https://journals.tultech.eu/index.php/eil/issue/feed 2026-09-19T20:44:41+02:00 Associate Editor: Mr. Amir Hedayati amir.hedayati@tultech.eu Open Journal Systems <p style="font-weight: 400;"><strong>Environmental Industry Letters (EIL)</strong> is an innovative open-access journal that sits at the intersection of environmental science and industrial development. Our mission is to offer a unique perspective on the mutually beneficial relationship between industries and the environment and, hence, promote practical and sustainable approaches to their coexistence. EIL maintains a global perspective, addressing the diverse needs and challenges faced by industries across developed and developing nations. The journal distinguishes itself by introducing fresh viewpoints into the scientific discourse, enriching our understanding of the intricate connection between industry and the environment.</p> <p style="font-weight: 400;"> </p> https://journals.tultech.eu/index.php/eil/article/view/698 2026-09-19T20:44:41+02:00 Farzan Khorasani Farzan.khorasani@student.lut.fi

<p><strong>Abstract<br></strong>Environmental impact assessment (EIA) of large hydropower schemes involves criteria that are simultaneously heterogeneous in scale, partly qualitative, and elicited under expert uncertainty, conditions for which fuzzy multi-criteria decision-making (MCDM) is well suited. This study develops an integrated fuzzy logic decision-making system combining fuzzy Analytic Hierarchy Process (fuzzy AHP), fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS), and a Mamdani fuzzy inference system (FIS), and applies it to a case study of six operating large hydropower schemes (Three Gorges, Itaipu, Belo Monte, Nam Theun 2, the Grand Ethiopian Renaissance Dam, and Xayaburi) evaluated against eight environmental, social and technical criteria. Criteria weights were derived with Buckley's fuzzy geometric-mean method (cross-checked against Chang's extent analysis, consistency ratio CR = 0.012), and used to rank alternatives by fuzzy-TOPSIS closeness coefficient. An independently parameterised Mamdani FIS provided a rule-based severity classification as a cross-check. The Xayaburi scheme obtained the most favourable composite ranking, driven by its comparatively small inundation footprint and low resettlement burden, despite documented severe biodiversity impacts; Monte Carlo weight-perturbation analysis (2,000 runs) confirmed this ranking is robust to plausible weight uncertainty (mean Spearman's rho = 0.85), while one-at-a-time ±20% perturbations left the top rank unchanged in all 16 scenarios. The Mamdani cross-check, however, classified five of the six schemes as “High” overall impact severity, underscoring that a favourable composite rank should not be read as low absolute impact. The framework, released with fully reproducible open-source Python code, offers environmental regulators and financing institutions a transparent, auditable decision-support tool for comparative hydropower EIA.</p>

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