Researches On Energy And Environmental Efficiency Based On Data Envelopment Analysis (DEA)

Ensuring energy supply, protecting the environment and promoting economic growth are three main goals of energy and environmental issues. The harmonious development of energy, environment and economy is mainly related to the aspects of the evaluation of energy and environmental efficiency, cleaner production, energy-saving technology, and energy and environmental policy. Specifically, the evaluation of energy and environment efficiency is a key issue. Effective and rational evaluation can provide accurate information for the energy and environmental policies and the implementation of energy conservation programs. In data envelopment analysis (DEA) framework, this paper focuses on energy and environmental efficiency evaluation, and mainly characterizes some special issues, such as the strategies of decision makers, the uncertainty of carbon emissions, and the difficulties in saving energy and reducing carbon emissions.The paper is organized as follows:In Chapter 1, we first illustrate the importance of the evaluation of energy and environmental efficiency. Then we review the DEA approach and the existing research on the evaluation of energy and environmental efficiency. Finally, we introduce the research methods, the main contents and the research significances.In Chapter 2, we first characterize the decision makers’different strategies for satisfying the environmental regulations. Then, based on the current literature and the range-adjusted measure (RAM), we propose non-radial DEA models to measure the unified efficiency (i.e., economic and environmental efficiency) under different strategies (i.e., increasing the capital investment and decreasing all inputs), and analyze the impact of transforming strategy on unified efficiency. In addition, we apply the proposed approach to study the unified efficiencies of regional industries in China (2006-2010).In Chapter 3, we first depict the uncertainty of CO2 emissions, and illustrate the important of this uncertainty on the evaluation of energy and CO2 emission efficiency. Then, based on chance constrained programming (CCP), we propose a radial stochastic DEA model, and extend the radial model to a non-radial one for evaluating pure energy and CO2 emission efficiencies. Furthermore, based on the non-radial model, we provide the measures of energy efficiency, CO2 emission efficiency, energy saving potential and CO2 emission reduction potential. We apply the proposed approach to evaluate regional efficiencies of energy and CO2 emission in China (2010).In Chapter 4, based on the difficulties in the advancement of energy conservation technology and the adjustment of energy consumption structure, we introduce the customized targets, and provide a step-by-step mechanism of energy saving and carbon emissions reduction for the inefficient decision-making unites (DMUs). In addition, we apply the proposed approach to analyze the regional energy saving and carbon emissions reduction targets in China.In Chapter 5, we summarize this study, and offer some suggestions for further research.In this paper, from the theoretical and practical perspective, we study three practical problems in the process of energy and environmental efficiency evaluation. Contributions of this paper are summarized as follows:(1) In Chapter 2, we provide a positive strategy (i.e., increasing capital investment in clean production technology) to increase the desirable outputs and decrease the undesirable outputs simultaneously. It can not be done by applying conventional DEA methods. In addition, we also provide the detailed targets for the adjustments of inputs, desirable outputs, and undesirable outputs.(2) In Chapter 3, we consider stochastic CO2 emissions in DEA framework, and our stochastic approach has higher efficiency discriminating power than traditional deterministic DEA models. Specifically, the stochastic DEA model can identify extremely efficient DMUs. This can not be found by adopting traditional deterministic approaches.(3) In Chapter 3, the uncertainty of CO2 emission has significant impacts on energy and CO2 emission efficiencies, especially on CO2 emission efficiency. It implies that decision makers should pay attention to the uncertainty of CO2 emissions in the process of efficiency evaluation, and ignoring the uncertainty would result in biased performance scores.(4) In Chapter 4, we analyze the difficulties in saving energy and reducing CO2 emissions, and provide a step-by-step mechanism of energy saving and CO2 emissions reduction for inefficient DMUs. This is consistent with the real situations, and also useful to the implementation of energy conservation and CO2 emissions reduction.