On-roadway in-cabin exposure to particulate matter: measurement results using both
continuous and time-integrated sampling approaches
Roby Greenwald, Michael H. Bergin, Fuyuen Yip, Tegan Boehmer, Priya Kewada, Martin M.
Shafer, James J. Schauer, Jeremy A. Sarnat
Supplementary Information
Methods
Study overview. This study was approved by the Emory University Institutional Review Board, and
written informed consent was provided by all participants. Each subject’s two commutes were
separated by at least two weeks and in some cases by several months. Commutes were
conducted in each subject’s personal vehicle and followed a scripted route of approximately two
hours duration during the morning rush period in Atlanta (7-9 am). The morning rush period was
selected so that subjects would be available for 3 hours of health endpoint measurements
following the commute. Commutes were conducted 2010-2011 during all seasons of the year and
in all meteorological conditions.
Figure S1. Map of the Atlanta region showing truck restrictions and the path of a typical
ACE-1 commute. Satellite photo courtesy of NASA.
With the exception of 1 subject, all commutes began and ended at Emory University, and subjects
were accompanied by a field technician who sat in the back seat of the subject’s vehicle. For the
subject that was the exception, pre-commute health measurements were performed at his
residence, and the commute ended at Emory University. Commute routes were selected to
emphasize the Atlanta Perimeter Highway, I-285, and to maximize the time spent on controlledaccess freeways (Figure S1). State regulation requires commercial traffic transiting Atlanta to use
I-285 when not making local deliveries. Accordingly, diesel truck traffic is typically higher on I-285
(5500 total vehicles and 530 trucks per hour on weekdays 7-9 am) while total traffic is higher on I75/85 in downtown (8900 vehicles and 380 trucks per hour on weekdays 7-9 am, data from
Georgia Department of Transportation public database for 2010-2011).
Continuous measurements. All continuous instrumentation, filter holders, and cascade impactors
were placed in a sampling tray located in the front passenger seat of the vehicle (Figure S2). A
continuous estimate of the PM2.5 mass concentration was calculated using an optical particle
counter (AeroTrak model 9306, TSI Inc.). This instrument includes 5 channels in the size range
spanning 0.3-2.5 µm and a sixth for Dp>2.5 µm. Mass concentration was estimated by first
converting the measured number concentration from the lower 5 channels to a volume
concentration by assuming that particles are spherical with a diameter equal to the log-midpoint of
the corresponding channel. For each commute, an estimate of particle density (referred to as
“synthetic density”) was obtained by integrating the time-resolved calculations of particle volume
and dividing by the measured mass from PM2.5 filters (method described below). The volume
Figure S2. Schematic of instrumentation for ACE-1. This bin rests in the front passenger seat
and filter flow is provided by vacuum pumps installed in the vehicle trunk.
concentration was subsequently converted to a mass concentration by applying the synthetic
density to each time-resolved measurement. The mean synthetic density for all commutes was
calculated to be 1.9±1.2 g·cm-3. Two different instruments were used for measurements of PNC
with the principal difference being the lower size limit of detection. The P-Trak (model 8525, TSI
Inc.) counts all particles larger than 20 nm and was used for all commutes while a handheld
condensation particle counter (CPC model 3007, TSI Inc.) counts all particles larger than 10 nm,
but was acquired in the second half of the study. Black carbon (BC, MicroAeth AE51, AethLabs),
particle-bound PAHs (pbPAHs, PAS 2000CE, EcoChem), and noise (HD600, Extech Instruments)
were also measured with continuous devices.
Integrated measurements. A 2-stage Harvard Compact Cascade Impactor (Demokritou et al.
2004) was operated at 30 L·min-1 to collect coarse and fine mode particulates for elemental
analysis using a polyurethane foam (PUF) substrate on the coarse stage and a 47 mm
polytetrafluoroethylene (PTFE) after-filter (SKC Inc.). In addition, fine particles were collected on 3
quartz fiber filters (SKC Inc.): a 47 mm filter for organic speciation operated at 30 L·min-1 and two
25 mm filters for elemental and organic carbon analysis operated at 15 L·min-1. Each filter holder
was preceded by a 2.5 µm size cut inertial impactor. Filter samples were not denuded to remove
gas-phase or semi-volatile components. The pumps were replaced with different models after 53
commutes, and there was not a significant difference in flow rate between the 2 sets of pumps;
however, the coefficient of variation was higher for the replacement pumps (0.13 and 0.38
respectively).
PM speciation. All analytical methods of PM speciation used for this study have been previously
described in the literature. Fine PM elemental composition was measured at the University of
Wisconsin (UWis) using inductively-coupled plasma-mass spectrometry analysis of cascade
impactor after-filters (Lough et al. 2005). Organic speciation (including alkanes, hopanes, and
PAHs) was also conducted at UWis using thermal desorption-mass spectrometry analysis of the
47 mm quartz fiber filters (Sheesley et al. 2007). The mass concentration of organic and
elemental carbon (OC and EC) was measured independently at both UWis and Georgia Tech
(GT) using thermal-optical transmittance analysis of a 1 cm2 punch from one of the 25 mm quartz
fiber filters (Birch and Cary 1996). An aqueous extract of water-soluble PM components was
prepared by immersing a 1 cm2 punch of a quartz fiber filter in 30 mL of ultrapure water and
placing in an ultrasonic bath for 30 minutes. This aqueous extract was analyzed at GT to
determine the content of water-soluble organic carbon (WSOC) (Hagler et al. 2007).
Results and Discussion
Study overview. A total of 81 commutes were completed with a mean±SD duration of 142±13
minutes. Three commutes (4% of the total) were canceled between enrollment and exposure
date. In each case, this was the second commute for a subject; in 1 case, the subject declined to
participate a second time and in 2 cases, the subjects relocated out of town before completing the
protocol. The most common type of vehicle was sedan/hatchback (52 commutes), followed by
SUV (22), minivan (2), station wagon (2) and pickup truck (3). Vehicle age ranged from less than
a year to 16 years with a median age of 5 years. Seven commutes were conducted in a hybrid
vehicle, and 2 in a diesel vehicle.
Figure S3. Correlation of continuous and integrated measurements. In each case, the filterbased measurement is on the x-axis, and the continuous measurement is on the yaxis. The sum of PAHs is the sum of fluoranthene, pyrene, benzo[ghi]fluoranthene,
benz[a]anthracene, benzo[b+k]fluoranthene, benzo[a]pyrene, benzo[e]pyrene,
benzo[ghi]perylene, and coronene.
Relationship between continuous and integrated measurements. There was modest correlation
between continuously-measured BC (integrated over the commute period) and filter-based EC
(Pearson’s r=0.72) (Figure S3(a)). The slope of the linear regression model was close to 1
(slope=1.1, p[H0:slope=1]=0.37) though the intercept was 2.8±0.41 µg·m-3. Figure S3(b) shows
the regression of pbPAH with the sum of the filter-based concentrations of fluoranthene, pyrene,
benzo[ghi]fluoranthene, benz[a]anthracene, benzo[b+k]fluoranthene, benzo[a]pyrene,
benzo[e]pyrene, benzo[ghi]perylene, and coronene. The values measured using both analytical
methods are modestly correlated (Pearson’s r=0.64); however, the slope of the regression is
significantly different than 1 (slope=5.5, p[H0:slope=1]<0.0001), and the continuous instrument
commonly recorded commute-mean values of approximately 100 ng·m-3 when corresponding
filter-based PAHs are below detection limit. Although both continuous and integrated PAH values
were similar to concentrations reported by previous studies (Riediker et al. 2003; Marr et al. 2006;
Sheesley et al. 2007; Thornhill et al. 2008), their relationship to each other must be interpreted
cautiously since the 2 measurements employ very different methodologies. The PAS 2000CE
uses a pulsed excimer lamp with a wavelength of 207 nm to photoionize components of the
sample (presumably PAHs) with ionization energy less than 6 eV (Marr et al. 2006). Vapor-phase
components are not collected whereas positively-charged particles are collected on a filter, and
the resulting electrical current is measured and converted to a pbPAH mass concentration.
Previous studies have shown that this device is sensitive to PAHs with 3 or more aromatic rings
(Ramamurthi and Chuang 1997), and may be responsive to semi-volatile PAHs that are
temporarily retained on the filter. Data presented here utilized the factory-set calibration of
electrical current to PAH mass; however, other studies have shown variability in this calibration
(Dunbar et al. 2001; Brachtl et al. 2009). A previous study in Mexico City showed good agreement
between the PAS 2000CE and filter-based measurements using a calibration factor determined
during the study from aerosol mass spectrometry data (Marr et al. 2006), but a study in California
using the factory calibration found the PAS 2000CE to measure a higher PAH concentration than
concurrent filter measurements, though not to the same degree as our findings. The PAS 2000CE
mass data presented here likely includes instrumental response to PAH species not measured by
TD-GC/MS and possibly semi-volatile components that were lost from corresponding filter
samples prior to analysis. In addition, the calibration factor used here may not have reflected the
influences of application-specific parameters such as aerosol size distribution and the
photoionization of non-PAH components.
References
Birch, M. E. and Cary, R. A. (1996). "Elemental carbon-based method for monitoring occupational
exposures to particulate diesel exhaust." Aerosol Sci. Technol. 25(3): 221-241.
Brachtl, M. V., Durant, J. L., Perez, C. P., Oviedo, J., Sempertegui, F., Naumova, E. N. and
Griffiths, J. K. (2009). "Spatial and temporal variations and mobile source emissions of
polycyclic aromatic hydrocarbons in Quito, Ecuador." Environ. Pollut. 157(2): 528-536.
Demokritou, P., Lee, S. J., Ferguson, S. T. and Koutrakis, P. (2004). "A compact multistage
(cascade) impactor for the characterization of atmospheric aerosols." J. Aerosol Sci 35(3):
281-299.
Dunbar, J. C., Lin, C.-I., Vergucht, I., Wong, J. and Durant, J. L. (2001). "Estimating the
contributions of mobile sources of PAH to urban air using real-time PAH monitoring." Sci.
Total Environ. 279(1–3): 1-19.
Hagler, G. S. W., Bergin, M. H., Smith, E. A. and Dibb, J. E. (2007). "A summer time series of
particulate carbon in the air and snow at Summit, Greenland." J. Geophys. Res. 112(D21):
D21309.
Lough, G. C., Schauer, J. J., Park, J.-S., Shafer, M. M., DeMinter, J. T. and Weinstein, J. P.
(2005). "Emissions of metals associated with motor vehicle roadways." Environ. Sci. Technol.
39(3): 826-836.
Marr, L. C., Dzepina, K., Jimenez, J. L., Reisen, F., Bethel, H. L., Arey, J., Gaffney, J. S., Marley,
N. A., Molina, L. T. and Molina, M. J. (2006). "Sources and transformations of particle-bound
polycyclic aromatic hydrocarbons in Mexico City." Atmospheric Chemistry and Physics 6(6):
1733-1745.
Ramamurthi, M. and Chuang, J. C. (1997). Field and laboratory evaluations of a real-time PAH
analyzer. Research Triangle Park, NC, US Environmental Protection Agency.
Riediker, M., Williams, R. W., Devlin, R. B., Griggs, T. R. and Bromberg, P. A. (2003). "Exposure
to particulate matter, volatile organic compounds, and other air pollutants inside patrol cars."
Environ. Sci. Technol. 37(10): 2084-2093.
Sheesley, R. J., Schauer, J. J., Meiritz, M., DeMinter, J. T., Bae, M.-S. and Turner, J. R. (2007).
"Daily variation in particle-phase source tracers in an urban atmosphere." Aerosol Sci.
Technol. 41(11): 981 - 993.
Thornhill, D. A., de Foy, B., Herndon, S. C., Onasch, T. B., Wood, E. C., Zavala, M., Molina, L. T.,
Gaffney, J. S., Marley, N. A. and Marr, L. C. (2008). "Spatial and temporal variability of
particulate polycyclic aromatic hydrocarbons in Mexico City." Atmospheric Chemistry and
Physics 8(12): 3093-3105.