The impact of vegetative and solid roadway barriers on particulate matter concentration in urban settings.

A potentially important approach for reducing exposure to traffic-related air pollution (TRAP) is the use of roadside barriers to reduce dispersion from highway sources to adjacent populated areas. The Trees Reducing Environmental Exposures (TREE) study investigated the effect of vegetative and solid barriers along major controlled-access highways in Atlanta, Georgia, USA by simultaneously sampling TRAP concentration at roadside locations in front of barriers and at comparison locations down-range. We measured black carbon (BC) mass concentration, particle number concentration (PNC), and the size distribution of ultrafine aerosols. Our sample sites encompassed the range of roadway barrier options in the Atlanta area: simple chain-link fences, solid barriers, and vegetative barriers. We used Generalized Linear Mixed Models (GLMMs) to estimate the effect of barrier type on the ratio of particle concentrations at the comparison site relative to the roadside site while controlling for covariates including wind direction, temperature, relative humidity, traffic volume, and distance to the roadway. Vegetative barriers exhibited the greatest TRAP reduction in terms of BC mass concentration (37% lower behind a vegetative barrier) as well as PNC (6.7% lower), and sensitivity analysis was consistent with this effect being more pronounced when the barrier was downwind of the highway. The ultrafine size distribution was comprised of modestly smaller particles on the highway side of the barrier. Non-highway particle sources were present at all sample sites, most commonly motor vehicle emissions from nearby arterials or secondary streets, which may have obscured the effect of roadside barriers.

The Intersectionality of Climate Change and Post-Stroke Aphasia.

Persons with communication disabilities including persons with post-stroke aphasia (PWAs) possess a vulnerability to climate change as a result of their communication impairments. The disproportionate effects of climate change are likely to exacerbate preexisting inequities in social determinants of health. Communication disability intersecting with other characteristics subject to discrimination (e.g., race, age, sex, income) may lead to inequities in climate-related adaptive capacity. This article echoes earlier concerns related to climate change and further educates healthcare professionals about the impact of climate change on the global human population, with particular consideration of PWAs. The aims of this article are the following: (1) to broaden the understanding of aphasiologists and clinicians caring for PWAs about climate change and the contributions of human activity (anthropogenic) to this crisis; (2) to describe climate change and its impact on health; (3) to detail the intersectionality of climate and health; (4) to explore climate change and its potential effects on PWAs; and (5) to offer hope through emissions reduction, adaptation, resilience, and immediate change.

Characterization of an Electronic Nicotine Delivery System (ENDS) Aerosol Generation Platform to Determine Exposure Risks.

Evaluating vaping parameters that influence electronic nicotine delivery system (ENDS) emission profiles and potentially hazardous exposure levels is essential to protecting human health. We developed an automated multi-channel ENDS aerosol generation system (EAGS) for characterizing size-resolved particle emissions across pod- and mod-type devices using real-time monitoring instruments, an exposure chamber, and vaping parameters including different ventilation rates, device type and age, e-liquid formulation, and atomizer setup. Results show the ENDS device type, e-liquid flavoring, and nicotine content can affect particle emissions. In general, pod-type devices have unimodal particle size distributions and higher number emissions, while mod-type devices have bimodal size distributions and higher mass emissions. For pod-type devices, later puff fractions emit lower aerosols, which is potentially associated with the change of coil resistance and power during ageing. For a mod-type device, an atomizer with a lower resistance coil and higher power generates larger particle emissions than an atomizer with a greater resistance coil and lower power. The unventilated scenario produces higher particle emission factors, except for particle mass emission from pod-type devices. The data provided herein indicate the EAGS can produce realistic and reproducible puff profiles of pod- and mod-type ENDS devices and therefore is a suitable platform for characterizing ENDS-associated exposure risks.

Toxicological Assessment of Particulate and Metal Hazards Associated with Vaping Frequency and Device Age.

Electronic nicotine delivery systems (ENDS) aerosols are complex mixtures of chemicals, metals, and particles that may present inhalation hazards and adverse respiratory health risks. Despite being considered a safer alternative to tobacco cigarettes, metal exposure levels and respiratory effects associated with device aging and vaping frequency have not been fully characterized. In this study, we utilize an automated multi-channel ENDS aerosol generation system (EAGS) to generate aerosols from JUUL pod-type ENDS using tobacco-flavored e-liquid. Aerosol puff fractions (1-50) and (101-150) are monitored and sampled using various collection media. Extracted aerosols are prepared for metal and toxicological analysis using human primary small airway epithelial cells (SAEC). ENDS aerosol-mediated cellular responses, including reactive oxygen species (ROS), oxidative stress, cell viability, and DNA damage, are evaluated after 24 h and 7-day exposures. Our results show higher particle concentrations in later puff fractions (0.135 mg/m3) than in initial puff fractions (0.00212 mg/m3). Later puff fraction aerosols contain higher toxic metal concentrations, including chromium, copper, and lead, which elicit increased levels of ROS followed by significant declines in total glutathione and cell viability. Notably, a 30% increase in DNA damage was observed after 7 days because of later puff fraction exposures. This work is consistent with ENDS aerosols becoming more hazardous across the use of pre-filled pod devices, which may threaten respiratory health.

Evaluation of the Use of Saliva Metabolome as a Surrogate of Blood Metabolome in Assessing Internal Exposures to Traffic-Related Air Pollution.

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Estimating minute ventilation and air pollution inhaled dose using heart rate, breath frequency, age, sex and forced vital capacity: A pooled-data analysis.

Air pollution inhaled dose is the product of pollutant concentration and minute ventilation ([Formula: see text]). Previous studies have parameterized the relationship between [Formula: see text] and variables such as heart rate (HR) and have observed substantial inter-subject variability. In this paper, we evaluate a method to estimate [Formula: see text] with easy-to-measure variables in an analysis of pooled-data from eight independent studies. We compiled a large diverse data set that is balanced with respect to age, sex and fitness level. We used linear mixed models to estimate [Formula: see text] with HR, breath frequency (fB), age, sex, height, and forced vital capacity (FVC) as predictors. FVC was estimated using the Global Lung Function Initiative method. We log-transformed the dependent and independent variables to produce a model in the form of a power function and assessed model performance using a ten-fold cross-validation procedure. The best performing model using HR as the only field-measured parameter was [Formula: see text] = e-9.59HR2.39age0.274sex-0.204FVC0.520 with HR in beats per minute, age in years, sex is 1 for males and 2 for females, FVC in liters, and a median(IQR) cross-validated percent error of 0.664(45.4)%. The best performing model overall was [Formula: see text] = e-8.57HR1.72fB0.611age0.298sex-0.206FVC0.614, where fB is breaths per minute, and a median(IQR) percent error of 1.20(37.9)%. The performance of these models is substantially better than any previously-published model when evaluated using this large pooled-data set. We did not observe an independent effect of height on [Formula: see text], nor an effect of race, though this may have been due to insufficient numbers of non-white participants. We did observe an effect of FVC such that these models over- or under-predict [Formula: see text] in persons whose measured FVC was substantially lower or higher than estimated FVC, respectively. Although additional measurements are necessary to confirm this finding regarding FVC, we recommend using measured FVC when possible.

Perturbations of the arginine metabolome following exposures to traffic-related air pollution in a panel of commuters with and without asthma.

BACKGROUND: Mechanisms underlying the effects of traffic-related air pollution on people with asthma remain largely unknown, despite the abundance of observational and controlled studies reporting associations between traffic sources and asthma exacerbation and hospitalizations. OBJECTIVES: To identify molecular pathways perturbed following traffic pollution exposures, we analyzed data as part of the Atlanta Commuters Exposure (ACE-2) study, a crossover panel of commuters with and without asthma. METHODS: We measured 27 air pollutants and conducted high-resolution metabolomics profiling on blood samples from 45 commuters before and after each exposure session. We evaluated metabolite and metabolic pathway perturbations using an untargeted metabolome-wide association study framework with pathway analyses and chemical annotation. RESULTS: Most of the measured pollutants were elevated in highway commutes (p < 0.05). From both negative and positive ionization modes, 17,586 and 9087 metabolic features were extracted from plasma, respectively. 494 and 220 unique features were associated with at least 3 of the 27 exposures, respectively (p < 0.05), after controlling confounders and false discovery rates. Pathway analysis indicated alteration of several inflammatory and oxidative stress related metabolic pathways, including leukotriene, vitamin E, cytochrome P450, and tryptophan metabolism. We identified and annotated 45 unique metabolites enriched in these pathways, including arginine, histidine, and methionine. Most of these metabolites were not only associated with multiple pollutants, but also differentially expressed between participants with and without asthma. The analysis indicated that these metabolites collectively participated in an interrelated molecular network centering on arginine metabolism, underlying the impact of traffic-related pollutants on individuals with asthma. CONCLUSIONS: We detected numerous significant metabolic perturbations associated with in-vehicle exposures during commuting and validated metabolites that were closely linked to several inflammatory and redox pathways, elucidating the potential molecular mechanisms of traffic-related air pollution toxicity. These results support future studies of metabolic markers of traffic exposures and the corresponding molecular mechanisms.

Quantification of malondialdehyde in exhaled breath condensate using pseudo two-dimensional ultra-performance liquid chromatography coupled with single quadrupole mass spectrometry.

We developed a robust analytical method for quantification of malondialdehyde (MDA) in exhaled breath condensate (EBC) via derivatization with 2,4-dinitrophenylhydrazine (DNPH). The target MDA-DNPH hydrazone was separated by ultra-performance liquid chromatography using two reversed-phase analytical columns (C18 and phenyl-hexyl) inter-connected via a two-position, six-port switching valve to a single-quadrupole mass spectrometer. The target derivative was analyzed under positive electrospray ionization using single ion monitoring mode (m/z = 235 for the target derivative, and m/z = 237 for its labeled isotopic analog). This pseudo two-dimensional chromatographic separation provided optimum separation conditions for the target derivative resulting in the limit of detection of 0.58 nM in EBC sample (or 36.2 pmol on-column amount), which is comparable to those reported previously using different techniques, including tandem mass spectrometry. Based on the calibration solutions, the method had a linear quantification range of 1.0-200 nM (r2 = 0.998). The method showed good relative recoveries (92.2-102.0%) and acceptable precisions (3.6-12.2% for inter-day precision, and 4.3-12.4% for intra-day precision for two quality control levels, prepared from 5 nM and 25 nM solutions). The derivative was found to be stable at room temperature for 48 h or during analysis. The method was used to analyze 205 exhaled breath condensate samples collected from individuals from a healthy population of student athletes. MDA was detected in approximately 95% of these samples, with concentrations ranging from 1.16 to 149.63 nM. The median concentration was 6.82 nM, (IQR 4.08-9.88). These data demonstrate that our method can be successfully used to measure MDA in population studies.

Particulate metal exposures induce plasma metabolome changes in a commuter panel study.

INTRODUCTION: Advances in liquid chromatography-mass spectrometry (LC-MS) have enabled high-resolution metabolomics (HRM) to emerge as a sensitive tool for measuring environmental exposures and corresponding biological response. Using measurements collected as part of a large, panel-based study of car commuters, the current analysis examines in-vehicle air pollution concentrations, targeted inflammatory biomarker levels, and metabolomic profiles to trace potential metabolic perturbations associated with on-road traffic exposures. METHODS: A 60-person panel of adults participated in a crossover study, where each participant conducted a highway commute and randomized to either a side-street commute or clinic exposure session. In addition to in-vehicle exposure characterizations, participants contributed pre- and post-exposure dried blood spots for 2-hr changes in targeted proinflammatory and vascular injury biomarkers and 10-hr changes in the plasma metabolome. Samples were analyzed on a Thermo QExactive MS system in positive and negative electrospray ionization (ESI) mode. Data were processed and analyzed in R using apLCMS, xMSanalyzer, and limma. Features associated with environmental exposures or biological endpoints were identified with a linear mixed effects model and annotated through human metabolic pathway analysis in mummichog. RESULTS: HRM detected 10-hr perturbations in 110 features associated with in-vehicle, particulate metal exposures (Al, Pb, and Fe) which reflect changes in arachidonic acid, leukotriene, and tryptophan metabolism. Two-hour changes in proinflammatory biomarkers hs-CRP, IL-6, IL-8, and IL-1ß were also associated with 10-hr changes in the plasma metabolome, suggesting diverse amino acid, leukotriene, and antioxidant metabolism effects. A putatively identified metabolite, 20-OH-LTB4, decreased after in-vehicle exposure to particulate metals, suggesting a subclinical immune response. CONCLUSIONS: Acute exposures to traffic-related air pollutants are associated with broad inflammatory response, including several traditional markers of inflammation.

Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution.

BACKGROUND: High-resolution metabolomics (HRM) is emerging as a sensitive tool for measuring environmental exposures and biological responses. The aim of this analysis is to assess the ability of high-resolution metabolomics (HRM) to reflect internal exposures to complex traffic-related air pollution mixtures. METHODS: We used untargeted HRM profiling to characterize plasma and saliva collected from participants in the Dorm Room Inhalation to Vehicle Emission (DRIVE) study to identify metabolic pathways associated with traffic emission exposures. We measured a suite of traffic-related pollutants at multiple ambient and indoor sites at varying distances from a major highway artery for 12 weeks in 2014. In parallel, 54 students living in dormitories near (20 m) or far (1.4 km) from the highway contributed plasma and saliva samples. Untargeted HRM profiling was completed for both plasma and saliva samples; metabolite and metabolic pathway alternations were evaluated using a metabolome-wide association study (MWAS) framework with pathway analyses. RESULTS: Weekly levels of traffic pollutants were significantly higher at the near dorm when compared to the far dorm (p < 0.05 for all pollutants). In total, 20,766 metabolic features were extracted from plasma samples and 29,013 from saliva samples. 45% of features were detected and shared in both plasma and saliva samples. 1291 unique metabolic features were significantly associated with at least one or more traffic indicator, including black carbon, carbon monoxide, nitrogen oxides and fine particulate matter (p < 0.05 for all significant features), after controlling for confounding and false discovery rate. Pathway analysis of metabolic features associated with traffic exposure indicated elicitation of inflammatory and oxidative stress related pathways, including leukotriene and vitamin E metabolism. We confirmed the chemical identities of 10 metabolites associated with traffic pollutants, including arginine, histidine, γ­linolenic acid, and hypoxanthine. CONCLUSIONS: Using HRM, we identified and verified biological perturbations associated with primary traffic pollutant in panel-based setting with repeated measurement. Observed response was consistent with endogenous metabolic signaling related to oxidative stress, inflammation, and nucleic acid damage and repair. Collectively, the current findings provide support for the use of untargeted HRM in the development of metabolic biomarkers of traffic pollution exposure and response.

Errors associated with the use of roadside monitoring in the estimation of acute traffic pollutant-related health effects.

Near-road monitoring creates opportunities to provide direct measurement on traffic-related air pollutants and to better understand the changing near-road environment. However, how such observations represent traffic-related air pollution exposures for estimating adverse health effect in epidemiologic studies remains unknown. A better understanding of potential exposure measurement error when utilizing near-road measurement is needed for the design and interpretation of the many observational studies linking traffic pollution and adverse health. The Dorm Room Inhalation to Vehicle Emission (DRIVE) study conducted near-road measurements of several single traffic indicators at six indoor and outdoor sites ranging from 0.01 to 2.3 km away from a heavily-trafficked (average annual daily traffic over 350,000) highway artery between September 2014 to January 2015. We examined spatiotemporal variability trends and assessed the potential for bias and errors when using a roadside monitor as a primary traffic pollution exposure surrogate, in lieu of more spatially-refined, proximal exposure indicators. Pollutant levels measured during DRIVE showed a low impact of this highway hotspot source. Primary pollutant species, including NO, CO, and BC declined to near background levels by 20-30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO2, specifically, exhibited spatial trends that differed from other single-pollutant primary traffic indicators. This finding provides some indication of limitations in the use of NO2 as a primary traffic exposure indicator in panel-based health effect studies. Interestingly, roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods, and more weakly correlated during other periods of the day. We found pronounced attenuation of observed changes in health effects when using measured pollutant from the near-road monitor as a surrogate for true exposure, and the magnitude varied substantially over the course of the day. Caution should be taken when using near-road monitoring network observations, alone, to investigate health effects of traffic pollutants.

Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies.

Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of -1.33% (95% confidence interval (CI): -2.45, -0.22) and -2.19% (95% CI: -3.46, -0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection.

INTRODUCTION: Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics. METHODS: Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform. RESULTS: The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41-0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics. CONCLUSIONS: Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.

A Novel Method for Quantifying the Inhaled Dose of Air Pollutants Based on Heart Rate, Breathing Rate and Forced Vital Capacity.

To better understand the interaction of physical activity and air pollution exposure, it is important to quantify the change in ventilation rate incurred by activity. In this paper, we describe a method for estimating ventilation using easily-measured variables such as heart rate (HR), breathing rate (fB), and forced vital capacity (FVC). We recruited healthy adolescents to use a treadmill while we continuously measured HR, fB, and the tidal volume (VT) of each breath. Participants began at rest then walked and ran at increasing speed until HR was 160-180 beats per minute followed by a cool down period. The novel feature of this method is that minute ventilation ([Formula: see text]) was normalized by FVC. We used general linear mixed models with a random effect for subject and identified nine potential predictor variables that influence either [Formula: see text] or FVC. We assessed predictive performance with a five-fold cross-validation procedure. We used a brute force selection process to identify the best performing models based on cross-validation percent error, the Akaike Information Criterion and the p-value of parameter estimates. We found a two-predictor model including HR and fB to have the best predictive performance ([Formula: see text]/FVC = -4.247+0.0595HR+0.226fB, mean percent error = 8.1±29%); however, given the ubiquity of HR measurements, a one-predictor model including HR may also be useful ([Formula: see text]/FVC = -3.859+0.101HR, mean percent error = 11.3±36%).

Air pollution, physical activity, and markers of acute airway oxidative stress and inflammation in adolescents.

BACKGROUND: The airway inflammatory response is likely the mechanism for adverse health effects related to exposure to air pollution. Increased ventilation rates during physical activity in the presence of air pollution increases the inhaled dose of pollutants. However, physical activity may moderate the relationship between air pollution and the inflammatory response. The present study aimed to characterize, among healthy adolescents, the relationship between dose of inhaled air pollution, physical activity, and markers of lung function, oxidative stress, and airway inflammation. METHODS: With a non-probability sample of adolescents, this observational study estimated the association between air pollution dose and outcome measures by use of general linear mixed models with an unstructured covariance structure and a random intercept for subjects to account for repeated measures within subjects. RESULTS: A one interquartile range (IQR) (i.e., 345.64 µg) increase in ozone (O3) inhaled dose was associated with a 29.16% average decrease in the percentage of total oxidized compounds (%Oxidized). A one IQR (i.e., 2.368E+10 particle) increase in total particle number count in the inhaled dose (PNT) was associated with an average decrease in forced expiratory flow (FEF25-75) of 0.168 L/second. Increasing activity levels attenuated the relationship between PNT inhaled dose and exhaled nitric oxide (eNO). The relationship between O3 inhaled dose and percent oxidized exhaled breath condensate cystine (%CYSS) was attenuated by activity level, with increasing activity levels corresponding to smaller changes from baseline for a constant O3 inhaled dose. CONCLUSIONS: The moderating effects of activity level suggest that peaks of high concentration doses of air pollution may overwhelm the endogenous redox balance of cells, resulting in increased airway inflammation. Further research that examines the relationships between dose peaks over time and inflammation could help to determine whether a high concentration dose over a short period of time has a different effect than a lower concentration dose over a longer period of time.

Modification of Traffic-related Respiratory Response by Asthma Control in a Population of Car Commuters.

BACKGROUND: Effects of traffic-related exposures on respiratory health are well documented, but little information is available about whether asthma control influences individual susceptibility. We analyzed data from the Atlanta Commuter Exposure study to evaluate modification of associations between rush-hour commuting, in- vehicle air pollution, and selected respiratory health outcomes by asthma control status. METHODS: Between 2009 and 2011, 39 adults participated in Atlanta Commuter Exposure, and each conducted two scripted rush-hour highway commutes. In-vehicle particulate components were measured during all commutes. Among adults with asthma, we evaluated asthma control by questionnaire and spirometry. Exhaled nitric oxide, forced expiratory volume in 1 second (FEV1), and other metrics of respiratory health were measured precommute and 0, 1, 2, and 3 hours postcommute. We used mixed effects linear regression to evaluate associations between commute-related exposures and postcommute changes in metrics of respiratory health by level of asthma control. RESULTS: We observed increased exhaled nitric oxide across all levels of asthma control compared with precommute measurements, with largest postcommute increases observed among participants with below-median asthma control (2 hours postcommute: 14.6% [95% confidence interval {CI} = 5.7, 24.2]; 3 hours postcommute: 19.5% [95% CI = 7.8, 32.5]). No associations between in-vehicle pollutants and percent of predicted FEV1 were observed, although higher PM2.5 was associated with lower FEV1 % predicted among participants with below-median asthma control (3 hours postcommute: -7.2 [95% CI = -11.8, -2.7]). CONCLUSIONS: Level of asthma control may influence respiratory response to in-vehicle exposures experienced during rush-hour commuting.

Exposure to traffic pollution, acute inflammation and autonomic response in a panel of car commuters.

BACKGROUND: Exposure to traffic pollution has been linked to numerous adverse health endpoints. Despite this, limited data examining traffic exposures during realistic commutes and acute response exists. OBJECTIVES: We conducted the Atlanta Commuters Exposures (ACE-1) Study, an extensive panel-based exposure and health study, to measure chemically-resolved in-vehicle exposures and corresponding changes in acute oxidative stress, lipid peroxidation, pulmonary and systemic inflammation and autonomic response. METHODS: We recruited 42 adults (21 with and 21 without asthma) to conduct two 2-h scripted highway commutes during morning rush hour in the metropolitan Atlanta area. A suite of in-vehicle particulate components were measured in the subjects' private vehicles. Biomarker measurements were conducted before, during, and immediately after the commutes and in 3 hourly intervals after commutes. RESULTS: At measurement time points within 3h after the commute, we observed mild to pronounced elevations relative to baseline in exhaled nitric oxide, C-reactive-protein, and exhaled malondialdehyde, indicative of pulmonary and systemic inflammation and oxidative stress initiation, as well as decreases relative to baseline levels in the time-domain heart-rate variability parameters, SDNN and rMSSD, indicative of autonomic dysfunction. We did not observe any detectable changes in lung function measurements (FEV1, FVC), the frequency-domain heart-rate variability parameter or other systemic biomarkers of vascular injury. Water soluble organic carbon was associated with changes in eNO at all post-commute time-points (p<0.0001). CONCLUSIONS: Our results point to measureable changes in pulmonary and autonomic biomarkers following a scripted 2-h highway commute.

On-Roadway In-Cabin Exposure to Particulate Matter: Measurement Results Using Both Continuous and Time-Integrated Sampling Approaches.

The Atlanta Commuters Exposure (ACE) Study was designed to measure in-cabin exposure to roadway particulate pollution and acute health response in a panel of adults with and without asthma following a 2-h scripted route along major highways in Atlanta. This article focuses on methods and results of both continuous and integrated approaches used to measure the concentration of PM2.5 mass, particle number concentration (PNC), black carbon (BC) mass, and particle-bound PAHs, in-cabin noise, PM elemental composition, elemental carbon, organic carbon, water-soluble organic carbon (WSOC) content, and speciation of a broad range of organic compounds including alkanes, hopanes, and PAHs. Speciated PM data indicates that in-cabin particles derive from three non-co-varying processes: the resuspension of road dust containing crustal elements and previously-deposited brake pad residue with a contribution of normal fuel combustion, incomplete combustion processes producing PAHs and carbon particles, and particles ablated from brake pads that have not previously deposited to the roadside environment. Most in-cabin pollutants were elevated during the warm season with the notable exception of PNC. PNC was not found to be correlated with most other pollutants. In-cabin concentrations were marginally higher when windows were open.

Exhaled breath condensate formate after inhaled allergen provocation in atopic asthmatics in vivo.

OBJECTIVE: The dual actions of S-nitrosoglutathione reductase comprise reduction of S-nitrosoglutathione, a potent endogenous airway smooth muscle relaxant that is depleted in asthmatics, and detoxification of formaldehyde to formate. Airway formate production is increased in children with asthma, suggesting increased activity of S-nitrosoglutathione reductase. We determined formate in exhaled breath condensate from adult atopic asthmatics with asthma exacerbation produced by inhaled allergen in vivo, METHODS: Twenty-two adult atopic asthmatics underwent inhaled allergen challenge using specific allergen. Exhaled breath condensate was collected at baseline, 1 h after inhalation of the provocative dose of allergen, and then every 2 h for 8 h during the challenge. Formate was analyzed by ion chromatography, RESULTS: Eleven asthmatics developed an isolated early airway response, and another 11 volunteers early response followed by late airway response (dual response). Formate concentrations doubled 1 h post-challenge in asthmatics with dual-airway response but essentially unchanged in patients with an isolated early reaction, CONCLUSIONS: Dual-airway response to allergen in atopic asthmatics could be associated with increased activity of S-nitrosoglutathione reductase as suggested by greater concentrations of formate in exhaled breath condensate. Measurement of formate in exhaled breath condensate could serve as a noninvasive biomarker of S-nitrosoglutathione reductase activity in vivo. Our results need to be confirmed in a larger group of asthmatics.

Associations between urban air pollution and pediatric asthma control in El Paso, Texas.

Exposure to traffic-related pollutants poses a serious health threat to residents of major urban centers around the world. In El Paso, Texas, this problem is exacerbated by the region's arid weather, frequent temperature inversions, heavy border traffic, and an aged, poorly maintained vehicle fleet. The impact of exposure to traffic pollution, particularly on children with asthma, is poorly understood. Tracking the environmental health burden related to traffic pollution in El Paso is difficult, especially within school microenvironments, because of the lack of sensitive environmental health indicator data. The Asthma Control Questionnaire (ACQ) is a survey tool for the measurement of overall asthma control, yet has not previously been considered as an outcome in air pollution health effect research. We conducted a repeated measure panel study to examine weekly associations between ACQ scores and traffic- and non-traffic air pollutants among asthmatic schoolchildren in El Paso. In the main one- and two-pollutant epidemiologic models, we found non-significant, albeit suggestive, positive associations between ACQ scores and respirable particulate matter (PM10), coarse particulate matter (PM10-2.5), fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), benzene, toluene, and ozone (O3). Notably, associations were stronger and significant for some subgroups, in particular among subjects taking daily inhaled corticosteroids. This pattern may indicate heightened immune system response in more severe asthmatics, those with worse asthma "control" and higher ACQ scores at baseline. If the ACQ is appropriately used in the context of air pollution studies, it could reflect clinically measurable and biologically relevant changes in lung function and asthma symptoms that result from poor air quality and may increase our understanding of how air pollution influences asthma exacerbation.