Laboratory Measurements of the Heterogeneous Oxidation of

of the Heterogeneous Oxidation of Condensed-Phase Organic Molecular Makers for Motor Vehicle Exhaust ... Publication Date (Web): September 20, 200...
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Environ. Sci. Technol. 2008, 42, 7950–7956

Laboratory Measurements of the Heterogeneous Oxidation of Condensed-Phase Organic Molecular Makers for Motor Vehicle Exhaust EMILY A. WEITKAMP, ANDREW T. LAMBE, NEIL M. DONAHUE, AND ALLEN L. ROBINSON* Center for Atmospheric Particle Studies, Carnegie Mellon University Pittsburgh, Pennsylvania 15213

Received March 14, 2008. Revised manuscript received June 20, 2008. Accepted August 11, 2008.

Triterpanoid hopanes and steranes are petroleum biomarkers used to apportion fine particulate matter to motor vehicle emissions. To investigate the chemical stability of these compounds, aerosolized motor oil was exposed to the hydroxyl radical (OH) in a smog chamber and the reaction rate constants of hopanes, steranes, and n-alkanes were measured. The experiments were conducted across a range of atmospheric conditions including low and high relative humidity (RH) and with mixtures of lubricating oil and secondary organic aerosol. Hopanes and steranes were found to react at atmospherically significant rates across the entire range of experimental conditions; they are estimated to have lifetimes on the order of several days at average summertime OH levels. The one experimental parameter that strongly influenced the effective rate constants was RH; oxidization of hopanes and steranes was about a factor of 4 slower at 75% RH than at 10% RH. Chemical mass balance (CMB) analysis was performed to illustrate the effects of oxidation on source apportionment estimates. As the extent of oxidation increases, traditional CMB analysis increasingly underestimates the contribution of gasoline vehicles but the diesel estimates are largely unaffected. The results demonstrate that even modest levels of oxidation can alter policy-relevant conclusions about the total and relative contribution of gasoline and diesel vehicle emissions to ambient fine particle concentrations.

Introduction Motor vehicles are an important source of organic aerosols and fine particulate matter in urban areas. One approach used to quantify their contribution is to analyze organic molecular marker data with a receptor model (1). Molecular markers are individual organic compounds whose atmospheric concentrations are thought to be dominated by emissions from a single source class (1). Important markers for motor vehicle emissions are steranes and triterpanoid hopanes, which are associated with unburned lubricating oil (1). A critical assumption underlying the use of molecular markers in source apportionment models is that these species are chemically stable (1). However, field measurements indicate that hopanes and steranes may be oxidizing in * Corresponding author phone: (412) 268-3657; fax: (412) 2683348; e-mail: [email protected]. 7950

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regional air masses during the summer (2). For example, hopane-to-elemental-carbon ratios exhibit strong seasonal and spatial patterns that are consistent with oxidation. This, in turn, drives large and unexpected seasonal shifts in the contribution of gasoline vehicle emissions predicted by chemical mass balance analysis (3). There is no doubt that particulate matter is bombarded by oxidants. Hopanes and steranes are saturated compounds and therefore will react with the hydroxyl radical (OH). OH reacts with near unit efficiency with organic surfaces (4) and particles (5). This implies a chemical lifetime for saturated species on the order of one week under typical summertime conditions (2). However, the multiphase oxidation of trace organic constituents inside of complex atmospheric particles is not well understood. Few studies have considered oxidation of condensed phase organics by OH and we are not aware of any data on the oxidation kinetics of hopanes and steranes. This paper presents laboratory measurements of the heterogeneous oxidation of molecular markers for vehicle exhaust. Aerosolized motor oil was exposed to OH inside a smog chamber; filter samples were collected and analyzed to determine changes in molecular composition; and a relative rate approach was used to derive reaction kinetics for hopanes, steranes, and n-alkanes. The data were then used in conjunction with the chemical mass balance model to investigate the potential effects of oxidation on source apportionment estimates.

Materials and Methods We conducted aerosol oxidation experiments in the 12 m3 Carnegie Mellon University smog chamber. Aerosols were added by flash vaporizing motor oil at 425 °C. Unburned lubricating oil is the dominant component of organic particulate matter in vehicles emissions (6, 7); therefore, flashvaporized oil particles provide an atmospherically relevant matrix to study molecular marker oxidation. OH was generated in the dark using the reaction of 2,3-dimethyl-2-butene (TME) and ozone (5). OH concentrations ranged from 0.6 to 40 × 106 molec cm-3, which spans typical atmospheric conditions (8). They were inferred from the measured decay of toluene and m-xylene in conjunction with published kinetic data (9). OH concentrations were not constant; in a typical experiment they varied by about a factor of 2. To simulate a range of atmospheric conditions, we conducted experiments at low (10 ( 5%) and high (75 ( 10%) relative humidity, with new and used motor oil, and with and without secondary organic aerosol (SOA) formed from ozonolysis from R-pinene. The initial aerosol concentrations in the smog chamber were high, between 250-15 000 µg m-3, to ensure adequate mass was collected for chemical analysis. In the SOA coating experiments, R-pinene and O3 were added to generate SOA. Substantial amounts of SOA were formed, almost doubling the initial aerosol mass. The changes in molecular composition of condensedphase organics were determined by collecting filter samples, which were solvent extracted and analyzed using gas chromatography mass spectrometry (10, 11). The goal was not to comprehensively analyze the motor oil, but to determine the decay of key molecular markers in a realistic matrix. The data from the smog chamber experiments were analyzed using a relative-rate approach to determine effective reaction rate constants for each target species (10–12). Additional details on the experimental methods are described in the Supporting Information. Wall-Loss Correction. To quantify the oxidation of the target species, smog chamber data must be corrected for the 10.1021/es800745x CCC: $40.75

 2008 American Chemical Society

Published on Web 09/20/2008

FIGURE 1. Time series of measured sterane mass fractions for (a) control experiment in which no TME was added to the chamber and (b) oxidation experiment with average [OH] ∼ 4 × 106 molec cm-3. In panel (a), ∼3 ppmv ozone was added to the chamber at 3.3 h. Error bars indicate one relative standard deviation of mass fractions measured in control experiments. loss of particles to the chamber walls. In our previous kinetic studies, we have accounted for wall losses by taking the ratio of a reactive target species with that of another nonreactive species in the aerosol (10–12). This is not possible when OH is the oxidant because all organic species are susceptible to OH attack. Therefore, we use particle-phase mass fractions to account for wall loss; this assumes that the wall-loss rate of any individual condensed phase species is the same as that of the overall particle mass. A complication is that processes other than wall loss can alter the total particle mass. For example, secondary organic aerosol formation (SOA) will cause particle-phase mass fractions of the target species to decrease, which could be misinterpreted as chemical loss. Alternatively, evaporation due to either dilution (13) and/or chemistry (14) might mask any chemical loss. To avoid these potential biases, the particle-phase mass fractions were defined as the ratio of the measured target species concentration to the wall-loss corrected concentration of the motor oil particles and not the actual measured particle mass. The wall-loss corrected concentrations were based on the initial particle mass concentration measured with the SMPS (assuming a particle density of 1g cm-3) and a first-order wall loss rate constant determined for each experiment before TME was added to the chamber. This approach is essentially the same as that used to interpret data from SOA yield experiments performed in our chamber with aerosol seeds (15). A detail is that the wall-loss rate often slows as the particle size increases during an experiment due to, for example, coagulation; if this occurred then we have underestimated the chemical loss. This effect is typically small, but it means that we are presenting a somewhat conservative estimate of the chemical loss.

Results Figure 1 plots time series of the particle-phase mass fractions for androstane and cholestane measured during a control experiment (Figure 1a) and an oxidation experiment (Figure 1b). During the control experiment, the OH source was not used (O3 but no TME is added to the chamber); about half the particle mass was lost to the walls, but the particle-phase mass fractions of the target species remained constant. This demonstrates the approach used for wall loss correction and that the high levels O3 required by OH source do not alter the concentrations of the target compounds. When the motor oil particles were exposed to OH, the mass fractions of all of the target species decrease. For example, Figure 1b shows that the cholestane and androstane mass fractions decreased by 50-80% after 5 h of exposure to an average OH concentration of 4 ((1) × 106 molec cm-3, a typical daytime concentration in the summer (8). Since OH reactions are likely confined to a narrow surface layer

FIGURE 2. Chromatograms of total ion current illustrating the changes in bulk organic composition due to OH attack. Panel (a) is a chromatogram of fresh (unoxidized) motor oil. Panels (b) and (c) display the difference between the chromatogram of an oxidized sample minus that of an unoxidized sample from the same experiment to show the changes in the nonpolar and polar-plus-nonpolar fractions, respectively. Panels (b) and (c) also show the difference in chromatograms for samples taken at the beginning and end of a control experiment. Negative values in (b) and (c) indicate material that is consumed during the oxidation. (2, 16), the substantial reduction in target species concentrations suggests that mass transfer within the particles continuously brings fresh reagents to the particle surface. The chromatograms of total ion current (TIC) shown in Figure 2 reveal that a large fraction of the organics is being transformed by OH oxidation. As a reference, Figure 2a shows a TIC chromatogram from a control experiment. The dominant feature is the unresolved complex mixture (UCM) of straight, branched, and cyclic hydrocarbons that elutes between 20 and 30 min. To illustrate the substantial effects of OH oxidation, Figures 2b and c show the differences between chromatograms from two samples collected in the same oxidation experiment. One sample was collected before exposure to OH and the second after exposure to 4 × 106 molec cm-3 of OH for about 4 h. Positive values indicate organic material formed during oxidation. Prior to subtraction, each chromatogram was scaled to account for the particle mass collected on the filter and the recovery of the internal standard. The difference chromatogram shown in Figure 2b is for the standard extraction without derivatization, which reveals the changes in the nonpolar fraction. Oxidation dramatically reduces the amount of nonpolar UCM that elutes between 20 and 30 min, which means that a large fraction of the organics are being oxidized, not just the target compounds, VOL. 42, NO. 21, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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underscoring that all hydrocarbons are susceptible to OH attack. As a reference, Figure 2b also shows a difference chromatogram from a control experiment; it shows essentially no change in the amount of nonpolar UCM when the particles are not exposed to OH. Figure 2c plots another difference chromatogram for the same two samples as Figure 2b, but here the extracts were derivitized immediately prior to GC-MS analysis using BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide) with 1% trimethylchlorosilane and pyridine added as a catalyst (10, 11). BSTFA converts acid and alcohol groups into their corresponding trimethylsilyl esters and ethers; therefore, Figure 2c illustrates the combined changes of the polar and nonpolar fractions. Figure 2c shows that oxidation produces a lot of material that elutes during the first 20 min of the analysis. Since this feature does not appear in the nonpolar difference chromatogram (Figure 2b), it must correspond to polar material with lower molecular weight than the parent compounds, implying that carbon-carbon bond cleavage is important. Figures 2b and c show that oxidation decreased the amount of mass that elutes between 20 and 30 minutes. The reduction was less in the derivitized samples, implying that heterogeneous oxidation also created some high molecular weight polar material with the same or similar carbon number as the parent compounds. A complication for interpreting Figure 2c is that SOA formation may have produced some of the low molecular weight, polar material. We carefully evaluated the data for evidence of SOA formation by comparing the SMPS data to the wall-loss corrected estimate. For the experiment shown in Figures 2b and c there was little difference between these two values, which indicates either little SOA formation or that any SOA formation was matched by particle evaporation. Since the gas-phase tracers (m-xylene and toluene) are known SOA precursors, there is some SOA formation in every experiment. SOA formed from oxidation of light aromatics is estimated to contribute between 2 and 12% of the final suspended particle mass based on their measured decay and published yield data (17, 18). Another concern is SOA formation from low-volatility vapors (19). These experiments were performed with degassed oil at high particle mass concentrations (typically >1000 µg m-3), which should minimize the mass of these vapors. Therefore, we attribute the majority of the small polar material shown in Figure 2c to heterogeneous processing. Molina et al. (14) proposed that OH oxidation causes substantial loss of organic particle mass. Comparisons of the measured and wall-loss corrected particle mass indicate that, within experimental uncertainty, there was no evidence for evaporative mass loss in our experiments. Important differences between the two studies are that we use real particles versus self-assembled monolayers and that our OH concentrations are 1-2 orders of magnitude lower. As a final check on our data, we calculated a rough estimate of the effective uptake coefficient for each experiment. An effective uptake coefficient compares the overall oxidation rate to the OH collision rate; it therefore indicates the number of reactions per OH collision. Since we only measured a very small fraction of the organic mass, we do not know the overall oxidation rate. Instead, we estimated it using the measured decay rate of a target species, which assumes that all of the organics oxidize at the same rate. The roughly factor of 2 difference in the decay rate of androstane versus cholestane shown in Figure 1b indicates that this is an imperfect assumption; in fact, across the small set of species we did measure, the oxidation rate varied by about a factor of 4. As discussed below, we attribute some of this variability to differences volatility and gas-particle partitioning. Depending on the species chosen, the estimated effective uptake coefficients ranged from 0.1 to 8 across the set of experiments. 7952

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Although this variability underscores the significant uncertainty in our calculation, the estimates do reinforce the conclusion that OH reacts very efficiently with organic particles (4, 5). An effective uptake coefficient can exceed one due to secondary chemistry; for example, Hearn and Smith (20) report an effective uptake coefficient of 2 for OH oxidation of BES particles. Relative Rate Analysis. Figure 3 presents relative rate plots that compare all of the experimental data. The experiments spanned a wide range of conditions: 10-75% RH, 250-15 000 µg-m-3, new and used motor oil, and with and without SOA condensed on the particles. Figure 3a is a condensed-phase relative rate plot that compares the measured decay of trisnorhopane, norhopane, hopane and androstane to that of cholestane. The initial composition of the particles is indicated by the points in the upper-right-hand corner of the plot. Oxidation decreases the mass fractions, shifting the data toward the left and/or downward in a relative rate plot. The lines shown in Figure 3a are linear regressions of the data versus cholestane. The slopes of these lines are ratios of effective rate constants (see eq S.1 in the Supporting Information). Slopes greater than one indicates that the target species reacts faster than cholestane. Androstane always reacted at 1.8 times the rate of cholestane and all of the hopanes reacted 30% slower than cholestane. Although Figure 3a does not differentiate the data by experiment, the tight clustering of the data by species indicates that there were no systematic experiment-to-experiment differences in the relative oxidation rate of two condensed-phase species. Figure 3b presents a mixed-phase relative rate plot of cholestane versus m-xylene. The advantage of a mixed-phase analysis is that a gas-phase species provides a consistent reference point because its rate constant does not vary during an experiment or from experiment to experiment. The cholestane data from each experiment organize along a line in Figure 3b, with the slope indicating effective oxidation rate constant relative to m-xylene (eq (S.2) in online Supporting Information). The fact that the data from each experiment organize along a straight line means that the cholestane effective rate constant did evolve during an experiment. However, the slope of this line varied from experiment-to-experiment; therefore the oxidation rate of cholestane varied with experimental conditions. The most important experimental parameter was relative humidity (RH). Gray shading is used in Figure 3b to visually group the experiments by RH. Although there is some experiment-to-experiment variability within each RH group, the effective rate constant for cholestane measured at 75% RH was, on average, a factor of 4 smaller than that measured at 10% RH. The strong linear correlations shown in Figure 3a mean that essentially the same RH dependence was observed for every target compound. The decrease in the effective rate constants under high RH conditions is important, but our results provide little insight into the underlying mechanism. Po¨schl et al. (21) attribute slower oxidation at high RH to competitive water uptake and surface/bulk shielding effects. Increasing RH also decreased the effective rate constants for ozonolysis of unsaturated species in meat-grease aerosol (10). However, Kamens et al. (22) reported more rapid decay of PAHs at high RH. Within experimental uncertainty, SOA, particle mass concentration and new versus used motor oil did not alter the effective rate constants (Figure 3b). The influence of all of these parameters was investigated at low RH. Since OH oxidation is thought to be confined to a thin surface layer (2, 16), the fact that condensing substantial amounts of SOA onto the motor oil particles did not change the oxidation rate constant is significant. The most likely explanation is

FIGURE 3. Compilation of relative kinetics data. (a) Condensed-phase relative kinetics plot of androstane and three hopanes versus cholestane. (b) Mixed-phase relative kinetics plot of cholestane versus m-xylene; symbol shape designates type of experiment with different colors/shading to indicate specific experiments. Grey shaded regions in panel (b) define the range of reaction rates measured under low and high RH conditions as discussed in the text. (c) Condensed-phase relative kinetics plot comparing select n-alkanes versus cholestane. (d) Effective rate constant ratios as a function of carbon number; dashed line is the calculated vapor phase fraction of the n-alkanes plotted against the right axis. The dashed lines in (a) and (c) are linear regressions with indicated slopes. The error bars in panels (a)-(c) indicate one relative standard deviation of mass fractions measured in control experiments; they are only shown on selected points for visual clarity. The error bars in (d) are statistical uncertainty of linear regressions used to calculate effective rate constant ratios. χi is the particle phase mass fraction; the data in panels (a)-(c) are normalized by the intercept of a linear regression of the data from each experiment (χi,o). that the SOA formed a quasi-ideal solution with all of the particle-phase organics as opposed to a surface coating. We previously reported that SOA decreased the reaction rate of unsaturated compounds with ozone (10). Ozonolysis is more of a bulk phenomenon compared to OH oxidation. Therefore, SOA may alter the ozone solubility of the particle matrix but have little effect on OH reactions confined to a thin surface layer. Figure 3a indicates that hopanes and steranes were oxidized at different rates. To investigate these differences, Figure 3c presents a condensed-phase relative rate plot that compares the oxidation rate of several n-alkanes to cholestane, including n-docosane (C-22), n-tricosane (C-23), ntetracosane (C-24), and n-hexacosane (C-26). The data are from a subset of the experiments conducted at low RH that had n-alkane data well above our detection limits. The slopes of the linear regression shown in Figure 3c reveal that the effective rate constant ratios increase with decreasing carbon number; for example, n-tricosane reacts twice as fast as n-hexacosane. Figure 3d plots relative rate constants for n-alkanes and hopanes as a function of carbon number. These rate constants were determined by the linear regressions with cholestane as shown in Figures 3a and c. Except for n-nonacosane (C29), the n-alkanes reacted faster with decreasing carbon

number. Androstane also reacted relatively rapidly; it is a C-19 compound. Literature data (9) indicates that the vapor-phase lifetimes of large saturated compounds are about 10 times shorter than the condensed-phase lifetimes measured here. Consequently, when 10% of the material is in the vapor phase, the effective rate constant will double and the overall lifetime will be half the condensed-phase lifetime. This hypothesis is supported by gas-particle partitioning calculations; the dashed line in Figure 3d shows the estimated vapor fractions for n-alkanes at our experimental conditions based on literature vapor pressure data compiled in Scifinder Scholar. The relative rate data for n-alkanes mirror the partitioning estimate. Another potential explanation is that more volatile species are more surface active. Figures 3a and d indicate that there are also systematic differences in the effective rate constant for condensed phase species. For example, all of the hopanes consistently reacted 30% slower than cholestane; all of these compounds exist entirely in the condensed phase under the conditions of these experiments. A potential explanation is that cholestane is more surface active than hopanes and therefore more susceptible to OH attack. However little is known about the spatial distribution of species within a particle. Hopanes and steranes are multicyclic compounds that differ primarily in VOL. 42, NO. 21, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Effective OH Rate Constants for Hopanes and Steranes in Motor Oil Aerosol effective rate constant (cm3 molec-1 sec-1) compound 5R-androstanea 5R-Cholestanea 18 17 17 17

R R R R

(H)-22,29,30-trisnorneohopaneb (H)-22,29,30-trisnorhopanea (H), 21β(H)-30-norhopanea (H), 21β(H)-hopaneb

CAS no. Steranes 438-22-2 481-21-0 Hopanes 55199-72-9 53584-59-1 53584-60-4 13849-96-2

low RH (× 10-11)

high RH (× 10-11)

1.5-3.4 0.8-1.9

0.5-0.7 0.05-0.3

0.5-1.1 0.6-1.3 0.6-1.3 0.6-1.3

NA 0.04-0.2 0.04-0.2 0.04-0.2

a Authentic quantitative standard from Chiron AS (hopanes) or Sigma Aldrich (steranes). quantitative standard for similar compound in series.

their number of rings: hopanes have five rings while steranes have four rings. The data for nonacosane (C-29) are a puzzle. This species is predicted to be entirely in the condensed phase, but reacted about 50% faster than similar carbonnumber species. The reason for this is not known. Table 1 lists effective rate constants for the hopanes and steranes derived from the slopes of linear regressions with m-xylene. The data from each experiment were fit separately and the ranges reported in Table 1 are based on minimum and maximum slopes at low and high RH conditions. For example, the edges of the gray areas drawn in Figure 3b were defined by the bounding fits calculated for the cholestane data. The slopes were converted to effective rates using a published reaction rate constant of m-xylene, 2.31 × 10-11 cm3 molec-1 sec-1 (9). Table 1 lists effective not true rate constants because they represent a complex coupling of chemistry and mass transfer (10–12). Their applicability depends on how well the conditions of our experiments reproduce those in the atmosphere. Our experiments feature particles with realistic composition exposed to atmospherically relevant oxidant concentrations over multihour time scales. Since heterogeneous oxidation rates can strongly depend on particle composition (11), this should help ensure our data are atmospherically relevant because the concentrations and gradients of species within our particles should be similar to those in atmospheric particles. However, the high particle concentrations used here bias partitioning toward the condensed phase relative to more dilute atmospheric conditions. Therefore, the carbon-number dependence shown in Figure 3d suggests that our data may systematically underestimate the effective rate constant for species that are semivolatile in the atmosphere but exist exclusively in the condensed phase under the conditions of these experiments. We did conduct one experiment at “low” concentrations, 250 µg m-3 of organic aerosol. Most of the target species were below detection limits in these samples, but the oxidation rate of cholestane was the same as that measured at much higher concentrations (bow-tie point in Figure 3b). However, across our entire range of experimental conditions cholestane exists almost exclusively in the condensed phase. The average mass median diameter in these experiments was about 300 nm, which is about 50% larger than fresh motor vehicle emissions (23). Decreasing particle size increases effective rate constants (16). Implications for Receptor Modeling. To illustrate the atmospheric significance of the measured rate constants, Figure 4a plots the calculated decay of norhopane over a one-week period, the likely range of ages of most particles in an urban area. The calculations assume a typical average summertime OH concentration, 1 × 106 molec cm-3, and use the kinetic data listed in Table 1. Our data indicate that more than half of the norhopane is oxidized within two days of emission under low RH 7954

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b

Quantified using an authentic

FIGURE 4. (a) Predicted decay of norhopane at average summertime OH concentrations for the range of kinetic data listed in Table 1. (b) Average summertime and wintertime organic carbon (OC) apportioned to motor vehicles by CMB in Pittsburgh. Summertime CMB results are presented as a function of mean aerosol age (traditional CMB model results corresponds to a mean age of zero). The wintertime CMB results are for the traditional model (no oxidation). conditions. At high RH between 25 and 75% of norhopane will be oxidized after one week. This supports the conclusion that photo-oxidation reduces summertime hopane concentrations in regional air masses (2). In arid locations, oxidation may even influence hopane concentrations of local emissions. The results of this study indicate that the atmospheric lifetime of hopanes and steranes depends strongly on RH. Daytime RH levels in most locations are bounded by our experimental conditions, but the RH dependence between these two limits is not known. Does the rate constant vary smoothly with RH or is there a critical value at which the chemistry is “turned off,” similar to deliquescence? Another important consideration is the diurnal patterns of OH and RH; peak OH levels occur at mid-day when RH levels are close to their minimum. Therefore, conditions that favor oxidation may occur even in relatively humid locations. For example, on an average summertime day in Pittsburgh, PA the RH levels are less than 40% for almost 3 h in the early afternoon when OH concentrations are high.

The large extents of oxidation shown in Figure 4a at atmospherically relevant timescales had important implications for receptor modeling studies, which use hopanes, steranes, and EC to apportion ambient organic aerosols to vehicle emissions. These studies assume that these compounds are chemically stable (1, 3). To illustrate the potential biases of photo-oxidation on source contribution estimates, chemical mass balance (CMB) analysis was performed on the Pittsburgh Air Quality Study molecular marker data set (3, 24). We use the best-estimate CMB model from Subramanian et al. (24), which apportions the ambient organic aerosol to seven source classes using 20 fitting species. In this model, hopanes and EC are the key species for fitting gasoline and diesel vehicle emissions (steranes are not fit by the model). Figure 4b shows that the traditional (no oxidation) CMB model apportions about half as much OC to vehicles in the summer than the winter. The major difference is the predicted contribution of gasoline vehicles, which is much lower in the summer than in the winter. This causes a pronounced seasonal shift in the gasoline-diesel split, with diesel vehicles dominant in the summer and gasoline vehicles dominant in the winter. CMB predicts this shift because of the seasonally varying hopanes-to-EC ratios; such a shift is unexpected given the seasonal patterns in vehicle activity (2, 3). Figure 4b illustrates the effects of hopanes oxidation on the summertime CMB results. Aging was simulated by oxidizing the hopanes in the gasoline and diesel vehicle source profiles assuming 1 × 106 molec cm-3 of OH and the upper bound of the reaction rate constant measured at high RH conditions (0.2 × 10-11 cm3 molec cm-1 sec-1). Using this upper bound seems reasonable since the RH in the eastern U.S. is typically much lower than 75% during the day. Figure 4b plots the CMB model results in terms of the mean age of the emissions. It is also useful to consider the results in terms of the fractional decay of hopanes, which is given by the curve labeled “CMB calc” in Figure 4a. As expected, oxidation causes the traditional CMB model to underestimate the total contribution of motor vehicles. For example, Figure 4b indicates that, if the mean age of the vehicle emissions in Pittsburgh is four days, then the traditional CMB model will underestimate the total concentration of vehicle emissions by about factor of 2, which brings the summer and wintertime CMB results into agreement. The actual age of vehicle emissions in Pittsburgh is not known, but about two-thirds of these emissions are associated with regional transport (24). Oxidation has different effects on the estimated contribution of gasoline versus diesel vehicles. Oxidation causes the traditional CMB model to underestimate the contribution of gasoline vehicle emissions. For example, Figure 4 indicates that oxidation of about one-third of the hopanes will cause the traditional CMB model to underestimate the contribution of gasoline vehicle emissions by a factor of 2. Therefore, oxidation likely explains why multiple molecular marker studies apportion little ambient particulate matter to gasoline vehicle emissions in the summertime (3, 25, 26). The gasoline estimates are so sensitive because they are based on the residual hopanes not attributed diesel (3). In comparison, the diesel estimates are relatively constant because they are largely determined by EC concentrations. Figure 4 highlights that oxidation of even as little as onethird of the hopanes can substantially alter CMB estimates for motor vehicle emissions. Our data suggest that this amount of oxidation likely occurs under typical summertime conditions in areas strongly influenced by regional transport. This amount of oxidation is also well within the uncertainty of transport modeling studies used to evaluate the atmospheric stability of molecular markers (1, 27). Given the focus

of policy makers on motor vehicle emissions, potential biases associated with oxidation of vehicle emission markers need to be accounted for when developing control strategies. Although oxidation represents a substantial challenge to linear receptor models, the highly source specific nature of molecular markers means that these compounds will remain an essential tool for source apportionment studies; however, future studies must consider both mixing of emissions and oxidation as first-order processes.

Acknowledgments This research was supported by the EPA STAR program through the National Center for Environmental Research (NCER) under grant R832162 and NSF under grant ATM0748402. This paper has not been subject to EPA′s required peer and policy review, and therefore does not necessarily reflect the views of the Agency. No official endorsement should be inferred.

Supporting Information Available Additional details on experimental methods. This material is available free of charge via the Internet at http:// pubs.acs.org.

Literature Cited (1) Schauer, J. J.; Rogge, W. F.; Hildemann, L. M.; Mazurek, M. A.; Cass, G. R. Source apportionment of airborne particulate matter using organic compounds as tracers. Atmos. Environ. 1996, 30 (22), 3837–3855. (2) Robinson, A. L.; Donahue, N. M.; Rogge, W. F. Photochemical oxidation and changes in molecular composition of organic aerosol in the regional context J. Geophys. Res., [Atmos.] 2006, 111, D03302 doi: 10.1029/2005JD006265. (3) Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F.; Robinson, A. L. Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal trends in ambient marker concentrations. Atmos. Environ. 2006, 40, 8002–8019. (4) Bertram, A. K.; Ivanov, A. V.; Hunter, M.; Molina, L. T.; Molina, M. J. The reaction probability of OH on organic surfaces of tropospheric interest. J. Phys. Chem. 2001, 105, 9415–9421. (5) Lambe, A. T.; Zhang, J.; Sage, A. M.; Donahue, N. M. Controlled OH radical production via ozone-alkene reactions for use in aerosol aging studies. Environ. Sci. Technol. 2007, 41, 2357– 2363. (6) Schauer, J. J.; Kleeman, M. J.; Cass, G. R.; Simoneit, B. R. T. Measurement of emissions from air pollution sources. 2. C-1 through C-30 organic compounds from medium duty diesel trucks. Environ. Sci. Techno. 1999, 33 (10), 1578–1587. (7) Sakurai, H.; Tobias, H. J.; Park, K.; Zarling, D.; Docherty, S.; Kittelson, D. B.; McMurry, P. H.; Ziemann, P. J. On-line measurements of diesel nanoparticle composition and volatility. Atmos. Environ. 2003, 37 (9-10), 1199–1210. (8) Ren, X.; Brune, W. H.; Mao, J. M., M. J., Lesher, R. L.; Simpas, J. B.; Metcalf, A. R.; Schwab, J. J.; Cai, C. L.; Y., Demerjian, K. L.; Felton, H. D.; Boynton, G.; Adams, A.; Perry, J.; He, Y.; Zhou, X.; Hou, J. Behavior of OH and HO2 in the winter atmosphere in New York City Atmos. Environ. 2006, 40, S252-S263. (9) Atkinson, R.; Arey, J. Atmospheric degradation of volatile organic compounds. Chem. Rev. 2003, 103 (12), 4605–4638. (10) Weitkamp, E. A.; Huff Hartz, K. E.; Sage, A. M.; Donahue, N. M.; Robinson, A. L. Laboratory measurements of the heterogeneous oxidation of condensed-phase organic molecular makers for meat cooking emissions. Environ. Sci. Technol. 2008, 42, 51175182. (11) Huff Hartz, K. E.; Weitkamp, E. A.; Sage, A. M.; Donahue, N. M.; Robinson, A. L. Laboratory measurements of the oxidation kinetics of organic aerosol mixtures using a relative rate constants approach J. Geophys. Res. 2007, 112, D04204, doi: 10.1029/2006JD007526. (12) Donahue, N. M.; Robinson, A. L.; Huff Hartz, K. E.; Sage, A. M.; Weitkamp, E. A. Competitive oxidation in atmospheric aerosols: The case for relative kineticsGeophys. Res. Lett. 2005, 32, L16805, doi: 10.1029/2005GL022893. (13) Grieshop, A. P.; Donahue, N. M.; Robinson, A. L. Is the gasparticle partitioning in alpha-pinene secondary organic aerosol VOL. 42, NO. 21, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

7955

(14) (15)

(16)

(17) (18)

(19)

(20) (21)

7956

reversible? Geophys. Res. Lett. 2007, 34, L14810, doi: 10.1029/ 2007GL029987. Molina,M. J.; Ivanov, A. V.; Trakhtenberg, S.; Molina, L. T. Atmospheric evolution of organic aerosol Geophys. Res. Lett. 2004, 31, L22104, doi: 10.1029/2004GL020910. Pathak, R. K.; Stanier, C. O.; Donahue, N. M.; Pandis, S. N. Ozonolysis of R-pinene at atmospherically relevant concentrations: Temperature dependence of aerosol mass fractions (yields), J. Geophys. Res. 2007, 112, D03201, doi: 10.1029/ 2006JD007436. Worsnop, D. R.; Morris, J. W.; Shi, Q.; Davidovits, P.; Kolb,C. E. A chemical kinetic model for reactive transformations of aerosol particles Geophys. Res. Lett. 2002, 29, 20, doi: 10.1029/ 2002GL015542. Koo, B. Y.; Ansari, A. S.; Pandis, S. N. Integrated approaches to modeling the organic and inorganic atmospheric aerosol components. Atmos. Environ. 2003, 37 (34), 4757–4768. Ng, N. L.; Kroll, J. H.; Chan, A. W. H.; Chhabra, P. S.; Flagan, R. C.; Seinfeld, J. H. Secondary organic aerosol formation from m-xylene, toluene, and benzene. Atmos. Chem. Phys. 2007, 7, 3909–3922. Weitkamp, E. A.; Sage, A. M.; Pierce, J. R.; Donahue, N. M.; Robinson, A. L. Organic aerosol formation from photochemical oxidation of diesel exhaust in a smog chamber. Environ. Sci. Technol. 2007, 41 (20), 6969–6975. Hearn, J. D.; Smith, G. D. A mixed-phase relative rates technique for measuring aerosol reaction kinetics, Geophys. Res. Lett. 2006, 33, 17, doi: 10.1029/2006GL026963. Pöschl, U.; Letzel, T.; Schauer, C.; Niessner, R. Interaction of ozone and water vapor with spark discharge soot aerosol

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 42, NO. 21, 2008

(22)

(23)

(24)

(25)

(26)

(27)

particles coated with benzo[a]pyrene: O3 and H2O adsorption, benzo[a]pyrene degradation, and atmospheric implications. J. Phys. Chem. A 2001, 105 (16), 4029–4041. Kamens, R. M.; Guo, Z.; Fulcher, J. N.; Bell, D. A. Influence of humidity, sunlight, and temperature on the daytime decay of polyaromatic hydrocarbons on atmospheric soot particles. Environ. Sci. Technol. 1988, 22 (1), 103–108. Kleeman, M. J.; Schauer, J. J.; Cass, G. R. Size and composition distribution of fine particulate matter emitted from motor vehicles. Environ. Sci. Technol. 2000, 34 (7), 1132–1142. Subramanian, R.; Donahue, N. M.; Bernardo-Bricker, A.; Rogge, W. F.; Robinson, A. L. Insights into the primary-secondary and regionallocal contributions to organic aerosol and PM2.5 mass in Pittsburgh, Pennsylvania. Atmos. Environ. 2007, 41 (35), 7414–7433. Zheng, M.; Cass, G. R.; Schauer, J. J.; Edgerton, E. S. Source apportionment of PM2.5 in the southeastern United States using solvent-extractable organic compounds as tracers. Environ. Sci. Technol. 2002, 36 (11), 2361–2371. Brook, J. R.; Graham, L.; Charland, J. P.; Cheng, Y.; Fan, X.; Lu, G.; Li, S. M.; Lillyman, C.; MacDonald, P.; Caravaggio, G.; MacPhee, J. A. Investigation of the motor vehicle exhaust contribution to primary fine particle organic carbon in urban air. Atmos. Environ. 2007, 41, 119–135. Bhave, P. V.; Pouliot, G. A.; Zheng, M. Diagnostic model evaluation for carbonaceous PM2.5 using organic markers measured in the southeastern U.S. Environ. Sci. Technol. 2007, 41, 1577–1583.

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