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Pergamon Atmospheric Enuironment Vol. 31, No. 2, pp. 159-170, 1997 Copyright 0 1996 Elswicr Science Ltd
PIk S1352-2310(96)00197-5 Printed in Great Britain. All rights reacrved
1352-2310/97 $15.00 + 0.00
RAINWATER COMPOSITION IN EIGHT ARCTIC CATCHMENTS IN NORTHERN EUROPE (FINLAND,
NORWAY AND RUSSIA)
CLEMENS REIMANN,* PATRICE DE CARITAT,* JO H. HALLERAKER,* TORE VOLDEN,* MATTI diYRiiS,t HEIKKI NISKAVAARA,?
VIKTOR A. CHEKUSHINS and VLADIMIR A. PAVLOVS * Geological 1Survey of Norway, P.O. Box 3006, Lade, N-7002 Trondheim, Norway; t Geological Survey of Finland, P.O. Box 77, FIN-96101 Rovaniemi, Finland; and $Central Kola Expedition, Fersman St. 26,
184200 Apatity, Russia
(First received 1 March 1996 and in jinal form 16 June 1996)
Abstract-Monthly rainwater samples were collected during the summer of 1994 in eight arctic catchments in northern Europe (four in Russia, three in Finland, one in Norway), at different distances and wind directions from the emissions of the Russian nickel ore mining, roasting and smelting industry on the Kola Peninsula. Three stations consisting of five samplers each were placed in open areas in all the catchments. Results show that close to the smelters in Monchegorsk, rainwater is strongly enriched in Ni (633 x), Co, Cu, As, MO, Al (36 x ), V, Cd, Sb, Pb (11 x ), Zn, Fe, Sr, Na, S/SO, (6 x ), Cl, Cr, Se (4 x ) and Ag when compared to a Finnish background catchment. Three sources of elements can be differentiated: natural dust, sea spray and anthropogenic (smokestack emissions and dust). Correlation diagrams and element ratios can be used to identify the different industrial processes and even ore feed changes at one smelter. Copyright 0 1996 Elsevier Science Ltd
Key word index: Nickel, copper, smelter, Kola Peninsula, precipitation chemistry.
INTRODUCTION
The geological surveys of Finland (GTK) and Nor- way (NGU) and the Central Kola Expedition (CKE) in Russia are carrying out a major geochemical map- ping project (see World Wide Web site http://www. ngu.no/Kola) in a 188,CKKl km2 area north of the Arc- tic Circle, comprising the entire area between 24” and 35.5” E north to the Barents Sea (Fig. 1). As part of this project, eight c:atchments (hereafter abbreviated as Cl-CS) widely distributed in this area (Fig. 1) were investigated in detail in 1994. Sampled media were: snow (meltwater and filter residue), rainwater, stream water, organic stream sediments, terrestrial moss, top- soil (O-S cm), complete podzol profiles, Quaternary deposits and bedrock.
Some of the world’s largest point sources of SOz emissions (Gunn et al., 1995) are located within the study area, the nickel smelter at Nikel, the ore roast- ing plant at Zapoljarnij and the nickel smelter at Monchegorsk (Fig. 1) together accounting for about 400,000 t of SOz emissions yearly. Table 1 gives an overview of the emission data as released by Russian authorities for all major sources in the survey area for 1993 and 1994.
The results of rainwater sampling carried out dur- ing the summer months of 1994 are presented here.
A number of established rainwater monitoring sta- tions exist in the area (e.g. at Svanvik in Norway (Hagen et al., 1995), Pesosjar% and Vuoskojiirvi in Finland (Juntto, 1992)). As a rule, the number of elements monitored there is rather limited compared to the number of elements of interest for the Kola project. Other studies carried out on the composition of precipitation from this area (mostly snow) include Derome et al. (1991, 1992), Berg et al. (1994), Makarova et al. (1994), Jaffe et al. (1995), Kelley et al. (1995), Reimann et al. (1996) and Soveri and Peltonen (1996).
The aim of this study was to improve our under- standing of element sources, cycling, seasonal effects and variability on a relatively detailed scale, to aid the interpretation of the results of the planned low-den- sity (1 sample site per 10&600 km2) regional mapping project. The main characteristics of the eight catch- ments are summarised in Table 2.
SAMPLING
For this project a special rainwater sampling device had to be designed and constructed (Fig. 2), allowing for rough conditions. To collect the rain, new polyethylene bags-all from a single production batch and checked for
159
160 C. REIMANN et al.
Fig. I. Location of the study area for the regional mapping project and the catchments from which data are presented here. Svanvik (NILU’s official rainwater monitoring station) is located halfway between Kirkenes
and 0, close to the Russian border.
Table I. Official Russian emission data for 1993 and 1994 for the main sources of heavy metals and sulphur in the survey area (Committee for Ecology and Natural Resources (CENR), 1995)
t yr-’
Location Year Ni Cu Co V205 HF Cl HIS SO2 CO2 NO2
Murmansk 1993 - - - 98.4 - - - 30,991 4420 1651 1994 0.02 0.4 - 91.3 0.172 0.03 - 26,587 3540 1266
Nikel 1993 129.8 87.1 5.2 13.4 - - - 160,629 267 167 1994 136.1 81.9 5.2 12.9 - - - 129,160 244 158
Zapoljamyi 1993 152.3 74.8 5.4 23.1 - - - 66,629 499 286 1994 161.1 81.0 5.4 21.4 - - - 69,208 463 285
Monchegorsk 1993 1960.3 1049.1 89.2 57.2 - 365.4 27.7 136,880 1294 5117 1994 1618.8 933.7 81.5 59.8 - 341.3 18.1 97,715 917 1267
Olenegorsk 1993 - - - 0.3 - - - 3519 419 468 1994 - 0.03 - 0.4 - - - 3508 869 610
Apatity 1993 - - - 26.1 - - - 21,406 683 6927 1994 - - - 0.4 - - - 14,576 271 5141
Kirovsk 1993 - - - 51.7 - - - 3753 811 248 1994 - - - 43.6 - - - 4041 554 1358
contamination-were used. Although working in Arctic areas to avoid throughfall. A composite sample from the five areas where evaporation should not be a major problem, the samplers per station was taken monthly, avoiding bags that PE bags were nearly closed using a plastic strip (Fig. 2) and were visibly contaminated or contained far too much or too the outer tubes of the holders were covered with aluminimn little water compared to the others. The number of bags and foil during July and August. amount of water were recorded. The samples were com-
Three stations, each consisting of five samplers placed posited by pouring the rainwater from each sampler at each about IO m apart, were set up in all eight catchments in open station into a new large PE bag mounted in a PE bucket.
Tabl
e 2.
Sum
mar
y of
som
e ch
arac
teris
tics
of t
he d
iffer
ent
catc
hmen
ts
No.
N
ame
Coo
rdin
ates
A
nnua
l M
ean
tem
p.
of c
atch
men
t Si
ze
Elev
atio
n pr
ecip
. Ja
n/Ju
ly
Surf
ace
cove
r ou
tlet
(km
’)
(m a
.s.1
) (m
mY
W
b V
eget
atio
n B
edro
ck
pecu
liarit
ies
Russ
ia
Cl
Zapo
ljam
ij
c2
Mon
cheg
orsk
c3
Kiro
vsk
c4
Kur
ka
Nor
way
c5
Sk
jellb
ekke
n
Finl
and
C6
Kira
kka
Cl
Nar
uska
C8
Palla
s
69”2
7’01
”N
31”0
3’49
”E
67”5
0’3O
”N
32”5
4’48
”E
67”3
2’5O
”N
33”4
8’55
”E
67”4
1’25
”N
32”5
0’14
”E
69”2
1’25
”N
29”2
7’25
”E
69”3
5’12
”N
28”5
1’46
”E
67”2
1’44
”N
29”2
2’05
”E
68”0
9’14
”N
23”5
2’5O
”E
19.0
2 25
-373
45
4
22.3
8 12
8-50
7 39
1
20.0
1 24
&10
75
502
20.4
9 15
2466
50
2
34.5
6
11.8
6 11
&20
0 38
6
20.1
6 26
3-49
0 51
3
24.4
2 30
3-50
0 40
5
8&29
7 42
2
- 8.
0/12
.4
Birc
h fo
rest
tun
dra
- 9.
5/13
.1
Tech
noge
nic
dese
rt, b
irch
shru
bs
- 11
.5/1
2.8
Spru
ce f
ores
t, m
ount
ain
tund
ra
birc
h fo
rest
-
11.5
/12.
8 N
orth
ta
iga
spru
ce f
ores
t, bi
rch;
inc
ipie
nt
dete
riora
tion
- 8.
7/l 1
.2
Nor
th
taig
a pi
ne f
ores
t, bi
rch
- 11
.7/1
2.1
Nor
th
taig
a pi
ne f
ores
t
- 11
.4/1
2.6
Nor
th
taig
a sp
ruce
for
est
- 12
.4/1
2.9
Nor
th
taig
a sp
ruce
for
est
Gne
iss
Dac
ite a
nd a
ndes
ite
and
tul%
, gab
bro/
norit
e N
ephe
linite
Am
phib
olite
, gn
eiss
And
esite
, ba
salt
and
tuff
s, ‘b
lack
sha
le’,
min
or
carb
onat
es
Gra
nite
Gne
iss
Qua
rtrite
Till,
flu
viog
laci
al,
outc
rop
Till,
pro
ne
to e
rosi
on
Till,
dilu
vial
/elu
vial
Till,
flu
viog
laci
al
Till,
esk
er
Out
crop
, til
l, m
orai
ne
ridge
Till,
pea
t, ou
tcro
p
Till,
pea
t
“Fro
m
the
clos
est
met
eoro
logi
cal
stat
ion
(dat
a fr
om 1
994)
. b F
rom
the
clo
sest
met
eoro
logi
cal
stat
ion
(dat
a fr
om
1992
to 1
995)
.
162 C. REIMANN et al.
RAINWATER SAMPLER KOLA PROJECT
6.7 mm
PLASllC - BAG, lOOurn
BOLT, Smm- -
SELF-LOCK PLASTIC- STRIP/
TAPE -
2x2” WOODEN POLE ?-
TAPE - \ \ \ _- A 4L
‘&\ \ : \ : \ I \
: \ \
i--_A RAIN WATER 1
I COcm
PLASTIC BAG
Fig. 2. Construction drawing of the rainwater bulk sampler used for this project.
Rainwater composition 163
Water for cation analyses was sucked out of the bag using a PE syringe that was cleaned with rainwater three times before sampling. Water for anion analysis was poured out of the plastic-lined bucket into a 500 ml PE bottle. The total volume of precipitation was recorded after sampling, using a 2 / PE measurement cylinder. More details on sampling are given in Ayriis and Reimann (1995).
ANALYSIS
Samples for cation analysis (Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, MO, Na, Ni, P, Pb, Rb, S, Sb, Se, Sr, Th, Tl, U, V and Zn) were filtered through a 0.45 pm membrane filter (MilliporeTM Millex-HA) and acidified in the field -prior to analysis using ICP-AES and ICP-MS. Unfiltered and unacidified samples were taken to analyse for Br, Cl, F, NO,, PO, and SO, by ion chromato- graphy and to perform potentiometric determination of pH and electrical conductivity. All samples were analysed in the laboratory of the Geological Survey of Finland (GTK).
The GTK laboratory is accredited according to IS0 9001 and ISO-Guide 25. Quality control data suggest that some samples may be contaminated with Zn, the source apparent- ly being Teflon-coated rubber fittings whose coating wears off with time. Zn data presented here should thus be treated with care.
RESULTS
Table 3 summarises the analytical results for each of the eight catchments separately (median, minimum and maximum values).
DISCUSSION
Table 2 shows that the predominant sources of heavy metals in the whole area are the smelters in Monchegorsk (C2) and Nikel (including the ore roast- ing plant in Zapoljarnij (Cl)). The following suite of elements can be immediately identified as part of the emission spectrum of the Monchegorsk smelter: Ag, Al, As, B, Bi, Cd, Cl, Co, Cr, Cu, F(?), Fe, Mg, MO, Ni, Pb, S, Sb, Se, Si, TI, V and Zn.
Normalisation to a crustal element like Fe is often used to calculate enrichment factors in atmospheric chemistry (e.g. Galloway et al., 1982). We do not think this approach is justified as no such thing as a “crustal average” for any one element exists at a given place. The average composition of dust within an area will to a very large degree be determined by the local lithologies; element contents in different lithological domains can vary by several orders of magnitude and any calculation using a world-wide average will very likely be erroneous by at least one or two orders of magnitude.
One can, however, use a regional average for a given large area to calculate simple enrichment ratios. For our study, C7, situated in the centre of the study area and having the most widespread lithology (gneisses), should be fairly representative for the re-
gional background. When the enrichment ratios for C2, Monchegorsk, are calculated by dividing the me- dian observed for C2 by the median for C7, the follow- ing sequence is obtained (two values are given for those elements where the median in C7 is below the detection limit: the first value using half of the detec- tion limit for the calculation, the second using the detection limit): Ni (633), Co (1180/590), Cu (453) As (154), Mo(107/53), Al (36), V (27) Cd (15), Sb (26/13), Pb (11X Zn (IO), Fe (8), Sr (7), Na (6), S/Sob (6) Cl (6), Cr (5), Se (4) and Ag (6/3).
Ca, Cl and Na reach maximum levels in C 1. This is the catchment closest to the Barents Sea and these high concentrations are at least partly due to the additional input of sea spray. The high levels of Fe, K and Mn are related to increased dust input due to the open cast mining operations near Zapoljarnij (see Reimann et al., 1996).
When our data are compared with some published data from this area (Berg, 1994; Hagen et al., 1995), it is obvious that ours are low (by a factor of 2-lo), especially when the results from the Svanvik station are compared with those from C5 just 40 km to the south. For the majority of elements, the Svanvik data are even higher than our values from Cl near the roasting plant at Zapoljarnij. The main cause for the observed discrepancy presumably is the difference in practice when it comes to filtering or not filtering the rainwater samples (we filtered at 0.45 pm). Snow data (Reimann et al., 1996), where meltwater (< 0.45 pm) and filter residue data are compared, indicate that for Ni and Cu more than 60% of the total deposition in the vicinity of the nickel industry comes in particle size classes > 0.45 pm. Thus, filtering the samples explains the observed differences.
Comparison between our data and data published from northern Finland (Juntto, 1992) and other parts of the world (e.g. Galloway et al., 1982; Ross and Vermette, 1995) shows that ours fit very well within the ranges given.
Figure 3 shows boxplot comparisons of element levels and variations for Al, As, Cu, Ni, Rb, S04, V and pH in the eight catchments studied. Note that for some elements contents were log-transformed prior to plotting.
The boxplot as used in Fig. 3 is a useful graphic originating from exploratory data analysis (EDA) (Tukey, 1977). It provides a graphical data summary, relying solely on the inherent data structure and not on any assumptions about the normality of the data distribution. It basically divides the distribution of the results into quartiles, firstly by finding the median (displayed as a line in the box), and then doing the same for each of the remaining halves. These upper and lower points or “hinges” define the central box which thus in itself again contains 50% of all data. “Whiskers” are then drawn from the ends of the box, each extending 1.5 times the width of the box towards the maximum and the minimum (taken back to the last real data point). Any values outside of these
Tabl
e 3.
Sum
mar
y st
atis
tics
of r
ainw
ater
an
alys
is f
or t
he e
ight
cat
chm
ents
in
vest
igat
ed.T
he
high
est
med
ian
valu
e an
d th
e hi
ghes
t m
axim
um
valu
e fo
r an
y on
e el
emen
t ar
e pr
inte
d in
bol
d ty
pe.
Sam
ples
are
30
d co
mpo
site
sa
mpl
es f
or t
he s
umm
er (
May
to
Sept
embe
r)
of 1
994.
All
sam
ples
for
cat
ion
anal
ysis
wer
e fil
tere
d at
<
0.45
pm
and
aci
difie
d w
ith u
ltrap
ure
HN
O,
in th
e fie
ld; s
ampl
es
for
anio
n an
alys
is a
nd m
easu
rem
ent
of p
H a
nd E
C w
ere
left
untre
ated
Elem
ent
Uni
t C
l c2
c3
c4
C
S C
6 c7
C
8 m
edia
n m
edia
n m
edia
n m
edia
n m
edia
n m
edia
n m
edia
n m
edia
n ra
nge
rang
e ra
nge
rang
e ra
nge
rang
e ra
nge
rang
e
Ag
KG
-’ A
l K
c1
As
ILK
’ B
I%
~-’
Ba
P’g
~-’
Be
PC
’ B
i m
e-’
Br
fige-
’ C
a mg
G_'
Cd
w-’
Cl
mg/
-’
co
Pgd-
’
Cr
/Jgt
-’
cu
Pgd-
’
F m
g!-’
Fe
rnge
-’
K
mg/
-’
Li
fig/-’
Mg
mg!
-’
< 0.
01
0.03
<
0.01
0.
01
< 0.
01-0
.05
< 0.
01-0
.14
< 0.
01~.
05
< O
.OlG
O.0
6 12
.4
105
51
10.3
6.
@45
13
.427
2 30
-171
4.
7-68
0.
58
123
0.22
2.
7 0.
18-1
.34
3.6-
84.4
0.
1 l-2
.44
l-9.3
<
0.5
0.73
<
0.5
< 0.
5 <
0.52
.11
< 0.
s2.3
6 <
0.5-
0.79
<
0.50
.78
0.83
1.
07
0.99
0.
51
0.6-
2.3
0.6-
1.9
0.>2
.9
0.3-
1.2
all <
0.1
aU
< 0
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all
< 0.
1 aU
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1
aU <
0.0
3
all
< 0.
2
0.15
0.
08-0
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03-0
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36
0.14
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2 <
0.2
< 0.
2-0.
8 8.
3 4.
438
aU <
0.0
5
0.04
0.
01-8
.13
0.17
0.
040.
82
< 0.
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0.1-
05
0.1
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< 0.
03
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all <
0.2
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g9
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# <
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01~.
09
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02-0
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0.12
<
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0.04
<
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3
all
< 0.
2
< 0.
03
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all
< 0.
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09-0
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0.03
<
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2 0.
050.
7 0.
03
< 0.
024.
07
aU <
0.2
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0.64
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all
< 0.
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all
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l <
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01
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all
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34.7
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< 0
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< 0.
03
aI!, <
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0.02
XI.1
6 0.
03
< 0.
02-o
. 16
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< 0
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l <
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01
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03-0
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all
< 0.
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<
O.O
lXI.2
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1
2.5
1.62
5.7
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< 0.
5 <
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0.58
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4-0.
7 <
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14.1
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< 0.
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054.
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03
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06
all
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17
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0.
41.1
al
l <
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all
< 0.
03
all
< 0.
2
0.05
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02-o
. 14
0.06
<
0.02
4.33
0.
1 <
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0.3
< 0.
02
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0220
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all
< 0.
2
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0.
24-1
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all
< 0.
05
< 0.
01
< 0.
01&
0.01
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05
0.02
-0.2
6 <
0.1
< 0.
14.4
5 0.
02
< 0.
01~.
04
all
< 0.
01
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1.7-
7.4
0.07
c
0.05
-o. 1
<
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< 0.
516.
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< 0.
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03
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X%
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3 <
0.1
< 0.
1-0.
41
< 0.
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166 C. REIMANN et al.
1
0.1
Cl c2c3c4c5c6c7c6 #lo #I7 t15 #I6 #I5 #9 #I5 #I2
cl Q c3 c4 c5 c6 c7 ca #IO #I7 #I5 116 #I5 #9 #I5 #I2 As
t10 Y17 115 X16 t15 #9 #I5 #I2 1VZ
10 9 6 7 6
d 5 4 3 2 1 0
#IO #I7 #I5 #I6 #I5 #9 H5 #I2
.._.!6, Y.@!& ___..____________.____._______
._ _.. f---------- --- ---. -------- ---- _.__.__,_.____ ___._....._.__..._..-........
_______1_ .__._ ._._.._.._
_____p_,______ ________..._.._...._...... ._._.._...._..... _. .._.
Cl CT2 c3 c4 c5 c6 c7 c6 #IO t17 #I5 Xl6 #I5 #9 115 #I2 110 117 #I5 #I6 #I5 #9 #I5 #I2
6.5
6.0
5.5
5.0
4.5
4.0
_.~..._...__...__._......___________ ,________
cl c2 a c4 c5 c6 c7 c6 pE3,5
cl CL? c3 c4 c5 f.% c7 c6 #IO #I7 #I6 X16 #I5 $9 #I6 #12 #lo t17 #I5 116 #6 x6 112 #9
Fig. 3. Boxplot comparison of element levels and variations in the eight catchments (ClX8) studied.
whiskers are defined as data outliers. Important in- a factor of 10 above background). The SOz emissions formation about the data set, e.g. median, quartiles, are spread over a much larger area than the metals, skewness of the distribution and the existence of data thus explaining the much smaller differences between outliers, can all be extracted at one glance from this the catchments. Note, however, that the general pat- simple graphic. terns for Ni and SO4 (and all the other “main pol-
SO4 levels in the different catchments are much lutants”) are similar from Cl to C8, displaying the more similar than those of the metals (C2 “only” by typical anthropogenic or technogenic signature for
Rainwater composition 167
6.0 7.0 10.0 11.0
6.0 7.0 Ett~ in 1::
10.0 11.0
6.0 . TO t&h in l&
10.0 11.0
o.016+m i i ; ; ; ; ;
7.0 t&h in 1::
10.0 11.0
Fig. 4. Seasonal variations in rainwater samples as observedin C2, C4 and C7.
this area. A similair signature is apparent in other There is clearly an additional source for Al and V at media, such as snow @yrHs et al., 1995; Reimann et C3. Rb shows a pattern that is typical for an element al., 1995), stream water (Caritat et al., in preparation) originating from natural sources (geogenic dust), with and topsoil (Reimann et al., 1996). pH is lowest in C2 very little differences in levels between the catchments. and highest in C3; all other catchments show very It is interesting to note that elements mostly in- similar levels. A considerable input of basic rock dust fluenced by “geogenic” or, better, “natural” sources buffers the pH levels in precipitation around the (e.g. Ba, K, Li, Mn, Rb) generally show a much smaller smelters (Reimann et al., 1996). variation, while very large contrasts in concentration
o.ol*, I ; ; : ;
6.0 7.0 tf&h in 1%
10.0 11.0
o.lI:.::.:~: 6.0 7.0 6.0 10.0 11.0
Month in 1%
(j+_.: . . . :.. ../.... ?.. :. :.. r ---/r-~-,--
6.0 7.0 t%h in 1 k
168 C. REIMANN et al.
levels, a great variation within one catchment and generally severely skewed distributions seem to be typical of anthropogenic sources.
Seasonal variation
Variations in time and between the three stations within selected catchments are plotted in Fig. 4 for the same elements as in Fig. 3, but only for three catch- ments, C2, C4 (representing contamination at differ- ent distances from the smelter) and C7 (representing background). Note that a mixture of linear and logar- ithmic scales is used in these diagrams, depending on the observed element variability. For most elements, differences between catchments are much larger than seasonal effects and these again are larger than vari- ations between the three stations per catchment. An exception is Rb, which has a “natural” source. For Rb the largest difference is observed between the three stations in C7, in August. pH also shows a great variation for the C7 August samples. Note, however, that the scale for Rb is non-logarithmic and total variation is thus very low compared to the other elements. Differences in the emission-related elements over time are especially great in the Russian catch- ments; for Al they can be up to one order of magni- tude (C2: June vs August). Trends differ in the various catchments and can help to improve our understand- ing of the sources of different elements.
Figure 5 shows the seasonal variation of the Cu/Ni ratio at C2 and Cl. This ratio is of particular interest in this area as it is very different in the two ore types used in the Monchegorsk smelter, near C2. The ore roasting plant at Zapoljarnij (near Cl) processes only Pechenga ore with a CufNi ratio of about 0.5, whereas the Norilsk ore which, in addition to the Pechenga ore, is smelted at Monchegorsk has a Cu/Ni ratio of about 2 (Pechenga Nikel Combinat, personal com- munication). When this ratio is plotted, as it is re- vealed by the rainwater samples month after month, it
1~~-_-___----__-8__,_- *L -_. s m o~‘ll,‘,,,,‘~I,.,,.,. IIIl/mI_
5 6 7 8 9 10 11 12 MONTH IN 1994
Fig. 5. Seasonal variations in the Cu/Ni ratio in rainwater from C2 (Monchegorsk, where Pechenga ore and ore from Norilsk are used, which have different Cu/Ni ratios) and Cl
(Zapoljamij, where only Pechenga ore is roasted).
remains very constant in Cl at around 1 (median: O.S), but C2 shows a sharp drop from 6.5 to 2.5 in August, and throughout the autumn, indicating a change from the use of Norilsk ore to Pechenga ore.
Correlations
XY-diagrams (Fig. 6) show a generally very good correlation for samples from the Russian catchments, with the highest values in C2 lying on one trend with C4 and C3 (distance from source). Cl often shows an offset from the Monchegorsk trend due to the differ- ence in ore feed (compare Cu/Ni, As/Ni, Pb/Ni, V/Ni) as well as the difference in the technological process (roasting vs smelting). The differences in the ore feed at Monchegorsk are clearly displayed in two slightly offset trends for the C2 samples in these diagrams, one set coming close to the Cl trends.
Samples from the Norwegian catchment take an intermediate position, but are often closer to the C2 than to the Cl trend. This could be caused by mixed inputs from both smelting in Nikel and roasting in Zapoljarnij, or fractionation of the different elements with transport distance in the atmosphere, which would, for example, mean that Ni is deposited faster than Cu (differences in particle size distributions in the aerosol?). Such a fractionation can be clearly seen in the Ni/Pb diagram, where Pb is strongly enriched in relation to Ni in CS. The Finnish background samples, however, do not usually display any correla- tion or trend other than an enrichment/depletion in one or other element.
The Ni/V diagram shows that there must be a local source of V in, or close to, C3 because there is about 10 times more V than expected from the Ni content and the trend of the other catchments. This V source could be the coal-fired power plant in Apatity, ex- haust from diesel trucks in the opencast mine (road within the catchment), or simply lithology (local dust).
The Al contents in C3 show a strong offset in the Al/Ni diagram, clearly demonstrating that local dust from opencast mining is an important source of elements observed in rain in C3. Otherwise the cor- relation of Al with Ni for Cl, C2, C4 and C5 is surprisingly good, whereas that between Al and Rb is poor, arguing against a purely dust-related origin for the high Al levels. Al thus seems to have a fourfold origin: natural dust, anthropogenic “natural” dust ori- ginating from the mining of alkaline rocks in C3, smokestack emissions from the smelters, and wind blown “anthropogenic” soil dust due to the severely damaged vegetation cover around the smelters in C2, C4, Cl and C5.
CONCLUSIONS
The values obtained from the rainwater samples are generally very low for the 38 analysed elements/para- meters and, even with advanced analytical techniques (ICP-MS), results for many elements were at or below
Rainwater composition 169
0.01,' I I f i 1OOU loo00
sclsn
pH_GTK
Fig. 6. XY-diagrams for selected elements. Lines indicate element ratios as given in the figures.
the detection limit. The highest levels for almost all Finland. C5 in Norway has an intermediate position elements can be observed in C2, followed by Cl, C4 with regard to pollution. There are a few short-lived and C3, this sequence reflecting the distance from events, dependent on the wind direction, when very industrial plants. Most of the heavy metals (Co, As, high inputs of contaminants were registered here. Cu, MO, Ni, Sb) show enrichments of two to three Regional variation in element content was found to orders of magnitude in their median levels close to be much greater than temporal variations or vari- industry in Russia, compared to background levels in ations between the three stations per catchment. When
170 C. REIMANN et al.
time variations in rain chemistry in C2 are examined in more detail, drastic changes in element ratios can be detected, reflecting changes in the ore fed into the smelter (Pechenga vs Norilsk ore).
The following elements reach maximum concentra- tions in rainwater at C2: Ag, Al, As, B, Ba, Bi, Cd, Co, Cr (highest median, highest single value in C8), Cu, Li (highest median, highest single value in Cl), MO, Ni, Pb, S, Sb, Se, Si, Tl, V and Zn (highest median, highest single value in C6). Electrical conductivity also shows maximum values in C2, pH is lowest. Furthermore, clearly elevated levels can be observed for Ca, Cl, Fe, Mg, Na and Sr. All these elements can be attributed to industrial activity and can thus be classified as ‘<an- thropogenic”. Some (Al, B, Ca, Fe(?), Mg, Li, Sr) are probably further enriched or solely caused by in- creased dust input due to industry-related activities and/or destroyed vegetation cover in the surround- ings of the smelters.
Monitoring rainwater chemistry in eight catch- ments at different distances from major, well-defined pollution sources in an otherwise nearly pristine area proved to be very successful in determining the degree of contamination, the large number of pollutant ele- ments, the very sharp drop of almost all element levels with distance from the smelters, and in improving our understanding of the various sources of element input to the catchments studied.
Acknowledgements-Norwegian and Russian participation in this project was made possible by the Norwegian Ministry of the Environment with special project funds from the Norwegian Ministry of Foreign Affairs. We would like to thank the whole Kola Project team in all three countries and the fieldwork participants from Lithuania and Austria for their efforts in the field and for many stimulating discussions. Comments from two anonymous referees were greatly ap- preciated.
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