327 research outputs found

    Self‐Adaptive Multi‐Objective Climate Policies Align Mitigation and Adaptation Strategies

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    Intensifying climate change impacts can divert the economic resources away from emission reduction toward adaptation to reduce rising damages, jeopardizing temperature stabilization within safe levels. Indeed, the traditional static welfare-maximizing climate policy design leads to a conflict between mitigation and adaptation, invalidating the recently established consistency of cost-benefit analysis with the Paris Agreement's targets. Here, we show that this tension can be resolved by integrating multi-objective optimization and feedback control in the Dynamic Integrated Climate Economy model to design self-adaptive climate policies trading off welfare maximization with the Paris Agreement compliance. These policies allow adjusting against uncertainty as information on the socio-climatic system accumulates, thus representing the policy-making process more realistically. We show that, the costs being the same as in traditional methods, warming above 2 degrees C and the probability of overshooting can be drastically reduced, emphasizing the need for integrating adaptation and mitigation strategies and the value of embracing a self-adaptive, multi-objective perspective

    Angelo Lanzellotti

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    Breve profilo biografico del giurista Angelo Lanzellotti

    Presentazione al saggio “Il resto del lettino. Psicoanalisi e vita quotidiana” di Angelo Battistini (Guaraldi, Rimini).

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    Presentazione di una raccolta di scritti di Angelo Battistini tratti da una rubrica di argomento psicoanalitico del quotidiano “Il Resto del Carlino”. E’ stata illustrata la chiave di lettura che la pratica psicoanalitica consente di applicare all’attualità. E’ stato inoltre discusso il ruolo del modello interpretativo psicoanalitico applicato al contesto sociale

    From optimal to robust climate strategies: expanding integrated assessment model ensembles to manage economic, social, and environmental objectives

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    Cost-benefit integrated assessment models generate welfare-maximizing mitigation pathways under a set of assumptions to deal with deep uncertainty in future scenarios. These assumptions include socio-economic projections, the magnitude and dynamics of climate impacts on the economy, and physical climate response. As models explore the uncertainty space within the boundaries of their objective functions, they risk providing scenarios which are too narrow and not sufficiently robust. Here, we apply robust and multi-objective decision-making methods to extract relevant information from a large ensemble of optimal emissions-reduction pathways generated by a regionalized cost-benefit integrated assessment model under deterministic welfare optimization. We show that shifting the focus from optimal to robust solutions reduces the uncertainty in mitigation strategies and aligns them toward the Paris goals. Moreover, we analyze the trade-offs between climatic (temperature), social (inequality) and economic (welfare) objectives and illustrate four robust pathways under various decision-making criteria. We show that robust mitigation strategies can lead to regional emission-reduction strategies which are fair. Our results show how to extract more comprehensive climate strategies from available scenario ensembles and that the highest discrepancies at the local level policies are found in the developing and most-impacted regions
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