Skip to main content

Projected climate change impacts on Indiana’s Energy demand and supply


This paper estimates changes in future energy demand and supply for Indiana due to projected climate change impacts. We first estimate demand changes under both the business-as-usual emissions scenario (RCP 8.5) and a scenario based on reduced emissions consistent with a 2-degree increase in global mean temperature (RCP 4.5), on both a statewide basis and for major urban areas. We then use our adjusted statewide energy demand projections as an input to a comprehensive model of Indiana’s energy system, to project expected changes in the state’s energy supply under both scenarios. Finally, we consider the potential impacts of two policy scenarios—a carbon pricing scheme and a renewable energy investment tax credit—on emissions and future energy supply choices. Our results suggest that climate change will have a relatively modest effect on energy demand and supply in Indiana, slightly increasing commercial demand and decreasing residential demand but having little effect on energy supply choices. In addition, our results suggest the potential for policy proposals currently being adopted in other states, such as a relatively small carbon price or investment credits for renewable energy sources, to have a larger impact on the state’s future energy mix, increasing production from low or zero carbon energy sources and reducing emissions.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5


  1. “Net energy demand” indicates total energy demand in the state of Indiana attributed toward all types of end-uses.

  2. We only used post-1980s data to exclude the shock associated with the energy crisis in the U.S. in the 1970s.

  3. Historical climate data used included maximum and minimum temperature (TMAX, TMIN), total precipitation (PRCP), and average wind speed (WDSP) during 1960–2013. To match the temporal resolution of the IN-MARKAL model used in our supply analysis, we aggregated the climate data over the three seasons: summer (June–September), winter (December–March), and intermediate (April, May, October, November).

  4. Secular trends refer to the non-seasonal/non-cyclical trends in the non-climatic factors such as economic or population growth and technological advancements.


  • Amato AD, Ruth M, Kirshen P, Horwitz J (2005) Regional energy demand responses to climate change: methodology and application to the Commonwealth of Massachusetts. Clim Chang 71(1):175–201

    Article  Google Scholar 

  • Burtraw D (2008) Cap, auction, and trade: auctions and revenue recycling under carbon cap and trade. Accessed 15 December 2017

  • Elkhafif MAT (1996) An iterative approach for weather-correcting energy consumption data. Energy Econ 18:221–230

    Article  Google Scholar 

  • Energy Futures Initiative (2018) U.S. Energy and employment report. Accessed 3 July 2018

  • Filippelli G, Jay S, Gibson J, Wells E, Moreno-Madriñán MJ, Ogashawara I, Freeman J, Rosenthal F (in review). The current and future impacts of climate change on human health in Indiana. Clim Chang (under review)

  • Gotham, DJ, Angel JR, Pryor SC (2013) Vulnerability of the electricity and water sectors to climate change in the Midwest. In: Climate change in the Midwest: impacts, risks, vulnerability and adaptation, S.C. Pryor, ed., Indiana University Press, 158–177

  • Hamlet AF, Brun K, Robeson S, Widhalm M, Baldwin M (2018) Impacts of climate change on the state of Indiana: future projections based on statistical downscaling. Clim Change

  • Hastie T, Tibshirani R, Friedman JH (2008) The elements of statistical learning (second). Springer, New York

    Google Scholar 

  • International Energy Agency (2016) Energy Technology Perspectives 2016. Accessed 3 January 2018

  • International Energy Agency—Energy Technology Systems Analysis Program (IEA-ETSAP) (2011) Accessed 26 November 2017

  • Isaac M, Van Vuuren D (2009) Modeling global residential sector energy demand for heating and air conditioning in the context of climate change. Energy Policy 37(2):507–521

    Article  Google Scholar 

  • James G, Witten D, Hastie T, Tibshirani R (2013) An introduction to statistical learning—with applications in R. Springer-Verlag, New York

    Book  Google Scholar 

  • Kennedy CA, Stewart I, Facchini A, Cersosimo I, Mele R, Chen B, Uda M, Kansal A, Chiu A, Kim K, Dubeux C, LaRovere EL, Cunha B, Pincetl S, Keirstead J, Barles S, Pusaka S, Gunawa J, Adegbile M, Nazariha M, Hoque S, Marcotullio PJ, Otharan FG, Genena T, Ibrahim N, Farooqui R, Cervantes G, Sahin AD (2015) Energy and material flows of megacities. PNAS 112(19):5985–5990

  • Lu L (2015) An assessment of the efficacy and cost of alternative carbon mitigation policies for the state of Indiana. Dissertation, Purdue University

  • McNeil M, Letschert V, de la Rue du Can S (2008) Global potential of energy efficiency standards and labeling programs. Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley

    Book  Google Scholar 

  • Mukherjee S, Nateghi R (2017) Climate sensitivity of end-use electricity consumption in the built environment: an application to the state of Florida, United States. Energy 28

  • Mukherjee S, Nateghi R (2018a) A data-driven approach to assessing supply inadequacy risks due to climate-induced shifts in electricity demand. Risk Anal (under 3rd review)

  • Mukherjee S, Nateghi R (2018b) Estimating climate–demand nexus to support long-term adequacy planning in the energy sector. In: 2017 IEEE Power & Energy society general meeting. IEEE Xplore, pp 1–5

  • Nateghi R, Mukherjee S (2017) A multi-paradigm framework to assess the impacts of climate change on end-use energy demand. PLoS One 12(11):e0188033

    Article  Google Scholar 

  • Norman J, MacLean HL, Kennedy CA (2006) Comparing high and low residential density: life-cycle analysis of energy use and greenhouse gas emissions. J Urban Plan Dev 132(1):10–21

    Article  Google Scholar 

  • Prehoda EW, Pearce JM (2017) Potential lives saved by replacing coal with solar photovoltaic electricity production in the U.S. Renew Sust Energ Rev 80(Supplement C):710–715

    Article  Google Scholar 

  • Raymond L (2016) Reclaiming the atmospheric commons: the regional greenhouse gas initiative and a new model of emissions trading. MIT Press, Cambridge

    Book  Google Scholar 

  • Sailor DJ (2001) Relating residential and commercial sector electricity loads to climate—evaluating state level sensitivities and vulnerabilities. Energy 26:645–657

    Article  Google Scholar 

  • Sailor DJ, Muñoz JR (1997) Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—methodology and results for eight states. Energy 22:987–998

    Article  Google Scholar 

  • Singh S, Kennedy C (2015) Estimating future energy use and CO2 emissions of the world’s cities. Environ Pollut 203:271–278

    Article  Google Scholar 

  • Stehfest E, van Vuuren D, Kram T, Bouwman L, Alkemade R, Bakkenes M, Biemans H, Bouwman A, den Elzen M, Janse J, Lucas P, van Minnen J, Müller C, Prins A (2014) Integrated assessment of global environmental change with IMAGE 30—model description and policy applications Accessed 3 July 2018

  • (SUFG) State Utility Forecasting Group (2017) Indiana renewable energy resources study. Accessed 15 December 2017

  • (SUFG) State Utility Forecasting Group (2016) 2016 Indiana renewable energy Resources Study. Accessed 26 November 2017

  • Stern N, Stiglitz JE (2017) Report of the high-level commission on carbon prices. World Bank, Washington D.C

    Google Scholar 

  • U.S. Energy Information Agency (2016) State Energy Data System (SEDS) INDIANA: State Profile & Energy Estimates. Accessed 15 December 2017

  • U.S. Energy Information Agency (2017a) Commercial Building Energy Consumption Survey (CBECS). Accessed 10 May 2017

  • U.S. Energy Information Agency (2017b) Indiana State Energy Profile. Accessed 15 December 2017

  • U.S. Energy Information Agency (2017c) Residential Energy Consumption Survey (RECS). Accessed 15 December 2017

  • U.S. EPA (2013) Region Nine MARKAL database, database documentation. US Environmental Protection Agency, Cincinnati, OH, EPA/600/B-13/203

  • Wachs, E, Singh S (under review) Estimating spatial variations of urban energy demand in Indiana under future climate change scenarios. Clim Chang

  • Wilbanks T, Bilello D, Schmalzer D, Scott M et al (2013) Climate change and energy supply and use: technical report for the U.S. Department of Energy in support of the National Climate Assessment. Island Press, Washington, DC

    Google Scholar 

Download references


This paper is a contribution to the Indiana Climate Change Impacts Assessment (INCCIA). The IN CCIA is managed and supported by the Purdue Climate Change Research Center. The authors would like to acknowledge support for this research from the Purdue Center for the Environment, the Purdue Climate Change Research Center, as well as National Science Foundation grants #1728209 and #1826161, and the USDA National Institute of Food and Agriculture, Hatch project 1016213.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Leigh Raymond.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of a Special Issue on “The Indiana Climate Change Impacts Assessment” edited by Jeffrey Dukes, Melissa Widhalm, Daniel Vimont, and Linda Prokopy.

Electronic supplementary material


(DOCX 478 kb)


(DOCX 28 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Raymond, L., Gotham, D., McClain, W. et al. Projected climate change impacts on Indiana’s Energy demand and supply. Climatic Change 163, 1933–1947 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: