Time-efficient approach for environmental transformation and bioavailability assessment of isotopically enriched...

The increasing use of engineered nanoparticles (NPs) and their release into the environment requires an assessment of their fate and (eco-) toxicological effects. Previous studies have often focused on pristine NPs or NPs spiked into the effluent of simulated wastewater treatment plants (WWTP) fed with artificial wastewater, combined with unrealistic high exposure concentrations to overcome problems associated with high metal background concentrations. In this study environmentally transformed NPs were obtained by direct spiking into an anaerobic digester filled with municipal sewage sludge. Isotopically enriched ⁴⁶TiO₂ and ⁶⁸ZnONPs were synthesized and used in the study to allow tracing of their fate in WWTP matrices at environmentally relevant concentrations, despite the high Zn and Ti background levels. NP-spiked sludge was used to create exposure media for uptake studies with the benthic amphipod Hyalella azteca under freshwater and brackish conditions. The results show that while ⁶⁸ZnONPs nearly achieved the target concentration (90 versus 100 mg ⁶⁸Zn/kg) in the spiked sludge, the ⁴⁶TiO₂NPs reached only 33 % of the target concentration (100 mg ⁴⁶Ti /kg), despite the good homogeneity of the ⁴⁶Ti distribution in the spiked sludge. The latter discrepancy most likely reflects aggregation and subsequent sedimentation of the ⁴⁶TiO₂NPs in the digester unit. Exposure of H. azteca to transformed ⁶⁸ZnONPs at concentrations between 3.5 and 9.7 μg ⁶⁸Zn/L led to significant ⁶⁸Zn accumulation in tissues. Our results show that the transformation processes led to an up to 12 times reduced uptake of ⁶⁸Zn from the transformed as compared to the pristine ⁶⁸ZnONPs, and this effect was more pronounced at freshwater exposure conditions. The new method of spiking an anaerobic sludge digestion unit balances environmental relevance, costs, time-efficiency and NPs losses (compared to spiking complete WWTP pilot systems or laboratory models) but requires optimization for NPs prone to aggregation such as TiO₂NPs.