Source specificity and atmospheric processing of airborne PAHs: Implications for source apportionment

Atmospheric Environment 42 (2008) 8139–8149

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Review

Source specificity and atmospheric processing of airborne PAHs: Implications for source apportionment Elisabeth Galarneau* Air Quality Research Division, Environment Canada, 4905 Dufferin Street, Toronto, ON M3H 5T4, Canada

a r t i c l e i n f o

a b s t r a c t

Article history: Received 12 May 2008 Received in revised form 18 July 2008 Accepted 18 July 2008

Polycyclic aromatic hydrocarbons (PAHs) are emitted to the atmosphere from a variety of sources. Though classified as persistent organic pollutants (POPs), their levels are affected by atmospheric removal and transformation processes. Efforts have been made to conduct receptor modelling of PAHs for over 25 years, whereby ambient measurement data are manipulated to compare relative amounts of compounds to those expected in relevant sources. These relative amounts, which can be based on particle or total (gas þ particle) concentrations, are typically presented as diagnostic ratios of two isomeric species or as profiles representing several species at once. This review examines two of the assumptions necessary for conventional ratio- or profilebased source apportionment methods to be valid. The term ‘‘conventional’’ refers to the direct comparison of source and ambient data without accounting for alterations that occur in the atmosphere. These assumptions, namely source specificity and species conservation, do not generally hold for PAHs as a class. Though concerns over conventional source apportionment have been expressed for some time, studies continue to appear in the literature that do not account for its limitations. In an effort to contribute to the reversal of this trend, a set of conditions under which conventional source apportionment may be valid is presented herein. Research relating to emissions’ measurement analysis, numerical modelling and atmospheric processing is also suggested. Crown Copyright Ó 2008 Published by Elsevier Ltd. All rights reserved.

Keywords: Polycyclic aromatic hydrocarbons (PAHs) Diagnostic ratios Source apportionment Atmospheric processes Emissions

1. Introduction Source apportionment is an exercise crucial to the determination of control strategies for environmental pollutants. Beginning with the work of Daisey et al. (1979), numerous studies have used diagnostic ratios of PAH concentrations (typically isomers) to infer sources of airborne particulate PAH content (Neilsen, 1996; Dickhut et al., 2000; Kavouras et al., 2001; Yassaa et al., 2001; Park et al., 2002; Vasconcellos et al., 2003; Guo et al., 2003; Sienra et al., 2005; Bourotte et al., 2005; Dallarosa et al., 2005; Fang et al., 2006; Ding et al., 2007; Esen et al., 2008). The concept behind the diagnostic ratio has often been

* Tel.: þ1 416 739 4431; fax: þ1 416 739 4281. E-mail address: [email protected]

extended to profiles or signatures for which the relative amounts of multiple species are examined using multivariate methods (Harrison et al., 1996; Schauer et al., 1996; Dickhut et al., 2000; Guo et al., 2003; Bourotte et al., 2005; Dallarosa et al., 2005; Robinson et al., 2006; Wan et al., 2006; Lee and Kim, 2007). A limited number of studies have examined total (gas þ particle) concentrations (Simcik et al., 1999; Bi et al., 2003; Larsen and Baker, 2003; Ravindra et al., 2006; Battelle, 2007; Esen et al., 2008) in an attempt to account for the semivolatility of lower molecular weight PAH species. The validity of these approaches rests on many assumptions (Watson, 1984), two of which may be particularly problematic for PAHs. Firstly, each suspected source or source type is assumed to be associated with relative proportions of the species in question that are unique. Secondly, the relative proportions of the species in question

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E. Galarneau / Atmospheric Environment 42 (2008) 8139–8149

are assumed to be conserved between each emission source and the downwind point of measurement. Herein it is argued that these assumptions only hold for PAHs under a limited set of conditions. As such, the approach of using PAH ratios and/or profiles as if they are unique and conserved should be limited to those cases where the validity of the assumptions can be demonstrated. Though concerns over conventional source apportionment have been expressed for some time, studies continue to appear in the literature that do not account for its limitations (Bourotte et al., 2005; Dallarosa et al., 2005; Ravindra et al., 2006; Ding et al., 2007; Lee and Kim, 2007; Battelle, 2007; Ravindra et al., 2008a,b; Esen et al., 2008). Similar concerns have recently been expressed for multimedia fate studies (Zhang et al., 2005) and source apportionment of PAHs in sewage sludges (Katsoyiannis et al., 2007). 2. PAH source signatures are not unique by source type When using diagnostic ratios or profiles to apportion atmospheric PAH sources, studies typically examine broad categories of potential source types. Combustion of coal, oil, natural gas and wood as well as coke oven emissions and vehicle exhaust (sometimes separated into gasoline and diesel components) have been used in atmospheric studies (Harrison et al., 1996; Schauer et al., 1996; Simcik et al., 1999; Dickhut et al., 2000; Vasconcellos et al., 2003; Guo et al., 2003; Larsen and Baker, 2003; Sienra et al., 2005; Fang et al., 2006; Ding et al., 2007; Lee and Kim, 2007; Battelle, 2007; Ravindra et al., 2008a,b; Esen et al., 2008). However, PAH isomer ratios show substantial intrasource variability and intersource similarity, especially when grouped in coarse categories such as those noted above. For example, a recent review (Yunker et al., 2002) lists ratios for benz[a]anthracene (BaA) and chrysene (CHRY), in the form BaA/(BaA þ CHRY), of 0.18–0.49 for combustion of different types of coal and 0.12–0.44 for oil combustion, and concludes that sources are difficult to distinguish even when several ratios are examined together. The development of a PAH emissions inventory for southern Canada and the USA (Galarneau et al., 2007) allowed for the examination of several hundred sourcespecific emission factors based on compilations produced by US EPA (1998, 2003, 2004). The majority of the latter factors were reported as the sum of gas and particle emissions, and the interested reader is referred to Galarneau et al. (2007) for more detailed information on the calculation of these factors. A subset of factors for which relevant data were available in the primary sources (US EPA, 1998, 2003, 2004) was collated in diagnostic ratio form for four commonly examined isomer pairs: phenanthrene (PHEN) and anthracene (ANTH), fluoranthene (FLRT) and pyrene (PYR), benz[a]anthracene (BaA) and chrysene (CHRY), and indeno[1,2,3-cd]pyrene (IP) and benzo[ghi]perylene (BghiP). Collated data are presented in graphical form in Fig. 1 and summary statistics are listed in Table 1. In both presentations of the data, it can be seen that there is

substantial overlap between commonly reported ratios associated with different types of PAH emissions. At first glance, information presented in Fig. 1 suggests that some source types stand out from the others. For example, diesel vehicle ratios appear to be unique compared to other source types. However, as listed in Table 1, the diesel vehicle emissions’ data in the consulted compilations are relatively sparse and the corresponding confidence intervals on the mean ratios are large. Furthermore, conventional source apportionment studies generally seek to discriminate the contributions of several sources and every one of them must be unique to do so. Intrasource variability and intersource similarity suggest that PAH ratios are not specific to generic source types. Though the ratios of relevant isomers may not be unique, the ratios of non-isomeric species may well be. Unfortunately, the data in the consulted compilations include a mixture of particle and total (gas þ particle) concentrations along with a substantial subset of data for which phase is unspecified. Isomers can be compared because their volatilities and resulting particle/gas distributions are expected to be similar (Bidleman et al., 1986; Pankow, 1987) and the ratio of particulate concentrations should be close to that of total concentrations. This is not true for species of different volatilities. Data with single known phase were not available in sufficient quantity to allow for a comparison of profiles analogous to that conducted for ratios. Nonetheless, the results of the isomer ratio collation suggest that substantial variability would also be observed for the relative amounts of non-isomeric species. Because of the large variability in reported isomer ratios within each source type, it is unlikely that any single ratio or profile selected from the literature will be representative of a source in a different part of the world emitting under different conditions. Even if emissions data from a particular source are known to contribute to a downwind location’s ambient atmospheric PAH concentration, the variability of the source must be incorporated in any quantitative source apportionment exercise if valid results are to be produced. The load conditions under which an engine is tested have been shown to produce different PAH diagnostic ratios for the same vehicle burning the same fuel (Lim et al., 2007). Sources other than vehicle emissions are more difficult to test in such a rigorous and controlled manner. However, there is no reason to believe that variations in feedstock, combustion temperature and pollution control equipment will not cause variations in relative emissions of major PAH compounds. 3. Relative PAH concentrations are not conserved in the atmosphere PAHs are semivolatile and partition between the gas and particle phases of ambient air (Yamasaki et al., 1982). The vast majority of source apportionment studies examining PAHs limit their analysis to particle-phase compounds whereas studies examining the sum of gas and particle concentrations are relatively few. As discussed below, either representation of PAH concentrations leads to relative amount conservation under only limited conditions.

E. Galarneau / Atmospheric Environment 42 (2008) 8139–8149

a

b

MW 178: PHEN / (PHEN + ANTH)

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MW 202: FLRT / (FLRT + PYR)

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Coal Combustion

c

Diesel Vehicles

Gasoline Vehicles

Natural Gas Oil Vegetation Wood Combustion Combustion Combustion Combustion

Coal Combustion

d

MW 228: BaA / (BaA + CHRY)

Diesel Vehicles

Gasoline Vehicles

Natural Gas Oil Vegetation Wood Combustion Combustion Combustion Combustion

MW 276: IP / (IP + BghiP)

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Coal Combustion

Diesel Vehicles

Gasoline Vehicles

Natural Gas Oil Vegetation Wood Combustion Combustion Combustion Combustion

Coal Combustion

Diesel Vehicles

Gasoline Vehicles

Natural Gas Oil Vegetation Wood Combustion Combustion Combustion Combustion

Fig. 1. ‘‘Diagnostic ratios’’ for a variety of source categories for (a) phenanthrene (PHEN) and anthracene (ANTH), (b) fluoranthene (FLRT) and pyrene (PYR), (c) benz[a]anthracene (BaA) and chrysene (CHRY), and (d) indeno[1,2,3-cd]pyrene (IP) and benzo[ghi]perylene (BghiP). Boxes represent the 25th, 50th and 75th percentile values. Whiskers represent minimum and maximum values. Calculated from emission factors for which both isomers are reported in US EPA (1998, 2003, 2004).

downwind regions if the only processes acting on the air are related to vapour pressure. Such processes include particle/gas partitioning (Bidleman et al., 1986; Pankow, 1987), particle scavenging by precipitation and dry particle deposition. The magnitudes of the latter two removal

Some atmospheric fate processes relevant to PAHs are related to volatility as represented by sub-cooled liquid saturated vapour pressure (p0L ). PAH isomers have similar values of p0L (Offenberg and Baker, 1999) and, as such, their ratios should remain intact between sources and

Table 1 Summary statistics for compiled diagnostic ratiosa Ratio

Statisticb

Source type Coal combustion

Diesel vehicles

Gasoline vehicles

Natural gas combustion

Oil combustion

Vegetation combustion

Wood combustion

PHEN/(PHEN þ ANTH)

Mean s.d. N 95% W1/2

0.85 0.11 12 0.07

0.73 0.18 2 1.60

0.77 0.10 7 0.10

0.88 0.13 12 0.08

0.89 0.12 10 0.09

NA NA 0 NA

0.84 0.16 15 0.09

FLRT/FLRT þ PYR

Mean s.d. N 95% W1/2

0.57 0.21 14 0.12

0.40 0.05 2 0.49

0.52 0.13 7 0.13

0.49 0.18 20 0.08

0.52 0.20 12 0.13

0.49 0.07 5 0.09

0.51 0.16 24 0.07

BaA/BaA þ CHRY

Mean s.d. N 95% W1/2

0.46 0.19 14 0.11

0.65 0.28 2 2.50

0.50 0.10 6 0.11

0.39 0.15 12 0.10

0.50 0.22 15 0.12

NA NA 0 NA

0.59 0.25 10 0.18

IP/IP þ BghiP

Mean s.d. N 95% W1/2

0.48 0.29 11 0.19

0.19 0.13 2 1.18

0.32 0.11 5 0.13

0.32 0.17 8 0.14

0.36 0.14 6 0.15

0.35 0.04 3 0.11

0.42 0.18 9 0.14

a

Diagnostic ratios compiled for emission factors with both relevant isomers reported in US EPA (1998, 2003, 2004). s.d. ¼ standard deviation, N ¼ number of emission factors, 95% W1/2 ¼ half-width of the 95% confidence interval about the mean; the limits of the confidence interval are calculated as the mean  95% W1/2. b

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processes vary with particle size (Slinn, 1984, 1982) which, in turn, tends to vary with p0L (Offenberg and Baker, 1999). The octanol–air partition coefficient, KOA, has been proposed as an alternative volatility measure for semivolatile organic compounds in the atmosphere (Finizio et al., 1997). However, KOA and p0L values are highly correlated for PAHs (Xiao and Wania, 2003) and, as such, they are interchangeable in the arguments below. Some physicochemical properties do not vary uniformly with p0L . These include OH reaction rates for gas-phase PAHs, kOH (Brubaker and Hites, 1998), and air–water partition coefficients, KAW (Bamford et al., 1999), that affect gas-phase PAH scavenging by precipitation (Ligocki et al., 1985; Dickhut and Gustafson, 1995) and diffusive exchange with water bodies (Schwarzenbach et al., 1993). The simple numerical examples that follow illustrate the effects that atmospheric processing can have on the relative amounts of PAHs measured in air. Values typical of those measured by the Integrated Atmospheric Deposition Network (IADN) have been used for PAH and total suspended particle (TSP) concentrations in air (Galarneau et al., 2006) and for PAH concentrations in lake water (M. Neilson, Canada Centre for Inland Waters, Environment Canada, personal communication, 1999). Particle/gas partitioning is represented by a partition coefficient, Kp, which is the ratio of the PAH concentration associated with particles to that in the gas phase. The relationship between Kp and p0L

log Kp ¼ 0:8 log p0L  5:0

(1)

where Kp is in m3 mg1 and p0L is in Pa, is typical of those listed in a survey of the relevant literature (Bidleman and Harner, 2000). Sub-cooled liquid saturation vapour pressures, p0L , were taken from Offenberg and Baker (1999). For purposes of simplicity, it is assumed that equilibration between the particle and gas phases is relatively rapid. High-volume filter/sorbent sampling is thought to suffer from sampling artefacts caused by the rapid exchange of PAH mass between particle-loaded filters and the incoming gas phase (Cotham and Bidleman, 1995; Harner and Bidleman, 1998; Galarneau and Bidleman, 2006). In chamber experiments, uptake of gas-phase deuterated PAHs by particles has been seen to occur within minutes at warm temperatures (Kamens et al., 1995). At sub-freezing temperatures, however, the desorption of native PAHs from combustion particles was estimated to take several hours (Kamens et al., 1995). It is assumed in the following discussion that temperatures are warm enough to allow for mass transfer that is rapid relative to sample duration if particle/gas equilibrium is perturbed. 3.1. Reactivity The need to account for the chemical and photolytic reactivities of PAHs in source apportionment exercises has been known for some time. Starting with Duval and Friedlander (1982), several studies followed suit noting that reactivity was an important consideration (Schauer et al., 1996; Pistikopoulos et al., 1990a,b; Li and Kamens, 1993; Venkataraman and Friedlander, 1994). These studies

have applied correction factors to account for reactive losses or have limited the PAH species examined to those considered relatively unreactive. The reactivities of particulate PAHs are still under investigation. Numerous studies have found differences in the relative decay of particulate isomers (Lane and Katz, 1977; Butler and Crossley, 1981; Behymer and Hites, 1985; Pitts et al., 1986; Kamens et al., 1988; Esteve et al., 2004; Perraudin et al., 2005) and these appear to depend on the composition of the atmospheric particles to which the PAHs are bound (Behymer and Hites, 1988; McDow et al., 1994; McDow et al., 1995; Esteve et al., 2006). As such, the ratio of two particulate PAH species will be modified directly in proportion to their relative reactivities with respect to gasphase reactants and/or solar radiation. The effect of particlephase degradation on common particulate PAH diagnostic ratios such as that involving IP and BghiP cannot be presented with certainty at this time. The rate constant for the reaction between NO2 and IP sorbed on silica particles is an order of magnitude lower than that for BghiP (Perraudin et al., 2005) yet constants measured on more representative atmospheric particles such as SRM 1650a (diesel soot) show similar magnitudes for reaction with OH radicals (Esteve et al., 2006). Future results from this active research area will be useful in determining the importance of particlephase reactivity to airborne PAH source apportionment. Gas-phase reactivity also affects observed isomer ratios. Let us assume that an emission source releases 8 ng m3 of phenanthrene (PHEN) and 2 ng m3 of anthracene (ANTH) into an air parcel that holds 50 mg m3 of total suspended particles (TSP). Due to similar values of p0L , the isomer ratio of PHEN/(PHEN þ ANTH) will be 0.80 whether it is calculated with respect to particle or total (gas þ particle) concentrations. If we assume that the air compartment is subsequently exposed to a typical daytime OH radical concentration of 5  106 cm3 (Seinfeld and Pandis, 1998) for 15 min and that the gas-phase PAHs are degraded by OH radical attack according to Brubaker and Hites (1998), 12% of the gas-phase PHEN and 86% of the gas-phase ANTH will be degraded. Reequilibrating the particle/gas distributions of the new PHEN and ANTH concentrations at 290 K leads to a particulate PHEN/(PHEN þ ANTH) ratio of 0.96. In this case, the reequilibrated ratio is the same if total (gas þ particle) PHEN and ANTH concentrations are used rather than particulate concentrations alone. Such an increase (0.16 ratio units) in only 15 min demonstrates that PAH ratios will not necessarily be conserved between emission sources and downwind air. 3.2. Air–water exchange A lack of conservation of relative species concentrations can also occur if PAHs are exposed to precipitation or if an air mass spends time over water sufficient for diffusive air– water exchange to occur. Air–water partition coefficients (KAW, also known as dimensionless Henry’s law constants) can differ substantially between isomers and affect the pool of gas-phase compound which, once redistributed to atmospheric particles, affect the particulate isomer ratio. The equilibrium air–water partition coefficient, KAW, for benz[a]anthracene (BaA) is over three times higher than that of chrysene (CHRY) at 290 K (Bamford et al., 1999).

E. Galarneau / Atmospheric Environment 42 (2008) 8139–8149

3.2.1. Gas scavenging by precipitation Gas-phase scavenging of PAHs is thought to be proportional to KAW (Ligocki et al., 1985; Dickhut and Gustafson, 1995) and, as such, a higher fraction of gas-phase CHRY should be depleted during a rain event than gas-phase BaA. However, sample calculations show that this effect is small. If a 1 m2 land area receives a moderately heavy rainfall at 10 mm h1 for 60 min, the total amount of liquid water deposited to the land is 0.01 m3 (1 h  10 mm3 mm2 h1 1 m/1000 mm  1 m2). Before precipitation began, fresh emissions of BaA and CHRY were uniformly mixed to a total air concentration of 1 ng m3 each up to a cloud height of 2000 m at 290 K. The particulate BaA/ (BaA þ CHRY) ratio was initially 0.49. The latter value is not exactly 0.5 due to the small difference in p0L for the two isomers. Assuming that gas-phase PAHs equilibrate rapidly with falling raindrops (Simcik, 2004), the change in the BaA/(BaA þ CHRY) ratio increases as the fraction of TSP mass scavenged from the air increases. For particulate PAH concentrations, the post-rain ratio would range from 0.497 to 0.502 for particle removals of 0–99%, respectively. The total (gas þ particle) ratio is slightly more sensitive and would range from 0.507 to 0.520 under the same conditions. To two decimal places, these changes are barely detectable. Given that the difference in KAW values for isomers with appreciable gas-phase content in the atmosphere is largest for the BaA and CHRY pair (Bamford et al., 1999), the effect of rain on the relative amounts of airborne PAH isomers appears negligible. The same is not necessarily true for the precipitation scavenging of multiple PAH species having different particle size distributions. This is discussed later in the Section 3.4.1. 3.2.2. Diffusive air–water gas exchange Diffusive exchange between air and underlying water bodies is also affected by KAW. Typical BaA and CHRY concentrations of 0.1 ng L1 in water combined with the initial air concentrations and KAW values used in the precipitation example above lead to water–air fugacity ratios of 0.04 and 0.01, respectively, at 290 K. These fugacity ratios represent a strong tendency toward net gas-phase deposition from air to water, a result which has been observed consistently for PAHs in the Laurentian Great Lakes (Hoff et al., 1996; Hillery et al., 1998; Galarneau et al., 2000; Buehler et al., 2002; Blanchard et al., 2004). Using established mass transfer calculation methods (Schwarzenbach et al., 1993; Galarneau et al., 2000; Reid et al., 1987; see Supplementary data), fluxes from air to water at 290 K are 9.18 and 12.8 ng m2 h1 for BaA and CHRY, respectively. Ridal et al. (1997) examined the effect of mixing height from 0 to 150 m on the air–water gas exchange of a-HCH in Lake Ontario. This range of mixing heights is consistent with a surface atmospheric layer that is w10% of the depth of the planetary boundary layer which, in turn, can vary in depth from 50 to 3000 m (Garratt, 1992). If an air parcel laden with BaA and CHRY crosses Lake Ontario (85 km, US EPA and Environment Canada, 2007) at a wind speed of 5 m s1 (Ridal et al., 1997), appreciable changes in the BaA/(BaA þ CHRY) ratio can be observed for shallow (< w200 m) atmospheric mixing heights as shown in Fig. 2. The effect is seen whether

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particle or total (gas þ particle) concentration ratios are examined. As such, modifications to diagnostic ratios can occur for common regimes of atmospheric stability and over-water transit times. The latter considerations can be extended directly from diagnostic ratios to profiles involving multiple species since both examine relative amounts of PAHs in air. However, profiles are vulnerable to an additional set of alterations due to the fact that species of different volatilities are examined. Atmospheric fate processes that are related to p0L such as particle/gas partitioning, particlephase precipitation scavenging and particle dry deposition can occur and affect the relative concentrations of the PAH set as a whole. 3.3. Particle/gas partitioning Let us assume a hypothetical emission of 12 commonly measured PAHs with appreciable particulate content: PHEN, ANTH, FLRT, PYR, BaA, CHRY, IP and BghiP (defined earlier) along with benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP) and dibenz[a,h]anthracene (dBahA). The emission leads to an ambient particulate concentration of 1 ng m3 for each PAH and the air also contains 50 mg m3 of TSP. Though idealized for simplicity, this situation is not unrealistic. Long-term systematic measurements through IADN have shown that particulate PAHs tend to exist at concentrations of roughly the same magnitude whereas gas-phase concentrations show large interspecies differences (Galarneau et al., 2006; Sun et al., 2006). The initial temperature of the air parcel is 290 K but later falls to 285 K. The normalized particulate PAH profiles at the two temperatures look substantially different from one another as shown in Fig. 3. Given the difference between the profiles at these two temperatures and the fact that such a temperature range is commonly observed in the atmosphere, the use of profiles will not produce accurate results for source apportionment of airborne particulate PAHs unless temperature and TSP content (and sorption capacity) remain constant between sources and downwind air. Temperature changes acting alone will not affect profiles of total (gas þ particle) concentrations. 3.4. Particle deposition Particle scavenging by precipitation and dry particle deposition will affect the relative amounts of airborne PAHs since the rates of these processes are related to particle size (Slinn, 1982, 1984). Particulate PAHs tend to be distributed across the particle size spectrum in relation to their molecular weights, with lower molecular weight species typically associated with larger particles in ambient air (Van Vaeck and Van Cauwenberghe, 1978; Pistikopoulos et al., 1990a, Venkataraman et al., 1994; Poster et al., 1995; Allen et al., 1996; Kiss et al., 1998; Offenberg and Baker, 1999; Kaupp and McLachlan, 2000; Bae et al., 2002). p0L tends to decrease with increasing molecular weight, and logarithmic relationships between the mass median

E. Galarneau / Atmospheric Environment 42 (2008) 8139–8149

Diagnostic Ratio, BaA / (BaA + CHRY)

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0.59 0.58 Particle

Gas + Particle

0.57 0.56 0.55 0.54 0.53 0.52 0.51 0.50 0.49 100

150

200

250

300

350

400

450

500

Mixing Height (m) Fig. 2. Diagnostic ratio for BaA and CHRY as a function of atmospheric mixing height after crossing Lake Ontario. Wind speed ¼ 5 m s1, distance ¼ 85 km (US EPA and Environment Canada, 2007), temperature ¼ 290 K. Initial ratio is 0.49 for particle concentrations and 0.50 for gas þ particle concentrations.

diameters (mmd) of particulate PAHs and p0L have been observed (Offenberg and Baker, 1999). 3.4.1. Particle precipitation scavenging The effect of particle precipitation scavenging is examined in the following example. All particle mass is assumed to fall within the size bounds used by AURAMS, Environment Canada’s regional air quality model, which has 12 particle diameter (Dp) bins of equal logarithmic width (Dp,upper/Dp,lower ¼ 2) ranging from 0.01 to 40.96 mm (Gong et al., 2006). Let us assume a relationship between mmd and p0L that is identical to that observed at South Haven, Michigan (Offenberg and Baker, 1999), and a geometric standard deviation on the particle size distribution of 4.2 for all species (see the Chicago data in Table 1 of Offenberg and Baker, 1999). If we also assume the same precipitation intensity and duration as in the gas-scavenging example above and apply the size-dependent particle scavenging

coefficients developed by Andronache (2003, Fig. 2a therein), the post-rain particle size distributions are such that almost all of the mass in size bins 9 þ (Dp > 2.5 mm) has been removed. Two representative PAHs of different volatilities, PHEN and BghiP, are affected very differently (Fig. SD1 of the Supplementary data). The mass of BghiP is concentrated in the range of particles for which precipitation scavenging is relatively inefficient (the so-called Greenfield gap). Particulate PHEN, which began with a larger fraction of its mass in the range coarser than the Greenfield gap, is therefore more affected by the rainfall than that of relatively involatile BghiP. The resulting normalized particulate PAH profiles are shown in Fig. 4. The initially uniform concentration distribution (identical to that in Fig. 3 at 290 K) changes so that higher molecular weight species make up a greater proportion of total PAH mass after rain than before it. If the post-rain air is then allowed to reach particle-gas

0.12 290 K

285 K

Cp/ Cp

0.10

0.08

0.06

0.04

0.02

0.00 PHEN ANTH FLRT

PYR

BaA

CHRY

BbF

BkF

BaP

IP

dBahA BghiP

Fig. 3. Hypothetical particulate PAH profile at two temperatures for the same total (gas þ particle) concentration. CTSP ¼ 50 mg m3. log Kp ¼ 0.8 log p0L  5.0. log p0L values were taken from Offenberg and Baker (1999).

E. Galarneau / Atmospheric Environment 42 (2008) 8139–8149

equilibrium, assuming that gas-phase concentrations change very little (see gas-scavenging example), the profile tends toward that which existed before rain began. However, the originally uniform distribution of PAH concentrations is not regained. The total (gas þ particle) profile is difficult to depict graphically since equal particulate PAH concentrations of 1 ng m3 are associated with gas-phase concentrations ranging from 163 to 0.01 ng m3 for PHEN to BghiP, respectively, at 290 K. Small differences are observed between pre-rain and post-rain profiles for the higher molecular weight species (not shown). In quantitative terms, reductions of as much as 21% between initial and final normalized total concentrations are observed for higher molecular weight species. 3.4.2. Dry particle deposition Dry deposition velocities have similar relationships to particle size as do scavenging coefficients (Slinn, 1982; Zhang et al., 2001). As such, the differential removal of PAHs by dry particle deposition is expected to exhibit patterns similar to particle scavenging by precipitation. The simple examples above demonstrate that atmospheric fate processes can act differentially on individual PAHs and cause diagnostic ratios or profiles to be altered after emission. This is true for particulate or total (gas þ particle) concentrations. Therefore, the assumption that the relative amounts of PAHs at an emission source conserved during atmospheric residence is, as a general rule, not met. 3.5. Other considerations Apart from physicochemical transformations that can occur in the atmosphere, ambient air typically contains PAH contributions from several sources. Measured relative PAH amounts may not be indicative of the relevant source contributions simply by virtue of mixing and source strength differences, and this is problematic when

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examining diagnostic ratios. An elegant discussion of the effects of PAH source mixing is presented in Robinson et al. (2006). An additional caveat on the use of relative concentrations for source apportionment of PAHs is the fact that measurement uncertainty is large enough to have a marked effect on observed profiles. Repeated replicate ambient sampling has been conducted at five IADN sites and the grand average difference (average of species average differences) between concurrent side-by-side measurements examined in Galarneau et al. (2006) is 28% (unpublished data). If random measurement errors ranging conservatively between the negative and positive average values are applied to a uniform concentration profile of PAHs, the observed profile is distorted as shown in Fig. 5. Multivariate methods provide for estimates of measurement uncertainty but studies examining diagnostic ratios typically do not. 4. Refining the approach to conventional airborne PAH source apportionment The arguments presented above demonstrate that neither assumption required for conventional ratio- or profile-based source apportionment of PAHs holds true in all situations. Several studies have tried to adapt the diagnostic ratio or profile approach by accounting for the lack of conservation of species concentrations, particularly with respect to reactivity (Duval and Friedlander, 1982; Pistikopoulos et al., 1990b; Li and Kamens, 1993; Venkataraman and Friedlander, 1994; Schauer et al., 1996). However, source apportionment studies continue to be published based on the assumptions that species are conserved and that sources are distinguishable by their relative PAH concentrations (Bourotte et al., 2005; Dallarosa et al., 2005; Ravindra et al., 2006; Ding et al., 2007; Lee and Kim, 2007; Battelle, 2007; Ravindra et al., 2008a,b; Esen et al., 2008). Source apportionment by these methods holds obvious appeal because of their simplicity and ease of application. If valid, researchers at any location can compare the results of

0.12 after rain, no p/g equilibration

after rain, with p/g equilibration

0.10

Cp/ Cp

0.08 0.06

0.04 0.02 0.00 PHEN ANTH FLRT

PYR

BaA

CHRY

BbF

BkF

BaP

IP

dBahA BghiP

Fig. 4. Hypothetical particulate PAH profile affected by below-cloud particle scavenging. PM and PAH unimodal log-normal particle size distributions from Offenberg and Baker (1999). Particle size-dependent mass scavenging coefficients are from Fig. 2a in Andronache (2003). Rainfall duration of 1 h at 10 mm h1.

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0.12

0.1

C/ C

0.08

0.06

0.04

0.02

0 PHEN ANTH FLRT

PYR

BaA

CHRY

BbF

BkF

BaP

IP

dBahA BghiP

Fig. 5. Hypothetical uniform PAH profile affected by measurement imprecision. Random measurement error between 28% and þ28%. 28% is the grand average absolute percent difference between side-by-side PAH measurements conducted by the Integrated Atmospheric Deposition Network (Galarneau, unpublished data).

their measurements to published data and draw conclusions about source contributions. Such simplicity is of particular advantage to nations of the developing world whose scientific infrastructure may not have the capacity to develop and run sophisticated numerical models or to conduct extensive measurements to determine relevant source characteristics. A thorough examination of all the published literature on sources might yield relationships between individual PAH species that are indeed source-specific and universally applicable. Many studies have recently been published examining PAH emissions from motor vehicles (Zielinska et al., 2004; Lim et al., 2005, 2007), combustion of scrap tires (Chen et al., 2007), agricultural burning (Keshtkar and Ashbaugh, 2007) and residential wood combustion (Hays et al., 2003) but these are not included in compilations of PAH sources to the atmosphere (Yunker et al., 2002; US EPA, 1998, 2004). A systematic analysis of an updated compilation could provide guidance on distinguishing PAH sources in ambient air. The issue of atmospheric fate is complex to assess since many variable processes are involved. A recent multimedia fate modelling study (Zhang et al., 2005) used ‘‘rectification factors’’ to account for differential effects on isomers in environmental fate calculations. However, the use of such factors for the analysis of a real ambient data set would have to assume that sources and processes affect observed PAH levels uniformly across all the data. Because of variations in source strengths and atmospheric processing, such uniformity is not expected in the ambient atmosphere. Robinson et al. (2006) extended the diagnostic ratio approach by examining the relationships between different PAH ratios in a data set. The ambient data were collected in a location with one predominant PAH source. Though their

approach may be valid under such conditions (viz., local sources not strongly affected by atmospheric processing), it is difficult to envision how it would be valid for ambient air which contains PAHs from a mixture of sources that have undergone varying amounts of atmospheric processing. Early conventional multivariate methods such as chemical mass balance (CMB) models used the PAH profiles of suspected sources as input. Such an approach is biased by a priori assumptions of the number and nature of the contributing sources. This concern has been addressed by using factor-analysis methods such as principal component analysis (PCA) that segregate measured ambient concentrations according to groups of covarying elements and comparing those groups to suspected source profiles a posteriori. All of these conventional methods, however, assume that at least one PAH species associated with each source provides a unique identification. An exercise in which the ambient concentrations produced by a comprehensive air quality model were submitted to conventional source apportionment could provide quantitative guidance on the applicability of the latter. The source information would be known since it was explicitly input to the regional model and it could be made to vary in order to examine the effect on observed ambient concentrations. Such a study would be useful to evaluate the source mix and atmospheric conditions for which conventional methods might be successful. Because of the caveats associated with the use of diagnostic ratios and/or profiles in all but the most straightforward of cases, the sophisticated atmospheric processing represented in regional-scale air quality modelling may be the only useful approach to source apportionment of PAHs in ambient air. However, the latter approach has its constraints. Emissions’ inventories are highly aggregated

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entities for which many values are uncertain. Furthermore, such models are computationally intense. Discriminating between sources requires ‘‘tagging’’ the PAHs that arise from each of them, effectively treating each source/PAH combination as a separate species and consequently increasing computational loads. Due to the direct policy implications of source apportionment work, it is essential that the results be valid and accurate to the best possible scientific standard. The popular use of diagnostic ratios or profiles that are assumed to be unique among sources and conservative in the atmosphere does not always meet this standard. Such methods may prove to be valid under limited conditions but, as always, the onus is on investigators to demonstrate this. The caveats and examples presented in the preceding sections can be used to develop a set of conditions under which airborne PAH source apportionment may be practicable by the examination of relative species amounts. As a summary, these are 1. Potential source emissions data, whether used to identify sources a priori or a posteriori, should be representative of sources emitting to the ambient air under investigation, AND 2. The variation in relative species concentrations in the emissions of relevant sources should not render source identification ambiguous, AND 3. The uncertainty in measured concentrations in ambient air should not render source identification ambiguous, AND 4. All species examined should have similar reactivities with respect to atmospheric oxidants and solar radiation in both the gas and particle phases on the timescales of interest. Assessments of reactivity will be tentative since existing data show inconsistent differences for PAHs on model aerosol substrates and since gas-phase reactivities have not yet been measured for all commonly measured semivolatile PAHs, AND 5. All species examined should have similar Henry’s law constants if air parcel histories involve time spent over water sufficient for diffusive air–water exchange to occur, AND 6. Temperature variations between source and downwind ambient air should be small enough for relative species concentrations to be unaffected by changes in particle/ gas partitioning. Alternatively, only species with similar particle/gas partitioning characteristics should be examined if temperature variations are great between sources and downwind air, or only total (gas þ particle) concentrations should be examined, AND 7. All species examined should have particle size distributions that are similar enough to negate differences in particle scavenging by precipitation or particle dry deposition, OR 8. The source apportionment method used should account for all departures from the preceding guidelines. Suggested future research includes (1) the production and rigorous analysis of a database of emission factors from

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a variety of sources to examine the uniqueness of relative PAH species emissions among sources, (2) numerical experiments that combine regional air quality modelling with multivariate methods to assess the conditions under which the latter might be valid, and (3) determination of reactivities for the full suite of commonly measured PAHs under realistic conditions of oxidant concentration, solar radiation and, for particle-bound species, aerosol composition. Acknowledgements The author thanks Terry Bidleman, Pierrette Blanchard, Tom Harner, Sunling Gong and Leiming Zhang for helpful comments and suggestions. Appendix. Supplementary data Supplementary data associated with this article can be found in the online version, at doi:10.1016/j.atmosenv. 2008.07.025. References Allen, J.O., Dookeran, N.M., Smith, K.A., Sarofim, A.F., Taghizadeh, K., Lafleur, A.L., 1996. Measurement of polycyclic aromatic hydrocarbons associated with size-segregated atmospheric aerosols in Massachusetts. Environmental Science and Technology 30, 1023–1031. Andronache, C., 2003. Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions. Atmospheric Chemistry and Physics 3, 131–143. Bae, S.Y., Yi, S.M., Kim, Y.P., 2002. Temporal and spatial variations of the particle size distribution of PAHs and their dry deposition fluxes in Korea. Atmospheric Environment 36, 5491–5500. Bamford, H.A., Poster, D.L., Baker, J.E., 1999. Temperature dependence of Henry’s Law constants of thirteen polycyclic aromatic hydrocarbons between 4  C and 31  C. Environmental Toxicology and Chemistry 18, 1905–1912. Battelle, 2007. Source apportionment of data from four IADN and nearby speciated PM sites. Report prepared for the Great Lakes Commission, Ann Arbor, MI. Behymer, T.D., Hites, R.A., 1985. Photolysis of polycyclic aromatic hydrocarbons adsorbed on simulated atmospheric particulates. Environmental Science and Technology 19, 1004–1006. Behymer, T.D., Hites, R.A., 1988. Photolysis of polycyclic aromatic hydrocarbons adsorbed on fly ash. Environmental Science and Technology 22, 1311–1319. Bi, X., Sheng, G., Peng, P., Chen, Y., Zhang, Z., Fu, J., 2003. Distribution of particulate- and vapor-phase n-alkanes and polycyclic aromatic hydrocarbons in urban atmosphere of Guangzhou, China. Atmospheric Environment 37, 289–298. Bidleman, T.F., Billings, W.N., Foreman, W.T., 1986. Vapor-particle partitioning of semivolatile organic compounds: estimates from field collections. Environmental Science and Technology 20, 1038–1043. Bidleman, T.F., Harner, T., 2000. Sorption to aerosols. In: Boethling, R.S., Mackay, D. (Eds.), Handbook of Property Estimation Methods for Chemicals. Lewis Publishers, New York (Chapter 10). Blanchard, P., Audette, C.V., Hulting, M.L., Basu, I., Brice, K.A., Chan, C.H., Dryfhout-Clark, H., Froude, F., Hites, R.A., Neilson, M., 2004. Atmospheric Deposition of Toxic Substances to the Great Lakes: IADN Results to 2000. Environment Canada and US EPA, Toronto, ON. Bourotte, C., Forti, M.-C., Taniguchi, S., Bicego, M.C., Lotufo, P.A., 2005. A wintertime study of PAHs in fine and coarse aerosols in Sa˜o Paulo city, Brazil. Atmospheric Environment 39, 3799–3811. Brubaker Jr., W.W., Hites, R.A., 1998. OH reaction kinetics of polycyclic aromatic hydrocarbons and polychlorinated dibenzo-p-dioxins and dibenzofurans. Journal of Physical Chemistry A 102, 915–921. Buehler, S., Hafner, W., Basu, I., Brice, K.A., Chan, C.H., Froude, F., Galarneau, E., Hulting, M.L., Jantunen, L., Neilson, M., Puckett, K., Hites, R.A., 2002. Atmospheric Deposition of Toxic Substances to the Great Lakes: IADN Results to 1998. US EPA and Environment Canada, Chicago, IL.

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