facet	Yan Bu Erda Wang Ziyu Jiang
author_sort	Yan Bu
title	Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
title_short	Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
title_full	Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
title_fullStr	Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
title_full_unstemmed	Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach
title_sort	evaluating spatial characteristics and influential factors of industrial wastewater discharge in china: a spatial econometric approach
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/4487a4cc70fd4aa1995450aad669a310
work_keys_str_mv	AT yanbu evaluatingspatialcharacteristicsandinfluentialfactorsofindustrialwastewaterdischargeinchinaaspatialeconometricapproach AT erdawang evaluatingspatialcharacteristicsandinfluentialfactorsofindustrialwastewaterdischargeinchinaaspatialeconometricapproach AT ziyujiang evaluatingspatialcharacteristicsandinfluentialfactorsofindustrialwastewaterdischargeinchinaaspatialeconometricapproach
_version_	1718405838326988800

Evaluating spatial characteristics and influential factors of industrial wastewater discharge in China: A spatial econometric approach

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