### DIESEL TRUCK IDLING EMISSIONS
–MEASUREMENTS AT A PM 2.5 

### 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.ed u) 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 NT RC, 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: AUGU ST 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 - MEASUREM ENTS AT A PM 2.5 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 tru cks idle engines at night. As a result, high levels of PM 2.5 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 PM 2.5 resulting from diesel truck emissions on the interstate and at the truck stops. Most of the PM 2.5 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 PM 2.5 emissions which also contribute significantly to the concentrations measured at the site. The relative contributions of regional background, l ocal truck idling and trucks on the interstate to local PM 2.5 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 PM 2.5 concentrat ions near large truck stops, ports or border crossings.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.DIESEL TRUCK IDLING EMISSIONS - MEASUREM ENTS AT A PM 2.5 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 PM 2.5 were measured near the interchange often exceeding National Ambient Air Quality Standards. This paper pre sents the results of the air monitoring study illustrating the hourly, day
- of
- week, and seasonal patterns of PM 2.5 resulting from diesel truck emissions on the interstate and at the truck stops. Surprisingly, most of the PM 2.5 concentrations occurred duri ng 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 PM 2.5 emissions which also contribute significan tly to the concentrations measured at the site. The relative contributions of regional background, local truck idling and trucks on the interstate to local PM 2.5 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 PM 2.5 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). I NTRODUCTION Ambient monitors were installed at two locations to continuously measure ambient concentrations particulate matter PM 1.0 , PM 2.5 and PM 10 . These locations were named the Ramp Site and the Ridgetop Site. Both sites were located at the interchan ge 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 in terchange 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 cent ers, 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 are a. 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 sample d. PM 2.5 and PM 1.0 were measured using TEOMs (Tapered Element Oscillating Microbalance) at the Ramp Site. PM 10 and PM 2.5 were also measured using E
- BAM beta gage instruments at the Ramp Site. PM 10 was measured using an E
- BAM beta gage instruments at th e Ridgetop Site, while PM 2.5 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 COLLECT ION METHODS Traffic d ata 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 tractor
trailer 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 tr avel centers, and to check the accuracy of the RTMS automatic traffic counters. EIS (Electronic Integrated Systems, Inc of Toronto Canada) RTMS TM vehicle detection sensors were utilized to measure hourly vehicle counts, long truck counts, and vehicle aver age 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 lon ger than the average vehicle. This primarily provides a count of tractor
- trailer rigs, but not single unit trucks or cabs without trailers. AVERAGE DAILY TRAFFI C 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. T he 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 thr ough 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 condition s. 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 VEHI CLE TRAFFIC Figure 2 shows the variation of daily traffic volume by day of the week. As shown in the figure, Fridays h ave 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 VEH ICLE TRAFFIC Hourly trends in traffic wer e 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 a fternoon 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 o ccur 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 20000 40000 60000 80000 100000 120000
Monday Tuesday W e d

n e s d a y T h

u r s d a y Friday S a t u r d a y S u n d a y DayVehicles 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 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080

0 5 10 15 20 25 Hour of the DayFraction of ADT Sundays Fridays 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 hi ghest 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 fa ll 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 0.020 0.030 0.040 0.050 0.060 0.070

0 5 10 15 20 25 Hour of the DayFraction 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)

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

0 5 10 15 20 25 Hour of the DayTruck Fraction Sundays Fridays Wednesdays

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.IDLING TRUCKS AT TRA VEL CENTER S 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 20 0 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 M ATTER 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 PM 10 resu lts. Shown in Figure 7 are the hourly and 24
- hour average PM 10 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). Wh ile some of the highest concentrations were measured during winter (February) and summer (June) months, there was no clearly identifiable seasonal trend in PM 10 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

0 50 100 150 200 250

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 PM 10 Concentrations at the RAMP Site. Figure 8 shows the weekly trend in average hourly concentrations of PM 2.5 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 d ays and Saturday being the lowest truck traffic day. A definite pattern of high PM 2.5 levels at night and lower levels during the afternoon was measured for every day of the week. Average Weekly Profile

0 5 10 15 20 25 30

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00ug/m3 Ramp TEOM PM2.5

Mon Tue Wed Thur Fri Sat Sun Figure 8. Average Weekly Profile of 1 - Hour Average PM 2.5 Concentrations at the RAMP Site. 

### PM10 Ramp

0 50 100 150 200

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 Dateug/m^3 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 PM 2.5 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 consisten t 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 PM 2.5 concentrations shown in Figure 9 is due to background concentrations and not due to nearby emi ssions 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 PM 2.5 concentrations” as an estim ate of the PM 2.5 concentrations attributable to nearby emissions from trucks on the interstate and idling at the travel centers. The average hourly Delta PM 2.5 concentrations measured at the Ramp Site are shown in Figure 10. Figure 10 shows peak hourly c oncentrations 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 PM 2.5 concentrations show higher hourly variation than total PM 2.5 concentrations that include background. 

### Average Daily Profile

0 5 10 15 20 25

02468 10 12 14 16 18 20 22 Hoursug/m3 RampTEOM PM2.5 (ug/m3)

Figure 9. Daily Profile of 1 - Hour PM 2.5 Concentrations (20 - week average) at the Ramp Site.

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.Figur e 10. Daily Profile of 1 - Hour Delta PM 2.5 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 w inds 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 PM 2.5 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 PM 2.5 concentrations and the average wind speeds observed over the 20
- week study. Clearly the highest PM 2.5 concentrations occur when wind speeds are low and the lowest PM 2.5 concentrations occur when wind speeds are higher. Average Hourly Delta PM2.5 Concentrations

0.0 2.0 4.0 6.0 8.0 10.01357911131517192123 Hourug/m3 PM2.5

TRB 2007 Annual Meeting CD-ROM Paper revised from original submittal.Figure 11. Three graphs showing Delta PM 2.5 Concentrations, Wind Speeds, Emissions and Emissions Divided by Wind Speed. Delta PM2.5 Concentrations and Wind Speed

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.01357911131517192123 Hour PM2.5 (ug/m3) Wind Speed x 5 (m/s)

Delta PM2.5 Concentrations and Emissions

0.0 2.0 4.0 6.0 8.0 10.01471013161922 Hour PM2.5 (ug/m3) PM2.5 Emissions x 5 (kg/hr)

Delta PM2.5 Concentrations and Emissions Divided by Wind Speed

0.0 2.0 4.0 6.0 8.0 10.01357911131517192123 Hour 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 PM 2.5 emissions in the area. PM 2.5 emissions have been multiplied times 5 so the results can be plotted using the same y
- axis scale as used for PM 2.5 concentrations in ug/m3 . Idling trucks emit more PM 2.5 than trucks on the interstate especially during the night. As a result, the emission profile shows higher PM 2.5 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 PM 2.5 emissions and wind speeds, the PM 2.5 emission rates were divided by the wind speed and plotted on the same graph as the average hourly PM 2.5 concentration. The results are shown in Figure 11. The graph of PM 2.5 emi ssions adjusted for wind speed follows a very similar pattern as the observed PM 2.5 concentrations for this 20
- week period. This indicates that PM 2.5 concentrations measured at the Ramp Site are strongly influenced by PM 2.5 emissions from diesel trucks an d 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 PM 2.5 concentrations. EMISSION FACTORS Hourly estimate s 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 m odel (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 MO BILE6.2. 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 gro ss 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 PM 2.5 emission factor for HHDV8b trucks traveling on the interstate wa s 0.38 g/mile. The composite PM 2.5 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 PM 2.5 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 PM 2.5 . INTERSTATE EMISSIONS Hourly traffic counts on I
- 40 of all vehicles and trucks (long vehicles) were used to es timate hourly emissions of PM 2.5 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 emissio n 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 C enter 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 midnig ht 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 mo rning 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 Wednesd ay 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 th e 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 o f 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 reasonab ly estimated based on 40% of the truck hourly count on I
40 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 adjus ted 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 ob servations.

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 F ROM 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). Emissi ons of PM 2.5 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 interstat e. 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 truc ks on the interstate are highest during the afternoon when these vehicles contribute nearly 50% of the PM 2.5 . In contrast, idling trucks account for a large percentage of emissions at night, contributing up to 90% of PM 2.5 emissions. The average contribu tion over a 24
- hour day is 80% due to idling and 20% due to trucks on the interstate.

Figure 13. Average Hourly Emissions of PM 2.5from Trucks. Hourly Average PM2.5 Emissions from Trucks

0.00 0.50 1.00 1.50 2.001357911131517192123 Hour of Daykg/hr Total Interstate 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

0 100 200 300 400 500 600

0 10 20 30 40 50 HoursIdling Trucks at Watt Rd Predicted with 11-hour lag Based on Idling Truck Counts

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 continu ous 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 PM 2.5 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 Ridg etop 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 concentratio ns 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 conce ntration 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 PM 2.5 NAAQS USEPA has recently proposed to lower the National Ambient Air Quality Standard for PM 2.5 to 35 ug/m3. The air monitoring performed during this study showed potential exceedances of the annual NAAQS for PM 2.5 , but did not show any 24
- hour average concentrations exceeding the existing PM 2.5 NAAQS of 65 ug/m3. The monitoring results at the Ramp Si te 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 PM 2.5 levels exceeded 35 ug/m3. Table 2. Highest Measured 24 - Hour Average PM Concentrationsat 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 98 th

- percentile concentration as the basis for comparison to the NAAQS, then the PM 2.5 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 PM 2.5 . CONCLUSIONS Most of the PM 2.5 concentrations measu red 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 PM 2.5 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 PM 2.5 concentrations were attributable to vehicle emissions on the interstate. With respect to PM 2.5 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 PM 2.5 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 PM 2.5 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 reasonablyapproximate 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. PM 1.0 concentrations at the Ramp Site averaged 14.6 ug/m3, while PM 2.5 averaged 17.6 ug/m3. This indicates that particles less than 1.0
- micrometer diameter make up 83% of the measured PM 2.5 . This is consistent with the knowledge that diesel exhaust emissions are very small particles and much, if not all, of the PM 2.5 measured at the Ramp Site was due to diesel exhaust emissions. PM 10 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 contri buted at least 6.8 ug/m3 to average PM 10 levels at the Ramp Site. Five
- month average PM 10 concentrations were 70% and 80% higher than PM 2.5 concentrations measured at the Ramp and Ridge
- top Sites, respectively. In both cases, the PM 10 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 PM 2.5 air pollution concentrations. Hotspots are not well d efined, 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 PM 2.5 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 PM 2.5 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 PM 2.5 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 gre ater 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 concentrat ion 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 PM 2.5 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 fo r 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 th e 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 dilu ting 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. R EFERENCES (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 PM 2.5 Concentrations” Presented at the 98 thAnnual Meeting of the Air and Waste M anagement 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 Co ld
- Start and Steady
- State Idling Conditions and Reduction of Emissions from a Truck
- Stop Electrification Program” Presented at the 98 th 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 Researche r , 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 Emissi ons Heavy Duty Truck Emissions Air Quality Hot Spots PM2.5

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