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ID:
126593
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| Publication |
2013.
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| Summary/Abstract |
In the process of setting operational targets to achieve sustainable development of economy, environment and natural resources, estimation of potential energy saving and potential CO2 emission reduction becomes extremely important. This estimation can be conducted based on the energy efficiency evaluation for different decision-making units (DMUs) by data envelopment analysis (DEA). Non-fossil energy is an important component of energy consumption in China, and it has great impacts on energy efficiency and energy-related carbon dioxide (CO2) emissions. This paper proposes a non-radial DEA model to evaluate regional energy efficiencies in China. In the proposed model, non-fossil energy is treated as a fixed input. Based on the model, a method of measuring potential energy saving and CO2 emission reduction for efficiency improvement is also presented. The proposed approaches are illustrated by using a regional dataset in China. Based on the application results, some implications for improving energy efficiency and reducing CO2 emissions in China are provided.
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| 2 |
ID:
094879
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2010.
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| Summary/Abstract |
Data envelopment analysis (DEA) has been widely used in energy efficiency and environment efficiency analysis in recent years. Based on the existing environment DEA technology, this paper presents several DEA models for estimating the aggregated efficiency of resource and environment. These models can evaluate DMUs' energy efficiencies and environment efficiencies simultaneously. However, efficiency ranking results obtained from these models are not the same, and each model can provide some valuable information of DMUs' efficiencies, which we could not ignore. Under this situation, it may be hard for us to choose a specific model in practice. To address this kind of performance evaluation problem, the current paper extends Shannon-DEA procedure to establish a comprehensive efficiency measure for appraising DMUs' resource and environment efficiencies. In the proposed approach, the measure for evaluating a model's importance degree is provided, and the targets setting approach of inputs/outputs for DMU managers to improve DMUs' energy and environmental efficiencies is also discussed. We illustrate the proposed approach using real data set of 30 provinces in China.
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