Expert-based risk prioritization using fuzzy AHP and bow-tie modeling at Ethiopia's largest urban open dumpsite
Open dumping poses significant environmental, health, and socio-economic risks. The Repi dumpsite exemplifies these challenges. This study assessed perceived risks using an integrated fuzzy analytical hierarchy process (FAHP) and qualitative bow-tie model. Risks were identified and evaluated through the Delphi method based on expert judgments, and screened using risk matrix analysis. Screened risks were weighted and prioritized through FAHP pairwise comparisons, with consistency ratios ensuring logical judgments. Sensitivity analysis confirmed ranking robustness, with top risks unchanged across all scenarios. Twenty-eight risks were screened across environmental (9), health (11), and socio-economic (8) domains. Environmental risks ranked “Contamination of downstream water sources” highest (CW: 0.12445), followed by "Degradation of the surrounding soil and water quality, and unaesthetic appearance" (CW: 0.12284). Health and safety risks ranked "Occupational health risks to waste pickers" first (CW: 0.10039), followed by “Vector- and rodent-borne diseases" (CW: 0.09725). Socio-economic risks ranked “Loss of aesthetic value" first (CW: 0.13597), followed by "Decrease in quality of life" (CW: 0.13378). The Bow-tie model mapped causal pathways to critical control barriers, providing visual intervention pathways for targeted remediation. Findings support SDG 6 (Clean water), SDG 3 (Health), and SDG 11 (Sustainable cities). The framework is transferable, but site-specific recalibration is needed.
Authors
- Demamu Tagele Haligamo (ORCID: https://orcid.org/0000-0002-3592-1024)
- Tamru Tesseme Aragaw (ORCID: https://orcid.org/0000-0003-3557-5376)
- Esayas Alemayehu (ORCID: https://orcid.org/0000-0001-8843-1136)
Institutions
- Jimma University (ET)
- Arba Minch University (ET)
Publication Details
- Journal
- Case Studies in Chemical and Environmental Engineering
- Published
- 2026-08-21
- DOI
- https://doi.org/10.1016/j.cscee.2026.101471
- Primary Topic
- Multi-Criteria Decision Making
- Type
- article
- Field-Weighted Citation Impact
- 0.00