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

Response Surface Modeling of the Steady-State Impedance Responses of Gas Sensor Arrays Comprising Functionalized Carbon Nanotubes to Detect Ozone and Nitrogen Dioxide

Carbon nanotube (CNT) sensors provide a versatile chemical platform for ambient monitoring of ozone (O3) and nitrogen dioxide (NO2), two important airborne pollutants known to cause acute respiratory and cardiovascular health problems. CNTs have shown great potential for use as sensing layers due to their unique properties, including high surface to volume ratio, numerous active sites and crystal facets with high surface reactivity, and high thermal and electrical conductivity. With operational advantages such as compactness, low-power operation, and easy integration with electronics devices, nanotechnology is expected to have a significant impact on portable low-cost environmental sensors. Enhanced sensitivity is feasible by functionalizing the CNTs with polymers, metals, and metal oxides. This paper focuses on the design and performance of a two-element array of O3 and NO2 sensors comprising single-walled CNTs functionalized by covalent modification with organic functional groups. Unlike the conventional chemiresistor in which the change in DC resistance across the sensor terminals is measured, we characterize the sensor array response by measuring both the magnitude and phase of the AC impedance. Multivariate response provides higher degrees of freedom in sensor array data processing. The complex impedance of each sensor is measured at 5 kHz in a controlled gas-flow chamber using gas mixtures with O3 in the 60-120 ppb range and NO2 between 20 and 80 ppb. The measured data reveal response change in the 26-36% range for the O3 sensor and 5-31% for the NO2 sensor. Multivariate optimization is used to fit the laboratory measurements to a response surface mathematical model, from which sensitivity and selectivity are calculated. The ozone sensor exhibits high sensitivity (e.g., 5 to 6 MΩ/ppb for the impedance magnitude) and high selectivity (0.8 to 0.9) for interferent (NO2) levels below 30 ppb. However, the NO2 sensor is not selective.

Commuter exposure to particle-bound polycyclic aromatic hydrocarbons in Thessaloniki, Greece

Commuters are exposed to high air pollution levels daily, especially in areas with dense traffic. This study examines the commuter's exposure to polycyclic aromatic hydrocarbons (PAHs) in the city of Thessaloniki, Greece, under three different commuting modes: biking, travelling by private car, and riding public transportation means (buses). The study was carried out from 2015 to 2018 including 43 volunteers (15 cyclists, 17 car drivers/passengers, and 11 bus passengers). The personal exposure concentrations to particles smaller than 4-μm aerodynamic diameter (PM₄), constituting the respirable fraction of total airborne particles, and the associated PAHs were assessed for each commuting mode during the cold and the warm period of the year. Whereas the exposure of bus and car passengers to in-cabin PM₄ were higher in the cold season, the exposure of cyclists exhibited the opposite seasonality. In all commuting modes, exposure to PAHs was higher in the cold season. In both seasons, exposure concentration followed the order: cyclists > bus passengers > car passengers. The carcinogenic and mutagenic potencies of the exposure PAH concentrations were calculated using Benzo[a]pyrene (BaP) carcinogenic and mutagenic equivalency factors. The inhalation cancer risk (ICR) associated to PAHs was further estimated and compared between the different commuting modes. Our data can provide relevant information for transport decision-making and increase environmental awareness for a more rational approach to urban travelling.

Commuter types identified using clustering and their associations with source-specific PM2.5

Traffic-related fine particulate matter air pollution (tr-PM_2.5) has been associated with adverse health outcomes such as cardiopulmonary morbidity and mortality, with in-vehicle tr-PM_2.5 exposure contributing to total personal pollution exposure. Trip characteristics, including time of day, day of the week, and traffic congestion, are associated with in-vehicle PM_2.5 exposures. We hypothesized that some commuter characteristics, such as whether commuters travel primarily during rush hour, would also be associated with increased tr-PM_2.5 exposures. The commute data consisted of unscripted personal vehicle trips of 46 commuters in the Washington, D.C. metro area over 48-h, with a total of 320 trips. We identified commuter types using sparse K-means clustering, which identifies the hours throughout the day important for clustering commuters. Source-specific PM_2.5 over 48 h was estimated using Positive Matrix Factorization. Linear regression was used to estimate differences in source-specific PM_2.5 by commuter cluster. Two commuter clusters were identified using the clustering approach: rush hour commuters, who primarily travelled during rush hour, and sporadic commuters, who travelled throughout the day. The hours given the largest weights by sparse K-means were 7-8 a.m. and 6-7 p.m., corresponding to peak travel times. Integrated black carbon (BC) was higher for rush hour commuters (median = 3.1 μg/m³ (IQR = 1.5)) compared to sporadic commuters (2.0 μg/m³ (IQR = 1.9)). Mobile PM_2.5, consisting primarily of tailpipe emissions and brake/tire wear, was also higher for rush hour commuters (2.9 μg/m³ (IQR = 1.6)) compared to sporadic commuters (2.1 μg/m³ (IQR = 2.4)), though this difference was not statistically significant in regression models. Estimated differences between commuter types for secondary/mixed PM_2.5 and road salt PM_2.5 were smaller. Further research may elucidate whether commuter characteristics are an efficient way to identify individuals with highest tr-PM_2.5 exposures associated with commuting and to develop effective mitigation strategies.

Estimating exposure to traffic-related PM2.5 for women commuters using vehicle and personal monitoring

Exposure to traffic-related fine particulate matter air pollution (tr-PM_2.5) has been associated with adverse health outcomes including preterm birth and low birthweight. In-vehicle exposure to tr-PM_2.5 can contribute substantially to total tr-PM_2.5 exposure. Because average commuting habits of women differ from men, a research gap is estimating in-vehicle tr-PM_2.5 exposures for women commuters. For 46 women commuters in the Washington, D.C. metro area, we measured personal exposure to PM_2.5 during all vehicle trips taken in a 48-h sampling period. We also measured 48-h integrated PM_2.5 chemical constituents including black carbon and zinc. We identified trip times using vehicle monitors, specifically on-board diagnostics data loggers and dashboard cameras. For 386 trips, we estimated associations between PM_2.5 exposure and trip characteristics using linear mixed models accounting for participant, day, and time of day. Additionally, we estimated associations between rush hour trip PM_2.5 and 48-h integrated PM_2.5 chemical constituents using linear models. Exposure to PM_2.5 during trips was 1.9 μg/m³ (95% confidence interval (CI): 0.9, 2.9) higher than non-trip exposures and rush hour trip exposures were 3.2 μg/m³ (95% CI: 1.8, 4.6) higher than non-trip exposures on average. We did not find differences in PM_2.5 exposure by trip length. Although concentrations of tr-PM_2.5 chemical constituents were generally positively associated with rush hour trip PM_2.5, associations were weak indicating that other settings contribute to total tr-PM_2.5 exposure. Our study demonstrates the utility of combining vehicle monitors and personal PM_2.5 monitors for estimating personal exposure to tr-PM_2.5. Future work will investigate whether additional data collected by vehicle monitors, such as traffic and speed, can be leveraged to better understand tr-PM_2.5 exposure among commuters.

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-1β 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.

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.

Combustion-Related Organic Species in Temporally Resolved Urban Airborne Particulate Matter

Accurate characterization of the chemical composition of particulate matter (PM) is essential for improved understanding of source attribution and resultant health impacts. To explore this we conducted ambient monitoring of a suite of 15 combustion-related organic species in temporally resolved PM 2.5 samples during an ongoing animal exposure study in a near source environment in Detroit, MI. All of the 15 species detected were above the method detection limit in 8 hour samples. This study focused on two molecular classes: Polycyclic Aromatic Hydrocarbons (PAHs) and Hopanes measured in samples. Of the 12 PAHs studied, benzo[b]fluoranthene (169 pg m-3), benzo[g,h,i]perylene (124 pg m-3), and benzo[e]pyrene (118, pg m-3) exhibited the three highest mean concentrations while 17α(H),21β(H)-Hopane (189 pg m-3) and 17α(H),21β(H)-30-Norhopane (145 pg m-3) had the highest mean concentrations of the 3 Hopanes analyzed in samples. Ratios of individual compound concentrations to total compound concentrations (∑ 15 compounds) showed the greatest daily variation for 17α(H),21β(H)-Hopane (11-28%) and 17α(H),21β(H)-30-Norhopane (8-20%). Diagnostic PAH concentration ratios ([IP]/[IP + BP] (range 0.30 - 0.45), [BaP]/[BaP+BeP] (range 0.26 - 0.44), [BaP]/[BP] (range 0.41 - 0.82), [Bb]/[Bk] (range 2.07 - 2.66), in samples reflected impacts froma mixture of combustion sources consistent with greater prevalence of petroleum combustion source emissions (gasoline, diesel, kerosene, and crude oil) compared to coal or wood combustion emissions impacts at this urban site. Results from this study demonstrate that short duration sampling for organic speciation provides temporally relevant exposure information.

Ambient Size Distributions and Lung Deposition of Aerosol Dithiothreitol-Measured Oxidative Potential: Contrast between Soluble and Insoluble Particles

Ambient particulate matter may upset redox homeostasis, leading to oxidative stress and adverse health effects. Size distributions of water-insoluble and water-soluble OPDTT (dithiothreitol assay, measure of oxidative potential per air volume) are reported for a roadside site and an urban site. The average water-insoluble fractions were 23% and 51%, and 37% and 39%, for fine and coarse modes at the roadside and urban sites, respectively, measured during different periods. Water-soluble OPDTT was unimodal, peaked near 1-2.5 μm due to contributions from fine-mode organic components plus coarse-mode transition metal ions. In contrast, water-insoluble OPDTT was bimodal, with both fine and coarse modes. The main chemical components that drive both fractions appear to be the same, except that for water-insoluble OPDTT the compounds were absorbed on surfaces of soot and non-tailpipe traffic dust. They were largely externally mixed and deposited in different regions in the respiratory system, transition metal ions predominately in the upper regions and organic species, such as quinones, deeper in the lung. Although OPDTT per mass (toxicity) was highest for ultrafine particles, estimated lung deposition was mainly from accumulation and coarse particles. Contrasts in the phases of these forms of OPDTT deposited in the respiratory system may have differing health impacts.

Fine particulate-bound polycyclic aromatic hydrocarbons in vehicles in Rome, Italy

Urban commuters are exposed to elevated levels of air pollutants, especially in heavily polluted areas and traffic congested roads. In order to assess the contribution of commuting to citizens' exposure, measurements of fine particulate (PM_2.5) and polycyclic aromatic hydrocarbons (PAHs) were carried out in cars, busses, and metro trains, within the LIFE+ EXPAH Project. Monitoring campaigns were performed in Rome, Italy, from April 2011 to August 2012. Inside the busses, the concentration of total PAHs ranged from 2.7 to 6.6 ng/m³ during the winter and from 0.34 to 1.51 ng/m³ in the summer. In cars, internal concentrations were in the range 2.2-7.3 and 0.46-0.82 ng/m³, respectively, in the 2-year time. Analogous differences between seasons were observed examining the benzo[a]pyrene-equivalent carcinogenicity. In the metro trains, total PAHs ranged from 1.19 to 2.35 ng/m³ and PM_2.5 ranged from 17 to 31 μg/m³. The PM_2.5 concentration in all transport modes ranged from 10 to 160 μg/m³ during the cold season and 15-48 μg/m³ during the warm time. The average inside-to-outside ratio (R _I/O) was found to exceed 1.0 for PM_2.5 only in busses, probably due to dust re-suspension caused by crowding and passenger activity. The molecular PAH signature suggests that vehicle emissions and biomass combustion were the major sources of commuters' exposure to these toxicants in Rome. According to linear regression analysis, the PAH concentrations inside the vehicles were linked to those detected outside. Statistically significant differences (p < 0.05) were found between the in-vehicle locations and the urban pollution network stations, with higher PAH values detected, on the average, in these latter.

Scripted drives: A robust protocol for generating exposures to traffic-related air pollution

Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 μg/m3 PM2.5, 40 000 particles/cm3, 0.3 ppm CO, 4 μg/m3 BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used for generating reasonably consistent in-cabin increments of exposure to traffic-related air pollution.

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.