Climatic Change

, Volume 105, Issue 1–2, pp 91–108 | Cite as

Historical and future anthropogenic emission pathways derived from coupled climate–carbon cycle simulations

  • Erich RoecknerEmail author
  • M. A. Giorgetta
  • T. Crueger
  • M. Esch
  • Julia Pongratz


Using a coupled climate–carbon cycle model, fossil fuel carbon dioxide (CO2) emissions are derived through a reverse approach of prescribing atmospheric CO2 concentrations according to observations and future projections, respectively. In the second half of the twentieth century, the implied fossil fuel emissions, and also the carbon uptake by land and ocean, are within the range of observational estimates. Larger discrepancies exist in the earlier period (1860–1960), with small fossil fuel emissions and uncertain emissions from anthropogenic land cover change. In the IPCC SRES A1B scenario, the simulated fossil fuel emissions more than double until 2050 (17 GtC/year) and then decrease to 12 GtC/year by 2100. In addition to A1B, an aggressive mitigation scenario was employed, developed within the European ENSEMBLES project, that peaks at 530 ppm CO2(equiv) around 2050 and then decreases to approach 450 ppm during the twenty-second century. Consistent with the prescribed pathway of atmospheric CO2 in E1, the implied fossil fuel emissions increase from currently 8 GtC/year to about 10 by 2015 and decrease thereafter. In the 2050s (2090s) the emissions decrease to 3.4 (0.5) GtC/year, respectively. As in previous studies, our model simulates a positive climate–carbon cycle feedback which tends to reduce the implied emissions by roughly 1 GtC/year per degree global warming. Further, our results suggest that the 450 ppm stabilization scenario may not be sufficient to fulfill the European Union climate policy goal of limiting the global temperature increase to a maximum of 2°C compared to pre-industrial levels.


Carbon Cycle Gross Primary Production Land Cover Change Carbon Cycle Model Stabilization Scenario 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Erich Roeckner
    • 1
    Email author
  • M. A. Giorgetta
    • 1
  • T. Crueger
    • 1
  • M. Esch
    • 1
  • Julia Pongratz
    • 1
    • 2
  1. 1.Max Planck Institute for MeteorologyHamburgGermany
  2. 2.Department of Global EcologyCarnegie Institution of WashingtonStanfordUSA

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