JOURNAL ARTICLE

How to kill a powerline: Utility-on-utility violence, electricity capital, and the political ecology of climate delay.

  • Published In: Environment & Planning E: Nature & Space, 2026, v. 9, n. 1. P. 312 1 of 3

  • Database: Environment Complete 2 of 3

  • Authored By: Abreek-Zubiedat, Fatina; Katz, Irit; Kroot, Maddy 3 of 3

Abstract

This article examines how incumbent electricity capital—firms and infrastructures already operating within electricity markets—use structural and strategic tactics to delay new low-carbon energy projects, focusing on the dynamics between incumbents and new entrants rather than solely on carbon intensity. Through a case study of the New England Clean Energy Connect (NECEC) transmission line in Maine, it demonstrates how incumbent utilities, including fossil fuel and nuclear interests, financially supported and amplified pre-existing local opposition groups to slow the project's permitting and development, a process described as "utility-on-utility violence." The study highlights how this weaponization of public participation creates procedural injustices by limiting under-resourced community involvement and scapegoating opposition as astroturfed, thereby obscuring incumbent capital's role in climate delay. The article argues for policy reforms that enhance genuine public participation and discipline incumbent interference to support more democratic and equitable energy transitions.

Additional Information

  • Source:Environment & Planning E: Nature & Space. 2026/02, Vol. 9, Issue 1, p312
  • Document Type:Article
  • Subject Area:Politics and Government
  • Publication Date:2026
  • ISSN:2514-8486
  • DOI:10.1177/25148486251386257
  • Accession Number:191833545
  • Copyright Statement:Copyright of Environment & Planning E: Nature & Space is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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