应对气候变化、实现低碳转型是一项长期而艰巨的任务，也是一项复杂而综合的系统工程，需要明确的目标设置、合理的目标分解方法和科学的政策机制设计。因此，构建整合全球及中国分区数据的能源经济模型，对于分析政策对于经济、能源和排放的全国和区域影响，提出合理的政策建议十分重要。针对以上需求，本文开发构建了动态、多区、混合，充分考虑我国经济、能源系统特点，将最新全球与中国分区的能源、经济价值量和物理量数据整合一致的一般均衡模型——中国分区能源经济模型（China Regional Energy Model, 简称C-REM）。本文应用模型开展了针对节能减排政策的目标设置、分解和机制设计的多项案例分析，拓展改进了将可再生能源技术在CGE模型中详细建模的方法学。论文的主要结论有：（1）尽管“十二五”期间GDP碳强度下降指标在分解时已对中、西部地区有所倾斜，但相对于东部地区，中、西部地区的居民福利损失仍然较大；（2）建立全国性碳排放权交易市场能够通过充分利用各省成本较低的减排机会，使得全国平均居民福利损失相比分省独立碳市场的情况降低20%左右；（3）我国不同区域间通过国内贸易存在着大量的内涵排放转移，但若以消费内涵排放为基准分解减排目标，会显著增加福利损失，对于政策公平性的改善也较为有限；（4）建立全国碳市场可不影响效率的前提下，通过选择最能为大众所接受的居民福利变化分布对应的分解方案，来实现减排责任分配的公平性，受访的相关研究人员大多认为东部地区应承担较多的减排责任；（5）在实现相同绝对碳减排量的前提下，近期控制化石能源消费总量和控制碳排放总量的政策效果接近，反映出我国目前节能与减排工作的高度相关性；（6）与能源消费总量控制目标相比，能源强度目标作为分省层面的近中期节能减排目标更具稳健性；（7）当前的风电补贴水平基本能够支持我国完成2020年风电发展目标。相应的，本文提出以下政策建议：（1）在各试点地区开展碳交易试点工作的同时，应及时总结试点经验，加快全国统一碳市场的制度设计工作；（2）需要谨慎考虑是否将能源消费总量控制目标也设定为分省节能减排工作的约束性目标；（3）制定风电等可再生能源的发展目标和规划时，需要综合考虑资源禀赋、需求特征、网架结构以及支持预算等多方面因素；（4）需要更加重视经济、能源的统计工作，提升统计数据的时效性和可靠性，加强统计数据和统计口径的透明公开，努力解决中央、地方数据“两张皮”的现象。
Addressing climate change and transforming to a low-carbon economy has been an arduous and demanding task as well as a complicated and comprehensive system engineering challenge which calls for clear target setting, reasonable target allocation methods and scientific policy mechanism designing. Therefore, it is significant to establish an energy economic model that integrates global and China’s regional data for studying the impacts of energy and climate policies on economic, energy and emissions and for providing reasonable policy recommendations.For the above purpose, the present study develops and constructs the China Regional Energy Model (C-REM) which is a dynamic, multi-regional and comprehensive computable general equilibrium (CGE) model and integrates the latest global and China’s regional energy and economic flows measured by both value and physical unit. The paper employs the model to present case studies of target setting, allocation and mechanism design of energy saving and emissions reduction policy. Furthermore, the paper improves the methodology for renewable energy modeling in CGE modeling.Results show that (1) even though emission intensity reduction targets have been allocated more favorable for the central and western provinces, compared to eastern ones, central and western provinces still suffer more from relatively larger household welfare loss; (2) a national emissions trading market can fully utilize low-cost emissions reduction opportunities in all provinces so as to mitigate the welfare loss by around 20% compared to independent provincial level carbon markets; (3) considerable amount of emissions are embodied in domestic inter-regional trades in China; however, if the provincial targets are allocated based on emissions embodied in consumption, significant additional welfare loss will be caused, which could hamper the improvement of policy fairness; (4) a national emissions trading market can achieve the fairness of distributing emissions reduction responsibilities by choosing the permit allocation scheme which could lead the most acceptable distributional impacts without deteriorating the efficiency. Most of the interviewees believe that the eastern provinces should bear more reduction responsibilities; (5) With the same amount of absolute carbon emissions reduction, the impacts of fossil energy consumption cap is similar to carbon emissions cap in the near term, which reflects a strong correlation between the current energy saving and emissions reduction policies in China; (6) Compared to the energy consumption control targets, energy intensity targets at the provincial level in the mid-term are of more robustness; (7) The current wind power subsidy level is adequate to support the 2020 wind development target.The paper further provides the following policy recommendations. (1) The process of designing a national emissions trading market should be accelerated based on the experience of pilot markets; (2) Considerations should be taken when deciding whether the energy consumption control target should be set at provincial level; (3) Resource endowment, demand features, grid structure and subsidy budget should be taken into consideration when setting development targets and plans for renewable energy such as wind power; (4) More emphasis should be placed on statistic works in economic and energy aspects to improve the time effectiveness and validity of the data. Transparency should be improved in terms of data collection and calibration so as to bridge the gap between national value and provincial aggregates.
