RESEARCH ARTICLE

Longer-term and short-term variability in pollutionof fluvial sediments by dioxin-like and endocrinedisruptive compounds

P. Macikova & T. Kalabova & J. Klanova & P. Kukucka &

J. P. Giesy & K. Hilscherova

Received: 9 September 2013 /Accepted: 3 December 2013 /Published online: 22 December 2013# Springer-Verlag Berlin Heidelberg 2013

Abstract Changes in pollutant loads in relatively dynamicriver sediments, which contain very complex mixtures ofcompounds, can play a crucial role in the fate and effectsof pollutants in fluvial ecosystems. The contamination ofsediments by bioactive substances can be sensitivelyassessed by in vitro bioassays. This is the first study thatcharacterizes detailed short- and long-term changes inconcentrations of contaminants with several modes of

action in river sediments. One-year long monthly studydescribed seasonal and spatial variability of contaminationof sediments in a representative industrialized area bydioxin-like and endocrine disruptive chemicals. Therewere significant seasonal changes in both antiandrogenicand androgenic as well as dioxin-like potential of riversediments, while there were no general seasonal trends inestrogenicity. Aryl hydrocarbon receptor-dependent potency(dioxin-like potency) expressed as biological TCDD-equivalents (BIOTEQ) was in the range of 0.5–17.7 ng/g,dry mass (dm). The greatest BIOTEQ levels in sedimentswere observed during winter, particularly at locations down-stream of the industrial area. Estrogenicity expressed as estra-diol equivalents (EEQ) was in the range of 0.02–3.8 ng/g, dm.Antiandrogenicity was detected in all samples, while andro-genic potency in the range of 0.7–16.8 ng/g, dm dihydrotes-tosterone equivalents (DHT-EQ) was found in only 30 % ofsamples, most often during autumn, when antiandrogenicitywas the least. PAHs were predominant contaminants amonganalyzed pollutants, responsible, on average, for 13–21 % ofBIOTEQ. Longer-term changes in concentrations of BIOTEQcorresponded to seasonal fluctuations, whereas for EEQ, theinter-annual changes at some locations were greater thanseasonal variability during 1 year. The inter- as well asintra-annual variability in concentrations of both BIOTEQand EEQ at individual sites was greater in spring than inautumn which was related to hydrological conditions in theriver. This study stresses the importance of river hydrologyand its seasonal variations in the design of effective sam-pling campaigns, as well as in the interpretation of anymonitoring results.

Keywords Sediments . Seasonality .Monitoring .

Dioxin-like potency . Estrogenicity . Antiandrogenicity

Responsible editor: Ester Heath

Electronic supplementary material The online version of this article(doi:10.1007/s11356-013-2429-8) contains supplementary material,which is available to authorized users.

P. Macikova : T. Kalabova : J. Klanova : P. Kukucka :K. Hilscherova (*)Research Centre for Toxic Compounds in the Environment(RECETOX), Faculty of Science, Masaryk University, Kamenice753/5, 625 00 Brno, Czech Republice-mail: hilscherova@recetox.muni.cz

J. P. GiesyDepartment of Biomedical Veterinary Sciences and ToxicologyCentre, University of Saskatchewan, Saskatoon, SK, Canada

J. P. GiesyZoology Department and Centre for Integrative Toxicology,Michigan State University, East Lansing, MI 48824, USA

J. P. GiesyDepartment of Biology and Chemistry, City University of HongKong, Hong Kong SAR, People’s Republic of China

J. P. GiesyZoology Department, College of Science, King Saud University,P.O. Box 2455, Riyadh 11451, Saudi Arabia

J. P. GiesyEnvironmental Science Program, Nanjing University, Nanjing,China

Environ Sci Pollut Res (2014) 21:5007–5022DOI 10.1007/s11356-013-2429-8

Introduction

Sediments are considered as an important compartment ofaquatic ecosystems that provide substratum for benthic organ-isms and represent a deposit of nutrients that can be returnedto the biocycles during natural flooding (Forstner andSalomons 2010). Association with sediments and particulatematter also plays a crucial role in the fate and effects ofcontaminants in aquatic systems. Sediments serve as a sinkfor various hazardous chemicals, especially hydrophobic or-ganic contaminants (HOCs) due to their hydrophobic natureand low-water solubility. Important parameters for the bindingof organic pollutants to sediments are the specific surface ofparticles as well as quantity and quality of organic carbon(Jaffe 1991). Sediments contain a wide spectrum of com-pounds, of both natural and anthropogenic origin, that canaffect organisms through different modes of action to causeadditive, supra-additive, or infra-additive effects. AmongHOCs, polycyclic aromatic hydrocarbons (PAHs),polychlorinated biphenyls (PCBs), organochlorine pesticides(OCPs) or polychlorinated dibenzo-p -dioxins (PCDDs), anddibenzofurans (PCDFs) have been detected in sedimentsworldwide (Colombo et al. 2006; Hilscherova et al. 2010;Kannan et al. 2008; Koh et al. 2004). Apart from the tradi-tionally monitored hydrophobic pollutants, other classes ofcompounds such as pharmaceuticals and personal care prod-ucts, polyphenolic compounds, phthalates, or various pesti-cides may be present in sediments (Brack et al. 2007; Joblingand Tyler 2003; Vigano et al. 2008). It has also been shownthat sediments can serve as a sink of xenohormones and otherendocrine disrupting compounds (Higley et al. 2012; Pecket al. 2004; Urbatzka et al. 2007).

To achieve good water quality within the European Union(EU), the Water Framework Directive (Directive 2000/60/EC)has been introduced into the EU legislation and limits forconcentration of several hazardous priority substances in sur-face waters, so-called Environmental Quality Standards (EQS),have been defined (Directive 2008/105/EC). Recently, the listof priority substances has been revisited and EQS for morecompounds in surface waters as well as EQS for some com-pounds in biota have been proposed (European Commission2012). Contamination of sediments plays a crucial role in thepollution of aquatic environment. The Water FrameworkDirective recommends the monitoring of sediments at an ade-quate frequency to provide sufficient data for reliable determi-nation of long-term status and trends and to establish limits forcontaminants in sediments according to the local situation ineach country. Specific approaches for sediment quality assess-ment along with EQS for sediments are under development,which is one of the remaining challenges for better protectionof aquatic ecosystems. Sediment quality guidelines (SQGs)developed on the base of ecological and ecotoxicological in-formation for several HOCs as well as metals have been

introduced in Flanders, Belgium and incorporated intoFlemish legislation in 2010 (de Deckere et al. 2011). Anotherapproach was previously used in the Netherlands, where limitsfor some organic substances and pesticides were derived by useof the equilibrium partitioning method (Crommentuijn et al.2000). An SQG for PCBs corresponding to the regulatory fishconsumption limit based on biota-to-sediment accumulationfactor has been derived for the Rhone River basin, France(Babut et al. 2012). No SQG have been promulgated by theCzech Republic yet.

Implementation of EQS for priority substances in sedi-ments is a crucial step in better protection of aquatic environ-ments. However, priority pollutants remain to be identified.Recently, more attention has been driven to “emerging con-taminants” in addition to HOCs since they can elicit variousbiological responses (Brack et al. 2007; Kaplan 2013). Whilequantification of individual contaminants by instrumentalanalysis is an important tool to investigate the fate and distri-bution of known pollutants in the environment, possible bio-logical effects of complex mixture are difficult to predictsolely from chemical analysis. Instrumental analysis of indi-vidual, known contaminants does not account for possibleinteractions among chemicals or for those compounds thatare not identified or not quantified. Thus, various in vitrobioassays have been applied to characterize contaminationby bioactive substances in various environmental compart-ments, such as surface water, sediments, soil, air, or biota(e.g., Higley et al. 2012; Martinez-Gomez et al. 2013;Novak et al. 2009; Urbatzka et al. 2007; Wolz et al. 2011).In vitro bioassays are relatively rapid, cost-effective, anduseful, especially in screening and long-term monitoring ofcontamination. Some of these assays are applied to estimatethe potency of individual compounds as well as of complexmixtures to elicit biological responses mediated through spe-cific nuclear receptors, such as the aryl hydrocarbon receptor(AhR), estrogen receptor (ER), or androgen receptor (AR).Activation of the AhR is considered critical in mediatingeffects of dioxin-like compounds that have been shown tocause hepatotoxicity, teratogenicity, carcinogenesis,immunotoxicity, and other adverse effects (Janosek et al.2006). Estrogens and androgens are endogenous steroid sexhormones that control reproduction, development, differenti-ation, and growth. Functions of these hormones are mainlymediated by ER and AR, and many compounds have beenshown to disrupt their signaling (Janosek et al. 2006).Reproductive disorders, such as feminization or masculiniza-tion of aquatic vertebrates and invertebrates were observed inthe environment (as reviewed in Sumpter 2005). Exposure tosynthetic estrogens can even lead to collapse of whole fishpopulations (Kidd et al. 2007).

River sediments represent a dynamic system and theirpotential risks are connected primarily with transport anddeposition of contaminated solids in downstream regions

5008 Environ Sci Pollut Res (2014) 21:5007–5022

(Forstner et al. 2004; Hilscherova et al. 2003). Rivers canexhibit large differences in hydrodynamic characteristics dur-ing an annual cycle. In remobilization processes, pollutantsassociated with particles can be resuspended, thus, sedimentscan serve as a secondary source of contamination (Brinkmannet al. 2013; Hilscherova et al. 2007). Strong fluctuations inconcentrations of contaminants can occur upon strongerfloods that have been discussed in recent years in possiblerelation to the global climate change (Hunt 2002). Further,seasonal variability of contamination was observed at someplaces (Hilscherova et al. 2010; Zhao et al. 2011). Bothtemporal and spatial dynamics should be considered whenassessing contamination of river ecosystems as was docu-mented in a previous study (Hilscherova et al. 2010). Eventhough pollution of sediments by compounds with the above-listed modes of action has been reported from rivers in manyparts of the world, there is a lack of information regardinglong- as well as short-term variations or trends in their con-centrations and/or potencies.

The present year-long study was focused on temporal (bothseasonal and long-term) and spatial variability of contaminantsin river sediments of a typical industrial area in the south-eastern part of the Czech Republic (Central Europe) that rep-resents a suitable model ecosystem for research on the accu-mulation and distribution of pollutants on a local and regionalscale. The studied region is a part of Danube River basin,situated near the city of Zlin. It includes two rivers, theMorava and its tributary, the Drevnice (Fig. 1). This area hasbeen affected for many years by industrial and agriculturalactivities as well as effluents from wastewater treatment facili-ties and runoff from urban landscapes. Chemical, boot-and-shoe, plastics-and-rubber, food-stuff industry, agriculturalcrops and livestock production, as well as transport are amongthe most important sources of contamination (Hilscherovaet al. 2007). The goal of this year-long study with monthlysampling was to characterize seasonal and spatial variability ofcontamination of fluvial sediments by compounds with dioxin-like and endocrine disruptive modes of action. Sediments weresampled monthly at five locations throughout a whole year.Extracts of sediments were assessed for AhR-, ER-, and AR-dependent potencies. Another goal was to address longer-termtrends/variability through comparison of current and previousresults from the region (Hilscherova et al. 2010, 2002). Thus, acomparison of seasonal as well as inter-annual trends in con-tamination by bioactive compounds could be conducted.

Materials and methods

Sampling and locations

Sediments were collected, monthly, from July 2007 to July2008 at five locations in the south-eastern part of the Czech

Republic in the Morava River and its tributary Drevnice River(Fig. 1). The Malenovice (MA) location is situated on theDrevnice River and is affected mainly by contamination fromthe city of Zlin and its surroundings. The Belov (BE) locationis situated on the Morava River upstream from the confluencewith the Drevnice River, whereas the Spytihnev (SP) locationis downstream on Morava River and integrates contaminationfrom both rivers. The Certak oxbow lake (CR) is a uniquelocation that was separated from the active Morava Riverchannel in the 1930s, but water communication with the riveris provided via underground piping that enables the lake to actas a trap for suspended sediments from the river (Babek et al.2008). The Certak (CE) location is situated on the MoravaRiver near the oxbow lake to better assess differences betweenthe active and abandoned channel. Samples were taken fromeach location in a period of 28 days, in 15 sampling cam-paigns. A total of 73 samples were collected. Two samplescould not be obtained because of weather conditions. Sampleswere clustered according to four hydrologically defined sea-sons (Table S1): spring (March–May), summer (June–August), autumn (September–November), and winter(December–February). Data on river discharge and tempera-ture were obtained from gauging stations in Zlin (representa-tive for location MA), Kromeriz (representative for locationBE), and Spytihnev (representative for locations SP, CE). Thefollowing parameters were used: Q =average discharge overthe 28 days prior to each sampling campaign, Tactual=temper-ature on the day of sampling, Taverage=time-weighted, averagetemperature over the 28 days prior to each sampling cam-paign. Composite samples of surface sediments were collectedfrom the top 10-cm layer by use of pre-cleaned trowels. Largepieces of wood, leaves, and stones were removed manuallyand sediments were homogenized and freeze-dried. Dry sed-iments were sieved (2 mm). Total organic carbon content(TOC) was determined by use of high-temperature TOC/TNb Analyzer liquiTOC II (Elementar Analysensysteme,Hanau, Germany).

Chemical analysis

For quantification of organic pollutants, 10 g of freeze-driedsediments were extracted with dichloromethane by use ofautomated warm Soxhlet extraction (1 h, min. 15 cycles;Büchi B-811, Büchi, Switzerland). Laboratory blanks andreference material were analyzed with each set of samples.Surrogate recovery standards (final amount in each sample10 ng PCB30, 10 ng PCB185, 333 ngD8-naphthalene, 333 ngD10-phenanthrene, and 333 ng D12-perylene) and 13C la-beled PCDD/Fs standards (800 pg tetra-hexa PCDD/Fs,1,600 pg hepta-octa PCDD/Fs) were used prior to extraction.Extracts were cleaned-up on silica column (for PAHs analy-sis), sulfuric acid-modified silica column was used for analy-sis of organohalogens. Copper powder was used to remove

Environ Sci Pollut Res (2014) 21:5007–5022 5009

sulfur. Further fractionation step was needed to analyzedioxin-like PCBs (dl-PCBs) and PCDD/Fs. Samples wereapplied on columns containing charcoal/silica mixture andeluted with DCM/cyclohexane in fraction 1 (mono-ortho dl-PCBs) and with toluene in fraction 2 (PCDD/Fs, non-orthodl-PCBs). Terphenyl (200 ng/mL), PCB 121 (200 ng/mL) and13C-labeled PCDD/Fs (16 ng/mL) were used as injectionstandards for quantification of PAHs, PCBs, and PCDD/Fs,respectively. Samples were analyzed using GC-MS instru-ment (Agilent 6890N GC–Agilent 5973N MS, Agilent,USA), separation of individual compounds was achievedon a DB-5MS (J&W Agilent, USA) for indicator PCBs(congeners 28, 52, 101, 118, 138, 153, 180), OCPs (di-chlorodiphenyltrichloroethane p , p ′-DDT and its metabo-lites p , p ′-DDE, p , p ′-DDD; hexachlorocyclohexane iso-mers α-, β-, γ-, δ-HCH; hexachlorobenzene), and 16 US EPAPAHs. Concentrations of contaminants were quantified usingPesticideMix 13 (Dr. Ehrenstorfer GmbH, Germany) and PAHMix 27 (Promochem, Germany) standard mixtures.HRGC/HRMS instrumental analysis for PCDD/Fs and dl-PCBs (congeners 77, 81, 105, 114, 123, 126, 156, 157, 167,169, 189) was performed on Agilent 7890A GC (Agilent,USA) coupled to AutoSpec Premier MS (Waters, Micromass,

UK). The GC was fitted with a capillary column DB5-MS,60 m×0.25 mm i.d., 0.25-μm film. MS was operated in EI+mode at R >10 k (Kukucka et al. 2010).

Total potency of samples to cause AhR-mediated effects,expressed as 2,3,7,8-tetrachlorodibenzo-p -dioxin (TCDD)-equivalents (TEQ), were calculated as the sum of the productof concentrations of individual AhR-active compounds mul-tiplied by their relative potency (REP) to activate AhR-mediated responses in H4IIE-luc cells (Eq. 1).

TEQ ¼X

cX*REPX ð1Þ

TEQ for individual groups of pollutants were calculated(Eqs. 2 and 3).

PAHs−TEQ ¼X

cPAHs*REPPAHs ð2Þ

nonPAHs−TEQ ¼X

cPCBs*REPPCBs� �

þX

cPCDDs*REPPCDDs� �

þX

cPCDFs*REPPCDFs� �

ð3Þ

Fig. 1 Sampling localities on theMorava and Drevnice Rivers.MAMalenovice, BE Belov, SPSpytihnev, CE Certak Moravariver, CR Certak oxbow lake;arrows indicate the river flowdirection

5010 Environ Sci Pollut Res (2014) 21:5007–5022

REPs derived by Machala et al. (2001) were used forPAHs, REPs derived by Behnisch et al. (2003) were used forPCBs and PCDD/Fs (Table S2).

Bioassays

For in vitro testing, 20 g of freeze-dried sediments with-out any surrogate standards were extracted as describedabove (Section Chemical Analysis). Extracts were treatedwith copper powder to remove sulfur, enriched under agentle stream of nitrogen, and aliquots were transferredto ethanol (EtOH) and dimethyl sulfoxide (DMSO). Finalconcentration of sediment equivalents (SEQ) in the ex-tracts was 20 g/mL. Three different mammalian cell linestransfected with the luciferase gene under control ofseveral intracellular receptors were used to determinepotencies of extracts of sediments to interfere withreceptor-mediated responses. The potency to elicitdioxin-like effects via activation of AhR was quantifiedby use of the H4IIE-luc rat hepatocarcinoma cells(Hilscherova et al. 2001). ER-mediated response wasevaluated by use of MVLN human breast carcinoma cells(Demirpence et al. 1993). MDA-kb2 human breast can-cer cell line was used to assess AR-dependent response(Wilson et al. 2002).

H4IIE-luc cells were cultured in Dulbecco’s modifiedEagle’s medium (DMEM) containing 10 % (v /v ) fetal calfserum (FCS; both PAA laboratories, Austria) and exposed inthe same medium supplemented with 1 % (v /v ) gentamicin toprevent bacterial contamination. MVLN cells were cultured inDMEM/F12 medium (Sigma-Aldrich, Czech Republic) sup-plemented with 10 % (v /v ) FCS and exposed in DMEM/F12supplemented with 5 % (v /v ) stripped (dextran/charcoal treat-ed) FCS and 1 % (v /v ) gentamicin. MDA-kb2 cells werecultured in Leibowitz L-15 medium (Sigma-Aldrich, CzechRepublic) supplemented with 10 % (v /v ) FCS and exposed inLeibowitz L-15 medium supplemented with 5 % (v /v )stripped FCS and 1 % (v /v ) gentamicin. H4IIE-luc andMVLN cells were incubated and exposed at 5 % CO2 and37 °C. MDA-kb2 cells were incubated and exposed at 37 °Cwithout addition of CO2.

In the first step, test of cytotoxicity of the sediment extractswas conducted to determine the non-cytotoxic concentrationsfor testing of receptor-mediated effects. Upon testing, cellswere seeded into sterile 96-well microplates in exposure me-dium. After 24-h incubation, cells were exposed to extracts ofsediment samples in several dilutions. The greatest testedconcentration for cytotoxicity assessment was 100 mg SEQ/mL. Cytotoxicity of the samples was measured using colori-metric Neutral Red (NR) uptake assay (Babich andBorenfreund 1990). Fifty microliters of NR dissolved inDMEM (0.5 mg/mL) were added into each well with cellsand exposure medium after 24-h exposure. The mixture was

incubated with cells for 1 h and then the mediumwith NRwasremoved. An aliquot of 150 μL of lysis solution (water,ethanol, acetic acid) was added and cells were shaken for15 min (Orbital Shaker OS-20, BIOSAN, at 150 rpm).Absorbance was measured using a spectrophotometer(Tecan-Genios, λ =570 nm). Data from the cytotoxic sampledilutions were excluded from calculations.

The interference with the receptor signaling was tested atseveral dilutions that did not significantly affect the viabilityof the cells, in three independent experiments. Cells wereseeded into 96-well microplates and after 24-h incubation,exposed to extracts of sediment samples and appropriatestandard calibration for agonistic potency along with blanksand solvent controls (0.5 % v/v ). Reference compounds usedfor calibration were TCDD (Ultra Scientific, USA; concentra-tion range 0.4–500 pM in EtOH) for H4IIE-luc , 17β-estradiol(E2; Sigma-Aldrich, Czech Republic; 1.23–100 pM inDMSO) for MVLN, and dihydrotestosterone (DHT; Sigma-Aldrich, Czech Republic; 10 pM–10 μM in DMSO) forMDA-kb2, respectively. For ER- and AR-antagonistic poten-cy assessment, the exposure medium was supplemented withthe reference compound (competing ligand) at approximatelyEC50 level, e.g., 33.3 pM E2 (MVLN) and 1 nM DHT(MDA-kb2), thus solvent concentration was 1 % (v /v ). After24-h exposure, cells were lysed, Promega Steady Glo Kit(Promega, USA) was added and the intensity of luminescencewas measured by Luminoskan Ascent MicroplateLuminometer (Thermo Scientific).

Data analysis

After subtraction of solvent control response, effects elicitedby extracts of sediments were related to the luminescencecaused by the reference compounds in the transactivationassay. The dose–response curves were fitted using non-linearlogarithmic regression in GraphPad Prism (GraphPadSoftware, USA). AhR-mediated potency was expressed asTCDD-equivalents (BIOTEQ) calculated as EC50TCDD/EC50sample. Since many of the active samples did not reach50 % of E2max induction, to avoid any predictions beyond themeasured responses, estrogenicity was expressed as estradiolequivalents (EEQ) calculated as EC25E2/EC25sample.

Antiestrogenicity of samples was expressed as the concentra-tion (in sediment equivalents) that caused 25 % inhibition ofluminescence in the presence of the competing ligand E2(IC25). Androgenicity was expressed as DHT-equivalents(DHT-EQ) calculated as a point estimate based on the per-centage of the luminescence induction caused by the greatestnon-cytotoxic sample concentration because the dose–re-sponse curve for most samples did not exceed 20% induction.DHT-EQ was calculated as ECXDHT/ECX sample, where Xrepresents percentage induction of the greatest non-cytotoxicsample concentration. Antiandrogenicity was expressed as

Environ Sci Pollut Res (2014) 21:5007–5022 5011

percent inhibition of luminescence in the presence of thecompeting ligand DHT caused by the greatest concentrationthat was non-cytotoxic (as described for DHT-EQ).

The limit of detection (LOD) for each bioassay usedin this study was derived as the ratio of the lowestamount of standard that elicits statistically significantresponse per the greatest tested non-cytotoxic concentra-tion of SEQ. To calculate the LOD, the lowest concen-tration of reference compound significantly affecting thereceptor-mediated response (lowest observed effect con-centration for the receptor-mediated effect; LOEC), andthe greatest non-cytotoxic sample concentration (no ob-servable effects concentration for cytotoxicity; NOEC)were determined. Responses obtained for reference com-pounds and sample extracts were compared with solventcontrol response using ANOVA followed by Dunnet’s test todetermine significant effects (p <0.05). NonparametricKruskal-Wallis test was used in case of non-homogenousvariances (as tested by Levene’s test). The LOD was thencalculated as follows: LOD (pg/g, dry mass (dm) of sedi-ment) = LOECstandard ligand (pg/mL)/NOECsample (g SEQ/mL).Spatial and seasonal variability of dioxin-like toxicity (TEQ,BIOTEQ), estrogenic potency (EEQ), and antiandrogenicpotency (AA) was tested by nonparametric Kruskal-Wallistest and visualized using boxplots.

Multivariate variation of bioassays results as well aschemical and environmental parameters was furthersummarized in the principal component analysis(PCA) as an effective technique simplifying the corre-lation structure through linear transformation of theoriginal variables. PCA based on the correlation matrixwas performed to provide component loading vectorsexplaining the relationships among the bioassays, pol-lutants, and other parameters and component score vec-tors as pair-wise uncorrelated variables that were usedfor the final exploratory survey of the data from theexamined locations. Only variables with less than 10 %values below LOD were used for multivariate analysis.Values < LOD were replaced by ½ LOD. The variableswith non-normal distribution were transformed by log-arithmic transformation before use in PCA and para-metric correlation analyses. The most important vari-ables (estimates by eigenvalues) were selected for cre-ating PCA (active variables), some other variables werevisualized in the same ordination space as supplemen-tary variables. Biplot was used as a common graphicaltool representing not only projections on extracted prin-cipal components but also the 2-D loadings of originalvariables by lines. Additionally, Pearson’s correlationanalysis was used to quantify relationships betweenvariables. All statistical analyses were performed withthe software STATISTICA for Windows 10 (StatSoft,Inc. USA).

Results and discussion

This study documents variability of pollution in surfacesediments of the rivers during the year. Sediments containedall chemically analyzed classes of pollutants (Table 1) ateach location. SP was the most polluted location with thegreatest concentrations of most contaminants and also withthe greatest median of TOC content, whereas CR (oxbowlake) contained, overall, the least levels of contaminants.Detailed information about temporal and spatial distributionof HOCs will be described elsewhere (Prokes et al., inpreparation). Comparing the contamination in assessed areaswith SQGs derived from ecological and ecotoxicologicaldata by de Deckere et al. (2011) (Table S3), all of theinvestigated locations are polluted. The SQGs proposed tobe achieved in a long-term objective (so-called consensus 1values) were exceeded by concentrations of PAHs, PCBs,and DDE in all samples up to 6-, 7-, and 30-fold, respec-tively, especially in winter and spring (PAHs), and in autumn(PCBs, DDE). In the case of DDD, the SQGs were exceededeven more than 200-fold in winter samples from location SP.According to these results, the studied locations are not in agood ecological sediment status as it was defined in deDeckere et al. (2011) during the year. The SQGs proposedto be achieved as a short-term objective (consensus 2 values)were only slightly exceeded by concentrations of some PAHsand DDE (1.3-fold), while the concentration of DDDwas up to5-fold greater in winter samples from location SP than theproposed limits. Consensus 2 values are described as valuesabove which toxic and in situ effects are most likely to occur(de Deckere et al. 2011). From this point of view, all investi-gated sediments are likely to negatively affect biota. Desorptionof contaminants from sediments might enhance their bioavail-ability, which plays a crucial role in manifestation of toxiceffects on organisms. Results of previous studies indicated thatsediments from the studied area represent a potential source ofPAHs into the water column (Prokes et al. 2012).

Comparison of chemical analysis results to SQGs docu-ments pollution by HOCs. However, compounds other thanthose HOCs that were quantified were present in the mixturesin sediments; therefore, specific biological activities wereassessed in order to estimate the potential effects on organ-isms. Three transactivation cell lines were used to investigatespecific biological potential of sediment samples. Mixturesextracted from sediments were cytotoxic; therefore, extractswere first treated with copper to remove sulfur, which is afrequent cause of cytotoxicity. Cytotoxicity of treated extractswas measured by use of the NR assay for each cell line inorder to avoid any interference with specific endpoints mea-sured in this study. Only concentrations of extracts that did notcause cytotoxicity were included in the evaluation of specificpotencies. MDA-kb2 cells were more sensitive to effects onviability than were H4IIE-luc and MVLN cells. For MDA-

5012 Environ Sci Pollut Res (2014) 21:5007–5022

kb2 cells, the greatest NOEC corresponded to 50 mg SEQ/mLfor most samples, four sediment extracts from location MAshowed a greater cytotoxicity with NOEC of 15 mg SEQ/mL.For H4IIE-luc and MVLN cells, the cytotoxicity NOEC was100 mg SEQ/mL for all samples.

AhR-mediated potency

AhR-mediated potency, expressed as BIOTEQ, was found inextracts of all sediments and was in the range of 0.5–17.7 ng/g, dm of sediment (LOD=1.3 pg/g, dm). Seasonal changes inBIOTEQ were obvious at all locations except CR (Figs. 2aand 3). The greatest dioxin-like potency was detected insediments collected during winter. Concentrations ofBIOTEQ in sediments collected during winter were signifi-cantly greater than in those collected during summer, whichcontained the least concentration of BIOTEQ (p <0.05). Thesame trend was observed for content of TOC (Fig. S1), whichis an important parameter in accumulation of hydrophobicpollutants (Jaffe 1991). The trend of greatest concentrationsin winter was most pronounced in theMorava River below theconfluence with the Drevnice River (locations SP, CE). Therewas a trend of increasing concentration of BIOTEQ at SPcompared to upstream locations (MA, BE) in samples collect-ed during the summer and winter (Fig. 3 and S2). However,this trend was not obvious in spring and autumn, whichindicates that spatial differences can be more pronouncedduring some seasons. SP is an integrating location for con-tamination from both rivers and additional nearby sources ofpollution. Location CR (oxbow lake) was the least contami-nated location, with concentrations of BIOTEQ significantlylesser (p <0.05) than those in sediments from locations BE,SP, and CE (Fig. 2a, Table 1). CR also exhibited lesservariability among seasons with AhR-mediated potency onlyslightly greater in sediments collected during winter (Fig. 3).This finding demonstrates the function of the oxbow lake as amore stable deposit of various HOCs without greater fluctua-tions in pollution that are obvious in the active channel.Concentrations of BIOTEQ in sediments from all riverinelocations exhibited least variability during summer (Fig. 3),which was probably related to the least fluctuations in riverwater discharge during this season (Fig. S3). Variability inconcentrations of BIOTEQ was greater among all riverinelocations during winter and spring (Fig. 3).

Results of this study confirmed the role of PAHs as thepredominant contributors to the overall AhR-mediated po-tency observed in previous studies from the region(Hilscherova et al. 2001; Vondracek et al. 2001). TotalTEQ calculated from concentrations of individual AhR-active compounds (0.1–1.9 ng/g; Table 1) exhibited similarseasonal patterns as did concentrations of BIOTEQ(Fig. S4). However, concentrations of BIOTEQ were great-er than concentrations of TEQ in extracts of all sedimentsA

bbreviations

ofsitesas

inFig.1

PAHspolycyclicarom

atichydrocarbons,ind.P

CBsindicatorpolychlorinatedbiphenyls,dl-PCBsdioxin-likePCBs,PCDDspolychlorinateddibenzo-p-dioxins,P

CDFspolychlorinateddibenzofurans,

OCPsorganochlorine

pesticides,TO

Ctotalorganiccarbon,TEQ

TCDD-equivalent(derived

basedon

chem

ical

analysis),BIO

TEQ

TCDD-equivalent(bioassay-derived),EEQ

estradiol-equivalent

(bioassayderived),D

HT-EQ

dihydrotestosterone-equivalent

(bioassay-derived),A

Aantiandrogenicactiv

ity(bioassay-derived)

aTo

taln

umberof

samples

(n)with

observed

activ

ityisnotedin

bracketsin

case

whensignificantactivity

was

notd

etectedin

all1

5samplings

over

theyear

Environ Sci Pollut Res (2014) 21:5007–5022 5013

Tab

le1

Medianandrange(inbrackets)of

concentrations

ofpollu

tants,organiccarbon,and

biologicalpotenciesinextractsof

sedimentsfrom

studiedlocalitiesfrom

allsam

plingcampaigns

overayear

(based

onsedimentd

rymass)

Sampling

site

PAHs

(μg/g)

Ind.PC

Bs

(ng/g)

Dl-PC

Bs

(pg/g)

PCDDs

(pg/g)

PCDFs

(pg/g)

OCPs

(ng/g)

TOC(%

)TEQ(ng/g)

TEQ/

BIO

TEQ

(%)

BIO

TEQ

(ng/g)

EEQ(pg/g)

aDHT-EQ(ng/g)

aAA(%

inhibitio

n)

MA

4.4(0.6–14.3)

11.6(3.5–21.4)

399(179–494)

38(8–94)

15(2–23)

9.2(1.6–19)

3.3(0.6–7.7)

0.6(0.1–1.4)

14(5–52)

3.7(0.9–14.7)

99(20–954)

(n=13)

3.1(1.8–3.9)(n=3)

72(51–84)

BE

7.5(0.5–10.7)

7.5(1.7–10.5)

238(105–340)

90(11–190)

34(4–49)

16.7(0.9–53.1)

3.1(0.2–5.1)

1.0(0.1–1.2)

15(6–39)

4.9(1.0–12.6)

76(40–3,753)

2.8(1.4–8.3)(n=4)

68(17–91)

SP8.5(5.3–13.8)

12.0(6.5–33.4)

300(127–612)

354(152–818)

37(24–109)

25.3(8.9–58.1)

4.1(2.9–5.3)

0.9(0.6–1.9)

17(8–109)

6.4(1.5–17.7)

143(45–895)

4.1(0.7-5.9)(n=7)

72(32–98)

CE

5.2(3.0–9.0)

7.1(4.5–20.6)

317(142–643)

106(57–268)

17(11–24)

5.4(2.9– 39.5)

1.8(1.2–2.6)

0.7(0.4–1.1)

13(6–49)

3.7(1.3–15.4)

110(62–229)

5.4(0.8-16.8)

(n=7)

56(17–84)

CR

2.6(1.5–8.8)

6.2(0.7–13.7)

290(188–431)

52(36–94)

13(11–28)

5.3(1.2–11.6)

2.9(2.1–5.9)

0.3(0.2–0.9)

21(10–44)

1.9(0.5–5.3)

75(39–198)

(n=12)

1.9(n=1)

74(52–98)

with a single exception. Generally, only 13–21 % BIOTEQ(median values “TEQ/BIOTEQ (%)” among locations;Table 1) could be explained by the presence of knownAhR ligands, namely PAHs. PAHs accounted on averagefor 99.4% of the total TEQ, which is consistent with the resultsof previous studies conducted in this area (Hilscherova et al.2001; Vondracek et al. 2001). The main contributors amongPAHs were benzo[k]fluoranthene and indeno[123-cd]perylene. Other source of dioxin-like toxicity might be

azaarenes and oxygenated PAH derivatives (oxy-PAHs) thatwere previously detected in sediments from the studied area(Machala et al. 2001). Comparable levels of pollution withdioxin-like compounds were found in sediments from riversaffected by municipal and industrial activities from other areas,such as sediments from two Chinese rivers (BIOTEQ 0.3–13.9 ng/g, dm), where greatest potencies were observed infractions containing PAHs, OCPs, a portion of PCDD/Fs andunknown compounds (Song et al. 2006). In sediments from the

Fig. 2 Spatial and seasonalvariability of bioassay-derived: adioxin-like potency (BIOTEQ,pg/g, dm of sediment), b estro-genic potency (EEQ, pg/g, dm),c antiandrogenic potency (AA,% luminescence inhibition incompetition with DHT causedby the highest non-cytotoxicsample concentration) in sedi-ment samples from the 15sampling campaigns in July2007–July 2008 (n=73). Middleline is median, box means quar-tile range (25–75 %), whisker isnon-outlier range and trianglesare measured values

5014 Environ Sci Pollut Res (2014) 21:5007–5022

Netherlands, most AhR-mediated potency was caused by acid-labile compounds, such as PAHs (Houtman et al. 2004).Alternatively, only 6 % of AhR-mediated potency was attrib-uted to PAHs in sediments from Germany (Brack et al. 2008).Furthermore, PCDD/Fs were a major source of dioxin-likepotency observed in the sediments in the USAwhere concen-trations were as great as 19.9 and 17.7 ng/g, dm PCDDs andPCDFs, respectively (Hilscherova et al. 2003), and 46.5 ng/g,dm for the sum of PCDD/Fs (Kannan et al. 2008). However, inthe study, the results of which are reported here, dl-PCBs andPCDD/Fs, due to their relatively small concentrations relativeto PAHs, contributed little of the total concentrations of TEQ(Table 1). Despite their greater potency, the average contribu-tion of PCDDs, PCDFs, and dl-PCBs to the total TEQ wasonly 0.2, 0.3, and 0.1 %, respectively.

ER-mediated potency

Results of the bioassay documented the presence of estrogeniccompounds in almost all sediments. Estrogenic potencyexpressed as EEQ was detected in 93 % of samples in therange of 20–3,753 pg/g, dm, but most samples (88 %)contained 20–300 pg/g, dm (Fig. 2b). Four samples taken insummer 2007 at locations MA (n =1), BE (n =2), and SP (n =1) were noted for great values of EEQ that reached 895–3,753 pg/g, dm. These extreme concentrations are not includ-ed in Fig. 2b. Estrogenic potency of 7 % of the sedimentsamples (n =5) was less than the limit of detection (LOD=3.25 pg/g). Median concentration of EEQ among seasons wasgreatest in sediments from location SP, similarly to medianconcentration of BIOTEQ. Samples from BE and MA were

noted for a very variable estrogenicity among sampling cam-paigns including extreme EEQ values. When seasonal vari-ability throughout the year was taken into account, statisticallysignificant difference in estrogenic potency was observed onlybetween locations SP and CR. But there were more pro-nounced differences in separate seasons. For example, EEQwere always greater in SP compared to BE in autumn andwinter samples, while there was no such trend in the other twoseasons. The greatest median estrogenic potency across loca-tions was observed in summer (Fig. 2b), even without theextreme concentrations of EEQ observed in a few samples.These extremes could indicate exceptional inputs of(xeno-)estrogens of unknown origin that occurred during earlysummer 2007 at the above mentioned localities. No generalsignificant seasonal trends in estrogenicity were observed inthis study (Fig. 2b). However, sediments sampled at locationsMA and CE tended to have lesser concentrations of EEQ inspring compared to autumn. A similar trend was observedpreviously in this region (Hilscherova et al. 2010; Table 2).Alternatively, greater estrogenicity was observed in sedimentscollected in spring than in those collected in autumn in a studywhere a smaller sample set was compared (Creusot et al.2013).

A weak antiestrogenic potency in the presence of compet-ing E2 was detected only in two sediment samples taken fromCR in November and December 2007. Concentration of ex-tract causing 25 % inhibition of luminescence (IC25) in com-petition with E2 was 25.6 and 16.6 mg SEQ/mL, respectively.These two samples exhibited none and little estrogenic poten-cy, respectively, but the presence of estrogenic pollutantsmight be masked by antiestrogenic compounds present in

Fig. 3 Seasonal variability ofbioassay derived dioxin-like ac-tivity (BIOTEQ, pg/g, dm) ateach sampling site during the 15sampling campaigns in July2007–July 2008 (n =73). Middleline is median, box means quar-tile range (25–75 %), whisker isnon-outlier range and trianglesare measured values

Environ Sci Pollut Res (2014) 21:5007–5022 5015

these samples. There were four samples that elicited neitherestrogenic nor antiestrogenic potency. Antiestrogenic effectsmight play an important role in some regions. For example,81 % of sediments from the Pearl River, China, exhibitedestrogenicity but at the same time, 61 % of all samples wereantiestrogenic meaning that both estrogenic and antiestrogeniccompounds were present (Zhao et al. 2011). Sediments fromthe Svratka and Svitava Rivers that flows into theMorava Riverdownstream from the studied area of Zlin vicinity, elicited onlyantiestrogenic potencies (Jalova, personal communication) de-spite the fact that the region is relatively densely populated. Theestrogenicity detected in sediments from the region around thecity of Zlin indicates that there might be greater inputs ofestrogenic compounds due to less effective wastewater treat-ment plants (WWTPs) and/or more intensive agriculture.

ER-dependent potency was previously assessed in sam-ples from the studied area. Concentrations of EEQ were inthe range of 5–23 (Vondracek et al. 2001) and 10–1,200 pg/g, dm in extracts of sediments (Hilscherova et al. 2002).After major floods in 1997, antiestrogenic potencies becamemore apparent in sediments compared to the situation beforefloods (Hilscherova et al. 2002). Approximately 10 yearsafter the floods, regional median concentrations of EEQ insediments from the studied area were in the range of 10–340 pg/g, dm (Hilscherova et al. 2010). Estrogenic com-pounds (EEQ 21.3–29.9 pg/g, dm) were found in sedimentsfrom both upstream and downstream of WWTPs that areconsidered to be an important source of estrogenic com-pounds in UK; estrone (E1) and E2 were determined as

major estrogenic pollutants (Peck et al. 2004). On the otherhand, EEQ in the range of 3.3–10.6 pg/g, dm was detectedin sediments from downstream locations from WWTPs inKorea, whereas no potency was observed in upstream loca-tions (Oh et al. 2000). High contamination by estrogeniccompounds was observed in sediment from a river in Italy,where E1, estriol (E3), and nonylphenol contributed to theobserved estrogenicity; phthalates and octylphenol isomerswere suggested as potential contributors (Vigano et al.2008). In the area around the city of Zlin, rivers receivetreated effluents from a number of WWTPs as well asuntreated sewage effluents from smaller villages and farms.Effects of large as well as smaller towns as sources ofestrogenic compounds have been documented (Jarosovaet al. 2012; Vermeirssen et al. 2005). Natural and syntheticestrogens, such as E1, E2, E3, and ethinyl estradiol, werenot analyzed in our study but they can enter the rivers andare likely to accumulate in sediments (Luo et al. 2011; Pecket al. 2004; Streck 2009). Therefore, they could be impor-tant contributors to the estrogenic potency of extracts ofsediments. In addition, PAHs have been found to be asource of estrogenicity in sediments (Hilscherova et al.2002, 2010; Houtman et al. 2004; Luo et al. 2011). In thisstudy, concentrations of EEQ in sediments were not corre-lated with concentrations of measured PAHs. However,some of their metabolites produced in sediments by micro-bial degradation such as hydroxylated PAHs could play arole in the estrogenic effects (e.g., Hayakawa et al. 2007;Luan et al. 2006).

Table 2 Concentrations of AhR-mediated potency (BIOTEQ, pg TCDD/g, dm) and estrogenic potency (EEQ, pg E2/g, dm) of sediments atMalenovice(MA), Belov (BE) and Spytihnev (SP) determined by bioassays

BIOTEQ (pg TCDD/g) EEQ (pg E2/g)

MA BE SP MA BE SP

October 1996a 6,542 4,223 NA 239 39 NA

October 1997a 6,675 4,449 NA 1,134 93 NA

May 2005b 15,368 8,123 9,867 95 29 186

October 2005b 7,868 1,442 4,611 231 107 175

May 2006b 7,768 914 14,356 <1 <1 90

October 2006b 1,660 764 5,573 442 66 127

October 2007 5,506 6,488 7,779 124 85 178

May 2008 1,333 3,001 3,166 <3 51 130

Summer 2007 1,058–2,302 1,042–2,566 2,098–5,893 141–954 198–3,753 45–895

Autumn 2007 2,139–5,663 2,927–6,488 1,515–7,884 99–124 58–85 136–178

Winter 2007/08 3,708–13,797 3,413–12,624 10,276–17,722 60–167 44–117 122–154

Spring 2008 1,333–14,690 3,001–9,768 3,166–12,317 <3–76 51–212 87–130

Summer 2008 940–1,867 2,062 3,870–6,824 20–61 40 97–131

NA data not availablea Hilscherova et al. (2001) (2002)b Hilscherova et al. (2010)

5016 Environ Sci Pollut Res (2014) 21:5007–5022

AR-mediated potency

AA was more profound in extracts of sediments than andro-genic potency. All extracts at non-cytotoxic concentrationsinhibited luminescence in competition with natural ligandDHT with median inhibition during the year at 56–74 % atall sites (Table 1). Antiandrogenicity was greater in extracts ofsediments from CR than that from CE (Fig. 2c), namely insummer and winter. These results suggest that antiandrogeniccompounds could accumulate better in relatively stable sedi-ments of the oxbow lake. This could be also affected by lowerTOC content at CE compared to the other sites, since AAwasshown to correlate with organic carbon level (Fig. 4). The AAwas least in autumn and significantly greater concentrationswere observed in spring.

Androgenic potency expressed as DHT-EQ greater thanLOD (580 pg/g) was detected in 30 % of extracts of sedi-ments. Concentrations of DHT-EQ were 0.7–16.8 ng/g, dm.Androgenic potency was detected in at least one samplingperiod at all locations, but in more than half of samplesfrom the individual locations there was no detectableandrogenicity (Table 1). Androgenic potency was detectedmost frequently in samples from locations SP and CE,whereas only one sample from CR exhibited androgenicpotency. Androgenicity was detected most often in sedi-ments collected during autumn (73 % of autumn samples),

followed by summer (29 % of summer samples), whileonly three samples collected during winter and one duringspring were androgenic.

To our knowledge, this is the first study that documents thesignificant seasonal changes in both antiandrogenic and an-drogenic potential of organic extracts of sediments from ariver. Seasonal changes in both androgenic and antiandrogenicpotencies were in good agreement. The least antiandrogenicpotency, which was observed during autumn, corresponded tothe frequent detection of androgenicity in extracts of sedi-ments collected during autumn. Alternatively, AA wasgreatest in spring when only one sample was androgenic.Previously, AA potency of few sediment samples was shownto be greater in dry season compared to wet season (Zhao et al.2011). Furthermore, androgenic potency was observed in 34of 50 extracts of sediments collected in Germany, but seasonaltrends were not investigated (Galluba and Oehlmann 2012).

Antiandrogenic potency has been frequently detected instudies of unfractionated extracts of sediments (Hilscherovaet al. 2010; Zhao et al. 2011). In some studies, AA was apredominant effect in extracts of sediments, whereas andro-genic potency was found in only some fractions (Urbatzkaet al. 2007; Weiss et al. 2009). Effect-directed analysis waspreviously applied to reveal both AA and androgenic com-pounds in sediments. PAHs, such as fluoranthene,benz[a]anthracene, pyrene and phenanthrene, nonylphenol

Fig. 4 Pearson’s correlation coefficient of bioassay-derived dioxin-likepotency (BIOTEQ), estrogenic potency (EEQ), and antiandrogenic po-tency (AA) with other parameters. Dark bands indicate a significantcorrelation (p <0.05). Abbreviations as in Table 1; Σ DDT = sum ofconcentrations of dichlorodiphenyltrichloroethane (p , p ′-DDT) and itsmetabolites p , p ′-DDE, p , p ′-DDD; PAHs -TEQ TCDD-equivalent

calculated based on PAHs concentration, nonPAHs -TEQ TCDD-equivalent calculated based on dl-PCBs and PCDD/Fs concentration,Tactual river water temperature on the day of sampling, Taverage time-weighted, average temperature over the 28 days prior to each samplingcampaign, Q average discharge over the 28 days prior to each samplingcampaign

Environ Sci Pollut Res (2014) 21:5007–5022 5017

(Weiss et al. 2009), and the metabolite of DDT, p , p ′-DDE(Urbatzka et al. 2007) were found in antiandrogenic fractions.Various compounds, including oxygenated PAHs, organo-phosphates, musks, and steroids, were detected in androgenicfractions (Weiss et al. 2011). A number of contaminantsanalyzed in this study, including some PAHs, PCBs,PCDD/Fs, and OCPs, have also been reported to beantiandrogenic (Vinggaard et al. 2008).

Correlation and multivariate analysis

The correlation profiles of bioassay results with environmen-tal parameters and concentrations of measured residues aredisplayed as bivariate relationships (Fig. 4). Concentrations ofBIOTEQ were significantly positively correlated with TOC,clay content, and flow and negatively with temperature evenwhen the seasonal variability was taken into account. Thesecorrelations document a significant role of abiotic parametersin accumulation of dioxin-like compounds, which was dem-onstrated for TOC and clay also in a previous study(Hilscherova et al. 2010). The fine-grained fraction of sedi-ment particles plays an important role in the accumulation ofHOCs in sediments (Jaffe 1991). BIOTEQwas also correlatedwith concentrations of all studied classes of HOCs. The mostsignificant correlation has been found with PAHs and TEQderived from PAHs, which documents their important contri-bution to BIOTEQ. However, from the comparison of TEQand BIOTEQ it was calculated that only a negligible portionof dioxin-like activity was attributed to dl-PCBs andPCDD/Fs. The correlation does not imply causal relationshipbut rather indicates that compounds with similar propertieslike measured HOCs were responsible for the observed AhR-potency of sediments.

There was a significant negative correlation of concentra-tions of BIOTEQ with actual and average monthly tempera-ture (Fig. 4). This corresponds with the greater concentrationsof BIOTEQ observed during winter, which is probably relatedto slower rates of degradation of chemicals as well as greaterPAHs inputs from local combustion during colder periods.Furthermore, concentrations of EEQ were significantly corre-lated with actual temperature (Fig. 4). Concentrations of PAHsmight be partially reduced by microbial degradation that isgreater during warmer months. Consequently, this could resultin an increased estrogenic potency of sediments due to theformation of estrogenic metabolites, such as hydroxylatedPAHs (Hayakawa et al. 2007; Luan et al. 2006; Wang et al.2012). The opposite trend is observed during winter, becausemicrobial degradation is lower at lower temperatures. Further,lesser dilution of (xeno)estrogens can be expected duringwarmer months due to the lesser discharge (Sumpter 2005;Figs. S3 and S5). However, no significant correlation betweenconcentrations of EEQ and discharge was observed.

Antiandrogenic potency was significantly correlated withTOC (Fig. 4), which was also shown in a previous study(Hilscherova et al. 2010). Thus, relatively hydrophobic com-pounds are likely to contribute to the AA potency of extractsof sediments. However, no significant correlation was foundbetween AA and concentrations of studied HOCs amonglocations and seasons (Fig. 4). The only correlations withAAwere found with concentrations of p , p ′-DDE at locationMA and with both p , p ′-DDE and p , p ′-DDD in sedimentsfrom CE, respectively. These DDTmetabolites are consideredas antiandrogenic compounds (Vinggaard et al. 2008).

The data were further analyzed using multivariate PCA.Firstly, data from all localities and time points were includedin the PCA. The first and second principal components (PC)accounted for 54 % of the total variance (40 and 14 %,respectively), and simplified the multivariate pattern whichallowed the variables and samples to be projected onto a two-dimensional space (Fig. 5). Variables with the main influencewere TEQ, BIOTEQ and concentrations of measured HOCsin the direction of first PC, and EEQ and AA in the directionof second PC. Secondly, only locations from the active riverchannel were assessed and temperature (Tactual) and discharge(Q ) of the river were included as active variables in PCA(Fig. 6).1 The first and second PC accounted for 52 % of thetotal variance (39 and 13 %, respectively). Variables with themain influence were concentrations of most classes of HOCs(excluding dl-PCBs) in one direction and Tactual and Q in theother direction (Fig. 6a). The influence of EEQ and AA wasnot apparent anymore in this two-dimensional projection. AAwas the dominant parameter associated with PC3, whichexplained 10 % of the total variance.

AhR-mediated potency determined in bioassay (expressedas BIOTEQ) was clearly associated with concentrations ofanalyzed HOCs in the first PCA (Fig. 5a). However, if onlylocations from the active river channel were included,BIOTEQ was projected in the very same direction as HOCsalong PC1 but somewhat separated by the direction along PC2(Fig. 6a). This observation further supported the interpretationthat the observed AhR-mediated potency of sediments cannotbe fully explained by analyzed HOCs and there were othercontaminants with similar properties contributing to the po-tency. In contrast, analyzed HOCs cannot explain concentra-tions of EEQ and AA that were projected in a differentdirection from concentrations of HOCs in both multivariateanalyses (Figs. 5a and 6a).

When all locations and time points were included in theanalysis, the outcomes of specific bioassays used togetherwith concentrations of the measured pollutants as active var-iables did not separate the sediments from different locations

1 Locality CR (oxbow lake) has no water discharge (lentic locality) andtemperature was not measured, therefore, these two variables could nothave been included in Fig. 5.

5018 Environ Sci Pollut Res (2014) 21:5007–5022

(Fig. 5b). Seasonal variability of contamination had a strongerinfluence on the distribution of variables and samples in PCAthan the differences among locations. Results of differentsamplings from all locations were relatively overlapping andonly individual samples from various locations were outliers.Only if Tactual andQ were included as active variables in PCA,SP was obviously separated from the other locations in thedirection of greater pollutant concentrations (Fig. 6a, b). Inconclusion, seasonal changes play a dominant role and can bemore important in the studied locations than spatial differ-ences. This finding is consistent with the results of a previous

study, which demonstrated no good separation of samplesfrom several study regions in autumn compared to spring(Hilscherova et al. 2010).

Long-term trend analysis

Concentrations of dioxin-like and estrogenic potencies mea-sured in fluvial sediments from the three locations (MA, BE,and SP) (Table 2) during this study were compared to those ofseveral previous studies (Hilscherova et al. 2010, 2002). Datafrom autumn (October) were available from 5 years between

Fig. 5 Principal component analysis (PCA) based on the data from allsampling sites. The ordination diagrams show the relationship amongvariables (a) and distribution of samples according to localities (b).Variables marked by full circles were used for creating PCA (active

variables). Variables marked by empty circles are displayed in the sameordination space but they were not used for creating PCA (supplementaryvariables). Abbreviations as in Table 1 and Fig. 4

Fig. 6 Principal component analysis (PCA) based on data from sites inthe active river channel (i.e., except CR) including also flow and temper-ature. The ordination diagrams show the relationship among variables (a)and distribution of samples according to localities (b). Variables marked

by full circles were used for creating PCA (active variables). Variablesmarked by empty circles are displayed in the same ordination space butthey were not used for creating PCA (supplementary variables). Abbre-viations as in Table 1 and Fig. 4

Environ Sci Pollut Res (2014) 21:5007–5022 5019

1996 and 2008, while for spring (May) from three differentyears (2005–2008), respectively. There was no continuoustrend of changes in concentrations of BIOTEQ or EEQ thatwould indicate the decrease or increase of contamination intime. Rather, the long-term (inter-annual) differencescorresponded well with seasonal fluctuations documented inthe current study. Greater differences in potencies measured inthe bioassays were observed among spring samples fromdifferent years while concentrations were more stable duringautumn. Inter-annual as well as seasonal fluctuations were theleast at location SP; maximally 4- and 2-fold differences wereobserved in case of concentrations of BIOTEQ and EEQ,respectively. This was probably related to the greater overalldischarge and long-term greater contamination at this location.On the other hand, the greatest differences were found forlocation MA on river Drevnice (up to 11-fold for BIOTEQ),where discharge was relatively small and thus, fluctuations indischarge could have had larger effects. Both short- and long-term variability in contamination by estrogenic compoundswere substantially greater than in the case of dioxin-likecompounds. Inter-annual variation in concentrations of EEQwas greater than variation among seasons. Asmuch as 95- and51-fold difference in EEQ was observed at location MA andBE, respectively, when comparing situations between May2005, 2006, and 2008, while 25- and 4-fold difference wasobserved within estrogenic potency of sediments from thesetwo locations in spring 2008, respectively (Table 2). Thegreater differences on locations MA and BE are associatedmainly with a strong decrease of EEQ (below limit of detec-tion) in spring 2006, which is a result of local floods thatoccurred in the region (Hilscherova et al. 2010). Alternatively,differences in concentrations of EEQs in extracts of sedi-ments from location SP were only 2-fold among spring andautumn samples across the studied years. The results of this1-year study also show that concentrations of both BIOTEQand EEQ were more variable in spring compared to autumn.This is probably related to the hydrology of the studiedrivers. The discharge of the river was relatively less andstable in autumn 2007 (except for one major rainfall),whereas greater discharge with stronger fluctuations oc-curred in spring 2008 which can be linked to a greaterresuspension of sediments (Fig. S3). A similar comparisonof a smaller data set from sediments in a French rivershowed 3.6- and 5-fold inter-annual differences in dioxin-like and estrogenic potency, respectively (Creusot et al.2013). Unlike in this study, lesser fluctuation was found inspring than in autumn. However, spring was described asdry season, whereas autumn as wet season in the Frenchstudy, which differs from the hydrology situation in ourstudy region (Fig. S3). This supports the conclusion thathydrology of the river is a very important parameter thatneeds to be taken into account in evaluation of river sedi-ments contamination.

Conclusions

The characterization of toxic potencies of environmental mix-tures of pollutants might be an important step in the riskassessment of contaminated ecosystems allowing the assess-ment of potential risks connected with the exposure of organ-isms, next to comparing concentrations of selected contami-nants with quality criteria or EQS. This study documents thatthe endocrine disruptive and dioxin-like potencies observed insediments were not, respectively only to a minor extent,associated with routinely monitored hydrophobic organic pol-lutants. The contribution of PAHs, which were the predomi-nant contaminants in the studied region, to the dioxin-likepotency was 13–21 % across locations (median values).Despite the correlation between concentrations of dl-PCBsand PCDD/Fs with BIOTEQ, contribution of these contami-nants to the dioxin-like potency was negligible as calculatedbased on their concentrations and relative potencies in thebioassay. Analyzed HOCs could not explain the observedestrogenic and antiandrogenic activities. The bioassays usedin this study provided important information indicating thepresence of yet unknown pollutants with dioxin-like andendocrine disruptive potencies in sediments.

This 1-year long study of fluvial sediments also re-vealed seasonal differences in contamination with dioxin-like AA and androgenic compounds. Further, a long-termcomparison of the unique data set originating from threelocations point to a greater inter-annual fluctuations inestrogenic than dioxin-like potency. Both short-term andlong-term data documents greater fluctuations in biologicalpotencies as well as in river water discharge at the indi-vidual locations during spring season. Hence, hydrology ofthe river and its seasonal differences should be taken intoaccount both in design and interpretation of any monitor-ing studies. Locations and time points need to be chosencarefully to make sure that the variability of contaminationis not overlooked. In addition, to be able to monitor long-term trends in a region, it is necessary to sample in thesame period of the year and under comparable hydrolog-ical situation. If this is not possible, the interpretation ofresults from long-term monitoring should be corrected tothese factors.

Acknowledgments This research was supported by projectsENVISCREEN (Ministry of Education, Youth and Sports of CzechRepublic No. 2B08036) and CETOCOEN (CZ.1.05/2.1.00/01.0001)from the European Regional Development Fund. We acknowledge KlaraKomprdova, Roman Prokes, and Ondrej Sanka for their technical assis-tance. Prof. Giesy was supported by the Canada Research Chair program,a Visiting Distinguished Professorship in the Department of Biology andChemistry and State Key Laboratory inMarine Pollution, City Universityof Hong Kong, the 2012 “Great Level Foreign Experts”(#GDW20123200120) program, funded by the State Administration ofForeign Experts Affairs, the P.R. China to Nanjing University and theEinstein Professor Program of the Chinese Academy of Sciences.

5020 Environ Sci Pollut Res (2014) 21:5007–5022

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Fig. S1 Spatial and seasonal variability of total organic carbon (TOC, %) in sediment

samples from the 15 sampling campaigns in July 2007–July 2008 (n=73). Middle line is

median, box means quartile range (25-75%), whisker is non-outlier range, circles are outliers,

stars are extremes and triangles are measured values

Fig. S2 Spatial variability of bioassay derived dioxin-like potency (BIOTEQ, pg/g, dm) in

each season derived from the 15 sampling campaigns in July 2007–July 2008 (n=73). Middle

line is median, box means quartile range (25-75%), whisker is non-outlier range and triangles

are measured values

Fig. S3 Daily water discharge at gauging stations a Kromeriz (representative for site BE) and

Spytihnev (SP) on Morava River and b Zlin on Drevnice River (representative for site MA).

The numbers 1 and 15 show the dates of first and last (15th) sampling campaigns: 1 – June 20,

2007; 15 – July 16, 2008.

0

5

10

15

20

25

1.1.

2007

1.2.

2007

1.3.

2007

1.4.

2007

1.5.

2007

1.6.

2007

1.7.

2007

1.8.

2007

1.9.

2007

1.10

.200

7

1.11

.200

7

1.12

.200

7

1.1.

2008

1.2.

2008

1.3.

2008

1.4.

2008

1.5.

2008

1.6.

2008

1.7.

2008

1.8.

2008

1.9.

2008

1.10

.200

8

1.11

.200

8

1.12

.200

8

Flow

(m3 .s

-1)

Zlin

spring summer autumn winter spring summer autumn

b

a

0

100

200

300

1.1.

2007

1.2.

2007

1.3.

2007

1.4.

2007

1.5.

2007

1.6.

2007

1.7.

2007

1.8.

2007

1.9.

2007

1.10

.200

7

1.11

.200

7

1.12

.200

7

1.1.

2008

1.2.

2008

1.3.

2008

1.4.

2008

1.5.

2008

1.6.

2008

1.7.

2008

1.8.

2008

1.9.

2008

1.10

.200

8

1.11

.200

8

1.12

.200

8

Flow

(m3 .s

-1)

KromerizSpytihnev

summerspringwinterautumnsummer autumnspring

1 15

1 15

Fig. S4 Spatial and seasonal variability of predicted (chemically-derived) dioxin-like potency

(TEQ, pg/g, dm) in sediment samples derived from the 15 sampling campaigns in July 2007–

July 2008 (n=73).. Middle line is median, box means quartile range (25-75%), whisker is non-

outlier range and triangles are measured values

Fig. S5 Average daily water temperature (°C) at gauging stations a Kromeriz (representative

for site BE) and Spytihnev (SP) on Morava River and b Zlin on Drevnice River

(representative for site MA). The numbers 1 and 15 show the dates of first and last (15th)

sampling campaigns: 1 – June 20, 2007; 15 – July 16, 2008.

a

0

5

10

15

20

251.

1.20

07

1.2.

2007

1.3.

2007

1.4.

2007

1.5.

2007

1.6.

2007

1.7.

2007

1.8.

2007

1.9.

2007

1.10

.200

7

1.11

.200

7

1.12

.200

7

1.1.

2008

1.2.

2008

1.3.

2008

1.4.

2008

1.5.

2008

1.6.

2008

1.7.

2008

1.8.

2008

1.9.

2008

1.10

.200

8

1.11

.200

8

1.12

.200

8

Tem

pera

ture

(°C)

KromerizSpytihnev

b

spring summer springwinterautumn summer autumn

1 15

0

5

10

15

20

25

1.1.

2007

1.2.

2007

1.3.

2007

1.4.

2007

1.5.

2007

1.6.

2007

1.7.

2007

1.8.

2007

1.9.

2007

1.10

.200

7

1.11

.200

7

1.12

.200

7

1.1.

2008

1.2.

2008

1.3.

2008

1.4.

2008

1.5.

2008

1.6.

2008

1.7.

2008

1.8.

2008

1.9.

2008

1.10

.200

8

1.11

.200

8

1.12

.200

8

Tem

pera

ture

(°C)

Zlin

spring summer springwinterautumn summer autumn

1 15

Table S1 Sampling campaigns in each sampling season (samples were clustered according to

four hydrologically defined seasons)

Campaign no.

Sampling date Season

1 2007-06-20 Summer 2 2007-07-18

3 2007-08-15 4 2007-09-12

Autumn 5 2007-10-10 6 2007-11-07 7 2007-12-05

Winter 8 2008-01-02 9 2008-01-30

10 2008-02-27 11 2008-03-26

Spring 12 2008-04-23 13 2008-05-21 14 2008-06-18 Summer 15 2008-07-16

The sampling times from previous studies are listed in Table 2.

Table S2 Relative potencies (REP) of aryl hydrocarbon receptor (AhR) activation determined

in the test with H4IIE-luc cells (24 h exposure)

Compound REP Compound REP

PAHsa PCDDsb Fluoranthene 2.27×10-8 2,3,7,8-TCDD 1 Pyrene 1.78×10-6 1,2,3,7,8-PeCDD 0.54 Benzo(a)anthracene 7.04×10-6 1,2,3,4,7,8-HxCDD 0.30 Chrysene 1.01×10-4 1,2,3,6,7,8-HxCDD 0.14 Benzo(b)fluoranthene 3.35×10-5 1,2,3,7,8,9-HxCDD 6.60×10-2 Benzo(k)fluoranthene 1.64×10-3 1,2,3,4,6,7,8-HpCDD 4.60×10-2 Benzo(a)pyrene 9.01×10-5 OCDD 5.00×10-4 Indeno (123cd)pyrene 2.96×10-4

Dibenzo(ah)anthracene 1.17×10-3 PCBsb PCDFsb PCB 77 1.30×10-3 2,3,7,8-TCDF 0.32

PCB 81 4.20×10-3 1,2,3,7,8-PeCDF 0.21 PCB 126 6.70×10-2 2,3,4,7,8-PeCDF 0.50 PCB 169 3.40×10-3 1,2,3,4,7,8-HxCDF 0.13 PCB 105 1.20×10-5 1,2,3,6,7,8-HxCDF 3.90×10-2 PCB 114 4.80×10-5 1,2,3,7,8,9-HxCDF 0.11 PCB 123 2.40×10-5 2,3,4,6,7,8-HxCDF 0.18 PCB 156 2.10×10-4 1,2,3,4,6,7,8-HpCDF 2.90×10-2 PCB 157 8.00×10-5 1,2,3,4,7,8,9-HpCDF 4.10×10-2 PCB 167 8.20×10-6 OCDF 6.50×10-3 PCB 189 6.70×10-6

a Machala et al. (2001) b Behnisch et al. (2003)

Table S3 Sediment quality guidelines derived by de Deckere et al. (2011)

Consensus 1 value Consensus 2 value (µg/kg dry mass of sediment) (µg/kg dry mass of sediment) Naphthalene 200 6600 Acenaphthylene 30 5200 Acenaphthene 40 3300 Fluorene 40 260 Phenanthrene 180 890 Anthracene 30 170 Fluoranthene 250 1200 Pyrene 240 940 Benz[a]anthracene 120 600 Chrysene 150 830 Benzo[b]fluoranthene 170 660 Benzo[k]fluoranthene 80 320 Benzo[a]pyrene 140 600 Indeno[123cd]pyrene 120 480 Dibenz[ah]anthracene 20 120 Benzo[ghi]perylene 110 450 PCB 28 0.04 2 PCB 52 0.1 4.6 PCB 101 0.54 6.7 PCB 118 0.43 6.9 PCB 153 1.5 9.7 PCB 138 1 7.5 PCB 180 0.44 5.5 p,p'-DDE 0.31 6.8 p,p'-DDD 0.06 3.2 HCB 0.0004 0.72