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China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

Accurate understanding of the marginal energy-saving costs of energy-using entities is critical for regulatory authorities to formulate and implement energy-saving policies. This article brings out an easy-to-operate analytical framework to measure the marginal energy-saving cost and construct energy conservation supply curve with the help of data envelopment analysis and quantitative model. Furthermore, taking China's pulp and paper industry as an example, the authors discuss the difference of economic costs between industry energy-saving task assignment with and without considering the difference of marginal energy-saving costs of different energy using entities with the help of linear programming model. The main empirical results are as follow. First, there is a big difference in the industrial marginal energy-saving costs in different provinces. The difference between the highest and lowest energy-saving costs is twice as large. Second, the optimal energy-saving task assignment based on an accurate energy conservation supply curve can help to save nearly 35% of total economic cost. • An alternative method of measuring energy conservation cost is provided. • An optimal energy saving task assignment model is constructed. • The problem of trade-off between efficiency and equity in policy making is discussed. [ABSTRACT FROM AUTHOR]

Currently, China is at a critical stage of economic transformation and pollution control. The environmental pollution control efficiency (PCE) deserves more in-depth study. This paper adopts a three-stage global data envelopment analysis (DEA) model and a global Malmquist index model to measure the PCE and the sources of its changes in China from 1991 to 2019. Study shows that: (1) the overall level of PCE has remained low over the past 29 years, and it has a slowly fluctuating upward trend, with an average annual growth rate of only 0.92 %; (2) the lower pure technical efficiency hinders the effectiveness of environmental pollution control, which is mainly affected by the slow technological progress; and (3) at the provincial level, the overall efficiency of Shanghai and Guangxi has long been above 0.9, while the efficiency of other provinces has been below 0.9 for quite a long time. At the regional level, the Yangtze River Delta is the most effective area, while the Yellow River Basin is the most ineffective area. In consideration of this, we provide specific strategies for improving PCE of each province, from three aspects of increasing the capital input, optimizing the scale structure, and upgrading technology level. [Display omitted] [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

The paper introduces a robust methodology for evaluating complex electricity system efficiency, making several contributions. It systematically decomposes the electric power system into various processes, including power generation, transmission, distribution, and power consumption, with parallel sub-processes for production and domestic power consumption. Employing data envelopment analysis (DEA), the paper develops a network directional slacks-based (DSB) model to evaluate the whole system and the internal processes. The model is theoretically proven to be feasible, providing efficiency scores and identifying inefficiencies in the system and its processes. A noteworthy addition is the introduction of the DSB green Luenberger productivity index and its decomposition, offering an analysis of productivity changes in electricity systems. Empirical analysis covering 30 Chinese provinces from 2013 to 2019 uncovers the performance variations among provinces and processes, pointing out inefficiencies and changes in technology and efficiency over time. The empirical findings aim to support efforts in enhancing the overall efficiency of China's interprovincial power system. • We decompose the complex electric power system into four processes with dependence. • We build a network directional slacks-based (DSB) model for the complex power system. • We give a DSB green Luenberger productivity index (DPI) for our network model. • The efficiency score and DPI of the system are decomposed into those of processes. • We apply the model and indexes to electric power systems in Chinese provinces. [ABSTRACT FROM AUTHOR]

This paper examines the effects of HSR development on airport technical efficiency and the labor productivity at airports. Existing literature mainly focuses on the impacts of HSR on passenger traffic. In addition to passengers, HSR development may influence airports' other outputs such as cargo and flight movements together with various inputs. These inputs and outputs collectively determine airports' technical efficiency. With access to a dataset consisting of 46 Chinese airports and 16 Japanese airports from 2007 to 2015, the paper firstly adopts both the standard two-stage Data Envelopment Analysis (DEA) and double bootstrap methods to evaluate the impacts of HSR development on airports' technical efficiency. We then evaluate the effects of HSR on airport labor productivity which is measured by both work-load units per employee and aircraft movements per employee. Our main findings indicate that HSR development relates to a decline in airport efficiency. Airports located in cities that have better connectivity or accessibility in the HSR network suffer more efficiency loss than the others. It is also observed that the locational advantage of HSR stations relative to airports is negatively associated with airport efficiency. By contrast, good intermodal linkage between the airport and its nearest HSR station is positively correlated with airport efficiency. Furthermore, the study reports different results between China and Japan with respect to the effects of HSR on labor productivity. [ABSTRACT FROM AUTHOR]

• Incorporates the technological development into dynamic efficiency analysis. • Develops a new dynamic DEA model with carry-over and accumulation. • Evaluates the provincial industrial production of China. • Studies the spatial correlation of industrial production in China. In actual industrial production, technology shows an accumulative effect that exceeds the corresponding factor endowment in each period. This accumulation effect is accompanied by the whole industrial production and plays an important role in the evolution of industrialization as a bridge. In order to identify the status quo of industrial production more comprehensively, explore the role of technological accumulation in industrial production, and further promote industrialization, this paper constructs a new multi-period dynamic data envelopment analysis model reflecting the effect of technological accumulation. Furthermore, a spatial autocorrelation analysis is conducted to determine the spatial correlation of regional industrial production and to provide a reference for the coordinated development of industry among regions. A case study of China's industries was conducted, and the main results show the following: (1) The average industrial production efficiency is 0.806, and 17% of provinces have a score of less than 0.65. (2) There is an obvious positive spatial autocorrelation evolution trend in regional industrial production; the eastern coastal area is dominated by High-High clustering, and Low-Low clustering is concentrated in the northwest. (3) Technology accumulation aggravates the dispersion degree of regional industrial production efficiency. Finally, policy implications are put forward to promote industrialization and the coordinated development of interregional industry. [ABSTRACT FROM AUTHOR]

Over recent decades, China's economy has continued to develop steadily and rapidly, contributing to a large environmental cost. Therefore, many researchers propose various methods to evaluate environmental efficiency to deal with these serious issues accurately. This paper is the first to evaluate environmental efficiency using a model featuring not only a parallel structure with three component processes (primary, secondary, and tertiary industries) in the first stage but also a sewage treatment process in the second stage. Simultaneously, we propose radial but also nonradial versions of the Environmental Multiple Variable Return to Scale (EMVRS) model. These two models both consider shared inputs as well as shared outputs, and the proportion of the shared inputs and shared outputs utilized in each component process is assumed to be unknown. Additionally, we further analyze the factors influencing environmental efficiency by utilizing the Tobit model. The results when EMVRS is applied to Chinese provinces can be divided into 3 parts: (1) Most provinces do not purify wastewater appropriately contributing to the bad environmental efficiency. (2) The efficiency values of the three industry types are similar or identical to each other in most provinces. (3) The population of people employed negatively impacts environmental efficiency. [ABSTRACT FROM AUTHOR]

As an effective approach in ranking decision making units (DMUs), cross-efficiency evaluation is only extended to two basic network systems: series and parallel, which is not applicable to the common complex network system in reality. By using the directional distance function (DDF), this paper extends the cross-efficiency evaluation to a complex system called the parallel two-stage system, which consists of several independent parallel processes and each of them is a sub-system with a general two-stage series structure. The proposed method is able to decompose the cross-efficiency measure of the system into the weighted average of those of processes, stages and overall stages, respectively, and as a result, successfully achieves the layer-by-layer decomposition of cross-efficiency measures under complex nested networks. An empirical study on 40 open-ended equity funds in China from 2018 to 2020 verifies that the newly proposed method not only has a stronger performance discrimination power than self-evaluation, but also can identify the relationships among efficiencies of the system, processes and stages, and meanwhile it can reflect the effects of processes and stages on the system. More importantly, our method has a better practical value for actual fund investment selection. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the water-energy-food nexus (WEFN) system, focusing on its interlinked structure and dynamic characteristics. This paper proposes a dynamic series-loop data envelopment analysis (DEA) model with a directional distance function for measuring WEFN efficiency in China. A spatial Durbin model is constructed to investigate the impact of extreme temperatures on WEFN efficiency. The results are as follows. (1) Compared with the black-box DEA model and series network DEA model, a series-loop network DEA model can reflect the "networking effect" and "looping effect" in the WEFN system. (2) The WEFN system performs well with an average series-loop efficiency of 0.875, but the efficiency of the water subsystem scores low and needs improvement. (3) At the national level, extremely high and low temperatures have no significant effect on the WEFN efficiency in local or adjacent provinces, whereas average temperature promotes the WEFN efficiency in local provinces but hinders it in neighboring provinces. In the regions with a low temperature difference, average temperature has no impact on the WEFN efficiency of both the province itself and its neighboring provinces. Overall, this study provides valuable insights into the complex interlinkages within the WEFN system and highlights the importance of considering these relationships when improving the system efficiency. [ABSTRACT FROM AUTHOR]

The photovoltaic poverty alleviation (PV-PA) policy is a promising policy innovation to achieve sustainable development in China. Based on first-hand field investigation data of 18 prefecture-level cities and 110 counties in China's Henan Province, this paper first evaluated the efficiency of PV-PA policy and analyzed its spatial correlation characteristics by adopting data envelopment analysis, spatial autocorrelation analysis and social network analysis methods. The results show that: (1) the comprehensive efficiency of the PV-PA policy in Henan Province is good, and that of the prefecture-level is better than the county-level, with great differences; (2) comprehensive efficiency of the PV-PA policy shows a significant spatial agglomeration phenomenon at the county-level, and regional development imbalance exists; and (3) PV-PA policy network linkages at prefecture-level are relatively weak. Finally, this paper makes policy recommendations for optimizing project scale, promoting regional balanced development, strengthening supervision and management, and enhancing the cooperation between policymakers. • DEA was used to evaluate the efficiency of the PV-PA policy in China's 110 counties • Explored the spatial correlation patterns of the PV-PA policy efficiency • Constructed a spatial correlation network for the PV-PA policy efficiency • Comprehensive efficiency of PV-PA policy needs to be enhanced • Unbalanced development and regional uncoordinated situation needs improvement [ABSTRACT FROM AUTHOR]

In order to accurately analyze the safety management efficiency of China's coal enterprises, based on the panel data of 14 coal listed enterprises in 2012–2018, this paper analyzes the overall technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of safety management of sample enterprises by the Data Envelopment Analysis (DEA) model, and builds Tobit model of random panel effect to evaluate the impact of business management and safety investment on safety management efficiency. The results show that: in 2012–2018, the average values of TE, PTE and SE of sample enterprises are respectively 0.674, 0.777 and 0.864; all have great room for improvement. The development of PTE and SE in most sample enterprises is unbalanced; TE of sample enterprises does not significantly improve, and shows a trend of rising-decreasing-rising; safety investment, enterprise scale and labor productivity are significantly positively related to safety management technical efficiency, while safety training person time and employees quality are negatively correlated. This paper identified the positive and negative effects of various influencing factors on the safety management efficiency of coal enterprises, and analyzed the main reasons that hinder the improvement of safety efficiency, and puts forward corresponding countermeasures and suggestions, which are helpful for coal enterprises to effectively improve their safety management efficiency and economic efficiency. [ABSTRACT FROM AUTHOR]

As the world's largest energy consuming country, it is important to study the mechanisms of improving renewable energy and energy efficiency to achieve green economic growth in China and globally. Therefore, this study investigates the impact of environmental regulations on green economic growth and renewable energy development in China, respectively. First, this study measures the level of green economic growth in Chinese cities by the Metafrontier-Global-SBM super-efficient data envelopment analysis (DEA) model from the perspective of energy efficiency. And the environmental regulation intensity was measured using an improved fuzzy comprehensive evaluation method. Second, a spatial econometric model based on longitudinal data was constructed to examine the non-linear effects of environmental regulations on green economic growth and its spatial spillover and feedback effects. The results indicated a U-shaped non-linear effect of energy efficiency-related environmental regulation on green economic growth as well as a spatial spillover effect and spatial feedback effect. Finally, the impact of environmental regulation on renewable energy development was investigated. The results show that renewable energy development, an important component of green economic growth, is equally dependent on the implementation of environmental regulation policies and that environmental regulation makes a significant contribution to renewable energy development. The findings of this paper provide a basis for the realization of green economic growth and the formulation of renewable energy policies in China. • Impact of environmental regulation on renewable energy development was investigated. • A spatial econometric model of 286 Chinese cities from 2003 to 2018 was constructed. • Environmental regulation has a significant U-shaped effect on green economic growth. • Non-linear effects include spatial spillover and spatial feedback effects. • Environmental regulation promotes green growth earlier in resource-based cities. [ABSTRACT FROM AUTHOR]

The paper reports results from a use of non-radial DEA i.e., range adjusted measure (RAM) which belongs to data envelopment analysis to evaluate the performances of the truck restriction policy in China. We try to explore what is inside the "black box" on the restriction policy by empirical study. Using the non-radial DEA model, we work with an approach that allows a flexible designation of three input variables and two output variables based on varying perspectives in China. The multipurpose approach reveals whether one policy is truly beneficial instead of officials' arguments, captured in the form of DEA scores. The modified model can better reflect macro-transportation process while earlier relevant models ignored truckers. This paper contributes to increasing traffic volumes and decreasing traffic accidents from the point of technical efficiency. The results of our paper reveal that: (a) China's truck restriction policies have achieved a significant "level effect" on efficiency improvement. (b) There are remarkable provincial differences in the effectiveness of the restriction policy. (c) Slack decomposition shows that excessive investment is the main source of inefficiency. Moreover, we delivery policy implications that: (a) the restriction policies greatly contribute to the efficiencies, and stringent policies are still needed in the following days; (b) the policy-making should suit local conditions, according to our classification of 30 provinces; (c) based on the worst performance of capital stock variable, the authorities should focus more on regulation of investment in transportation sector at a latter stage. [ABSTRACT FROM AUTHOR]

An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers. Image 1 • The paper constructs two resource allocation models based on the DEA approach. • This research considers the allocation of public pollution treatment resources between different sectors. • Two strategies for resource allocation are composed to deal with different conditions relating to resources. • We apply the new models to measure the performance of 30 regions in China. [ABSTRACT FROM AUTHOR]

This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy. • A two-stage undesirable and desirable congestion model is designed innovatively. • Energy efficiency in transport sector is assessed from the perspective of congestion. • The factors affecting the undesirable congestion in transport sectors are analyzed. • Rational allocation of energy in transport sector is realized based on congestion. [ABSTRACT FROM AUTHOR]

How to assess the performance of funds to support the rural revitalization is closely concerned by both academics and industries. In this paper, taking agricultural loans and financial allocations as inputs, we open the dynamic internal structure of the funding to support the rural revitalization system (FSRRS), including the agricultural support funds system (ASFS) and the rural revitalization system (RRS). With the consideration of regional heterogeneity, we propose the dynamic network data envelopment analysis (DEA) models based on convex and nonconvex metafrontiers to measure the metatechnology-specific technical efficiency (MTE), group-specific technical efficiency (GTE) and technology gap ratio (TGR) of the overall system and subsystems. The proposed models are empirically applied to assess the efficiency of funding to support rural revitalization and regional heterogeneity of technologies for 31 provinces in China during 2017–2020. The results show that: (i) compared to the nonconvex metafrontier model, its convex counterpart underestimates the efficiency of each decision making unit (DMU), resulting in the unfairness of evaluation, in particular for the central and western regions; (ii) there is a difference in the efficiency of the overall system and the subsystems, where the RRS performance is superior to the ASFS performance, implying that the inefficiency of FSRRS is mainly attributed to the low utilization of agricultural support funds; (iii) the period efficiency of the overall system and subsystems show an increasing trend over time, and the magnitudes of increases are different across provinces (regions); (iv) the TGRs of various provinces (regions) exhibit a significant heterogeneity. • We open the dynamic internal structure of the funding to support rural revitalization system (FSRRS). • We propose nonconvex metafrontiers based models to measure the performance of FSRRS. • We discuss the efficiency of FSRRS and regional heterogeneity of technologies. • We provide theoretical and empirical evidence for the model selection of FSRRS evaluation. [ABSTRACT FROM AUTHOR]

With the completion of the poverty alleviation task in China, the Chinese economy has made great breakthroughs. Meanwhile, the implementation of Chinese "dual carbon" goal has entered an important window period of both strategic opportunities and difficulties. The emission of carbon dioxide (CO2) leads to the greenhouse effect, which affects the sustainable development of society. Therefore, this paper proposes an improved analytic hierarchy process (AHP) with Slacks-based measure integrating data envelopment analysis (SBMDEA) (AHP-SBMDEA) based efficiency evaluation model for different provincial-level administrative regions in China, which is used to analyze and optimize the Chinese energy structure of different provincial-level administrative regions. With coal, gasoline, petroleum, fuel oil, diesel, crude oil and natural gas as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, after linear weighted calculation of the results of the AHP-SP model and the SBMDEA model, the energy efficiency evaluation model of different provincial administrative regions in China is established. The results show that there is a large difference in efficiency between Chinese northern and southern regions, and the overall efficiency of southern regions is higher than that of northern regions. In addition, it is easier to find out the optimal energy efficiency benchmark, which can provide suggestions and help to guide the energy consumption input structure improvement of other inefficient provincial-level administrative regions. Furthermore, the energy structure can also be adjusted through the redundant variable calculated by the SBMDEA model. For example, Sichuan Province can reduce the consumption of the coal, the gasoline, the diesel, the fuel oil, the crude oil and the natural gas by 5269.95 × 10000 tons (WT), 513.01 WT, 59.05 WT, 34.37 WT, 4,73.33 WT and 130.37 billion cubic meters (BCM), respectively. Its CO2 emissions can be reduced by 1925.4 WT, and raise the efficiency of energy utilization in the province. [Display omitted] • Novel economy and CO 2 emissions evolution model based on a AHP-SBMDEA is proposed. • The proposed model can identify the optimal energy efficiency benchmark. • GDP per capita can be increased and CO 2 emissions can be decreased. [ABSTRACT FROM AUTHOR]

Optimizing greenhouse design is a complex challenge that involves the large combinational solution space and the interactions between design elements, outdoor climate, and crops. In addition, evaluating greenhouse performance requires consideration of economic and environmental dimensions, as well as different stakeholder priorities. This study aims to identify greenhouse designs that are efficient in terms of economic and environmental performance for both policy makers and investors for four locations in China. This paper made a novel combination of operational research methods with bio-economic modelling. Specifically, a bio-economic model was used to simulate the yield, energy use, and economic and environmental performance of different greenhouse designs. A genetic algorithm was used to explore the large solution space to reduce the computational effort. The overall performance of greenhouse design was evaluated using a directional distance function approach, which incorporated stakeholders' priorities for economic and environmental performance through the directional vector. The results identify several greenhouse designs that were found to be efficient in terms of economic and environmental performance for both investors and policymakers across various price scenarios. The most influential factors on operating income include the choice of lighting, structure, thermal screen, and CO 2 dosing rate. Among lighting options, LED lighting outperforms HPS lighting in terms of both economic and environmental performance. Specifically, incorporating LED lamps with an intensity of 200 μmol m−2 s−1 can increase annual operating income by 97.3 to 200.2 ¥ m−2, depending on the region. Conversely, low intensity lighting adversely impacts both economic and environmental performance. A synergistic relationship has been observed between lighting and CO 2 dosing. On the other hand, lighting is the primary contributor to greenhouse gas (GHG) emissions. Incorporating LED lighting with an intensity of 200 μmol m−2 s−1 can increase CO 2 equivalent emissions from 151.7 to 211.0 kg m−2. Incorporating thermal screens can effectively reduce GHG emissions. The study presents an optimization approach that can be applied to various complex agricultural systems with interactions between many factors and the presence of multiple stakeholders with conflict priorities. In addition, our study has practical implications for the greenhouse sector in China. The wide range of optimal solutions provides policy makers and investors with the flexibility to choose greenhouse designs that meet regional agricultural development goals and budget constraints. [Display omitted] • Greenhouse design needs to consider production, economic, and environmental interdependencies, andstakeholder preferences. • We used bio-economic modelling, genetic algorithm, and a directional distance function approach to evaluate greenhouse designs. • We identified several greenhouse designs with robust economic and environmental performances for four locations in China. • Lighting system, structure, thermal screen, and CO 2 dosing rate were among the most influential factors on operating income. • Lighting is the primary contributor to GHG emissions, while the use of thermal screens can effectively reduce GHG emissions. [ABSTRACT FROM AUTHOR]

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]

The metal industry (MI) in China is energy and emissions intensive. This paper tries to provide guidance for the green development transformation of China's MI, by investigating the green total-factor productivity (GTFP) and its influencing factors using a global data envelopment analysis and a spatial Tobit regression model. The estimation results show that: (1) from 2000 to 2015, GTFP of China's MI enjoyed a considerable improvement. However, the current value of GTFP of China's MI is still less than 0.5, indicating that GTFP of China's MI is far from efficient; (2) the spatial correlation test shows that GTFPs of China's provincial MIs have positive spatial correlations. Most of the provinces scattered in "high-high" and "low-low" agglomerations; (3) GTFP of China's MI is significantly positive related to the degree of marketization, fiscal decentralization, environmental regulation, industrial scale, is significantly negative related to resources endowment and product structure, and has "U" shaped relationship with the level of economic development. The above results suggest that China already has made remarkable achievements in promoting green development of its MI. However, there is much room for further improvement. Policy options for the green development transformation of China's MI include but are not limited to promoting market-oriented and financial system reforms, strengthening environmental supervision, and optimizing industrial scale and product structure. Finally, recommendations for the effective implementation of these policies are provided at the end of the study. • This paper analyzed the historical performance and influencing factors of GTFP of China's MI. • Results show that GTFP of China's MI achieved considerable improvement in the past few years. • However, the current level of GTFP of China's MI is still very low. • There are many effective policy options for further promoting GTFP growth of China's MI. • Some implications for the implementation of these policies are provided in this paper. [ABSTRACT FROM AUTHOR]

In the conventional data envelopment analysis (DEA) window analysis, a decision-making unit (DMU) in each window is treated as different units in each period so that the evaluation for one unit is performed on different scales over time. This paper proposes a novel window analysis based on common weight across time (CWAT), which evaluates each unit in each window by its common scale independent of time. The model for obtaining common weights is described as linear programming. And the paper suggests the Malmquist productivity index (MPI) on CWAT, CWAT MPI, to analyze productivity change by inheriting the result of window analysis. The numerical experiments are illustrated to examine the validity of CWAT and MPI, and the result shows that the proposed method provides a new evaluation scale compared to previous studies. The proposed model is applied to evaluate the performance of China 45 iron and steel enterprises during 2009–2017. The energy and environmental efficiency are calculated using CWAT, and CWAT MPI analyzes the productivity change. • We study a DEA window analysis based on common weights. • The proposed DEA window is represented by linear programming. • We discuss the Malmquist index in the DEA window. • The MPI is the geometric mean of all indices calculated in individual windows. • The performance of the iron and steel enterprises is evaluated. [ABSTRACT FROM AUTHOR]

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

Considering both regional heterogeneity and industrial heterogeneity, this paper proposes a three-hierarchy meta-frontier data envelopment analysis (DEA) to decompose energy efficiency and energy-saving potential into three components, i.e., industrial structure, regional balance development, and management. Based on this approach, the paper then analyses the historical evolution and current status of energy efficiency in China. The results show the following. (1) From 2001 to 2015, Mainland China's energy efficiency increased by a factor of 2.48, primarily because of technological progress and the optimization of its industrial structure. (2) Nonetheless, the current energy efficiency in Mainland China remains very low and energy inefficiency is as high as 0.5922, indicating that 59.22% of total energy consumption is invalidly used. Severe industrial structure inefficiency and regional balance development inefficiency are the two main factors responsible for the very low energy efficiency. (3) By promoting industrial restructuring, regional balance development, and management improvement, Mainland China is expected to save, respectively, 13.67%, 24.54%, and 61.73% of its current total invalid energy consumption. Based on the estimation results, this paper formulates strategies to improve energy efficiency and save energy for China's provinces based on their specific situations, considering not only the direction of industrial restructuring in both the short and long terms but also the path to improved energy efficiency. In addition, a brief discussion about the applicability and the preconditions for an application of the multi-hierarchy meta-frontier approach is given at the end of the paper. [ABSTRACT FROM AUTHOR]

Aquavoltaic is an essential tool in overcoming the ground-based photovoltaic (PV) development barrier and achieving China's carbon neutrality target. After summarizing aquavoltaic technologies and global cases, this paper assesses the effectiveness of 292 aquavoltaic plants in China using the data envelopment analysis (DEA) method. Six essential input and output variables are included: installed capacity, power generation, occupied water area, construction cost, PV modules, and global horizontal irradiation to offer an appropriate measure of aquavoltaics efficiency in China. This study also performed correlation analysis for PV module type, PV mounting mode, and ownership based on a Tobit regression model. The results show that the efficiencies of China's aquavoltaics have improved significantly between 2014 and 2022, with the emergence and popularity of high-power PV modules playing a pivotal role. Furthermore, the regional study discovered provincial efficiency varies substantially. This paper also gives two reference indicators for new aquavoltaics in the future. • The global aquavoltaic technologies and cases were summarized. • The history and status quo of aquavoltaics in China were reviewed. • Aquavoltaics' energy efficiency has increased significantly in China. • The high-power PV modules have a positive impact on efficiency growth. [ABSTRACT FROM AUTHOR]

Obtaining the most economic benefits while using the least resources and causing the least environmental damage is an urgent and key problem in achieving sustainable development. The concept of eco-efficiency provides a comprehensive perspective for observing and solving this problem. This paper proposes an extended data envelopment analysis model, named the WIN-US-SBM, as a comprehensive eco-efficiency evaluation method that can accommodate undesirable outputs, all the identification problems of decision-making units (DMUs), possible slacks of variables, and the problems of an insufficient number of available DMUs and intertemporal comparability. China's Western Taiwan Straits Economic Zone (WTS Economic Zone) is an important regional economic growth center. By applying WIN-US-SBM and ArcGIS software, we investigated data on the temporal and spatial evolution characteristics of eco-efficiency in the WTS Economic Zone for the years 2009–2016. Later, the global Malmquist–Luenberger index was used to decompose the sources of growth in eco-efficiency. Finally, the main driving factors of eco-efficiency were explored through a Tobit regression analysis. The empirical results show that: (1) The overall eco-efficiency of the WTS Economic Zone had greatly improved, increasing by 11.46% annually, and the cumulative growth rate of eco-efficiency was 110.84% from 2009 to 2016. (2) The eastern area had the highest average eco-efficiency, followed by the western area and the middle area in that order. Also, the growth rate of the middle area ranked first (16.68%), whereas the eastern area had the slowest growth in eco-efficiency (7.22%). (3) On the whole, the growth of eco-efficiency was driven mainly by technological progress and was restricted by the decrease in management level, which implies that policy makers should focus on improving management and technical levels. (4) High levels of economic development, population density, market openness, and industrial structure had positive effects on the eco-efficiency of the WTS Economic Zone, whereas energy intensity and expenditure on science and technology had negative impacts. • An extended DEA model is proposed to measure eco-efficiency more comprehensively. • The proposed model can be widely applied to input-output efficiency evaluations. • The eco-efficiency of the WTS Economic Zone was evaluated based on a novel model. • The growth of eco-efficiency was driven mainly by technological progress. • The eco-efficiency level is negatively related to energy intensity. [ABSTRACT FROM AUTHOR]

In recent years, the profit growth of wind power enterprises in China is generally weak, and the phenomenon of "wind curtailment" in some areas is relatively common. The comprehensive evaluation of wind power performance in various regions of China and the study of the driving forces of wind power performance differences in different regions are of great significance for scientific planning and layout of wind power investment. Based on the panel data, this paper combines Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to establish an evaluation model to evaluate the wind power performance of China's 29 provinces and cities from 2011 to 2018. Then uses the evaluation results as input data of Adaptive Neuro-Fuzzy Inference System (ANFIS) prediction model to predict the wind power performance of 2019 in various regions of China under the current policy and environment. Finally, the main factors affecting the performance of China's wind power generation are explored by establishing a regression model. The research results show that at present, the main factors affecting the performance of China's wind power generation are local power consumption capacity, economic development degree and the rate of wind abandonment. On the premise of solving the problem of wind curtailment, appropriately promoting power consumption and renewable energy policy reform, from Feed-in-Tariff (FiT) to a Renewable Portfolio Standard (RPS), are effective means to promote the development of wind power generation in China. Image 1067 • In wind-intensive areas, wind power performance levels are relatively low. • Power consumption capacity and wind curtailment rate are the main influencing factors. • Current policy cannot effectively solve the problem of wind curtailment. • Renewable energy policies with regional differences should be adopted. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the implementation of smart city policy (SCP) on energy efficiency (EE) in China. For this purpose, we have developed a non-convex metafrontier data envelopment analysis (DEA) approach to measure EE, and empirically examine the impacts of SCP on China's EE using Difference-in-Differences (DID) analysis, using a dataset of 251 cities between 2003 and 2016. Results show that there exists significant regional heterogeneity across cities, with the SCP exerting a significant positive effect on EE, indicating that the SCP can effectively improve EE during the study period. These findings are robust to different sub-sample, energy efficiency alternative measures, estimation strategies, and Baidu Search Index. Based on empirical results, the implications of SCP are outlined. • Energy efficiency measures of 251 Chinese prefectural-level cities are estimated. • Eastern region performs the best, followed by the central and western regions. • The effects of smart city policy on energy efficiency is investigated using DID method. • The smart city policy can effectively improve energy efficiency during the study period. • Empirical results are robust to different sub-sample, energy efficiency alternative measures, etc. [ABSTRACT FROM AUTHOR]

China has developed a remarkable economic growth in the past 30 years by accompanying with undesirable outputs. The assumptions of weak and strong of undesirable outputs have become the focus discussion in data envelopment analysis (DEA) models. To have a comprehensive environmental efficiency measurement, this paper proposes three DEA models considering weak disposability, strong disposability and distinguishing weak and strong disposability of undesirable outputs, respectively. We further combine with the Malmquist-Luenberger productivity index to assess the environmental efficiency and the dynamic change trend of 30 provinces in China from 2005 to 2014. The results show that distinguishing technical features of undesirable outputs makes a significant difference to final environmental efficiency score at different regions. The environmental efficiency of the whole nation, however, does not show any increasing trend during the ten years. Enhancing environmental efficiency of central and west area is an urgent task for Chinese government. The change trend of Malmquist-Luenberger productivity index and technological change shows a similar shape. Technical progress is the main driving force to enhance the environmental efficiency. Relevant suggestions are presented for improving the regional environmental efficiency in China in the future. [ABSTRACT FROM AUTHOR]

Data Envelopment Analysis (DEA) is used for not only assessing the performance of a set of homogeneous decision-making units (DMUs), but finding the target operating points to improve inefficient DMUs. When inefficient DMUs are far from their target, it will be impossible to reach those in a single move, therefore, a strategy of gradual improvements with intermediate targets has been proposed. In this study, we propose a method to determine benchmarking paths, which consider the improvement steps as the learning of the production functions, not the learning of inputs and outputs. Under the constant returns-to-scale (CRS) assumption, the paper, for each inefficient DMU, sets the ultimate target as the closest target and determines the shortest improvement path with existing DMUs by Dijkstra's algorithm, and this is illustrated with a numerical experiment. As a real-world example, the method is introduced to the irons and steel enterprises in China, so that the specific steps to make efficient ones has been pointed out. The proposed method is the first study to discuss stepwise benchmarking path from the perspective of the production function. • The benchmarking paths are composed of existing DMUs. • The ultimate target is set as the closest efficient DMU. • The inefficient DMU learns the production functions of DMUs. • The distance between two production functions is calculated. • Dijkstra's algorithm is used to find the optimal benchmarking path. [ABSTRACT FROM AUTHOR]

In the face of a rapidly ageing population, China's healthcare system is under mounting pressure to meet growing demand for more and better services. This paper aims to identify opportunities to improve the efficiency and quality of healthcare services in China. We first evaluate the healthcare performance of China's 31 provincial regions during the 2005–2019 period. The hospital efficiency is computed by using a window-based super-efficiency composite Data Envelopment Analysis model, while the healthcare quality is evaluated by using a window-based Technique for Order Preference by Similarity to an Ideal Solution method. Then, we investigate the impacts of socioeconomic factors, such as government subsidies, marketization, per capita Gross Domestic Product and demographic structure, on regional healthcare performance by use of regression analysis. The main findings include: 1) The nationwide healthcare performance has improved from 2005 to 2019 in part due to China's rapid economic growth, but more progress has been achieved in improving hospital efficiency than healthcare quality. 2) Government subsidies can improve both regional healthcare quality and hospital efficiency. While marketization can enhance hospital efficiency, private hospitals provide lower quality of care than public hospitals. 3) Regional hospital efficiency and healthcare quality are positively correlated, but a causal relationship cannot be established based on our empirical evidence. Based on our findings, we have the following recommendations for policymaking: 1) The government should increase subsidies to medical institutions in order to improve healthcare quality as well as hospital efficiency. 2) More subsidies should be allocated to regions having a high old-age dependency ratio. 3) More quality control and improvement efforts should be taken at private hospitals. • A comprehensive evaluation of China's provincial healthcare performance during 2005–2019. • Investigation of the socioeconomic determinants of regional healthcare performance. • Examination of the impacts of government subsidies and marketization on regional healthcare performance. • Analysis of the relationship between hospital efficiency and healthcare quality. [ABSTRACT FROM AUTHOR]

The development of higher education institutions (HEIs) is related to the future overall development of higher education in China. Studying the efficiency of provincial HEIs in China has great significance in deepening the reform of higher education evaluation, promoting coordinated regional development, and building a country powerful in its higher education. Based on the Super-SBM method, this paper creatively integrates meta-frontier theory and an index of international exchange and cooperation into an evaluation system for higher education efficiency. Taking 2011–2020 as the sample period, this study conducts a dynamic assessment of the higher education efficiency in 30 mainland Chinese provinces. It explores the differences in production technology in the eastern, central, and western regions, analyzing the environmental factors that affect the efficiency of higher education. The results show that during the sample period, the overall efficiency of higher education in China improved steadily. Efficiency Change is the main driving force. The three regions have significantly different technology gap ratio, and the structure of resource allocation significantly impacts efficiency. Therefore, this study's main recommendations are that the Chinese government should not only deepen the coordinated development of higher education between regions but also pay more attention to solving the problem of unbalanced development between China's geographical regions. At the same time, educational authorities should expand the number of ordinary colleges and universities in the central and western regions, develop non-financial funding sources, and improve the level of refined management of HEIs. • This study measures the efficiency and evolution of China's HESs in the second decade of the 21st century. • It considers the effects of regional heterogeneity on the efficiencies of HESs. • It incorporates higher vocational colleges into HES efficiency evaluation. • The result shows that the efficiency of Chinese HES show obvious geographical characteristics. [ABSTRACT FROM AUTHOR]

To obtain high-quality human resources and to gain advantages in the context of global competition, countries are constantly promoting the development of higher education. Enormous human and financial resources were invested in this "battle". However, the "inputs" consumed by universities are largely ignored. A major issue, evaluating how well a country's universities make use of input resources in their output path, is of economic and social significance. The focus of this study is to embed the concept of capacity utilization in education and to assess the university's performance. We construct an attainable output-oriented capacity utilization measurement model by taking into account the heterogeneity of the region. According to the usage of the input, we divide the decision making units into four areas and identify the causes of inefficiency. Thus, the methodology proposed in this study provides policymakers an applicable tool on differences in educational inputs across regions. To illustrate the method, we conduct an empirical analysis using data from 54 universities directly under the Ministry of Education in China. • By embedding the concept of CU in the education sector, we propose a conceptual theoretical framework and assessing the utilization of university inputs. • We construct an attainable output-oriented CU measurement model by taking into account the attainability of variable inputs. • By dividing decision making units into four types according to the causes of inefficiencies, this paper proposes an CU analysis paradigm. [ABSTRACT FROM AUTHOR]

By proposing a three-hierarchy meta-frontier data envelopment analysis (DEA), this paper first decomposes CO 2 -emissions efficiency and the potential for emissions reduction into the following three components: structural, technical, and management. Based on these components, we then conduct an empirical analysis of China’s total-factor CO 2 -emissions efficiency, its potential for CO 2 -emissions reduction, and its corresponding implementation path. The results show that CO 2 -emissions efficiency in Mainland China is relatively low because of structural inefficiency, technical inefficiency, and management inefficiency. The Chinese government is expected to realize a large quantity of CO 2 -emissions reduction potential (nearly 40% of the current total CO 2 -emissions) through adjusting the industrial structure, narrowing the technology gap among regions, promoting the reform of marketization, and strengthening environmental regulation. The causes of CO 2 -emissions inefficiency and the distribution of potential reductions in emissions show a distinct spatial difference characteristic. Therefore, this paper also formulates emissions-reduction strategies for China's 30 provinces according to their specific situations, noting the direction of the industrial structure adjustment and the path to improving CO 2 -emissions efficiency. [ABSTRACT FROM AUTHOR]

This paper utilizes the slacks-based measure (SBM) undesirable model to analyze the environmental regulation efficiency (ERE) from 2003 to 2013, and uses the Data Envelopment Analysis (DEA) Malmquist productivity index to divide the environmental regulation total factor productivity (ERTFP) into a technical progress index, pure technical efficiency index and a scale efficiency index from the perspective of scale change. The results show that the ERE presents “polarized” effect and the ERTFP has an obvious “agglomeration” effect in China. There is also a very significant “match-up” effect between the ERE and economic development level. In addition, the paper also finds that the technical progress index has the largest contribution to ERTFP, followed by pure technical efficiency index and then the scale efficiency index. The preceding results can provide scientific suggestions for regional environmental departments. [ABSTRACT FROM AUTHOR]

In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China's economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China's sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China's sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China's sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

The development of China's forestry resources has never been more challenging due to serious problems such as shortage, inferiority and uneven distribution of forestry resources. Therefore, the study and evaluation of China's forestry resources has a great significance to improve efficiency and ensure the sustainable development of the forestry resource. Meanwhile, the vast territory, huge population and widespread forest landscape of China have led to the numerous indexes and the huge data. To perform the research and evaluation accurately, this paper utilized the big data theory to analyze the relevant data of China's forestry resources. This study collected the data from 31 inland provinces and municipalities of China from 2005 to 2013, after which we carefully examined economic, social and ecological factors to choose assessment indexes and processed data accordingly. Firstly, we performed a cross-sectional dataset analysis using the method of data envelopment analysis to investigate the forestry resources efficiency in 31 inland provinces and municipalities of China in years 2008, 2012 and 2013. Secondly, we analyzed time series data of the 31 inland provinces and municipalities from 2005 to 2013 using the Malmquist total factor productivity index method. Our results showed the dominant factor that restraining forestry resources efficiency for the 31 inland provinces and municipalities is the implemented technology. So we suggest increasing the investment in science and technology to improve the overall efficiency of forestry resources, along with improvement of operation and management by relevant administrative departments to improve technology utilization. The innovation of this paper lies in the dynamic process of analysis. [ABSTRACT FROM AUTHOR]

Because of China’s rapid economic development, its transportation system has become one of China’s high-energy-consumption and high-pollution-emission sectors. However, little research has been done which pays close attention to China’s transportation system, especially in terms of energy and environmental efficiency evaluation. In this paper, data envelopment analysis (DEA) is applied to measure the energy and environment performance of transportation systems in China with the goal of sustainable development. This paper treats transportation as a parallel system consisting of subsystems for passenger transportation and freight transportation, and extends a parallel DEA approach to evaluate the efficiency of each subsystem. An efficiency decomposition procedure is proposed to obtain the highest achievable subsystem efficiency. Our empirical study on 30 of mainland China’s provincial-level regions shows that most of them have a low efficiency in their transportation system and the two parallel subsystems. There are large efficiency differences between the passenger and freight transportation subsystems. In addition, unbalanced development has occurred in the three large areas of China, with the east having the highest efficiency, followed by central China and then west. Therefore, more measures should be taken to balance and coordinate the development between the three large areas and between the two subsystems within them. Our analysis approach gives data for determining effective measures. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of Chinese economy and the advancement of urbanization and industrialization, the transportation industry caused serious environmental pollution and resource waste problems. The eco-efficiency of Chinese transportation industry has become a hot spot of society. Recently, China announced several initiatives to stabilize and expand employment, so that the efficient and sustainable development of industries cannot be based on the premise of reducing the labor force. However, traditional efficiency measures usually assume that inputs can be reduced at will, which is insufficient to correctly represent the observed practice. In this paper, we investigate the eco-efficiency of the transportation industry in 30 Chinese provinces incorporating the non-discretionary input labor and undesirable output CO 2 emission. Data envelopment analysis and directional distance function approaches are employed in constructing the measurement model. Our empirical results reveal explicit spatial features of the eco-efficiency in various provinces and show significant correlation between eco-efficiency and industrial structure, technological, and management factors. To examine the validity of our proposed models, comparative studies were further conducted and illustrated that the introduction of non-discretionary inputs and the selection of direction vectors have a crucial impact on the results of eco-efficiency. Based on the empirical results and our summarized policy implications, we found several deficiencies in the real policies and put forward corresponding policy suggestions for the industry and government. • Existing studies pay little attention to the non-discretionary input factors. • We propose a DEA model to incorporate the non-discretionary input. • This paper investigates the eco-efficiency of Chinese transportation industry. • Based on the empirical results and the existing policies, this paper puts forward several policy suggestions to the government and industry. [ABSTRACT FROM AUTHOR]

Schematic diagram of the research framework: A new network DEA method. [Display omitted] • A new network DEA allocation model considering cross-border transmission of SO 2. • The WRF-CMAQ is combined with the DEA allocation model for the first time. • The principles of optimal efficiency, GDP protection and fairness is considered. • The per capita relative deprivation coefficient was used to evaluate the fairness. • The new network DEA model is a powerful tool for SO 2 emission rights allocation. Currently SO 2 emission rights are allocated without considering the cross-border transmission characteristics of pollutants, and the allocation scheme cannot reflect the fact that air pollutant overflows in space. In this paper, the WRF (Weather Research and Forecasting Model)-CMAQ (Community Multiscale Air Quality) is combined with the data envelopment analysis (DEA) allocation model for the first time, and a two-stage (Stage-1: SO 2 formation, Stage-2: SO 2 treatment) network DEA allocation model is proposed with the SO 2 spatial transmission taken as the intermediate output or input index between decision-making units. Based on the principles of efficiency, economic protection and fairness, the model is applied to the study of SO 2 emission rights allocation in the Yangtze River Delta city agglomeration with high homogeneity in China. The results show that: (1) When the weight coefficient (α 1) in stage-1 is 0.7, 0.8 or 0.9, the per capita relative deprivation coefficient (PRDC) of each decision-making unit (DMU) is less than 0.5 in the allocation scheme, indicating that our scheme can be used as a reference to allocate emission rights in the Yangtze River Delta city agglomeration. (2) With great robustness and universality, our allocation model allows decision-makers to adjust the GDP constraint coefficient and the weight coefficients in the two stages according to their preferences, so as to obtain the optimal allocation results. The model proposed in this paper can help decision-makers to formulate effective policies to reduce pollutant emission, and promote energy conservation & emission reduction and coordinate environmental governance in regions of city agglomerations. [ABSTRACT FROM AUTHOR]

Photovoltaic poverty alleviation power stations (PPAPS) are the foundation of poverty alleviation, whose operation and maintenance (O&M) status is the key to ensuring long-term poverty reduction advantages. As part of PPAPS′ O&M performance, the role of the O&M contracts has yet to be proven. This paper uses a three-stage data envelopment analysis (DEA) model and grey relation analysis (GRA) to analyze the O&M performance efficiency of PPAPS and the influencing factors of contract governance from field data of 110 counties in Henan Province, China. The results show that:1) the O&M efficiency of the PPAPS is relatively high and inconsistent across the region, which has not yet attained optimal productivity; 2) the present efficiency is mainly determined by the initial investment size and installed capacity; 3) the governance factors of O&M contracts affect the performance efficiency of PPAPS, which may lead to overestimation; and 4) longer contract term and higher performance incentive coefficients may result in inefficiencies at the initial stage of PPAPS′ use, while government subsidies allocation and timely O&M cost settlement have little impact on O&M efficiency. This paper proposes corresponding policy recommendations finally. • This paper focuses on the true O&M performance efficiency of PPAPS and influencing factors of contractual. • PPAPS′ O&M performance efficiency is relatively high with regional differences among counties. • The initial investment and capacity installed mostly determined the present efficiency. • Longer O&M contract terms and a higher achievements drive will result in inefficiency at the initial stage of PPAPS. [ABSTRACT FROM AUTHOR]

• Game method is used in interval cross evaluation. • Build a variety of evaluation strategies to linearize the model. • Using entropy theory to aggregate the results of different evaluation strategies. Cross-efficiency evaluation is an effective method for the ranking of decision-making units (DMUs) in data envelopment analysis, which is the performed method for peer-evaluation and self-evaluation. In most cross-efficiency evaluation methods, the peer evaluation result is completely constrained by the evaluator's optimal self-evaluation weights. DMUs are connected by a competitive relationship; therefore, they can be regarded as players in the game and the cross efficiency value can be regarded as payment because of this competition. DMUs need to consider the impact of their own weights on other DMUs to identify a set of weights for evaluating themselves. Based on the idea of non-cooperative games in the cross evaluation of DMUs, this paper considers the interval cross game efficiency of DMUs with the interval data. The interval data theory is combined, the best production state and the worst production state are taken as reference states, and four evaluation strategy models are proposed according to the opposition and coordination relationship. Then, the bijective and injective interval game cross models, as well as the algorithm corresponding to the four evaluation strategies are constructed. Moreover, the result of the self-evaluation is used as the initial parameter to prove the existence of the solution and the convergence of the algorithm. Based on the priority relationship of the evaluation results under different strategies, the interval entropy method is used to aggregate the results and obtain the final cross efficiency of the interval game. Furthermore, both the applicability and superiority of this model are exemplified by an example. Finally, based on the method of this paper, the efficiency of forest carbon sequestration in China are studied, seven natural regions in China are ranked by forest carbon sequestration efficiency values reasonably, and the current regions development of forest carbon sequestration in China are evaluated. [ABSTRACT FROM AUTHOR]

It is important to investigate the sustainability nexus using composite ecological efficiency (eco-efficiency) indicators from quantitative and computational modeling perspectives. To provide a more comprehensive measure of eco-efficiency, this paper develops three data envelopment analysis (DEA) models incorporating metafrontier and undesirable outputs into a slacks-based measure (SBM), an epsilon-based measure (EBM), and minimum distance to weak efficient frontier (MinDW), respectively, named Meta-U-SBM, Meta-U-EBM, and Meta-U-MinDW. We show theoretically: if a decision-making unit (DMU) is being Meta-U-SBM-efficient, it is also being Meta-U-EBM-efficient and Meta-U-MinDW-efficient, and vice versa. For each DMU, its score measured by Meta-U-MinDW is the highest, while its score measured by Meta-U-SBM is the lowest. Using the proposed models, we make a first empirical attempt at measuring the eco-efficiency of the Key Environmental Protection prefecture-level cities in China from 2003 to 2015. The results show that: (1) the eco-efficiency of eastern cities performs the best, followed by central cities and western cities. Cities not listed as resource-based (RB) outperform RB cities; (2) eastern cities are closer to metafrontier than central and western cities; and (3) efficiency change and technological progress dominate the basic trend of the eco-efficiency growth. Results derived from the proposed methodologies can help managers and policymakers in the city to assess sustainability development quantitatively and comprehensively, they can also provide implications for the environmental management of sustainability development at city level. Policy implementations are presented based on the empirical results. [ABSTRACT FROM AUTHOR]

• A high spatial resolution CO 2 emissions inventory of 280 Chinese cities was compiled. • Three methods were compared to evaluate the carbon efficiency of Chinese cities. • The best and worst-performing cities were consistent regardless of different methods. • Top-ranking cities were located in the coastal regions of China. • Lagging-behind cities were located in the central and western regions of China. Comprehensive and accurate city-level carbon dioxide emissions inventory is key to success in China's pursuit of low-carbon development. Based on a high-resolution gridded data, this paper evaluates and benchmarks the carbon emissions efficiency of 280 Chinese cities using three different methods, i.e., composite index, data envelopment analysis and stochastic frontier analysis. The comparative analysis reveals that the average carbon emissions efficiency of Chinese cities is about 70–90%, with only 9 efficient cities (3%). Although the ranking of intermediate cities varies greatly according to the method employed, the most and least carbon-efficient cities remain consistent. While the best-performing cities are found in the coastal regions, the worst-performing cities are located in the central and western regions, which suggests an imbalanced low-carbon development in China. Guided by the results, local governments are encouraged to compete and learn from similar ranking benchmarks in a new regime of "Top Runner City". Finally, the scores of carbon emissions efficiency can provide a scientific basis for the bottom-up allocation of carbon emissions rights to boost the development of the nationwide carbon market in China. [ABSTRACT FROM AUTHOR]

Abstract In recent years, urban energy efficiency has received much attention from researchers. However, ignorance of the competitive relationships among regions results in inaccurate energy efficiency. Game cross-efficiency data envelopment analysis (DEA), which can account for the competitive relationships, is a reliable method to measure energy efficiency. First, this paper applies game cross-efficiency DEA to analyze the urban total factor energy efficiency (UTFEE) of 26 Chinese prefectural-level cities from 2005 to 2015 under environmental constraints. Then, a comparative analysis and a concrete analysis are conducted based on the urban energy efficiency. Finally, a Tobit model is used to examine the effects of 10 potential influence factors. The measurement results show that the urban energy efficiency considering the competitive relationship is lower than the traditionally calculated efficiency. Additionally, the urban energy efficiency did not improve during the research period. Furthermore, regression analysis suggests that economic development and city scale can promote urban energy efficiency, while government expenditure, industrial structures, energy prices, foreign investments, research investments and production endowment have negative impacts on urban energy efficiency. According to our results, some implications of theory and practice are discussed for researchers and policy makers. [ABSTRACT FROM AUTHOR]

Abstract China is the world's largest producer and consumer of non-ferrous metals, and the non-ferrous metals industry is energy- and emission-intensive. The CO 2 emissions of the industry have increased nearly four times from the level in 2000 to reach 310 million tons in 2014. To cope with the issues of CO 2 emission and other environmental problems under the background of low-carbon development, it is necessary to analyze the CO 2 emission performance of China's non-ferrous metals industry. Based on group heterogeneity, this paper uses data envelopment analysis to calculate the Shephard distance function and then uses the Shephard distance function and non-parametric meta-frontier methods to construct the meta-frontier Malmquist CO 2 emission performance index (MMCPI) of China's non-ferrous metals industry during the period 2006–2014. The index is further decomposed into three parts: technical efficiency change, technological progress change and technological catch-up effect. The results showed that the MMCPI of China's non-ferrous metals industry exhibits an upward trend during the review period. The improvement in CO 2 emission performance is most significant in the central region, followed by the eastern and western regions. Based on the decomposition of MMCPI, the effect of technological progress are significantly different for the different regions, indicating that more targeted policies are need for different regions. [ABSTRACT FROM AUTHOR]

Abstract Improving CO 2 emissions efficiency has become a crucial task faced by China to develop a low-carbon economy and choose a CO 2 emissions mitigation path. Existing researches have focused on estimating national CO 2 emissions efficiency, but have ignored the industrial heterogeneity in the region or explanation for inefficiency. To fill the gaps, this paper applies a metafrontier-Malmquist index analysis method combined with a three-level common frontier model to comprehensively estimate and decompose the carbon emissions efficiency and dynamic changes of China's industries and regions during 2010–2015. First, we use data envelopment analysis with directional distance function by considering three-level frontiers to calculate CO 2 emissions efficiency. Results show that China's overall CO 2 emissions efficiency is at the middle level with an average value of 0.511. The efficiency of CO 2 emissions in the eastern region is the highest, followed by the central and western regions, and the CO 2 emissions efficiency in the tertiary industries is greater than that in the primary and secondary industries. Second, we decompose CO 2 emissions efficiency into technological, industrial and management efficiency, and found that management efficiency is the main reason for low CO 2 emissions efficiency in developed regions and industries. Third, the Malmquist-Luenberger index is utilized to decompose CO 2 emissions efficiency into 9 items, and we obtained that continuous technological progress is the leading cause driving different degrees of improvement in CO 2 emissions efficiency. Graphical abstract Image Highlights • Apply non-radial model to estimate CO 2 emissions efficiency of China. • Use industrial, technical and managerial efficiency to explain inefficiency. • Build three-level metafrontier-Malmquist-Luenberger index to discuss dynamic changes. • Eastern region and tertiary industry have the highest CO 2 emissions efficiency. • Continuous technological progress is the main reason for gaps of efficiency. [ABSTRACT FROM AUTHOR]

Abstract Carbon emissions trading is one of the important economic means to solve the environmental externality. Based on the data of CO 2 emissions from the thermal power plants over the period from 2005 to 2010 in China, this paper uses no-parametric optimization models to estimate the potential economic gains and potential carbon emissions reduction under three allocation strategies of carbon emissions trading allowance. Results show that the maximum potential gains can be obtained by the spatial allocation scenario for the combination of CO 2 -SO 2 emissions trading, and the output growth ratio among power plants varies huge. The establishment of jointed CO 2 -SO 2 emissions trading is usually highly beneficial to achieve the three targets, including the optimal allocation of resources, the increase of potential gains and the reduction of pollutant emissions. [ABSTRACT FROM AUTHOR]