Search

This research was aimed at providing an accurate low-dose benzene exposure assessment method, prospectively suitable to exposure limit values in the low ppb range, such as in the present-day chemical, petrochemical, foundry and pharmaceutical industry. The project addresses the need for a robust and fully validated method of personal exposure measurements considering that the Occupational Exposure Limit Value for benzene will be significantly lowered in the next few years. Diffusive sampling offers a reliable alternative to pumped sampling methods, intrinsic safety in potentially explosive atmospheres, lightness and ease of use. The tested diffusive sampler is radiello® with the RAD145 adsorption substrate. This configuration is packed with graphitised charcoal suitable for thermal desorption and analysis by HRGC-FID or HRGC-MS.The experiments have been conducted following the ISO 23320 standard in the range from 0.005 to 0.1 ppm (16 to 320 µg/m3), yielding a full validation of the sampling and analytical method. The sampler performances have fulfilled all requisites of the ISO 23320 standard, in particular: bias due to the selection of a non-ideal sorbent is lower than 10 % (no significant back diffusion of benzene due to concentration change in the atmosphere); bias due to storage of samples for up to 2 months is lower than 10 %; nominal uptake rate for benzene on RAD145 is 32.3 mL/min; expanded uncertainty of the sampling and analytical method is 22.1 % in the concentration range from 80 to 320 µg/m³. The sampling and analytical method is therefore fit-for-purpose for the personal exposure measurements aimed at testing compliance with lowered occupational exposure limit values for benzene. The method is also fit for short duration exposure monitoring related to specific tasks, and other volatile organic compounds, usually found in the same workplaces, such as aliphatic and aromatic hydrocarbons and some oxygenated compounds, have been also studied. In particular, n-hexane and isopropyl benzene (also known as cumene), whose classification is currently under revision, can be efficiently monitored by this technique.

Objectives: This study aims to develop and validate a sampler to measure workers’ exposure to the vapor and mist of benzyl alcohol. Methods: Recovery rate, extraction and desorption rates, breakthrough, and storage stability were tested using Slim-J connected to a glass fiber filter upstream (the connected sampler). The recovery rate of the connected sampler was compared with that of XAD-7. Benzyl alcohol on the filter was extracted, and that in Slim-J resin was desorbed by methanol with an internal standard (N,N-dimethylformamide). Benzyl alcohol was quantified through gas chromatography using a flame ionization detector (GC/FID). Air sampling was conducted by attaching the connected sampler to the chest of a worker during bridge paint film removal. Results: Calibration curves showed linearity with correlation coefficients >0.999. The lower limit of quantification was 0.54 mg/m3 of the airborne concentration at 5-mL desorption with 120-L air sampling. The recovery rates of the connected sampler were 101–103%, whereas those of XAD-7 were 72–78%. The average extraction efficiency from the filters was 105.3%, whereas those from Slim-J were 94.5%. No breakthrough was recognized by aeration at 1 L/min for 120 min. Benzyl alcohol in the sampler was stable for up to 7 days. The sampled air by the connected sampler during bridge paint film removal indicated an isolated peak by GC/FID. Conclusions: The connected sampler is reliable and suitable for measuring levels of personal exposure to benzyl alcohol in vapor and mist phases.

A method based on the use of GC coupled to Q-exactive Orbitrap mass spectrometry (GC-Orbitrap-MS) has been developed for the analysis of polycyclic aromatic hydrocarbons (PAHs) at sub-picogram levels. Outdoor ambient air particulate matter (PM2.5) and standard reference materials (SRM2260a) were analyzed in full scan mode showing low instrumental uncertainties (1–22%) and high linearity over a wide concentration range (0.5 pg and 500 pg/μL). Good reproducibility was obtained compared to the use of conventional single quadrupole GC–MS of PM samples. The quantification limit of the GC-Orbitrap-MS method for full scan analysis of PAHs in outdoor ambient air PM samples was 0.5 pg/μL. This low limit allowed the analysis of PAHs in samples collected with low volumes (< 0.5 m3), such as punch samples from whole filters or filter strips from personal exposure monitoring equipment. PAHs were successfully analyzed in filter strips from real-time Aethalometer AE51 equivalent black carbon (eBC) analyzers used in urban and rural sites, and in personal exposure monitors of firefighters during prescribed burns. The correlations between PAHs and eBC in these analyses were very strong (r2 ≥ 0.93). However, the equations obtained reflected the dominance of different emission sources, such as traffic in urban areas, wood burning for domestic heating, or wildfires. The method reported here affords the analyses of PAHs in high precision studies of atmospheric PM samples, e.g., high frequency sampling of low volumes, affording personal exposure monitoring assessments. [ABSTRACT FROM AUTHOR]

In this study fine particulate matter (PM2.5) levels throughout the Copenhagen metro system are measured for the first time and found to be ∼10 times the roadside levels in Copenhagen. In this Part 2 article, low-cost sensor (LCS) nodes designed for personal-exposure monitoring are tested against a conventional mid-range device (TSI DustTrak), and gravimetric methods. The nodes were found to be effective for personal exposure measurements inside the metro system, with R2 values of > 0.8 at 1-min and > 0.9 at 5-min time-resolution, with an average slope of 1.01 in both cases, in comparison to the reference, which is impressive for this dynamic environment. Micro-environment (ME) classification techniques are also developed and tested, involving the use of auxiliary sensors, measuring light, carbon dioxide, humidity, temperature and motion. The output from these sensors is used to distinguish between specific MEs, namely, being aboard trains travelling above- or under- ground, with 83 % accuracy, and determining whether sensors were aboard a train or stationary at a platform with 92 % accuracy. This information was used to show a 143 % increase in mean PM2.5 concentration for underground sections relative to overground, and 22 % increase for train vs. platform measurements. The ME classification method can also be used to improve calibration models, assist in accurate exposure assessment based on detailed time-activity patterns, and facilitate field studies that do not require personnel to record time-activity diaries.

Objectives: We aimed to develop a method to determine workers' personal exposure levels to N‐(phosphonomethyl)glycine (glyphosate) for their risk assessments. Methods: The proposed method was assessed as follows: recovery, stability of samples on storage, method limit of quantification, and reproducibility. Glyphosate in air was sampled using an air‐sampling cassette containing a glass fiber filter. Ultrapure water was used to extract glyphosate from sampler filters. After derivation with 9‐fluorenylmethyloxycarbonyl chloride, samples were analyzed by high‐performance liquid chromatography using a fluorescence detector. Results: Spiked samples indicated an overall recovery of 101%. After 7 days of storage at 4°C, recoveries were approximately 100%. The method limit of quantification was 0.060 μg/sample. Relative standard deviations representing overall reproducibility, defined as precision, were 1.4%–1.8%. Conclusions: The method developed in this study allows 4‐h personal exposure monitoring of glyphosate at 0.250–500 μg/m3. Thus, this method can be used to estimate worker exposure to glyphosate. [ABSTRACT FROM AUTHOR]

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60–69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques.

This study investigated the determinants of personal exposures (PE) to coarse (PM 2.5-10) and fine particulate matter (PM 2.5) for elderly communities in Hong Kong. The mean PE PM 2.5 and PM 2.5-10 were 23.6 ± 10.8 and 13.5 ± 22.1 μg/m3, respectively during the sampling period. Approximately 76% of study subjects presented statistically significant differences between PE and ambient origin for PM 2.5 compared to approximately 56% for PM 2.5-10 , possibly due to the coarse-size particles being more influenced by similar sources (road dust and construction dust emissions) compared to the PM 2.5 particles. Individual PE to ambient (P/A) ratios for PM 2.5 all exceeded unity (≥1), suggesting the dominant influences of non-ambient particles contributed towards total PE values. There were about 80% individual P/A ratios (≤1) for PM 2.5-10 , implying possible effective infiltration prevention of larger size particulate matter particles leading to dominant influences from the outdoor sources. The higher concentration of NO 3 − and SO 4 2− in PM 2.5-10 compared to PM 2.5 suggests possible heterogeneous reactions of alkaline minerals leading to the formation of NO 3 − and SO 4 2− in PM 2.5-10 particles. The PE and ambient OC/EC ratios in PM 2.5 (8.8 ± 3.3 and 10.4 ± 22.4, respectively) and in PM 2.5-10 (6.0 ± 1.9 and 3.0 ± 1.1, respectively) suggest possible secondary formed OC from surrounding rural areas. Heterogeneous distributions (COD >0.2) between the PE and ambient concentrations were found for both the PM 2.5 and PM 2.5-10 samples. The calibration coefficient as the association between personal and surrogate exposure measure of PE to PM 2.5 (0.84) was higher than PM 2.5-10 (0.52). The findings further confirm that local sources were the dominant contributor to the coarse particles and these coefficients can potentially be used to estimate different PE to PM 2.5 and PM 2.5-10 conditions. A comprehensive understanding of the PE to determinants in coarse particles is essential to further reduce potential exposure misclassification. [Display omitted] • P/A ratios ≤1 for PM 2.5-10 implied infiltration prevention of larger PM particles. • PAHs and OPAHs in PM 2.5 were ∼1.0–31.1 and ∼1.9–20.8 times higher than PM 2.5-10 • COD >0.2 for PM 2.5 and PM 2.5-10 confirmed spatial heterogeneous distributions. • Lower PM 2.5-10 exposure coefficient suggested dominant effects of local sources. [ABSTRACT FROM AUTHOR]

The human exposome affects child development and health later in life, but its personal external levels, variability, and correlations are largely unknown. We characterized the personal external exposome of pregnant women and children in eight European cities. Panel studies included 167 pregnant women and 183 children (aged 6–11 years). A personal exposure monitoring kit composed of smartphone, accelerometer, ultraviolet (UV) dosimeter, and two air pollution monitors were used to monitor physical activity (PA), fine particulate matter (PM 2.5), black carbon, traffic-related noise, UV-B radiation, and natural outdoor environments (NOE). 77% of women performed the adult recommendation of ≥150 min/week of moderate to vigorous PA (MVPA), while only 3% of children achieved the childhood recommendation of ≥60 min/day MVPA. 11% of women and 17% of children were exposed to daily PM 2.5 levels higher than recommended (≥25μg/m3). Mean exposure to noise ranged from Lden 51.1 dB in Kaunas to Lden 65.2 dB in Barcelona. 4% of women and 23% of children exceeded the recommended maximum of 2 Standard-Erythemal-Dose of UV-B at least once a week. 33% of women and 43% of children never reached the minimum NOE contact recommendation of ≥30 min/week. The variations in air and noise pollution exposure were dominated by between-city variability, while most of the variation observed for NOE contact and PA was between-participants. The correlations between all personal exposures ranged from very low to low (Rho < 0.30). The levels of personal external exposures in both pregnant women and children are above the health recommendations, and there is little correlation between the different exposures. The assessment of the personal external exposome is feasible but sampling requires from one day to more than one year depending on exposure due to high variability between and within cities and participants. • The assessment of the personal external exposome is feasible. • Personal external exposures are above the health recommendations. • Personal external exposures are highly variable within person. • External exposure variability can bias health effects estimation. • There is little correlation between the different external exposures. [ABSTRACT FROM AUTHOR]

Abstract To assess environmental exposures at the individual level, new assessment methods and tools are required. We developed an exposure assessment system (ExpoApp) for smartphones. ExpoApp integrates: (i) geo-location and accelerometry measurements from a waist attached smartphone, (ii) data from portable monitors, (iii) geographic information systems, and (iv) individual's information. ExpoApp calculates time spent in microenvironments, physical activity level, inhalation rate, and environmental exposures and doses (e.g., green spaces, inhaled ultrafine particles- UFP). We deployed ExpoApp in a panel study of 158 adults from five cities (Amsterdam and Utrecht- the Netherlands, Basel- Switzerland, Norwich- UK, and Torino- Italy) with an UFP monitor. To evaluate ExpoApp, participants also carried a reference accelerometer (ActiGraph) and completed a travel-activity diary (TAD). System reliability and validity of measurements were evaluated by comparing the monitoring failure rate and the agreement on time spent in microenvironments and physical activity with the reference tools. There were only significant failure rate differences between ExpoApp and ActiGraph in Norwich. Agreement on time in microenvironments and physical activity level between ExpoApp and reference tools was 86.6% (86.5–86.7) and 75.7% (71.5–79.4), respectively. ExpoApp estimated that participants inhaled 16.5 × 1010 particles/day of UFP and had almost no contact with green spaces (24% of participants spent ≥30 min/day in green spaces). Participants with more contact with green spaces had higher inhaled dose of UFP, except for the Netherlands, where the relationship was the inverse. ExpoApp is a reliable system and provides accurate individual's measurements, which may help to understand the role of environmental exposures on the origin and course of diseases. Highlights • ExpoApp uses built-in smartphone sensors, portable monitors, and geographic data. • ExpoApp can estimate inhaled ultrafine particles and contact with green spaces. • ExpoApp was evaluated in a panel study of 158 adults from five European cities. • ExpoApp is a reliable system and its measurements are accurate. • Exposure to ultrafine particles varied according to contact with green spaces and city. [ABSTRACT FROM AUTHOR]

Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged ? and (2) How far have these technologies and their applications progressed to provide answers and solutions ? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose . Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve. [ABSTRACT FROM AUTHOR]

Smartphone-based sensing is becoming a convenient way to collect data in science, especially in environmental research. Recent studies that use smartphone sensing methods focus predominantly on single sensors that provide quantitative measurements. However, interdisciplinary projects call for study designs that connect both, quantitative and qualitative data gathered by smartphone sensors. Therefore, we present a novel open-source task automation solution and its evaluation in a personal exposure study with cyclists. We designed an automation script that advances the sensing process with regard to data collection, management and storage of acoustic noise, geolocation, light level, timestamp, and qualitative user perception. The benefits of this approach are highlighted based on data visualization and user handling evaluation. Even though the automation script is limited by the technical features of the smartphone and the quality of the sensor data, we conclude that task automation is a reliable and smart solution to integrate passive and active smartphone sensing methods that involve data processing and transfer. Such an application is a smart tool gathering data in population studies.

Air pollution is a recognized risk factor for impaired lung health and increased morbidity and mortality globally. Fine particulate matter (PM 2.5) has been linked to respiratory illness, but assessing personal PM 2.5 exposure remains difficult, especially in children. The MicroPEM™ and Enhanced Children's MicroPEM™ (ECM) are personal fine particulate matter exposure monitors that have not been well-evaluated for young children. We aimed to assess compliance and acceptability of these monitors and to investigate risk factors associated with fine particulate matter in mother-child pairs. Mother-child pairs, enrolled in a South African birth cohort, the Drakenstein Child Health Study, were recruited. A MicroPEM (mother) and ECM (child), issued to each participant and worn over 24 h, quantified PM 2.5 exposure. Home environment, wearability, and wearing compliance were assessed. Linear regression identified associations between variables characterising the home environment and PM 2.5 levels. From August to November 2016, 86 mothers and 75 children (age 1–4 years) had results. Fossil fuels were used in 21% of homes; maternal smoking (37%) and exposure to household tobacco smoke (89%) was high. Waking wearing compliance of the devices was 59% in children and 56% in mothers. PM 2.5 exposures were above the World Health Organization recommend 24-h interim target (IT-4 25 μg/m3) in 38/75 (51%) children, and in 44/86 (51%) mothers. Winter, smoking and public transport were associated with higher concentrations of PM 2.5 in mothers. Whereas, for the children higher concentrations of PM 2.5 were associated with winter and two or more household smokers; while lower concentrations were associated with age, weight-for-age z-score and households that had fewer than two basic dimensions. Wearability for children was reported as "very easy" in the majority (n = 54, 63%) with similar acceptability in mothers (n = 55, 64%). The MicroPEM and ECM provide wearable low-burden personal exposure monitoring tools for women and children with reasonable rates of acceptability. High exposure to fine particulate matter in children is concerning; strategies to minimise exposure need to be strengthened. [Display omitted] • Personal sampling of fine particulate matter exposure is possible even in young children. • The weak correlation between maternal and child PM 2.5 indicates it may be important to directly measure child exposure. • Acceptable compliance was found but design of device holders are important considerations for further studies. • Exposures exceeded recommended PM 2.5 interim targets for half of mothers and children. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sources and dynamics of harmful particles in metro systems are not well characterised. • Fine particulate matter and CO2 were measured in the entire Copenhagen Metro. • High particle concentrations were found despite the system's modernity. • A closed tunnel design and carriage ventilation with tunnel air are the likely causes of the problem. • Sliding doors alone are insufficient for keeping the air clean in carriages and at stations. The Copenhagen Metro comprises four lines, the M1, M2, M3 and M4, with 25 subterranean stations and an additional 14 stations above ground, serving ca. 80 million passengers annually. In this study we measure fine particulate matter (PM 2.5) and carbon dioxide (CO 2) concentrations in stations and in trains across the entire system. In partially underground lines, high PM 2.5 concentrations with an average of 109 μg m−3 are found in below-ground stations. The observed correlation between PM 2.5 concentration and distance between a station and a tunnel exit is attributed to ventilation via the piston effect. The piston effect via tunnel draught relief shafts was therefore found to be relatively limited. Filter samples of particulate matter are analysed using particle-induced X-ray emission and show an iron content of 88.6 % by mass which is quite different from above-ground particulate matter and consistent with particle production by train wheels, rails and brakes. The average concentration measured at the stations of a recently opened (2019) fully underground M3 closed loop line is 168 μg m−3, further demonstrating that while piston effect-driven ventilation is effective in close proximity to tunnel openings, it is relatively limited via tunnel draught relief shafts. Measurements onboard trains show even higher PM 2.5 concentrations and the patterns in CO 2 concentrations suggest carriage ventilation by tunnel air. Ventilation via doors during platform stops caused a drop in observed PM (and CO 2) at stations, but the system is surprisingly polluted despite its recent construction. CO 2 mixing ratios ranged from ambient to around 600 ppm. Measures should be taken to control PM levels using a combination of source control and increased clean air supply of the Copenhagen and other similar metro systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • Particulate matter (PM) levels on the CPH metro are measured with low-cost sensors. • Low-costs sensors perform well, due to stable conditions and a primary PM source. • Fine micro-environment classification using sensors and machine learning is tested. • PM concentrations in different micro-environments of the metro are characterised. • Measurements made whilst mobile on undergrounds trains gave the highest PM levels (edited). In this study fine particulate matter (PM 2.5) levels throughout the Copenhagen metro system are measured for the first time and found to be ∼ 10 times the roadside levels in Copenhagen. In this Part 2 article, low-cost sensor (LCS) nodes designed for personal-exposure monitoring are tested against a conventional mid-range device (TSI DustTrak), and gravimetric methods. The nodes were found to be effective for personal exposure measurements inside the metro system, with R 2 values of > 0.8 at 1-min and > 0.9 at 5-min time-resolution, with an average slope of 1.01 in both cases, in comparison to the reference, which is impressive for this dynamic environment. Micro-environment (ME) classification techniques are also developed and tested, involving the use of auxiliary sensors, measuring light, carbon dioxide, humidity, temperature and motion. The output from these sensors is used to distinguish between specific MEs, namely, being aboard trains travelling above- or under- ground, with 83 % accuracy, and determining whether sensors were aboard a train or stationary at a platform with 92 % accuracy. This information was used to show a 143 % increase in mean PM 2.5 concentration for underground sections relative to overground, and 22 % increase for train vs. platform measurements. The ME classification method can also be used to improve calibration models, assist in accurate exposure assessment based on detailed time-activity patterns, and facilitate field studies that do not require personnel to record time-activity diaries. [ABSTRACT FROM AUTHOR]

Personal exposure monitoring for select polycyclic aromatic hydrocarbons (PAHs) was performed as part of the National Human Exposure Assessment Survey (NHEXAS) Pilot Study in Baltimore, MD and in four surrounding counties (NHEXAS-Maryland). An objective of this effort was to establish environmental exposure estimates for non-scripted subpopulations involved in their normal activities. Participants, children, and adults (ages 13-84) were randomly selected from urban, suburban, and rural areas near Baltimore. Twenty-four hour PM sample collections (∼5.8 m) were performed using personal environmental monitors. Monitoring was performed for 47 households and 6 sampling Cycles during 1995-1996. A total of 233 personal air samples were available from the participants with eight PAHs speciated (e.g., chrysene, benzo(a)pyrene) as well as an aggregate grouping (total carcinogenic PAHs). Results indicate that ∼50 % of the selected samples had detectable concentrations for 3 to 5 of the individual PAHs depending upon spatial setting. Noted differences were observed between exposure concentrations from individuals living in rural areas as compared to urban/suburban environments. Mean benzo(a)pyrene concentrations were observed to be 0.10 ng/m across the entire sampling population. This represented a value well below the World Health Organization's 1.0 ng/m ambient air guideline for this PAH. [ABSTRACT FROM AUTHOR]

Background: Levels of fine particulate matter [≤2.5 μm in aerodynamic diameter (PM2.5)] are associated with alterations in arterial hemodynamics and vascular function. However, the characteristics of the same-day exposure.response relationships remain unclear. Objectives: We aimed to explore the effects of personal PM2.5 exposures within the preceding 24 hr on blood pressure (BP), heart rate (HR), brachial artery diameter (BAD), endothelial function [flow-mediated dilatation (FMD)], and nitroglycerin-mediated dilatation (NMD). Methods: Fifty-one nonsmoking subjects had up to 5 consecutive days of 24-hr personal PM2.5 monitoring and daily cardiovascular (CV) measurements during summer and/or winter periods. The associations between integrated hour-long total personal PM2.5 exposure (TPE) levels (continuous nephelometry among compliant subjects with low secondhand tobacco smoke exposures; n.=.30) with the CV outcomes were assessed over a 24-hr period by linear mixed models. Results: We observed the strongest associations (and smallest estimation errors) between HR and TPE recorded 1.10 hr before CV measurements. The associations were not pronounced for the other time lags (11--24 hr). The associations between TPE and FMD or BAD did not show as clear a temporal pattern. However, we found some suggestion of a negative association with FMD and a positive association with BAD related to TPE just before measurement (0--2 hr). Conclusions: Brief elevations in ambient TPE levels encountered during routine daily activity were associated with small increases in HR and trends toward conduit arterial vasodilatation and endothelial dysfunction within a few hours of exposure. These responses could reflect acute PM2.5-induced autonomic imbalance and may factor in the associated rapid increase in CV risk among susceptible individuals. [ABSTRACT FROM AUTHOR]

Human exposure research has consistently shown that, for most volatile organic compounds (VOCs), personal exposures are vastly different from outdoor air concentrations. Therefore, risk estimates based on ambient measurements may over- or underestimate risk, leading to ineffective or inefficient management strategies. In the present study we examine the extent of exposure misclassification and its impact on risk for exposure estimated by the U.S. Environmental Protection Agency (U.S. EPA) Assessment System for Population Exposure Nationwide (ASPEN) model relative to monitoring results from a community-based exposure assessment conducted in Baltimore, Maryland (USA). This study is the first direct comparison of the ASPEN model (as used by the U.S. EPA for the Cumulative Exposure Project and subsequently the National-Scale Air Toxics Assessment) and human exposure data to estimate health risks. A random sampling strategy was used to recruit 33 nonsmoking adult community residents. Passive air sampling badges were used to assess 3-day time-weighted-average personal exposure as well as outdoor and indoor residential concentrations of VOCs for each study participant. In general, personal exposures were greater than indoor VOC concentrations, which were greater than outdoor VOC concentrations. Public health risks due to actual personal exposures were estimated. In comparing measured personal exposures and indoor and outdoor VOC concentrations with ASPEN model estimates for ambient concentrations, our data suggest that ASPEN was reasonably accurate as a surrogate for personal exposures (measured exposures of community residents) for VOCs emitted primarily from mobile sources or VOCs that occur as global ’background’ source pollutant with no indoor source contributions. Otherwise, the ASPEN model estimates were generally lower than measured personal exposures and the estimated health risks. ASPEN's lower exposures resulted in proportional underestimation of cumulative cancer risk when pollutant exposures were combined to estimate cumulative risk. Median cumulative lifetime cancer risk based on personal exposures was 3-fold greater than estimates based on ASPEN-modeled concentrations. These findings demonstrate the significance of indoor exposure sources and the importance of indoor and/or personal monitoring for accurate assessment of risk. Environmental health policies may not be sufficient in reducing exposures and risks if they are based solely on modeled ambient VOC concentrations. Results from our study underscore the need for a coordinated multimedia approach to exposure assessment for setting public health policy. [ABSTRACT FROM AUTHOR]

The US Environmental Protection Agency has recently performed the Research Triangle Park Particulate Matter Panel Study. This was a 1-year investigation of PM and related co-pollutants involving participants living within the RTP area of North Carolina. Primary goals were to characterize the relationships between ambient and residential PM measures to those obtained from personal exposure monitoring and estimate ambient source contributions to personal and indoor mass concentrations. A total of 38 participants living in 37 homes were involved in personal, residential indoor, residential outdoor and ambient PM2.5 exposure monitoring. Participants were 30 non-smoking hypertensive African-Americans living in a low-moderate SES neighborhood (SE Raleigh, NC) and a cohort of eight individuals having implanted cardiac defibrillators (Chapel Hill, NC). Residential and ambient monitoring of PM10 and PM10–2.5 (coarse by differential) was also performed. The volunteers were monitored for seven consecutive days during each of four seasons (summer 2000, fall 2000, winter 2001, spring 2001). Individual PM2.5 personal exposure concentrations ranged from 4 to 218 μg m−3 during the study. The highest personal exposures were determined to be the result of passive environmental tobacco exposures. Subsequently, ∼7% of the total number of personal exposure trials were excluded to minimize this pollutant''s effect upon the overall analysis. Results indicated that a pooled data set (seasons, cohorts, residences, participants) was appropriate for investigation of the basic mass concentration relationships. Daily personal PM2.5 mass concentrations were typically higher than their associated residential or ambient measurements (mean personal=23.0, indoor=19.1, outdoor=19.3, ambient=19.2 μg m−3). Mean personal PM2.5 exposures were observed to be only moderately correlated to ambient PM2.5 concentrations (r=0.39). [Copyright &y& Elsevier]

The personal exposure of children aged 9 – 11 years to particulate matter (PM10 and PM2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM10 and PM2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM10 during winter, spring and summer were 72, 54 and 35 µg/m3 respectively and for PM2.5 22, 17 and 18 µg/m3 respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed. [ABSTRACT FROM AUTHOR]

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60–69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques. [ABSTRACT FROM AUTHOR]

Environmental exposures are one of the greatest threats to human health, yet we lack tools to answer simple questions about our exposures: what are our personal exposure profiles and how do they change overtime (external exposome), how toxic are these chemicals, and what are the sources of these exposures? To capture variation in personal exposures to airborne chemicals in the gas and particulate phases and identify exposures which pose the greatest health risk, wearable exposure monitors can be deployed. In this study, we deployed passive air sampler wristbands with 84 healthy participants (aged 60–69 years) as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Participants wore the wristband samplers for 3 days each month for five consecutive months. Passive samplers were analyzed using a novel gas chromatography high resolution mass spectrometry data-processing workflow to overcome the bottleneck of processing large datasets and improve confidence in the resulting identified features. The toxicity of chemicals observed frequently in personal exposures were predicted to identify exposures of potential concern via inhalation route or other routes of airborne contaminant exposure. Three exposures were highlighted based on elevated toxicity: dichlorvos from insecticides (mosquito/malaria control), naphthalene partly from mothballs, and 183 polyaromatic hydrocarbons from multiple sources. Other exposures explored in this study are linked to diet and personal care products, cigarette smoke, sunscreen, and antimicrobial soaps. We highlight the potential for this workflow employing wearable passive samplers for prioritizing chemicals of concern at both the community and individual level, and characterizing sources of exposures for follow up interventions. Image 1 • Wristband passive samplers were used to detect 615 personal chemical exposures. • Exposure profiles of adults (aged 60–69) were most strongly associated with temperature. • In colder months, exposures increased from cooking, cleaning, and household products. • In warmer months, mosquito repellent, sunscreen, and second-hand smoke dominated exposures. [ABSTRACT FROM AUTHOR]

Compared to the general population, firefighters are known to sustain greater levels of exposure to hazardous compounds, despite their personal protective equipment, also known as turnout gear. Among the most significant toxins that firefighters are chronically exposed to are polycyclic aromatic hydrocarbons (PAHs). Additionally, firefighters have also been noted to exhibit an increased incidence of certain types of cancer. Considering a probable link between exposure to PAHs and increased rates of cancer in the fire service, we aim to document ambient chemical concentrations in the firefighter work environment. Our strategy involves the use of silicone-based wristbands that have the capacity to passively sorb PAHs. To determine if wristbands can serve as an effective chemical monitoring device for the fire service, silicone wristbands were pilot-tested as personal sampling devices for work environment risk monitoring in active-duty firefighters. Recovered wristbands underwent multiple extraction steps, followed by GC-MS analysis to demonstrate their efficacy in monitoring PAHs in the firefighter environment. Initial findings from all wristband samples taken from firefighters showed multiple exposures to various PAHs of concern for the health of the firefighters when in a fire environment. In addition to PAH monitoring, we examined known and potential sources of PAH contamination in their work environment. To that end, profiles of elevated PAH concentrations were documented at various fire stations throughout South Florida, for individual firefighters both during station duties and active fire response. • Firefighters are occupationally exposed to toxic and carcinogenic compounds such as polyaromatic hydrocarbons (PAHs). • Silicone-based passive sampling presents an easy, affordable means to document firefighter exposure. • PAH exposure observed on wristbands of firefighters reporting to fire scenes was greater than for non-fire wristbands. • Diagnostic PAH ratios support exposure originating from diesel combustion observed in the fire service environment. [ABSTRACT FROM AUTHOR]

In everyday life, people are exposed to different concentrations of airborne particles depending on the microenvironment where they perform their different activities. Such exposure can lead to high sub-micron particle doses. The received dose depends on particle concentration to which people are exposed (typically expressed in terms of number or surface area), time spent in each activity or microenvironment (time activity pattern) and amount of air inhaled (inhalation rate). To estimate an actual value of the received dose, all these parameters should be measured under real-life conditions; in fact, the concentrations should be measured on a personal scale (i.e. through a direct exposure assessment), whereas time activity patterns and inhalation rates specific to the activity performed should be considered. The difficulties in obtaining direct measurements of these parameters usually lead to adopt time activity patterns and inhalation rates already available in scientific literature for typical populations, and local outdoor particle concentrations measured with fixed monitoring stations and extrapolated for all the other microenvironments. To overcome these limitations, we propose a full-field method for estimating the received dose of a population sample, in which all the parameters (concentration levels, time activity patterns and inhalation rates) are measured under real-life conditions (also including the inhalation rates, that were evaluated on the basis of the measured heart rates). Specifically, 34 volunteers were continuously monitored for seven days and the data of sub-micron particle concentrations, activities performed, and inhalation rates were recorded. The received dose was calculated with the proposed method and compared with those obtained from different simplified methodologies that consider typical data of particle concentrations, time activity patterns and inhalation rates obtained from literature. The results show that, depending on the methodology used, the differences in the received daily dose can be significant, with a general underestimation of the most simplified method., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Smartphone-based sensing is becoming a convenient way to collect data in science, especially in environmental research. Recent studies that use smartphone sensing methods focus predominantly on single sensors that provide quantitative measurements. However, interdisciplinary projects call for study designs that connect both, quantitative and qualitative data gathered by smartphone sensors. Therefore, we present a novel open-source task automation solution and its evaluation in a personal exposure study with cyclists. We designed an automation script that advances the sensing process with regard to data collection, management and storage of acoustic noise, geolocation, light level, timestamp, and qualitative user perception. The benefits of this approach are highlighted based on data visualization and user handling evaluation. Even though the automation script is limited by the technical features of the smartphone and the quality of the sensor data, we conclude that task automation is a reliable and smart solution to integrate passive and active smartphone sensing methods that involve data processing and transfer. Such an application is a smart tool gathering data in population studies.

Objectives: The purpose of this research was to develop a method for monitoring personal exposure to benzyl violet 4B (BV) and direct blue 15 (DB) in workplace air for risk assessment., Methods: We evaluated the utility of the proposed method by examining the following: recovery; method limit of quantification; reproducibility; and storage stability of the samples., Results: An air sampling cassette containing a glass fiber filter was chosen as the sampler. BV and DB were extracted from the sampler filters with a solution of water and methanol (7:3, v/v) and then analyzed by a high-performance liquid chromatograph equipped with a photo-diode array detector. The overall recoveries from spiked samplers were 94-102% and 94-99% for BV and DB, respectively. The recovery after seven days of storage at 4°C exceeded 95%. The method limits of quantification were 0.250 and 1.25 μg/sample for BV and DB, respectively. The relative standard deviations, which represent the overall reproducibility defined as precision, were 0.6-4.1% and 0.8-2.9% for BV and DB, respectively., Conclusions: The proposed method enables 4 h personal exposure monitoring of BV and DB at concentrations of 1-2,000 μg/m 3 for BV and 5-2,000 μg/m 3 for DB, with a 240 l sampling. Thus, the proposed method is useful for estimating worker exposure to BV and DB.