Industrial Water-Use Efficiency Under the Dual Constraints of Resources and Environment: An Empirical Study Based on SBM-Undesirable and Meta-Frontier Models

2020 ◽  
pp. 305-330
Author(s):  
Jing Li ◽  
Xiaocan Ma
Keyword(s):  
Empirical Study ◽  
Water Use Efficiency ◽  
Water Use ◽  
Industrial Water ◽  
Industrial Water Use ◽  
Use Efficiency ◽  
Dual Constraints

scholarly journals Evaluation of industrial water use efficiency considering pollutant discharge in China

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0221363 ◽  
Author(s):  
Rongrong Xu ◽  
Yongxiang Wu ◽  
Gaoxu Wang ◽  
Xuan Zhang ◽  
Wei Wu ◽  
...  
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Industrial Water ◽  
Industrial Water Use ◽  
Use Efficiency ◽  
Pollutant Discharge

A study of industrial relative water use efficiency of Beijing: an application of data envelopment analysis

Water Policy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 326-343 ◽  
Author(s):  
Hongrui Wang ◽  
Hongli Liu ◽  
Cheng Wang ◽  
Ying Bai ◽  
Linlin Fan
Keyword(s):  
Data Envelopment Analysis ◽  
Water Use Efficiency ◽  
Water Use ◽  
Data Envelopment ◽  
Industrial Water ◽  
Efficiency Improvement ◽  
Evaluation Scheme ◽  
Industrial Water Use ◽  
Relative Water ◽  
Use Efficiency

Abstract Evaluating and improving water use efficiency is considered one of the main ways of tackling water shortage challenges in water-scarce cities. A useful indicator for evaluating industrial water use efficiency is the relative water use efficiency (RWUE). In this paper, an industrial RWUE evaluation scheme is proposed based on data envelopment analysis (DEA) theory. In this scheme, the RWUE is divided into overall efficiency (OE), pure technical efficiency (PTE), and scale efficiency (SE). In order to help decision-makers specify the focal industry of efficiency improvement, direct water use is distinguished from indirect water use. By employing this industrial RWUE evaluation scheme, this research calculated the industrial RWUEs for 25 representative industries of Beijing (1990–2010). Results show that the OE, PTE, and SE of Beijing have improved significantly. In the primary industry, the scale adjustment fundamentally lifted OE. For the secondary industries, there still exists much room for water use efficiency improvement in technical innovation. Some emerging tertiary industries replaced traditional tertiary industries as the most efficient water users. This study serves as a valuable reference for the implementation of the Strictest Administration of Water Resources (SAWR) of China, and provides policy-makers worldwide with a useful framework of understating industrial water use efficiency.

A Hybrid ARIMA and BP Neural Network Model to Forecast Industrial Water Use Efficiency

2014 ◽  
Vol 1010-1012 ◽  
pp. 1042-1046
Author(s):  
Xing Hua Fan ◽  
Cheng Ning
Keyword(s):  
Neural Network ◽  
Water Use Efficiency ◽  
Water Use ◽  
Hybrid Model ◽  
Network Model ◽  
Neural Network Model ◽  
Back Propagation ◽  
Industrial Water ◽  
Industrial Water Use ◽  
Use Efficiency

Accurate prediction of water use efficiency is very important to water management.We proposed a hybrid autoregressive integrated moving average (ARIMA) and Back Propagation (BP) neural network model to predict industrial water use efficiency. The procedure of the hybrid model consisted three steps: linear modelling, nonlinear modelling and combining. Jiangsu province was selected as a case study area. Empirical results show good fitness of the hybrid model. Based on the empirical forecasting results, policy suggestions are provided to strengthen management of water resources.

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