中国作为最大的发展中国家，同时，作为温室气体排放的主要国家之一，在气候变化领域既面临着来自诸如CDM等合作机制的资金与技术，更面临着来自发达国家的要求承诺减排的谈判压力。综合地考虑能源、环境和经济的相互影响，定量地评估国际气候谈判中潜在的代价与收益，是进行科学决策的必要基础。 本研究建立了一个综合描述中国经济、能源、环境系统的动态可计算一般均衡（CGE）模型（TEDCGE），用于分析在中国实施温室气体控制政策的代价；同时，建立了一个全球碳排放贸易局部均衡模型（TRCW），用于研究中国的CDM市场潜力。TEDCGE包括10个部门（其中4个能源部门）、两类消费者，采用递推动态机制，由1997年投入产出表构建的社会核算矩阵（SAM）校准参数。TRCW模型根据马拉喀什协定的相关规定考虑了美国的退出、碳汇项目、热空气规模、交易成本、适应性基金、垄断供给等现实因素，同时，中国的成本数据来自TEDCGE，可考察中国CDM市场潜力在各部门间的分配。利用上述模型，对2010年在中国实施碳税政策的假设情景进行了模拟；对京都议定书第一承诺期的CDM市场结构进行了分析；对CGE模型的不确定性进行了研究，包括参数的先验分布及其不确定性的传播、参数的全局灵敏度分析。 研究结果表明：控制中国温室气体排放的社会代价很高，是减排技术成本的2倍；马拉喀什协定下中国的CDM市场规模很小，利润收入仅约1.5亿$/年，其中重工业和电力分别占40%和20%左右；CGE模型结果对部分参数比较敏感，并且不同输出变量对应的敏感参数并不完全一样；在TEDCGE模型中碳税水平对资本/能源替代弹性及能源间替代弹性非常敏感，而影响GDP损失率的关键参数只有能源间替代弹性；从部门参数来看，重工业和电力行业的上述替代弹性对结果的影响很大，而其它行业的则很小。
Being the largest developing country, as well as a major Greenhouse Gases (GHGs) emission source in the world, China is not only facing potential benefits from investments and technology transfer through the cooperation mechanisms, e.g. Clean Development Mechanism (CDM), but also the increasing critical negotiation pressures requiring to take the burden of mitigation. This thesis is thus focusing on providing a supporting analytical framework for determining and assessing relevant policies, which explicitly incorporate potential costs and benefits confronted in the international climate change negotiation. Within the framework, the computable general equilibrium (CGE) approach was employed to develop an integrated dynamic energy-economy-environment model (TEDCGE) for China’s climate change policy analysis, and a partial equilibrium model of global carbon reduction trade (TRCW) was constructed to simulate the market structure of CDM under different scenarios. The TEDCGE was developed through a recursive dynamic mechanism and consisted of 10 sectors and 2 types of consumers. It was calibrated through the social accounting matrix (SAM), derived mainly from the latest 1997 input-output table published by the central government. In contrast to the current carbon trade models treating China as a separate region and using inputs from other global general equilibrium models, the TRCW applied China’s marginal abatement cost curve from TEDCGE. This enabled the coupling model to simulate the market structure of CDM within the framework taking into account both externally international share and internally sectoral distribution. A number of factors that may influence the magnitude of the CDM were described in the TRCW, which, among others, included the carbon sink project, ‘supplementarity’ restriction, limits on use of the three flexible mechanisms, transaction cost, adaptation fund, monopolistic supply, the America’s rejection of the Kyoto Protocol, and so on. Applying a counterfactual carbon tax policy in 2010 to the TEDCGE to perform a holistic assessment of the impacts on China’s macro- and sectoral economy gave a representation of potential costs of controlling the GHGs. On the other hand, the potential profits or the size of CDM from the international cooperation was estimated by inputting the stipulations of the Marrakech Accords into the TRCW for the First Commitment Period (2008-2012). In addition, the parameter uncertainty in the CGE modeling was investigated. All the substitution elasticities in the model were treated as random variables drawn from pre-specified distributions that were established on the basis of literature review. The uncertainty propagation was analyzed through a Monte Carlo simulation, and the relative importance of each parameter to the deviations of CGE model’s output was identified by a global sensitivity analysis. The results indicated that there was a high social cost for curbing GHGs emissions in China, which was about two times of the technical abatement cost. A low demand, low price international carbon market scenario was likely present under the Marrackech Accords. Consequently, the CDM potential of China for the First Commitment Period was estimated to be only about 150 million $ of profits per year, for which the heavy industry and electricity may account 40% and 20% respectively. The uncertainty analysis concluded that not only was describing uncertainty in CGE model possible, but that it had important quantitative and qualitative consequences. “Analyses without consideration of uncertainty were therefore likely to be misleading in their conclusions”. The CGE model results were sensitive to part of the parameters, and the critical parameters to different endogenous variables were varied. The carbon tax level corresponding to a predefined carbon reduction rate in TEDCGE, for example, was quite sensitive to both capital-energy substitution elasticity and inter-fuel substitution elasticity in production function, while the key parameter for GDP loss rate was only the inter-fuel substitution elasticity. From the view of sectoral parameter comparison, the heavy industry and electricity were of vital importance.
