Personal Exposure Monitoring Research Articles

A New Method Proposed for the Estimation of Exposure to Atmospheric Pollution through the Analysis of Black Pigments on the Lung Surface

Megacities can be considered excellent laboratories for studying the effects of the urban environment on human health. Typically, exposure to pollution is estimated according to daily or annual averages of pollutant concentrations, collected at monitoring stations, using satellite data for remote sensing of pollutant levels, considering proximity to major roads, or through personal exposure monitoring with portable sensors. However, these approaches fall short in identifying individual exposure values over a lifetime. It is well established that individuals living in large urban areas inhale atmospheric particles containing carbonaceous components, resulting in the deposition of black pigments in lung tissue, known as black carbon or anthracosis. This study aims to detail the procedures for assessing the deposition of such pigments, which serve as an estimate of an individual’s exposure to atmospheric pollution particles. Data collection involves administering detailed questionnaires and capturing lung images in the autopsy room. The analysis is based on macroscopic quantification of black pigments, supplemented by an evaluation of personal habits and the clinical histories of the individuals. This method of estimating lifetime exposure to inhaled particles provides a valuable tool for understanding the correlation between urban living and its potential health effects.

Exposure to airborne particulate matter in working from office and working from home employees

ABSTRACT The main aim of this study is to quantitatively evaluate the differences, in terms of exposure to PM (particulate matter), between WFO (working-from-office) and WFH (working-from-home) conditions. Two measurement surveys were performed: a long-term and a short-term campaign, focused on the monitoring of personal exposure to size-fractionated PM in these different working conditions. Results of the long-term campaign show that the WFH subject is exposed to higher (up to 4 times) PM concentration, compared to the WFO subject. Specific activities performed by the subjects impacted their exposure concentrations, even if the most relevant contribution to total exposure was made by desk work. Results of the short-term campaign indicate that the subjects can be divided into two groups: subjects most exposed during the WFH mode (HE_H – Higher_Exposure_Home) and subjects most exposed during the WFO mode (HE_O – Higher_Exposure_Office). HE_H group is exposed to levels of pollutants up to 4 times higher in the domestic than in the office environment, during the moment of desk work. The HE_O group is exposed to higher (double) concentration levels during desk work during the WFO day. Considering the possible growing trend towards remote work it is important to evaluate these “new domestic offices” comprehensively.

Disposable indicator card for personal monitoring of solar exposure

Although the Earths atmosphere provides substantial reduction of the incident radiant power in the most harmful spectral ranges, excessive exposure of untrained and/or unprotected human skin to solar radiation can easily result into acute and chronic adverse effects onto human skin. In order to reduce these effects, a simple tool for monitoring the incident radiant dose is proposed. We report on the design, development, lab scale fabrication, calibration and the roll-to-roll printing production of a photosensitive indicator cards intended for personal monitoring of solar exposure to which the user has been subjected. Two types of cards are being discussed. The first one is supposed as high sensitive one with a dose response to 1 and 2 SEDs, the second one is a less sensitive with a dose response to 3 and 4 SEDs. The calibration of the cards was performed with polychromatic simulated solar radiation without determining the spectral response, therefore we refer to the device as indicator card, not dosimeters. Moreover, properties of the photosensitive formulation employed for the fabrication of the indicator are presented alongside with the calibration of the printed indicator to dermatologically relevant values of the received solar exposure dose. Special attention is also paid to the large-scale practical production of such indicators by the roll-to-roll printing technology. Mechanical properties, stability, durability, practical utilisation, and other features are critically assessed.

Piloting co-developed behaviour change interventions to reduce exposure to air pollution and improve self-reported asthma-related health.

Exposure to air pollution can exacerbate asthma with immediate and long-term health consequences. Behaviour changes can reduce exposure to air pollution, yet its 'invisible' nature often leaves individuals unaware of their exposure, complicating the identification of appropriate behaviour modifications. Moreover, making health behaviour changes can be challenging, necessitating additional support from healthcare professionals. This pilot study used personal exposure monitoring, data feedback, and co-developed behaviour change interventions with individuals with asthma, with the goal of reducing personal exposure to PM2.5 and subsequently improving asthma-related health. Twenty-eight participants conducted baseline exposure monitoring for one-week, simultaneously keeping asthma symptom and medication diaries (previously published in McCarron et al., 2023). Participants were then randomised into control (n = 8) or intervention (n = 9) groups. Intervention participants received PM2.5 exposure feedback and worked with researchers to co-develop behaviour change interventions based on a health behaviour change programme which they implemented during the follow-up monitoring week. Control group participants received no feedback or intervention during the study. All interventions focused on the home environment. Intervention group participants reduced their at-home exposure by an average of 5.7 µg/m³ over the monitoring week (-23.0 to +3.2 µg/m³), whereas the control group had a reduction of 4.7 µg/m³ (-15.6 to +0.4 µg/m³). Furthermore, intervention group participants experienced a 4.6% decrease in participant-hours with reported asthma symptoms, while the control group saw a 0.5% increase. Similarly, the intervention group's asthma-related quality of life improved compared to the control group. This pilot study investigated a novel behaviour change intervention, utilising personal exposure monitoring, data feedback, and co-developed interventions guided by a health behaviour change programme. The study aimed to reduce personal exposure to fine particulate matter (PM2.5) and improve self-reported asthma-related health. Conducting a randomised controlled trial with 28 participants, co-developed intervention successfully targeted exposure peaks within participants' home microenvironments, resulting in a reduction in at-home personal exposure to PM2.5 and improving self-reported asthma-related health. The study contributes valuable insights into the environmental exposure-health relationship and highlights the potential of the intervention for individual-level decision-making to protect human health.

Personal exposure monitoring of fine and coarse particulate matter using exposure assessment models for elderly residents in Hong Kong

This study investigated the determinants of personal exposures (PE) to coarse (PM2.5-10) and fine particulate matter (PM2.5) for elderly communities in Hong Kong. The mean PE PM2.5 and PM2.5-10 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 PM2.5 compared to approximately 56% for PM2.5-10, possibly due to the coarse-size particles being more influenced by similar sources (road dust and construction dust emissions) compared to the PM2.5 particles. Individual PE to ambient (P/A) ratios for PM2.5 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 PM2.5-10, implying possible effective infiltration prevention of larger size particulate matter particles leading to dominant influences from the outdoor sources. The higher concentration of NO3− and SO42− in PM2.5-10 compared to PM2.5 suggests possible heterogeneous reactions of alkaline minerals leading to the formation of NO3− and SO42− in PM2.5-10 particles. The PE and ambient OC/EC ratios in PM2.5 (8.8 ± 3.3 and 10.4 ± 22.4, respectively) and in PM2.5-10 (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 PM2.5 and PM2.5-10 samples. The calibration coefficient as the association between personal and surrogate exposure measure of PE to PM2.5 (0.84) was higher than PM2.5-10 (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 PM2.5 and PM2.5-10 conditions. A comprehensive understanding of the PE to determinants in coarse particles is essential to further reduce potential exposure misclassification.

Personal exposure monitoring to polycyclic aromatic hydrocarbons bound to size-segregated aerosol

Air pollution is a global problem, where impaired air quality significantly damages human health and the environment. Twenty-four hours of personal exposure to size-segregated airborne particulate matter (PM) and associated polycyclic aromatic hydrocarbons (PAHs) were measured in 129 non-smoking residents living in two Czech cities, Ostrava (an industrial area with high levels of air pollution) and Ceske Budejovice (an agricultural area with lower air pollution level) in various seasons between years 2018–2020. Particulate matter (PM) was sampled by cascade impactors based on their aerodynamic diameter (dae, μm) and divided into size fractions: coarse (2.5 < dae), fine (0.25 < dae < 2.5) and ultrafine (<0.25). Size distributions of 20 priority PAHs adsorbed on these PM fractions were analyzed by gas chromatography coupled to tandem mass spectrometry in electron ionization (GC-EI-MS/MS). The total concentration of ∑20PAHs to which residents were exposed ranged from 0.09 ng/m3 to 47.18 ng/m3. A higher level of PAHs was detected in Ostrava (mean: 5.59 ng/m3) than in Ceske Budejovice (mean: 1.96 ng/m3). Statistically significant concentration differences between PAHs in individual seasons were observed in both sampled localities, with higher concentrations measured in winter than in summer. Fine and ultrafine particles predominated in the mass composition of the particulate matter. The ultrafine particle size contained 67–80% of total PAHs. Respiratory health risk was estimated based on inhalation cancer risk (ICR). Cancer risk attributable to personal inhalation exposure ranged from 2.8 × 10−8 to 4.3 × 10−4. In winter, higher cancer risk were found in Ostrava, mainly caused by a high concentration of carcinogenic PAHs bound to ultrafine particles. Overall, the personal monitoring data confirmed a higher air pollution burden in the industrial area and the winter season and highlighted the importance of focusing on ultrafine particles as the main carriers of potentially mutagenic and carcinogenic substances, such as PAHs. In addition, personal monitoring data provided more detailed and accurate information on individual-level exposures, revealing significant differences in exposure concentrations in people living in the same area.

Study of the Suitability of a Personal Exposure Monitor to Assess Air Quality

Study of the Suitability of a Personal Exposure Monitor to Assess Air Quality

ZnO Decorated Graphene-Based NFC Tag for Personal NO2 Exposure Monitoring during a Workday.

This paper presents the integration of a sensing layer over interdigitated electrodes and an electronic circuit on the same flexible printed circuit board. This integration provides an effective technique to use this design as a wearable gas measuring system in a target application, exhibiting high performance, low power consumption, and being lightweight for on-site monitoring. The wearable system proves the concept of using an NFC tag combined with a chemoresistive gas sensor as a cumulative gas sensor, having the possibility of holding the data for a working day, and completely capturing the exposure of a person to NO2 concentrations. Three different types of sensors were tested, depositing the sensing layers on gold electrodes over Kapton substrate: bare graphene, graphene decorated with 5 wt.% zinc oxide nanoflowers, or nanopillars. The deposited layers were characterized using FESEM, EDX, XRD, and Raman spectroscopy to determine their crystalline structure, morphological and chemical compositions. The gas sensing performance of the sensors was analyzed against NO2 (dry and humid conditions) and other interfering species (dry conditions) to check their sensitivity and selectivity. The resultant-built wearable NFC tag system accumulates the data in a non-volatile memory every minute and has an average low power consumption of 24.9 µW in dynamic operation. Also, it can be easily attached to a work vest.

Long-term monitoring of indoor, outdoor, and personal exposure to gaseous chemical compounds

Seasonal variations of chemical compounds in indoor air and outdoor air and personal exposure to these chemicals were continuously monitored for 6 years using four types of passive sampling devices: PSD-BPE/DNPH packed with 2,4-dinitrophenylhydrazine and trans-1,2-bis(2-pyridyl)ethylene coated silica for ozone and carbonyls; PSD-VOC packed with Carboxen 572 or Active Carbon Beads particles for volatile organic compounds; PSD-TEA packed with triethanolamine impregnated silica for acid gases; and PSD-TEA packed with phosphoric acid impregnated silica for basic gases. Many chemical compounds except for nitrogen dioxide, formic acid, and benzene showed seasonal variations with high concentrations in summer and low concentrations in winter. In particular, formaldehyde, nonanal, 2-ethyl-1-hexanol, 2,2,4-trimethyl-1,3-pentanediol monoisobutyrate, and ammonia concentrations showed remarkable seasonal variation. For example, the concentration of formaldehyde in February and August was 5.9 and 40 μg/m3, respectively, a difference of about 7 times. Although there were large differences in the concentrations in each house, the fluctuation pattern was almost the same every year in each house. By contrast, nitrogen dioxide, formic acid, and benzene concentrations were low in summer and high in winter. These compounds were generated by kerosine and gas stoves in winter. Long-term continuous monitoring revealed that annual mean concentrations could be estimated using data from February and August. Personal exposure concentrations could be classified into four patterns: chemicals affected by the indoor environment such as formaldehyde, chemicals affected by the outdoor environment such as ozone, chemicals affected by the occupational environment such as hexane, and background level chemicals such as benzene (without kerosine and gas stoves). Indoor and outdoor measurements are means to investigate the “health” of each environment. Personal exposure measurement using PSD-samplers is suitable for assessing the health risk of chemical compounds to humans.

Personal exposure to fine particulate matter (PM2.5) and self-reported asthma-related health

PM2.5 (fine particulate matter ≤2.5 μm in diameter) is a key pollutant that can produce acute asthma exacerbations and longer-term deterioration of respiratory health. Individual exposure to PM2.5 is unique and varies across microenvironments. Low-cost sensors (LCS) can collect data at a spatiotemporal resolution previously unattainable, allowing the study of exposures across microenvironments. The aim of this study is to investigate the acute effects of personal exposure to PM2.5 on self-reported asthma-related health.Twenty-eight non-smoking adults with asthma living in Scotland collected PM2.5 personal exposure data using LCS. Measurements were made at a 2-min time resolution for a period of 7 days as participants conducted their typical daily routines. Concurrently, participants were asked to keep a detailed time-activity diary, logging their activities and microenvironments, along with hourly information on their respiratory health and medication use. Health outcomes were modelled as a function of hourly PM2.5 concentration (plus 1- and 2-h lag) using generalized mixed-effects models adjusted for temperature and relative humidity.Personal exposures to PM2.5 varied across microenvironments, with the largest average microenvironmental exposure observed in private residences (11.5 ± 48.6 μg/m3) and lowest in the work microenvironment (2.9 ± 11.3 μg/m3). The most frequently reported asthma symptoms, wheezing, chest tightness and cough, were reported on 3.4%, 1.6% and 1.6% of participant-hours, respectively. The odds of reporting asthma symptoms increased per interquartile range (IQR) in PM2.5 exposure (odds ratio (OR) 1.29, 95% CI 1.07–1.54) for same-hour exposure. Despite this, no association was observed between reliever inhaler use (non-routine, non-exercise related) and PM2.5 exposure (OR 1.02, 95% CI 0.71–1.48).Current air quality monitoring practices are inadequate to detect acute asthma symptom prevalence resulting from PM2.5 exposure; to detect these requires high-resolution air quality data and health information collected in situ. Personal exposure monitoring could have significant implications for asthma self-management and clinical practice.

Obesity-related cardiometabolic indicators modify the associations of personal noise exposure with heart rate variability: A further investigation on the Study among Obese and Normal-weight Adults (SONA)

Elucidating the associations between environmental noise and heart rate variability (HRV) would be beneficial for the prevention and control of detrimental cardiovascular changes. Obese people have been found to manifest heightened susceptibility to the adverse effects of noise on HRV. However, the underlying mechanisms remain unclear. Based on 53 normal-weight and 44 obese young adults aged 18–26 years in Beijing, China, this study aimed to investigate the role of obesity-related cardiometabolic indicators for associations between short-term environmental noise exposure and HRV in the real-world context. The participants underwent personal noise exposure and ambulatory electrocardiogram monitoring using portable devices at 5-min intervals for 24 continuous hours. Obesity-related blood pressure, glucose and lipid metabolism, and inflammatory indicators were subsequently examined. Generalized mixed-effect models were used to estimate the associations between noise exposure and HRV parameters. The C-peptide, homeostasis model assessment of insulin resistance (HOMA-IR), and leptin levels were higher in obese participants compared to normal-weight participants. We observed amplified associations between short-term noise exposure and decreases in HRV among participants with higher C-peptide, HOMA-IR, and leptin levels. For instance, a 1 dB(A) increment in 3 h-average noise exposure level preceding each measurement was associated with changes of −0.20% (95%CI: −0.45%, 0.04%) and −1.35% (95%CI: −1.85%, −0.86%) in standard deviation of all normal to normal intervals (SDNN) among participants with lower and higher C-peptide levels, respectively (P for interaction <0.05). Meanwhile, co-existing fine particulate matter (PM2.5) could amplify the associations between noise and HRV among obese participants and participants with higher C-peptide, HOMA-IR, and leptin levels. The more apparent associations of short-term exposure to environmental noise with HRV and the effect modification by PM2.5 may be partially explained by the higher C-peptide, HOMA-IR, and leptin levels of obese people.

Understanding the time-activity pattern to improve the measurement of personal exposure: An exploratory and experimental research

Although ambient fine particulate matter (PM2.5) concentrations and their components are commonly used as proxies for personal exposure monitoring, developing an accurate and cost-effective method to use these proxies for personal exposure measurement continues to pose a significant challenge. Herein, we propose a scenario-based exposure model to precisely estimate personal exposure level of heavy metal(loid)s (HMs) using scenario HMs concentrations and time-activity patterns. Personal exposure levels and ambient pollution levels for PM2.5 and HMs differed significantly with corresponding personal/ambient ratios of approximately 2, and exposure scenarios could narrow the assessment error gap by 26.1–45.4%. Using a scenario-based exposure model, we assessed the associated health risks of a large sample population and identified that the carcinogenic risk of As exceeded 1 × 10−6, while we observed non-carcinogenic risks from As, Cd, Ni, and Mn in personal exposure to PM2.5. We conclude that the scenario-based exposure model is a preferential alternative for monitoring personal exposure compared to ambient concentrations. This method ensures the feasibility of personal exposure monitoring and health risk assessments in large-scale studies.

Emissions and Exposures Associated with the Use of an Inconel Powder during Directed Energy Deposition Additive Manufacturing.

Additive manufacturing (AM) has been linked to potential exposure-related health risks, however, there is a paucity of sufficient research. This study aimed to supply information regarding emissions and exposure during directed energy deposition (DED) AM using inconel 718, with the main constituents being nickel, chromium, and cobalt. By using standardized occupational hygiene methods, the measurement strategy consisted of a combined approach, including powder characterization, particle emission monitoring, and personal exposure monitoring of AM operators. Powder characterization of virgin and used powder indicated no significant difference in particle size, shape, or elemental composition. Particle number emissions ranged between 102 and 105 p/cm3 for submicron particles (<1 µm in size). There was no significant difference in the particle emission rate between the three phases of AM or the two types of DED machines (p > 0.05). The particle emission rate for submicron particles peaked at 2.8 × 109 p/min. Metals of concern to human health were detected during the AM process but were considerably lower than the relevant exposure limits. This study confirms particle emissions, predominantly in the submicron range, above the background concentration during DED AM and, although insignificant in terms of potential health effects, AM operators are exposed to detectable concentrations of the metal constituents of inconel.

Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis.

Mobile ambient air quality monitoring is rapidly changing the current paradigm of air quality monitoring and growing as an important tool to address air quality and climate data gaps across the globe. This review seeks to provide a systematic understanding of the current landscape of advances and applications in this field. We observe a rapidly growing number of air quality studies employing mobile monitoring, with low-cost sensor usage drastically increasing in recent years. A prominent research gap was revealed, highlighting the double burden of severe air pollution and poor air quality monitoring in low- and middle-income regions. Experiment-design-wise, the advances in low-cost monitoring technology show great potential in bridging this gap while bringing unique opportunities for real-time personal exposure, large-scale deployment, and diversified monitoring strategies. The median value of unique observations at the same location in spatial regression studies is ten, which can be used as a rule-of-thumb for future experiment design. Data-analysis-wise, even though data mining techniques have been extensively employed in air quality analysis and modeling, future research can benefit from exploring air quality information from nontabular data, such as images and natural language.

Assessment of children's personal and land use regression model-estimated exposure to NO2 in Springfield, Massachusetts

Ambient nitrogen dioxide (NO2) is derived from tailpipe vehicle emission and is linked with various of health outcomes. Personal exposure monitoring is crucial for accurate assessment of the associated disease risks. This study aimed to evaluate the utility of a wearable air pollutant sampler in determining the personal NO2 exposure of school children for comparison with a model-based personal exposure assessment. We employed cost-effective, wearable passive samplers to directly measure personal exposure of 25 children (aged 12–13 years) in Springfield, MA to NO2 over a five-day period in winter 2018. NO2 levels were additionally measured at 40 outdoor sites in the same region using stationary passive samplers. A land use regression (LUR) model was developed based on the ambient NO2 measures, with a good prediction performance (R2 = 0.72) using road lengths, distance to highway, and institutional land area as predictor variables. Time-weighted averages (TWA), which incorporated the time-activity patterns of participants and LUR-derived estimates in children's primary microenvironments (homes, the school and commute paths), were calculated as an indirect measure of personal NO2 exposure. Results indicated that the conventional residence-based exposure estimate approach, often used in epidemiological studies, differed from the direct personal exposure and could overestimate the personal exposure by up to 109 %. TWA improved personal NO2 exposure estimates by accounting for the time activity patterns of individuals, a difference of 5.4 % ± 34.2 % was found for exposures compared to wristband measurements. Nevertheless, the personal wristband measurements exhibited a large variability due to the potential contributions from indoor and in-vehicle NO2 sources. The findings suggest that exposure to NO2 can be highly personalized based on individual activities and contact with pollutants in specific microenvironments, reaffirming the importance of measuring personal exposure.

Optimal sensor placement for personal inhalation exposure detection in static and dynamic office environments

Modern health and productivity concerns related to air pollutant exposure in buildings have sparked the need for occupant-centric monitoring and ventilation control. The existing personal exposure monitoring is often restricted to stationary air quality sensors and static occupancy. This study aims to identify optimal stationary sensor placement that best represents exposure to CO2, PM2.5, and PM10 under static and dynamic office occupancies. A total of 48 controlled chamber experiments were executed in four office layouts with variation of occupant numbers (2, 4, 6 or 8), activities (sitting/standing and static/dynamic), ventilation strategies (mixing/displacement) and air change rates (0.5–0.7 h−1, 2.4–2.6 h−1, and 3.8–4.2 h−1). The breathing zone concentration of a reference occupant was monitored with concurrent measurements at seven stationary locations: front edge of the desk, sides of two desks, two sidewalls, and two exhaust vents. The proximity of sensors to the reference occupant and ventilation rate/strategy were important determinants of personal exposure detection. Regression analyses showed that the wall- and desk-mounted CO2 sensors near the occupant (<1 m) best captured CO2 exposure under dynamic–standing activities (R2∼0.4). The wall immediately behind the seated occupant and the ceiling-mounted exhaust near the standing occupant (<1–1.5 m) were the best sensor placements for capturing exposure to particles (R2=0.8–0.9). Separating static from dynamic occupancy activities resulted in improved exposure prediction by 1.4-6.1× . This study is a step towards provision of practical guidelines on stationary air quality sensor placement indoors with the consideration of dynamic occupancy profiles.

Assessing exposure to air pollution during pregnancy:The role of personal exposure monitoring.

Dr. Wellenius serves as a consultant to the Health Effects Institute (Boston, MA) and Google, LLC (Mountain View, CA).

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship between personal and stationary air pollutant measurements in residences of 37 participants working from home during the heating season. Stationary environmental monitors (SEMs) were located in the bedroom, living room or home office and personal exposure monitors (PEMs) were worn by the participants. SEMs and PEMs included both real-time sensors and passive samplers. During three consecutive weekdays, continuous data were obtained for particle number concentration (size range 0.3–10 μm), carbon dioxide (CO2), and total volatile organic compounds (TVOC), while passive samplers collected integrated measures of 36 volatile organic compounds (VOCs) and semi volatile organic compounds (SVOCs). The personal cloud effect was detected in >80% of the participants for CO2 and >50% participants for PM10. Multiple linear regression analysis showed that a single CO2 monitor placed in the bedroom efficiently represented personal exposure to CO2 (R2 = 0.90) and moderately so for PM10 (R2 = 0.55). Adding a second or third sensor in a residence did not lead to improved exposure estimates for CO2, with only 6–9% improvement for particles. Selecting data from SEMs when participants were in the same room improved personal exposure estimates by 33% for CO2 and 5% for particles. Out of 36 detected VOCs and SVOCs, 13 had at least 50% higher concentrations in personal versus stationary samples. Findings from this study aid improved understanding of the complex dynamics of gaseous and particle pollutants and their sources in residences, and could support the development of refined procedures for residential air quality monitoring and inhalation exposure assessment.

135 The Role of Passive Sampling in Environmental Monitoring – Theory &amp; Recent Advancements

Abstract Passive sampling is an established technique in the monitoring and characterisation of Volatile Organic Compounds (VOCs). Employed across various fields such as personal exposure monitoring, large-scale environmental studies and indoor air monitoring. Passive sampling provides a cheap, convenient and reliable method of characterising a range of VOCs across several samples in large-scale air monitoring programmes. Passive sampling possesses several favourable qualities to alternative methods, such as no pump requirements and a non-invasive design. Further to this, early sorbent-based passive samplers were required to undergo solvent extraction as a preparation step before analysis. The solvent extraction limited air-speed effects at the surface of the badge, preventing the stable conditions required for passive sampling. Recent developments allow analytes to desorb from the sampler via thermal desorption (TD), improving sensitivity and accuracy that were unachievable through earlier sorbent-based sampling devices. Within this presentation I will detail the latest TD-compatible passive samplers, exploring axial and radial sampling technologies and how these technologies are advancing environmental monitoring.

Performance evaluation of portable dual-spot micro-aethalometers for source identification of black carbon aerosols: application to wildfire smoke and traffic emissions in the Pacific Northwest

Abstract. Black carbon (BC) is a component of particulate matter, emitted from the incomplete combustion of carbonaceous fuels. The presence of BC in the atmosphere can disrupt the atmospheric radiation budget, and exposure to BC can adversely affect human health. Multi-wavelength light-absorption-based dual-spot aethalometers can be used to quantify the source and characteristics of BC from traffic or biomass-burning-based sources. However, aethalometer measurements are affected by artifacts such as aerosol loading and light scattering; hence, they often need correction to reduce measurement uncertainty. This work assesses the performance of the recently developed portable aethalometer (MA300, AethLabs). Due to their portability and ease of usage, MA300s can be suitable for mobile and personal exposure monitoring. Here, we evaluate BC concentration and source apportionment accuracy of three MA300 units relative to a widely used aethalometer, the AE33 (Magee Scientific). Synchronous field measurements were performed at a major traffic intersection during regular and wildfire-smoke-affected days in Vancouver, Canada. We find that MA300-reported BC mass concentrations were strongly correlated (Slope range between 0.73 and 1.01, with R2 = 0.9) compared to the reference instrument, yet there is visible instrumental variability in the normalized concentrations (5 %) across three units. The mean absolute error of MA300-reported BC concentrations ranged between 0.44–0.98 µg m−3, with the highest deviations observed in wildfire-smoke-affected polluted days. From the aerosol light absorption measurement perspective, MA300s tend to underestimate the absorption coefficients (babs) across the five wavelengths. UV channel light absorption results were subjected to the highest amount of noise and were found to be consistently underestimating in all the MA300 units, leading to systematic bias in source apportionment analysis. Absorption Ångström exponent values from the MA300 units were able to capture the variability of aerosol sources within a day, with a mean value of 1.15 during clean days and 1.46 during wildfire-smoke-affected days. We investigated the application of the latest non-linear aethalometer correction protocols in the MA300 and found that flow fluctuations enhanced noise across all channels, compared to onboard instrument correction. We also identify that the UV (λ = 370 nm) channel absorption measurements are most sensitive to instrumental artifacts during the wildfire-smoke-affected period. Hence, as an alternative to traditional UV and IR (λ = 880 nm)-based BC source apportionment methods, in this work, we tested the blue (λ = 470 nm) and IR wavelengths for BC source apportionment calculation. When the blue–IR-based source apportionment technique is adopted instead of the UV–IR, there is a 10 % (on average) decrease in the percentage difference of the apportioned components from the reference monitor.