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Apportionment of Motor Vehicle Emissions from Fast Changes in Number Concentration and Chemical Composition of Ultrafine Particles Near a Roadway Intersection Joseph P. Klems, M. Ross Pennington, Christopher A. Zordan, Lauren McFadden, and Murray V. Johnston* Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware 19716, United States
bS Supporting Information ABSTRACT: High frequency spikes in ultrafine number concentration near a roadway intersection arise from motor vehicles that accelerate after a red light turns green. The present work describes a method to determine the contribution of motor vehicles to the total ambient ultrafine particle mass by correlating these number concentration spikes with fast changes in ultrafine particle chemical composition measured with the nano aerosol mass spectrometer, NAMS. Measurements were performed at an urban air quality monitoring site in Wilmington, Delaware during the summer and winter of 2009. Motor vehicles were found to contribute 48% of the ultrafine particle mass in the winter measurement period, but only 16% of the ultrafine particle mass in the summer period. Chemical composition profiles and contributions to the ultrafine particle mass of spark vs diesel vehicles were estimated by correlating still camera images, chemical composition and spike contribution at each time interval.. The spark and diesel contributions were roughly equal, but the uncertainty in the split was large. The distribution of emissions from individual vehicles was determined by correlating camera images with the spike contribution to particle number concentration at each time interval. A small percentage of motor vehicles were found to emit a disproportionally large concentration of ultrafine particles, and these high emitters included both spark ignition and diesel vehicles.
’ INTRODUCTION Ambient ultrafine particles have been linked to negative health outcomes, and this relationship appears to be especially strong for ultrafine particles from vehicle exhaust.1,2 In order to develop exposure models and regulations to limit exposure, it is important to understand both the spatial and temporal distribution of these particles. We have used fast measurements of ambient ultrafine number concentration in an urban location (Wilmington, Delaware) to show that intense spikes in concentration occur at regular time intervals, especially during periods of high motor vehicle traffic.3,4 Correlation with other data including wind direction, wind speed and traffic flow at an intersection adjacent to the measurement site showed that these spikes originated from motor vehicles that accelerated from a stop at the intersection. Wavelet analysis was used to separate spikes from the slower time varying background and to quantify their contribution, which ranged from 6 to 35% of the daily ultrafine number concentration with hourly contributions sometimes exceeding 50%. While spikes in ultrafine number concentration are clearly linked with motor vehicle emissions, they do not represent the full impact of motor vehicles on the ambient ultrafine concentration since motor vehicle emissions also contribute to the background. Apportionment of the full contribution of motor vehicles to the ultrafine number concentration requires fast measurements of chemical composition in addition to number concentration. r 2011 American Chemical Society
The composition of fresh and aged ultrafine particles originating from motor vehicle tailpipe emissions has been studied in some detail.5,6 In general, ultrafine particles from motor vehicles are dominated by carbonaceous material and inorganic ions such as sulfate and ammonium.7,8 After emission into the atmosphere, the particle composition may change. As the tailpipe plume dilutes and cools, semivolatile chemical species will partition on and off the particles.9 This dynamic process creates spatial variability in particle size distribution and number concentration, as well as the concentrations of gas and particle phase pollutants.10,11 For this reason, motor vehicle emission profiles obtained from ambient particle composition measurements may differ from tailpipe studies. For example, a diesel profile generated by Ogulei12 from ambient composition measurements shows that diesel emissions are dominated by elemental carbon and contain no organic carbon, whereas tailpipe studies by Zhu6 show that there is a significant level of water-soluble organic material. Inconsistency in the relative abundance of chemical species also exists between the vehicle profiles generated within a single ambient study, with one diesel profile showing large amounts of sulfate relative to Received: December 16, 2010 Accepted: June 2, 2011 Revised: March 30, 2011 Published: June 13, 2011 5637
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elemental carbon, and another showing large amounts of elemental carbon relative to sulfate depending on the procedure used to extract the profiles.12,13 A complicating factor in this work is that chemical composition measurements are typically performed on a combination of fine and ultrafine particles; for example, PM2.5 rather than on ultrafine particles alone. The present work describes a method to determine the contribution of motor vehicles to the total ambient ultrafine particle number concentration by correlating fast changes in concentration with fast changes in ultrafine particle chemical composition. Chemical composition was measured with the nano aerosol mass spectrometer (NAMS), which restricts the analysis to particles in the appropriate size range.14,15 Still camera images of the roadway adjacent to the measurement site were also made, allowing the number and types of the vehicles associated with spikes in number concentration to be determined. The image and composition data permitted emission profiles for chemical composition and number concentration to be estimated for spark ignition (SI) and heavy diesel (HD) vehicles.
’ EXPERIMENTAL SECTION Data Collection. Highly time-resolved ultrafine particle measurements were performed during the summer and winter of 2009 in Wilmington, Delaware as a part of the ULTRAfine Aerosol Characterization Experiment (ULTRACE). The composition of individual particles in the 2025 nm size range was obtained online and in real-time with the nano aerosol mass spectrometer (NAMS).14,15 At the same time, ambient particle number concentrations were measured with a condensation particle counter (CPC; model 3025A, TSI Inc., St. Paul, Minnesota) having a cutoff diameter of 3 nm. Highly time-resolved particle size distributions were obtained during a six day period of the winter campaign with a fast mobility particle sizer (FMPS; model 3091, TSI Inc., St. Paul, Minnesota). The measurement site represents an urban setting and has been described elsewhere3 along with the basic operation of the FMPS, CPC and NAMS.3,16 Briefly, ambient particles were sampled by the CPC and FMPS at a height of approximately 6 m through inlets fashioned from copper tubing, whereas the NAMS sampled particles through a separate PM10 inlet also at a height of approximately 6 m. During ULTRACE, the NAMS was tuned to analyze 2025 nm mass normalized diameter (dmn) particles,14,17 which corresponded to a mobility diameter (dm) of 1825 nm for 1.01.6 g/cm3 density particles. As highlighted in Supporting Information Figure S1, the size range analyzed by NAMS was toward the lower end of the particle sizes observed in this study. Inside the NAMS, individual particles were ablated with a high irradiance Nd:YAG laser to give a quantitative measure of the atomic composition.16 The atomic composition was then used to infer the molecular composition, specifically the relative amounts SO42, NO3, NH4þ, SiO2, “high” O:C ratio (g0.25) and “low” O:C ratio ( 0.75) were selected and the vehicles accelerating past the site during these events were counted and classified as being SI or HD using the recorded image data. The P cutoff of 0.75 was chosen because the data points above this level have the highest number of NAMS hits per minute and the fewest number of questionable vehicle designations, for example light duty trucks that may or may not be diesel. Because these events were found predominantly in the winter, SI and HD profiles were obtained only for this time period. The resulting data set consisted of 20 min of real time data including 139 particle hits, 29 observed HD vehicles and 412 observed SI vehicles. Because of the relatively small number of samples and large error, the SI and HD profiles obtained by the procedure below should be considered only as estimates. Additionally, the model assumed that every vehicle in a certain class (SI or HD) emitted the same number of particles. The value of P (the spike intensity percentage) was separated into HD and SI contributions using eqs 5 and 6. 10ND ð5Þ D i ¼ Pi 10ND þ NSI Si ¼ Pi Di
ð6Þ
where D is the HD contribution to the particle spike percentage, ND is the number of HD vehicles observed, NSI is the number of SI vehicles observed, and S is the SI contribution to the particle spike percentage. The number of HD vehicles was multiplied by a factor of 10 to account for the higher per vehicle emissions observed in diesel engines. The multiplier was chosen by varying its value between 0 and 100 and determining where the minimum in the prediction error was located. This value also agreed well with values found in the literature.18 Varying the multiplier did have a minor impact on the diesel profiles and is discussed in more detail later. The SI and HD contributions were then used as inputs in the model as shown in eq 7: i Þ C~i ¼ ðSI Si Þ þ ðHD Di Þ þ ðB P
ð7Þ
where the spike (MV) chemical composition profile of eq 1 is partitioned into spark ignition (SI), and diesel (HD) profiles. SI and HD were varied to minimize the difference between the observed and predicted chemical species. Once again, 25% of the samples were removed to produce the 20 sets of SI and HD profiles used to determine the averages and standard deviations of the chemical components. To estimate the SI and HD contribution to the entire data set, the SI, HD and B profiles i were then used as inputs for eq 7 and the values of Si and Di and P were then varied, to minimize the error between the observed and predicted average chemical profiles. Individual Vehicle Emissions. Emission contributions for individual vehicles were generated by dividing the average number 5639
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Figure 2. (A) Chemical composition profiles of particle spikes observed in the Winter CPC, FMPS and Summer CPC datasets. (B) Chemical composition profiles of the backgrounds observed in the Winter CPC, FMPS and Summer CPC datasets. (C) Spark ignition and heavy diesel chemical profiles generated from the Winter CPC dataset. Error bars are one standard deviation about the mean.
concentration of a particle spike by the number of vehicles present at the time of the spike. The spikes used in this analysis were typically 40s long, with peak number concentrations of approximately 4500 particles/cm3. This method of calculating emission contributions assumed that each vehicle present emitted the same fraction of the observed particles. While not necessarily true on a vehicle-to-vehicle basis, it is likely representative of the fleet once all the emission contributions are averaged together. Number concentration data obtained during periods when the wind was from 270 to 330° were analyzed, which corresponded to the closest, albeit most lightly used, roadway at the site. This sector was the most free from interfering background emissions. The smaller number of vehicles allowed the particle emissions from a greater fraction of single vehicles to be determined. All data manipulation and pretreatment was performed using the MATLAB computing environment and its associated toolboxes. Modeling was performed in Microsoft Excel using the Solver Add-in to minimize the prediction error.
’ RESULTS AND DISCUSSION The main goal of this work is to determine the contribution of motor vehicle emissions to the ambient ultrafine particle mass. The approach is based on characterization of spikes in number
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concentration that arise from motor vehicle emissions. These spikes allow chemical composition profiles for motor vehicle emission to be determined, which are then used to apportion the contribution of motor vehicles to the ultrafine particle mass based on its chemical composition. Characterization of the spikes also allows the impact of individual vehicles to be assessed. Chemical Composition of the Particle Spikes. A strong positive correlation was observed between the “low” O:C content (defined as carbonaceous matter having an O:C atomic ratio less than 0.25) of the analyzed particles vs relative spike intensity from the 1825 nm (dm) FMPS data. This plot, shown in Supporting Information Figure S3, clearly indicates that the particle spikes were composed primarily of this material as would be expected from tailpipe emission measurements. No similar correlation was observed for any of the other apportioned molecular species. However, this observation does not necessarily mean that these other species were not present in the spikes, just that they were more strongly associated with the background. When the modeling and validation procedures described in the Experimental Section were applied to the number concentration and chemical composition data in the winter data set, the chemical composition profiles in Figure 2A were obtained for the spikes. Not surprisingly, these profiles were dominated by low O:C carbonaceous matter, but also contained low levels of other molecular species. There is little difference between the profiles generated from CPC (all particle sizes) and FMPS (restricted to 1925 nm dm) number concentration data suggesting that the chemical composition measurements in the size range analyzed by NAMS are generally representative of particles across the full size range of ultrafine particles. The slight increase in sulfate relative to low O:C matter for the profile generated from the CPC data may indicate that diesel vehicles contribute more than spark ignition vehicles to the number concentration and chemical composition outside the range analyzed by NAMS, since sulfate may be associated with diesel vehicles rather than spark ignition (see below). This observation is also consistent with a particle size distribution for spark ignition vehicles skewed toward a lower size than that for diesel vehicles.19 The spike chemical composition profile generated by the summer CPC data set is compared to the winter CPC data set in Figure 2A. The only noteworthy seasonal difference is an increase in the amount of high O:C carbonaceous matter in the summer profile, which is expected due to the substantial increase in photochemical activity during this time period. Chemical Composition of the Background. The background chemical composition profiles for the summer and winter CPC data are shown in Figure 2B. The winter profile contains significant amounts of sulfate, nitrate and ammonium in addition to a large amount of low O:C carbonaceous matter. The presence of low O:C matter in the background chemical composition profile indicates a significant contribution from combustion, most likely motor vehicles. These particles could be from motor vehicles on a nearby highway, whose emissions are carried downwind to the measurement site and processed by the atmosphere along the way, or they could arise from motor vehicles on the roadways adjacent to the site but the emissions are not correlated with specific spike events. The presence of the inorganic ions in the background profile is not surprising considering that photochemical activity will produce inorganic salts such as ammonium sulfate and ammonium nitrate. What is not immediately clear is whether the photochemical and 5640
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Table 1. Apportioned Motor Vehicle and Background Contributions to the Ultrafine Particle Mass. Errors shown are one standard deviation about the mean. Summer 2009
Winter 2009
8 ( 1%
19 ( 2%
Background motor vehicle contribution to mass concentration Total motor vehicle contribution to total mass concentration
8 ( 2% 16 ( 2%
29 ( 3% 48 ( 2%
Nonmotor vehicle contribution to total mass concentration
84 ( 2%
52 ( 2%
Spike contribution to mass concentration
SI vehicle contribution to spike mass concentration
51 ( 20%
HD vehicle contribution to spike mass concentration
49 ( 20%
Figure 3. Visual representation of removing the motor vehicle (MV) composition profile from the ambient chemical composition during a 1-minute time interval to obtain the motor vehicle contribution to ambient ultrafine particle mass. Each composition profile has been normalized to sum to one.
combustion portions of the background exist as separate particles, or if the combustion particles are atmospherically processed by growth of secondary components. Further examination of the single particle mass spectra shows that the mass fractions of ammonium and sulfate ions are greater than the mass fraction of the low O:C carbonaceous material in 20% of the particles detected during the winter campaign. In the summer background profile, sulfate constitutes almost half the mass, or over twice the level of the winter profile. Additionally, 36% of the particles detected during the summer are clearly from a mixed photochemical and vehicular origin (low O:C carbonaceous matter with significant amounts of secondary components), an increase of 16% over the winter. In the apportionment that follows in the next section, only the mass fraction of these internally mixed particles that corresponds to the fresh motor vehicle emission profiles is assigned to the motor vehicle contribution. Apportioned Ultrafine Particle Mass from Motor Vehicle Emissions. Apportioned motor vehicle contributions to the total ultrafine particle mass for both seasons are summarized in Table 1. Particles originating from motor vehicle spikes represented a larger mass fraction in the winter than the summer. To
capture the motor vehicle contribution to background, the following assumptions and approximations were made. First, although it was likely that the composition of the background particles changed due to atmospheric processing, it was assumed that the motor vehicle portion of the background chemical composition could be represented by the motor vehicle profile from the spikes. Second, all of the low O:C ratio carbonaceous matter in the background particles was attributed to motor vehicle emissions rather than other combustion sources. In this regard, the apportioned motor vehicle contribution should be considered as an upper limit. The motor vehicle contribution to the total ultrafine particle mass (spikes and background) was determined in the following manner and is summarized in Figure 3. The low O:C portion of the motor vehicle profile was set equal to the low O:C mass in the averaged ambient chemical composition of a 1-minute time interval. The other chemical species in the motor vehicle profile were scaled accordingly to maintain the same relative distribution of chemical species. The scaled motor vehicle profile was then subtracted from the ambient chemical composition, and the percentage decrease in mass was taken as the motor vehicle contribution at 5641
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Figure 4. Distribution of individual vehicle emissions obtained by correlating particle spike data with still camera images.
this time interval. The motor vehicle contribution for each 1-minute time interval was then weighted by the CPC number concentration during that time interval, and the weighted contributions were averaged over the entire measurement period. With this approach, motor vehicle emissions were found to account for 48 ( 2% of the winter and 16 ( 1% of the summer ultrafine particle mass. The motor vehicle contributions to the background were determined by subtracting the known seasonal spike percentages from the total motor vehicle contributions. As shown in Table 1, motor vehicles contributed a total of 29 ( 3% of the background in winter and 8 ( 2% in the summer. This apportionment method is based on mass because internally mixed particles are apportioned on the basis of their mass fraction associated with motor vehicle emissions. Although these results apply directly only to the size range analyzed (2025 nm dia.), they can be thought to indicate the motor vehicle mass fraction of all ultrafine particles insofar as the chemical composition does not change with particle size, as suggested by the winter CPC and FMPS profiles in Figure 2A. Estimated SI and HD Profiles. HD and SI profiles were generated from the most intense particle spike events in the December 2009 time period as described in the Experimental Section. The chemical composition profiles resulting from the SI/HD split are shown in Figure 2C. The major difference between the two is the significant amount of sulfate apportioned to the diesel profile, while the SI profile is composed almost entirely of low O:C carbonaceous matter. The apportionment of sulfate to the diesel profile is confirmed by gas phase SO2 measurements. The correlation coefficient between SO2 concentration during the time period of a spike and the number diesel vehicles observed in the camera images during the same time period is 0.6, while that between the SO2 concentration and number of spark ignition vehicles is 0.3 (Supporting Information Figure S4). Enhanced apportionment of sulfate to the diesel profile is consistent with tailpipe measurements of both types of vehicles.8 Although current regulations stipulate low-sulfur diesel fuel, many of the diesel vehicles passing by the site during this time period were associated with snow removal from a major storm, and these vehicles may have operated with a different fuel. To confirm that the diesel profile accurately predicted the presence of diesel vehicles, correlations were taken between the 1-minute averaged single particle mass spectra and the diesel profile. During time
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periods with a high correlation (r > 0.99) there were 3 times more diesel vehicles present than when the diesel profile was anticorrelated with the mass spectra. Varying the diesel multiplier used in the model did have a minor effect on the diesel profile obtained from the model. In particular, increasing the multiplier above 10 caused a greater amount of low O:C carbonaceous matter and a lesser amount sulfate to be apportioned to the HD profile, but every HD profile generated from the model had significantly more sulfate than the SI profile. The winter time SI and HD profiles obtained from the most intense spikes were used to determine the contribution of motor vehicles to the winter data set and estimate the contribution of each type of vehicle. These results are summarized in Table 1. Although bounded by a large error, SI and HD had approximately equal contributions, despite HD vehicles representing only 6% of the vehicles observed. The error values shown are one standard deviation about the mean and result from the uncertainty surrounding the chemical profiles. Average Number Concentration of Motor Vehicle Emissions. The emission contribution of an individual vehicle, defined as its contribution to the particle number concentration of a spike, can be determined by dividing the particle number concentration of a spike by the number of vehicles observed in the camera images during the spike. The full procedure is discussed in the Experimental Section. Figure 4 shows the results, plotted as cumulative number of vehicles vs particle emission contribution for the winter data set. The median emission contribution was 524 particles/cm3 per vehicle while the average was 1300 ( 200 particles/cm3 per vehicle (95% CI). Published data from 2005, which allowed for the calculation of vehicle emission contribution and had a similar percentage of on road diesel traffic, gave an average per vehicle emission factor of approximately 1900 particles/cm3per vehicle.18 The value determined in the present study was slightly lower than this, and possibly reflects the changes in emission control technology since 2005. Figure 4 also shows that despite the average emission contribution being approximately 1300 particles/cm3 per vehicle, almost 90% of the vehicles passing by the measurement site had lower emission contributions than the average. Furthermore, when the camera images from spikes representing the top 10% of the emission contributions were analyzed, no correlation was observed to any one vehicle type, leading to the conclusion that a small percentage of motor vehicles emit a disproportionally large number of ultrafine particles, and these high emitters include both spark ignition and diesel vehicles.
’ ASSOCIATED CONTENT
bS
Supporting Information. Four figures referenced in the text. This material is available free of charge via the Internet at http://pubs.acs.org.
’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected].
’ ACKNOWLEDGMENT This research was funded by the Health Effects Institute through agreement number 4775-RFPA06-4/07-9. Research described in this article was conducted under contract to the Health Effects 5642
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Environmental Science & Technology Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Agreement CR-83234701) and certain motor vehicle and engine manufacturers. The contents of this article do not necessarily reflect the views of HEI, or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. J.P.K. acknowledges graduate fellowship support from NSF grant EPS-0814251.
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