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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Measuring the Energy and Carbon Emission Efficiency of Regional Transportation Systems in China: Chance-Constrained DEA Models
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Measuring the Energy and Carbon Emission Efficiency of Regional Transportation Systems in China: Chance-Constrained DEA Models

机译：测量中国区域交通系统的能源和碳排放效率：机会约束的DEA模型

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摘要

In China, the transportation sector contributes about 18% of the total carbon emissions. This research contributes to measuring the energy and carbon emission efficiency (ECEE) of regional transportation systems (RTS) in China considering uncertain carbon emissions. A radial chance-constrained data envelopment analysis (DEA) model is developed to estimate the overall efficiency, and a nonradial chance-constrained DEA model is presented to evaluate the pure energy efficiency (PEE) and the pure carbon emission efficiency (PCEE). We prove that the proposed chance-constrained DEA models can effectively address the uncertain carbon emissions when measuring efficiency. We find that most of China’s RTS have low ECEE and the inefficiencies are mainly due to the lower gasoline utilization efficiency and the lower kerosene utilization efficiency. In addition, east China performs better than central China, and central China performs better than west China. In China, the unbalanced regional development of the ECEE in transportation corresponds with the unbalanced regional economic development. We provide some valuable suggestions based on the evaluation of the potential cuts in each kind of energy and the potential decreases in carbon emissions.
机译：在中国，交通部门占总碳排放量的约18％。考虑到不确定的碳排放，该研究有助于测量地区交通系统（RTS）的能源和碳排放效率（RTS）的能源和碳排放效率（RTS）。开发了一种径向机会约束的数据包络分析（DEA）模型来估计整体效率，并且提出了一种非分离机会约束的DEA模型来评估纯能效（PEE）和纯碳排放效率（PCEE）。我们证明，当测量效率时，所提出的机会约束的DEA模型可以有效地解决不确定的碳排放。我们发现，中国大部分RTS都有低eCEE，效率低下主要是由于汽油利用效率较低和煤油利用率较低的效率。此外，华东表现优于中国中部，中美洲比西部更好。在中国，eCEE在交通的不平衡区域发展与不平衡的区域经济发展相符。我们根据每种能量中的潜在切割的评估提供一些有价值的建议，并且碳排放量的潜力降低。

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