The rapid development of nanotechnology has stimulated the use of silver nanoparticles (AgNPs) in various fields that leads to their presence in different ecosystem compartments, in particular aquatic ecosystems. Several studies have shown that a variety of living organisms are affected by AgNPs. Therefore, a methodology to assess the risk of AgNPs for aquatic ecosystems was developed. The methodology is based on fuzzy logic, a proven method for dealing with variables with an associated uncertainty, as is the case with many variables related to AgNPs. After a careful literature search, a selection of relevant variables was carried out and the fuzzy model was designed. From inputs such as AgNPs’ size, shape, and coating, it is possible to determine their level of toxicity which, together with their level of concentration, are sufficient to create a risk assessment. Two case studies to assess this methodology are presented, one involving continuous effluent from a wastewater treatment plant and the second involving an accidental spill. The results showed that the accidental spills have a higher risk than WWTP release, with the combination of Plates–BPEI being the most toxic one. This approach can be adapted to different situations and types of nanoparticles, making it highly useful for both stakeholders and decision makers.

This paper aims to create a new model for assessing the ecosystem risk in rivers and wetlands that are linked to accidental spills of silver nanoparticles (AgNPs) in soil/groundwater. Due to the uncertainty of the modeling inputs, a combination of two well-known risk assessment methodologies (Monte Carlo and fuzzy logic) were used. To test the new model, two hypothetical, accidental AgNP soil spill case studies were evaluated; both of which were located at the end of the Llobregat River basin within the metropolitan area of Barcelona (NE Spain). In both cases, the soil spill reached groundwater. In the first case, it was discharged into a river, and in the second case, it recharged a wetland. Concerning the results, in the first case study, a medium-risk assessment was achieved for most cases (83%), with just 10% of them falling below the future legal threshold concentration value. In the second case study, a high-risk assessment was obtained for most cases (84%), and none of the cases complied with the threshold value. A sensitivity analysis was conducted for the concentration and risk. The developed tool was proven capable of assessing risk in aquatic ecosystems when dealing with uncertain and variable data, which is an improvement compared to other risk assessment methodologies.