Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China

With the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control wa...

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Main Authors: Min An, Weijun He, Dagmawi Mulugeta Degefu, Zaiyi Liao, Zhaofang Zhang, Liang Yuan
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:http://www.mdpi.com/1660-4601/15/9/1892
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spelling doaj-ca449943f453442fa49eb8c2087f2d2d2020-11-24T21:23:20ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012018-08-01159189210.3390/ijerph15091892ijerph15091892Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in ChinaMin An0Weijun He1Dagmawi Mulugeta Degefu2Zaiyi Liao3Zhaofang Zhang4Liang Yuan5Business School, Hohai University, Nanjing 211100, ChinaCollege of Economics & Management, Three Gorges University, Yichang 443002, ChinaFaculty of Engineering and Architectural Science, Ryerson University, Toronto, ON M5B 2K3, CanadaFaculty of Engineering and Architectural Science, Ryerson University, Toronto, ON M5B 2K3, CanadaBusiness School, Hohai University, Nanjing 211100, ChinaCollege of Economics & Management, Three Gorges University, Yichang 443002, ChinaWith the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control water pollution. Based on the input and output urban wastewater treatment data of the 31 provinces of mainland China for the period 2011–2015, the spatial variation of urban water pollution and the efficiency of wastewater treatment plants were measured and mapped. The exploratory spatial data analysis (ESDA) model and super-efficiency data envelopment analysis (DEA) combined Malmquist index were used to achieve this goal. The following insight was obtained from the results. (1) The intensity of urban wastewater discharge increased, and the urban wastewater discharge showed a spatial agglomeration trend for the period 2011 to 2015. (2) The average inefficiency of wastewater treatment plants (WWTPs) for the study period was 39.2%. The plants’ efficiencies worsened from the eastern to western parts of the country. (3) The main reasons for the low efficiency were the lack of technological upgrade and scale-up. The technological upgrade rate was −4.8%, while the scale efficiency increases as a result of scaling up was −0.2%. Therefore, to improve the wastewater treatment efficiency of the country, the provinces should work together to increase capital investment and technological advancement.http://www.mdpi.com/1660-4601/15/9/1892spatial patternurban wastewater treatment plantstreatment efficiencydata envelopment analysisexploratory spatial data analysis
collection DOAJ
language English
format Article
sources DOAJ
author Min An
Weijun He
Dagmawi Mulugeta Degefu
Zaiyi Liao
Zhaofang Zhang
Liang Yuan
spellingShingle Min An
Weijun He
Dagmawi Mulugeta Degefu
Zaiyi Liao
Zhaofang Zhang
Liang Yuan
Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
International Journal of Environmental Research and Public Health
spatial pattern
urban wastewater treatment plants
treatment efficiency
data envelopment analysis
exploratory spatial data analysis
author_facet Min An
Weijun He
Dagmawi Mulugeta Degefu
Zaiyi Liao
Zhaofang Zhang
Liang Yuan
author_sort Min An
title Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
title_short Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
title_full Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
title_fullStr Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
title_full_unstemmed Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China
title_sort spatial patterns of urban wastewater discharge and treatment plants efficiency in china
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2018-08-01
description With the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control water pollution. Based on the input and output urban wastewater treatment data of the 31 provinces of mainland China for the period 2011–2015, the spatial variation of urban water pollution and the efficiency of wastewater treatment plants were measured and mapped. The exploratory spatial data analysis (ESDA) model and super-efficiency data envelopment analysis (DEA) combined Malmquist index were used to achieve this goal. The following insight was obtained from the results. (1) The intensity of urban wastewater discharge increased, and the urban wastewater discharge showed a spatial agglomeration trend for the period 2011 to 2015. (2) The average inefficiency of wastewater treatment plants (WWTPs) for the study period was 39.2%. The plants’ efficiencies worsened from the eastern to western parts of the country. (3) The main reasons for the low efficiency were the lack of technological upgrade and scale-up. The technological upgrade rate was −4.8%, while the scale efficiency increases as a result of scaling up was −0.2%. Therefore, to improve the wastewater treatment efficiency of the country, the provinces should work together to increase capital investment and technological advancement.
topic spatial pattern
urban wastewater treatment plants
treatment efficiency
data envelopment analysis
exploratory spatial data analysis
url http://www.mdpi.com/1660-4601/15/9/1892
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