Assessment of PM2.5 Concentration at University Transit Bus Stops Using Low-Cost Aerosol Monitors by Student Commuters.

Particulate matter of 2.5 µm and smaller (PM2.5) is known to cause many respiratory health problems, such as asthma and heart disease. A primary source of PM2.5 is emissions from cars, trucks, and buses. Emissions from university transit bus systems could create zones of high PM2.5 concentration at their bus stops. This work recruited seven university students who regularly utilized the transit system to use a low-cost personal aerosol monitor (AirBeam) each time they arrived at a campus bus stop. Each participant measured PM2.5 concentrations every time they were at a transit-served bus stop over four weeks. PM2.5 concentration data from the AirBeam were compared with an ADR-1500 high-cost monitor and EPA PM2.5 reference measurements. This methodology allowed for identifying higher-than-average concentration zones at the transit bus stops compared to average measurements for the county. By increasing access to microenvironmental data, this project can contribute to public health efforts of personal protection and prevention by allowing individuals to measure and understand their exposure to PM2.5 at the bus stop. This work can also aid commuters, especially those with pre-existing conditions who use public transportation, in making more informed health decisions and better protecting themselves against new or worsening respiratory conditions.

[Personal nitrogen oxides exposure levels and related influencing factors in adults over 35 years old in Tianjin and Shanghai].

OBJECTIVE: To investigate personal exposures to nitrogen oxides (NOX) and nitrogen di-oxide (NO2) and the influence of baseline personal characteristics, living environment and daily activity patterns of the participants on the exposures among adults over 35 in Tianjin and Shanghai. METHODS: In this panel study, 91 healthy nonsmoking adults aged over 35 from Tianjin and Shanghai participated in our study. The study was conducted in summer and winter. The participants were followed for three times with an interval of at least two weeks. Only participants in Shanghai were followed once in winter because of the COVID-19 pandemic. Twenty-seven participants completed follow-up visits in both seasons. We measured their 24 h personal exposures to NOX and NO2and collected their baseline and time-activity information through questionnaire/diary. The linear mixed model was used to analyze the associations between potential influencing factors and personal NOX and NO2 exposure levels. RESULTS: There were 349 follow-up visits with valid 24 h personal NO2 and NOX exposure measurements in the two cities. The ave-rage 24 h personal exposures to NO2 and NOX (volume fraction) in Tianjin participants were 18.0×10-9 and 26.2×10-9 in summer, and 31.0×10-9 and 54.9×10-9 in winter, respectively; and the average 24 h personal exposures to NO2 and NOX in Shanghai participants were 38.7×10-9 and 100.0×10-9 in summer, and 45.5×10-9 and 139.2×10-9 in winter, respectively. The results of univariate regression analysis showed that their personal NOX exposure levels were significantly associated with city, season, gender, average daily cooking times, and ambient NO2 concentrations measured at fixed-site monitoring stations. In addition to the above factors, the personal NOX exposure levels were also significantly associated with educational level and the personal NO2 exposure levels were also significantly associated with passive smoking, average daily home time, cooking energy type, residential distance from main traffic road, and use of kitchen ventilators. Multivariate regression analysis showed that the personal exposure levels of NO2 and NOX were significantly lower in Tianjin than that in Shanghai, were significantly lower in summer than that in winter, and were significantly and positively associated with ambient NO2 concentrations measured at fixed-site monitoring stations. In addition, personal NOX exposure levels were significantly lower in females than in males, and personal NO2 exposure levels were significantly positively associated with average daily cooking times and significantly inversely associated with average daily home time. For every interquartile range (IQR) increase (12.7×10-9) in ambient NO2, the personal NO2 exposure levels increased by 27.5% (95%CI: 17.0%-38.9%), and personal NOX exposure levels increased by 16.1% (95%CI: 7.1%-25.8%). CONCLUSION: Season, city and ambient NO2 concentrations are significant influencing factors of personal exposure levels of NO2and NOX. At the same time, the personal exposures levels of NO2are also affected by lifestyle factors. Our study provides scientific evidence for making precise air pollution control decisions and reducing the exposure levels of NOX in the population.

A comprehensive review of 5G NR RF-EMF exposure assessment technologies: fundamentals, advancements, challenges, niches, and implications.

This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as "sensors" or "sensor nodes", that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.

Personal Exposure to Sulfuric Acid in the Electroplating Industry: Development and Validation of a Predictive Model.

This study aimed to measure personal exposure to sulfuric acid in the electroplating industry to establish a predictive model and test its validation. We collected indoor air parameters and related information from four electroplating plants. Silica gel sorbents were used to collect air samples using high-performance ion chromatography. We collected air samples from three plants (i.e., Plant B, Plant C, and Plant D) and applied multiple linear regressions to build a predictive model. Eight samples collected from the fourth plant (i.e., Plant A) were used to validate the model. A total of 41 samples were collected with a mean of 25.0 ± 9.8 µg/m3 (range 12.1-51.7 µg/m3) in this study, including Plant A (8 samples, 17.5 ± 2.8 µg/m3, 13.0-22.0 µg/m3), Plant B (11 samples, 36.5 ± 9.7 µg/m3, 23.1-51.7 µg/m3), Plant C (11 samples, 16.4 ± 1.7 µg/m3, 12.1-17.8 µg/m3), and Plant D (11 samples, 27.4 ± 1.7 µg/m3, 24.1-29.9 µg/m3). Plant B was significantly higher in sulfuric acid than the other plants. Workers from the electroplating process plants were exposed to sulfuric acid at 29.0 ± 11.5 µg/m3. The predictive model for personal exposure to sulfuric acid fit the data well (r2 = 0.853; adjusted r2 = 0.837) and had an accuracy of 5.52 µg/m3 (bias ± precision; 4.98 ± 2.38 µg/m3), validated by the personal sampling of the fourth plant. This study observed that sulfuric acid exposure was lower than the permissible exposure level of 1000 µg/m3 in Taiwan and the United States, and only two samples were lower than the European Union standard of 50 µg/m3. The developed model can be applied in epidemiological studies to predict personal exposure to sulfuric acid in plants using electroplating.

Validity of Mobility-Based Exposure Assessment of Air Pollution: A Comparative Analysis with Home-Based Exposure Assessment.

Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.

Characterization of airborne endotoxin in personal exposure to fine particulate matter (PM2.5) and bioreactivity for elderly residents in Hong Kong.

The heavy metals and bioreactivity properties of endotoxin in personal exposure to fine particulate matter (PM2.5) were characterized in the analysis. The average personal exposure concentrations to PM2.5 were ranged from 6.8 to 96.6 µg/m3. The mean personal PM2.5 concentrations in spring, summer, autumn, and winter were 32.1±15.8, 22.4±11.8, 35.3±11.9, and 50.2±19.9 µg/m3, respectively. There were 85 % of study targets exceeded the World Health Organization (WHO) PM2.5 threshold (24 hours). The mean endotoxin concentrations ranged from 1.086 ± 0.384-1.912 ± 0.419 EU/m3, with a geometric mean (GM) varied from 1.034 to 1.869. The concentration of iron (Fe) (0.008-1.16 µg/m3) was one of the most abundant transition metals in the samples that could affect endotoxin toxicity under Toll-Like Receptor 4 (TLR4) stimulation. In summer, the interleukin 6 (IL-6) levels showed statistically significant differences compared to other seasons. Spearman correlation analysis showed endotoxin concentrations were positively correlated with chromium (Cr) and nickel (Ni), implying possible roles as nutrients and further transport via adhering to the surface of fine inorganic particles. Mixed-effects model analysis demonstrated that Tumor necrosis factor-α (TNF-α) production was positively associated with endotoxin concentration and Cr as a combined exposure factor. The Cr contained the highest combined effect (0.205-0.262), suggesting that Cr can potentially exacerbate the effect of endotoxin on inflammation and oxidative stress. The findings will be useful for practical policies for mitigating air pollution to protect the public health of the citizens.

Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression.

Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disorder of the central nervous system, leading to progressive functional impairments. Predicting disease progression with a probabilistic and time-dependent approach might help suggest interventions for a better management of the disease. Recently, there has been increasing focus on the impact of air pollutants as environmental factors influencing disease progression. This study employs a Continuous-Time Markov Model (CMM) to explore the impact of air pollution measurements on MS progression using longitudinal data from MS patients in Italy between 2013 and 2022. Preliminary findings indicate a relationship between air pollution and MS progression, with pollutants like Particulate Matter with a diameter of 10 micrometers (PM10) or 2.5 micrometers (PM2.5), Nitrogen Dioxide (NO2), and Carbon Monoxide (CO) showing potential effects on disease activity.

Nasal filter reveal exposure risks of inhalable particulates and heavy metals in urban women.

Urban populations, especially women, are vunerable to exposure to airborne pollution, particularly inhalable particulates (PM10). Thus, more accurate measurement of PM10 levels and evaluating their health effects is critical for guiding policy to improve human health. Previous studies obtained personal PM10 with time-weighted average by air filter-based sampling (AFS), which ignores individual differences and behavioral patterns. Here, we used nasal filters instead of AFS to obtain actual inhaled PM10 under short-term exposure for urban dwelling women during a severe haze event in Beijing in 2016. The levels of six heavy metals such as As, Cd, Ni, Cr, Pb, and Co in PM10 were investigated, and carcinogenic and non-carcinogenic risks evaluated based on an adjusted US EPA health risk assessment model. The health endpoints for urban dwelling women were further assessed through an exposure-reponse model. We found that the hourly inhaled dose of PM10 obtained through the nasal filter was about 2.5-17.6 times that obtained by AFS, which also resulted in 4.41-11.30 times more morbidity than estimated by AFS (p < 0.05). Proximity to traffic emissions resulted in greater exposure to particulate matter (>18.8 µg/kg·h) and heavy metals (>2.2 ng/kg·h), and these populations are therefore at greatest risk of developing non-cancer (HI = 4.16) and cancer (Rt = 7.8 × 10-3) related morbities.

Association between exposure to airborne trichloramine and health effects in indoor swimming pool workers.

OBJECTIVE: The main objective of this study was to comprehensively investigate the association between trichloramine (TCA) exposure and respiratory health effects in swimming pool workers. METHODOLOGY: In this study, air sampling was performed for TCA concentrations at fixed locations (static measurements) and on individual workers (personal measurements) in six indoor public swimming pools during periods of high swimmer attendance over the winter school break. Health effects were evaluated using questionnaires and fractional exhaled nitric oxide (FENO) tests performed before and after the working day. RESULTS: In these swimming pools, the environmental TCA concentration ranged from 0.11 to 0.88 mg/m³. Worker exposure ranged from 0.05 to 0.72 mg/m³ for personal measurements. Furthermore, in each swimming pool, the average worker exposure to TCA exceeded the recommended occupational exposure limit of 0.35 mg/m³. Personal TCA measurements were consistently lower than static measurements performed around the pool, with a reduction ranging from 21% to 49%. This can be explained by the time that the workers spend in the pool area, office, and break room. The most common respiratory health effects self-reported by the workers were coughing, shortness of breath, and sneezing with prevalence rates of 38%, 37%, and 35%, respectively. This study demonstrated an association between TCA exposure and eye irritation. Analysis of the FENO tests revealed that individuals with preexisting asthma or allergies exhibited sustained FENO elevation. CONCLUSION: The findings suggest that occupational exposure to TCA in indoor swimming pools is a matter of concern. Implementing and improving workplace safety measures is crucial for safeguarding the respiratory health of swimming pool workers.

Frequency of personal care product use among reproductive-aged Black individuals and associations with socio-demographic characteristics.

BACKGROUND: Compared to White women, Black women in the United States are more likely to use personal care products (PCPs) with higher concentrations of endocrine-disrupting chemicals (EDCs) and harsher chemical formulations. This may contribute to differential health outcomes in Black women such as increased risk of breast cancer, cardiometabolic outcomes, adverse birth outcomes, and uterine fibroids. OBJECTIVE: Classify distinct PCP use patterns across multiple types of products and examine how patterns vary by socio-demographic characteristics. METHODS: The Study of Environment, Lifestyle and Fibroids is a cohort study of reproductive-aged Black individuals living around Detroit, Michigan. Using self-reported data on frequency of PCP collected between 2013-2018, we employed latent class analysis to identify distinct groups of participants with similar PCP use. Socio-demographic characteristics were compared across latent classes. RESULTS: Among 1562 participants, we identified 6 latent classes: Lower Overall; Higher Nailcare; Higher Skincare; Moderate Overall; Higher Makeup/Haircare/Skincare; Higher Overall. Makeup and nailcare usage were the most predictive for classifying participants into groups. Participants in classes with less frequent use of all PCPs and those with only high use of nailcare products, were more likely to report lower socio-economic status (SES), be current smokers, have a body mass index of ≥35 kg/m2, and have ≥3 births. In comparison, participants in classes with average and more frequent use of PCPs were more likely to report higher SES, be non-smokers, be nulliparous, and have ever used oral contraceptives. IMPACT STATEMENT: This study is one of the first detailed assessments of PCP usage among a large cohort of young adult Black women that considers multiple product categories including makeup, hair, skin, nail, and vaginal products. Latent class analysis was used to capture complex patterns of PCP use and identify distinct groups of individuals with similar product use. Although the latent classes are specific to this study population, the identified socio-demographic characteristics or behaviors associated with latent classes may inform targeted and impactful exposure reduction strategies in similar populations.

Monitoring human exposure to four parabens and triclosan: comparing silicone wristbands with spot urine samples as predictors of internal dose.

BACKGROUND: People are exposed to a variety of chemicals each day as a result of their personal care product (PCP) use. OBJECTIVE: This study was designed to determine if silicone wristbands provide a quantitative estimate of internal dose for phenols commonly associated with PCPs, with a focus on triclosan and four parabens: methyl-, ethyl-, propyl-, and butylparaben. Uptake of these compounds into wristbands and correlations with internal dose were assessed. METHODS: Ten adults from central North Carolina wore five silicone wristbands, with one wristband removed each day for 5 days. Each participant provided a 24 h urine sample and a random spot urine sample each day, in which paraben and triclosan metabolites were evaluated. RESULTS: All parabens and triclosan were detected frequently in wristbands and, except for butylparaben, in urine samples. Wristband and spot urine concentrations of parabens and triclosan were both compared to a measurement of internal dose (i.e., the total metabolite mass excreted over 5 days as a measurement of internal dose). IMPACT STATEMENT: The two most hydrophobic compounds investigated, butylparaben and triclosan, displayed significant linear uptake in wristbands over 5 days, whereas concentrations of methyl- and ethylparaben displayed a steady state concentration. In general, wristbands and spot urine samples were similarly correlated to internal dose for frequently detected parabens and triclosan.  However, wristbands have additional advantages including higher detection rates and reduced participant burden that may make them more suitable tools for assessing exposure to PCPs.

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

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. IMPACT STATEMENT: 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.

Chronic household air pollution and exposure patterns among Himalayan nomads.

BACKGROUND: Household air pollution (HAP) is a major risk factor of non-communicable diseases, causing millions of premature deaths each year in developing nations. Populations living at high altitudes are particularly vulnerable to HAP and associated health outcomes. OBJECTIVES: This study aims to explore the relationships between activity patterns, HAP, and an HAP biomarker among 100 Himalayan nomadic households during both cooking and heating-only periods. METHODS: Household CO was monitored in 100 rural homes in Qinghai, China, at 3500 m on the Himalayan Plateau among Himalayan nomads. Carboxyhemoglobin (COHb) was used as a biomarker to assess exposure among 100 male and 100 female heads of household. Linear mixed-effects models were used to explore the relationship between COHb and activity patterns. RESULTS: Cooking periods were associated with 7 times higher household CO concentrations compared with heating periods (94 ± 56 ppm and 13 ± 11 ppm, respectively). Over the three-day biomarker-monitoring period in each house, 99% of subjects had at least one COHb measurement exceeding the WHO safety level of 2%. Cooking was associated with a 32% increase in COHb (p < 0.001). IMPACT STATEMENT: This study on household air pollution (HAP) in high-altitude regions provides important insights into the exposure patterns of nomadic households in Qinghai, China. The study found that cooking is the primary factor influencing acute carbon monoxide (CO) exposure among women, while heating alone is sufficient to elevate CO exposure above WHO guidelines. The results suggest that cooking-only interventions have the potential to reduce HAP exposure among women, but solutions for both cooking and heating may be required to reduce COHb to below WHO guidelines. This study's findings may inform future interventions for fuel and stove selection to reduce HAP and exposure among other populations.

Potential exposure of adults and children to particles from resuspended nano-enabled consumer sprays.

The increasing application of nanotechnology has resulted in a growing number of nano-enabled consumer products, and they could be important contributors to indoor particulate matter, with potential adverse health effects. This study investigated the exposure of adults and children to the released and resuspended manufactured particles from seven nano-enabled consumer sprays. Sedimentation and resuspension of released particles were investigated in a newly constructed 2.8 × 1.6 × 2.4 m3 chamber. The resuspension of deposited particles was investigated as a function of product type, flooring material (e.g., carpet and vinyl), resuspension force (e.g., walking by an adult and motion of a robotic sampler that simulated a child), and measurement height. The concentration of released and resuspended particles in the air was determined using Button Aerosol Samplers (SKC Inc.) with 25-mm 2 µm-pore PTFE filters. Samplers were positioned in the experimenter's breathing zone (e.g., 1.5 m for adults and 0.3 m for a child-simulating robot) and at fixed stations of 0.3 m and 1.1 m heights. Resuspended particle mass concentrations ranged from 28 to 905 µg/m3, and the resuspension rates of deposited spray particles for the same variable combinations varied from 10-4 to 10-1 h-1, depending on product type, flooring material, sampling height, and resuspension force. Particle resuspension rates from carpet were up to 320 % higher than resuspension rates from vinyl flooring, resuspension rates measured at 0.3 m were up to 195 % higher than the rates measured with a 1.1 m stationary sampler, and resuspension rates due to a walking adult were up to 243 % higher than resuspension rates caused to a moving robot that simulated a child. Overall, these data on the resuspension of particles from nano-enabled consumer sprays could help us understand the resulting exposures and support future studies on human exposure reduction.

The Association Between Personal Air Pollution Exposures and Fractional Exhaled Nitric Oxide (FeNO): A Systematic Review.

PURPOSE OF REVIEW: Airway inflammation is a common biological response to many types of environmental exposures and can lead to increased nitric oxide (NO) concentrations in exhaled breath. In recent years, several studies have evaluated airway inflammation using fractional exhaled nitric oxide (FeNO) as a biomarker of exposures to a range of air pollutants. This systematic review aims to summarize the studies that collected personal-level air pollution data to assess the air pollution-induced FeNO responses and to determine if utilizing personal-level data resulted in an improved characterization of the relationship between air pollution exposures and FeNO compared to using only ambient air pollution exposure data. RECENT FINDINGS: Thirty-six eligible studies were identified. Overall, the studies included in this review establish that an increase in personal exposure to particulate and gaseous air pollutants can significantly increase FeNO. Nine out of the 12 studies reported statistically significant FeNO increases with increasing personal PM2.5 exposures, and up to 11.5% increase in FeNO per IQR increase in exposure has also been reported between FeNO and exposure to gas-phase pollutants, such as ozone, NO2, and benzene. Furthermore, factors such as chronic respiratory diseases, allergies, and medication use were found to be effect modifiers for air pollution-induced FeNO responses. About half of the studies that compared the effect estimates using both personal and ambient air pollution exposure methods reported that only personal exposure yielded significant associations with FeNO response. The evidence from the reviewed studies confirms that FeNO is a sensitive biomarker for air pollutant-induced airway inflammation. Personal air pollution exposure assessment is recommended to accurately assess the air pollution-induced FeNO responses. Furthermore, comprehensive adjustments for the potential confounding factors including the personal exposures of the co-pollutants, respiratory disease status, allergy status, and usage of medications for asthma and allergies are recommended while assessing the air pollution-induced FeNO responses.

Comparison of personal exposure to black carbon levels with fixed-site monitoring data and with dispersion modelling and the influence of activity patterns and environment.

BACKGROUND: Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known. OBJECTIVE: We aimed to explore this relation for black carbon (BC) in central Stockholm. METHODS: Families (n = 46) with an infant, one parent working and one parent on parental leave, carried battery-operated BC instruments for 7 days. Routine BC monitoring data were obtained from rural background (RB) and urban background (UB) sites. Outdoor levels of BC at home and work were estimated in 24 h periods by dispersion modelling based on hourly real-time meteorological data, and statistical meteorological data representing annual mean conditions. Global radiation, air pressure, precipitation, temperature, and wind speed data were obtained from the UB station. All families lived in the city centre, within 4 km of the UB station. RESULTS: The average level of 24 h personal BC was 425 (s.d. 181) ng/m3 for parents on leave, and 394 (s.d. 143) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) ng/m3 at UB. Modelled BC levels at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24 h BC variability for parents on leave and 25% for working parents. Modelled home BC and observed air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents. IMPACT: Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to actual personal exposure is often not known. In this study we showed that both routine monitoring and modelled data explained less than 35% of variability in personal black carbon exposure. Hence, short-term health effects studies based on fixed site monitoring or spatio-temporal modelling are likely to be underpowered and subject to bias.

Sources of personal PM2.5 exposure during pregnancy in the MADRES cohort.

BACKGROUND: Personal exposure to fine particulate matter (PM2.5) is impacted by different sources each with different chemical composition. Determining these sources is important for reducing personal exposure and its health risks especially during pregnancy. OBJECTIVE: Identify main sources and their contributions to the personal PM2.5 exposure in 213 women in the 3rd trimester of pregnancy in Los Angeles, CA. METHODS: We measured 48-hr integrated personal PM2.5 exposure and analyzed filters for PM2.5 mass, elemental composition, and optical carbon fractions. We used the EPA Positive Matrix Factorization (PMF) model to resolve and quantify the major sources of personal PM2.5 exposure. We then investigated bivariate relationships between sources, time-activity patterns, and environmental exposures in activity spaces and residential neighborhoods to further understand sources. RESULTS: Mean personal PM2.5 mass concentration was 22.3 (SD = 16.6) µg/m3. Twenty-five species and PM2.5 mass were used in PMF with a final R2 of 0.48. We identified six sources (with major species in profiles and % contribution to PM2.5 mass) as follows: secondhand smoking (SHS) (brown carbon, environmental tobacco smoke; 65.3%), fuel oil (nickel, vanadium; 11.7%), crustal (aluminum, calcium, silicon; 11.5%), fresh sea salt (sodium, chlorine; 4.7%), aged sea salt (sodium, magnesium, sulfur; 4.3%), and traffic (black carbon, zinc; 2.6%). SHS was significantly greater in apartments compared to houses. Crustal source was correlated with more occupants in the household. Aged sea salt increased with temperature and outdoor ozone, while fresh sea salt was highest on days with westerly winds from the Pacific Ocean. Traffic was positively correlated with ambient NO2 and traffic-related NOx at residence. Overall, 76.8% of personal PM2.5 mass came from indoor or personal compared to outdoor sources. IMPACT: We conducted source apportionment of personal PM2.5 samples in pregnancy in Los Angeles, CA. Among identified sources, secondhand smoking contributed the most to the personal exposure. In addition, traffic, crustal, fuel oil, fresh and aged sea salt sources were also identified as main sources. Traffic sources contained markers of combustion and non-exhaust wear emissions. Crustal source was correlated with more occupants in the household. Aged sea salt source increased with temperature and outdoor ozone and fresh sea salt source was highest on days with westerly winds from the Pacific Ocean.