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This work explores methods to address climate change by applying optimization techniques in a top-down approach. A decision model is proposed to minimize temperature anomalies compared to pre-industrial levels between 2025 and 2100 by varying greenhouse gases (GHG), namely CO 2 and CH 4 . Two objective functions are minimized. The first one considers the overall sum of the temperature anomalies by 2100, while the latter minimizes the temperature anomaly at the end of the century. Two different emission trends are assumed: a gradual (gaussian) fall in emissions or a fast (exponential) decline. The reduction of GHG emissions is constrained to a set of IPCC scenarios identified by assessing economic, social, and technological trends in the next decades. The uncertainty analysis of the decision problem solutions suggests that temperature anomalies can be limited to the range of 0.8–2°C.
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Arrighini et al. (2024) studied this question.
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