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Setting cumulative emissions targets to reduce the risk of dangerous climate change.


ABSTRACT: Avoiding "dangerous anthropogenic interference with the climate system" requires stabilization of atmospheric greenhouse gas concentrations and substantial reductions in anthropogenic emissions. Here, we present an inverse approach to coupled climate-carbon cycle modeling, which allows us to estimate the probability that any given level of carbon dioxide (CO2) emissions will exceed specified long-term global mean temperature targets for "dangerous anthropogenic interference," taking into consideration uncertainties in climate sensitivity and the carbon cycle response to climate change. We show that to stabilize global mean temperature increase at 2 degrees C above preindustrial levels with a probability of at least 0.66, cumulative CO2 emissions from 2000 to 2500 must not exceed a median estimate of 590 petagrams of carbon (PgC) (range, 200 to 950 PgC). If the 2 degrees C temperature stabilization target is to be met with a probability of at least 0.9, median total allowable CO2 emissions are 170 PgC (range, -220 to 700 PgC). Furthermore, these estimates of cumulative CO2 emissions, compatible with a specified temperature stabilization target, are independent of the path taken to stabilization. Our analysis therefore supports an international policy framework aimed at avoiding dangerous anthropogenic interference formulated on the basis of total allowable greenhouse gas emissions.

SUBMITTER: Zickfeld K 

PROVIDER: S-EPMC2752604 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Setting cumulative emissions targets to reduce the risk of dangerous climate change.

Zickfeld Kirsten K   Eby Michael M   Matthews H Damon HD   Weaver Andrew J AJ  

Proceedings of the National Academy of Sciences of the United States of America 20090817 38


Avoiding "dangerous anthropogenic interference with the climate system" requires stabilization of atmospheric greenhouse gas concentrations and substantial reductions in anthropogenic emissions. Here, we present an inverse approach to coupled climate-carbon cycle modeling, which allows us to estimate the probability that any given level of carbon dioxide (CO2) emissions will exceed specified long-term global mean temperature targets for "dangerous anthropogenic interference," taking into conside  ...[more]

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