基于贝叶斯网络的林业碳汇项目风险评价

【目的】发展林业碳汇是应对气候变化的重要途径,随着我国碳交易市场的逐步建立与完善,林业碳汇项目开发受到广泛关注,发展前景良好,但也面临诸多不确定性与风险。基于贝叶斯网络原理,对林业碳汇项目进行系统风险评价,为项目风险管理提供参考。【方法】以中国核证自愿减排(China certified emission reduction,CCER)林业碳汇项目为研究对象,利用多领域林业碳汇专家知识,通过确定网络结构与计算风险参数,构建基于贝叶斯网络的林业碳汇项目风险评价模型。结合专家访谈和实地调研信息,确定林业碳汇项目风险清单,并在此基础上确定风险贝叶斯网络结构;根据专家对各类风险因子发生概率及影响大小的打分,利用熵权法计算风险因子权重,以此获得每位专家对于风险源及总风险的评价结果,得到贝叶斯网络运行的全部参数。利用构建的风险评价模型,测度CCER林业碳汇项目整体风险水平并判断各类风险的主要风险因子;考虑不同类型CCER林业碳汇项目的特征差异,对该风险评价模型进行适应性调整,纳入项目类型节点,通过贝叶斯网络的节点概率模拟功能,计算4类CCER林业碳汇项目的风险值,比较不同类型CCER林业碳汇项目的风险差异。【结果】①CCER林业碳汇项目整体风险值为1.932,四大类风险的风险水平由高到低分别为政策风险、市场风险、技术风险和自然风险,风险值分别为2.150、2.022、1.925、1.546;②CCER林业碳汇项目中政策风险的主要风险因子为林业碳汇交易规则变化、国家减排政策变化;市场风险的主要风险因子为劳动力价格上涨、土地租金上涨;技术风险的主要风险因子为项目未能获得签发、项目未能获得备案;自然风险的主要风险因子为病虫害、森林火灾;③不同类型CCER林业碳汇项目风险水平由高到低分别为碳汇造林项目、竹子造林项目、森林经营项目、竹林经营项目,风险值分别为2.221、2.121、1.954、1.705。【结论】贝叶斯网络能够综合考虑风险水平及风险影响关系两方面信息,在项目风险评价方面具有一定优势。当前条件下CCER林业碳汇项目风险水平中等,政策风险与市场风险相对较高,企业主体参与林业碳汇项目投资决策时,应密切关注碳汇市场相关政策变化,对项目风险进行科学评估;有关部门应注重降低政策不确定性引发的系统性风险,并提高碳汇市场的稳定性与活跃性;简化林业碳汇项目开发程序,以降低项目开发的交易成本。

Risk assessments of forestry carbon sequestration projects based on Bayesian network

【Objective】Developing forestry carbon sequestration is an important way to address climate change. With the gradual establishment and improvement of China’s carbon markets, forestry carbon sequestration projects have received widespread attention and have good development prospects, but they also face many uncertainties and risks. This study conducted a systematic risk assessment for forestry carbon sequestration projects under the Bayesian network principle and provided a scientific reference for risk management for other projects.【Method】Taking CCER (China certified emission reduction) forestry carbon sequestration projects as the research object, and using expert knowledge form multi-domain forestry carbon sequestration, this study constructed a risk assessment model for forestry carbon sequestration projects based on the Bayesian network by determining the network structure and calculating risk parameters. We combined the information of expert interviews and investigations to determine the risk list, and then determined the Bayesian network structure associated with the risk. We used the entropy weight method to calculate risk factor weight according to the expert’s scoring of the occurrence probability and the impact of various risk factors, so as to obtain the assessment result of each expert on the risk source and the total risk. Finally, all the parameters of the Bayesian network operation were obtained. Using the constructed risk assessment model, we measured the overall risk level of CCER forestry carbon sequestration projects and determined the main risk factors for various risks. Considering the differences in the characteristics of different types of CCER forestry carbon sequestration projects, the risk assessment model was adaptively adjusted by including project-type nodes. This was done to calculate the risk values of four types of CCER forestry carbon sequestration projects through the node probability simulation function of the Bayesian network and to compare the risk diffe-rences of different types of these four projects.【Result】①The overall risk value of CCER forestry carbon sequestration projects was 1.932. Further, the risk levels of the four types from high to low were policy risk, market risk, technical risk, and natural risk, with the corresponding risk values being 2.150, 2.022, 1.925 and 1.546, respectively. ②For CCER forestry carbon sequestration projects, the main risk factors of policy risk were changes in forestry carbon sequestration trading rules and changes in national emission reduction policies. Meanwhile, the main risk factors of market risk included rising labor prices and rising costs of rented land. The main risk factors of technical risk were the projects failing to be issued and the projects failing to be filed; whereas, the main risk factors of natural risk included diseases, pests, and forest fires. ③The risk levels of different types of CCER forestry carbon sequestration projects from high to low were carbon sequestration afforestation project, bamboo afforestation project, forest management project and bamboo forest management project, with risk values of 2.221, 2.121, 1.954 and 1.705, respectively.【Conclusion】The Bayesian network can comprehensively consider both risk level and risk impact information, and had certain advantages in the project risk assessment. The risk level of CCER forestry carbon sequestration projects was medium, and the policy risks and market risks were relatively high under the current conditions. When making investment decisions for forestry carbon sequestration projects, enterprise entities should pay close attention to changes in carbon sequestration market policies and scientifically to evaluate project risks. Relevant departments should focus on reducing systemic risks caused by policy uncertainties, and improve the stability and activity of the carbon sequestration market, as well as simplify the development process of forestry carbon sequestration projects to reduce the transaction costs of the project development.