An adaptive Monte Carlo method for evaluating uncertainty in confidence level of non-targeted principal component analysis classification

Quality control of spectroscopic data in non-targeted analysis – Development of a multivariate control chart

(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.

The GUM Supplement 1 presented the adaptive Monte Carlo (AMC) method. A basic implementation of an AMC procedure involves carrying out an increasing number of Monte Carlo trials until four parameters have stabilized in a statistical sense. Although the AMC method has been successfully used for uncertainty evaluations, the amount of stored data was seen as significant, and even after achieving stability, it can be lost with the increase in the number of trials. To overcome these problems, two modifications to the AMC method were proposed, implemented and validated. The first is related to data storage, while the second consists of applying an alternative criterion to assess convergence. After modifications, the AMC was named the modified adaptive Monte Carlo (MAMC) method and was applied when estimating the uncertainty of measurements carried out with a micrometer. The MAMC effectiveness was validated through the comparison of the uncertainty values and those from the application of the GUM and AMC methods. Under the evaluated experimental conditions, the MAMC showed greater repeatability when compared to AMC, regarding the number of trials to be carried out. This factor contributes toward the higher reliability of this method. The amount of data to be stored and manipulated through the application of the MAMC method was decreased significantly. This fact may increase the adoption of the AMC method.

Advanced wastewater treatment such as powdered activated carbon (PAC) reduces the load of organic micropollutants entering the aquatic environment. Since mobile and persistent compounds accumulate in water cycles, treatment strategies need to be evaluated for the removal of (very) polar compounds. Thereby, non-targeted analysis gives a global picture of the molecular fingerprint (including these very polar molecules) of water samples. Target and non-target screening were conducted using polarity-extended chromatography hyphenated with mass spectrometry. Samples treated with different types and concentrations of PAC were compared to untreated samples. Molecular features were extracted from the analytical data to determine fold changes, perform a principal component analysis and for significance testing. The results suggest that a part of the polar target analytes was adsorbed but also some byproducts might be formed or desorbed from the PAC.

An integrated non-targeted and targeted analysis approach for identification of semi-volatile organic compounds in indoor dust

Non-targeted analysis (NTA) methods are widely used for chemical discovery but seldom employed for quantitation due to a lack of robust methods to estimate chemical concentrations with confidence limits. Herein, we present and evaluate new statistical methods for quantitative NTA (qNTA) using high-resolution mass spectrometry (HRMS) data from EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). Experimental intensities of ENTACT analytes were observed at multiple concentrations using a semi-automated NTA workflow. Chemical concentrations and corresponding confidence limits were first estimated using traditional calibration curves. Two qNTA estimation methods were then implemented using experimental response factor (RF) data (where RF = intensity/concentration). The bounded response factor method used a non-parametric bootstrap procedure to estimate select quantiles of training set RF distributions. Quantile estimates then were applied to test set HRMS intensities to inversely estimate concentrations with confidence limits. The ionization efficiency estimation method restricted the distribution of likely RFs for each analyte using ionization efficiency predictions. Given the intended future use for chemical risk characterization, predicted upper confidence limits (protective values) were compared to known chemical concentrations. Using traditional calibration curves, 95% of upper confidence limits were within ~tenfold of the true concentrations. The error increased to ~60-fold (ESI+) and ~120-fold (ESI-) for the ionization efficiency estimation method and to ~150-fold (ESI+) and ~130-fold (ESI-) for the bounded response factor method. This work demonstrates successful implementation of confidence limit estimation strategies to support qNTA studies and marks a crucial step towards translating NTA data in a risk-based context.

The increasing worldwide release of anthropogenic chemicals compounds into the aquatic ecosystems has led serious contamination of freshwater resources.  This study investigated the chemical composition of the water and sediments of L'Albufera Natural Park, Valencia, Spain, an area heavily impacted by intensive agriculture, surrounded by an industrial belt, highly urbanized and historically polluted. The goal was to assess the different water sources and anthropogenic influence in this managed area using nontarget analysis (NTA) combined with high-resolution mass spectrometry (HRMS). Surface water and sediment samples were collected from 51 sites during two sampling events in the May/June 2019 and September/October 2019. These two periods were selected because the most relevant crop in the area are rice fields and these two periods coincides with the starting of the cultivation and the harvest. The HRMS data was processed using Compound Discoverer™ version 3.3, and the results were analyzed using Principal Component Analysis (PCA). Agricultural practices are one of the most important sources of contaminants (mostly pesticides) including at concentrations >100 ng L-1 acetamiprid, azoxystrobin, chlorfenvinfos, chlorpyrifos, difenoconazole, dimethoate, fluvalinate, imazalil, imidacloprid, omethoate, propazine, tebuconazole, terbumeton deethyl, terbuthylazine, thiabendazole and tricyclazole. Increased presence and intensity of organic contaminants along the waterway was observed, indicating significant anthropogenic influence in the area. The NTA and post-processing were evaluated for reproducibility, demonstrating robustness with a 71.2% average reproducibility for compounds detected the 2 sampling trips. A detection frequency of 80% was the set criterion for detected compounds suggested as tracers. To prioritize samples, hierarchical cluster analysis was employed, and potential tracers for each water source were determined. Additionally, urban-influenced contaminants such as insect repellents, pharmaceuticals, and non-agricultural herbicides were identified along the channels that transports treated wastewater to the Natural Park. This study highlights the impact of human activities on L’Albufera Natural Park and demonstrates the effectiveness of NTA in differentiating and tracking water sources. The results emphasize the importance of reproducibility in NTA and provide guidance on implementing monitoring strategies by prioritizing samples based on chemical compositions.

The present study has generated a workflow based on nontarget analysis (NTA) with Compound Discoverer Ver 3.1 to characterize a set of source-discriminating compounds identified in water samples from locations in South Florida (USA), particularly those describing a freshwater environment (Everglades based), urban impacted areas (septic tank driven), and coastal (Biscayne Bay) endmembers in and around the Charles Deering Estate property in the Village of Palmetto Bay. Waters from an interconnected managed canal system were assessed to evaluate the influence of localized emissions. Septic tank effluents influence the water in many Southeast Florida environments due to their diminished onsite treatment capacity based on the limestone-dominated geology and canal systems providing a relatively unobstructed connection pathway. Through a combination of high-resolution mass spectrometry and statistical analyses, a set of tracers and indicators was determined (azelaic acid, decanophenone, galaxolidone, methyl violet, monoolein, metoprolol, and 1-stearoylglycerol). Tentatively identified compounds were generally assigned to various categories such as dyes, personal care products, and pharmaceuticals. The NTA Compound Discoverer Ver 3.1 compound data (presented as principal component analysis and Kendrick mass defect plots) showed apparent differences between wastewater-influenced sites and non-wastewater-influenced sites along with the ranked "Top10" compounds found at each location. Waters from different locations were also compared using the presence of sucralose to further inform the NTA. The most septic-influenced site contained 3594 ± 94 ng/L of sucralose with concentrations declining steadily and reaching the lowest concentrations in Biscayne Bay of 122 ± 94 ng/L. The sucralose concentrations provided further evidence of septic influence on this system. Sucralose was determined to be a conservative tracer between the freshwater and coastal sources and complementary to other probable unique tracers of septic tank effluent identified by the NTA. Environ Toxicol Chem 2022;41:1165-1178. © 2022 SETAC.

Nontarget analysis has gained prominence in screening novel perfluoroalkyl and polyfluoroalkyl substances (PFASs) in the environment, yet remaining limited in human biological matrices. In this study, 155 whole blood samples were collected from the general population in Shijiazhuang City, China. By nontarget analysis, 31 legacy and novel PFASs were assigned with the confidence level of 3 or above. For the first time, 11 PFASs were identified in human blood, including C1 and C3 perfluoroalkyl sulfonic acids (PFSAs), C4 ether PFSA, C8 ether perfluoroalkyl carboxylic acid (ether PFCA), C4-5 unsaturated perfluoroalkyl alcohols, C9-10 carboxylic acid-perfluoroalkyl sulfonamides (CA-PFSMs), and C1 perfluoroalkyl sulfonamide. It is surprising that the targeted PFASs were the highest in the suburban population which was impacted by industrial emission, while the novel PFASs identified by nontarget analysis, such as C1 PFSA and C9-11 CA-PFSMs, were the highest in the rural population who often drank contaminated groundwater. Combining the toxicity prediction results of the bioaccumulation potential, lethality to rats, and binding affinity to target proteins, C3 PFSA, C4 and C7 ether PFSAs, and C9-11 CA-PFSMs exhibit great health risks. These findings emphasize the necessity of broadening nontarget analysis in assessing the PFAS exposure risks, particularly in rural populations.

Discrimination of Brazilian green canephora coffee beans by ultraviolet–visible spectroscopy as a non-target analysis: A tool for recognizing geographical indications

Per- and polyfluoroalkyl substances (PFAS) have carcinogenic potential but are understudied in relation to childhood cancers. We examined associations between targeted and non-targeted PFAS measured in newborn dried blood spots (DBS) and the risk of childhood acute lymphoblastic leukemia (ALL) in Los Angeles County, California, accounting for maternal and child characteristics. ALL cases (n = 125) diagnosed before age 18 years during 2000-2015 and controls (n = 219) were selected from a registry-based study using stratified sampling based on birth year and birth address within a PFAS-contaminated water district according to the USEPA Third Unregulated Contaminant Monitoring Rule. We calculated design-based odds ratios (OR) and 95% confidence intervals (CI) for the effect of PFAS exposures, independently and adjusting for other PFAS. We also conducted non-linear and stratified analyses. Of the 17 PFAS quantified using targeted analysis, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) had the highest mean concentrations in DBS, with 4690 and 10,307 pg/g dried blood among cases compared to 4245 and 8142 pg/g dried blood among controls, respectively. The highest risks were observed for the 4th exposure quartile compared with the 1st quartile (PFOA OR = 1.56, CI: 0.42, 5.73; PFOS OR = 1.64, CI: 0.44, 6.14). In non-linear statistical analyses of joint PFOA and PFOS exposures adjusted for other detected PFAS, we also found that ALL risk increased with increasing levels of log2-PFOA and log2-PFOS. Non-targeted analysis identified 26 additional PFAS, for which elevated risk of childhood ALL was associated with a doubling of C4HF7O3 exposure (OR = 5.04, CI: 1.08, 23.63) and the highest quartile of C10HF19O5 exposure (OR = 5.20, CI: 1.15, 23.56). Associations were generally stronger among non-Hispanic participants compared to Hispanic participants, but these analyses were limited by small sample sizes and should be considered exploratory. There was some suggestion that high PFOA and PFOS exposures measured at birth, as well as certain PFAS detected by non-targeted approaches, were related to childhood ALL risk. This study of childhood ALL in Los Angeles County, California found increased risk among children with the highest PFOA and PFOS levels measured in neonatal dried blood spots. These risks were stronger among non-Hispanic children, and the greatest risk was observed for joint PFOA and PFOS exposure adjusting for other detected PFAS and maternal/child characteristics. We also observed possible associations with PFAS discovered by non-targeted analysis. Our results highlight the utility of dried blood spots as a matrix for assessing early life exposures as well as the value of hybrid targeted and non-targeted approaches to measure PFAS in health studies.

"Daqu" is a fermentation starter and substrate complex that is used to initiate fermentations for the production of Chinese liquor (alcoholic spirit). Several different types of Daqu are customary used, having different flavours, i.e. light, strong, or sauce flavor. With the aim to develop objective methods to characterize and distinguish such different types of Daqu, nontargeted analyses of extracts from three typical flavor types of Daqu were carried out using (1)H nuclear magnetic resonance (NMR) spectroscopy. A significant separation of spectra of Daqu of light-flavor, strong-flavor and sauce-flavor types was achieved using principal components analysis. The separation could be attributed to higher levels of glycerol, malate, acetate and N-acetylglutamine in light-flavor Daqu; higher levels of mannitol, betaine, trimethylamine and pyroglutamate in strong-flavor Daqu; and higher levels of lactate, isoleucine, leucine, isovalerate and valine in sauce-flavor Daqu. These metabolites were regarded as the representative metabolites or biomarkers characteristic for each type of Daqu and could be associated with some of the microorganisms that have been reported in Daqu. This study highlights the application of nontargeted analysis techniques based on NMR in process research and quality control in Daqu production and liquor fermentation.

Specific targeted quantification combined with non-targeted metabolite profiling for quality evaluation of Gastrodia elata tubers from different geographical origins and cultivars

Non-targeted analysis is the determination of the chemical composition of a complex mixture without a priori knowledge regarding the identities or quantities of the compound. These techniques can be performed in a wide variety of materials and areas of study. Methods and results between laboratories can vary widely based on the compounds of interest and user expertise, which can cause poor interlaboratory comparability of non-targeted results. To address this knowledge gap, three research grade test materials were developed to allow for the comparison of instrument methods, specifically reversed-phase liquid chromatography with positive electrospray ionization mass spectrometry. The materials were shipped to thirty-one participating laboratories to be analyzed by their own non-targeted analysis instrumental method. Of the participants, twenty-three laboratories submitted good quality datasets and could be further evaluated. Using principal components analysis, the differences and similarities of the analytical methods could be examined. Overall, there were no obvious trends or associations between the methods of different laboratories and the review of the principal components analysis revealed no notable parameters that caused significant clustering or separation.

Unraveling the chemical fingerprint of the Miami River sources: Insights from high-resolution mass spectrometry and nontarget analysis