Dry Deposition of Semivolatile Organic Compounds to Lake Michigan

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Environ. Sci. Technol. 1995, 29, 2123-2132

Dry Deposition of Semivolatile Oqanic Compounds to Lake Michigan NICOLA PIRRONE AND GERALD J. KEELER* Air Quality Laboratory, The University of Michigan, A n n Arbor, Michigan 481 09-2029

THOMAS M . H O L S E N Pritzker Department of Environmental Engineering, Illinois Institute of Technology, Chicago, Illinois 60616

The Lake Michigan Urban Air Toxics Study (LMUATS) was carried out from July 8 to August 9, 1991, in the southern Lake Michigan basin. The investigation was the first aimed at assessing the impact of the Chicago/Gary urban plume on the deposition of hazardous air pollutants (HAPs) to Lake Michigan. The concentrations of a large number of semivolatile organic compounds (SOCs) were measured at four locations (Kankakee, IL; Chicago, IL; over Lake Michigan onboard the R/V Laurentian; and South Haven, MI). These sites were chosen as they are often linked by air mass transport with air masses reaching South Haven, after passing through Chicago, often having an over-water path to the downwind site. The University of Michigan R/V lawentianwas also deployed off-shore of Chicago t o measure the concentrations of HAPs as they were transported out over the water. A hybrid-receptor deposition (HRD) modeling approach, which utilized measured atmospheric concentrations at a receptor site together with observed meteorological data in a lagrangian dispersion modeling framework, was used to estimate both gas exchange across the air-water interface and particle dry deposition of SOCs to Lake Michigan. The atmospheric concentrations of selected pesticides, PCBs, and PAHs measured during the LMUATS were used as input to the HRD model. The comparison between the measured and calculated ambient concentrations gives reasonable results with measured/calculated concentration ratios in the range of 0.3-1.9 for pesticides, 0.9-2.6 for PCBs, and 0.5-3.8 for PAHs. A comparison of deposition fluxes obtained in this study with those found in literature reveals large differences for some compounds, especially for those that are primarily in the particle phase. This finding suggests that assuming constant values of critical parameters controlling the transfer processes of gaseous and particulate SOCs from the atmosphere to the water surface may result in estimates with large uncertainties.

0013-936W95/0929-2123$09.00/0

0 1995 American Chemical Society

Introduction Vapor exchange across the air-water interface,particle dry deposition, and aerosol scavenging by precipitation are recognized as the major transfer pathways of organic compounds from the atmosphere in the Great Lakes (1-8). Several studies have shown that the Great Lakes may act as both sources and sinks of semivolatile organic compounds (SOCs)depending on the season and location (24, 6-10). These compounds, which include chlorinated pesticides, polychlorinated biphenyls (PCBs),and polycyclic aromatic hydrocarbons (PAHs) exist in the atmosphere in both the vapor phase and adsorbed to suspended particulate matter (1, 11, 12). The distribution of the contaminant between the vapor and the particle phase is a function of the contaminant’s vapor pressure, chemical composition, concentration of suspended particulate matter in the air, particle surface area, and the ambient temperature (1,2, 11-13). SOCs with vapor pressures 1 Pa (i.e., naphthalene, fluorene, phenanthrene) are primarily found in the gas phase in the atmosphere and in the dissolved aqueous phase. These SOCs,therefore,may have significant exchange across the air-water interface (1,2). Contami- ~(Le., PCBs greater nants with vapor pressures ~ 1 0 Pa than penta-PCBs,benzo[ghQperylene)occur mainly in the particle phase in the atmosphere (1, 13, 14) and undergo little exchange in the gas phase. SOCswith vapor pressures in the range of 10-2-10-6 Pa are found in both phases in the atmosphere with the fraction in the particle phase varying between 20 and 90%. Once the contaminant is partitioned between the gas and particle phase, its transfer from the atmosphere to a water surface will depend upon meteorological conditions (e.g., humidity, wind speed, atmospheric stability), the contaminant’s particle size distribution, water wave dynamics, and bubbles ejection (15-17) as well as the concentration gradient at the airwater interface. In recent years, several studies have evaluated the dry deposition flux and vapor exchange of SOCs to the Great Lakes (1-6,9,18,19). The purpose ofthis paper is to present a new model developed to calculatethe dry deposition flux of SOCs in both the gas and particle phases to Lake Michigan during the Lake Michigan Urban Air Toxics Study (LMUATS) (20). The model, which was initiallydeveloped to estimate the deposition flux of particlate trace elements to large bodies of water (211, was modified to account for spatial and temporalvariations in the vapor-particle distributions, particle deposition velocities,and air-water gas exchange coefficients during transport over lakes. The model was used with data collected around Lake Michigan during LMUATS, which included measurements of the concentrations of selected pesticides, PCBs, and PAHs at several sampling locations.

Methods Sample Collection. Ambient air samples were collected in Chicago, IL, on the roof of Farr Hall,a 4-story building on the campus of Illinois Institute of Technology (IIT);in South Haven, MI, a rural location 3 km from the eastern side of Lake Michigan; and onboard the RIV Laurentian located * Author to whom correspondence should be addressed.

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FIGURE 1. Sampling sites location and backward trajectories ending in South Haven and traversing Lake Michigan on July 10 and 19-22, 1991. IIT, Illinois Institute of Technology, Chicago, II; SHV, South Haven, MI; RVA, RV Laurentian.

5-10 km off-shoreof Chicago (Figure 1) (21). Total (vapor particle) ambient concentrations of pesticides and PCBs were collectedwith a PS- 1 sampler loaded with a prebaked quartz fiber filter (20 x 25 cm) and a polyurethane foam (PUF) backup cartridge (7.8cm diameter x 7.5 cm thick). Concentrations of total (vapor + particle) PAHs were determined using a second PS-1 sampler loaded with a prebaked quartz fiber filter (20 x 25 cm) followed by an XAD-2 backup cartridge. Twelve-hour samples were taken at flow rates of 0.5-0.7 m3/mindaily at all locations. After sampling, the filters and backup absorbent samples were stored at -10 "C until extraction (20, 23). Analytical Procedures. The PUF plugs used for the sampling of pesticides and PCBs were cleaned with soap and water: rinsed with tap water, distilled water, and methanol; and placed in a clean oven at 150 "C to remove the solvent (20, 23). After sampling, the PUF plugs and quartz filters were both extracted for 12-24 h with dichloromethane in a Soxhlet apparatus. Prior to extraction, all samples were spiked with 3,3',4,4'-tetrachlorobiphenyl to monitor analytical recovery. The extracts were fractioned on an alumina column consistingof 10%water-deactivated alumina (3 g: neutral, 80-200 mesh, activated at 450 OC). The column was elutedwith 1mL ofhexane. The combined eluant was solvent exchanged to hexane, and internal

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standards were added before concentratingto a finalvolume of 0.5 mL using a rotary evaporator. Analysis of pesticides and PCBs was performed on a Fison VG Autospec highresolution mass spectrometer equipped with an HewelettPackard 5890 gas chromatograph and CTC-A autosampler and a 60 m x 0.32 mm DB-5 column U&W Scientific).Since a mixture of heat-sensitive pesticides was analyzed in conjunction with high-boilingPCBs, injector temperature (250"C), inertness, and injectiontechnique were optimized to decrease the amount of thermal degradation of the target pesticides. The column temperature was increased from 45 to 300 "C at a rate of 5 "C/min. For PAH analysis, the filter and XAD-2 were combined and extracted for 12-24 hwith dichloromethane in a Soxhlet apparatus (231, After extraction, the dichloromethane extracts were concentrated by Kuderna-Danish (K-D) evaporation to a final volume of 1 mL. Known amounts of deuterated phenanthrene, 1000 ng, and 9-phenyl anthracene, 200 ng, were added to the concentrated sample extracts to monitor analytical recovery. The concentrates were then transferred from K-D tubes to GC vials for analysis on a TSQ-45 GClMSlMSoperatedin GUMS mode. Helium was used as the carrier gas. The GC column was a 60 m x 0.25 mm DB-5 column (0.25 pm film thickness, Supelco). The GC temperature was held at 70 "C for 2 min

TABLE 1

Percent Recovery and Mean RSD of QA Samples Collected during LMUATS YO recoverya hexachlorobenzene y-HCH (lindane) trans- no n ac h Io r dieldrin 4,4’-dichlorobiphenyl 2,4,4‘-trichlorobiphenyl 2,2’,5,5’-tetrachlorobiphenyl 3,3’,4,4‘-tetrachlorobiphenyl 2,2’,4,5,5’-pentachlorobiphenyl 2,2’,3,4,4‘,5’-hexachlorobiphenyl 2,2’,4,4’,5,5’-hexachlorobiphenyl total di-PCB total tri-PCB total tetra-PCB total penta-PCB total hexa-PCB total hepta-PCB fluorene anthracene fluoranthene pyrene benz[alanthracene chrysene benzo[elpyrene benzo[alpyrene indeno[l,2,3-c,dlpyrene di benzo[a,hlanthracene benzo[g,h,/lperylene

106-195 25-30 65- 129 61 -93 73- 130 86- 109 78-84 77-109 89-114 61-76 63-80

96-116 111-123 97-108 95-102 101-126 96-127 84-102 99-116 121-136 104-132

mean O h RSD of duplicate sampled 27 33 52 41

38 38 42 22 37 74 6.1 15 31 31 27 13 19 15 16 1.9 20

RSD range 0.8-61.1 4.2-68 2.3-75 7.2-77

6-64 14-71 4-72 12-43 15-59 34-141 1.6-12 21-21 11-67 24-40 5.6-61 0.6-21 13-24 13-16 8-27 1.O-3.0 17-24

a For PCBs and pesticides, the reported values are the range of four spiked samples, for PAHs, the reported values are the range of two spiked samples. b The reported values are for 14 paired samples from the South Haven site.

and then increased to 290 “C at a rate of 8 “Clmin. The audit sample extracts were analyzed by GClMS in selected ion monitoring (SIM) mode with the same operating conditions used for the samples. Quality Assurance. Four PCB and pesticide audit samples were spiked and analyzed. The percent recovery for these samples ranged from 25 to 195% (Table 1). The lowest recovery was for lindane, and the highest recovery was for hexachlorobenzene. Ignoring these two compounds, the average recovery was 80% with a standard deviation of 11. Two PAH audit samples were also spiked and analyzed. The percent recovery for the PAH compounds ranged from 84 to 136%with an average of 110% and a standard deviation of 14. The total analytical precision was evaluated with 14 paired samples collected at the South Haven site using parallel PS-1 sampling. The RSD of the duplicate sample analyses averaged 29% and ranged from 1 to 141 (Table 1). Surrogate recovery in the 72 samples averaged 81%with a standard deviation of 12. In general, blank concentrationswere less than 10%of the sample concentrations for most compounds except for pyrene, fluoranthene, and total dichloro PCBs, which for low concentration samples occasionally had blank concentrations as high as 50% of the sample concentrations. All reported values are blank corrected. Modeling. The transport of atmospheric contaminants in the lower layer of the atmosphere and their transfer to a water surface is affected by the physical-chemical properties of the contaminants, meteorological parameters, their particle size distribution, vapor-particle conversion, water wave dynamics, and bubble ejection (5, 7,1519-21, 24-28).

The hybrid-receptor deposition model formulated to estimate the deposition flux of particulate trace metals over

Lake Michigan (20,21)was modified as described below to account for vapor-particle partitioning, and the dry deposition flux of organic compounds in both the gas and particle phases. The dry deposition flux, F,of SOCs along an over-water trajectory is given by

where j is the trajectory segment index that increases along the over-water trajectory (for both the forward and backward modes) beginning at the monitoring site, x is the total ambient concentration of SOC along each trajectory traversingLake Michigan, R is the gas constant (8.3Pa m3/ mol IC), Ta-wis the absolute temperature at the air-water interface,Q, is the fraction of the contaminant in the particle phase, vd is the deposition velocity of particles with a given mass median diameter (MMD) for which the SOC is associated, k o is ~ the overall air-water transfer coefficient for SOCs in the gas phase, C,is the SOC concentration in the dissolved aqueous phase, and H is the Henry’s law constant. Unfortunately,C,was not measured for any of the SOCs during LMUATS, and therefore its spatial and temporal variation in the aqueous dissolved phase was not determined. McConnell et al. (6‘) reported the mean a-HCH and y-HCH concentrations in the dissolved aqueous phase, calculatedfrom 11samples collected during a2-week cruise over Lake Michigan in August 1991, showed relatively little variation(standarddeviationless than 30%of the arithmetic mean). Similar results were obtained by Cleckner (43) during a 5-day cruise over Lake Michigan in September 1993. In that study,the standard deviationofthe arithmetic mean of C,for a number of PAHs was in the range of 3040%. A sensitivity analysis of the model revealed that, as VOL. 29, NO. 8, 1995 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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expected, an increase in C, produces a nearly linear decrease in the deposition of SOCs to the air-water interface; similarly, a decrease of C,causes an increase of SOC volatilizationof the same order of magnitude. In this work, &was assumed to be constant. If a similarvariation in C, can be assumed for the LMUATS period as was found above (30-40%), the uncertaintyin the model’s results due to the unmodeled variation of C, during the over-water transport is expected to be lower than that due to other model’s parameters (Le., aerosol surface area, fraction of the contaminant in the particle and gas phase). In this paper, eq 1 is a dynamic equation allowing both x and v d to vary with time and space during the transport of air masses over Lake Michigan. Mixed-layer trajectories were calculated with the Air Resources Laboratories Atmospheric Transport and Dispersion (ARL-ATAD)Model (15) using upper-air data collected for the Lake Michigan Ozone Study (LMOS) as well as the routine upper-air observations from the National Weather Service ( N W S ) . The trajectories were used to determine the most probable path of an air mass traversing Lake Michigan as well as the lake surface area intersected by the air mass. The trajectories definethe wind speed and mixing layer depth moving backward or forward from the receptor sites in 3-h time steps. Three-day trajectories calculatedfor each day of the study were matched with the 12-hintegrated SOC samples beginning at 9 PM CDT and ending at 9 AM CDT. The model was run in two different modes. When sampling sites were downwind of the lake, backward trajectories were utilized. When sampling sites were upwind of the lake, forward trajectories were utilized. A virtual source, VS, construct was used to account for the spatial and temporal variations of ambient concentrations of contaminants due to atmospheric dispersion, particle deposition, and vapor exchange at the air-water interface along the air mass trajectory (21).The VS was defined as an area source, equivalent to all sources contributingto the observed pollutant concentration,which falls along the path of the calculated air mass trajectory. The distance, DVS, of the virtual source from the lake shore was determined through an optimization process that minimized the ratio between calculatedand measured SOC concentration at each sampling site. The virtual source construct was only applied for air masses that moved backward over the lake from the sampling site (21).When the air masses move from the sampling site to the lake (forwardmode), the measured SOC concentration represents the source term in the mass balance equation as will be discussed later. Assuming the contaminant is uniformly distributed in the air parcel of volume V(t) = x(t)y(t)z(t),the temporal variation of the atmospheric concentration of contaminants along the over-water trajectory is obtained with the following equation: M ( f )= X(t)x(t)y(t)z(t)- Vd(t)x(t)x(t)y(t/2)f $. k o ~ ( t ) I ~ ( t )-( l~(t))RT,-,(t)lH(t)- Cwl(t)y(t/2)t (2) where MU) is the mass of contaminant in the volume V(t). Assuming no loss of contaminant through the upper level of the transport layer, a constant time step At, a constant particle deposition velocity along the over-water trajectory segment j, and no chemical transformation of the contaminant in the air mass traversing the lake and assuming a constant ambient concentration during each segment j, 2126

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eq 2 leads to the following mass balances:

Equations 3 and 3’ are for trajectories in the backward and forware mode, respectively. The first term on the right side of the eqs 3 and 3’ represents the mass of contaminant in the volume I$ and I$-l, respectively; the second term is the mass of contaminant in the particle phase deposited over the water surface of area xjyj and ~j-1yj-~, respectively; and the third term accounts for the mass of contaminant associated with gas phase that is deposited to and/or evaporated from the water interface. The term on the left side of eqs 3 and 3’ is the mass of contaminant advected along the subsequent trajectory segment after accounting for atmospheric dispersion and particle dry deposition and gas exchange at the air-water interface. The uncertainty in the model’s results due to the assumption made in developing eqs 3 and 3’ are discussed in Pirrone etal. (21). The time-dependent pollutant concentrations along the trajectories are derived from eqs 3 and 3’, which lead to the following expressions for backward trajectories:

koL,At/z~j]

V j > 2 (5)

and for forward trajectories: k1J-1

where

+

is the total ambient concentration (vapor particle phase) of the SOC measured at the sampling site (j = l), Xj is the distance traveled by the virtual plume, zj is the transport layer depth,yi is the crosswind virtual plume width (following the conventional symbolism yj = 20J, and n is the number of trajectory segments over the lake characterized byaconstant time step At. The dry depositionvelocity v , of particles is calculated with a two-layer deposition model, which accounts for water wave dynamics and spray formation at air-water interface. More detailson the model parameters and formulation can be found in the companion paper (21). The overall air-water transfer coefficient ( ~ o L )the , Henry’s law constant (H),and the fraction of the contaminant in the particle phase (p) were calculated along the over-water trajectories based on recent work in the literature (1,2,4,9,13,14, 18,25-27, 29-33, 35,36). The fraction of SOC in the particles phase (p)at a given temperature at the air-water interface (Ta-w)is calculated

x1

TABLE 2

Arithmetic Mean and Standard Deviation of Ambient Concentration (pg/m3) of Pesticides: PCBs,” and PAHS“ Measured in Chicago, II; in South Haven, MI; and Onboard the R/V Laurentian during LMUATS a-HCH hexachlorobenzene y H C H (lindane) trans-nonachlor dieldrin total penta-PCB deca-PCB total PCBs fluorene anthracene fluoranthene pyrene benzblanthracene chrysene benzo[elpyrene benzoMpyrene indeno[l,2,3-c,dpyrene dibenz[a,hlanthracene benzo[g,h,ilperylene

Chicago

South Haven

RNL

112 f 39 68 f 40 58 f 36 55 f 29 159 f 76 707 f 479 0.20f 0.9 2139 f 1214 53600 f 33550 7590 f 5870 46580 f 29260 23580 f 14370 3020 f 2780 5170 f 3820 2810 f 2610 3040 f 3880 3900 f 3170 1390 f 890 3320 f 2350

128 f 27 55 & 23 90 f 104 31 f 21 169 f 90 263 f 127 0.10 f 0.6 672 f 279 3450 f 1900 130 f 60 1500 f 910 770 f 420 140 f 150 310 f 360 170 f 200 140 f 160 260 f 330 160 f 130 210 f 260

170 f 205 104 f 154 103 f 100 12 f 7.1 46 f 25 290 f 163 0.04f 0.01 808 f 357 7170 f 4500 270 f 250 3220 f 2860 1600 f 1520 260 f 390 620 f 860 250 f 320 250 f 310 410 f 520 210 f 160 330 f 430

a Number of samples collected: 31 in Chicago and 30 in South Haven. Number of samples collected: 17 on RN Laurentian and 30 in South Haven.

using Junge’sequation (26,27,35,361.The subcooled liquid vapor pressure, P, appearing in the Junge’s equation is obtained through the Clausius-Clapeyron equation, previously validated for PAHs (8, 13, 29) and PCBs (22, 37): log Pj = a

+ b/T,-w,

(7)

where a and b are regression coefficients estimated from vapor pressure capillary GC method data obtained at different temperatures (2,30, 31, 36, 44).

Results and Discussion The Lake Michigan Urban Air Toxics Study was an investigation aimed at assessing the impact of the Chicago/ Gary urban plume on the deposition of hazardous air pollutants (HAPS)into Lake Michigan (20). One of the major objectives of the LMUATS was to provide an initial assessment of the relative importance of the urban input to the total loadings of (HAPS)to Lake Michigan (including differentiation of the contribution of the ChicagolGary urban plume from the regional air mass). In order to accomplishthis objective, a comprehensive suite of atmosphericmeasurements was performed during the month-long study. The levels of a large number of SOCs were measured at locations that are often linked by air mass transport. The ambient SOC concentrations observed at land-based sites and over water aboard the RIV Laurentian were used as input to a hybrid-receptor depositionmodelto estimate gas exchange at the air-water interface and particle dry deposition of SOCs to Lake Michigan during LMUATS (211. A statistical summary of the SOC concentrations measured at three of the four LMUATS sites is given in Table 2. Measured ambient concentrations of pesticides such as a-HCH, y-HCH, and dieldrin were slightly higher in South Haven than in Chicago. Hexachlorobenzene, trans-nonachlor, total PCBs, and specific PCB congenerswere higher in Chicago than in South Haven by a factor of 2-15. The pesticide and PCB concentrationsmeasuredin South Haven were used as input to the hybrid-receptor model, and predicted concentrationswere compared to those measured at the IIT site in Chicago.

At the IIT site, the measured PAH concentrations were 5-28 times higher on average than those measured onboard

the RIV Laurentian. The differences between pesticides and PCB concentrations measured at the IIT and RIV Laurentian site were much lower (within a factor of 3-4). The difference between PAHs concentrations measured at IIT and over water aboard the RIV Laurentian cannot be explained by atmospheric dispersion calculations, even if one used a low dispersion coefficient (q=- 0.5). This finding suggests that local PAH sources influenced the PAH concentrations measured at the IIT site and that these concentrations were not typical of those in the air masses that intersected the RIV Laurentian and South Haven sites. (It is also likely that some of the more reactive PAHs were removed from the atmosphere during transport between Chicago and the other sites.) For these reasons, the PAH concentrations measured at the South Haven site were used as input to the model, and predicted concentrations were compared to those measured on the RIV Laurentian. In order to validate and to calibrate the model, the 12-h integrated ambient samples taken from 9 AM to 9 PM CDT dailyon July 19-21,1991, were used as input to the model. On these days, the trajectories indicate that the air mass reaching the South Haven site first passed through the Chicago urbanlindustrial area (Figure 1). Comparisons were made between predicted and measured ambient concentrations at the receptor site at IIT in Chicago for the pesticides and PCBs and for PAHs onboard the RIV Laurentian using backward trajectories, which originated in South Haven. In order to calculate dry deposition velocities for SOCs in the particle phase, particle size distributions must be measured or estimated. Since only total ambient concentrations were measured (gas + particle), average MMDs deduced from measured deposition velocities available in the literature were used to estimate the dry deposition flux of contaminants and their temporal and spatial variations over Lake Michigan. Dry deposition velocities of PCBs associatedwith particulate matter were found to range from 0.02 to 1 cmls (10, 19, 38, 391,while the dry deposition velocity for total PCBs varied from 0.38 to 0.58 cmls with VOL. 29, NO. 8 , 1995 /ENVIRONMENTAL SCIENCE &TECHNOLOGY

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>

u

-

Wmd speed = I 4 ds I-. ...

~

.~

.

.

.

~

1

. . ..1

I 0001

I

1 01

I

IO

Mass Median Diameter (um)

FIGURE 2. Deposition velocity vs the mass median diameter and wind speed obtained with Pirrone et al. (21)model.

an average of 0.5 cmls (1, 40-42). The dry deposition velocity of the PAHs was estimated to be 0.37 cmls for the particle phase and 0.46 cmls for totalPAHs (39). PAHs and PCBs measured in Chicago were found to be mostly in the gas phase (>75%),with lesser amounts in the fine (1520%) and coarse (3-6%) particle phase (41). However, coarse particles were responsible for the majority ('80%) of PAHs and PCBs dry deposition flux due to their large depositionvelocities.Assumingaparticle densityof2 g/cm3 and a roughness coefficient of zo for the water surface in the range of 0.0005-0.05 cm (211, the theoretical MMD equivalent to the above particle deposition velocities is in the range of 0.4-4.6 pm. In these modeling calculations, a MMD of 1.6pm was used to estimate the dry deposition flux of particle-bound pesticides, PCBs, and PAHs as well as their temporal and spatialvariationsover Lake Michigan. Figure 2 shows the change in deposition velocity with particle diameter for both low and high wind speeds. At low wind speeds ( < 2 m/s), the variation in the deposition velocity with particle diameter is linear. At higher wind speeds ( > 4 m/s), the deposition velocity of micron and submicron particles increases by a factor of 3 for 0.5 pm diameter particles, by a factor of 7 for 0.7 pm diameter particles, and by a factor of 10 for 1.3pm diameter particles compared to those obtained at lowwind speeds. For coarse particles, these variations are 40% on average for 4 pm diameter particles and 5-8% on average for 6pm diameter particles. During LMUATS, the deposition velocity of 1.6 pm diameter particles was found to vary by a factor 12 along the trajectories that traversed Lake Michigan. This variation was mostly due to changes in wind speed during transport. More information about changes in deposition velocity during transport can be found elsewhere (21). The variations in gas-particle distributions (v,) were mostly related to the molecular weight of the compounds and daily fluctuations of the ambient temperature in the air masses traversing the lake. The fraction of the SOC in the particle phase vaned by a factor of 6 for low molecular weight compounds such as fluorene, while for low vapor pressure and high molecular weight compounds such as benzo[alpyrene, these variations were much lower. Arithmetic mean and standard deviations for p, estimated for each trajectory segment over the lake, are given in Table 3. The dependence of v, on the ambient temperature is higher for low molecular weight compounds (SD 250% of the mean), whereas high molecular weight compounds show less variability (SD