Non-target Analysis and Chemometric Evaluation of a Passive Sampler Monitoring of Small Streams

Farmland's silent threat: Comprehensive multimedia assessment of micropollutants through non-targeted screening and targeted analysis in agricultural systems

Intricate agricultural ecosystems markedly influence the dynamics of organic micropollutants, posing substantial threats to aquatic organisms and human health. This study examined the occurrence and distribution of organic micropollutants across soils, ditch sediment, and water within highly intensified farming setups. Using a non-targeted screening method, we identified 405 micropollutants across 10 sampling sites, which mainly included pesticides, pharmaceuticals, industrial chemicals, and personal care products. This inventory comprised emerging contaminants, banned pesticides, and controlled pharmaceuticals that had eluded detection via conventional monitoring. Targeted analysis showed concentrations of 3.99-1021 ng/g in soils, 4.67-2488 ng/g in sediment, and 12.5-9373 ng/L in water, respectively, for Σ40pesticides, Σ8pharmaceuticals, and Σ3industrial chemicals, indicating notable spatial variability. Soil organic carbon content and wastewater discharge were likely responsible for their spatial distribution. Principal component analysis and correlation analysis revealed a potential transfer of micropollutants across the three media. Particularly, a heightened correlation was decerned between soil and sediment micropollutant levels, highlighting the role of sorption processes. Risk quotients surpassed the threshold of 1 for 13-23 micropollutants across the three media, indicating high environmental risks. This study highlights the importance of employing non-targeted and targeted screening in assessing and managing environmental risks associated with micropollutants.

Recognition of screening out hierarchical toxic contaminants tuned by quantified pseudo-components from complex engineering co-combustion

Co-combustion of industrial and municipal solid wastes has emerged as the most promising disposal technology, yet its effect on unknown contaminants generation remains rarely revealed due to waste complexity. Hence, six batches of large-scale engineering experiments were designed in an incinerator of 650 t/d, which overcame the inauthenticity and deviation of laboratory tests. 953-1772 non-targeted compounds were screened in fly ash. Targeting the impact of co-combustion, a pseudo-component matrix model was innovatively integrated to quantitatively extract nine components from complex wastes grouped into biomass and plastic. Thus, the influence was evaluated across eight dimensions, covering molecular characteristics and toxicity. The effect of co-combustion with biomass pseudo-components was insignificant. However, co-combustion with high ratios of plastic pseudo-components induced higher potential risks, significantly promoting the formation of unsaturated hydrocarbons, highly unsaturated compounds (DBE≥15), and cyclic compounds by 19 %- 49 %, 17 %- 31 %, and 7 %- 27 %, respectively. Especially, blending with high ratios of PET plastic pseudo-components produced more species of contaminants. Unique 2 Level I toxicants, bromomethyl benzene and benzofuran-2-carbaldehyde, as well as 4 Level II toxicants, were locked, receiving no concern in previous combustion. The results highlighted risks during high proportion plastics co-combustion, which can help pollution reduction by tuning source wastes to enable healthy co-combustion.

Identification of Key Toxic Substances Considering Metabolic Activation: A Combination of Transcriptome and Nontarget Analysis

There have been numerous studies using effect-directed analysis (EDA) to identify key toxic substances present in source and drinking water, but none of these studies have considered the effects of metabolic activation. This study developed a comprehensive method including a pretreatment process based on an in vitro metabolic activation system, a comprehensive biological effect evaluation based on concentration-dependent transcriptome (CDT), and a chemical feature identification based on nontarget chemical analysis (NTA), to evaluate the changes in the toxic effects and differences in the chemical composition after metabolism. Models for matching metabolites and precursors as well as data-driven identification methods were further constructed to identify toxic metabolites and key toxic precursor substances in drinking water samples from the Yangtze River. After metabolism, the metabolic samples showed a general trend of reduced toxicity in terms of overall biological potency (mean: 3.2-fold). However, metabolic activation led to an increase in some types of toxic effects, including pathways such as excision repair, mismatch repair, protein processing in endoplasmic reticulum, nucleotide excision repair, and DNA replication. Meanwhile, metabolic samples showed a decrease (17.8%) in the number of peaks and average peak area after metabolism, while overall polarity, hydrophilicity, and average molecular weight increased slightly (10.3%). Based on the models for matching of metabolites and precursors and the data-driven identification methods, 32 chemicals were efficiently identified as key toxic substances as main contributors to explain the different transcriptome biological effects such as cellular component, development, and DNA damage related, including 15 industrial compounds, 7 PPCPs, 6 pesticides, and 4 natural products. This study avoids the process of structure elucidation of toxic metabolites and can trace them directly to the precursors based on MS spectra, providing a new idea for the identification of key toxic pollutants of metabolites.

Combustion-Derived Pollutants Linked with Kidney Disease in Low-Lying Flood-Affected Areas in the Balkans

Tens of thousands of people in southern Europe suffer from Balkan endemic nephropathy (BEN), and four times as many are at risk. Incidental ingestion of aristolochic acids (AAs), stemming from the ubiquitousAristolochia clematitis(birthwort) weed in the region, leads to DNA adduct-induced toxicity in kidney cells, the primary cause of BEN. Numerous cofactors, including toxic organics and metals, have been investigated, but all have shown small contributions to the overall BEN relative to non-BEN village distribution gradients. Here, we reveal that combustion-derived pollutants from wood and coal burning in Serbia also contaminate arable soil and test as plausible causative factors of BEN. Using a GC-MS screening method, biomass-burning-derived furfural and coal-burning-derived medium-chain alkanes were detected in soil samples from BEN endemic areas levels at up to 63-times and 14-times higher, respectively, than in nonendemic areas. Significantly higher amounts were also detected in colocated wheat grains. Coexposure studies with cultured kidney cells showed that these pollutants enhance DNA adduct formation by AA, - the cause of AA nephrotoxicity and carcinogenicity. With the coincidence of birthwort-derived AAs and the widespread practice of biomass and coal burning for household cooking and heating purposes and agricultural burning in rural low-lying flood-affected areas in the Balkans, these results implicate combustion-derived pollutants in promoting the development of BEN.

Non-target screening in water analysis: recent trends of data evaluation, quality assurance, and their future perspectives

This trend article provides an overview of recent advancements in Non-Target Screening (NTS) for water quality assessment, focusing on new methods in data evaluation, qualification, quantification, and quality assurance (QA/QC). It highlights the evolution in NTS data processing, where open-source platforms address challenges in result comparability and data complexity. Advanced chemometrics and machine learning (ML) are pivotal for trend identification and correlation analysis, with a growing emphasis on automated workflows and robust classification models. The article also discusses the rigorous QA/QC measures essential in NTS, such as internal standards, batch effect monitoring, and matrix effect assessment. It examines the progress in quantitative NTS (qNTS), noting advancements in ionization efficiency-based quantification and predictive modeling despite challenges in sample variability and analytical standards. Selected studies illustrate NTS's role in water analysis, combining high-resolution mass spectrometry with chromatographic techniques for enhanced chemical exposure assessment. The article addresses chemical identification and prioritization challenges, highlighting the integration of database searches and computational tools for efficiency. Finally, the article outlines the future research needs in NTS, including establishing comprehensive guidelines, improving QA/QC measures, and reporting results. It underscores the potential to integrate multivariate chemometrics, AI/ML tools, and multi-way methods into NTS workflows and combine various data sources to understand ecosystem health and protection comprehensively.

Ozonation products of purine derivatives, the basic structures of antiviral micropollutants

Purine and its nucleobases adenine and guanine are the basic structures of a large group of antiviral agents such as acyclovir and penciclovir. Hence, their ozonation is of interest with regard to wastewater treatment due to the formation of products that could affect the aquatic environment. In this study, the transformation products of the mentioned substances are investigated under different defined reaction conditions in order to gain insight into the ozonation characteristics of this compound class. Results show that examining related molecules significantly improves product screening by compiling known products and analogues leading to comprehensive candidate lists, for the purines with a total number of >120 candidates (including possible duplicates for several purines) of which 49 were detected for the derivatives studied. One product, cyanuric acid, which was previously postulated for adenine, was tentatively confirmed and quantified for the first time for the reaction of purine and adenine with ozone. In addition, two prioritisation approaches are presented to identify the major products that are either formed under specific reaction conditions or are potentially relevant for structurally related pollutants. First, principal component analysis allowed the prioritisation of the products formed according to reaction conditions. In the analysis of guanine and the two antivirals, this approach showed that at neutral and basic pH the 2-imino-5-oxoimidazoline products dominated while at acidic pH either analogues of 5-amino-2,4-imidazolidinedione or 2,4-diamino-1,3-oxazol-5-(2H)-one were abundant. A second approach prioritising common products in the ozonation of all three basic structures revealed the formation of two products that had not been reported before: C4H8O3 and C3H2N2O3, presumably oxalylurea. Both molecules or their analogues may also be formed from related micropollutants. Overall, examining basic structures and exemplary micropollutants in combination was shown to be a worthwhile approach to gain knowledge on the ozonation of a whole range of compounds.

Exploring the efficacy of metabarcoding and non-target screening for detecting treated wastewater

Wastewater treatment processes can eliminate many pollutants, yet remainder pollutants contain organic compounds and microorganisms released into ecosystems. These remainder pollutants have the potential to adversely impact downstream ecosystem processes, but their presence is currently not being monitored. This study was set out with the aim of investigating the effectiveness and sensitivity of non-target screening of chemical compounds, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding techniques for detecting treated wastewater in receiving waters. We aimed at assessing the impact of introducing 33 % treated wastewater into a triplicated large-scale mesocosm setup during a 10-day exposure period. Discharge of treated wastewater significantly altered the chemical signature as well as the microeukaryotic and prokaryotic diversity of the mesocosms. Non-target screening, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding detected these changes with significant covariation of the detected pattern between methods. The 18S V9 rRNA gene metabarcoding exhibited superior sensitivity immediately following the introduction of treated wastewater and remained one of the top-performing methods throughout the study. Full-length 16S rRNA gene metabarcoding demonstrated sensitivity only in the initial hour, but became insignificant thereafter. The non-target screening approach was effective throughout the experiment and in contrast to the metabarcoding methods the signal to noise ratio remained similar during the experiment resulting in an increasing relative strength of this method. Based on our findings, we conclude that all methods employed for monitoring environmental disturbances from various sources are suitable. The distinguishing factor of these methods is their ability to detect unknown pollutants and organisms, which sets them apart from previously utilized approaches and allows for a more comprehensive perspective. Given their diverse strengths, particularly in terms of temporal resolution, these methods are best suited as complementary approaches.

Nontarget Chemical Composition of Surface Waters May Reflect Ecosystem Processes More than Discrete Source Contributions

We investigated environmental, landscape, and microbial factors that could structure the spatiotemporal variability in the nontarget chemical composition of four riverine systems in the Oregon Coast Range, USA. We hypothesized that the nontarget chemical composition in river water would be structured by broad-scale landscape gradients in each watershed. Instead, only a weak relationship existed between the nontarget chemical composition and land cover gradients. Overall, the effects of microbial communities and environmental variables on chemical composition were nearly twice as large as those of the landscape, and much of the influence of environmental variables on the chemical composition was mediated through the microbial community (i.e., environment affects microbes, which affect chemicals). Therefore, we found little evidence to support our hypothesis that chemical spatiotemporal variability was related to broad-scale landscape gradients. Instead, we found qualitative and quantitative evidence to suggest that chemical spatiotemporal variability of these rivers is controlled by changes in microbial and seasonal hydrologic processes. While the contributions of discrete chemical sources are undeniable, water chemistry is undoubtedly impacted by broad-scale continuous sources. Our results suggest that diagnostic chemical signatures can be developed to monitor ecosystem processes, which are otherwise challenging or impossible to study with existing off-the-shelf sensors.

Critical review on data processing algorithms in non-target screening: challenges and opportunities to improve result comparability

Non-target screening (NTS) is a powerful environmental and analytical chemistry approach for detecting and identifying unknown compounds in complex samples. High-resolution mass spectrometry has enhanced NTS capabilities but created challenges in data analysis, including data preprocessing, peak detection, and feature extraction. This review provides an in-depth understanding of NTS data processing methods, focusing on centroiding, extracted ion chromatogram (XIC) building, chromatographic peak characterization, alignment, componentization, and prioritization of features. We discuss the strengths and weaknesses of various algorithms, the influence of user input parameters on the results, and the need for automated parameter optimization. We address uncertainty and data quality issues, emphasizing the importance of incorporating confidence intervals and raw data quality assessment in data processing workflows. Furthermore, we highlight the need for cross-study comparability and propose potential solutions, such as utilizing standardized statistics and open-access data exchange platforms. In conclusion, we offer future perspectives and recommendations for developers and users of NTS data processing algorithms and workflows. By addressing these challenges and capitalizing on the opportunities presented, the NTS community can advance the field, improve the reliability of results, and enhance data comparability across different studies.

Chemometers: an integrative tool for chemical assessment in multimedia environments

We propose novel chemometers - passive equilibrium samplers of, e.g., silicone - as an integrative tool for the assessment of hydrophobic organic compounds in multimedia environments. The traditional way of assessing levels of organic pollutants across different environmental compartments is to compare the chemical concentration normalized to the major sorptive phase in two or more media. These sorptive phases for hydrophobic organic compounds differ between compartments, e.g., lipids in biota and organic carbon in sediments. Hence, comparability across media can suffer due to differences in sorptive capacities, but also extraction protocols and bioavailability. Chemometers overcome these drawbacks; they are a common, universal and well-defined polymer reference phase for sampling of a large range of nonpolar organic pollutants in different matrices like biota, sediment and water. When bringing the chemometer into direct contact with the sample, the chemicals partition between the sample and the polymer until thermodynamic equilibrium partitioning is established. At equilibrium, the chemical concentrations in the chemometers can be determined and directly compared between media, e.g., between organisms of different trophic levels or inhabiting different areas, between organs within an organism or between biotic and abiotic compartments, amongst others. Chemometers hence allow expressing the data on a common basis, as the equilibrium partitioning concentrations in the polymer, circumventing normalizations. The approach is based on chemical activity rather than total concentrations, and as such, gives a measure of the "effective concentration" of a compound or a mixture. Furthermore, chemical activity is the main driver for partitioning, biouptake and toxicity. As an additional benefit, the extracts of the chemometers only require limited cleanup efforts, avoiding introduction of a bias between chemicals of different persistence, and can be submitted to both chemical analysis and/or bioanalytical profiling.

Combining Passive Sampling with Suspect and Nontarget Screening to Characterize Organic Micropollutants in Streams Draining Mixed-Use Watersheds

Organic micropollutants (OMPs) represent an anthropogenic stressor on stream ecosystems. In this work, we combined passive sampling with suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry to characterize complex mixtures of OMPs in streams draining mixed-use watersheds. Suspect screening identified 122 unique OMPs for target quantification in polar organic chemical integrative samplers (POCIS) and grab samples collected from 20 stream sites in upstate New York over two sampling seasons. Hierarchical clustering established the co-occurrence profiles of OMPs in connection with watershed attributes indicative of anthropogenic influences. Nontarget screening leveraging the time-integrative nature of POCIS and the cross-site variability in watershed attributes prioritized and confirmed 11 additional compounds that were ubiquitously present in monitored streams. Field sampling rates for 37 OMPs that simultaneously occurred in POCIS and grab samples spanned the range of 0.02 to 0.22 L/d with a median value of 0.07 L/d. Comparative analyses of the daily average loads, cumulative exposure-activity ratios, and multi-substance potentially affected fractions supported the feasibility of complementing grab sampling with POCIS for OMP load estimation and screening-level risk assessments. Overall, this work demonstrated a multi-watershed sampling and screening approach that can be adapted to assess OMP contamination in streams across landscapes.