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The air change rates of motor vehicles are relevant to the sheltering effect from air pollutants entering from outside a vehicle and also to the interior concentrations from any sources inside its passenger compartment. We made more than 100 air change rate measurements on four motor vehicles under moving and stationary conditions; we also measured the carbon monoxide (CO) and fine particle (PM(2.5)) decay rates from 14 cigarettes smoked inside the vehicle. With the vehicle stationary and the fan off, the ventilation rate in air changes per hour (ACH) was less than 1 h(-1) with the windows closed and increased to 6.5 h(-1) with one window fully opened. The vehicle speed, window position, ventilation system, and air conditioner setting was found to affect the ACH. For closed windows and passive ventilation (fan off and no recirculation), the ACH was linearly related to the vehicle speed over the range from 15 to 72 mph (25 to 116 km h(-1)). With a vehicle moving, windows closed, and the ventilation system off (or the air conditioner set to AC Max), the ACH was less than 6.6 h(-1) for speeds ranging from 20 to 72 mph (32 to 116 km h(-1)). Opening a single window by 3'' (7.6 cm) increased the ACH by 8-16 times. For the 14 cigarettes smoked in vehicles, the deposition rate k and the air change rate a were correlated, following the equation k=1.3a (R(2)=82%; n=14). With recirculation on (or AC Max) and closed windows, the interior PM(2.5) concentration exceeded 2000 microg m(-3) momentarily for all cigarettes tested, regardless of speed. The concentration time series measured inside the vehicle followed the mathematical solutions of the indoor mass balance model, and the 24-h average personal exposure to PM(2.5) could exceed 35 microg m(-3) for just two cigarettes smoked inside the vehicle.
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Air change rates of motor vehicles and in-vehicle pollutant concentrations
from secondhand smoke
Stanford University, Stanford, California, USA
The air change rates of motor vehicles are relevant to the sheltering effect from air pollutants entering from outside a vehicle and also to the interior
concentrations from any sources inside its passenger compartment. We made more than 100 air change rate measurements on four motor vehicles under
moving and stationary conditions; we also measured the carbon monoxide (CO) and fine particle (PM
) decay rates from 14 cigarettes smoked inside the
vehicle. With the vehicle stationary and the fan off, the ventilation rate in air changes per hour (ACH) was less than 1 h
with the windows closed and
increased to 6.5 h
with one window fully opened. The vehicle speed, window position, ventilation system, and air conditioner setting was found to affect
the ACH. For closed windows and passive ventilation (fan off and no recirculation), the ACH was linearly related to the vehicle speed over the range from
15 to 72 mph (25 to 116kmh
). With a vehicle moving, windows closed, and the ventilation system off (or the air conditioner set to AC Max), the ACH
for speeds ranging from 20 to 72 mph (32 to 116 km h
). Opening a single window by 300 (7.6 cm) increased the ACH by 8–16
times. For the 14 cigarettes smoked in vehicles, the deposition rate kand the air change rate awere correlated, following the equation k¼1.3a(R
n¼14). With recirculation on (or AC Max) and closed windows, the interior PM
concentration exceeded 2000 mgm
momentarily for all cigarettes
tested, regardless of speed. The concentration time series measured inside the vehicle followed the mathematical solutions of the indoor mass balance
model, and the 24-h average personal exposure to PM
could exceed 35 mgm
for just two cigarettes smoked inside the vehicle.
Journal of Exposure Science and Environmental Epidemiology advance online publication, 18 July 2007; doi:10.1038/sj.jes.7500601
Keywords: motor vehicle, air change rate, secondhand smoke, particulate matter, carbon monoxide, benzene.
Time budget studies using diaries show that Americans
spend, on average, more than an hour (5–6% of the day) in
enclosed vehicles such as buses, vans, automobiles, and
trucks (Klepeis et al., 2001). Because of its small physical
volume, smoking in a motor vehicle’s passenger compart-
ment potentially can expose children and other passengers in
a car or van to very high concentrations of the pollutants
from secondhand smoke. An important factor affecting
interior concentrations is the ventilation rate, usually
reported in air changes per hour (ACH), which is affected
by the vehicle speed, ventilation settings, and window
positions. Our literature review indicates there have been
relatively few published measurement studies of secondhand
smoke in motor vehicles, nor of the factors affecting interior
concentrations. This study presents new air change rate
measurement data on stationary and moving vehicles,
including experiments and concentration measurements with
a real smoker inside the vehicle. These results are intended to
help us understand and predict in-vehicle exposures from
pollutants on roadways.
Review of studies
We briefly review past studies of vehicular air change rates,
with emphasis on studies examining the effect of vehicle speed
and ventilation settings on air change rates.
Engelmann et al. (1992) studied five stationary auto-
mobiles to determine the ‘‘sheltering effect’’ that an enclosed
vehicle offers against accidental releases of toxic airborne
gases and particles outside the vehicle on or near the
roadway. They conducted experiments with tracer gases
(ethane and ethylene) in a garage to measure the air change
rates of stationary vehicles. Using solutions to the mass
balance equation, they reported that a parked car with the
windows closed provides a substantial level of protection over
short time periods. With the air conditioning (AC) system
off, they found that the ACHs for a stationary vehicle ranged
from 0.42 to 1.09 h
. With the AC on, their reported ACHs
ranged from 1.96 to 3.23 h
fan on, from 8.7 to 10.7h
Ott et al. (1992) used a Langan L15 CO monitor to
measure carbon monoxide (CO) concentrations and a MIE
Received 15 March 2007; accepted 29 April 2007
1. Address all correspondence to: Dr. W. Ott, Stanford University,
Statistics, 1008 Cardiff Lane, Redwood City, California 94061, USA.
Tel.: þ1 650 364 1430. Fax: þ1 650 365 8292.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
r2007 Nature Publishing Group All rights reserved 1559-0631/07/$30.00
Miniram PDM-3 optical scattering monitor to measure
respirable particle concentrations (RSP or PM
) in a 1986
Mazda four-door sedan with a real smoker. The smoker sat
in the front passenger seat and smoked a cigarette every
15 min while the vehicle traveled at 20 mph on residential
streets free of traffic. With the windows closed and the vent
open, they observed a ‘‘sawtooth’’ concentration time series,
with CO concentrations reaching peak values of approxi-
mately 16 ppm for each cigarette. Based on this Miniram
optical particle monitor, they reported maximum RSP
concentrations above 2000 mgm
. They calculated the
vehicle’s ACH as 7.27 h
using the measured decay rate
of interior CO concentrations. They used a tape measure to
determine the vehicle’s volume as 3.7 m
and thus the rate of
air flow into the vehicle with the open vent and windows
closed at 20 mph was (3.7 m
)(7.27 h
)¼26.9 m
did not report a decay rate for particulate matter for the
vehicle, but they studied an enclosed chamber with volume
similar to that of a car (3.07 m
) and found an ACH of
5.71 h
with a particle decay rate of 7.26 h
that the difference between the particle decay rate and the
ACH is due to deposition of particles on interior surfaces, but
they did not investigate the effect of different window
positions or ventilation system settings on the ACH.
Ott et al. (1994) reported an ACH of 1.4 h
on a
Volkswagon station wagon (‘‘Squareback’’) when it was
stationary. With the windows closed and the vehicle moving
at 20 mph, they reported an ACH of 13 h
driver’s window fully open and the front passenger window
open 300 (1.2 cm), they measured an ACH ranging from 60 to
120 h
Fletcher and Saunders (1994) studied the air change rates
of five vehicles for different wind speeds and wind directions.
They determined leakage characteristics with the vents open
and with them closed. They used a tracer gas method to
release sulfur hexaflouide (SF
) inside one vehicle to measure
its ACH at constant speeds between 35 and 70 mph (56 and
113 km h
). They reported that the ACH for a vehicle
moving at a particular speed was greater than for a stationary
vehicle with wind passing it at the same speed, presumably
because the leakage characteristics of a moving vehicle on the
road are different than for a parked vehicle. Using their
measurement data, they derived an empirical equation for the
ACH versus speed that we will test in this paper.
Park et al. (1998) measured the ACHs under four different
conditions in three stationary automobiles. With the
windows closed and no mechanical ventilation, they reported
the ACH between 1.0 and 3.0 h
; with the ventilation set on
recirculation, they reported the ACH between 1.8 and
3.7 h
. With windows closed and the fan set on fresh air,
the ACH was between 13.3 and 26.1 h
. With a window
open, but no mechanical ventilation, the ACH ranged from
36.2 to 47.5 h
. They used the single-compartment mass
balance model to estimate interior concentrations from dry-
cleaned clothes and cigarette smoking, but they did not
make measurements of interior pollutant concentrations for
Rodes et al. (1998) reported the ACH of a 1997 Ford
Explorer with the windows closed and the vent fan set on
Low as 1.8 h
stationary; 5.6 h
at 35 mph; and 13.5 h
at 55 mph. For the vent set on high, they reported the ACH
of 10.7 h
with the vehicle stationary; 35.7 h
at 35 mph;
and 55.5 h
at 55 mph. For a 1997 Ford Taurus at 55 mph,
they found an ACH of 14 h
at the low vent setting and
76 h
at the high vent setting. Although their study did not
investigate the effect of window positions and vent settings
for all the vehicles, they reported that the ACH was
associated with the vehicle speed for the Ford Explorer.
Offermann et al. (2002) measured pollutant concentrations
with a smoker in a 1996 minivan driving at an average speed
of 18 mph under three different ventilation scenarios: (a)
driver’s window open and ventilation system off, (b)
windows closed and ventilation system on, and (c) windows
closed with ventilation off. With the window open and the
ventilation system off, they reported an ACH of 71 h
With the ventilation system on and the windows closed, they
measured an ACH of 60 h
, which dropped to 4.9 h
the ventilation system was turned off. Interior respirable
particle concentrations from smoking varied by factors from
13 to 300 times the outdoor concentration, depending on the
ventilation setting. They estimated that the particle exposure
for a 5-h automobile trip with two cigarettes smoked per
hour would be 25 times higher than the same exposure
scenario in a residence.
Park et al. (1998) conclude that the air change rate of a
vehicle is important for predicting the interior concentrations
of pollutants. With the exception of Fletcher and Saunders
(1994) and the measurements in Ott et al. (1994),
our literature review found no other published studies of
ACHs in moving vehicles under different ventilation and
window settings. Because of the importance of the vehicle’s
air change rate for exposure analysis, we made new
measurements of the ACHs of 4 motor vehicles under a
variety of conditions.
This study measured the air change rates of stationary and
moving vehicles under different ventilation conditions and
window positions to examine six hypotheses:
A moving vehicle’s ACH is a function of the ventilation
system settings, window positions, and vehicle speed.
With recirculation system off (vent open), the ACH will
follow the empirical equation for the vehicle’s speed
proposed by Fletcher and Saunders (1994) for passive
Air change rates of motor vehiclesOttetal.
2Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
At speeds above 20 mph, opening a single window by 300
(1.2 cm) causes a relatively large increase in the vehicle’s
The piecewise continuous exponential solutions to the
mass balance equation can predict accurately the concen-
trations inside the motor vehicle.
The ACH of the vehicle is important for estimating
interior air pollutant exposures.
A single cigarette smoked inside a vehicle can elevate interior
fine particle (PM
) mass concentrations above 2000 mgm
A main study goal was to provide new data on the
ventilation rates of motor vehicles under both stationary and
moving conditions. We also hoped to verify the high particle
concentrations for smoking predicted by Ott et al. (1992) and
by Park et al. (1998).
We studied the factors affecting the vehicle’s ventilation rates
and the interior concentrations of four motor vehicles (see
Table 1) when a cigarette was smoked in the passenger
compartment. We used three basic approaches: (1) fixed
quantities of tracer gases released into the passenger compart-
ment that became well mixed and caused a concentration decay
with time that was measured; (2) cigarettes smoked by a
smoker inside the vehicle, and (3) tracer gas releases at
controlled emission ratesFfor example, SF
Fto determine
the vehicle’s parameters. In our moving vehicle studies, we
located long roadway segments with minimal traffic during the
day on which it was possible to drive at a constant speed for
adequate time periods. Background concentrations were
measured both before and after each source emission.
Measurement Methods
The measurement methods and instruments included a Bru
and Kjær Multi-gas Model 1302 monitor, TSI Model
AM510 SidePaktPersonal Aerosol Monitor, TSI Model
8510 Piezobalance mass monitor, 2 Langan T15 CO
monitors for the front and back seats, a constant flow pump
(Amtek Alpha-2 Air Sampler) with Tedlar
bags (SKC-
West Inc., Fullerton, CA, USA) that were shipped to a
participating laboratory (AtmAA Inc., Calabasas, CA,
USA) for benzene analysis by gas chromatography (GC).
The TSI AM510 SidePaktpersonal aerosol monitor is a
portable (10.5 12.7 7.1 cm), battery-operated instrument
that uses 901light scattering with a 670-nm laser diode. It is
designed to measure over a concentration range of 1 mgm
20 mg m
and was equipped for our studies with a size
impactor measuring fine particles with diameters under 2.5 mm
). This monitor arrives from the manufacturer factory-
calibrated to the respirable fraction of ISO 12103-1,A1 test
dust (formerly Arizona test dust) and the operations manual
recommends that the user reset its ‘‘custom calibration factor’’
for the aerosol under investigation (TSI, 2003). We conducted
nine experiments in a 44 m
room with Marlboro regular filter
cigarettes under controlled conditions and compared the
SidePak monitor with our laboratory standard TSI 8510
piezobalance mass monitors. We then reset the SidePak’s
custom calibration factor from its factory setting of 1.0 to 0.33
based on these results, as recommended by the manufacturer.
The calibration of the laboratory TSI piezobalance monitors
has been verified in nine earlier experiments in an 8.9 m
chamber in which piezobalance mass readings were compared
with two cyclone mass filters that were weighed on a precision
laboratory scale (R
Determining Air Change Rates and Vehicle Volumes
An obvious way to determine the volume of a vehicle is to
measure its interior dimensions manually with a tape
measure. We divided the interior of each vehicle into several
large rectangular volumes and we measured the length,
width, and height of each volume. Internal furnishings, such
as seats, dashboard, and middle separators were converted to
estimated volumes that were subtracted from the overall
volume. Because some portions of seats and curved surfaces
are hollow, some smaller compartments may be unintention-
ally omitted, thus underestimating the true vehicle’s volume.
An alternative approach relied on a large cylinder of SF
tracer gas and a mass flow controller to provide a constant SF
flow rate , with the Bru
¨el and Kjær 1302 Multi-gas monitor
measuring the SF
concentrations inside the vehicle continu-
ously. We tested this method and found the vehicle often
required several hours for its mixing volume to reach an
equilibrium concentration (neither increasing nor decreasing).
The interior mixing volume obtained with this method was
slightly larger than for the manual method, and we found it
necessary to place the vehicle in a partly enclosed garage to
reduce the effect of time-varying winds. Although this approach
worked for a stationary vehicle, it could not be used on a
moving vehicle, because the Bru
¨el and Kjær monitor was
sensitive to vibration, and moving the monitor caused a
malfunction with repeated error messages on the digital display.
Ta b l e 1 . Dimensions of motor vehicles in study.
Vehicle Year and model Length Height Width Measured volume ( m
) Volume by decay (m
A 2005 Toyota Corolla (compact) 178.300 (70.2 cm) 58.500 (23 cm) 66.900 (26.3 cm) 2.6 2.7
B 2005 Ford Taurus (mid-size) 197.600 (77.8 cm) 56.100 (22.1 cm) 73.000 (28.8 cm) 2.2 2.4
C 1999 Lexus RX-300 (SUV) 180.100 (71 cm) 65.700 (25.9 cm) 70.500 (27.8 cm) 4.7 5.5
D 1999 Jeep Grand Cherokee Limited 18300 (72 cm) 6500 (25.6 cm) 70.500 (27.8 cm) 2.6 3.0
Air change rates of motor vehicles Ott et al.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14 3
A third approach was to fill a Tedlar sampling bag with a
known quantity of tracer gas, release the full contents of the
bag rapidly inside the vehicle, and measure the concentration
decay in the vehicle as a function of time. CO has the
advantage that existing ambient levels were extremely low in
California (typically less than 1.5 ppm) and CO can be
measured with high precision using real-time monitors with
automatic data loggers (Langan Products, San Francisco,
CA, USA). To fill each bag with a known quantity of CO, we
used an electronic mass flow controller (Brooks 5896)
attached to a Size D gas cylinder containing 99.99% pure
CO from Scott Specialty Gases (Longmont, CO, USA), a
Gilibrator primary flow calibrator (Sensidyne, Clearwater,
FL, USA), and a stop watch (see Figure 1). By setting the
mass flow controller flow rate to 200 cm
and timing
the flow with the stop watch to 2 min, for example, a 1 l
empty bag was filled with (200 cm
)(2 min) ¼400 cm
Figure 1 shows an acrylic plastic bag squeezer apparatus that
we constructed for this study, permitting the full amount of
gas inside the bag to be released rapidly inside the test vehicle.
When the vehicle was stationary, the bag’s valve was
opened inside the vehicle with a weight placed on the bag
squeezer, and the car door was promptly closed before the
contents were emitted. When the vehicle was moving, the
investigators were traveling inside the car, and a third CO
instrument with a digital display was used to verify the safety
levels of the interior concentrations, which were kept under
100 ppm. The contents of the bag were fully emptied by this
quick release method in less than a minute, or nearly
instantaneously relative to the longer residence times of the
air in the vehicle.
Mage and Ott (1996) observed that the pollutant
concentration in a mixing volume reaches its well-mixed
state, or gamma period, after a short period of time with
normal convective mixing, and thereafter the concentration
time series follows an exponential decay curve. By making a
semi-log plot of the concentration versus time for the well-
mixed portion of the curve, one can extend this curve
backward in time and use the peak estimation approach to
find the concentration that would have occurred if the
volume were well mixed when the tracer gas was initially
released from the bag (Ott, 2006).
Figure 2 illustrates how we determined the volume of Vehicle
C, a 1999 Lexus RX 300, by the rapid tracer gas release of a
400 cm
bag of pure CO at time t¼37 min. The vehicle was
parked with its windows closed, and CO concentrations were
measured at 12-s time intervals on both the front and rear
sets. The exponential function was fitted by linear regression
to the portions of the decay curve after t¼65 min, when the
two curves became very close together. Once the parameters
of this exponential function were determined, we computed
the mixing volume vof Vehicle C by dividing the 400 cm
released by the concentration x
¼72.7 ppm predicted
to occur at the bag-release time if the vehicle had been
uniformly mixed for the entire time period:
v¼400 cm3
¼400 cm3
72:7ppm ¼400106m3
Mass Flow
Bag Release Apparatus
Figure 1. Diagram showing (a) system used to fill sampling bags with a specific quantity of tracer gas and (b) bag release apparatus constructed of
Acrylic plastic with a hinge to squeeze the bag, causing a rapid release of the bag’s contents inside the motor vehicle.
Air change rates of motor vehiclesOttetal.
4Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
ACH of Vehicle A
Vehicle A was a 2005 Toyota Corolla rented from a dealer,
and we used the CO tracer gas release method to measure the
ACHs for various window and door positions (Table 2). The
front and rear seat ACHs were similar and were averaged. At
20 mph (32 km h
), we found that the mean ACH ranged
from 1.6 to 71 h
depending on the fan, window, and
recirculation system settings. With the vehicle parked or
traveling at 20 mph and recirculation on but the fan off,
which limits the entry of outdoor air, the ACH was 2.4 h
or less. Turning off the recirculation control raised the ACH
to 12 h
and setting the fan to Low increased the ACH to
35 h
. Opening the passenger window by 300 (7.6 cm) had
approximately the same effect as setting the fan to its lowest
position (36 h
), while opening both the driver and
passenger windows by 600 increased the ACH to 54 h
Opening one passenger window fully had about the same
effect as opening both front windows together (69 and
71 h
, respectively).
ACH of Vehicle B
Vehicle B was a 2005 Ford Taurus sedan that we rented from
a dealer for 4 days and we used the CO tracer gas controlled
release method to measure the ACH at constant speeds
ranging from 20 to 72 mph (32 to 116 km h
) for a variety
of window settings and ventilation system settings (Table 3;
Figures 3 and 4). During a 4.5-h time period of measure-
ments, this vehicle also was driven at constant speeds on low-
traffic roads with a real smoker present in the front passenger
seat (Figure 6).
fan control on the left side of the dashboard and a ventilation
system control on the right side. The fan control was set to its
lowest position and remained there, while the ventilation
system control was changed to each of 4 cases: Vent Off, Vent
On, AC On, and AC Max. There was no clearly labeled
recirculation control on the dashboard, although the Vent
Off and AC Max settings caused a recirculation state. We
investigated three cases of Vehicle B parked (stationary),
along with 21 cases of speeds at 20, 25, 50, 60, and 72 mph
(Table 3).
In most experiments, the measured front seat ACH and
rear seat ACH were nearly the same, indicating relatively
uniform mixing inside the vehicles (Tables 2 and 3). When
Vehicle B was parked and its front passenger seat window
was fully open, the measured front and rear seat ACHs were
6.6 and 6.4 h
, respectively (Table 3). On the two stationary
experiments in which the right front passenger door was fully
opened after the tracer gas was released, the front seat
monitor reported a higher ACH than the rear seat monitor,
which is explained by the increased air flow through the open
front door. With an open door, the average ACHs in the two
experiments were 68.6 and 57.9 h
, or about 10 times higher
than with the door closed and one window open.
At 20 mph with the Vent Off and windows closed, the ACH
measured in Vehicle B was 1.9 h
(Table 3), which was Vehicle
B’s lowest ACH while driving and was in the same range as
Vehicle A’s ACH at 20 mp with its recirculation control On
(Table 2). At 50 mph (80.5 km h
setting, Table 3 shows that Vehicle B’s ACH was 4.1 h
72 mph (km/h), the ACH was 5.0 h
. With the ventilation
system set to AC Max and the windows closed, we measured an
ACH of 5.6 h
at 60 mph, and the ACH’s for the two drives at
72 mph with AC Max were 6.6 and 6.0 h
. Opening one
window by just 300 (7.6 cm) during the Vent Off case caused the
ACH to increase from 1.9 to 28.9–30.8h
at 20 mph
Figure 2. CO concentration versus time for a 4 00 cm
bag of pure CO
release in Vehicle C while it was parked to measure the vehicle’s air
change rate and mixing volume. The concentration at the coincident
release point of 72.7 ppm gives a calculated mixing volume of
(400 cm
)/(72.7 ppm) ¼5.5 m
Ta b l e 2 . Air change rate measurements on Vehicle A (2005 Toyota
Speed (mph) Windows and
Recirc. Fan Air change rate (h
0 (Parked) All Closed On Off 0.92 F0.92
20 All Closed On Off 1.6 1.5 1.6
20 All Closed On Off 2.4 2.4 2.4
20 All Closed On Off 2.8 1.5 2.2
20 All Closed Off Off 12 12 12
20 All Closed Off Low 34 35 35
20 Pass. Open 300 On Off 38 33 36
20 Driver+Pass.
open 600
Off Off 44 63 54
20 Pass. Fully
On Off 77 60 69
20 All Fully
On Off 71 F71
Air change rates of motor vehicles Ott et al.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14 5
(32 km h
); from 4.1 to 51.7 h
at 50 mph (80 km h
); and
from 5.0 to 44.4 h
at 72 mph (116 km h
). Similarly,
opening the passenger window by 300 in the AC Max setting
caused the ACH to increase from 5.6 to 48.5 h
at 60 mph
(96.5 km h
) and from 6.6 to 54.0 h
at 72 mph
(116 km h
). The results show that opening a single window
by 300 increased the vehicle’s ACH by 8 to 12 times, and the
ACH depended on the vehicle speed once the window was open.
Finally, with the Vent On and the windows closed, Table 3
shows that Vehicle B’s ACH was 30.3 h
at 20 mph
(32 km h
); 28.4 and 35.6 h
on two successive drives at
60 mph (96.5 km h
); and 32.9 h
on one drive at 72 mph
Ta b l e 3 . Air change rate measurements of Vehicle B (2005 Ford Taurus).
Speed (mph) Windows and doors Ventilation system Air change rate (h
Front seat Rear seat Mean
0 (Parked) Window fully open Off 6.6 6.4 6.5
0 (Parked) Door fully open Vent on 81.0 56.1 68.6
0 (Parked) Door fully open Vent on 74.9 40.8 57.9
20 All closed Vent off 1.9 1.9 1.9
20 Window opened 300 00 31.4 30.2 30.8
20 All closed AC on 28.0 30.7 29.4
20 All closed Vent on 30.3 30.2 30.3
20 Window opened 300 Vent off 29.1 28.7 28.9
25 All closed Vent on 38.8 31.1 35.0
50 All closed Vent off 3.9 4.3 4.1
50 Window opened 300 Vent off 47.4 55.9 51.7
60 All closed Vent on 22.9 33.9 28.4
60 All closed Vent on 40.5 30.7 35.6
60 All closed AC on 27.4 30.0 28.7
60 All closed AC max 5.5 5.6 5.6
60 Window opened 300 AC max 44.8 52.1 48.5
72 All closed Vent off 4.0 5.9 5.0
72 Window opened 300 00 44.3 44.4 44.4
72 All closed Vent on 29.0 36.8 32.9
72 All closed AC on 27.3 32.5 29.9
72 All closed AC max 6.4 6.7 6.6
72 Window opened 300 00 41.6 66.3 54.0
72 All closed AC max 6.1 5.9 6.0
72 Window opened 300 00 43.8 49.7 46.8
Figure 3. CO concentrations measured in the front and rear seats of Vehicle B for bag release experiments at a variety of speeds and ventilation
system settings.
Air change rates of motor vehiclesOttetal.
6Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
(116 km h
). Similarly, with the AC On, the ACH was
29.4 h
at 20 mph; 28.7 h
at 60 mph, and 29.9 h
72 mph. There is no evidence that the ACH was correlated
with the vehicle speed during the eight Vent On and AC On
cases. A possible explanation is that the Ford Taurus
automatically turns on its ventilation fan for these cases,
and the strong fan activity dominates the ventilation inside
the car’s passenger compartment. It is noteworthy that for
Figure 4. Examples of CO concentration decay curves for eight air change rate measurement experiments in Vehicle B. The rapid bag release
occurred in the front seat, and the monitor was located in the back seat of the vehicle.
Air change rates of motor vehicles Ott et al.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14 7
eight cases of Vent On or AC On with the windows closed,
the ACHs ranged from 28.4 to 35.6 h
, indicating that the
Vent On and AC On settings caused relatively high air
change rates above 28 h
for all the speeds tested.
In contrast, Driving Vehicle B with the Vent Off or AC
Max settings with the windows closed produced a relatively
low ACH of 6.6 h
or less at nearly all speeds. The lowest
air change rate while moving (1.9 h
) was at 20 mph with
the Vent Off setting. In comparison, as described above,
selecting Vent On, AC On, or opening a passenger window
by 300 increased the vehicle’s ACH to more than 28 h
Passive Ventilation State
Differences in ventilation control designs of the vehicles made
it difficult to set the recirculation system of all the vehicles in
the exact same manner. Vehicles A and C each had a clearly
marked ‘‘recirculation control’’ on the dashboard that could
be set On or Off, but Vehicles B and D did not have
recirculation controls. We concluded that setting the AC
control, fan control, and recirculation control to Off on
Vehicles A and C opened the fresh air vents without the
mechanical ventilation system operating, which was the same
as the passive ventilation case for the vehicles studied by
Fletcher and Saunders (1994). We made 50 measurements of
the ACH in Vehicles A and C for this passive ventilation case
and the regression analysis gave a straight line was not too
different from the empirical equation A¼0.60V
oped by Fletcher and Saunders (see Figure 5). Because their
exponent 1.25 is close to 1.0, their equation plots nearly as a
straight line and it appears close to the slope of our regression
line. Our straight-line regression equation A¼0.62 V3.4
covered a speed range from 15 to 72 mph, giving an observed
ACH ranging from 5.9 to 41.2 h
. Because we could not set
the controls on Vehicles B and D to a similar passive
ventilation state (recirculation off and no fan operating), we
could not test the empirical equation of Fletcher and
Saunders (1994) on these two vehicles.
Effect of Smoking on Interior Concentrations
In our first cigarette test in Vehicle A, we lit a Marlboro
regular filter cigarette in the passenger compartment and let it
smolder until putting it out just before its filter was ignited.
At 20 mph with the windows closed and the fan and air
conditioner Off, the peak CO concentration was 19 ppm with
a mean of 11.2 ppm for a 40-min time period. The measured
ACH was approximately 1.9 h
(1.96 h
from the back
seat monitor; 1.8 h
from the front seat monitor). The peak
concentration was 3035 mgm
and the mean was
1163 mgm
averaged over 46 min. The particle decay rate
was 6.1 h
, which corresponds to a calculated particle
deposition rate of 6.1–2 ¼4.1 mgm
For Vehicles B and D, we contacted volunteer smokers
and asked them to sit in the front passenger seat and smoke a
series of cigarettes at prescribed times while we drove the
vehicles at constant speeds, fixed window settings, and
specified ventilation and air conditioner settings. We selected
roadways with minimal traffic, allowing the vehicle to
maintain a constant speed for an extended time period: the
full time over which the cigarette was smoked including its
decay period. We made simultaneous measurements of
continuous CO and PM
concentrations inside the passen-
ger compartment of the vehicle.
In a test drive of Vehicle B, a Marlboro regular filter
cigarette first was smoked by the volunteer smoker with the
vehicle stationary (Cig no. 1 in Figure 6, top panel); then
four cigarettes were smoked at 20 mph and three were
smoked at 60 mph (Figure 6, bottom). With the vehicle
stationary and the front passenger window fully open,
the average PM
concentration was 82.4 mgm
over 38.7 min), with a maximum 12-s concentration of
705 mgm
(Table 4). The maximum 12-s reading usually
exhibited much variability during the smoking period and,
except where noted in Table 4, the averaging time for each
cigarette usually was long enough to cover the entire time
period until the cigarette’s concentration was no longer
detectable by the monitor.
The average concentration for Cig no. 1 can be converted
to a common 24-h reference time for comparison by
using the ratio of the cigarette averaging times to the
number of minutes in a day; that is,
(24 h day
)(60 min h
)¼1440 min day
x24 h¼ð82:4mgm
1440 min ¼2:2mgm3ð2Þ
Here, the average concentration of x24h¼2:2mgm
3can be
interpreted as the 24-h incremental exposure (IE
nonsmoking passenger in the car would receive if that
V, Speed (mph)
10 20 30 40 50 60 70
A, Air Change Rate (h-1)
Fletcher and Saunders Model
Vehicle C ACH vs. Speed
Vehicle A ACH vs. Speed
Vehicles A and C
Windows Closed
Fan Off
Equation: A = 0.60V1.25
Linear Regression
R2 = 85.9%
Slope = 0.62mi-1
Intercept = -3.4h-1
n = 50
Figure 5. Observed air change rate versus speed for Vehicles A and C
with the windows closed and passive ventilation (fan and recirculation
system off), showing closeness of the linear regression line for our data
to the empirical equation A¼0.60V
proposed by Fletcher and
Saunders (1994).
Air change rates of motor vehiclesOttetal.
8Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
Figure 6. PM
concentration measured inside Vehicle B at two different speeds F20 mph (top panel) and 60 mph (bottom panel)Fwhile a real
smoker smoked eight Marlboro regular filter cigarettes for various window and ventilation system settings.
Ta b l e 4 . Particulate mass concentrations in vehicles with a smoker smoking a cigarette.
Vehicle Cig. No. Speed
Windows Ventilation system Max. PM
Avg. time
Mean PM
B 1 0 Parked, passenger window open All off 705 38.7 82.4
B 2 20 Windows closed AC max 3184 27.2
B 3 20 Passenger window open 300 AC off 685 12.5 119
B 4 20 Passenger window fully open AC off 371 10.8 96.6
B 5 20 Windows closed AC regular 2,389 15.0 529
B 6 60 Windows closed AC regular 1394 14.5 465
B 7 60 Passenger window open 300 AC off 608 9.0 119
B 8 59 Windows closed AC max 3808 43.0
D 1 62 Windows closed Vent off, recirc. 3212 25.7 1150
D 2 62 Windows closed AC on, recirc. 2828 31.0 1060
D 3 62 Windows closed AC on, no recirc. 1138 14.5 420
D 4 60 Windows closed AC on, no recirc. 1051 25.7 203.6
D 5 60 Windows closed, opened 200 Vent off, recirc. 3104 37.3
Decay period not fully completed.
Air change rates of motor vehicles Ott et al.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14 9
person’s exposure were zero during the remainder of the 24-h
time period. Although Cig no. 2 of Vehicle B did not fully
complete its decay period, its mean concentration of
1113 mgm
for 27.2 min gave an incremental exposure of
21 mgm
for 24 h using Eq. 2. Thus, smoking four cigarettes
in this car at 60 mph with AC Max and the windows closed
would cause a 24-h incremental exposure of IE
(4)(21 mgm
)¼84 mgm
, which is well above the EPA
health-based ambient standard of 35 mgm
for 24 h,
whereas smoking two cigarettes would give IE
(2)(21 mgm
)¼42 mgm
, which is also above EPA’s
standard of 35 mgm
averaged over 24 h.
ACH and Particle Decay Parameters
A smoking cigarette emits both particulate matter and CO
and the resulting concentrations can be measured as a
function of time. By subtracting the background CO
concentration and plotting the measured CO concentration
time series on semilogarithmic paper during the decay period,
the slope of the CO time series plot gives the ventilation rate a
of the vehicle. The particulate matter concentration decay
rate f
¼aþkis obtained in a similar manner, except that it
is the sum of the air change rate aand the particle deposition
rate k, because particles tend to plate out on interior surfaces
of the vehicle. We solved for the particle deposition rate kas
a. Ott et al. (1992) derive these equations for a
motor vehicle and they are discussed more generally in Ott
(2006) and Wallace and Smith (2006) (in the equations
predicted in Ott, Langan, and Switzer (1992), the definition
of the deposition parameter kis slightly different but
represents the same deposition phenomenon).
In the eight smoking experiments on Vehicle B (Table 5)
and five smoking experiments on Vehicle D (Table 6), we
measured both the air change rates and particle decay rates
using cigarettes smoked by the smokers as the sources of the
elevated interior CO and particulate matter. The ACH
ranged from 3.0 to 78.6 h
and the particle decay rate
ranged from 7.7 to 194.4 h
; the particle decay rate was
found to be correlated with the ACH. Including the 1
cigarette smoked in Vehicle A, the combined regression
analysis for 14 cigarettes gave R
¼82% and the particle
decay rate was 2.3 times the ACH, or f
¼2.3a. Subtracting
the ACH from the decay rate gives a relationship between the
deposition rate and the ACH as k¼1.3a. The individual
deposition parameters ranging from k¼1.7 h
k¼138 h
also were correlated with the ventilatory air
change rate a(R
¼61%). The increased rate of particle
deposition with the increased ACH is important and is
explained by the greater turbulence associated with higher
ventilation activity. Using the relationship of k¼1.3afor the
fine particle deposition rate, and solving for the indoor
outdoor ratio a/(aþk) used in indoor air models, we obtain
a/(aþk)¼a/(aþ1.3a)¼1/2.3 ¼0.44, which is the predicted
ratio of the long-term average indoor concentration to the
outdoor concentration for fine particulate matter infiltrating
air quality modeling settings, such as rooms and homes.
Mathematical Modeling of Concentrations
In the drive shown in Figure 6, the smoker began smoking
Cig no. 2 in Vehicle B at 1:39 PM and finished the cigarette
at 1:44 PM, so the cigarette lasted 5 min. We can apply the
piecewise continuous exponential solutions to the mass
balance equation described by Ott et al. (1992) to the data
for Cig no. 2. For particulate matter, the model requires
parameter values for the particle deposition rate kand the
source emission rate in mg min
For Cig no. 2 in Vehicle B, the overall particle decay rate
was estimated as f
¼7.7 h
(Table 5). The cigarette lasted
for 5 min and the mixing volume of the vehicle determined by
the CO tracer gas decay method was 2.4 m
(Table 1). Using
these values and a revised version of the QuickBASIC
computer program described in Ott et al. (1992) for
predicting concentrations for a single cigarette at 10-s time
increments, a satisfactory fit of the model to the data was
found for a PM
source strength of 2. 2 mg min
emissions for this cigarette based on its 5-min smoking
time would be (5 min)(2.2 mg min
)¼11 mg, which is
consistent with the PM
emission factors reported by
Daisey et al. (1998). Klepeis et al. (1996) report a lower
Ta b l e 5 . Air change and particle decay rates from smoking in a 2005 Ford Taurus sedan (Vehicle B).
Cig No. S peed (mph) Windows Air conditioner Decay rate f
) Deposition rate k(h
1 0 One fully open AC off 39.5 19.2 20.3
2 20 All closed AC max 7.7 3.0 4.7
00 AC off 42.4 20.9 21.5
4 20 One fully open AC off 151.4 78.6 72.8
5 20 All closed AC regular 48.0 32.1 15.9
6 60 All closed AC regular 48.8 38.6 16.7
00 AC off 194.4 56.4 138.0
8 60 All closed AC max 12.9 5.1 7.8
The deposition rate kis the particle decay rate minus the air change rate a;thatis,k¼f
Air change rates of motor vehiclesOttetal.
10 Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
emission rate of 1.43 mg min
of RSP (PM
measurements at two smoking lounges where a mixture of
brands were smoked with a typical smoking time of 10 min.
Their results give a source strength of 14.3 mg for multiple
brands, which is relatively close to the source strength of
11 mg for this particular Marlboro regular filter cigarette.
Figure 7 shows the PM
concentration measured for Cig
no. 2 in Vehicle B and the concentration predicted by the
model. The slight difference in timing of the maxima of the
two curves probably results from imperfect mixing inside
the vehicle as well as uncertainty about the exact time at
which the cigarette stopped its emission after it was
extinguished. The two time series curves are similar in shape,
indicating that the air in the vehicle behaved like a well-mixed
compartment to a reasonable approximation and that
published source emission rates can be used to model
cigarette concentrations inside the vehicle with reasonable
Benzene Example
We can illustrate a practical use of these findings by applying
this methodology to a new vehicle not used in our study and
to another air pollutant. We rented a Chevrolet Malibou
sedan and asked a volunteer smoker to smoke three
cigarettes, one every 15 min, while riding in the passenger
seat of the the vehicle. While the cigarettes were being
smoked, we used a 200 cm
pump to collect seven
samples by filling Tedlar bags inside the vehicle for
subsequent laboratory GC analysis of benzene concentra-
tions. The vehicle was driven at 20 mph in residential
neighborhoods during the day when there was virtually no
other vehicular traffic on these residential streets. The
windows were closed and the recirculation was Off with the
ventilation fan set to Off. Using the linear equation in
Figure 5 for the ACH versus speed, which gives approxi-
mately the same result as the equation of Fletcher and
Saunders (1994), we estimate the ACH of this vehicle as
. Daisey et al. (1998) report an emission factor for
benzene of 406771 mg per cigarette for an average of six
American cigarettes representing 62.5% of the brands sold in
California, which gives a benzene emission rate for a 10-min
cigarette in their study of 40.6 mgmin
. In our test car, the
first cigarette smoked by the smoker lasted 7 min and the
second and the third cigarettes lasted 8 min. Using the
sequential mass balance equations (Ott et al., 1992) and a car
volume of 3.7 m
, the calculated benzene concentration curve
for the first cigarette reached 52 mgm
and then decayed
downward until reaching the upward trend caused by the
next cigarette, with the three cigarettes resembling three teeth
of a ‘‘sawtooth’’ pattern (Figure 8). The air samples were
collected in seven sampling bags and the height of each
crosshatched rectangle is the average benzene concentration
measured during the bag’s collection period. The correlation
coefficient between the predicted concentration for each bag
and the measured concentration was r¼0.68, and the model
overestimated the benzene concentration for the first cigarette
but showed better agreement on the second and third
cigarettes. The mean of the measured benzene concentrations
for the three cigarettes was 25 mgm
averaged over 1 h.
The motor vehicle shows a much wider range of air change
rates than those measured in homes. When the vehicle was
stationary, the measured ACH typically was less than 1 h
Park et al. (1998) observed an ACH less than 3 h
for a
stationary vehicle with closed windows and no mechanical
ventilation. Their study found that the ACH of a stationary
vehicle was affected by winds, which we confirmed and
therefore conducted our stationary vehicle ACH measure-
ments in a partially enclosed garage. In our studies, opening
fully a single window of a parked vehicle increased the ACH
to 6.5 h
and opening a door increased the ACH to 68 h
The vehicle speed had a significant effect on the ACH,
especially when a vent or window was open. For closed
windows, we observed a linear relationship between the ACH
72 mph, which was similar to the curvilinear equation
developed by Fletcher and Saunders (1994). This finding
applies only to vehicles that can be set to a passive ventilation
state with an open vent and no mechanical ventilation
(recirculation control off and no fan operating). For a
moving vehicle with the windows closed, the lowest ACH
occurred with the ventilation system off or the air conditioner
set to its maximum setting (AC Max) and was less than 7 h
Ta b l e 6 . Air change rates and particle decay parameters from smoking in a 1999 Jeep Cherokee (Vehicle D).
Cig No. Speed (mph) Windows Air conditioner Decay rate f
) Deposition rate k(h
1 62 All closed All off 7.7 6.0 1.7
2 62 All closed AC on 12.7 8.2 4.5
3 62 All closed AC on, no recirc 59.6 28.4 31.0
4 60 All closed AC on, no recirc. 59.6 23.4 36.9
00 All off 10.9 7.7 3.2
Air change rates of motor vehicles Ott et al.
Journal of Exposure Science and Environmental Epidemiology (2007), 1–14 11
for all speeds ranging from 20 to 72 mph (32 to 116 km h
Opening a single window by even a small amount (300)
increased the ACH by 8–16 times; with the vent off, for
example, Vehcile B’s ACH increased from 1.9 to 30.8h
20 mph; from 4.1 to 51.7h
at 50 mph; and from 6 to
46.8 h
at 72 mph.
Smoking a cigarette in a car allows determining both air
change rate from the CO concentration time series and the
fine particle decay rate from the particle concentration time
series. Our studies confirmed the predictions by Park et al.
(1998) from a model that fine particle concentrations could
exceed 2000–3000 mgm
in a moving vehicle with the
windows closed, and our findings also verified the high in-
vehicle particle concentrations measured by Ott et al. (1992)
in one vehicle. Our studies produced results similar to the
findings of Rees and Connolly (2006), who measured CO
Figure 7. PM
measurements in Vehicle C for Marlboro Regular Filter Cigarette No. 2 smoked by a real smoker at 20 mph showing (a) semi-log
plot of particle decay period, and (b) time series predicted using a mathematical model with cigarette emission of 14 mg, compared with the measure
concentration time series.
Figure 8. Measured benzene concentration for a smoker in a
Chevrolet Malibou driving at 20 mph with the window closed,
compared with piecewise continuous benzene concentrations calcu-
lated for three cigarettes using the mass balance equations.
Air change rates of motor vehiclesOttetal.
12 Journal of Exposure Science and Environmental Epidemiology (2007), 1–14
and PM
in three automobiles during 45 trials with
volunteer drivers and smokers recruited from the general
community. They reported mean PM
concentrations of
272 mgm
for the windows closed and 51 mgm
for the
windows open during 5-min smoking period, with higher
peak levels observed briefly (505 mgm
closed and
104 mgm
open). Their drivers maintained speeds between
30 and 40 mph, and they did not use air conditioning or air
recirculation, which helps explain why their peak concentra-
tions were less than 2000 mgm
. They also report that
legislation banning smoking in cars with young children
present was adopted in Arkansas in 2006, and similar
smoking bans with children have been introduced in the
states of California, Georgia, Michigan, New Jersey,
New York, Pennsylvania, and Vermont. An important new
scientific finding of our study was that the particle deposition
rate was correlated with the air change rate, producing a
relatively simple equation for calculating the deposition rate
for particulate matter in a car from cigarette smoking. The
high particle concentrations inside cars with smokers are due
to the small volumes of the passenger compartments, and the
concentrations become extremely high with the low air
change rates caused by closing windows and air conditioning.
These extremely high particle concentrations constitute a
serious health risk for adults and children who are passengers
This study has provided new measurement data on air
change rates in moving vehicles and their relationship to
vehicle speed, ventilation settings, and window positions. It
also provided information for estimating interior concentra-
tions from smoking inside a vehicle. Our main findings are:
The rapid release of a known quantity of tracer gas inside
the vehicle allows calculation of both the air change rate
and the mixing volume.
Opening a single window by 300 increased the vehicle’s air
change rate by about tenfold, ranging from 8 to12 times
for various speeds and ventilation settings.
With the vent open (recirculation off), the air change rate
for Vehicles A and C was related to the speed by the
empirical equation of Fletcher and Saunders (1994), which
should be valid for any vehicle under passive ventilation
Using parameters estimated from the motor vehicle
measurements, the time series of particulate matter and
CO concentrations predicted by the model agreed well
with the concentrations measured in the vehicle.
A cigarette is a source of CO and fine particles that can be
used for simultaneously determining the air change rate
and the particle decay rate in a vehicle.
Smoking a single Marlboro Regular Filter cigarette with
the vehicle stationary and the passenger window fully open
caused a 38.7-min pH
average of 82.4 mgm
With recirculation on (or AC Max) and closed windows,
the PM
mass concentration momentarily exceeded
2000 mg/m
for all cigarettes smoked in the vehicles and
the mean PM
concentration from a single cigarette at
20 mph in Vehicle A was 1113 mgm
averaged over
27.2 min.
The 24-h incremental exposure for one cigarette was
21 mgm
would cause an incremental 24-h exposure of 42 mgm
which is above the recent EPA health-based PM
ambient standard of 35 mg/m
for 24 h.
The relatively high PM
concentrations from smoking
inside a vehicle can be explained by two factors: (a) the
high particle source emissions of a cigarette (about 12
14 mg), and (b) the relatively small mixing volume of a
motor vehicle (2–6 m
was found to be correlated with
the air change rate ain the vehicles tested (f
¼82%; n¼14); these results give an indoor–outdoor
ratio of a/(aþk)¼0.43.
For three cigarettes smoked inside a vehicle, the interior
benzene concentration was measured to be 25 mgm
averaged over 60 min.
There are few published studies available in the literature
on the air change rates of motor vehicles, especially moving
vehicles. The air change rate is relevant both to the interior
concentrations caused by sources inside the vehicle and to the
‘‘sheltering effect’’ of a vehicle from toxic releases infiltrating
from outside into the vehicle. It is hoped that these
measurements of air change rates and interior concentrations
from smoking under different conditions will give useful data
to improve the accuracy of estimates of air pollutant
exposures inside motor vehicles.
We are grateful to the Flight Attendant Medical Research
Institute (FAMRI) for funding this research. Grateful
appreciation also is extended to Pamela Shreve, Gloria
Duenas, and Johnny Fonda for their personal help conduct-
ing this research.
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... Besides, the passive ventilation airflow (Qps) refers to the air entering the HVAC system, which is not induced by the operation of the fan, but because of for example the vehicle's speed or wind speed. This flow is accounted for in the total ventilation flow in the studied vehicles and it also passes the filter (Ott et al. 2008;Lee et al. 2015a). Thus, it is not considered infiltration. ...
... The passive ventilation airflow Qps entering the cabin has been found linearly related to the vehicle driving speed vspeed (Ott et al. 2008). Linear regression of the measured passive ventilation data has reported an experience coefficient of 0.21 m −1 (Lee et al. 2015b). ...
... During the sensitivity analysis, the deposition rate β (h −1 ) was varied within the literature-reported range of 0.5-12.6 (h −1 ) (Ott et al. 2008;Ding et al. 2016;Harik et al. 2017). A higher β (h −1 ) leads to a higher Qdep. ...
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The main aim of this study is to develop a mathematical size-dependent vehicle cabin model for particulate matter concentration including PM 2.5 (particles of aerodynamic diameter less than 2.5 μm) and UFPs (ultrafine particles of aerodynamic diameter less than 100 nm), as well as CO 2 concentration. The ventilation airflow rate and cabin volume parameters are defined from a previously developed vehicle model for climate system design. The model simulates different filter statuses, application of pre-ionization, different airflow rates and recirculation degrees. Both particle mass and count concentration within 10–2530 nm are simulated. Parameters in the model are defined from either available component test data (for example filter efficiencies) or assumptions from corresponding studies (for example particle infiltration and deposition rates). To validate the model, road measurements of particle and CO 2 concentrations outside two vehicles were used as model inputs. The simulated inside PM 2.5 , UFP and CO 2 concentration were compared with the inside measurements. Generally, the simulation agrees well with measured data (Person’s r 0.89–0.92), and the simulation of aged filter with ionization is showing higher deviation than others. The simulation using medium airflows agrees better than the simulation using other airflows, both lower and higher. The reason for this may be that the filter efficiency data used in the model were obtained at airflows close to the medium airflow. When all size bins are compared, the sizes of 100–300 nm were slightly overestimated. The results indicated that among others, expanded filter efficiency data as a function of filter ageing and airflow rate would possibly enhance the simulation accuracy. An initial application sample study on recirculation degrees presents the model’s possible application in developing advanced climate control strategies.
... Ott et al. 39 and Saber and Bazargan 40 studied the persistence of cigarette smoke inside the cabin of a passenger car subject to different ventilation scenarios, while M€ uller et al. 41 assessed the concentration of contaminants entering from outside the cabin. However, these studies did not examine the microclimate within the cabin or the transport of airborne pathogens from occupant to occupant. ...
... This approach mimics the mixing of a high Schmidt number species, such as smoke or aerosols released within the cabin. 39 We note that the RANS approach employed here is not as accurate as direct numerical simulations (DNS) where the full Navier-Stokes equations are solved, resolving all relevant length scales and time scales of the turbulent flow. Similarly, other approaches, such as large eddy simulations (LES), might offer improvements in accuracy compared the Reynolds-averaged approach. ...
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Identifying the potential routes of airborne transmission during transportation is of critical importance to limit the spread of the SARS-CoV-2 virus. Here, we numerically solve the Reynolds-averaged Navier-Stokes equations along with the transport equation for a passive scalar in order to study aerosol transmission inside the passenger cabin of an automobile. Extending the previous work on this topic, we explore several driving scenarios including the effects of having the windows fully open, half-open, and one-quarter open, the effect of opening a moon roof, and the scaling of the aerosol transport as a function of vehicle speed. The flow in the passenger cabin is largely driven by the external surface pressure distribution on the vehicle, and the relative concentration of aerosols in the cabin scales inversely with vehicle speed. For the simplified geometry studied here, we find that the half-open windows configuration has almost the same ventilation effectively as the one with the windows fully open. The utility of the moonroof as an effective exit vent for removing the aerosols generated within the cabin space is discussed. Using our results, we propose a "speed-time" map, which gives guidance regarding the relative risk of transmission between driver and passenger as a function of trip duration and vehicle speed. A few strategies for the removal of airborne contaminants during low-speed driving, or in a situation where the vehicle is stuck in traffic, are suggested.
... The literature on well-mixed models is substantial, i.e., the spaces considered include aircraft cabins [26], buses [27], hospital wards [28,29], and residential buildings [30,31], or recent case study scenarios of different indoor settings [32]. Experiments have investigated the transport dynamics of pollutants in differently sized indoor spaces [9,33,14] and how human presence and activity can affect these dynamics [15,34,35]. Studies have also looked at how aerosols can transfer from room to room [36,13,17]. ...
... For near-field disease transmission the temporal dynamics of aerosol dispersion is highly dependent on the activity-duration author room volume (m 3 ) ACH (hr −1 ) τ (min) measurement duration (min) description Ishizu [ [11] 548 NA 2.6 32 CO concentration, cigarette in Tavern Miller and Nazaroff [12] 36 0.03-1.7 23-40 150-240 cigarette smoke, 2 compartments Ott et al. [13] 34 4 44 225 CO concentration, cigar smoke, 2 compartments Ott et al. [14] 3-5 3-56.4 0.3-7.8 NA < 2.5µm particles, cigarette in car Qian et al. [15] 242 NA 43 70 < 10µm particles in 2 story house Stephens et al. [16] 45 NA 23.6 59 10 − 100nm particles, 3D printer emissions, conditioned air Poon et al. [17] 11.9 40.6 11.8 32 < 100nm particles, cooking in source room, 2 compartments of the source and the dispersion mechanism. ...
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Airborne diseases can be transmitted by infectious aerosols in the near field, i.e., in close proximity, or in the far field, i.e., byinfectious aerosols that are well mixed within the indoor air. Is it possible to say which mode of disease transmission is predominantin large indoor spaces? We addressed this question by measuring the transport of aerosols equivalent to the size of human respiratoryparticles in two large hardware stores (V > 10 000 m3). We found that aerosol concentrations in both stores decreased rapidly andalmost independently of aerosol size, despite the different ventilation systems. A persistent and directional airflow on the order ofa few cm/s was observed in both stores. Consequently, aerosol dynamics in such open settings can be expected to be dominated byturbulent dispersion and sweeping, and the accumulation of infectious aerosols in the indoor air is unlikely to contribute significantlyto the risk of infection as long as the occupancy of the store is not too high. Under these conditions, well-fitting face masks are anexcellent means of preventing disease transmission by human aerosols.
... The air exchange rates (AERs) significantly affect the incabin air quality of vehicles (Atkinson et al. 2017;Chan and Chung 2003;Knibbs et al. 2010). The AERs associated with vehicles are generally not known but estimated from systematic investigation and varied significantly with each trip even conducted from same vehicle due to its widely dependence over driving speed (Knibbs et al. 2009;Ott et al. 2008;Rodes et al. 1998). The low AERs are usually associated with new vehicles due to airtight windows sealing and cabin structure, or car moving at slower speed that resulted in low air flow dynamics or pressure differences around the vehicle . ...
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Vehicle occupants spend prolonged durations inside the cabin due to longer commute or congested road networks. The poor in-cabin air quality and prolonged travel duration contribute a significant fraction to occupant’s daily exposure levels. The intrusion of outside air pollutants inside vehicle through ventilation system and cabin leakages are recognized as dominant factors that influence the in-transit air quality. In the present study, mobile campaign was conducted from regular passenger cars to investigate the impact of vehicle characteristics, ventilation settings, fan strength, and driving speed over in-cabin particle number concentration (PNC) and air exchange rates (AERs) under realistic driving conditions. Under outside air (OA) mode, outdoor ambient air is drawn inside the vehicle cabin whereas, under recirculation (RC) mode, in-cabin air is recirculated by ventilation fan. The average in-cabin total PNC measured under OA and RC modes are 6.61E + 07 # m⁻³ and 2.02E + 07 # m⁻³ respectively. The AERs estimated under realistic driving conditions with OA and RC modes had mean (median) values of 17.44 (12.65) h⁻¹ and 8.24 (6.99) h⁻¹ respectively. The AERs potential influencing parameters (vehicle age, mileage, speed, cabin volume, and fan operating strength) were measured for each trip. A Generalized Estimating Equation (GEE) model was developed and outcomes revealed that vehicle age and cabin volume are statistically significant factors in determining the AERs under OA and RC modes respectively. However, vehicle speed and fan strength variables were positively associated with AERs but not statistically significant under OA mode.
... The variables affecting the degree to which airborne particulate pollution penetrates any given vehicle include (but are not limited to) the in-vehicle/ambient air pressure difference, vehicle speed, wind direction and speed (relative to the direction of vehicular motion), and air conditioning mode (Muilenberg et al., 1991;Lee et al., 2015b). The mode of particle deposition can also significantly influence the characteristics of particulate dispersal within vehicles (Ott et al., 2008). Furthermore, intra-vehicular windspeed (with windows open), surface-to-volume ratios, and passenger behavior can also exert profound effects on particle deposition patterns inside vehicles (Gong et al., 2009). ...
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Field measurements of in-vehicle carbon dioxide (CO2), PM0.3, PM1.0, PM2.5, and PM10 mass concentrations were conducted along three main roadways in Dalian, China, during spring, summer, and winter. The temperature, relative humidity, and air pressure both inside and outside the vehicle were recorded simultaneously. A correlation analysis was used to evaluate the dominant factors influencing the CO2 and particle mass concentrations. Two semi-empirical pollutant models describing the in-vehicle CO2 and particle mass concentrations were established and validated using field data. The in-vehicle CO2 concentration exceeded the 1000 ppm limit during the majority of the period. Among the different cases, the averaged in-vehicle CO2 concentration under international air conditioning (AC) conditions was highest at 2977.9 ± 914.1–3866.7 ± 1035.9 ppm. In contrast, the in-vehicle PM2.5 mass concentration did not reveal significant variation among the different cases. These results, especially those of semi-empirical pollutant dispersion models, could predict in-vehicle pollutant exposure levels, providing useful guidance for optimized ventilation control in vehicles.
... The method of ventilating a vehicle passenger compartment has a significant effect on the levels of pollution experienced by the occupants as the use of air conditioning can effectively reduce exposure levels in most cases (Da-Lie et al., 2013). Ventilation rates, whether driven by fan, natural leakages or open windows determine the amount of outdoor air that is capable of entering the passenger cabin (Ott et al., 2008;Knibbs et al., 2009a). Chan et al. (2002a) found the average PM10 to be the highest in a non-air conditioned bus. ...
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This study identified and measured in-cabin passengers and pedestrians’ exposures to air pollutants along some selected roadways in Lagos city. This was with a view to fashioning out the control measures to mitigate exposures to those pollutants as well as determining the level of effectiveness of the control measures. Six roadways were chosen to represent the residential, commercial and industrial areas of Lagos city. Concentrations of Particulate matter (PM), Carbon monoxide (CO) and Volatile Organic Compounds (VOCs) were simultaneously measured on each of the pre-determined six roadways during the morning and afternoon commuting periods for people going by car, bus, Bus Rapid Transit (BRT) vehicles as well as for pedestrians adjacent to each of these roadways. None of these vehicles was air-conditioned. Particulate matter concentrations were measured using GT 331 Aerosol Mass Monitor from MET-One while concentrations of CO and VOCs were measured using portable ‘multiRAE’. The measurements were done two times per day, for two weeks spanning Monday to Saturday each week. The morning measurements were done between 07:00 and 10:00 a.m (designated as rush hours) while the afternoon measurements were done between 1:00 and 3:00 p.m (designated as non-rush hours). Measurements were taken at both roadway directions and each direction of movement lasted for a minimum of 30 minutes. The results showed the highest average CO and VOCs exposure levels in cars, followed by buses. Pedestrians were exposed to the lowest average concentrations of CO and VOCs. Pedestrians were found to be exposed to highest average PM10, PM7, PM2.5, PM1, and TSP concentrations, while commuters in cars, BRT and buses were exposed to respective decreasing concentrations of PM10 and PM7. Similarly, commuters in BRT, cars and buses were exposed to lowest concentrations of PM2.5, PM1 and TSP respectively. The result revealed that car commuters were consistently exposed to higher levels of CO and VOCs than commuters in any other modes of transportation. Though, pedestrians were exposed to lowest concentrations of CO and VOCs, they were exposed to higher concentrations of particulate matter. Students’ T-test revealed a statistically significant difference (p<0.05) in the exposure levels inside various modes of transportation especially for CO and VOCs, while rush hour and non-rush hour exposure levels were statistically similar (p<0.05). The research concluded that both commuters and pedestrians in Lagos city were exposed to pollutants concentrations that are below limits set by air quality regulatory bodies. To mitigate exposures of commuters and pedestrians to air pollutants, availability of good ventilation system in vehicles and the use of reliable and user-friendly mass transit system as against individually-owned cars should be encouraged. Other measures that can be adopted include provision of pedestrian facilities, avoidance of exhaust leakage, technological improvement in fuel combustion, presence of functional in-built air filter in vehicles and choice of route with less traffic congestion.
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COVID-19 have significant impact on travel behaviour and greenhouse gases (GHG), especially for the most affected city in India, Mumbai metropolitan region (MMR). The present study attempts to explore the risk on different modes of transportation and GHG emissions (based on change in travel behavior) during peak/non-peak hours in a day by an online/offline survey for commuters in Indian metropolitan cities like MMR, Delhi and Bengaluru. In MMR, the probability of infection in car estimated to be 0.88 and 0.29 during peak and non-peak hour, respectively, considering all windows open. The risk of infection in public transportation system such as in bus (0.307), train (0.521), and metro (0.26) observed to be lower than in private vehicles. Furthermore, impact of COVID-19 on GHG emissions have also been explored considering three scenarios. The GHG emissions have been estimated for base (3.83–16.87 tonne), lockdown (0.22–0.48 tonne) and unlocking (2.13–9.30 tonne) scenarios. It has been observed that emissions are highest during base scenario and lowest during lockdown situation. This study will be a breakthrough in understanding the impact of pandemic on environment and transportation. The study shall help transport planners and decision makers to operate public transport during pandemic like situation such that the modal share of public transportation is always highest. It shall also help in regulating the GHG emissions causing climate change.
The ubiquity of formaldehyde emitted in indoor and in-cabin environments can adversely affect health. This study proposes a novel full-range C-history method to rapidly, accurately and simultaneously determine the three key parameters (initial emittable concentration, partition coefficient, diffusion coefficient) that characterize the emission behaviors of formaldehyde from indoor building and vehicle cabin materials, by means of hybrid optimization. The key parameters of formaldehyde emissions from six building materials and five vehicle cabin materials at various temperatures, were determined. Independent experiments and sensitivity analysis verify the effectiveness and robustness of the method. We also demonstrate that the determined key parameters can be used for predicting multi-source emissions from different material combinations that are widely encountered in realistic indoor and in-cabin environments. Furthermore, based on a constructed vehicle cabin and the determined key parameters, we make a first attempt to estimate the human carcinogenic potential (HCP) of formaldehyde for taxi drivers and passengers at two temperatures (25 °C, 34 °C). The HCP for taxi drivers at both temperatures exceeds 10⁻⁶ cases, indicating relatively high potential risk. This study should be helpful for pre-evaluation of indoor and in-cabin air quality, and can assist designers in selecting appropriate materials to achieve effective source control.
The COVID-19 pandemic affected many areas of public life and industry. This also applies to research particularly that relies on scientific studies with test persons. In order to minimize the risk of infection, several aspects of experiment design including the setting might require alteration. An extensive review of the latest research involving the COVID-19 pandemic as a blueprint for dealing with other health situations has been conducted in order to develop a step-by-step approach to plan a study with regard to infection protection. As a result, a generic six-step concept was developed that is applicable for scientific studies in both stationary rooms and vehicles while being adaptable to the respective circumstances. The infection protection measures determined through research were implemented in the individual sub-steps from study planning to execution. They allow a step-by-step approach to prevent infections in scientific studies with different settings during a pandemic and in situations where increased hygiene measures are required.
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The modeling of the indoor concentration distribution produced by sources and sinks of pollutants is complicated by nonuniform mixing in a building or large room. Two common approaches to predicting the concentration distribution are to treat either the indoor volume as containing multiple microenvironments with uniform mixing within each, or to treat the entire volume as a single uniformly mixed compartment with an empirical mixing factor m that is introduced to correct for nonuniform mixing. We review the literature on the use of m and show that this empirical approach violates a basic principle of mass conservation. We propose a new conceptual model for the case of an episodic source of pollution in a building or room by defining the source operating conditions within three periods, tα, tβ, and tγ, where tα is the time while the source is emitting; tβ is the time after the source stops emitting, but while the concentration distribution is nonuniform in the building; and tγ is the time from the point where the indoor concentration becomes uniform until it becomes nondetectable above the background value. We define the state of uniform concentration as when the coefficient of variation of concentration (standard deviation/mean) throughout the volume becomes less than 0.1. We show that, with this definition, the assumption of uniform mixing for the entire volume may not lead to serious errors in predictions of exposures if tγ >> (tα + tβ).
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We measured exposures to ETS in a moving minivan under three different ventilation scenarios: drivers window open/ventilation off, windows closed/ventilation on, and windows closed/ventilation off. The driver smoked a single cigarette while we measured the concentration of ETS using laser aerosol monitors and the outside air exchange rate using a tracer gas decay technique. The indoor concentrations of respirable particulate matter increased during smoking by factors of 13 to 300 depending upon the ventilation configuration. The calculated exposure for a five hour automobile trip with the windows closed/ventilation off and with a smoking rate of 2 cigarettes per hour is 25 times higher than the same exposure scenario in a residence. Smoking low tar cigarettes or operation of air cleaners or ventilation equipment cannot reduce concentrations in automobiles to acceptable levels. The most effective solution to protecting passengers from ETS exposure is not to smoke in the automobile. INTRODUCTION Environmental tobacco smoke (ETS) contains thousands of compounds many of which are toxic and irritating and some of which are known carcinogens. These compounds include gas phase compounds such as carbon monoxide, formaldehyde and hydrogen cyanide. In addition, ETS contains airborne particulate matter (i.e. tar) that consists of fine liquid droplets of condensed organic matter that contain many toxic compounds including benzo(a)pyrene and other carcinogenic polycyclic aromatic compounds. The particulate phase compounds are in the respirable range (i.e. less than 3 µm mass medium diameter). Automobiles typically have some type of mechanical ventilation system. These ventilation systems provide an adjustable supply of air that can provide heating, or if air conditioning is installed, cooling. These ventilation systems can be set to provide outside air or recirculated air (i.e. called "economy mode" in some automobiles with air conditioning). Automotive ventilation systems typically do not have filters which can significantly reduce air contaminant concentrations from ETS. In automobiles exposures can be significant because of the very small indoor air mixing volume (i.e. less than a couple m 3). In this study we measured the exposure to ETS in a moving automobile under three different operation scenarios: drivers window open and ventilation off, windows closed and ventilation on, and windows closed and ventilation off. METHODS For each test the driver smoked a single low tar cigarette while driving a 1996 minivan on city streets. We measured the real time concentration of ETS in the rear seat at breathing height and in the outside air using laser aerosol monitors that were calibrated for the same brand tobacco smoke in an environmental chamber. We also simultaneously measured the outside air exchange rate in the automobile using a tracer gas decay technique.
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Carbon monoxide (CO) exposures were measured inside a motor vehicle during 88 standardized drives on a major urban arterial highway, El Camino Real (traffic volume of 30,500-45,000 vehicles per day), over a 13-1/2 month period. On each trip (lasting between 31 and 61 minutes), the test vehicle drove the same 5.9-mile segment of roadway in both directions, for a total of 11.8 miles, passing through 20 intersections with traffic lights (10 in each direction) in three California cities (Menlo Park, Palo Alto, and Los Altos). Earlier tests showed that the test vehicle was free of CO intrusion. For the 88 trips, the mean CO concentration was 9.8 ppm, with a standard deviation of 5.8 ppm. Of nine covariates that were examined to explain the variability in the mean CO exposures observed on the 88 trips (ambient CO at two fixed stations, atmospheric stability, seasonal trend function, time of day, average surrounding vehicle count, trip duration, proportion of time stopped at lights, and instrument type), a fairly strong seasonal trend was found. A model consisting of only a single measure of traffic volume and a seasonal trend component had substantial predictive power (R2 = 0.68); by contrast, the ambient CO levels, although partially correlated with average exposures, contributed comparatively little predictive power to the model. The CO exposures experienced while drivers waited at the red lights at an intersection ranged from 6.8 to 14.9 ppm and differed considerably from intersection to intersection.(ABSTRACT TRUNCATED AT 250 WORDS)
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The air exchange rates or air changes per hour (ACH) were measured under 4 conditions in 3 stationary automobiles. The ACH ranged between 1.0 and 3.0 h-1 with windows closed and no mechanical ventilation, between 1.8 and 3.7 h-1 for windows closed with fan set on recirculation, between 13.3 and 26.1 h-1 for window open with no mechanical ventilation, and between 36.2 and 47.5 h-1 for window closed with the fan set on fresh air. ACHs for windows closed with no ventilation were higher for the older automobile than for the newer automobiles. With the windows closed and fan turned off, ACH was not influenced by wind speed (p > 0.05). When the window was open, ACH appeared to be greatly affected by wind speed (R2 = 0.86). These measurements are relevant to understanding exposures inside automobiles to sources such as dry-cleaned clothes, cigarettes and airbags. Therefore, to understand the in-vehicle exposure to these internal sources, perchloroethylene (PCE) emitted from dry-cleaned clothes and environmental tobacco smoke (ETS) inside a vehicle were modeled for simulated driving cycles. Airbag deployment was also modeled for estimating exposure level to alkaline particulate and carbon monoxide (CO). Average exposure to PCE inside a vehicle for 30 minutes period was high (approximately 780 micrograms/m3); however, this is only 6% of the two-week exposure that is influenced by the storage of dry cleaned clothing at home. On the other hand, the exposure levels of respirable suspended particulate (RSP) and formaldehyde due to ETS could reach 2.1 mg/m3 and 0.11 ppm, respectively, when a person smokes inside a driving car even with the window open. In modeling the in-vehicle concentrations following airbag deployment, the average CO level over 20 minutes would not appear to present problem (less than 28 ppm). The peak concentration of respirable particulate would have exceeded 140 mg/m3. Since most of the particle mass is composed of alkaline material, these high levels might be expected to cause harmful effects on susceptible people, such as asthmatics. In all modeled cases, ACH would significantly affect build-up and dilution of pollutants originating from internal sources. Frequent stopping in congested urban traffic can greatly increase short-term exposures.
The protection offered occupants of stationary automobiles against airborne gases and respirable particles, such as might result from an accidental release, was measured and found to be substantial. For the four autos tested with the air conditioning (AC) system on and in recirculate position, the equilibrium ratios of inside/outside concentrations (I/O) for 2-μm diameter particles were less than 0.2, and some ratios were as small as 0.014. With both the AC compressor and the system fan off, the I/O for five autos ranged from 0.04 to 0.18. These low ratios are primarily a result of deposition within the autos. However, three of the five autos had substantially higher I/O ratios when the AC fan was on than when off, indicating that for some autos the AC caused significant added intake of outside air. Air exchange rates for the five stationary autos were on the order of 0.5h−1 with AC off, and 2.5 h−1 with AC on.
The project was carried out to determine the likely infiltration rate of a gas into a stationary motor vehicle for different wind speeds and directions. Measurements were first made on five vehicles under both positive and negative pressures to determine their leakage characteristics both with the vents open and with them closed. A tracer gas method was then used to determine the air change rates in the vehicles for different wind speeds and directions. Measurements on one vehicle enabled a constant to be evaluated which enabled infiltration rates to be found for other vehicles in terms of leakage characteristics and wind conditions. Predicted values of air change rates can be used to estimate the build-up of a contaminant infiltrating into a vehicle.In the second part of the project the scenario considered was that of a vehicle moving through a cloud of contaminant. Measurements of air change rates (ACH) were made on a vehicle driven at constant speeds of between 35 and 70 mph (15 and 32 m/s). Although the variation of ACH with speed was similar to that for the stationary vehicle in an airflow, a higher ACH was found for the moving vehicle than would be predicted for the stationary vehicle, using the leakage characteristics.
This project measured 2-hour integrated concentrations of PM10, PM2.5, metals and a number of organic chemicals including benzene and MTBE inside vehicles on California roadways. Using continuous samplers, particle counts, black carbon, and CO were also measured. In addition to measuring in-vehicle levels, the investigators measured pollutant levels just outside the vehicle, at roadside stations, and ambient air monitoring stations. Different driving scenarios were designed to assess the effects of a number of factors on in-vehicle pollutant levels. These factors included roadway type, carpool lanes, traffic conditions, geographical locations, vehicle type, and vehicle ventilation conditions. The statewide average in-vehicle concentrations of benzene, MTBE, and formaldehyde ranged from 3--22 {micro}g/m{sup 3}, 3--90 {micro}g/m{sup 3}, and 0---22 {micro}g/m{sup 3}, respectively. The ranges of mean PM10 and PM2.5 in-vehicle levels in Sacramento were 20--40 {micro}g/m{sup 3} and 6--22 {micro}g/m{sup 3}, respectively. In general, pollutant levels inside or just outside the vehicles were higher than those measured at the roadside stations or the ambient air stations. In-vehicle pollutant levels were consistently higher in Los Angeles than Sacramento. Pollutant levels measured inside vehicles traveling in a carpool lane were much lower than those in the right-hand, slower lanes. Under the study conditions, factors such as vehicle type and ventilation and little effect on in-vehicle pollutant levels. Other factors, such as roadway type, freeway congestion level, and time-of-day had some influence on in-vehicle pollution levels.
A mathematical multiple-smoker model for predicting the minute-by-minute indoor time series and time-averaged pollutant concentrations from environmental tobacco smoke (ETS) was developed and tested during 10 visits to glass-enclosed public smoking lounges at two international airports in the San Francisco Bay Area. The model is based on the mass balance equation and uses counts of active smokers as input. Its predictions were compared with the time series measurements of carbon monoxide (CO) and respirable suspended particles (RSP). The experimental time series for RSP was determined by averaging the readings (2-min averages) from moni tors at three widely-spaced locations in the lounge. At 8 out of the 10 visits, instantaneous CO concentrations also were measured every 2−3 min from a single monitor at the center of the room. The average emission rates per cigarette for CO and RSP for two visits in which the air exchange rates were measured were found to be 11.9 and 1.43 mg/min, respectively, which are consistent with values reported elsewhere in the literature. There was excellent agreement (0−12% error) between the observed RSP and CO concentration time series average and average concentrations predicted by the model for all study visits. Regression results between observed and predicted time series were also excellent. The average difference between the time-averaged RSP concentrations measured at the three widely spaced locations in the room and the average concentration across the room was about 12%. These results suggest that the model can be used by human exposure assessors and smoking lounge designers to predict the average exposures that people will experience for visits of typical duration.