In the field of exposure-driven risk assessment of engineered nanoparticles (NPs), the highly complex interactions of NPs with natural components in surface waters are considered key factors to understand their fate and behavior in the environment. However, since experimental approaches aiming at imitating environmentally relevant conditions include many parameters and lead to a high number of outcomes, statistical tools can be extremely useful to support the results' interpretation. In this context, a multimethod approach was applied to investigate the colloidal behavior of TiO2 NPs in both artificial waters and natural brackish water (from the Venice lagoon, Italy), in the presence of standard kaolinite and natural organic matter (NOM), or of the fine fraction of natural colloidal particles (NCPs) from the lagoon sediment. In detail, the experimental data obtained, i.e. hydrodynamic size, surface charge and sedimentation velocity values, were i) statistically treated by hierarchical clustering and ii) merged into a global stability index (IG). The hierarchical clustering allowed to group the dispersions into three colloidal stability classes, where the main discriminant was the medium composition (i.e. ionic strength and presence of NOM), while the IG allowed to establish a colloidal stability ranking of the dispersions within each class. Moreover, the comparison among the different dispersions suggested that kaolinite could be considered as a suitable surrogate for NCPs, to estimate the colloidal behavior and environmental fate of TiO2 NPs in natural aqueous media.
Keywords: Cluster analysis; Global stability index; Kaolinite; Nanoparticles; Natural colloidal particles; Natural waters.
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