Climate Models Assume Endless Growth, and It May Be Hiding the Best Ways to Save the Planet

The computer models that shape global climate policy may be quietly steering humanity toward the hardest possible path to a livable future. A new Perspective published in Frontiers in Energy Research argues that integrated assessment models, or IAMs, the powerful simulation tools that underpin the mitigation scenarios in reports by the Intergovernmental Panel on Climate Change, are built on a structural assumption so pervasive that it is rarely questioned: perpetual economic growth. According to authors Baxter Kamana-Williams and Emily Grubert of the University of Notre Dame, that assumption is not just debatable, it may be actively obscuring feasible transition strategies that could prevent catastrophic climate change.

IAMs are the mapmakers of climate policy. They weave together energy systems, economics, technology, land use and emissions into quantitative pictures of the coming decades, allowing analysts to compare long-term decarbonization pathways and their trade-offs. When the IPCC’s Sixth Assessment Report presents scenarios compatible with limiting warming to 1.5 or 2 degrees Celsius, those pathways overwhelmingly come from IAMs. The problem, the authors contend, is that almost every scenario in that report assumes gross domestic product keeps rising until 2100, and that assumption cascades through everything the models produce.

The coupling between growth and environmental harm is the crux of the issue. Historically, economic growth has been tightly linked to rising greenhouse gas emissions, resource extraction and ecological degradation. The concept of green growth, championed by institutions like the World Bank, the OECD and the United Nations Environment Programme, holds that technological improvement can decouple GDP from environmental impact, allowing prosperity to rise while emissions fall. But the empirical record is sobering. Observed decoupling rates remain far too slow to deliver the required emissions cuts, and the only periods of declining absolute resource use have coincided with economic recessions. A widely cited review by Hickel and Kallis concluded that green growth theory lacks empirical support, and that sustained global green growth is incompatible with the 1.5 degrees Celsius carbon budget, fitting within the 2 degrees budget only with near-zero economic growth.

When models assume growth must continue regardless, they are forced into increasingly heroic compensating assumptions. Because GDP and energy demand rise together in these frameworks, the models lean on technology to slash emissions intensity instead. That means unprecedented deployment of negative emissions technologies, such as carbon dioxide removal, alongside extraordinary gains in energy efficiency. The numbers are stark: IPCC-aligned pathways assume an average of 6 gigatonnes of carbon dioxide removed per year by 2050 and 13 gigatonnes per year by 2100. Current intentional removal, excluding forestry, stands at roughly 2 megatonnes per year, primarily from biochar, bioenergy with carbon capture, enhanced weathering and direct air capture. Closing that gap would require growth rates several orders of magnitude beyond anything demonstrated, which experts have described as extremely challenging. If that deployment fails, the planet could be locked into a high-warming trajectory.

The authors dissect how this growth bias is embedded in model architecture. In the MESSAGE model, GDP is an exogenous input, typically calibrated to the shared socioeconomic pathways, all of which assume GDP increases through 2100. In the WITCH model, GDP is computed endogenously, but its key driver, total factor productivity, is calibrated to match those same external projections. Either way, growth is baked in. More fundamentally, the utility functions that IAMs optimize treat welfare as a monotonically increasing function of per capita consumption, so the models are structurally programmed to maximize consumption subject to emissions constraints. Following the classic IPAT framework, where environmental impact depends on population, affluence and technology, they hold population fixed, assume affluence rises, and leave technology to do all the work.

That structure produces two troubling consequences. First, it prioritizes aggregate economic output over equity and wellbeing, and technological fixes over sociopolitical ones. Second, it can lead to ethically fraught conclusions. Because population appears as a demand driver, some studies propose climate mitigation through incentivizing lower birth rates, adjusting the population term in the equation rather than questioning affluence or its distribution. The authors argue that making the math work by shrinking the number of people, while assuming perpetual growth and unequal resource distribution, should prompt serious introspection rather than acceptance.

The empirical case for rethinking the wellbeing-growth link is substantial. GDP correlates with life expectancy, health and subjective wellbeing only up to a point, beyond which returns become marginal. Social and political factors, including income distribution, democratic participation and high-quality public services, mediate that relationship and can matter more than consumption itself. In some high-income countries, wellbeing can actually increase when consumption decreases, a finding that aggregate models simply cannot capture. Meanwhile, growth remains strongly correlated with ecological degradation that directly harms human welfare, even when carbon emissions are accounted for.

Alternatives exist, and the paper surveys them. Degrowth frameworks reject the hegemony of economic growth as an organizing principle, prioritizing the downscaling of production and consumption and the redistribution of resources to improve wellbeing, social justice and environmental sustainability. Notably, degrowth does not require depopulation or reduced quality of life; its focus is not necessarily less, but different. Sufficiency approaches aim to improve wellbeing directly by prioritizing consumption that enhances it and avoiding the rest, recognizing that wellbeing gains stagnate beyond a certain level of energy and material use. Both draw support from movements such as Buen Vivir, commons-based communities and the global justice movement, and both are inherently pluralist, favoring socially and culturally appropriate solutions over a single global prescription.

The authors propose a concrete reframing: models should optimize for service provision and the material requirements of decent living standards, rather than economic proxies. Research by Rao and Min and by Millward-Hopkins and colleagues offers quantifiable benchmarks, including roughly 2,000 to 2,150 kilocalories of food per person per day, 60 square meters of floor space per household, 50 liters of water per person daily, 4 kilograms of new clothing per year, and 5,000 to 15,000 passenger-kilometers of mobility annually. Strikingly, meeting these standards for everyone on Earth would require substantially less per capita energy than most of the world currently uses, though inequality can double the energy needed to secure universal decent living. The authors argue these material wellbeing indicators should sit directly in IAM objective functions, with economic growth treated as a model output rather than an input or constraint, and with scenarios still compared across both growth and post-growth assumptions.

Early evidence suggests the shift is tractable. Li and colleagues modified the MESSAGE model by making GDP endogenous and replacing the logarithmic utility function with a non-monotonic one that peaks at a specified consumption level. Applied to Australia, the modified model showed that reducing consumption lowers greenhouse gas emissions, infrastructure requirements and dependence on negative emissions technologies. The broader implication is that the solution space for climate policy is far larger than current models admit. A robust transition pathway, the authors suggest, requires limited technological optimism and support across models with different foundational assumptions. Without widening the lens, the maps that guide policymakers remain incomplete, and humanity may be pursuing the most technologically perilous route to safety while feasible alternatives go unexplored.

Subject of Research: The role of perpetual economic growth assumptions in integrated assessment models and their effect on climate mitigation pathways

Article Title: Structural green growth assumptions in energy system models obscure alternative transition strategies

Article References: Kamana-Williams, B., & Grubert, E. (2026). Structural green growth assumptions in energy system models obscure alternative transition strategies. Frontiers in Energy Research, 14, Article 1984182. https://doi.org/10.3389/fenrg.2026.1984182

Image Credits: AI Generated

DOI: 10.3389/fenrg.2026.1984182

Keywords: integrated assessment models, climate change mitigation, economic growth, degrowth, green growth, GDP, decent living standards, negative emissions, carbon dioxide removal, IPCC, sufficiency, energy system modeling