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Characteristics of halogenated flame retardants in the atmosphere of Dalian, China
Journal Pre-proof Characteristics of halogenated flame retardants in the atmosphere of Dalian, China Yan Wang, Yuwei Zhang, Feng Tan, Ya Yang, Zhenping Qu, Jacob Kvasnicka, Jingwen Chen PII:
S1352-2310(19)30858-1
DOI:
https://doi.org/10.1016/j.atmosenv.2019.117219
Reference:
AEA 117219
To appear in:
Atmospheric Environment
Received Date: 10 September 2019 Revised Date:
15 November 2019
Accepted Date: 9 December 2019
Please cite this article as: Wang, Y., Zhang, Y., Tan, F., Yang, Y., Qu, Z., Kvasnicka, J., Chen, J., Characteristics of halogenated flame retardants in the atmosphere of Dalian, China, Atmospheric Environment (2020), doi: https://doi.org/10.1016/j.atmosenv.2019.117219. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
Author Contribution Statement Yan Wang: Conceptualization, Methodology, Investigation, Resources, Data Curation, Writing - Original Draft, Supervision, Project administration, Funding acquisition Yuwei Zhang: Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft Feng Tan: Resources, Writing - Review & Editing, Project administration Ya Yang: Validation, Formal analysis, Investigation Zhenping Qu: Resources, Writing - Review & Editing Jacob Kvasnick: Formal analysis, Writing - Review & Editing Jingwen Chen: Resources, Writing - Review & Editing, Supervision, Funding acquisition
Graphical abstract
1
Characteristics of halogenated flame retardants in the atmosphere of Dalian,
2
China
3
Yan Wang a, *, Yuwei Zhang a, Feng Tan a, Ya Yang a, Zhenping Qu a, Jacob Kvasnicka
4
b
5
a
6
School of Environmental Science and Technology, Dalian University of Technology,
7
Dalian 116024, China
8
b
, Jingwen Chen a Key Laboratory of Industrial Ecology and Environmental Engineering (MOE),
Department of Earth Sciences, University of Toronto, Toronto M5S 3B1, Canada
9 10
* Corresponding author. E-mail: [email protected]
11
1
12
Abstract
13
Samples of gas and fine particulate matter (PM2.5) were collected in Dalian,
14
China, a typical coastal city, to determine the concentrations, seasonal variations,
15
influential factors, sources, and gas-PM2.5 partitioning of polybrominated diphenyl
16
ethers (PBDEs), novel brominated flame retardants (NBFRs), and dechlorane plus
17
(DPs) in the ambient air. Annual average concentrations of Σ7PBDEs, BDE209,
18
Σ6NBFRs, and DPs were 4.40±2.93, 1460±2500, 7.81±6.85, and 0.15±0.14 pg/m3 for
19
the gas phase, and 2.68±1.64, 4291±4306, 13.6±23.4, and 0.31±0.22 pg/m3 for the
20
fine particle phase, respectively. BDE209 was the dominant congener, followed by
21
HBB and BEH-TEBP, and seasonal variations in air concentrations were apparent for
22
BFRs, especially those in the gas phase. Moreover, meteorological parameters and
23
criteria air pollutants revealed significant positive correlations between temperature
24
and less-brominated BFRs in the gas phase, and between PM2.5 and highly-brominated
25
BFRs in the particle phase. This suggests that the presence of these compounds in
26
ambient air may largely result from combustion-related processes. Furthermore, an
27
analysis of the gas-PM2.5 partitioning of BFRs and DPs suggested that BFRs and DPs
28
mostly attained equilibrium, except for some NBFRs. Due to the ban of commercial
29
penta-, octa-, and deca-BDEs by the Stockholm Convention, emissions from historical
30
use and combustion are becoming the important sources of PBDEs in China.
31
Keywords: Brominated flame retardants; PM2.5; Air; Meteorological conditions;
32
Gas-PM2.5 partitioning
33 2
34
1. Introduction
35
Polybrominated diphenyl ethers (PBDEs) had been extensively used as flame
36
retardants in electronic circuitries, textiles, furniture, and building materials.
37
Commercial penta-, octa-, and deca-BDEs were classified as persistent organic
38
pollutants (POPs) and banned by the Stockholm Convention for their toxicity and
39
potential for bioaccumulation and long-range transport. With the phasing out of
40
PBDEs, tons of dechlorane pluses (DPs) and novel brominated flame retardants
41
(NBFRs),
42
pentabromoethylbenzene (PBEB), bis (2,4,6-tribromophenoxy) ethane (BTBPE),
43
2-ethylhexyl
44
(2-ethylhexyl)-3,4,5,6-tetrabromophthalate (BEH-TEBP), have been extensively used
45
as substitutes (Li et al., 2015). The estimated annual production of DBDPE and
46
BTBPE is between several thousands and tens of thousands of tons (Xiong et al.,
47
2019). However, several NBFRs exhibit similar properties to POPs (Kuramochi et al.,
48
2014), being persistent, toxic, and bioaccumulative (Covaci et al., 2011). Nowadays,
49
PBDEs, NBFRs, and DPs have been frequently detected in multiple environment
50
matrices of China, such as air (Zhao et al., 2013; Ma et al., 2017), soil (Zheng et al.,
51
2015; Sun et al., 2016), and water (Moller et al., 2011; Wang et al., 2017).
such
as
hexabromobenzene
(HBB),
tetrabromobenzoate
pentabromotoluene
(EH-TBB),
(PBT),
bis
52
Air is the primary environmental matrix for semivolatile organic compounds
53
(SVOCs), and thus plays a significant role in their transport and fate. In the
54
atmosphere,
55
FR-containing materials, industrial emissions, and combustions (Odabasi et al., 2009;
these
compounds
mainly
3
originate
from
volatilization
from
56
Wang et al., 2010b). Previous studies (Wang et al., 2011; Kuramochi et al., 2014)
57
have suggested that less-brominated PBDEs in urban air were primarily from indoor
58
sources, whereas highly-brominated PBDEs were mainly from combustion-related
59
sources, such as power plants and vehicles, which contain bromine in feedstock or
60
fuel (Chang et al., 2014a; Chang et al., 2014b). However, the main sources of PBDEs
61
in the air are still unclear, especially after the banning of commercial PBDEs. Since
62
certain criteria air pollutants, such as SO2 and NO2, are indicators of fossil fuel
63
combustion, an analysis of the relationship between these air pollutants and PBDEs
64
may allow us to better understand sources of PBDEs in air.
65
Meteorological conditions, such as air temperature, relative humidity, wind speed
66
(Li et al., 2016b), and solar irradiation (Chen et al., 2015), can significantly influence
67
atmospheric concentrations, gas-PM2.5 partitioning, as well as atmospheric fates of
68
POPs. For instance, relatively high wind speed can dilute and disperse POPs in the
69
atmosphere, whereas high temperature can promote volatilization of POPs from
70
various sources (Yang et al., 2013) and affect their gas-PM2.5 partitioning. Solar
71
irradiation, however, can either increase the air concentrations of POPs by increasing
72
air temperature (visible light) or decrease their concentrations by promoting
73
photodegradation (UV) (Liu et al., 2015).
74
Although attention has been devoted to the environmental fate of PBDEs,
75
NBFRs (Covaci et al., 2011), and DPs (Ren et al., 2008) in the atmosphere, little
76
information is available on seasonality and gas-PM2.5 partitioning of BFRs and DPs in
77
the air, and the potential influences of criteria air pollutants. Thus, the main objectives 4
78
of this study were to: (1) characterize the influences of meteorological factors and
79
criteria air pollutants on their atmospheric levels, (2) identify their potential sources,
80
and (3) investigate their partitioning between gas phase and PM2.5.
81 82
2. Materials and methods
83
2.1 Sample collection
84
Dalian is the third largest city of Northeast China and is an important center of
85
both heavy and light industries. Gas and PM2.5 samples were collected separately on a
86
building rooftop (~12 m high) located on the urban campus of Dalian University of
87
Technology [38.886°N, 121.528°E]. A 48-hour air sample was collected from 8:00
88
AM every Monday from November 7th, 2016 to November 6th, 2017, using a
89
high-volume air sampler at a sampling rate of 0.3 m3/min. Air was first passed
90
through a quartz fiber filter (Whatman, pre-baked at 450°C for 4 h), and then through
91
a polyurethane foam plug (PUF, 6.5 cm diameter × 7.5 cm high, pre-cleaned by ethyl
92
acetate and dichloromethane). In total, 52 gaseous and 52 particle air samples were
93
collected. All samples were wrapped with aluminum foil, placed into polythene
94
zip-bags, and stored at -20°C until further analysis. Meteorological parameters were
95
monitored simultaneously using a wireless weather station (DAVIS Vantage Pro2)
96
close to the air sampler (Table S1 in the Supporting Information, SI). Concentrations
97
of four Criteria Air Pollutants, including SO2, NO2, O3, and CO, were obtained from
98
an online data repository maintained by the Dalian Environmental Protection Bureau
99
(Table S2, SI). 5
100 101
2.2 Sample preparation and extraction
102
PUF plug and filter samples were spiked with surrogate standards (PCB198 and
103
PCB209, Dr. Ehrenstorfer GmbH, Germany), and extracted twice with DCM:
104
n-hexane (1:1, v/v) at 100°C for 5 min using an accelerated solvent extraction
105
(ASE350, Dionex Inc.). The extracts were concentrated under a gentle stream of
106
nitrogen to ~0.5 mL after solvent-exchange to n-hexane, and cleaned up on a silica gel
107
column containing 3 cm silica gel (3% deactivated) at the bottom, 3 cm acidic silica
108
gel (silica gel: sulfuric acid=1:1, m/m) in the middle, and topped with 0.5 cm of
109
anhydrous sodium sulfate. PBDEs were eluted with 20 mL DCM: n-hexane (1:1, v/v),
110
and finally concentrated to ~30 µL. Prior to instrumental analysis, PCB208 was added
111
as the internal standard.
112 113
2.3 Instrumental analysis
114
Agilent 6890GC-5975MS applied with a DB5-MS capillary column (30 m ×
115
0.25 mm i.d. × 0.25 µm) was used for the separation of target 8 PBDEs, 6 NBFRs,
116
and 2 DPs, including BDE28, PBT, PBEB, HBB, BDE47, BDE100, BDE99, EH-TBB,
117
BDE154, BDE153, BDE183, BTBPE, BEH-TEBP, anti-DP, syn-DP, and BDE209. 1
118
µL of each extract was injected in the splitless mode. Helium was used as the carrier
119
gas at a flow rate of 1.2 mL/min. The oven temperature program was as follows: 80°C
120
for 1 min, increased to 210°C at a rate of 20°C/min, increased to 260°C at a rate of
121
10°C/min, increased to 300°C at a rate of 15°C/min, and then held for 20 min. 6
122 123
2.4 Quality assurance and quality control (QA/QC)
124
One procedural blank and one field blank were run with each batch of 10
125
samples to control potential contaminations. No target compounds were detected in
126
any blank samples, except for BDE209 (< 10%) and HBB (< 8%). The breakthrough
127
of the gaseous BFRs and DPs was tested using a second PUF plug (3.5 cm thick) in
128
series with the first one. Breakthroughs of BFRs are less than 10%. Method detection
129
limits (MDL) were calculated as the mean concentration of blanks plus three times the
130
standard deviation. The MDLs were 24.6 pg/m3 for BDE209 and 0.01-0.11 pg/m3 for
131
NBFRs, DPs, and other PBDEs. The average surrogate recoveries for PCB198 and
132
PCB209 in all samples were 93 ± 14% and 96 ± 15% for the gas phase and 87 ± 12%
133
and 84 ± 10% for the particle phase, respectively. The results were corrected by
134
blanks, but not by the surrogate recovery rates. The concentrations of target
135
compounds below the MDL were assigned zero for sums and 1/2MDL for correlation
136
analysis.
137 138
3. Results and discussion
139
3.1 Concentrations of BFRs and DPs in the air
140
The sum of BDE28, 47, 99, 100, 153, 154, and 183 is expressed as Σ7PBDEs. As
141
shown in Fig. 1 and Table S3 of SI, Σ7PBDEs in the gas phase ranged from 0.28 to
142
11.6 pg/m3 with an average of 4.40 ± 2.93 pg/m3, while Σ7PBDEs in the PM2.5 ranged
143
from 0.86 to 10.4 pg/m3 with an average of 2.68 ± 1.64 pg/m3. BDE28 exhibited the 7
144
highest level among those seven PBDEs in the gas phase followed by BDE47 and
145
BDE183, whereas BDE183 exhibited the highest level in PM2.5 followed by BDE99
146
and BDE153. Σ7PBDEs in gas phase were comparable with those (N.D.-28.8 pg/m3)
147
measured using PUF-passive air sampler in the industrial zones of Pakistan (Khan et
148
al., 2017), while Σ7PBDEs in both gas and PM2.5 (1.28-17.0 pg/m3) were also
149
comparable with those measured in urban area of Beijing (N.D.–23.6 pg/m3), China
150
(Shi et al., 2013b). The lowest concentration was discovered in the sample collected
151
during the timeframe of August 14-16, 2017 with a rainfall, while the highest
152
concentration was in the sample collected from September 4-6, 2017. The
153
concentrations of BDE209 were 26.4-15200 (average: 1460 ± 2500) pg/m3 in the gas
154
phase and 244-19600 (4290 ± 4310) pg/m3 in PM2.5. The levels of BDE209 in both
155
gas and PM2.5 in this study (707-19900 pg/m3) were much higher than those from the
156
urban area of Beijing (30.7-454 pg/m3), China (Shi et al., 2013a).
157
The total concentrations of 6 NBFRs (Σ6NBFRs) in the gas phase ranged from
158
0.27 to 25.3 (7.81 ± 6.85) pg/m3, while Σ6NBFRs in the PM2.5 ranged from 2.16 to
159
132 (13.6 ± 23.4) pg/m3. The dominant compounds were HBB followed by
160
BEH-TEBP in both gas phase and PM2.5. The total concentrations of DPs were in the
161
ranges of 0.02-0.74 (0.15 ± 0.14) pg/m3 and 0.03-1.06 (0.31 ± 0.22) pg/m3 in the gas
162
phase and PM2.5, respectively. The total concentrations of NBFRs and DPs in both gas
163
and PM2.5 were over three orders of magnitude lower than those measured in the
164
e-waste recycling areas of Karachi (gas and PM2.5; Σ6NBFRs (including DBDPE)
165
21.0-170 ng/m3, DPs: 15.0-85.0 ng/m3), Pakistan (Iqbal et al., 2017). Meanwhile, 8
166
levels of DPs in this study are comparable with concentrations observed in the air of
167
Atlantic Ocean (0.05-1.6 pg/m3) (Moller et al., 2012).
168 169
3.2 Compositions of BFRs and DPs in the air
170
The composition of BFRs and DPs are in the order of PBDEs > NBFRs > DPs.
171
For PBDEs, the predominant congener was BDE209 in both gas phase (98.4 ± 2.56%)
172
and PM2.5 (99.8 ± 0.25%). Relatively high abundances of BDE28 (0.5 ± 0.89%) were
173
also observed in the gas phase, which can be attributed to its low molecular weight
174
and high volatility. Besides BDE209, BDE183 also exhibited relatively high
175
abundances in both gas and particle phases. Although, BDE183 is the major
176
component in the octa-BDE commercial mixture along with BDE153 and 154 (Shi et
177
al., 2013b), debromination of high brominated PBDEs, such as BDE209, may also be
178
a possible source for those compounds in the atmosphere (Gerecke et al., 2005; Ahn et
179
al., 2006). Meanwhile, HBB, a replacement of deca-BDE product, was the dominant
180
NBFR congener (36.1 ± 21.2% of NBFRs in gas phase and 72.5 ± 17.2% in PM2.5),
181
followed by BEH-TEBP (gas 27.8 ± 18.7%, PM2.5 12.8 ± 12%). HBB is still produced
182
in China (Li et al., 2016a) and can also be degraded from polymeric BFRs (Moller et
183
al., 2011). For DPs, the relative abundances of syn-DP were lower than those of
184
anti-DP with the fsyn values (fsyn=syn-DP/(syn-DP+anti-DP) of 0.31±0.10 and
185
0.24±0.10 in the gas phase and PM2.5, respectively. The fsyn ratio was as slightly lower
186
than that of the commercial mixture (fsyn=0.4) (Wang et al., 2010a), suggesting a
187
fractionation of DPs in the atmosphere. 9
188 189
3.3 Seasonal variations of BFRs and DPs in the air
190
BFR concentrations in the air showed obvious seasonal variations, especially in
191
the gas phase. The average concentrations of Σ8PBDEs and Σ6NBFRs in the gas phase
192
both followed the order: summer > spring > autumn > winter. However, Σ8PBDEs in
193
PM2.5 were higher in winter than those in other seasons following the order: winter >
194
spring > summer > autumn. Meanwhile, Σ6NBFRs in PM2.5 were in the order of
195
spring > summer > autumn > winter. Not surprisingly, elevated gas-phase
196
concentrations of BFRs were observed during summer, since temperature is a major
197
factor affecting the seasonal variations of POPs in the air (Li et al., 2015). High
198
temperature may accelerate the volatilization of BFRs from various sources and from
199
fine particles, and intense solar radiation during summer may also promote
200
debromination of highly-brominated BFRs in the atmosphere (Gouin et al., 2002).
201
Meanwhile, as shown in Fig. 1, the relative proportion of PBDEs in the gas phase
202
relative to the particle phase increased with increasing temperature (Yang et al., 2012),
203
especially in summer from June to August. Surprisingly, concentrations of BDE209
204
decreased in both gas and PM2.5 phases after May 22nd, 2017 especially in PM2.5,
205
which may be due to the decreasing emissions from industries (may be due to the ban
206
of commercial deca-BDE). The high concentrations of Σ8PBDEs in PM2.5 in winter
207
may be due to the elevated PM2.5 and PBDE emissions from combustions such as
208
coal-heating combustion. The relatively high concentrations of Σ6NBFRs in PM2.5 in
209
spring and summer were caused by some specific emissions of HBB on March 27 and 10
210
July 17, 2017. Concentrations of DPs did not display any obvious seasonal trends,
211
which may be due to the relatively low air concentrations observed in this study.
212 213
3.4 Influences of meteorological conditions
214
In order to assess the influence of meteorological conditions on temporal trends
215
of BFRs and DPs in the atmosphere, we tested for correlations (Table 1 and Table S4,
216
SI). Temperature was significantly positively correlated (p < 0.006) with most BFRs
217
in the gas phase, including PBT, PBEB, HBB, BEH-TEBP, BDE28, 47, 100, 154, and
218
209, but negatively correlated (p < 0.04) with some BFRs in PM2.5, such as PBEB,
219
BEH-TEBP, BDE100, 99,153, and 209. This suggests that gas-PM2.5 partitioning of
220
BFRs is, to some extent, influenced by air temperature. The strong temperature
221
dependence observed for BFRs in the gas phase is similar to that observed in a
222
previous study (Li et al., 2015), which suggested that higher emissions of these
223
compounds are associated with increasing temperature. Correlations between
224
highly-brominated BFRs and temperature were weaker than those for less-brominated
225
BFRs, which may be due to their different volatilities and by their partitioning being
226
driven by physicochemical properties (Li et al., 2016b). Correlations between
227
BDE154, BEH-TEBP, BDE209 and temperature were positive for gas-phase
228
compounds but negative for these in PM2.5, suggesting that temperature significantly
229
influenced gas-PM2.5 partitioning for these three compounds. Solar radiation can
230
increase both volatilization (via increasing the temperature) and photodegradation of
231
highly-brominated PBDEs (Fang et al., 2008; Lagalante et al., 2011). Correlations 11
232
between BFRs and solar radiation were similar to those for temperature, except for
233
BDE183. Significant negative correlation (p < 0.01) was observed between solar
234
radiation and BDE183 in both gas phase and PM2.5, which suggests that influence of
235
solar radiation on the photodegradation was more important than that on the
236
volatilization for BDE183. Less-brominated BFRs in the gas phase were significantly
237
positively correlated (p < 0.05) with humidity, but negatively correlated (p < 0.05)
238
with wind speed, whereas correlations between BFRs in PM2.5 and humidity/wind
239
speed were mostly not significant. High wind speed can easily dilute the BFR
240
concentrations in the gas phase (Li et al., 2016b), but not for those in PM2.5.
241
Meanwhile, higher relative humidity may also lead to higher gas-phase concentrations
242
of POPs, since hydrophobic organic compounds have low tendencies to adsorb to
243
hydrated particles (Pankow et al., 1993). Air pressure was significantly negatively
244
correlated (p < 0.05) with most gas-phase BFRs, possibly because increased air
245
pressure may decrease the volatilization of BFRs. The influence of rainfall on air
246
concentrations of BFRs was not statistically significant, due to a limited number of
247
samples collected during rainy days.
248 249
3.5 Source apportionment
250
3.5.1 Correlations between BFR and DP congeners
251
Properties and use patterns of commercial flame retardant mixtures can influence
252
their concentrations and compositions (Ma et al., 2017), as well as their environmental
253
fates (La Guardia et al., 2006). Significant positive correlations (p < 0.047, Table S5, 12
254
SI) were observed among less-brominated BFRs, such as BDE28, 47, 100, PBT,
255
PBEB, and HBB in the gas phase (r: 0.359-0.885) or BDE28, 99, 100, PBT, PBEB,
256
and HBB in PM2.5 (r: 0.286-0.992), suggesting that they may originate from similar
257
sources and undergo similar environmental processes. A previous study (Wang et al.,
258
2017) also found a significant positive correlation between HBB and BDE47,
259
suggesting similar sources such as debromination from highly-brominated PBDEs or
260
polymeric BFRs. However, BDE99 in the gas phase only correlated with BDE100 and
261
some high BFRs such as BDE153 and BDE154, whereas BDE47 in PM2.5 had no
262
correlation with any BFRs or DPs. This interesting result suggests that BDE47 or
263
BDE99 may have other sources such as photodegradation or heterogeneous reaction.
264
Meanwhile, significant correlation was discovered between EH-TBB and BEH-TEBP,
265
which are commonly used as substitutes of penta-BDE (Covaci et al., 2011), in the
266
gas phase (p=0.034) but not in PM2.5 (p=0.065). BDE99, BDE153, and BDE154 were
267
also significantly positively correlated with each other in both the gas phase and PM2.5
268
(p < 0.001), which suggests similar sources, e.g., degradation from BDE209
269
(Kajiwara et al., 2008; Chen et al., 2015). A significant positive correlation (p < 0.05)
270
was also found between syn-DP and anti-DP, again indicating similar sources.
271 272
3.5.2 Correlations between BFRs/DPs and criteria air pollutants
273
Previous studies (Chang et al., 2014a; Chang et al., 2014b) have suggested
274
combustion or biomass burning as important sources of PBDEs. Combustion,
275
especially of fossil fuels, is also an important source of fine particles (e.g. PM2.5), SO2, 13
276
NO2, and CO in the atmosphere of China (Ding et al., 2018). To investigate the
277
potential influence of combustion on atmospheric levels of BFRs, correlations
278
between BFRs and criteria air pollutants were estimated and are shown in Table 1 and
279
Table S4, SI. Although SO2/NO2 were negatively correlated (p < 0.05) with low
280
molecular weight BFRs (BDE28, 47, 100, PBT, PBEB, and HBB) in the gas phase,
281
but positively correlated with high molecular weight BFRs in PM2.5, these may be
282
pseudo-correlations since they were both correlated with temperature. However,
283
BDE154 and BDE183 in particles were significant correlated with SO2, NO2, and CO,
284
but not with temperature, suggesting similar sources of these compounds, e.g., coal
285
combustion. The concentrations of fine particles (PM2.5, µg/m3) was significantly
286
correlated with highly-brominated BFRs such as BDE99, 100, 153, 154, 183, 209,
287
BTBPE, and BEH-TEBP in PM2.5 but not in the gas phase. This suggests that
288
increased concentration of fine particles, especially in winter, also elevated the
289
concentrations of particle-bound BFRs, which may be generated together from
290
combustions (Dong et al., 2015).
291 292
3.5.3 Principal component analysis
293
In this study, 14 BFRs, 2 DPs, 6 criteria air pollutants, and 6 meteorological
294
parameters were treated as independent variables for principle component analysis
295
(PCA). The loading plot is shown in Fig. 2. Contaminants located near each other may
296
originate from similar sources or undergo similar environmental processes. Two
297
principle components were extracted with 22% of PC1 and 21% of PC2, respectively. 14
298
Generally, variables can be divided into two main groups. Group 1 includes
299
temperature, solar irradiation, humidity, O3, and some less-brominated BFRs in the
300
gas phase, such as BDE28, 47, 100, 154, PBT, PBEB, and HBB. This implies that
301
these chemicals were significantly influenced by temperature-induced volatilization.
302
Group 2 consists of PM, SO2, NO2, CO, almost all HFRs in PM2.5 (except for BDE47
303
and HBB), and some gas-phase PBDEs (BDE99, 153, and 183). These compounds
304
may be significantly influenced by combustion and PM. TBB, DPs, and BDE209 in
305
the gas phase, which were not in these two groups, may be influenced by other
306
factors.
307 308
3.6 Gas-PM2.5 partitioning
309
Gas-particle partitioning is an important process influencing levels, transport, and
310
removal of POPs in the air (Tian et al., 2011). However, little is known of the
311
gas-particle partitioning of NBFRs, especially partitioning between the gas phase and
312
PM2.5. The measured gas-PM2.5 partition coefficients (Kp, m3/µg) and particle
313
fractions (fp) of atmospheric BFRs and DPs were calculated as follows (Pankow,
314
1994):
315
Kp = (Cp/CPM2.5)/Cg
(1)
316
fp = Cp/(Cg + Cp)
(2)
317
where CPM2.5 is the concentration of PM2.5 (µg/m3), Cp and Cg are the BFR
318
concentrations in PM2.5 and gas phase, respectively.
319
PM2.5 fractions of BFRs and DPs in the air during different seasons are shown in 15
320
Fig. 3. Generally, highly-brominated congeners are more particle-bound than
321
less-brominated ones during the same season. BDE28 (fp: 23±21%), PBT (31±29%),
322
and PBEB (30±25%) were mainly in the gas phase with syn-DP (61±20%), anti-DP
323
(68±19%), and BDE209 (63±31%) mostly in PM2.5, while the PM2.5 fractions of other
324
BFRs varied widely with sampling period. The PM2.5 fractions of most PBDEs in this
325
study are comparable with those measured in previous studies (Su et al., 2009; He et
326
al., 2019), except BDE183 and BDE209, which were lower than their results. This
327
may be because we only collected fine particles instead of total suspended particles.
328
Significant seasonality was discovered for the particle fractions of most BFRs, which
329
were much higher in winter but lower in summer than in other seasons. This may be
330
due to a strong influence of ambient temperature on their gas-particle partitioning
331
(Wong et al., 2001; Harner and Shoeib, 2002). Two exceptions are noteworthy.
332
EH-TBB and BDE153 were higher in autumn, while BDE183 and BTBPE were
333
higher in summer. Significant negative correlations (p≤0.003) were also observed
334
between the PM2.5 fractions of most BFRs and temperature, except for those four
335
BFRs. This suggests that these BFRs may be affected by certain sources or reactions.
336
For instance, as mentioned above, BDE183 in PM2.5 may be influenced by coal
337
combustion.
338
Subcooled liquid vapor pressure (PºL) and octanol-air partition coefficient (Koa)
339
have been widely used to predict gas-PM2.5 partitioning of SVOCs (Yang et al., 2018).
340
Previous studies have suggested that the logarithm of Kp generally follows a linear
341
relationship with log PºL (Pankow and Bidleman, 1991, 1992) and log Koa (Harner 16
342
and Bidleman, 1998; Pankow, 1998) under ambient temperatures and prevailing
343
particle characteristics and concentrations. The PºL and Koa values of PBDEs at 25ºC
344
shown here are based on Xu et al. (Xu et al., 2007), while the PºL and Koa values of
345
NBFRs and DPs at 25ºC were from Zhang et al (Zhang et al., 2016). As shown in Fig.
346
4, significant linear correlations were apparent for average log Kp versus log PºL (r2 =
347
0.675, p=0.0003) and log Koa (r2 = 0.631, p=0.001) for most of the BFRs and DPs,
348
except HBB and BEH-TEBP. This implies that most BFRs and DPs reach equilibrium
349
between the gas phase and fine particles. HBB and BEH-TEBP may have specific
350
sources considering their relatively high concentrations compared with other NBFRs,
351
and thus did not achieve equilibrium. The slope values are -0.191 and 0.143 for log Kp
352
vs. log PºL and log Koa respectively, which significantly differ from -1 or 1.
353
Theoretically, the slope of log Kp vs. log PºL equals -1 when chemicals reach
354
equilibrium between gas phase and PM2.5 (Pankow and Bidleman, 1992). However,
355
the slope being different to -1 may also suggest equilibrium at rural sites (Simcik et al.,
356
1998), since it can be influenced by many factors, such as ambient temperature,
357
non-exchangeability, or sampling sites (Ma et al., 2019). Smaller slopes were also
358
discovered in the urban (−0.200) and rural (−0.109) areas of Chaohu City, China (He
359
et al., 2019) and the urban areas (−0.201) of Florence, Italy (Cincinelli et al., 2014).
360 361
4. Conclusions
362
This study included a comprehensive interpretation of the characteristics,
363
influential factors, potential sources, and gas-PM2.5 partitioning of atmospheric BFRs 17
364
and DPs in Dalian, China. Significant seasonality was observed for gas-phase BFRs,
365
with higher levels apparent during summer. Meteorological conditions significantly
366
influenced the air levels of BFRs in Dalian, especially air temperature and solar
367
irradiation. Source apportionment suggested that less-brominated BFRs may originate
368
mainly from temperature-derived volatilizations or from degradation, while
369
highly-brominated BFRs may be associated with combustion or biomass burning. An
370
assessment of gas-PM2.5 partitioning suggested that most BFRs had reached
371
equilibrium, except HBB and BEH-TEBP. Despite the ban of PBDEs by the
372
Stockholm Convention, emissions from historical use or combustion are still
373
continuing, highlighting a need for further investigations.
374 375 376 377
Appendix A. Supplementary data Table S1-S5. Supplementary data associated with this article can be found in the online version.
378 379
Acknowledgements
380
This study was supported by the Key Laboratory of Coastal Environmental
381
Processes and Ecological Remediation, YICCAS (No. 2018KFJJ06), the National
382
Natural Science Foundation of China (Nos. 21976023 and 21577010), and the
383
Program of Introducing Talents of Discipline to Universities (B13012).
384 385
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538
22
539
Figures and Tables
540
Fig. 1 PBDEs, NBFRs, DPs, and BDE209 in the gas phase and PM2.5 of Dalian.
541
Fig. 2 Two-dimensional principal component loading plot of BFRs, DPs, criteria air
542
pollutants, and meteorological parameters.
543
Fig. 3 PM2.5 fractions of BFRs and DPs during different seasons.
544
Fig. 4 Liner correlations of log PºL and log Koa against average log Kp for BFRs and
545
DPs.
546 547 548
Table 1 Correlation coefficient matrix between main BFR congeners, criteria air pollutants, and meteorological parameters.
549
23
550
Fig. 1 PBDEs, NBFRs, DPs, and BDE209 in the gas phase and PM2.5 of Dalian.
551 552
24
553 554
Fig. 2 Two-dimensional principal component loading plot of BFRs, DPs, air pollutants, and meteorological parameters.
555
556 557
25
558
Fig. 3 PM2.5 fractions of BFRs and DPs during different seasons.
559 560
26
561
Fig. 4 Liner correlations of log PºL and log Koa against average log Kp for BFRs and
562
DPs.
563 564
27
565
Table 1 Correlation coefficient matrix between main BFR congeners, criteria air
566
pollutants, and meteorological parameters. BDE28
PBT
HBB BDE47 BDE100 BDE99 BDE154 BDE153 BDE183 BEH-TEBP
BDE209
Gas phase PM2.5
-0.223
0.09
-0.181
0.053
0.171
-0.264
-0.191
SO2
-.434** -.673** -.568** -.606** -.413**
.284*
-0.201
.335*
.631**
-.404**
-.344*
NO2
-.303* -.448** -.475** -.480** -.379**
0.175
-0.256
0.199
.441**
-.384**
-0.274
a
.503** .833** .739** .815** .599**
-0.01
.427**
-0.203
-.535**
.533**
.402**
.490** .658** .640** .669**
-0.168
0.265
-0.195
-.525**
0.244
.371**
T
SR
b
0.01
-.340* -0.268 -0.261
.326*
PM2.5 phase PM2.5
0.261
0.249
0.075
-0.013
.389** .576** .430**
.333*
0.204
.391**
.340*
SO2
0.246
0.201
-0.096
0.002
.502** .565** .480**
.543**
.450**
0.274
.307*
NO2
.306*
.284*
-0.063
-0.07
.596** .703** .633**
.519**
.406**
0.262
.292*
-0.226 -0.196
0.088
-0.131
-.353* -.430** -0.203
-.296*
-0.252
-.325*
-.320*
-0.192 -0.168
0.018
0.128
-.348* -.395** -0.225
-.368** -.440**
-0.111
-0.106
T
a
SR
567 568 569 570
b
*Statistically significant correlations at p < 0.05 level. **Statistically significant correlations at p < 0.01 level. a
Temperature.
b
Solar radiation.
28
Highlights Temperature, degradation, and combustion significantly affected air levels of BFRs. Gas-PM2.5 partitioning of BFRs and DPs suggested most of them reached equilibrium. PBDE emission from historical use or combustion still continues despite their ban.
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
S1352-2310(19)30858-1
DOI:
https://doi.org/10.1016/j.atmosenv.2019.117219
Reference:
AEA 117219
To appear in:
Atmospheric Environment
Received Date: 10 September 2019 Revised Date:
15 November 2019
Accepted Date: 9 December 2019
Please cite this article as: Wang, Y., Zhang, Y., Tan, F., Yang, Y., Qu, Z., Kvasnicka, J., Chen, J., Characteristics of halogenated flame retardants in the atmosphere of Dalian, China, Atmospheric Environment (2020), doi: https://doi.org/10.1016/j.atmosenv.2019.117219. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
Author Contribution Statement Yan Wang: Conceptualization, Methodology, Investigation, Resources, Data Curation, Writing - Original Draft, Supervision, Project administration, Funding acquisition Yuwei Zhang: Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft Feng Tan: Resources, Writing - Review & Editing, Project administration Ya Yang: Validation, Formal analysis, Investigation Zhenping Qu: Resources, Writing - Review & Editing Jacob Kvasnick: Formal analysis, Writing - Review & Editing Jingwen Chen: Resources, Writing - Review & Editing, Supervision, Funding acquisition
Graphical abstract
1
Characteristics of halogenated flame retardants in the atmosphere of Dalian,
2
China
3
Yan Wang a, *, Yuwei Zhang a, Feng Tan a, Ya Yang a, Zhenping Qu a, Jacob Kvasnicka
4
b
5
a
6
School of Environmental Science and Technology, Dalian University of Technology,
7
Dalian 116024, China
8
b
, Jingwen Chen a Key Laboratory of Industrial Ecology and Environmental Engineering (MOE),
Department of Earth Sciences, University of Toronto, Toronto M5S 3B1, Canada
9 10
* Corresponding author. E-mail: [email protected]
11
1
12
Abstract
13
Samples of gas and fine particulate matter (PM2.5) were collected in Dalian,
14
China, a typical coastal city, to determine the concentrations, seasonal variations,
15
influential factors, sources, and gas-PM2.5 partitioning of polybrominated diphenyl
16
ethers (PBDEs), novel brominated flame retardants (NBFRs), and dechlorane plus
17
(DPs) in the ambient air. Annual average concentrations of Σ7PBDEs, BDE209,
18
Σ6NBFRs, and DPs were 4.40±2.93, 1460±2500, 7.81±6.85, and 0.15±0.14 pg/m3 for
19
the gas phase, and 2.68±1.64, 4291±4306, 13.6±23.4, and 0.31±0.22 pg/m3 for the
20
fine particle phase, respectively. BDE209 was the dominant congener, followed by
21
HBB and BEH-TEBP, and seasonal variations in air concentrations were apparent for
22
BFRs, especially those in the gas phase. Moreover, meteorological parameters and
23
criteria air pollutants revealed significant positive correlations between temperature
24
and less-brominated BFRs in the gas phase, and between PM2.5 and highly-brominated
25
BFRs in the particle phase. This suggests that the presence of these compounds in
26
ambient air may largely result from combustion-related processes. Furthermore, an
27
analysis of the gas-PM2.5 partitioning of BFRs and DPs suggested that BFRs and DPs
28
mostly attained equilibrium, except for some NBFRs. Due to the ban of commercial
29
penta-, octa-, and deca-BDEs by the Stockholm Convention, emissions from historical
30
use and combustion are becoming the important sources of PBDEs in China.
31
Keywords: Brominated flame retardants; PM2.5; Air; Meteorological conditions;
32
Gas-PM2.5 partitioning
33 2
34
1. Introduction
35
Polybrominated diphenyl ethers (PBDEs) had been extensively used as flame
36
retardants in electronic circuitries, textiles, furniture, and building materials.
37
Commercial penta-, octa-, and deca-BDEs were classified as persistent organic
38
pollutants (POPs) and banned by the Stockholm Convention for their toxicity and
39
potential for bioaccumulation and long-range transport. With the phasing out of
40
PBDEs, tons of dechlorane pluses (DPs) and novel brominated flame retardants
41
(NBFRs),
42
pentabromoethylbenzene (PBEB), bis (2,4,6-tribromophenoxy) ethane (BTBPE),
43
2-ethylhexyl
44
(2-ethylhexyl)-3,4,5,6-tetrabromophthalate (BEH-TEBP), have been extensively used
45
as substitutes (Li et al., 2015). The estimated annual production of DBDPE and
46
BTBPE is between several thousands and tens of thousands of tons (Xiong et al.,
47
2019). However, several NBFRs exhibit similar properties to POPs (Kuramochi et al.,
48
2014), being persistent, toxic, and bioaccumulative (Covaci et al., 2011). Nowadays,
49
PBDEs, NBFRs, and DPs have been frequently detected in multiple environment
50
matrices of China, such as air (Zhao et al., 2013; Ma et al., 2017), soil (Zheng et al.,
51
2015; Sun et al., 2016), and water (Moller et al., 2011; Wang et al., 2017).
such
as
hexabromobenzene
(HBB),
tetrabromobenzoate
pentabromotoluene
(EH-TBB),
(PBT),
bis
52
Air is the primary environmental matrix for semivolatile organic compounds
53
(SVOCs), and thus plays a significant role in their transport and fate. In the
54
atmosphere,
55
FR-containing materials, industrial emissions, and combustions (Odabasi et al., 2009;
these
compounds
mainly
3
originate
from
volatilization
from
56
Wang et al., 2010b). Previous studies (Wang et al., 2011; Kuramochi et al., 2014)
57
have suggested that less-brominated PBDEs in urban air were primarily from indoor
58
sources, whereas highly-brominated PBDEs were mainly from combustion-related
59
sources, such as power plants and vehicles, which contain bromine in feedstock or
60
fuel (Chang et al., 2014a; Chang et al., 2014b). However, the main sources of PBDEs
61
in the air are still unclear, especially after the banning of commercial PBDEs. Since
62
certain criteria air pollutants, such as SO2 and NO2, are indicators of fossil fuel
63
combustion, an analysis of the relationship between these air pollutants and PBDEs
64
may allow us to better understand sources of PBDEs in air.
65
Meteorological conditions, such as air temperature, relative humidity, wind speed
66
(Li et al., 2016b), and solar irradiation (Chen et al., 2015), can significantly influence
67
atmospheric concentrations, gas-PM2.5 partitioning, as well as atmospheric fates of
68
POPs. For instance, relatively high wind speed can dilute and disperse POPs in the
69
atmosphere, whereas high temperature can promote volatilization of POPs from
70
various sources (Yang et al., 2013) and affect their gas-PM2.5 partitioning. Solar
71
irradiation, however, can either increase the air concentrations of POPs by increasing
72
air temperature (visible light) or decrease their concentrations by promoting
73
photodegradation (UV) (Liu et al., 2015).
74
Although attention has been devoted to the environmental fate of PBDEs,
75
NBFRs (Covaci et al., 2011), and DPs (Ren et al., 2008) in the atmosphere, little
76
information is available on seasonality and gas-PM2.5 partitioning of BFRs and DPs in
77
the air, and the potential influences of criteria air pollutants. Thus, the main objectives 4
78
of this study were to: (1) characterize the influences of meteorological factors and
79
criteria air pollutants on their atmospheric levels, (2) identify their potential sources,
80
and (3) investigate their partitioning between gas phase and PM2.5.
81 82
2. Materials and methods
83
2.1 Sample collection
84
Dalian is the third largest city of Northeast China and is an important center of
85
both heavy and light industries. Gas and PM2.5 samples were collected separately on a
86
building rooftop (~12 m high) located on the urban campus of Dalian University of
87
Technology [38.886°N, 121.528°E]. A 48-hour air sample was collected from 8:00
88
AM every Monday from November 7th, 2016 to November 6th, 2017, using a
89
high-volume air sampler at a sampling rate of 0.3 m3/min. Air was first passed
90
through a quartz fiber filter (Whatman, pre-baked at 450°C for 4 h), and then through
91
a polyurethane foam plug (PUF, 6.5 cm diameter × 7.5 cm high, pre-cleaned by ethyl
92
acetate and dichloromethane). In total, 52 gaseous and 52 particle air samples were
93
collected. All samples were wrapped with aluminum foil, placed into polythene
94
zip-bags, and stored at -20°C until further analysis. Meteorological parameters were
95
monitored simultaneously using a wireless weather station (DAVIS Vantage Pro2)
96
close to the air sampler (Table S1 in the Supporting Information, SI). Concentrations
97
of four Criteria Air Pollutants, including SO2, NO2, O3, and CO, were obtained from
98
an online data repository maintained by the Dalian Environmental Protection Bureau
99
(Table S2, SI). 5
100 101
2.2 Sample preparation and extraction
102
PUF plug and filter samples were spiked with surrogate standards (PCB198 and
103
PCB209, Dr. Ehrenstorfer GmbH, Germany), and extracted twice with DCM:
104
n-hexane (1:1, v/v) at 100°C for 5 min using an accelerated solvent extraction
105
(ASE350, Dionex Inc.). The extracts were concentrated under a gentle stream of
106
nitrogen to ~0.5 mL after solvent-exchange to n-hexane, and cleaned up on a silica gel
107
column containing 3 cm silica gel (3% deactivated) at the bottom, 3 cm acidic silica
108
gel (silica gel: sulfuric acid=1:1, m/m) in the middle, and topped with 0.5 cm of
109
anhydrous sodium sulfate. PBDEs were eluted with 20 mL DCM: n-hexane (1:1, v/v),
110
and finally concentrated to ~30 µL. Prior to instrumental analysis, PCB208 was added
111
as the internal standard.
112 113
2.3 Instrumental analysis
114
Agilent 6890GC-5975MS applied with a DB5-MS capillary column (30 m ×
115
0.25 mm i.d. × 0.25 µm) was used for the separation of target 8 PBDEs, 6 NBFRs,
116
and 2 DPs, including BDE28, PBT, PBEB, HBB, BDE47, BDE100, BDE99, EH-TBB,
117
BDE154, BDE153, BDE183, BTBPE, BEH-TEBP, anti-DP, syn-DP, and BDE209. 1
118
µL of each extract was injected in the splitless mode. Helium was used as the carrier
119
gas at a flow rate of 1.2 mL/min. The oven temperature program was as follows: 80°C
120
for 1 min, increased to 210°C at a rate of 20°C/min, increased to 260°C at a rate of
121
10°C/min, increased to 300°C at a rate of 15°C/min, and then held for 20 min. 6
122 123
2.4 Quality assurance and quality control (QA/QC)
124
One procedural blank and one field blank were run with each batch of 10
125
samples to control potential contaminations. No target compounds were detected in
126
any blank samples, except for BDE209 (< 10%) and HBB (< 8%). The breakthrough
127
of the gaseous BFRs and DPs was tested using a second PUF plug (3.5 cm thick) in
128
series with the first one. Breakthroughs of BFRs are less than 10%. Method detection
129
limits (MDL) were calculated as the mean concentration of blanks plus three times the
130
standard deviation. The MDLs were 24.6 pg/m3 for BDE209 and 0.01-0.11 pg/m3 for
131
NBFRs, DPs, and other PBDEs. The average surrogate recoveries for PCB198 and
132
PCB209 in all samples were 93 ± 14% and 96 ± 15% for the gas phase and 87 ± 12%
133
and 84 ± 10% for the particle phase, respectively. The results were corrected by
134
blanks, but not by the surrogate recovery rates. The concentrations of target
135
compounds below the MDL were assigned zero for sums and 1/2MDL for correlation
136
analysis.
137 138
3. Results and discussion
139
3.1 Concentrations of BFRs and DPs in the air
140
The sum of BDE28, 47, 99, 100, 153, 154, and 183 is expressed as Σ7PBDEs. As
141
shown in Fig. 1 and Table S3 of SI, Σ7PBDEs in the gas phase ranged from 0.28 to
142
11.6 pg/m3 with an average of 4.40 ± 2.93 pg/m3, while Σ7PBDEs in the PM2.5 ranged
143
from 0.86 to 10.4 pg/m3 with an average of 2.68 ± 1.64 pg/m3. BDE28 exhibited the 7
144
highest level among those seven PBDEs in the gas phase followed by BDE47 and
145
BDE183, whereas BDE183 exhibited the highest level in PM2.5 followed by BDE99
146
and BDE153. Σ7PBDEs in gas phase were comparable with those (N.D.-28.8 pg/m3)
147
measured using PUF-passive air sampler in the industrial zones of Pakistan (Khan et
148
al., 2017), while Σ7PBDEs in both gas and PM2.5 (1.28-17.0 pg/m3) were also
149
comparable with those measured in urban area of Beijing (N.D.–23.6 pg/m3), China
150
(Shi et al., 2013b). The lowest concentration was discovered in the sample collected
151
during the timeframe of August 14-16, 2017 with a rainfall, while the highest
152
concentration was in the sample collected from September 4-6, 2017. The
153
concentrations of BDE209 were 26.4-15200 (average: 1460 ± 2500) pg/m3 in the gas
154
phase and 244-19600 (4290 ± 4310) pg/m3 in PM2.5. The levels of BDE209 in both
155
gas and PM2.5 in this study (707-19900 pg/m3) were much higher than those from the
156
urban area of Beijing (30.7-454 pg/m3), China (Shi et al., 2013a).
157
The total concentrations of 6 NBFRs (Σ6NBFRs) in the gas phase ranged from
158
0.27 to 25.3 (7.81 ± 6.85) pg/m3, while Σ6NBFRs in the PM2.5 ranged from 2.16 to
159
132 (13.6 ± 23.4) pg/m3. The dominant compounds were HBB followed by
160
BEH-TEBP in both gas phase and PM2.5. The total concentrations of DPs were in the
161
ranges of 0.02-0.74 (0.15 ± 0.14) pg/m3 and 0.03-1.06 (0.31 ± 0.22) pg/m3 in the gas
162
phase and PM2.5, respectively. The total concentrations of NBFRs and DPs in both gas
163
and PM2.5 were over three orders of magnitude lower than those measured in the
164
e-waste recycling areas of Karachi (gas and PM2.5; Σ6NBFRs (including DBDPE)
165
21.0-170 ng/m3, DPs: 15.0-85.0 ng/m3), Pakistan (Iqbal et al., 2017). Meanwhile, 8
166
levels of DPs in this study are comparable with concentrations observed in the air of
167
Atlantic Ocean (0.05-1.6 pg/m3) (Moller et al., 2012).
168 169
3.2 Compositions of BFRs and DPs in the air
170
The composition of BFRs and DPs are in the order of PBDEs > NBFRs > DPs.
171
For PBDEs, the predominant congener was BDE209 in both gas phase (98.4 ± 2.56%)
172
and PM2.5 (99.8 ± 0.25%). Relatively high abundances of BDE28 (0.5 ± 0.89%) were
173
also observed in the gas phase, which can be attributed to its low molecular weight
174
and high volatility. Besides BDE209, BDE183 also exhibited relatively high
175
abundances in both gas and particle phases. Although, BDE183 is the major
176
component in the octa-BDE commercial mixture along with BDE153 and 154 (Shi et
177
al., 2013b), debromination of high brominated PBDEs, such as BDE209, may also be
178
a possible source for those compounds in the atmosphere (Gerecke et al., 2005; Ahn et
179
al., 2006). Meanwhile, HBB, a replacement of deca-BDE product, was the dominant
180
NBFR congener (36.1 ± 21.2% of NBFRs in gas phase and 72.5 ± 17.2% in PM2.5),
181
followed by BEH-TEBP (gas 27.8 ± 18.7%, PM2.5 12.8 ± 12%). HBB is still produced
182
in China (Li et al., 2016a) and can also be degraded from polymeric BFRs (Moller et
183
al., 2011). For DPs, the relative abundances of syn-DP were lower than those of
184
anti-DP with the fsyn values (fsyn=syn-DP/(syn-DP+anti-DP) of 0.31±0.10 and
185
0.24±0.10 in the gas phase and PM2.5, respectively. The fsyn ratio was as slightly lower
186
than that of the commercial mixture (fsyn=0.4) (Wang et al., 2010a), suggesting a
187
fractionation of DPs in the atmosphere. 9
188 189
3.3 Seasonal variations of BFRs and DPs in the air
190
BFR concentrations in the air showed obvious seasonal variations, especially in
191
the gas phase. The average concentrations of Σ8PBDEs and Σ6NBFRs in the gas phase
192
both followed the order: summer > spring > autumn > winter. However, Σ8PBDEs in
193
PM2.5 were higher in winter than those in other seasons following the order: winter >
194
spring > summer > autumn. Meanwhile, Σ6NBFRs in PM2.5 were in the order of
195
spring > summer > autumn > winter. Not surprisingly, elevated gas-phase
196
concentrations of BFRs were observed during summer, since temperature is a major
197
factor affecting the seasonal variations of POPs in the air (Li et al., 2015). High
198
temperature may accelerate the volatilization of BFRs from various sources and from
199
fine particles, and intense solar radiation during summer may also promote
200
debromination of highly-brominated BFRs in the atmosphere (Gouin et al., 2002).
201
Meanwhile, as shown in Fig. 1, the relative proportion of PBDEs in the gas phase
202
relative to the particle phase increased with increasing temperature (Yang et al., 2012),
203
especially in summer from June to August. Surprisingly, concentrations of BDE209
204
decreased in both gas and PM2.5 phases after May 22nd, 2017 especially in PM2.5,
205
which may be due to the decreasing emissions from industries (may be due to the ban
206
of commercial deca-BDE). The high concentrations of Σ8PBDEs in PM2.5 in winter
207
may be due to the elevated PM2.5 and PBDE emissions from combustions such as
208
coal-heating combustion. The relatively high concentrations of Σ6NBFRs in PM2.5 in
209
spring and summer were caused by some specific emissions of HBB on March 27 and 10
210
July 17, 2017. Concentrations of DPs did not display any obvious seasonal trends,
211
which may be due to the relatively low air concentrations observed in this study.
212 213
3.4 Influences of meteorological conditions
214
In order to assess the influence of meteorological conditions on temporal trends
215
of BFRs and DPs in the atmosphere, we tested for correlations (Table 1 and Table S4,
216
SI). Temperature was significantly positively correlated (p < 0.006) with most BFRs
217
in the gas phase, including PBT, PBEB, HBB, BEH-TEBP, BDE28, 47, 100, 154, and
218
209, but negatively correlated (p < 0.04) with some BFRs in PM2.5, such as PBEB,
219
BEH-TEBP, BDE100, 99,153, and 209. This suggests that gas-PM2.5 partitioning of
220
BFRs is, to some extent, influenced by air temperature. The strong temperature
221
dependence observed for BFRs in the gas phase is similar to that observed in a
222
previous study (Li et al., 2015), which suggested that higher emissions of these
223
compounds are associated with increasing temperature. Correlations between
224
highly-brominated BFRs and temperature were weaker than those for less-brominated
225
BFRs, which may be due to their different volatilities and by their partitioning being
226
driven by physicochemical properties (Li et al., 2016b). Correlations between
227
BDE154, BEH-TEBP, BDE209 and temperature were positive for gas-phase
228
compounds but negative for these in PM2.5, suggesting that temperature significantly
229
influenced gas-PM2.5 partitioning for these three compounds. Solar radiation can
230
increase both volatilization (via increasing the temperature) and photodegradation of
231
highly-brominated PBDEs (Fang et al., 2008; Lagalante et al., 2011). Correlations 11
232
between BFRs and solar radiation were similar to those for temperature, except for
233
BDE183. Significant negative correlation (p < 0.01) was observed between solar
234
radiation and BDE183 in both gas phase and PM2.5, which suggests that influence of
235
solar radiation on the photodegradation was more important than that on the
236
volatilization for BDE183. Less-brominated BFRs in the gas phase were significantly
237
positively correlated (p < 0.05) with humidity, but negatively correlated (p < 0.05)
238
with wind speed, whereas correlations between BFRs in PM2.5 and humidity/wind
239
speed were mostly not significant. High wind speed can easily dilute the BFR
240
concentrations in the gas phase (Li et al., 2016b), but not for those in PM2.5.
241
Meanwhile, higher relative humidity may also lead to higher gas-phase concentrations
242
of POPs, since hydrophobic organic compounds have low tendencies to adsorb to
243
hydrated particles (Pankow et al., 1993). Air pressure was significantly negatively
244
correlated (p < 0.05) with most gas-phase BFRs, possibly because increased air
245
pressure may decrease the volatilization of BFRs. The influence of rainfall on air
246
concentrations of BFRs was not statistically significant, due to a limited number of
247
samples collected during rainy days.
248 249
3.5 Source apportionment
250
3.5.1 Correlations between BFR and DP congeners
251
Properties and use patterns of commercial flame retardant mixtures can influence
252
their concentrations and compositions (Ma et al., 2017), as well as their environmental
253
fates (La Guardia et al., 2006). Significant positive correlations (p < 0.047, Table S5, 12
254
SI) were observed among less-brominated BFRs, such as BDE28, 47, 100, PBT,
255
PBEB, and HBB in the gas phase (r: 0.359-0.885) or BDE28, 99, 100, PBT, PBEB,
256
and HBB in PM2.5 (r: 0.286-0.992), suggesting that they may originate from similar
257
sources and undergo similar environmental processes. A previous study (Wang et al.,
258
2017) also found a significant positive correlation between HBB and BDE47,
259
suggesting similar sources such as debromination from highly-brominated PBDEs or
260
polymeric BFRs. However, BDE99 in the gas phase only correlated with BDE100 and
261
some high BFRs such as BDE153 and BDE154, whereas BDE47 in PM2.5 had no
262
correlation with any BFRs or DPs. This interesting result suggests that BDE47 or
263
BDE99 may have other sources such as photodegradation or heterogeneous reaction.
264
Meanwhile, significant correlation was discovered between EH-TBB and BEH-TEBP,
265
which are commonly used as substitutes of penta-BDE (Covaci et al., 2011), in the
266
gas phase (p=0.034) but not in PM2.5 (p=0.065). BDE99, BDE153, and BDE154 were
267
also significantly positively correlated with each other in both the gas phase and PM2.5
268
(p < 0.001), which suggests similar sources, e.g., degradation from BDE209
269
(Kajiwara et al., 2008; Chen et al., 2015). A significant positive correlation (p < 0.05)
270
was also found between syn-DP and anti-DP, again indicating similar sources.
271 272
3.5.2 Correlations between BFRs/DPs and criteria air pollutants
273
Previous studies (Chang et al., 2014a; Chang et al., 2014b) have suggested
274
combustion or biomass burning as important sources of PBDEs. Combustion,
275
especially of fossil fuels, is also an important source of fine particles (e.g. PM2.5), SO2, 13
276
NO2, and CO in the atmosphere of China (Ding et al., 2018). To investigate the
277
potential influence of combustion on atmospheric levels of BFRs, correlations
278
between BFRs and criteria air pollutants were estimated and are shown in Table 1 and
279
Table S4, SI. Although SO2/NO2 were negatively correlated (p < 0.05) with low
280
molecular weight BFRs (BDE28, 47, 100, PBT, PBEB, and HBB) in the gas phase,
281
but positively correlated with high molecular weight BFRs in PM2.5, these may be
282
pseudo-correlations since they were both correlated with temperature. However,
283
BDE154 and BDE183 in particles were significant correlated with SO2, NO2, and CO,
284
but not with temperature, suggesting similar sources of these compounds, e.g., coal
285
combustion. The concentrations of fine particles (PM2.5, µg/m3) was significantly
286
correlated with highly-brominated BFRs such as BDE99, 100, 153, 154, 183, 209,
287
BTBPE, and BEH-TEBP in PM2.5 but not in the gas phase. This suggests that
288
increased concentration of fine particles, especially in winter, also elevated the
289
concentrations of particle-bound BFRs, which may be generated together from
290
combustions (Dong et al., 2015).
291 292
3.5.3 Principal component analysis
293
In this study, 14 BFRs, 2 DPs, 6 criteria air pollutants, and 6 meteorological
294
parameters were treated as independent variables for principle component analysis
295
(PCA). The loading plot is shown in Fig. 2. Contaminants located near each other may
296
originate from similar sources or undergo similar environmental processes. Two
297
principle components were extracted with 22% of PC1 and 21% of PC2, respectively. 14
298
Generally, variables can be divided into two main groups. Group 1 includes
299
temperature, solar irradiation, humidity, O3, and some less-brominated BFRs in the
300
gas phase, such as BDE28, 47, 100, 154, PBT, PBEB, and HBB. This implies that
301
these chemicals were significantly influenced by temperature-induced volatilization.
302
Group 2 consists of PM, SO2, NO2, CO, almost all HFRs in PM2.5 (except for BDE47
303
and HBB), and some gas-phase PBDEs (BDE99, 153, and 183). These compounds
304
may be significantly influenced by combustion and PM. TBB, DPs, and BDE209 in
305
the gas phase, which were not in these two groups, may be influenced by other
306
factors.
307 308
3.6 Gas-PM2.5 partitioning
309
Gas-particle partitioning is an important process influencing levels, transport, and
310
removal of POPs in the air (Tian et al., 2011). However, little is known of the
311
gas-particle partitioning of NBFRs, especially partitioning between the gas phase and
312
PM2.5. The measured gas-PM2.5 partition coefficients (Kp, m3/µg) and particle
313
fractions (fp) of atmospheric BFRs and DPs were calculated as follows (Pankow,
314
1994):
315
Kp = (Cp/CPM2.5)/Cg
(1)
316
fp = Cp/(Cg + Cp)
(2)
317
where CPM2.5 is the concentration of PM2.5 (µg/m3), Cp and Cg are the BFR
318
concentrations in PM2.5 and gas phase, respectively.
319
PM2.5 fractions of BFRs and DPs in the air during different seasons are shown in 15
320
Fig. 3. Generally, highly-brominated congeners are more particle-bound than
321
less-brominated ones during the same season. BDE28 (fp: 23±21%), PBT (31±29%),
322
and PBEB (30±25%) were mainly in the gas phase with syn-DP (61±20%), anti-DP
323
(68±19%), and BDE209 (63±31%) mostly in PM2.5, while the PM2.5 fractions of other
324
BFRs varied widely with sampling period. The PM2.5 fractions of most PBDEs in this
325
study are comparable with those measured in previous studies (Su et al., 2009; He et
326
al., 2019), except BDE183 and BDE209, which were lower than their results. This
327
may be because we only collected fine particles instead of total suspended particles.
328
Significant seasonality was discovered for the particle fractions of most BFRs, which
329
were much higher in winter but lower in summer than in other seasons. This may be
330
due to a strong influence of ambient temperature on their gas-particle partitioning
331
(Wong et al., 2001; Harner and Shoeib, 2002). Two exceptions are noteworthy.
332
EH-TBB and BDE153 were higher in autumn, while BDE183 and BTBPE were
333
higher in summer. Significant negative correlations (p≤0.003) were also observed
334
between the PM2.5 fractions of most BFRs and temperature, except for those four
335
BFRs. This suggests that these BFRs may be affected by certain sources or reactions.
336
For instance, as mentioned above, BDE183 in PM2.5 may be influenced by coal
337
combustion.
338
Subcooled liquid vapor pressure (PºL) and octanol-air partition coefficient (Koa)
339
have been widely used to predict gas-PM2.5 partitioning of SVOCs (Yang et al., 2018).
340
Previous studies have suggested that the logarithm of Kp generally follows a linear
341
relationship with log PºL (Pankow and Bidleman, 1991, 1992) and log Koa (Harner 16
342
and Bidleman, 1998; Pankow, 1998) under ambient temperatures and prevailing
343
particle characteristics and concentrations. The PºL and Koa values of PBDEs at 25ºC
344
shown here are based on Xu et al. (Xu et al., 2007), while the PºL and Koa values of
345
NBFRs and DPs at 25ºC were from Zhang et al (Zhang et al., 2016). As shown in Fig.
346
4, significant linear correlations were apparent for average log Kp versus log PºL (r2 =
347
0.675, p=0.0003) and log Koa (r2 = 0.631, p=0.001) for most of the BFRs and DPs,
348
except HBB and BEH-TEBP. This implies that most BFRs and DPs reach equilibrium
349
between the gas phase and fine particles. HBB and BEH-TEBP may have specific
350
sources considering their relatively high concentrations compared with other NBFRs,
351
and thus did not achieve equilibrium. The slope values are -0.191 and 0.143 for log Kp
352
vs. log PºL and log Koa respectively, which significantly differ from -1 or 1.
353
Theoretically, the slope of log Kp vs. log PºL equals -1 when chemicals reach
354
equilibrium between gas phase and PM2.5 (Pankow and Bidleman, 1992). However,
355
the slope being different to -1 may also suggest equilibrium at rural sites (Simcik et al.,
356
1998), since it can be influenced by many factors, such as ambient temperature,
357
non-exchangeability, or sampling sites (Ma et al., 2019). Smaller slopes were also
358
discovered in the urban (−0.200) and rural (−0.109) areas of Chaohu City, China (He
359
et al., 2019) and the urban areas (−0.201) of Florence, Italy (Cincinelli et al., 2014).
360 361
4. Conclusions
362
This study included a comprehensive interpretation of the characteristics,
363
influential factors, potential sources, and gas-PM2.5 partitioning of atmospheric BFRs 17
364
and DPs in Dalian, China. Significant seasonality was observed for gas-phase BFRs,
365
with higher levels apparent during summer. Meteorological conditions significantly
366
influenced the air levels of BFRs in Dalian, especially air temperature and solar
367
irradiation. Source apportionment suggested that less-brominated BFRs may originate
368
mainly from temperature-derived volatilizations or from degradation, while
369
highly-brominated BFRs may be associated with combustion or biomass burning. An
370
assessment of gas-PM2.5 partitioning suggested that most BFRs had reached
371
equilibrium, except HBB and BEH-TEBP. Despite the ban of PBDEs by the
372
Stockholm Convention, emissions from historical use or combustion are still
373
continuing, highlighting a need for further investigations.
374 375 376 377
Appendix A. Supplementary data Table S1-S5. Supplementary data associated with this article can be found in the online version.
378 379
Acknowledgements
380
This study was supported by the Key Laboratory of Coastal Environmental
381
Processes and Ecological Remediation, YICCAS (No. 2018KFJJ06), the National
382
Natural Science Foundation of China (Nos. 21976023 and 21577010), and the
383
Program of Introducing Talents of Discipline to Universities (B13012).
384 385
Reference 18
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538
22
539
Figures and Tables
540
Fig. 1 PBDEs, NBFRs, DPs, and BDE209 in the gas phase and PM2.5 of Dalian.
541
Fig. 2 Two-dimensional principal component loading plot of BFRs, DPs, criteria air
542
pollutants, and meteorological parameters.
543
Fig. 3 PM2.5 fractions of BFRs and DPs during different seasons.
544
Fig. 4 Liner correlations of log PºL and log Koa against average log Kp for BFRs and
545
DPs.
546 547 548
Table 1 Correlation coefficient matrix between main BFR congeners, criteria air pollutants, and meteorological parameters.
549
23
550
Fig. 1 PBDEs, NBFRs, DPs, and BDE209 in the gas phase and PM2.5 of Dalian.
551 552
24
553 554
Fig. 2 Two-dimensional principal component loading plot of BFRs, DPs, air pollutants, and meteorological parameters.
555
556 557
25
558
Fig. 3 PM2.5 fractions of BFRs and DPs during different seasons.
559 560
26
561
Fig. 4 Liner correlations of log PºL and log Koa against average log Kp for BFRs and
562
DPs.
563 564
27
565
Table 1 Correlation coefficient matrix between main BFR congeners, criteria air
566
pollutants, and meteorological parameters. BDE28
PBT
HBB BDE47 BDE100 BDE99 BDE154 BDE153 BDE183 BEH-TEBP
BDE209
Gas phase PM2.5
-0.223
0.09
-0.181
0.053
0.171
-0.264
-0.191
SO2
-.434** -.673** -.568** -.606** -.413**
.284*
-0.201
.335*
.631**
-.404**
-.344*
NO2
-.303* -.448** -.475** -.480** -.379**
0.175
-0.256
0.199
.441**
-.384**
-0.274
a
.503** .833** .739** .815** .599**
-0.01
.427**
-0.203
-.535**
.533**
.402**
.490** .658** .640** .669**
-0.168
0.265
-0.195
-.525**
0.244
.371**
T
SR
b
0.01
-.340* -0.268 -0.261
.326*
PM2.5 phase PM2.5
0.261
0.249
0.075
-0.013
.389** .576** .430**
.333*
0.204
.391**
.340*
SO2
0.246
0.201
-0.096
0.002
.502** .565** .480**
.543**
.450**
0.274
.307*
NO2
.306*
.284*
-0.063
-0.07
.596** .703** .633**
.519**
.406**
0.262
.292*
-0.226 -0.196
0.088
-0.131
-.353* -.430** -0.203
-.296*
-0.252
-.325*
-.320*
-0.192 -0.168
0.018
0.128
-.348* -.395** -0.225
-.368** -.440**
-0.111
-0.106
T
a
SR
567 568 569 570
b
*Statistically significant correlations at p < 0.05 level. **Statistically significant correlations at p < 0.01 level. a
Temperature.
b
Solar radiation.
28
Highlights Temperature, degradation, and combustion significantly affected air levels of BFRs. Gas-PM2.5 partitioning of BFRs and DPs suggested most of them reached equilibrium. PBDE emission from historical use or combustion still continues despite their ban.
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: