This article was written by Kevin Rennert, Frank Errickson, Brian C. Prest, Lisa Rennels, Richard G. Newell, William Pizer, Cora Kingdon, Jordan Wingenroth, Roger Cooke, Bryan Parthum, David Smith, Kevin Cromar, Delavane Diaz, Frances C. Moore, Ulrich K. Müller, Richard J. Plevin, Adrian E. Raftery, Hana Ševčíková, Hannah Sheets, James H. Stock, Tammy Tan, Mark Watson, Tony E. Wong & David Anthoff
Rationale: The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography, and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency, and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-413/t-CO2: 5-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2 percent, a value 3.6-times higher than the US government’s current value of $51/t-CO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source GIVE model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared to estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.