Mass size distribution study of aerosol particles
using samples from Arctic Ocean expedition 2001
(AOE01)
Arash Gharibia,*, Keith Biggb, Erik Swietlickia, Caroline Leckb
a
Division of Nuclear Physics, Lund University, P.O. Box 118, SE-221 00 Lund, Sweden
b
Meteorological Institute of Stockholm University (S-106 91 Stockholm)
Abstract
During Arctic Ocean Expedition 2001 (AOE01) total, fine and coarse mass concentrations of
aerosol particles has been measured in Pack Ice (PI) region. The aerodynamic diameter
equivalent (EAD < 10 m) has been used for total mass concentration. The diameter of
aerosol particles set to 2 m < EAD < 10 m for coarse fraction and EAD < 2 m for fine
fraction. The aerosol particles were collected using stacked filters (SFU) and cascade
impactors e.g. a Low Pressure Impactor (LPI) and a Small Deposit area Impactor (SDI). The
results from parallel samples, taken with the different devices analyzed by PIXE technique,
were compared. The results have even been compared with three pervious Arctic expeditions
namely AOE-96 and IAOE-91. Total mass concentration of Cl and S as a function of marine
transport time (Mtr) presented. Log-normal fitting of size distribution is applied on the PIXE
results corresponding pack ice region data. Log-normal size distribution parameters such as
geometric mean diameter (Dg) and concentration for each, coarse, accumulation and Aitken
mode calculated and presented in an extensive table for trace elements.
1. Introduction
The Arctic Ocean is climatologically sensitive and plays very important roll for the regional
global radiation balance and earth climate. In the Arctic, these are major factors for the global
radiation balance, Pack Ice (pack ice influence temperature and humidity of the air), clouds
and fogs. Atmospheric aerosol particles affect the climate both direct and indirect. The direct
effect refers to aerosol particles scatter back sunlight (short-wave) to space, thus affecting the
global radiation balance. This will increase the Earth’s albedo, and results in a net cooling
influence on the climate. This will primarily happen in clear sky weather condition.
The direct effect will include the impacts of aerosol particles absorption in clear (and cloudy)
sky on the temperature and humidity profiles. It may feedback on cloud formation and cloud
cover. Furthermore, indirect way is related to an increase in the number and decrease in size
of cloud droplets (for constant liquid water content), due to the aerosol particles acting as
Cloud Condensation Nuclei (CCN). This will increase the optical depth of the cloud and
cloud albedo. Finally, the indirect effect is related to an increase in the cloud liquid water
content. This can be done by increase in cloud droplets size which will reduce precipitation
efficiency of the clouds. This will affect the cloud lifetime and cloud height. The clouds and
fogs reflectivity can be changed through sulphur aerosol particles when they act as a cloud
condensation nuclei (CCN). The CCN particles do not necessarily need to be sulphur they
may be any soluble particle of sufficient size. The sulphur can come from the Ocean,
dimethylsulfide (DMS) or from fossil combustion (sulphur dioxide) and biomass burning.
*
Corresponding author: arash.gharibi@nuclear.lu.se
2. Experimental set-up
The impactor type used in the expedition, were four low pressure impactors LPIA, LPIB,
SDIA and SDIB, with high size resolution. The LPI impactor consists of 13 impaction stages
and the experimental cut-points d50-values 0.030-10.33 m. SDI is a 12 stage multi-jet low
pressure cascade impactor which can classify the aerosol particles into 12 size fraction (d50values 0.045-8.39 m) according to their aerodynamic diameter. Both LPI and SDI sample
the aerosol particles through inertial impaction onto filters.
2.1 The sampling system
The data discussed in the present paper were all obtained from aerosol collectors and
instruments that were connected to a sampling manifold that was quipped with an equivalent
aerodynamic diameter (EAD) of 10 m cut-off. The SFU sampler consist of two sequential
47-mm diameter polycarbonate filter holder, which contained a coarse mode of 8-mm pore
size Nuclepore polycarbonate and a fine mode of 0,4 mm pore size Nuclepore polycarbonate
filter, respectively. The coarse filter had a 50% collection efficiency at 2 m EAD, and thus
collected particles in the size range of 2 to 10 m EAD. The fine filter collected all particles
less than 2 m EAD. The SFU operated at a flow rate of 32 (average) Lmin-1. Twenty two
samples were collected with this device. The SDI and LPI were operated at a flow rate of 10
L min-1. The collection foils in SDI consisted of a very thin AP1 film whereas LPIA7 to
LPIA14 consisted of a 1.5 m thick KIMFOL film and LPIA1 to LPIA6 consisted of a 1.5
m thick Nuclepore polycarbonate film. The collection time per SDI sample was 20- 60 hours
while for LPI was 10-75 hours. A total of 9 and 14 samples were collected for SDI and LPI
respectively.
Sampler
Inlet
Stages
Flow (l/min)
Backing
LPIA(1-6)
LPIA(7-14)
SDI
SFUA
10 m
"
"
"
13
"
12
2
10
"
"
32
Nuclepore
Kimfol
AP1
Nuclepore
Table 1.Different sampler used in AEO-01and their properties e.g. cut off
diameter, stages and so on.
2.2 The PIXE analyses
A proton beam of a 2.55 MeV was used in PIXE analyses (Macro beam-line). The beam size
was 0.63 mm2 and 0.92 mm2 for SDI, LPI and SFU samples, respectively. The PIXE spectra
were accumulated with a HPGe X-ray detector with an absorber of 1mm hole (myler). The
spectra were collected for a proton beam preset charge of 25 C to 50 C. Finally, the
resulting X-ray spectra were evaluated with GUPIX a fitting program which converts peak
areas to elemental concentrations. Details of the Macro beam line set up and PIXE spectrum
analysis and quantification procedures can be found in [5].
3 Results
The AOE01 aerosol study program covered the following Arctic region, MIZ, OW, PI 3 Ice
Drift and PI4. The range to separate fine and coarse fraction of aerosol particles set to be 0<
DEAD <2 m and 2< DEAD <10 m respectively. In table 2a and 2b describes effective
sampling time, wind velocity, marine transport time and several other important parameters
from the AOE01 expedition.
To validate the quality of our data a comparison of the results from various samplers were an
obligation. For this reason, the total mass concentration of elements has been compared with
each other for all overlapped samplers. Even though there is a difference in the results
obtained from various impactors (SDI, LPI and SFU) still the data set is most of the time
gives an acceptable result. There are two points clearly above and three points below the other
points. This is difficult to explain but it can be due to over sampling of SDIB (two points
above) and sampling artifacts for three points below [3]. See even figure 2 below. Thus, the
best candidates were data sets from SDIA7-9 and SDIB7-9 samples because all conditions
were the same. As an example, the size distribution for S plotted in figure 3 to show how well
these two data set matches.
Total
1000
SFU
LPIA
SDIB
M(ng/m 3)
SDIA
100
Cl
10
1
0
2
4
6
8
10
12
14
Figure 1.Atmospheric Cl concentration for overlapped sampler obtained from various
aerosol collection devices. The lines are to guide the eyes.
Total
1000
LPIA
SDIA
SDIB
M (ng/m 3)
SFU
Cl
100
10
1
0
2
4
6
8
10
12
14
W (m/s)
Figure 2.Atmospheric Cl concentration from various aerosol particles collection
devices as function of median wind speed.
400
SDIA7
350
SDIB7
3
dM/dlogDp (ng/m )
S
300
250
200
150
100
50
0
0,01
0,1
1
10
100
d(µm)
Figure 3.Size distribution of the Arctic aerosol over pack ice has been plotted to show
validity of the data. As expected S show a large peak for fine and a small peak for
coarse mode.
Sample
Station
LPIA
MIZ
"
"
"
"
OW
PI 3
DRIFT
"
"
"
"
"
"
"
"
"
"
"
"
"
"
"
"
PI 4
Sample no.
Mtr Median (h)
LPIA SDIA SDIB SFUA
1
2
3
1
4
2
5
"
6
3
"
4
7
5
8
2
6
"
"
7
9
3
8
"
"
9
10
4
10
"
"
11
11
5
12
"
"
13
12
6
14
"
"
15
13
7
7
16
"
"
"
17
14
8
8
18
"
"
"
19
"
9
9
20
"
"
"
21
22
LPIA
0
0
>120
>120
>120
62,8
"
72
84
"
44
"
72
"
55,5
"
>120
"
47,6
"
36
"
"
"
Sampling period
LPIA
SDIA
SDIB
(Julian day)
(Julian day)
(Julian day)
186,53
187
187,56 187,9
190,25 190,8
192,38 192,9
192,93 193,4
196,58 197,6
"
"
207,96
209
214,42 215,8
214,42 215,8
"
"
"
"
216,72 218,7
216,8 218,7
"
"
"
"
218,82 220,8
218,84 220,7
"
"
"
"
221,54 223,6
221,54 223,6
"
"
"
"
224,48 227,5
224,48 227,5
"
"
"
"
227,58 229,5 227,63 229,5 227,63 229,5
"
"
"
"
"
"
229,57 233,4 229,63 231,5 229,63 231,5
"
"
"
"
"
"
"
"
231,63 233,4 231,63 233,4
"
"
"
"
"
"
Eff. sam. time (min)
SDIA SDIB SFUA LPIA
676
455
>120 747
>120 724
>120 675
13,8 1440
72
"
72 1436
84
84 1994
96,2
"
"
44 113 2860
"
44
"
48
48 2788
84
"
"
55,5 49,7 2456
70,5
"
"
>120 >120 3610
"
>120
"
47,6 47,6 >120 2780
47,6
"
"
"
36
36 28,6 4512
"
"
40
"
45,3 45,3 94,8
"
34,5
"
"
"
25,8
SDIA SDIB SFUA
1994
"
2755
"
2715
"
2456
"
3610
"
2703 2703
"
"
2262 2262
"
"
2091 2091
"
"
766
1477
"
725
673
1436
1378
588
1420
1366
1359
1367
1013
1365
2264
1265
1338
1370
1030
1325
1124
1018
1200
SFUA
(Julian day)
190,25
192,38
"
196,58
197,12
207,96
214,42
215,44
216,72
217,76
218,82
219,8
221,54
222,64
224,48
226,56
227,58
228,56
229,57
230,59
231,57
232,69
236,76
190,78
193,4
"
197,09
197,58
208,96
215,42
215,85
217,71
218,71
219,76
220,75
222,58
223,59
226,5
227,5
228,51
229,51
230,29
231,51
232,5
233,43
237,59
Table 2.a
% time average of SFUA by
*=LPIA
*=SDIA
*=SDIB
%=SFU / *
%=SFU / *
%=SFU / *
Wind Speed (m/s)
LPIA
min
median
SDIA
max
3
7,2
10,9
min
median
SDIB
max
min
median
SFUA
max
min
median
max
3,1
4,9
6,1
(3-1) 98
1,8
4,6
7,3
1,8
4,6
7,3
(4-2) 49
2,6
5,1
6,9
2,6
5,9
9,1
(5-2) 46
4,4
7,8
9,1
"
"
"
(6-3) 50
8,7
11,3
13,5
8,7
11
13,3
13,5
(6-4) 47
"
"
"
9,5
11,6
(7-5)100
3,1
6,3
9,6
3,1
6,3
9,6
0,7
9,9
15,2
15,2
7,6
12,8
15,2
(8-6) 69
(2-6) 69
(8-7) 29
(2-7) 29
"
"
"
"
"
"
0,7
3,1
7,9
(9-8) 51
(3-8) 52
2,7
7,1
10,5
2,7
7,1
10,5
5,1
8,1
10,5
0,7
9,9
(9-9) 48
(3-9) 50
"
"
"
"
"
"
2,7
5,8
9
(10-10) 49
(4-10) 50
1,2
7,3
13
1,7
7,5
13
5
8,7
13
(10-11) 49
(4-11) 50
"
"
"
"
"
"
1,2
4,4
10,8
(11-12) 41
(5-12) 41
0,3
5,2
9,6
0,3
5,2
9,6
0,3
4
8,5
(11-13) 56
(5-13) 55
"
"
"
"
"
"
2,3
6,5
9,6
(12-14) 63
(6-14) 63
1,1
3,3
9,1
1,1
3,3
9,1
1,1
3,4
9,1
(12-15) 35
(6-15) 35
"
"
"
"
"
"
1,4
3,1
5,6
4,7
6,6
11,9
6,7
11,9
4,7
8,05
11,9
4,1
5,9
10,1
5,2
9,4
0,4
4,8
6,1
1,7
6,4
9,4
(13-16) 48
(7-16) 50
(7-16) 50
(13-17) 49
(7-17) 51
(7-17) 51
"
"
"
"
(14-18) 23
(8-18) 45
(8-18) 45
0,2
5
10,2
0,2
(14-19) 30
(8-19) 58
(8-19) 58
"
"
"
"
(14-20) 25
(9-20) 54
(9-20) 54
"
"
"
0,9
4,8
10,2
0,9
4,8
10,2
0,9
3,3
5,8
(14-21) 23
(9-21) 49
(9-21) 49
"
"
"
"
"
"
"
"
"
5,4
7,5
10,2
0,5
3
6,3
5
6,7
11,9
5
5,2
9,4
0,2
"
"
Table 2.b.The number inside brackets is a sum of % time average of two or more impactor.
For example (8-6) 69 and (8-7) 29 means the running time of SFUA6 and SFUA7 together
cover 98 % of the running time of the LPIA8.
3.1 Log-normal fitting (results)
Log-normal fitting of size distributions are a major tool for structural analyses because they
indicate the appearance of relative maxima while reducing the number of distribution
parameters (Jost Heinyzenberg et al).
The results of best-fit log-normal distribution as obtained by minimising 2 are shown in table
3. This is done on all SDI data for Cl and S. The plots show the mass concentration (ng/m3),
obtained from the fitting, as function of Dg (Geometric mean diameter) in m. The estimated
mass concentration of the aerosol particles was comparable to that obtained by PIXE analysis.
All SDI impactor show a coarse mode, 1<Dg <3 m, accumulation mode, 0.3<Dg <1 m, and
Aitken mode with 0.1<Dg <0.3 m. Geometric mean diameter (Dg), Geometric standard
deviation (g) and total mass concentration (mj) resulting from the fitting are presented in
table 3.
3.2 Marin Transport Time
The time air mass spent over the pack ice is defined marine as transport time (Mtr). Transport
time from open water is very essential since it influences the amount of sea-salt remaining
consequently contributes strongly to coarse fraction of aerosol particles.
During summer, there is no atmospheric transport of air to the central Arctic Ocean therefore
the anthropogenic pollutants presence are minimal. However, there is some transport of air to
the central Arctic from lower latitudes. Furthermore, the losses of soluble particles are large
as the air progresses towards the North Pole because of the accompanying fogs.
Total
1000
LPIA
SDIA
M (ng/m 3)
SDIB
SFU
S
100
10
1
0
20
40
60
Mtr (h)
80
100
120
140
Total
1000
LPIA
SDIA
M (ng/m 3)
SDIB
SFU
Cl
100
10
1
0
20
40
60
80
100
120
140
Mtr (h)
Figure 4a and 4b.Total mass concentration (ng/m3) of Cl and S for all samplers, SDI, LPI and
SFU, has been plotted as function of Mtr. Normally it shouldn’t be any increase in mass
concentration of Cl after 2-3 days trajectories unless the local wind speed is also increase.
Cl
K
Ca
Ti
Fe
Zn
Br
SDIB03
m(ng/m3)
Dg (m)
sg(m)
SDIB02
223,09 151,06
0,14
0,11
1,12
1,31
Si
S
10,39
0,11
1,37
1,15
0,14
1,14
2,45
0,14
1,14
0,65
0,11
1,32
0,72
0,11
1,21
0,45
0,21
3,49
0,03
0,13
1,20
m(ng/m3)
Dg (m)
sg(m)
118,63 1200,0 19,18
0,27
0,3
0,25
2,34
1,3
1,14
m(ng/m3)
Dg (m)
sg(m)
241,02 114,21 142,78
1,18
0,67
0,85
1,71
1,43
1,30
13,48
1,33
1,59
14,84
1,31
1,57
1,69
0,86
1,17
3,43
1,23
2,60
4,71
0,81
1,10
0,00
0,47
1,02
m(ng/m3)
Dg (m)
sg(m)
28,50
0,95
1,31
300,0
1,4
1,3
m(ng/m3)
Dg (m)
sg(m)
264,40 450,16
4,31
1,82
1,44
1,34
0,43
3,46
5,00
0,00
0,00
0,00
0,56
3,19
1,75
0,12
1,42
1,75
m(ng/m3)
Dg (m)
sg(m)
86,45
2,57
2,25
160,0
3,5
2,6
3
mj tot(ng/m ) 464,12 529,67 603,33
mi tot(ng/m3) 416,41 540,04 625,12
SDIB04
Si
S
Cl
14,62
17,30
2,77
4,15
5,72
0,15
17,95
K
21,75
Ca
2,80
Ti
4,83
Fe
4,02
Zn
0,15
Br
Si
S
40,55
0,10
1,53
6,91
0,18
1,70
2,47
0,14
1,70
1,60
0,13
1,52
1,52
0,13
1,32
0,40
0,17
1,42
0,16
0,14
1,71
0,00
0,18
1,01
m(ng/m3)
Dg (m)
sg(m)
255,34 657,36
0,21
0,28
4,11
1,92
m(ng/m3)
Dg (m)
sg(m)
65,09
0,76
1,55
39,03
1,07
2,46
60,28
1,58
1,50
2,13
1,58
1,50
3,50
1,54
1,83
0,30
1,54
1,83
1,00
1,38
2,11
0,25
1,18
1,73
0,01
2,79
1,23
m(ng/m3)
Dg (m)
sg(m)
29,86
0,80
1,44
m(ng/m3)
Dg (m)
sg(m)
77,05
3,24
2,18
m(ng/m3)
Dg (m)
sg(m)
47,71
3,68
1,77
67,19
4,60
5,10
1,82
1,40
0,41
0,01
74,13
Cl
4,03
K
4,52
Ca
2,04
Ti
1,41
Fe
0,51
Zn
0,02
Br
0,39
0,78
4,85
UDL
m(ng/m3)
Dg (m)
sg(m)
24,82 117,45
0,11
0,30
1,55
1,81
6,76
0,19
5,00
2,47
0,69
3,75
2,38
0,15
3,46
1,64
0,25
1,76
0,41
0,06
5,00
m(ng/m3)
Dg (m)
sg(m)
157,53 41,89
0,90
2,15
5,00
1,80
51,55
2,08
1,72
1,59
2,70
1,48
4,80
2,23
1,58
0,25
1,17
1,11
0,95
1,08
5,00
mj tot(ng/m ) 182,35 159,34
mi tot(ng/m3) 167,47 181,12
SDIB08
Si
S
58,32
4,06
7,17
1,89
1,36
0,39
60,85
Cl
4,26
K
7,88
Ca
1,98
Ti
1,17
Fe
0,39
Zn
3
3
m(ng/m )
Dg (m)
sg(m)
6,20
0,61
5,00
m(ng/m3)
Dg (m)
sg(m)
9,62
0,40
1,52
0,16
0,17
4,80
0,56
1,01
1,88
3,22
1,86
1,63
0,29
0,93
4,94
0,42
2,15
2,76
UDL
1,75
0,78
4,91
0,42
0,17
1,23
m(ng/m3)
Dg (m)
sg(m)
4,66
0,74
5,00
Zn
Br
0,10
0,15
1,75
0,01
0,14
1,24
2,00
2,12
1,80
0,79
0,63
1,10
0,47
0,77
1,41
0,11
0,70
1,20
0,07
1,33
1,33
0,29
1,52
1,15
2,02
5,11
1,62
0,41
1,58
5,00
0,06
4,49
1,14
6,00
1,33
3,17
0,62
0,14
5,58
Ca
1,34
Ti
3,04
Fe
0,53
Zn
0,11
Br
1,43
0,10
1,64
3,82
0,37
1,52
0,34
0,16
1,23
0,27
0,15
2,92
0,04
0,31
1,56
1,71
1,22
5,00
0,40
1,35
1,52
3,82
2,05
0,67
0,04
3,95
Ti
1,63
Fe
0,73
Zn
0,04
Br
UDL
1,55
0,78
4,91
0,55
0,78
4,91
0,02
1,31
1,92
98,50
1,90
1,81
7,47
0,14
2,22
12,07
1,28
2,20
27,54 236,05
1,91
1,64
1,85
1,65
10,61
0,40
1,86
0,16
0,27
4,80
0,66
1,86
1,49
2,82
1,86
1,60
4,66
11,27
4,01
Si
12,08
S
SDIB09
3
m(ng/m )
Dg (m)
sg(m)
5,88
0,69
5,00
m(ng/m3)
Dg (m)
sg(m)
0,74
2,52
5,00
Fe
0,68
0,15
2,64
10,60
1,22
2,41
3
3
###### mj tot(ng/m )
mi tot(ng/m3)
0,02
0,93
4,92
Ti
0,25
0,32
1,14
mj tot(ng/m ) 332,90 684,91 243,52 12,07 12,03
mi tot(ng/m3) 293,94 726,40 237,69 14,87 11,96
SDIB07
Si
S
Cl
K
Ca
m(ng/m3)
Dg (m)
sg(m)
Br
Ca
4,00
0,46
1,35
3
88,66
0,14
1,13
3
K
4,34
2,02
2,57
mj tot(ng/m ) 233,57 1660,0 117,67 4,34
mi tot(ng/m3) 233,11 1321,2 130,38 5,40
SDI05
Si
S
Cl
K
m(ng/m3)
Dg (m)
sg(m)
mj tot(ng/m ) 230,81 79,58
mi tot(ng/m3) 187,12 80,05
SDIB06
Si
S
Cl
0,23
1,27
2,22
0,12
2,15
1,76
2,98
0,23
0,12 ######
1,55
0,55
0,02
2,91
Cl
0,22
K
0,12
Ca
0,01
Ti
1,29
Fe
0,52
Zn
0,02
Br
5,25
0,45
1,50
0,18
0,18
4,80
0,20
1,35
5,00
0,11
0,28
1,41
UDL
1,85
0,78
5,00
0,55
0,78
4,91
0,02
1,31
1,92
0,28
2,31
1,61
3,32
3,46
1,60
0,02
0,08
1,56
2,83
mj tot(ng/m3)
6,20
10,17
3,39
0,29
0,42
######
1,75
1,15
0,02
mj tot(ng/m3)
5,88
5,53
3,50
0,20
0,19 ######
1,85
0,55
mi tot(ng/m3)
5,76
Si
10,87
S
3,69
Cl
0,29
K
0,39
Ca
0,93
Zn
0,01
Br
mi tot(ng/m3)
Ti
1,69
Fe
SDIA08
5,70
Si
5,68
S
3,63
Cl
0,19
K
0,19
Ca
0,01
Ti
1,83
Fe
0,67
Zn
Br
m(ng/m3)
Dg (m)
sg(m)
72,47 224,45
0,11
0,32
1,49
1,79
8,88
0,16
1,49
6,47
0,51
4,64
2,97
0,13
1,32
0,26
0,13
1,32
1,99
0,33
5,00
0,79
0,46
5,00
0,04
0,21
1,72
m(ng/m3)
Dg (m)
sg(m)
2,25
0,14
2,74
9,44
0,39
1,47
0,10
0,13
2,00
0,17
0,59
5,00
0,25
0,96
2,34
UDL
1,88
0,58
5,00
0,65
0,72
5,00
0,02
0,45
5,00
m(ng/m3)
Dg (m)
sg(m)
80,22
0,60
1,87
51,42
1,80
1,66
2,10
1,59
2,36
0,20
1,59
4,86
0,00
2,03
5,00
m(ng/m3)
Dg (m)
sg(m)
0,58
0,86
1,32
1,15
1,24
1,27
2,97
1,95
1,70
m(ng/m3)
Dg (m)
sg(m)
32,94
3,45
1,57
m(ng/m3)
Dg (m)
sg(m)
3,40
2,79
4,67
3,14
0,65
0,02
3,45
0,68
0,02
SDIA07
16,81
1,95
1,89
1,26
4,10
1,16
mj tot(ng/m3) 185,62 241,26
60,30
6,47
5,07
0,46
1,99
0,79
0,04
mj tot(ng/m3)
6,23
10,60
3,07
0,17
0,25
mi tot(ng/m3) 184,95 252,68
SDIA09
Si
S
61,25
Cl
6,66
K
5,25
Ca
0,39
Ti
1,84
Fe
0,83
Zn
0,04
Br
mi tot(ng/m3)
5,27
10,85
3,07
0,22
0,25
0,44
1,72
2,65
0,41
3,48
3,41
0,08
1,49
5,00
1,98
0,75
5,00
0,76
0,88
5,00
0,04
0,50
5,00
m(ng/m3)
Dg (m)
sg(m)
9,56
0,62
5,00
4,94
0,29
1,47
0,37
0,03
5,00
m(ng/m3)
Dg (m)
sg(m)
1,81
2,99
1,06
1,51
0,48
2,77
4,06
1,84
1,78
mj tot(ng/m3)
11,37
6,44
4,43
0,44
0,98
0,08
5,61
0,76
0,04
mi tot(ng/m3)
9,14
6,42
4,23
0,51
1,19
0,09
4,14
1,34
0,04
0,57
2,81
1,11
0,02
3,63
2,74
1,15
Table 3. Log-normal Size Distribution Parameters for Si, S, Cl, K, Ca, Ti, Fe, Zn, and Br.
1000
SDIB02
Si
S
Cl
K
Ca
Fe
M (ng/m3)
100
10
1
0,1
0,01
0,1
1
10
100
Dg (m)
Figure 6.The best-fitting, log-normal distribution on SDIB02 data for elements Si, S,
Cl, K, Ca, and Fe. Two modes Dg corresponding to 0.1-0.3 m and 0.3-1.0 m
particles is evident.
10000
4
Enrichment Factor VS Cl
SDI
5
6
1000
S
100
10
1
0,01
0,1
1
10
100
d(µm)
Figure 7.Enrichment factor for S versus Cl in sea salt for three SDI impactor samples
taken over pack ice. ( Jag har tagit från EAC abstractet.)
ALL SDI
ALL MODE
Enrichment Factor VS Si
Min
Max
K
10(-1)
10(1)
Ca
10(0)
10(-2)
Ti
10(-2)
10(0)
Mn
10(-1)
10(-1)
Fe
10(-3)
10(0)
Ni
10(-1)
10(1)
Zn
10(0)
10(1)
Table 3.Enrichment factors calculated for K, Ca, Ti, Mn, Fe, Ni and Zn versus Si in soil dusts
for all SDI samples in pack ice region of the Arctic Ocean.
3.3 Comparison with other Arctic data sets
Median atmospheric concentrations (ng/m3 STP) during AOE01; comparison with IAOE96
and IAOE91. The compared elements are Si, S, Cl, K, Ca, Ti, Fe, Zn, and Br. The data were
derived from the SFU data where correspond to pack ice in the Arctic Ocean. The IAOE96
and IAOE91 data used in the figure below were taken from Maenhaut W. et al. [3].
AOE01
AOE96
IAOE91
AOE01
AOE96
IAOE91
Table3.
Coarse
Fine
Coarse
Fine
Coarse
Fine
Coarse
Fine
Coarse
Fine
Coarse
Fine
Si
50,59
77,71
1,9
1,6
17,4
4,6
Ti
0,31
0,75
0,18
0,44
0,2
S
31,95
37,79
17
26
6
26
Fe
1,89
1,26
1,63
0,42
10,03
0,57
Cl
18,12
17,27
46
60
13,6
4
Zn
0,50
0,36
1,03
0,08
0,11
0,07
K
1,92
2,49
2,5
2,3
0,98
1,12
Br
2,85
2,99
0,43
0,144
0,106
Ca
1,54
3,79
2,1
2,4
2,24
0,76
4. Discussion
In open water whitecaps are responsible for bubble formation and breaking waves are
responsible for bursting them. This is the process behind particle production in open seas. In
small open leads e.g. pack ice region in Arctic Ocean, whitecaps are produced but breaking
waves are not strong enough to break them because of insufficient space between the leads.
Our results indicate the total mass concentration of chlorine (Cl) increase with increasing
wind speed (see figure 2) in pack ice region. Particle production thus occurs in the vicinity of
open leads. It is well known that total particle concentration logM is linearly related to wind
speed. Therefore in open leads particle production will take place if the wind speed is high
enough. In the Arctic region whitecap production and breaking occurs. The question is what
materials this process will inject into the atmosphere. The hypotheses are that there are two
clearly different processes taking place when bubbles burst.
One is from the material of the bubbles surface injected into the air. This is usually called film
droplets.
The second is materials accreted to the bubbles while they are moving towards the sea surface
(jet droplets). The size of the film droplets are between 0.1 to 0.3 m while the jet droplets
have sizes between 0.3 to 1.0 m, see figure 6. The results of calculations of enrichment
factors show elements as K, Ca, Ti, Mn, Fe, Ni and Zn appears to come from soil dust, see
table no. 3. The explanation is continental crust attached to ice which can be transport to
Arctic via Arctic current. When the ice melts the soil dust will be release into the ocean. If the
composition of the biota in Arctic Ocean was know it could also be interpreted that the trace
elements originate from biota. Since there is no data available on the trace element
concentration in the ocean biota, it is our hypothesis that these elements may derive from
biota. The elements as K, Ca, Ti, Mn, Fe, Ni and Zn are very crucial to marine life.
5. Summary
Measurements of aerosol mass concentrations distribution during AOE01 were used to define
the physical and chemical properties of marine origin particles in the pack ice region of the
Arctic Ocean.
Acknowledgements
We would like to thank all the staff of PIXE group at Lund University.
We owe thanks to Swedish Polar Research Secretariat, which provide us a fantastic
environment to collect our data on icebreaker ODEN during Arctic Ocean 2001 expedition.
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