Environ. Sci. Technol. 2010, 44, 2029–2034
Secondary Organic Aerosol Formation from High-NOx Photo-Oxidation of Low Volatility Precursors: n-Alkanes ALBERT A. PRESTO, MARISSA A. MIRACOLO, NEIL M. DONAHUE,* AND ALLEN L. ROBINSON Center for Atmospheric Particle Studies, Carnegie Mellon University
Received December 7, 2009. Revised manuscript received January 28, 2010. Accepted February 4, 2010.
Smog chamber experiments were conducted to investigate secondary organic aerosol (SOA) formation from photo-oxidation of low-volatility precursors; n-alkanes were chosen as a model system. The experiments feature atmospherically relevant organic aerosol concentrations (COA). Under high-NOx conditions SOA yields increased with increasing carbon number (lower volatility) for n-decane, n-dodecane, npentadecane, and n-heptadecane, reaching a yield of 0.51 for heptadecane at a COA of 15.4 µg m-3. As with other photooxidation systems, aerosol yield increased with UV intensity. Due to the log-linear relationship between n-alkane carbon number and vapor pressure as well as a relatively consistent product distribution it was possible to develop an empirical parametrization for SOA yields for n-alkanes between C12 and C17. This parametrization was implemented using the volatility basis set framework and is designed for use in chemical transport models. For COA < 2 µg m-3, the SOA mass spectrum, as measured with an aerosol mass spectrometer, had a large contribution from m/z 44, indicative of highly oxygenated products. At higher COA, the mass spectrum was dominated by m/z 30, indicative of organic nitrates. The data support the conclusion that lower volatility organic vapors are important SOA precursors.
Introduction Recent research has indicated that low-volatility organic vapors are a potentially important source of ambient secondary organic aerosol (SOA) (1-5). In particular, the intermediate-volatility organic compounds (IVOCs) are an important class of precursors. IVOCs have saturation concentrations (C*) between 103-106 µg m-3, corresponding to C12-C20 n-alkanes (6, 7). IVOCs exist as vapors in the atmosphere. Many of the IVOC species emitted from anthropogenic sources are reduced hydrocarbons (8), while more oxygenated IVOCs can be formed from atmospheric oxidation. Diesel fuel, for example, is a complex mixture of saturated and aromatic hydrocarbons that fall primarily in the IVOC volatility window (9). Because of their low volatility, IVOCs are expected to have high SOA yields. Therefore, we expect that IVOCs could be a significant source of ambient SOA. * Corresponding author e-mail:
[email protected]. 10.1021/es903712r
2010 American Chemical Society
Published on Web 02/18/2010
Very little experimental work has been published on formation of SOA from low-volatility organics. Lim and Ziemann (2, 3) published SOA mass yields for n-alkanes at high organic aerosol loadings (COA J 1000 µg m-3; COA ) concentration of organic aerosol). Chan et al. (1) recently investigated SOA formation from naphthalene and substituted naphthalenes, which are aromatic IVOCs. At COA ) 10 µg m-3 under high-NOx conditions, Chan et al. observed SOA mass yields between 0.2-0.3. High SOA mass yields were also observed for the IVOC sesquiterpene longifolene under high-NOx conditions (10). The n-alkanes are a good model system for studying SOA formation from IVOCs. They are present in varying fractions in gasoline, diesel fuel, and lubricating oil and are emitted from vehicular and other combustion sources (8, 9, 11). Additionally, because much of the IVOC mass is present as an unresolved complex mixture (UCM) of cyclic and branched saturated hydrocarbons (8), studies of SOA formation from n-alkanes and other identified IVOC constituents (e.g., cycloalkanes) offer important insights into SOA formation from IVOC emissions as a whole. Traditional SOA models include, at best, a very limited treatment of SOA production from low-volatility organics (12); in these models SOA results primarily from the oxidation of VOCs such as single-ring aromatics or monoterpenes (12, 13). Such SOA models underpredict SOA concentrations in ambient (14, 15) and laboratory (16, 17) environments. Recent modeling studies have shown that including SOA production from IVOCs can help improve model-measurement agreement. For example, Dzepina et al. (18) updated the model used by Volkamer et al. (15) to simulate conditions found in Mexico City in 2003. Including low-volatility organics significantly increased predicted SOA concentrations, though the predicted ‘nontraditional’ IVOC-derived SOA was much less oxygenated than field observations. More comprehensive treatment of low-volatility organics also improved model performance throughout the eastern United States (5, 12, 19). While IVOCs are clearly important, extensive experimental work is required to develop quantitative representations of SOA formation from IVOCs that can describe both the amount of SOA formation and the SOA composition (i.e., oxidation state). With the n-alkanes we can systematically explore the effect of precursor volatility in a system where the chemical mechanisms (presumably) remain the same through the sequence. In this paper, we have examined the photooxidation of several n-alkanes under high-NOx conditions with atmospherically relevant organic aerosol concentrations. We present SOA yield measurements, along with a parametrization to predict SOA yields for n-alkanes that were not explicitly tested. To our knowledge this is the first report of SOA yields from n-alkanes at atmospherically relevant COA.
Experimental Section Experiments were conducted in a temperature-controlled 12-m3 Teflon smog chamber. All experiments were conducted at 295 K and 100 µg m-3 bins, the maximum COA tested would need to exceed 100 µg m-3. Finally, the fitting procedure used to constrain these yields includes an implicit assumption that the reaction product distribution remains constant during an experiment. That is almost certainly not true here because of multigenerational processing caused by the sustained OH exposure. Therefore, these fitting parameters only approximate the product volatility distribution near the midpoint of the experiment. Rather than fit the yield data for each of the alkanes separately, we have elected to develop a parametrization for the yield curves for the series of n-C12sn-C16. Additional carbons on an n-alkane backbone reduce vapor pressure by about a factor of 10 for 2 carbons (7); however, for large carbon numbers this should not directly change the reaction mechanism or the product distribution (23). Therefore, we expect that much like vapor pressure, the SOA yields for the series of n-alkanes would change log-linearly with carbon number. We modeled this by shifting the n-heptadecane Ri distribution above along the C* (volatility) axis. The treatment used here is similar to the temperature dependence of the volatility basis set discussed by Donahue et al. (26) For the n-alkanes in question, we shift C* from the reference case (n-C17) following eqs 1 and 2. Adjusting C* has the effect of shifting the curve in Figure 2b along the COA axis while preserving its shape. C*new )
C*ref b
(1)
vap # ) - log(Pvap)) ≈ f(log(Cref ) - log(C#)) b ) f(log(Pref
(2) Here, b is an empirically defined function determined by interpolating between the measured yield data for ndodecane and n-heptadecane. By definition, b ) 1 for n-heptadecane. The results of this yield paramaterization are shown in Table 1 and Figure 2a. In addition, Table S2 lists the yield values for the different n-alkanes mapped onto the standard C* bins of the volatility basis set (exact decades at 295 K) for ease of implementation in chemical transport models. The dashed lines in Figure 2a show that the parametrized yield curves for n-pentadecane and n-dodecane, based on the C17 data, accurately represent the measured data. Figure S2 (Supporting Information) shows the interpolated yield curves for other n-alkanes, n-C12sn-C16. VOL. 44, NO. 6, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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Were the reaction mechanisms identical for the series of n-alkanes, and if they proceeded to an equal extent for each precursor, we would expect log(b) to change by 0.5 per added carbon. Such a shift in log(b) would mirror the factor of 10 change in vapor pressure per 2 carbons in the molecule (7). This is the case between n-C12 and n-C15 (Figure S3, Supporting Information). However, above n-C15 log(b) drops off sharply. We believe this fall off occurs because the firstgeneration products of these larger n-alkanes partition substantially into the condensed phase, delaying their subsequent oxidation and thus decreasing the SOA yields. While the intrinsic gas-phase mechanism does not change, the chemistry that actually occurs inside the chamber does because of differences in gas-particle partitioning. This is an extension of the phenomenon we have already reported comparing n-C17 to n-C25 photo-oxidation (27). Aerosol Composition. Aerosol composition was monitored using a quadrupole aerosol mass spectrometer (QAMS, Aerodyne Research, Inc.) (28, 29). We used the fragmentation table of Allan et al. (30) to deconvolve the mass spectrum and the method of Grieshop et al. (31) to determine aerosol contributions to the signal at m/z ) 28. We discuss the contribution of three key fragments to the SOA as a function of COA. These fragments were m/z ) 30, 44, and 55 (f30, f44, f55). The evidence indicates that the m/z ) 30 (NO+) signal arises solely from organic, rather than inorganic, nitrates. This is consistent with our previous treatment of laboratorygenerated SOA (27). Nitric acid is produced in these experiments from the OH+NO2 reaction; however, there is no base, such as NH3, to form inorganic nitrate. The formation of inorganic nitrate such as NH4NO3 would cause the NH4:SO4 mass ratio observed by the AMS to increase during an experiment. In these experiments, the NH4:SO4 ratio was constant, consistent with minimal formation of inorganic nitrate. The m/z ) 44 signal is dominated by CO2+, which is an important indicator of oxygen content in organic aerosol (32). The m/z ) 55 signal (C4H7+ and C3H3O+) appears to be an important fragment in the AMS that is present in both reduced, hydrocarbon-like aerosol (28) and oxidized ambient aerosol (33). For the n-alkane SOA studied here and previously (27), m/z ) 55 is the most abundant fragment ion heavier than m/z ) 44. Figure 3 shows f44, f30, and f55 for n-pentadecane SOA as a function of COA. The trends presented in Figure 3 were also observed for the other n-alkanes tested here (see Figures S4-S6, Supporting Information). Figure 3 shows that f44 is a strong function of COA, with more oxygenated aerosol forming at lower COA. This phenomenon has been observed previously and is attributed to the partitioning of less oxygenated species to the aerosol phase with increasing COA (27, 34). The high f44 (>10%) observed at the lowest COA is consistent with our previous results for n-heptadecane (27) and further confirmation that under high-NOx and low-COA conditions IVOCs are capable of generating highly oxygenated organic aerosol on atmospherically relevant time scales. For each of the experiments shown in Figure 3, f44 reaches a minimum at a COA of ∼3 µg m-3 before rising slightly with COA. For any given experiment, the COA axis is essentially a time axis, as the wall-loss-corrected organic aerosol concentration either rises or remains constant as an experiment progresses (Figure 1). The slight rise in f44 with increasing COA > 3 µg m-3 is likely the result of multigenerational chemistry producing progressively more oxidized products in the later stages of the experiment. Consistent with the trends in the scaling parameter b discussed above, f44 generally decreases with carbon number at a given COA, suggesting that the SOA produced from larger n-alkanes is somewhat less oxidized. 2032
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FIGURE 3. Q-AMS data for f44 (mass fraction of m/z ) 44 in the organic mass spectrum), f30, and f55 as a function of COA for SOA formed from photo-oxidation of n-pentadecane. Points with error bars (1σ) are averages over several AMS scans to reduce clutter. Points without error bars represent single AMS scans at 5-min resolution. The numbers in parentheses in the legend are the jNO2 values. For COA > ∼2 µg m-3, m/z ) 30 is the most abundant fragment ion in the organic mass spectrum. This is consistent with the findings of Lim and Ziemann (2, 35), who determined that alkane-derived SOA is dominated by nitrate-containing species. Our previous study of n-heptadecane SOA showed only a very small contribution of m/z ) 30, whereas for n-pentadecane f30 is always large. The cause for the decrease in f30 for COA > 2 µg m-3 is not obvious. The multigenerational chemistry that contributes to the rise in f44 might consume organic nitrates, thereby reducing f30, but if this is the case the exchange is not one-for-one. Also, the decrease in f30 does not appear to be the result of relatively reduced species partitioning into the SOA, as both f55 and f57 (not shown) remain constant as COA rises. UV intensity does not appear to affect aerosol composition as strongly as it affects aerosol yield. In all three panels of Figure 3, the SOA formed in the experiment with high UV intensity had mass spectra similar to the two experiments with lower UV intensity. The conclusions drawn from Figure 3 are confirmed by analysis of the full mass spectra from the high- and low-UV experiments. One might expect higher SOA yield to correspond to more oxygenated products from increased radical cycling and multigenerational chemistry; however, the mass spectrum does not bear this out. Atmospheric Implications. The SOA yield data presented here are further evidence that oxidation of low-volatility organic vapors is a potentially important source of ambient SOA. While IVOCs only make up a few percent of the total hydrocarbon budget, their mass emissions are almost certainly larger than POA emissions (5, 12). The n-alkanes are a small fraction of the IVOC emissions, which are dominated by UCM (8), but they form an informative homologous series to explore systematic changes in SOA formation through the range of IVOCs. For diesel exhaust, the ratio of IVOC UCM to n-alkanes (roughly corresponding
to the “semi-volatile” species in ref 8) is >10. Because branched hydrocarbons have lower SOA yields than straight chain or cyclic alkanes (3) and because the SOA mass yields of branched hydrocarbons depend in part on the number of branch points, it is not straightforward to convert the SOA yields presented here to equivalent SOA mass yields for “UCM-like” mixtures. However, by investigating SOA production from well-defined precursors s n-alkanes, cyclic alkanes, etc. s we can place constraints on the effective UCM SOA mass yield. The high SOA yields observed here and elsewhere (1-3) for IVOCs imply that low-volatility precursors may be the dominant source of SOA from combustion systems. This represents a significant departure from traditional SOA models, which assign most of the anthropogenic SOA mass to oxidation products of single-ring aromatics (13). These VOCs have large emissions but low SOA yields (22, 36), especially under the high-NOx conditions typical of urban areas. The UV dependence of the SOA yield is puzzling. OH concentrations are higher during the high-UV experiments, suggesting that there might be more generations of oxidation producing more SOA. More photochemical cycling would imply more oxygenated SOA, but this is not confirmed by the AMS data. One can imagine two limiting cases regarding increased OH concentrations. If the OH+alkane reaction is rate limiting, adding OH will increase the fractional consumption of the alkane but will have little effect on the total extent of reaction. This would produce more SOA with similar composition as the low-UV (or low-OH) case, and the net impact would be to move up and to the right along the yield curve. If the reactions of OH and gas-phase products are rate limiting, adding OH to the system would produce more SOA mass and higher f44 in the AMS. We observe something of a hybrid case s more mass (higher yield) but a constant f44. The results presented here are consistent with recent results from this laboratory for the photo-oxidation of diesel fuel and motor oil (4). However, the systematic variation of SOA mass yields and properties through the n-alkane sequence will greatly assist development of systematic parametrizations of SOA formation and aging from IVOCs. Oxidation of diesel fuel, a complex mixture of IVOCs, produced a significant amount of SOA. Oxidation of motor oil, a mixture of SVOCs, led to SOA production that was balanced by evaporation of POA. The net production of OA from the SVOC system was small at high-NOx conditions. For both diesel fuel and motor oil, SOA production was greater under high-NOx conditions. At low COA, the photo-oxidation of IVOCs is a source of oxygenated OA (27). However, the relationship between f44 and COA is steep, and in many locations (COA > ∼2 µg m-3) IVOC-derived SOA will initially be less oxidized than the highly oxygenated OOA factor observed with aerosol mass spectrometers throughout the northern hemisphere (37). However, Figure 3 illustrates that multiple generations of chemistry may eventually produce highly oxygenated species. Similar behavior has recently been observed for the photooxidation of R-pinene. The slow rise in f44 in experimental systems s a few percent over several hours (38) s further indicates that OA constantly evolves over long time scales, on the order of days, and that short chamber experiments likely do not reproduce the complete transformation from emissions to OOA.
Acknowledgments This work was supported by the EPA STAR program through the National Center for Environmental Research (NCER) under grant R833748. This paper has not been subjected 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 Tables S1 and S2 and Figures S1-S6. This material is available free of charge via the Internet at http://pubs.acs.org.
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