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  • 标题:Multi-objective optimal control of a simple stochastic climate-economy model
  • 本地全文:下载
  • 作者:Angelo Carlino ; Matteo Giuliani ; Massimo Tavoni
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:16593-16598
  • DOI:10.1016/j.ifacol.2020.12.786
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIntegrated assessment modelling of climate change aims to provide quantitative solutions to inform international climate policy by employing models where socio-economic and climatic systems are integrated. Among these models, DICE (Dynamic Integrated Climate-Economy), is used to perform cost-benefit analysis that returns as output the optimal emission reduction pathway. The model makes some important assumptions: future socioeconomic and climate system evolution is deterministic and economic damages of climate change are a quadratic function of the atmospheric temperature. In this study, propose a multi-objective stochastic optimal control problem formulation of the DICE model in order to account for stochastic disturbances and to align with physical targets posed by international agreements on climate change mitigation. The solutions are control policies that can handle stochastic disturbances outperforming the static inter-temporal optimization approach traditionally adopted. Moreover, such control policies are able to deal with multiple objectives making explicit the trade-offs between economic and environmental objectives.
  • 关键词:KeywordsClimate change impactadaptation measuresEnvironmental decision support systems
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