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首页> 外文期刊>Journal of Cleaner Production >A more scientific allocation scheme of carbon dioxide emissions allowances: The case from China
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A more scientific allocation scheme of carbon dioxide emissions allowances: The case from China

机译:更科学的二氧化碳排放配额分配方案:以中国为例

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Efficient allocation of carbon dioxide (CO2) emissions allowances is essential to the realization of the emissions reduction goal. Using China as an example, this study applies a zero sum gains data envelopment analysis (ZSG-DEA) model to translate the country's reduction target into provincial goals based on the Chinese government's 2020 reduction goal. To evaluate efficiency scores, we employ the Epsilon based measure model that combines radial and non-radial characteristics. Different from prior studies, we emphasize the effect of industrial structure on CO2 emissions and calculate a composite gross domestic product (GDP) index as one of the output variables. By utilizing the ZSG-DEA model and based on China's provincial CO2 emissions allowances as the input variable, the composite GDP index, and the population as the output variable, we obtain an optimal reallocation scheme after four iterations. A comparison between the results and official reduction goals shows that the government should increase CO2 emissions allowances appropriately for most provinces with high proportions (more than 40%) of second industry increment in GDP, thereby carrying implications for policymakers. With China as an example, these findings have global implications as regards developing a more scientific allocation scheme, especially for regions with unbalanced industrial structures. (C) 2019 Elsevier Ltd. All rights reserved.
机译:有效分配二氧化碳(CO2)排放配额对于实现减排目标至关重要。以中国为例,本研究应用零和收益数据包络分析(ZSG-DEA)模型,根据中国政府的2020年减排目标将国家的减排目标转化为省级目标。为了评估效率得分,我们采用了基于Epsilon的测量模型,该模型结合了径向和非径向特征。与先前的研究不同,我们强调产业结构对CO2排放的影响,并计算综合国内生产总值(GDP)指数作为产出变量之一。通过使用ZSG-DEA模型,并以中国的省级CO2排放配额为输入变量,复合GDP指数和人口为输出变量,我们经过四次迭代获得了最优的再分配方案。结果与官方减排目标之间的比较表明,政府应适当提高大部分第二产业占GDP比例较高(超过40%)的省份的CO2排放配额,从而对决策者产生影响。以中国为例,这些发现对于制定更科学的分配方案具有全球意义,特别是对于产业结构不平衡的地区。 (C)2019 Elsevier Ltd.保留所有权利。

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