Non-target Screening Method Research Articles

GC/MS Screening of Substances Released from Post-Consumer Recycled HDPE Pellets into 95% Ethanol: Reproducibility and Variation between Production Batches

The use of post-consumer recycled (PCR) plastic materials in sensitive packaging applications, such as for cosmetic products and detergents, requires a clear understanding of the identities and quantities of chemical substances, which they may release into packed products. With many potential sources of and thus different types of potentially releasable substances, a reliable non-targeted screening method is required to assess these materials. Such a method should be readily applicable in industrial practice and provide a realistic estimation of substance release. This investigation focused on the use of gas chromatography/coupled mass spectrometry (GC/MS) to analyze substances, which recycled HDPE (rHDPE) plastic pellets release into 95% ethanol under accelerated testing conditions. The results of the repeated testing of reference samples clearly demonstrated the good reproducibility of the described methodology, with standard deviations of repeated determinations of the total released substance amounts of 6.8–8.1%. The application to several production batches of three commercial rHDPE grades additionally demonstrated that the batch-to-batch variation of substances which rHDPE materials release can be confined to less than 10% of variation of the total detectable substance amount. The described methodology is therefore seen as a pragmatic, repeatable assessment of recycled HDPE plastic batches with a view to substance release.

Targeted and non-targeted identification of dye and chemical contaminants in Loji River, Indonesia using FT-ICR-MS

This study utilized liquid chromatography (LC) alongside Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to explore the dyes and chemical contaminants in Loji River, Indonesia. We tentatively identified a total of 655 contaminants at various confidence level, subsequently classifying them into 22 distinct categories. Of the 54 dyes we detected, 12 corresponded with entries in our specialized in-house database. These 12 dyes were further confirmed by reference standards, matching both retention time (RT) and MS/MS spectra. LC-FT-ICR MS data showed that dyes from printing batik and textile industries are key contributors to river pollution. Particularly noteworthy were two sample locations that displayed substantial contamination, predominantly from azoic and reactive dyes. Additionally, pharmaceuticals were identified as one of the most frequently occurring contaminants, underscoring the inadequacies in the area's sewage management. To corroborate these findings, we conducted physicochemical, phytotoxicity, and acute toxicity tests, all of which verified the harmful effects of the Loji River's water on both the local flora and human populations. Notably, water samples that tested positive for dye contamination exhibited elevated toxicity levels. To the best of our knowledge, this study is pioneering in its molecular-level investigation of dye contamination in Southeast Asian rivers. Our results accentuate the pressing need for both targeted and non-targeted screening methods to identify contaminants in the surface waters of developing nations.

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.

A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.

The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non-targeted screening method for P&VDs for their comprehensive risk assessment. In this study, a modified support vector machine (SVM)-assisted metabolomics approach by screening eligible variables to represent marker compounds of 124 multi-class P&VDs in maize was developed based on the results of high-performance liquid chromatography-tandem mass spectrometry. Principal component analysis and orthogonal partial least squares discriminant analysis indicate the existence of variables with obvious inter-group differences, which were further investigated by S-plot plots, permutation tests, and variable importance in projection to obtain eligible variables. Meanwhile, SVM recursive feature elimination under the radial basis function was employed to obtain the weight-squared values of all the variables ranging from large to small for the screening of eligible variables as well. Pairwise t-tests and fold changes of concentration were further employed to confirm these eligible variables to represent marker compounds. The results indicate that 120 out of 124 P&VDs can be identified by the SVM-assisted metabolomics method, while only 109 P&VDs can be found by the metabolomics method alone, implying that SVM can promote the screening accuracy of the metabolomics method. In addition, the method's practicability was validated by the real contaminated maize samples, which provide a bright application prospect in non-targeted screening of contaminants. The limits of detection for 120 P&VDs in maize samples were calculated to be 0.3~1.5 µg/kg.

Non-target screening and prioritization of organic contaminants in seawater desalination and their ecological risk assessment

The impact of desalination brine on the marine environment is a global concern. Regarding this, salinity is generally accepted as the major environmental factor in desalination concentrate. However, recent studies have shown that the influence of organic contaminants in brine cannot be ignored. Therefore, a non-targeted screening method based on comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC × GC-qMS) was developed for identifying organic contaminants in the desalination brine. A total of 404 compounds were tentatively identified from four seawater desalination plants (three reverse osmosis plants and one multiple effect distillation plant) in China. The identified compounds were prioritized based on their persistence, bioaccumulation, ecotoxicity, usage, and detection frequency. Twenty-one (21) compounds (seven phthalates, ten pesticides, four trihalomethanes) were then selected for further quantitative analysis and ecological risk assessment, including compounds from the priority list along with substances from the same chemical classes. Ecologically risky substances in brine include diisobutylphthalate and bis(2-Ethylhexyl) phthalate, atrazine and acetochlor, and bromoform. Most of the contaminants come from raw seawater, and no high risk contaminants introduced by the desalination process have been found except for disinfection by-products. In brine discharge management, people believed that all pollution in raw seawater was concentrated by desalination process. This study shows that not all pollutants are concentrated during the desalination process. In this study, the total concentration of pesticide in the brine increased by 58.42%. The concentration of ∑PAEs decreased by 13.65% in reverse osmosis desalination plants and increased by 10.96% in the multi-effect distillation plant. The concentration of trihalomethane increased significantly in the desalination concentrate. The change in the concentration of pollutants in the desalination concentrate was related to the pretreatment method and the chemical characteristics of the contaminants. The method and results given in this study hinted a new idea to identify and control the environmental impact factors of brine.

Fragmentation characteristics-based nontargeted screening method of exogenous chemical residues in animal-derived foods using reversed-phase and hydrophilic interaction liquid chromatography–high-resolution mass spectrometry

Fragmentation characteristics are crucial for nontargeted screening to discover and identify unknown exogenous chemical residues in animal-derived foods. In this study, first, fragmentation characteristics of 51 classes of exogenous chemical residues were summarized based on experimental mass spectra of standards in reversed-phase and hydrophilic interaction liquid chromatography–high-resolution mass spectrometry (MS) and mass spectra from the MassBank of North America (MoNA) library. According to the proportion of fragmentation characteristics to the total number of chemical residues in each class, four screening levels were defined to classify 51 classes of chemical residues. Then, a nontargeted screening method was developed based on the fragmentation characteristics. The evaluation results of 82 standards indicated that more than 90 % of the chemical residues with MS/MS spectra can be identified at concentrations of 100 and 500 μg/kg, and about 80 % can be identified at 10 μg/kg. Finally, the nontargeted screening method was applied to 16 meat samples and 21 egg samples as examples. As a result, eight chemical residues and transformation products (TPs) of 5 classes in the exemplary samples were found and identified, in which 3 TPs of azithromycin were identified by fragmentation characteristics-assisted structure interpretation. The results demonstrated the practicability of the nontargeted screening method for routine risk screening of food safety.

Unveiling per- and polyfluoroalkyl substance contamination in Chinese paper products and assessing their exposure risk

The contamination characteristics, migration patterns and health risks of per- and polyfluoroalkyl substances (PFAS) were investigated in 66 Chinese paper products by using target and non-target screening methods. Among 57 target PFASs, 5 and 6 PFASs were found in the hygiene paper products (<LOQ-12.6 ng/g) and stationery paper products (<LOQ-8.8 ng/g), respectively. A total of 25 PFASs were detected in the 39 food contact paper products, with the highest concentration of 1630 ng/g. Suspect and non-target analysis have found 28 PFASs with confidence levels 1–3, 132 certain PFAS compounds (level 4) and 56 homologue groups (level 5), containing newly identified long-chain polyfluorocarboxylic acid (9:3/11:3FTCA, 11:3/13:3FTUCA) and X:2 FTOH-Sulfate. A potential transformation relationship between the detected PFAS was proposed, starting from X:2 FTOH and finally transforming to CnF2n+1COOH. Microwave heating can increase the release of PFAS in popcorn bags and convert long-chain PFAS into short-chain ones. The migration experiments indicated that the ethanol in food simulants can increase the migration of PFAS, and short-chain PFAS exhibits a greater migration trend. The estimated daily intake (EDI) values for 6 of 18 paper bowls/plates exceeded the recommendation of 0.63 ng/kg bw/day by the European Food Safety Authority (EFSA), posing a potential threat to human health.

Development and evaluation of a comprehensive workflow for suspect screening of exposome-related xenobiotics and phase II metabolites in diverse human biofluids

Suspect and non-target screening (SNTS) methods are being promoted in order to decode the human exposome since a wide chemical space can be analysed in a diversity of human biofluids. However, SNTS approaches in the exposomics field are infra-studied in comparison to environmental or food monitoring studies. In this work, a comprehensive suspect screening workflow was developed to annotate exposome-related xenobiotics and phase II metabolites in diverse human biofluids. Precisely, human urine, breast milk, saliva and ovarian follicular fluid were employed as samples and analysed by means of ultra-high performance liquid chromatography coupled with high resolution tandem mass spectrometry (UHPLC-HRMS/MS). To automate the workflow, the “peak rating” parameter implemented in Compound Discoverer 3.3.2 was optimized to avoid time-consuming manual revision of chromatographic peaks. In addition, the presence of endogenous molecules that might interfere with the annotation of xenobiotics was carefully studied as the employment of inclusion and exclusion suspect lists. To evaluate the workflow, limits of identification (LOIs) and type I and II errors (i.e., false positives and negatives, respectively) were calculated in both standard solutions and spiked biofluids using 161 xenobiotics and 22 metabolites. For 80.3 % of the suspects, LOIs below 15 ng/mL were achieved. In terms of type I errors, only two cases were identified in standards and spiked samples. Regarding type II errors, the 7.7 % errors accounted in standards increased to 17.4 % in real samples. Lastly, the use of an inclusion list for endogens was favoured since it avoided 18.7 % of potential type I errors, while the exclusion list caused 7.2 % of type II errors despite making the annotation workflow less time-consuming.

Application of Nontarget High-Resolution Mass Spectrometry Fingerprints for Qualitative and Quantitative Source Apportionment: A Real Case Study.

High-resolution mass spectrometry (HRMS) provides extensive chemical data, facilitating the differentiation and quantification of contaminants of emerging concerns (CECs) in aquatic environments. This study utilizes liquid chromatography-HRMS for source apportionment in Chebei Stream, an urban water stream in Guangzhou, South China. Initially, 254 features were identified as potential CECs by the nontarget screening (NTS) method. We then established 1689, 1317, and 15,759 source-specific HRMS fingerprints for three distinct sources, the mainstream (C3), the tributary (T2), and the rain runoff (R1), qualitatively assessing the contribution from each source downstream. Subsequently, 32, 55, and 3142 quantitative fingerprints were isolated for sites C3, T2, and R1, respectively, employing dilution curve screening for source attribution. The final contribution estimates downstream from sites C3, T2, and R1 span 32-96, 12-23, and 8-23%, respectively. Cumulative contributions from these sources accurately mirrored actual conditions, fluctuating between 103 and 114% across C6 to C8 sites. Yet, with further tributary integration, the overall source contribution dipped to 52%. The findings from this research present a pioneering instance of applying HRMS fingerprints for qualitative and quantitative source tracking in real-world scenarios, which empowers the development of more effective strategies for environmental protection.

Reproducibility in nontarget screening (NTS) of environmental emerging contaminants: Assessing different HLB SPE cartridges and instruments

Non-targeted screening (NTS) methods are integral in environmental research for detecting emerging contaminants. However, their efficacy can be influenced by variations in hydrophilic-lipophilic balance (HLB) solid phase extraction (SPE) cartridges and high-resolution mass spectrometry (HRMS) instruments across different laboratories. In this study, we scrutinized the influence of five HLB SPE cartridges (Nano, Weiqi, CNW, Waters, and J&K) and four LC-HRMS platforms (Agilent, Waters, Thermo, and AB SCIEX) on the identification of emerging environmental contaminants. Our results demonstrate that 87.6 % of the target compounds and over 59.6 % of the non-target features were consistently detected across all tested HLB cartridges, with an overall 71.2 % universally identified across the four LC-HRMS systems. Discrepancies in detection rates were primarily attributable to variations in retention time stability, mass stability of precursors and fragments, system cleanliness affecting fold change and p-values, and fragment response. These findings confirm the necessity of refining parameter criteria for NTS. Moreover, our study confirms the efficacy of the PyHRMS tool in analyzing and processing data from multiple instrumental platforms, reinforcing its utility for multi-platform NTS. Overall, our findings underscore the reliability and robustness of NTS methods in identifying potential water contaminants, while also highlighting factors that may influence these outcomes.

Nontargeted screening method for detection of illicit adulterants in dietary supplements and herbal medicines using UHPLC-QTOF-MS with fine-tuned Spec2Vec-based spectral similarity and chemical classification filter

Liquid chromatography-mass spectrometry (LC-MS) is a widely utilized technique for inspecting adulteration. Unscrupulous businesses persistently introduce novel illegal adulterants, making it necessary to develop methods to screen compounds not present in the current library. Conventional cosine similarity for mass spectral libraries matching is limited in their ability to identify structurally similar compounds. In our previous study, comparison of performance among four advanced similarity algorithms revealed that Spec2Vec exhibited the best performance in terms of both detection capability and false discovery rate, making it the chosen method for identifying illegal adulterants. However, Spec2Vec still exhibited worse performance compared to MS2DeepScore and entropy similarity in the aspects of detection capability and false discovery rate, respectively. In this study, our objective was to optimize the performance of spectral similarity for a specific compound class by fine-tuning a pretrained Spec2Vec model. Additionally, we implemented the chemical classification tool CANOPUS to address the issue of similarities in backbone structures between illegal adulterants and compounds found in herbal medicine, which can lead to false positives. We utilized glucocorticoids as potentially illicit adulterants to provide a proof-of-concept, and the results demonstrated that the fine-tuned Spec2Vec model not only exhibits a significant improvement in detection ability compared to the original model but also achieves comparable performance to MS2Deepscore. Moreover, the fine-tuned Spec2Vec model shows notably fewer false positives in comparison to MS2Deepscore. Overall, this proposed pipeline demonstrates high effectiveness and competitiveness in inspecting illegal adulterants, enhancing the analysis of large-scale MS data.

Applying machine learning on high-performance thin-layer chromatography using the complementary developing solvents concept

Predicting chromatographic results is a difficult task for many analysts, especially in Thin-Layer Chromatography (TLC) where reproducibility is always a critical point. The availability of suitable equipment and rigorous standardization of parameters has transformed TLC into High-Performance Thin-Layer Chromatography (HPTLC) and made reproducibility of results a reality. With recent non-targeted screening methods using the concept of complementary developing solvents, HPTLC has become a medium to high throughput technique that generates large sets of data, allowing the construction of predictive models. In this study, we evaluated to which extend HPTLC RF are decoded from molecular chemical properties. Various regressors (support vector machine, random forest, linear regression) trained with 178 reference substances predicted the RF values of 20 reference substances belonging to different chemical classes. We show that the performance of the model is bound to the similarity between the training and the test sets. The proposed methodology further encourages the use of computational methods for evaluation of HPTLC data. Thus, the nature of an unknown zone within the chromatogram could be matched with potential candidates based on predicted RF.

Comprehensive discovery and migration evaluation of antimicrobial drugs and their transformation products in a swine farm by target, suspect, and nontarget screening

Swine farms contaminated the surrounding environment through manure application and biogas slurry irrigation, hence causing the wide residual of multiple antimicrobial drugs (ADs) and their transformation products (TPs). This study performed target, suspect, and nontarget screening methods to comprehensively investigate the pollution profiles of ADs in a typical swine farm, and characterize the potential transformed pathway of TPs and distinguish specific reactions of different catalog of ADs. Samples of fresh feces, compost, biogas slurry, topsoil, column soil, groundwater and plants were analyzed using the database containing 98 target analytes, 679 suspected parent ADs, and ∼ 107 TPs. In total, 29 ADs were quantitively detected, and tetracyclines (TCs) were mostly frequently detected ADs with the concentrations up to 4251 ng/g in topsoil. Soil column investigation revealed that doxycycline (DOX) and tetracycline (TC) in soil could migrate to depths of approximately 1 m in soil. Suspect screening identified 75 parent ADs, with 10 being reported for the first time in environmental media. Semi-quantification of ADs revealed that one of the less-concerned ADs, clinafloxacin, was detected to exceed 5000 ng/L in biogas slurry, suggesting that significant attentions should be paid to these less-concerned ADs. Moreover, 314 TPs was identified, and most of them were found to undergo microbial/enzymatic metabolism pathways. Overall, our study displays a comprehensive overview of ADs and their TPs in swine farming environments, and provides an inventory of crucial list that worthy of concern. The results emphasize the need to quantify the levels and distribution of previously overlooked ADs and their TPs in livestock farms.

Discovery and occurrence of organophosphorothioate esters in food contact plastics and foodstuffs from South China: Dietary intake assessment

A recent study revealed the presence of non-pesticide organothiophosphate esters (OTPEs) — precursors to organophosphate esters (OPEs) contaminants — in river water. Since OPEs have demonstrated adverse reproductive outcomes in humans, this accentuates the urgency to explore the prevalence of non-pesticide OTPEs in other potential human exposure matrices. In this study, a nontarget screening method based on high-resolution mass spectrometry was used to identify OTPEs in food contact plastic (FCP) samples collected from South China. O,O,O-triphenyl phosphorothioate (TPhPt) and O,O,O-tris(2,4-di-tert-butylphenyl) phosphorothioate (AO168 = S) were unequivocally identified (Level 1), while O,O-di(di-butylphenyl) O-methyl phosphorothioate (BDBPMPt) was tentatively identified (Level 2b, indicating probable structure based on diagnostic evidence). Among n = 70 FCP samples, AO168 = S emerged with the highest detection frequency and median concentration of 74 % and 111 ng/g, respectively. Significant Pearson correlations were observed in log-transformed peak areas of AO168 = S and TPhPt in FCPs with their respective oxons, respectively. Occurrences of AO168 = S and TPhPt were further investigated in n = 100 foodstuff samples using a market basket method. AO168 = S and TPhPt exhibited detection frequencies of 43 % and 44 % in all food items with mean concentrations of 2.17 ng/g wet weight (ww) (range: <0.53–67.8 ng/g ww) and 0.112 ng/g ww (range: <0.006–2.39 ng/g ww), respectively. The highest mean concentrations for AO168 = S and TPhPt were found in vegetables (4.62 ng/g ww) and oil (3.00 ng/g ww), respectively. The median estimated daily intakes (EDIs) of AO168 = S and TPhPt via diet were calculated as 10.4 and 1.51 ng/kg body weight/day, respectively. For AO168 = S, only meat and vegetables contributed to the median EDI, whereas for TPhPt, oil was identified as the principal contributor to the median EDI. This study for the first time evaluated human exposure to OTPEs via diet, providing new insights to overall human exposure to OPEs.

Rapid screening and risk assessment of various elements in ultrafine granular powder of Panax quinquefolius L.

IntroductionPanax quinquefolius L. is obtained from a man-shaped root of several species of the genus Panax of the family Araliceae indigenous, which is thought to increase memory, decrease aging, and possess both digestion regulating and liver-protective activity. The widely used in daily life, making its risk assessment a matter of great importance. This research investigates the application of inductively coupled plasma mass spectrometry (ICP-MS) for rapid, non-targeted screening and risk assessment of various heavy metals and toxic agents in Panax quinquefolius L.'s ultrafine granular powder. MethodsThe Panax quinquefolius L. was ground to ultrafine granular powder and subjected to microwave digestion for pre-treatment. ICP-MS was then employed to scan all elements within the full spectrum range, allowing identification of heavy metals and toxic elements using the non-targeted detection method. Subsequently, risk assessment was conducted for Pb, Cu, Ni, Mn, Al, Hg, As, and Cd present in the powder, following the basic steps of risk assessment. ResultsThe concentrations of Pb, Cd, As, Hg, and Cu in ultrafine granular Panax quinquefolius L. powder were found to be below the limits established by the current pharmacopeia. Notably, essential trace elements for the human body, namely Ca, Fe, Mn, Zn, and Mg, were relatively abundant in the powder, with concentrations ranging from 1441.30 to 4016.20, 51.16 to 577.04, 34.78 to 121.99, 17.85 to 83.49, and 1017.69 to 3194.16 mg/kg, respectively. The risk assessment indicated that, in terms of exposure to toxic elements, the order for a person consuming ultrafine granular Panax quinquefolius L. powder would be: Al > Mn > Cu > Ni > Pb > Cd > As > Hg. Importantly, the non-cancer risks associated with Ni, Pb, Al, Mn, Cd, As, Hg, and Cu in the ultrafine granular Panax quinquefolius L. powder were all within acceptable levels. ConclusionThis study successfully establishes a multi-element non-targeted rapid screening method combined with risk assessment techniques, enabling swift determination of harmful target element concentrations and risk profiles in ultrafine granular Panax quinquefolius L. powder. This approach serves as a technical reserve for effectively responding to incidents of toxicity potentially associated with traditional Chinese medicine.

SWATH-F: A Novel Nontarget Strategy Based on the SWATH-MS Deconvolution Method Assisting in Annotating PFAS Homologues in Multisample Studies.

In order to identify emerging per- and polyfluoroalkyl substances (PFASs) and their alternatives in the environment or population, we need to perform extensive profiling of PFASs to determine their distribution in samples. The sequential window acquisition of all theoretical fragment-ion spectra (SWATH mode) is capable of obtaining a wide range of MS2 spectra but is difficult for direct identification of PFASs due to its complex MS2 spectra, and the nontarget screening method is difficult to identify due to its lack of a priori information. In this study, we demonstrated the great potential of SWATH-F, a nontarget fragment-based homologue screening method in combination with the SWATH-MS deconvolution, for detecting PFASs. We evaluated the application of SWATH-F to gradient spiked samples and real population serum samples, compared it with nontarget homologue screening in the information-dependent acquisition mode (IDA mode), and obtained better results for SWATH-F with 276% improvement (IDA:17 PFASs, SWATH-F: 64 PFASs) in identification. In addition, we automated the screening and identification process of SWATH-F to facilitate its use by researchers. SWATH-F is freely available on GitHub (https://github.com/njuIrene/SWATH-F) under an MIT license.

Non-targeted and suspect screening analysis using ion exchange chromatography-Orbitrap tandem mass spectrometry reveals polar and very mobile xenobiotics in Danish drinking water

Non-targeted and suspect screening analysis is gaining approval across the scientific and regulatory community to monitor the chemical status in the environment and thus environmental quality. These holistic screening analyses provides the means to perform suspect screening and go beyond to discover previously undescribed chemical pollutants in environmental samples. In a case study, we developed and optimized a high-resolution tandem mass spectrometry platform hyphenated with anion exchange chromatography to screen drinking water samples in Denmark. The optimized non-targeted screening method was able to detect anionic and polar compounds and was successfully applied to drinking water from two drinking water facilities. Following a data analysis pipeline optimization, anionic pesticide residues and other environmental contaminants were detected at confidence identification level 1 such as dimethachlor ESA, mecoprop, and dichlorprop in drinking water. In addition to these three substances, it was possible to detect another 1662 compounds, of which 97 were annotated at confidence identification level 2. More research is urgently needed to health risk prioritize the detected substances and to determine their concentrations.

Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective.

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Ultrahigh performance LC/FT-MS non-targeted screening for biomass burning organic aerosol with MZmine2 and MFAssignR

In recent years, ultrahigh performance liquid chromatography Fourier transform mass spectrometry (LC/FT-MS) based non-targeted screening (NTS) methods have become increasingly popular for comprehensive analysis of complex organic mixtures. However, applying these methods for environmental complex mixture analysis is challenging due to the extreme complexity of natural samples and a lack of standard samples or surrogates for environmental complex mixtures. Furthermore, limited molecular markers in the databases and insufficient data processing software workflows make the application of these methods more challenging for environmental complex mixtures. In this work, we implement a new NTS data processing workflow to process data collected from ultrahigh performance liquid chromatography and Fourier transform Orbitrap Elite Mass Spectrometry (LC/FT-MS) by combining MZmine2 and MFAssignR, two opensource data processing tools and commercial Mesquite liquid smoke as a surrogate for biomass burning organic aerosol. MZmine2.53 data extraction followed MFAssignR molecular formula assignment offered noise free and highly accurate 1733 individual molecular formulas presented in liquid smoke with 4906 molecular species, including isomers. The results of this new approach were consistent with the results of direct infusion FT-MS analysis confirming its reliability. Over 90% of the molecular formulas presented in mesquite liquid smoke were matched with the molecular formulas of ambient biomass burning organic aerosol. This suggests the potential use of commercial liquid smoke is an acceptable surrogate for biomass burning organic aerosol research. The presented method significantly improves the identification of the molecular composition of biomass burning organic aerosol by successfully addressing some of the limitations related to the data analysis and giving a semi quantitative insight into the analysis.

Integrating data dependent and data independent non-target screening methods for monitoring emerging contaminants in the Pearl River of Guangdong Province, China

The occurrence of Contaminants of Emerging Concern (CECs) in the Pearl River of Guandong province, China, was characterized using a nontarget screening (NTS) strategy combining both data dependent and data independent acquisition techniques. Our analysis identified 620 unique compounds, including pharmaceuticals (137), pesticides (124), industrial materials (68), personal care products (32), veterinary drugs (27), plasticizers or flame retardants (11), etc. Out of these compounds, 40 CECs were found with a detection frequency of over 60 %, including diazepam, a well-known drug to treat anxiety, insomnia, convulsion, etc., which had the highest detection rate at 98 %. Risk quotients (RQs) were calculated for CECs identified with high confidence (Level 1, confirmed with authentic standards), and it was found that 12 CECs had RQs > 1, with notable concern for pretilachlor (detection frequency: 48 %; 0.8–19.0 ng/L), bensulfuron-methyl (86 %, 3.1–56.2 ng/L), imidacloprid (80 %, 5.3–62.8 ng/L) and thiamethoxam (86 %, 9.1–99.9 ng/L), which exhibited RQs exceeding the threshold of concern (RQ > 1) at 46–80 % of sampling sites. Additionally, tentative identification of potential structurally related compounds provided valuable insight into the parent-product relationships in complex samples. This study highlights the importance and urgency of using NTS for CECs in the environment and presents a novel data sharing approach, which facilitates other scientists to assess, investigate further, and perform retrospective analyses.