Environ. Sci. Technol. 1997, 31, 3405-3412
Particulate Emission Rates from In-Use High-Emitting Vehicles Recruited in Orange County, California STEVEN H. CADLE AND PATRICIA A. MULAWA* General Motors Research and Development Center, MC 480-106-269, 30500 Mound Road, Warren, Michigan 48090-9055 JAMES BALL Ford Motor Company, Scientific Research Laboratories, Mail Drop 3083, P.O. Box 2053, Dearborn, Michigan 48121 CLAUDIA DONASE AND ARNIE WEIBEL Chrysler Corporation, CIMS 481-39-06, 800 Chrysler Center Drive East, Auburn Hills, Michigan 48236-2757 JOHN C. SAGEBIEL Desert Research Institute, EEEC, P.O. Box 60220, Reno, Nevada 89506-0020 KENNETH T. KNAPP U.S. EPA Mobile Source Emissions Branch, Mail Drop 48, Research Triangle Park, North Carolina 27711 RICHARD SNOW ManTech Environmental Technology, P.O. Box 12313, Research Triangle Park, North Carolina 27709
One hundred three in-use vehicles identified as high hydrocarbon and/or carbon monoxide emitters by remote sensing and roadside visual, underhood checks during a 1995 South Coast Air Quality Management District program were tested on the IM240 cycle using a transportable dynamometer. Seventy-one of these vehicles were repaired as part of the program and were retested. Seventeen vehicles in the fleet initially emitted visible smoke from the tailpipe and were classified as “smokers”. The fleet ranged in age from 6 to 22 years, with a median age of 12.3 years. Exhaust HC, CO, NOx, and particulate emissions (PM10) were measured. PM-10 mass and the elemental and carbonaceous composition of the particulate matter were determined. The average fleet PM-10 emission rate was 0.138 g/mi, while the average emission rate for smokers was 0.395 g/mi. It was concluded that the casual observation of smoking vehicles was not very successful in identifying high PM-10 emitting vehicles. The particulate matter composition was primarily carbonaceous, with a variable distribution between the elemental and organic carbon fractions, and showed no significant difference in the percent organic carbon fraction between smokers and non-smokers. The PM composition differed, on average, between pre-repair and post-repair samples. The effect of the California Smog Check repair program on PM emission rates could not be evaluated due to concerns regarding the effect of vehicle conditioning on these measurements.
S0013-936X(97)00025-4 CCC: $14.00
1997 American Chemical Society
Introduction Atmospheric particulate matter has long been a concern because it may cause health effects, reduces visibility, impacts the climate, can cause damage to exposed surface materials, and soils monuments and other architectural structures. Health effects concerns have increased recently due to a series of epidemiological studies that have correlated increases in human morbidity and mortality in several cities throughout the country to PM-10, particulate matter with a diameter of 10 µm or less (1, 2). The national ambient air quality standard for particulate matter is 150 µg/m3 over a 24-h period for PM-10. As of September 1996, the U.S. Environmental Protection Agency reported that 81 areas remained out of compliance with this standard (3). On a national basis, the U.S. EPA estimates that the largest contributor to primary particulate matter is fugitive dust (89%). Nationally all highway vehicles account for only 3% of the total. On the other hand, the mobile source contribution to PM-10, calculated using the Chemical Mass Balance Receptor Model, has been reported to be as high as 50% in Phoenix during the winter of 1989-1990 (4) and 59% at a midtown Manhattan site located near a bus stop (5). These estimates may represent upper limit values based on the limitations of the method to distinguish between different sources of chemically similar pollutants. The U.S. EPA has recently proposed a new PM-2.5 ambient air quality standard of 50 µg/m3, in addition to the existing PM-10 standard. This will decrease the importance of sources of large particles such as fugitive dust. Particulate emission rates from light-duty vehicles have decreased dramatically over the years. Vehicles manufactured before 1975 emitted between 0.15 and 0.25 g/mi total particulate when operated on the leaded gasoline available at that time (6). Use of unleaded gasoline in such vehicles resulted in a reduction of total particulate emissions to about 0.025 g/mi. Some early oxidation catalyst cars equipped with air pumps showed sulfate emission rates as high as 0.020 g/mi. However, emission rates of total particles were below 0.010 g/mi for most production catalyst vehicles. Federal Tier I light-duty vehicles, which phased into use starting in 1994, must meet a 0.080 g/mi standard for the first 50 000 mi or a 0.10 g/mi standard for 100 000 mi. Recent data (7-9) indicate that properly functioning light-duty gasoline vehicles manufactured between 1986 and 1990 have particulate matter emission rates lower than 0.010 g/mi. These vehicles were obtained from manufacturers’ fleets with odometer readings ranging from 6000 to 35 000 miles. There is little information regarding particulate emission rates from current in-use light-duty gasoline vehicles. PM10 emission rates were measured for 31 1964-1970 model year vehicles in the Unocal SCRAP program (10). PM-10 ranged from 0.1 to 16.8 g/mi with an average of 1.51 g/mi, clearly indicating that there is a population of very old, malfunctioning vehicles with high particulate matter emission rates. Hildemann (11) tested seven 1977-1983 catalyst inuse vehicles with an average odometer reading of 76 000 mi. The average PM-2.0 was 0.0176 g/mi. Gertler (12) measured the fleet average PM-10 emission rate of heavy- and lightduty vehicles passing through the Ft. McHenry Tunnel during July 1993. The heavy- and light-duty vehicle fleet average emission rates of PM-10 were 0.67 ( 0.13 and 0.015 ( 0.060 g/mi, respectively. Sagebiel (13) reported PM-10 emission rates from 23 1976-1990 vehicles that were recruited as high HC and/or CO emitters as part of the Clark and Washoe Remote Sensing Study (CAWRSS) conducted in Nevada. Vehicles were tested at roadside using the IM240 test cycle. The average emission rate was 0.183 g/mi. Six of the vehicles
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were identified as having visible smoke emissions. The average emission rate for the smokers was 0.558 g/mi while that for the non-smokers was 0.051 g/mi. We participated in a remote sensing study in Orange County, CA, designed to identify and repair high emitting vehicles during the spring of 1995 (14). High emitting vehicles were identified by remote sensing, chassis dynamometer tested at roadside using the IM240, sent to commercial repair facilities, repaired using the California Smog Check test (BAR90), and retested. PM-10 samples were collected during the IM240 tests. The results are presented in this paper.
Experimental Section Overview of the Program. The Orange County Remote Sensing Study was conducted between May 8 and May 26, 1995, on surface streets in the towns of Costa Mesa and Santa Ana, CA. The study was sponsored by the South Coast Air Quality Management District and was conducted by the Desert Research Institute (DRI). The U.S. EPA provided and operated a portable chassis dynamometer as part of the study. The Environmental Research Consortium sponsored the particulate matter measurements that are reported herein. The DRI final report provides experimental details as well as the remote sensing results of the study (14). Two remote sensors separated by a distance of approximately 25 m were used to identify high emitting vehicles in the fleet that passed by the roadside sites. The selection criteria for a high emitter was that the average of the two readings be equal to or above 0.1% HC and/or 4% CO. Vehicles that met these criteria were immediately waved over by police officers. The driver was interviewed to ensure that the vehicle was not in a cold start mode, and the vehicle was inspected for exhaust system integrity, fuel level, and condition of the tires to determine if it could be tested on the chassis dynamometer. Drivers whose vehicles passed this inspection were asked to volunteer for the program. Recruited vehicles generally were tested within 24 h of recruitment on the EPA transportable chassis dynamometer. The vehicles were driven onto the dynamometer, conditioned at 50 mph cruise for 2-3 min, and then tested on the IM240 test schedule. Vehicles were tested using the fuel on-board when recruited. At the time of this study Orange County was required to use Federal reformulated gasoline. HC, CO, NOx, and CO2 concentrations in the CVS dilution tunnel were monitored continuously during the test. A subjective decision based on the IM240 results was made as to whether the vehicles were high emitters. High emitters were then trucked to a commercial repair facility. The first action at the repair facility was to conduct a BAR90 emissions test. The facility was instructed to perform all the necessary repairs to bring the vehicles into compliance with the state of California I/M Smog Check standards and to confirm the effectiveness of the repairs by performing a second BAR90 test. Information on particulate emissions was not provided to the repair facility, and there were no instructions to perform repairs to reduce particulate matter emissions. Repaired vehicles were trucked back to the roadside dynamometer site and retested. Vehicles which failed the retest were returned to the same facility for further repair. Sampling. PM-10 samples were collected on both 37 mm diameter, 2.0 µm pore size Gelman Teflo and 37 mm diameter Pallflex Tissue Quartz 2500 QAT-UP filters. Quartz filters were prefired at 900 °C for 3 h to remove any carbon. Samples were drawn at a flow rate of 30 L/min through isokinetic sample probes using mass flow controlled pumps. Flow was measured periodically with a dry gas meter. The sample probes were connected to PM-10 cyclones (University Research Glassware, Chapel Hill, NC) equipped with filter holders. A 24 mm diameter, 26.5 cm long straight tube was inserted between the cyclone and the filter holder as a flow straightening section. One Teflon filter sample and one quartz
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filter sample were collected simultaneously for each IM240 test. Seven Teflon filter field blanks were also collected. The weight change for these blanks ranged from a loss of 6 µg to a gain of 4 µg with an average of no weight change. Mass and metals were determined from the Teflon filter. Organic and elemental carbon were determined from the quartz filter. In seven tests, a second Teflon filter was substituted for the quartz filter so duplicate mass determinations could be made. Analysis. Mass, organic and elemental carbon, and metals analyses were conducted at DRI. Standard EPA PM-10 methods were employed (15). Prior to sampling, Teflon filters were stored at least 1 month in a controlled environment and at least 1 week in the weighing environment to stabilize mass. After sampling, Teflon filters were equilibrated at least 24 h at 30% RH and 20 °C prior to weighing. Mass measurements were accepted if replicate weighings agreed to within (10 µg. This resulted in a lower limit of detection for mass of 2.0 mg/mi. A 0.512 cm2 punch was removed from the quartz filters for carbon analysis by the DRI thermal/optical reflectance (TOR) method (16). Results include organic carbon (OC), which is defined as the carbon evolved in a pure helium atmosphere at a temperature of 550 °C after correcting for any carbonization, and elemental carbon (EC), which is the remaining carbon that required oxygen for removal. The lower limits of detection for OC and EC were 0.86 and 0.34 mg/mi. Metals were analyzed on the Teflon filters using X-ray fluorescence (XRF).
Results and Discussion Vehicles. All vehicles included in this study were recruited on the basis of their having high HC and/or CO emissions as determined by the remote sensing measurements. Vehicles were recruited randomly as needed for testing. Remote sensing records showed that the recruited vehicles represented approximately 9% of the fleet at these locations (14). Most vehicles greater than 20 years old and some larger cars and vans that physically did not fit on the dynamometer were excluded. Vehicles that subsequently were found to have low emissions on the IM240 were not included in the repair and retest portion of the study. While it is reasonable to assume that vehicles that are in a poor state of repair may have both high gas phase and particulate matter emissions, it is not known how closely these emissions correlate. Therefore, the tested vehicle fleet cannot be assumed to be representative of the population of high PM-10 emitters in the in-use fleet at these locations. PM-10 samples were collected from 103 vehicles tested as received. This will be referred to as the complete fleet. Seventy-four of the complete fleet vehicles were cars, with the remainder of the vehicles being light-duty trucks. An additional vehicle tested had such high particulate emissions that the filters plugged, preventing an accurate determination of the emission rate. It has been excluded from the data set. Ninety of these vehicles were also tested after repair. Some vehicles went through more than one repair and retest cycle. PM-10 emissions from the intermediate test cycles will not be discussed. DRI, as part of the overall study, made the determination of which vehicles had completed the full test and repair sequence with valid data. Seventy-one of the 90 vehicles fell into this category. These vehicles will be referred to as the test/repair fleet. In addition, the DRI staff collecting PM-10 samples were requested to make a note of any vehicles tested that had visible smoke emissions. There were 17 smokers identified in the complete fleet of which 12 were captured in the test/repair fleet. Table 1 gives the fleet mean and median ages and odometer readings for the complete fleet, the test/repair fleet, and the subfleets of smokers and non-smokers. The complete and test/repair fleets were also separated into light-duty car and light-duty truck fleets. Ages and odometer readings for these subfleets are also presented in Table 1. Drivers were
TABLE 1. Vehicle Fleet Age and Odometer fleet
no. of vehicles
mean age, (years)
median age, (years)
range age, (years)
mean odom (mi)
median odom (mi)
range odom (mi)
complete complete (non-smokers) complete (smokers) complete (cars only) complete (trucks only) test/repair test/repair (non-smokers) test/repair (smokers) test/repair (cars only) test/repair (trucks only)
103 86 17 74 29 71 59 12 49 22
12.3 12.3 12.4 12.8 11.2 12.5 12.6 11.9 12.9 11.5
11.0 11.0 12.0 12.0 10.0 11.0 11.0 11.5 13.0 10.5
6-22 6-22 8-21 6-21 7-22 7-22 7-22 8-17 7-20 7-22
125 564 123 938 134 345 124 909 127 157 122 402 119 172 138 270 116 835 134 073
126 659 124 564 138 809 123 853 134 775 128 689 123 884 141 777 117 912 138 682
40K-301K 40K-301K 60K-228K 40K-301K 62K-199K 40K-228K 40K-216K 50K-228K 40K-228K 62K-199K
TABLE 2. PM-10 Emission Rates fleet
no. of vehicles
mean PM-10, (g/mi)
median PM-10, (g/mi)
PM-10 range, (g/mi)
complete complete: non-smokers complete: smokers complete: cars only complete: trucks only test/repair (pre repair) test/repair (post repair) test/repair: non-smokers (pre-repair) test/repair: non-smokers (post-repair) test/repair: smokers (pre-repair) test/repair: smokers (post-repair) test/repair: cars only (pre-repair) test/repair: cars only (post-repair) test/repair: trucks only (pre-repair) test/repair: trucks only (post-repair)
103 86 17 74 29 71 71 59 59 12 12 49 49 22 22
0.138 0.094 0.395 0.146 0.116 0.139 0.167 0.104 0.141 0.308 0.291 0.155 0.171 0.103 0.156
0.084 0.055 0.338 0.077 0.087 0.088 0.108 0.066 0.103 0.252 0.200 0.084 0.110 0.088 0.104
0.003-1.097 0.003-0.475 0.019-1.097 0.003-1.097 0.005-0.780 0.003-1.097 0.002-1.038 0.003-0.475 0.002-0.566 0.019-1.097 0.027-1.038 0.003-1.097 0.002-1.038 0.005-0.402 0.004-0.763
interviewed as to whether the odometer had turned over (passed the 100 000 mi mark) and whether the odometer was working. Non-working odometers were deleted from the database. The odometer readings for those vehicles whose odometers were reported to have turned over had 100 000 mi added to them. This adjustment was significant. For example, the average corrected and uncorrected odometer readings for the complete fleet were 125 358 and 90 861 mi, respectively. Differences in the fleet and subfleet average odometer readings were modest. The vehicles in the fleet ranged in age from 6 to 22 years, where the age of a 1995 MY vehicle was defined as zero, a 1994 vehicle as 1 year, etc. A vehicle age histogram of the fleets was not very even, with a peak in the distribution occurring in the 10-12 year range and a median age of 12.3 years (available in the Supporting Information). These distributions are in agreement with other remote sensing and roadside vehicle studies that show that few new vehicles are high emitters and that the largest population of high emitters is usually in the 9-11 year age range (17). There were modest variations in the ages of the various subfleets. PM-10 Pre-Repair Emission Rates. Duplicate Teflon filter PM-10 samples were collected for seven tests. The average percent difference in collected mass was 0.5%, with a range of -18 to +11%. It was concluded that there were no systematic differences in the two sampling trains. Ten duplicate IM240 tests were conducted. The duplicate test was conducted within a few minutes of the first test with no additional conditioning. Nine of the tests were on vehicles before they entered the repair cycle. The tenth test was on one of the vehicles after it had completed one repair/test cycle. The repair was not effective, and it was returned for further repair. The filter masses collected from the paired tests were compared. In all but one case, the second IM240 mass was smaller than the first. The test with a higher mass on the duplicate was the vehicle that had returned from the repair/test cycle. The average difference for all 10 runs was
a 32% decrease. If the two lowest mass emission runs (32 and 87 µg) are dropped from the data, then the average change in mass is a decrease of 24.2%. The average FID HC results for the same tests were also examined to determine if they followed a similar trend. The average change in HC concentration for the 10 tests was an increase of 10.8%. For the eight tests with highest PM-10 emissions the average HC increase was 8.9%. It was concluded that the HC emission data did not indicate a major change in the vehicle operating conditions between the first and second tests. One explanation for the PM-10 decrease could be that the IM240 cycle contains more severe driving than the vehicles had experienced recently on road, or during the conditioning, with the result being the re-entrainment of particulate matter from the exhaust system. Clearly, more extensive studies of test cycle and vehicle conditioning effects are needed to understand these results. The PM-10 emission rate from the first of the duplicate tests was used in the rest of the data analysis, since it is most representative of the as-received vehicle condition. Table 2 gives the average PM-10 emission rates for the vehicle fleets. Individual values are available in the ERC final report (18). For the complete fleet, the average PM-10 emission rate was 0.138 g/mi, with a range of 0.003-1.097 g/mi on the IM240. Figure 1 shows the PM-10 emission rate histograms for the complete and test/repair fleets with smoker and non-smoker breakdowns. Average PM-10 emission rates in the complete fleet for those vehicles that had been visually identified as non-smoking and smoking vehicles were 0.096 and 0.395 g/mi, respectively. However, as shown in Figure 1, there was considerable overlap in the range of PM-10 emissions for these two groups of vehicles; smokers had PM10 rates as low as 0.019 g/mi while non-smokers had rates as high as 0.475 g/mi. Similar results were found for the test/repair fleet. Thus, the casual visual identification of smokers used in this study can only be considered partially successful in identifying the higher PM-10 emitting vehicles.
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FIGURE 1. Fleet PM-10 emission rate distributions. It is clear that the current in-use high mileage, older vehicles can have significantly higher PM-10 emission rates than new vehicles and higher than the rates used in the EPA MOBILE model. However, since recruitment in this test program was neither random nor based on any particulate emission criteria, the tested fleet cannot be assumed to be representative of the population of high PM-10 emitters in the in-use fleet at these locations. It is recommended that additional work be performed measuring PM-10 emission rates using the FTP test cycle on randomly recruited in-use vehicles to provide data more appropriate for inventory model use. Table 2 also gives PM-10 emission rates for the complete fleet separated into light-duty cars and trucks. While cars had a higher mean PM-10 emission rate than trucks (0.147 vs 0.116 g/mi), the car median rate (0.077 g/mi) was lower than that of the trucks (0.087 g/mi). Similar results were found for the test/repair fleet. The relationship between vehicle age and the PM-10 emission rate for the complete fleet was examined (available in the Supporting Information). While there is a hint that emissions increase with age, a linear regression showed no significant correlation. Examining only non-smoking vehicles does not significantly increase the correlation. Dividing the complete fleet into deciles based on PM-10 concentration showed that the three lowest decile groups averaged 11, 11.3, and 12.5 years old, while the three highest averaged 13.6, 12.1, and 13.6 years old. The relationship between PM-10 emission rates and odometer reading was also explored. Regressions showed no significant correlation. Post-Repair Emission Rates. Table 2 gives the average PM-10 post-repair emission rates for the test/repair fleet and subfleets of non-smokers/smokers and cars/trucks. The average and median rates for all but the smoker fleet were higher after repair than before. There were both significant increases and decreases in post-repair PM-10 emission rates relative to the pre-repair rates. The average emission rates for HC, CO, and NOx were 6.3, 74.5, and 1.2 g/mi for the pre-repair fleet and 1.5, 28.7, and 1.5 g/mi for the post-repair fleet. On an individual car basis the average percent decrease on repair was 75.6, 61.5, and 8.9% for HC, CO, and NOx, respectively. Ninety-nine percent of the vehicles had lower HC emissions, 93% had lower CO, and 55% had lower NOx after repair. Increases in NOx for some vehicles are expected since operation at rich air-to-fuel ratios will dramatically increase CO emissions, will significantly increase HC emissions, and will decrease NOx. Thus repairs that return a vehicle to proper operation at the stoichiometric air-to-fuel ratio can increase NOx. The increase in PM-10 emissions after repair is surprising, especially when one considers that the back-to-back replicate IM240 tests showed significant decreases in PM-10 emission
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rate for all vehicles tested in the as-received condition. There are no data regarding the reproducibility of PM-10 emissions over time from high emitting vehicles. However, based on observations of gaseous emissions from high emitters, considerable random variability is expected. The possibility that some repairs resulted in an increased PM-10 emissions rate was considered despite the fact that we know of no mechanism that would account for large increases in PM-10 emissions after repairs aimed at reducing HC and CO emissions. Reducing rich operation, increasing catalyst efficiency, and reducing misfire, the types of repairs expected to reduce HC and CO emissions, did not seem to provide as much benefit for PM-10 reduction. The repair data, which were assembled by the Desert Research Institute (14), were examined by sorting the vehicles three ways: (1) by the change in PM emission rate after repair, (2) by the ratio of pre- and post-repair PM emission rate, and (3) by the post-repair PM emission rate. Within each sorted set the vehicles were grouped into bins (high, medium, or low) of approximately equal number to reflect the magnitude of the change, ratio or post-repair emission rate. Repair frequency for the different categories of repair was examined for the three sorted sets. Complicating the interpretation of the data was the fact that most vehicles received multiple repairs. Thus, it was not possible to examine the impact of a single type of repair. No significant trends were apparent when the vehicles were sorted by the change in emission rate or by the ratio of emission rates. Some trends were seen when the repair frequency was based strictly on the postrepair emission rate. More repairs were made on the air injection system, catalyst, EGR valve, and engine vacuum for the highest emitting PM-10 vehicles than for the medium or low emitters. It may be that these repairs changed the combustion/exhaust system sufficiently so that there was a temporary increase in PM-10 emissions due to the removal of deposits. An alternate explanation for increased PM after repair deals with the vehicle conditioning. Vehicles were trucked to and from the repair facility. While at the test facility they received both before and after repair BAR90 emission tests. These tests must be performed on a warmed-up vehicle. Therefore, it is likely that vehicles were idled or run under no-load conditions for extended periods of time both before and after repair. They may have also been operated at idle during the diagnosis and repair process. If particulate matter is stored in the exhaust system during such periods, it could be released later during more severe operation. While there was a 50 mph cruise driven on the dynamometer before the IM240, this may not have been sufficient to return the vehicle to its previous operating condition. While we view this as the most likely explanation of the PM-10 emission rate increases, future work to address the issues of conditioning effects needs to be undertaken. It is concluded that the effects of repair on particulate emissions can not be assessed from the results of this study. Relationship between PM-10 and Exhaust HC. The EPA Motor Vehicle-Related Air Toxics Study (19) indicated that there were insufficient PM emission rate data to directly estimate the PM-10 emissions from the in-use light-duty gasoline vehicle fleet. However, it noted that particulate emissions tend to increase as total HC emissions increase. For the purposes of that report, it was estimated that particulate matter is 1.1% of the mass of total HC emitted on an FTP. The relationship between PM-10 and HC emission rate on the IM240 was examined for the data collected during the CARWSS study . For non-smoking vehicles the PM-10 emission rate averaged 2.0% of the HC rate, while for smokers it averaged 9.0% of the HC emission rate. The fact that PM10 rates, on average, increased after repairs that significantly reduced HC emissions would suggest that there is no direct relationship between these two species. However, as noted
FIGURE 3. Histograms of the percent organic carbon for pre-repair vehicles. FIGURE 2. Comparison of FID HC and particulate emission rates for the complete fleet. above, the post-repair data are probably influenced by test conditioning effects. Therefore, the pre-repair vehicle fleet relationship between PM-10 and HC emission rates was examined. For the complete fleet, PM-10 averaged 4.36 ( 6.16% of the HC emission rate with a range of 0.04-36.5%. The median value was 2.1%. The average for non-smokers was 3.84 ( 5.56% of the HC emission rate with a range of 0.04-36.5% and a median of 1.9%, while that for smokers was 6.97 ( 8.30% with a range of 0.99-35.0% and a median of 4.8%. Figure 2 plots HC and PM-10 emissions for the complete fleet. The correlation derived from linear regression is weak, with an r of 0.44. Correlations based separately on non-smokers and smokers were slightly improved with r values of 0.47 and 0.54. Overall, there appears to be no simple relationship between PM-10 and HC emission rates. This result is not surprising since high emissions of these species can be due to multiple, independent causes. Carbon Emission Rates. Organic (OC) and elemental (EC) carbon PM-10 emission rates were determined for 67 prerepair vehicles. OC and EC emission rates were also measured for 47 of these vehicles after repair. A linear regression analysis of the total carbon emission rates and the PM-10 emission rates for the 47 pre-repair vehicles showed that the correlation was very high (r 2 ) 0.98), and the slope indicated that total carbon (TC) exceeded the mass by 11%. This excess mass may be due to several factors: (1) the impact of filter inhomogeneities on the carbon analysis which uses a small section of the filter, (2) the adsorption of gaseous hydrocarbons on the quartz filters used for carbon sampling that does not occur on Teflon filters, and (3) the difference in particle collection efficiency between Teflon (mass) and quartz (carbon) filters . This problem was also observed in the CAWRSS study (13). The possibility of inhomogeneities has been addressed by analyzing multiple punches from CAWRSS samples and others obtained using the same sampling system and agreement has been good. The correlation between total carbon and PM-10 mass emission rates for the post-repair vehicles was also excellent (r 2 ) 0.95), with the regression line having a slope of 1.01. These results indicate that the particulate matter collected was predominantly carbonaceous in makeup. The percent of the total carbon identified as OC in the individual samples varied widely, ranging from 18.6 to 96.9% of the total carbon for the pre-repair vehicles. Figure 3 is a histogram of the percent OC of the total carbon for the 67 pre-repair vehicles. The frequency is plotted against the upper end of the respective range, i.e., 17 vehicles had a percent OC between 70 and 80%. The average % OC was 70.6 ( 18.2 for
the 67 vehicle set and 68.8 ( 17.8 for the 47 vehicle set with matching post-repair data. The range was the same for the two sets. A linear regression between OC and TC had a slope of 0.79 and an r 2 of 0.91. Five of the vehicles in this data set had been identified as smokers. There was no significant difference in the % OC between the smokers and non-smokers. The post-repair vehicles had a % OC range of 9.8-89.9%, with an average of 51.3 ( 21.6%. The linear regression between OC and TC had a slope of 0.514 and an r 2 of 0.80. While the % OC appears to be much lower for the vehicles after repair, a paired t-test showed that the differences were not statistically significant at the 95% confidence level (p ) 0.103). Elemental Analysis. PM-10 samples from 63 of the vehicles that were tested both pre- and post-repair were analyzed for 40 elements by XRF. The average emission rates, standard deviations of the rates, minimum and maximum values, and average calculated uncertainties are summarized in Table 3. The PM-10 emission rates for this subset of vehicles had a range of 0.003-0.47 g/mi with an average of 0.110 g/mi for the pre-repair vehicles and a range of 0.0021-0.54 g/mi with an average of 0.129 g/mi for the post-repair vehicles. The pre-repair elemental analysis data were examined for outliers by examining linear regression plots between species and by comparing the maximum values to the means. Two Cl, two Si, one Pb, and three Fe data points were judged to be outliers. These have been retained in Table 3, but were removed for other analyses. Of the elements listed in Table 3, 12 have average concentrations that are at least twice the average uncertainty. These elements are Mg, Al, Si, P, S, Cl, Ca, Fe, Cu, Br, Zn, and Pb. The average emission rates of all of these elements were low, ranging from 0.0067 mg/mi for Br to 0.65 mg/mi for Si. The sum of the emission rates of the 12 elements for the pre-repair vehicles ranged from 0.22 to 7.76 mg/mi, with an average of 1.96 mg/mi. These rates accounted for between 0.41 and 12.3% of the total PM-10 mass, with the average being 3.50%. Addition of all the other measured elements increases the total average emission rate to 2.07 mg/mi, which was 3.94% of the total PM-10 emission rate. While these elements are a relatively small percentage of the total PM-10 emissions, they do provide some information regarding the source of the carbonaceous material that comprises the bulk of the PM-10 emissions. Table 4 gives r 2 values for correlations between the PM-10 mass and the 12 elements for the pre-repair vehicles. Since PM-10 mass was highly correlated to total carbon, the correlations with PM can be considered a surrogate for correlation with total carbon as well. PM-10 correlates best with S, Zn, and Ca (r 2 ) 0.42, 0.41, and 0.50, respectively). Zn, P, Ca, Mg, and Cu are all well correlated, with r 2 ranging from 0.55 to 0.95. All of these elements are commonly present in engine oil. Zn and P are
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TABLE 3. Statistics for PM Emission Rates of Elementsc emission rate before repair, (mg/mi)
emission rate after repair, (mg/mi)
species
av
SD
av uncert
min
max
av
SD
av uncert
min
max
sodium magnesium aluminum silicona phosphorus sulfur chlorinea,b potassium calcium titanium vanadium chromium manganese irona nickel copper zinc bromine molybdenum palladium cadmium iodine tin antimony barium lanthanum leada,b
0.0076 0.0755 0.1124 1.273 0.2423 0.2713 0.5367 0.0147 0.2007 0.0012 0.0008 0.0048 0.0049 0.2760 0.0052 0.0087 0.2035 0.0067 0.0020 0.0012 0.0017 0.0032 0.0072 0.0047 0.0238 0.0196 0.0287
0.0186 0.0693 0.3234 3.629 0.3359 0.2968 3.773 0.0259 0.2371 0.0025 0.0044 0.0120 0.0096 0.6437 0.0181 0.0141 0.2642 0.0204 0.0054 0.0028 0.0034 0.0051 0.0081 0.0071 0.0312 0.0321 0.0469
0.1135 0.0383 0.0651 0.4073 0.1047 0.0193 0.1656 0.0179 0.0387 0.0692 0.0344 0.0119 0.0075 0.0210 0.0056 0.0045 0.0122 0.0031 0.0075 0.0263 0.0296 0.0353 0.0441 0.0531 0.1938 0.2586 0.0078
0.0000 0.0000 0.0000 0.0929 0.0121 0.0008 0.0017 0.0000 0.0116 0.0000 0.0000 0.0000 0.0000 0.0109 0.0000 0.0000 0.0037 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0848 0.4311 2.554 25.10 1.928 1.311 30.01 0.1410 1.414 0.0147 0.0331 0.0644 0.0705 4.025 0.1403 0.0884 1.576 0.1180 0.0335 0.0113 0.0152 0.0224 0.0271 0.0262 0.1166 0.1349 0.2590
0.0030 0.1838 0.3981 1.456 0.8695 0.5895 4.124 0.0297 0.7898 0.0037 0.0042 0.0198 0.0258 1.304 0.0166 0.0311 0.8861 0.0159 0.0102 0.0017 0.0025 0.0032 0.0138 0.0047 0.0363 0.0295 0.1608
0.0112 0.1855 0.4734 1.412 1.222 0.6462 10.31 0.0360 1.103 0.0060 0.0115 0.0338 0.0438 1.939 0.0183 0.0349 1.219 0.0372 0.0258 0.0036 0.0049 0.0047 0.0142 0.0080 0.0368 0.0396 0.3456
0.2531 0.0505 0.1372 0.4646 0.3658 0.0351 1.158 0.0196 0.1355 0.0700 0.0353 0.0115 0.0071 0.0688 0.0050 0.0046 0.0454 0.0033 0.0072 0.0269 0.0302 0.0359 0.0433 0.0538 0.1948 0.2596 0.0124
0.0000 0.0000 0.0000 0.0537 0.0233 0.0039 0.0051 0.0000 0.0121 0.0000 0.0000 0.0000 0.0000 0.0220 0.0000 0.0000 0.0133 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0008
0.0713 0.8886 2.616 6.606 5.372 3.811 69.59 0.1859 4.841 0.0318 0.0608 0.2341 0.2288 10.56 0.0903 0.1631 5.406 0.2310 0.1570 0.0174 0.0193 0.0186 0.0533 0.0332 0.1217 0.1766 2.458
a Average pre-repair Si, Cl, Fe, and Pb emission rates with outliers removed were 0.650, 0.054, 0.143, and 0.0249 mg/mi, respectively. b Average post-repair Cl and Pb with outliers removed were 3.07 and 0.124 mg/mi, respectively. c Co, Ga, As, Se, Rb, Sr,Y, Zr, Ag, Au, Hg, Th, and U emission rates were determined to be
