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

Global Sustainability 5 (e18) (2022)
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Abstract

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.

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Simon Hollnaicher
Bielefeld University (PhD)

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