Understanding the Dependence of Micropollutant Biotransformation Rates on Short-Term Temperature Shifts

Impact of long-term temperature shifts on activated sludge microbiome dynamics and micropollutant removal

Micropollutants removal efficiency strongly vary across different aerobic wastewater treatment plants, resulting in their frequent detection in surface and ground waters. Seasonal temperature variation is a major factor influencing plant performance, but it is still unclear how prolonged periods of temperature change impact microbiome and micropollutant biotransformation. This work investigates the effect of long-term temperature variation on the microbial dynamics in an activated sludge system, and the impact on micropollutant biotransformation. Sequencing batch reactors were used as model system and 4-40 °C temperature range was studied. 16S rRNA amplicon sequencing showed that temperature drives microbial structure (gDNA) and activity (RNA), rather than time, and this was stronger below 15 °C and above 25 °C. The microbial community was richest and more diverse at 20 °C, while rarer and more specific taxa became predominant over time, at more extreme temperatures. This suggested that less abundant taxa might be responsible for maintaining the biotransformation capability in the activated sludge at extreme temperatures. Micropollutant biotransformation rates mostly deviated from the classic Arrhenius model below 15 °C and above 25 °C, indicating that prolonged exposure to temperature changes leads to temperature-induced taxonomic shifts, resulting in the emerging of different sets of biotransformation pathways over different temperature ranges.

Influence of Season on Biodegradation Rates in Rivers

Biodegradation plays a key role in the fate of chemicals in the environment. The variability of biodegradation in time can cause uncertainty in evaluating the environmental persistence and risk of chemicals. However, the seasonality of biodegradation in rivers has not yet been the subject of environmentally relevant testing and systematic investigation for large numbers of chemicals. In this work, we studied the biodegradation of 96 compounds during four seasons at four locations (up- and downstream of WWTPs located on two Swedish rivers). Significant seasonality (ANOVA, p < 0.05) of the first-order rate constant for primary biodegradation was observed for most compounds. Variations in pH and total bacterial cell count were not the major factors explaining the seasonality of biodegradation. Deviation from the classical Arrhenius-type behavior was observed for most of the studied compounds, which calls into question the application of this relationship to correct biodegradation rate constants for differences in environmental temperature. Similarities in magnitude and seasonality of biodegradation rate constants were observed for some groups of chemicals possessing the same functional groups. Moreover, reduced seasonality of biodegradation was observed downstream of WWTPs, while biodegradation rates of most compounds were not significantly different between up- and downstream.

Modeling Free Nitrous Acid Inhibition on the Removal of Nitrogen and Atenolol during Sidestream Partial Nitritation Processes

Sidestream serves as an important reservoir collecting pharmaceuticals from sludge. However, the knowledge on sidestream pharmaceutical removal is still insufficient. In this work, atenolol biodegradation during sidestream partial nitritation (PN) processes characterized by high free nitrous acid (FNA) accumulation was modeled. To describe the FNA inhibition on ammonia oxidation and atenolol removal, Vadivelu-type and Hellinga-type inhibition kinetics were introduced into the model framework. Four inhibitory parameters along with four biodegradation kinetic parameters were calibrated and validated separately with eight sets of batch experimental data and 60 days' PN reactor operational data. The developed model could accurately reproduce the dynamics of nitrogen and atenolol. The model prediction further revealed that atenolol biodegradation efficiencies by ammonia-oxidizing bacteria (AOB)-induced cometabolism, AOB-induced metabolism, and heterotrophic bacteria-induced biodegradation were 0, ∼ 60, and ∼35% in the absence of ammonium and FNA; ∼ 14, ∼ 29, and ∼28% at 0.03 mg-N L-1 FNA; and 7, 15, and 5% at 0.19 mg-N L-1 FNA. Model simulation showed that the nitritation efficiency of ∼99% and atenolol removal efficiency of 57.5% in the PN process could be achieved simultaneously by controlling pH at 8.5, while 89.2% total nitrogen and 57.1% atenolol were removed to the maximum at pH of 7.0 in PN coupling with the anammox process. The pH-based operational strategy to regulate FNA levels was mathematically demonstrated to be effective for achieving the simultaneous removal of nitrogen and atenolol in PN-based sidestream processes.

Toxicokinetic-Toxicodynamic Model to Assess Thermal Stress

Temperature is a crucial environmental factor affecting the distribution and performance of ectothermic organisms. This study introduces a new temperature damage model to interpret their thermal stress. Inspired by the ecotoxicological damage model in the General Unified Threshold model for Survival (GUTS) framework, the temperature damage model assumes that damage depends on the balance between temperature-dependent accumulation and constant repair. Mortality due to temperature stress is driven by the damage level exceeding a threshold. Model calibration showed a good agreement with the measured survival of Gammarus pulex exposed to different constant temperatures. Further, model simulations, including constant temperatures, daily temperature fluctuations, and heatwaves, demonstrated the model's ability to predict temperature effects for various environmental scenarios. With this, the present study contributes to the mechanistic understanding of temperature as a single stressor while facilitating the incorporation of temperature as an additional stressor alongside chemicals in mechanistic multistressor effect models.

Predicting micropollutant fate during wastewater treatment using refined classical kinetic model based on quantitative monitoring in multi-metropolitan regions of South Korea

This study aimed to implement an extensive prediction model for the fate of micropollutants (MPs) in wastewater treatment plants (WWTPs). Five WWTPs equipped with seven different biological treatment processes were monitored from 2020 to 2022 with three to four sampling events in each year, and 27 datasets for 20 MPs were collected. Among these datasets, 12 were used to investigate the behavior and fate of MPs in WWTPs in South Korea. Metformin, acetaminophen, caffeine, naproxen, and ibuprofen were the MPs with the highest influent concentrations (ranging from 3,933.3-187,637.0 ng L-1) at all WWTPs. More than 90% of MPs were removed by biological treatment processes in all WWTPs. The Kruskal-Wallis test verified that their efficacy did not differ statistically (p-value > 0.05). Meanwhile, to refine the performance of the prediction model, this study optimized the biodegradation rate constants (kbio) of each MP according to the variation of seasonal water temperature. As a result, compared to the original prediction model, the mean difference between the actual data and predicted results (MEAN) decreased by 6.77%, while the Nash-Sutcliffe efficiency (NSE) increased by 0.226. The final MEAN and NSE for the refined prediction model were calculated to be 5.09% and 0.964, respectively. The prediction model made accurate predictions, even for MPs exhibiting behaviors different from other cases, such as estriol and atrazine. Consequently, the optimization strategy proposed in this study was determined to be effective because the overall removal efficiencies of MPs were successfully predicted even with limited reference datasets.

Benchmarking the Persistence of Active Pharmaceutical Ingredients in River Systems

Assessing the persistence of organic micropollutants from field data has been notoriously laborious, requiring extensive data including emissions and chemical properties, and the application of detailed mass-balance models, which often contain parameters that are impossible to measure. To overcome some of these obstacles, we developed the concept of persistence benchmarking for large rivers that receive numerous emissions and provide enough residence time to observe the dissipation of compounds. We estimated the dissipation rate constants of 41 compounds (mostly active pharmaceutical ingredients) from five measurement campaigns in the Rhine and Danube rivers using concentration rate profiles with respect to carbamazepine. Dissipation rates clearly distinguished between known fast- and slow-degrading compounds, and campaign-specific boundary conditions had an influence on a minor subset of compounds only. Benchmarking provided reasonable estimates on summer total system half-lives in the Rhine compared to previous laboratory experiments and a mass-balance modeling study. Consequently, benchmarking can be a straightforward persistence assessment method of continuously emitted organic micropollutants in large river systems, especially when it is supported by field monitoring campaigns of proper analytical quality and spatial resolution.

Do biotransformation data from laboratory experiments reflect micropollutant degradation in a large river basin?

Identifying a chemical's potential for biotransformation in the aquatic environment is crucial to predict its fate and manage its potential hazards. Due to the complexity of natural water bodies, especially river networks, biotransformation is often studied in laboratory experiments, assuming that study outcomes can be extrapolated to compound behavior in the field. Here, we investigated to what extent outcomes of laboratory simulation studies indeed reflect biotransformation kinetics observed in riverine systems. To determine in-field biotransformation, we measured loads of 27 wastewater treatment plant effluent-borne compounds along the Rhine and its major tributaries during two seasons. Up to 21 compounds were detected at each sampling location. Measured compound loads were used in an inverse model framework of the Rhine river basin to derive k'_bio,field values - a compound-specific parameter describing the compounds' average biotransformation potential during the field studies. To support model calibration, we performed phototransformation and sorption experiments with all the study compounds, identifying 5 compounds that are susceptible towards direct phototransformation and determining K_oc values covering four orders of magnitude. On the laboratory side, we used a similar inverse model framework to derive k'_bio,lab values from water-sediment experiments run according to a modified OECD 308-type protocol. The comparison of k'_bio,lab and k'_bio,field revealed that their absolute values differed, pointing towards faster transformation in the Rhine river basin. Yet, we could demonstrate that relative rankings of biotransformation potential and groups of compounds with low, moderate and high persistence agree reasonably well between laboratory and field outcomes. Overall, our results provide evidence that laboratory-based biotransformation studies using the modified OECD 308 protocol and k'_bio values derived thereof bear considerable potential to reflect biotransformation of micropollutants in one of the largest European river basins.

Speed it up: How temperature drives toxicokinetics of organic contaminants in freshwater amphipods

The acceleration of global climate change draws increasing attention towards interactive effects of temperature and organic contaminants. Many studies reported a higher sensitivity of aquatic invertebrates towards contaminant exposure with increasing or fluctuating temperatures. The hypothesis of this study was that the higher sensitivity of invertebrates is associated with the changes of toxicokinetic processes that determine internal concentrations of contaminants and consequently toxic effects. Therefore, the influence of temperature on toxicokinetic processes and the underlying mechanisms were studied in two key amphipod species (Gammarus pulex and Hyalella azteca). Bioconcentration experiments were carried out at four different temperatures with a mixture of 12 exposure relevant polar organic contaminants. Tissue and medium samples were taken in regular intervals and analysed by online solid-phase extraction liquid chromatography high-resolution tandem mass spectrometry. Subsequently, toxicokinetic rates were modelled and analysed in dependence of the exposure temperature using the Arrhenius equation. An exponential relationship between toxicokinetic rates versus temperature was observed and could be well depicted by applying the Arrhenius equation. Due to a similar Arrhenius temperature of uptake and elimination rates, the bioconcentration factors of the contaminants were generally constant across the temperature range. Furthermore, the Arrhenius temperature of the toxicokinetic rates and respiration was mostly similar. However, in some cases (citalopram, cyprodinil), the bioconcentration factor appeared to be temperature dependent, which could potentially be explained by the influence of temperature on active uptake mechanisms or biotransformation. The observed temperature effects on toxicokinetics may be particularly relevant in non-equilibrated systems, such as exposure peaks in summer as exemplified by the exposure modelling of a field measured pesticide peak where the internal concentrations increased by up to fourfold along the temperature gradient. The results provide novel insights into the mechanisms of chemical uptake, biotransformation and elimination in different climate scenarios and can improve environmental risk assessment.

Mechanism of β-blocker biodegradation by wastewater microorganisms

The recalcitrant β-blockers have been widely detected in aquatic environments up to several hundred μg/L, which are major contributors to β1 antagonistic activities in wastewater. Their biodegradation mechanisms remain obscure, hindering the development of efficient removal techniques. This study constructed the biodegradation pathways for three typical β-blockers, namely atenolol, metoprolol, and propranolol, assessed the toxicity of their major biotransformation products, and identified the key enzyme catalyzing the O-dealkylation reaction leading to pollutant mineralization. Atenolol and metoprolol degradation was more efficient than that of propranolol by activated sludge, producing metoprolol acid (MTPA) as a major intermediate. Hydrogenophaga sp. YM1 isolated from activated sludge possess the α-ketoglutarate dependent dioxygenase (TfdA) responsible for O-dealkylation of MTPA and propranolol, producing 4-hydroxyphenylacetic acid (4-HPA) that can be further degraded and ultimately enters the TCA cycle. The role of TfdA was verified by proteomics, enzyme stimulation/inhibition tests, and gene knockout experiments. Molecular docking suggests its different interactions with MTPA and propranolol. Acetate facilitated the degradation of β-blockers efficiently. The results may shed light on enhanced biological removals of broader β-blockers and their transformation products in the environment.

Evaluation of temperature corrections for pesticide half-lives in tropical and temperate soils

Temperature is a key factor that influences pesticide degradation. Extrapolating degradation half-lives (DT50) measured at a given temperature to different temperatures remains challenging, especially for tropical conditions with high temperatures. In this study, the use of the standard Arrhenius equation for correcting temperature effects on pesticide degradation in soils was evaluated and its performance was compared with that of alternative Arrhenius-based equations. To do so, a database of 509 DT50 values measured between 5 and 35 °C for 32 pesticides on tropical and temperate soils was compiled for the first time through an extensive literature search. The temperature correction models were fitted to the database using linear mixed regression approaches that included soil type and compound effects. No difference in the temperature dependence of DT50 between tropical and temperate soils was detected, regardless of the model. A comparison of the prediction performances of the models showed that constant activation energy (E_a) cannot be considered valid for the whole range of temperatures. The classical Arrhenius equation with an E_a of 65.4 kJ.mol^-1, as recommended by the European Food Safety Authority (EFSA), was shown to be valid for correcting the DT50 only for temperatures ranging from 5 to 20 °C. However, for temperatures greater than 20 °C, which are common in tropical environments, the median E_a was significantly lower at 10.3 kJ.mol^-1. These findings suggest the need to adapt the standard temperature correction of the European pesticide risk assessment temperature procedure when it is applied in tropical settings.

Modelling and prediction of the effect of operational parameters on the fate of contaminants of emerging concern in WWTPs

Wastewater treatment plants (WWTPs) provide a barrier against the discharge of contaminants of emerging concern (CECs) into the environment. The removal of CECs is highly WWTP-specific and the underlying mechanisms are still poorly understood, hampering the optimization of biological treatment steps for their removal. To fill this knowledge gap, we assessed the influence of four operational parameters of activated sludge biological treatment, namely total suspended solids, temperature, pH and redox conditions, on the sorption and biodegradation of four CECs under controlled laboratory conditions. Design of Experiments was used to better address the factors influencing CECs removal and interactions among operational parameters. The derived statistical models showed results in concordance with previous studies and indicated how sorption and biodegradation of the investigated CECs depend on most tested parameters and few of their interactions. The predictions of the developed models have been compared with literature values, indicating how the tested parameters are responsible for most of the variability of sorption, while they could not reliably generalize biodegradation rates. The developed models were also implemented as an extension of a mechanistic biological treatment model, successfully describing the dynamic behaviour of a large-scale WWTP, which was observed during a three-day continuous monitoring campaign. Compared to a traditional modelling approach, the one including the developed models showed on average almost a three-fold uncertainty reduction, favouring its use to aid WWTP managers and regulators for improved assessment of CEC fate and removal. Finally, the models highlighted that, while higher temperatures and solids concentrations generically favoured CECs removal, removal efficiency vary significantly due to operational parameters and no globally optimum conditions for CECs removal exist. The use of these models opens the door to the combined dynamic management of both traditional contaminants and CECs in WWTPs.

Scientific concepts and methods for moving persistence assessments into the 21st century

The evaluation of a chemical substance's persistence is key to understanding its environmental fate, exposure concentration, and, ultimately, environmental risk. Traditional biodegradation test methods were developed many years ago for soluble, nonvolatile, single-constituent test substances, which do not represent the wide range of manufactured chemical substances. In addition, the Organisation for Economic Co-operation and Development (OECD) screening and simulation test methods do not fully reflect the environmental conditions into which substances are released and, therefore, estimates of chemical degradation half-lives can be very uncertain and may misrepresent real environmental processes. In this paper, we address the challenges and limitations facing current test methods and the scientific advances that are helping to both understand and provide solutions to them. Some of these advancements include the following: (1) robust methods that provide a deeper understanding of microbial composition, diversity, and abundance to ensure consistency and/or interpret variability between tests; (2) benchmarking tools and reference substances that aid in persistence evaluations through comparison against substances with well-quantified degradation profiles; (3) analytical methods that allow quantification for parent and metabolites at environmentally relevant concentrations, and inform on test substance bioavailability, biochemical pathways, rates of primary versus overall degradation, and rates of metabolite formation and decay; (4) modeling tools that predict the likelihood of microbial biotransformation, as well as biochemical pathways; and (5) modeling approaches that allow for derivation of more generally applicable biotransformation rate constants, by accounting for physical and/or chemical processes and test system design when evaluating test data. We also identify that, while such advancements could improve the certainty and accuracy of persistence assessments, the mechanisms and processes by which they are translated into regulatory practice and development of new OECD test guidelines need improving and accelerating. Where uncertainty remains, holistic weight of evidence approaches may be required to accurately assess the persistence of chemicals. Integr Environ Assess Manag 2022;18:1454-1487. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

The role of the sewer system in estimating urban emissions of chemicals of emerging concern

The use of chemicals by society has resulted in calls for more effective control of their emissions. Many of these chemicals are poorly characterized because of lacking data on their use, environmental fate and toxicity, as well as lacking detection techniques. These compounds are sometimes referred to as contaminants of emerging concern (CECs). Urban areas are an important source of CECs, where these are typically first collected in sewer systems and then discharged into the environment after being treated in a wastewater treatment plant. A combination of emission estimation techniques and environmental fate models can support the early identification and management of CEC-related environmental problems. However, scientific insight in the processes driving the fate of CECs in sewer systems is limited and scattered. Biotransformation, sorption and ion-trapping can decrease CEC loads, whereas enzymatic deconjugation of conjugated metabolites can increase CEC loads as metabolites are back-transformed into their parent respective compounds. These fate processes need to be considered when estimating CEC emissions. This literature review collates the fragmented knowledge and data on in-sewer fate of CECs to develop practical guidelines for water managers on how to deal with in-sewer fate of CECs and highlights future research needs. It was assessed to what extent empirical data is in-line with text-book knowledge and integrated sewer modelling approaches. Experimental half-lives (n = 277) of 96 organic CECs were collected from literature. The findings of this literature review can be used to support environmental modelling efforts and to optimize monitoring campaigns, including field studies in the context of wastewater-based epidemiology.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11157-022-09638-9.

Enabling forecasts of environmental exposure to chemicals in European agriculture under global change

European agricultural development in the 21st century will be affected by a host of global changes, including climate change, changes in agricultural technologies and practices, and a shift towards a circular economy. The type and quantity of chemicals used, emitted, and cycled through agricultural systems in Europe will change, driven by shifts in the use patterns of pesticides, veterinary pharmaceuticals, reclaimed wastewater used for irrigation, and biosolids. Climate change will also impact the chemical persistence, fate, and transport processes that dictate environmental exposure. Here, we review the literature to identify research that will enable scenario-based forecasting of environmental exposures to organic chemicals in European agriculture under global change. Enabling exposure forecasts requires understanding current and possible future 1.) emissions, 2.) persistence and transformation, and 3.) fate and transport of agricultural chemicals. We discuss current knowledge in these three areas, the impact global change drivers may have on them, and we identify knowledge and data gaps that must be overcome to enable predictive scenario-based forecasts of environmental exposure under global change. Key research gaps identified are: improved understanding of relationships between global change and chemical emissions in agricultural settings; better understanding of environment-microbe interactions in the context of chemical degradation under future conditions; and better methods for downscaling climate change-driven intense precipitation events for chemical fate and transport modelling. We introduce a set of narrative Agricultural Chemical Exposure (ACE) scenarios - augmenting the IPCC's Shared Socio-economic Pathways (SSPs) - as a framework for forecasting chemical exposure in European agriculture. The proposed ACE scenarios cover a plausible range of optimistic to pessimistic 21st century development pathways. Filling the knowledge and data gaps identified within this study and using the ACE scenario approach for chemical exposure forecasting will support stakeholder planning and regulatory intervention strategies to ensure European agricultural practices develop in a sustainable manner.

Free Nitrous Acid Inhibits Atenolol Removal during the Sidestream Partial Nitritation Process through Regulating Microbial-Induced Metabolic Types

Limited studies have attempted to evaluate pharmaceutical removal during the sidestream partial nitritation (PN) process. In this work, atenolol biodegradation by PN cultures was investigated by maintaining ammonium and pH at different levels. For the first time, free nitrous acid (FNA), other than ammonium, pH, and free ammonia, was demonstrated to inhibit atenolol removal, with biodegradation efficiencies of ∼98, ∼67, and ∼28% within 6 days at average FNA levels of 0, 0.03, and 0.19 mg-N L^-1, respectively. Ammonia-oxidizing bacteria (AOB)-induced metabolism was predominant despite varying FNA concentrations. In the absence of ammonium/FNA, atenolol was mostly biodegraded via AOB-induced metabolism (65%) and heterotroph-induced metabolism (33%). AOB-induced metabolism was largely inhibited (down to 29%) at 0.03 mg-N L^-1 FNA, while ∼27 and ∼11% were degraded via heterotroph-induced metabolism and AOB-induced cometabolism, respectively. Higher FNA (0.19 mg-N L^-1) substantially reduced atenolol biodegradation via heterotroph-induced metabolism (4%), AOB-induced metabolism (16%), and AOB-induced cometabolism (8%). Newly identified products and pathways were related to metabolic types and FNA levels: (i) deamination and decarbonylation (AOB-induced cometabolism, 0.03 mg-N L^-1 FNA); (ii) deamination from atenolol acid (heterotrophic biodegradation); and (iii) nitro-substitution (reaction with nitrite). This suggests limiting FNA to realize simultaneous nitrogen and pharmaceutical removal during the sidestream process.

Temperature, phytoplankton density and bacteria diversity drive the biotransformation of micropollutants in a lake ecosystem

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.

Methodological Advances to Study Contaminant Biotransformation: New Prospects for Understanding and Reducing Environmental Persistence?

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.

Separation of Photochemical and Non-Photochemical Diurnal In-Stream Attenuation of Micropollutants

For a better process understanding of in-stream attenuation of trace organic contaminants (TrOCs), quantitative comparisons between field studies under different environmental conditions and controlled laboratory experiments are important to separate different processes. However, this is hampered by the challenge to transfer kinetics from the laboratory to different field conditions due to the lack of good quantitative measures to account for different boundary conditions. For phototransformation, in situ light conditions in a river are difficult to determine because light is reduced, for instance, by absorption, scattering on suspended particles, and shading effects. In this study, we present an approach to separate photochemical from non-photochemical diurnal in-stream attenuation based on rate constants relative to diclofenac, as a reference compound, to account for the difference in the in situ light conditions combined with laboratory experiments. 12 out of 45 detected target TrOCs showed a diurnal attenuation at a selected river stretch. A non-photochemical process, potentially biotransformation, was responsible for the diurnal attenuation of bisoprolol, metoprolol, O-desmethylvenlafaxine, tramadol, and venlafaxine. Attenuation of amisulpride, flufenamic acid, hydrochlorothiazide, naproxen, and xipamide can be quantitatively explained by phototransformation, partially for sotalol. Attenuation rate constants of hydrochlorothiazide at different field sites from this study and from published data range over 2 orders of magnitude. Differences can be quantitatively explained by different light exposures but not by water chemical parameters.