ARTICLE IN PRESS

AE International – North America

1352-2310/$ - se

doi:10.1016/j.at

�Correspond+1713 743 426

E-mail addr

Atmospheric Environment 38 (2004) 6687–6699

www.elsevier.com/locate/atmosenv

Concentrations and vapor–particle partitioning ofpolychlorinated dibenzo-p-dioxins and dibenzofurans

in ambient air of Houston, TX

Oscar Correaa, Hanadi Rifaia,�, Loren Rauna, Monica Suareza, Larry Koenigb

aCivil & Environmental Engineering Department, University of Houston, 4800 Calhoun Road, N107 Engineering Bldg 1,

Houston, TX 77204-4003, USAbTexas Commission on Environmental Quality, P.O. Box 13087, Austin, TX 78711-3087, USA

Received 26 May 2004; accepted 2 September 2004

Abstract

The levels of the 2,3,7,8-substituted congeners of polychlorinated dibenzo-p-dioxins (2,3,7,8-PCDDs) and

polychlorinated dibenzofurans (2,3,7,8-PCDFs) were measured in ambient air in Houston, TX between September

2002 and April 2003. Samples collected from five locations showed that the monthly total average 2,3,7,8-PCDD/PCDF

concentrations ranged from 808 to 1760 fgm�3 with an average of 1235 fgm�3, consistent with their counterparts from

other urban areas. From the measured concentrations, it was also observed that: (i) Houston exhibited low 2,3,7,8-

TCDD and 2,3,7,8-TCDF concentrations, (ii) the fall and winter V/P ratios for Houston were close to one, probably

due to elevated winter temperatures, (iii) the highest chlorinated 2,3,7,8-PCDD/PCDFs exhibited the highest

concentrations, and (iv) 2,3,7,8-substituted congeners of PCDDs were the major contributors to the International Toxic

Equivalent. The last three observations differ from the literature.

Gas–particle partitioning (Koa-based and P�L-based) models were used to describe the distribution of the 2,3,7,8-

substituted congeners for Houston. It was determined that P�L estimates using retention indices were more accurate than

those obtained with entropy-based approaches. The research demonstrates that PM2.5 and PM10 can be used instead of

total suspended particle to estimate Kp, although it was shown that PM10 is more appropriate for relating the

particulate fraction to Koa. Finally, the research demonstrates that Kp�P�L partitioning models are improved by adding

relative humidity as a variable to the correlation analysis.

r 2004 Elsevier Ltd. All rights reserved.

Keywords: Dioxins; Furans; Congeners; Urban ambient air; Vapor/particle partitioning

1. Introduction

Polychlorinated dibenzo-p-dioxins (PCDDs) and

polychlorinated dibenzofurans (PCDFs) are two groups

of tricyclic, planar, chlorinated aromatic compounds

e front matter r 2004 Elsevier Ltd. All rights reserve

mosenv.2004.09.005

ing author. Tel.: +1713 743 4271; fax:

0.

ess: Hanadi.Rifai@mail.uh.edu (H. Rifai).

with similar chemical properties. All are non-polar,

poorly water soluble, lipophilic, stable chemicals

(Rappe, 1996; Alcock and Jones, 1996), but the level

of toxicity varies considerably among the different

PCDD and PCDF congeners. Dioxins and dibenzofur-

ans encompass 210 congeners (75 PCDDs and 135

PCDFs), however, only 17 of them, the 2,3,7,8-

substituted congeners, are of concern because they are

endocrine disruptors and cause various forms of cancer.

d.

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–66996688

Dioxins began to be significantly incorporated into

the environment in the 1930s due to the large-scale

production and use of chlorinated chemicals. Dioxin

levels continued to rise until the 1990s but have since

decreased dramatically (Rappe, 1996; McKay, 2002).

However, it is still thought that the population continues

to be exposed to significant amounts of these toxics

(Alcock and Jones, 1996; Alcock et al., 1998).

During their transport in the atmosphere, dioxins,

and dibenzofurans can be removed by reactions or by

deposition (Bidleman, 1988; Lohmann et al., 1999a;

Alcock et al., 2001). Their fate is principally governed by

their gas–particle partitioning. Thus, researchers have

recently focused their attention on measuring and

predicting the partitioning of these semi-volatile organic

compounds (SOCs) into the particle (P) and vapor (V)

phases. Different partitioning approaches have been

proposed in the general literature. One approach is

based on the dependence of the V/P ratio on tempera-

ture and the total suspended particle (TSP) concentra-

tion. This interaction has suggested a general correlation

based on SOC volatility, and as a result, the subcooled

liquid vapor pressure (P�L) has been used as a descriptor

of SOC partitioning. In another approach, the octanol/

air partitioning coefficient (Koa) has been used, and Koa-

based models have been successfully employed to

explain the partitioning of polychlorinated biphenyls

(PCBs), polychlorinated naphthalenes (PCNs), polycyc-

lic aromatic hydrocarbons (PAHs), and PCDD/PCDFs.

Few partitioning studies for dioxins have been

reported in the literature possibly due to the extremely

low levels of PCDD/PCDFs in the atmosphere and the

fact that long sampling periods are sometimes required

to provide enough sample for analysis and detection.

This paper presents results from ambient air monitoring

for dioxins in Houston, TX at five locations over a

period of 8 months. Houston is home to as many as 40

industrial sectors and 170 facilities including wood

preserving, pulp and paper mills, alkalies and chlorine,

plastics and synthetic resins, industrial organic chemi-

cals and petroleum refining that are potential dioxin

sources within the study area. Ambient dioxin concen-

trations are compared to their counterparts measured in

other cities around the world. More importantly, the

paper presents the distribution of dioxins congeners

between the vapor and particulate phases. The Houston

data are modeled using P�L and Koa partitioning

approaches and the adequacy of these partitioning

approaches for describing the Houston data is discussed.

2. Methods and materials

2.1. Sampling sites

Dioxin levels were monitored at five different sam-

pling sites. Two of the sampling stations had co-located

samplers for quality control purposes. The monitoring

sites represent different levels of industrialization across

the city. The monitors at Clinton Drive (C403) and

Haden Road (C603) are located in an industrial area,

while Mont Belvieu (C610) is in a semi-rural area. Lang

Road (C408) and Bayland Park (C53) are located in

mostly residential areas. The co-located samplers were

set up at C403 and C408 (Fig. 1). Sampling was initiated

in September 2002 for the first four sites and in March

2003 for Bayland Park.

2.2. Sample collection

Ambient air samples were collected using high-volume

samplers (Tisch Environmental Inc., Cleves, OH) in

compliance with USEPA Method TO-9A (1999) and

designed to collect both vapor and particle-bound

phases. Air is first drawn through a Whatman 102-mm

bindless quartz QMA micro-fiber filter where atmo-

spheric particles of X0.1mm in diameter are retained.

Air then passes through a polyurethane foam (PUF)

plug used to adsorb vapors. Samples were collected

by running the monitors approximately 5 days a

week, 4 weeksmonth�1. During sample collection, the

quartz filter was replaced weekly to avoid signifi-

cant pressure drops. At the end of the monthly

event, the sample, consisting of four filters and one

PUF per monitor, was analyzed for 2,3,7,8-substituted

congeners.

The air flow rate was calibrated to 0.25m3min�1

prior to initiation of the monthly sampling and checked

at the conclusion of sampling event. An average

flow rate ranging from 0.24 to 0.27m3min�1 was

recorded at all locations during the sampling period.

This range of flow rates allowed processing a total

volume of air varying from 6200 to 7700m3 per monthly

sample, well above the minimum of 4000m3 of air

established as an adequate monthly sample in other

dioxin assessments. The volumes collected allowed

achieving a target detection limit of approximately

0.7 fgm�3 for 2,3,7,8-TCDD, a required concentration

to minimize non-detects. The sampler motors were

replaced every 500 h of operation to avoid motor

malfunctions that might cause loss of sample. Quartz-

fiber filters were baked at 400 1C for 5 h and dried

in a clean atmosphere prior to use. Likewise, the

PUF adsorbent plugs were subjected to a 16-hour

Soxhlet extraction with acetone at approximately 4

cycles h�1 to ensure cleanliness. The PUF plugs

were then air dried in a clean atmosphere, placed in

glass cartridges, and spiked with 37Cl4-2,3,7,8-TCDD

(1000 pg), 13C12-2,3,7,8-TCDD, 13C12-2,3,4,7,8-PeCDF,13C12-1,2,3,4,7,8-HxCDD, 13C12-1,2,3,4,7,8-HxCDF,

and 13C12-1,2,3,4,7,8,9-HpCDF (4000 pg each). The

PUF plugs were wrapped in aluminum foil for protec-

tion from light prior to their use in the field.

ARTICLE IN PRESS

Fig. 1. Sampling locations.

O. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6689

2.3. Analytical methods

The 2,3,7,8-substituted congeners of PCDDs and

PCDFs in air were quantified by high-resolution gas

chromatography/high-resolution mass spectrometry

(HRGC/HRMS) following USEPA method TO-9A

(1999) at a commercial laboratory. After the air samples

were collected, both the filter and PUF were combined

and spiked with nine chlorinated internal standards

along with four brominated internal standards (e.g.,13C12-2,3,7,8-TCDD and 13C12-2,3,7,8-TBDD). The

filter and PUF were then Soxhlet extracted with toluene

for 16 h. The extract was subsequently refluxed in

hexane and subjected to an acid/base clean-up proce-

dure followed by clean-up on micro-columns of silica

gel, alumina, and carbon. The extract was spiked with

0.5 ng 13C12-1,2,3,4-TCDD prior to HRGC–HRMS

analysis to determine the recovery efficiencies achieved

for the 13C12-labeled internal standards. The purified

extracts were concentrated to 10mL before analysis by

gas chromatographic mass spectrometry. The array of

sample extracts was subjected to HRGC–HRMS se-

lected ion monitoring analysis using a 60-m DB-5 or a

60-m SP-2331 fused silica capillary column to establish

the sampler efficiency, extraction efficiency, and the

concentration achieved for the 2,3,7,8-PCDD/PCDFs

congeners.

2.4. Quality control

A number of field and laboratory blanks were taken

with each set of samples and processed in an identical

manner to the samples. None of the lower chlorinated

congeners were detected in the blanks. OCDD and

1,2,3,4,6,7,8-HpCDD, two higher chlorinated conge-

ners, were the most prevalent contaminants in the

blanks, encompassing 70% of the total 2,3,7,8-substi-

tuted congeners. However, their concentrations in the

blanks corresponded to o1.0% and 0.2%, respectively,

of the concentrations found in the air samples. Sample

concentrations for the entire study were not blank

corrected.

Results obtained at the co-located sites were consis-

tent and indicated good agreement between the dupli-

cate samples. Of the 17 congeners, 2,3,7,8-TCDD was

the most difficult to quantify since its concentrations

were particularly low. In cases where the 2,3,7,8-

substituted congeners were not detected, their concen-

tration was taken to be half of the detection limit.

Method detection limits (in pg sample�1) are summar-

ized in Table 1. Also included in Table 1 are the

International Toxic Equivalent Factors (TEFs) used to

convert the concentrations of the dioxin and furan

mixtures to Toxic Equivalent (TEQ) concentrations of

2,3,7,8-TCDD. The average recoveries in the period

ARTICLE IN PRESS

Table 1

Method detection limits and Texas and International TEFs for

dioxins

Congener Method detection

limit (pg)

I-TEFs

2,3,7,8-TCDD 3.38 1

1,2,3,7,8-PeCDD 24.8 0.5

1,2,3,4,7,8-HxCDD 24.2 0.1

1,2,3,6,7,8-HxCDD 25.9 0.1

1,2,3,7,8,9-HxCDD 21.7 0.1

1,2,3,4,6,7,8-HpCDD 11.3 0.01

OCDD 39.4 0.001

2,3,7,8-TCDF 3.28 0.1

1,2,3,7,8-PeCDF 11 0.05

2,3,4,7,8-PeCDF 5.85 0.5

1,2,3,4,7,8-HxCDF 15.5 0.1

1,2,3,6,7,8-HxCDF 10.5 0.1

2,3,4,6,7,8-HxCDF 16.1 0.1

1,2,3,7,8,9-HxCDF 28.8 0.1

1,2,3,4,6,7,8-HpCDF 8.91 0.01

1,2,3,4,7,8,9-HpCDF 19.9 0.01

OCDF 39.7 0.001

Note: 1 pg=10�12 g. TEFs: toxic equivalent factors.

O. Correa et al. / Atmospheric Environment 38 (2004) 6687–66996690

sampled were as: TCDD, 89%, TCDF, 91%,

PeCDD, 84%, PeCDF, 94%, HxCDD, 97%, HxCDF,

95%, HpCDD, 87%, HpCDF, 95%, and OCDD,

75%. Concentrations reported were not corrected for

recovery.

2.5. V/P partitioning

The vapor–particle partitioning (V/P) ratio, defined as

the ratio of dioxin that will exist in the vapor phase

compared with the particle phase, was studied using the

co-located sampler at Lang Road (C408). The filter and

the PUF plug were analyzed separately. The filter

concentration represents the concentration sorbed to

particles and the PUF concentration represents the

concentration in the vapor phase. This definition has

some limiting aspects: (i) particles with a diameter

o0.1mm would not be retained by the quartz filter and

would be absorbed by the PUF, (ii) temperature

fluctuations during the sampling period can cause

particle-bound material on the filter to vaporize and be

assimilated by the PUF (Bidleman and Foreman, 1987;

Bidleman, 1988), (iii) high-volume sampling is suscep-

tible to several potential artifacts, as has been docu-

mented by numerous researchers over the last years

(Mader and Pankow, 2001a, b). The gaseous adsorption

to the filter surface can cause both positive and negative

biases in the measured particulate- and gas-phase

concentrations, respectively, and (iv) there is the

potential for breakthrough on the PUF for large sample

volumes. However, a test made on the PUF plug showed

that breakthrough on the PUF was not occurring for the

volumes that were sampled in the present study. In this

test, an air volume of 7657m3 (with a temperature

fluctuation between 66 and 91 1F) was drawn through

the PUF plug at the co-located site C403. The PUF plug

was cut into two halves (upper and lower) and analyzed

for 2,3,7,8-substituted congeners. The analysis showed

that the upper section contained a total concentration of

86 fgm�3 for 2,3,7,8-substituted congeners while in the

lower section, these analytes were not detected. Thus, no

breakthrough had occurred.

3. Results and discussion

3.1. Total ambient PCDD/PCDF concentrations

The total ambient 2,3,7,8-substituted congener mean

concentrations for the five sites are summarized in Table

2. The temperature summarized in Table 2 corresponds

to the monthly average temperature. The concentrations

in Table 2 were not adjusted to a standard temperature

and pressure. The average concentrations for the

individual congeners ranged from 0.6 to 1103 fgm�3.

The sample location exhibiting the lowest and highest

total concentrations during the sampling period was the

semi-rural sampler, Mont Belvieu (C610). Most of the

total concentration of 2,3,7,8-substituted congeners is

attributed to OCDD with a mean contribution of 63%

when the individual congeners are summed.

The individual PCDD congener data appear to follow

a general trend of increasing concentration with

increasing level of chlorination (Table 2) as would be

expected. The trend found in the individual PCDF

congener data, however, was contrary to that reported

by Eitzer and Hites (1989). The highest chlorinated

2,3,7,8-PCDFs exhibited the highest concentrations

within the group of furans, e.g., 1,2,3,4,6,7,8-HpCDF

and OCDF in this study (Table 2).

In order to compare total 2,3,7,8-PCDDs to total

2,3,7,8-PCDFs, the ratio of the sum of 2,3,7,8-PCDD

congeners divided by the sum of 2,3,7,8-PCDF con-

geners was calculated. The lowest and highest ratios

were calculated for Haden Road in December and

Mont Belvieu in January with values of 1.0 and 20.9,

respectively. The ratios calculated for each monthly

sampling event ranged from 2.7 in December to 8.4 in

November with an arithmetic mean of 5.5. These ratios

are comparable to those presented in the literature (see

Tiernan et al., 1989; Edgerton et al., 1989; Hunt et al.,

1997; Bleux and De Fre, 2000). Variation in the PCDD/

PCDF ratio from month to month could be due to

differences in local emission sources, meteorological

conditions, air mass movement, atmospheric residence

times, seasonality effects, and ‘‘weathering’’ factors (e.g.,

ARTICLE IN PRESS

Table 2

Mean 2,3,7,8-PCDD/PCDF concentrations (fgm�3) for the period September 2002–April 2003 (the standard deviations are shown in

parenthesis)

Year 2002 2003 Mean

Month September October November December January February March April

Average temp. (1F) 79.6 66.4 60.2 56.3 50.1 53.2 63.6 70.7 62.5

No. of samples 4 4 4 4 4 4 5 5 —

2,3,7,8-TCDD 1.3 (0.3) 1.1(0.7) 0.6 (0.3) 1.0 (0.5) 1.4 (0.2) 0.6 (0.3) 0.6 (0.4) 0.8 (0.3) 0.9 (0.3)

1,2,3,7,8-PeCDD 4 (2) 4 (4) 4 (2) 4 (2) 6 (2) 3 (1) 5 (3) 3 (1) 4 (1)

1,2,3,4,7,8-HxCDD 5 (2) 5 (4) 8 (3) 7 (4) 9 (2) 5 (3) 7 (4) 4 (2) 6 (2)

1,2,3,6,7,8-HxCDD 10 (4) 12 (12) 14 (6) 13 (7) 17 (4) 9 (5) 14 (7) 8 (4) 12 (3)

1,2,3,7,8,9-HxCDD 9 (4) 11 (11) 14 (6) 12 (7) 18 (5) 9 (5) 14 (7) 8 (3) 12 (3)

1,2,3,4,6,7,8-HpCDD 179 (77) 187 (147) 298 (121) 196 (115) 299 (109) 147 (87) 258 (120) 123 (41) 211 (67)

OCDD 674 (212) 740 (532) 1103 (361) 705 (470) 1080 (434) 536 (314) 938 (408) 470 (141) 781 (237)

2,3,7,8-TCDF 5 (1) 4 (3) 3 (1) 14 (14) 6 (3) 3 (1) 3 (1) 3 (2) 5 (4)

1,2,3,7,8-PeCDF 4 (0.4) 4 (3) 4 (2) 10 (7) 7 (3) 3 (1) 4 (1) 3 (1) 5 (2)

2,3,4,7,8-PeCDF 6 (0.4) 5 (4) 7 (3) 19 (14) 10 (4) 5 (2) 5 (2) 4 (1) 8 (5)

1,2,3,4,7,8-HxCDF 6 (0.5) 8 (6) 12 (7) 24 (23) 13 (5) 6 (3) 8 (3) 6 (2) 10 (6)

1,2,3,6,7,8-HxCDF 6 (0.4) 7 (5) 9 (4) 27 (36) 11 (4) 5 (2) 7 (2) 5 (2) 9 (7)

2,3,4,6,7,8-HxCDF 8 (0.1) 9 (7) 13 (5) 25 (24) 14 (4) 8 (4) 10 (4) 6 (2) 11 (6)

1,2,3,7,8,9-HxCDF 2 (0.1) 4 (3) 4 (2) 9 (9) 4 (1) 3 (1) 3 (1) 2 (1) 4 (2)

1,2,3,4,6,7,8-HpCDF 36 (2) 44 (31) 57 (24) 103 (126) 55 (17) 27 (12) 42 (15) 27 (9) 49 (25)

1,2,3,4,7,8,9-HpCDF 4 (1) 6 (4) 7 (4) 14 (17) 6 (2) 4 (2) 4 (1) 4 (1) 6 (3)

OCDF 38 (9) 45 (30) 56 (27) 107 (138) 204 (322) 93 (136) 129 (194) 132 (241) 101 (55)

S2,3,7,8-(PCDD+PCDF) 997 1096 1613 1290 1760 866 1451 808 1235

S2,3,7,8-PCDD 882 961 1442 939 1431 708 1236 617 1027

S2,3,7,8-PCDF 115 135 171 351 330 157 215 191 208

2,3,7,8-PCDD/PCDF ratio 7.7 7.1 8.4 2.7 4.3 4.5 5.8 3.2 5.5

I-TEQ (fgm�3) 15 15 19 30 24 12 17 11 18

O. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6691

chemical reactivity with oxidizing species, photolysis,

wet/dry deposition, scavenging by vegetation).

The total International TEQ (I-TEQ) for all sites for

the sampling period ranged from 4 to 55 fgm�3, with

2,3,4,7,8-PeCDF making the major contribution to the

total I-TEQ (up to 57%). This finding is consistent with

emissions from industrial sources (Luthardt et al., 2000;

Kouimtzis et al., 2002). Similarly, the monthly average

contribution to the total I-TEQ of 2,3,4,7,8-PeCDF was

20% (16–32%), making 2,3,4,7,8-PeCDF the congener

with the highest contribution. Other significant con-

tributions to the total I-TEQ were: 2,3,7,8-HxCDFs,

2,3,7,8-HxCDDs, 1,2,3,7,8-PeCDD, 1,2,3,4,6,7,8-

HpCDD, 2,3,7,8-TCDD, and OCDD with 19%

(17–28%), 19% (11–21%), 12% (7–15%), 12%

(7–16%), 6% (3–9%), and 5% (2–6%), respectively.

The mean I-TEQ data for each monthly event are

included in Table 2. With the exception of the

September and November events, the site exhibiting

the highest total I-TEQ was Haden Road (C603), the

sampler in the industrialized area. It was noted that the

highest summed congener concentration did not corre-

spond to the highest observed total I-TEQ. It was also

noted that the 2,3,7,8-substituted congeners of PCDDs

were not only the major contributors to the summed

congener concentrations (�83%), but also to the I-TEQ

(�53%). While this first observation is in agreement

with previous studies (Lohmann et al., 1999b, 2000a),

the second finding is not (e.g., see Lohmann et al.,

1999a; Kouimtzis et al., 2002).

Table 3 compares the 2,3,7,8-substituted congener

data from different locations around the world. The

Houston data, as can be seen in Table 3, are typical for

an urban area, with OCDD making the major contribu-

tion to the total concentration. Additionally, the total

concentration of 2,3,7,8-PCDDs is higher than that for

2,3,7,8-PCDFs as is the case in the other studies in Table

3. However, it was observed that Houston exhibits

relatively low levels of 2,3,7,8-TCDD and 2,3,7,8-TCDF

compared to these other studies.

3.2. PCDDs/PCDFs in vapor and particulate phases

The percentage of the 2,3,7,8-substituted congeners

associated with the particulate fraction is presented in

Table 4. The 4-CDD/CDFs ranged between 9% and

38% with a mean of 20% in the particulate fraction (i.e.,

primarily in the gas phase), the 5-6-CDD/CDFs ranged

ARTIC

LEIN

PRES

S

Table 3

Comparison of Houston air concentrations (fgm�3) of the 2,3,7,8-substituted congeners to other studies

Location Reference Polychlorinated dibenzo-p-dioxins (2,3,7,8-PCDDs) Polychlorinated dibenzofurans (2,3,7,8-PCDFs) Total

2,3,7,8-

TCDD

1,2,3,

7,8-

PeCDD

1,2,3,

4,7,8-

HxCDD

1,2,3,

6,7,8-

HxCDD

1,2,3,

7,8,9-

HxCDD

1,2,3,4,

6,7,8-

HpCDD

OCDD 2,3,7,8-

TCDF

1,2,3,

7,8-

PeCDF

2,3,4,

7,8-

PeCDF

1,2,3,

4,7,8-

HxCDF

1,2,3,

6,7,8-

HxCDF

1,2,3,

7,8,9-

HxCDF

2,3,4,

6,7,8-

HxCDF

1,2,3,

4,6,7,8-

HpCDF

1,2,3,4,

7,8,9-

HpCDF

OCDF

Houston, TX,

USA

This study 0.9 4 6 12 12 211 781 5 5 8 10 9 11 4 49 6 101 1235

Athens, Greece Mandalakis et al.

(2002)

17 6 3 29 42 81 127 27 31 53 47 20 22 13 100 14 70 702

Bridgeport, CT,

USAa

CDEP-BAM

(2000)

1.1 6 7 12 12 124 467 12 8 13 19 13 14 30 59 8 70 873

Bristol, CT, USAb CDEP-BAM

(2000)

0.7 3 5 8 9 92 290 6 5 8 13 8 9 14 34 5 34 544

Site outside

Lankaster, UK

Lohmann et al.

(1999a)

1.7 10 12 28 22 260 1300 12 24 20 28 23 3 28 88 13 72 1945

Lankaster, UKc Lohmann et al.

(2000a)

4 17 16 31 26 268 780 25 7 49 75 58 7 63 198 29 160 1813

Industrial

complex, South

Koread

Oh et al. (2001) 4 4 9 14 10 92 222 58 59 84 81 65 31 89 259 46 381 1508

Gothenburg,

SwedeneTysklind et al.

(1993)

4 2 3 6 81 109 263 11 11 9 18 9 1 13 23 94 50 707

Los Angeles, CA,

USAf

Maisel and Hunt

(1990)

5 20 38 42 43 250 1900 21 77 77 150 250 42 35 95 9 56 3110

Padre Island, TX,

USAg

Cleverly et al.

(2000)

0.1 0.7 0.7 1.8 1.5 32 102 0.6 0.6 0.8 1.4 1.0 0.1 1.3 7.1 0.4 4.9 157

Big Bend, TX,

USAg

Cleverly et al.

(2000)

0.0 0.1 0.3 0.6 0.6 8.9 29 0.2 0.2 0.4 0.6 0.6 0.1 0.8 3.9 0.4 3.3 50

aCorrespond to an average of 16 samples.bAverage of 15 samples.cAverage of 8 samples.dIndustrial complex of chemical and oil refinery industries in South Korea; correspond to an average of three samples.eMean of three samples.fWinter of 1987; non-detected taken half of the detection limit.g2000 average.

O.

Co

rreaet

al.

/A

tmo

sph

ericE

nviro

nm

ent

38

(2

00

4)

66

87

–6

69

96692

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6693

between 17% and 88% with a mean of 53% (i.e., equally

divided between the two phases), and the 7-8-CDD/

CDFs ranged from 65% to 100% with a mean of 91%

(i.e., mostly sorbed in the particulate phase). Overall and

based on the data in Table 4, it can be seen that 2,3,7,8-

PCDDs tend to be more associated with the particulate

phase than the 2,3,7,8-PCDF congeners. These trends

probably reflect the lower vapor pressures of the more

chlorinated compounds when compared with the less

chlorinated compounds and the 2,3,7,8-PCDDs when

compared with the 2,3,7,8-PCDFs (Lee and Jones,

1999). The mean percentage in the particulate fraction

for all the samples for the 2,3,7,8-PCDD congeners

varied from 25% to 98%, with the majority 450%

while the 2,3,7,8-PCDF congeners fluctuated between

15% and 96%.

The total vapor to particle-bound ratios (V/P)

corresponding to the fall, winter, and spring seasons

were 0.92, 0.94, and 1.87, respectively, indicating that

winter ratios in Houston (with a winter average

temperature of 53 1F) may not be as low as those

reported by others. For example, Eitzer and Hites (1989)

reported winter V/P ratios of o0.5 for Bloomington, IN

(winter average temperature o37 1F).

Table 4

Percentage of each 2,3,7,8-PCDD/PCDF congener associated with th

2,3,7,8-PCDD/PCDFs–particle-bound frac

October November January

Congener

2,3,7,8-TCDDa 0.23 0.38 0.20

1,2,3,7,8-PeCDD 0.37 0.65 0.39

1,2,3,4,7,8-HxCDD 0.66 0.85 0.74

1,2,3,6,7,8-HxCDD 0.69 0.84 0.76

1,2,3,7,8,9-HxCDD 0.75 0.88 0.82

1,2,3,4,6,7,8-HpCDD 0.92 0.99 0.97

OCDD 0.99 1.00 0.99

2,3,7,8-TCDF 0.15 0.20 0.13

1,2,3,7,8-PeCDF 0.29 0.27 0.28

2,3,4,7,8-PeCDF 0.36 0.37 0.42

1,2,3,4,7,8-HxCDF 0.52 0.45 0.68

1,2,3,6,7,8-HxCDF 0.53 0.52 0.68

2,3,4,6,7,8-HxCDF 0.73 0.73 0.83

1,2,3,7,8,9-HxCDF 0.74 0.68 0.84

1,2,3,4,6,7,8-HpCDF 0.84 0.89 0.93

1,2,3,4,7,8,9-HpCDF 0.94 0.93 0.98

OCDF 0.97 0.99 0.99

Temperature (1F) 65.39 58.82 50.03

PM2.5 (mgm�3) 8.0 8.6 9.9

PM10 (mgm�3) 19.6 16.5 23.4

RH (%) 91.4 80.4 77.3

Note: Number in italics correspond to those congeners that were beloaFor 2,3,7,8-TCDD, the particle-bound concentrations were belowbCorrelation coefficients (r) were estimated with those particle-bou

above the detection limit.

Partitioning is significantly influenced by the vapor

pressure, a property strongly related to temperature.

The correlation between the mass fraction of each

congener associated with the particulate phase versus

temperature was analyzed by linear regression. With the

exception of 2,3,7,8-TCDD, the analysis showed a

negative correlation of the particulate fraction with

temperature (see correlation coefficients in Table 4). As

the temperature increased, the fraction associated with

particles decreased.

3.3. Modeling V/P partitioning

The observed data for Houston were analyzed using

four theoretical and experimental models that have been

proposed by different researchers to describe the

gas–particle phase distribution. The partitioning models

studied in this research include: a theoretically based

model by Junge (1977) and Pankow (1987) and two

experimentally defined models by Yamassaki et al.

(1982), Finzio et al. (1997), and Harner and Bidleman

(1998). Two of these models use the octanol/air

partitioning coefficient (Koa) as a descriptor of the

gas–particle partitioning of SOCs, while the other

e particulate phase over time

tion [P=ðV þ PÞ]

February March April Mean rb

0.21 0.21 0.26 0.2570.05 —

0.41 0.19 0.41 0.4070.14 �0.21

0.70 0.41 0.40 0.6370.15 �0.63

0.70 0.41 0.42 0.6370.14 �0.62

0.76 0.47 0.50 0.7070.14 �0.62

0.95 0.86 0.74 0.9070.07 �0.77

0.99 0.98 0.95 0.9870.02 �0.74

0.21 0.09 0.14 0.1570.04 �0.34

0.31 0.17 0.21 0.2670.05 �0.47

0.45 0.21 0.26 0.3570.07 �0.77

0.64 0.32 0.37 0.5070.12 �0.81

0.66 0.34 0.35 0.5170.12 �0.85

0.82 0.48 0.51 0.6870.12 �0.79

0.78 0.47 0.52 0.6770.12 �0.73

0.91 0.70 0.65 0.8270.09 �0.83

0.77 0.79 0.83 0.8570.07 �0.77

0.92 0.96 0.93 0.9670.03 �0.93

50.91 62.39 69.64 59.53 —

7.6 10.9 11.7

14.4 23.8 19.3

77.4 73.2 73.4

w the detection limit in either of the two phases.

the detection.

nd fractions for which the concentrations in both phases were

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–66996694

models use the subcooled liquid vapor pressure (P�L).

For the P�L-based models, the gas saturation method

implemented by Rordorf (1989) and the retention index

method initially developed by Eitzer and Hites (1988,

1998) were used to estimate the vapor pressure of the

2,3,7,8-substituted congeners. The Koa was calculated

using the Harner et al. (2000) method. The V/P

partitioning analysis in this study was made in two

ways: firstly, considering all the data (detects+non-

detects) and secondly, excluding those congeners below

the detection limit in either of the two phases. No

significant differences were found between these two

analyses. The V/P results reported in this study

correspond to the second analysis, that is, excluding

the non-detected concentrations in either of the two

phases.

3.3.1. Junge–Pankow model

Junge (1977) and Pankow (1987) based their parti-

tioning model on the linear Langmuir sorption isotherm.

The particle-bound fraction (f) of a specific chemical

was defined as

f ¼Cp

Cg þ Cp¼

cyP�L þ cy

; (1)

where Cp and Cg are the particulate and gas phase-

associated atmospheric concentrations, respectively, y is

the total suspended particulate surface area concentra-

tion (cm2 aerosol cm�3 air), P�L is the subcooled vapor

pressure of the pure compound (Pa), and c is a

parameter that depends on the heat of condensation of

the chemicals and the surface properties. The particle-

bound fraction (f) is related to the V/P ratio using

V=P ¼ 1=f21: A value of c ¼ 0:172Pam; assumed by

Junge for high molecular weight organics, was also used

in this study. Particle surface areas (y) of 4.2� 10�5 for

clean continental background, 3.5� 10�4 for back-

ground plus local sources, 1.5� 10�4 for rural condi-

tions and 1.1� 10�3m2m�3 for urban uses were

employed based on the work by Whitby (1978). In

this research, two methodologies were employed to

calculate P�L:

(i)

Rordorf (1989) related the vapor pressure of the

crystalline solid (P�s ) and the subcooled liquid vapor

pressure (P�L) using

logP�s

P�L

� �¼ �

DSF=R� �

ðTm=TÞ � 1� �2:3026

; (2)

where P�s is the solid-phase vapor pressure, DSF is

the entropy of fusion at the melting point (Tm)

(Jmol�1K�1), R is the universal gas constant

(8.314 Jmol�1K�1), and T is the ambient tempera-

ture (K).

(ii)

Eitzer and Hites (1988, 1998) correlated P�L for

PCDD/PCDFs with gas chromatographic retention

indices (GC-RI). The correlation was modified by

Hung et al. (2002) using the retention indices (RIs)

of Donnelly et al. (1987) and Hale et al. (1985), and

the vapor pressure estimates of p,p0-DDT suggested

by Lei et al. (1999) over the range 0–100 1C:

log P�L ¼

�1:34 RIð Þ

Tþ 1:67� 10�3 RIð Þ

�1320

Tþ 8:087: ð3Þ

The four different y values presented earlier along

with the two methods for calculating P�L were used to

generate the theoretical curves of f versus log P�L shown

in Fig. 2. The Houston data were then plotted in Fig. 2.

In general, it can be seen that the lower chlorinated

congeners (log P�L4� 4:5) were closer to the rural

partitioning curve in both approaches. In contrast, the

higher chlorinated congeners (log P�Lo� 4:5) tended to

follow the urban partitioning curve when Rordorf’s P�L

was used and the background plus local sources curve

with the Hung et al. (2002) approach. Using the Hung et

al. correlation, it was found that most of the data were

concentrated in the zone delineated between the rural

and background plus local sources curves.

3.3.2. log Kp � log P�L model

Yamassaki et al. (1982) defined the gas–particle

partitioning coefficient, Kp, as

Kp ¼ðF=TSPÞ

A; (4)

where Kp (m3mg�1) is the partitioning coefficient, F

(fgm�3) and A (fgm�3) are the analyte concentrations in

the particle and gas phases, respectively, and TSP is the

total suspended particle concentration (mgm�3). logKp

is linearly related to log P�L using

log Kp ¼ mr log P�L þ br: (5)

In this study, PM2.5 is proposed for use instead of TSP

in Eqs. (4) and (5) since TSP is no longer routinely

measured. PM2.5 data, obtained from the City of

Houston air-monitoring network, are summarized in

Table 4. The gas-to-particle partitioning coefficient (Kp),

thus, is redefined as

Kp ¼ðF=PM2:5Þ

A: (6)

Using Eqs. (5) and (6), logKp was plotted against

log P�L; where the P�

L values were determined using the

Rordorf (1989) and Hung et al. (2002) correlations. The

data for each monthly sampling event are shown in

Fig. 3. The slopes of the regression lines that best fit the

complete set of data are �1.23 and �1.09 using Rordorf

and Hung et al., respectively. The regression coefficients

for each set of P�L values were higher using the Hung

ARTICLE IN PRESS

0

0.2

0.4

0.6

0.8

1

-7 -6 -5 -4 -3 -2LogPL˚ (Rordorf)

Par

ticul

ate

frac

tion

(� )

October

November

January

February

March

April

Urban

Rural

CleanBackgroundBackground+local sources

0

0.2

0.4

0.6

0.8

1

-7 -6 -5 -4 -3 -2LogPL˚ (Hung et al.)

Par

ticul

ate

frac

tion

(�)

October

November

January

February

March

April

Urban

Rural

Clean Background

Background+localsources(B)

(A)

Fig. 2. Junge–Pankow model with predicted and measured 2,3,7,8-PCDD/PCDFs distributions based on subcooled liquid vapor

pressure data given by (A) Rodorf and (B) Hung et al. data from C408 (Lang Road).

O. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6695

et al. approach (r2 of 0.86 in Fig. 3B). This result validates

the fact that subcooled liquid vapor pressures derived

from GC-RI methods describe more accurately experi-

mental observations for PCDD/PCDF partitioning. The

proposed use of PM2.5 instead of TSP was compared with

results obtained by using PM10 in Eq. (4) to calculate Kp.

The analysis with PM10 yielded very similar regression

coefficients to those obtained with PM2.5.

In addition, since it is well established that the relative

humidity (RH, %) can affect Kp and since Houston has

high levels of humidity (average RH ranges from about

90% in the morning to about 60% in the afternoon), the

logarithm of the observed Kp values (expressed in terms

of both PM2.5 and PM10) was regressed against the RH

and logarithm of the subcooled liquid vapor pressure.

Based on the results of this analysis, it was observed that

better correlations are obtained when the percentage of

RH is included as a correlation parameter in Eq. (5). An

r2 of 0.91 was found when Kp, expressed in terms of

PM2.5, was correlated with RH along with log P�L: In

contrast, an r2 of 0.88 was obtained with Kp expressed as

a function of PM10 and correlated with the same

parameters (log P�L and RH).

3.3.3. log Kp � log Koa models

3.3.3.1. Finzio et al. model. Finzio et al. (1997)

correlated the partition coefficient (Kp) with the

octanol–air partition coefficient (Koa):

log Kp ¼ m log Koa þ b; (7)

where Koa is estimated from the octanol/water partition

coefficient (Kow) and Henry’s law constant (H), using a

relationship derived by Govers and Krop (1998):

Koa ¼KowRT

H: (8)

ARTICLE IN PRESS

LogK p = 1.2551LogK oa - 15.041

r 2 = 0.799

-2.5

-1.5

-0.5

0.5

1.5

2.5

10 11 12 13

LogKoa

LogK

p

October

November

January

February

March

April

Best fit

Fig. 4. logKp–logKoa for 2,3,7,8-PCDD/PCDFs.

LogK p = -1.2347LogP L ˚ - 6.2341

r 2 = 0.547

-2.5

-1.5

-0.5

0.5

1.5

2.5

-6 -5 -4 -3Log P L ˚ (Rordorf)

LogK

p

October

November

January

February

March

April

Best fit

(A)

LogK p = -1.0899LogP L ˚ - 5.7623

r 2 = 0.856

-2.5

-1.5

-0.5

0.5

1.5

2.5

-7 -6 -5 -4 -3Log P L ˚ (Hung et al.)

LogK

p

October

November

January

February

March

April

Best fit

(B)

Fig. 3. log Kp � log P�L plot for 2,3,7,8-PCDD/PCDFs using subcooled liquid vapor pressure data with (A) Rordorf and (B) Hung

et al. correlations.

O. Correa et al. / Atmospheric Environment 38 (2004) 6687–66996696

Harner et al. (2000) derived a simple method for

estimating Koa that correlates measured Koa values

against reported retention time indexes (RTI) for

dioxins and furans at a single temperature:

log Koa ¼ a0 þ b0ðRTIÞ; (9)

where a0 and b0 are coefficients that are estimated using

empirical relationships with temperature. Results using

Eq. (7) for the Houston data are presented in Fig. 4. The

data in Fig. 4 suggest that the octanol/air partition

coefficient is a satisfactory descriptor of the gas–particle

partitioning process. The monthly correlation coeffi-

cients for this model ranged from 0.86 to 0.96 and were

40.87 for most cases. The slope obtained in this study

was 1.26 and the y-intercept was equal to �15.04 for the

2,3,7,8-substituted congeners. These results are consis-

tent with values reported in the literature (e.g., see

Lohmann et al., 2000b).

3.3.3.2. Harner and Bidleman model. Harner and

Bidleman (1998) modified the work of Finzio et al.

(1997) and developed an octanol/air partition coefficient

adsorption model that requires knowledge of Koa and

fom (the organic matter fraction):

log Kp ¼ mr log Koa þ log f om � 11:91: (10)

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6697

In this study, the particulate fraction (f) is calculatedusing

f ¼KpðPM2:5Þ

KpðPM2:5Þ þ 1; (11)

where Kp is calculated using Eq. (7) and PM2.5 is used

instead of TSP. Fig. 5A shows the mean measured and

predicted particulate fractions using 10%, 20%, and

30% aerosol organic matter contents for an average

PM2.5 concentration of 9.4 mgm�3.

In general, it is noted from Fig. 5A that the

adsorption model proposed by Harner and Bidleman

(1998) underestimates the particulate fraction of 2,3,7,8-

PCDD/PCDFs for Houston. This indicates that their

model is sensitive to the particulate matter concentra-

tions. To test this hypothesis, the predicted particulate

fractions at 10%, 20%, and 30% of organic matter were

estimated using the PM10 concentration and the results

were compared with the predicted particulate fractions

obtained at PM2.5. The average PM10 concentration was

19.5mgm�3. The data in Fig. 5B confirm that PM10 is

more appropriate for use in Eq. (11). The data in Fig. 5B

0

0.2

0.4

0.6

0.8

1

9 10 11 12LogKoa

Par

ticul

ate

frac

tion

(� )

0

0.2

0.4

0.6

0.8

1

9 10 11 12LogKoa

Par

ticul

ate

frac

tion

(� )

(B)

(A)

Fig. 5. Mean observed and predicted percentage of 2,3,7,8-PCDD/PC

Koa using Harner and Bidleman model and (A) PM2.5 concentration

also illustrate that the observed particulate fractions of

2,3,7,8-PCDD/PCDFs are close to the partitioning

predicted by 20–30% organic matter curves, a finding

that is in agreement with Lohmann et al. (2000b).

In summary, the levels of 2,3,7,8-PCDDs and 2,3,7,8-

PCDFs were measured for ambient air in Houston, TX.

The average total summed concentration of the 2,3,7,8-

substituted congeners measured at five stations was

1235 fgm�3 and the average I-TEQ was calculated to be

18 fg I-TEQm�3. Relatively low 4-CDD/CDFs concen-

trations were measured. The 4-CDD/CDFs were found

to be primarily associated with the gas phase. In

contrast, the 5-6-CDD/CDFs were found evenly dis-

tributed between the two phases, while the 7-8-CDD/

CDFs were found mostly sorbed to the particulate

phase. While the Houston data were comparable to

dioxin measurements in other studies, three notable

differences were observed: (i) V/P ratios in the winter

were not as low as those reported in the literature

probably due to Houston’s relatively warm tempera-

tures; (ii) the highest chlorinated 2,3,7,8-PCDD/PCDFs

exhibited the highest concentrations; and (iii) congeners

13 14

30% o.m.

20% o.m.

10% o.m.

Observed Mean

PM 2.5 = 9.4 µg/m3

13 14

30% o.m.

20% o.m.

10% o.m.

Observed Mean

PM 10 = 19.5 µg/m3

DFs in particulate fraction plotted as a function of logarithm of

and (B) PM10 concentration (om stands for organic matter).

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–66996698

of PCDD were the major contributors to the I-TEQ.

The observed ambient data for Houston were modeled

using P�L-based and Koa-based models to describe the

gas–particle partitioning of SOCs. It was determined in

this research that P�L values calculated using RIs were

better estimates of the subcooled liquid vapor pressure

than those obtained using entropy approaches. In the P�L

models, the gas–particle partitioning coefficient (Kp) was

redefined in terms of PM2.5 and PM10 instead of TSP.

Although satisfactory correlation coefficients were

obtained using log Kp � log P�L and logKp–logKoa

models, the log Kp � log P�L model resulted in the

highest correlation coefficient. While an r2 of 0.86 was

obtained with the log Kp � log P�L model, an r2 of 0.80

was found with the logKp–logKoa model. The P�L-based

model was also found to better fit the monthly

experimental data. In general, the r2 values ranged from

0.90 to 0.98 with the log Kp � log P�L model against

0.86–0.96 obtained with the logKp–logKoa. The regres-

sion lines obtained with P�L in the different sampling

events were less steep and closer to equilibrium

conditions than those obtained with Koa.

Acknowledgments

The authors thank the Texas Commission on Envir-

onmental Quality (TCEQ) and the Texas Advanced

Technology Program for financial support. We also

gratefully acknowledge The Houston Regional Mon-

itoring Corporation (HRM) and the City of Houston for

providing access to their monitoring sites.

References

Alcock, R.E., Jones, K.C., 1996. Dioxins in the environment: a

review of trend data. Environmental Science and Technol-

ogy 30, 3133–3143.

Alcock, R.E., Behnisch, P.A., Jones, K.C., Hagenmaier, H.,

1998. Dioxin-like PCBs in the environment—human ex-

posure and the significance of sources. Chemosphere 37,

1457–1472.

Alcock, R.E., Sweetman, A.J., Jones, K.C., 2001. A congener-

specific PCDD/F emissions inventory for the UK: do

current estimates account for the measured atmospheric

burden? Chemosphere 43, 183–194.

Bidleman, T.F., 1988. Atmospheric processes. Environmental

Science and Technology 22, 361–367.

Bidleman, T.F., Foreman, W.T., 1987. Vapor–particle parti-

tioning of semivolatile organic compounds. In: Hites, R.A.,

Eisenreich, S.J. (Eds.), Sources and Fates of Aquatic

Pollutants. American Chemical Society, Washington, DC,

pp. 27–56.

Bleux, N., De Fre, R., 2000. Measurements and modeling of

PCDD/PCDF concentrations in particle and gas phase in

Flanders. Journal of Aerosol Science 31, S358–S359.

CDEP-BAM, 2000. Evaluation of the Long Duration Ambient

Air Dioxin Database. Connecticut, Department of Envir-

onmental Protection, Bureau of Air Management, Acton,

MA, p. 62.

Cleverly, D.H., Winters, D., Ferrario, J., Schaum, J., Schweer,

G., Buchert, J., Greene, C., Dupuy, A., Byrne, C., 2000. The

National Dioxin Air monitoring Network (NDAMN):

results of the first year of atmospheric measurements of

CDDs, CDFs and dioxin-like PCBs in rural and agricultural

areas of the United States: June 1998–June 1999. Organo-

halogen Compounds 45, 248–251.

Donnelly, J.R., Munslow, W.D., Mitchum, R.K., Sovocool,

G.W., 1987. Correlation of structure with retention index

for chlorinated dibenzo-p-dioxins. Journal of Chromato-

graphy 392, 51–63.

Edgerton, S.A., Czuczwa, J.M., Rench, J.D., 1989. Ambient air

concentrations of polychlorinated dibenzo-p-dioxins and

dibenzofurans in Ohio: sources and health risk assessment.

Chemosphere 18, 1713–1730.

Eitzer, B.D., Hites, R.A., 1988. Vapor pressures of chlorinated

dioxins and dibenzofurans. Environmental Science and

Technology 22, 1362–1364.

Eitzer, B.D., Hites, R.A., 1989. Polychlorinated dibenzo-p-

dioxins and dibenzofurans in the ambient atmosphere of

Bloomington, Indiana. Environmental Science and Tech-

nology 23, 1389–1395.

Eitzer, B.D., Hites, R.A., 1998. Additions and corrections:

vapor pressures of chlorinated dioxins and dibenzofurans.

Environmental Science and Technology 32, 2804.

Finzio, A., Mackay, D., Bidleman, T., Harner, T., 1997.

Octanol–air partition coefficient as a predictor of partition-

ing of semi-volatile organic chemicals to aerosols. Atmo-

spheric Environment 31, 2289–2296.

Govers, H.A.J., Krop, H.B., 1998. Partition constants of

chlorinated dibenzofurans and dibenzo-p-dioxins. Chemo-

sphere 37, 2139–2152.

Hale, M.D., Hileman, F.D., Mazer, T., Shell, T.L., Noble,

R.W., Brooks, J.J., 1985. Mathematical modeling of

temperature programmed capillary gas chromatographic

retention indexes for polychlorinated dibenzofurans. Ana-

lytical Chemistry 57, 640–648.

Harner, T., Bidleman, T.F., 1998. Octanol–air partition

coefficient for describing particle/gas partitioning of aro-

matic compounds in urban air. Environmental Science and

Technology 32, 1494–1502.

Harner, T., Green, N.J.L., Jones, K.C., 2000. Measurements of

octanol–air partition coefficients for PCDD/Fs: a tool in

assessing air–soil equilibrium status. Environmental Science

and Technology 34, 3109–3114.

Hung, H., Blanchard, P., Poole, G., Thibert, B., Chiu, C.H., 2002.

Measurement of particle-bound polychlorinated dibenzo-p-

dioxins and dibenzofurans (PCDD/Fs) in Arctic air at Alert,

Nunavut, Canada. Atmospheric Environment 36, 1041–1050.

Hunt, G.T., Maisel, B.E., Zielinska, B.A., 1997. A source of

PCDDs/PCDFs in the atmosphere of Phoenix, AZ.

Organohalogen Compounds 33, 145–150.

Junge, C.E., 1977. Basic consideration about trace constituents

in the atmosphere as related to the fate of global pollutants.

In: Suffet, I.H. (Ed.), Fate of Pollutants in the Air and

Water Environments. Part I. Wiley-Interscience, New York,

NY, pp. 7–26.

ARTICLE IN PRESSO. Correa et al. / Atmospheric Environment 38 (2004) 6687–6699 6699

Kouimtzis, T., Samara, C., Voutsa, D., Balafoutis, Ch., Muller,

L., 2002. PCDD/Fs and PCBs in airborne particulate matter

of the greater Thessaloniki area, N. Greece Chemosphere

47, 193–205.

Lee, R.G., Jones, K.C., 1999. Gas–particle partitioning of

atmospheric PCDD/Fs: measurements and observations on

modeling. Environmental Science and Technology 33,

3596–3604.

Lei, Y.D., Wania, F., Shiu, W.Y., 1999. Vapor pressures of the

polychlorinated naphthalenes. Journal of Chemical Engi-

neering Data 44, 577–582.

Lohmann, N., Green, N.J., Jones, K.C., 1999a. Detailed studies

of the factors controlling atmospheric PCDD/F concentra-

tions. Environmental Science and Technology 33,

4440–4447.

Lohmann, N., Green, N.J., Jones, K.C., 1999b. Atmospheric

transport of polychlorinated dibenzo-p-dioxins and diben-

zofurans (PCDD/Fs) in air masses across the United

Kingdom and Ireland: evidence of emissions and depletion.

Environmental Science and Technology 33, 2872–2878.

Lohmann, R.L., Lee, R.G.M., Green, N.J.L., Jones, K.C.,

2000a. Gas–particle partitioning of PCDD/Fs in daily air

samples. Atmospheric Environment 34, 2529–2537.

Lohmann, R., Harner, T., Thomas, G.O., Jones, K.C., 2000b.

A comparative study of the gas–particle partitioning of

PCDD/Fs, PCBs, and PAHs. Environmental Science and

Technology 34, 4943–4951.

Luthardt, P., Mayer, J., Fuchs, J., 2000. Total TEQ emissions

(PCDD/F and PCB) from industrial sources. Organohalo-

gen Compounds 45, 344–347.

McKay, G., 2002. Dioxin characterisation, formation and

minimisation during municipal solid waste (MSW) incin-

eration: review. Chemical Engineering Journal 86, 343–368.

Mader, B.T., Pankow, J.F., 2001a. Gas/solid partitioning of

semivolatile organic compounds (SOCs) to air filters. 3. An

analysis of gas adsorption artifacts in measurements of

atmospheric SOCs and organic carbon (OC) when using

Teflon membrane filters and quartz fiber filters. Environ-

mental Science and Technology 35, 3422–3432.

Mader, B.T., Pankow, J.F., 2001b. Gas/solid partitioning of

semivolatile organic compounds (SOCs) to air filters. 2.

Partitioning of polychlorinated dibenzodioxins, polychlori-

nated dibenzofurans, and polycyclic aromatic hydrocarbons

to quartz fiber filters. Atmospheric Environment 35,

1217–1223.

Maisel, B.E., Hunt, G.T., 1990. Background concentrations of

PCDDs/PCDFs in ambient air—a comparison of toxic

equivalency factor (TEF) models. Chemosphere 20,

771–778.

Mandalakis, M., Tsapakis, M., Tsoga, A., Stephanou, E.G.,

2002. Gas–particle concentrations and distribution of

aliphatic hydrocarbons, PAHs, PCBs and PCDD/Fs in the

atmosphere of Athens (Greece). Atmospheric Environment

36, 4023–4035.

Oh, J.E., Choi, J.S., Chang, Y.S., 2001. Gas/particle partition-

ing of polychlorinated dibenzo-p-dioxins and dibenzofurans

in atmosphere; evaluation of predicting models. Atmo-

spheric Environment 35, 4125–4134.

Pankow, J.F., 1987. Review and comparative analysis of the

theories on partitioning between the gas and aerosol

particulate phases in the atmosphere. Atmospheric Envir-

onment 21, 2275–2283.

Rappe, C., 1996. Sources and environmental concentrations of

dioxins and related compounds. Pure and Applied Chem-

istry 68, 1781–1789.

Rordorf, B.F., 1989. Prediction of vapor pressures, boiling

points and enthalpies of fusion for twenty-nine halogenated

dibenzo-p-dioxins and fifty-five dibenzofurans by a vapor

pressure correlation method. Chemosphere 18, 783–789.

Tiernan, T.O., Wagel, D.J., Vanness, G.F., Garrett, J.H.,

Solch, J.G., Harden, L.A., 1989. PCDD/PCDF in the

ambient air of a metropolitan area in the US. Chemosphere

19, 541–546.

Tysklind, M., Fangmark, I., Marklund, S., Lindskon, A.,

Thaning, L., 1993. Atmospheric transport and transfor-

mation of polychlorinated dibenzo-p-dioxins and dibenzo-

furans. Environmental Science and Technology 27,

2190–2197.

USEPA, 1999. Compendium method TO-9A, ‘‘Determination

of polychlorinated, polybrominated and brominated/chlori-

nated dibenzo-p-dioxins and dibenzofurans in ambient air’’.

EPA/625/R-96/010b. Center for Environmental Research

Information, Office of Research and Development, Cincin-

nati, OH.

Whitby, K.T., 1978. The physical characteristics of sulfur

aerosols. Atmospheric Environment 12, 135–159.

Yamassaki, H., Kuwata, K., Miyamoto, H., 1982. Effects of

ambient temperature on aspects of airborne polycyclic

aromatic hydrocarbons. Environmental Science and Tech-

nology 16, 189–194.