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Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma

Author

Listed:
  • Diana Mitsova

    (Florida Atlantic University)

  • Ann-Margaret Esnard

    (Georgia State University)

  • Alka Sapat

    (Florida Atlantic University)

  • Betty S. Lai

    (Lynch School of Education, Boston College)

Abstract

Large-scale damage to the power infrastructure from hurricanes and high-wind events can have devastating ripple effects on infrastructure, the broader economy, households, communities, and regions. Using Hurricane Irma’s impact on Florida as a case study, we examined: (1) differences in electric power outages and restoration rates between urban and rural counties; (2) the duration of electric power outages in counties exposed to tropical storm force winds versus hurricane Category 1 force winds; and (3) the relationship between the duration of power outage and socioeconomic vulnerability. We used power outage data for the period September 9, 2017–September 29, 2017. At the peak of the power outages following Hurricane Irma, over 36% of all accounts in Florida were without electricity. We found that the rural counties, predominantly served by rural electric cooperatives and municipally owned utilities, experienced longer power outages and much slower and uneven restoration times. Results of three spatial lag models show that large percentages of customers served by rural electric cooperatives and municipally owned utilities were a strong predictor of the duration of extended power outages. There was also a strong positive association across all three models between power outage duration and urban/rural county designation. Finally, there is positive spatial dependence between power outages and several social vulnerability indicators. Three socioeconomic variables found to be statistically significant highlight three different aspects of vulnerability to power outages: minority groups, population with sensory, physical and mental disability, and economic vulnerability expressed as unemployment rate. The findings from our study have broader planning and policy relevance beyond our case study area, and highlight the need for additional research to deepen our understanding of how power restoration after hurricanes contributes to and is impacted by the socioeconomic vulnerabilities of communities.

Suggested Citation

  • Diana Mitsova & Ann-Margaret Esnard & Alka Sapat & Betty S. Lai, 2018. "Socioeconomic vulnerability and electric power restoration timelines in Florida: the case of Hurricane Irma," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 689-709, November.
    • Handle: RePEc:spr:nathaz:v:94:y:2018:i:2:d:10.1007_s11069-018-3413-x
    DOI: 10.1007/s11069-018-3413-x
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    Cited by:

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    2. Natalie Coleman & Chenyue Liu & Yiqing Zhao & Ali Mostafavi, 2023. "Lifestyle pattern analysis unveils recovery trajectories of communities impacted by disasters," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    3. Diana Mitsova & Monica Escaleras & Alka Sapat & Ann-Margaret Esnard & Alberto J. Lamadrid, 2019. "The Effects of Infrastructure Service Disruptions and Socio-Economic Vulnerability on Hurricane Recovery," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    4. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. Wenjuan Sun & Paolo Bocchini & Brian D. Davison, 2020. "Applications of artificial intelligence for disaster management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2631-2689, September.
    6. Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani & Koskela, Liinu, 2021. "Linking socio-economic aspects to power system disruption models," Energy, Elsevier, vol. 222(C).
    7. Vivian Do & Heather McBrien & Nina M. Flores & Alexander J. Northrop & Jeffrey Schlegelmilch & Mathew V. Kiang & Joan A. Casey, 2023. "Spatiotemporal distribution of power outages with climate events and social vulnerability in the USA," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    8. Paul Nduhuura & Matthias Garschagen & Abdellatif Zerga, 2020. "Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana," Energies, MDPI, vol. 13(17), pages 1-26, August.
    9. Sisi Meng & Pallab Mozumder, 2021. "Hurricane Sandy: Damages, Disruptions and Pathways to Recovery," Economics of Disasters and Climate Change, Springer, vol. 5(2), pages 223-247, July.
    10. Cheng-Chun Lee & Mikel Maron & Ali Mostafavi, 2022. "Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.

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