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OCEANOLOGIA
ORIGINAL RESEARCH ARTICLE
Distribution of metals and extent of contamination in sediments from the south-eastern Baltic Sea (Lithuanian zone)
Nijolé Remeikaité-Nikiené a,b,*; Galina Garnaga-Budré a,d, Galina Lujaniené b, Kçstutis Joksasc,e, Algirdas Stankeviciusa,d, Vitalijus Malejevas a,b, Ruta Bariseviciuté b
a Environmental Protection Agency, Department of Marine Research, Klaipeda, Lithuania b State Research Institute Center for Physical Sciences and Technology, Vilnius, Lithuania c Nature Research Center, Institute of Geology and Geography, Vilnius, Lithuania d Klaipeda University, Klaipeda, Lithuania e Vilnius University, Vilnius, Lithuania
Received 24 December 2016; accepted 15 November 2017
KEYWORDS
Metals;
Enrichment factor;
Geoaccumulation
index;
Contamination factor; The Baltic Sea; The Curonian Lagoon
Summary The distribution of metals (Pb, Cu, Cd, Ni, Cr, Zn) in surface sediments and the potential pollution sources in the south-eastern part (SE) of the Baltic Sea (Lithuanian zone) were investigated in relation to the environmental characteristics (amount of fine-grained particles, TOC content in sediments, origin of sedimentary organic matter, salinity, water depth) in 2011 — 2014. The higher metal concentrations were measured in sediments of the Curonian Lagoon and in the open waters. An approach using various environmental indices (enrichment factor EF, geoaccumulation index Igeo and contamination factor CF) was used to quantitatively assess a contamination degree. The principal component analysis (PCA) was applied in order to further scrutinize pollution from metal sources. The values of the contamination indices showed no/very low sediment contamination with Ni and Cr, minor—moderate contamination with Cu, Zn and Pb and moderate—considerable pollution with Cd. The strong relationships among metals suggested their similar distribution pattern and a combination of natural and anthropogenic sources. The higher metal concentrations coincided with an increasing amount of fine-grained fraction and organic carbon. In the territorial waters, the distribution of elements was related to the water
* Corresponding author. Environmental Protection Agency, Department of Marine Research, Taikosav. 26, LT-91222, Klaipeda, Lithuania. Tel. +370 46 41 0450; fax. +370 46 41 0460.
E-mail addresses: n.remeikaite@gmail.com, n.remeikaite@aaa.am.lt (N. Remeikaite-Nikiene). Peer review under the responsibility of Institute of Oceanology of the Polish Academy of Sciences.
https://doi.org/10.1016/j.oceano.2017.11.001
0078-3234/© 2017 Institute of Oceanology of the Polish Academy of Sciences. Production and hosting by Elsevier Sp. z o.o. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
of Pages 14
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depth. In addition, the binding of metals with insoluble iron sulphides might explain their high concentrations at the most remote and deepest stations.
© 2017 Institute of Oceanology of the Polish Academy of Sciences. Production and hosting by Elsevier Sp. z o.o. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
The intense development of anthropogenic activities since the late 19th century has resulted in enhanced loads of pollutants (e.g., nutrients, metals) from a large densely populated catchment area to the Baltic Sea (HELCOM, 2010). For example, a nearly threefold increase in Cu and Zn accumulation rates was observed in the Gulf of Finland from the period of 1850—1900 to 1975—1998 (Vaalgamaa and Conley, 2008). Metals enter the Baltic Sea either adsorbed onto suspended particles or in dissolved forms mostly through the rivers discharge (Leivuori et al., 2000; Yurkovskis and Poikane, 2008). The significant input of cadmium, lead and mercury via atmospheric deposition was also reported by HELCOM (2010). For instance, 47.5 tonnes of cadmium and 274.2 tonnes of lead entered the Baltic Sea as waterborne pollutants, while the atmospheric deposition accounted for 7.1 tonnes of cadmium and 234 tonnes of lead (HELCOM, 2010). In water systems metals tend to accumulate in sediments in association with organic matter, fine-grained sediments, sulphides and iron-manganese hydroxides and they may be released with changing conditions in sediments, such as changes in pH, dissolved oxygen or temperature (Dang etal., 2015; Leivuori etal., 2000). Several elements, such as Zn and Cu, are known to be essential elements for life, while others, such as Pb and Cd, do not play any physiological role and are highly toxic to all organisms even at low concentration (Jakimska et al., 2011). Therefore, among the metals, particular attention is paid to mercury, cadmium, lead and nickel which are identified as priority and priority hazardous substances by European Commision (Directive 2013/39/EU). To maintain marine ecosystems, management plans considering the human-induced contamination have to be established, where pollutant distribution and transport pattern, sources of contamination and behaviour in ecosystems need to be identified. Since metals originating from natural (e.g., erosion) and anthropogenic sources accumulate together in sediments, it is important (while not an easy task) to determine the ratio between the natural and artificial constituents of sediments (García et al., 2008; Ho et al., 2012).
A common approach to estimate an anthropogenic impact on sediments is to calculate the contamination factors for metal concentrations above uncontaminated background levels. For this purpose, many different enrichment calculation methods (e.g., enrichment factor, geoaccumulation index and contamination factor) have been used in various studies (e.g., Bonnailetal., 2016; Costa etal., 2015; Zalewskaetal., 2015). In spite of many geochemical studies (e.g., Emelyanov et al., 2001, 2014, 2015; Mazeika et al., 2004; Pustelnikovas
et al., 2007) in the SE Baltic Sea area, the results which concern the extent of the sediment pollution with heavy metals are lacking. The reported bulk metal concentrations may show the natural geochemical peculiarities in the region, however, they do not reflect the ratio between the natural and human-induced pollution of sediments. Moreover, due to the different methodologies (in particular, leaching methods) used by the scientists, it is difficult to compare and estimate the degree of the sediment pollution with heavy metals.
The main tasks of the present study were: (i) to evaluate the distribution of metals in bottom sediments of the SE Baltic Sea (Lithuanian zone) and to define the most polluted sites; (ii) to clarify the influence of the environmental factors (mineral and organic constituents of sediments, origin of organic matter, water depth and salinity) on the accumulation of metals; (iii) to identify the possible sources of contamination and the main driving factors in the Curonian Lagoon, Klaipeda Strait, coastal waters and offshore area. In order to assess a degree of contamination of the SE Baltic Sea, the enrichment factor (EF), the geoaccumulation index (Igeo) and the contamination factor (CF) were calculated. Results might be used in preparing the management plans and strategies for the initial assessment of the human-induced contamination in the SE Baltic Sea.
2. Methods
2.1. Study area
The area of this study includes the Lithuanian part of the Curonian Lagoon and the Baltic Sea (the SE Baltic Sea) (Fig. 1).
The Curonian Lagoon is a shallow semi-enclosed transitory brackish-to-fresh water body separated from the SE Baltic Sea by a narrow Curonian Spit (Fig. 1). The southern and central parts of the lagoon are freshwater (<0.5%), while the northern part is oligohaline with irregular salinity (from 0 to 8%) fluctuations (Remeikaité-Nikiené et al., 2012). The mean depth of the lagoon is 3.8 m. The lithological composition of the bottom sediments in the Curonian Lagoon is heterogeneous of the main 4 types — medium sand, fine sand, coarse silt and fine silty mud (Trimonis et al., 2003).
The lagoon is connected to the Baltic Sea through the narrow Klaipéda Strait where the Klaipéda town and the Klaipéda Port are located. This is the area where the intensive transfer and settling of sedimentary matter, provided by the Nemunas River and saline water, take place. The Nemu-nas River mostly supplies silty (0.01—0.1 mm) and clayey (<0.01 mm) particles into the lagoon, while saline water
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19 WE 20 WE 21 WE 22 WE
Figure 1 The map of the study area in the Lithuanian part of the Curonian Lagoon and the Baltic Sea.
intrusions bring sandy (0.1—0.25 mm) marine sediments. High concentrations of metals are measured in harbour and they may be the source of internal pollution due to sediment dredging which reactivates the contaminants in the sediments (Pustelnikovas et al., 2007).
The active hydrodynamics in the Lithuanian coastal waters prevents the lack of oxygen in the water column. However, hypoxic conditions and appearance of hydrogen sulfide (H2S) were often recorded in the Gotland Deep (Eme-lyanov, 2014). The sand and gravel are the typical sediments in the shallow and exposed SE Baltic Sea coastal waters, while mud and silt accumulate in a deeper area (Bitinas et al., 2005; Emelyanov, 2001). The observed linear sedimentation rates mostly vary between 1.0 and 2.0 mmy~1 in the open Baltic Sea waters (Mazeika et al., 2004) and 2.5—3.6 mm y~1 or even 5—15mmy~1 (Pustelnikovas, 2008 and references therein) in the Curonian Lagoon.
For the data analysis, the research stations were grouped according to the salinity zonation and taking into account the principal sedimentary environments: (1) the Curonian Lagoon; (2) the Klaipeda Strait; (3) territorial waters of the SE Baltic Sea and (4) open waters (Table 1). The stations were located in order to reflect the main anthropogenic pressures: (1) the impact of the Nemunas River (stations in the Curonian Lagoon, K12, K10, K14, K5); (2) the impact of
the discharge from the Nemunas River and saline water intrusion (K1, K2, K3) as well as the industrial activities in the Klaipeda Port (in Malku Bay, st. K3A, K3B); (3) the impact of the plume of the Curonian Lagoon into the Baltic Sea (st. 3, 4, 5); (4) the impact of the activities in the BQtinge oil terminal (st. B-1, 1B, B-4); (5) the impact of the dumping of the dredged sediments from the Klaipeda Port (st. 20, 20A). The remaining sampling sites in the Lithuanian territorial waters and the Exclusive economic zone are situated in order to observe the common contamination trends.
2.2. Bottom sediments sampling and analysis
Bottom sediment samples were taken three times per year (in spring, summer, autumn) in the Baltic Sea and in the Curonian Lagoon during the period of 2011—2014. Sediments were collected from r/v Vejunas (Klaipeda) using a Van Veen grab sampler (sampling area of 0.1 m2). Sediments from the uppermost layer (0—5 cm) were subsampled, stored in individual plastic containers and frozen on board (at -20°C) until further processing in the laboratory (Remeikaite-Nikiene et al., 2016). The types of bottom sediments of the Curonian Lagoon were characterized on the basis of the decimal granulometric classification according to the dominant fraction and the median diameter (Md) according to EN ISO
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Table 1 The main morphometric and hydrological characteristics of the study area.
Research zones
Stations, No.
Variability of salinity
Water depth, m Variability in sediment types
The Curonian
Lagoon The Klaipeda Strait Baltic Sea territorial -coastal waters Baltic Sea open waters
K10, K12, K14, K6, K5
K1, K2, K3, K3A, K3B
4, 3, 5, 2, 6, 7, 20, 20A, 1B, 64,
64A1, 64B, B-1, B-4, S-1, N-6
65, 66, N-3, CHEMSEA1-8, CHG1, CHG2, CHG5, R7
0.5 (st. K12)-7 (st. 1.8-5.6 K5)
0.5-8 4-15
0.5 (st. 4)—8 12-46
7-12 40-117
Fine sand, silt, with shell
deposits
Fine sand, silt
Fine sand, sand, gravel,
aleurite, glacial deposits
Silt, aleurite, sand, gravel
14688-1: 2004 and EN ISO 14688-2: 2004. Implementing the WFD requirements, the sediment samples for the granulo-metric analysis were taken from the Curonian Lagoon and its outflow to the Baltic Sea area (transitional waters) in 2012. The suggested frequency of monitoring of the coastal waters is once per six years, thus, the sediment samples from the coastal and open sea area were not taken for the granulometric analysis in 2011—2014.
The analysis of metals was performed in two laboratories. For the national monitoring purposes sediment samples were analyzed at the laboratory of the Environment Research Department of the Environmental Protection Agency (EPA, accredited according to the ISO/IEC 17025) in 2011—2014. A 0.5 g of each dried sediment sample was leached with 6 ml of nitric acid (>69%) in a microwave, diluted to 50 ml, and then analyzed by atomic absorption spectrometry with the graphite furnace (AAS) or/and the inductively coupled plasma optical emission spectrometer (ICP-OES). Concentrations of Cd were analyzed by AAS according to ISO 15586:2003. The ICP-OES method (IS011885:2007) was used for the analysis of Cr, Zn and Al. Both methods were used for the analysis of Pb, Cu and Ni depending on the concentrations of these metals in samples. The precision of the analytical procedures, expressed as the standard deviation, ranged within approximately from 5.2 to 14% for AAS and from 7.6 to 18% for ICP-OES methods. The certified reference materials CRM BCR-277R (IRM) and ICP Multielement standard solution (Merck) were used. The limit of determination for the AAS method ranged from 0.01 mg kg~1 for Cd to 0.10 mg kg~1 for Pb and Ni; for the ICP method - from 0.20 mg kg~1 for Cr to 4.5 mg kg~1 for Cu.
For the metal investigation the samples from several common stations (Nemunas, K3A, 4, 5, 6, 7, 20A, 65, 66, CHEMSEA2) and new stations (CHG1, R7) were analyzed at the Institute of Geology and Geography of the Nature Research Center (NRC) in 2011 and 2013. For metal (Pb, Cu, Cd, Ni, Cr, Zn, Fe and Al) analysis the total digestion method was used. A 0.25 g of each freeze-dried sediment sample was heated using a microwave in concentrated acids mixture (HNO3-HClO4-HF) to fuming and taken to dryness. The residue was dissolved in HCl (Loring and Rantala, 1992). The content of trace elements in the bottom sediments was analyzed with Perkin Elmer Optima 7000 DV ICP-OES. For quality control of the results the NIST Standard reference material 2702 (Inorganics in Marine Sediments) was used. The limit of detection for the ICP method ranged from 0.07 mg l~1 for Cd to 1.4 mg l~1 for Pb. The precision of the analytical procedures,
expressed as the standard deviation, was approximately up to 15%.
The amount of TOC and the isotopic signatures were analyzed in samples taken during the period of 2012— 2014. For the total nitrogen (%), organic carbon (%) and isotope ratio measurements (S13C, S15N) the sediment samples were acidified with 2 M HCl to remove carbonates, then dried at 60°C overnight and weighed (3^90 mg depending on the organic matter content) into tin capsules. The measurements were made on a FlashEA1112 elemental analyzer connected to the isotope ratio mass spectrometer (Thermo Finnigan Delta Plus Advantage).
2.3. Estimation of EFs
The sediment pollution intensity indices (enrichment factor — EF, geoaccumulation index — Iseo, contamination factor — CF) were calculated in the study. Since no background data of metals in uncontaminated marine sediments in the study area are available, therefore, the global Earth's shale values for metals reported by Turekian and Wedepohl (1961) were used as background values for metals (Pb = 20; Cu = 45; Cd = 0.3; Ni = 68; Cr = 90; Zn = 95 mg kg~1 dry weight).
The EFs are widely used to calculate the ratio between uncontaminated background levels and contaminated sediment layers (e.g., Costa et al., 2015; Selvaraj et al., 2010; Zalewska et al., 2015). In the calculations of EFs, the normalization against Al is widely applied, mainly because it has a minor anthropogenic input and it is not significantly influenced by changes in the redox potential as compared with Fe (Ho et al., 2012 and references therein; Selvaraj et al., 2010).
The EFs were calculated as follows (Zalewska et al., 2015):
EF —
Csample = Nsample Cshale= Nshale
where C and N refer to the concentrations of the elements (e.g. Cu) and normalizers (e.g. Al) in the sample of surface sediments (sample) and the Earth's shale (shale), respectively.
For the evaluation of EF data, the following classification (Costa et al., 2015; Zalewska et al., 2015) was used: EF <1 — indicates no enrichment, EF <3 — minor enrichment, EF between 3 and 5 — moderate enrichment, EF between 5 and 10 — moderately severe enrichment, EF between 10 and 25 — severe enrichment, EF between 25 and 50 —
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Table 2 The average (¿standard deviation) metal concentrations after partial and total leaching in the common stations (Nemunas, 4, 5, 6, 7, 20A, 65, 66 and CHEMSEA2) (t = t-test, *p < 0.05).
Method Pb Cu Cd Ni Cr Zn Al, %
Partial leachinga 3.81 ± 1.4 1.4 ±0.9 0.04 ± 0.02 2.8 t±1.1 8.4 ±3.6 12.1 ±3.4 0.19 ±0.07
Total leachinga 7.52 ± 1.3 2.4 ±0.9 0.11 ±0.05 2.3 ! ±0.9 16. 6± 11.1 14.2 ± 3.9 1.54 ±0.15
Statistics t = 5.18* t = -1.88 t = -3.29* t = 0.79 t = -1.89 t = - 0.99 t = -21.48*
Partial leachingb 16. 6 ± 13.1 8.4 ±4.5 0.33 ± 0.30 10. 4 ±6.5 20. 3 ±5.3 42.3 ± 29.1 0.79 ±0.50
Total leachingb 13. 9 ± 10.1 11.2 ±4.9 0.38 ±0.11 20. 9 ±14.4 31. 5 ±13.4 39.5 ± 17.7 3.20 ±0.70
Statistics t = 0 .21 t = -0.31 t = -0.18 t = -0.63 t = -1.10 t = 0 .11 t = -3.94*
The stations with similar type of sediments were grouped. a Nemunas, 4, 5, 6, 7, 20A, 66 (fine sand, sand). b 65, CHEMSEA2 (aleurites).
very severe enrichment, EF >50 — extremely severe enrichment. The EF values lower than 1.5 (García et al., 2008) or <2 (Abreu et al., 2016) indicate that the metal is entirely from crustal materials or natural processes, whereas EF values higher than 1.5 or 2 suggest an increasing portion of the anthropogenic sources (Abreu et al., 2016; García et al., 2008). The enrichment factors (EFs) were calculated based only on the total metal concentrations since the significant differences between Al content after partial an total extraction methods were observed (Table 2).
The geoaccumulation index (Igeo) is also quite widely applied in assessments of the sediment pollution with metals (García et al., 2008; Müller, 1979; Zalewska et al., 2015):
Igeo = Log2
Cn 1.5Bn
where Cn is the concentration of the element in the enriched samples, and the Bn is the background or pristine value of the element. Factor 1.5 is introduced to minimize the effect of possible variations in the background values which may be attributed to lithologic variations in the sediments. The method assesses the degree of metal pollution in terms of seven enrichment classes based on the increasing numerical values of the index: Igeo < 0, uncontaminated; 0 < Igeo < 1, uncontaminated to moderately contaminated; 1 < Igeo < 2, moderately contaminated; 2 < Igeo < 3, moderately to heavily contaminated; 3 < Igeo < 4, heavily contaminated; 4 < Igeo < 5, heavily to extremely contaminated; 5 > Igeo, extremely contaminated (García et al., 2008; Müller, 1979; Zalewska et al., 2015).
The method of the contamination factor (CF) evaluates the enrichment in metals in relation to the background concentrations of each metal in sediments. CF is the ratio obtained by dividing the concentration of each metal in the sediments by the background value (Bonnail et al., 2016):
Cref '
where Cs and Cref are concentrations of the element in the sediment sample and the background or pristine value of the element, respectively. The method of the CF calculation is identical to the EF calculation, except the fact that the CFs do not normalize concentrations against the normalizing element. In order to evaluate the degree of contamination in sediments, the following gradations are proposed: CF < 1,
no/low contamination; 1 < CF <3, moderate; 3 < CF <6, considerable; 6 < CF — very high contamination (Bonnail etal., 2016; Hakanson, 1980).
2.4. Data preparation and the statistical analysis
Measurements below limits of quantification (LoQ) were treated as half the LoQ value of the compound considered. The data of metals (Pb, Cu, Cd, Ni, Cr, Zn, Al) in the sediments obtained by using partial and total extraction methods were compared from nine stations (Nemunas, 4, 5, 6, 7, 20A, 65, 66 and CHEMSEA2) in order to have the view on the contamination extent of the Lithuanian marine zone as reliable as possible. The comparison of the pre-treatment methods in this study is assumed to be important since: (i) the reference values (concentrations in the Earth's shale, Turekian and Wedepohl, 1961) showed the total concentrations; and (ii) it was necessary to know whether the national monitoring data on Al (partial digestion) might be used for the normalization purposes. The mean concentrations for both pre-treatment methods are shown in Table 2. The mean concentrations after partial and total leaching were compared via the parametric t-test. The post hoc Tukey HSD test was used to find out significant differences among the spatial distribution of metal concentrations. The Pearson's coefficient was used to identify the relationships among trace and major elements, TOC, carbon isotopic signatures, the particle size, water depth and salinity. The analysis was performed applying SigmaPlot 12.5 software. The PCA was used in order to identify sources of pollution with metals and to scrutinize the distribution pattern. This technique clusters variables into groups, such that variables belonging to one group are highly correlated with one another. Four datasets were analyzed separately: (1) the Curonian Lagoon; (2) the Klaipeda Strait; (3) territorial waters of the SE Baltic Sea and (4) open waters. The number of factors extracted from the variables was determined according to the Kaiser's rule. This criterion retains only factors with eigenvalues that exceed one. The analysis was performed applying Statistica 7 software.
3. Results and discussion
3.1. Assessment of sediment contamination
The nitric acid only partly leaches mineral-bounded pollutants, therefore, the real contamination of the sediments
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might be not revealed (Vallius, 1999). As it was shown by Birch (2017), the sediment pre-treatment with the strong acids resulted in a 4—9 fold elevation in metal concentrations. Despite that fact, both methods are common within the HELCOM countries, and the partial leaching technique is used to evaluate the anthropogenic share of the metal concentration in sediments (e.g., Ebbing et al., 2002; Leivuori et al., 2000; Vallius, 1999). During this study, the comparison between the nitric acid extraction and the total digestion showed statistically different mean concentrations of lead and cadmium in sandy sediments, while no differences were observed in aleurites (Table 2). However, the concentrations of aluminium were about 4—8 times lower in the partial digestion than in the total leaching and, therefore, no Al-normalized enrichment factors (EFs) were calculated based on the national monitoring data. Unfortunately, no national monitoring data on metal concentrations from the silty sediments (st. CHG1, R7) were available for the methodological comparison. In general, our results demonstrated that despite different sediment pre-treatment methods, the datasets of most metals might be used in parallel in this study for the common assessment of the chemical sediment status. Spatial variations of the average contents of metals and the "metal pollution hotspots" are illustrated in Fig. 2. The comparison of metal concentrations in the water bodies revealed that the amount of elements accumulated in the Curonian Lagoon sediments was about 1.4—4.0 times
higher than in the sediments of the Baltic Sea and it might show that the lagoon acts as a sink for many pollutants entering from the catchment. Among the stations, the higher concentrations of metals (Tukey HSD test, p < 0.05) were measured in sediments of the Klaipeda Strait (st. K1, K3A, K3B), the central part of the Curonian Lagoon (st. K10) and the open sea (st. CHEMSEA2, CHG1 and R7) (Fig. 2). The prevalent metal accumulation in sediments in most cases coincided with the increase of its organic (TOC) and mineral (Al, silt fraction) constituents (Table 3). The TOC values in sediments ranged from <1% to 10% dry weight (d.w.) with a consequently higher amount in sediments from the accumulation areas in the Curonian Lagoon (8.40% at the st. K10) and the open sea (7.59% at the st. R7). Results might be explained by the affinity of metals to the organic matter and the clay fraction of the sediment as well as the formation of e.g. organic complexes (Emelyanov et al., 2015; Pustelnikovas et al., 2007; Zalewska et al., 2015). The concentration and retention of metals in the sediments are also affected by the oxygen saturation and occurrence of hydrogen sulphide, which periodically accumulates in the bottom of the Gotland and Gdansk Deeps (Emelyanov, 2014; Zalewska et al., 2015). In exposed and oxic waters, iron/manganese-oxides/hydroxides are important carriers of metals in sediments, while under reducing conditions some part of the iron fraction can be fixed in sediment layers in the form of iron sulphides (Emelyanov, 2014; Müller, 1999). The strong correlation
20°0'0"E 21° OWE
Figure 2 Distribution of Pb, Cu, Cd, Ni, Cr and Zn (the average values) in the SE Baltic Sea in 2011—2014.
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19 WE 20°0'0"E 21 °0'0"E
20°0'0"E 21 "0'0"E
Figure 0010. (Continued).
(Table 3) among all metals and the sulphur amount in the open sea sediments might indicate binding of metals with insoluble sulphides.
In order to quantitatively evaluate the pollution extent at the stations with the elevated metal concentrations (K1, K3A, K3B, K10, CHEMSEA2, CHG1 and R7), the contamination factors (EF, Igeo and CF) were calculated. In this study, the average EFs for the studied metals varied between 0.5 and 9.9 (Table 4). The mean EFs for the open sea sites were: Cd (5.5) >Pb (2.8) > Zn (1.7) > Cr, Cu (1.1) > Ni (0.6) and showed no/minor enrichment with all elements except with Cd. The EF for Cd showed a moderately severe enrichment which might be attributed to the anthropogenic sources (EF >1.5—2.0).
The low geoaccumulation index (Igeo) values (<0) for Cu, Ni, Cr showed that these metals had not contaminated SE Baltic Sea sediments. The calculated Igeo values (0 < Igeo < 1) for Cd at the K10, CHEMSEA2 and R7 sites, for Pb at the CHG1 and R7 sites and for Zn (only CHG1 site) indicated that sediments from the investigated locations were uncontaminated to moderately contaminated with Cd, Pb and Zn. The highest Igeo value (2.3) calculated for Cd at the station CHG1 indicated moderately to highly polluted sediments (Table 4). The state of the sediment contamination based on the CF values (Table 4) showed that sediments exhibited low levels of contamination (CF < 1) for Ni and Cr;
moderate (1 < CF < 3) forCd (K10, CHEMSEA2, R7), Cu (only CHG1), Pb (CHEMSEA2, CHG1 and R7) and Zn (CHG1 and R7); and very high contamination (6 < CF) for Cd (at CHG1) (Table 4).
In summary, the values of the contamination factors (EF, Igeo and CF) pointed out a higher sediment pollution extent in the open sea as compared with the Klaipeda Strait (Table 4). Based on the average values of EF, Igeo and CF, the sediment contamination degree in the open waters was defined as moderate—considerable for Cd, minor—moderate for lead, zinc and copper and low for nickel and chromium (Table 4). The sediment pollution extent based on the EFs and Igeo values was comparable with the most recent data reported for the southern Baltic Sea by Zalewska et al. (2015). When comparing the average EFs values, the Baltic Sea open waters showed a higher contamination with Cd (EF = 5.5 in this study and EF = 1.7 reported by Zalewska et al., 2015), but similar contents of Pb (EF = 2.8 and EF = 2.2, respectively) and Zn (EF = 1.7 and EF = 1.5, respectively) for the SE Gotland Basin. The adjacent Gdansk Deep was also minor contaminated with Zn and Pb (EF = 2.2 and 2.7, respectively), while the enrichment factor for Cd (EF = 7.2) indicated a moderately severe enrichment (Zalewska et al., 2015). The obtained results pointed out the similar extent of sediment pollution with Zn and Pb in the Gdansk and Gotland Deeps, and a higher contamination with Cd in the Gdansk Deep.
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20 0'0"E Figure 0010. (Continued).
3.2. Identification of pollution sources
The principal component analysis (PCA) and the Pearson correlation matrix used in the study provided important tools for a better understanding of the source identification and the dynamics of the pollutants. The PCA extracted a small number of factors (Principal Components, PCs) for exploring the similarity of distribution behaviour of metals and analyzing the relationships among the observed variables (Table 3). The PCs with eigenvalues >1 were extracted for metals in sediments datasets, accounting for about 81 —92% of the total variance (Table 3).
The Curonian Lagoon (without Klaipeda Strait). Only one PC (with eigenvalue >1) was extracted from the database which explained about 92% of the total variance of metals (Table 3). The PC1 was correlated with Pb, Cu, Cd, Ni, Cr, Zn, Al, TOC and the amount (%) of fine particles (<0.063 mm). The strong relationships among metals (Table 3) suggested their similar source and mechanism of distribution in sediments, while each source type was not defined. In some studies, a lithogenic (natural) origin is presumed for metals related with Al, since it is a common element in soil parent materials (e.g., Levei et al., 2014). However, the significant correlation may show the supply of aluminosilicate of the mainland origin contaminated with metals from intensive agricultural activities. The highest amount of pollutants
enters the Curonian Lagoon with the riverine discharge, affected by the municipal sewage discharge, industrial and agricultural activities within catchment areas (The Nemunas River Basin District Management Plan, 2010). In 2011—2013, on the average, 11.3 t y1 of Cr, 26.0ty~1 ofCu, 14.6ty~1 of Ni and 82.2 ty~1 of Zn entered the Curonian Lagoon via riverine discharge (Environmental Protection Agency data, unpublished). Pb, Cu, Cd and Zn are well-known elements of agricultural activities, specifically related to an application of pesticides and phosphate fertilizers (Wang et al., 2015). Consequently, metals originated from mainland sources accumulate in the central part of the lagoon characterized by slower dynamics and high primary production resulting in a high TOC amount. Besides the pollution of mainland origin, close to the sampling station K10 there is a marina for small boats, which may contribute to the inputs of metals and oil hydrocarbon to the sediments with the fuel residues.
The Klaipeda Strait. The PC1 explained about 70% of the total variance with high loadings of Pb, Cd, Ni, Cr, Zn, Al, TOC, salinity and amount (%) of fine particles (<0.063 mm) in sediments. On the plot of scores the relatively higher concentrations of elements appeared at the K1, K3A and K3B sites (not shown). The observed strong positive correlations for metals (Table 3) suggested that they had common geo-chemical behaviours and probably originated from similar pollution sources, while the possibility to identify a clear
N. Remeikaitè-Nikienè et al./Oceanologia xxx (2017) xxx—xxx 9
19°0'0"E 20°0'0"E 21 "0'0"E
20' 0'0"E 21 °0'0"E
Figure 0010. (Continued).
origin of metals was limited. On the one hand, contaminants from the rivers catchment area are carried into the harbour area, on the other hand, local pollution also appears from sources in the port itself (Galkus et al., 2012 and references therein). The increasing accumulation of trace metals in sediments at the station K1 might be greatly influenced by the flocculation processes which are often amplified by the increase of pollution. When colloidal particles move downwards from freshwater into the marine environment, floccu-lation causing larger particles to form and settle on the seafloor takes place. Flocculation processes in the marine water-freshwater interface have been widely reported in other studies (Karbassi et al., 2013; Palanques et al., 1995). The correlation between metal concentrations in sediments and salinity (Table 3) might support this explanation. Despite the significantly high metal concentrations at K1, K3A and 3B sites, the contamination factors (lgeo, CF) indicated uncontaminated/low contaminated sediments. The PC2 accounted for 19.4% of the total variance and was dominated by Cu (Table 3). Copper occurred as an important parameter at sites K3A and K3B and probably might be related to the urban and industrial activities taking place in the Klaipeda Port. The station K3B was established to track the impact of domestic and industrial effluent inputs, whereas st. K3A was located in the semi-enclosed Malku Bay in order to evaluate the impact of the floating docks
of the ship repair company. Stagnation and low oxygen conditions are prevalent in the technogenic sedimentation zone of the Klaipeda Strait resulting in 5—50 times higher metal concentrations than in the natural sedimentation zone (Pustelnikovas et al., 2007). The elevated concentrations of metals in sediments and moderate pollution with copper level were indicated previously by other authors (Galkus et al., 2012).
Territorial waters. Three main PCs explained about 83% of the total variance (Table 3). The PC1 (53% of the total variance) identified a large group of variables containing all metals together with a water depth, thus confirming the distribution of elements depending on the water depth. Results (Table 3) showed that the major source for the metal accumulation in coastal sediments had a lithological material (Al), while the material of biotic origin (TOC) probably had a secondary importance. The PC2 explained 15.8% of the total variance with the moderate loadings of Cd, salinity and the water depth (Table 3). On the score plot, the elements defined by the PC1 and PC2 were related to the stations 64A1, 20, 20A and 4 (not shown) and it probably showed the mainland origin of metals: an input with the freshwater discharge (stations 4 and 64A1) as well as the sediment dumping from the Klaipeda Port area (st. 20 and 20A).
Open waters. Only one PC (with eigenvalue >1) was extracted from the database which explained about 81% of
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20°0'0"E Figure 0010. (Continued).
the total variance of metals (Table 3). The PC1 was highly correlated with all metals, TOC, water depth, the amount of sulphur and iron. Since Cd and Pb are scarce in rocks, their presence in the marine environment is usually related to anthropogenic inputs from the atmosphere and rivers (Prego et al., 1999). As it was shown, the concentrations of Pb and Cd in the open waters were clearly higher than the concentrations in the Earth's shale and showed an anthropogenic origin of pollutants (EFs >1.5—2.0). Regarding nickel, Renner et al. (1998) claimed that Ni, as well as Mn and Co, entered the southern Baltic as a result of natural erosion processes. Therefore, the strong correlations among all elements should refer to a similar distribution pattern and a combination of natural and anthropogenic sources.
The sources of metals and their distribution pathways might be indirectly identified using the C and N isotopic signatures of organic matter. The S13C and S15N signatures (from -31.3 to -23.3%, S15N from 0.6 to 11.2%), as well as low C N-1 ratio (~7), suggested that the SOM in the SE Baltic Sea was mostly derived from a contribution of marine and freshwater algae (Remeikaite-Nikiene et al., 2016). The trace elements from water might be incorporated in living phytoplankton cells and, in this respect, phytoplankton plays an important role in the transport of metals (Aigars et al., 2014) as well as other toxic pollutants (e.g., TBTcompounds, Filipkowska et al., 2014) from the water column to the
bottom sediments. The presence of blooms of phytoplankton in the late spring and summer provides ideal conditions for the considerable metal accumulation from the water layer in sediments. Several studies (e.g., Lin et al., 2016; Thorsson et al., 2008) have shown that the increasing eutrophication and consequently organic matter settling to the seafloor can have a significant effect on the increasing bioaccumulation of associated contaminants in the benthic organisms. Since the decrease of the freshwater organic matter towards offshore is observed (Remeikaite-Nikiene et al., 2016, 2017), the influence of terrestrial contaminants is believed to decrease towards open waters. The weak negative correlation between metals and S13C of SOM values (r = from -0.36 to -0.60, p < 0.05) in territorial waters might show a general tendency of decreasing transport of contaminants in association with freshwater phytoplankton. The correlation between metals and S13C values for the open sea was not significant. Considering an increase of the marine phyto-plankton contribution at the open sea stations (Remei-kaite-Nikiene et al., 2016), it is believed that marine phytoplankton is probably not directly involved in the metal transport from terrestrial sources, although it uptakes metals deposited from the atmosphere and is likely involved in the further sedimentation and redistribution processes of finegrained particles. An exception was R7 site which was characterized by the lowest S13C value (-31.8 ±0.3%) and a
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20°0'0"E Figure 0010. (Continued).
Table 3 Results of the PCA for the distinct research zones. The dominant loadings are given in bold.
Variables Curonian Lagoon Klaipèda Strait PC1 PC1 PC2 Territorial waters PC1 PC2 PC3 Open sea PC1
Pb -0.97 -0.98 0.04 -0.53 -0.14 -0.24 0.98
Cu -0.99 -0.37 -0.84 -0.94 -0.01 0.15 0.99
Cd -0.99 -0.96 0.13 -0.64 0.60 -0.36 0.99
Ni -0.98 -0.98 0.03 -0.97 -0.06 0.19 0.99
Cr -0.99 -0.73 -0.38 -0.54 0.39 0.56 0.98
Zn -0.95 -0.84 -0.48 -0.99 0.01 0.04 0.98
Al -0.98 -0.95 0.27 -0.93 -0.12 0.29 0.98
TOC -0.98 -0.85 0.53 -0.43 -0.10 -0.79 0.99
<0.063 a -0.71 -0.91 -0.30 - - - -
Depth -0.20 -0.48 0.66 -0.65 -0.64 -0.31 0.80
Salinity 0.06 -0.90 0.22 0.15 -0.77 0.35 0.36
Feb - - - - - - 0.99
Sb - - - - - - 0.99
Eigenvalues 8.25 6.69 1.74 5.26 1.58 1.48 8.12
% of variance 91.68 69.95 18.47 52.61 15.76 14.84 81.25
Cumulative % 91.68 69.95 88.42 52.61 68.36 83.20 81.25
a Data on the particle size were available only for the Curonian Lagoon. b Data on Fe and S were available only for the open sea stations.
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Table 4 The enrichment factor (EF)a, geoaccumulation index (/geo)band the contamination factor (CF)c of trace metals in selected sediments from the SE Baltic Sea. In bold - the values >0 (/geo) and >1 (EF, CF).
Stations Pb Cu Cd Ni Cr Zn
EF lgeo CF EF lgeo CF EF lgeo CF EF lgeo CF EF lgeo CF EF lgeo CF
K10 — -0.9 0.8 — -2.4 0.3 — 0.4 2.0 — -2.7 0.2 — -2.3 0.3 — -1.2 0.7
K3A - -2.1 0.4 — -0.9 0.8 — -2.2 0.3 — -3.6 0.1 — -2.0 0.4 — -1.9 0.4
K3B — -2.0 0.4 — -1.5 0.5 — -1.5 0.5 — -3.2 0.2 — -3.0 0.2 — -1.4 0.6
K1 — -1.5 0.5 — -2.7 0.2 — -0.8 0.8 — -2.7 0.2 — -2.5 0.3 — -1.6 0.5
CHEMSEA2 2.3 -0.5 1.1 0.8 -2.5 0.4 4.1 0.3 1.9 0.5 -2.8 0.2 1.0 -1.7 0.5 1.2 -1.4 0.6
CHG1 3.1 0.6 2.3 1.6 -0.4 1.2 9.9 2.3 7.3 0.7 -1.5 0.5 1.2 -0.8 0.8 2.2 0.1 1.7
R7 3.1 0.8 2.5 0.9 -0.9 0.8 2.4 0.2 1.7 0.7 -1.4 0.6 1.1 -0.9 0.8 1.8 -0.1 1.5
The EFs, lseo, CFs for the open sea stations (CHEMSEA2, CHG1 and R7) calculated based on the total concentrations. a EF < 1, no enrichment; 1 < EF <3, minor enrichment; 3 < EF <5, moderate enrichment; 5 < EF <10, moderately severe enrichment; 10 < EF < 25, severe enrichment; 25 < EF < 50, extremely severe enrichment (Zalewska et al., 2015). b lseo <0, uncontaminated; 0 <lgeo <1, uncontaminated to moderately contaminated; 1 <lgeo <2, moderately contaminated; 2 < lgeo < 3, moderately to heavily contaminated; 3 < lgeo < 4, heavily contaminated; 4 < lgeo < 5, heavily to extremely contaminated; 5 > lgeo, extremely contaminated (Müller, 1979; Zalewska et al., 2015).
c CF <1, no/low contamination; 1 < CF <3, moderate; 3 < CF <6, considerable; 6 < CF — very high (Hakanson, 1980; Bonnail et al., 2016).
relatively high S15N value (6.8%) (Remeikaitè-Nikienè et al., 2016) similar to those, reported for the freshwater ecosystems (Remeikaitè-Nikienè et al., 2016, 2017). Apparently, this site is influenced by the considerable amounts of elements discharged to the sea by the Vistula River. In the Gdansk Deep, an intensive accumulation of trace metals supplied by the Vistula River was reported in other studies (Emelyanov, 2014; Zalewska et al., 2015).
4. Conclusions
The present study showed the higher concentrations of metals in sediments of the Curonian Lagoon (stations K1, K3A, K3B in Klaipèda Strait and K10 near the Nida settlement) and the Baltic Sea open waters (stations CHEMSEA2, CHG1 and R7). Based on the average values of EF, /geo and CF, the sediment contamination degree in the open waters was defined as moderate—considerable for Cd, minor—moderate for lead, zinc and copper and low for nickel and chromium. Although the PCA applied to the data set provided the qualitative information about the distribution pattern of elements, it was not adequate for supplying the quantitative information regarding the contributions of each source type. Results showed that the metal accumulation in sediments was affected by the grain-size, amount of TOC, depth variability, and thus the anthropogenic component was not easily discernible by the lithogenic one. Based on the PCA results, the only Cu in the Malku Bay might be attributed to the anthropogenic source, however, metal enrichment was not confirmed based on the values of /geo and CF.
Acknowledgments
We appreciate the anonymous reviewers for their valuable comments and suggestions to improve the quality of the manuscript. The authors would like to thank all the team members from the Environmental Protection Agency, the Geology and Geography Institute of the Nature Research Centre, the Center for Physical Sciences and Technology,
the crews of the vessel r/v Vejunas for their help and support during sampling and analysis.
The samples were taken and analysis was completed in the frame of the State monitoring and by implementing the projects: (1) "Application of isotope methods to assess spreading of organic substances in the Baltic Sea" which was financed by the Research Council of Lithuania" (contract No. MIP-080/2012); (2) EU part-financed project "Chemical munitions search and assessment (CHEMSEA)".
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