DIESEL TRUCK IDLING EMISSIONS – MEASUREMENTS AT A 

PM2.5 HOT SPOT

Paper No. 07-2609

Authors: 

Corresponding Author:

Terry L. Miller

Department of Civil and Environmental Engineering, 73B Perkins Hall

The University of Tennessee, Knoxville, TN 37996-2010

(phone 865-974-7731, fax 865-974-2669, email tmiller3@utk.edu)

Joshua S. Fu

Department of Civil and Environmental Engineering, 59 Perkins Hall

The University of Tennessee, Knoxville, TN 37996-2010 

(phone 865-974-2629, fax 865-974-2669, email jsfu@utk.edu)

Boris Hromis 

Department of Civil and Environmental Engineering, 70 Perkins Hall

The University of Tennessee, Knoxville, TN 37996-2010 

(phone 865-974-4785, fax 865-974-2669, email bhromis@utk.edu)

John M. Storey

Oak Ridge National Laboratory

Bldg NTRC, MS 6472

P.O. Box 2008

Oak Ridge, TN 37831-6472 

(phone 865-946-1232, fax 865-946-1248, email storeyjm@ornl.gov)

James E. Parks

Oak Ridge National Laboratory

Bldg NTRC, MS 6472

P.O. Box 2008

Oak Ridge, TN 37831-6472 

(phone 865-946-1283, fax 865-946-1248, email parksjeii@ornl.gov)

DATE SUBMITTED: AUGUST 1, 2006. REVISED: NOVEMBER 15, 2006.

Word Count: 5462 words text + 14 Figures/Tables = Total 8962 Equiv Words

TRB Paper No. 07-2609.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
DIESEL TRUCK IDLING EMISSIONS - MEASUREMENTS AT A PM2.5 HOT 

SPOT

Authors: Terry Miller, Josh Fu and Boris Hromis, University of Tennessee; John Storey 

and James Parks, Oak Ridge National Laboratory.

ABSTRACT

The University of Tennessee and Oak Ridge National Laboratory conducted a 5-month 

long air monitoring study at the Watt Road interchange on I-40 in Knoxville Tennessee 

where there are 20,000 heavy-duty trucks per day traveling the interstate. In addition, 

there are 3 large truck stops (also called travel centers) at this interchange where as many 

as 400 trucks idle engines at night. As a result, high levels of PM2.5 were measured near 

the interchange often exceeding National Ambient Air Quality Standards. This paper 

presents the results of the air monitoring study illustrating the hourly, day-of-week, and

seasonal patterns of PM2.5 resulting from diesel truck emissions on the interstate and at 

the truck stops. Most of the PM2.5 concentrations occurred during the night when the 

largest contribution of emissions was from idling trucks rather than trucks on the 

interstate. A nearby background air monitoring site was used to identify the contribution 

of regional PM2.5 emissions which also contribute significantly to the concentrations 

measured at the site. The relative contributions of regional background, local truck idling 

and trucks on the interstate to local PM2.5 concentrations are presented and discussed in 

the paper. The results indicate the potential significance of diesel truck idling emissions 

to the occurrence of hot-spots of high PM2.5 concentrations near large truck stops, ports 

or border crossings.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
DIESEL TRUCK IDLING EMISSIONS - MEASUREMENTS AT A PM2.5 HOT 

SPOT

Authors: Terry Miller, Josh Fu and Boris Hromis, University of Tennessee; John Storey 

and James Parks, Oak Ridge National Laboratory.

ABSTRACT

The University of Tennessee and Oak Ridge National Laboratory conducted a 5-month 

long air monitoring study at the Watt Road interchange on I-40 in Knoxville Tennessee 

where there are 20,000 heavy-duty trucks per day traveling the interstate. In addition, 

there are 3 large truck stops at this interchange where as many as 400 trucks idle engines 

at night. As a result, high levels of PM2.5 were measured near the interchange often 

exceeding National Ambient Air Quality Standards. This paper presents the results of 

the air monitoring study illustrating the hourly, day-of-week, and seasonal patterns of 

PM2.5 resulting from diesel truck emissions on the interstate and at the truck stops. 

Surprisingly, most of the PM2.5 concentrations occurred during the night when the largest 

contribution of emissions was from idling trucks rather than trucks on the interstate. A 

nearby background air monitoring site was used to identify the contribution of regional 

PM2.5 emissions which also contribute significantly to the concentrations measured at the 

site. The relative contributions of regional background, local truck idling and trucks on 

the interstate to local PM2.5 concentrations are presented and discussed in the paper. The 

results indicate the potential significance of diesel truck idling emissions to the 

occurrence of hot-spots of high PM2.5 concentrations near large truck stops, ports or 

border crossings. The significance of truck idling emissions are similar to the findings of 

other studies (1-8).

INTRODUCTION

Ambient monitors were installed at two locations to continuously measure ambient 

concentrations particulate matter PM1.0, PM2.5 and PM10. These locations were named the 

Ramp Site and the Ridgetop Site. Both sites were located at the interchange of I-40 and 

Watt Road in Knoxville Tennessee. The Ramp Site was located 100 feet south of the 

eastbound interstate shoulder and 100 feet north of the eastbound off-ramp within the 

highway right-of-way. The Ridgetop Site was located southeast of the interchange on top 

of Black Oak Ridge, 300 feet higher than the Ramp Site elevation. The intended purpose 

of the site locations was that the Ramp Site would measure the highest concentrations due 

to vehicle emissions on the interstate and nearby travel centers, while the Ridgetop Site 

would measure background concentrations in the general area. Monitoring was 

conducted continuously from January through June of 2005 at both sites. Figure 1 shows 

the locations of both sites on an aerial photograph of the area. The two sites are 3300 feet 

apart. 

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Figure 1. Site map at I-40 and Watt Road showing locations of monitoring sites, the 

interstate and nearby truck travel centers. Scale: Monitoring sites are 3300 ft apart.

INSTRUMENTATION

Continuous monitoring instruments were installed in portable trailers at each site and 

connected to standard electrical power. Each trailer was equipped with air heaters and air 

conditioners to maintain a constant 72-degree temperature for stable operation of the 

instrumentation. Air samples were drawn from sampling probes on the trailer roofs at a 

height of 4 meters above the ground. PM samplers utilized particle size separation 

impactors to control the size of particles being sampled. PM2.5 and PM1.0 were measured 

using TEOMs (Tapered Element Oscillating Microbalance) at the Ramp Site. PM10 and 

PM2.5 were also measured using E-BAM beta gage instruments at the Ramp Site. PM10 

was measured using an E-BAM beta gage instruments at the Ridgetop Site, while PM2.5

was measured using a TEOM. Each site was also equipped with continuously monitoring 

meteorological packages measuring one-hour average wind speed, wind direction, 

standard deviation of wind direction, solar intensity, temperature, humidity, and rainfall. 

The wind sensors were located at the top of 10-meter high towers at each site. All data 

were recorded on digital data loggers and downloaded to PCs in a standard spreadsheet 

format.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
TRAFFIC DATA COLLECTION METHODS

Traffic data were collected using a combination of manual observation counts, pneumatic 

road tube traffic counters, and side-fired radar traffic counters. Road tube counters were 

used to obtain hourly vehicle counts on the eastbound and westbound off-ramps of the 

interstate at Watt Road. Manual counts were used to estimate the percent of tractortrailer trucks exiting the interstate at the road tube locations, to estimate vehicle traffic 

and truck volumes on the Watt Road overpass, to count idling trucks at the travel centers, 

and to check the accuracy of the RTMS automatic traffic counters. EIS (Electronic 

Integrated Systems, Inc of Toronto Canada) RTMSTM vehicle detection sensors were 

utilized to measure hourly vehicle counts, long truck counts, and vehicle average speeds 

on the I-40. The RTMS provides 5-minute counts of total vehicles, average vehicle 

speeds and long truck counts 24 hours per day for each of 6 traffic lanes (3 eastbound and 

3 westbound). Long trucks are defined as those more than 2.5 times longer than the 

average vehicle. This primarily provides a count of tractor-trailer rigs, but not single unit 

trucks or cabs without trailers. 

AVERAGE DAILY TRAFFIC RESULTS 

Data were collected using the RTMS units covering the period from 2/7/05 to 6/30/05. 

Traffic volume, truck volume and vehicle speeds were monitored every hour for the 20-

week period. 

The average vehicle count was 90,498 vehicles per day on I-40 just east of Watt Rd. The 

average daily long truck count was 17,361 trucks/day. The average percentage of trucks 

of all vehicles was 19.2%. While there were reproducible patterns of traffic variation by 

day-of-week and by hour-of-day, there was no appreciable seasonal change in traffic 

volumes over the 20-week period (i.e. January through June 2005). 

The RTMS units also measure average vehicle speeds. Daily average vehicle speed 

measured over the 20-week period was 63 mph. Most hourly average speeds ranged 

from 60 to 70 mph with dips to 50 mph during peak hour traffic conditions. During the 

highest congestion conditions speeds sometimes dropped to 10 to 20 mph for very short 

periods. This section of interstate has 6 lanes of traffic which is more than enough to 

accommodate the traffic volumes using the facility most of the time. As a result, vehicle 

speeds stayed in the 60 to 70 mph range most of the time except during traffic incidents.

DAILY TRENDS IN VEHICLE TRAFFIC

Figure 2 shows the variation of daily traffic volume by day of the week. As shown in the 

figure, Fridays have the highest total vehicle traffic volume with more than 100,000 

vehicles per day. Wednesdays and Thursdays generally were the highest truck traffic 

days averaging almost 20,000 long trucks/day. Saturdays and Sundays showed the 

lowest traffic volumes of any day of the week averaging 82,275 vehicles/day and 14,627 

trucks/day. Total daily traffic volume was pretty well balanced equally between 

eastbound and westbound vehicles. 

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
HOURLY TRENDS IN VEHICLE TRAFFIC

Hourly trends in traffic were clearly different on weekdays versus weekends. Figure 3 

shows the hourly variation of traffic on I-40 at Watt Rd measured on Sundays, 

Wednesdays, and Fridays during the 20-week period. On weekdays total vehicle traffic 

shows the “classic” morning and afternoon rush-hour peaks. The city of Knoxville is to 

the east, so this traffic reflects the morning and afternoon peaks due to the commute from 

home to work and back. On weekends the traffic volume slowly rises during the early 

morning, peaking during the early afternoon. Figure 3 shows total vehicle traffic as the 

fraction of the average daily traffic (ADT) that occurs each hour. Peak hour traffic 

volumes usually reach 6 to 7 percent of the ADT peaking in the late afternoon. Minimum 

traffic volumes occur in the early morning hours around 5 am with hourly traffic only 1 

to 2 percent of the ADT.

Figure 2 Daily Traffic Volume by Day of the Week 

0

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60000

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Tuesday

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Saturday

Sunday

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Vehicles per Day

Total Trucks

Total Vehicles

Figure 3. Hourly Vehicle Traffic as a Fraction of Daily Vehicle ADT on I-40 at 

Watt Rd for Sundays, Wednesdays, and Fridays (20-week avg)

0.000

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Wednesdays

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Hourly variations in truck traffic follow a different pattern as illustrated in Figure 4. 

There is no morning peak during weekdays or weekends. The truck traffic slowly 

increases from a low at 5 am and does not peak until 6 or 7 pm. The hourly peak rate is 

5.5 to 6 percent of the daily truck volume. At night, the truck volume drops off to 2 

percent or less of daily truck volume per hour between 2 am to 6 am. 

On weekends the hourly trends of truck traffic is pretty similar to the trends in the rest of 

the traffic as shown in Figure 4 for Sundays. Traffic volume is lowest at 5 am, then 

gradually increases and does not peak until late afternoon with the highest hourly traffic 

equal to about 6.5 percent of the daily traffic. Figure 5 shows the fraction of trucks by 

hour of day. Truck fractions peak around 33% of total traffic during the late night and 

early morning hours (11 pm to 3 am) on weekdays and fall to 15% during midday. 

Figure 4. Hourly Truck Traffic as a Fraction of Daily Truck ADT on I-40 at Watt 

Rd for Sundays, Wednesdays, and Fridays (20-week avg)

0.000

0.010

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0.030

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0.070

0 5 10 15 20 25

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Fraction of Truck ADT

Sundays

Fridays

Wednesdays

Figure 5. Hourly Average Truck Fractions on I-40 at Watt Rd for Sundays, 

Wednesdays, and Fridays (20-week avg)

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Truck Fraction

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Wednesdays

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
IDLING TRUCKS AT TRAVEL CENTERS

Trucks idle at the travel centers while waiting to refuel, while truck drivers eat meals, and 

during hoteling when drivers sleep or rest. There are a total of approximately 700 truck 

parking spaces at the 3 travel centers and along the interstate ramps where trucks 

sometimes park. The largest travel center is the Petro facility on the southeast side of the 

interchange. This facility has 270 truck parking spaces. During previous studies (1) the 

number of idling trucks was counted at the Petro facility at various times of the day. 

Figure 6 shows the results of 8-days of idling truck counts performed during December 

2004. As shown in Figure 6, the highest number of idling trucks was 150 to 200 

observed during the late night hours from 10 pm to 7 am. During the day, most truck 

drivers leave the site reducing the number of idling vehicles to less than 50 during 

midday. The number of idling trucks measured during a previous 8-month study showed

a similar pattern (1). Trucks also idle at the Travel America and Flying J travel centers. 

On a typical night, there are often more than 400 trucks idling at the three travel centers. 

This value will drop to 100 or less during midday. 

PARTICULATE MATTER AIR MONITORING RESULTS

The results of PM monitoring are illustrated in the four graphs shown in Figures 7 - 10. 

Figure 7 shows the seasonal variability of results over the 20-week study. The most 

complete data set for the 20-weeks was the PM10 results. Shown in Figure 7 are the 

hourly and 24-hour average PM10 concentrations measured at the RAMP Site. Lots of 

variability was observed in the 1-hour average concentrations ranging from near zero to 

more than 150 ug/m3 (micrograms per cubic meter). While some of the highest 

concentrations were measured during winter (February) and summer (June) months, there 

was no clearly identifiable seasonal trend in PM10 concentrations.

Figure 6. Number of Idling Trucks by Time of Day at the 

Petro Truck Stop During 8 Days of Testing - Dec 15-22, 2004

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150

200

250

0 5 10 15 20 25

Time of Day (Hour)

Number of Trucks

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Figure 7. Hourly and 24-hour average PM10 Concentrations at the RAMP Site.

Figure 8 shows the weekly trend in average hourly concentrations of PM2.5 by day of the 

week. Wednesday showed the highest concentrations while Saturday showed the lowest 

concentrations, consistent with Wednesday being one of the highest truck traffic days and 

Saturday being the lowest truck traffic day. A definite pattern of high PM2.5 levels at 

night and lower levels during the afternoon was measured for every day of the week.

Average Weekly Profile

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30

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00

ug/m3

Ramp TEOM PM2.5

Mon Tue Wed Thur Fri Sat Sun

Figure 8. Average Weekly Profile of 1-Hour Average PM2.5 Concentrations at the 

RAMP Site.

PM10 Ramp

0

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1/25/05 2/14/05 3/6/05 3/26/05 4/15/05 5/5/05 5/25/05 6/14/05 7/4/05 7/24/05

Date

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1-hr Avg. Ramp(EBAM)

PM10

24-hr Avg. Ramp(EBAM)

PM10

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Figure 9 shows the daily trend of hourly PM2.5 concentrations measured for the entire 20-

week period. The highest concentrations were measured at night, while the lowest 

concentrations were measured in the afternoon. This is consistent with the higher PM 

emissions from idling trucks at night compared to the lower idling truck emissions during 

the afternoon. A significant portion of the PM2.5 concentrations shown in Figure 9 is due 

to background concentrations and not due to nearby emissions from trucks. The average 

measured concentrations at the Ridgetop Site were used to estimate background levels. 

These concentrations were subtracted from the concentrations measured at the Ramp Site 

to yield “Delta PM2.5 concentrations” as an estimate of the PM2.5 concentrations 

attributable to nearby emissions from trucks on the interstate and idling at the travel 

centers. The average hourly Delta PM2.5 concentrations measured at the Ramp Site are 

shown in Figure 10. Figure 10 shows peak hourly concentrations near 8 ug/m3 from 7-9 

am when many trucks exit the travel centers. Average hourly concentrations fell to less 

than 2 ug/m3 during late afternoon (4 – 7 pm) when truck occupancy at the travel centers 

was low, but truck traffic on the interstate was high. Delta PM2.5 concentrations show 

higher hourly variation than total PM2.5 concentrations that include background. 

Average Daily Profile

0

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02468 10 12 14 16 18 20 22

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ug/m3

RampTEOM PM2.5 (ug/m3)

Figure 9. Daily Profile of 1-Hour PM2.5 Concentrations (20-week average) at the 

Ramp Site.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Figure 10. Daily Profile of 1-Hour Delta PM2.5 Concentrations (without 

background) at the Ramp Site.

METEOROLOGY

Wind direction patterns were complex at the study site with different patterns observed at 

the two measurement sites. The Ridgetop Site showed winds from all directions except 

the southeast. The prevailing wind direction measured at the Ridgetop Site was from the 

northwest. Wind directions measured at the Ramp Site on the valley floor showed the 

wind to be channeled in a predominantly northeast/southwest alignment just like the 

valley floor. The prevailing direction during the night was out of the northeast (more 

than 25% of the time). The prevailing direction during the day was out of the southwest 

to west. Very little winds blew from out of the southeast or the northwest (night or day) 

as measured at the Ramp Site. Wind speeds during the day tended to be higher than at 

night as illustrated in the graph in Figure 11 showing average hourly wind speeds for 20 

weeks during the study. In Figure 11 hourly wind speeds have been multiplied times 5 so 

it could be plotted on the same graph showing hourly average PM2.5 concentrations in 

ug/m3. Higher wind speeds during the day provide more air to dilute air pollutants 

generally causing lower concentrations during the day and higher concentrations at night. 

This inverse relationship between wind speed and air pollution concentration is illustrated 

in Figure 11 which shows the hourly average PM2.5 concentrations and the average wind 

speeds observed over the 20-week study. Clearly the highest PM2.5 concentrations occur 

when wind speeds are low and the lowest PM2.5 concentrations occur when wind speeds 

are higher.

Average Hourly Delta PM2.5 Concentrations

0.0

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ug/m3

PM2.5

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Figure 11. Three graphs showing Delta PM2.5 Concentrations, Wind Speeds, 

Emissions and Emissions Divided by Wind Speed.

Delta PM2.5 Concentrations and Wind Speed

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Speed

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PM2.5 ug/m3

5x Emission/wind speed

(kg-s/m-hr)

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Also shown in Figure 11 is a curve of estimated PM2.5 emissions in the area. PM2.5

emissions have been multiplied times 5 so the results can be plotted using the same y-axis 

scale as used for PM2.5 concentrations in ug/m3. Idling trucks emit more PM2.5 than 

trucks on the interstate especially during the night. As a result, the emission profile 

shows higher PM2.5 emissions during the night than during the day with the highest value 

at 6 am and the lowest at 4 pm. 

To illustrate the combined effect of PM2.5 emissions and wind speeds, the PM2.5 emission 

rates were divided by the wind speed and plotted on the same graph as the average hourly 

PM2.5 concentration. The results are shown in Figure 11. The graph of PM2.5 emissions 

adjusted for wind speed follows a very similar pattern as the observed PM2.5

concentrations for this 20-week period. This indicates that PM2.5 concentrations 

measured at the Ramp Site are strongly influenced by PM2.5 emissions from diesel trucks 

and wind speeds. Other factors may also be significant such as atmospheric stability and 

wind direction, but over a 20-week period, emissions and wind speeds appear to be 

dominant factors influencing PM2.5 concentrations. 

EMISSION FACTORS

Hourly estimates of emissions as shown in Figure 11 were calculated using the USEPA 

MOBILE emission factor model. Emission estimates were developed for moving 

vehicles on the interstate and idling trucks in the travel centers. USEPA has developed 

the MOBILE emissions model (2) for the purpose of estimating air pollution emission 

factors for cars and trucks operating on highways and streets. The model accounts for 

emissions as a function of vehicle type, and calendar year. PM emission factors do not 

vary by speed in MOBILE6.2. The emission factors were calculated for the national 

average vehicle type and age mix for calendar year 2005. Emission factors were 

calculated for heavy-duty diesel trucks class HDDV8b which is the heaviest diesel 

vehicle class (>60,000 lbs gross vehicle weight rating) in the MOBILE model and typical 

of the 18-wheeler tractor-trailer trucks that were counted as “long vehicles” by the traffic 

counters used for this study. The PM2.5 emission factor for HHDV8b trucks traveling on 

the interstate was 0.38 g/mile. The composite PM2.5 emission factor for all other vehicles 

traveling on the interstate was 0.027 g/mile. Even though HDDV8b vehicles averaged 

only 22% of the vehicles on the interstate, the PM2.5 emissions were 80% attributable to 

HDDV8b trucks and 20% attributable to all other vehicles on the interstate. 

The MOBILE model does not predict idling truck emissions. USEPA has however 

published recommended emission factors for idling diesel trucks for use in developing 

State Emission Inventories and Implementation Plans (3). The emission factor used in 

this study for idling trucks at the travel centers was 3.68 grams/hour of PM2.5. 

INTERSTATE EMISSIONS

Hourly traffic counts on I-40 of all vehicles and trucks (long vehicles) were used to 

estimate hourly emissions of PM2.5 from the interstate. The hourly truck count was 

multiplied times 0.38 g/mile to yield an hourly emission rate in grams/hour. This 

emission estimate applied to traffic operating over a 1.0-mile segment of I-40 (i.e. within

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
± 0.5 miles of the Ramp Site). The emissions of these pollutants were then estimated for 

every hour of the study when traffic data were available. 

IDLING TRUCK EMISSIONS

Estimates of emissions from idling trucks were based on the idling truck emission factor 

(3.68 g/hour) and counts of idling trucks by hour of the day at the Petro Travel Center. 

The Petro Travel Center was the largest of the three travel centers at Watt Rd where 

diesel trucks were parked while drivers rested. The Petro Travel Center had 268 truck 

parking spaces, and the other two travel centers had approximately 432 truck parking 

spaces for a total of 700 spaces at all three travel centers combined. Manual counts of the 

number of trucks parked and trucks idling at the Petro Travel Center during a previous 

study (1) were used to estimate the number of idling trucks each hour of the day at all 

travel centers combined. On weekdays, truck use at the Petro Travel Center was the 

highest. All available spaces were usually in use by midnight each night and continued to 

be used until 6 am when trucks began to leave. The number of idling trucks at night was 

often 2/3 of the total with up to 180 idling trucks per night (See Figure 6). Trucks 

continued to leave the travel center during the morning up until about noon when the 

number of idling trucks was typically 50 or less. By late afternoon the number of trucks 

parked at the Petro Travel Center would usually begin to increase for the rest of the day 

and early evening until the site was full of trucks again at midnight. The number of 

idling trucks at all three travel centers was estimated by multiplying the ratio of the 

number of parking spaces at all three travel centers (700) to the number of parking spaces 

at the Petro Center. On Wednesday nights, following the highest truck travel day, the 

total number of idling trucks at all three travel centers was estimated at 468. 

Truck parking and idling at the travel centers are usually less on weekends than on 

weekdays, but detailed counts of the number of parked and idling trucks were not 

available during the entire study period. Truck traffic counts on I-40 also showed that 

truck volumes were less on weekends than during the week. A model was developed so 

that hourly estimates of the number of trucks idling at the travel centers could be 

estimated for every hour of the study based on the interstate truck counts that were 

available for the entire study. It was found that the number of idling trucks at the three 

travel centers could be reasonably estimated based on 40% of the truck hourly count on I40 for the same day, but with an 11-hour lag time. Figure 12 shows the results of this 

model compared to the estimated number of idling trucks based on manual counts at the 

Petro Travel Center adjusted for the additional parking spaces at the two other travel 

centers. The 11-hour lag time was selected by “trial and error” after trying other lag 

times. The 11-hour lag time fit the observed truck counts fairly closely as can be seen in 

the Figure 12.

Using the model, the highest number of idling trucks was predicted to occur during the 

late night-time period between midnight and 6 am, and the lowest number of idling trucks 

were predicted to occur between noon and 5 pm. This is consistent with observations.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
Emissions of idling trucks for each hour of the study was estimated based on the number 

of idling trucks occurring each hour times the idling emission factor.

Figure 12. Predicted Hourly Idling Trucks Compared to Counted Values.

EMISSIONS FROM INTERSTATE TRAFFIC VERSUS IDLING TRUCKS

Emission estimates from trucks on the interstate and idling trucks were combined to 

determine the trend of emissions for all sources in the study area (i.e. within 0.5 miles of 

the Ramp Monitoring Site). Emissions of PM2.5 from light-duty vehicles were not 

considered because their emission factors are more than 100 times lower than for heavy 

diesel trucks. Figure 13 illustrates the relative contribution of idling diesel trucks versus 

all trucks on the interstate. The graph shows the emissions attributable to idling trucks, 

trucks on the interstate, and the total emissions by hour of the day for the entire 20-week 

period of the study. As illustrated in Figure 13, the relative contribution of emissions 

from trucks on the interstate are highest during the afternoon when these vehicles 

contribute nearly 50% of the PM2.5. In contrast, idling trucks account for a large 

percentage of emissions at night, contributing up to 90% of PM2.5 emissions. The 

average contribution over a 24-hour day is 80% due to idling and 20% due to trucks on 

the interstate.

Figure 13. Average Hourly Emissions of PM2.5 from Trucks. 

Hourly Average PM2.5 Emissions from Trucks 

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Idling

Predicting Idling Trucks at 3 Travel Centers Combined Using 40% of Hourly 

Interstate Truck Volume and an 11-hour Lag Time and Wednesday Data 

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TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
SUMMARY OF AIR MONITORING RESULTS

Table 1 presents a summary of the results of 5-months of continuous air monitoring near 

a six-lane interstate with approximately 100,000 vehicles per day including 20,000 

heavy-duty diesel trucks, and near three truck travel centers with 700 parking spaces 

where up to 400 diesel trucks idle engines at night. The table shows the average 

concentrations of PM measured at the Ramp and Ridge-top Sites for the duration of the 

study (typically 5-months), and for selected averaging times. Only PM2.5 concentrations 

showed the potential for exceeding NAAQS (National Ambient Air Quality Standards) 

and then only at the Ramp Site located in the interstate interchange within the highway 

right-of-way. 

 Table 1. Summary of Continuous Air Monitoring Results

The Ramp Site monitoring location should represent a “worst case” scenario for air 

quality impacts for emissions from the interstate because measurements were made 

within the highway right-of-way and concentrations outside the highway right-of-way 

should be lower due to atmospheric dispersion as distance from the road increases. 

The column labeled “Delta Conc” in Table 1 is the difference between the concentrations 

measured at the Ramp Site and the background Ridgetop Site. PM concentrations 

measured at the background site were consistent with PM measured at other area 

monitoring stations where PM is attributable largely to regional sources of all types. The 

“Delta Conc” represents an estimate of the concentrations attributable to vehicle 

emissions in the near vicinity of the Ramp Site. This estimate is probably lower than the 

actual value, in that the background site was not perfect and sometimes was impacted by 

local emissions. As a result the background concentration may be overestimated and the 

“Delta Conc” underestimated. The “Delta Conc” values are all below the NAAQS.

Pollutant Avg

Time

Ramp

Site

(ug/m3)

Ridgetop

Site

(ug/m3)

Delta

Conc

(ug/m3)

NAAQS

(ug/m3)

PM1.0 5-mo 14.6 NA NA NA

PM2.5

TEOM

5-mo 17.6 12.8 4.8 15

1-yr avg

PM2.5

TEOM

24-hr

max

47.6 35.3 13.0 65

PM2.5

EBAM

5-mo 16.2 NA NA 15

1-yr avg

PM2.5

EBAM

24-hr

max

49.0 NA NA 65

PM10 5-mo 29.7 22.9 6.8 50

1-yr avg

PM10 24-hr

max

99 75 24 150

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
USEPA’S PROPOSED 24-HOUR AVERAGE PM2.5 NAAQS

USEPA has recently proposed to lower the National Ambient Air Quality Standard for 

PM2.5 to 35 ug/m3. The air monitoring performed during this study showed potential 

exceedances of the annual NAAQS for PM2.5, but did not show any 24-hour average 

concentrations exceeding the existing PM2.5 NAAQS of 65 ug/m3. The monitoring 

results at the Ramp Site did, however, show several exceedances of USEPA’s proposed 

new standard. Table 2 shows the measured concentrations of PM on eight days during 

the study when PM2.5 levels exceeded 35 ug/m3. 

Table 2. Highest Measured 24-Hour Average PM Concentrations at the Ramp Site. 

Concentrations at the Ramp Site exceeded 35 ug/m3 eight times over a 5-month period. 

This is equivalent to exceeding the proposed NAAQS five percent of the time. The 

existing NAAQS allows 24-hour concentrations to be exceeded no more than two percent 

of the time. If the proposed standard also uses the 98th-percentile concentration as the 

basis for comparison to the NAAQS, then the PM2.5 levels at this site are likely to exceed 

both the annual and the 24-hour average NAAQS. This indicates that idling truck 

facilities like the ones near the Ramp monitoring site are potential hotspots with respect 

to both the annual and the 24-hour average NAAQS for PM2.5.

CONCLUSIONS

Most of the PM2.5 concentrations measured during this study were attributable to idling 

emissions from diesel trucks in the travel centers. Based on estimates of vehicle 

emissions within ± 0.5 miles of the monitoring site, 80% of the PM2.5 concentrations 

Ramp Ramp Ramp Ridgetop Delta Ridgetop

PM2.5 PM2.5 PM2.5 PM2.5 PM2.5 PM10

TEOM EBAM Average

(ug/m3) (ug/m3) (ug/m3) (ug/m3) (ug/m3) (ug/m3)

Day

19-Apr 36.9 36.9 30.5 6.4 39.5

13-May 35.2 35.2 28.2 7.0 40.2

19-May 36 36.9 36.5 31.9 4.6 45.4

22-Jun 41 41.0 34.5 6.5 49.1

23-Jun 47.6 48.9 48.3 35.3 13.0 50.3

24-Jun 41.6 39.3 40.5 29.4 11.1 41.9

25-Jun 43.8 43.1 43.5 32.4 11.1 46.2

26-Jun 38.3 41 39.7 31.2 8.5 44.4

Average 40.2 31.7 8.5 44.6

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
measured were attributable to idling trucks, while 20% of the PM2.5 concentrations were 

attributable to vehicle emissions on the interstate. 

With respect to PM2.5 air quality “hot spots” the greater concern should be the impact of 

large travel centers with hundreds of idling diesel trucks, rather than emissions of diesel 

trucks traveling free-flowing interstates. In this study the average PM2.5 concentration at 

the Ramp Site attributable to idling trucks was 3.8 ug/m3, while the concentration 

attributable to exhaust emissions from vehicles on the interstate was only 1.0 ug/m3. 

This is based on a Delta PM2.5 of 4.8 with 80% of emissions from idling trucks and 20% 

from vehicles on the interstate as illustrated in Figure 13. These estimates are based on 5 

months of data, but should reasonably approximate an annual mean for comparison to the 

NAAQS. (Note: Traffic incidents and/or congestion due to construction might cause a 

short-term PM problem.)

Other interesting results are shown in Table 1. PM1.0 concentrations at the Ramp Site 

averaged 14.6 ug/m3, while PM2.5 averaged 17.6 ug/m3. This indicates that particles less 

than 1.0-micrometer diameter make up 83% of the measured PM2.5. This is consistent 

with the knowledge that diesel exhaust emissions are very small particles and much, if 

not all, of the PM2.5 measured at the Ramp Site was due to diesel exhaust emissions. 

PM10 concentrations measured at the Ramp Site averaged 29.7 ug/m3 which was 6.8 

ug/m3 higher than measured at the Ridgetop Site. This indicates that vehicle emissions 

contributed at least 6.8 ug/m3 to average PM10 levels at the Ramp Site. Five-month 

average PM10 concentrations were 70% and 80% higher than PM2.5 concentrations 

measured at the Ramp and Ridge-top Sites, respectively. In both cases, the PM10

concentrations were well below NAAQS and should not be a significant “hot-spot” 

problem.

The results of this study support the theory that diesel truck idling at travel centers 

represents a potential “hotspot” for PM2.5 air pollution concentrations. Hotspots are not 

well defined, but are generally thought to be localized areas where air pollution levels are 

significantly elevated above background concentrations. The California Air Resources 

Board (CARB) has identified truck idling as a cause of “hotspots” stating: “Idling 

emissions are particularly significant at idling “hotspots” such as truck stops, travel 

centers, and rest areas where truck drivers stop to rest for long hours” (5). 

The lateral extent of these “hotspots” depends on the magnitude of the emissions 

occurring within a small area and meteorological conditions. Large numbers of idling 

diesel trucks, parked closely together at a travel center, can create an emission source 

capable of significantly elevating ambient PM2.5 concentrations above background over a 

distance of at least 2000 feet. In this study, the Ramp monitoring station was located 

between 1000 to 2000 feet of 400 or more idling trucks at three travel centers. The PM2.5

concentrations measured were significantly above background concentrations by an 

average of 4.8 ug/m3 (5-month average), and up to 13.0 ug/m3 for a 24-hour average 

period. 

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
In a previous study (1), dispersion modeling of idling truck emissions was performed at 

the same site. Figure 14 shows the results dispersion modeling of annual average PM2.5

concentrations resulting from emissions of idling trucks at the travel centers and 

emissions from moving trucks on I-40. Concentrations isopleths shown in the figure do 

not include background concentrations. Maximum concentrations greater than 12 ug/m3 

were predicted to occur near the two travel centers south of the interstate. Predicted 

concentrations decreased with distance from the travel centers, dropping to 1.0 ug/m3, 

2000 ft west of the two travel centers. The annual concentration predicted at the location 

of the Ramp monitoring site (shown as a red dot) was 3.2 ug/m3, compared to a 5-month 

average measured concentration of 4.8 ug/m3 (excluding background). The predicted 

concentrations were about 65% of measured concentrations without background. 

The monitoring results and the modeling results both support a conclusion that diesel 

truck idling emissions may cause elevated ambient concentrations of PM2.5 to distances 

of approximately 2000 ft from the travel centers. This may be used as a first order 

approximation of the lateral extent of the potential “hotspot”. The significance of 

“hotspots” at other locations will depend on the number of idling trucks, the size and 

shape of the parking area, meteorological conditions, and the level of background 

concentrations occurring at the site. In areas where background concentrations are high 

compared to the NAAQS, even small increases in ambient concentrations from idling 

trucks may be significant. 

Figure 14. Isopleths of Predicted PM2.5 Annual Concentrations (ug/m3)

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
RESEARCH NEEDS

FWHA and State DOTs often have to do project level analyses for Environmental Impact 

Statements for new transportation projects and as a component of Conformity Analysis 

for consistency with State Implementation Plans (SIPs). Truck stops and travel-centers, 

however, are usually private projects and not part of Federal or State transportation 

projects. As a result, it is not clear that hotspot analyses would be required under federal 

rules for these situations. Furthermore, there is no existing mechanism to define the 

boundaries of a hotspot for project level analysis. Such a boundary would vary for 

different air pollutants and for different averaging times (e.g. 1-hour, 24-hour, and 

annual). Research is needed to better define the attributes of projects with sufficient 

emissions to create potential hotspots needing project level air quality analyses 

identifying the pollutants to consider, the distance near the project to be analyzed, and the 

meteorological conditions and averaging times that are important. Other factors that may 

be important include the extent of buffer zones separating travel centers from highways 

and neighboring receptors, the influence of noise barriers and trees in diluting and mixing 

air pollutants, and how different sizes and configurations of travel centers, truck stops, 

port areas, border crossing, and weigh stations influence the magnitude and extent of 

potential air quality hotspots near transportation facilities. 

ACKNOWLEDGEMENTS

This research was funded by the Federal Highway Administration. The project officer 

was Kevin Black. The opinions expressed in this paper are those of the authors and do 

not necessarily represent the policies or opinions of FHWA. 

REFERENCES

(1) Indale, G., Miller, T., and Davis, W, “Effects of Heavy-Duty Diesel Vehicle 

Emissions on Ambient Air Quality at a Truck Stop – Measurements and Modeling 

of NOx and PM2.5 Concentrations” Presented at the 98th Annual Meeting of the 

Air and Waste Management Association, Minneapolis, MN, Paper No. 05-A-641-

AWMA, June 2005.

(2) USEPA – “MOBILE6.2 Emissions Model User Manual” Available at the USEPA 

web site: www.epa.gov/oms/m6.htm

(3) USEPA Office of Transportation and Air Quality, “Guidance for Quantifying and 

Using Long Duration Idling Emission Reductions in State Implementation Plans 

and Transportation Conformity”, January 2004, Publication No. EPA420-R-02-

025. 

(4) Calcagno, J., Davis, W., Miller, T. “Evaluation of Heavy-Duty Diesel Vehicle 

Emissions During Cold-Start and Steady-State Idling Conditions and Reduction 

of Emissions from a Truck-Stop Electrification Program” Presented at the 98th

Annual Meeting of the Air and Waste Management Association, Minneapolis, 

MN, Paper No. 05-A-1265-AWMA, June 2005. 

(5) “Draft Proposal for Regulations Limiting Truck Idling”, Memo from Robert 

Cross, Chief Mobile Source Division, California Air Resources Board. May 9, 

2003. Staff Draft Proposal, 03/16/03. Available at (www.arb.ca.gov).

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.
(6) Perrot, Thomas L. et.al. “Truck Stop Electrification as a Long-Haul Tractor Idling 

Alternative” Presented at the TRB Annual Meeting 2004.

(7) Zietsman, Joe and Bochner, Brian; “Research Seeks Solutions to Reduce Truck 

Idling”. Texas Transportation Researcher, a publication of the Texas 

Transportation Institute, Texas A&M University, Vol 41, No 1, 2005.

(8) “CMAQ and Idle Reduction Techniques”, Federal Highway Administration 

Publication FHWA-HEP-05-020, HEP-10-05(4M)E, October 2005. 

KEY WORDS

Idling Emissions

Heavy Duty Truck Emissions

Air Quality Hot Spots

PM2.5 

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.