Multi-objective optimal control of a simple stochastic climate-economy model. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Carlino, Angelo; Giuliani, Matteo; Tavoni, Massimo; Castelletti, Andrea
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 16593
• Page End: 16598
• Publication Date: 2020
• Subjects: Climate change impact -- adaptation measures -- Environmental decision support systems; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.786
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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.