Disaggregation of energy-saving targets for China's provinces: modeling results and real choices

Disaggregation of energy-saving targets for China's provinces: modeling results and real choices
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中国各省节能目标分解:建模结果与实际选择

DOI:
10.1016/j.jclepro.2014.09.079
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发表时间:
2015-09
影响因子:
11.1
通讯作者:
Zhao B. H.
Zhao B. H.
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Zhang L. X.;Feng Y. Y.;Zhao B. H.

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从“十一五”开始,到“十二五”,中国制定了能效提升的量化和约束性目标。借鉴国际上气候变化负担分担的经验,提出了中国省级节能目标分解的框架。基于公平和效率的原则,通过权衡责任、能力和潜力的不同选择偏好,建立了四个情景。此外,还建立了考虑或忽略边际节能成本的非线性和线性分配模型。将该框架应用于十二五期间国家节能16%目标的分解,结果表明,最终的分配方案在很大程度上取决于决策者的选择偏好。37.26%的极端减排目标落在上海采用线性分配法的责任偏好(RP)方案中,而考虑边际节能成本的能力偏好(CP)情景与30个省份接受的实际方案最为接近。制定这样一个框架可以作为一种可行的政策工具,帮助中国以具有成本效益的方式并根据其区域发展战略实现其保护目标。
Starting with the 11th Five-Year Plan (FYP) and continuing in the 12th FYP, quantitative and binding targets have been set for energy-efficiency improvement in China. Drawing on international experience in burden-sharing on climate change, this paper presents a framework for provincial-level disaggregation of energy-saving targets in China. Based on principles of equity and efficiency, four scenarios have been established by weighting different choice preferences of responsibility, capacity, and potential. In addition, nonlinear and linear allocation models have been developed by considering or ignoring marginal energy-saving cost. When this framework was applied to the disaggregation of the national energy saving target of 16% during the 12th FYP, the results show that the final allocation schemes are largely determined by the policy maker's choice preferences. The extreme reduction target of 37.26% fell to Shanghai under responsibility preferring (RP) using the linear allocation method, while the capability preferring (CP) scenario considering marginal energy-saving cost is the closest to the actual scheme accepted by the 30 provinces. Development of such a framework may serve as a feasible policy instrument to help China achieve its conservation targets in a cost-effective way and in accordance with its regional development strategies.
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