Contamination presence and dynamics at a polluted site: spatial analysis of integrated data and joint conceptual modeling approach

Ciampi, Paolo;Esposito, Carlo;Cassiani, Giorgio;Deidda, Gian Piero;Flores-Orozco, Adrian;Rizzetto, Paolo;Chiappa, Andrea;Bernabei, Manuele;Gardon, Andrea;Petrangeli Papini, Marco

2022-01-01

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Abstract

Contaminated sites are complex systems posing challenges for their characterization as both contaminant distribution and hydrogeological properties vary markedly at the metric scale, yet may extend over broad areas, with serious issues of spatial under-sampling in the space. Characterization with sufficient spatial resolution is thus, one of the main concerns and still open areas of research. To this end, the joint use of direct and indirect (i.e., geophysical) investigation methods is a very promising approach. This paper presents a case study aspiring to demonstrate the benefit of a multidisciplinary approach in the characterization of a hydrocarbon-contaminated site. Detailed multi-source data, collected via stratigraphic boreholes, laser-induced fluorescence (LIF) surveys, electrical resistivity tomography (ERT) prospecting, groundwater hydrochemical monitoring, and gas chromatography–mass spectrometry (GC–MS) analyses were compiled into an interactive big-data package for modelling activities. The final product is a comprehensive conceptual hydro-geophysical model overlapping multi-modality data and capturing hydrogeological and geophysical structures, as well as contamination distribution in space and dynamics in time. The convergence of knowledge in the joint model verifies the possibility of discriminating geophysical findings based on lithological features and contamination effects, unmasking the real characteristics of the pollutant, the contamination mechanisms, and the residual phase hydrocarbon sequestration linked to the hydrogeological dynamics and adopted remediation actions. The emerging conceptual site model (CSM), emphasizing the necessity of a large amount of multi-source data for its reliable, high-resolution reconstruction, appears as the necessary tool for the design of remedial actions, as well as for the monitoring of remediation performance.