Normatively Robust Mitigation Policy to Equitably Distribute the Remaining Carbon Budget

Addressing climate change through collective action is hindered by the unequal distribution of burdens and responsibilities and deep uncertainties inherent in the Human-Earth system. As a result, policymakers must navigate both empirical uncertainties within socioeconomic and climate systems, as well as normative uncertainties stemming from stakeholders' diverse values. Addressing these value differences is critical, as perceptions of fairness in mitigation policies are essential for their acceptance and implementation. While classical decision-making under deep uncertainty (DMDU) techniques have not yet been applied to problems involving normative uncertainty, they can be adapted for climate policymaking where multiple stakeholders hold conflicting values and policy objectives.

This study integrates three principles of distributive justice—Limitarianism, Utilitarianism, and Prioritarianism—to allocate the remaining carbon budget necessary to limit global warming below 2°C. We apply Limitarianism using emergent constraints—an established climate modelling method that identifies a remaining carbon budget robust across diverse climate and socioeconomic uncertainties—to determine a carbon budget that achieves the 2°C target. Building upon this robust emission limit, we compare Utilitarian and Prioritarian frameworks to distribute the remaining carbon budget among different nations and generations. The JUSTICE Integrated Assessment Model (IAM) operationalizes these principles within a multi-objective framework to search for Pareto-optimal mitigation policies that balance environmental and economic objectives while evaluating policy options through various lenses of distributive justice.

We utilize two established decision-making frameworks to develop adaptive mitigation policies: Multi-Objective Robust Decision-Making (MORDM) and Evolutionary Multi-Objective Direct Policy Search (EMODPS). MORDM rigorously tests potential policies against deep uncertainties to identify robust, Pareto-optimal choices. Simultaneously, EMODPS fine-tunes policies to reconcile stakeholders' diverse objectives, ensuring policies are adaptive and robust across both empirical uncertainties and normative values. These adaptive policies utilize feedback mechanisms providing flexibility to accommodate diverse future scenarios. This flexibility also facilitates the management of trade-offs between conflicting goals and values.

Our findings demonstrate that normatively robust policies can bridge the gap among policymakers with diverse perspectives by maintaining robustness across deep uncertainties, conflicting ethical viewpoints, and multiple objectives. We highlight the pivotal role of normative clarity in facilitating stakeholder dialogue and ensuring that climate policies are scientifically sound and socially equitable.