Non-target trend analysis for the identification of transformation products during ozonation experiments of citalopram and four of its biodegradation products

Robust polymer hybrid and assembly materials from structure tailoring to efficient catalytic remediation of emerging pollutants

A massive amount of toxic substances and harmful chemicals are released every day into the outer environment, imposing serious environmental impacts on both land and aquatic animals. To date, research is constantly in progress to determine the best catalytic material for the effective remediation of these harmful pollutants. Hybrid nanomaterials prepared by combining functional polymers with inorganic nanostructures got attention as a promising area of research owing to their remarkable multifunctional properties deriving from their entire nanocomposite structure. The versatility of the existing nanomaterials' design in polymer-inorganic hybrids, with respect to their structure, composition, and architecture, opens new prospects for catalytic applications in environmental remediation. This review article provides comprehensive detail on catalytic polymer nanocomposites and highlights how they might act as a catalyst in the remediation of toxic pollutants. Additionally, it provides a detailed clarification of the processing of design and synthetic ways for manufacturing polymer nanocomposites and explores further into the concepts of precise design methodologies. Polymer nanocomposites are used for treating pollutants (electrocatalytic, biocatalytic, catalytic, and redox degradation). The three catalytic techniques that are frequently used are thoroughly illustrated. Furthermore, significant improvements in the method through which the aforementioned catalytic process and pollutants are extensively discussed. The final section summarizes challenges in research and the potential of catalytic polymer nanocomposites for environmental remediation.

Transformation mechanisms of the antidepressant citalopram in a moving bed biofilm reactor: Substrate-depended pathways, eco-toxicities and enantiomeric profiles

Citalopram (CIT) is one of the most consumed antidepressants and frequently detected in aquatic environments worldwide. Conventional wastewater treatment cannot remove this neuronal active pharmaceutical efficiently. Past studies showed that moving bed biofilm reactors (MBBRs) can degrade CIT but the exact transformation pathways and toxicity reduction remained unclear. In this study, the effects of substrate stimulation on CIT transformation in an MBBR were systematically investigated. The results showed that a co-metabolic stimulation by acetate increased the transformation rate by 54 % and 24 % at high (300 μg/L) and environmental concentration (1.8 μg/L) of CIT, respectively. Conversely, the complex substrates in raw wastewater reduced the reaction rates by 44 %, suggesting a competitive inhibition on the enzymatic sites. The substrate stimulation changed the enantiomeric fraction (EF) of CIT from racemic (EF=0.5) to 0.60 at the high CIT concentrations, while those at lower concentrations resulted in an EF of 0.33, indicating that probably different enantioselective enzymes degraded CIT at high concentrations than at low concentrations, i.e., the presence of 300 µg/L CIT was possibly sufficient to induce the synthesis of different enantioselective enzymes, than those originally present. Through non-target and target analysis, in total 19 transformation products (TPs) including 7 TPs that were hitherto not mentioned in the literature were identified. Among these were quaternary amines, alkenes and conjugate TPs. The major transformation pathways were a) nitrile hydrolysis (up to 43 %), b) amide hydrolysis, and c) N-oxidation. Dosing acetate up-regulated significantly the amide hydrolysis, N-oxidation and conjugation pathways but inhibited the N-demethylation and α-carbon hydroxylation pathways. The in-silico toxicity assessment of CIT and its TPs suggested the overall eco-toxic potential of TPs was reduced by MBBR. Furthermore, the degradation under carbon-limited (famine) conditions favored the formation of the more toxic carboxamide, N-desmethyl and alkene TPs, while carbon-rich conditions, promoted the production of the less toxic carboxylic acid, N-oxide and ester TPs. Therefore, this study demonstrated that a) the co-metabolic stimulation of CIT metabolization by dosing a simple carbon source or b) inhibition of CIT metabolization by complex substrates; c) substrate stimulation made a difference on CIT transformation rates, enantiomeric profiles, pathways and toxic potentials. Overall, a simple-carbon co-metabolic stimulated MBBR was an efficient up-regulation strategy to minimize hazardous CIT and CIT-TPs as much as possible.

Guidance document on the impact of water treatment processes on residues of active substances or their metabolites in water abstracted for the production of drinking water

This guidance document provides a tiered framework for risk assessors and facilitates risk managers in making decisions concerning the approval of active substances (AS) that are chemicals in plant protection products (PPPs) and biocidal products, and authorisation of the products. Based on the approaches presented in this document, a conclusion can be drawn on the impact of water treatment processes on residues of the AS or its metabolites in surface water and/or groundwater abstracted for the production of drinking water, i.e. the formation of transformation products (TPs). This guidance enables the identification of actual public health concerns from exposure to harmful compounds generated during the processing of water for the production of drinking water, and it focuses on water treatment methods commonly used in the European Union (EU). The tiered framework determines whether residues from PPP use or residues from biocidal product use can be present in water at water abstraction locations. Approaches, including experimental methods, are described that can be used to assess whether harmful TPs may form during water treatment and, if so, how to assess the impact of exposure to these water treatment TPs (tTPs) and other residues including environmental TPs (eTPs) on human and domesticated animal health through the consumption of TPs via drinking water. The types of studies or information that would be required are described while avoiding vertebrate testing as much as possible. The framework integrates the use of weight-of-evidence and, when possible alternative (new approach) methods to avoid as far as possible the need for additional testing.

Environmental concerns and bioaccumulation of psychiatric drugs in water bodies - Conventional versus biocatalytic systems of mitigation

The COVID-19 pandemic has brought increments in market sales and prescription of medicines commonly used to treat mental health disorders, such as depression, anxiety, stress, and related problems. The increasing use of these drugs, named psychiatric drugs, has led to their persistence in aquatic systems (bioaccumulation), since they are recalcitrant to conventional physical and chemical treatments typically used in wastewater treatment plants. An emerging environmental concern caused by the bioaccumulation of psychiatric drugs has been attributed to the potential ecological and toxicological risk that these medicines might have over human health, animals, and plants. Thus, by the application of biocatalysis-assisted techniques, it is possible to efficiently remove psychiatric drugs from water. Biocatalysis, is a widely employed and highly efficient process implemented in the biotransformation of a wide range of contaminants, since it has important differences in terms of catalytic behavior, compared to common treatment techniques, including photodegradation, Fenton, and thermal treatments, among others. Moreover, it is noticed the importance to monitor transformation products of degradation and biodegradation, since according to the applied removal technique, different toxic transformation products have been reported to appear after the application of physical and chemical procedures. In addition, this work deals with the discussion of differences existing between high- and low-income countries, according to their environmental regulations regarding waste management policies, especially waste of the drug industry.

Application of Ozonation-Biodegradation Hybrid System for Polycyclic Aromatic Hydrocarbons Degradation

Creosote, a mixture of polycyclic aromatic hydrocarbons (PAHs), was and is a wood impregnate of widespread use. Over the years the accumulation of creosote PAHs in soils and freshwaters has increased, causing a threat to ecosystems. The combined ozonation-biodegradation process is proposed to improve the slow and inefficient biodegradation of creosote hydrocarbons. The impact of different ozonation methods on the biodegradation of model wastewater was evaluated. The biodegradation rate, the changes in chemical oxygen demand, and the total organic carbon concentration were measured in order to provide insight into the process. Moreover, the bacteria consortium activity was monitored during the biodegradation step of the process. The collected data confirmed the research hypothesis, which was that the hybrid method can improve biodegradation. The pre-ozonation followed by inoculation with a bacteria consortium resulted in a significant increase in the biodegradation rate. It allows for the shortening of the time required for the consortium to reach maximum degradation effectiveness and cell activity. Hence, the study gives an important and useful perspective for the decontamination of creosote-polluted ecosystems.

Occurrence of pharmaceuticals in the wastewater of a Greek hospital: Combining consumption data collection and LC-QTOF-MS analysis

In this article we applied drug consumption approach and chemical analysis in parallel to investigate the concentrations of a large number of pharmaceuticals in different streams of a General Hospital. Drugs consumption data was collected during two periods (Period 1, 2) and the predicted environmental concentrations (PECs) were estimated for the wastewater of a building housing specific medical services (Point A) and for the entire hospital (Point B). Hospital wastewater samples (HWW) samples were also collected from these points and periods and the measured environmental concentrations (MEC) were determined using UHPLC-ESI-QTOF-MS/MS. According to consumption data, the highest number of drugs was consumed in the departments of Hematology, Intensive Care Unit, Cardiology, Internal Medicine, and Oncology, while the number of active substances used in the hospital was 413 (Period 1) and 362 (Period 2). For most substances, much higher PEC and MEC values were found at the HWW of Point A indicating that on-site treatment of this stream could be examined in the future. The application of wide-scope target analysis allowed the quantification of 122 compounds, while 21 additional substances were identified using suspect screening. The highest mean concentrations in Period 1 were found for acetaminophen (1100 μg/L) and rifaximin (723 μg/L), while in Period 2 for iopromide (458 μg/L) and acyclovir (408 μg/L). Among the detected compounds, 19 metabolites were determined. Atenolol acid, 1-hydroxy-midazolam and clopidogrel carboxylic acid were quantified at concentrations much higher than parent compounds indicating the importance of metabolites' monitoring in HWW. Calculation of PEC/MEC ratio for 36 pharmaceuticals showed sufficient correlation of these values for 19 % to 33 % of the substances depending on the examined period and sampling point. The parallel collection of drugs consumption data and chemical analysis give a thorough picture of the substances present in HWW and their main sources, facilitating decision-making for their better management.

TrendProbe: Time profile analysis of emerging contaminants by LC-HRMS non-target screening and deep learning convolutional neural network

Peak prioritization is one of the key steps in non-target screening of environmental samples to direct the identification efforts to relevant and important features. Occurrence of chemicals is sometimes a function of time and their presence in consecutive days (trend) reveals important aspects such as discharges from agricultural, industrial or domestic activities. This study presents a validated computational framework based on deep learning conventional neural network to classify trends of chemicals over 30 consecutive days of sampling in two sampling sites (upstream and downstream of a river). From trend analysis and factor analysis, the chemicals could be classified into periodic, spill, increasing, decreasing and false trend. The developed method was validated with list of 42 reference standards (target screening) and applied to samples. 25 compounds were selected by the deep learning and identified via non-target screening. Three classes of surfactants were identified for the first time in river water and two of them were never reported in the literature. Overall, 21 new homologous series of the newly identified surfactants were tentatively identified. The aquatic toxicity of the identified compounds was estimated by in silico tools and a few compounds along with their homologous series showed potential risk to aquatic environment.