From data to reliable conclusions: Identification and comparison of persistent micropollutants and transformation products in 37 wastewater samples by non-target screening prioritization

Instrumental and theoretical advancements in pulsed elution-LC × LC: Investigation of pulse parameters and application to wastewater effluent

Due to the decoupling of the first (1D) and second (2D) dimension in pulsed elution-LC × LC (PE-LC × LC), method development is more flexible and straightforward compared to fast comprehensive LC × LC where the dependencies of key parameters between the two dimensions limits its flexibility. In this study we present a method for pulse generation, which is based on a switching valve alternating between one pump that delivers the gradient and a second pump that delivers low eluotrophic strength for the pause state. Consequently, the dwell volume of the system was circumvented and 7.5, and 3.75 times shorter pulse widths could be generated at flow rates of 0.2, and 0.4 mL/min with satisfactory accuracies between programmed and observed mobile phase composition (relative deviation of 6.0 %). We investigated how key parameters including pulse width and step height, 2D gradient time and flow rate affected the peak capacity in PE-LC × LC. The conditions yielding the highest peak capacity for the PE-LC × LC- high-resolution mass spectrometry (HRMS) system were applied to a wastewater effluent sample. The results were compared to a one dimensional (1D)-LC-HRMS chromatogram. The peak capacity increased with a factor 34 from 112 for the 1D-LC run to 3770 for PE-LC × LC-HRMS after correction for undersampling. The analysis time for PE-LC × LC-HRMS was 12.1 h compared to 67.5 min for the 1D-LC-HRMS run. The purity of the mass spectra improved for PE-LC × LC-HRMS by a factor 2.6 (p-value 3.3 × 10-6) and 2.0 (p-value 2.5 × 10-3) for the low and high collision energy trace compared to the 1D-LC-HRMS analysis. Furthermore, the signal-to-noise ratio (S/N) was 4.2 times higher (range: 0.06-56.7, p-value 3.8 × 10-2) compared to the 1D-LC-HRMS separation based on 42 identified compounds. The improvements in S/N were explained by the lower peak volume obtained in the PE-LC × LC-HRMS.

Non-targeted screening and photolysis transformation of tire-related compounds in roadway runoff

Roadway runoff serves as a crucial pathway for transporting contaminants of emerging concern (CECs) from urban environments to receiving water bodies. Tire-related compounds originating from tire wear particles (TWPs) have been frequently detected, posing a potential ecological threat. Yet, the photolysis of tire-related compounds within roadway runoff remains inadequately acknowledged. Addressing this deficit, our study utilized high-resolution mass spectrometry (HRMS) to characterize the chemical profile of roadway runoff across eight strategically selected sites in Guangzhou, China. 219 chemicals were identified or detected within different confidence levels. Among them, 29 tire-related contaminants were validated with reference standards, including hexa(methoxymethyl)melamine (HMMM), 1,3-diphenylguanidine (DPG), dicyclohexylurea (DCU), and N-cyclohexyl-2-benzothiazol-amine (DCMA). HMMM exhibited with the abundance ranging from 2.30 × 104-3.10 × 106, followed by DPG, 1.69 × 104-8.34 × 106. Runoff sample were exposed to irradiation of 500 W mercury lamp for photodegradation experiment. Photolysis results indicated that tire-related compounds with a low photolysis rate, notably DCU, DCMA, and DPG, are more likely to persist within the runoff. The photolytic rates were significantly correlated with the spatial distribution patterns of these contaminants. Our findings underscore TWPs as a significant source of pollution in water bodies, emphasizing the need for enhanced environmental monitoring and assessment strategies.

Self-Organizing Maps: An AI Tool for Identifying Unexpected Source Signatures in Non-Target Screening Analysis of Urban Wastewater by HPLC-HRMS

(1) Background: Monitoring effluent in water treatment plants has a key role in identifying potential pollutants that might be released into the environment. A non-target analysis approach can be used for identifying unknown substances and source-specific multipollutant signatures. (2) Methods: Urban and industrial wastewater effluent were analyzed by HPLC-HRMS for non-target analysis. The anomalous infiltration of industrial wastewater into urban wastewater was investigated by analyzing the mass spectra data of "unknown common" compounds using principal component analysis (PCA) and the Self-Organizing Map (SOM) AI tool. The outcomes of the models were compared. (3) Results: The outlier detection was more straightforward in the SOM model than in the PCA one. The differences among the samples could not be completely perceived in the PCA model. Moreover, since PCA involves the calculation of new variables based on the original experimental ones, it is not possible to reconstruct a chromatogram that displays the recurring patterns in the urban WTP samples. This can be achieved using the SOM outcomes. (4) Conclusions: When comparing a large number of samples, the SOM AI tool is highly efficient in terms of calculation, visualization, and identifying outliers. Interpreting PCA visualization and outlier detection becomes challenging when dealing with a large sample size.

Phototransformation of Brominated Disinfection Byproducts and Toxicity Elimination in Sunlit-Ozonated Reclaimed Water

Ozonation is universally used during water treatment but can form hazardous brominated disinfection byproducts (Br-DBPs). While sunlight exposure is advised to reduce the risk of Br-DBPs, their phototransformation pathways remain insufficiently understood. Here, sunlight irradiation was found to reduce adsorbable organic bromine by 63%. Applying high-resolution mass spectrometry, the study investigated transformations of dissolved organic matter in sunlit-ozonated reclaimed water, revealing the number and abundance of assigned formulas decreased after irradiation. The Br-DBPs with O/C < 0.6 and MW > 400 Da were decreased or removed after irradiation, with the majority being CHOBr compounds. The peak intensity reduction ratio of CHOBr compounds correlated positively with double bound equivalent minus oxygen ratios but negatively with O/C, suggesting that photo-susceptible CHOBr compounds were highly unsaturated. Mass difference analysis revealed that the photodegradation pathways were mainly oxidation aligned with debromination. Three typical CHOBr molecular structures were resolved, and their photoproducts were proposed. Toxicity estimates indicated decreased toxicity in these photoproducts compared to their parent compounds, in line with experimentally determined values. Our proposed phototransformation pathways for Br-DBPs enhance our comprehension of their degradation and irradiation-induced toxicity reduction in reclaimed water, further illuminating their transformation under sunlight in widespread environmental scenarios.

Quantitative Nontarget Analysis of CECs in Environmental Samples Can Be Improved by Considering All Mass Adducts

Quantitative nontarget analysis (qNTA) for liquid chromatography coupled to high-resolution mass spectrometry enables a more comprehensive assessment of environmental samples. Previous studies have shown that correlations between a compound's ionization efficiency and a range of molecular descriptors can predict the compound's concentration within a factor of 5. In this study, the qNTA approach was further improved by considering all mass adducts instead of only the protonated ion. The model was based on a quantitative structure-property relationship (QSPR), including 216 contaminants of emerging concern (CECs), of which 80 exhibited adduct formation that accounted for >10% of the total peak intensity. When all mass adducts were included, the test set coefficient of determination improved to Q2 = 0.855 compared to Q2 = 0.670 when only the protonated ions were considered (test set median RF error factor 1.6). The inclusion of all adducts was also important to transfer the RF QSPR model reliably. It was assumed that RF variations are sequence-dependent; therefore, a second QSPR model for the prediction of the transferability factor was built for each sequence. For validation, samples were analyzed up to two years apart. The median prediction fold change was 1.74 for analytical standards (63 compounds) and 2.4 for enriched wastewater effluent samples (41 compounds), with 80% of the compounds predicted within a fold change of 2.4 and 3.3, respectively. The model was also validated on a second instrument, where 80% of the 26 compounds in wastewater effluent were predicted within a factor of 3.8.

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Supercritical Fluid Chromatography Coupled to High-Resolution Mass Spectrometry Reveals Persistent Mobile Organic Compounds with Unknown Toxicity in Wastewater Effluents

Broad screening approaches for monitoring wastewater are normally based on reversed-phase liquid chromatography (LC) coupled to high-resolution mass spectrometry (HRMS). This method is not sufficient for the very polar micropollutants, neglected in the past due to a lack of suitable analytical methods. In this study, we used supercritical fluid chromatography (SFC) to detect very polar and yet-undetected micropollutants in wastewater effluents. We tentatively identified 85 compounds, whereas 18 have only rarely been detected and 11 have not previously been detected in wastewater effluents such as 17α-hydroxypregnenolone, a likely transformation product (TP) of steroids, and 1H-indole-3-carboxamide, a likely TP from new synthetic cannabinoids. Suspect screening of 25 effluent wastewater samples from 8 wastewater treatment plants revealed several distinct potential pollution sources such as a pharmaceutical company and a golf court. The analysis of the same samples with LC-HRMS showed clearly how SFC increases the ionization efficiency for low-molecular-weight micropollutants (m/z < 300 Da) by a factor 2 to 87 times, which significantly improved the mass spectra for identifying very polar compounds. In order to assess which micropollutants might be of environmental concern, literature and toxicological databases were screened. There was a lack of available hazard and bio-activity data for regulatory-relevant in vitro and in vivo assays for >50% of the micropollutants. Especially, 70% of the data were lacking for the whole organism (in vivo) tests.

Nontargeted Screening in Environmental Analysis: An Example Showing Migration of Chemicals from Reusable Sports Plastic Bottles into Drinking Water

In this extended special feature to celebrate the 35th anniversary edition of LCGC Europe, leading figures from the separation science community explore contemporary trends in separation science and identify possible future developments.