Climatic Change

, Volume 123, Issue 3–4, pp 571–582 | Cite as

Temperature control, emission abatement and costs: key EMF 27 results from Environment Canada’s Integrated Assessment Model

  • Yunfa Zhu
  • Madanmohan Ghosh


This paper investigates the potential impacts of alternative international climate change scenarios based on different policies and technological circumstances on future emission pathways and abatement costs. It also examines if these hypothetical scenarios could result in significant emission reductions required to control the global temperature from rising to no more than 2.5 °C above preindustrial level. Using an integrated assessment model, this paper examines these issues under 12 scenarios derived from four policy perspectives and three technology dimensions. Results show that the no-policy-change baseline scenarios lead to high global average temperatures in the future. To control the temperature efficiently, every global region will be required to undertake considerable abatement efforts. Current country pledges alone, even if fully implemented, cannot control the global temperature in the future to within a comfortable zone. There will still be large gap between the reductions needed to meet the 2.5 degree objective, associated with 550 ppm and the reductions associated with existing abatement efforts. Further stringent policies together with favourable technological conditions may lead to the desired level of temperature control. Participation by only a subset of nations not only makes achieving the temperature goal difficult but also costly. To achieve temperature control efficiently, global coordination and full participation by all regions are necessary and global participation may reduce global abatement costs. It is worth noting that abatement costs vary widely across regions under different policy and technology scenarios.


Abatement Cost Baseline Scenario Policy Scenario Emission Abatement Preindustrial Level 
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.



We are grateful to Christoph Böhringer and Thomas Rutherford for helping us with model development. We thank the three anonymous referees and Derek Hermanutz, Nick Macaluso, Jessica Norup, Julie Vanderschot, Katherine Monahan, Deming Luo, Muhammad Shahid Siddiqui and Cheng-Marshal Wang for insightful comments on an earlier version of the paper. Views expressed in this paper are those of the authors and do not necessarily reflect those of Environment Canada or the Government of Canada.

Supplementary material

10584_2013_1002_MOESM1_ESM.docx (32 kb)
ESM 1 (DOCX 32 kb)


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Copyright information

© Crown Copyright as represented by: Environment Canada 2013

Authors and Affiliations

  1. 1.Analysis and Modeling Division, Strategic Policy Branch (SPB)Environment CanadaGatineauCanada

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