Evaluating the recycling efficiency of industrial water use systems in China: Basin differences and factor analysis

Zhuang, Yuan; Zhang, Lina; Chiu, Yung‐ho; Guo, Zhansheng; Chu, Yu; Du, Xinya

doi:10.1016/j.jenvman.2022.115313

Cited by 21 publications

(5 citation statements)

References 41 publications

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“…In the past, because of the lack of effective supervision, there was a significant investment in industrial water consumption, accompanied by serious waste. At present, the country has taken the Yangtze River Economic Belt as a pilot demonstration zone for ecological protection [44].…”

Section: Results Of Iwguementioning

confidence: 99%

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Research on the Effects of Different Environmental Regulation Tools on China’s Industrial Water Green Use Efficiency—Comparison between the Yellow River Basin and the Yangtze River Economic Belt

Yang,

Liu,

Khan

2024

Sustainability

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Improving industrial water green use efficiency (IWGUE) is a primary means to ensure the production, living, and ecological use of water quantity and quality, while effective environmental regulation tools are important to promote efficiency. This paper calculates the industrial water green use efficiency in China’s 30 provinces from 2010 to 2022 by the SE-SBM model and divides environmental regulatory tools into command-based, market-oriented, and voluntary types. The panel Tobit model is constructed to test the impact and differences in the effects of three environmental regulations on regional industrial water green use efficiency. The results show the following: (1) Under the constraint of undesired output, IWGUE fluctuates upward slowly in China, and the potential for improving the efficiency value is enormous, with significant regional and basin-level differences. (2) At the national level, the impact of command-based and market-oriented environmental regulations on IWGUE shows a U-shaped trend, while the positive promoting effect of voluntary environmental regulations on efficiency is not significant. (3) In the Yellow River Basin, the impact of three types of environmental regulations on IWGUE shows a U-shaped pattern. Command-based and voluntary environmental regulations have crossed the inflection point and have a significant promoting effect on efficiency, while market-oriented environmental regulations have not yet crossed the inflection point. (4) In the Yangtze River Economic Belt, the impact of command-based and market-oriented environmental regulations on IWGUE shows a U-shaped pattern, while voluntary environmental regulations have a significant promoting effect on efficiency. This study may provide a reference for tailored policy design to improve industrial water efficiency in China from the perspective of environmental regulations.

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Section: Results Of Iwguementioning

confidence: 99%

“…Sustainability 2024, 16, x FOR PEER REVIEW 9 of 16 industrial water consumption, accompanied by serious waste. At present, the country has taken the Yangtze River Economic Belt as a pilot demonstration zone for ecological protection [44].…”

Section: Results Of Iwguementioning

confidence: 99%

Research on the Effects of Different Environmental Regulation Tools on China’s Industrial Water Green Use Efficiency—Comparison between the Yellow River Basin and the Yangtze River Economic Belt

Yang,

Liu,

Khan

2024

Sustainability

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“…Many studies have found that economic development, environmental awareness, and spatial variation characteristics are the main drivers of industrial wastewater, , which directly affects water quality . More factors affect the investment in industrial wastewater pollution treatment .…”

Section: Resultsmentioning

confidence: 99%

Machine Learning-Based Predominant Driving Factors Impacting Urban Industrial Wastewater Discharge in the Yellow River Basin

Xia

Dai

et al. 2023

ACS EST Water

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Environmental pollution control has become an important task of ecological protection, which is one of the major strategies for high-quality development of the Yellow River basin (YRB) in China. In this paper, a machine learning model is constructed to explore the driving factors that affect industrial wastewater discharge (IWD) in prefecture-level cities in the YRB. On the basis of statistical data from 2003 to 2018, the relationship between IWD and gross regional product in the YRB obeyed the Environmental Kuznets Curve (EKC) and reached an inflection point in 2010, but not all cities fit the EKC. Therefore, three machine learning algorithms, including weighted k-nearest neighbor (knn), random forest, and support vector machine, are used to construct a regression model of IWD. The knn achieved the best fitting, with determination coefficients (R 2 ) of 0.98 and 0.91 in the training and testing sets, respectively. Variable importance and partial dependence plots explain the machine learning model well. This work provides ideas for the management of IWD in prefecture-level cities in the YRB and references for environmental pollution in other cities.

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“…Secondly, according to local conditions, promote the upgrading of the industrial structure of cities, develop a circular economy within the river basin, and comprehensively promote water conservation and pollution control [26]. Strictly implement the relevant national industrial policies and environmental policies, combine the actual conditions of the city to effectively promote the integration of informatization and industrialization, increase the effective embedding of advanced production factors into the local industrial base, and vigorously develop resource-saving and environmentally friendly modern manufacturing and service industries, establish and improve a modern industrial system guided by green ecology, and increase the output contribution rate of human resources and intellectual capital; vigorously promote ecological treatment and restoration technologies according to the actual conditions of regional cities, and improve the circular economy in the basin, in the process of urban development and industrial upgrading, establish the idea of focusing on the process of water pollution prevention and combine it with terminal treatment, and encourage enterprises to implement cleaner production and water recycling; improve urban pipe network transformation and promotion of water-saving appliances, meanwhile, speed up the construction of urban domestic sewage treatment and reclaim water utilization facilities, and promote the recycling of sewage.…”

Section: Discussionmentioning

confidence: 99%

Research on Spatial Difference, Distribution Dynamics and Influencing Factors of Urban Water-Use Efficiency in the Yellow River Basin

2022

Sustainability

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This study creatively uses the Dagum Gini coefficient, Kernel density estimation, and Markov chain to measure the spatial difference and distribution dynamics of urban water-use efficiency in the Yellow River Basin from 2008 to 2018 accurately and also analyzes its formation mechanism by using the Spatial Durbin Model. The results show that the hypervariable density and the intraregional differences constitute the main source of regional differences in the whole basin; the dynamic evolution characteristics of the urban water-use efficiency distribution in different reaches are different. The spatial factors have a non-negligible impact; the urbanization process and population density spatial spillover effects are negative in the state of spatial interaction; the spillover effect of upgrading the industrial structure is positive; the direct and spillover effects of openness are both positive; and the direct effect of the water-use structure is positive. In order to improve the urban water-use efficiency in the Yellow River Basin, it is necessary to comprehensively promote new urbanization, upgrade industrial structures, promote energy conservation and emission reduction, construct business environments, and establish an inter-regional coordination mechanism.

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Evaluating the recycling efficiency of industrial water use systems in China: Basin differences and factor analysis

Cited by 21 publications

References 41 publications

Research on the Effects of Different Environmental Regulation Tools on China’s Industrial Water Green Use Efficiency—Comparison between the Yellow River Basin and the Yangtze River Economic Belt

Research on the Effects of Different Environmental Regulation Tools on China’s Industrial Water Green Use Efficiency—Comparison between the Yellow River Basin and the Yangtze River Economic Belt

Machine Learning-Based Predominant Driving Factors Impacting Urban Industrial Wastewater Discharge in the Yellow River Basin

Research on Spatial Difference, Distribution Dynamics and Influencing Factors of Urban Water-Use Efficiency in the Yellow River Basin

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