On economic modeling of carbon dioxide removal: values, bias, and norms for good policy-advising modeling

Abstract

Non-technical summary Integrated assessment models (IAMs) are important scientific tools for advising policymakers and the public on climate mitigation. Recent results of modeling exercises relied upon large amounts of techniques that can capture carbon dioxide from the atmosphere, undoing current and past emissions. I argue that the reliance on such techniques unduly shifts risk to future generations and away from current high emitting countries. From an ethical point of view, this is problematic. IAM studies need to be more explicit about the value positions that evidence of mitigation pathways depends upon and should represent a wider array of plausible value positions. Technical summary This paper analyzes the nonepistemic value judgments involved in modeling Carbon Dioxide Removal (CDR) techniques. The comparably high uncertainty of these techniques gives rise to epistemic risk when large-scale CDR is relied upon in most scenario evidence. Technological assumptions on CDR are thus entangled with nonepistemic value judgments. In particular, the reliance on large-scale CDR implies shifting risk to future generations and thereby gives a one-sided answer to questions of intergenerational justice. This bias in integrated assessment modeling is problematic given the policy-advising role of integrated modeling. Modeling climate mitigation should focus on transforming these implicit value positions into explicit scenario parameters and should aim to provide scenario evidence on the complete array of value-laden mitigation strategies. Social media summary The ethics of mitigation pathways, for example in relation to CDR, must be made transparent and plural.