JOURNAL ARTICLE
The ILC's Draft Principles on Environmental Protection in Armed Conflict: Legal and Humanitarian Perspectives.
Published In: African Journal of Law & Justice System, 2025, v. 4, n. 2. P. 31 1 of 3
Database: Africa Studies Source 2 of 3
Authored By: Laisani, John; Choma, Hlako 3 of 3
Abstract
This article critically examines the International Law Commission’s (ILC) Draft Principles on Environmental Protection in Armed Conflict, focusing on their legal and humanitarian implications. It highlights how armed conflicts cause extensive environmental degradation—such as deforestation, water contamination, and biodiversity loss—that disproportionately affects vulnerable populations and exacerbates human rights violations related to health, food security, and access to clean water. The study analyses the interplay of international humanitarian, environmental, and human rights law underpinning the ILC’s 28 draft principles, noting significant enforcement and compliance challenges, especially due to the lack of binding mechanisms and limited state participation in key treaties. Drawing on case studies including the Russia-Ukraine war and conflicts in the Sahel, the article underscores the need for stronger international legal frameworks, enhanced accountability measures (such as a proposed International Environmental Court), and integration of environmental protection into conflict resolution and post-conflict recovery to safeguard ecosystems and human rights in war-affected regions.
Additional Information
- Source:African Journal of Law & Justice System. 2025/08, Vol. 4, Issue 2, p31
- Document Type:Article
- Subject Area:Politics and Government
- Publication Date:2025
- ISSN:2753-3115
- DOI:10.31920/2753-3123/2025/v4n2a2
- Accession Number:187879614
- Copyright Statement:Copyright of African Journal of Law & Justice System is the property of Adonis & Abbey Publishers Ltd. 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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