Occurrences of microorganic pollutants in the Kumho River by a comprehensive target analysis using LC-Q/TOF-MS with sequential window acquisition of all theoretical fragment ion spectra (SWATH)

Unlocking the future potential of SWATH-MS: Advancing non-target screening workflow for the qualitative and quantitative analysis of emerging contaminants

SWATH-MS offers a robust data-independent acquisition method for complex proteomics and metabolomics. This study presents a detailed non-target screening workflow utilizing SWATH-MS to detect and analyze emerging contaminants (ECs) in aquatic environments. Our workflow, covering peak picking, alignment, prioritization, structure identification, and quantification, effectively identified all qualifying peaks from 298 standard compounds with different concentrations, discarding any that did not meet the criteria. In extracts of real water samples spiked at 100 and 10 ng/mL, our workflow prioritized 2083 and 1328 features, respectively. Following structure identification, these features were assigned confidence levels ranging from 1 to 5. Of these, 215 and 92 spiked standards achieved level 1. The remaining standards were not recognized as level 1 due to low intensities or poor peak shapes that failed to meet certain criteria. Additionally, using fragment ion peak areas for quantification significantly improved the linearity of standard curves, enhancing R2 values for ∼63 % of the standards. Incorporating fragment ion data improved quantification accuracy, increasing compounds within the 80 %-120 % range from 78 % to 90 % at 100 ng/mL and within the 50 %-150 % range from 36 % to 69 % at 10 ng/mL. These findings underscore SWATH-MS's potential to enhance monitoring of ECs and ecological risk assessments, providing critical insights for environmental management.

Assessment of occurrence, source appointment, and ecological risks of pharmaceuticals and personal care products in the water-sediment interface of Qiantang River in the Hangzhou region

Pharmaceuticals and personal care products (PPCPs) have received global attention owing to their potential risks to human health and the ecological environment. However, limited research has explored the occurrence and ecological risks of PPCPs in the Qiantang River (QTR). QTR, the largest water system in Zhejiang Province, China, is significantly influenced by human activities. This study investigated the occurrence, distribution, and ecological risks of 10 types of PPCPs in both surface water and sediment within QTR. The findings revealed that the concentrations of PPCPs detected in surface water ranged from 81.26 to 149.45 ng L-1 during the wet season (April) and from 98.66 to 198.55 ng L-1 during the dry season (September). Moreover, in the sediments, PPCP concentration ranged from 63.24 to 80.66 and 72.54 to 75.06 ng per g dw during both wet and dry seasons, respectively. Among the selected PPCPs, triclosan (TCS) exhibited the highest concentration across, different phases and seasons, followed by benzotriazole in surface water. The analysis of sediment-water equilibrium distribution indicated that the diffusion tendency of PPCPs was closely correlated with their molecular weights. Particularly, TCS exhibited dynamic equilibrium between water and sediment. Principal component analysis and positive matrix factorization model results indicated similar pollution sources for the detected PPCPs. The dominant sources of the detected PPCPs were identified as wastewater of electroplating enterprises, discharge from wastewater treatment plants, and domestic sewage. The ecological risk assessment based on the risk quotient method revealed that TCS with the highest detected concentration posed a high risk in surface water and a low risk in sediment across all sampling sites. However, other detected PPCPs showed either no or low risks. Additionally, PPCPs showed a higher ecological risk during the dry season than during the wet season.

Proposal for priority emerging pollutants in the Nakdong river, Korea: Application of EU watch list mechanisms

The Nakdong River, the longest in Korea, has received numerous pollutants from heavily industrialized and densely populated areas while being used as a drinking water source. A number of research have reported occurrences of emerging pollutants (EPs) in the river. The results requested efficient monitoring and systematic management strategies such as EU watch list under Water Framework Directive. The aim of this study is to propose a watch list through preliminary monitoring of the river and risk-based prioritization approach. As candidates for monitoring target, 632 substances were selected based on literature and database searches. Among them, 175 substances were subjected to target screening method whereas 457 were evaluated via suspect screening. A risk-based prioritization was applied to substances quantified through target screening based on concentrations, and a scoring-based prioritization was applied to substances tentatively identified through suspect screening. Sampling campaigns (n = 12) were conducted from October 2020 to September 2021, at 8 sampling sites along the river. As a result, 130 target substances were quantified above the LOQ. Among the 21 substances whose priority score was assigned through risk-based prioritization, telmisartan and iprobenfos were identified with very high environmental risk while candesartan, TBEP, imidacloprid, azithromycin and clotrimazole were classified with high or intermediate risk. As result of the scoring system for 39 tentatively identified substances, 6 substances (benzophenone, caprolactam, metolachlor oxanilic acid, heptaethylene glycol, octaethylene glycol and pentaethylene glycol), which were then confirmed with reference standards, showed a potential environmental risk. Those substances prioritized through target and suspect screening followed by scoring systems can be a subset for the watch list and potential targets for nationwide water quality monitoring program in the future.

Transgenerational effects of benzotriazole on the gene expression, growth, and reproduction of Daphnia magna

Due to its widespread and intensive use as a corrosion inhibitor, benzotriazole is ubiquitously detected from a few parts per billion to several hundred parts per million in aquatic environments. The long-term toxicity of benzotriazole is unclear despite its low acute toxicity. Therefore, we investigated the transgenerational effects of benzotriazole at the genomic and individual levels using the freshwater zooplankton Daphnia magna. Maternal exposure to sublethal concentrations (15 and 30 mg/L) of benzotriazole exerted transgenerational effects on D. magna at the genomic and individual levels even in descendants that have never been exposed to benzotriazole. Significant alterations in the expression of Cyp, GST, Vtg1, and Hb and in neonate size were observed in the unexposed F3 generation, confirming the transgenerational effect of benzotriazole. Interestingly, detoxification related genes Cyp and GST were unaffected or downregulated in the exposed generation but upregulated in the following unexposed generations. Furthermore, continuous multigenerational exposure to an environmental concentration (4.3 μg/L) of benzotriazole also upregulated detoxification genes in decent generations but exerted no individual-level effects in subsequent generations.

Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers

Mass spectrometry (MS) is one of the most widely used analytical techniques in many fields. Recent developments in chemical and biological researches have drawn much attention to the measurement of substances with low abundances in samples. Continuous efforts have been made consequently to further improve the sensitivity of MS. Modifications on the mass analyzers of mass spectrometers offer a direct, universal and practical way to obtain higher sensitivity. This review provides a comprehensive overview of the latest developments in mass analyzers for the improvement of mass spectrometers' sensitivity, including quadrupole, ion trap, time-of-flight (TOF) and Fourier transform ion cyclotron (FT-ICR), as well as different combinations of these mass analyzers. The advantages and limitations of different mass analyzers and their combinations are compared and discussed. This review provides guidance to the selection of suitable mass spectrometers in chemical and biological analytical applications. It is also beneficial to the development of novel mass spectrometers.

Concentrations and distributions of neonicotinoids in drinking water treatment plants in South Korea

We investigated the fates of seven neonicotinoids (NNIs) in full-scale drinking water treatment plants and assessed human exposure to NNIs through consuming drinking water. The total NNI concentrations in raw water and treated water samples from the drinking water treatment plants were 20.4-166 ng/L (median 118 ng/L) and 1.11-94.7 ng/L (median 20.4 ng/L), respectively. The dinotefuran (DIN) concentrations in raw water collected in different seasons were different, and the highest DIN concentration was found in summer. The drinking water treatment processes removed >91% of the NNIs except DIN and thiamethoxam (THIAM), for which the mean removal rates were 70% and 74%, respectively. The removal rates for all of the NNIs were higher for the granular activated carbon filtration process (mean 83.5%) than the other drinking water treatment plant processes (coagulation/sedimentation 22.3%, ozonation 29.2%). However, the removal rates in the granular activated carbon process were lower for DIN and THIAM (61.0% and 59.2%, respectively) than the other NNIs. Significant correlations were found between the NNI removal rates and physicochemical properties (solubility in water and log (octanol-water partition coefficient)). The estimated mean human exposure to NNIs in drinking water was 0.528 ng/(kg body weight d).

Occurrence and risk assessment of herbicides and fungicides in atmospheric particulate matter in Hanoi, Vietnam

Vietnam is a Southeast Asian developing country with rapidly increasing air pollution, especially in large cities. Over 350,000 chemicals and chemical mixtures are produced and used in Vietnam; however, the country has only implemented air quality standards for 44 substances, which are primarily focused on inorganic and volatile organic compounds. Although numerous pesticides are frequently applied across large cities in Vietnam, information on their concentrations in atmospheric particulate matter (APM) is limited. Therefore, to investigate their occurrence and health effects, 187 pesticides in APM were screened using the liquid chromatography-mass spectrometry-quadrupole time of flight- Sequential Window Acquisition of All Theoretical Fragment Ion Spectra method (LC-QTOF-MS-SWATH). A total of 22 pesticides (16 fungicides and 6 herbicides) were quantified in the dry and rainy seasons. Among them, 19 substances were quantified in APM for the first time in Vietnam. Their median total concentrations in the dry season were higher than those in the rainy season, and the concentrations in the daytime were one-third of the night-time concentrations in both seasons. Their total levels ranged from 0.82 to 21.1 ng m^-3 (median, 3.63 ng m^-3), the detection frequencies of 9 pesticides were higher than 70%, and 7-14 pesticides were detected per sample (median, 10). Some of the detected pesticides were likely sourced from their prevalent use in amenity turf protection (e.g., in parks and public roads) and weed control (e.g., in gardens, floriculture, and agriculture). The total daily intake (DI_air) values for adults, children, and infants were 8.17E-06, 2.06E-05, and 2.45E-05 mg kg^-1 d^-1, respectively, and the highest Hazard Quotients (HQs) were 4.81E-04, 1.22E-03, and 1.44E-03, respectively. All HQs and HIs of the pesticides were < 1 for all population groups (adults, children, and infants), indicating negligible exposure risks.

Comprehensive study of insecticides in atmospheric particulate matter in Hanoi, Vietnam: Occurrences and human risk assessment

Air pollution is the most serious environmental issue in Vietnam, particularly in big cities. Air pollutants that are set as environmental standards are regularly monitored by the public institutions. Whereas, environmental data on organic micro-pollutants in atmospheric particulate matters (APMs) is limited, including PAHs and POPs. Although massive pesticides are used in big cities, their data in APMs in Vietnam is very scarce. In order to elucidate their occurrence in the ambient air in Hanoi and their health effects, we surveyed 107 insecticides in APMs by a novel target screening method using LC-QTOF-MS-SWATH. A total of 19 insecticides were detected in the dry and the rainy seasons. Among them, 16 substances are, to our knowledge, reported for the first time in the literature. Their total concentrations varied from 0.47 to 27.0 ng m^-3 (median, 3.6 ng m^-3), detection frequencies of 12 compounds are higher than 42%, and the number of insecticides detected per each sample ranging from 5 to 13 (median, 9). Total concentrations in the dry season were generally higher than in the rainy season, and concentrations at night were higher than daytime in both seasons. The level of insecticides depends not only on the season, but also on its physicochemical properties, its application conditions, and the meteorological conditions. Their emission sources could be related to agricultural usage, floricultural activities, and pest control in houses. The total maximum daily intake (DI_air) through inhalation for adults and children were 2.39E-05 mg kg^-1 d^-1 and 2.98E-05 mg kg^-1 d^-1, respectively. The highest Hazard Quotients (HQs) were 1.34E-03 and 3.37E-03, and the highest Hazard Indices (HIs) were 2.71E-03 and 6.33E-03 for adults and children, respectively. All values of HQs, and HIs of insecticides were less than 1, indicating that health risk would be negligible.

Replacing the internal standard to estimate micropollutants using deep and machine learning

Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquatic and ecological environmental systems. These pollutants have the propensity to wreak havoc on human health and the ecological system; hence, it is important to persistently monitor micropollutants in the environment. Micropollutants are commonly quantified via target analysis using high resolution mass spectrometry and the stable isotope labeled (SIL) standard. However, the cost-intensiveness of this standard presents a major obstacle in measuring micropollutants. This study resolved this problem by developing data-driven models, including deep learning (DL) and machine learning (ML), to estimate the concentration of micropollutants without resorting to the SIL standard. Our study hypothesized that natural organic matter (NOM) could replace internal standards if there was a specific mass spectrum (MS) subset, including NOM information, which correlated with an SIL standard peak. Therefore, we analyzed the MS to find the specific MS subsets for replacing the SIL standard peak. Thirty-five alternative MS subsets were determined for applying DL and ML as input data. Thereafter, we trained four different DL models, namely, ResNet101, GoogLeNet, VGG16, and Inception v3, as well as three different ML models, i.e., random forest (RF), support vector machine (SVM), and artificial neural network (ANN). A total of 680 MS data were used for the model training to estimate five different micropollutants, namely Sulpiride, Metformin, and Benzotriazole. Among the DL models, ResNet 101 exhibited the highest model performance, showing that the average validation R² and MSE were 0.84 and 0.26 ng/L, respectively, while RF was the best in the ML models, manifesting R² and MSE values of 0.69 and 0.58 ng/L. The trained models showed accurate training and validation results for the estimation of the five micropollutant concentrations. Therefore, this study demonstrates that the suggested analysis has a potential for alternative micropollutant measurement that has rapid and economic vantages.