Industrial sites affected by anthropogenic contamination, both past and present-day, commonly have intricate pollutant patterns, and source discrimination can be thus highly challenging. To this goal, this paper presents a novel approach combining multivariate statistics and environmental forensic techniques. The efficiency of this methodology was exemplified in a severely polluted estuarine area (Avilés, Spain), where factor analysis and clustering were performed to identify sub-areas with distinct geochemical behaviour. Once six clusters were defined and a pollution index applied, forensic tools revealed that the As speciation, Pb isotopes, and PAHs molecular ratios were useful to categorise the cluster groups on the basis of distinct pollution sources: Zn-smelting, coaly particles and waste disposal. Overall, this methodology offers valuable insight into pollution sources identification, which can be extended to comparable scenarios of complexly polluted environmental compartments. The information gathered using this approach is also important for the planning of risk assessment procedures and potential remediation strategies.

Department of Environmental Geosciences Faculty of Environmental Sciences Czech University of Life Sciences Kamýcká 129 16500 Prague Czech Republic

Escuela Superior de Ingenieros de Minas y Energía Campus de Vegazana University of León 24071 León Spain

INDUROT and Environmental Biogeochemistry and Raw Materials Group Campus de Mieres University of Oviedo 33600 Mieres Spain

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