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PAHs in the atmospheric aerosols and seawater in the North–West Pacific ocean and sea of Japan
Journal Pre-proof PAHs in the atmospheric aerosols and seawater in the North–West Pacific ocean and sea of Japan Andrey S. Neroda, Anna A. Goncharova, Vasily F. Mishukov PII:
S1352-2310(19)30756-3
DOI:
https://doi.org/10.1016/j.atmosenv.2019.117117
Reference:
AEA 117117
To appear in:
Atmospheric Environment
Received Date: 7 June 2019 Revised Date:
31 October 2019
Accepted Date: 5 November 2019
Please cite this article as: Neroda, A.S., Goncharova, A.A., Mishukov, V.F., PAHs in the atmospheric aerosols and seawater in the North–West Pacific ocean and sea of Japan, Atmospheric Environment (2019), doi: https://doi.org/10.1016/j.atmosenv.2019.117117. 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.
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PAHs in the atmospheric aerosols and seawater in the North–West Pacific Ocean and Sea of Japan
3 4 5
Andrey S. Neroda [email protected], Anna A. Goncharova [email protected], Vasily F. Mishukov [email protected]
6 7
V.I.Il`ichev Pacific Oceanological Institute, FEB RAS, 43, Baltiyskaya Street, Vladivostok, 690041, Russia. Phone: +7 (423) 231-1400, fax: +7 (423) 231-2573 E-mail: [email protected]
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Abstract
10
PAHs were analyzed in samples of atmospheric aerosols and suspended matter in seawater
11
collected in the Sea of Japan, Sea of Okhotsk and the North-Western Pacific in June – July 2012.
12
The concentrations of Σ(15) PAHs in the suspended matter of seawater ranged between 1984.7 pg/L
13
to 30260.3 pg/L. The concentration of Σ(14) PAHs in marine aerosols ranged from 17.09 pg/m3 on
14
June 19-22, 2012 in the northern part of the Sea of Japan, the La Perouse Strait to 142.47 pg/m3 on
15
June 25 - 28, 2012 near middle Kuril Islands. The results of diagnostic ratios analysis indicate that
16
the primary sources of PAH are pyrogenic. This paper discusses the main anthropogenic (coal-fired
17
power plants and population) and natural sources (wildfires) of PAHs and their effect on the
18
concentration of these compounds in the marine air and suspended matter of seawater. Long-range
19
atmospheric transport of PAHs from the continent to the ocean is shown using HYSPLIT backward
20
trajectories. Active fire products (MODIS and VIIRS) data were used to build a regression model.
21
The model as a whole explains 58% and 75% of the Σ 5-ring PAHs and BaP variations in seawater
22
in June-July 2012, respectively. The analysis shows that anthropogenic sources were not a
23
significant contribution factor for PAHs in the seawater at the Sea of Japan during this period.
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Keywords: aerosols, PAH, seawater, wildfires, Pacific Ocean
26 27 28 29
1. Introduction
30
Polycyclic aromatic hydrocarbons (PAHs) are persistent organic compounds of various
31
structures, containing two or more aromatic rings. Significant toxicity of PAHs makes them an
32
important subject of environmental research. They have proven mutagenic (Kawanaka et al., 2004)
33
and carcinogenic effects on living organisms (Pashin and Bakhitova, 1979). The actual level of
34
PAHs toxicity varies, and according to the Agency for Toxic Substances and Disease Registry, 17
35
commonly found PAHs are considered to be of greatest concern. Two-ring Naphthalene (Nap);
36
three-ring PAHs were Acenaphthylene (Ace), Fluorene (Fle), Anthracene (Ant) and Phenanthrene
37
(Phe); four-ring PAHs were Fluoranthene (Flu), Pyrene (Pyr), benz[a]anthracene (BaA) and
38
Chrysene (Chr); five-ring PAHs were Benzo[b]fluoranthene (BbF), Benzo[k]fluoranthene (BkF),
39
Benzo[a]pyrene (BaP), Benzo[e]pyrene and Dibenz[a,h]anthracene (DBA); six-ring PAHs were
40
Benzo[ghi]perylene (BgPe) and Indeno[1,2,3-cd]pyrene (IDP).
41
Most PAHs have pyrogenic origin; they are formed through thermal decomposition and
42
recombination (pyrolysis and pyrosynthesis) of organic molecules. Other PAHs are formed at lower
43
temperatures during crude oil maturation and are thus called petrogenic. A common route of these
44
PAHs into the environment is spills of oil and its products. Sources of PAHs can be either natural or
45
anthropogenic. Natural sources include forest fires, burning of grass, volcanic activity, and
46
biological activity of microorganisms (Dat and Chang, 2017). Anthropogenic sources, which are
47
predominant in urban environments, include burning of wood, coal, gasoline, and diesel (Lee et al.,
48
1995) and other industrial processes (Mostert et al., 2010).
49
Over the past few decades of the 20th century, PAH levels have gradually decreased
50
(Menichini 1992), but intensive industrialization in East Asia led to an increase the PAH's in the
51
environment (Tang et al., 2018). The atmospheric outflow of PAHs only from China was estimated
52
to be 8092 tons/yr (Lang et al., 2008). Out of that amount, the 1.4 tons of PAHs reached North
53
America after more than nine days. PAHs have attracted much attention in studies on marine
54
environment pollution due to their adverse effect on marine organisms (Vecchiato et al., 2018). It is
55
known that PAHs in seawater tends to concentrate near the surface (Marty et al., 1978). PAHs are
56
usually insoluble in water, and they are usually found adsorbed on particles and gradually settle on
57
the bottom of water bodies as the deep sea sediments (Louvado et al., 2015), where they can
58
subsequently harm benthic organisms (Liu et al., 2012). PAHs actively accumulate in aquatic
59
organisms and then are transmitted to people through food chains, thereby creating a threat to
60
human health (Qiu et al., 2009). González-Gaya reported that diffusive PAHs from the atmosphere
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to the ocean represent a key perturbation of the oceanic carbon cycle and global atmospheric input
62
of polycyclic aromatic hydrocarbons to the global ocean is estimated at 90000 tons/month
63
(González-Gaya et al., 2016).
64
Given the significant influence of PAH concentrations on marine organisms and humans, it
65
is essential to have more simultaneous PAH observations in air and water of the open ocean, which
66
are still limited. It becomes necessary to search for methods and approaches for identifying the
67
sources affecting the content of pollutants in the surface waters of the ocean and the marine
68
atmosphere.
69
In connection with this, it becomes necessary to search for methods and approaches for
70
identifying the sources affecting the content of pollutants in the surface waters of the ocean and the
71
marine atmosphere.
72
The objective of this research is to increase knowledge about the global distribution of
73
PAHs in the marine boundary layer of air and sea surface and assess the role of the atmosphere in
74
the long-range transport of PAHs in aerosols. Another goal is to assess the role of natural and
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anthropogenic sources of PAHs in marine aerosols and surface waters of the Japanese, Okhotsk and
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north-eastern parts of the Pacific Ocean by long-range atmospheric transport.
77 78 79
2. Method 2.1 Samples
80
Atmospheric aerosols and surface seawater samples were collected during the 56th cruise of
81
the research vessel, "Professor Gagarinsky". The voyage started on June 13, 2012, in the port of
82
Vladivostok, went through La Perouse Strait into the Sea of Okhotsk, reached the Pacific Ocean on
83
June 25, 2012, then went through Tsugaru Strait back into the Sea of Japan, and ended on July 9,
84
2012, in Vladivostok. Overall the voyage covered area from 131.00, to 135.5 East Longitude and
85
from 35.5 to 47.00 North Latitude. Atmospheric aerosols (9 samples) were collected on Pallflex
86
TISSUQUARTZ (8x10 inch) membrane filters using high-volume air sampler (Model 120SL,
87
KIMOTO ELECTRIC, Japan) placed at the front of the ship's upper deck to avoid contamination
88
with the ship's exhaust gases. Before and after the sampling, the filters were dried to constant weight
89
in a desiccator and then weighed. The sampling time of one sample was 56 to 74 hours, depending
90
on the vessel course, pumped air volume was between 1500 and 2500 m3.
91
Seawater samples (26 samples) were taken using a bucket made of HDPEа from the surface.
92
Immediately after sampling the water samples were filtered into 55 mm Whatman GF/F filters (pore
93
size of 0.7 µm) using a glass vacuum filtration device (<0.015 MPa). The average water volume per
94
sample was 18 liters.
95
96
2.1.1 Extraction of PAHs (Aerosols)
97
When determining the concentrations of PAHs, aerosol filters were cut into small pieces
98
which were put in a flask, and then extracted twice with a solvent mixture of benzene/ethanol (3: 1)
99
40 mL with ultrasound activation for 30 min. The surrogate recovery standards (Nap-d8, Phe-d10,
100
Ace-d10, Pyr-d10, and BaP-d12) were added immediately after cutting the filters. After filtering and
101
adding 100 µl of dimethyl sulfoxide (DMSO), the solvents were evaporated under a weak vacuum
102
(1000 Pa, room temperature). After that, 900 µL of acetonitrile was added to the remaining 100µl of
103
DMSO. The qualitative and quantitative determination of PAH was carried out using HPLC (high-
104
performance
105
chromatographic column, 250 mm long and with internal diameter 4.6 mm (GL Sciences Inc.,
106
Tokyo, Japan) was used for the separation. Acetonitrile/water mixture was used as the mobile phase;
107
the feed rate of the mobile phase was 1 mL/min. As a result, concentrations of the following 14
108
PAHs were determined from each filter: the 2-ring PAH was Nap; 3-ring PAHs were Ace, Fle, Ant;
109
4-ring PAHs were Flu, Pyr, BaA, and Chr; 5-ring PAHs were BeP, BbF, BkF, BaP; 6-ring PAHs
110
were BghiPe and IDP. Nap (in the seawater), Phe (in the aerosols) and DBA (in the aerosols and the
111
seawater) could not be quantified.
liquid
chromatography)
and
a
fluorescent
detector.
An
Interstil ODS-P
112 113
2.1.2 Extraction of PAHs (Seawater)
114
Fourteen (15) PAHs were quantified in the all (26) surface water samples: 3-ring PAHs were
115
Ace, Fle, Ant and Phe; 4-ring PAHs were Flu, Pyr, BaA, and Chr; 5-ring PAHs were BeP, BbF,
116
BkF, BaP, and DBA; 6-ring PAHs were BgPe and IDP. Measuring of PAH concentrations was
117
performed on the HPLC system (L series, Hitachi High Technologies, Japan). Extraction of PAHs
118
for marine samples proceeded in the same way as with aerosol samples, except that dichloromethane
119
(50 mL) was used instead of a solvent mixture of benzene/ethanol. (Hayakawa et al., 2016).
120 121
2.3 Statistical analysis
122
The atmosphere is both the accumulator and the channel of transfer of substances coming
123
from different sources. The release of matter into the atmosphere can occur from natural and
124
anthropogenic sources. Biomass burning is both a natural and anthropogenic source of atmospheric
125
aerosols. As an anthropogenic source, it includes burning wood, burning grass residues after harvest.
126
Biomass burning is an important source of atmospheric gases and PM throughout the world. From
127
80% to 90% of the particles formed from burning forests have a diameter of less than 1 µm (Alonso-
128
Blanco et al., 2012), which contributes to the fact that aerosols from burning biomass can be
129
transported thousands of kilometers from the source (Alves et al., 2011). PAHs with five and six
130
rings are known to have been introduced into the marine environment mainly by dry and wet
131
deposition (Chen et al., 2016). Backward trajectories analysis was used to test a hypothesis that
132
PAHs in the samples come mostly from wild biomass burning (forest and grass fires) and not from
133
sources associated with human population centers (coal and petroleum combustion). The analysis
134
included comparing HYSPLIT backward trajectories with data from MODIS Active Fires product,
135
data on population density, and data about locations of biomass burning power plants.
136
2.3.1 Backward trajectories
137
The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT, version 4.9) model
138
(Stein et al., 2015) was used to analyze directions of atmospheric transport of PAHs to the sampling
139
sites. HYSPLIT backward trajectories were built using gridded meteorological data downloaded
140
from NOAA's Air Resources Laboratory servers. Specifically, this research used a 0.5° Global Data
141
Assimilation System (GDAS) model provided by the National Weather Service's National Center
142
for Environmental Prediction (NCEP).
143
For the atmospheric samples, this research used backward trajectories with 1-hour interval
144
using GPS data on the location of the vessel as endpoint parameters, 625 trajectories in total.
145
In this research, the atmospheric particulate matter deposition at the sampling sites is considered as
146
the main contributing factor to PAH water concentrations. Horizontal or vertical mixing of the
147
surface water was not considered significant in the short term. With these assumptions in mind,
148
backward air trajectories for each water sample were calculated for five days before the sampling
149
time. A total of 3120 backward trajectories for all seawater samples locations were calculated.
150
The duration of modeled backward trajectories was five days (120 hours) because Draxler
151
and Hess noted (Draxler and Hess, 1997) that longer trajectories typically have a significant radial
152
error. The altitude parameter of all endpoints was chosen to be 50 m above sea level.
153
In order to calculate active fire concentration for a trajectory, it is presented as a collection of line
154
segments on a geographical grid. These segments are determined from the trajectory points given by
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HYSPLIT model using a variation of Bresenham's line algorithm. The algorithm counted the
156
number of fires in 0.50 area along each line segment of a trajectory. The same algorithm is used to
157
calculate power plant concentration and average population density.
158
2.3.2 Active Fire Data Sources
159
Two NASA fire products were used to calculate the active fire concentration parameter, the
160
Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging
161
Spectroradiometer (MODIS). Their resolutions are 375 m and 1 km respectively. Fire detection in
162
these products is performed by contextual thresholding algorithms using radiometric signals from
163
4µm and 11 µm channels.
164
NASA distributes both products as simple text files, with every line containing latitude,
165
longitude, and date data for pixels classified as thermal anomalies by the algorithms. The products
166
present fire pixels with varying confidence levels. MODIS gives confidence in percentages; VIIRS
167
classifies confidence as either low, normal, and high. The algorithm in this study considered
168
MODIS fire with a confidence level above 55% and VIIRS pixels with normal and high confidence.
169 170
2.3.3 Population Density
171
The data on population density comes from the Gridded Population of the World, Version 4
172
(CIESIN 2018). Its data on the number of people per square kilometer is based on counts from
173
national censuses and population registers. The data in various formats and resolutions are free for
174
download.
175
The files for this data set are available as global rasters in ASCII (text) format. The ASCII
176
data used in this research had 15 arc-minute resolution (0.25 degree). The data were stored in
177
WGS84, geographic coordinate system (latitude/longitude).
178 179
2.3.4 Power Plant
180
Coal-fired power plants are a significant source of atmospheric PAHs (Wang et al., 2015).
181
Data on the location of coal and gas power plant comes from The Global Power Plant Database,
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which is a comprehensive, open source database of power plants around the world. Each power
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plant is geolocated, and entries contain information on plant capacity and fuel type. (Global Energy
184
Observatory) built and put into operation by 2012.
185 186
According to U.S. Energy Information Administration data, China peaked in manufacturing of bituminous coal in 2012. (https://www.eia.gov/beta/international/).
187
3. Results and discussion
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3.1 PAH in the aerosols
189
The concentration of Σ(14) PAHs in marine aerosols ranged from 17.09 pg/m3 in a sample
190
#3 taken on June 19-22, 2012 in the northern part of the Sea of Japan, the La Perouse Strait to
191
142.47 pg/m3 in sample #5 taken on June 25 - 28, 2012 near middle Kuril Islands. Fig. 1 shows the
192
rout of the ship together with concentrations of five-ring and six-ring PAHs in aerosol samples. The
193
R=BeP/(BeP+BaP) is usually used (Fang et al., 1999; Li et al., 2006) for ascertaining the aging
194
process. This ratio allows in outline determination of the source location. The 120-hour backward
195
trajectories constructed for sample #5 showed that air masses came from the north-eastern part of
196
Russia, passed over the Sea of Okhotsk. The R=BeP/(BeP+BaP) ratios for all atmospheric samples
197
ranged from 0.54 to 0.81, with an average value of 0.71. Studies show that for aerosol samples
198
collected near their source, this coefficient (R) is between 0.45 and 0.57. If the source is located at a
199
considerable distance, the PAHs are subjected to photochemical destruction (photolysis) during
200
long-range aerosol transport, and the concentrations of benz(a)pyrene decrease more rapidly than
201
benz(e)pyrene so that R in the samples varies from 0.6 to 0.83. High values of R in this study
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indicate predomination of remote sources of PAHs vs. local ones (e.g., ship exhaust). The only
203
sample with low R=0.54 is sample #3 (Fig. 2) taken on June 19-22, 2012 in the La Perouse Strait,
204
that has the lowest PAHs concentration.
205 206
Fig. 1 Map of aerosol sampling sites with concentrations of five- and six-ring PAHs. Blue dots show
207
the ship's route. Bars indicate the places where the filters were changed.
208
209 9
0.9 BaP
BeP/(BeP+BaP)
8
0.8
7
0.7
6
0.6
5
0.5
4
0.4
3
0.3
2
0.2
1
0.1
0
BeP/(BeP+BaP)
5-ring PAH, pg/L
BeP
0 1
2
3
4
5
6
7
8
9
Sample number
210 211
Fig. 2 The ratios R=BeP/(BeP+BaP) for air samples.
212
The ratios BaA/(BaA + Chr) were used to determine the source types, petrogenic, pyrogenic,
213
or mixed sources (Yunker et al., 2002). Researches usually use this ratio for approximate
214
identification of sources of PAH. It is burning oil products or burning wood, grass, and coal. Values
215
below 0.40 indicate petrogenic sources, values from 0.40 to 0.50 indicate oil burning, and values
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above 0.50 indicate PAHs from burning wood, grass, and coal. Fig. 3 shows these two coefficients
217
in two profiles. The ratio of Flu/(Flu + Pyr) in all samples of marine aerosols was above 0.5, which
218
indicates that the sources of PAHs were combustion processes (Grass, wood, coal combustion). The
219
BaA/(BaA + Chr) ratios also indicate combustion processes, with mixed sources for two samples:
220
sample #3 in the La Perouse Strait and sample #4 from southern Sakhalin Island to the Bussol Strait
221
near Urup Island. This can be explained by proximity to the Sakhalin-2 production complex, which
222
includes a liquefied natural gas plant, a crude oil export terminal and the Prigorodnoye port. Another
223
expected factor for this site is gas flaring on the eastern part of Sakhalin and the shelf. PAH
224
concentrations in atmospheric aerosols were in good agreement with PAH data in ocean aerosols
225
from other studies (Ma, Yuxin, et al., 2013).
226 227
The PAH concentrations for each aerosol and seawater sample is presented in Tab.1 and Tab.2 at the end of this paper.
228 229
Fig. 3 Diagnostic ratios calculated for air samples and sea samples. The two samples of atmospheric
230
aerosols are encircled together with the corresponding (in time and place of sampling) samples of
231
suspended matter in sea water, which have high concentrations of PAHs.
232 233
3.2 Seawater samples (Suspended particulate matter).
234
The sum of concentrations of eleven PAHs (four, five and six-ring) in the suspended matter
235
of seawater ranged between 1117.16 pg/L for June 30, 2012 sample to 5543.8 pg/L for June 17,
236
2012 sample. The highest concentrations of PAHs were observed in areas close to the city of
237
Vladivostok Fig. 4. The sum of concentrations of two-ring and three-ring PAHs ranged from 893.23
238
pg/L to 15669.19 pg/L. It should be noted that these PAHs are contained to a greater extent in the
239
soluble fraction, and two PAHs (Nap and Phe) were not found in several samples of suspended
240
matter (Tab. 2).
241 242
Fig. 4 Map of seawater sampling sites with concentrations of five- and six-ring PAHs The BeP/(BeP + BaP) ratios in the suspended matter of seawater ranged from 0.44 to 0.99,
243 244
with an average value of 0.72 (
245
Fig. 5). For most samples, the ratio was above 0.6, which indicates the remoteness of the PAHs
246
sources (Fang et al., 1999; Li et al., 2006). For samples #2, #3, #4, #9, and #13, the BeP/(BeP +
247
BaP)
ratio
was
below
0.6,
indicating
presence
of
local
PAH
sources.
248 800
1.2 BeP
BaP
BeP/(BeP+BaP)
700 1
0.8 500
400
0.6
BeP/(BeP+BaP)
5-ring PAH, pg/L
600
300 0.4 200 0.2 100
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
249
Sample number
250 251
Fig. 5 Ratios R=BeP/(BeP+BaP) for seawater samples
252
The ratios Flu/(Flu + Pyr) and BaA/(BaA + Chr) in most samples of the suspended matter in
253
seawater were above 0.5 and 0.35, respectively, indicating that the PAH sources were combustion
254
processes. In samples #10 and #11 (Fig. 3), the ratio of BaA/(BaA + Chr) was below 0.2, which
255
indicates petrogenic sources. Petrogenic PAHs are associated with spills of crude and processed oil
256
(Soclo et al., 2000). These samples were taken in the area from the Strait of La Perouse to the
257
middle Kurile Islands. In this area, as already mentioned above, there is a plant for the production of
258
liquefied natural gas (southern Sakhalin) to the north of the sampling point. The Karakumneft tanker
259
accident that occurred in early 2012 and resulted in the spill of 300 cubic meters of oil, also speaks
260
of the petrogenic origin of PAH's in the area.
261 262
The Flu/(Flu + Pyr) ratios for sample #12 (Fig. 3) were above 0.57, but below 0.35 for BaA/(BaA + Chr), which indicates different sources(mixed sources).
263 264 265 266
It must be noted that Flu and Pyr exhibit different rates of photodegradation, as do BaA and Chr, and that can considerably affect the Flu/(Flu + Pyr) and BaA/(BaA + Chr) ratios. According to Flu/(Flu+Pyr) ratios, was shown that the primary sources of PAH in surface seawater and atmospheric aerosols were pyrogenic sources (burning of wood, grass, and coal).
267
Backward trajectories analysis with active fires satellite data shows that the primary source
268
of PAHs in the seawater samples was biomass burning. Correlation coefficients between PAHs
269
concentrations and the active fire parameters for MODIS and VIIRS were similar, so, for simplicity,
270
only MODIS active fire data is discussed.
271
The correlation between the concentrations of individual PAHs, the sum of PAHs, the sum
272
of 5-ring PAHs in the suspended matter of seawater and the concentration of active fires recorded
273
along 120 hour backward trajectories to the sampling site showed that there is a positive relationship
274
with the total PAH was 0.62 (p=0.001). The sum of 5-ring PAHs was 0.77 (p=0.0001). The sum of
275
6-ring PAHs was 0.71 (p=0.0001); the sum of 4-ring PAHs was 0.46 (p=0.018). The active fire
276
parameter also significantly correlated with each PAHs, most strongly with BaP (0.87, p=0.001). On
277
the other hand, the population density parameter showed a significant correlation only with BaA
278
0.61 (p=0.001). Correlation between the power plant concentration and individual PAHs and their
279
sums was also below the significance threshold except for BaA (0.5, p=0.008).
280
For marine aerosols, we used the Spearman and Kendall tau correlations (this type of
281
correlation was chosen due to the small number of samples) between the concentration of PAHs and
282
the sum of active fires recorded along 120-hour return paths to the sampling site. The results showed
283
a significant positive correlation (0.93, p < 0.05) between the sum of 5-ring PAHs and active fire
284
concentration. Significant positive correlation between total PAHs and active fire concentration was
285
0.81, (p < 0.05). For sum of 4-ring PAHs was - (0.91, p < 0.05). A similar correlation (0.74, p <
286
0.05) was with Ace, Flu (0.84, p < 0.05), Pyr (0.84, p < 0.05), Chr (0.76, p < 0.05), BeP (0.86, p <
287
0.05) BbF (0.86, p < 0.05) and BkF (0.89, p < 0.05). At the same time, no correlation was found
288
between any PAH concentrations or individual PAHs and the population density and coal-fired
289
power plants.
290
It is known that population density impacts wildfire frequency. Studies show that an
291
increase in the population density reduces the frequency of fires, except for sparsely populated
292
areas, where the effect is only slightly positive (Knorr et al., 2014). Another study showed that
293
specifically for the region examined in this paper relationship between fires and population is
294
positive for some areas (north-eastern Siberia, central China) and negative for others (Northeastern
295
China) (Bistinas et al., 2013). Average population density and average fire concentration calculated
296
for backward trajectories were not significantly correlated.
297
Fig. 6 shows five-day backward trajectories of air masses to the seawater sampling sites. The
298
backward trajectories for samples 2.8 and 9 have few intersections with the sites of active fires on
299
the continent, which corresponds to the minimum values of the amount of PAHs in samples of
300
suspended solids in sea water The backward trajectories for samples 3 through 7 have more
301
intersections with the sites of active fires, which corresponds to the maximum values of the amount
302
of PAHs in samples of suspended solids in sea water. The values are shown in Fig. 8.
303
304
305
306 307
Fig. 6 Backward trajectories for seawater samples from #2 to #9. Orange dots show active fires for
308
corresponding dates.
309
Fig. 7 shows five-day backward trajectories of air masses to the segments of the ship’s route
310
on which the aerosol samples were taken. The high number of intersections with active fires for
311
sample 5 may explain high PAHs concentration for that sample. While low number of active fires
312
for sample 3 corresponds to low concentration of PAHs in that sample.
313
314 315 316
Fig. 7 Backward trajectories for aerosol samples #3 (left) and #5 (right). Orange dots show active fires for corresponding dates.
0.016
2500 Σ(BeP+BbF+BkF+BaP) MODIS Active Fires, confidence 45-100% MODIS Active Fires, confidence 55-100%
0.014
2000
0.01
1500
0.008 1000
0.006
Summ 5-ring PAH, Pg/L
Active fires concentration
0.012
0.004 500 0.002
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Sample number
317 318
Fig. 8 The total of the 5-ring PAHs in the suspended matter of seawater and the active fire
319
concentration (Active fires per 1000 km2) along the backward trajectories of the movement of air
320
masses (data from MODIS Active Fires product).
321 322
3.3 Multiple regression analysis
323
Multiple regression analysis was performed using SPSS Statistics 12 (x64). The measured
324
PAH concentrations of marine and air samples include the natural and anthropogenic factors were
325
used to build a multiple regression model. Variables considered for inclusion in the model were the
326
ones that had some of the highest pairwise correlations with the PAH concentrations. Those were
327
active fires concentration along 120-hour backward trajectories and population density.
328
The final model with the best fit to the data set included one variable: the active fires along
329
120-hour backward trajectories. The correlation for the regression was 0.77 with adjusted =0.58,
330
meaning that the model as a whole explains 58% of the SUM 5-ring PAHs variation. The
331
significance of the calculated correlation was statistically evaluated using t-test and F-test. The
332
regression was found significant with F=35.3, p < 0.0001. A separate multiple regression analysis
333
was conducted for BaP. The correlation for the regression was 0.87 with adjusted =0.75, F=74.1, p
334
< 0.0001. The model as a whole explains 75% of the BaP variation in the surface water.
335 336 337
Conclusions
338
PAH concentrations in the Sea of Japan were higher than in the surface waters of the north-
339
eastern Pacific. This is due to the proximity of the continental sources of PAHs to the Sea of Japan.
340
In turn, in the north-eastern Pacific Ocean, intensive processes of PAH mixing in ocean water
341
reduce their concentration. The results indicate that the primary source of PAH, according to PAH
342
molecular ratios Flu/(Flu + Pyr), in surface water and marine aerosols in the Sea of Japan and the
343
north-eastern Pacific in June-July 2012 was pyrogenic (burning of grass, wood, and coal). The
344
wildfires explained more than 75% of BaP variation in seawater in June-July 2012. The strong
345
correlation between active fires and PAHs concentrations in the suspended matter can be explained
346
by the fact that the surface seawater accumulates particulate matter. A method was proposed for
347
estimating the contribution of natural and anthropogenic sources to PAH concentration using
348
HYSPLIT backward trajectories and satellite data.
349 350
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461
Tab. 1 PAH concentrations (pg/m3) in aerosol samples
Two-ring Sampling period
462
Three-ring
Four-ring
Five-ring
Six-ring
Nap
Ace
Fle
Ant
Flu
Pyr
BaA
Chr
BeP
BbF
BkF
BaP
BgPe
IDP
Aerosol µg/m3
06/13/2012
06/16/2012
16.26
0.75
1.90
n/d
8.62
9.12
4.28
6.15
2.88
6.93
2.56
1.67
n/d
n/d
26.41
06/16/2012
06/19/2012
15.61
0.56
3.44
0.25
7.28
7.58
2.11
4.08
3.42
5.43
1.89
1.96
4.93
6.28
26.12
06/19/2012
06/22/2012
4.81
0.25
0.56
0.07
2.13
2.31
0.69
1.10
0.61
1.46
0.48
0.53
0.99
1.11
30.35
06/22/2012
06/25/2012
15.02
0.56
3.87
n/d
7.49
8.12
2.61
3.93
2.34
4.80
1.22
0.72
2.01
2.45
11.84
06/25/2012
06/28/2012
20.67
0.92
4.39
0.90
22.28
23.89
7.93
12.85
7.84
17.81
5.05
3.41
6.60
7.93
29.53
06/28/2012
07/01/2012
18.10
0.98
1.11
0.62
10.90
10.91
2.20
3.02
5.05
6.51
2.20
2.01
14.05
12.25
25.46
07/01/2012
07/04/2012
11.17
0.74
n/d
0.26
9.32
10.53
1.94
3.30
3.34
7.54
1.88
0.85
4.18
4.05
22.02
07/04/2012
07/07/2012
14.01
0.83
2.67
0.31
12.73
13.98
1.71
4.30
5.52
8.65
2.24
1.25
4.57
5.10
18.98
07/07/2012
07/09/2012
14.01
0.83
2.67
0.31
12.73
13.98
1.71
4.30
5.52
8.65
2.24
1.25
4.57
5.10
25.74
463
Tab. 2 PAH concentrations in seawater samples (pg/L)
№
Date
Two-ring
Three-ring
NaP
Ace
Fle
Phe
Four-ring Ant
Flu
Five-ring
Six-ring
Pyr
BaA
Chr
BeP
BbF
BkF
BaP
DBA
BgPe
IDP
1
6/13/2012
n/d
36.80
360.62
22676.28
197.40
2780.01
2718.38
113.53
87.36
188.09
618.12
37.54
75.59
104.88
230.95
139.66
2
6/14/2012
n/d
9.83
174.91
11733.29
111.09
1544.40
1495.44
59.92
31.78
102.07
469.79
47.62
76.08
n/d
198.00
112.54
3
6/15/2012
n/d
4.79
68.65
2693.33
149.97
1633.33
1313.67
49.26
12.67
58.27
194.16
12.73
73.64
n/d
55.53
78.01
4
6/16/2012
n/d
0.26
32.89
n/d
99.02
1676.34
1408.14
76.30
38.51
76.31
239.85
4.93
58.49
n/d
102.26
87.22
5
6/17/2012
n/d
2.99
264.97
12779.57
134.16
1425.73
1241.99
133.81
193.64
744.99
937.85
102.51
237.68
25.07
349.93
150.60
6
6/17/2012
n/d
0.33
161.64
5601.61
59.06
711.10
625.47
50.11
73.48
481.18
992.02
34.26
112.01
93.30
333.72
95.60
7
6/18/2012
250.44
17.13
102.20
n/d
105.84
1130.83
1068.48
91.26
115.62
322.35
352.97
39.57
70.44
43.83
125.11
38.37
8
6/19/2012
126.36
4.27
33.43
n/d
64.92
496.88
470.01
40.06
34.60
40.20
92.79
8.08
10.31
3.75
16.07
14.67
9
6/20/2012
41.18
1.97
24.22
n/d
199.30
728.05
597.75
29.79
14.99
22.84
69.05
10.34
19.35
5.00
17.46
16.13
10
6/21/2012
13.91
2.59
6.16
n/d
131.24
771.54
527.17
4.11
52.16
16.97
70.17
3.80
9.52
3.67
3.95
16.12
11
6/22/2012
24.37
2.43
9.85
n/d
137.28
613.99
421.85
9.98
48.51
21.00
46.50
3.64
9.71
n/d
20.37
14.44
12
6/23/2012
15.34
3.14
22.21
15269.13
359.37
742.22
528.39
16.35
45.41
45.70
64.70
5.93
15.37
n/d
10.53
11.69
13
6/24/2012
15.01
3.35
16.15
n/d
114.97
748.83
493.58
10.96
2.88
17.29
48.76
2.85
17.34
n/d
8.77
20.47
14
6/25/2012
12.99
1.64
7.19
n/d
95.13
1005.30
652.80
16.17
0.69
18.63
54.44
2.44
11.92
n/d
14.39
18.54
15
6/26/2012
25.12
0.76
40.77
7459.03
76.53
540.23
449.00
18.92
9.58
45.32
65.41
10.59
16.25
2.27
30.51
20.89
16
6/27/2012
16.07
2.35
25.65
13621.06
196.69
572.18
646.14
21.97
80.07
34.12
49.28
6.17
8.39
3.77
15.97
10.84
17
6/27/2012
26.91
2.05
32.18
10782.66
139.77
612.45
629.72
36.92
13.08
26.46
37.82
3.96
5.36
3.71
6.00
7.02
18
6/28/2012
13.67
3.01
31.74
14418.74
233.98
606.13
632.76
21.95
75.77
25.66
74.50
7.90
16.83
2.45
31.80
20.38
19
6/29/2012
27.24
1.64
23.36
8554.04
172.22
529.95
454.08
11.09
3.77
37.37
65.90
3.21
6.86
3.41
7.78
5.38
20
6/30/2012
19.72
5.53
21.71
715.76
130.51
471.17
440.71
11.05
1.29
58.23
63.75
4.43
11.37
5.89
30.02
19.25
21
7/2/2012
25.66
1.34
18.43
1082.37
185.52
658.83
496.17
10.23
0.60
39.86
67.00
4.60
12.38
5.17
23.27
14.49
22
7/3/2012
58.06
0.50
18.35
8860.12
223.37
604.28
476.14
9.40
3.55
38.08
45.23
3.89
9.69
3.93
17.43
12.54
23
7/4/2012
24.73
0.89
18.05
3193.68
165.79
750.13
586.78
9.06
1.40
19.44
33.92
1.53
3.67
2.96
5.68
8.49
24
7/5/2012
42.83
3.44
11.58
n/d
89.06
835.41
581.23
3.59
0.39
16.67
23.81
0.62
2.75
n/d
2.16
3.91
25
7/6/2012
91.49
2.72
3.50
n/d
52.18
683.02
590.64
10.12
4.08
231.15
139.00
2.22
3.52
n/d
38.52
3.28
26
7/8/2012
60.70
0.35
50.88
7978.87
78.55
937.17
806.01
98.64
63.74
24.12
178.61
7.78
8.07
0.89
15.67
12.94
Long-range atmospheric transport plays important role in transfer PAH to Ocean. Forest fires increase 5-ring PAH concentrations in the surface seawater. A new approach is proposed for studying PAH variations in surface seawater.
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:
Andrey Neroda Anna Goncharova Vasiliy Mishukov
S1352-2310(19)30756-3
DOI:
https://doi.org/10.1016/j.atmosenv.2019.117117
Reference:
AEA 117117
To appear in:
Atmospheric Environment
Received Date: 7 June 2019 Revised Date:
31 October 2019
Accepted Date: 5 November 2019
Please cite this article as: Neroda, A.S., Goncharova, A.A., Mishukov, V.F., PAHs in the atmospheric aerosols and seawater in the North–West Pacific ocean and sea of Japan, Atmospheric Environment (2019), doi: https://doi.org/10.1016/j.atmosenv.2019.117117. 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.
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PAHs in the atmospheric aerosols and seawater in the North–West Pacific Ocean and Sea of Japan
3 4 5
Andrey S. Neroda [email protected], Anna A. Goncharova [email protected], Vasily F. Mishukov [email protected]
6 7
V.I.Il`ichev Pacific Oceanological Institute, FEB RAS, 43, Baltiyskaya Street, Vladivostok, 690041, Russia. Phone: +7 (423) 231-1400, fax: +7 (423) 231-2573 E-mail: [email protected]
8 9
Abstract
10
PAHs were analyzed in samples of atmospheric aerosols and suspended matter in seawater
11
collected in the Sea of Japan, Sea of Okhotsk and the North-Western Pacific in June – July 2012.
12
The concentrations of Σ(15) PAHs in the suspended matter of seawater ranged between 1984.7 pg/L
13
to 30260.3 pg/L. The concentration of Σ(14) PAHs in marine aerosols ranged from 17.09 pg/m3 on
14
June 19-22, 2012 in the northern part of the Sea of Japan, the La Perouse Strait to 142.47 pg/m3 on
15
June 25 - 28, 2012 near middle Kuril Islands. The results of diagnostic ratios analysis indicate that
16
the primary sources of PAH are pyrogenic. This paper discusses the main anthropogenic (coal-fired
17
power plants and population) and natural sources (wildfires) of PAHs and their effect on the
18
concentration of these compounds in the marine air and suspended matter of seawater. Long-range
19
atmospheric transport of PAHs from the continent to the ocean is shown using HYSPLIT backward
20
trajectories. Active fire products (MODIS and VIIRS) data were used to build a regression model.
21
The model as a whole explains 58% and 75% of the Σ 5-ring PAHs and BaP variations in seawater
22
in June-July 2012, respectively. The analysis shows that anthropogenic sources were not a
23
significant contribution factor for PAHs in the seawater at the Sea of Japan during this period.
24 25
Keywords: aerosols, PAH, seawater, wildfires, Pacific Ocean
26 27 28 29
1. Introduction
30
Polycyclic aromatic hydrocarbons (PAHs) are persistent organic compounds of various
31
structures, containing two or more aromatic rings. Significant toxicity of PAHs makes them an
32
important subject of environmental research. They have proven mutagenic (Kawanaka et al., 2004)
33
and carcinogenic effects on living organisms (Pashin and Bakhitova, 1979). The actual level of
34
PAHs toxicity varies, and according to the Agency for Toxic Substances and Disease Registry, 17
35
commonly found PAHs are considered to be of greatest concern. Two-ring Naphthalene (Nap);
36
three-ring PAHs were Acenaphthylene (Ace), Fluorene (Fle), Anthracene (Ant) and Phenanthrene
37
(Phe); four-ring PAHs were Fluoranthene (Flu), Pyrene (Pyr), benz[a]anthracene (BaA) and
38
Chrysene (Chr); five-ring PAHs were Benzo[b]fluoranthene (BbF), Benzo[k]fluoranthene (BkF),
39
Benzo[a]pyrene (BaP), Benzo[e]pyrene and Dibenz[a,h]anthracene (DBA); six-ring PAHs were
40
Benzo[ghi]perylene (BgPe) and Indeno[1,2,3-cd]pyrene (IDP).
41
Most PAHs have pyrogenic origin; they are formed through thermal decomposition and
42
recombination (pyrolysis and pyrosynthesis) of organic molecules. Other PAHs are formed at lower
43
temperatures during crude oil maturation and are thus called petrogenic. A common route of these
44
PAHs into the environment is spills of oil and its products. Sources of PAHs can be either natural or
45
anthropogenic. Natural sources include forest fires, burning of grass, volcanic activity, and
46
biological activity of microorganisms (Dat and Chang, 2017). Anthropogenic sources, which are
47
predominant in urban environments, include burning of wood, coal, gasoline, and diesel (Lee et al.,
48
1995) and other industrial processes (Mostert et al., 2010).
49
Over the past few decades of the 20th century, PAH levels have gradually decreased
50
(Menichini 1992), but intensive industrialization in East Asia led to an increase the PAH's in the
51
environment (Tang et al., 2018). The atmospheric outflow of PAHs only from China was estimated
52
to be 8092 tons/yr (Lang et al., 2008). Out of that amount, the 1.4 tons of PAHs reached North
53
America after more than nine days. PAHs have attracted much attention in studies on marine
54
environment pollution due to their adverse effect on marine organisms (Vecchiato et al., 2018). It is
55
known that PAHs in seawater tends to concentrate near the surface (Marty et al., 1978). PAHs are
56
usually insoluble in water, and they are usually found adsorbed on particles and gradually settle on
57
the bottom of water bodies as the deep sea sediments (Louvado et al., 2015), where they can
58
subsequently harm benthic organisms (Liu et al., 2012). PAHs actively accumulate in aquatic
59
organisms and then are transmitted to people through food chains, thereby creating a threat to
60
human health (Qiu et al., 2009). González-Gaya reported that diffusive PAHs from the atmosphere
61
to the ocean represent a key perturbation of the oceanic carbon cycle and global atmospheric input
62
of polycyclic aromatic hydrocarbons to the global ocean is estimated at 90000 tons/month
63
(González-Gaya et al., 2016).
64
Given the significant influence of PAH concentrations on marine organisms and humans, it
65
is essential to have more simultaneous PAH observations in air and water of the open ocean, which
66
are still limited. It becomes necessary to search for methods and approaches for identifying the
67
sources affecting the content of pollutants in the surface waters of the ocean and the marine
68
atmosphere.
69
In connection with this, it becomes necessary to search for methods and approaches for
70
identifying the sources affecting the content of pollutants in the surface waters of the ocean and the
71
marine atmosphere.
72
The objective of this research is to increase knowledge about the global distribution of
73
PAHs in the marine boundary layer of air and sea surface and assess the role of the atmosphere in
74
the long-range transport of PAHs in aerosols. Another goal is to assess the role of natural and
75
anthropogenic sources of PAHs in marine aerosols and surface waters of the Japanese, Okhotsk and
76
north-eastern parts of the Pacific Ocean by long-range atmospheric transport.
77 78 79
2. Method 2.1 Samples
80
Atmospheric aerosols and surface seawater samples were collected during the 56th cruise of
81
the research vessel, "Professor Gagarinsky". The voyage started on June 13, 2012, in the port of
82
Vladivostok, went through La Perouse Strait into the Sea of Okhotsk, reached the Pacific Ocean on
83
June 25, 2012, then went through Tsugaru Strait back into the Sea of Japan, and ended on July 9,
84
2012, in Vladivostok. Overall the voyage covered area from 131.00, to 135.5 East Longitude and
85
from 35.5 to 47.00 North Latitude. Atmospheric aerosols (9 samples) were collected on Pallflex
86
TISSUQUARTZ (8x10 inch) membrane filters using high-volume air sampler (Model 120SL,
87
KIMOTO ELECTRIC, Japan) placed at the front of the ship's upper deck to avoid contamination
88
with the ship's exhaust gases. Before and after the sampling, the filters were dried to constant weight
89
in a desiccator and then weighed. The sampling time of one sample was 56 to 74 hours, depending
90
on the vessel course, pumped air volume was between 1500 and 2500 m3.
91
Seawater samples (26 samples) were taken using a bucket made of HDPEа from the surface.
92
Immediately after sampling the water samples were filtered into 55 mm Whatman GF/F filters (pore
93
size of 0.7 µm) using a glass vacuum filtration device (<0.015 MPa). The average water volume per
94
sample was 18 liters.
95
96
2.1.1 Extraction of PAHs (Aerosols)
97
When determining the concentrations of PAHs, aerosol filters were cut into small pieces
98
which were put in a flask, and then extracted twice with a solvent mixture of benzene/ethanol (3: 1)
99
40 mL with ultrasound activation for 30 min. The surrogate recovery standards (Nap-d8, Phe-d10,
100
Ace-d10, Pyr-d10, and BaP-d12) were added immediately after cutting the filters. After filtering and
101
adding 100 µl of dimethyl sulfoxide (DMSO), the solvents were evaporated under a weak vacuum
102
(1000 Pa, room temperature). After that, 900 µL of acetonitrile was added to the remaining 100µl of
103
DMSO. The qualitative and quantitative determination of PAH was carried out using HPLC (high-
104
performance
105
chromatographic column, 250 mm long and with internal diameter 4.6 mm (GL Sciences Inc.,
106
Tokyo, Japan) was used for the separation. Acetonitrile/water mixture was used as the mobile phase;
107
the feed rate of the mobile phase was 1 mL/min. As a result, concentrations of the following 14
108
PAHs were determined from each filter: the 2-ring PAH was Nap; 3-ring PAHs were Ace, Fle, Ant;
109
4-ring PAHs were Flu, Pyr, BaA, and Chr; 5-ring PAHs were BeP, BbF, BkF, BaP; 6-ring PAHs
110
were BghiPe and IDP. Nap (in the seawater), Phe (in the aerosols) and DBA (in the aerosols and the
111
seawater) could not be quantified.
liquid
chromatography)
and
a
fluorescent
detector.
An
Interstil ODS-P
112 113
2.1.2 Extraction of PAHs (Seawater)
114
Fourteen (15) PAHs were quantified in the all (26) surface water samples: 3-ring PAHs were
115
Ace, Fle, Ant and Phe; 4-ring PAHs were Flu, Pyr, BaA, and Chr; 5-ring PAHs were BeP, BbF,
116
BkF, BaP, and DBA; 6-ring PAHs were BgPe and IDP. Measuring of PAH concentrations was
117
performed on the HPLC system (L series, Hitachi High Technologies, Japan). Extraction of PAHs
118
for marine samples proceeded in the same way as with aerosol samples, except that dichloromethane
119
(50 mL) was used instead of a solvent mixture of benzene/ethanol. (Hayakawa et al., 2016).
120 121
2.3 Statistical analysis
122
The atmosphere is both the accumulator and the channel of transfer of substances coming
123
from different sources. The release of matter into the atmosphere can occur from natural and
124
anthropogenic sources. Biomass burning is both a natural and anthropogenic source of atmospheric
125
aerosols. As an anthropogenic source, it includes burning wood, burning grass residues after harvest.
126
Biomass burning is an important source of atmospheric gases and PM throughout the world. From
127
80% to 90% of the particles formed from burning forests have a diameter of less than 1 µm (Alonso-
128
Blanco et al., 2012), which contributes to the fact that aerosols from burning biomass can be
129
transported thousands of kilometers from the source (Alves et al., 2011). PAHs with five and six
130
rings are known to have been introduced into the marine environment mainly by dry and wet
131
deposition (Chen et al., 2016). Backward trajectories analysis was used to test a hypothesis that
132
PAHs in the samples come mostly from wild biomass burning (forest and grass fires) and not from
133
sources associated with human population centers (coal and petroleum combustion). The analysis
134
included comparing HYSPLIT backward trajectories with data from MODIS Active Fires product,
135
data on population density, and data about locations of biomass burning power plants.
136
2.3.1 Backward trajectories
137
The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT, version 4.9) model
138
(Stein et al., 2015) was used to analyze directions of atmospheric transport of PAHs to the sampling
139
sites. HYSPLIT backward trajectories were built using gridded meteorological data downloaded
140
from NOAA's Air Resources Laboratory servers. Specifically, this research used a 0.5° Global Data
141
Assimilation System (GDAS) model provided by the National Weather Service's National Center
142
for Environmental Prediction (NCEP).
143
For the atmospheric samples, this research used backward trajectories with 1-hour interval
144
using GPS data on the location of the vessel as endpoint parameters, 625 trajectories in total.
145
In this research, the atmospheric particulate matter deposition at the sampling sites is considered as
146
the main contributing factor to PAH water concentrations. Horizontal or vertical mixing of the
147
surface water was not considered significant in the short term. With these assumptions in mind,
148
backward air trajectories for each water sample were calculated for five days before the sampling
149
time. A total of 3120 backward trajectories for all seawater samples locations were calculated.
150
The duration of modeled backward trajectories was five days (120 hours) because Draxler
151
and Hess noted (Draxler and Hess, 1997) that longer trajectories typically have a significant radial
152
error. The altitude parameter of all endpoints was chosen to be 50 m above sea level.
153
In order to calculate active fire concentration for a trajectory, it is presented as a collection of line
154
segments on a geographical grid. These segments are determined from the trajectory points given by
155
HYSPLIT model using a variation of Bresenham's line algorithm. The algorithm counted the
156
number of fires in 0.50 area along each line segment of a trajectory. The same algorithm is used to
157
calculate power plant concentration and average population density.
158
2.3.2 Active Fire Data Sources
159
Two NASA fire products were used to calculate the active fire concentration parameter, the
160
Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging
161
Spectroradiometer (MODIS). Their resolutions are 375 m and 1 km respectively. Fire detection in
162
these products is performed by contextual thresholding algorithms using radiometric signals from
163
4µm and 11 µm channels.
164
NASA distributes both products as simple text files, with every line containing latitude,
165
longitude, and date data for pixels classified as thermal anomalies by the algorithms. The products
166
present fire pixels with varying confidence levels. MODIS gives confidence in percentages; VIIRS
167
classifies confidence as either low, normal, and high. The algorithm in this study considered
168
MODIS fire with a confidence level above 55% and VIIRS pixels with normal and high confidence.
169 170
2.3.3 Population Density
171
The data on population density comes from the Gridded Population of the World, Version 4
172
(CIESIN 2018). Its data on the number of people per square kilometer is based on counts from
173
national censuses and population registers. The data in various formats and resolutions are free for
174
download.
175
The files for this data set are available as global rasters in ASCII (text) format. The ASCII
176
data used in this research had 15 arc-minute resolution (0.25 degree). The data were stored in
177
WGS84, geographic coordinate system (latitude/longitude).
178 179
2.3.4 Power Plant
180
Coal-fired power plants are a significant source of atmospheric PAHs (Wang et al., 2015).
181
Data on the location of coal and gas power plant comes from The Global Power Plant Database,
182
which is a comprehensive, open source database of power plants around the world. Each power
183
plant is geolocated, and entries contain information on plant capacity and fuel type. (Global Energy
184
Observatory) built and put into operation by 2012.
185 186
According to U.S. Energy Information Administration data, China peaked in manufacturing of bituminous coal in 2012. (https://www.eia.gov/beta/international/).
187
3. Results and discussion
188
3.1 PAH in the aerosols
189
The concentration of Σ(14) PAHs in marine aerosols ranged from 17.09 pg/m3 in a sample
190
#3 taken on June 19-22, 2012 in the northern part of the Sea of Japan, the La Perouse Strait to
191
142.47 pg/m3 in sample #5 taken on June 25 - 28, 2012 near middle Kuril Islands. Fig. 1 shows the
192
rout of the ship together with concentrations of five-ring and six-ring PAHs in aerosol samples. The
193
R=BeP/(BeP+BaP) is usually used (Fang et al., 1999; Li et al., 2006) for ascertaining the aging
194
process. This ratio allows in outline determination of the source location. The 120-hour backward
195
trajectories constructed for sample #5 showed that air masses came from the north-eastern part of
196
Russia, passed over the Sea of Okhotsk. The R=BeP/(BeP+BaP) ratios for all atmospheric samples
197
ranged from 0.54 to 0.81, with an average value of 0.71. Studies show that for aerosol samples
198
collected near their source, this coefficient (R) is between 0.45 and 0.57. If the source is located at a
199
considerable distance, the PAHs are subjected to photochemical destruction (photolysis) during
200
long-range aerosol transport, and the concentrations of benz(a)pyrene decrease more rapidly than
201
benz(e)pyrene so that R in the samples varies from 0.6 to 0.83. High values of R in this study
202
indicate predomination of remote sources of PAHs vs. local ones (e.g., ship exhaust). The only
203
sample with low R=0.54 is sample #3 (Fig. 2) taken on June 19-22, 2012 in the La Perouse Strait,
204
that has the lowest PAHs concentration.
205 206
Fig. 1 Map of aerosol sampling sites with concentrations of five- and six-ring PAHs. Blue dots show
207
the ship's route. Bars indicate the places where the filters were changed.
208
209 9
0.9 BaP
BeP/(BeP+BaP)
8
0.8
7
0.7
6
0.6
5
0.5
4
0.4
3
0.3
2
0.2
1
0.1
0
BeP/(BeP+BaP)
5-ring PAH, pg/L
BeP
0 1
2
3
4
5
6
7
8
9
Sample number
210 211
Fig. 2 The ratios R=BeP/(BeP+BaP) for air samples.
212
The ratios BaA/(BaA + Chr) were used to determine the source types, petrogenic, pyrogenic,
213
or mixed sources (Yunker et al., 2002). Researches usually use this ratio for approximate
214
identification of sources of PAH. It is burning oil products or burning wood, grass, and coal. Values
215
below 0.40 indicate petrogenic sources, values from 0.40 to 0.50 indicate oil burning, and values
216
above 0.50 indicate PAHs from burning wood, grass, and coal. Fig. 3 shows these two coefficients
217
in two profiles. The ratio of Flu/(Flu + Pyr) in all samples of marine aerosols was above 0.5, which
218
indicates that the sources of PAHs were combustion processes (Grass, wood, coal combustion). The
219
BaA/(BaA + Chr) ratios also indicate combustion processes, with mixed sources for two samples:
220
sample #3 in the La Perouse Strait and sample #4 from southern Sakhalin Island to the Bussol Strait
221
near Urup Island. This can be explained by proximity to the Sakhalin-2 production complex, which
222
includes a liquefied natural gas plant, a crude oil export terminal and the Prigorodnoye port. Another
223
expected factor for this site is gas flaring on the eastern part of Sakhalin and the shelf. PAH
224
concentrations in atmospheric aerosols were in good agreement with PAH data in ocean aerosols
225
from other studies (Ma, Yuxin, et al., 2013).
226 227
The PAH concentrations for each aerosol and seawater sample is presented in Tab.1 and Tab.2 at the end of this paper.
228 229
Fig. 3 Diagnostic ratios calculated for air samples and sea samples. The two samples of atmospheric
230
aerosols are encircled together with the corresponding (in time and place of sampling) samples of
231
suspended matter in sea water, which have high concentrations of PAHs.
232 233
3.2 Seawater samples (Suspended particulate matter).
234
The sum of concentrations of eleven PAHs (four, five and six-ring) in the suspended matter
235
of seawater ranged between 1117.16 pg/L for June 30, 2012 sample to 5543.8 pg/L for June 17,
236
2012 sample. The highest concentrations of PAHs were observed in areas close to the city of
237
Vladivostok Fig. 4. The sum of concentrations of two-ring and three-ring PAHs ranged from 893.23
238
pg/L to 15669.19 pg/L. It should be noted that these PAHs are contained to a greater extent in the
239
soluble fraction, and two PAHs (Nap and Phe) were not found in several samples of suspended
240
matter (Tab. 2).
241 242
Fig. 4 Map of seawater sampling sites with concentrations of five- and six-ring PAHs The BeP/(BeP + BaP) ratios in the suspended matter of seawater ranged from 0.44 to 0.99,
243 244
with an average value of 0.72 (
245
Fig. 5). For most samples, the ratio was above 0.6, which indicates the remoteness of the PAHs
246
sources (Fang et al., 1999; Li et al., 2006). For samples #2, #3, #4, #9, and #13, the BeP/(BeP +
247
BaP)
ratio
was
below
0.6,
indicating
presence
of
local
PAH
sources.
248 800
1.2 BeP
BaP
BeP/(BeP+BaP)
700 1
0.8 500
400
0.6
BeP/(BeP+BaP)
5-ring PAH, pg/L
600
300 0.4 200 0.2 100
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
249
Sample number
250 251
Fig. 5 Ratios R=BeP/(BeP+BaP) for seawater samples
252
The ratios Flu/(Flu + Pyr) and BaA/(BaA + Chr) in most samples of the suspended matter in
253
seawater were above 0.5 and 0.35, respectively, indicating that the PAH sources were combustion
254
processes. In samples #10 and #11 (Fig. 3), the ratio of BaA/(BaA + Chr) was below 0.2, which
255
indicates petrogenic sources. Petrogenic PAHs are associated with spills of crude and processed oil
256
(Soclo et al., 2000). These samples were taken in the area from the Strait of La Perouse to the
257
middle Kurile Islands. In this area, as already mentioned above, there is a plant for the production of
258
liquefied natural gas (southern Sakhalin) to the north of the sampling point. The Karakumneft tanker
259
accident that occurred in early 2012 and resulted in the spill of 300 cubic meters of oil, also speaks
260
of the petrogenic origin of PAH's in the area.
261 262
The Flu/(Flu + Pyr) ratios for sample #12 (Fig. 3) were above 0.57, but below 0.35 for BaA/(BaA + Chr), which indicates different sources(mixed sources).
263 264 265 266
It must be noted that Flu and Pyr exhibit different rates of photodegradation, as do BaA and Chr, and that can considerably affect the Flu/(Flu + Pyr) and BaA/(BaA + Chr) ratios. According to Flu/(Flu+Pyr) ratios, was shown that the primary sources of PAH in surface seawater and atmospheric aerosols were pyrogenic sources (burning of wood, grass, and coal).
267
Backward trajectories analysis with active fires satellite data shows that the primary source
268
of PAHs in the seawater samples was biomass burning. Correlation coefficients between PAHs
269
concentrations and the active fire parameters for MODIS and VIIRS were similar, so, for simplicity,
270
only MODIS active fire data is discussed.
271
The correlation between the concentrations of individual PAHs, the sum of PAHs, the sum
272
of 5-ring PAHs in the suspended matter of seawater and the concentration of active fires recorded
273
along 120 hour backward trajectories to the sampling site showed that there is a positive relationship
274
with the total PAH was 0.62 (p=0.001). The sum of 5-ring PAHs was 0.77 (p=0.0001). The sum of
275
6-ring PAHs was 0.71 (p=0.0001); the sum of 4-ring PAHs was 0.46 (p=0.018). The active fire
276
parameter also significantly correlated with each PAHs, most strongly with BaP (0.87, p=0.001). On
277
the other hand, the population density parameter showed a significant correlation only with BaA
278
0.61 (p=0.001). Correlation between the power plant concentration and individual PAHs and their
279
sums was also below the significance threshold except for BaA (0.5, p=0.008).
280
For marine aerosols, we used the Spearman and Kendall tau correlations (this type of
281
correlation was chosen due to the small number of samples) between the concentration of PAHs and
282
the sum of active fires recorded along 120-hour return paths to the sampling site. The results showed
283
a significant positive correlation (0.93, p < 0.05) between the sum of 5-ring PAHs and active fire
284
concentration. Significant positive correlation between total PAHs and active fire concentration was
285
0.81, (p < 0.05). For sum of 4-ring PAHs was - (0.91, p < 0.05). A similar correlation (0.74, p <
286
0.05) was with Ace, Flu (0.84, p < 0.05), Pyr (0.84, p < 0.05), Chr (0.76, p < 0.05), BeP (0.86, p <
287
0.05) BbF (0.86, p < 0.05) and BkF (0.89, p < 0.05). At the same time, no correlation was found
288
between any PAH concentrations or individual PAHs and the population density and coal-fired
289
power plants.
290
It is known that population density impacts wildfire frequency. Studies show that an
291
increase in the population density reduces the frequency of fires, except for sparsely populated
292
areas, where the effect is only slightly positive (Knorr et al., 2014). Another study showed that
293
specifically for the region examined in this paper relationship between fires and population is
294
positive for some areas (north-eastern Siberia, central China) and negative for others (Northeastern
295
China) (Bistinas et al., 2013). Average population density and average fire concentration calculated
296
for backward trajectories were not significantly correlated.
297
Fig. 6 shows five-day backward trajectories of air masses to the seawater sampling sites. The
298
backward trajectories for samples 2.8 and 9 have few intersections with the sites of active fires on
299
the continent, which corresponds to the minimum values of the amount of PAHs in samples of
300
suspended solids in sea water The backward trajectories for samples 3 through 7 have more
301
intersections with the sites of active fires, which corresponds to the maximum values of the amount
302
of PAHs in samples of suspended solids in sea water. The values are shown in Fig. 8.
303
304
305
306 307
Fig. 6 Backward trajectories for seawater samples from #2 to #9. Orange dots show active fires for
308
corresponding dates.
309
Fig. 7 shows five-day backward trajectories of air masses to the segments of the ship’s route
310
on which the aerosol samples were taken. The high number of intersections with active fires for
311
sample 5 may explain high PAHs concentration for that sample. While low number of active fires
312
for sample 3 corresponds to low concentration of PAHs in that sample.
313
314 315 316
Fig. 7 Backward trajectories for aerosol samples #3 (left) and #5 (right). Orange dots show active fires for corresponding dates.
0.016
2500 Σ(BeP+BbF+BkF+BaP) MODIS Active Fires, confidence 45-100% MODIS Active Fires, confidence 55-100%
0.014
2000
0.01
1500
0.008 1000
0.006
Summ 5-ring PAH, Pg/L
Active fires concentration
0.012
0.004 500 0.002
0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Sample number
317 318
Fig. 8 The total of the 5-ring PAHs in the suspended matter of seawater and the active fire
319
concentration (Active fires per 1000 km2) along the backward trajectories of the movement of air
320
masses (data from MODIS Active Fires product).
321 322
3.3 Multiple regression analysis
323
Multiple regression analysis was performed using SPSS Statistics 12 (x64). The measured
324
PAH concentrations of marine and air samples include the natural and anthropogenic factors were
325
used to build a multiple regression model. Variables considered for inclusion in the model were the
326
ones that had some of the highest pairwise correlations with the PAH concentrations. Those were
327
active fires concentration along 120-hour backward trajectories and population density.
328
The final model with the best fit to the data set included one variable: the active fires along
329
120-hour backward trajectories. The correlation for the regression was 0.77 with adjusted =0.58,
330
meaning that the model as a whole explains 58% of the SUM 5-ring PAHs variation. The
331
significance of the calculated correlation was statistically evaluated using t-test and F-test. The
332
regression was found significant with F=35.3, p < 0.0001. A separate multiple regression analysis
333
was conducted for BaP. The correlation for the regression was 0.87 with adjusted =0.75, F=74.1, p
334
< 0.0001. The model as a whole explains 75% of the BaP variation in the surface water.
335 336 337
Conclusions
338
PAH concentrations in the Sea of Japan were higher than in the surface waters of the north-
339
eastern Pacific. This is due to the proximity of the continental sources of PAHs to the Sea of Japan.
340
In turn, in the north-eastern Pacific Ocean, intensive processes of PAH mixing in ocean water
341
reduce their concentration. The results indicate that the primary source of PAH, according to PAH
342
molecular ratios Flu/(Flu + Pyr), in surface water and marine aerosols in the Sea of Japan and the
343
north-eastern Pacific in June-July 2012 was pyrogenic (burning of grass, wood, and coal). The
344
wildfires explained more than 75% of BaP variation in seawater in June-July 2012. The strong
345
correlation between active fires and PAHs concentrations in the suspended matter can be explained
346
by the fact that the surface seawater accumulates particulate matter. A method was proposed for
347
estimating the contribution of natural and anthropogenic sources to PAH concentration using
348
HYSPLIT backward trajectories and satellite data.
349 350
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461
Tab. 1 PAH concentrations (pg/m3) in aerosol samples
Two-ring Sampling period
462
Three-ring
Four-ring
Five-ring
Six-ring
Nap
Ace
Fle
Ant
Flu
Pyr
BaA
Chr
BeP
BbF
BkF
BaP
BgPe
IDP
Aerosol µg/m3
06/13/2012
06/16/2012
16.26
0.75
1.90
n/d
8.62
9.12
4.28
6.15
2.88
6.93
2.56
1.67
n/d
n/d
26.41
06/16/2012
06/19/2012
15.61
0.56
3.44
0.25
7.28
7.58
2.11
4.08
3.42
5.43
1.89
1.96
4.93
6.28
26.12
06/19/2012
06/22/2012
4.81
0.25
0.56
0.07
2.13
2.31
0.69
1.10
0.61
1.46
0.48
0.53
0.99
1.11
30.35
06/22/2012
06/25/2012
15.02
0.56
3.87
n/d
7.49
8.12
2.61
3.93
2.34
4.80
1.22
0.72
2.01
2.45
11.84
06/25/2012
06/28/2012
20.67
0.92
4.39
0.90
22.28
23.89
7.93
12.85
7.84
17.81
5.05
3.41
6.60
7.93
29.53
06/28/2012
07/01/2012
18.10
0.98
1.11
0.62
10.90
10.91
2.20
3.02
5.05
6.51
2.20
2.01
14.05
12.25
25.46
07/01/2012
07/04/2012
11.17
0.74
n/d
0.26
9.32
10.53
1.94
3.30
3.34
7.54
1.88
0.85
4.18
4.05
22.02
07/04/2012
07/07/2012
14.01
0.83
2.67
0.31
12.73
13.98
1.71
4.30
5.52
8.65
2.24
1.25
4.57
5.10
18.98
07/07/2012
07/09/2012
14.01
0.83
2.67
0.31
12.73
13.98
1.71
4.30
5.52
8.65
2.24
1.25
4.57
5.10
25.74
463
Tab. 2 PAH concentrations in seawater samples (pg/L)
№
Date
Two-ring
Three-ring
NaP
Ace
Fle
Phe
Four-ring Ant
Flu
Five-ring
Six-ring
Pyr
BaA
Chr
BeP
BbF
BkF
BaP
DBA
BgPe
IDP
1
6/13/2012
n/d
36.80
360.62
22676.28
197.40
2780.01
2718.38
113.53
87.36
188.09
618.12
37.54
75.59
104.88
230.95
139.66
2
6/14/2012
n/d
9.83
174.91
11733.29
111.09
1544.40
1495.44
59.92
31.78
102.07
469.79
47.62
76.08
n/d
198.00
112.54
3
6/15/2012
n/d
4.79
68.65
2693.33
149.97
1633.33
1313.67
49.26
12.67
58.27
194.16
12.73
73.64
n/d
55.53
78.01
4
6/16/2012
n/d
0.26
32.89
n/d
99.02
1676.34
1408.14
76.30
38.51
76.31
239.85
4.93
58.49
n/d
102.26
87.22
5
6/17/2012
n/d
2.99
264.97
12779.57
134.16
1425.73
1241.99
133.81
193.64
744.99
937.85
102.51
237.68
25.07
349.93
150.60
6
6/17/2012
n/d
0.33
161.64
5601.61
59.06
711.10
625.47
50.11
73.48
481.18
992.02
34.26
112.01
93.30
333.72
95.60
7
6/18/2012
250.44
17.13
102.20
n/d
105.84
1130.83
1068.48
91.26
115.62
322.35
352.97
39.57
70.44
43.83
125.11
38.37
8
6/19/2012
126.36
4.27
33.43
n/d
64.92
496.88
470.01
40.06
34.60
40.20
92.79
8.08
10.31
3.75
16.07
14.67
9
6/20/2012
41.18
1.97
24.22
n/d
199.30
728.05
597.75
29.79
14.99
22.84
69.05
10.34
19.35
5.00
17.46
16.13
10
6/21/2012
13.91
2.59
6.16
n/d
131.24
771.54
527.17
4.11
52.16
16.97
70.17
3.80
9.52
3.67
3.95
16.12
11
6/22/2012
24.37
2.43
9.85
n/d
137.28
613.99
421.85
9.98
48.51
21.00
46.50
3.64
9.71
n/d
20.37
14.44
12
6/23/2012
15.34
3.14
22.21
15269.13
359.37
742.22
528.39
16.35
45.41
45.70
64.70
5.93
15.37
n/d
10.53
11.69
13
6/24/2012
15.01
3.35
16.15
n/d
114.97
748.83
493.58
10.96
2.88
17.29
48.76
2.85
17.34
n/d
8.77
20.47
14
6/25/2012
12.99
1.64
7.19
n/d
95.13
1005.30
652.80
16.17
0.69
18.63
54.44
2.44
11.92
n/d
14.39
18.54
15
6/26/2012
25.12
0.76
40.77
7459.03
76.53
540.23
449.00
18.92
9.58
45.32
65.41
10.59
16.25
2.27
30.51
20.89
16
6/27/2012
16.07
2.35
25.65
13621.06
196.69
572.18
646.14
21.97
80.07
34.12
49.28
6.17
8.39
3.77
15.97
10.84
17
6/27/2012
26.91
2.05
32.18
10782.66
139.77
612.45
629.72
36.92
13.08
26.46
37.82
3.96
5.36
3.71
6.00
7.02
18
6/28/2012
13.67
3.01
31.74
14418.74
233.98
606.13
632.76
21.95
75.77
25.66
74.50
7.90
16.83
2.45
31.80
20.38
19
6/29/2012
27.24
1.64
23.36
8554.04
172.22
529.95
454.08
11.09
3.77
37.37
65.90
3.21
6.86
3.41
7.78
5.38
20
6/30/2012
19.72
5.53
21.71
715.76
130.51
471.17
440.71
11.05
1.29
58.23
63.75
4.43
11.37
5.89
30.02
19.25
21
7/2/2012
25.66
1.34
18.43
1082.37
185.52
658.83
496.17
10.23
0.60
39.86
67.00
4.60
12.38
5.17
23.27
14.49
22
7/3/2012
58.06
0.50
18.35
8860.12
223.37
604.28
476.14
9.40
3.55
38.08
45.23
3.89
9.69
3.93
17.43
12.54
23
7/4/2012
24.73
0.89
18.05
3193.68
165.79
750.13
586.78
9.06
1.40
19.44
33.92
1.53
3.67
2.96
5.68
8.49
24
7/5/2012
42.83
3.44
11.58
n/d
89.06
835.41
581.23
3.59
0.39
16.67
23.81
0.62
2.75
n/d
2.16
3.91
25
7/6/2012
91.49
2.72
3.50
n/d
52.18
683.02
590.64
10.12
4.08
231.15
139.00
2.22
3.52
n/d
38.52
3.28
26
7/8/2012
60.70
0.35
50.88
7978.87
78.55
937.17
806.01
98.64
63.74
24.12
178.61
7.78
8.07
0.89
15.67
12.94
Long-range atmospheric transport plays important role in transfer PAH to Ocean. Forest fires increase 5-ring PAH concentrations in the surface seawater. A new approach is proposed for studying PAH variations in surface seawater.
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:
Andrey Neroda Anna Goncharova Vasiliy Mishukov