Heliyon (Jan 2024)
Multiple-criteria decision analysis techniques for anaerobic digester technology assessment
Abstract
Effective decision-making requires the evaluation of several criteria rather than a single, preferred criterion. The best decision options (alternatives) are recommended to decision-makers when a multi-criteria decision problem is addressed. This study develops a multi-criteria selection method for the assessment of small-scale anaerobic digester technology by combining two existing methods. The Simple Multi-Attribute Rating Technique (SMART) and the Analytical Hierarchy Process (AHP) approaches of multiple-criteria decision analysis were used as a decision support tool, and the preferred anaerobic digester technology was selected from a list of eleven potential small-scale digester technologies used in low to middle-income countries. These techniques were applied under two scenarios for a case study in the South African smallholder farmers. Scenario 1 involves a subsistence smallholder farming context, while scenario 2 involves a commercially oriented smallholder farming context. The overall results revealed that the DIY Biobag and Puxin digester design models achieved 82.1 and 73.7 % preference in comparison to other digester technologies for scenarios 1 and 2, respectively. The Biobag digester technology achieved the highest ranking, which is consistent with the significant cost advantage and technical characteristics of the technology. However, for those households with sufficient access to funds for the initial expenditure, the method identifies the Puxin digester as the most appropriate alternative, excluding cases where underground construction is not possible. The AGAMA BiogasPro digester was ranked in the second position in both scenarios. A sensitivity analysis was conducted to determine the effect of changes in the assessment criteria weights and found the selected alternatives stable and robust. Finally, it can be concluded that the developed technology selection model contributed a knowledge-based framework to be used in various situations by different decision-makers, thereby providing a method applicable to particular local conditions to identify the most suitable technology choices.
