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The critical role of humidity in modeling summer electricity demand across the United States

Author

Listed:
  • Debora Maia-Silva

    (Purdue University)

  • Rohini Kumar

    (Helmholtz Centre for Environmental Research-UFZ)

  • Roshanak Nateghi

    (Purdue University
    Purdue University)

Abstract

Cooling demand is projected to increase under climate change. However, most of the existing projections are based on rising air temperatures alone, ignoring that rising temperatures are associated with increased humidity; a lethal combination that could significantly increase morbidity and mortality rates during extreme heat events. We bridge this gap by identifying the key measures of heat stress, considering both air temperature and near-surface humidity, in characterizing the climate sensitivity of electricity demand at a national scale. Here we show that in many of the high energy consuming states, such as California and Texas, projections based on air temperature alone underestimates cooling demand by as much as 10–15% under both present and future climate scenarios. Our results establish that air temperature is a necessary but not sufficient variable for adequately characterizing the climate sensitivity of cooling load, and that near-surface humidity plays an equally important role.

Suggested Citation

  • Debora Maia-Silva & Rohini Kumar & Roshanak Nateghi, 2020. "The critical role of humidity in modeling summer electricity demand across the United States," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15393-8
    DOI: 10.1038/s41467-020-15393-8
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    Cited by:

    1. Jing-Li Fan & Zezheng Li & Xi Huang & Kai Li & Xian Zhang & Xi Lu & Jianzhong Wu & Klaus Hubacek & Bo Shen, 2023. "A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Pezalla, Simon & Obringer, Renee, 2023. "Evaluating the household-level climate-electricity nexus across three cities through statistical learning techniques," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    3. Yaqing Sheng & Jinpeng Liu & Delin Wei & Xiaohua Song, 2021. "Heterogeneous Study of Multiple Disturbance Factors Outside Residential Electricity Consumption: A Case Study of Beijing," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    4. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    5. Zhang, Yuejuan & Li, Xian-Xiang & Xin, Rui & Chew, Lup Wai & Liu, Chun-Ho, 2024. "Applicability of data-driven methods in modeling electricity demand-climate nexus: A tale of Singapore and Hong Kong," Energy, Elsevier, vol. 300(C).
    6. Edward Manderson & Timothy Considine, 2021. "The Effect of Temperature on Energy Demand and the Role of Adaptation," Economics Discussion Paper Series 2112, Economics, The University of Manchester.
    7. Jose M. Garrido-Perez & David Barriopedro & Ricardo García-Herrera & Carlos Ordóñez, 2021. "Impact of climate change on Spanish electricity demand," Climatic Change, Springer, vol. 165(3), pages 1-18, April.

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