Scenario-targeted toxicity assessment through multiple endpoint bioassays in a soil posing unacceptable environmental risk according to regulatory screening values.

Lanestosa is a chronically polluted site (derelict mine) where the soil (Lanestosa (LA) soil) exceeds screening values (SVs) of regulatory policies in force (Basque Country; Europe) for Zn, Pb and Cd. A scenario-targeted toxicity assessment was carried out on the basis of a multi-endpoint bioassay approach. Acute and chronic toxicity bioassays were conducted with selected test species (Vibrio fischeri, Dictyostelium discoideum, Lactuca sativa, Raphanus sativus and Eisenia fetida) in combination with chemical analysis of soils and elutriates and with bioaccumulation studies in earthworms. Besides, the toxicity profile was compared with that of the mine runoff (RO) soil and of a fresh artificially polluted soil (LAAPS) resembling LA soil pollutant profile. Extractability studies in LA soil revealed that Pb, Zn and Cd were highly available for exchange and/or release into the environment. Indeed, Pb and Zn were accumulated in earthworms and LA soil resulted to be toxic. Soil respiration, V. fischeri, vegetative and developmental cycles of D. discoideum and survival and juvenile production of E. fetida were severely affected. These results confirmed that LA soil had unacceptable environmental risk and demanded intervention. In contrast, although Pb and Zn concentrations in RO soil revealed also unacceptable risk, both metal extractability and toxicity were much lower than in LA soil. Thus, within the polluted site, the need for intervention varied between areas that posed dissimilar risk. Besides, since LAAPS, with a high exchangeable metal fraction, was the most toxic, ageing under in situ natural conditions seemingly contributed to attenuate LA soil risk. As a whole, combining multi-endpoint bioassays with scenario-targeted analysis (including leaching and ageing) provides reliable risk assessment in soils posing unacceptable environmental risk according to SVs, which is useful to optimise the required intervention measures.