基于贝叶斯网络的控排企业林业碳汇需求机理与仿真研究

doi:10.18402/resci.2018.09.12

摘要/Abstract

摘要：

研究控排企业的林业碳汇需求,对于引导企业科学选择减排路径与有效发挥林业碳汇抵消企业碳排放的作用而言至关重要。以控排企业为对象,将其对林业碳汇抵消碳排放机制的认知与响应统一纳入贝叶斯网络,从而揭示控排企业林业碳汇需求机理,并从林业碳汇减排量、抵消比例、价格决定、风险承担等多个维度进行仿真。研究表明：林业碳汇需求是控排企业自身及环境因素复杂作用的动态过程;尽管在森林增汇与减排方面表现出较高的认知与认可,但面对当前充裕的碳配额及不明确的林业碳汇市场预期,控排企业期望林业碳汇占CCER的比例及购买林业碳汇的意愿并不高,且倾向于林业碳汇的价格由政府主导,而风险由交易双方共担。因此,激发林业碳汇需求须在掌握控排企业阶段性特征的基础上,通过碳交易制度创新,推进排放配额管理及林业碳汇融入国家碳排放权交易体系,同时稳定企业购买林业碳汇的收益预期。

关键词: 林业碳汇, 控排企业, 需求, 贝叶斯网络

Abstract:

To guide enterprises for a scientific identification the path of emission reduction and effectively plays an offset role of forestry carbon sequestration to the carbon emissions. It is vital to study the enterprises’ demand for forestry carbon sequestration. The carbon emission control enterprises, i. e., the cognition and response of forestry carbon sequestration carbon offset mechanism are integrated into a Bayesian network. The current study illustrated the mechanism of forestry carbon sequestration demand and simulated the multi-dimensions such as the emission reduction, offset ratio, price determination, and risk sharing of forestry carbon sequestration. The demand for forestry carbon sequestration is a dynamic process of the complicated action among the carbon emission control enterprises and the environmental factors. The carbon emission control enterprises did show a high recognition and accreditation of increasing carbon sink and reducing emission of forest. Confronted with the abundant carbon quota as well as the unclear expectation of forestry carbon sequestration, the expected proportion of forestry carbon sequestration to CCER and the willingness to buy forestry carbon sequestration are not high. And the prices of forestry carbon sequestration are inclined to be dominated by the government and the risks are expected to be shared by both trading parties. In order to stimulate the demand for forestry carbon sequestration, based on the stage characteristics of the carbon emission control enterprises, the government should promote the allocation of emission quotas and forestry carbon sequestration into the national carbon emissions trading system through the carbon trading system innovation, with stabilizing prospective earnings from purchasing of forestry carbon sequestration.

Key words: forestry carbon sequestration, carbon emission control enterprises, demand, Bayesian Network

祁慧博, 龙飞. 基于贝叶斯网络的控排企业林业碳汇需求机理与仿真研究[J]. 资源科学, 2018, 40(9): 1822-1830.

Huibo QI, Fei LONG. Mechanism and simulation of carbon emission control enterprises’ forestry carbon sequestration demand based on Bayesian Network[J]. Resources Science, 2018, 40(9): 1822-1830.

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P(个体特征∣认知)		是否了解森林在		是否了解林业碳汇交易		是否了解CCER
		气候变化中的作用		是否了解林业碳汇交易		是否了解CCER
		是	否	是	否	是	否
学历	大专	0.24	0.45	0.20	0.47	0.14	0.63
	本科	0.45	0.35	0.45	0.38	0.50	0.28
	硕士	0.30	0.20	0.35	0.15	0.36	0.09
行业	电力	0.36	0.32	0.32	0.38	0.33	0.36
	钢铁	0.33	0.35	0.34	0.33	0.34	0.33
	化工	0.31	0.33	0.34	0.29	0.33	0.31
职位	中层管理者	0.15	0.20	0.12	0.23	0.10	0.26
	基层管理者	0.40	0.23	0.38	0.30	0.40	0.28
	专业技术员	0.30	0.26	0.33	0.23	0.33	0.23
	一般员工	0.15	0.30	0.17	0.25	0.16	0.23
部门	研发	0.04	0.08	0.50	0.06	0.03	0.10
	能源	0.64	0.41	0.62	0.47	0.65	0.49
	行政管理	0.32	0.51	0.33	0.46	0.32	0.40

P(认知,环境∣评价)		与其他减排项目相比,林业碳汇项目减排量如何
P(认知,环境∣评价)		更好	一般	更差
是否了解森林在气候变化中的作用	是	0.86	0.70	0.62
是否了解森林在气候变化中的作用	否	0.14	0.30	0.38
是否了解林业碳汇交易	是	0.84	0.59	0.59
是否了解林业碳汇交易	否	0.16	0.41	0.41
本企业在低碳方面可以领先同行其他企业	完全不同意	0.46	0.49	0.49
	不同意	0.37	0.28	0.32
	不确定	0.16	0.21	0.18
	同意	0.01	0.02	0.01
	完全同意	0.00	0.00	0.00
通过技术减排完成减排指标很困难	完全不同意	0.28	0.13	0.16
	不同意	0.34	0.23	0.18
	不确定	0.19	0.26	0.13
	同意	0.11	0.23	0.33
	完全同意	0.07	0.15	0.21

P(需求∣期望)		林业碳汇价格应如何决定				林业碳汇风险应由谁承担
P(需求∣期望)		市场决定	政府调控	市场为主,政府为辅	政府为主,市场为辅	买方承担	卖方承担	买卖双方共同承担
是否必要强制购买林业碳汇	是	0.69	0.71	0.84	0.81	0.83	0.51	0.81
是否必要强制购买林业碳汇	否	0.31	0.29	0.16	0.19	0.17	0.49	0.19
愿意购买林业碳汇用于抵消碳排放	完全不同意	0.16	0.17	0.34	0.06	0.06	0.03	0.29
	不同意	0.09	0.38	0.23	0.05	0.04	0.03	0.29
	不确定	0.48	0	0.06	0.02	0	0.26	0.22
	同意	0.13	0.24	0.19	0.37	0.38	0.39	0.10
	完全同意	0.13	0.20	0.19	0.50	0.52	0.29	0.10
林业碳汇占CCER的比例	5%以下	0.22	0.35	0.28	0.64	0.63	0.58	0.15
	5%~10%	0.40	0.56	0.62	0.17	0.17	0.19	0.64
	10%以上	0.38	0.08	0.10	0.19	0.20	0.23	0.21