Making waves: The NORMAN antibiotic resistant bacteria and resistance genes database (NORMAN ARB&ARG)-An invitation for collaboration to tackle antibiotic resistance.

With the global concerns on antibiotic resistance (AR) as a public health issue, it is pivotal to have data exchange platforms for studies on antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment. For this purpose, the NORMAN Association is hosting the NORMAN ARB&ARG database, which was developed within the European project ANSWER. The present article provides an overview on the database functionalities, the extraction and the contribution of data to the database. In this study, AR data from three studies from China and Nepal were extracted and imported into the NORMAN ARB&ARG in addition to the existing AR data from 11 studies (mainly European studies) on the database. This feasibility study demonstrates how the scientific community can share their data on AR to generate an international evidence base to inform AR mitigation strategies. The open and FAIR data are of high potential relevance for regulatory applications, including the development of emission limit values / environmental quality standards in relation to AR. The growth in sharing of data and analytical methods will foster collaboration on risk management of AR worldwide, and facilitate the harmonization in the effort for identification and surveillance of critical hotspots of AR. The NORMAN ARB&ARG database is publicly available at: https://www.norman-network.com/nds/bacteria/.

Significant Turning Point: Common Buzzard (Buteo buteo) Exposure to Second-Generation Anticoagulant Rodenticides in the United Kingdom.

Second-generation anticoagulant rodenticides (SGARs) are widely used to control rodent populations, resulting in the serious secondary exposure of predators to these contaminants. In the United Kingdom (UK), professional use and purchase of SGARs were revised in the 2010s. Certain highly toxic SGARs have been authorized since then to be used outdoors around buildings as resistance-breaking chemicals under risk mitigation procedures. However, it is still uncertain whether and how these regulatory changes have influenced the secondary exposure of birds of prey to SGARs. Based on biomonitoring of the UK Common Buzzard (Buteo buteo) collected from 2001 to 2019, we assessed the temporal trend of exposure to SGARs and statistically determined potential turning points. The magnitude of difenacoum decreased over time with a seasonal fluctuation, while the magnitude and prevalence of more toxic brodifacoum, authorized to be used outdoors around buildings after the regulatory changes, increased. The summer of 2016 was statistically identified as a turning point for exposure to brodifacoum and summed SGARs that increased after this point. This time point coincided with the aforementioned regulatory changes. Our findings suggest a possible shift in SGAR use to brodifacoum from difenacoum over the decades, which may pose higher risks of impacts on wildlife.

What is in the fish? Collaborative trial in suspect and non-target screening of organic micropollutants using LC- and GC-HRMS.

A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69 % of spiked compounds using LC-HRMS and 20-60 % of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants' own suspect lists led to putative identification of on average ∼145 and ∼20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ∼42 and ∼56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values from -9.9 to 16 and mass-to-charge ratios (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.

The importance of in-year seasonal fluctuations for biomonitoring of apex predators: A case study of 14 essential and non-essential elements in the liver of the common buzzard (Buteobuteo) in the United Kingdom.

Trace elements are chemical contaminants spread in the environment by anthropogenic activities and threaten wildlife and human health. Many studies have investigated this contamination in apex raptors as sentinel birds. However, there is limited data for long-term biomonitoring of multiple trace elements in raptors. In the present study, we measured the concentrations of 14 essential and non-essential trace elements in the livers of the common buzzard (Buteo buteo) collected in the United Kingdom from 2001 to 2019 and investigated whether concentrations have changed during this period. In addition, we estimated the importance of selected variables for modelling element accumulations in tissues. Except for cadmium, hepatic concentrations of harmful elements in most buzzards were lower than the biological significance level of each element. Hepatic concentrations of certain elements, including lead, cadmium, and arsenic, varied markedly seasonally within years. Their peak was in late winter and trough in late summer, except copper which showed an opposite seasonal pattern. In addition, lead in the liver consistently increased over time, whereas strontium showed a decreasing trend. Hepatic concentrations of cadmium, mercury, and chromium increased with age, whereas selenium and chromium were influenced by sex. Hepatic concentrations of arsenic and chromium also differed between different regions. Overall, our samples showed a low risk of harmful effects of most elements compared to the thresholds reported in the literature. Seasonal fluctuation was an important descriptor of exposure, which might be related to the diet of the buzzard, the ecology of their prey, and human activities such as the use of lead shot for hunting. However, elucidating reasons for these observed trends needs further examination, and biomonitoring studies exploring the effects of variables such as age, sex, and seasonality are required.

Wide-Scope Target and Suspect Screening of Antibiotics in Effluent Wastewater from Wastewater Treatment Plants in Europe.

The occurrence of antibiotics in the environment could result in the development of antibiotic-resistant bacteria, which could result in a public health crisis. The occurrence of 676 antibiotics and the main transformation products (TPs) was investigated in the 48 wastewater treatment plants (WWTPs) from 11 countries (Germany, Romania, Serbia, Croatia, Slovenia, Hungary, Slovakia, Czechia, Austria, Cyprus, and Greece) by target and suspect screening. Target screening involved the investigation of antibiotics with reference standards (40 antibiotics). Suspect screening covered 676 antibiotics retrieved from the NORMAN Substance Database (antibiotic list on NORMAN network). Forty-seven antibiotics were detected in effluent wastewater samples: thirty-two by target screening and fifteen additional ones by suspect screening. An ecotoxicological risk assessment was performed based on occurrence data and predicted no effect concentration (PNEC), which involved the derivation of frequency of appearance (FoA), frequency of PNEC exceedance (FoE), and extent of PNEC exceedance (EoE). Azithromycin, erythromycin, clarithromycin, ofloxacin, and ciprofloxacin were prioritized as the calculated risk score was above 1. The median of antibiotics' load to freshwater ecosystems was 0.59 g/day/WWTP. The detection of antibiotics across countries indicates the presence of antibiotics in the ecosystems of Europe, which may trigger unwanted responses from the ecosystem, including antibiotic resistance.

Wide-scope target screening characterization of legacy and emerging contaminants in the Danube River Basin by liquid and gas chromatography coupled with high-resolution mass spectrometry.

A state-of-the-art wide-scope target screening of 2,362 chemicals and their transformation products (TPs) was performed in samples collected within the Joint Danube Survey 4 (JDS4) performed in 2019. The analysed contaminants of emerging concern (CECs) included three major categories: plant protection products (PPPs), industrial chemicals and pharmaceuticals and personal care products (PPCPs). In total, 586 CECs were detected in the samples including 158 PPPs, 71 industrial chemicals, 348 PPCPs, and 9 other chemicals. A wide-variety of sample matrices were collected including influent and effluent wastewater, groundwater, river water, sediment and biota. Forty-five CECs (19 PPPs, 8 industrial chemicals, 18 PPCPs) were detected at levels above their ecotoxicological thresholds (lowest predicted no-effect concentration (PNEC) values) in one or more of the investigated environmental compartments, indicating potential adverse effects on the impacted ecosystems. Among them 12 are legacy substances; 33 are emerging and qualify as potential Danube River Basin Specific Pollutants (RBSPs). Moreover, the efficiency of the wastewater treatment plants (WWTPs) was evaluated using 20 selected performance indicator chemicals. WWTPs showed effective removal (removal rate ≥80%) and medium removal (removal rate 25-80%) for 6 and 8 of the indicator chemicals, respectively. However, numerous contaminants passed the WWTPs with a lower removal rate. Further investigation on performance of WWTPs is suggested at catchment level to improve their removal efficiency. WWTP effluents are proven to be one of the major sources of contaminants in the Danube River Basin (DRB). Other sources include sewage discharges, industrial and agricultural activities. Continuous monitoring of the detected CECs is suggested to ensure water quality of the studied area.

In situ detection of the genotoxic potential as one of the lines of evidence in the weight-of-evidence approach-the Joint Danube Survey 4 Case Study.

Environmental studies which aim to assess the ecological impact of chemical and other types of pollution should employ a complex weight-of-evidence approach with multiple lines of evidence (LoEs). This study focused on in situ genotoxicological methods such as the comet and micronucleus assays and randomly amplified polymorphic DNA analysis as one of the multiple LoEs (LoE3) on the fish species Alburnus alburnus (bleak) as a bioindicator. The study was carried out within the Joint Danube Survey 4 (JDS4) at nine sites in the Danube River Basin in the Republic of Serbia. Out of nine sampling sites, two were situated at the Tisa, Sava, and Velika Morava rivers, and three sites were at the Danube River. The three additionally employed LoEs were: SumTUwater calculated based on the monitoring data in the database of the Serbian Environmental Protection Agency (SEPA) (LoE1); in vitro analyses of JDS4 water extracts employing genotoxicological methods (LoE2); assessment of the ecological status/potential by SEPA and indication of the ecological status for the sites performed within the JDS4 (LoE4). The analyzed biomarker responses in the bleak were integrated into the unique integrated biomarker response index which was used to rank the sites. The highest pollution pressure was recorded at JDS4 39 and JDS4 36, while the lowest was at JDS4 35. The impact of pollution was confirmed at three sites, JDS4 33, 40, and 41, by all four LoEs. At other sampling sites, a difference was observed regarding the pollution depending on the employed LoEs. This indicates the importance of implementing a comprehensive weight-of-evidence approach to ensure the impact of pollution is not overlooked when using only one LoE as is often the case in environmental studies.

Advanced throughput analytical strategies for the comprehensive HRMS screening of organic micropollutants in eggs of different bird species.

Raptors are ideal indicators for biomonitoring studies using wildlife in order to assess the environmental pollution in the terrestrial ecosystem, since they are placed in the highest trophic position in the food webs and their life expectancy is relatively long. In this study, 26 eggs of 4 bird species (Peregrine falcon, Eurasian curlew, Little owl and Eagle owl) collected in Germany, were investigated for the presence of persistent organic pollutants (POPs) and thousands of contaminants of emerging concern (CECs). Generic sample preparation protocols were followed for the extraction of the analytes and the purification of the extracts, and the samples were analyzed both by liquid (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS), for capturing a wide range of organic micropollutants with different physicochemical properties. State-of-the-art screening methodologies were applied in the acquired HRMS data, including wide-scope target analysis of 2448 known pollutants and suspect screening of over 65,000 environmentally relevant compounds. Overall, 58 pollutants from different chemical classes, such as plant protection products, per- and polyfluoroalkyl substances and medicinal products, as well as their transformation products, were determined through target analysis. Most of the detected compounds were lipophilic (logP>2), although the presence of (semi)polar contaminants should not be overlooked, underlying the need for holistic analytical approaches in environmental monitoring studies. p,p'-DDE, PCB 153 and PCB138, PFOS and methylparaben were the most frequently detected compounds. 50 additional substances were identified and semi-quantified through suspect screening workflows, including mainly compounds of industrial use with high production volume.

Assessment of contaminants of emerging concern in European apex predators and their prey by LC-QToF MS wide-scope target analysis.

Apex predators are good indicators of environmental pollution since they are relatively long-lived and their high trophic position and spatiotemporal exposure to chemicals provides insights into the persistent, bioaccumulative and toxic (PBT) properties of chemicals. Although monitoring data from apex predators can considerably support chemicals' management, there is a lack of pan-European studies, and longer-term monitoring of chemicals in organisms from higher trophic levels. The present study investigated the occurrence of contaminants of emerging concern (CECs) in 67 freshwater, marine and terrestrial apex predators and in freshwater and marine prey, gathered from four European countries. Generic sample preparation protocols for the extraction of CECs with a broad range of physicochemical properties and the purification of the extracts were used. The analysis was performed utilizing liquid (LC) chromatography coupled to high resolution mass spectrometry (HRMS), while the acquired chromatograms were screened for the presence of more than 2,200 CECs through wide-scope target analysis. In total, 145 CECs were determined in the apex predator and their prey samples belonging in different categories, such as pharmaceuticals, plant protection products, per- and polyfluoroalkyl substances, their metabolites and transformation products. Higher concentration levels were measured in predators compared to prey, suggesting that biomagnification of chemicals through the food chain occurs. The compounds were prioritized for further regulatory risk assessment based on their frequency of detection and their concentration levels. The majority of the prioritized CECs were lipophilic, although the presence of more polar contaminants should not be neglected. This indicates that holistic analytical approaches are required to fully characterize the chemical universe of biota samples. Therefore, the present survey is an attempt to systematically investigate the presence of thousands of chemicals at a European level, aiming to use these data for better chemicals management and contribute to EU Zero Pollution Ambition.

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry.

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/). Supplementary Information: The online version contains supplementary material available at 10.1186/s12302-022-00680-6.

Making use of apex predator sample collections: an integrated workflow for quality assured sample processing, analysis and digital sample freezing of archived samples.

Using monitoring data from apex predators for chemicals risk assessment can provide important information on bioaccumulating as well as biomagnifying chemicals in food webs. A survey among European institutions involved in chemical risk assessment on their experiences with apex predator data in chemical risk assessment revealed great interest in using such data. However, the respondents indicated that constraints were related to expected high costs, lack of standardisation and harmonised quality criteria for exposure assessment, data access, and regulatory acceptance/application. During the Life APEX project, we demonstrated that European sample collections (i.e. environmental specimen banks (ESBs), research collection (RCs), natural history museums (NHMs)) archive a large variety of biological samples that can be readily used for chemical analysis once appropriate quality assurance/control (QA/QC) measures have been developed and implemented. We therefore issued a second survey on sampling, processing and archiving procedures in European sample collections to derive key quality QA/QC criteria for chemical analysis. The survey revealed great differences in QA/QC measures between ESBs, NHMs and RCs. Whereas basic information such as sampling location, date and biometric data were mostly available across institutions, protocols to accompany the sampling strategy with respect to chemical analysis were only available for ESBs. For RCs, the applied QA/QC measures vary with the respective research question, whereas NHMs are generally less aware of e.g. chemical cross-contamination issues. Based on the survey we derived key indicators for assessing the quality of biota samples that can be easily implemented in online databases. Furthermore, we provide a QA/QC workflow not only for sampling and processing but also for the chemical analysis of biota samples. We focussed on comprehensive analytical techniques such as non-target screening and provided insights into subsequent storage of high-resolution chromatograms in online databases (i.e. digital sample freezing platform) to ultimately support chemicals risk assessment.

European scale assessment of the potential of ozonation and activated carbon treatment to reduce micropollutant emissions with wastewater.

Micropollutants (MPs) in wastewater pose a growing concern for their potential adverse effects on the receiving aquatic environment, and some countries have started requiring that wastewater treatment plants remove them to a certain extent. Broad spectrum advanced treatment processes, such as ozonation, activated carbon or their combination, are expected to yield a significant reduction in the toxicity of effluents. Here we quantify the reduction of effluent toxicity potentially achieved by implementing these advanced treatment solutions in a selection of European wastewater treatment plants. To this end, we refer to a list of "total pollution proxy substances" (TPPS) composed of 1337 chemicals commonly found in wastewater effluents according to a compilation of datasets of measured concentrations. We consider these substances as an approximation of the "chemical universe" impinging on the European wastewater system. We evaluate the fate of the TPPS in conventional and advanced treatment plants using a compilation of experimental physicochemical properties that describe their sorption, volatilization and biodegradation during activated sludge treatment, as well as known removal efficiency in ozonation and activated carbon treatment, while filling the gaps through in silico prediction models. We estimate that the discharge of micropollutants with wastewater effluents in the European Union has a cumulative MP toxicity to the environment equal to the discharge of untreated wastewater of ca. 160 million population equivalents (PE), i.e. about 30 % of the generated wastewater in the EU. If all plants above a capacity of 100,000 PE were equipped with advanced treatment, we show that this load would be reduced to about 95 million PE. In addition, implementing advanced treatment in wastewater plants above 10,000 PE discharging to water bodies with an average dilution ratio smaller than 10 would yield a widespread improvement in terms of exposure of freshwater ecosystems to micropollutants, almost halving the part of the stream network exposed to the highest toxic risks. Our analysis provides background for a cost-effectiveness appraisal of advanced treatment "at the end of the pipe", which could lead to optimized interventions. This should not be regarded as a stand-alone solution, but as a complement to policies for the control of emissions at the source for the most problematic MPs.

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such as shipping activities and wastewater inputs from large coastal cities. Significant loads of chemical pollutants are being continuously brought in by major European rivers. This study investigated the spatial distribution of chemicals in the Ukrainian shelf (the northwestern part of the Black Sea) and their main sources. Chemical occurrence data used in the study was generated within the Joint Black Sea Surveys (JBSS), which took place in 2016 and 2017 as a part of the EU/UNDP EMBLAS II project (www.emblasproject.org). During the JBSS, seawater samples were analyzed by a non-target screening workflow using liquid chromatography high-resolution mass spectrometry (LC-HRMS). Open-source algorithms were applied to generate a combined dataset of 30,489 detected chemical signals and their intensities. Out of these, 35 compounds were tentatively identified by the application of a non-target screening identification workflow based on automated matching of their mass spectra against those in available mass spectral libraries. The dataset was used to generate images, representing spatial distribution of each of the signals. These images were then used as an input to a deep learning convolutional neural network classification model. The study resulted in the development of an open-source end-to-end workflow for the estimation of the pollution load by chemicals contributed by the two major inflowing rivers (Danube and Dnieper) and other, so far unidentified, sources. A dedicated dashboard was built to facilitate data visualization per detected signal/compound. The presented model proved to be especially useful at the prioritization of signals of unknown compounds, which is of key importance for the follow up structure elucidation efforts of bulky non-target screening data. The deep learning approach for peak prioritization of unknown chemicals in the environment has been used for the first time.

Target and suspect screening of 4777 per- and polyfluoroalkyl substances (PFAS) in river water, wastewater, groundwater and biota samples in the Danube River Basin.

Per- and polyfluoroalkyl substances (PFAS) are under regulatory scrutiny since some of them are persistent, bioaccumulative, and toxic. The occurrence of 4777 PFAS was investigated in the Danube River Basin (DRB; 11 countries) using target and suspect screening. Target screening involved investigation of PFAS with 56 commercially available reference standards. Suspect screening covered 4777 PFAS retrieved from the NORMAN Substance Database, including all individual PFAS lists submitted to the NORMAN Suspect List Exchange Database. Mass spectrometry fragmentation patterns and retention time index predictions of the studied PFAS were established for their screening by liquid chromatography - high resolution mass spectrometry using NORMAN Digital Sample Freezing Platform (DSFP). In total, 82 PFAS were detected in the studied 95 samples of river water, wastewater, groundwater, biota and sediments. Suspect screening detected 72 PFAS that were missed by target screening. Predicted no effect concentrations (PNECs) were derived for each PFAS via a quantitative structure-toxicity relationship (QSTR)-based approach and used for assessment of their environmental risk. Risk characterization revealed 18 PFAS of environmental concern in at least one matrix. The presence of PFAS in all studied environmental compartments across the DRB indicates a potentially large-scale migration of PFAS in Europe, which might require their further systematic regulatory monitoring.

First Novel Workflow for Semiquantification of Emerging Contaminants in Environmental Samples Analyzed by Gas Chromatography-Atmospheric Pressure Chemical Ionization-Quadrupole Time of Flight-Mass Spectrometry.

The ionization efficiency of emerging contaminants was modeled for the first time in gas chromatography-high-resolution mass spectrometry (GC-HRMS) which is coupled to an atmospheric pressure chemical ionization source (APCI). The recent chemical space has been expanded in environmental samples such as soil, indoor dust, and sediments thanks to recent use of high-resolution mass spectrometric techniques; however, many of these chemicals have remained unquantified. Chemical exposure in dust can pose potential risk to human health, and semiquantitative analysis is potentially of need to semiquantify these newly identified substances and assist with their risk assessment and environmental fate. In this study, a rigorously tested semiquantification workflow was proposed based on GC-APCI-HRMS ionization efficiency measurements of 78 emerging contaminants. The mechanism of ionization of compounds in the APCI source was discussed via a simple connectivity index and topological structure. The quantitative structure-property relationship (QSPR)-based model was also built to predict the APCI ionization efficiencies of unknowns and later use it for their quantification analyses. The proposed semiquantification method could be transferred into the household indoor dust sample matrix, and it could include the effect of recovery and matrix in the predictions of actual concentrations of analytes. A suspect compound, which falls inside the application domain of the tool, can be semiquantified by an online web application, free of access at http://trams.chem.uoa.gr/semiquantification/.

A novel workflow for semi-quantification of emerging contaminants in environmental samples analyzed by LC-HRMS.

There is an increasing need for developing a strategy to quantify the newly identified substances in environmental samples, where there are not always reference standards available. The semi-quantitative analysis can assist risk assessment of chemicals and their environmental fate. In this study, a rigorously tested and system-independent semi-quantification workflow is proposed based on ionization efficiency measurement of emerging contaminants analyzed in liquid chromatography-high-resolution mass spectrometry. The quantitative structure-property relationship (QSPR)-based model was built to predict the ionization efficiency of unknown compounds which can be later used for their semi-quantification. The proposed semi-quantification method was applied and tested in real environmental seawater samples. All semi-quantification-related calculations can be performed online and free of access at http://trams.chem.uoa.gr/semiquantification/ .

A Multi-Label Classifier for Predicting the Most Appropriate Instrumental Method for the Analysis of Contaminants of Emerging Concern.

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) and gas chromatography-high resolution mass spectrometry (GC-HRMS) have revolutionized analytical chemistry among many other disciplines. These advanced instrumentations allow to theoretically capture the whole chemical universe that is contained in samples, giving unimaginable opportunities to the scientific community. Laboratories equipped with these instruments produce a lot of data daily that can be digitally archived. Digital storage of data opens up the opportunity for retrospective suspect screening investigations for the occurrence of chemicals in the stored chromatograms. The first step of this approach involves the prediction of which data is more appropriate to be searched. In this study, we built an optimized multi-label classifier for predicting the most appropriate instrumental method (LC-HRMS or GC-HRMS or both) for the analysis of chemicals in digital specimens. The approach involved the generation of a baseline model based on the knowledge that an expert would use and the generation of an optimized machine learning model. A multi-step feature selection approach, a model selection strategy, and optimization of the classifier's hyperparameters led to a model with accuracy that outperformed the baseline implementation. The models were used to predict the most appropriate instrumental technique for new substances. The scripts are available at GitHub and the dataset at Zenodo.

Bacterial communities of the Black Sea exhibit activity against persistent organic pollutants in the water column and sediments.

The ability of bacteria to degrade organic pollutants influences their fate in the environment, impact on the other biota and accumulation in the food web. The aim of this study was to evaluate abundance and expression activity of the catabolic genes targeting widespread pollutants, such as polyaromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and hexachloro-cyclohexane (HCH) in the Black Sea water column and sediments. Concentrations of PAHs, PCBs and HCH were determined by gas chromatography (GC) coupled to mass spectrometry (MS) and electron capture (ECD) detectors. bphA1, PAH-RHDα, nahAc, linA and linB that encode biphenyl 2,3 dioxygenase, α-subunits of ring hydroxylating dioxygenases, naphthalene dioxygenase, dehydrochlorinase and halidohydrolase correspondently were quantified by quantitative PCR. More recalcitrant PAHs, PCBs and HCH tended to accumulate in the Black Sea environments. In water samples, 3- and 4-ringed PAHs outnumbered naphthalene, while PAHs with > 4 rings prevailed in the sediments. Congeners with 4-8 chlorines with ortho-position of the substituents were the most abundant among the PCBs. ß-HCH was determined at highest concentration in water samples, and total amount of HCH exceeded its legacy Environmental Quality Standard value. bphA1, was the most numerous gene in water layers (105 copies/mL) and sediments (105 copies/mg), followed by linB and PAH-RHDα genes (103 copies/mL; 105 copies/mg). The least abundant genes were linA (103 copies/mL; 104 copies/mg) and nahAc (102 copies/mL; 104 copies/mg). The most widely distributed gene bphА1 was one of the least expressed (10-3-10-2 copies/mL; 10-1 copies/mg). The most actively expressed genes were linB (101-102 copies/mL; 103 copies/mg), PAH-RHDα (101 copies/mL; 102 copies/mg) and linA (10-1-100 copies/mL; 100 copies/mg). Interaction of bacteria with PAHs, PCBs and HCH is evidenced by high copy numbers of the catabolic genes that initiate their degradation. More persistent compounds, such as high-molecular weight PAHs or ß-HCH are accumulating in the Black Sea water and sediments, albeit microbial activity is directed against them.

Application of a novel prioritisation strategy using non-target screening for evaluation of temporal trends (1969-2017) of contaminants of emerging concern (CECs) in archived lynx muscle tissue samples.

Most environmental monitoring studies of contaminants of emerging concern (CECs) focus on aquatic species and target specific classes of CECs. Even with wide-scope target screening methods, relevant CECs may be missed. In this study, non-target screening (NTS) was used for tentative identification of potential CECs in muscle tissue of the terrestrial top predator Eurasian lynx (Lynx lynx). Temporal trend analysis was applied as a prioritisation tool for archived samples, using univariate statistical tests (Mann-Kendall and Spearman rank). Pooled lynx muscle tissue collected from 1969 to 2017 was analysed with an eight-point time series using a previously validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 12,941 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 104 and 61 features with statistically significant increasing and decreasing trends, respectively. Following probable molecular formula assignment and elucidation with MetFrag, two compounds with increasing trends, and one with a decreasing trend, were tentatively identified. These results show that, despite low expected concentration levels and high matrix effects in terrestrial species, it is possible to prioritise CECs in archived lynx samples using NTS and univariate statistical approaches.

SARS-CoV-2 wastewater surveillance data can predict hospitalizations and ICU admissions.

We measured SARS-CoV-2 RNA load in raw wastewater in Attica, Greece, by RT-qPCR for the environmental surveillance of COVID-19 for 6 months. The lag between RNA load and pandemic indicators (COVID-19 hospital and intensive care unit (ICU) admissions) was calculated using a grid search. Our results showed that RNA load in raw wastewater is a leading indicator of positive COVID-19 cases, new hospitalization and admission into ICUs by 5, 8 and 9 days, respectively. Modelling techniques based on distributed/fixed lag modelling, linear regression and artificial neural networks were utilized to build relationships between SARS-CoV-2 RNA load in wastewater and pandemic health indicators. SARS-CoV-2 mutation analysis in wastewater during the third pandemic wave revealed that the alpha-variant was dominant. Our results demonstrate that clinical and environmental surveillance data can be combined to create robust models to study the on-going COVID-19 infection dynamics and provide an early warning for increased hospital admissions.