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Natural gas consumption and climate: a comprehensive set of predictive state-level models for the United States

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  • Sailor, David J.
  • Rosen, Jesse N.
  • Muñoz, J.Ricardo

Abstract

Separate models correlating natural gas (NG) consumption to climate have been developed for the residential and commercial sectors of the 50 U.S. states. The models relate a population-weighted average temperature to state per capita NG consumption on a monthly basis. The majority of the models have Pearson correlation coefficients greater than 0.90 supporting the use of temperature as the sole independent parameter. The sensitivities of the models to a 1°C increase in temperature, are compared for each state and the monthly sensitivity to climate integrated over the entire U.S. is investigated for a range of temperature perturbations. The predicted impact of a 1°C increase in mean monthly temperature on U.S. consumption is an 8.1% decrease in the residential sector and a 5.9% decrease in the commercial sector. In terms of the net consumption normalized over the study period (1984–1993) this corresponds to a 111.8TWh decrease in the residential sector and a 47.0TWh decrease in the commercial sector. The largest change for a single month occurs in January when consumption would decrease 19.7TWh in the residential sector and 7.4TWh in the commercial sector.

Suggested Citation

  • Sailor, David J. & Rosen, Jesse N. & Muñoz, J.Ricardo, 1998. "Natural gas consumption and climate: a comprehensive set of predictive state-level models for the United States," Energy, Elsevier, vol. 23(2), pages 91-103.
    • Handle: RePEc:eee:energy:v:23:y:1998:i:2:p:91-103
    DOI: 10.1016/S0360-5442(97)00073-X
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    Cited by:

    1. Yau, Y.H. & Pean, H.L., 2011. "The climate change impact on air conditioner system and reliability in Malaysia—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4939-4949.
    2. Fazle Wahid & Hamid Ullah & Sher Ali & Sajjad Ahmad Jan & Abid Ali & Azhar Khan & Imran Ali Khan & Maryam Bibi, 2021. "The Determinants and Forecasting of Electricity Consumption in Pakistan," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 241-248.
    3. Li, Danny H.W. & Yang, Liu & Lam, Joseph C., 2012. "Impact of climate change on energy use in the built environment in different climate zones – A review," Energy, Elsevier, vol. 42(1), pages 103-112.
    4. Spoladore, Alessandro & Borelli, Davide & Devia, Francesco & Mora, Flavio & Schenone, Corrado, 2016. "Model for forecasting residential heat demand based on natural gas consumption and energy performance indicators," Applied Energy, Elsevier, vol. 182(C), pages 488-499.
    5. Lam, Joseph C. & Tang, H.L. & Li, Danny H.W., 2008. "Seasonal variations in residential and commercial sector electricity consumption in Hong Kong," Energy, Elsevier, vol. 33(3), pages 513-523.
    6. Jianhua Huang & Kevin Robert Gurney, 2016. "Impact of climate change on U.S. building energy demand: sensitivity to spatiotemporal scales, balance point temperature, and population distribution," Climatic Change, Springer, vol. 137(1), pages 171-185, July.
    7. Huang, Jianhua & Gurney, Kevin Robert, 2016. "The variation of climate change impact on building energy consumption to building type and spatiotemporal scale," Energy, Elsevier, vol. 111(C), pages 137-153.
    8. Ruth, Matthias & Lin, Ai-Chen, 2006. "Regional energy demand and adaptations to climate change: Methodology and application to the state of Maryland, USA," Energy Policy, Elsevier, vol. 34(17), pages 2820-2833, November.
    9. Askari, S. & Montazerin, N. & Zarandi, M.H. Fazel, 2015. "Forecasting semi-dynamic response of natural gas networks to nodal gas consumptions using genetic fuzzy systems," Energy, Elsevier, vol. 83(C), pages 252-266.

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