concentrations and vapor–particle partitioning of polychlorinated dibenzo-p-dioxins and...
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Atmospheric Environment 38 (2004) 6687–6699
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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: [email protected] (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.
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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 thecrystalline 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 forPCDD/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.
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