A multi-criteria evaluation of marine pollution systems based on expert-driven analysis and robust ranking methods

The selection of effective coastal marine pollution monitoring systems requires integrating multiple technical, economic, and operational considerations. A decision-support approach is developed to compare five monitoring configurations using criteria that capture detection capability, spatial and temporal coverage, cost, robustness, and energy-related constraints. Expert input is obtained from 120 participants, with 110 responses meeting the consistency requirements, yielding an average consistency ratio of 0.064. The calculated weights indicate that detection capability (0.29) and coverage (0.24) are the most important factors in the assessment. The analysis identifies the underwater sensor network as the highest-ranked alternative, achieving a closeness coefficient of 0.56, followed by the cabled coastal observatory (0.53) and mobile autonomous platforms (0.49). The influence of parameter uncertainty is examined through a sensitivity analysis, in which ± 20% variations in criterion weights produce only limited changes in the ranking order. Additional stochastic simulations, based on ± 0.5 perturbations in performance scores over 100 runs, show low variability, with standard deviations below 0.02 across all alternatives. The results demonstrate consistent ranking behavior and highlight the importance of balanced system performance. The proposed approach supports informed decision-making and can be adapted to different monitoring contexts and evolving technological conditions.