Gerenciamento de áreas contaminadas de uma companhia de logística: proposta metodológica para hierarquização das intervenções

Abstract

Prioritizing contaminated-site liabilities is essential to guide interventions, reduce risks, and allocate resources in facilities with different levels of technical, environmental, and operational complexity. This technical study, developed as a case study, aimed to develop and apply a multicriteria decision matrix to rank four contaminated sites previously considered critical within a logistics company and to propose conceptual site rehabilitation strategies. The research was based on secondary data obtained from the corporate inventory, environmental reports, and technical and regulatory documents related to contaminated-site management. The methodology comprised data collection and systematization, selection of nine decision criteria, definition of classification scales, weighting of the criteria using the Analytic Hierarchy Process, and calculation of the final prioritization index. The criteria addressed the potential reach of risk, affected environmental media, presence of active sources and free-phase product, hydraulic conductivity, plume extent, estimated volume of contaminated soil, contaminant diversity, and operational interference caused by remediation. The consistency ratio was 0.044, indicating acceptable coherence among the judgments. The results identified Site B – SP as the highest-priority site, accounting for 27.5% of the relative score, followed by Sites C – RJ, D – MG, and A – SP. Its position was mainly associated with recurring free-phase product, an active source under control, impacts on multiple environmental media, and proximity to an environmentally sensitive area. Site-specific technical recommendations were proposed for all four sites, including, as applicable, conceptual site model updates, source and free-phase product control, migration containment, treatment of remaining contaminant phases, and environmental monitoring. The proposed matrix organizes dispersed technical information, makes the decision factors explicit, and supports decision-making, provided that the results are interpreted as a relative prioritization and complemented by site-specific feasibility assessments.