Risk assessments of forestry carbon sequestration projects based on Bayesian network

doi:10.12302/j.issn.1000-2006.201912050

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2021, Vol. 45 ›› Issue (4): 210-218.doi: 10.12302/j.issn.1000-2006.201912050

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Risk assessments of forestry carbon sequestration projects based on Bayesian network

GAO Qinyi¹(), PAN Chunxia², LIU Qiang¹^,³, GU Guangtong¹, ZHU Yalu¹, WU Weiguang¹^,³^,^*()

1. School of Economics and Management, Zhejiang Agriculture and Forestry University,Lin’an 311300, China
2. Anji County Natural Resources and Planning Bureau, Anji 313300, China
3. Research Academy for Rural Revitalization of Zhejiang Province, Zhejiang Agriculture and Forestry University, Lin’an 311300,China

Received:2019-12-24 Accepted:2020-04-15 Online:2021-07-30 Published:2021-07-30
Contact: WU Weiguang E-mail:gggqy66@163.com;wuwgccap@126.com

Abstract

Abstract:

【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.

Key words: forestry carbon sequestration, risk assessment, Bayesian network, China certified emission reduction (CCER)

CLC Number:

S7-9
F316.2

GAO Qinyi, PAN Chunxia, LIU Qiang, GU Guangtong, ZHU Yalu, WU Weiguang. Risk assessments of forestry carbon sequestration projects based on Bayesian network[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2021, 45(4): 210-218.

Figures/Tables 6

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References 26

[1]	DANG P T H, BROUWER R, DAVIDSON M. The economic costs of avoided deforestation in the developing world:a meta-analysis[J]. J For Econ, 2014, 20(1):1-16.DOI: 10.1016/j.jfe.2013.06.004. doi: 10.1016/j.jfe.2013.06.004
[2]	王科, 陈沫. 中国碳交易市场回顾与展望[J]. 北京理工大学学报(社会科学版), 2018, 20(2):24-31.
	WANG K, CHEN M. Review and prospect of China’s carbon trading system[J]. J Beijing Inst Technol(Soc Sci Ed), 2018, 20(2):24-31.DOI: 10.15918/j.jbitss1009-3370.2018.5237. doi: 10.15918/j.jbitss1009-3370.2018.5237
[3]	石柳, 唐玉华, 张捷. 我国林业碳汇市场供需研究:以广东长隆碳汇造林项目为例[J]. 中国环境管理, 2017, 9(1):104-110.
	SHI L, TANG Y H, ZHANG J. Supply-demand analysis of the forest carbon sink market in China:illustrated by the Guangdong Chimelong Sink Afforestation Project[J]. Environ Conformity Assess, 2017, 9(1):104-110.DOI: 10.16868/j.cnki.1674-6252.2017.01.104. doi: 10.16868/j.cnki.1674-6252.2017.01.104
[4]	陈娟丽. 我国林业碳汇存在的障碍及法律对策[J]. 西北农林科技大学学报(社会科学版), 2015, 15(5):154-160.
	CHEN J L. Obstacles existing in China’s forestry carbon sequestration and legal countermeasures[J]. J Northwest A F Univ(Soc Sci Ed), 2015, 15(5):154-160.DOI: 10.13968/j.cnki.1009-9107.2015.05.024. doi: 10.13968/j.cnki.1009-9107.2015.05.024
[5]	武曙红, 张小全. CDM林业碳汇项目的非持久性风险分析[J]. 林业科学, 2007, 43(8):123-126.
	WU S H, ZHANG X Q. Analyses on non-permanence issues of CDM forestry project[J]. Sci Silvae Sin, 2007, 43(8):123-126.DOI: 10.3321/j.issn:1001-7488.2007.08.021. doi: 10.3321/j.issn:1001-7488.2007.08.021
[6]	马建平, 庄贵阳. CDM项目开发的风险因素识别与规避对策[J]. 华中科技大学学报(社会科学版), 2011, 25(2):87-92.
	MA J P, ZHUANG G Y. Risk factor identification and avoidance measures in CDM project development[J]. J Huazhong Univ Sci Techno(Soc Sci Ed), 2011, 25(2):87-92.DOI: 10.19648/j.cnki.jhustss1980.2011.02.015. doi: 10.19648/j.cnki.jhustss1980.2011.02.015
[7]	PASGAARD M, SUN Z, MÜLLER D, et al. Challenges and opportunities for REDD+:a reality check from perspectives of effectiveness,efficiency and equity[J]. Environ Sci Policy, 2016, 63:161-169.DOI: 10.1016/j.envsci.2016.05.021. doi: 10.1016/j.envsci.2016.05.021
[8]	金婷, 吴伟光, 刘强, 等. 林业CCER碳汇项目风险评估模型与应用:以安吉竹林经营碳汇项目为例[J]. 世界林业研究, 2018, 31(4):91-96.
	JIN T, WU W G, LIU Q, et al. Risk assessment model of forestry-based CCER project and its application:a case study of Anji bamboo forest sink project[J]. World For Res, 2018, 31(4):91-96.DOI: 10.13348/j.cnki.sjlyyj.2018.0051.y. doi: 10.13348/j.cnki.sjlyyj.2018.0051.y
[9]	王丹, 王宁. 基于模糊分析的CDM项目风险评估模拟研究[J]. 资源与产业, 2011, 13(4):50-54.
	WANG D, WANG N. Simulation of CDM project risk assessment based on fuzzy analysis[J]. Resour Ind, 2011, 13(4):50-54.DOI: 10.3969/j.issn.1673-2464.2011.04.010. doi: 10.3969/j.issn.1673-2464.2011.04.010
[10]	陈卓旋, 周伟, 高岚. 基于层次分析法的碳汇林经营风险评价[J]. 林业与环境科学, 2018, 34(6):90-97.
	CHEN Z X, ZHOU W, GAO L. The evaluation of carbon forest management risks based on analytic hierarchy process[J]. For Environ Sci, 2018, 34(6):90-97.DOI: 10.3969/j.issn.1006-4427.2018.06.015. doi: 10.3969/j.issn.1006-4427.2018.06.015
[11]	YET B, CONSTANTINOU A, FENTON N, et al. A Bayesian network framework for project cost,benefit and risk analysis with an agricultural development case study[J]. Expert Syst Appl, 2016, 60:141-155.DOI: 10.1016/j.eswa.2016.05.005. doi: 10.1016/j.eswa.2016.05.005
[12]	沈屏, 周虹, 翟印礼. 林业碳汇贸易风险浅析[C]// 第二届中国林业学术大会—S10 林业与气候变化论文集.南宁, 2009:139-141.
	SHEN P, ZHOU H, ZHAI Y L. Risk analysis of forestry carbon sequestration trade[C]// The 2nd China Forestry Academic Conference:S10 Collection of Papers on Forestry and Climate Change.Nanning, 2009:139-141.
[13]	张小有, 黄冰冰, 杨华领. 江西省CDM林业碳汇项目投资探析[J]. 林业经济, 2016, 38(12):46-49.
	ZHANG X Y, HUANG B B, YANG H L. Investment analysis of CDM forestry carbon sink project in Jiangxi Province[J]. For Econ, 2016, 38(12):46-49.DOI: 10.13843/j.cnki.lyjj.2016.12.008. doi: 10.13843/j.cnki.lyjj.2016.12.008
[14]	张静娉, 高岚. 我国碳汇林经营风险的识别研究[J]. 中南林业科技大学学报(社会科学版), 2016, 10(2):14-18.
	ZHANG J P, GAO L. Research on identification of the forest carbon sinks business risk in China[J]. J Central South Univ For Technol(Soc Sci), 2016, 10(2):14-18.DOI: 10.14067/j.cnki.1673-9272.2016.02.004. doi: 10.14067/j.cnki.1673-9272.2016.02.004
[15]	张颖, 张莉莉, 金笙. 基于分类分析的中国碳交易价格变化分析:兼对林业碳汇造林的讨论[J]. 北京林业大学学报, 2019, 41(2):116-124.
	ZHANG Y, ZHANG L L, JIN S. Carbon trading price changes in China’s carbon emission rights trading trials based on classification analysis:a discussion on forestry carbon sequestration afforestation[J]. J Beijing For Univ, 2019, 41(2):116-124.DOI: 10.13332/j.1000-1522.20180198. doi: 10.13332/j.1000-1522.20180198
[16]	张颖, 曹先磊. 中国自愿减排量的开发及其发展潜力的经济学研究[C]// 2016第五届国际清洁能源论坛论文集.澳门, 2016:259-279.
	ZHANG Y, CAO X L. Economic research on development and potential of voluntary emission reduction in China[C]// Proceedings of the 5th International Clean Energy Forum 2016.Macau, 2016: 259-279.
[17]	陈晓红, 胡维, 王陟昀. 自愿减排碳交易市场价格影响因素实证研究:以美国芝加哥气候交易所(CCX)为例[J]. 中国管理科学, 2013, 21(4):74-81.
	CHEN X H, HU W, WANG Z Y. Empirical research on price impact factors of carbon exchange of vo-luntary market:evidence from CCX of USA[J]. Chin J Manag Sci, 2013, 21(4):74-81.DOI: 10.16381/j.cnki.issn1003-207x.2013.04.009. doi: 10.16381/j.cnki.issn1003-207x.2013.04.009
[18]	孙雨薇, 王灿. 碳市场政策下企业对碳信用的支付意愿及影响因素研究[J]. 中国人口·资源与环境, 2017, 27(3):11-21.
	SUN Y W, WANG C. Estimate companies’ willingness to pay for carbon credit and the influencing factors[J]. China Popul Resour Environ, 2017, 27(3):11-21.DOI: 10.3969/j.issn.1002-2104.2017.03.002. doi: 10.3969/j.issn.1002-2104.2017.03.002
[19]	周彩贤, 张峰, 于海群, 等. 北京市林业碳汇交易项目开发实践[J]. 林业经济, 2015, 37(2):118-121.
	ZHOU C X, ZHANG F, YU H Q, et al. Forestry carbon trading project development practice in Beijing[J]. For Econ, 2015, 37(2):118-121.DOI: 10.13843/j.cnki.lyjj.2015.02.022. doi: 10.13843/j.cnki.lyjj.2015.02.022
[20]	王丹舟, 杨德天. 中国碳排放权交易价格的驱动因素[J]. 首都经济贸易大学学报, 2018, 20(5):87-95.
	WANG D Z, YANG D T. Driving factors of China’s carbon emission rights’ price:based on data of Guangzhou carbon emissions exchange[J]. J Cap Univ Econ Bus, 2018, 20(5):87-95.DOI: 10.13504/j.cnki.issn1008-2700.2018.05.010. doi: 10.13504/j.cnki.issn1008-2700.2018.05.010
[21]	ALBEROLA E, CHEVALLIER J, CHÈZE B. Price drivers and structural breaks in European carbon prices 2005-2007[J]. Energy Policy, 2008, 36(2):787-797.DOI: 10.1016/j.enpol.2007.10.029. doi: 10.1016/j.enpol.2007.10.029
[22]	黄宰胜, 陈钦. 基于造林成本法的林业碳汇成本收益影响因素分析[J]. 资源科学, 2016, 38(3):485-492.
	HUANG Z S, CHEN Q. Influencing factors analysis of forestry carbon sequestration cost-benefit based on afforestation cost methods[J]. Resour Sci, 2016, 38(3):485-492.DOI: 10.18402/resci.2016.03.11. doi: 10.18402/resci.2016.03.11
[23]	何清华, 杨德磊, 罗岚, 等. 基于贝叶斯网络的大型复杂工程项目群进度风险分析[J]. 软科学, 2016, 30(4):120-126,139.
	HE Q H, Yang D L, LUO L, et al. Research of large scale and complex construction programs’ schedule risk based on Bayesian Network[J]. Soft Sci, 2016, 30(4):120-126,139.DOI: 10.13956/j.ss.1001-8409.2016.04.26. doi: 10.13956/j.ss.1001-8409.2016.04.26
[24]	KUO C. Managing ship safety[M]. London: Lloyd’s of London Press, 1998.
[25]	LEE E, PARK Y, SHIN J G. Large engineering project risk ma-nagement using a Bayesian belief network[J]. Expert Syst Appl, 2009, 36(3):5880-5887.DOI: 10.1016/j.eswa.2008.07.057. doi: 10.1016/j.eswa.2008.07.057
[26]	曹先磊, 程宝栋. 中国林业碳汇核证减排量项目市场发展的现状、问题与建议[J]. 环境保护, 2018, 46(15):27-34.
	CAO X L, CHENG B D. Market development of forestry carbon sequestration project of China certified emission reduction:current situation,challenges and suggestions[J]. Environ Prot, 2018, 46(15):27-34.DOI: 10.14026/j.cnki.0253-9705.2018.15.006. doi: 10.14026/j.cnki.0253-9705.2018.15.006

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省份 province	项目开发机构(主体) project development organization (subject)		碳市场交易平台 carbon market trading platform		高校及科研机构 universities and scientific research institutions		林业政府部门 forestry government department		其他相关部门 other relevant departments		合计 sum
省份 province	人数 number	占比/% proportion	人数 number	占比/% proportion	人数 number	占比/% proportion	人数 number	占比/% proportion	人数 number	占比/% proportion	人数 number	占比/% proportion
广东省 Guangdong	17	37.0	7	15.2	6	13.0	16	34.8	0	0.0	46	100.0
福建省 Fujian	12	36.4	0	0.0	10	30.3	6	18.2	5	15.2	33	100.0
江西省 Jiangxi	9	100.0	0	0.0	0	0.0	0	0.0	0	0.0	9	100.0
浙江省 Zhejiang	4	19.0	1	4.8	13	61.9	3	14.3	0	0.0	21	100.0
其他省 other	0	0.0	1	10.0	7	70.0	0	0.0	2	20.0	10	100.0

风险源 sources of risk	风险因子 risk factor	互信息值 mutual information value	风险源 sources of risk	风险因子 risk factor	互信息值 mutual information value
自然风险 natural risk	森林火灾	0.118	市场风险 market risk	碳价格下降	0.002
	病虫害	0.157		劳动力价格上涨	0.004
	风灾雪灾	0.105		土地租金上涨	0.004
	地质灾害	0.092		利率上涨导致融资成本增加	0.003
技术风险 technical risk	项目参与者未能按技术标准执行	0.004		碳市场供给过剩	0.002
	项目参与者未按作业设计实施	0.005	政策风险 policy risk	林业碳汇项目认定标准变化	0.047
	项目参与者中途退出项目	0.012		国家减排政策变化	0.109
	项目未能获得备案	0.014		林业碳汇交易规则变化	0.113
	项目未能获得签发	0.016		国际气候谈判进程不确定性很大	0.063

项目类型 project type	风险状态概率/% risk status distribution			风险值 risk value
项目类型 project type	低 low	中 medium	高 high	风险值 risk value
碳汇造林 carbon sequestration afforestation	22.9	32.1	45.0	2.221
森林经营 forest management	25.5	53.6	20.9	1.954
竹子造林 bamboo afforestation	10.6	66.7	22.7	2.121
竹林经营 bamboo management	41.1	47.6	11.4	1.705

Risk assessments of forestry carbon sequestration projects based on Bayesian network

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