IDMI Analysis of Regional Low-Carbon Development Based on System Dynamic Simulation

• Published in: Transactions of Tianjin University Vol. 19; no. 5; pp. 338 - 344
• Main Author: 贺嫒嫒 Hu Eric 谭欣
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2013; School of Mechanical Engineering, University of Adelaide, 5005 SA, Australia%School of Mechanical Engineering, University of Adelaide, 5005 SA, Australia%School of Environmental Science and Technology, Tianjin University, Tianjin 300072, China; School of Environmental Science and Technology, Tianjin University, Tianjin 300072, China
• Subjects: Engineering; Humanities and Social Sciences; Mechanical Engineering; multidisciplinary; Science; 中国政府; 低碳; 决策者; 决策过程; 分析基; 动态仿真; 系统; 评价方法; system dynamics; low-carbon economy; IDMI; decision-making
• ISSN: 1006-4982; 1995-8196
• DOI: 10.1007/s12209-013-2130-5

During the decision-making process, especially in multi-disciplinary complex cases, assessment technique is needed to assist policy-makers in making the right decision. Many of such assessment techniques have been developed for policy-makers, but the inevitable subjectivity of policy-makers often becomes the main obstacle in making the right or proper policy. Interlink decision-making index （IDMI） is a newly proposed assessment method with the advantages of being simple to use and having less human interference over other methods, as it does not require a weighting process of each selection criterion. This paper implements IDMI to assist with decision-making in national or regional low-carbon development, using China as a case study. The Chinese government has annotmced its carbon emission reduction target along with other development targets by 2020. Many policy settings can be chosen in order to achieve those targets. The problem is how to determine the best setting and the means by which decision-makers can avoid subjectivity and extremes. A number of policy setting options are generated carefully by a system dynamic model under different policy scenarios. The IDMI demonstrates a perfect way to assist in selecting the ＂best＂ among all the options that can achieve the goals within the acceptable range.