Patterns of Personal Exposure to Urban Pollutants Using Personal Passive Samplers and GC × GC/ToF-MS

Determining personal exposure to high production volume chemicals (HPVCs) and polycyclic aromatic hydrocarbons (PAHs) with silicone wristbands: A pilot study

High production volume chemicals (HPVCs) and polycyclic aromatic hydrocarbons (PAHs) are semi-volatile organic compounds (semi-VOCs) of great environmental concern because of their presence worldwide and health problems resulting from long-term exposure to some of them. It is essential to have robust analytical methods to monitor the concentrations of these compounds not only in environmental samples but also individual exposure. In this pilot study we develop and validate a multiresidue analytical method based on ultrasound-assisted extraction and gas-chromatography mass spectrometry for the simultaneous determination of 56 semi-VOCs using silicone wristbands (SWBs) as personal passive samplers. The developed method provided recoveries between 43% and 114% on sampled SWBs and method detection and quantification limits in the range of 0.1-35 ng/g and 0.3-119 ng/g, respectively. A preliminary study was performed with a small group of adults living in the industrial city of Tarragona (north-eastern Spain) to evaluate the applicability of SWBs for monitoring individual exposure to the studied HPVCs and PAHs. Benzothiazoles, benzenesulfonamides, UV stabilisers and phenolic antioxidants were determined for the first time in SWBs. Phthalates (PAEs), stood out above the rest, accounting for 52% of the total concentrations. Diethylhexyl phthalate was the compound found at the highest concentrations with values between 1.1 and 82 μg/g. Carcinogenic and non-carcinogenic dermal risk assessment was performed for adults and considering two scenarios (low and high). PAHs were the compounds with the highest carcinogenic and non-carcinogenic dermal risk regardless of the exposure scenario. The second family of compounds that contributed the most to the total risk were PAEs but high punctual concentrations of these compounds caused significant differences between exposure scenarios.

Biomonitoring of particulate matter and volatile organic compounds using honey bees and their products. A contemporary overview

Airborne pollutants like particulate matter and volatile organic compounds can negatively impact microbial, plant, and animal life as well as human health. Traditional environmental monitoring, while crucial, often relies on expensive equipment at limited locations, leading to gaps in geographical coverage. To obtain a low-cost, easily deployed environmental monitoring grid, the use of European honey bees (Apis mellifera) as biomonitor can offer a promising alternative. Their extensive foraging in the landscape exposes them to environmental contaminants like particulate matter and organic compounds. Once collected, these pollutants are carried back into the hives, where they can subsequently be sampled and quantified using various techniques. This potentially makes honey bee colonies a cost-effective and valuable long-term monitoring tool for particulate matter and organic compounds. This review, through the critical insight of the most recent pertinent literature, explores the suitability of honey bees and their products as biomarkers for environmental monitoring of these pollutants, addressing sample preparation approaches and chemical analytical methods. Overall, the presented information will aid researchers in initiating further investigations in this pivotal field, incorporating additional chemicals and innovative, non-invasive sampling matrices compatible with the beehive environment.

Assessment of silicone wristbands for monitoring personal exposure to chlorinated paraffins (C8-36): A pilot study

Chlorinated paraffins (CPs) are a major environmental concern due to their ubiquitous presence in the environment. Since human exposure to CPs can significantly differ among individuals, it is essential to have an effective tool for monitoring personal exposure to CPs. In this pilot study, silicone wristbands (SWBs) were employed as a personal passive sampler to measure time-weighted average exposure to CPs. Twelve participants were asked to wear a pre-cleaned wristband for a week during the summer of 2022, and three field samplers (FSs) in different micro-environments were also deployed. The samples were then analyzed for CP homologs by LC-Q-TOFMS. In worn SWBs, the median concentrations of quantifiable CP classes were 19 ng/g wb, 110 ng/g wb, and 13 ng/g wb for ∑SCCPs, ∑MCCPs, and ∑LCCPs (C_18-20), respectively. For the first time, lipid content is reported in worn SWBs, which could be a potential impact factor in the kinetics of the accumulation process for CPs. Results showed that micro-environments were key contributors to dermal exposure to CPs, while a few outliers suggested other sources of exposure. CP exposure via dermal contact showed an increased contribution and thus poses a nonnegligible potential risk to humans in daily life. Results presented here provide proof of concept of the use of SWBs as a cheap and non-invasive personal sampler in exposure studies.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions

PURPOSE OF REVIEW

We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale.

RECENT FINDINGS

Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction

Mobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection step performed using the multivariate adaptive regression splines (MARS) tool. Although RT was found to be the most important, according to Kruskal-Wallis ANOVA analysis, it is insufficient to build a robust model, which justifies the need to expand the input layer with 2D descriptors. Therefore the following molecular descriptors: MPC10, WTPT-2, AATS8s, minaaCH, GATS7c, RotBtFrac, ATSC7v and ATSC1p, which were characterized by a high predicting potential were used to improve the classification performance. As a result of machine learning procedure ten of the most accurate neural networks were selected. The external validation showed that the final models are characterized by a high general accuracy score (85.71-96.43%). The high predicting abilities were also confirmed by the micro-averaged Matthews correlation coefficient (MAMCC) (0.73-0.88). To evaluate the applicability of the models, new retention times of selected POPs and EPs including pesticides, polycyclic aromatic hydrocarbons, pharmaceuticals, fragrances and personal care products were measured and used for mobility prediction. Further, the classifiers were used for photodegradation and chlorination products of two popular sunscreen agents, 2-ethyl-hexyl-4-methoxycinnamate and 2-ethylhexyl 4-(dimethylamino)benzoate.

Personal air pollutant exposure monitoring in South African children in the VHEMBE birth cohort

The burden of disease associated with environmental exposures disproportionately impacts residents of low- and middle-income countries. Children living in rural regions of these countries may experience higher exposure to insecticides from indoor residual spraying used for malaria control and household air pollution. This study evaluated environmental exposures of children living in a rural region of South Africa. Quantifying exposure levels and identifying characteristics that are associated with exposure in this geographic region has been challenging due to limitations with available monitoring techniques. Wearable passive samplers have recently been shown to be a convenient and reliable tool for assessing personal exposures. In this study, a passive sampler wristband, known as Fresh Air wristband, was worn by 49 children (five-years of age) residing in the Limpopo province of South Africa. The study leveraged ongoing research within the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE) birth cohort. A wide range of chemicals (35 in total) were detected using the wristbands, including polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides, phthalates, and organophosphate esters (OPEs) flame retardants. Higher concentrations of PAHs were observed among children from households that fell below the food poverty threshold, did not have access to electric cookstoves/burners, or reported longer times of cooking or burning materials during the sampling period. Concentrations of p,p'-DDD and p,p'-DDT were also found to be elevated for children from households falling below the food poverty threshold as well as for children whose households were sprayed for malaria control within the previous 1.5 years. This study demonstrates the feasibility of using passive sampler wristbands as a non-invasive method for personal exposure assessment of children in rural regions of South Africa to complex mixtures environmental contaminants derived from a combination of sources. Future studies are needed to further identify and understand the effects of airborne environmental contaminants on childhood development and strategies to mitigate exposures.

Silicone wristbands as personal passive sampling devices: Current knowledge, recommendations for use, and future directions

Personal chemical exposure assessment is necessary to determine the frequency and magnitude of individual chemical exposures, especially since chemicals present in everyday environments may lead to adverse health outcomes. In the last decade, silicone wristbands have emerged as a new chemical exposure assessment tool and have since been utilized for assessing personal exposure to a wide range of chemicals in a variety of populations. Silicone wristbands can be powerful tools for quantifying personal exposure to chemical mixtures in a single sample, associating exposure with health outcomes, and potentially overcoming some of the challenges associated with quantifying the chemical exposome. However, as their popularity grows, it is crucial that they are used in the appropriate context and within the limits of the technology. This review serves as a guide for researchers interested in utilizing silicone wristbands as a personal exposure assessment tool. Along with briefly discussing the passive sampling theory behind silicone wristbands, this review performs an in-depth comparison of wristbands to other common exposure assessment tools, including biomarkers of exposure measured in biospecimens, and evaluates their utility in exposure assessments and epidemiological studies. Finally, this review includes recommendations for utilizing silicone wristbands to evaluate personal chemical exposure and provides suggestions on what research is needed to recognize silicone wristbands as a premier chemical exposure assessment tool.

Simulating comprehensive two-dimensional gas chromatography mass spectrometry data with realistic run-to-run shifting to evaluate the robustness of tile-based Fisher ratio analysis

Untargeted analysis of comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data has the potential to be hindered by run-to-run retention time shifting. To address this challenge, tile-based Fisher ratio (F-ratio) analysis (FRA) has been developed, which utilizes a supervised, untargeted approach involving a chromatographic segmentation routine termed "tiling" combined with the ANOVA F-ratio statistic to discover class-distinguishing analytes while minimizing false positives arising from shifting. The tiling algorithm is designed to account for retention shifting in both separation dimensions. Although applications of FRA have been reported, there remains a need to thoroughly evaluate the robustness of FRA for different levels of run-to-run retention shifting in order to broaden the scope of its application. To this end, a novel method of simulating GC×GC-TOFMS chromatograms with realistic run-to-run shifting is presented by random generation of low-frequency "shift functions". The dimensionless retention-time precision, <δ_r>, which is four times the standard deviation in retention time normalized to the peak width-at-base is used as a key modeling variable along with the 2D chromatographic saturation, α_e,2D, and within-class relative standard deviation in peak area, RSD_wc. We demonstrate that all three of these variables operate together to impact true positive discovery. To quantify the "success" of true positive discovery, GC×GC-TOFMS datasets for various combinations of <δ_r>, α_e,2D, and RSD_wc were simulated and then analyzed by FRA using a wide range of relative tile areas (RTA), which is a dimensionless measure of tile size. Since each hit in the FRA hit list was known a priori as either a true or false positive based on the simulation inputs, receiver operating characteristic (ROC) curves were readily constructed. Then, the area under the ROC curve (AUROC) was used as a metric for discovery "success" for various combinations of the modeling variables. Based on the results of this study, recommendations for tile size selection and experimental design are provided, and further supported by comparison to previous tile-based FRA applications. For instance, values for <δ_r>, α_e,2D, and RSD_wc obtained from a GC×GC-TOFMS dataset of yeast metabolites suggested an optimum RTA of 6.25, corresponding closely to the RTA of 4.00 employed in the study, implying the simulation results obtained here can be generalized to real datasets.

Characterizing the external exposome using passive samplers-comparative assessment of chemical exposures using different wearable form factors

BACKGROUND

Organic contaminants are released into the air from building materials/furnishings, personal care, and household products. Wearable passive samplers have emerged as tools to characterize personal chemical exposures. The optimal placement of these samplers on an individual to best capture airborne exposures has yet to be evaluated.

OBJECTIVE

To compare personal exposure to airborne contaminants detected using wearable passive air samplers placed at different positions on the body.

METHODS

Participants (n = 32) simultaneously wore four passive Fresh Air samplers, on their head, chest, wrist, and foot for 24 hours. Exposure to 56 airborne organic contaminants was evaluated using thermal desorption gas chromatography high resolution mass spectrometry with a targeted data analysis approach.

RESULTS

Distinct exposure patterns were detected by samplers positioned on different parts of the body. Chest and wrist samplers were the most similar with correlations identified for 20% of chemical exposures (Spearman's Rho > 0.8, p < 0.05). In contrast, the greatest differences were found for head and foot samplers with the weakest correlations across evaluated exposures (8% compounds, Spearman's Rho > 0.8, p < 0.05).

SIGNIFICANCE

The placement of wearable passive air samplers influences the exposures captured and should be considered in future exposure and epidemiological studies.

IMPACT STATEMENT

Traditional approaches for assessing personal exposure to airborne contaminants with active samplers presents challenges due to their cost, size, and weight. Wearable passive samplers have recently emerged as a non-invasive, lower cost tool for measuring environmental exposures. While these samplers can be worn on different parts of the body, their position can influence the type of exposure that is captured. This study comprehensively evaluates the exposure to airborne chemical contaminants measured at different passive sampler positions worn on the head, chest, wrist, and foot. Findings provide guidance on sampler placement based on chemicals and emission sources of interest.

Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives

Considering the chemical complexity and toxicity data gaps of environmental mixtures, most studies evaluate the chemical risk individually. However, humans are usually exposed to a cocktail of chemicals in real life. Mixture health assessment remains to be a research area having significant knowledge gaps. Characterization of chemical composition and bioactivity/toxicity are the two critical aspects of mixture health assessments. This review seeks to introduce the recent progress and tools for the chemical and biological characterization of environmental mixtures. The state-of-the-art techniques include the sampling, extraction, rapid detection methods, and the in vitro, in vivo, and in silico approaches to generate the toxicity data of an environmental mixture. Application of these novel methods, or new approach methodologies (NAMs), has increased the throughput of generating chemical and toxicity data for mixtures and thus refined the mixture health assessment. Combined with computational methods, the chemical and biological information would shed light on identifying the bioactive/toxic components in an environmental mixture.

A systematic review of the use of silicone wristbands for environmental exposure assessment, with a focus on polycyclic aromatic hydrocarbons (PAHs)

BACKGROUND

Exposure assessment is critical for connecting environmental pollutants to health outcomes and evaluating impacts of interventions or environmental policies. Silicone wristbands (SWBs) show promise for multi-pollutant exposure assessment, including polycyclic aromatic hydrocarbons (PAHs), a ubiquitous class of toxic environmental pollutants.

OBJECTIVE

To review published studies where SWBs were worn on the wrist for human environmental exposure assessments and evaluate the ability of SWBs to capture personal exposures, identify gaps which need to be addressed to implement this tool, and make recommendations for future studies to advance the field of exposure science through utilization of SWBs.

METHODS

We performed a systematic search and a cited reference search in Scopus and extracted key study descriptions.

RESULTS

Thirty-nine unique studies were identified, with analytes including PAHs, pesticides, flame retardants, and tobacco products. SWBs were shipped under ambient conditions without apparent analyte loss, indicating utility for global exposure and health studies. Nineteen articles detected a total of 60 PAHs in at least one SWB. Correlations with other concurrent biological and air measurements indicate the SWB captures exposure to flame retardants, tobacco products, and PAHs.

SIGNIFICANCE

SWBs show promise as a simple-to-deploy tool to estimate environmental and occupational exposures to chemical mixtures, including PAHs.

Silicone Wristbands in Exposure Assessment: Analytical Considerations and Comparison with Other Approaches

Humans are exposed to numerous potentially harmful chemicals throughout their lifetime. Although many studies have addressed this issue, the data on chronic exposure is still lacking. Hence, there is a growing interest in methods and tools allowing to longitudinally track personal exposure to multiple chemicals via different routes. Since the seminal work, silicone wristbands (WBs) have been increasingly used to facilitate human exposure assessment, as using WBs as a wearable sampler offers new insights into measuring chemical risks involved in many ambient and occupational scenarios. However, the literature lacks a detailed overview regarding methodologies being used; a comprehensive comparison with other approaches of personal exposure assessment is needed as well. Therefore, the aim of this review is fourfold. First, we summarize hitherto conducted research that employed silicone WBs as personal passive samplers. Second, all pre-analytical and analytical steps used to obtain exposure data are discussed. Third, we compare main characteristics of WBs with key features of selected matrices used in exposure assessment, namely urine, blood, hand wipes, active air sampling, and settled dust. Finally, we discuss future needs of research employing silicone WBs. Our work shows a variety of possibilities, advantages, and caveats associated with employment of silicone WBs as personal passive samplers. Although further research is necessary, silicone WBs have already been proven valuable as a tool for longitudinal assessment of personal exposure.

Operationalizing the Exposome Using Passive Silicone Samplers

The exposome, which is defined as the cumulative effect of environmental exposures and corresponding biological responses, aims to provide a comprehensive measure for evaluating non-genetic causes of disease. Operationalization of the exposome for environmental health and precision medicine has been limited by the lack of a universal approach for characterizing complex exposures, particularly as they vary temporally and geographically. To overcome these challenges, passive sampling devices (PSDs) provide a key measurement strategy for deep exposome phenotyping, which aims to provide comprehensive chemical assessment using untargeted high-resolution mass spectrometry for exposome-wide association studies. To highlight the advantages of silicone PSDs, we review their use in population studies and evaluate the broad range of applications and chemical classes characterized using these samplers. We assess key aspects of incorporating PSDs within observational studies, including the need to preclean samplers prior to use to remove impurities that interfere with compound detection, analytical considerations, and cost. We close with strategies on how to incorporate measures of the external exposome using PSDs, and their advantages for reducing variability in exposure measures and providing a more thorough accounting of the exposome. Continued development and application of silicone PSDs will facilitate greater understanding of how environmental exposures drive disease risk, while providing a feasible strategy for incorporating untargeted, high-resolution characterization of the external exposome in human studies.

Firefighter exposures to potential endocrine disrupting chemicals measured by military-style silicone dog tags

Studies suggest that exposure to potential endocrine disrupting chemicals (pEDCs) may contribute to adverse health outcomes, but pEDC exposures among firefighters have not been fully characterized. Previously, we demonstrated the military-style silicone dog tag as a personal passive sampling device for assessing polycyclic aromatic hydrocarbon exposures among structural firefighters. This follow-up analysis examined the pEDC exposures based on department call volume, duty shift, and questionnaire variables. Structural firefighters (n = 56) were from one high and one low fire call volume department (Kansas City, MO metropolitan area) and wore separate dog tags while on- and off-duty (n_dogtags = 110). The targeted 1530 analyte semi-quantitative screening method was conducted using gas chromatography mass spectrometry (n_pEDCs = 433). A total of 47 pEDCs were detected, and several less-frequently-detected pEDCs (<75%) were more commonly detected in off- compared to on-duty dog tags (conditional logistic regression). Of the 11 phthalates and fragrances detected most frequently (>75%), off-duty pEDC concentrations were strongly correlated (r = 0.31-0.82, p < 0.05), suggesting co-applications of phthalates and fragrances in consumer products. Questionnaire variables of "regular use of conventional cleaning products" and "fireplace in the home" were associated with select elevated pEDC concentrations by duty shift (paired t-test). This suggested researchers should include detailed questions about consumer product use and home environment when examining personal pEDC exposures.

Automated high confidence compound identification of electron ionization mass spectra for nontargeted analysis

Nontargeted analysis based on mass spectrometry is a rising practice in environmental monitoring for identifying contaminants of emerging concern. Nontargeted analysis performed using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC/TOF-MS) generates large numbers of possible analytes. Moreover, the default spectral library similarity score-based search algorithm used by LECO® ChromaTOF® does not ensure that high similarity scores result in correct library matches. Therefore, an additional manual screening is necessary, but leads to human errors especially when dealing with large amounts of data. To improve the speed and accuracy of the chemical identification, we developed CINeMA.py (Classification Is Never Manual Again). This programming suite automates GC×GC/TOF-MS data interpretation by determining the confidence of a match between the observed analyte mass spectrum and the LECO® ChromaTOF® software generated library hit from the NIST Electron Ionization Mass Spectral (NIST EI-MS) library. Our script allows the user to evaluate the confidence of the match using an algorithmic method that mimics the manual curation process and two different machine learning approaches (neural networks and random forest). The script allows the user to adjust various parameters (e.g., similarity threshold) and study their effects on prediction accuracy. To test CINeMA.py, we used data from two different environmental contaminant studies: an EPA study on household dust and a study on stormwater runoff. Using a reference set based on the analysis performed by highly trained users of the ChromaTOF and GC×GC/TOF-MS systems, the random forest model had the highest prediction accuracies of 86% and 83% on the EPA and Stormwater data sets, respectively. The algorithmic approach had the second-best prediction accuracy (82% and 79%), while the neural network accuracy had the lowest (63% and 67%). All the approaches required less than 1 min to classify 986 observed analytes, whereas manual data analysis required hours or days to complete. Our methods were also able to detect high confidence matches missed during the manual review. Overall, CINeMA.py provides users with a powerful suite of tools that should significantly speed-up data analysis while reducing the possibilities of manual errors and discrepancies among users, and can be applicable to other GC/EI-MS instrument based nontargeted analysis.

Exploring personal chemical exposures in China with wearable air pollutant monitors: A repeated-measure study in healthy older adults in Jinan, China

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p < 0.05). Specifically, dimethyl phthalate (r_s = 0.31) decreased as temperatures declined, while nitrobenzene (r_s = -0.35) and naphthalene (r_s = -0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p < 0.05) and hexachlorobutadiene was lower across participants (p < 0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements.

Optimized workflow for unknown screening using gas chromatography high-resolution mass spectrometry expands identification of contaminants in silicone personal passive samplers

RATIONALE

Silicone wristbands have emerged as valuable passive samplers for monitoring of personal exposure to environmental contaminants in the rapidly developing field of exposomics. Once deployed, silicone wristbands collect and hold a wealth of chemical information that can be interrogated using high-resolution mass spectrometry (HRMS) to provide a broad coverage of chemical mixtures.

METHODS

Gas chromatography coupled to Orbitrap™ mass spectrometry (GC/Orbitrap™ MS) was used to simultaneously perform suspect screening (using in-house database) and unknown screening (using vendor databases) of extracts from wristbands worn by volunteers. The goal of this study was to optimize a workflow that allows detection of low levels of priority pollutants, with high reliability. In this regard, a data processing workflow for GC/Orbitrap™ MS was developed using a mixture of 123 environmentally relevant standards consisting of pesticides, flame retardants, organophosphate esters, and polycyclic aromatic hydrocarbons as test compounds.

RESULTS

The optimized unknown screening workflow using a search index threshold of 750 resulted in positive identification of 70 analytes in validation samples, and a reduction in the number of false positives by over 50%. An average of 26 compounds with high confidence identification, 7 level 1 compounds and 19 level 2 compounds, were observed in worn wristbands. The data were further analyzed via suspect screening and retrospective suspect screening to identify an additional 36 compounds.

CONCLUSIONS

This study provides three important findings: (1) a clear evidence of the importance of sample cleanup in addressing complex sample matrices for unknown analysis, (2) a valuable workflow for the identification of unknown contaminants in silicone wristband samplers using electron ionization HRMS data, and (3) a novel application of GC/Orbitrap™ MS for the unknown analysis of organic contaminants that can be used in exposomics studies.

Nicotine, Cotinine, and Tobacco-Specific Nitrosamines Measured in Children's Silicone Wristbands in Relation to Secondhand Smoke and E-cigarette Vapor Exposure

INTRODUCTION

Simple silicone wristbands (WB) hold promise for exposure assessment in children. We previously reported strong correlations between nicotine in WB worn by children and urinary cotinine (UC). Here, we investigated differences in WB chemical concentrations among children exposed to secondhand smoke from conventional cigarettes (CC) or secondhand vapor from electronic cigarettes (EC), and children living with nonusers of either product (NS).

METHODS

Children (n = 53) wore three WB and a passive nicotine air sampler for 7 days and one WB for 2 days, and gave a urine sample on day 7. Caregivers reported daily exposures during the 7-day period. We determined nicotine, cotinine, and tobacco-specific nitrosamines (TSNAs) concentrations in WB, nicotine in air samplers, and UC through isotope-dilution liquid chromatography with triple-quadrupole mass spectrometry.

RESULTS

Nicotine and cotinine levels in WB in children differentiated between groups of children recruited into NS, EC exposed, and CC exposed groups in a similar manner to UC. WB levels were significantly higher in the CC group (WB nicotine median 233.8 ng/g silicone, UC median 3.6 ng/mL, n = 15) than the EC group (WB nicotine median: 28.9 ng/g, UC 0.5 ng/mL, n = 19), and both CC and EC group levels were higher than the NS group (WB nicotine median: 3.7 ng/g, UC 0.1 ng/mL, n = 19). TSNAs, including the known carcinogen NNK, were detected in 39% of WB.

CONCLUSIONS

Silicone WB show promise for sensitive detection of exposure to tobacco-related contaminants from traditional and electronic cigarettes and have potential for tobacco control efforts.

IMPLICATIONS

Silicone WB worn by children can absorb nicotine, cotinine, and tobacco-specific nitrosamines, and amounts of these compounds are closely related to the child's urinary cotinine. Levels of tobacco-specific compounds in the silicone WB can distinguish patterns of children's exposure to secondhand smoke and e-cigarette vapor. Silicone WB are simple to use and acceptable to children and, therefore, may be useful for tobacco control activities such as parental awareness and behavior change, and effects of smoke-free policy implementation.

Local Air Quality Issues and Research Priorities Through the Lenses of Chilean Experts: An Ontological Analysis

Air pollution problems can be large, complex, and ill-structured. They can vary from location to location and combine many complex components: urban expansion, increasing vehicles and industrial emissions, biomass burning, geographic and meteorological conditions, cultural aspects, and economic effects. However, the existing research, accumulated knowledge, and local research priorities are spread over many disciplines and lack a systematic mapping to help manage and develop new strategies for researchers and policy makers. Ontological analysis can be used as a tool to capture this complexity through simple natural-language descriptions and a structured terminology. We describe the development of an ontological framework for "Air Quality Management in Chile" and its application to evaluate the current state of the research. The process was based on focus groups and validated by a panel of multidisciplinary experts. We used the developed framework to highlight the topics that have been heavily emphasized, lightly emphasized, or overlooked in the Chilean research. The framework developed can help researchers, practitioners, and policy makers systematically navigate the domain and provide the opportunity to correct blind spots by enabling more informed hypotheses that deal with air quality issues at a national level. We believe that applying this same process to different countries will yield different results (due to differences in local knowledge and experience). The framework presented could be used to evaluate other important stakeholders (government, media, NGOs, etc.), which will provide a complete picture of how local societies deal with air quality issues at different levels. Additionally, local government institutions will benefit from this analysis by improving funding allocation and opening new research opportunities to improve the distribution of the local body of knowledge. Integr Environ Assess Manag 2021;17:273-281. © 2020 SETAC.

Catching flame retardants and pesticides in silicone wristbands: Evidence of exposure to current and legacy pollutants in Uruguayan children

Children are exposed to many potentially toxic compounds in their daily lives and are vulnerable to the harmful effects. To date, very few non-invasive methods are available to quantify children's exposure to environmental chemicals. Due to their ease of implementation, silicone wristbands have emerged as passive samplers to study personal environmental exposures and have the potential to greatly increase our knowledge of chemical exposures in vulnerable population groups. Nevertheless, there is a limited number of studies monitoring children's exposures via silicone wristbands. In this study, we implemented this sampling technique in ongoing research activities in Montevideo, Uruguay which aim to monitor chemical exposures in a cohort of elementary school children. The silicone wristbands were worn by 24 children for 7 days; they were quantitatively analyzed using gas chromatography with tandem mass spectrometry for 45 chemical pollutants, including polychlorinated biphenyls (PCBs), pesticides, polybrominated diphenyl ethers (PBDEs), organophosphorus flame retardants (OPFRs), and novel halogenated flame-retardant chemicals (NHFRs). All classes of chemicals, except NHFRs, were identified in the passive samplers. The average number of analytes detected in each wristband was 13 ±3. OPFRs were consistently the most abundant class of analytes detected. Median concentrations of ΣOPFRs, ΣPBDEs, ΣPCBs, and dichlorodiphenyltrichloroethane (DDT) and its metabolites (dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD)) were 1020, 3.00, 0.52 and 3.79 ng/g wristband, respectively. Two major findings result from this research; differences in trends of two OPFRs (TCPP and TDCPP) are observed between studies in Uruguay and the United States, and the detection of DDT, a chemical banned in several countries, suggests that children's exposure profiles in these settings may differ from other parts of the world. This was the first study to examine children's exposome in South America using silicone wristbands and clearly points to a need for further studies.

Molecular Characterization of Atmospheric Organic Aerosol by Mass Spectrometry

Atmospheric aerosol, particulate matter suspended in the air we breathe, exerts a strong impact on our health and the environment. Controlling the amount of particulate matter in air is difficult, as there are many ways particles can form by both natural and anthropogenic processes. We gain insight into the sources of particulate matter through chemical composition measurements. A substantial portion of atmospheric aerosol is organic, and this organic matter is exceedingly complex on a molecular scale, encompassing hundreds to thousands of individual compounds that distribute between the gas and particle phases. Because of this complexity, no single analytical technique is sufficient. However, mass spectrometry plays a crucial role owing to its combination of high sensitivity and molecular specificity. This review surveys the various ways mass spectrometry is used to characterize atmospheric organic aerosol at a molecular level, tracing these methods from inception to current practice, with emphasis on current and emerging areas of research. Both offline and online approaches are covered, and molecular measurements with them are discussed in the context of identifying sources and elucidating the underlying chemical mechanisms of particle formation. There is an ongoing need to improve existing techniques and develop new ones if we are to further advance our knowledge of how to mitigate the unwanted health and environmental impacts of particles.