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Pollution levels, pollutant distribution and potential source assessments based on multivariate analysis (chemometrics) were made for harbour sediments from two Arctic locations; Hammerfest in Norway and Sisimiut in Greenland. High levels of heavy metals were detected in addition to organic pollutants. Preliminary assessments based on principal component analysis (PCA) revealed different sources and pollutant distribution in the sediments of the two harbours. Tributyltin (TBT) was, however, found to originate from point source(s), and the highest concentrations of TBT in both harbours were found adjacent to the former shipyards. Polyaromatic hydrocarbons (PAH) ratios and PCA plots revealed that the predominant source in both harbours was pyrogenic related to coal/biomass combustion. Comparison of commercial polychlorinated biphenyls (PCB) mixtures with PCB compositions in the sediments indicated relation primarily to German, Russian and American mixtures in Hammerfest; and American, Russian and Japanese mixtures in Sisimiut. PCA was shown to be an important tool for identifying pollutant sources and differences in pollutant composition in relation to sediment characteristics.
Content may be subject to copyright.
Chemometric Analysis for Pollution Source Assessment
of Harbour Sediments in Arctic Locations
Kristine B. Pedersen &Tore Lejon &Pernille E. Jensen &
Lisbeth M. Ottosen
Received: 25 November 2014 /Accepted: 6 April 2015
#Springer International Publishing Switzerland 2015
Abstract Pollution levels, pollutant distribution and
potential source assessments based on multivariate anal-
ysis (chemometrics) were made for harbour sediments
from two Arctic locations; Hammerfest in Norway and
Sisimiut in Greenland. High levels of heavy metals were
detected in addition to organic pollutants. Preliminary
assessments based on principal component analysis
(PCA) revealed different sources and pollutant distribu-
tion in the sediments of the two harbours. Tributyltin
(TBT) was, however, found to originate from point
source(s), and the highest concentrations of TBT in both
harbours were found adjacent to the former shipyards.
Polyaromatic hydrocarbons (PAH) ratios and PCA plots
revealed that the predominant source in both harbours
was pyrogenic related to coal/biomass combustion.
Comparison of commercial polychlorinated biphenyls
(PCB) mixtures with PCB compositions in the sedi-
ments indicated relation primarily to German, Russian
and American mixtures in Hammerfest; and American,
Russian and Japanese mixtures in Sisimiut. PCA was
shown to be an important tool for identifying pollutant
sources and differences in pollutant composition in re-
lation to sediment characteristics.
Keywords Harbour sediments .Heavy metals .PAH .
PCB .TBT.Principal component analysis
1 Introduction
International focus on the Arctic environment has in-
creased during the past decade due to the environmental
and geopolitical changes in the region. The effects of
climate change in the Arctic have become apparent,
accumulation of persistent pollutants in the environmen-
tal as well as bioaccumulation in the food chain of Arctic
mammals has been reported (Hung et al. 2010;OSPAR
2008; Rigét et al. 2010) and the northern areas are
continuously becoming more accessible for transport
and economic exploitation of mineral resources. There
is an international acknowledgement that countries out-
side the Arctic regions have an impact on the environ-
ment via air- and waterborne transport (LRTAP 2010).
The European Union (EU) is for instance developing an
Arctic policy based on the environmental and geopolit-
ical changes in the Arctic with the aim of supporting the
industrial development opportunities in an environmen-
tally sound way for the benefit of the European Arctic
population and citizens of the EU (Commission 2012).
In addition, the EU has qualified the impacts/effects of
human activities of the EU countries on the Arctic
environment in the Arctic Footprint and Assessment
Water Air Soil Pollut (2015) 226:150
DOI 10.1007/s11270-015-2416-4
Electronic supplementary material The online version of this
article (doi:10.1007/s11270-015-2416-4) contains supplementary
material, which is available to authorized users.
K. B. Pedersen :T. Lejon (*)
Department of Chemistry, University of TromsøThe Arctic
University of Norway, Postbox 6050, Langnes, 9037 Tromsø,
P. E . Jens e n :L. M. Ottosen
Arctic Technology Centre, Department of Civil Engineering,
Technical University of Denmark, Building 118,
2800 Lyngby, Denmark
project (Institute 2010). With respect to global sources
of pollution via long-range transport of pollutants and
effect on human health and the environment in the
Arctic, the Arctic Monitoring and Assessment Pro-
gramme (AMAP) of the Arctic Council focuses on
persistent organic pollutants (POPs), among these
polychlorinated biphenyls (PCB) and the heavy metals
Cd, Hg and Pb. Bioaccumulation of these priority pol-
lutants has been registered in mammals and humans in
the Arctic due to both local/regional and global sources
(AMAP 2002;Hungetal.2010). In addition to these
pollutants countries represented in the Arctic Council
include polyaromatic hydrocarbons (PAH), tributyltin
(TBT) and the heavy metals As, Cr, Cu, Ni and Zn as
priority pollutants (CCME; Danish EPA 2005; SFT
2007; USEPA). Research on the long-range transport
of these pollutants has not been extensive.
The increasing human activities in Arctic regions
such due to the economic exploitation increase the po-
tential local and regional environmental loads. The on-
going and expected increasing industrial development
especially within the mining, and oil and gas industries
in for instance Greenland, Northern Norway and NW
Russia, accentuates the need for continuously improv-
ing environmental management systems and technolo-
gies for minimising the environmental impact of the
increasing local/regional human activities. One area of
concern is the removal of pollutants that pose risk to
human health and the environment.
Harbours act as sinks for a wide variety of pollutants
caused by anthropogenic activities in the harbour as well
as on land. Examples of harbours located in Arctic
regions that have been exposed to several local sources
of pollution over the past 5060 years are Hammerfest
in Northern Norway and Sisimiut in Greenland. In
Hammerfest, environmental investigations have re-
vealed complex composition of pollutants such as heavy
metals, PAH, PCB and TBT in the harbour sediments at
levels posing risk for human health and the environment
(Norwegian Environment Agency 2014). In Sisimiut,
high levels of Cd and Cu have been registered (Ottosen
and Villumsen 2006), investigations of organic pollut-
ants have however not been conducted. Hammerfest
harbour has been identified as one of the 17 harbours
of highest priority for remedial actions by the Norwe-
gian national action plan for polluted seabed (Ministry
of Environment 2007). In 2008, remedial actions to
remove and stabilise 1200 m
of polluted sediments
from part of the harbour were implemented (Norwegian
Environment Agency 2014). There however still remain
large areas of the harbour in need of remedial actions in
order to meet the environmental goals of Hammerfest
municipality. There are currently no remedial action
plans for the harbour in Sisimiut, however, due to the
increased national/international focus on the Arctic en-
vironment; similar remediation plans from the authori-
ties may be expected in the future.
Prior to implementing remedial action plans, it ap-
pears to be instrumental to identify the potential pollu-
tion sources to better understand and control/prevent
further pollution of the sediments. Statistical analyses
of the distribution of pollutants in relation to sediment
properties, e.g. grain size, content of organic matter and
buffer capacity, can extract trends linked to the pollution
sources. Principal component analysis (PCA) is a che-
mometric statistical tool for visualising the differences
and similarities in large data sets by calculating principal
components. These are mutually orthogonal vectors that
represent independent and uncorrelated variation of the
initial descriptors (pollutants/sediment properties), so
correlated descriptors are then described by the same
principal component. The systematic variation in the
data set can hence be simplified by using fewer new
descriptors than the original number of variables, and
this simplification is done without loss of systematic
information (Carlson and Carlson 2005).
Score plots are obtained by projecting the original data
onto the calculated orthogonal principal component vec-
tors. The influence of each original descriptor to the
principal component is reflected in a loading plot. De-
scriptors which have a strong contribution to the variation
depicted in the score plot are found far from the origin in
the loading plot. Positively correlated descriptors are
projected close to each other, while negatively correlated
descriptors are projected opposite to each other with
respect to the origin (Carlson and Carlson 2005).
mation on pollutant distribution in sediment/soil/water
and to assess sources of pollution (Cheng et al. 2009;De
Luca et al. 2004;Fengetal.2014; Gao et al. 2013;Jan
et al. 2010). In some studies, PCA plots were used to
assess the distribution of PCB congeners and PAH com-
ponents in sediments and coupled with ratio calculations
of selected components, possible sources of pollution
were identified (Countway et al. 2003;Fengetal.2014;
Gao et al. 2013;Hartmannetal.2004).
The main focus of this study was to compare the
distribution of pollutants related to sediment properties
150 Page 2 of 15 Water Air Soil Pollut (2015) 226:150
for two harbours, Hammerfest and Sisimiut, located in
the Arctic for the assessment of possible differences in
pollution sources. This involved a preliminary chemo-
metric (PCA) assessment of the pollutant distribution
patterns in relation to sediment properties and in depth
evaluation of PCA plots of PAH components and PCB
congeners to evaluate possible pollution sources.
2.1 Statement of Human and Animal Rights
The procedures and experiments undertaken in this
study were in accordance with the Helsinki Declaration
of 1975, as revised in 2000 and 2008.
2.2 Sample Collection
Sediments from Sisimiut, Greenland and Hammer-
fest, Norway were sampled from the top 10 cm of
the seabed using a Van Veen grab and were kept
frozen during transport and stored in a freezer until
analysed. The sediments were sampled at different
locations in the harbours based on potential land-
based pollution sources resulting in five sediments
from Hammerfest and four sediments from Sisimiut
sample points, and adjacent potential sources of pol-
lution are listed in Table 1.
Potential sources of pollution in Sisimiut include:
&Petrol station adjacent to the harbour (local oil spills,
leakage from pipes/tanks etc.)
&Fish factory adjacent to the harbour (discharge of
processed shrimp/crab with possible biomagnifications
of pollutants in shells)
&Former shipyard
&Discharge of untreated wastewater
&Discharge from boats
&Diffuse sources include boat traffic, urban run-off,
incineration of waste, district heating (limited use of
fossil fuels for energy production) and household
heating (stoves/oil boilers)
Potential sources of pollution in Hammerfest include:
&Petrol station adjacent to the harbour
&Former shipyard
&Discharge of untreated wastewater and sewage
&Outlet from freshwater lake, Storvatn, in
which elevated concentrations of PAH and
PCB in the lake sediments has been measured
(Akvaplan-Niva 2008)
&Fire of Hammerfest 1944 (in connection with the
withdrawal of the German occupation)
&Diffuse sources include boat traffic, district heating
(mostly sustainable energy sources and limited
incineration of waste), household heating (stoves/
oil boilers) and Melkøya (liquefied natural gas
processing station).
Based on the pollution sources in the two towns,
harbour sediments may be polluted by the following
pollutants; heavy metals, PAH, PCB and TBT. Disper-
sion pathways from land based sources include subsur-
face water, rainwater, cable routes, freshwater outlets
and snow melting (annually approximately 6 months
of snow cover in both towns). Dispersion pathways in
the harbour sediments include resuspension of sedi-
ments and marine species.
2.3 Analytical
Major elements and heavy metal concentrations (P, Al,
Ca, Fe, K, Mg, Mn, Na, V, Cr, Cu, Ni, Pb, Zn) were
measured based on digestion (Danish standard DS259).
Sediment dried at 105 °C (1.0 g) and HNO
(9 M,
Solid particles were subsequently removed by vacuum
filtration through a 0.45 μm filter, and the liquid was
diluted to 100 mL. Metal concentrations in the liquid
were measured by Inductively Coupled PlasmaOptical
Tabl e 1 Sample points and potential sources of pollution
Harbour Sampling
Point sources of pollution
Hammerfest H_1 Former shipyard
H_2 Petrol station
H_3 Outlet from Storvatn (freshwater lake)
H_4 Sewage discharge
Sisimiut S_1 Former shipyard
S_2 Petrol station
S_3 Shrimp factory
S_4 Marina
Water Air Soil Pollut (2015) 226:150 Page 3 of 15 150
Emission Spectroscopy (ICP-OES) and are given as
milligram metal per kilogram dry matter.
Mercury, TBTand organic components (PAH16, PCB
and total hydrocarbons (THC)) were measured at a li-
censed laboratory, Eurofins in Moss, Norway. Mercury
was measured by Norwegian Standard NS 4768. PAH,
measurements included 16 PAH components and seven
PCB congeners, selected based on sediment quality
criteria for Denmark, Norway and OSPAR (Protection
of the Marine Environment of the North-East Atlantic).
The PAH components were acenaphtene, acenaphtylene,
anthracene, benzo(a)anthracene, benzo(a)pyrene,
benzo(b)flouranthene, benzo(k)fluoranthene,
benzo(ghi)perylene, chrysene, dibenzo(a,h)anthracene,
fluoranthene, fluorine, indeno(1,2,3-cd)pyrene, naphtha-
lene, phenanthrene and pyrene. The seven measured
PCB congeners were PCB28, PCB52, PCB101,
PCB118, PCB138, PCB153 and PCB180.
Chloride content was measured by agitating sedi-
ment (10 g) dried at 40
C with micropore water
(40 mL) for 20 h. Solid particles were removed by
0.45 μm vacuum filtration, and the chloride concentra-
tion was measured by ion chromatography. Measure-
ment deviation was ±10 %.
Carbonate content was measured by treating dried
sediment (5.0 g) with HCl (3 M; 20 mL), and the
developed CO
was measured volumetrically in a
Scheibler apparatus, calibrated with CaCO
ment deviation was ±15 %.
Organic matter was based on loss of ignition of dried
sediment (2.5 g) being heated at 550
C for an hour.
Measurement deviation was ±10 %.
Total Carbon (TC) and sulfur (S) were measured by
high temperature combustion. Dried sediment (0.5 g)
was combusted (1350
C) converting all carbon and
sulfide into carbon dioxide and sulfur dioxide, respec-
tively. The gasses were passed through scrubber tubes to
remove interferences, and the carbon dioxide and sulfur
dioxide were measured by infrared detector. Measure-
ment deviation was ±5-10 %.
Nitrogen (N) was measured by the Kjeldahl method.
Dried sediment (1.0 g) was heated to 370
(conc., 15 mL) and K
(7 g) until white fumes were
observed (approx. 90 min) and subsequent to cooling
250 mL distilled water was added to the mixture. The
pH of the mixture was raised by adding NaOH (45 %),
and subsequently, the mixture was distilled and the
vapours were trapped in HCl (15 %, 85 mL). The
trapped vapour solution was subsequently titrated with
NaOH (5 M). Measurement deviation was ±10 %.
Cation exchange capacity (CEC) was measured by
extraction with NH
and subsequent cation
exchange with NaCl. Dried sediment (10 g) was agi-
tated with NH
(1 M, pH 7, 30 mL) for
5 min and subsequently centrifuged (2500 rpm,
10 min). The liquid was discarded and the step was
repeated two additional times. Subsequently, the step
was repeated two times using NH
(0.1 M,
30 mL). The sediment was then agitated with NaCl
(10 %, 20 mL) for 5 min and subsequently centrifuged
(2500 rpm, 10 min), and the step repeated three addi-
tional times. The liquids from all four NaCl treatments
were combined and diluted to 200 mL, and ammoni-
um content was measured by flow injection analysis.
Measurement deviation was ±10 %.
pH (KCl). Dried sediment (5.0 g) was agitated with KCl
(1 M, 12.5 mL) for an hour, and the pH was measured
using a radiometric analytical electrode. Measurement
deviation was ±1 %.
Conductivity. Dried sediment (5.0 g) was agitated with
distilled water (25 mL) for an hour, and the conductivity
was measured using a radiometric analytical electrode.
Measurement deviation was ±10 %.
Grain size was measured by wet sieving and dry
sieving. Wet sediment (75 g), distilled water (350 mL)
and Na
O (0.1 M, 10 mL) were agitated for
24 h. The slurry was then sieved through a 63 μmsieve
and the fraction above 63 μm was subsequently dried and
sieved for 15 min in a mechanical shaker using sieves with
screen openings of 0.063, 0.080, 0.125, 0.25, 1.0 and
2.0 mm. The slurry fraction below 63 μm was transferred
to Andreasen pipette for gravitational sedimentation.
Stokes law was used for estimating the time required
for particles to settle 20 cm and samples representing the
Sequential extraction was made in four steps based
on the improvement of the three-step method (Rauret
et al. 1999) described by Standards, Measurements and
Testing Program of the European Union. Air-dried sed-
iment (0.5 g) was first extracted with acetic acid
(0.11 M, 20 mL, pH 3) for 16 h; secondly, extracted
with hydroxylammonium chloride (0.1 M, 20 mL; pH
2) for 16 h; thirdly, extracted with hydrogen peroxide
(8.8 M, 5 mL) for 1 h, followed by extraction at 85
150 Page 4 of 15 Water Air Soil Pollut (2015) 226:150
for 1 h, followed by evaporation of liquid at 85
subsequently the cooled solid fraction was extracted
with ammonium acetate (1 M, 25 mL, pH 2) for 16 h;
and fourthly, digestion according to DS259 on the re-
maining solid particles was made, following the descrip-
tion above. Measurement deviation was ±5-20 %.
2.4 PCA Modelling
In this study, SimcaP11 Software was used for PCA of
the sediment properties and pollutant levels. Since the
values of the descriptors of the sediments varied in
magnitude, the data were logarithmically transformed
and subsequently centred and scaled to unit variance in
the calculated PCA models. The number of significant
components was determined by cross-validation.
3 Results and Discussion
3.1 Pollutant Levels in Harbour Sediments
The concentrations of heavy metals, organic pollutants
and TBT in the studied sediments are given in Tables 2
and 3and are compared to the assessment concentra-
tions (BAC) of OSPAR. The concentrations of all PAH
components and PCB congeners are provided in sup-
plementary material (Table 7). The BACs are based on
statistical calculations in which there is a 90 % proba-
bility that the observed mean concentration will be
below the BAC when the true mean concentration is
equivalent to the background concentration (BC)
(OSPAR 2009). OSPAR recommends using
hydrofluoric acid in metal analysis (digestion) in order
to dissolve all metal in the sediment matrix. Nitric acid,
though not as effective as hydrofluoric acid, was used in
this study due to health, safety and environmental con-
siderations, and the true concentrations may thus be
higher than registered. The BAC values are none the
less used for assessing pollutant levels in the sediments.
The concentrations of As, Cr and Ni are well below
BAC levels in all of the sediments and are assumed to be
equivalent to igneous levels. The concentrations of the
other heavy metals (Cd, Cu, Hg, Pb and Zn) exceed the
BAC levels in some or all of the sediments with up to 17
times the BAC (Fig. 2). Concentrations of the organic
pollutants (PAH, Benzo(a)pyrene (B(a)P), PCB exceed
the BAC levels with up to 500 times for the organics
(Fig. 2) and 1800 times for TBT (Table 3).
The sediment quality criteria of OSPAR do not include
THC, which nonetheless has been included in Table 3
since it is related to the organic pollutants and/or the
organic matter in the sediments. The THC content in all
of the sediments is mainly related to the fraction C
and may be phytogenic rather than petrogenic hydrocar-
bons. The highest level of THC in Hammerfest was found
in sample H4, which was sampled adjacent to the former
sewage discharge point in the harbour (Table 1). Generally,
higher levels of THC were found in Sisimiut with the
highest concentrations found in the sediments sampled
adjacent to the shoreline (points S1, S2 and S3 in Table 1).
Elevated concentrations of PAH and PCB were
observed in all sample points in the two harbours
(Table 3,Fig.2). In Hammerfest, the highest concen-
trations were found in H4 adjacent to the former
sewage outlet. The highest concentrations of organic
Tabl e 2 Heavy metal concentrations in the sediments
Sample As Cd Cr Cu Hg Ni Pb Zn
H_1 6.3±0.8 0.13±0.03 15.2±0.1 116±39 0.31±0.01 9.5±0.4 48.6±3.6 82.8±6.0
H_2 4.0±0.5 0.25±0.14 8.4±0.3 33.1±2.5 0.92±0.02 5.1±0.3 220± 10 64.4± 5.9
H_3 5.0±0.3 0.27±0.04 22.7±0.5 54.3±9.9 0.54±0.01 14.8±0.4 46.3±1.1 140±7.5
H_4 21.0±0.7 1.10±0.14 46.5±11 167±29 1.19± 0.03 23.0± 0.8 152±44 537±72
H_5 5.9±0.4 0.14±0.03 24.3±0.7 46.8±1.3 0.32±0.01 15.3±0.7 41.7±2.4 94.0±6.5
S_1 18.7±0.2 0.54±0.05 37.1±1.2 216±8.9 0.30±0.01 18.3±0.5 72.8±3.7 343±21
S_2 8.5±0.3 0.70±0.09 24.0±1.6 125±3.8 0.10±0.02 13.0±1.4 38.6±4.1 239±12.4
S_3 9.2±0.1 0.38±0.06 25.2±3.7 184±39 0.09±0.01 18.0±6.2 57.1±6.0 957±173
S_4 3.3±0.1 0.09±0.02 10.0±1.3 42.2±4.2 0.01±0.00 6.0±0.5 7.8± 3.3 81.8± 10.1
OSPAR BAC 25.0 0.31 81 27.0 0.07 36.0 38.0 122
Water Air Soil Pollut (2015) 226:150 Page 5 of 15 150
pollutants in Sisimiut harbour were found adjacent to
the former shipyard (S1), the shrimp factory (S3) and
the petrol station (S2).
The concentration of Hg is generally high in Ham-
merfest harbour, especially at H2 (petrol station), H3
(freshwater lake outlet) and H4 (sewage discharge).
The concentrations of Cd, Cu, Pb and Zn are high at
the sewage discharge, which could indicate either
urban origin or that heavy metals have higher affinity
for organic matter. The concentration of Pb is in addi-
tion high in the vicinity of the petrol station (H2),
which might be due to earlier use of leaded gasoline
(Fig. 1). In Sisimiut, the concentrations of heavy
metals are generally low at the marina (S4), while high
levels of Cu were registered in the remaining sampling
points of the harbour and a high concentration of Zn
Tabl e 3 Concentrations of organic pollutants and TBT in the sediments
mg/kg μg/kg
H_1 6.2±1.9 0.50±0.13 0.08±0.02 410±123 1,800±720
H_2 4.6±1.4 0.34±0.09 0.03± 0.01 240±72 290±116
H_3 8.9±2.7 0.66±0.17 0.28± 0.07 380±114 71±28
H_4 70.0±21 4.30±1.1 0.55±0.14 1000±300 110±44
H_5 9.1±2.7 0.71±0.18 0.08±0.02 340±102 32±13
S_1 38.0±11 2.00±0.50 0.18±0.04 2300± 690 590±236
S_2 7.6±2.3 0.52±0.13 0.22± 0.05 1800±540 220±88
S_3 13.0±3.9 0.74±0.19 0.14±0.04 1600±480 160±64
S_4 10.0±3.0 0.55±0.14 0.02±0.003 330± 99 14±5.6
OSPAR BAC 0.36 0.03 0.001 1.0
B(a)P benzo(a)pyrene
Fig. 1 Pollutant concentrations compared to BAC in sediments from Hammerfest (H) and Sisimiut (S)
150 Page 6 of 15 Water Air Soil Pollut (2015) 226:150
was registered at the petrol station. The concentrations
of Cd and Pb in Sisimiut around or slightly elevated
compared to the BACs.
In both harbours, PAH, PCB, TBT, Cu and Zn
exceeded the sediment quality criteria and in Hammer-
fest Cd, Hg and Pb also exceeded the criteria. These
pollutants were hence the focus of this study.
It is worth noting that although POPs and TBT have
been observed in sediments of pristine areas in the
Arctic, the concentrations are much lower than those
registered in this study (Evenset et al. 2007;Evenset
et al. 2004;Harrisetal.2011;Jiaoetal.2009; Strand
et al. 2006; Viglino et al. 2004). The concentrations of
As, Cd, Cr and Ni in the sediments from the two har-
bours are equivalent to those found in remote areas
(Evenset et al. 2007; Lu et al. 2013). The previous
studies found that parts of the metal content originate
from global dispersion; however, levels are not signifi-
cantly higher than background levels (Evenset et al.
2007; Evenset et al. 2004). The concentrations of Cu,
Hg, Pb and Zn observed in remote Arctic areas, al-
though affected by global sources, are lower than con-
centrations of Cu, Hg, Pb and Zn observed in parts of the
harbours. Even though long-range transport of pollut-
ants has occurred to pristine areas in the Arctic, local
sources appear to have had larger impact on pollutant
levels in Hammerfest and Sisimiut harbours.
3.2 Sediment Characteristics
Ranges of the sediment characteristic in the two har-
bours of Hammerfest and Sisimiut are summarised in
Table 4. In general, the ranges in the sediment charac-
teristics are larger in Hammerfest than in Sisimiut,
which is accentuated by the PCA scores plot (Fig. 2)
with a larger dispersion of the Hammerfest sediments.
The two first components in the plot explain 70 % of the
variation in the sediment characteristics. In addition, the
scores plot illustrates that sediments from the same
Tabl e 4 Sediment characteristic
ranges in the sediments from
Hammerfest and Sisimiut
Characteristic Units Hammerfest Sisimiut
Carbonate %0.759 0.79
Organic matter %4.815 2.48.5
TC %3.110 1.15.3
S%0.21.2 0.30.8
N%0.010.5 0.10.5
CEC meq/100 g 2.413 0.74.3
pH 7.08.4 7.08.0
Conductivity mS/cm 7.820 5.610
Grain size
Clay (<2 μm) %4.38.9 0.88.8
Silt (263 μm) 12.238 5.052
Sand (63200 μm) 5477 3890
Gravel (>200 μm) 0.322 0.64.0
Chloride mg/kg 640014,100 57007900
P6453100 7902900
Al 19008700 25006600
Ba 591340 42160
Ca 450017,1000 600014,200
Fe 430018,600 500014,500
K9504400 7402300
Mg 46009000 19006000
Mn 40130 40110
Na 380015,500 25007200
V1580 1570
Water Air Soil Pollut (2015) 226:150 Page 7 of 15 150
harbour do not necessarily exhibit the same variation in
sediment characteristics.
The accompanying loadings plot (Fig. 2)illustrates
which sediment characteristics have strong contribu-
tions to the variations in the scores plot. All parameters
apart from Ba have an influence in the dispersion of the
first component (p1) whilethe strongest contributions to
the second component (p2) is related to grain size, Ca,
carbonate, Mg and C, as they are found far from the
origin in either dimension. The clustering of Al, Fe, K,
Mn, Na and chloride close to organic matter and silt
indicates a relation between these variables. The clus-
tering of Ca and carbonate close to gravel may be related
to shells and corals larger than 2 mm.
3.3 Distribution of Pollutants Related to Sediment
For both harbours loading plots (Fig. 3) show that the
major part of the target pollutants is clustered around
organic matter and/or finer grain sizes (silt/clay). In
Sisimiut, Zn may differ slightly from this trend,
which would be in line with the much higher level
registered adjacent to the petrol station (S3 in Ta-
ble 2). In Hammerfest TBT, Hg and Pb deviate from
the general trend which may be related to pollutant
sources and/or different binding patterns to the sedi-
ment. TBT is known to have higher affinity for or-
ganic matter, accordingly the deviation from this
trend in Hammerfest may be related to specific pol-
lutant sources rather than sediment properties, which
is in line with the highest concentration of TBT being
found adjacent to the former shipyard (H1); the ele-
vated concentrations of TBT in other parts of the
harbour (Table 3) may be due to general boat traffic.
Even though the use of TBT as a biocide in anti-
fouling was completely banned in 2008, TBT can
remain in eco-systems for many years; hence remain-
ing an environmental issue for the aquatic environ-
ment of harbours for many years to come.
Fig. 2 PCA score and loading
plot of sediment characteristics
150 Page 8 of 15 Water Air Soil Pollut (2015) 226:150
The loading plot for Hammerfest implies that PAH is
related to the organic matter in the sediments, and the
pollutant levels (Fig. 1) further support a point sourceof
PAH which may be related to sewage discharge (H4). In
Sisimiut, the same trend is not apparent, which may
indicate that the PAH pollution origins from several
diffuse sources such as harbour activities, urban run-
off, and to a lesser extent from long-range atmospheric
transportation. In both harbours, PCB is not closely
related to the content of organic matter indicating that
the PCB pollution in the sediments may be due to
several point sources as well as diffuse sources such as
urban run-off and to a lesser degree long-range atmo-
spheric transportation. A point source in Hammerfest
may be Storvatn, in which high levels of PCB have
previously been found in the sediments (Akvaplan-Niva
2008); high PCB levels were found adjacent to the
freshwater outlet in the harbour (H3 in Table 3).
In this study, the binding of heavy metals in the
sediments was assessed by determining the metal
partitioning by sequential extraction of the exchange-
able (including carbonates), reducible, oxidisable and
residual fractions. In order to investigate the possible
correlations between the heavy metals in each sedi-
ment fraction, PCAs were conducted applying the
metal/heavy metal concentrations in each fraction and
relevant sediment characteristics. Carbonate and CEC
were included in the exchangeable fraction and the
organic matter, TC, S and N were included in the
oxidisable fractions. The loading plots of metal con-
centrations in each fraction (not shown) did not reveal
any correlations between sediment characteristics and
metal concentrations, apart from carbonate and Ca and
to a lesser extent Mg.
Plotting of the different metal concentrations
against each other for each sediment fraction showed
correlations between some of the metals. Metals
which were correlated were different in the two har-
bours as well as in the different fractions and were
related to the mineral composition. It is interesting to
a b
Fig. 3 PCA score and accompanying loading plots of sediment characteristics and pollutant levels in Hammerfest (aand b) and Sisimiut (c
and d)
Water Air Soil Pollut (2015) 226:150 Page 9 of 15 150
note that for both harbours correlations between Al,
Fe, K, Mg, Mn, Cr and Ni were found as exemplified
by Al-Ni correlation in the Hammerfest sediments
(Fig. 4). In addition, no correlations between major
elements and Cd, Cu, Hg, Pb and Zn were found
indicating different binding patterns in the sediment
implying that besides igneous content, these heavy
metals may also stem from anthropogenic sources.
This is also in line with the high concentrations found
in the sediments (Fig. 2). Based on PCA alone, it is
however not possible to evaluate the potential pollut-
ant sources. The environmental investigations howev-
er indicated that heavy metal pollution in both har-
bours is related to diffuse sources from both land-
and sea-based activities.
3.4 Distribution of PAH
The preliminary assessment of the PAH pollution in the
sediment indicated a point source in Hammerfest and
several, diffuse sources in Sisimiut. The ratios of the
selected PAH components have been widely used to
identify pollution sources in sediments (Countway et al.
2003;Fengetal.2014; Soclo et al. 2000; Yunker et al.
2002). In cases of mixed PAH pollution derived from
diffuse sources, the PAH ratios can be used for evaluat-
ing predominant sources, if such exist. The PAH ratio
antracene/(anthracene/phenantrene) has previously
been used as an indication for petrogenic (<0.1) and
pyrogenic (>0.1) sources (Soclo et al. 2000); the sedi-
ments from Hammerfest and Sisimiut all have values
above0.1 indicatingpyrogenic source(s) of PAHpollu-
tion (Table 5). The PAH ratios fluoranthene/(fluoran-
thene+pyrene) and indeno(123-cd)pyrene/
(indeno(1,2,3-cd)pyrene+ benzo(ghi)perylene) can in
addition indicate whether pyrogenic sources originate
from liquid fossil fuel combustion (0.4-0.5/0.2-0.5) or
coal/biomass combustion (>0.5/>0.5) (Feng et al.
2014). Calculations of these ratios (Table 5)giveam-
biguous results with no clear indication of combustion
sources,whichcouldbe due tomixed pollution sources,
for instance combustion from incineration plants and
fuel combustion from vehicles/vessels. It appears that
the PAH pollution in Sisimiut stems from mixed com-
bustion sources to a larger extent than in Hammerfest
Fig. 4 Correlation between the Al and Ni concentrations in the following fractions of the sediment: aexchangeable; breducible; c
oxidisable and dresidual
150 Page 10 of 15 Water Air Soil Pollut (2015) 226:150
To further assess the possible PAH sources, PAH ratios
of petrogenic and combustion sources based on data from
(Yunker et al. 2002) were compared to the PAH ratios of
the sediments (Fig. 5). The plot of the fluoranthene/(fluo-
ranthene+pyrene) ratio versus the indeno(123-cd)pyrene/
(indeno(1,2,3-cd)pyrene+ benzo(ghi)perylene) ratio indi-
cates that sources of the PAH pollution in the sediments of
both Hammerfest and Sisimiut are combustion of coal/
biomass rather than liquid fossil fuels.
According to Statistics Norway, the main sources of
PAH air emissions in 2012 were aluminium industry
(50 %), fuelwood (23 %) and traffic (15 %) (SSB2014),
and since the production of aluminium does not take
place in Hammerfest, it is not unlikely that the biggest
source of PAH pollution is from the combustion of
wood, and may partly include components from the
burning of Hammerfest town in 1944. In Sisimiut, the
pyrogenic sources may stem from present and past
incineration of waste and combustion of fuel from ve-
hicles or household heating by oil boilers.
3.5 Distribution of PCB
The preliminary assessment of the PCB pollution in
both harbours indicated diffuse sources such as urban
run-off and/or long range atmospheric transport. PCB is
expected to constitute part of the waste cycle for years to
come since PCB is still present in products and mate-
rials; e.g. cable insulation, thermal insulation materials,
paint, plastics, transformers, hydraulic oil; produced
before the production and use of PCB was prohibited
on a global scale more than 10 years ago. In addition,
several studies have revealed inadvertent production of
PCB congeners in the manufacturing of paint pigments
(Anezaki and Nakano 2014; Guo et al. 2014;Huand
Hornbuckle 2009; Shang et al. 2014).
In this study, seven of the 209 PCB congeners were
analysed (Table 6). Since the seven analysed PCB con-
geners in this study represent tri- (28), tetra- (52), penta-
(101, 118), hexa- (138,153) and hepta- (180)
chlorobiphenyls, the composition of these congeners
may reveal difference in the diffusive sources of PCB
pollution in the sediments. The PCA score plot of the
variation in the seven congeners of the sediments in
Hammerfest and Sisimiut (Fig. 6) reveals that H4 and
S4 stand out compared to the clustering of the sediments
Tabl e 5 PAH ratios of Hammerfest and Sisimiut sediments
An/(An+Phe) (Fl/Fl+ Py) Ip/(Ip+Bghip)
Ratio Source Ratio Combustion Ratio Combustion
H1 0.23 Pyrogenic 0.55 Coal/biomass 0.46 Fuel
H2 0.21 Pyrogenic 0.56 Coal/biomass 0.47 Fuel
H3 0.30 Pyrogenic 0.52 Coal/biomass 0.45 Fuel
H4 0.29 Pyrogenic 0.57 Coal/biomass 0.45 Fuel
H5 0.24 Pyrogenic 0.56 Coal/biomass 0.43 Fuel
S1 0.23 Pyrogenic 0.59 Coal/biomass 0.50 Coal/biomass
S2 0.21 Pyrogenic 0.58 Coal/biomass 0.49 Fuel
S3 0.24 Pyrogenic 0.61 Coal/biomass 0.52 Coal/biomass
S4 0.26 Pyrogenic 0.61 Coal/biomass 0.52 Coal/biomass
An anthracene; Phe Phenantrene; Fl fluoranthene; Py pyrene; Ip ideno(1,2,3-cd)pyrene; Bghip Benzo(ghi)perylene
Fig. 5 Comparison of PAH ratios of petrogenic and pyrogenic
sources; and the studied sediments. Petrogenic and pyrogenic PAH
ratio data from Yunker et al. 2002
Water Air Soil Pollut (2015) 226:150 Page 11 of 15 150
Fig. 6 PCA score plot of seven
PCB congeners in the
Hammerfest and Sisimiut
Tabl e 6 Composition of seven
PCB congeners in the harbour
sediments as well as in Aroclor,
Clophen, Svovol and Kanechlor
PCB mixtures calculated as per-
centage of the total PCB7, based
on data from (Hop et al. 2001;
Takasuga et al. 2005;USDepart-
ment of Health and Human
Services 2000)
AC Aroclor; KC Kanechlor
PCB mixture PCB28 PCB52 PCB101 PCB118 PCB138 PCB153 PCB180
H1 1 12 11 9 30 24 13
H2 1 12 10 6 29 26 16
H3 039 5312922
H4 159 5322918
H5 1138 7312614
S1 01619152718 6
S2 01021202518 5
S3 0172015211710
S4 32719191513 4
AC1016 65 35 0 0 0 0 0
AC1242 58 30 6 6 1 1 0
AC1248A 23 44 14 15 2 2 0
AC1248B 34 34 12 14 3 2 1
AC1254A 0 3 19 48 21 6 1
AC1254A 1 19 25 23 18 12 2
AC1260 0 1 10 2 21 29 37
Clophen A50 0 19 22 29 15 14 1
Clophen A60 0 3 13 8 28 29 19
Sovol 0 2 23 27 27 16 5
KC400 22 42 16 12 4 3 0
KC500 1 13 26 19 23 17 1
KC1000 1 13 27 18 22 17 1
KC600 1 2 10 2 20 39 26
150 Page 12 of 15 Water Air Soil Pollut (2015) 226:150
with respect to the specific harbour. S4 has PCB pollu-
tion level a magnitude lower than registered in the other
Sisimiut sediments. The ratio of PCB180/PCB28 is
approximately 1 for S4 and 2430 for the other sedi-
ments in Sisimiut indicating lower relative content of the
more highly chlorinated biphenyls.
As was the case with PAH, H4 displays different
variation in the composition of PCB indicating different
sources or sediment binding/degradation than for the
other sediments in Hammerfest. The preliminary assess-
ment revealed that there was not a clear relation between
organic matter and PCB, which could indicate that PCB
is dispersed differently than PAH, and there may be
additional sources to sewage discharge at H4. Disper-
sion from Storvatn could be a source, which would
explain that H3 (Storvatn outlet) is situated closer to
H4 in the PCA plot than the other sediments.
The commercially produced PCB mixtures contained
different compositions of PCB congeners according to
their use. The PCA has been used in several studies for
comparing specific PCB mixture compositions with
observed PCB pollution in sediments to assess which
commercial mixture(s) the PCB pollution may originate
from (Hartmann et al. 2004; Zhang et al. 2007). In this
study, the seven analysed PCB congeners in the nine
sediments were compared to the composition of the
following PCB mixtures (Table 6): Kanechlor
(manufactured in Japan), Aroclor (US, UK), Clophen
(Germany) and Svovol (Russia).
The PCA score plot of the commercial PCB mixtures
and the harbour sediments indicate that the PCB pollu-
tion in Hammerfest is mainly related to Clophen A60
and Sovol (Fig. 7). This is in line with a study of 64 PCB
congeners in Storvatn, in which the major part of the
PCB pollution (approximately 82 %) was found to be
related to Clophen A60, Aroclor 1254, Aroclor 1260
and Sovol (Akvaplan-Niva 2008). This further implies
that applying the seven PCB congeners in this study can
be used in PCA for qualitative indications of PCB
mixture sources. The PCB pollution in Sisimiut is clus-
tered in a different part of the PCA score plot (Fig. 7)
and appears to be related to Kanechlor 500, Kanechlor
1000, Sovol and Aroclor 1254. Whether the relation to
the Kanechlor and Sovol mixtures is due to long-range
atmospheric or local emissions of products
manufactured with the Russian/Japanese mixtures is
not clear and further analysis to confirm/rule out such
indications entails analysis of more PCB congeners.
4 Conclusion
The preliminary PCA assessment based on concentra-
tions of heavy metals, PAH, PCB and TBT and respec-
tively the sediment characteristics indicated different
sources and pollutant distribution in the two harbours.
One exception was TBT which was not found to be
related to sediment characteristics, indicating point
sources resulting in locally high TBT concentrations.
In both harbours, TBT concentrations were highest; up
to 1800 times the non-polluted level; in sediments adja-
cent to the former shipyards.
The in depth PAH, source analyses were based on
both a PAH ratio assessment and PCA and indicated that
Fig. 7 PCA score plot of the
seven PCB congeners of the
Hammerfest and Sisimiut
sediments compared to
commercial PCB mixtures
Water Air Soil Pollut (2015) 226:150 Page 13 of 15 150
the predominant source of PAH pollution in both har-
bours was pyrogenic coal/biomass. This was in line with
the second largest PAH air emissions in Norway being
related to wood combustion. PCA of PAH composition
indicated that the PAH pollution in the two harbours
may origin from diffuse as well as point sources such as
sewage discharge.
The PCB composition (seven congeners) in the sed-
iments was compared to commercial PCB mixtures in a
PCA plot. The PCB pollution in Hammerfest was found
to mainly be correlated to European, Russian and Amer-
ican manufacturers, while the PCB pollution in Sisimiut
was related to other PCB mixtures manufactured in the
US, Russia and Japan. PCA of the PCB congeners in the
sediments indicated several diffuse sources of pollution.
Although long-range transport of POPs, TBT and
metals has previously been established, the concentration
levels of pollutants in this study were higher than those
reported in pristine areas of the Arctic, indicating that
local sources were more significant than global sources.
The study showed that PCA can be used as an im-
portant tool, along with pollutant levels and mapping of
potential sources, for identifying pollutant sources and
differences in pollutant composition in relation to sedi-
ment characteristics.
Acknowledgments The Northern Environmental Waste Man-
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Council of Norway through NORDSATSNING (grant number
195160) and Eni Norge AS, is acknowledged for funding. Ham-
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assistance in sampling of sediments in Hammerfest. Tore Lejon
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The present study employed epiphytic lichens as biomonitor and passive air sampler for the assessment of fifteen (15) atmospheric polycyclic aromatic hydrocarbons (PAHs) in some major cities in three regions of Ghana. A total of 36 composite lichen samples were collected and analysed using Gas Chromatography - Tandem Mass Spectrometry (GC-MS-MS). The total PAH recorded ranged between 1909.9 ng/kg (A36) and 250091.4 ng/kg (W15). Due to the inherent deficiencies in using a single source apportionment tool, multiple source apportionment methods including diagnostic ratios, principal component analysis/absolute principal component scores (PCA-APCS) and APCS with automatic linear model (APCS–ALM) were used to ascertain the source of PAHs in the lichens. The diagnostic ratios revealed a mix source of wood/grass and petrol/petroleum fuel combustion, with the major source ascribing to wood/grass combustion. The source apportionment confirmatory statistical test conducted with the PCA-APCS and APCS–ALM, were in good agreement with the diagnostic ratio. Both PCA-APCS and APCS–ALM suggested two significant sources (p<0.0), with wood/grass combustion as the major (contributing 77.8%) and mix petroleum related sources being the other with 22.2% contribution of PAHs to the receptor sites. The study found PCA-APCS and especially APCS–ALM to be an effective statistical tool for PAH source apportionment in passive air samplers. To our knowledge, this is the first use of lichens for PAH monitoring in the country. Therefore, this study could serve as an inexpensive and real time bio-monitoring tool for air quality assessment in the African sub-region and the world at large.
... In the present work, we coupled different multivariate techniques aiming at identifying the differences and similarities between clusters hidden in the generated datasets, extracting principal components (new variance descriptors) able to simplify the systematic variation of original dataset without loss of information (Wang et al. 2009;Pedersen et al. 2015;Mali et al. 2017a). ...
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The Gulf of Naples located in a high anthropized coastal area is subjected to an infrastructural intervention for the installation of a submarine power pipeline. In order to evaluate the distribution of contaminants in the seafloor sediments, a preliminary study has been conducted in the area using multivariate techniques. The statistic approach was performed to gain insights on the occurrence of organic and inorganic contaminants within the area, aiming to identify the relevant hot spots. Three geographical sub-areas influenced by different contaminant association were recognized: Torre Annunziata (TA), Capri (CA), and middle offshore (MO). TA and CA resulted marked by a severe contamination pattern due to anthropogenic pressures. In addition, the influence of the depositional basin in governing the contamination trend has been pointed out. The supervised technique PLS_DA resulted to be a powerful tool in addressing the complexity of the huge dataset acquired during the marine survey, highlighting the main trends in the variability of quality indicators, orienting thus the deeper investigations during follow-up monitoring activities.
... Where the abbreviated names have the same meaning as there are in Table 2. automatic linear regression (APCA-MALR) modelling were conducted with IBMS SPSS Vs 22.0 software. APCA-MLR receptor model for source apportionment has been successfully employed in literature Pedersen et al., 2015;Jiang et al., 2015;Gholizadeh et al., 2016;Adjei et al., 2019;Chen et al., 2019;Chen et al., 2020;Li et al., 2020;Han et al., 2021). The source apportionment was further ascertained by the APCAmultiple automatic linear regression (APCA-MALR) modelling which helped predict the influence of each predictor variable on the factor components obtained from the APCA in pictorial forms. ...
The presence of U.S. EPA priority organic contaminants in drinking water poses a dire health risk on consumers. Packaged drinking water such as plastic sachet drinking water has significantly gained market in both developed and developing countries, especially, its dominance in the Ghanaian market. The treatment process, packaging, and storage of the sachet drinking water contribute to the levels of genotoxic semi-volatile phenols, p-chloroaniline, and plasticizers contamination in the drinking water. The study thus sought to investigate the levels of semi-volatile phenols, p-chloroaniline, and plasticizer contaminants in sachet drinking water on the Ghanaian market and the associated health risk of exposure. The study also investigated the possible sources of the contaminants. A total of thirty (30) different brands of sachet water on the Ghanaian market were studied. The samples were extracted in replicates (n = 3) using Solid Phase Extraction (SPE) cartridges and further analysed with GC–MS (SIM mode). The source apportionment was conducted using absolute principal component analysis coupled with multiple, linear regression (APCA-MLR) and automatic linear regression (APCA-MALR) modelling. The mean total levels for the phenols, p-chloroaniline, and plasticizers were between 210.2 and 18,914.9, 11.2 and 18,871.0, and 21.2 and 69,834.1 ng/L respectively. The cumulative non-cancer risk (hazard quotient) and cancer risk upon exposure were computed to range between 2.1 × 10⁻³ and 1.2 and 1.5 × 10⁻⁷ and 1.3 × 10⁻⁴ respectively. About 37% of the samples had elevated cancer risk (>10⁻⁶) which may contribute to the existing incidence, cause for concern. The five sources found for the contaminants were apportioned as “environmental background (major)”, “water treatment/disinfectant”, “plastic/plasticizers”, “storage and preservation”, and “residual inter-conversion/degradation sources”.
... Sprovieri et al. (2007) found that surface sediments in Naples Harbor (Italy) were contaminated with metals (N3-time enrichment), PAHs (dominated by 3-5 rings and NNOAA ERM), and PCBs (dominated by tetra-and penta-chlorobiphenyls and high toxic level). Besides metals, PAHs, and PCBs were contaminated in two Arctic ports, Hammerfest in Norway and Sisimiut in Greenland, Pedersen et al. (2015) further identified that tributyltin (an antifouling biocide) was contaminated in sediments of the two ports by point sources, the former shipyards, up to 1800 times greater than the non-polluted sites. Furthermore, they apportioned sedimentary PAHs deriving from pyrogenic coal/biomass combustion, and sedimentary PCBs from European, Russian, and American manufacturers in the Hammerfest port and from US, Russia, and Japan in the Sisimiut port. ...
... Principal component analysis with multiple linear regression (PCA-MLR) have been successfully employed for source apportionment in environmental studies [66][67][68]. The PCA-MLR were conducted to help apportion likely sources for PAHs, phthalates, 2-chloronaphthalene and SVCOCs in the toilet tissue papers. ...
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The presence of phthalates, polycyclic aromatic hydrocarbons (PAHs) and semi-volatile chlorinated organic compounds (SVCOC) in toilet tissue papers may be detrimental to the health of consumers upon exposure. This study therefore, sought to investigate the levels of these toxicants in toilet tissue papers on the Ghanaian market and the associated risk of exposure. The study also sought to conduct source apportionments for analytes. A total of 32 composite toilet tissue samples from 8 different brands were analysed in replicates for PAHs, phthalates and SVCOCs. Analysis was conducted using Shimadzu GCMS QP 2020 with the MS operated in SIM mode. The results showed elevated levels of PAHs, phthalates, and appreciable levels of SVCOCs in the toilets tissue papers. The risk assessment conducted, showed an associated elevated cancer risk >10-4 for PAHs in all samples and DEHP in samples NN, BB and SF. The risk associated with the levels of carcinogenic SVCOCs were found to be > 10-5 but < 10-4.The hazard indices (HI) calculated for non-cancer effects, showed risk levels < 1.0 for phthalates in most toilet paper samples except for samples BB and SF. The HI recorded for chlorophenols were all <1. Cumulatively, these values suggested elevated cancer and non-cancer risk associated with the dermal use of the toilet tissue papers on the Ghanaian market. The PCA-MLR source apportionment suggested two significant sources of SVOCs in the toilet tissue papers. PAHs, phthalates and 2-chloronaphthalene were of one source (oil base source) whereas SVCOCs were of another source (bleaching process).
... Hence, the prevalent KC 500 and KC 600 could have been released from vessels that frequently landed at the port. In KC 600, the contribution of PCB 153 was almost twice the one of PCB 138 (Pedersen et al., 2015;Takasuga et al., 2005). In our study, site A was the closest to Port Elizabeth and also inside Jeffreys Bay (Fig. 2), a semi-closed location determined its weaker tidal current compared to the wide-open site C and site B. This could be one reason why PCB 153 was more abundant than PCB 138 in samples from site A. Yet, higher concentrations of PCB 138 at sites B and C were unusual and could not be explained. ...
Chokka squid (Loligo reynaudii) from three sites along the South African coast were analyzed for halogenated natural products (HNPs) and anthropogenic persistent organic pollutants (POPs). HNPs were generally more than one order of magnitude more abundant than POPs. The most prevalent pollutant, i.e. the HNP 2,3,3',4,4',5,5'-heptachloro-1'-methyl-1,2'-bipyrrole (Q1), was detected in all chokka squid samples with mean concentrations of 105, 98 and 45 ng/g lipid mass, respectively, at the Indian Ocean (site A), between both oceans (site B) and the South Atlantic Ocean (site C). In addition, bromine containing polyhalogenated 1'-methyl-1,2'-bipyrroles (PMBPs), 2,4,6-tribromophenol (2,4,6-TBP, up to 28 ng/g lipid mass), polybrominated methoxy diphenyl ethers, MHC-1, TBMP and other HNPs were also detected. Polychlorinated biphenyls (PCBs) were the predominant class of anthropogenic POPs. PCB 153 was the most abundant PCB congener in chokka squid from the Indian Ocean, and PCB 138 in samples from the South Atlantic Ocean and between both oceans.
While the coastal pollution of persistent toxic substances (PTSs) has been widely documented, information on offshore environments remains limited. Here, we investigated the spatial distribution and sources of PTSs in the offshore sediments (n = 34) of South Korea. Sediment samples collected from the Yellow Sea (n = 18), the South Sea (n = 10), and the East Sea (n = 6), in 2017–18 were analyzed for a total of 71 PTSs. Target compounds include 31 PCBs, 15 PAHs, 9 emerging PAHs (e-PAHs), 10 styrene oligomers (SOs), and 6 alkylphenols (APs). Sedimentary PCBs showed relatively low concentrations with no significant difference across the three seas (0.16–6.9 ng g⁻¹ normalized organic carbon, OC). Low-chlorinated PCBs (tri- and tetra Cl-CBs) were predominant (mean: 77%), primarily indicating atmospheric inputs. PAHs widely accumulated in the three seas with low to moderate level (22–250 ng g⁻¹ OC), and dominated by high molecular weight PAHs (4–6 rings). PMF analysis revealed coast-specific PAHs sources; i.e., originated from mainly coke production (77%) in the Yellow Sea, vehicle emissions (68%) in the South Sea, and fossil fuel combustion (49%) in the East Sea. SOs showed significant contamination than other PTSs, with elevated concentrations in the Yellow Sea (mean: 350 ng g⁻¹ OC). APs showed a similar regional distribution to SOs, but concentrations were much lower (mean: 17 ng g⁻¹ OC). SOs and APs seemed to be introduced from rivers and estuaries on the west coast of Korea, where industrial and municipal activities are concentrated, then might be transported to offshore through tide or currents. Overall, the novel data presented for various PTSs in offshore Korean sediments warrant the necessity of a long-term monitoring effort and urgent management practice to protect marine ecosystem.
Maritime activities in the subarctic and Arctic Ocean are predicted to substantially increase in the future due to climate change and declining sea ice cover. Inevitably, the consequences will be seen in impacts on marine ecosystems in this region at many different levels, such as increased pollution load due to antifouling biocides, polycyclic aromatic hydrocarbons, metals and pharmaceuticals. Here we discuss the current situation and evaluate the effect of increased shipping on the environmental status of subarctic and Arctic waters, in relation to elevated loads of both legacy and emerging pollutants in the region. It is of high importance to evaluate the current levels of selected pollutants, which will most likely rise in near future. Furthermore, it is important to improve our understanding of the effects of these pollutants on marine organisms at high latitudes, as the pollutants may behave differently in cold environments compared to organisms at lower latitudes, due to dissimilar physiological responses and adaptations of the cold-water organisms. Integrative studies are needed to better understand the impact of pollutants on the marine fauna while monitoring programmes and research should be continued, with an increased capacity for emerging pollutants of concern.
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High concentrations of Cu of up to 200 mg/kg, and Cd of up to 4.0 mg/kg, were found in sediments from the aquatic environment around Sisimiut, Greenland. These concentrations are four times higher than the limiting concentration where toxicological effects are expected. The pollution could be linked to human activities in Sisimiut, a link that have not been investigated previously in Greenland. Except from the most polluted samples there was good correlation between heavy metal concentration and organic matter. Also some relationship between fine fraction and heavy metal concentration was observed.
The non-Aroclor congener 3,3'-dichlorobiphenyl (PCB 11) has been recently detected in air, water, sediment, and biota. It has been known since at least the 1970s that this congener is produced inadvertently during the production of certain organic pigments. PCB 11 was previously measured at parts-per-billion (ppb) levels in various printed materials obtained in the US. In this work, PCB 11 was detected in samples of common consumer goods including magazines, advertisements, maps, postcards, brochures, napkins, and garments from 26 countries in five continents at concentrations ranging from 0.27 to 86 ppb. Leaching tests confirmed that PCB 11 could be released from these materials into water. We also examined whether the known sources of PCB 11 were large enough to account for the levels of PCB 11 measured in the air, water, soil and sediment of the Delaware River Basin. A mass flow analysis suggests that the outflows and sequestration of PCB 11 in the basin total between 30 and 280 kg y-1. If PCB 11 concentrations in pigments were at the maximum average (125 ppm) allowed under the Toxic Substances Control Act (TSCA), the estimated input of PCB 11 to the Delaware River Basin would be on the order of 42 kg y-1. Despite the large uncertainty in these numbers, the results suggest that pigments may plausibly account for the levels of PCB 11 measured in the environment.
In this work, principal component analysis/multiple linear regression (PCA/MLR), positive matrix factorization (PMF), and UNMIX model were employed to apportion potential sources of polycyclic aromatic hydrocarbons (PAHs) in surface sediments from middle and lower reaches of the Yellow River, based on the measured PAHs concentrations in sediments collected from 22 sites in November 2005. The results suggested that pyrogenic sources were major sources of PAHs. Further analysis indicated that source contributions of PAHs compared well among PCA/MLR, PMF, and UNMIX. Vehicles contributed 25.1-36.7 %, coal 34.0-41.6 %, and biomass burning and coke oven 29.2-33.2 % of the total PAHs, respectively. Coal combustion and traffic-related pollution contributed approximately 70 % of anthropogenic PAHs to sediments, which demonstrated that energy consumption was a predominant factor of PAH pollution in middle and lower reaches of the Yellow River. In addition, the distributions of contribution for each identified source category were studied, which showed similar distributed patterns for each source category among the sampling sites.
A non-Aroclor PCB congener, 3,3'-dichlorobiphenyl (PCB 11) has recently attracted wide concerns because of its environmental ubiquity and specific sources potentially associated with yellow pigment production. In order to investigate PCB 11 and other PCBs in the yellow pigment products, 24 yellow pigment samples were collected from three different manufacturing plants in China. ∑20PCBs and PCB 11 were in the range of 50.7-9.19×10(5)ngg(-1) and 41.7-9.18×10(5)ngg(-1), respectively, which was much higher than those reported in previous study. The corresponding TEQ values ranged between 0.16 and 4.21×10(3)ng WHO2005-TEQkg(-1). The contribution of PCB 11 to ∑20PCBs reached up to 85.5% (median value) followed by PCB 28, PCB 77, and PCB 52 with contributions of 10.5%, 6.70%, and 5.40%, respectively. Significant differences were observed for PCB 11 concentrations among the different types of yellow pigment from the same plant and among the same sample types from different plants. The PCB 11 concentrations in diarylide yellow pigments produced from 3,3'-dichlorbenzidine were the highest in all the samples. It demonstrates that yellow pigment is a significant source not only for the widespread pollution of PCB 11 but also for other PCBs, especially for the lower chlorinated congeners.
The concentration levels and congener profiles of polychlorinated biphenyls (PCBs), pentachlorobenzene (PeCBz), and hexachlorobenzene (HxCBz) were assessed in commercially available organic pigments. Among the azo-type pigments tested, PCB-11, which is synthesized from 3,3'-dichlorobendizine, and PCB-52, which is synthesized from 2,2',5,5'-tetrachlorobendizine, were the major congeners detected. It is speculated that these were byproducts of chlorobendizine, which has a very similar structure. The total PCB concentrations in this type of pigment ranged from 0.0070 to 740 mg/kg. Among the phthalocyanine-type pigments, highly chlorinated PCBs, mainly composed of PCB-209, PeCBz, and HxCBz were detected. Their concentration levels ranged from 0.011 to 2.5 mg/kg, 0.0035 to 8.4 mg/kg, and 0.027 to 75 mg/kg, respectively. It is suggested that PeCBz and HxCBz were formed as byproducts and converted into PCBs at the time of synthesizing the phthalocyanine green. For the polycyclic-type pigments that were assessed, a distinctive PCB congener profile was detected that suggested an impact of their raw materials and the organic solvent used in the pigment synthesis. PCB pollution from PCB-11, PCB-52, and PCB-209 pigments is of particular concern; therefore, the monthly variations in atmospheric concentrations of these pollutants were measured in an urban area (Sapporo city) and an industrial area (Muroran city). The study detected a certain level of PCB-11, which is not included in PCB technical mixtures, and revealed continuing PCB pollution originating from pigments in the ambient air.
Surface water samples were collected along the salinity gradient of the York River, VA Estuary, between June 1998 and April 1999, to examine spatial and temporal variability in particulate polycyclic aromatic hydrocarbon (PAH) concentrations and their interactions with suspended particulate organic matter (POM). Specifically, relationships with source-specific lipid biomarker compounds (sterols and fatty acids) were examined to assess PAH associations with POM and to help elucidate PAH sources and modes of entry into the estuary. Principal component analysis (PCA) revealed that PAHs in the estuary can be classified into three groups: volatile, soot-associated and perylene. The three PAH groups differed in their relationships with particulate organic carbon (POC) as well as with source-specific lipid biomarkers reflecting processes controlling their delivery to the estuary. The more volatile PAHs showed a strong positive correlation with biomarkers for autochthonous (i.e. plankton-derived) POM, but only weak correlations with total POC in spring/early summer. In contrast, all PAHs except perylene were correlated with sterols of vascular plant/freshwater microalgal origin (i.e. allochthonous) during fall/winter. Perylene concentrations decreased from the head to the mouth of the estuary and were correlated with terrestrial biomarkers, suggesting that the freshwater end-member is the dominant source of perylene to this system. The varying relationships between distinct groups of PAHs and lipid biomarkers indicate that very specific pools of POM play an important role in the fate and transport of hydrophobic organic contaminants.
The surface sediment samples taken from 30 sites of the Yangtze Estuary in both the flood and dry seasons were analyzed to reveal the spatial and seasonal distributions of polychlorinated biphenyls (PCBs). Samples collected in the flood season showed higher PCB concentrations, larger PCB fluctuations and higher portions of large grain sediments in the inner estuary area compared with those collected in the dry season, indicating significant seasonal variations of PCBs. The effects of the physicochemical characteristics (TOC and grain size) of surface sediments on the distributions of PCBs were also investigated. Masked by various other factors, the TOC contents and sediment grain sizes did not exhibit a strong influence on the distributions of PCBs. Analysis of the PCB homolog and congener distribution patterns revealed a predominant proportion of light PCBs with 2-3 chlorines. According to the PCB homolog profiles and principal component analysis (PCA) of source contributions, non-point sources including atmospheric deposition and surface runoff associated with stormwater were suggested to be the major sources of PCBs in the surface sediments of the Yangtze Estuary.
Trace metal contents (Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb and Zn) have been measured in 27 surface sediment samples collected from Kongsfjorden, Svalbard, Norwegian Arctic. The analyses yielded concentration values (in mg kg(-1)) of 0.13-0.63 for Cd, 11.89-21.90 for Co, 48.65-81.84 for Cr, 21.26-36.60 for Cu, 299.59-683.48 for Mn, 22.43-35.39 for Ni, 10.68-36.59 for Pb, 50.28-199.07 for Zn and 8.09-65.34 for Hg (in ng g(-1)), respectively. Relative cumulative frequency method has been used to define the baseline values of these metals, which (in mg kg(-1)) were 0.14 for Cd, 13.56 for Co, 57.86 for Cr, 25.14 for Cu, 364.08 for Mn, 26.22 for Ni, 17.46 for Pb, 70.49 for Zn and 9.76 for Hg (in ng g(-1)), respectively. The enrichment factor analysis indicated that Hg showed some extent of anthropogenic pollution, while Pb, Zn and Cd showed limited anthropogenic contamination in the study areas.
This study identified sources of mercury (Hg) in downtown Toronto, Canada by analyzing gaseous elemental mercury (GEM), mercury associated with particles with sizes less than 2.5 microns (PHg < 2.5), and gaseous oxidized inorganic mercury (GOIM), commonly referred to as reactive gaseous mercury (RGM), and air pollutants (CO, NOx, O3, PM2.5, SO2) concentrations between Dec 2003 and Nov 2004. The data were analyzed using Positive Matrix Factorization (PMF) model, Principal Components Analysis (PCA), ratio analysis, back trajectories, and correlation analyses. The analyses suggest industrial sources (chemical production, metal production, sewage treatment), rather than coal combustion, were the major contributors to measured Hg levels. Overlap in source profiles for the Hg sources listed in the Canadian National Pollutant Release Inventory (NPRI) and lack of source profiles for urban sources were the major limitations to positively identifying sources from the PMF and PCA factors. Correlation analyses revealed direct emissions were the sources of GOIM in spring, summer, and fall, and the occurrence of GEM oxidation by ozone in the summer. Elevated Hg events are attributed to emissions from urban sources near the sampling site, regional point sources, and photochemical processes involving ozone.
Polycyclic Aromatic Hydrocarbons (PAHs) were identified and quantified in recent sediments of the Cotonou coastal zones (Benin) in the total concentration range 25–1450 ng g−1, while the Aquitaine sediment samples (France) exhibited total PAH concentrations in the range 4–855 ng g−1. The highest contents of PAHs were found in the harbours, as well in Cotonou as in the Aquitaine region, with the maximum values in the Cotonou harbour. However, the PAH concentrations were comparable with those of slightly contaminated zones. Good correlations observed between a certain number of pairs of isomer PAH concentrations allowed to identify six origin molecular indices that were used to identify the PAH contamination sources in the studied sampling stations: Phe/An, Flt/Py, Chry/BaA, LMW/HMW, Per/∑(PAH), and Per/∑(penta-aromatics). In general, the Cotonou lagoon sampling sites were contaminated mainly by petrogenic PAHs, due to petroleum trade at individual scale along the lagoon, and also waste oils from mechanics shops; the Aquitaine samples were polluted by pyrolytic origin PAHs. Interferences of rather petrogenic and pyrolytic PAH contaminations were noticed in the harbours due to petroleum products deliveries and fuel combustion emissions from the ships staying alongside the quays. Diagenetic origin of perylene was confirmed in this study, but its possible formation by combustion of organic matter was also considered because of the relatively higher concentrations of this PAH in the harbours of Cotonou and of Aquitaine region sediment samples.