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Direct and indirect threats by organic micropollutants can only be reliably assessed and prevented if the exposure to these chemicals is known, which in turn requires a confident estimate of their emitted amounts into the environment. APIs (Active Pharmaceutical Ingredients) enter surface waters mostly through the sewer system and wastewater treatment plants (WWTPs). However, their effluent fluxes are highly variable and influenced by several different factors that challenge robust emission estimates. Here, we defined a dimensionless, theoretically consumption-independent ‘escape factor’ (kesc) for estimating the amount of APIs (expected to be) present in WWTP effluents. The factor is determined as the proportion of marketed and actually emitted amounts of APIs. A large collection of German and Swiss monitoring datasets were analysed to calculate stochastic kesc values for 31 APIs, reflecting both the magnitude and uncertainty of consumption-normalised emissions. Escape factors provide an easy-to-use tool for the estimation of average API emissions and expected variability from numerous WWTPs given that consumption data are provided, thereby supporting simulation modeling of the fate of APIs in stream networks or exposure assessments.

This study presents a nation-wide assessment of the influence of chemical and pharmaceutical manufacturing (CPM) wastewaters on synthetic organic contaminant (SOC) emissions to Swiss surface waters. Geographic Information System (GIS) based analysis of the presence of CPM in wastewater treatment plant (WWTP) catchments revealed wide distribution of this industrial sector across Switzerland, suggesting that one-third of the 718 Swiss WWTPs may be influenced by CPM wastewaters. To reflect the diversity of this type of wastewaters, we investigated the effluents of 11 WWTPs of diverse sizes and technologies, which treated 0-100% wastewater from a variety of CPM activities. In an extensive sampling campaign, we collected temporally high resolved (i.e., daily) samples for 2-3 months to capture the dynamics of CPM discharges. The > 850 samples were then measured with liquid chromatography high-resolution mass spectrometry (LC-HRMS). Non-target characterization of the LC-HRMS time series datasets revealed that CPM wastewaters left a highly variable and site-specific signature in the effluents of the WWTPs. Particularly, compared to WWTPs with purely domestic input, a larger variety of substances (up to 15 times more compounds) with higher maximum concentrations (1-2 orders of magnitude) and more uncommon substances were found in CPM-influenced effluents. Moreover, in the latter, highly fluctuating discharges often contributed to a substantial fraction of the overall emissions. The largely varying characteristics of CPM discharges between different facilities were primarily related to the type of activities at the industries (i.e., production versus processing of chemicals) as well as to the pre-treatment and storage of CPM wastewaters. Eventually, for one WWTP, LC-HRMS time series were correlated with ecotoxicity time series obtained from bioassays and major toxic components could be identified. Overall, in view of their potential relevance to water quality, a strong focus on SOC discharges from CPM is essential, including the design of situation-specific monitoring, as well as risk assessment and mitigation strategies that consider the variability of industrial emissions., Water Research, 215, ISSN:0043-1354, ISSN:1879-2448

Chemicals’ half-lives derived from biotransformation simulation studies are central metrics for persistence assessment in international regulatory frameworks. To determine the persistence of chemic...

Temperature is a key factor that influences chemical biotransformation potential and rates, on which exposure and fate models rely to predict the environmental (micro)pollutant fate. Arrhenius-based models are currently implemented in environmental exposure assessment to adapt biotransformation rates to actual temperatures, assuming validity in the 0-30 °C range. However, evidence on how temperature shifts affect the physicochemical and microbial features in biological systems is scarce, questioning the validity of the existing modeling approaches. In this work, laboratory-scale batch assays were designed to investigate how a mixed microbial community responds to short-term temperature shifts, and how this impacts its ability to biotransform a range of structurally diverse micropollutants. Our results revealed three distinct kinetic responses at temperatures above 20 °C, mostly deviating from the classic Arrhenius-type behavior. Micropollutants with similar temperature responses appeared to undergo mostly similar initial biotransformation reactions, with substitution-type reactions maintaining Arrhenius-type behavior up to higher temperatures than oxidation-type reactions. Above 20 °C, the microbial community also showed marked shifts in both composition and activity, which mostly correlated with the observed deviations from Arrhenius-type behavior, with compositional changes becoming a more relevant factor in biotransformations catalyzed by more specific enzymes (e.g., oxidation reactions). Our findings underline the need to re-examine and further develop current environmental fate models by integrating biological aspects, to improve accuracy in predicting the environmental fate of micropollutants.

This study presents a nontarget approach to detect discharges from pharmaceutical production in municipal wastewater treatment plant (WWTP) effluents and to estimate their relevance on the total emissions. Daily composite samples were collected for 3 months at two WWTPs in Switzerland, measured using liquid chromatography high-resolution mass spectrometry, and time series were generated for all features detected. The extent of intensity variation in the time series was used to differentiate relatively constant domestic inputs from highly fluctuating industrial emissions. We show that an intensity variation threshold of 10 correctly classifies compounds of known origin and reveals clear differences between the two WWTPs. At the WWTP receiving wastewater from a pharmaceutical manufacturing site, (i) 10 times as many potential industrial emissions were detected as compared to the WWTP receiving purely domestic wastewater; (ii) for 11 pharmaceuticals peak concentrations, >10 μg/L and up to 214 μg/L were quantified, which are clearly above typical municipal wastewater concentrations; and (iii) a pharmaceutical not authorized in Switzerland was identified. Signatures of potential industrial emissions were even traceable at the downstream Rhine monitoring station at a >4000-fold dilution. Several of them occurred repeatedly, suggesting that they were linked to regular production, not to accidents. Our results demonstrate that small wastewater volumes from a single industry not only left a clear signature in the effluents of the respective WWTP but also influenced the water quality of one of Europe's most important river systems. Overall, these findings indicate that pharmaceutical production is a relevant emission source even in highly developed countries with a strong focus on water quality, such as Switzerland.

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 (R2 of around 0.8) and low average errors (

The lack of fundamental insights on the fate of micropollutants during conventional activated sludge treatment in wastewater treatment plants (WWTPs) presents one of the biggest challenges in optimizing their removal. To address this challenge, we designed a study to identify the drivers of micropollutant removal in WWTPs. We calculated the removal efficiency of micropollutants across the activated sludge process of full-scale wastewater treatment plants from literature-reported data. Our final dataset consisted of 529 independent observations for 84 micropollutants along with a set of associated activated sludge process parameters. We used the Eawag pathway prediction system to predict initial biotransformations for each of the 84 micropollutants and hierarchical clustering to group chemicals based on similarities in their predicted initial sets of biotransformations. We then applied stability selection to generate well-performing models that can be interpreted to uncover the key factors contributing to the range of removal efficiencies calculated for each cluster of micropollutants. The key factors considered in stability selection included six physicochemical properties of the micropollutants and six activated sludge process parameters. The sludge–water partitioning coefficient, molecular weight, solids retention time, influent micropollutant concentration, and dissolved oxygen levels were consistently identified as key factors of micropollutant removal for clusters of micropollutants that undergo certain types of initial biotransformations. Our findings highlight the importance of considering initial biotransformations when evaluating micropollutant removal and identify important process parameters that determine the fate of micropollutants during activated sludge treatment.

Despite their strict environmental regulations and state-of-the-art wastewater treatment infrastructure, chemical and pharmaceutical industries in Switzerland leave a clear footprint in treated wastewater that is released into the open environment.

Biotransformation of chemical contaminants is of importance in various natural and engineered systems. However, in complex microbial communities and with chemical contaminants at low concentrations, our current understanding of biotransformation at the level of enzyme-chemical interactions is limited. Here, we explored an approach to identify associations between micropollutant biotransformation and specific gene products in complex microbial communities, using association mining between chemical and metatranscriptomic data obtained from experiments with activated sludge grown at different solid retention times. We successfully demonstrate proportional relationships between the measured rate constants and associated gene transcripts for nitrification as a major community function, but also for the biotransformation of two nitrile-containing micropollutants (bromoxynil and acetamiprid) and transcripts of nitrile hydratases, a class of enzymes that we experimentally confirmed to produce the detected amide transformation products. As these results suggest that metatranscriptomic information can indeed be quantitatively correlated with low abundant community functions such as micropollutant biotransformation in complex microbial communities, we proceeded to explore the potential of association mining to highlight enzymes likely involved in catalyzing less well-understood micropollutant biotransformation reactions. Specifically, we use the cases of nitrile hydration and oxidative biotransformation reactions to show that the consideration of additional experimental evidence (such as information on biotransformation pathways) increases the likelihood of detecting plausible novel enzyme-chemical relationships. Finally, we identify a cluster of mono- and dioxygenase fourth-level enzyme classes that most strongly correlate with oxidative micropollutant biotransformation reactions in activated sludge.

Biotransformation is the most important process removing manmade chemicals from the environment, yet mechanisms governing this essential ecosystem function are underexplored. To understand these mechanisms, we conducted experiments in flow-through systems, by colonizing stream biofilms under different conditions of mixing river water with treated (and ultrafiltered) wastewater. We performed biotransformation experiments with those biofilms, using a set of 75 micropollutants, and could disentangle potential mechanisms determining the biotransformation potential of stream biofilms. We showed that the increased biotransformation potential downstream of wastewater treatment plants that we observed for specific micropollutants contained in household wastewaters (downstream effect) is caused by microorganisms released with the treated effluent, rather than by the in-stream exposure to those micropollutants. Complementary data from 16S rRNA amplicon-sequencing revealed 146 amplicon sequence variants (ASVs) that followed the observed biotransformation patterns. Our results align with findings for community tolerance, and provide clear experimental evidence that microorganisms released with treated wastewater integrate into downstream biofilms and impact crucial ecosystem functions., Water Research, 217, ISSN:0043-1354, ISSN:1879-2448

[Image: see text] Complex microbial communities in environmental systems play a key role in the detoxification of chemical contaminants by transforming them into less active metabolites or by complete mineralization. Biotransformation, i.e., transformation by microbes, is well understood for a number of priority pollutants, but a similar level of understanding is lacking for many emerging contaminants encountered at low concentrations and in complex mixtures across natural and engineered systems. Any advanced approaches aiming to reduce environmental exposure to such contaminants (e.g., novel engineered biological water treatment systems, design of readily degradable chemicals, or improved regulatory assessment strategies to determine contaminant persistence a priori) will depend on understanding the causal links among contaminant removal, the key driving agents of biotransformation at low concentrations (i.e., relevant microbes and their metabolic activities), and how their presence and activity depend on environmental conditions. In this Perspective, we present the current understanding and recent methodological advances that can help to identify such links, even in complex environmental microbiomes and for contaminants present at low concentrations in complex chemical mixtures. We discuss the ensuing insights into contaminant biotransformation across varying environments and conditions and ask how much closer we have come to designing improved approaches to reducing environmental exposure to contaminants.

MotivationThe ability to assess and engineer biotransformation of chemical contaminants present in the environment requires knowledge on which enzymes can catalyze specific contaminant biotransformation reactions. For the majority of over 100’000 chemicals in commerce such knowledge is not available. Enumeration of enzyme classes potentially catalyzing observed orde novopredicted contaminant biotransformation reactions can support research that aims at experimentally uncovering enzymes involved in contaminant biotransformation in complex natural microbial communities.DatabaseenviLink is a new data module integrated into the enviPath database and contains 316 theoretically derived linkages between generalized biotransformation rules used for contaminant biotransformation prediction in enviPath and 3rdlevel EC classes. Rule-EC linkages have been derived using two reaction databases, i.e., Eawag-BBD in enviPath, focused on contaminant biotransformation reactions, and KEGG. 32.6% of identified rule-EC linkages overlap between the two databases, whereas 40.2% and 27.2%, respectively, are originating from Eawag-BBD and KEGG only.Implementation and availabilityenviLink is encoded in RDF triples as part of the enviPath RDF database. enviPath is hosted on a public webserver (envipath.org) and all data is freely available for non-commercial use. enviLink can be searched online for individual transformation rules of interest (https://tinyurl.com/y63ath3k) and is also fully downloadable from the supporting materials (i.e., Jupyter notebook “enviLink” and tsv files provided through GitHub athttps://github.com/emanuel-schmid/enviLink).

The emergence and spread of antibiotic resistance is a major societal challenge and new antibiotics are needed to successfully fight bacterial infections. Because the release of antibiotics into wastewater and downstream environments is expected to contribute to the problem of antibiotic resistance, it would be beneficial to consider the environmental fate of antibiotics in the development of novel antibiotics. In this article, we discuss the possibility of designing peptide-based antibiotics that are stable during treatment (e.g. in human blood), but rapidly inactivated through hydrolysis by peptidases after their secretion into wastewater. In the first part, we review studies on the biotransformation of peptide-based antibiotics during biological wastewater treatment and on the specificity of dissolved extracellular peptidases derived from wastewater. In the second part, we present first results of our endeavour to identify peptide bonds that are stable in human blood plasma and susceptible to hydrolysis by the industrially produced peptidase Subtilisin A.

For most micropollutants (MPs) present in surface waters, such as pesticides and pharmaceuticals, the contribution of biotransformation to their overall removal from lake ecosystems is largely unknown. This study aims at empirically determining the biotransformation rate constants for 35 MPs at different periods of the year and depths of a meso-eutrophic lake. We then tested statistically the association of environmental parameters and microbial community composition with the biotransformation rate constants obtained. Biotransformation was observed for 14 out of 35 studied MPs for at least one sampling time. Large variations in biotransformation rate constants were observed over the seasons and between compounds. Overall, the transformation of MPs was mostly influenced by the lake's temperature, phytoplankton density and bacterial diversity. However, some individual MPs were not following the general trend or association with microorganism biomass. The antidepressant mianserin, for instance, was transformed in all experiments and depths, but did not show any relationship with measured environmental parameters, suggesting the importance of specific microorganisms in its transformation. The results presented here contribute to our understanding of the fate of MPs in surface waters and thus support improved risk assessment of contaminants in the environment., Water Research, 202, ISSN:0043-1354, ISSN:1879-2448

Despite their strict environmental regulations and state-of-the-art wastewater treatment infrastructure, chemical and pharmaceutical industries in Switzerland leave a clear footprint in treated wastewater that is released into the open environment.

In this work, emissions of active pharmaceutical ingredients (APIs) from formulating pharmaceutical industries (FPIs) were investigated for the first time based on detailed production information and compared to overall API emissions in wastewater treatment plant (WWTP) effluents. At two municipal WWTPs, both receiving wastewater from several FPIs, two months’ daily effluent samples were collected and measured using liquid chromatography high-resolution mass spectrometry (LC-HRMS). Thirty-three APIs formulated during the sampling period as well as >120 organic contaminants commonly present in WWTP effluents were quantified. On the basis of their time patterns and manufacturing data, industrial contributions were found for 22 of 26 APIs (85%) detected in the samples and processed by the FPIs. API emissions from FPIs led to daily concentration increases of up to 300-fold, despite pretreatment of the industrial wastewater. However, emissions from FPIs seemed to depend on the type of formulating activity, with granulation and mixing being most prone to API losses. Losses from FPIs were responsible for the highest concentrations and for up to 60% of the daily total API emissions measured. Furthermore, screening for suspects in LC-HRMS data resulted in the detection of unexpected emissions from FPIs, demonstrating the value of these data to comprehensively assess industrial API losses. Overall, this study showed that FPIs were relevant contributors of APIs emitted in the WWTP effluents, although only a minor fraction (

Micropollutants are ubiquitously found in natural surface waters and pose a potential risk to aquatic organisms. Stream biofilms, consisting of bacteria, algae and other microorganisms potentially contribute to bioremediating aquatic environments by biotransforming xenobiotic substances. When investigating the potential of stream biofilms to remove micropollutants from the water column, it is important to distinguish between different fate processes, such as biotransformation, passive sorption and active bioaccumulation. However, due to the complex nature of the biofilm community and its extracellular matrix, this task is often difficult. In this study, we combined biotransformation experiments involving natural stream biofilms collected up- and downstream of wastewater treatment plant outfalls with the QuEChERS extraction method to distinguish between the different fate processes. The QuEChERS extraction proved to be a suitable method for a broad range of micropollutants (> 80% of the investigated compounds). We found that 31 out of 63 compounds were biotransformed by the biofilms, with the majority being substitution-type biotransformations, and that downstream biofilms have an increased biotransformation potential towards specific wastewater-relevant micropollutants. Overall, using the experimental and analytical strategy developed, stream biofilms were demonstrated to have a broad inherent micropollutant biotransformation potential, and to thus contribute to bioremediation and improving ecosystem health.

Citalopram (CTR) is a worldwide highly consumed antidepressant which has demonstrated incomplete removal by conventional wastewater treatment. Despite its global ubiquitous presence in different environmental compartments, little is known about its behaviour and transformation processes during wastewater treatment. The present study aims to expand the knowledge on fate and transformation of CTR during the biological treatment process. For this purpose, batch reactors were set up to assess biotic, abiotic and sorption losses of this compound. One of the main objectives of the study was the identification of the formed transformation products (TPs) by applying suspect and non-target strategies based on liquid chromatography quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS). The complementary use of reversed phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) for the identification of polar TPs, and the application of in-house developed quantitative structure-retention relationship (QSRR) prediction models, in addition to the comprehensive evaluation of the obtained MS/MS spectra, provided valuable information to support identification. In total, fourteen TPs were detected and thirteen of them were tentatively identified. Four compounds were confirmed (N-desmethylCTR, CTR amide, CTR carboxylic acid and 3-oxo-CTR) through the purchase of the corresponding reference standard. Probable structures based on diagnostic evidence were proposed for the additional nine TPs. Eleven TPs are reported for the first time. A transformation pathway for the biotransformation of CTR was proposed. The presence of the identified TPs was assessed in real wastewater samples through retrospective analysis, resulting in the detection of five compounds. Finally, the potential ecotoxicological risk posed by CTR and its TPs to different trophic levels of aquatic organisms was evaluated by means of risk quotients.

The biotransformation of some micropollutants has previously been observed to be positively associated with ammonia oxidation activities and the transcript abundance of the archaeal ammonia monooxygenase gene (amoA) in nitrifying activated sludge. Given the increasing interest in and potential importance of ammonia-oxidizing archaea (AOA), we investigated the capabilities of an AOA pure culture, Nitrososphaera gargensis, to biotransform ten micropollutants belonging to three structurally similar groups (i.e., phenylureas, tertiary amides, and tertiary amines). N. gargensis was able to biotransform two of the tertiary amines, mianserin (MIA) and ranitidine (RAN), exhibiting similar compound specificity as two ammonia-oxidizing bacteria (AOB) strains that were tested for comparison. The same MIA and RAN biotransformation reactions were carried out by both the AOA and AOB strains. The major transformation product (TP) of MIA, α-oxo MIA was likely formed via a two-step oxidation reaction. The first hydroxylation step is typically catalyzed by monooxygenases. Three RAN TP candidates were identified from nontarget analysis. Their tentative structures and possible biotransformation pathways were proposed. The biotransformation of MIA and RAN only occurred when ammonia oxidation was active, suggesting cometabolic transformations. Consistently, a comparative proteomic analysis revealed no significant differential expression of any protein-encoding gene in N. gargensis grown on ammonium with MIA or RAN compared with standard cultivation on ammonium only. Taken together, this study provides first important insights regarding the roles played by AOA in micropollutant biotransformation.

Active pharmaceutical ingredients (APIs) have raised considerable concern over the past decade due to their widespread detection in water resources and their potential to affect ecosystem health. This triggered many attempts to prioritize the large number of known APIs to target monitoring efforts and testing of fate and effects. However, so far, a comprehensive approach to screen for their presence in surface waters has been missing. Here, we explore a combination of an automated suspect screening approach based on liquid chromatography coupled to high-resolution mass spectrometry and a model-based prioritization using consumption data, readily predictable fate properties and a generic mass balance model for activated sludge treatment to comprehensively detect APIs with relevant exposure in wastewater treatment plant effluents. The procedure afforded the detection of 27 APIs that had not been covered in our previous target method, which included 119 parent APIs. The newly detected APIs included seven compounds with a high potential for bioaccumulation and persistence, and also three compounds that were suspected to stem from point sources rather than from consumption as medicines. Analytical suspect screening proved to be more selective than model-based prioritization, making it the method of choice for focusing analytical method development or fate and effect testing on those APIs most relevant to the aquatic environment. However, we found that state-of-the-practice exposure modeling used to predict potential high-exposure substances can be a useful complement to point toward oversights and known or suspected detection gaps in the analytical method, most of which were related to insufficient ionization.

The main removal process for polar organic micropollutants during activated sludge treatment is biotransformation, which often leads to the formation of stable transformation products (TPs). Because the analysis of TPs is challenging, the use of pathway prediction systems can help by generating a list of suspected TPs. To complete and refine pathway prediction, comprehensive biotransformation studies for compounds exhibiting pertinent functional groups under environmentally relevant conditions are needed. Because many polar organic micropollutants present in wastewater contain one or several amine functional groups, we systematically explored amine biotransformation by conducting experiments with 19 compounds that contained 25 structurally diverse primary, secondary, and tertiary amine moieties. The identification of 144 TP candidates and the structure elucidation of 101 of these resulted in a comprehensive view on initial amine biotransformation reactions. The reactions with the highest relevance were N-oxidation, N-dealkylation, N-acetylation, and N-succinylation. Whereas many of the observed reactions were similar to those known for the mammalian metabolism of amine-containing xenobiotics, some N-acylation reactions were not previously described. In general, different reactions at the amine functional group occurred in parallel. Finally, recommendations on how these findings can be implemented to improve microbial pathway prediction of amine-containing micropollutants are given.

Wastewater treatment plant (WWTP) effluents release not only chemical constituents in watersheds, but also contain microorganisms. Thus, an understanding of what microorganisms are released and how they change microbial communities within natural streams is needed. To characterize the community shifts in streams receiving WWTP effluent, we sampled water-column microorganisms from upstream, downstream, and the effluent of WWTPs located on 23 headwater streams in which no other effluent was released upstream. We characterized the bacterial community by sequencing the V3-V4 region of the 16S rRNA gene. We hypothesized that the downstream community profile would be a hydraulic mixture between the two sources (i.e., upstream and effluent). In ordination analyses, the downstream bacterial community profile was a mixture between the upstream and effluent. For 14 of the sites, the main contribution (>50%) to the downstream community originated from bacteria in the WWTP effluent and significant shifts in relative abundance of specific sequence variants were detected. These shifts in sequence variants may serve as general bioindicators of wastewater-effluent influenced streams, with a human-gut related Ruminococcus genus displaying the highest shift (30-fold higher abundances downstream). However, not all taxa composition changes were predicted based on hydraulic mixing alone. Specifically, the decrease of Cyanobacteria/Chloroplast reads was not adequately described by hydraulic mixing. The potential alteration of stream microbial communities via a high inflow of human-gut related bacteria and a decrease in autotrophic functional groups resulting from WWTP effluent creates the potential for general shifts in stream ecosystem function.

Aerobic biodegradation half-lives (half-lives) are key parameters used to evaluate pesticide persistence in soil. However, half-life estimates for individual pesticides often span several orders of magnitude, reflecting the impact that various environmental or experimental parameters have on half-lives in soil. In this work, we collected literature-reported half-lives for eleven pesticides along with associated metadata describing the environmental or experimental conditions under which they were derived. We then developed a multivariable framework to discover relationships between the half-lives and associated metadata. We first compared data for the herbicide atrazine collected from 95 laboratory and 65 field studies. We discovered that atrazine application history and soil texture were the parameters that have the largest influence on the observed half-lives in both types of studies. We then extended the analysis to include ten additional pesticides with data collected exclusively from laboratory studies. We found that, when data were available, pesticide application history and biomass concentrations were always positively associated with half-lives. The relevance of other parameters varied among the pesticides, but in some cases the variability could be explained by the physicochemical properties of the pesticides. For example, we found that the relative significance of the organic carbon content of soil for determining half-lives depends on the relative solubility of the pesticide. Altogether, our analyses highlight the reciprocal influence of both environmental parameters and intrinsic physicochemical properties for determining half-lives in soil.

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.

A remaining challenge within microbial ecology is to understand the determinants of richness and diversity observed in environmental microbial communities. In a range of systems, including activated sludge bioreactors, the microbial residence time (MRT) has been previously shown to shape the microbial community composition. However, the physiological and ecological mechanisms driving this influence have remained unclear. Here, this relationship is explored by analyzing an activated sludge system fed with municipal wastewater. Using a model designed in this study based on Monod-growth kinetics, longer MRTs were shown to increase the range of growth parameters that enable persistence, resulting in increased richness and diversity in the modeled community. In laboratory experiments, six sequencing batch reactors treating domestic wastewater were operated in parallel at MRTs between 1 and 15 days. The communities were characterized using both 16S ribosomal RNA and non-target messenger RNA sequencing (metatranscriptomic analysis), and model-predicted monotonic increases in richness were confirmed in both profiles. Accordingly, taxonomic Shannon diversity also increased with MRT. In contrast, the diversity in enzyme class annotations resulting from the metatranscriptomic analysis displayed a non-monotonic trend over the MRT gradient. Disproportionately high abundances of transcripts encoding for rarer enzymes occur at longer MRTs and lead to the disconnect between taxonomic and functional diversity profiles.

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.

To optimize removal of organic micropollutants from the water cycle, understanding the processes during activated sludge treatment is essential. In this study, we hypothesize that aliphatic amines, which are highly abundant among organic micropollutants, are partly removed from the water phase in activated sludge through ion trapping in protozoa. In ion trapping, which has been extensively investigated in medical research, the neutral species of amine-containing compounds diffuse through the cell membrane and further into acidic vesicles present in eukaryotic cells such as protozoa. There they become trapped because diffusion of the positively charged species formed in the acidic vesicles is strongly hindered. We tested our hypothesis with two experiments. First, we studied the distribution of the fluorescent amine acridine orange in activated sludge by confocal fluorescence imaging. We observed intense fluorescence in distinct compartments of the protozoa, but not in the bacterial biomass. Second, we investigated the distribution of 12 amine-containing and eight control micropollutants in both regular activated sludge and sludge where the protozoa had been inactivated. In contrast to most control compounds, the amine-containing micropollutants displayed a distinctly different behavior in the noninhibited sludge compared to the inhibited one: (i) more removal from the liquid phase; (ii) deviation from first-order kinetics for the removal from the liquid phase; and (iii) higher amounts in the solid phase. These results provide strong evidence that ion trapping in protozoa occurs and that it is an important removal mechanism for amine-containing micropollutants in batch experiments with activated sludge that has so far gone unnoticed. We expect that our findings will trigger further investigations on the importance of this process in full-scale wastewater treatment systems, including its relevance for accumulation of ammonium.