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Wastewater treatment plants (WWTPs) play a pivotal role in natural water recycling and safeguarding the water security of approximately 42% of the world's population, yet they confront challenges posed by escalating energy consumption and regional energy constraints. In this study, we developed an evaluation framework that integrated regional energy scarcity with the operation conditions of WWTPs to quantify their energy efficiencies by applying multiregional input–output (MRIO) analysis and data envelopment analysis (DEA). A case study using this framework was conducted on 3776 WWTPs in 30 provinces in China. The results showed that the average scarcity-based energy efficiency level of WWTPs in China was low, of which those in northern provinces were higher compared to southeastern provinces. Furthermore, only 24 WWTPs in China attained the highest efficiency levels, while the rest had different degrees of input redundancy, indicating an energy-saving potential of 9.05 × 109 kWh. This paper enables the development of optimal efficiency strategies for WWTPs in different provinces considering the potential energy scarcity risks caused by trading activities. • The DEA and MRIO analyses were combined for 3776 WWTPs in China. • Efficiency evaluation index was modified considering energy scarcity levels. • Scarcity-based energy efficiency assessment framework for WWTPs was developed. [ABSTRACT FROM AUTHOR]

Improving energy efficiency has been recognized as the most effective way to reduce the greenhouse effect and achieve sustainable development. From the perspective of air emissions, this paper adopts data envelopment analysis approach to evaluate the energy efficiency in China’s coastal areas over the period of 2000–2012. Carbon dioxide, sulfur dioxide and nitrogen oxide are treated as undesirable outputs of energy consumptions. The proposed global Epsilon-based measure is used to estimate the static energy efficiency with an annual cross-section of data. The weights of the three undesirable outputs are determined according to their treatment costs. A global Malmquist-Luenberger productivity index based on directional distance function is employed to dynamically evaluate the energy efficiency. The results indicate the following in China’s coastal areas: (1) the level of economic development is positively related to energy efficiency scores; (2) energy efficiency scores decrease when considering undesirable outputs except Beijing and Hainan; (3) the Circum-Bohai Sea Economic Region greatly improves energy efficiency and has great potential of air emission; (4) the annual growth rate of Malmquist-Luenberger productivity index change is overestimated; (5) energy efficiency improvement is mainly driven by technological improvement, and scale efficiency and management level are the main obstacles. [ABSTRACT FROM AUTHOR]

The use of data envelopment analysis (DEA) in China’s regional energy efficiency and carbon emission efficiency (EE&CE) assessment has received increasing attention in recent years. This paper conducted a comprehensive survey of empirical studies published in 2006–2015 on China’s regional EE&CE assessment using DEA-type models. The main features used in previous studies were identified, and then the methodological framework for deriving the EE&CE indicators as well as six widely used DEA models were introduced. These DEA models were compared and applied to measure China’s regional EE&CE in 30 provinces/regions between 1995 and 2012. The empirical study indicates that China’s regional EE&CE remained stable in the 9th Five Year Plan (1996–2000), then decreased in the 10th Five Year Plan (2000–2005), and increased a bit in the 11th Five Year Plan (2006–2010). The east region of China had the highest EE&CE while the central area had the lowest. By way of conclusion, some useful points relating to model selection are summarized from both methodological and empirical aspects. [ABSTRACT FROM AUTHOR]

• The new power supply structure resulting from the new policy has been considered. • The new models project the inefficient points onto a more realistic efficient frontier. • The new models have the power to allocate the shared resources. • Results show that the power production stage is allocated less shared resources. • The power sale stage's efficiency is lower than the one of power production stage. To relieve the problems of energy shortage and environmental pollution, many countries have implemented a variety of policies to improve the energy efficiency of the power industry. To understand the impacts of such policies on energy efficiency, this paper constructs novel network data envelopment analysis models to recognize the policy-induced structural changes in the power system. Compared with previous studies, the new models project the inefficient points onto a more realistic efficient production frontier, considering how the distribution proportion of shared resources will change when the power system, modeled as a power generation stage and a power sale stage, is led by the latter stage. Our empirical study on China's power system shows that the province of Guangdong and the eastern region of China perform best, and all power production stages perform better than the corresponding power sale stages. The development of the two power subsystems in the four regions is unbalanced. More than half of the power supply systems choose to allocate more proportion of the shared resources to the sale stage rather than use a more balanced distribution between the two stages. [ABSTRACT FROM AUTHOR]

Abstract: Evaluation of the energy and emissions efficiency of Chinese regions has recently attracted increasing interest. A number of previous studies have contributed to the measurement of energy efficiency using various types of data envelopment analysis (DEA) techniques. However, most of these DEA-based energy efficiency analyses were restricted to the radial expansions of outputs or radial contractions of inputs. In this paper, we utilize the multi-directional efficiency analysis (MEA) approach instead of the traditional radial DEA to investigate Chinese regional energy and emissions efficiency. Since MEA selects benchmarks such that the input contractions or output expansions are proportional to the potential improvement identified by considering the improvement potential in each input or output variable separately, not just the efficiency status but also the efficiency patterns of different Chinese regions and areas can be detected. The empirical study results indicate that, in general, the MEA efficiency of China experienced an increasing process over the study period 1997–2010; the east area overall is more MEA efficient than the central area and the west area of China during the study period; the significant higher MEA efficiency of the east area to the central area and the west area are due to both the higher energy specific efficiency and the higher emissions specific efficiency of the east area compared to the other two areas; the provinces of Hebei, Shanxi, Inner Mongolia, Shandong, Henan, and Hubei etc. have both high energy saving potentials and high emissions reduction potentials, thus they will play the most important roles in China’s effort on energy conservation and CO2 emissions mitigation. [Copyright &y& Elsevier]

Abstract: This paper uses nonparametric efficiency analysis technique to estimate the energy efficiency, potential emission reductions and marginal abatement costs of energy-related CO2 emissions in China. We employ a non-radial slacks-based data envelopment analysis (DEA) model for estimating the potential reductions and efficiency of CO2 emissions for China. The dual model of the slacks-based DEA model is then used to estimate the marginal abatement costs of CO2 emissions. An empirical study based on China’s panel data (2001–2010) is carried out and some policy implications are also discussed. [Copyright &y& Elsevier]

• A data envelopment analysis model was built to assess the operation energy efficiency. • Wastewater treatment plants' distances from effective level were compared. • Disparities of results among regions and treatment processes adopted are evident. The energy use intensity of wastewater treatment facilities has been increasing in recent decades in China. In this paper, data envelopment analysis is used to evaluate the energy efficiency of municipal wastewater treatment plants (WWTPs) in China. In the DEA model, the six input indicators were load rate, design scale, unit electricity consumption, sludge generation, actual treatment volume and accumulated electricity consumption, and the six outputs were COD, BOD, SS, NH 3 -N, TN and TP pollutant removals per amount of electricity consumption. A total of 4100 plants were assessed in China in 2018. The relative efficiencies of 14 plants at 1.0, with an average electricity consumption of 0.091 kWh/m3 compared to the national average consumption of 0.38 kWh/m3, served as a benchmark for the remaining inefficient plants. According to the Malmquist index results, during 2014–2018, on average, 40.54% of the WWTPs experienced productivity improvements, 71.24% of the plants increased their technical efficiency relative to the frontier, and 27.21% of the plants showed progress on the production frontier. Western areas in China consume a large proportion of renewable energy with higher energy efficiency levels, while central and eastern areas had lower energy efficiency trends and high pollutant emissions levels. The oxidation pond method has the highest comprehensive technical efficiency of 0.446, nearly eight times the average efficiency level. It is suggested that wastewater treatment industries should not only consider technical efficiency increases but also match their pollutant burdens and implementation of discharge standards with energy-saving targets. [ABSTRACT FROM AUTHOR]

• Energy & environmental inefficiency of the 45 cities in China is analyzed. • Variable-specific productivity growth measures are used. • Bounded-adjusted Measure and Luenberger Productivity Indicator are applied. • Dagum Gini coefficient is employed to measure the regional disparities of energy use. • Policy guidelines are presented based on the productivity change directions. Analyzing green transformation of energy use and pollutant emissions in China's "Three Regions and Ten Urban Agglomerations" (TRTAs) allows effectively promoting sustainable development in the country. This paper applies Data Envelopment Analysis, namely the Bounded-adjusted Measure (BAM) relying on the additive structure, to measure the technical inefficiency and productivity change across TRTAs in China. The technical inefficiency and productivity change observed for TRTAs are 0.29 and 2.29% respectively. The decomposition results indicate that industrial energy consumption, industrial sulfur dioxide (SO 2), and industrial soot & dust emissions are the main variables causing TRTAs' industrial operation inefficiency. Spatially, environmental inefficiency of the above-mentioned three variables in North China Urban Agglomeration (NA) is higher than those in Northwest, Yangtze and Pearl River Delta Urban Agglomerations (NWA, YRDA, and PRDA respectively). Decomposition of the Gini coefficient shows that the performance associated with the three variables varies among the regions with intra-regional differentiation of the PRDA being the highest. Given the regional patterns in productivity change, more efforts should be directed towards improving technical progress on industrial energy conservation in NWA. Furthermore, regulations on industrial air pollutant emissions, joint mitigation and monitoring of the key indicators in PRDA should also be emphasized. [ABSTRACT FROM AUTHOR]

• Multi-tier heterogeneities can be assessed by the proposed decomposition framework. • Technology progress were mainly responsible for lowering energy intensity. • Regional equilibrium development did not significantly narrow the technology gap. • Industrial reorganization had opposite effect in narrow energy and output technology gap. • Contributions of various factors on energy intensity were differed across provinces. This paper proposed a novel meta-frontier multi-tier approach which can reveal the impacts of industrial structure reorganization, regional equilibrium development, and management efficiency on energy intensity change. China's energy intensity was used to demonstrate the proposed approach. Based on the empirical results, this study found that during 2000–2016, China's energy intensity witnessed a considerable decline. Potential energy intensity change and technological progress were the dominant contributors responsible for lowering energy intensity. In addition to conventional factors, the new provided six factors also have important impacts on energy intensity during the study years. First, the output-oriented industrial technological gap facilitated to lower energy intensity, while the energy-oriented industrial technological gap slightly impeded energy intensity decline. Second, the regional technological gap impeded energy intensity decline, indicating that China's efforts of regional equilibrium development failed to narrow the energy-saving technology gap between regions. Third, energy-oriented pure technical efficiency decreased energy intensity, while output-oriented pure technical efficiency increased energy intensity. It implies that management efficiency in energy market was optimized, however, there exist management inefficiency in output market. Over multiple spatial scales, the performances of different factors were distinctly various, local governments should establish and implement policies tailored to their characteristics. [ABSTRACT FROM AUTHOR]