Measuring Inside Vehicle Pollutants
(June 10, 1999)

This page updated July 20, 2005.


Final Report, ARB Contract No. 95-339

Supported by ARB Contract 95-339 and AQMD Contract 98055

Prepared By
Charles Rodes, Ph.D., Linda Sheldon, Ph.D., Don Whitaker,
Andy Clayton, Kelley Fitzgerald, and Jim Flanagan, Ph.D.
Research Triangle Institute
Research Triangle Park, NC 27709

Frank DiGenova
Sierra Research
Sacramento, CA 95814

Susanne Hering, PhD
Aerosol Dynamics
Berkeley, CA 94710

Cliff Frazier
Desert Research Institute
Reno, NV 89506

Prepared For

California Environmental Protection Agency
Air Resources Board
P. O. Box 2815
2020 L Street
Sacramento, CA 95812-2815

South Coast Air Quality Management District
21865 East Copley Drive
Diamond Bar, California 91765-4182


December 1998

BACKGROUND - In order to evaluate Californians’ total exposure to air pollutants, it is necessary to account for the important microenvironments where people spend the majority of their time. Pollutant concentration data are very limited for many microenvironments, including vehicle passenger compartments. This study was conducted to characterize the concentration levels of selected pollutants inside commuting vehicles in the Sacramento and Los Angeles areas in California. The researchers collected samples integrated over two hours for PM2.5 and PM10 mass, a number of particle-associated elements, and 13 VOCs, including methyl-tertiary-butyl-ether (MTBE), benzene and formaldehyde. In addition, continuous measurements were made for carbon monoxide (CO), black carbon, and particle count for different particle sizes, ranging from 0.15 to 2.5 mm. This is the first study to measure PM2.5 and PM10 concentrations inside vehicles. The use of continuous samplers for measuring both particle count and black carbon, while commuting, is also ground-breaking and innovative. 
The research was "range-finding" for a wide variety of commuter exposure scenarios, rather than an in-depth evaluation of a few situations. Study objectives included measuring the concentrations of selected pollutants inside and outside the vehicles to evaluate the influences of: 1) freeway conditions (rush versus non-rush), 2) roadway types (freeway, arterial and rural), 3) four vehicle types (2 sedans, a sport-utility vehicle and a California school bus), 4) two driver-adjusted vent settings, 5) the time of day (a.m. versus p.m.), and 6) the relationships among pollutant concentrations inside and outside the vehicles compared to roadside and the nearest ambient fixed site monitoring location. The results of this study can be used to define methodologies for assessing both commute-average and real-time in-vehicle concentrations, improve the estimates of current Californians’ in-vehicle pollutant exposures, assess the relative contributions of in-vehicle concentrations to total air exposure, suggest actions that drivers and passengers could take to reduce their in-vehicle exposures to air pollutants, and determine the need and feasibility of future in-vehicle studies. 
METHODS – In September and October of 1997, researchers collected a number of 2-hour pollutant concentration measurements inside vehicles during 13 "commutes" in Sacramento and 16 in Los Angeles. Similar measurements were made simultaneously outside the vehicles, along the roadways, and at the nearest ambient air monitoring stations. A variety of scenarios were studied based on variables such as roadway type, traffic congestion, ventilation setting, and vehicle type. Two runs, one in the morning and one in the afternoon, were typically conducted for each scenario. The study also included several in-vehicle special driving scenarios: 1) a California school bus following a student route in Sacramento, 2) comparison of a sedan traveling in an LA carpool lane versus one traveling in a congested right hand lane, and 3) a sedan encountering situations that would maximize the in-vehicle pollutant concentration levels. 
A driving protocol was followed that highlighted trailing behind heavy duty diesel (HDD) vehicles and diesel city buses when possible, to estimate their contributions to the measured pollutants. This focus on trailing specific polluting vehicles provided potentially "high end" estimates of the in-vehicle concentrations for particle count and black carbon.
Two-hour integrated samples for PM2.5 and PM10 were collected by MSP personal impactors on Teflon filters. The filters were weighed for particle mass and later analyzed for elemental concentrations by XRF. Except for formaldehyde, all the VOCs were collected by SUMMA evacuated canisters and were analyzed by GC/MS. Formaldehyde was collected by DNPH cartridges for subsequent HPLC analysis. Continuous CO monitoring was measured by Draeger monitors.
Real-time black carbon concentrations were measured with an Aethalometer, while particle counts were measured with
a LAS-X optical particle counter. The continuous data were reduced to both 1-minute and 120-minute "commute" averages.
RESULTS – Pollutant levels measured inside vehicles traveling in a carpool lane were much lower than those in the right-hand, slower lane. As expected, in-vehicle pollutant concentrations obtained from freeway rush drives were higher than those from freeway non-rush drives. Under the study conditions, factors such as vehicle type and vehicle ventilation settings were shown to have little effect on the in-vehicle pollutant levels. Other factors such as roadway type and time-of-day appeared to have some indirect influence on the in-vehicle pollutant levels. Elevated levels of both fine particles and black carbon were measured inside the test vehicle when it followed diesel-powered vehicles. Other pollutant measurement highlights included: (a) most pollutant levels, especially the VOCs, were elevated inside and outside the vehicles, relative to either the roadside or ambient station concentrations, (b) most pollutant levels were extremely low at the rural site near Sacramento, relative to any of the arterial or freeway locations, (c) most pollutant levels were somewhat higher in Los Angeles than in Sacramento, (d) particle concentrations were typically significantly higher outside the vehicles than inside, presumably due to losses in the vehicle ventilation systems (and other factors) - while significant differences were not observed between inside and outside levels of gas phase pollutants for the same vehicle, (e) in-vehicle pollutant concentrations for some individual commutes were substantially influenced by the tailpipe emissions from single polluting "target" lead vehicles, and (f) total in-vehicle LAS-X particle count / cm3 (0.15 to 2.5 mm) was a fair predictor of integrated PM2.5 mass concentration.
The mean ranges of selected in-vehicle pollutant concentrations (both integrated and continuous measures) by location are summarized as follows:




Los Angeles

Los Angeles

MTBE, g/m3

3 to 36

2 to 7

20 to 90

10 to 26

Benzene, g/m3

3 to 15

1 to 3

10 to 22

3 to 7

Toluene, g/m3

7 to 46

4 to 8

22 to 54

10 to 40

PM2.5 , g/m3

6 to 22

6 to 11

29 to 107

32 to 64

PM10 , g/m3

14 to 39

20 to 30

35 to 105

54 to 103

Formaldehyde, g/m3

5 to 14

2 to 4

< MQL to 22

< 7 to 19

CO, ppm

< MQL to 3


3 to 6


Black Carbon, g/m3

< MQL to 10


3 to 40


Total Particles, cm3

10 to 1,100


2,200 to 4,600


Table Notes: *Means of 2 to 4 Commutes; < MQL – Below Quantification Limit; NA – Not Available

The methodology highlights for this study included demonstrating that: (a) in-vehicle VOCs, PM2.5 and PM10 gravimetric mass concentrations could be successfully determined, even though the samples were integrated over very short two-hour periods, (b) real-time black carbon monitoring was feasible inside a commuting vehicle, (c) useable, integrated two-hour
in-vehicle samples for NO2 and PAHs could not be collected, (d) the relatively low levels of CO currently found in commuting California vehicles posed a substantial measurement problem for low-cost monitors with elevated MQLs, and (e) continuous monitoring of in-vehicle particle count (< 2.5 mm) and black carbon concentrations could readily be associated with emission of diesel-powered and poorly tuned gasoline-powered vehicles just ahead of the study vehicles. 
CONCLUSIONS – This study provided, for the first time, a variety of in-vehicle pollutant concentration levels for California vehicles. The study design also provided an indication of the potential influence of specific tested factors on in-vehicle concentration levels for selected pollutants. However, because the number of drives designed for testing a specific factor was typically small, some of the results should be confirmed by future studies with larger sample sizes and enhanced study designs. In addition, some of the possible confounding variables that may affect the results include: (a) the experimental driving protocol (trailing specific polluting target vehicles), (b) the high air exchange rate between the cabin and outside air during all the runs, (c) the local meteorology (e.g., wind speed), (d) the potential influence of emissions from the lead vehicle, and (e) the distance between the test vehicle and the lead vehicle. 
Other significant conclusions were: (a) the influence of individual polluting vehicles immediately in front of the test vehicles was substantial on in-vehicle levels, even for short periods, occasionally accounting for 30 to 50 % of the total in-vehicle commute concentrations, (b) the inside-to-outside ratio of particle mass for particles <2.5 mm ranged from 0.6 to 0.8, (c) concentrations inside a California school bus were very low in Sacramento, reflecting the generally low concentrations in the residential neighborhood, (d) LA  non-carpool lane commutes generally have substantially higher in-vehicle pollutant concentrations by 30 to 60 %, as compared to the carpool lanes (the use of which additionally reduced total commute air exposures by reducing total commuting time), (e) maximum concentration situations during commutes (e.g., closely trailing a diesel city bus in a downtown street canyon) could readily double the short-term in-vehicle concentrations for selected pollutants, and (f) roadside pollutant measurements were low by a factor of at least two for predicting in-vehicle levels for many commuting scenarios, but provided significantly better indications of in-vehicle pollutant concentrations than did ambient sites, which were often low by a factor of three or more (especially for VOCs).
Recommendations for future work include: a) conducting a more in-depth analysis of the extensive data bases developed in this study – especially for the real-time measurements, b) obtaining more representative commute data across different locations, seasons, traffic conditions, etc., c) improving the sampling equipment for real-time measurements of particles, d) developing suitable sampling methodologies for collecting measureable, short-term samples of NO2 and PAHs, e) further quantifying the advantages of carpool commuting relative to reducing pollutant exposures, f) further evaluating the relative importance of single lead vehicles on in-vehicle exposures, especially when following heavy duty diesel vehicles and older, gasoline powered vehicles, and g) developing relationships between trailing distance and in-vehicle concentrations. The robust database developed to meet study objectives undoubtedly contains a wealth of additional information that can be related to in-vehicle passenger exposures. Although the limited number of commutes conducted for each scenario cannot be construed as completely representative, the quality and consistency of the data strongly suggest that the proposed focused studies be considered.