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Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector

Author

Listed:
  • Page Kyle
  • Leon Clarke
  • Fang Rong
  • Steven J. Smith

Abstract

Buildings are the dominant driver of daily and seasonal electric load cycles, and account for 40 percent of U.S. final energy use. They account for roughly 10 percent of direct U.S. CO2 emissions and roughly 40 percent once indirect emissions from electricity generation are included. This paper explores the possible evolution of this sector over the coming century, its potential role in climate action and response to climate policies, and the potential benefits of advances in building technologies for addressing climate change. The paper presents a set of scenarios based on a detailed, service-based model of the U.S. buildings sector that is embedded within a long-term, global, integrated assessment model, MiniCAM. Eight scenarios are created in total, combining two sets of assumptions regarding U.S. building service demand growth, two sets of assumptions regarding the improvements in building energy technologies, and two assumptions regarding long-term U.S. climate action Ð a no-climate¥action assumption and an assumption of market-based policies to reduce U.S. CO2 emissions consistent with a 450 ppmv global target. Through these eight scenarios, the paper comments on the implications of continued growth in building service demands, the ability of efficiency measures to reduce emissions, and the strong link between decarbonization of electricity generation and building sector emissions.

Suggested Citation

  • Page Kyle & Leon Clarke & Fang Rong & Steven J. Smith, 2010. "Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 145-172.
  • Handle: RePEc:aen:journl:2010v31-02-a06
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    Citations

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    Cited by:

    1. Yu, Sha & Eom, Jiyong & Zhou, Yuyu & Evans, Meredydd & Clarke, Leon, 2014. "Scenarios of building energy demand for China with a detailed regional representation," Energy, Elsevier, vol. 67(C), pages 284-297.
    2. Zhao, Rui & Zhou, Xiao & Han, Jiaojie & Liu, Chengliang, 2016. "For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 262-274.
    3. Scott, Michael J. & Daly, Don S. & Hathaway, John E. & Lansing, Carina S. & Liu, Ying & McJeon, Haewon C. & Moss, Richard H. & Patel, Pralit L. & Peterson, Marty J. & Rice, Jennie S. & Zhou, Yuyu, 2015. "Calculating impacts of energy standards on energy demand in U.S. buildings with uncertainty in an integrated assessment model," Energy, Elsevier, vol. 90(P2), pages 1682-1694.
    4. Zhou, Yuyu & Clarke, Leon & Eom, Jiyong & Kyle, Page & Patel, Pralit & Kim, Son H. & Dirks, James & Jensen, Erik & Liu, Ying & Rice, Jennie & Schmidt, Laurel & Seiple, Timothy, 2014. "Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework," Applied Energy, Elsevier, vol. 113(C), pages 1077-1088.
    5. Eom, Jiyong & Clarke, Leon & Kim, Son H. & Kyle, Page & Patel, Pralit, 2012. "China's building energy demand: Long-term implications from a detailed assessment," Energy, Elsevier, vol. 46(1), pages 405-419.
    6. James McFarland & Yuyu Zhou & Leon Clarke & Patrick Sullivan & Jesse Colman & Wendy Jaglom & Michelle Colley & Pralit Patel & Jiyon Eom & Son Kim & G. Kyle & Peter Schultz & Boddu Venkatesh & Juanita , 2015. "Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison," Climatic Change, Springer, vol. 131(1), pages 111-125, July.
    7. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    8. Chaturvedi, Vaibhav & Kim, Sonny & Smith, Steven J. & Clarke, Leon & Yuyu, Zhou & Kyle, Page & Patel, Pralit, 2013. "Model evaluation and hindcasting: An experiment with an integrated assessment model," Energy, Elsevier, vol. 61(C), pages 479-490.
    9. Scott, Michael J. & Daly, Don S. & Zhou, Yuyu & Rice, Jennie S. & Patel, Pralit L. & McJeon, Haewon C. & Page Kyle, G. & Kim, Son H. & Eom, Jiyong & Clarke, Leon E., 2014. "Evaluating sub-national building-energy efficiency policy options under uncertainty: Efficient sensitivity testing of alternative climate, technological, and socioeconomic futures in a regional integr," Energy Economics, Elsevier, vol. 43(C), pages 22-33.
    10. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    11. repec:eee:enepol:v:110:y:2017:i:c:p:331-341 is not listed on IDEAS
    12. Daioglou, Vassilis & van Ruijven, Bas J. & van Vuuren, Detlef P., 2012. "Model projections for household energy use in developing countries," Energy, Elsevier, vol. 37(1), pages 601-615.

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    JEL classification:

    • F0 - International Economics - - General

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