Multi-objective optimal control of a simple stochastic climate-economy model

被引:4
|
作者
Carlino, Angelo [1 ]
Giuliani, Matteo [1 ]
Tavoni, Massimo [2 ,3 ]
Castelletti, Andrea [1 ]
机构
[1] Politecn Milan, Dept Elect Informat & Bioengn, Milan, Italy
[2] Ctr Euro Mediterraneo Cambiamenti Climat, RFF CMCC European Inst Econ & Environm, Milan, Italy
[3] Politecn Milan, Dept Management Econ & Ind Engn, Milan, Italy
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词
Climate change impact and adaptation measures; Environmental decision support systems; INTEGRATED ASSESSMENT MODELS; SOCIAL COST; UNCERTAINTY;
D O I
10.1016/j.ifacol.2020.12.786
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Integrated 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. Copyright (C) 2020 The Authors.
引用
收藏
页码:16593 / 16598
页数:6
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