Energy resilience in the Arctic states: An integrated assessment and policy implications for sustainable transitions


Li R., PATA U. K., Ma M., Pisarenko Z. V., Kadet V. V., Wang Q.

Geoscience Frontiers, vol.17, no.4, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 4
  • Publication Date: 2026
  • Doi Number: 10.1016/j.gsf.2026.102335
  • Journal Name: Geoscience Frontiers
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Geobase
  • Keywords: Arctic energy resilience, Energy import dependence, Governance effectiveness, Spatiotemporal analysis, Sustainability pathways
  • Azerbaijan State University of Economics (UNEC) Affiliated: No

Abstract

Energy resilience has become a central requirement for sustainable energy transitions at high latitudes, where climate hazards and geopolitical shocks intersect. This study develops an integrated measurement–evolution–mechanism framework to assess energy resilience in the eight Arctic states from 2014 to 2023, combining a three-dimension indicator system (resistance, adaptability, recovery), projection-pursuit–based composite scoring, distributional dynamics, and data-driven driver identification. Using official statistics, we estimate annual national resilience scores, track spatiotemporal patterns, and quantify the relative importance of structural, economic, and governance factors. Three main results emerge. First, the region exhibits a steady rise in resilience, but persistent stratification: the United States and Russia remain consistently highest; Canada and Denmark are stable at mid-high levels; Finland trends downward; Sweden, Iceland, and Norway remain lower, with renewed divergence after 2021. Second, three archetypes are identified: a recovery–resistance–dominated group with weak adaptability (Iceland, Sweden, Finland); an adaptability-advantaged group (Canada, United States, Denmark, Russia); and a low comprehensive-resilience case (Norway). Third, energy import dependence is the dominant determinant, followed by green policy intensity, government effectiveness, and human capital investment; the random forest model explains approximately 88% of cross-country variation, underscoring robust, nonlinear driver effects. Policy priorities include reducing import exposure and single-fuel risks, accelerating renewable and flexibility investments, diversifying industrial structures, and strengthening fiscal–institutional capacity and education to support adaptive and rapid recovery. The framework is transferable beyond the Arctic, linking quantitative diagnostics to actionable pathways for renewable-led, climate-robust energy systems.