Building fairness perspectives into climate policy

Unabated global warming is an existential threat to all of humanity, and mitigation of and adaptation to climate change present challenges no individual nation can address on its own. Thus, concerted actions by many countries are needed. Yet, current efforts by the international community are lackluster. The combined pledges declared by nations to reduce greenhouse gas (GHG) emissions, even if enacted, fall far short of what is needed to realize even the less ambitious goal of the Paris Agreement, which is to limit global warming to 2°C above the pre-industrial level. Clearly, a much more determined effort by the international community to cut GHG emissions is required, and the willingness of countries to make the necessary contributions to climate action critically depends on whether they perceive as fair their shares of the burdens and benefits this implies. This reality is recognized in the Paris Agreement, through which countries are required to submit their nationally determined contributions along with justification of why they consider their commitments to be fair.

Integrated assessment models (IAMs) are powerful tools that allow researchers to design and explore policy options for efficient climate adaptation and mitigation. Yet, their potential to facilitate an international agreement on concerted climate action has so far not been fully realized. IAMs tend to focus on globally cost-efficient policies, leaving the question of the distribution of the costs and benefits of such policies up to nations to resolve during climate negotiations. In the absence of commonly accepted principles guiding such a distribution, however, climate negotiations seem to have reached an impasse. The situation is not helped by the fact that many countries argue that globally cost-efficient policies would impose on them an unfair share of the overall burdens of climate action.

In our study, recently published in the journal Sustainability, my colleagues and I set out to address the following question: how can existing and well-established IAMs be used to find climate policies that are not only optimal but can also be presented to individual nations as fair to their interests, thus boosting their willingness to implement them? In our opinion, the main obstacle to finding such policies is that the current setup of IAMs favors policies that are globally cost-efficient. This means that a model deploys mitigation options – in any region, any sector, and at any time – so that, overall, the considered climate action is achieved at the lowest possible cost. However, this often results in recommendations that are difficult to present as fair to all parties concerned.

As a practical solution to this problem, we propose replacing original objective functions used in the existing IAM frameworks that give preference to globally cost-efficient policies with other objective functions that are appealing from the fairness perspective.

To this end, as a first step, we reviewed different concepts of fairness developed in the philosophical literature. Next, we presented a selection of objective functions that are practical to optimize within existing IAMs and lead to policy recommendations that can be presented to individual countries as fair using arguments in line with the notions of fairness these functions represent.

The proposed suite of objective functions corresponding to various approaches to fairness offer practical ways of exploring what climate policies may look like if they were guided by different approaches to fairness. This will allow representatives of countries participating in climate negotiations better to understand the implications of different approaches to fairness and to choose the most suitable fairness arguments in support of their nationally determined contributions.

Moreover, as countries differ in their preferred notions of fairness and unanimous support for any single fair policy is unlikely, application of this suite of objective functions within existing IAM frameworks will allow users to chart the set of fair climate policies. This will allow delineating a space within which a compromise can be forged by homing in on a common climate policy that all parties perceive as fair to their interests and thus have incentives to implement.

When setting up their models and presenting their results, modelers tend to avoid open value judgements, e.g., regarding the most desirable climate policy options. This is, on the one hand, a genuine effort to maintain scientific objectivity, and, on the other, an attempt to avoid the notoriously difficult problem of representing qualitative ethical notions, such as fairness, within quantitative modeling frameworks. Yet, seemingly neutral assumptions, like striving for cost-optimal policies, may themselves be implicit value judgements. This negatively impacts the transparency and legitimacy of the models and undermines trust in the resultant policy recommendations. Our paper offers a discussion on the ethical implications of employing different objective functions and provides guidelines for modelers on how different notions of fairness can be represented within IAMs, thus improving transparency and building trust in their results among the public and policymakers.

Reference

Żebrowski, P., Dieckmann, U., Brännström, Å., Franklin, O., and Rovenskaya, E. (2022). Sharing the burdens of climate mitigation and adaptation: Incorporating fairness perspectives into policy optimization models. Sustainability 14(7), 3737. doi:10.3390/su14073737 [pure.iiasa.ac.at/17905]

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.