排放交易
政府(语言学)
灵活性(工程)
激励
补贴
环境经济学
业务
方案(数学)
审查
温室气体
产业组织
经济
微观经济学
生态学
数学分析
生物
哲学
语言学
管理
法学
市场经济
政治学
数学
作者
Xiangnan Song,Meng Shen,Yujie Lu,Liyin Shen,Hongyang Zhang
标识
DOI:10.1016/j.eiar.2021.106624
摘要
The building sector accounts for the largest proportion of global carbon emissions. The implementation of a market-based emission trading scheme offers a wider range of strategic choices and greater flexibility for building owners to reduce carbon emissions, but few of them are enthusiastic and actively engaged. To address the problem, this study explores how governments can effectively guide the carbon mitigation actions of building owners under an emission trading scheme (ETS) by continually adjusting and optimizing their regulation strategies. First, an extended evolutionary game model is built, considering the synergistic effect of multiple regulation policies, to theoretically depict the long-term interactive, extensive correlative, and dynamic feedback relationship between the government and building owners. Second, taking advantage of system dynamics as a policy laboratory, a scenario cultivation and simulation analysis is conducted to fully investigate the implementation effects of different regulation strategies based on the behavioral responses of building owners under different scenarios. The city of Shenzhen is a pioneer in covering the building sector in its carbon trading scheme in China, and its hotels above four stars are selected as the realistic setting for the simulation analysis. The results demonstrate that under the emission trading scheme, compared with increasing levels of carbon monitoring and non-financial incentives for building owners, intervention measures, including penalties, subsidies, and public scrutiny, are more efficient and important for the government. These findings provide important theoretical guidance and practical implications for the government to further adjust and optimize its carbon regulation strategies for the building sector.
科研通智能强力驱动
Strongly Powered by AbleSci AI