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1.5 °C carbon budget dependent on carbon cycle uncertainty and future non-CO2 forcing.


ABSTRACT: Estimates of the 1.5?°C carbon budget vary widely among recent studies, emphasizing the need to better understand and quantify key sources of uncertainty. Here we quantify the impact of carbon cycle uncertainty and non-CO2 forcing on the 1.5?°C carbon budget in the context of a prescribed 1.5?°C temperature stabilization scenario. We use Bayes theorem to weight members of a perturbed parameter ensemble with varying land and ocean carbon uptake, to derive an estimate for the fossil fuel (FF) carbon budget of 469 PgC since 1850, with a 95% likelihood range of (411,528) PgC. CO2 emissions from land-use change (LUC) add about 230 PgC. Our best estimate of the total (FF?+?LUC) carbon budget for 1.5?°C is therefore 699 PgC, which corresponds to about 11 years of current emissions. Non-CO2 greenhouse gas and aerosol emissions represent equivalent cumulative CO2 emissions of about 510 PgC and -180 PgC for 1.5?°C, respectively. The increased LUC, high non-CO2 emissions and decreased aerosols in our scenario, cause the long-term FF carbon budget to decrease following temperature stabilization. In this scenario, negative emissions would be required to compensate not only for the increasing non-CO2 climate forcing, but also for the declining natural carbon sinks.

SUBMITTER: Mengis N 

PROVIDER: S-EPMC5895820 | biostudies-other | 2018 Apr

REPOSITORIES: biostudies-other

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1.5 °C carbon budget dependent on carbon cycle uncertainty and future non-CO<sub>2</sub> forcing.

Mengis Nadine N   Partanen Antti-Ilari AI   Jalbert Jonathan J   Matthews H Damon HD  

Scientific reports 20180411 1


Estimates of the 1.5 °C carbon budget vary widely among recent studies, emphasizing the need to better understand and quantify key sources of uncertainty. Here we quantify the impact of carbon cycle uncertainty and non-CO<sub>2</sub> forcing on the 1.5 °C carbon budget in the context of a prescribed 1.5 °C temperature stabilization scenario. We use Bayes theorem to weight members of a perturbed parameter ensemble with varying land and ocean carbon uptake, to derive an estimate for the fossil fue  ...[more]

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