Supporting Information€¦ · 1 Supporting Information Modeling gas/particle partitioning of...
Transcript of Supporting Information€¦ · 1 Supporting Information Modeling gas/particle partitioning of...
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Supporting Information
Modeling gas/particle partitioning of polybrominated diphenyl
ethers (PBDEs) in atmosphere: A review
Li-Na Qiao1,2,3, Peng-Tuan Hu1,2,3, Robie Macdonald4, Kurunthachalam Kannan5, Anatoly
Nikolaev6, Yi-Fan Li1,2,3,7*
1 International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), State Key
Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin
150090, China
2 International Joint Research Center for Arctic Environment and Ecosystem (IJRC-AEE),
Polar Academy, Harbin Institute of Technology, Harbin 150090, China
3 School of Environment, Harbin Institute of Technology, Harbin 150090, China
4 Institute of Ocean Sciences, Department of Fisheries and Oceans, P.O. Box 6000, Sidney,
BC, V8L 4B2, Canada
5 Department of Pediatrics and Department of Environmental Medicine, New York University
School of Medicine, New York, NY 10016, USA
6 Institute of Natural Sciences, North-Eastern Federal University, Russia
7 IJRC-PTS-NA, Toronto, Ontario, M2N 6X9, Canada
*Corresponding author:
E-mail address: [email protected] (Yi-Fan Li)
IJRC-PTS
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Text
S1. Equilibrium models
S1.1 Junge-Pankow model
The Junge-Pankow (J-P) model was originally suggested by Junge and later critically
reviewed by Pankow, assuming the SVOCs are entirely adsorbed onto the surface of particle
matters. The particulate phase fraction (ϕP) in the J-P model could be calculates by
𝜙P =𝐶J𝜃
𝐶J𝜃+𝑃L (S1)
where Ɵ (cm2surfacecm-3
air) is the particle surface area concentration, which was assumed to be
1.1×10−5 for urban air (Bidleman, 1988) , 1.5×10−6 for rural air (Bidleman, 1988). CJ (Pa cm)
is based on the heat of desorption from the particle surface, the heat of vaporization of the
compound, and the moles of adsorption sites on the aerosol and typically used as 17.2 Pa cm.
The PL (Pa) is the sub-cooled liquid vapor pressure, which is a function of temperature T (K).
S1.2 Harner-Bidleman model
Pankow et al. (Pankow, 1994) derived the equations to describe the G/P partitioning of
SVOCs based adsorption mechanism,
𝐾P = 𝑁𝑠𝐴𝑡𝑠𝑝𝑇𝑒(𝑄1−𝑄𝑣) 𝑅𝑇⁄
1600𝑃𝐿0 (𝑃𝐿
0 in torr) (S2)
And based on both adsorption and absorption mechanism,
𝐾P = 1
𝑃𝐿0 [
𝑁𝑠𝐴𝑡𝑠𝑝𝑇𝑒(𝑄1−𝑄𝑣) 𝑅𝑇⁄
1600+
760𝑓𝑂𝑀𝑅𝑇
𝑀𝑊𝑜𝑚𝜁𝑜𝑚106] (𝑃𝐿0 in torr) (S3)
Then, an absorption mechanism for gas-particle partitioning of SVOCs was described in
relation to the chemical octanol-air partition coefficient, KOA (unitless), by Finizio et al.(Finizio
et al., 1997),
log𝐾P = log𝐾𝑂𝐴 + log1.22×10−12𝑓𝑂𝑀𝑀𝑜𝑐𝑡𝜁𝑜𝑐𝑡
𝑀𝑊𝑜𝑚𝜁𝑜𝑚 (S4)
Later, Pankow modified the absorption equation(Pankow, 1998),
log𝐾P = log𝐾𝑂𝐴 + log𝜁𝑜𝑐𝑡
𝜁𝑜𝑚+ log
𝑀𝑜𝑐𝑡𝑓𝑂𝑀
1012𝑀𝑊𝑜𝑚𝜌𝑜𝑐𝑡 (S5)
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With assuming absorption is the main processes between gas- and particle- phases, Harner
and Bidleman derived an absorption equation under equilibrium condition to calculate KP,
designed as KP-HB, given by (Harner and Bidleman, 1998)
log KP-HB = log KOA + log fOM -11.91 (S6)
where fOM is the fraction of the particle mass.
S1.3 Dachs-Eisenreich model
Dachs-Eisenreich (D-E) model was developed considering both absorption and adsorption
mechanisms(Dachs and Eisenreich, 2000). Assuming that EC is a surrogate for the soot phase,
in this study, the D-E model can be formulated as
KP-DE = KP-HB + KP-EC (S7)
where KP-HB represents the absorption term of D-E model, whereas KP-EC is the adsorption term
of D-E model, which is given by
KP-EC = 10-12fECKSA (S8)
where KSA is the soot-air partition coefficient (L kg-1), fEC (unitless) is the fraction of elemental
carbon (EC) in particle matters(Zhen et al., 2014).
Then, van Noort(van Noort, 2003) introduced the equation by a thermodynamic
estimation model to estimate the value of KSA for different PBDE congeners:
log𝐾𝑆𝐴 = −0.85log𝑃𝐿 + 8.94 − log (998
𝑎𝐸𝐶) (S9)
The value of 18.21 m2g-1 was used for αEC in the present study.
S1.4 pp-LFER model
The poly-parameter liner free energy relationship (pp-LFER) model considers the G/P
partitioning of SVOCs at molecular level. This pp-LFER approach was developed by
Abraham(Abraham, 1993), and modified by Goss(Goss, 2005) to form a single pp-LFER
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equation (Eq.S10)
log 𝐾𝑃‐L = 𝑠𝑆 + 𝑎𝐴 + 𝑏𝐵 + 𝑣𝑉 + 𝑙𝐿 + 𝑐 (S10)
where the capital letter V is the molar volume, L is the hexadecane/air partition coefficient, S
characterizes the dipolarity/polarizability of the substance, A describes the H-bond donor
properties, B the H-bond acceptor properties. The descriptors S, A, and B characterize the
specific interactions. The two descriptors L, V are used to describe non-specific interactions
like cavity formation energy and the energy that comes from dispersive van der Waals
interaction(Endo and Goss, 2014). The corresponding small letters are known as system
parameters and reflect the matrix-specific solute-independent energetic contribution to the KP.
The system parameters are given in Table S3.
Before making the use of the pp-LFER model to predict the G/P partitioning behavior, the
chemical descriptors need to be known for each target compounds. However, the descriptors
are not available for most of the chemicals, such as BDE-209. For BDE-209, the parameters of
pp-LFER model are calculated by present study.
The molecular formula of BDE-209 is C12Br10O. The V value is calculated by the
following equation:
𝑉 = ∑ (𝑉𝑋𝑖×𝑁𝑖)−(∑ 𝑁𝑖𝑖 +1)×6.56𝑖
100 (S11)
where the i represents the atom in the chemical, such as C, Br and O. Ni is the number of the i
atom in the chemical. When estimating the value of V, it should be noted that in the calculation
of molecular characteristic volumes, 6.56 cm3mol-1 is subtracted for each bond, no matter
whether single, double or triple. The list of atomic Vx values (cm3mol-1) needed for the
calculation of capital letter V of BDE-209 are as follows: C, 16.35; Br, 26.21; O,
12.43(Abraham and Mcgowan, 1987).
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A is zero for all the PBDE congeners. The S, B, L values reported by Stenzel(Stenzel et
al., 2013) for PBDEs congeners have linear relationship with the molecular weight,
respectively. The linear relationship of the S=0.0007MW + 1.0788 (R2 = 0.8772), B =
0.001MW - 0.145 (R2 = 0.9791), L = 0.0125MW + 4.5865 (R2 = 0.9969). Then the parameters
of BDE-209 needed for the LFER model could be gained.
S1.5 mp-pp-LFER model
Later, GÖtz developed the pp-LFER sorption model to predict the G/P partitioning of
SVOCs, considering the multiphase of particles(GÖtz et al., 2007).
𝐾P∗
= ∑ 𝐶𝑖𝐾𝑖,
𝑏𝑢𝑙𝑘
𝑎𝑖𝑟
𝑖⋯𝑛𝑖 + ∑ 𝐶𝑗𝐾
𝑗,𝑠𝑢𝑟𝑓
𝑎𝑖𝑟
𝑗⋯𝑛𝑗 (S12)
With considering the element carbon, (NH4)2SO4, NH4Cl as the adsorbent in adsorption process,
and the organic matter and organic polymers as the absorbent in the absorption process. The
G/P partitioning quotient, 𝐾𝑃‐𝑚𝐿 , in unit of μg/m3, could be calculated by the following
equation (Shahpoury et al., 2016),
𝐾𝑃‐𝑚𝐿 = (𝐾𝐸𝐶 × 𝑎𝐸𝐶 × 𝑓𝐸𝐶 + 𝐾(𝑁𝐻4)2𝑆𝑂4× 𝑎(𝑁𝐻4)2𝑆𝑂4
× 𝑓(𝑁𝐻4)2𝑆𝑂4+ 𝐾𝑁𝐻4𝐶𝑙 × 𝑎𝑁𝐻4𝐶𝑙 ×
𝑓𝑁𝐻4𝐶𝑙 + 𝐾𝐷𝑀𝑆𝑂/𝜌𝐷𝑀𝑆𝑂 × 𝑓𝑂𝑀,1 + 𝐾𝑃𝑈 × 𝑓𝑂𝑀,2) × 10−6 (S13)
The parameters in Eq. (S13) are shown in SI Table S4, respectively.
The log KP values calculated by Eqs (S10), and (S13) should be corrected by temperature
using the following equation:
𝑙og𝐾P = 𝑙og𝐾𝑃0 + (∆𝐻𝑣𝑎𝑝/2.303R)(1/T − 1/T0) (S14)
where the ∆Hvap (KJ/mol) of PBDEs are shown in SI Table S3.
S2 QSPR model
QSPR model is an empirical model considering the molecular mechanism and the effect
of temperature into the G/P partitioning behavior of PBDEs. Quantum chemical computations
were implemented at B3LYP/6-31G (d,p) level of theory based on the neutral electronic ground
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state of PBDE congeners by Gaussian 09 software package. The logKP value at the ambient
temperature range from 10 to 30 oC could be calculated by
𝑙og𝐾𝑃 = (0.026 ± 0.001)𝑉′ + (−0.030 ± 0.005)𝑇 + (−0.858 ± 0.272)𝑞𝐶− + (3.864 ±
1.342)𝑞𝐻+ + (0.002 ± 1.394) (S15)
In above equation, the V’ is the molecular volume, T is the ambient temperature (K), qC-
is the most negative charge on a carbon atom, qH+ is the most positive charge on a hydrogen
atom. The values of these parameters are shown in SI Table S5.
S3 The characteristic condensation temperature of PBDEs
A parameter, the characteristic temperature of condensation (TC), was developed (Wania
and Mackay, 1996) at which the chemical is equally partitioned between the gaseous and
particulate phases. Equation to calculate the values of TC was not given in the paper (Wania
and Mackay, 1996), however, we found out that the characteristic condensation temperature
was calculated by assuming the chemical’s logPL(TC) equals -4. As shown in Table S9, using
the values of TC given by (Wania and Mackay, 1996), and the published Clausius-Clapeyron
coefficients AL and BL values, we can calculate the values of logPL(TC) (= AL + BL / TC) which
is equal to -4 for all chemicals listed in the Table. Taking -HCH for example, as shown in the
Table S9 from the paper (see following table), the values of TC for -HCH is -40oC, and the
parameters AL is 11.34 and BL is -3575, then logPL(TC) = 11.34 - 3575/(273.15-40) = -4. Thus,
we calculated the characteristic condensation temperature of PBDEs in that method, with the
AL and BL shown in Table S1. The Tc of PBDEs is shown in Fig. 6. By using equation logKOA
= 6.46 - logPL (Yang et al, 2019), we have logKOA(TC) = 10.46.
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Figures
Fig. S1. logKOA for selected SVOCs (PBDEs, PCBs, PAHs, PCNs, OCPs, PCDD/Fs) at the
temperature of 25oC. Two vertical dashed lines represent two threshold values of logKOA
(logKOA1 and logKOA2). It is notice that PBDEs have highest values of logKOA from 9.5 for
BDE-28 to 15.1 for BDE-209.
BD
E-2
8
BD
E-4
7
BD
E-9
9
BD
E-1
00
BD
E-1
53
BD
E-1
54
BD
E-1
83
BD
E-2
09
4
6
8
10
12
14
16
log K
OA
logKOA1
logKOA2
PBDEs
PC
B-1
8
PC
B-4
4
PC
B-9
5
PC
B-1
26
PC
B-1
53
PC
B-1
55
PC
B-1
80
PC
B-1
87
PCBs
Acy
Flu
Ph
e
Pyr
BaA
Ch
r
Bap
Db
ah
A
SVOCs
PAHs
CN
-13
CN
-27
CN
-46
CN
-52
CN
-53
CN
-69
CN
-72
CN
-73
PCNs
α-H
CH
β-H
CH
EN
d I
EN
d I
I
CC
CN
TN
p,p
'-D
DE
OCPs
TC
DD
PeC
DD
Hx
CD
D
OC
DD
TC
DF
PeC
DF
Hx
CD
F
OC
DF
PCDD/Fs
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Fig. S2. The G/P partition coefficients of PBDEs as functions of logKOA calculated by two
equations. First one is G/P partition equation logKP-HB at equilibrium (Eq. (7)), presented by
the dark blue straight line, and the second one is our newly developed G/P partition equation
at steady state logKP-LMY (Eq. (13)), presented by the red curve in the figure. Two threshold
values of logKOA (logKOA1 and logKOA2, represented by two vertical purple dashed lines) divide
the range of logKOA into three domains: the equilibrium (EQ) domain, the nonequilibrium (NE)
domain, and the maximum partition (MP) domain (Li et al., 2015).
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Fig. S3. The first and second threshold temperatures, tTH1 and tTH2 for 8 PBDE congeners,
which divide the temperature space into the same three domains (EQ, NE, and MP).
-30
-20
-10
0
10
20
30
40
50
60
70
80
28 47 99 100 153 154 183 209
Th
resh
old
Tem
pera
ture o
C
PBDEs
tTH1 tTH2
EQ Domain
NE Domain
MP Domain
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Fig. S4. The ranges of logKOA of selected 5 PBDEs for the three different temperature spans
(50 − -50oC, 38 − -22oC, and 30 − 10oC). The ranges of logKOA for the QSPR and L-J models
are shorter since these two models are empirical ones with monitoring temperature being 30
− 10oC for the former and 38 − -22oC for the latter.
BDE-28
BDE-47
BDE-99
BDE-100
BDE-153
BDE-154
BDE-183
BDE-209
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
logKOA
PB
DE
s
EQ NE MP
logKOA1 logKOA2
-50oC — 50oC
-22oC — 38oC
10oC — 30oC
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Fig. S5. The predicted logKP (m3μg-1) versus logKOA for eight selected PBDE congeners (BDE-
28, -47, -99, -100, -153, -154, -183, -209) by H-B model, D-E model, pp-LFER model, mp-pp-
LFER model, J-P model, QSPR model, L-J empirical model, and L-M-Y model.
-6
-4
-2
0
2
4
6
8
10
12
14
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
log
KP
m
3μ
g-1
log KOA
pp-LFER-28 pp-LFER-47 pp-LFER-99 pp-LFER-100
pp-LFER-153 pp-LFER-154 pp-LFER-183 pp-LFER-209
mp-pp-LFER-28 mp-pp-LFER-47 mp-pp-LFER-99 mp-pp-LFER-100
mp-pp-LFER-153 mp-pp-LFER-154 mp-pp-LFER-183 mp-pp-LFER-209
L-J-28 L-J-47 L-J-99 L-J-100
L-J-153 L-J-154 L-J-183 QSPR-28
QSPR-47 QSPR-99 QSPR-100 QSPR-153
QSPR-154 QSPR-183 QSPR-209 D-E
J-P H-B L-M-Y
log KOA2
10 - 30 oC
-22 - 38 oC
-50 - 50 oC
-1.53
MP
log KOA1
EQ NE
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Fig. S6. The logKP of 8 PBDEs congeners predicted by H-B model and D-E model vs logKOA.
(a): fOM=0.1, fEC=0.02; (b): fOM=0.1, fEC=0.05; (c): fOM=0.1, fEC=0.1; (d): fOM=0.1 and fEC=0.2.
The two dashed blue lines give the ±1 log unit boundary for logKP-HB. The two dashed gray
lines represent the two logKOA threshold values (logKOA1 and logKOA2).
-6
-4
-2
0
2
4
6
8
8.5 10.5 12.5 14.5 16.5 18.5
log
KP
m3
μg
-1
log KOA
D-E model H-B model
fOM=0.1 fEC=0.02
(a)
20
EQ NE MP
log KOA2log KOA1 -6
-4
-2
0
2
4
6
8
8.5 10.5 12.5 14.5 16.5 18.5
log
KP
m3
μg
-1
log KOA
D-E model H-B model
fOM=0.1 fEC=0.05
(b)
20
EQ NE MP
log KOA2log KOA1
-6
-4
-2
0
2
4
6
8
8.5 10.5 12.5 14.5 16.5 18.5
log
KP
m3
μg
-1
log KOA
D-E model H-B model
fOM=0.1 fEC=0.1
(c)
20
EQ NE MP
log KOA2log KOA1 -6
-4
-2
0
2
4
6
8
8.5 10.5 12.5 14.5 16.5 18.5
log
KP
m3
μg
-1
log KOA
D-E model H-B model
fOM=0.1 fEC=0.2
(d)
20
EQ NE MP
log KOA2log KOA1
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Fig. S7. Variation of logKP-LMY (the thick red line) and logKP-LJ (the thin lines) versus logKOA
for the seven PBDE congeners (BDE-28, -47, -99, -100, -153, 154, and -183). The line of
logKP-HB (the thick blue line) is also included for comparison.
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Tables
Table S1. Parameters AO, BO, AL, and BL for all 209 PBDE congeners (Yang et al., 2018).
PBDEs Ao Bo AL BL PBDEs Ao Bo AL BL
BDE-1 -4.14 3415 10.60 -3415 BDE-37 -4.61 4286 11.07 -4286
BDE-2 -3.90 3415 10.36 -3415 BDE-38 -4.84 4286 11.3 -4286
BDE-3 -3.70 3415 10.16 -3415 BDE-39 -4.84 4286 11.3 -4286
BDE-4 -4.93 3851 11.39 -3851 BDE-40 -6.08 4722 12.54 -4722
BDE-5 -4.71 3851 11.17 -3851 BDE-41 -5.86 4722 12.32 -4722
BDE-6 -4.71 3851 11.17 -3851 BDE-42 -5.86 4722 12.32 -4722
BDE-7 -4.49 3851 10.95 -3851 BDE-43 -6.08 4722 12.54 -4722
BDE-8 -4.49 3851 10.95 -3851 BDE-44 -6.08 4722 12.54 -4722
BDE-9 -4.71 3851 11.17 -3851 BDE-45 -6.30 4722 12.76 -4722
BDE-10 -4.95 3851 11.41 -3851 BDE-46 -6.30 4722 12.76 -4722
BDE-11 -4.49 3851 10.95 -3851 BDE-47 -5.64 4722 12.1 -4722
BDE-12 -4.26 3851 10.72 -3851 BDE-48 -5.86 4722 12.32 -4722
BDE-13 -4.26 3851 10.72 -3851 BDE-49 -5.86 4722 12.32 -4722
BDE-14 -4.49 3851 10.95 -3851 BDE-50 -6.08 4722 12.54 -4722
BDE-15 -4.03 3851 10.49 -3851 BDE-51 -6.08 4722 12.54 -4722
BDE-16 -5.51 4286 11.97 -4286 BDE-52 -6.08 4722 12.54 -4722
BDE-17 -5.29 4286 11.75 -4286 BDE-53 -6.30 4722 12.76 -4722
BDE-18 -5.51 4286 11.97 -4286 BDE-54 -6.52 4722 12.98 -4722
BDE-19 -5.73 4286 12.19 -4286 BDE-55 -5.64 4722 12.1 -4722
BDE-20 -5.29 4286 11.75 -4286 BDE-56 -5.64 4722 12.1 -4722
BDE-21 -5.07 4286 11.53 -4286 BDE-57 -5.86 4722 12.32 -4722
BDE-22 -5.06 4286 11.52 -4286 BDE-58 -5.86 4722 12.32 -4722
BDE-23 -5.29 4286 11.75 -4286 BDE-59 -6.08 4722 12.54 -4722
BDE-24 -5.51 4286 11.97 -4286 BDE-60 -5.41 4722 11.87 -4722
BDE-25 -5.06 4286 11.52 -4286 BDE-61 -5.64 4722 12.1 -4722
BDE-26 -5.29 4286 11.75 -4286 BDE-62 -5.86 4722 12.32 -4722
BDE-27 -5.51 4286 11.97 -4286 BDE-63 -5.64 4722 12.1 -4722
BDE-28 -4.84 4286 11.30 -4286 BDE-64 -5.86 4722 12.32 -4722
BDE-29 -5.06 4286 11.52 -4286 BDE-65 -6.08 4722 12.54 -4722
BDE-30 -5.28 4286 11.74 -4286 BDE-66 -5.42 4722 11.88 -4722
BDE-31 -5.06 4286 11.52 -4286 BDE-67 -5.64 4722 12.1 -4722
BDE-32 -5.29 4286 11.75 -4286 BDE-68 -5.64 4722 12.1 -4722
BDE-33 -5.06 4286 11.52 -4286 BDE-69 -5.86 4722 12.32 -4722
BDE-34 -5.29 4286 11.75 -4286 BDE-70 -5.64 4722 12.1 -4722
BDE-35 -4.84 4286 11.3 -4286 BDE-71 -5.86 4722 12.32 -4722
BDE-36 -5.06 4286 11.52 -4286 BDE-72 -5.86 4722 12.32 -4722
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Table S1. Parameters AO, BO, AL, and BL for all 209 PBDE congeners (Yang et al., 2018).
PBDEs Ao Bo AL BL PBDEs Ao Bo AL BL
BDE-73 -6.08 4722 12.54 -4722 BDE-110 -6.43 5157 12.89 -5157
BDE-74 -5.41 4722 11.87 -4722 BDE-111 -6.43 5157 12.89 -5157
BDE-75 -5.63 4722 12.09 -4722 BDE-112 -6.65 5157 13.11 -5157
BDE-76 -5.64 4722 12.1 -4722 BDE-113 -6.65 5157 13.11 -5157
BDE-77 -5.19 4722 11.65 -4722 BDE-114 -5.99 5157 12.45 -5157
BDE-78 -5.41 4722 11.87 -4722 BDE-115 -6.21 5157 12.67 -5157
BDE-79 -5.41 4722 11.87 -4722 BDE-116 -6.43 5157 12.89 -5157
BDE-80 -5.64 4722 12.1 -4722 BDE-117 -6.43 5157 12.89 -5157
BDE-81 -5.19 4722 11.65 -4722 BDE-118 -5.99 5157 12.45 -5157
BDE-82 -6.43 5157 12.89 -5157 BDE-119 -6.21 5157 12.67 -5157
BDE-83 -6.65 5157 13.11 -5157 BDE-120 -6.21 5157 12.67 -5157
BDE-84 -6.87 5157 13.33 -5157 BDE-121 -6.43 5157 12.89 -5157
BDE-85 -6.24 5157 12.7 -5157 BDE-122 -6.21 5157 12.67 -5157
BDE-86 -6.43 5157 12.89 -5157 BDE-123 -5.99 5157 12.45 -5157
BDE-87 -6.43 5157 12.89 -5157 BDE-124 -6.21 5157 12.67 -5157
BDE-88 -6.65 5157 13.11 -5157 BDE-125 -6.43 5157 12.89 -5157
BDE-89 -6.65 5157 13.11 -5157 BDE-126 -5.80 5157 12.26 -5157
BDE-90 -6.43 5157 12.89 -5157 BDE-127 -5.99 5157 12.45 -5157
BDE-91 -6.65 5157 13.11 -5157 BDE-128 -6.78 5592 13.24 -5592
BDE-92 -6.65 5157 13.11 -5157 BDE-129 -7.00 5592 13.46 -5592
BDE-93 -6.87 5157 13.33 -5157 BDE-130 -7.00 5592 13.46 -5592
BDE-94 -6.87 5157 13.33 -5157 BDE-131 -7.22 5592 13.68 -5592
BDE-95 -6.87 5157 13.33 -5157 BDE-132 -7.22 5592 13.68 -5592
BDE-96 -7.10 5157 13.56 -5157 BDE-133 -7.22 5592 13.68 -5592
BDE-97 -6.43 5157 12.89 -5157 BDE-134 -7.45 5592 13.91 -5592
BDE-98 -6.65 5157 13.11 -5157 BDE-135 -7.45 5592 13.91 -5592
BDE-99 -6.21 5157 12.67 -5157 BDE-136 -7.67 5592 14.13 -5592
BDE-100 -6.44 5157 12.9 -5157 BDE-137 -6.78 5592 13.24 -5592
BDE-101 -6.43 5157 12.89 -5157 BDE-138 -6.78 5592 13.24 -5592
BDE-102 -6.65 5157 13.11 -5157 BDE-139 -7.00 5592 13.46 -5592
BDE-103 -6.65 5157 13.11 -5157 BDE-140 -7.00 5592 13.46 -5592
BDE-104 -6.87 5157 13.33 -5157 BDE-141 -7.00 5592 13.46 -5592
BDE-105 -5.99 5157 12.45 -5157 BDE-142 -7.22 5592 13.68 -5592
BDE-106 -6.21 5157 12.67 -5157 BDE-143 -7.22 5592 13.68 -5592
BDE-107 -6.21 5157 12.67 -5157 BDE-144 -7.22 5592 13.68 -5592
BDE-108 -6.21 5157 12.67 -5157 BDE-145 -7.45 5592 13.91 -5592
BDE-109 -6.43 5157 12.89 -5157 BDE-146 -7.00 5592 13.46 -5592
15
16
Table S1. Parameters AO, BO, AL, and BL for all 209 PBDE congeners (Yang et al., 2018).
PBDEs Ao Bo AL BL PBDEs Ao Bo AL BL
BDE-147 -7.22 5592 13.68 -5592 BDE-179 -8.24 6027 14.7 -6027
BDE-148 -7.22 5592 13.68 -5592 BDE-180 -7.35 6027 13.81 -6027
BDE-149 -7.22 5592 13.68 -5592 BDE-181 -7.57 6027 14.03 -6027
BDE-150 -7.45 5592 13.91 -5592 BDE-182 -7.57 6027 14.03 -6027
BDE-151 -7.45 5592 13.91 -5592 BDE-183 -7.44 6027 13.9 -6027
BDE-152 -7.67 5592 14.13 -5592 BDE-184 -7.80 6027 14.26 -6027
BDE-153 -6.76 5592 13.22 -5592 BDE-185 -7.80 6027 14.26 -6027
BDE-154 -7.02 5592 13.48 -5592 BDE-186 -8.02 6027 14.48 -6027
BDE-155 -7.22 5592 13.68 -5592 BDE-187 -7.80 6027 14.26 -6027
BDE-156 -6.53 5592 12.99 -5592 BDE-188 -8.02 6027 14.48 -6027
BDE-157 -6.56 5592 13.02 -5592 BDE-189 -7.13 6027 13.59 -6027
BDE-158 -6.78 5592 13.24 -5592 BDE-190 -7.35 6027 13.81 -6027
BDE-159 -6.78 5592 13.24 -5592 BDE-191 -7.35 6027 13.81 -6027
BDE-160 -7.00 5592 13.46 -5592 BDE-192 -7.57 6027 14.03 -6027
BDE-161 -7.00 5592 13.46 -5592 BDE-193 -7.57 6027 14.03 -6027
BDE-162 -6.78 5592 13.24 -5592 BDE-194 -7.93 6463 14.39 -6463
BDE-163 -7.00 5592 13.46 -5592 BDE-195 -8.15 6463 14.61 -6463
BDE-164 -7.00 5592 13.46 -5592 BDE-196 -8.15 6463 14.61 -6463
BDE-165 -7.22 5592 13.68 -5592 BDE-197 -8.37 6463 14.83 -6463
BDE-166 -6.78 5592 13.24 -5592 BDE-198 -8.37 6463 14.83 -6463
BDE-167 -6.56 5592 13.02 -5592 BDE-199 -8.37 6463 14.83 -6463
BDE-168 -6.78 5592 13.24 -5592 BDE-200 -8.59 6463 15.05 -6463
BDE-169 -6.34 5592 12.8 -5592 BDE-201 -8.59 6463 15.05 -6463
BDE-170 -7.35 6027 13.81 -6027 BDE-202 -8.81 6463 15.27 -6463
BDE-171 -7.57 6027 14.03 -6027 BDE-203 -8.15 6463 14.61 -6463
BDE-172 -7.57 6027 14.03 -6027 BDE-204 -8.37 6463 14.83 -6463
BDE-173 -7.80 6027 14.26 -6027 BDE-205 -7.93 6463 14.39 -6463
BDE-174 -7.80 6027 14.26 -6027 BDE-206 -8.72 6898 15.18 -6898
BDE-175 -7.80 6027 14.26 -6027 BDE-207 -8.94 6898 15.4 -6898
BDE-176 -8.02 6027 14.48 -6027 BDE-208 -9.16 6898 15.62 -6898
BDE-177 -7.80 6027 14.26 -6027 BDE-209 -9.50 7333 15.96 -7333
BDE-178 -8.02 6027 14.48 -6027
16
17
Table S2. Comparisons for different modes
No. Model Absorption Adsorption State
condition
Linear or not
vs logKOA Equation Ref.
1 Junge-Pankow
model N Y Equilibrium Y ϕ =
𝐶𝐽𝜃
𝐶𝐽𝜃 + 𝑃𝐿0 (Pankow, 1987)
2 Harner-Bidleman
model Y N Equilibrium Y log𝐾𝑃−𝐻𝐵 = log𝐾𝑂𝐴 + log𝑓𝑂𝑀 − 11.91 (Harner and
Bidleman, 1998)
3 Dachs-Eisenreich
model Y Y Equilibrium Y 𝐾P−DE = 𝐾𝑃−HB + 10−12𝑓
𝐸𝐶𝐾𝑆𝐴 (Dachs and
Eisenreich, 2000)
4 pp-LFER model Y Y Equilibrium Y log𝐾P−L = 𝑠𝑆 + 𝑎𝐴 + 𝑏𝐵 + 𝑣𝑉 + 𝑙𝐿 + 𝑐 (Goss, 2005)
5 Li-Jia Empirical
model NA NA Empirical
model
N log𝐾P−LJ =0.011𝐵𝑜(log𝐾𝑂𝐴 − 12.27)
𝑙𝑜𝑔𝐾𝑂𝐴 − 𝐴𝑜− 2.74log𝐾𝑂𝐴 + 31.85
(Li and Jia, 2014)
6 Li-Ma-Yang
model Y N Steady State N log𝐾P−LMY = log𝐾𝑃−𝐸𝑞 + log 𝛼 (Li et al., 2015)
7 mp-pp-LFER
model Y Y Equilibrium Y 𝐾P−mL = (𝐾𝐸𝐶 × 𝑎𝐸𝐶 × 𝑓𝐸𝐶 + 𝐾(𝑁𝐻4)2𝑆𝑂4
× 𝑎(𝑁𝐻4)2𝑆𝑂4× 𝑓(𝑁𝐻4)2𝑆𝑂4
+ 𝐾𝑁𝐻4𝐶𝑙 × 𝑎𝑁𝐻4𝐶𝑙 × 𝑓𝑁𝐻4𝐶𝑙
+ 𝐾𝐷𝑀𝑆𝑂/𝜌𝐷𝑀𝑆𝑂 × 𝑓𝑂𝑀,1 + 𝐾𝑃𝑈 × 𝑓𝑂𝑀,2) × 10−6
(Shahpoury et al.,
2016)
8 QSPR model Y Y Empirical
model
N log𝐾P−QSPR = 0.026𝑉′ − 0.030𝑇 − 0.858𝑞𝐶− + 3.864𝑞𝐻+
+ 0.002
(Wei et al., 2017)
17
18
Table S3. the Abraham solvation parameters of PBDEs and the system parameters used
in pp-LFER model and mp-pp-LFER model, and the values of ∆Hvap for 8 PBDEs.
PBDEs Abraham solvation parameters
Ref. ∆Hvap
KJ/mol Ref.
S A B V L
BDE-28 1.38 0 0.27 1.908 9.68 (Stenzel et al., 2013) 94 (Tittlemier and
Tomy, 2001)
BDE-47 1.45 0 0.34 2.083 10.66 (Stenzel et al., 2013) 103 (Tittlemier and
Tomy, 2001)
BDE-99 1.51 0 0.44 2.258 11.71 (Stenzel et al., 2013) 105 (Tittlemier and
Tomy, 2001)
BDE-100 1.48 0 0.41 2.258 11.48 (Stenzel et al., 2013) 102 (Tittlemier et al.,
2002)
BDE-153 1.54 0 0.52 2.433 12.65 (Stenzel et al., 2013) 108 (Wong et al.,
2001)
BDE-154 1.5 0 0.53 2.433 12.58 (Stenzel et al., 2013) 113 (Tittlemier et al.,
2002)
BDE-183 1.65 0 0.57 2.608 13.62 (Stenzel et al., 2013) 118 (Tittlemier et al.,
2002)
BDE-209 1.75 0 0.81 3.133 16.58 Calculated in
present study 133 Present study
system parameters
s a b v l c T(K) Ref
1.19 3.37 0.03 0.73 0.66 -7.08 288 (Arp et al., 2008)
18
19
Table S4. The parameters for mp-pp-LFER model 1
Parameters System Unit e s a b v l c T(K) Ref.
𝐾EC NIST diesel soot-air m3airm
2surface - - 2.7 2.45 - 1.09 -8.47 288 (Roth et al., 2005)
K(NH4)2SO4 (NH4)2SO4 (60% RH) m3
air m-
2surface
- - 2.13 5.34 - 0.88 -8.47 288 (Goss et al., 2003)
KNH4Cl NH4Cl (60% RH) m3
air m-
2surface
- - 2.28 4.72 - 0.92 -8.47 288 (Goss et al., 2003)
KDSMO Dry dimethyl sulfoxide-
air Lair L
-1solvent -0.22 2.9 5.04 0 - 0.72 -0.56 298
(Abraham et al.,
2010)
KPU Polyurethane ether (PU)-
air Lair kg-1
PU - 1.69 3.66 0 0.36 0.71 -0.15 288 (Kamprad and Goss,
2007)
Parameters Value
m2 g-1 Parameters
Value
m2 g-1 Parameters
Value
m2 g-1 Parameters
Value
kg m-3 Ref.
aEC 18.21 a(NH4)2SO4 0.13 aNH4Cl 0.083 𝜌DMSO 1100 (Shahpoury et al.,
2016)
Parameters Value Parameters Value Parameters Value Parameters Value Ref.
fEC 0.02 f(NH4)2SO4 0.15 fNH4Cl 0.002 𝑓OM,1/ 𝑓OM,2 3/2 (Shahpoury et al.,
2016)
2
19
20
Table S5. the parameters of PBDEs used in QSPR model (10 ~ 30 oC)
PBDEs V’ (cm3/mol) qC- qH+ Ref.
BDE-28 174.081 -0.109 0.133 (Wei et al., 2017; Zhang et al.,
2009)
BDE-47 210.227 -0.107 0.136 (Wei et al., 2017; Zhang et al.,
2009)
BDE-99 208.103 -0.556 0.138 (Wei et al., 2017; Zhang et al.,
2009)
BDE-100 224.883 -0.105 0.136 (Wei et al., 2017; Zhang et al.,
2009)
BDE-153 238.100 -0.107 0.143 (Wei et al., 2017; Zhang et al.,
2009)
BDE-154 234.867 -0.106 0.140 (Wei et al., 2017; Zhang et al.,
2009)
BDE-183 260.177 -0.107 0.142 (Wei et al., 2017; Zhang et al.,
2009)
BDE-209 289.937 0 0 (Wei et al., 2017; Zhang et al.,
2009)
20
21
Table S6. Sources of the data used in the paper
Sampling
sites
Sampling
period
Sample
number PBDEs*
Temperature
(oC) Ref.
Palmer station,
Antarctic
2010.10.19-
2010.11.11 7
BDE-28、-47、-99、-
100 -1.5 ~ 2
(Khairy et
al., 2016)
Arctic Alaska 2013.07.06-
2013.09.04 30
BDE-17, -28, -47, -66,
-71, -85, -99, -100, -
138, -153, -154,
-183, and -209
-2.5 ~ 16.8
(Davie-
Martin et
al., 2016)
northern
Greece
2013.01.16-
2013.06.02 16
BDE-15, -17, -28, -
49+71, -47, -66, -99, -
100, -153, -154,
-183
10 ~26 (Besis et
al., 2016)
Florence, Italy 2009.06.08-
2009.12.17 12
BDE-28, -47, -99, -
100, -153, -154,
-183, and -209
7 ~ 23
(Cincinell
i et al.,
2014)
Kyoto, Japan
2000.08.17-
2001.02.05;
2001.09.04-07
5
BDE-28, -47, -49, -66, -
77, -99, -100, -153, -
154, -183
3 ~ 29
(Hayakaw
a et al.,
2004)
China 2008.09-
2009.08 >700
BDE-17, -28, -47, -66,
-85, -99, -100, -138, -
153, -154,
-183, and -209
-22 ~ 38
(Li et al.,
2017;
Yang et
al., 2013)
Harbin, China 2008.08.05-
2013.07.02 223
BDE-17, -28, -47, -66,
-85, -99, -100, -138, -
153, -154,
-183, and -209
-27 ~ 29 (Li et al.,
2016)
Izmir Bay,
Turkey
2005.07.06-13
2005.11.20-26 15
BDE-28, -47, -99, -
100, -153, -154,
and -209a
5 ~ 32
(Cetin
and
Odabasi,
2007)
Zurich,
Switzerland
2010.08.20-24
2011.01.29-
2011.02.06
31
BDE -28, -47, -99, -
100, -138, -153, -183,
and -209
-2.5 ~21b
(Bogdal
et al.,
2014)
Pairs, France 2008.05.26-
2009.05.25 27
BDE -28, -47, -99, -
100, -138, -153, -154, -
183, and -209 a
1.3 ~ 22.5 (Tlili et
al., 2012)
Tengchong,
China
2005.10.22-
2006.12.27 60
BDE -28, -47, -99, -
100, and -209 a ----
(Xu et al.,
2011)
Alert, Canada 2007.01.01 54 BDE-47, -99, -100, -
153, and -209 -32.43 ~ 5.3
(Xiao et
al., 2012)
*BDE-28, -47, -99, -100, -153, -154, -183, -209 are considered in present study. aBDE-209 is included in present study b the temperature range is based on the weather given in weather channel.com
21
22
Table S7. The percentage (%) of data point predicted within one order of magnitude accuracy for PBDEs dataset.
Domains PBDEs J-P H-B D-E L-J* L-M-Y pp-LFER mp-pp-LFER QSPR*
EQ Domain
BDE-28 66.74 94.28 94.7 94.28 94.49 59.32 4.02 45.55
BDE-47 45.74 94.26 94.26 91.31 93.93 81.84 88.52 72.95
BDE-99 52.43 94.59 92.43 89.73 96.22 79.46 82.16 71.89
BDE-100 37.63 93.30 92.27 92.78 96.39 89.18 73.20 85.57
BDE-153 ---- ---- ---- ---- ---- ---- ---- ----
BDE-154 14.29 71.43 71.43 100 85.71 100 28.57 ----
BDE-183 ---- ---- ---- ---- ---- ---- ---- ----
BDE-209 ---- ---- ---- ---- ---- ---- ---- ----
NE Domain
BDE-28 38 90 90 94 98 96 62 ----
BDE-47 11.56 75.38 73.87 94.97 94.97 90.45 40.2 ----
BDE-99 12.04 81.48 81.48 87.04 95.37 96.30 47.22 66.67
BDE-100 69.48 90.82 90.07 98.26 98.76 97.52 79.90 81.39
BDE-153 7.19 65.27 58.68 95.81 97.01 94.61 21.56 86.23
BDE-154 7.25 62.32 59.42 95.65 95.65 59.42 13.04 90.34
BDE-183 0 40 40 100 100 100 0 40
BDE-209 ---- ---- ---- ---- ---- ---- ---- ----
MP Domain
BDE-28 ---- ---- ---- ---- ---- ---- ---- ----
BDE-47 0 10.34 5.17 77.59 96.55 37.93 0 ----
BDE-99 0 7.55 7.55 87.74 95.28 36.79 2.83 ----
BDE-100 0 8.47 6.78 83.05 94.92 30.51 1.69 ----
BDE-153 0 6.45 5.65 95.16 94.76 38.31 0.40 37.10
BDE-154 0 18.94 18.18 92.42 92.42 37.88 0 31.82
BDE-183 0 3.66 3.38 84.51 92.39 27.61 0 54.93
BDE-209 0 0 0 ---- 91.86 0 0 53.61
*: The monitoring data point out of the application of L-J empirical model and QSPR model are taken as out of one order of magnitude accuracy.
22
23
Table S8. The root mean square errors (RMSE) of eight models for PBDEs dataset.
Domains PBDEs J-P H-B D-E L-J* L-M-Y pp-LFER mp-pp-LFER QSPR*
EQ Domain
BDE-28 0.96 0.52 0.51 0.51 0.53 1.03 0.53 0.91
BDE-47 1.16 0.52 0.53 0.55 0.51 0.78 0.67 0.56
BDE-99 1.16 0.49 0.51 0.66 0.46 0.76 0.77 0.71
BDE-100 1.26 0.55 0.58 0.56 0.49 0.64 0.85 0.53
BDE-153 ---- ---- ---- ---- ---- ---- ---- ----
BDE-154 1.69 0.85 0.90 0.54 0.65 0.54 1.47 ----
BDE-183 ---- ---- ---- ---- ---- ---- ---- ----
BDE-209 ---- ---- ---- ---- ---- ---- ---- ----
NE Domain
BDE-28 1.3 0.65 0.68 0.53 0.45 0.48 0.98 -----
BDE-47 1.8 0.85 0.89 0.51 0.49 0.58 1.31 ----
BDE-99 1.73 0.78 0.82 0.61 0.49 0.55 1.23 0.69
BDE-100 1.10 0.52 0.54 0.33 0.28 0.35 0.77 0.27
BDE-153 1.84 0.99 1.03 0.54 0.48 0.52 1.51 0.63
BDE-154 1.86 0.99 1.03 0.47 0.48 0.53 1.67 0.53
BDE-183 2.03 1.12 1.16 0.44 0.42 0.48 1.95 0.65
BDE-209 ---- ---- ---- ---- ---- ---- ---- ----
MP Domain
BDE-28 ---- ---- ---- ---- ---- ---- ---- ----
BDE-47 2.63 1.65 1.68 0.43 0.4 1.36 2.32 ----
BDE-99 2.93 1.98 2.00 0.47 0.46 1.47 2.57 ----
BDE-100 3.10 2.02 2.05 0.48 0.47 1.50 2.53 ----
BDE-153 3.30 2.40 2.42 0.53 0.51 1.65 2.95 0.51
BDE-154 2.96 2.10 2.13 0.56 0.54 1.57 2.86 0.59
BDE-183 3.74 2.96 2.98 0.68 0.57 2.30 3.80 0.65
BDE-209 5.98 5.13 5.13 ---- 0.57 4.33 7.15 0.59
*: The monitoring data point in the application of L-J empirical model and QSPR model are considered for the RMSE
23
24
Table S9. Temperature of condensation Tc for POPs (From Table 1, Wania and Mackay,
1996), Clausius-Clapeyron coefficients AL and BL, and calculated values of logPL (All
equal to -4).
Group POPs TC/°C AL BL log(PL/Pa)
PAHs Naphthalene
Anthracene -33 11.18 -3642 -4
Pyrene -15 11.92 -4104 -4
Flouranthene -10 11.35 -4040 -4
Benz[a]anthracene 12 12.63 -4742 -4
Benzolalpyrene 47 11.59 -4989 -4
PCBs 2,4,4'-C3B (#28) -22 12.2 -4075 -4
2,2',5,5'-C4B (#52) -15 12.36 -4220 -4
2,2',4,5,5'-C5B(#101) -2 12.67 -4514 -4
2,2',4,4',5,5'-C6B (#153) 10 12.85 -4775 -4
2,2',3,3',4,4',6-C7B(#171) 20 13.07 -5008 -4
2,2',3,3',4,4',5,5'-C8B (#194) 37 13.43 -5402 -4
CBzs HC6Bz -36 11.11 -3582 -4
Pesticides -HCH -40 11.34 -3575 -4
-HCH -30 11.15 -3680 -4
p,p'-DDT 13 13.02 -4865 -4
p,p'-DDE -2 12.79 -4554 -4
p,p'-DDD 7 12.49 -4622 -4
cis-Chlordane -6 12.04 -4284 -4
trans-Chlordane -9 11.96 -4216 -4
Dieldrin -11 12.46 -4310 -4
Note: The values of AL and BL for PCBs are from Falconer et al., 1994, all others are from Hinckley et
al, 1990.
Hinckley, D.A., Bidleman, T.F., Foreman, W.T., Determination of vapor pressures for nonpolar and
semipolar organic compounds from gas chromatographic retention data. Journal of Chemical &
Engineering Data 1990, 35, 232-237.
Falconer, Renee L.,Bidleman, Terry F,Vapor pressures and predicted particle/gas distributions of
polychlorinated biphenyl congeners as functions of temperature and ortho-chlorine substitution,
Atmospheric Environment,1994,28,547-554
24
25
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