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{"id":24056,"date":"2017-06-09T10:07:06","date_gmt":"2017-06-09T09:07:06","guid":{"rendered":"https:\/\/www.lse.ac.uk\/granthaminstitute\/?post_type=publication&p=24056"},"modified":"2024-09-18T17:23:08","modified_gmt":"2024-09-18T16:23:08","slug":"estimating-the-economic-impact-of-the-permafrost-carbon-feedback-2","status":"publish","type":"publication","link":"https:\/\/www.lse.ac.uk\/granthaminstitute\/publication\/estimating-the-economic-impact-of-the-permafrost-carbon-feedback-2\/","title":{"rendered":"Estimating the economic impact of the permafrost carbon feedback"},"content":{"rendered":"\n

The permafrost carbon feedback (PCF) is not currently taken into account in economic assessments of climate change, yet it could have important implications for the social cost of carbon (SCC) and the associated choice of the optimal greenhouse gas emission pathway. Although this feedback is still imperfectly known, there are enough estimates of its potential strength to now include it in our assessments. In this paper, I present a model of the PCF and integrate this feedback in the DICE Integrated Assessment Model to examine its consequences. I find that doing so increases the SCC by 10–20% in the baseline scenario, but that this impact is much more significant in the case of a damage function which is more reactive to very high temperature changes, and can reach up to 220%. It follows that setting industrial emission targets without taking into account this feedback would lead to excessive atmospheric carbon: I find that it increases the optimal emission control rate by circa 5% points on average over the period 2015–2110 and that this difference becomes much more significant when the constraint of limiting the increase in global mean temperature to +2∘+2∘C or +1.5∘+1.5∘C is added to the model.<\/p>\n

Clim. Change Econ.<\/i>
\nhttps:\/\/doi.org\/10.1142\/S2010007817500087