Climatic Change

, Volume 123, Issue 3–4, pp 597–609 | Cite as

Role of energy efficiency in climate change mitigation policy for India: assessment of co-benefits and opportunities within an integrated assessment modeling framework

  • Vaibhav Chaturvedi
  • Priyadarshi R. Shukla


Addressing the challenges of global warming requires interventions on both the energy supply and demand side. With the supply side responses being thoroughly discussed in the literature, our paper focuses on analyzing the role of end use efficiency improvements for Indian climate change mitigation policy and the associated co-benefits, within the integrated assessment modeling framework of Global Change Assessment Model (GCAM). Six scenarios are analyzed here in total- one no climate policy and two climate policy cases, and within each of these one scenario with reference end use energy technology assumptions and another with advance end use energy technology assumptions has been analyzed. The paper has some important insights. Final energy demand and emissions in India are significantly reduced with energy efficiency improvements, and the role of this policy is important especially for the building and transportation sector under both reference and climate policy scenarios. Though energy efficiency policy should be an integral part of climate policy, by itself it is not sufficient for achieving mitigation targets, and a climate policy is necessary for achieving mitigation goals. There are significant co-benefits of energy efficiency improvements. Energy security for India is improved with reduced oil, coal and gas imports. Significant reduction in local pollutant gases is found which is important for local health concerns. Capital investment requirement for Indian electricity generation is reduced, more so for the climate policy scenarios, and finally there are significant savings in terms of reduced abatement cost for meeting climate change mitigation goals.


Energy Efficiency Climate Policy Abatement Cost Energy Efficiency Improvement Policy 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.



The authors are grateful for research support provided by the Global Technology Strategy Program. The authors acknowledge long-term support for GCAM development from the Integrated Assessment Research Program in the Office of Science of the U.S. Department of Energy. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. The views and opinions expressed in this paper are those of the authors alone.

Supplementary material

10584_2013_898_MOESM1_ESM.docx (202 kb)
ESM 1 (DOCX 201 kb)


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Copyright information

© U.S. Government 2013

Authors and Affiliations

  1. 1.Joint Global Change Research Institute, Pacific Northwest National Laboratory and University of MarylandCollege ParkUSA
  2. 2.Indian Institute of Management AhmedabadAhmedabadIndia

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