Distribution of organic and inorganic substances in the sediments of the “Great Bačka Canal”, a European environmental hotspot

Science of the Total Environment 601–602 (2017) 833–844

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Distribution of organic and inorganic substances in the sediments of the “Great Bačka Canal”, a European environmental hotspot Dejan Krčmar ⁎, Miloš Dubovina, Nenad Grba, Vesna Pešić, Malcolm Watson, Jelena Tričković, Božo Dalmacija University of Novi Sad Faculty of Sciences, Department of Chemistry, Biochemistry and Environmental Protection, Trg Dositeja Obradovica 3, 21000 Novi Sad, Serbia

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Physico-chemical parameters were analysed in the extremely polluted sediment of Great Bačka Canal. • Heavy metals and PAHs showed novel significant spatial and temporal variations. • PCA/FA suggested complexing of PAHs with heavy metals. • Zn, Cr, Cu, As, dibenzo[a,h]anthracene and benzo[a]pyrene identified as substances of concern. • Heavy metals have markedly higher ecological risks and need remediation techniques.

a r t i c l e

i n f o

Article history: Received 14 February 2017 Received in revised form 28 April 2017 Accepted 26 May 2017 Available online xxxx Editor: Kevin V. Thomas Keywords: Extremely polluted sediment Heavy metals PAHs Toxicological effect PCA/FA analysis

a b s t r a c t The Great Bačka Canal in Serbia is one of the most polluted waterways in Europe. Surface sediments from the canal were subject to systematic annual monitoring between 2007 and 2014 at 33 representative sampling sites. Eight heavy metals (Ni, Zn, Cd, Cr, Cu, Pb, As and Hg), mineral oils, 16 EPA PAHs and selected pesticides and polychlorinated biphenyls (PCB) were monitored. This study aims to evaluate the quality of the sediments and determine the potential ecological risks in order to establish pollutants of interest. The spatial and temporal influence of different and intense sources of pollution are investigated. The analysis includes multivariate statistical methods (factor analysis of principal component analysis (PCA/FA)) in order to assess the extent and origin (anthropogenic or natural, geogenic sources) of the contaminants detected in the sediment samples and the risks the present to the environment. Various sources, predominantly the food industry, were found to be responsible for most of the contamination by Cd, Cu, Cr and Zn, the mineral oils and PAHs (dibenzo[a,h]anthracene and benzo[a]pyrene contributed 86.0% of the total between 2007 and 2014). In contrast, the As was convincingly of geogenic origin, and the Hg, Pb and Ni present exhibit dual origins. Cd and Cu significantly raise the levels of potential ecological risk at all sampling locations, demonstrating the long-term effects of bioaccumulation and biomagnification. Significantly, the results of this work indicate that Cu, As and dibenzo[a,h]anthracene should be added to the EU watch list of emerging contaminants. This is supported by significant national and similar environmental data from countries in the region. © 2017 Elsevier B.V. All rights reserved.

⁎ Corresponding author. E-mail address: [email protected] (D. Krčmar).

http://dx.doi.org/10.1016/j.scitotenv.2017.05.251 0048-9697/© 2017 Elsevier B.V. All rights reserved.

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1. Introduction The Great Bačka Canal is an integrated part of the large Hydro-system Danube-Tisza-Danube, designed for melioration (drainage and irrigation) of the developed agricultural region. The 6 km investigated section (Fig. 1) is located in Vrbas, a settlement with a population of 25,000. The Canal is practically non-navigable and without runoff, has accumulated around 400,000 m3 of contaminated sediment, resulting in a water depth of b0.50 m. This implies highly disturbed water quality, and the impossibility of river transport, which is very important for the food industry in the region, due to connection of the Canal with the Danube and Tisa rivers. It also represents a huge ecological problem and risk to the local and wider area, as part of the pollution from the Canal flows into these two rivers. According to the "Official report on environmental conditions in the region", the Great Bačka Canal is a European environmental hot spot (Serbian Environmental Protection Agency, 2011), being one of the most polluted water bodies in Europe, with pollution in this area seriously endangering both the surface hydrography and the whole concept of nature preservation in the region (Devic et al., 2014 and Grizelj et al., 2011). For some time, in accordance with national legislation (RS 50/2012) and European Union Directive 2013/39/EU (EC, 2013) recommendations, sediments from this area, areas similarly polluted and nearby natural resources on the Ramsar list, have all been monitored for heavy metals, organic pollutants and other priority substances (Prokić et al., 2016; Grba et al., 2016; Grba et al., 2017; Ilijević et al., 2015; Savić et al., 2013; Dalmacija et al. 2010 and 2008; Crnković et al., 2008; Pantelic et al., 2008; Škrbić et al., 2005; Milenkovic et al., 2005; Belic et al., 2004 and Stojsic and Skoric, 1996). The monitoring program consists of 8 heavy metals (Ni, Zn, Cd, Cr, Cu, Pb, As and Hg), 16 PAHs, selected pesticides (aldrin, dieldrin, endrin, (α-HCH, β-HCH, γ-HCH (lindane), δ-HCH, heptachlor, heptachlorepoxide, endosulfan, DDT and its metabolites) and polychlorinated biphenyls (PCB) described as sum of congeners (28, 52, 101, 118, 138, 153 and 180). Monitored

activities were carried out according to the Serbian legislation and European recommendations, in order to investigate the level and origin of pollution in the Great Bačka Canal. In almost all cases, the results for pesticides and PCBs were below the limits of detection (LOD), with some variation: in 2007, dieldrin (0.74 μg/kg), α-HCH (3.78 μg/kg), γ-HCH (2.08 μg/kg) and δ-HCH (0.90 μg/kg) were detected, whereas for 2014 there were no measurements above the LOD. This data was inconsistent, was therefore excluded from the analysis in this paper. Based on the aforementioned literature data, elevated concentrations were detected for these parameters in the sediments and aquatic systems of watersheds in the vicinity of the investigated area of the Great Bačka Canal, e.g. Tisa (Sakan et al., 2013 and 2007) to the north and the Danube river in the south (Pavlović et al., 2016). These studies suggest that organic and inorganic substances from surrounding industrial sources may substantially degrade these and surrounding areas. Monitoring programs have been based on previous studies at this location (Dalmacija et al., 2006), and also on certain characteristics of the investigation area, such as the steady economic growth of the food industry (the metal industry was also active in the past (before 2007) with poor quality effluents, agriculture activities, flooding processes and others. In a wider context, many studies have confirmed the selection of the monitored pollutants (predominantly heavy metals and PAHs) in sediments across Europe (Gómez-Ramírez et al., 2014; Panagos et al., 2013 and Rippey et al., 2008). Special focus was given to heavy metals (Ni, Zn, Cd, Cr, Cu, Pb, As and Hg) and the 16 selected EPA PAHs (PAH16) in surface sediments (up to 0.50 m), calculated on the dry weight, during investigations in 2007 and 2014 in the Great Bačka Canal. The aim of this study was therefore determine the behaviour of selected significant parameters on the basis of long time monitoring data. The choice of specific multiple indicators was supported by chemometric analyses which were carried out in order to explore the degree of geological, anthropogenic and ecological hazard in the wider region of the Great Bačka Canal. The ecological and human risks are

Fig. 1. Map of sampling sites (S1 to S33) in Great Bačka Canal and the wider investigated area.

D. Krčmar et al. / Science of the Total Environment 601–602 (2017) 833–844

evaluated using several inorganic (e.g. the potential ecological risk factor (ERi) and the ecological risk indices (RI) developed by Hakanson, 1980) and organic synthetic parameters (toxic equivalency factors (TEFs) and total benzo[a]pyrene - equivalent concentration (B[a]Peq) by Nisbet and LaGoy, 1992). The quality of the investigated sediments and sources of contamination will define a specific approach to sediment management for this region and will inform the selection of Best Available Techniques (BAT) for remediation, dredging and disposal. At the local level, this approach will provide information useful for the city and municipal stakeholders, local enterprises and the policy makers of the municipality, bearing in mind the great agricultural potential of the region (crops of sunflower, sugar beet, corn, wheat etc.). This study will also demonstrate the need for adding additional substances to the EU watch list of emerging substances (Carvalho et al., 2015). 2. Materials and methods 2.1. Sampling sites and sample collection The Great Bačka Canal forms part of the Danube-Tisa-Danube (DTD) drainage network, which connects the river flows of the Danube and Tisa through Northern Serbia (Vojvodina) at the southern margin of the Pannonian Basin. The Canal is 118 km long and links the Danube at Bezdan with Tisa at Becej. On the banks of the Canal are urban settlements Vrbas, Kula and Crvenka. The Canal was built in the 17th century, in order to facilitate drainage, irrigation and transport. The upstream section consists of the Vrbas-Bezdan canal (80.9 km), and the downstream section consists of the part of the Bečej-Bogojevo canal, between Bečej and the triangle shaped area near Vrbas (39.0 km) (Fig. 1). The Great Bačka Canal has four sluice gates and four shipping locks, at Bezdan, Mali Stapar, Vrbas and Bečej. The Canal is fed its water gravitationally from the Danube, by means of water intake pumps near Bezdan, gravitationally from the Bački kanal, by means of tributaries Krivaja and Beljanska bara and from the first aquifer layer (Stojanović et al., 2014). The pollution in the Canal came in the second half of the 20th century as a result of the rapid development of industry and inadequate waste water treatment, with effluents discharged directly into the recipient. This study focused primarily on highly contaminated sediments in the Great Bačka Canal in the town of Vrbas. This 6 km long stretch of canal represents a sink for all the pollution from the industrial and municipal wastewater of Vrbas, Kula and Crvenka. Via the lateral channels (I-61, I-64, I-KC III) around 400,000 m3 of sediment contaminated with heavy metals has accumulated (Fig. 1). The study is based on a comparison of the results obtained during two periods of research (2007 and 2014). The data analysed was obtained from monitoring sediment profiles S1 to S33, which were selected due to their significant proximity to various anthropogenic and natural influences. For chemical characterisation of the sediments, surface sediment profiles were investigated, with samples taken from a representative depth profile from 0 to 0.50 m. The consistent vertical pollution distribution of the substances investigated with similar geo-chemical characteristics were compared to deeper samples of up to 1 m (Krčmar, 2006). This sediment profile therefore reflects the sedimentation process and accumulation of pollutants in the recent past (2007– 2014). Samples were collected during 2007 and 2014. Fresh sediments were collected by Eijkelkamp core sampler from each location, according to standard method for sediment sampling ISO 5667–12:1995. Samples were taken from left and right side and the middle of the Canal. Sampling point selection criteria were based on previous investigations of the spatial distribution of industries and related pollution. The locations were densely distributed in the upper section of the canal, at the industrial locations downstream from Vrbas lock (S33 to S14 samples), as this section has not been dredged, suggesting the buildup of a great

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amount of contaminated sediment. The sampling points from S13 to S1 downstream were previously dredged, but are under the influences of industry and pollutant transfer. Location accessibility and the need for representative samples also informed the eaxact choice of location (Krčmar, 2006). Sediment samples were collected in glass jars (for the analysis of organics) and plastic containers (for analysis of heavy metals). The samples were stored at 4 °C and transported to the laboratory immediately for further analysis. All materials used for sampling, treatment and storage of samples and solutions were carefully chosen, acid-cleaned and conditioned to minimize sample contamination (EPA, 2004). The same sampling procedures were used to sample other locations to provide background analyte values. Sampling site Sback was sampled from 25 to 50 cm depth, and is located north-west of the Great Backa Can at the confluence of the Tisa and Danube rivers, as shown in Fig. 1. The background values of heavy metals were uniformly distributed and reported as mean values of 10 samples from 2007 to 2014, two samples per year, from natural sediments without anthropogenic influences. The mean values are similar to the median values of these natural samples (Horckmans et al., 2005). 2.2. Physico-chemical analyses 2.2.1. Reagents and standards For the purpose of the physico-chemical analyses, deionized water was used, obtained by Labconco system (resistivity at 25 °C 18 MΩ·cm). All glassware and plastic materials used were previously cleaned by soaking in dilute acid for at least 24 h and rinsed abundantly in deionized water. For metals analysis, standard solutions were prepared from analytical grade Suprapure quality reagents (Merck or J.T. Baker). For the purpose of the digestion of the sediment samples HNO3 and HCl Suprapure acids were used (Merck). PAHs standard solution was purchased from Dr. Ehrenstorfer (PAHMix 64 in Benzene/Dichloromethane = 50/50 in concentration of 2000 mg L−1 of each compound). Phenanthrene-d10 was used as the internal standard (Supelco, 2000 μg mL−1 in methanol solution). For the mineral oil (total petroleum hydrocarbons (OILm)) determination, a standard mixture of mineral oils of different boiling points: type A (diesel oil without additives) and Type B (lubricating oils free of additives), and n-decane (C10H22), n-eikosan(C20H42) and tetracontane (C40H82) was purchased from Dr. Ehrenstorfer. All organic solvents used were for organic residue analysis, and were purchased from J.T Baker and Pestanal. Florisil with granulation of 150 μm to 250 μm (60 mesh to 100 mesh) was purchased from Sigma–Aldrich. Pseudo-total trace metal contents were determined in triplicate after nitric acid digestion by standard method (USEPA Method 3051a, 2007b) and the mean values reported. Relative standard deviations (% RSD) obtained (n = 3) were below 10.0%. Metal contents were determined by AAS (Perkin Elmer AAnalyst™ 700) according to the standard method (USEPA Method 7010, 2007d). The microwave digestion method used was validated using the Trace Elements on Fresh Water Sediment CRM (Sigma-Aldrich). 2.2.2. Preparation and characterisation of sediment samples The sediment samples collected were air dried in accordance with method ISO 11464:2006. Samples were then passed through a 250 μm sieve and characterised for the following parameters: Oxidation – reduction potential was determined by modified APHA AWA WEF 2580 protocol (Rice et al., 2012). Dry matter was according to the EN 12879:2000 protocol; organic matter (OM) expressed as loss on ignition according to EN 12879:2000; and clay content, fraction b2 μm, according to ISO 11277:2009. Chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) were determined by EPA Protocols (EPA, 1986). According to the recommendations in Serbian legislation (RS 50/ 2012), only the clay fraction was analysed. The metal contents for a

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given sediment were corrected to a standard sediment with 25.0% clay and 10.0% organic matter (RS 50/2012). For determining the pseudo-total metals content of the investigated sediments, an HNO3 HCl mixture (3:1) was used for acid digestion in microwave oven Milestone, Stare E microwave) (EPA 3051A). Sediment extracts were analysed for Ni, Zn, Cd, Cr, Cu and Pb by flame atomic absorption spectrometry-FAAS (Perkin Elmer, AAnalyst 700) in accordance with EPA method 7000b. Arsenic was measured by graphite furnace atomic absorption spectrometry-GFAAS according to EPA method 7010. Hg was measured by cold vapour atomic absorption spectrometry by modified EN 1483:2007 method. The mineral oils in the sediment were measured by gas chromatography–flame ionization detection (GC–FID; Agilent Technologies 6890) according to ISO/TR 11046:1994 method. PAHs were analysed by gas chromatography with mass detection (Agilent Technologies 7890A GC System/5975C VL MSD) with Agilent J&W Scientific DB-5MS column according to the EPA methods 8270C (EPA, 2008), 3660B (EPA, 1996b), 3630C (EPA, 1996a) and 3550b (EPA, 2007a). As laboratory quality assurance and quality control methods included the use of standard operating procedures, calibration with standards, analysis of reagent blanks, recovery of spiked samples and analysis of replicates the method detection limits (MDL), practical quantitation levels (PQL), recoveries and precision expressed as the relative standard deviation (RSD) of the analytical methods for the investigated heavy metals are presented in Table 1 in Supplementary material (SM1). For PAHs, method detection limits (MDL) and practical quantitation levels (PQL) were determined during the validation of methods for analysis of samples with low contents of analyte in 6 replicated. MDLs were calculated as 3 X STD (standard deviation), while PQLs were calculated as 5 X MDL. The MDLs, PQLs and STD for each parameter are given in the Supplementary material (ST1). The precision of PAHs was determined by analysis of a 12 triplicate certified reference material by Certified Reference Material, PAHs, PCBs and Pesticides in Fresh water Sediment (CNS391-50 g), Fluka. For all samples extractions were performed in triplicate, and the results are expressed as the mean. The 16 US EPA priority PAHs (PAH16) quantified in this study were; naphthalene (Nap), anthracene (Ant), phenanthrene (Phe), fluoranthene (Flur), benzo[a]anthracene (BaA), chrysene (Chr), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), benzo[g,h,i] - perylene (BghiP) and indeno [1,2,3-cd] pyrene (InP), pyrene (Pyr), benzobenzo[b]fluoranthene (BbF), dibenzo[a,h]anthracene (DahA), acenaphthene (Ace), acenaphthylene (Acy) and fluorine (Flo). All analyses were carried out in triplicate, and the results were expressed as the mean.

2.3. Data analysis After detailed analysis of the concentrations of the substances investigated in the Great Bačka Canal in 2007 and 2014, several major synthetic multiparameter indicators were applied to gain a complete picture of the complex pollution situation. These indicators were divided into two major groups, one for inorganic and the second for organic pollutants. The origins (anthropogenic or geogenic) and toxicity (toxicity and carcinogenicity effect on biota) of both groups of parameters were determined.

2.3.1. Inorganic indicators First, the well-known and very useful geo-accumulation index (Igeo) (Müller, 1979) was calculated in order to distinguish geogenic and anthropogenic factors, followed by the potential ecological risk factor (ERi) as a measure of potential toxicity to biota and the ecological risk index (RI) (Hakanson, 1980) presented as the sum of all ERi for heavy metals in the sediments at each sampling site (calculation methods and categorization key given in the Supplementary material (SM 2.).

2.3.2. Organic indicators In order to compare and systematize the nature of inorganic and organic substances in this specific and complex pollution hot spot, several organic indices were also calculated. The permanent, intensive and extremely high diffuse pressure on biota from pollution from industry, agriculture and settlements in the region requires a complex multicriterion approach in order to determine the sources, level and fate of pollution. In this research the focus of organic pollutants was on potential sources and the carcinogenicity effect of PAHs, based on their persistence at the 33 sites investigated in 2007 and 2014. The first determinant of PAHs was classifying its origin as petrogenic, mixed or pyrogenic using several diagnostic ratios (Table 1). LMW/ HMW ratio values were calculated based on petrogenic sources including PAHs with low molecular weights (LMW) containing 2–3 benzene rings, while pyrogenic sources mostly include PAHs with high molecular weights (HMW) containing 4–6 benzene rings (Malik et al., 2011; Luo et al., 2008; Nagy, 2007; Wang et al., 2006; Doong and Lin, 2004; Rocher et al., 2004; Maldonado et al., 1999). In addition, several parameters were used for classification of pyrogenic, mixed, petrogenic fuel combustion or grass, coal and wood combustion origin (Vane et al., 2014). The four selected PAH ratios were not in agreement (Table 1), and so the total index was calculated in order to define the sources of PAHs in a investigated sediment matrix (Orecchio, 2010; Mannino and Orecchio, 2008; Yunker et al., 2002). Total index = Flur/(Flur + Pyr)/0.40 + Ant/ (Ant + Phe)/0.20 + BaA/(BaA + Chr)/0.10 + InP/(InP + BghiP)/0.50. Values of this index above 4 represent PAHs originating prevalently from high temperature processes (combustion) while lower values indicate prevalently low temperature sources (petroleum products). In order to quantify the potential carcinogenicity of the sediment, toxic equivalency factors (TEFs) were calculated based on 7 carcinogenic PAHs (CANPAHs) relative to benzo[a]pyrene. Using relative potency of the different PAHs to be considered in a site-specific risk assessment (Nisbet and LaGoy, 1992) the estimation of the total benzo[a]pyrene equivalent concentration (B[a]Peq) were calculated as: Total B[a]Peq = ∑ iCi × TEFi. The Ci is the concentration of individual CANPAHs and TEFi is the corresponding toxic equivalency factor as followed: (TEF (BaA) = 0.10, TEF (Chr) = 0.001, TEF(BkF) = 0.01, TEF (BaP) = 1.00, TEF (BbF) = 0.10, TEF (InP) = 0.10 and TEF (DahA) = 1.00). 2.4. Statistical analysis of data set In order to design a systematic monitoring of highly contaminated sediment using multiple variables the followed statistical and empirical procedures were applied. Each of the inorganic and organic parameters were measured with the same sampling frequency at 33 sampling sites (S1–S33) in each year (66 samples in total). After removing outliers, a summary of 15 variables and 66 samples were considered for statistical processing, thereby satisfying criteria for the number of minimal analysed samples (Henry et al., 1984) when selecting key variables of interest by particular sources. Organic and inorganic data processing was carried out using STATISTICA (Statsoft Inc., USA; version 12.0 for Windows), particularly the principal component analysis/factor analysis (PCA/FA) on the average organic and inorganic data sets, characterising the collected sediment samples in order to select key variables of interest by particular sources (anthropogenic, geochemical or chemistry (complexation) features). This approach was suggested by several authors (Zhiyuan et al., 2011; Liu et al., 2009 and Idris, 2008). PCA is a dimensionality reduction technique that helps to simplify data and make it easier to visualize by finding a set of principal components (PCs) which are responsible for the majority of variation in the data. FA is used to extract a lower dimensional linear structure from the data and is a powerful means for detecting similarities among samples. FA can reduce the contribution of less significant variables obtained from PCA, and a new group of variables known as varifactors (VFs) is extracted through rotating the axis defined by PCA (Duan et al., 2016).

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Table 1 Characteristic PAH molecular diagnostic ratios for surface sediments (from 0 to 50-cm depth) from sites S1 to S33 of 33 samples from Great Bačka Channel for 2007 and 2014. Molecular diagnostic ratio

Samples from 2007

Source parameters

Range

Mean

RSD(%)

Range

Samples from 2014 Mean

RSD(%)

Source parameter classification Petrogenic

Pyrogenic

LMW/HMW Flur/(Flur + Pyr) InP/(InP + BghiP) Ant/(Ant + Phe) BaA/(BaA + Chr) Phe/Ant Total index

0.19–0.76 0.15–0.62 0.08–0.93 0.02–0.62 0.06–0.98 0.62–42.67 2.13–13.92

0.47 0.33 0.57 0.15 0.41 15.50 6.77

32.46 37.75 40.67 94.44 57.52 94.78 38.93

0.10–3.65 0.24–0.90 0.08–0.92 0.01–0.22 0.10–0.99 3.47–163.93 3.86–13.94

1.00 0.64 0.53 0.10 0.48 19.56 7.89

64.63 27.96 41.75 54.60 52.09 158.35 34.15

N1.00 b0.40 b0.20 b0.10 b0.20 N10.00 b0.4

b1.00 N0.40 N0.50 N0.10 N0.35 b10.00 N0.4

This approach is able to illuminate temporal and spatial variations in sediment quality and to identify the potential influencing factors that explain changes in sediment quality parameters in the Great Bačka Canal. Pearson's correlation coefficient analysis was used due to identify the relationships among contaminants in the surface (up to 0.5 m) sediments and their probable sources. Ward's method was used with squared Euclidean distances, as a measure of similarity to assess the interrelationships among the sampling sites. Analysis of variance (ANOVA) was performed to analyse the significant spatial and temporal differences (p b 0.05). The wider dependence of organic and inorganic parameters on the three factor components was illustrated by three-dimensional scatter plot. 3. Results and discussion 3.1. Results of sediment characterisation The monitoring program was carried out in 2007 and 2014, sampling surface sediments (from 0 to 0.50 m), at 33 locations on the Great Bačka Canal. All 16 EPA PAHs were measured, calculated on the dry weight, including 10 PAHs (Nap, Ant, Phe, Flur, BaA, Chr, BkF, BaP, BghiP and InP) given in national legislation (RS 50/2012) and four heavy metals (Cd, Pb, Hg and Ni) from the priority substances list (EC, 2013). In accordance with the Serbian legislation and site-specific characteristics, 4 more metals (Zn, Cr, Cu and As) and mineral oils (OILm) were also monitored. Due to the intense pollution pressures by water transfer observed in the lateral channels (I-61, I-64, I-KC III and the main canal, Fig. 1), COD and BOD5 were also measured. The average BOD5/COD ratios at each sampling site ranged from 0.23 to 0.64, with an average value of 0.48, indicating a low to moderate contribution of biodegradable organic matter in the total organic matter budget, which may affect the distribution of other organic and inorganic pollutants. These organic compounds originate mainly from the food industry, which for decades

Fuel combustion

Grass/coal/wood combustion

0.40–0.50 0.20–0.50

N0.50 N0.50

has discharged effluents without pre-treatment directly into the canal, and untreated municipal wastewaters. The influence of pig farms and diffuse sources of pollution from the agricultural area are also present (Fridrich et al., 2014). Spatially, between the 33 selected locations, an uneven distribution of the average amount of organic matter, mineral oil and almost all heavy metals except As, was observed. The mean and RSD values (e.g. for Zn 1850 mg/kg (RSD 104%), Ni 102 mg/kg (RSD 58.0%), Cd 3.14 mg/kg (RSD 50.7%), Cu 315.63 (RSD 50%) and Cr 179 mg/kg (RSD 138%)) were greater in 2007, although they were still high levels of heavy metals in 2014 (Table 2). Generally, the mean and RSD values of ∑PAH16 (523 μg/kg (RSD 29.8%) in 2007 and 870 μg/kg (RSD 48.4%) in 2014) show an opposite pattern, with higher concentrations in 2014 (Table 3). The average content of organic matter expressed as loss on ignition ranged from 8.40–19.5% in 2007 with mean values of 15.8 and from 9.70 to 47.2% in 2014 with average values of 19 in 2014 (Table 2). Based on these results, it can be concluded that most of the sediment samples represent sediments with relatively low to medium organic carbon contents. Inorganic and organic parameters (range, mean and RSD values) in the surface sediments of Great Bačka Canal are listed in Tables 2 and 3. During the investigation period (2007 and 2014), all parameters showed significant spatial variations (ANOVA, p b 0.05) and the concentrations in the surface sediments corresponding with industrial activities in 2007, as well as municipal wastewater discharge and agricultural wastewater. Although a large number of both organic and inorganic parameters showed variations with high RSD (Tables 2 and 3), no particular temporal trend due to seasonal variation was observed. 3.2. Inorganic substances in sediment and ecological indices With the exception of arsenic, which is of geological origin (Dalmacija, 1998), the mean values for the heavy metals at all 33 sites

Table 2 Comparison between heavy metal concentrations(mg/kg dry weight), mineral oil (mg/kg) and sum of PAH10 (μg/kg dry weight) of all sites (S1–S33) for 2007 and 2014 from investigated area of Great Bačka Channel with relevant natural, national and different international regulations values. Sediments from this study

Comparison data

Samples from 2007

Ni Zn Cd Cr Cu Pb As Hg OM Min. oil ∑PAH10

Samples from 2014

Natural and legislation values

Sediment quality guidelines (SQGs)

Range

Mean

RSD(%)

Range

Mean

RSD(%)

Sback

UCC

Northern Serbia

RS 50/2012

ÖNORM S 2088–2

ERL

ERM

TEL

PEL

26.0–345.39 110–8500 0.17–7.80 1.70–1100 42.0–620 8.28–150 4.50–36.84 0.27–1.60 8.40–19.5 40.27–81.82 182.47–957

102.07 1847.19 3.14 179.23 315.63 52.84 18.88 0.90 15.85 63.88 349.67

57.94 103.91 50.67 137.66 50.07 59.49 50.07 56.04 26.84 21.38 39.01

19.77–172.03 55.57–1098.43 0.07–3.23 38.70–2329.44 25.09–447.48 8.31–128.74 3.43–52.41 0.05–3.29 9.70–47.2 84.0–2561 234.87–2542.32

72.32 419.60 0.60 359.99 192.68 37.06 22.66 0.49 19.12 812.27 746.63

55.61 60.59 117.68 149.56 56.77 71.53 55.25 116.63 39.24 75.97 58.79

28.29 86.68 0.15 31.98 21.78 15.31 30.89 0.13 / / /

44.0 71.0 0.098 85.0 25.0 17.0 5.10 0.05 / / /

36.8 76.3 2.85 41.0 28.9 17.0 / / / / /

44.0 430 6.40 240 110 310 42.0 1.60 / 3000 10,000

60.0 300 1.00 100 100 100 20.0 1.00 / / /

30.0 120 5.00 80.0 70.0 35.0 33.0 0.15 / / /

50.0 270 9.00 145 390 110 85.0 1.30 / / /

18.0 123 0.60 37.3 35.7 35.0 5.90 0.17 / / /

36.0 315 3.53 90.0 197 91.3 17.0 0.49 / / /

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Table 3 Concentrations and risk assessment guideline values of PAHs (μg/kg dry weight) in surface sediments from S1 to S33 sampling sites from investigated area of Great Bačka Channel for 2007 and 2014 with relevant local and different international regulations values. Sediment concentrations (μg/kg)

Comparison data Samples from 2007

PAHs

Aromatic ring

Nap 2 Ant 3 Phe 3 Flur 3 Flo 3 Ace 3 Acy 3 Pyr 4 b 4 BaA b 4 Chr 5 BkFb 5 BaPa 5 BbFb BghiP 6 b 6 InP b 6 DahA ∑PAH10 ∑PAH16 ∑CANPAHs ∑CANPAHs/∑PAH16 ∗ 100% ∑PbaPeq

Samples from 2014

SQG (μg/kg)

Range

Mean

RSD(%)

Range

Mean

RSD(%)

ERL

ERM

TEL

PEL

1.82–25.0 3.00–95.0 20.0–150 6.00–55.0 6.91–53.10 0.65–1.70 1.05–1.89 27.40–156 1.00–99.0 1.00–180 7.00–63.0 14.0–90.0 2.61–96.0 2.00–80.0 1.00–187 7.29–132 182.47–957 253–1044.37 121.42–599.50 28.95–69.48 (%) 42.58–221.75

9.16 15.06 83.27 32.70 22.68 0.90 1.51 72.76 24.0 45.82 33.41 50.64 28.24 20.03 35.58 47.12 349.67 522.88 264.80 51.10 (%) 106.63

87.34 144.14 44.44 39.16 63.85 20.71 16.99 59.37 95.02 97.08 59.71 50.32 109.26 87.83 115.96 96.69 39.01 29.82 34.99 21.49 57.13

1.82–84.0 3.00–131 28.0–892 17.0–221 4.81–43.19 0.22–0.98 0.91–1.67 20.33–95.22 6.00–113 1.00–339 23.0–216 8.00–126 0.22–76.72 9.00–520 1.00–290 5.29–102.21 234.87–2542.32 365.08–2610.34 146.48–1117.80 16.11–59.61 30.56–176.95

16.37 25.69 237.57 100.86 17.05 0.65 1.28 50.84 43.97 76.23 73.51 41.40 21.33 68.56 69.69 37.07 746.63 870.47 361.97 41.71 90.34

133.97 114.92 81.19 56.57 70.93 24.67 17.37 52.81 66.77 98.80 54.26 69.99 120.53 151.56 107.75 96.07 58.79 48.43 52.80 24.04 39.58

340 85.0 225 600 35.0 20.0 40.0 350 230 400 280 400 320 85.0 240 63.4 / / / / /

2100 960 1380 3600 640 500 640 2200 1600 2800 1620 2500 1880 NG NG 260 / / / / /

NG NG 41.90 111 NG 10.0 10.0 53.0 31.70 57.10 60.0 31.90 70.0 NG NG 6.22 / / / / /

NG NG 515 2355 NG 90.0 130 875 385 862 610 782 710 NG NG 135 / / / / /

NG = No guideline. Note: Classified by the IARC as follows: a Carcinogenic to humans (group 1). b Possibly cancerogenic to humans (group 2B).

exceed the background (analyte) values (Sback, Table 2). The geoaccumulation index (Igeo) (Müller, 1979), potential ecological risk factor (ERi) and ecological risk index (RI) (Hakanson, 1980) were therefore used to gain a clearer picture of the status of the sediment (Supplementary data, Figs. 1 and 2). Low Igeo values have lower reliability, due to possible variations in heavy metals concentration and other factors. This study thus focuses on Igeo values above 1, which are classified as moderately polluted (class 2) or worse. Integrated Igeo, ERi and RI category values are given in Supplementary data (Table 2.), where the Igeo values are plotted in Fig. 1, ERi values are presented in Table 3 and RI values are plotted in Fig. 2. Before elaborating the synthetic parameters it is important to note that in the upper course of Great Backa Canal there is historical evidence of high industrial activity (two sugar refineries, a metal works, a

tannery, an edible oil refinery, slaughterhouses, etc.). The discharged of untreated or partially treated wastewater into the Canal by these industries has placed an intensive and large pressure on the sediment and aquatic ecosystems. Anthropogenic sources were confirmed by sequential extraction procedure for Ni, Zn, Cd, Cr, Cu and Pb (Krčmar et al., 2013 and Krčmar, 2010). Metal mobility was based upon the modified BCR (European Community Bureau of Reference) sequential procedure (Jamali et al., 2009). Results showed these metals were in the adsorbed, removable and carbonate fractions and are therefore readily bioavailable, and were of anthropogenic origin, as confirmed by the synthetic parameters below. Generally, the Igeo index ranged from − 4.80 for Cr to 6.00 for Zn (Fig. 1a, Supplementary data) in 2007 and from − 3.80 for As to 5.60 for Cr in 2014 (Fig. 1b, Supplementary data) confirming a general

Fig. 2. PAHs cross plots for the ratios BaA/(BaA + Chr) vs InP/(InP + BgP). Circles represent 33 samples from the Great Bačka Canal obtained from the surface sediment data set (up to 0.5 m) for 2007 a) and 2014 b) respectively.

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decreasing in the level of pollution over time. Interestingly, Cr has the highest variance from − 4.80 to 4.50 in 2007 and maximum I geo values in 2014. This suggests great periodical anthropogenic input of Cr, with negative I geo (− 0.30) values at S18, seven years after the decline in industrial activity. The high Igeo for the heavy metals in this study, particularly Cd and Cr, indicates they pose a risk of secondary water pollution and harmful effects to biota such as bioaccumulation and biomagnification due to remobilization, transport, redistribution and bioturbation of inorganic pollutants in river sediments and alluvial soils (Hilscherova et al., 2007 and Koethe, 2003). The 2007 mean ERi for Cd was about 650, classified as a very high potential ecological risk to biota, but by 2014, the mean level decreased to considerable risk (ERi = 124) due to lower industrial activity. Although large numbers of diffuse pollution sources are present in this area, the lower risk was confirmed by the sequential extraction data relating to the distribution of metals in the different fractions. Cd may originate by leaching from agricultural soil after fertilization or from landfills (Grant and Sheppard, 2008) as 53.0% of the samples were defined as moderate risk based on the CPR risk classification. The mean Igeo of 3.54 indicates moderately to strongly polluted levels at almost all sites, confirming permanent sources of pollution in the larger area. In 2014, the sharp reduction in the mean Cd value (Igeo = 0.55) is probably due to a decrease in agricultural activity and a possible redistribution of this metal in the sediment. The high Igeo levels of Cu (3.05 in 2007 and 2.28 in 2014) indicate a steady state of moderately to strongly polluted levels at almost all investigated sites, demonstrating the negaative impact of wastewater from the surrounding farms and the corrosion of metal structures of nonfunctional industrial facilities. The lower Zn Igeo levels followed this trend (Fig. 1a and 1b, Supplementary data). Mean Ni Igeo values decreased from 1.06 to 0.55 between 2007 and 2014. This metal is now mainly of geogenic origin, but in 2007 most locations were either moderately to strongly polluted, with dominantly anthropogenic influences. By 2014, most locations were practically unpolluted to moderately polluted. Igeo values were lower for Pb and somewhat higher for Hg, but followed this same trend. In contrast, as shown in Fig. 1a and b, the values for As are the lowest, categorised this parameter as practically uncontaminated by anthropogenic influence. There is no significant distribution of concentration by locations, but some patterns may be noted. In the northern area in the vicinity of industrial influences, S28 and S29 were very strongly polluted by Cr and strongly Cu in 2014. Locations S13 to S15 were similarly polluted for Zn, Cd, Cr and Cu in 2007, and locations S7 to S28 were contaminated with Zn, Cd, Cu and Hg. Generally, the heavy metal pollution is decreasing over time. In addition to the As and part of the Ni contamination, Pb is mainly from geogenic origin, with mean Igeo values below 1. Potential ecological risk factor (ERi) mean values were below 40 for Ni, Zn, Cr, Pb and As, showing low risk to biota (Table 3, Supplementary material). Hg is associated with considerable risk in 2014 and high ecological risk level in 2007. The ecological status improved greatly for Cd, falling from very high to considerable potential risk (ERi = 124) in 2014. Cu values in 2007 and 2014 suggest it poses a moderate risk to biota. The ecological risk index (RI) values for all heavy metals at all 33 sampling sites showed significant reductions between 2007 and 2014, falling from mostly high to moderate risk status (Supplementary data, Fig. 2.). By, 2014 RI values for most samples are below 300 (low to moderate risk), with the exceptions of sites S9, S13-S15 and S18, which are still high risk (RI above 600). No particular sources of pollution were observed in the vicinities of these high risk locations. It is likely that the meander of the canal led to the accumulation of toxic sediments at these sites. The large variation in the values of these indices and the mean heavy metal concentrations describe periodical intense pollution in the area.

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3.2.1. Organic sediment pollution sources and toxicity indices‚ based on carcinogenic PAHs According to several diagnostic PAH ratios, the organic pollution of the surface sediments (from 0 to 50.0-cm depth) in the Great Bačka Canal in 2007 and 2014 was predominantly pyrogenic (Table 1). Flur/ (Flur + Pyr) ratios above 0.50 (ranged from 0.24 to 0.90 in 2014, mean value 0.64, Table 1) and InP/(InP + BghiP) value of 0.53 indicate the pyrogenic origin of the PAHs, which probably result from agricultural fires (burning of crop residues in the fields and woods) and coal (individual combustion chamber) combustion. The values of these parameters in 2007 suggest mixed petro (Flur/(Flur + Pyr) ratios of 0.33) from fossil fuels and industrial waste and pyrogenic sources due to higher industrial and agriculture production. The ratio of phenanthrene to anthracene (Phe/Ant) has been widely used to distinguish petrogenic and pyrolytic sources of PAHs. PAHs of petrogenic origin are generally characterised by Phe/Ant values N 10.0, whereas combustion processes often result in low Phe/An ratios (b10.0) (Mzoughi and Chouba, 2011; Lima et al., 2005). In our samples, petrogenic inputs dominated, particularly in 2014 (Table 1). According to this data, the general conclusion should be that there were mixed sources of pollution. It should however be noted that these ratios have criticized (e.g. Lima et al., 2005) due to the potential of PAH weathering to modify the ratios found at different sources. The cross plots of diagnostic ratios of PAHs for the 33 sampling sites were plotted in Fig. 2. In 2007, most of the samples are from mixed and pyrogenic sources. Samples from the northern industrial area (S21, S25, S26, S29 and S30, Fig. 1) in particular are pyrogenic. The characteristic PAH molecular diagnostic ratios in 2014 suggest most of the samples have pyrogenic and mixed sources, mainly from agricultural activity. To gain more information about the origin of the PAHs, the total index was also calculated. The results from Table 1 confirmed combustion processes as the main source of PAHs in the sediment samples, with the mean value in 2007 (6.77) increasing slightly by 2014 (7.89). After the analysis of the PAH sources, the toxicity level of the PAHs was assessed. Unlike the heavy metal concentrations, the mean sum of carcinogenic PAHS (∑CANPAHs) increased in 2014 (362 μg/kg) compared to 2007 (265 μg/kg, Table 3). The mean total contribution of these compounds to the sum of PAH16 (∑CANPAHs/∑PAH16 × 100%) was lower in 2014 (41.7%, compared to 51.1% in 2007), implying a greater prevalence of non-carcinogenic PAHs. In 2007, the values of ∑B[a]Peq from the 33 sampling sites varied from 42.9 to 222 μg/kg with a mean value of 107 μg/kg, and varied from 30.6 to 177 μg/kg in 2014 (mean value 90.3 μg/kg, Table 3), confirming the carcinogenic potency in the sediment. This observation has implications for local residents who could be affected by the carcinogenic potency of the relatively high B[a]Peq values in the sediments, as it could create a potential risk through enrichment in the food chain (Mizwar et al., 2016). The contribution of the different carcinogenic PAHs to the total benzo[a]pyrene equivalent concentration (B[a]Peq) decreased in the following orders: During 2007: BaP (49.9%) N DahA (37.4%) N InP (4.86%) N BbF (4.15%) N BaA (3.21%) N BkF (0.42%) N Chr (0.06%); during 2014: BaP (44.7%) N DahA (39.8%) N InP (6.97%) N BaA (6.22%) N BbF (2.43%) N BkF (0.86%) N Chr (0.11%). The contributions of BaP and DahA are presented in Fig. 3 with the sum of PAH16 for each sampling site. The Ant concentrations were added due to results from the statistical analysis (3D factor components scatter plot, Fig. 4) which showed its capacity to complex with heavy metals. Ant and BaP are probably best used as local urban indicators because under summer atmospheric conditions, they will not transport long distances (Yunker et al., 2002) and due to its carcinogenic characteristics, DahA also represents a useful parameter. Between 2007 and 2014, the concentrations of BaP and DahA decreased, whereas Ant and the sum of PAH16 increased (Fig. 3, Table 3). Bearing in mind the decrease in industrial activity after 2007, this anomaly could be explained by the uneven dynamics of a variety of non-actinomycete bacteria which can metabolize large numbers of PAHs (Zhang

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Fig. 3. The results of characteristic PAHs of interest (Ant, BaP and DahA) and ∑PAH16 (divided by 10 indicated in the figure as (∑PAH16)/10) are presented for each year 2007 a) and 2014 b) respectively.

et al., 2006; Siddiqi et al., 2002 and Watanabe, 2001) and fungi, especially white-rot fungi, which are capable of degrading PAHs in soils (Boyle et al., 1998). PAHs may also originate from fertilizer (Nam et al., 2003) with loss mechanisms in the soil, such as abiotic degradation, volatilization, biodegradation, transboundary transfer and via crops (Moreda et al., 1998). The concentrations of all these PAHs varies from the south (S4 to S9), via the middle (S19 to S23) to the northern (S28 to S33) bank of the Canal (Fig. 3). This could be attributed to accumulation from the river and diffuse PAHs source from the surrounding area, which is mainly agricultural. The significant contributions of BaP and DahA to the ∑BaPeq observed during this investigating period strongly suggests that these compound should be considered in the assessment of human and ecological risk from exposure to PAHs locally, and in the wider region. Based on the degree of contamination, none of the surface sediments are in need of PAH remediation, but further assessment of the environmental risks associated with the carcinogenic PAHs in this highly contaminated area should be continued. A more frequent or continual monitoring program is required to detect new pollution and investigate its origin. With a larger data set, clustering of heavy metals, organic parameters and PAHs can be observed with greater accuracy and reliability, increasing the confidence in the identification of particular pollution sources and their distributions in this region.

3.3. Application of sediment quality guidelines In order to evaluate the quality of the investigated sediments, the measurements made in this study were compared to the natural and legislation values of several international sediment quality guidelines (SQGs), including national legislation (RS 50/12), the related Austrian regulative (ÖNORM S 2088-2 2000) and several other sediment or soil quality guidelines from around the world: UCC (Upper Continental Crust) for loess sediment (Rudnick and Gao, 2004), threshold effect level (TEL), probable effect level (PEL), effects range-low (ERL) and the effects range-median (ERM) given by Burton (2002). TELs represent low threshold concentrations below which adverse effects upon sediment dwelling fauna would be expected only infrequently, and the PELs represents high threshold concentrations above which toxic effects on ecosystems are likely to occur (Bai et al., 2015). Concentrations at or above ERM values represent a probable effect range within which adverse biological effects frequently occur and concentrations below the ERL represent a minimal-effect range that estimates conditions where biological effects are rarely observed. Contaminant concentrations in sediments between the ERL and ERM represent the range within which biological effects will occasionally occur (Binelli et al., 2008).

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Fig. 4. 3D Factor Plots in Related Space (loading of three BFs and AFs) obtained from the surface sediment data set (up to 0.5 m) for 2007 and 2014 respectively.

An interesting comparison may be made with the global levels of inorganic compounds for loess sediment such as the UCC values (Table 2). If the measured values are higher, enrichment of heavy metals in the sites investigated is implied, and further investigation and risk assessment is recommended, with a focus on potential harm to humans, consumable plants and groundwater ecosystems, according to the features of the site.

Remediation of contaminated sites could be conducted by using two well-applied processes described in the Pre-Feasibility Study with a general plan for dredging, depositing and remediation of canal sediments (2015). Solidification can increase the compressive strength, decrease permeability, and encapsulate hazardous constituents, and stabilization can convert contaminants into less soluble, mobile, or toxic forms (EPA, 2007a, b, c, d, e and Wilk, 2007).

3.3.1. Heavy metals sediment quality guidelines With the exception of the geogenic As, all heavy metals concentrations in the investigated sediments were several times higher than the native background values. Zn and Cu have extremely high mean values in comparison (Table 2). In 2007, only Hg had lower mean values than those prescribed by the Austrian regulative (ÖNORM S 2088-2 2000). All mean values of heavy metals have higher values than the UCC for loess sediment. Although the Cd means from 2014 are lower than the Northern Serbia (Vojvodina) (Kostić, 2001), national norm (RS 50/ 2012) and SQG values, earlier, the 2007 mean Cd values were higher than those prescribed by the Austrian regulative (ÖNORM S 2088-2 2000) and natural values, indicating anthropogenic Cd sources such as sewage sludge, manure and the application of cadmium-containing fertilisers to the surrounding fields (Grant and Sheppard, 2008). Ni, Zn and Cr have mean values higher than the ERL, ERM, TEL and PEL (Table 2), indicating they are present at concentrations which are harmful to biota. The contents of Cu, Pb and Hg from 2007, and Cu, Pb and Hg from 2014 were higher than the ERL and TEL. The decrease in Pb sediment values from 2007 (52.8 mg/kg) to 2014 (37.0 mg/kg) correlates with the conversion from leaded to unleaded fuel in Serbia after 2007. The mean value for arsenic (18.8 mg/kg in 2007 and 22.6 in 2014) is only lower than the ERM, and represents a concentration where adverse effects are likely to occur and also has a significant impact on biota, although it should be noted that higher natural values of these metals in the investigated area have been previously observed (Dalmacija, 1998). Once again, all the other heavy metals apart from As significantly exceed the background values, implying anthropogenic origin. It is important to note that the maximum and mean values in 2007 and 2014 for Cu and Cr (Table 2) exceed the prescribed remediation values (RS 50/2012). The sediment is therefore in need to remediation.

3.3.2. PAHs and mineral oil sediment quality guidelines National legislation (RS 50/2012) regulates the total concentration of 10 priority PAHs (Nap, Ant, Phe, Flur, BaA, Chr, BkF, BaP, BghiP and InP), which ranged from 182.5 to 2542 μg/kg, with mean values of 349.7 to 746.6 μg/kg respectively in 2007 and 2014 (Table 2). Compared to the RS 50/2012 values for the sum of PAH10 (10,000 μg/kg), these levels should have a minor effect on biota. In 2007, the sum of PAH16 had a mean level of 522.9 μg/kg, corresponding to weakly contaminated sediment (from 200 μg/kg to 600 μg/kg), and a mean value of 870.5 μg/kg in 2014, classified as contaminated (from 600 to 1000 μg/kg), as proposed by Maliszewska-Kordybach (1996). However, according to the national prescribed values, there is no need remediate the organic sediment pollution. The assessment of pollution in alluvial sediments is a complex process regarding to geochemical distribution and complexing of PAHs with heavy metals and others compound. Sediment Quality Guidelines values (SQGs) for PAH16 are presented in Table 3. The TEL was exceeded for Phe, Pyr, BaP and DahA in 2007 and Phe, BaA, Chr, BkF, BaP and DahA in 2014, suggesting that adverse biological effects might occasionally occur in the investigated region. DahA is also one of the most carcinogenic PAHs (Collins et al., 1991; Burton, 2002; Nicolaus et al., 2015; Montuori et al., 2016). Mineral oils were between 40.0 and 82.0 mg/kg in 2007, and varied widely in 2014 84.0 to 2561 mg/kg. The mean value of 812 mg/kg was lower than the values given in RS 50/2012 (Table 2). Periodical industry and diffuse sources are the likely cause of these elevated mineral oil concentrations, corroborated by the high RSD value of 75.97%. As explained below, PCA/FA analysis of the entire data set determined the common origin of the selected PAHs and heavy metals. Based on the concentration levels and synthetic indices given above, it can be stated that the concentrations of organic and inorganic

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pollutants are increasing in the examined Great Bačka Canal sediment, to levels likely to impact the agricultural land, potentially reducing the quality of local farm produce and limiting its salability. Several phytotoxicity studies have been carried out in regions with similar plant cultures. Li et al. (2012) described the ability of heavy metals to translocate from the soil to the edible parts of crops using an accumulation factor (AF). The average AFs of heavy metals in all crops were in the order Cd N Zn N Cu N Ni N Pb N Cr. It was shown that among the five categories of crops, the total AF for each metal was in the order leafy crop N inflorescence crop N root crop N grain crop (rice) N fruit crop and also report that Cd has the highest AF value (Khan et al., 2015). The influence of the bioavailable fraction of organic pollutants, particularly PAHs, on local farmland has been investigated (Rončević et al., 2016). In general, the smaller PAHs were found to be more likely to accumulate. The percent of accumulated phenanthrene was between 29.0% (for Cucumis sativus L. seed) and 69.0% (for Cucurbita pepo seeds) and for pyrene, the accumulated amounts varied from 13.0% (Zea mays seed) to 49.0%, (Cucumis sativus L. seed). Benzo(a)pyrene accumulation varied between 7.00 and 27.0% for the crop seeds investigated. The sediment results given in this work, when compared with Roncevic et al., suggest the strong possibility of crop contamination. Further studies should thus be made to quantify the crop bioavailability of the organic and inorganic compounds in the sediments.

3.4. Multivariate statistical analyses 3.4.1. Principal component analysis/factor analysis and other synthetic parameters In order to extract and analyse the most relevant data in this research, and identify parameters which interact with one another, PCA/ FA analysis of the entire data set was applied (Supplementary data (Table 4.). When considering complexation between organic matter with other compounds, it should be noted that the complex assemblages of organic molecules in fluvial sediments reflect the contaminant inputs into rivers, as well as the composition of naturally occurring sedimentary organic matter (Micić et al., 2013). Natural organic matter (NOM) in river sediments may derive from input of terrestrial vegetation from the drainagne basin and may also derive from primary producers within the water column, as well as from bacterial degradation and many other sources (Micic et al., 2011). Interactions between metals and natural organic matter can result in sorption. The metal contaminant pool requires time to diffuse into micro- or nanopores and be absorbed into organic matter and soil particles (Reid et al., 2000). Metal complexing also has a direct influence on metal adsorption to organic matter and the organic acid functional groups typically present in organic matter have a high affinity for metal cations. By loadings of experimental variables (15) on significant principal components for the Great Backa Canal data set (33 samples from 0 to 50 cm depth for 2007 and 2014), four Verimax Factors with eigenvalues N 1 were identified. The analysis below focused on values with loading N 0.70, considered as significant (strong). For the investigated sediments, in 2007 and 2014, BFs explained 72.3% and 71.7% of the total variance in the sediment quality data set. BF1, the first and most important component, accounted for 33.7% of the total variance. It was significantly correlated with Cd, Cr and Pb and moderately correlated with Cu (Table 4). This clustering is dominantly due to anthropogenic impact, although and Pb could be partly from geological (natural) origin, from the fine fraction of the parent Pannonian sediment. At the confluence of the river Sava in the Danube, suspended sediments have roughly constant Pb concentrations of 50.0 mg/kg (Klaver et al., 2007), similar to the mean values of this study (37.0 mg/kg in 2014 to 53.0 mg/kg in 2007). As expected, PC loadings (35.2%) from 2014 for AF1 indicate the Ni, Zn, Cu, OM and Cd as highly anthropogenic, while Cr and Pb were moderately loaded, probably from dual origin.

The second loadings show a different kind of complexing. In 2007, Ni, PAH16 and Ant have high loadings with moderate correlation (Table 5, Supplement material) and in 2014 negatively high BaP, PAH16 and positively moderate loading of As were identified. In the third BF, As and Hg were strongly geogenic, confirming their grouping in Fig. 4 with OM and Clay. In AF3 Ant, moderate mineral oil (r = 0.626, p b 0.01, Table 6 in Supplementary material) and Pb loads indicate spillage probably from industry, oil combustion, and exhaust gases from nearby roads. The BF4 from 2007 showing the different origins of DahA (0.74) and Clay (−0.77), showing no geogenic origin of this PAH, which is associated with mineral oil and Zn as described later. The fourth PC negative loadings from 2014 for Clay (− 0.78) and As (− 0.62) imply the geogenic origin of this heavy metal. Hg has moderate positive loading (0.62) that defines the origin of this metal as dominantly anthropogenic in 2014. Also in Fig. 4 a), the grouping of As, Hg, Clay and OM in 2007 representing the sorption of Hg by clay minerals and organic matter as important sorbents of heavy metals (Cruz-Guzman et al., 2003). In this related space, Pb, Cd and Cr show anthropogenic sources of pollution, which was also observed in the Pearson correlation analysis (for Pb and Cd r = 0.69, p b 0.01, and r = 0.48, p b 0.01 for Pb and Cr, Table 5 in Supplementary material). The complexing of Ant with mineral oil in the 3D scatter plot for both 2007 and 2014, could be explained by the majority of PAHs with 2–3 rings originating from waste mineral oil (74.7% and 73.1%, respectively) (Wu et al., 2016), further confirmed by AF3 from 2014 with strong loadings (0.84 and 0.81 respectively). In 2007 from BF4, DahA showed strong loading, and mineral oil, OM and Zn moderate loading. This could be the decomposition of mineral oil as organometallic compounds in the sediment where huge amounts of Zn could be detected (Vazquez-Duhalt, 1989). The DahA association with mineral oil also implies the presence of engine oil in the sediment (Wu et al., 2016). In 2014, As and Hg have different sources, while BaP is associated with the clay fraction and PAH16. The high partition coefficient (Kow) values of 6.84 for DahA (Table 1, Supplementary material) imply its sorbs onto organic matter (Ferrarese et al., 2008; Muller, 2002 and Wild and Jones, 1995). Heavy metals (Ni, Zn, Cu, Cr, Cd and Pb) are also in this group. The sequential extraction results show that the largest proportion of metals in the sediment are in the oxidisable fraction, indicating a high binding affinity for organic material (Jain, 2004 and Caplat et al., 2005), as is evident in Fig. 4b. The grouping of BaP and PAH16 is shown in Fig. 4. In 2007 these parameters have similar origins as Ni and Cu, and in 2014, in accordance with decreasing anthropogenic activities, are regrouped with clay. Although there are similarities in the two periods of research, it is clear that the reduction in pressure by the lower industrial activity in 2014 causes and slows the shifting of values and distribution patterns from pollutants to more natural order. The contribution of natural attenuation plays a key role in decreasing anthropogenic influences.

4. Conclusion It can be concluded that in the case of dredging the sediment from the Great Backa Canal, spatial focus should be given to the immobilization of heavy metals, in particular Cd, Cu, Cr and Zn, due to their high geo and ecological indices. The sediments investigated are sufficiently contaminated to require remediation (e.g. solidification and stabilization) or controlled disposal. The organic micro-pollutants such as the 16 US EPA priority PAHs are generally not an ecological problem and were not detected in concentrations that would require special treatment for this kind of sediment. The bioacomulation effect on local residents and enrichment in the food chain could nonetheless significantly affect the carcinogenic potency of these substances. Accordingly, systematic monitoring should

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