For many polar organic micropollutants, biotransformation by activated sludge microorganisms is a major removal process during wastewater treatment. However, our current understanding of how wastewater treatment operations influence microbial communities and their micropollutant biotransformation potential is limited, leaving major parts of observed variability in biotransformation rates across treatment facilities unexplained. Here, we present biotransformation rate constants for 42 micropollutants belonging to different chemical classes along a gradient of solids retention time (SRT). The geometric mean of biomass-normalized first-order rate constants shows a clear increase between 3 and 15 d SRT by 160% and 87%, respectively, in two experiments. However, individual micropollutants show a variety of trends. Rate constants of oxidative biotransformation reactions mostly increased with SRT. Yet, nitrifying activity could be excluded as primary driver. For substances undergoing other than oxidative reactions, i.e., mostly substitution-type reactions, more diverse dependencies on SRT were observed. Most remarkably, characteristic trends were observed for groups of substances undergoing similar types of initial transformation reaction, suggesting that shared enzymes or enzyme systems that are conjointly regulated catalyze biotransformation reactions within such groups. These findings open up opportunities for correlating rate constants with measures of enzyme abundance such as genes or gene products, which in turn should help to identify enzymes associated with the respective biotransformation reactions.

The presence of antibiotics in treated wastewater and consequently in surface and groundwater resources raises concerns about the formation and spread of antibiotic resistance. Improving the removal of antibiotics during wastewater treatment therefore is a prime objective of environmental engineering. Here we obtained a detailed picture of the fate of sulfonamide antibiotics during activated sludge treatment using a combination of analytical methods. We show that pterin-sulfonamide conjugates, which are formed when sulfonamides interact with their target enzyme to inhibit folic acid synthesis, represent a major biotransformation route for sulfonamides in laboratory batch experiments with activated sludge. The same major conjugates were also present in the effluents of nine Swiss wastewater treatment plants. The demonstration of this biotransformation route, which is related to bacterial growth, helps explain seemingly contradictory views on optimal conditions for sulfonamide removal. More importantly, since pterin-sulfonamide conjugates show retained antibiotic activity, our findings suggest that risk from exposure to sulfonamide antibiotics may be less reduced during wastewater treatment than previously assumed. Our results thus further emphasize the inadequacy of focusing on parent compound removal and the importance of investigating biotransformation pathways and removal of bioactivity to properly assess contaminant removal in both engineered and natural systems.

In vitro bioassays are increasingly used for water quality monitoring. Surface water samples often need to be enriched to observe an effect and solid-phase extraction (SPE) is commonly applied for this purpose. The applied methods are typically optimised for the recovery of target chemicals and not for effect recovery for bioassays. A review of the few studies that have evaluated SPE recovery for bioassays showed a lack of experimentally determined recoveries. Therefore, we systematically measured effect recovery of a mixture of 579 organic chemicals covering a wide range of physicochemical properties that were spiked into a pristine water sample and extracted using large volume solid-phase extraction (LVSPE). Assays indicative of activation of xenobiotic metabolism, hormone receptor-mediated effects and adaptive stress responses were applied, with non-specific effects determined through cytotoxicity measurements. Overall, effect recovery was found to be similar to chemical recovery for the majority of bioassays and LVSPE blanks had no effect. Multi-layer SPE exhibited greater recovery of spiked chemicals compared to LVSPE, but the blanks triggered cytotoxicity at high enrichment. Chemical recovery data together with single chemical effect data were used to retrospectively estimate with reverse recovery modelling that there was typically less than 30% effect loss expected due to reduced SPE recovery in published surface water monitoring studies. The combination of targeted experiments and mixture modelling clearly shows the utility of SPE as a sample preparation method for surface water samples, but also emphasizes the need for adequate controls when extraction methods are adapted from chemical analysis workflows.

Compartment-specific degradation half-lives are essential pieces of information in the regulatory risk assessment of synthetic chemicals. However, their measurement according to regulatory testing guidelines is laborious and costly. Despite the obvious ecological and economic benefits of knowing environmental degradability as early as possible, its consideration in the early phases of rational chemical design is therefore challenging. Here, we explore the possibility to use half-lives determined in highly time-and work-efficient biotransformation experiments with activated sludge and mixtures of chemicals to predict soil half-lives from regulatory simulation studies. We experimentally determined half-lives for 52 structurally diverse agrochemical active ingredients in batch reactors with three concentrations of the same activated sludge. We then developed bi-and multivariate models for predicting half-lives in soil by regressing the experimentally determined half-lives in activated sludge against average soil half-lives of the same chemicals extracted from regulatory data. The models differed in how we accounted for sorption-related bioavailability differences in soil and activated sludge. The best performing models exhibited good coefficients-of-determination (R 2 of around 0.8), low average errors (< factor of 3 in half-life predictions) and were robust in cross-validation. From a practical perspective, these results suggest that it may indeed be possible to read across from half-lives determined in highly efficient biotransformation experiments in activated sludge to soil half-lives, which are obtained from much more work-and resource-intense regulatory studies, and that these predictions are clearly superior to predictions based on the output of the publicly available BIOWIN QSBR model. From a theoretical perspective, these results suggest that soil and activated sludge microbial communities, although certainly different in terms of taxonomic composition, may be functionally similar with respect to the enzymatic transformation of environmentally relevant concentrations of a diverse range of chemical compounds.

No abstract