Robust assessment of moderate heavy metal contamination levels in floodplain sediments: A case study on the Jizera River, Czech Republic

Science of the Total Environment 452–453 (2013) 233–245

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Robust assessment of moderate heavy metal contamination levels in floodplain sediments: A case study on the Jizera River, Czech Republic T. Matys Grygar a, b,⁎, T. Nováková a, c, O. Bábek d, J. Elznicová b, N. Vadinová b a

Institute of Inorganic Chemistry AS CR, v.v.i., 250 68 Řež, Czech Republic Faculty of Environment, J.E. Purkyně University in Ústí nad Labem, Králova Výšina 3132/7, 400 96 Ústí nad Labem, Czech Republic Institute of Geochemistry, Mineralogy and Mineral Resources, Faculty of Science, Charles University in Prague, Albertov 6, 128 43 Prague 2, Czech Republic d Department of Geology, Faculty of Science, Palacký University Olomouc, 17. listopadu 1192/12, 771 46 Olomouc, Czech Republic b c

H I G H L I G H T S • • • •

Assessment of background values and heavy metal enrichment in floodplain soil Methods to handle facies bias of enrichment factors in floodplain fines An approach that integrates geography, geophysics and geochemistry Natural enrichment by heavy metals must be considered when enrichment factors are ~1.5.

a r t i c l e

i n f o

Article history: Received 23 November 2012 Received in revised form 20 February 2013 Accepted 25 February 2013 Available online 20 March 2013 Keywords: Heavy metals Pollution Background Fluvial sediments Enrichment factor

a b s t r a c t Enrichment factors for Cr, Cu, Ni, Pb and Zn in floodplain fines from the middle and the lower courses of the Jizera River (a tributary of the Elbe River in the Czech Republic) were evaluated to compare the original contamination profiles with post-depositional and pedogenic changes. Background concentrations of heavy metals were assessed from uncontaminated sediments (soils) in the study area that belong to the same sedimentary facies and were not affected by reductimorphic processes. Facies assignment is accessible by geophysical imaging combined with core analysis. Sediments from point bars and channel banks in direct contact with riverine water are more heavily polluted than overbank fines from the distal floodplain. The point pollution source, a century-old battery and car production facility in the city of Mladá Boleslav, has certainly been responsible for Ni and Cr pollution, contributed substantially to Cu and Pb pollution, and had a less significant effect on the Zn enrichment factor. Although the use of soil enrichment factors has been criticized, these factors help to manage hydraulic sorting and recognition of post-depositional migration in soil profiles of floodplain sediments. When moderate pollution (enrichment factor about 1.5 for Cu, Pb and Zn) is found, background concentrations must be carefully evaluated and natural enrichment must be taken into account. Studies of such small enrichment factors contribute to the understanding of the dispersal and fates of pollutants in floodplains. © 2013 Elsevier B.V. All rights reserved.

1. Introduction

et al., 2005). Variations of ratios of the stable isotopes of lead (mainly Pb, 207Pb and 208Pb) in sediments and soils, regarded as proof of anthropogenic Pb from leaded gasoline, can include significant natural contributions from climatic and biogeochemical processes (Reimann et al., 2012). Sucharova et al. (2011) have recently criticized the direct comparison of Pb content and Pb isotope ratios between humus and underlying B horizons due to their different origins. Natural soil variability is so great that it is hardly possible to evaluate anthropogenic pollution in soil by trace metals from medium to large scale geochemical mapping without knowing local geochemical conditions at each site (Reimann and de Caritat, 2005; Reimann and Garret, 2005; Yesilonis et al., 2008; Desaules, 2012; Petrotou et al., 2012). Natural processes and geological variability can blur or distort data or give false results, particularly when pollution levels are low or derive from different remote or diffuse sources,

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The reliable evaluation of anthropogenic impacts in sediments is a relevant topic for current science as well as practical decision making. Several recent examples show that this task is complex even in an apparently simple and traditional case such as the reconstruction of industrial heavy metal pollution. Increased Hg concentrations in the youngest lake sediments in the Canadian Arctic have been attributed to global atmospheric pollution, but enhanced Hg scavenging from water columns due to global warming should also be taken into account as a cause for increased Hg concentrations (Outridge ⁎ Corresponding author at: Institute of Inorganic Chemistry AS CR, v.v.i., 250 68 Řež, Czech Republic. Tel.: +420 603787409. E-mail address: [email protected] (T. Matys Grygar). 0048-9697/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scitotenv.2013.02.085

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which is the case in most European floodplains without hot spots such as mines or metallurgical operations in their watersheds. Floodplains are widespread sedimentary environments in continental settings. Because particulate anthropogenic pollutants (fly ash, dust) are transported and disseminated more efficiently by rivers than by the atmosphere, floodplains in most industrialized countries are polluted by heavy metals. The value of floodplains as pollution archives is diminished by the spatiotemporal variability of sediment deposition and reworking inherent to floodplains. Fluvial archives are more prone to hiatuses and deposition irregularities than other sedimentary environments (Sadler, 1981; Lewin and Macklin, 2003). Sediment sorting considerably affects the spatial distribution of pollutants in floodplains (Macklin et al., 1994; Wyżga and Ciszewski, 2010 and references therein), and chemical (reactive) pollutants may undergo post-depositional mobilization due to soil processes, particularly those processes that are driven by variable water tables (Hudson-Edwards et al., 1998; Svennen and Van der Sluys, 1998; Du Laing et al., 2009). But if these phenomena are taken into account (or are negligible), floodplain sediments can allow the reconstruction of anthropogenic pollution from time periods before appropriate analytical techniques and monitoring were available (Macklin et al., 1994; Bølviken et al., 1996 and references therein; Middelkoop, 2000; Meybeck et al., 2007; Le Cloarec et al., 2011; Matys Grygar et al., 2012; Ayrault et al., 2012). Pollution as a chemostratigraphic marker has created correlation surfaces for phenomena such as the onset of pollution (Grygar et al., 2010; Notebaert et al., 2011; Matys Grygar et al., 2011). Pollutants at moderate enrichment factors of approximately 2 can be identified in overbank fines from European lowland rivers (Matys Grygar et al., 2012; Nováková et al., 2013). Moderate enrichment factors can resemble observations of non-polluted soil profiles (Reimann and Garret, 2005). Moderate enrichment does not represent an environmental threat, but may occur in all inhabited floodplains including areas impacted “only” by fertilizers, agrochemicals, pigments, transportation, coal burning and other common sources of heavy metals. The resulting weak contamination signal could be a sedimentary marker of the periods of collective regional impacts and not limited to particular sites (Zalasiewicz et al., 2011). We examine effects that may blur this pollution signal in the Jizera floodplain (Fig. 1), which is not considered to be severely polluted, but which flows through the city of Mladá Boleslav where there is a century-long tradition of car and electric battery production. We test a hypothesis that moderate pollution in floodplain sediments can preserve information about pollution sources and spatial heterogeneity of floodplains.

2. Materials and methods 2.1. Study area The Jizera River (the Izera River in Poland), a tributary of the Elbe River (the Labe River in the Czech Republic), rises at the Czech– Poland border. The total length and watershed area of this river are 165 km and 2193 km 2, respectively. The Jizera's mean annual discharge is 22.3 m 3/s in Bakov nad Jizerou (river kilometer 49.10, Fig. 1). In this study area, the floodplain elevation decreases from 217 to 185 m a.s.l. between profiles J2 (river kilometer 61–62) and J4 (river kilometer 13–14), respectively. The Mladá Boleslav climate area (the main part of the study area) is relatively dry with cumulative precipitation of 200–300 mm and 350–400 mm in the winter and the summer seasons, respectively. The floodplain surface consists of sandy Cretaceous Cenomanian–Turonian marine sediments. The Jizera floodplain is inundated seasonally by overbank floods, not only after spring thaws but also after heavy summer rains, particularly in areas immediately downstream from Mladá Boleslav. Due to this frequent inundation, the floodplain is used primarily for hay production.

Evidence of overbank flooding was apparent at most coring sites, especially in the late winter and the early spring seasons. The watersheds of the central and the lower courses of the Jizera are primarily used for agriculture, and only small areas are forested (Fig. 1). In the 20th century, a sugar refinery operated in the town of Mnichovo Hradiště. The city of Mladá Boleslav was the most important industrial center in the study area with respect to heavy metal pollution. This city was founded in the second half of the 10th century, and its current population is 44,252. The Laurin & Klement factory was founded in Mladá Boleslav in 1895 and originally produced bicycles and motorcycles. More recently, the Laurin & Klement factory manufactured cars. In 1925, the Laurin & Klement factory was acquired by the Škoda Works, and Škoda Auto is now part of the Volkswagen Group. The Company for Accumulator Production was founded in 1903, and started the production of starting batteries for Varta AG in 1925 (500 t Pb processed annually), their brand was changed to Akuma in 1953.

2.2. Sample collection and analysis The upper 2–3 m of the Jizera basin fill was accessible by hand drilling. Most sampling and analytical methods used in this study have been described previously (Grygar et al., 2010; Matys Grygar et al., 2011; Nováková et al., 2013). Sediments were sampled using a hand-drilling set by Eijkelkamp (Giesbeek, the Netherlands) consisting of a 1 m long groove corer and an optional number of 1 m long extension rods. Thirty-three cores from 12 sites were included in this study. Sampling site locations are shown in Fig. 1. These sampling sites were located at least 1 km from built-up areas, and there was no evidence of human intervention other than hay production. All sampling sites were situated within the area inundated by at least Q5 (maximum 5-year) discharges. Soil samples were air-dried at room temperature, ground manually and analyzed in the laboratory. Cation exchange capacity was determined as ΔCu, which is the consumption of [Cu(trien)] 2+ complex (trien = 1,4,7,10-tetraazadekane, or triethylenetetramine) in mmol Cu2+/g (Meier and Kahr, 1999; Grygar et al., 2009). The parameter ΔCu is a quantitative measure of expandable clay minerals and, if the percentage of expandable minerals in clay is constant, ΔCu is proportional to the % of clay in soil (Grygar et al., 2010). Elemental analysis was performed by X-ray fluorescence (XRF) with a MiniPAL 4.0 spectrometer (PANalytical, Almelo, the Netherlands) and an air-cooled Rh tube with a 9 W maximum input and a Peltier-cooled energy dispersive Si detector. The elements listed in Table 1, Ca, P, S and Si, were analyzed by XRF. The quality of these measurements was sufficient for this study, and their low cost allowed us to analyze every core sample (1297 samples) in this study. Repeatability of XRF signal acquisition is expressed in Table 1 by relative standard deviations. The XRF results were calibrated using ICP-MS spectroscopy performed under conditions described by Grygar et al. (2010), Matys Grygar et al. (2011, 2012) and Nováková et al. (2013), and the calibration curves are shown in Table 1. Calcium, P, S and Si were not analyzed by ICP-MS. For calibration purposes, only the Jizera samples were used for Ni XrF, and the Morava sediments from previous studies (Matys Grygar et al., 2011, 2012) were used for other elements. Enrichment factors were calculated using Eqs. (1) and (2), which are discussed below. Background concentrations of heavy metals were estimated by a regression analysis of plots of heavy metal content versus suitable normalizing element concentrations in unpolluted sediments unaffected by reductimorphic processes (Fig. 2). The resulting equations (Table 2) were used to calculate expected background concentrations in the upper polluted sediment strata. This procedure to calculate background concentrations is discussed in more detail in the Results and the Discussion sections.

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Fig. 1. A map of the study area and sampling sites, where J1, J3 and J5 contain several cores across the floodplain. The yellow-hatched area is the corresponding part of the Jizera watershed. The red line is a motorway that parallels the studied river course.

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Table 1 Calibration curves for XRF analyses. R.s.d. is relative standard deviation of XRF readings, c.p.s. is counts per seconds (readings of XRF spectrometer). Element

R.s.d. (%)

Calibration curve for XRF analyses

Number of samples

r2

Rb Ti Pb Zn Cu Cr Ni

4.0 2.7 4.4 3.8 9.9 2.9 3.7

Rb (ppm) = 1.376 Rb (c.p.s.) Ti (ppm) = 6.666 Ti (c.p.s.) Pb (ppm) = 3.836 Pb (c.p.s.)-8.098 Zn (ppm) = 2.451 Zn (c.p.s.) Cu (ppm) = 2.601 Cu (c.p.s.)-6.176 Cr (ppm) = 4.073 Cr (c.p.s.)–34.95 Ni (ppm) = 3.133 Ni (c.p.s.)–19.499

157 243 292 299 298 153 11

0.887 0.631 0.876 0.905 0.789 0.683 0.959

2.3. Geographic data sources River dynamics were evaluated by comparing historical maps from the 2nd Austrian Military Survey (prepared during the first half of the 19th century) and orthophotomaps from 1953 and 2011. A more detailed overview of the J5 section in Mnichovo Hradiště-Veselá was obtained by manually vectorizing and geo-referencing corresponding map sheets from the Imperial Copies of Stable Cadastral Maps (1842). Inundated floodplain areas were visualized by Q5, Q20 and Q100 shape files provided by Povodí Labe (state administrator of the Elbe watershed). Data sources were processed using ArcGIS10.0 software (Esri, Redlands, CA). 2.4. Geophysical measurement by electrical resistivity tomography Electrical resistivity tomography (ERT) is an effective method to map buried sediment bodies. The ERT method is based on the resistivity contrast between resistive sands and gravels and conductive silts and clays (Baines et al., 2002; Musset and Khan, 2000). We measured three 2D resistivity sections (J1, J3 and J5) using an ARES automatic geoelectric system (GF Instruments, the Czech Republic) as shown in Fig. 1. These three sections were selected in locations where the floodplain was relatively wide (at least 200 m from the channel to the floodplain edge). A Wenner–Schlumberger array of 64 electrodes was used with 2 or 3 m electrode spacing. Sections that ranged from 190 to 381 m were evaluated by using the roll-along method with 16 electrode increments. Stacks of four pulses with 0.5 s pulse length were used for each measured point. The maximum depth of the apparent resistivity pseudosection was 33 m. The inverse model resistivity section was produced from the

Table 2 Background functions for Pb, Zn, Cu, Cr and Ni. All concentrations are in ppm. Element

Normalization curves for background concentrations

Number of samples

r2

Pb vs. Ti Zn vs. Ti Cu vs. Rb Cr vs. Ti Ni vs. Ti

Pb = 0.011⋅Ti Zn = 0.000013 ∗ (Ti)2 + 0.0086⋅Ti Cu = 0.154⋅Rb Cr = 0.0174⋅Ti Ni = 0.0061⋅Ti

146 146 146 146 146

0.75 0.86 0.47 0.36 0.65

apparent resistivity pseudosection by the least-square inversion method using RES2DINV software (Geotomo Software, Malaysia). To interpret depth profiles, the database of drill cores collected by the Czech Geological Survey (Prague) was used. Coring for geochemical analyses was performed along ERT sections. Cores were numbered J1/x, J3/x and J5/x, where x is the distance of the core from the beginning of the ERT section. Relative positions of the beginning of the section, the cores, and the river channel are shown in Fig. 3. 3. Results 3.1. Sediment profiles Most profiles have an upper 0.5 to 2 m thick layer of overbank fines (Fig. 2), which are brown clayey–silty sediments with minor sand admixture and only a few sandy intercalations that are a few mm thick. Typically, black Mn–Fe oxide concretions (with a diameter of approximately 1 mm) are found at depths of 0.3–1 m, while rusty Fe oxide stains in a partly discolored, grayish matrix are observed below the concretions. The corresponding Mn accumulations and Fe variations are shown in Fig. 2. The A horizon is shown by color contrast in some profiles. In most cases, soil structure is developed in overbank fines, particularly when the A horizon is apparent, and below the fines, the sediment is usually consolidated, tough, brown to yellowish brown in color and does not contain any laminations or sandy strata. Near the river channel, the top strata of overbank fines are less consolidated, pedogenically affected, and compacted, and there is no evidence of soil structure, discernible A horizons or Mn and Fe oxide accumulations in the top 1–2 m. Obviously, these sediments were deposited at rates higher than distal floodplain fines, and they contain sandy strata or large proportion of sand. Typical examples

Fig. 2. Depth profiles of selected elements in core J3/200. Asterisks in the Mn/Ti column show the Mn accumulation in concretions in a prevalently oxic sediment zone. The gray-hatched area is a reductimorphic zone with decreased or scattered Mn, Fe and Zn contents and scattered or increased Cu contents. The gray rectangle (“safe depths”) highlights sediments that are suitable for background evaluation.

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Fig. 3. The ERT images of the three sections J1, J3 and J5, which are arranged from upstream (top) to downstream (bottom). Double arrows indicate sediment core positions.

are J1/220, which includes levee sediments (see below), and the J5/15, the J5/29, and the J5/45 sediments of lateral accretions (see below). Sandy sediments, sometimes with gravel admixture, underlay overbank fines. Boundaries between underlying coarser sediments and overlying overbank fines are mostly stepwise, with gradual upward fining, occasionally laminated, and have interfaces that are several dm thick, which we interpret as point bar sediments. The common occurrence of this sedimentary pattern indicates lateral shifting of channels in the past. Wood fragments were found at the top of these buried point bar sediments, slightly below the overbank fines, in two profiles in the J1 section: first, in J1/220, at a depth of 300 cm, with 14C age 650 ± 25 BP, and second, in J1/54, at a depth of 220 cm, with 14C age 520 ± 30 BP (Poznań Radiocarbon Laboratory, Poland, Poz-43650 and Poz-43737). Because wood fragments might be reworked in tops of point bars and paleochannel deposits (Notebaert et al., 2011), these 14C data represent maximum age estimates for

overlying floodplain fines, and an estimate of the minimum mean vertical aggradation rate of overbank fines of approximately 0.4 cm/y. According to the description of deeper cores from hydrological and geological surveys at sites less than 400 m from the J1, the J3 and the J5 sections (obtained from the Czech Geological Survey), the base of the coarse, sandy, gravely and pebbly deposits is at a depth of 4–11 m, and these deposits are thought to be from the Quaternary age. Below these Quaternary deposits, there are Cretaceous (Turonian) rocks: marls or fine marly sandstones, which are shown by ERT imaging. 3.2. Geophysical imaging by ERT The ERT method visualizes internal structures at depths that are an order of magnitude greater than depths that we accessed by hand-drilling. However, resolution in the top 3 m of soil is sufficient to identify sediment bodies from several centuries. Most ERT sections in

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the Jizera floodplain showed a characteristic horizontal arrangement of contrasting resistivity domains (Fig. 3). The most prominent, laterally continuous high-resistivity layer (from ~100 to ~400 Ω m) was invariably detected between ~4 and ~13 m below the surface and only occasionally at the surface. Lithological control from boreholes shows that this zone coincides with coarse grained Quaternary sands with variable proportions of gravel and pebbles. Typically, dry sands have higher resistivity values (from 500 to 5000 Ω m) than clays (from 1 to 100 Ω m; Musset and Khan, 2000). When these sediments are saturated, their resistivity logically decreases, but their lithological contrast is maintained (Baines et al., 2002). Consistent with case studies from the literature (Bersezio et al., 2007; Giocoli et al., 2008), this high-resistivity layer is interpreted as laterally accreted sands and gravels due to horizontal channel migration. Lateral accretion units are bound by a sharp basal surface (from ~ 10 to ~ 13 m below the current floodplain surface). Beneath the lateral accretion units, there are zones of variable resistivity that, according to borehole data (above), represent the pre-Quaternary basement. This flat, nearly horizontal basal surface represents the maximum depth of Quaternary river erosion (the base level of erosion). The overlying, uppermost low-resistivity layer (from b 20 to ~ 100 Ω m) coincides with overbank fines, silty clays and sandy to silty clays lying horizontally on top of lateral accretion units. This assignment corresponds to flat surface morphology and evidence of flooding. Some floodplain deposits are cut by thin zones with very low resistivity (from b10 to ~ 40 Ω m; Brodce), which coincide with vegetation patterns in orthophotomaps and are interpreted as recently abandoned channels. Several parts of the sections show non-planar arrangements of resistivity domains. The presence of levee sediments (Fig. 3) is inferred in section J1/220 from the proximity of this site to the present-day channel and the characteristic wedge shape of the high-resistivity (coarser-grained) domains, which become thinner in the proximal-to-distal direction. Deposits with probable inputs of colluvia, in an infiltration zone just below the sloping floodplain edge, were detected in section J1/54. The contrasting structure along the current channel bank in section J5, and sampled in sections J5/15, J5/29 and J5/49, revealed sandy lateral deposition units of former point bars or the river channel, which was confirmed by an analysis of historical maps (below).

3.3. Heavy metal background The comparison of heavy metal contents in different locations requires a careful evaluation of their background concentrations to identify possible local geochemical variations. In Fig. 4, elemental analyses and ΔCu are compared with Al/Si ratios (a proxy for the proportion of aluminosilicates, which are mainly clay minerals, to quartz and feldspars, which are grain size proxies, Grygar et al., 2010; Matys Grygar et al., 2011). The finer the sediment, the larger the Al/Si ratio, but even coarse and gravely sands have non-zero Al/Si ratios in Jizera sediments because their coarse fractions contain considerable amounts of Al-bearing minerals such as micas and feldspars. Typical depth profiles of selected elements are shown in Fig. 2. Matrix elements such as Al, Ti and K are interrelated by their joint occurrence in clay and silt size fractions, which consist mostly of natural aluminosilicates and heavy minerals (Ti). The elements Mn and Fe partially correlate with these matrix elements, and their correlations are strongest with Ti, but their actual content at depths between approximately 0.5 and 2 m is also affected by secondary precipitates related to redox changes in floodplain fills. Heavy metals, in particular Cu, Pb, and Zn, and to a lesser extent Cr and Ni, are enriched in the top layers. This enrichment of the top layers is always associated with increased Ca, P and S contents in topsoil and roughly coincides with the A horizon in places where soil horizons are clearly distinguishable.

The data for ΔCu and Al/Si correlate roughly, but several sediment profiles have somewhat different clay assemblages (Fig. 4, panel I). Distinct profiles from the northernmost part of the study area, for the upstream (profiles J2 and J8) and the downstream (section J5) areas of the city of Mnichovo Hradiště, have smaller ΔCu values at given Al/Si ratios, i.e., less expandable clay in the aluminosilicate assemblage. In section J3/70, the ΔCu and Al/Si results are not correlated, probably because these profiles occur in a material that is a mixture from different sources (probably colluvial and fluvial sources). No geogenic heterogeneity was found in the relationships among Al, K, Ti and Fe in these sediments, which is consistent with the otherwise rather uniform geology of the central and the lower courses of the Jizera in this study. The increase of heavy metal contents in top layers was expressed conventionally by the enrichment factor: EF ¼ ½actual=½background

ð1Þ

where [actual] is a measured concentration or its ratio to a suitable immobile element (in this study we use Ti and Rb) unaffected by anthropogenic pollution (normalized concentration), and [background] is an estimated (extrapolated) concentration from uncontaminated pre-industrial sediments. Background functions for Jizera sediments were obtained by least-squares fitting data from overbank fines at depths between the base of the heavy metalenriched top layer (from approximately 20 to 50 cm) and the top of the reductimorphic zone (from approximately 70 to 150 cm). In the underlying reductimorphic zone, the sediments show clear signs of Fe-oxide migrations, with Fe spikes and reductions in overall Mn and Fe contents in XRF spectra (Fig. 2, gray-hatched rectangle), and corresponding color patterns that are visible to the unaided human eye in the cores. To identify the deep samples with original (synsedimentary) geochemistry, we used the methodology described previously (Matys Grygar et al., 2011, 2012; Nováková et al., 2013). In Fig. 2, the depth intervals for obtaining reliable background functions are marked with a gray rectangle in which Ti-normalized Fe and heavy metal contents are practically constant. We found that Mn oxide concretions (spiky Mn enrichments, asterisks in Fig. 2) were not associated with changes in heavy metal contents. Strata with overly large sand contents and correspondingly low Al/Si XRF signal ratios (b0.06 c.p.s./c.p.s., where c.p.s. are counts per second) and ΔCu (b0.02 mmol/g) were excluded from these calculations because, as clay-poor lithology, they do not guarantee stable depth profiles of heavy metals. Several profiles were excluded, such as sections J1/54 and J3/70 from the floodplain edges, where overbank fines probably mixed with colluvial sediments. In sections J5/15, J5/29 and J5/45 and cores taken from river banks (sections J6BŘ, J7, J8BŘ), no sediments fulfilled the criteria for the background — the sediments were polluted to significant depths with heavy metal concentrations that increased with depth. The resulting background functions are listed in Table 2. 3.4. EFs in polluted sediments The EFs were obtained for all 33 profiles in this study, as shown in Fig. 1. These EFs exhibited both lateral (effects of the position–distance to the river channel) and downstream variability. The lateral variability of pollution (normalized element content or maximum EFs) at a given position along the river course is shown for two sites in Figs. 5 and 6. Maximal EFs were obtained as the median of the three largest adjacent EF values in each profile. Section J5 (Fig. 5) included profiles with sandy sediments (lateral-accretion deposits, probably point bars) capped with overbank fines. These facies assignments for the profiles of sections J5/15, J5/29 and J5/45 are based on sediment lithology, ERT and maps. The lateral-accretion deposits are more heavily contaminated (EFs of Cu,

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Fig. 4. Relationships between Al/Si XRF signal ratios and XRF signals for selected elements (panels A–H) and ΔCu (panel I). “Purely lithogenic” elements are shown in panels A to C with regression lines, and elements with surface enrichment are present in panels D to H with lines to visualize non-enriched sediments. In panel I, three groups of points are distinguished: J2, J8 and J5, which are the most upstream sediments from Mohelnice nad Jizerou and Mnichovo Hradiště-Veselá. The J3/70 profile with colluvium is from the floodplain edge in Brodce. The points from other places show a clear relationship between expandable clay mineral content (ΔCu) and grain-size proxy (Al/Si).

Pb and Zn are larger) than the vertically deposited overbank fines (sections J5/75, J5/110 and J5/150, Fig. 5). The profile J5/75 was retrieved from the bank of the river channel depicted in the 1842 historical map. Only sections J5/110 and J5/150 can be considered to be distal floodplain sediments during the 19th and 20th centuries. Two of three sediment profiles taken from channel banks (less than 1 m from the current bank) have larger EFs than distal floodplain sediments in the nearby floodplain farther from the channel, and unlike the other floodplain profiles, their pollution level increases downwards (within the first meter of their profiles). This behavior is shown in Fig. 6 for three profiles from the floodplain in Mohelnice nad Jizerou (upstream of Mnichovo Hradiště). Longitudinal changes of maximum EFs in floodplain fines are shown in Fig. 7. In this figure, profiles from channel banks, lateral deposits, and floodplain edges (discussed above) are not shown; the aim of the comparison was to determine pollution from the city of Mladá Boleslav recorded in sediments from the same sedimentary environment, a distal floodplain.

4. Discussion 4.1. River dynamics and the importance of floodplain architecture In its central and lower courses, the Jizera is a meandering river with two local parallel channels, according to historical and current maps. Some depressions from filled paleochannels or secondary channels can also be found. Results for 14C dates in the J1 section indicate that a layer of overbank fines, up to 2 m thick, was deposited during several centuries. This layer is consistent with the excessive layer of lateral accretion complex and abandoned paleochannels filled by additional conducting (finer) sediments shown by ERT imaging (Fig. 3). New accommodation spaces for recently deposited overbank fines in the Jizera floodplain have been continuously re-created by lateral erosion. In such cases, the concept of EF as a measure of pollution is well substantiated by observations of the substantial fractions of recent pollutants in newly deposited sediments on older reworked material.

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Fig. 5. The facies dependence of the Pb/Ti depth profiles in cores from section J5. In the aerial photograph, the black-hatched contour is the river course in Stable Cadastral Maps (1842), and the reddish area marks the Q5 inundation. In these graphs, the greenish rectangle identifies the natural background (two-σ limits).

On the other hand, the Jizera channel has been relatively stable over the past 150 years (between the 2nd Austrio-Hungarian Military Survey and the present study): only 37% of river reach lateral shifts of the channel position have exceeded the estimated map uncertainty of approximately 5 m. The lateral shift near section J5 (Fig. 5) is among the most pronounced natural channel movements in this study area. The total length of the Jizera has decreased by only 4%. The Jizera has not been embanked or realigned in a way that is similar to many other European rivers with unconfined, laterally moving channels and seasonal floodplain inundation. However, the Jizera has been modified by less conspicuous measures such as stone bank reinforcement, weir construction and maintenance, channel cleaning and removal of sediments from post-flood bank erosion, which now effectively limit lateral erosion and excessive sediment reworking. The Jizera River channel is considered to be artificially confined. The assignment of floodplain fine facies based on ERT results, i.e., overbank fines (vertically deposited blanket or levee deposits), laterally deposited point bar sediments, or abandoned channel fills, is indispensable to describing the nature of floodplain sediments. Vertically deposited blankets of overbank fines have the most continuous

sedimentation, while other facies may be reworked and deposited in an event-like (discontinuous) manner. Sampling floodplain fines at a given depth without considering facies would be arbitrary with respect to temporal aspects. In addition, facies play a crucial role in sediment sorting, and pollution history can only be reconstructed by comparing deposits of the same nature. The ERT results showed that the topmost 2 m of the Jizera floodplain consist mostly of vertically deposited blankets of overbank fines, which are a prerequisite for the interpretation of their geochemistry in this study. Sediments deposited by other mechanisms require particular attention, which is discussed in part 4.2. Notebaert et al. (2011) recently showed an example of variations in floodplain architecture and pollutant deposits in three Belgian rivers. 4.2. Facies bias in EF assessment Actual pollutant content in fluvial sediments is affected by hydraulic sorting (Macklin et al., 1994; Wyżga and Ciszewski, 2010 and references therein; Babek et al., 2010), which contributes to the formation of pollutant gradients perpendicular to channels. Coarser channel sediments

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Fig. 7. Heavy metal enrichment factors in sampling sites along the river course with a double arrow at the position of the city of Mladá Boleslav. Only distal floodplain cores are included (channel bank profiles and lateral deposits are not shown). Lines at EF = 1.4 and 1.6 indicate possible upper estimates of natural enrichments for Zn and Pb, respectively. The Cu content is calculated by Rb-normalization, and other elements are determined by Ti normalization. Fig. 6. Depth profiles of Pb and Zn (normalized to Ti) in cores from the distal floodplain (J4), the proximal floodplain (J8) and the channel bank (J8/BŘ) from the same river reach in Mohelnice nad Jizerou. The depth profile in J8/BŘ is anomalous (downward increasing EFs).

and proximal floodplain fines (point bars, levee sediments) may be more (Nováková et al., 2013) or less polluted (Wyżga and Ciszewski, 2010) than distal floodplain fines, depending on actual grain sizes and specific densities of pollutant-bearing particles with respect to other sediment components. Thus, the reconstruction of temporal trends and the evaluation of point sources along the river course should be conducted using the same facies, which have undergone the same hydraulic sorting. Meybeck et al. (2007) used floodplain sediments with a constant percentage of Al to reconstruct the pollution history in the Seine watershed; in fact, this approach could limit the facies bias. Sometimes, sieving is used before sediment analysis (Aulinger et al., 2002; Krüger et al., 2006) to suppress differences explicitly related to grain sizes. Sieving is a rather formal measure because the primary problem in floodplain sediments is hydraulic sorting prior to their deposition. Selection of sedimentary facies, together with the use of normalization, is obviously a more robust option. We have selected distal floodplain sediments within an area inundated at least annually for further evaluations because they are most evenly deposited (as a “blanket” of a fine mud) and least endangered by sediment reworking shortly after deposition. In addition, distal floodplain sediments are finer and less porous than proximal floodplain or channel sediments, which is important for vertical stability of pollutants (Ciszewski et al., 2008). Lithology was similar for distal floodplain sediments in the study area according to

lithology proxies (Al/Si XRF signal ratio and ΔCu), and these sediments generally are among the finest sediments present in the floodplain. At least basic knowledge of spatial distributions of facies types, i.e., floodplain architecture, is required for this approach. Most current studies of floodplain architecture are performed using drill cores with a sufficient spatial density (Houben, 2007; Notebaert et al., 2011). In our previous work, we performed facies assignment from cored sediment samples by chemical proxies of lithology, including contents of selected elements (Rb, Zr) and ΔCu, all after “calibration” by granulometry (Grygar et al., 2010; Matys Grygar et al., 2011). However, such assignments must be supported by spatial relations between lithological units. This approach may be conveniently achieved by geophysical imaging. The ERT techniques have already been applied to identify buried fluvial channels, point bar surfaces, fluvial aquifers and fine-grained lacustrine deposits (Bersezio et al., 2007; Crook et al., 2008; Giocoli et al., 2008; Doetsch et al., 2012). The interpretation of ERT images of Jizera sections is also based on our recent knowledge of the active anastomosing–meandering channel system of the Morava River in the eastern Czech Republic (Homola, 2012). Our results for the Morava River showed horizontal arrangements of resistivity domains and vertical stacking of fluvial facies (checked by borehole data) that were very similar to those observed in Jizera sections in this study. Furthermore, ERT helped us to identify sediments from facies other than distal floodplain sediments in the Jizera floodplain in this study. Phenomena responsible for EFs variability in the Jizera floodplain are depicted in Fig. 8. Interactions of river water with sediments,

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Fig. 8. Processes causing post-depositional changes of heavy metals in the floodplain sediments.

including evaporative accumulation of soluble components in topmost porous sediments, are most intensive in river banks and levees, as shown for Ca 2 + by Wolfert et al. (2002). We suppose that the joint upward gradient of Ca and most analyzed heavy metals (Fig. 2) is actually due to the evaporation-driven transport of soil solutions. Infiltration of river water and sorption of pollutants are demonstrated for point bars in Fig. 5 and channel banks in Fig. 6. Because of variable pollutant concentrations in some erosion banks of the Morava River and vertical instability of pollutants in sandy strata, we have found these results to be unreliable for correlations (Matys Grygar et al., 2012). Therefore, we did not include deposits from actual erosion banks in this study, although these deposits are easily accessible and sometimes used for sampling (Svennen and Van der Sluys, 1998). This dependence of pollutant contents on facies and pollutant migration, related to the interactions of river and ground water with sediments, contrasts with the opinion of Bølviken et al. (2004) on small lateral variability of geochemical floodplain mapping. Obviously, the evaluation of pollutants depends on acceptable variability with respect to actual pollution. Reductimorphic sediments can contain post-deposition remobilized trace elements (Swennen and Van der Sluys, 1998; Du Laing et al., 2009). It seems obvious that the zones should not be sampled to obtain background functions for pollutants. The recommendation of “… taking the background samples as deep as possible …” or at predefined depths (Demetriades, 2008) can hardly be accepted for moderately polluted sites unless redox states of sediments in each site are specified. In the Jizera floodplain, nearly every profile at a depth greater than 100–150 cm was strongly affected by the redox movements of Fe oxides and pollutants. The reliable depths for background samples were mostly 50–120 cm, but they were quite site-specific. Subjectively defined (Bourennane et al., 2010) BOTTOM depths can hardly be recommended, because depths below which Mn and Fe oxides are transformed are site specific. The best option is to evaluate individual depth profiles in the field and in the laboratory with continuous and detailed sampling of each core. Such an individual approach and detailed sampling has also been recommended by Macklin et al. (1994) and Bølviken et al. (2004) for overbank sediments and

Desaules (2012) for soils. However, this approach is not always implemented in case studies and geochemical mapping. 4.3. Geochemical background in floodplain sediments The EF definition in Eq. (1) differs from the original concept in which the actual ratio of examined and normalizing elements was compared with average crustal values (Reimann and de Caritat, 2005; Desaules, 2012 and references in both those reports). Currently, EFs with on-site references are used mostly to assess anthropogenic enrichment in sediments and soils. The choice of an on-site reference (background) is a prerequisite for the evaluations of actual trace element concentrations in anthropogenically affected sediments and soils (Reimann and Garret, 2005; Abrahim and Parker, 2008; Desaules, 2012). Plots of the contents of examined elements versus normalizing elements are conventional tools for background extrapolations. We obtained satisfactory regression curves by choosing either linear or quadratic functions with intercepts equal to zero (Table 2). The uncommon use of non-linear regression for Zn versus Ti can be rationalized by a variable dependence of individual elements on particle size fractions. Straight background lines (constant ratio of target and normalizing elements) are usually obtained for marine sediments, where size sorting is much less important than the highly variable percentages of autochthonous sediment components. The opposite behavior is true for floodplain sediments, where particle size distributions are highly variable (Grygar et al., 2010; Matys Grygar et al., 2011; Notebaert et al., 2011), and autochthonous components are negligible except where backswamp deposits occur. 4.4. Natural enrichment and other disturbances in floodplain archives In floodplains in the Czech Republic (and probably also in most Central and some West European rivers with dispersed pollution sources), the top polluted layer roughly coincides with the soil A horizon. In the Czech Republic, industrial pollution in sediment records started 50–100 years ago except for places with historical

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mining or metal processing activities. Two profiles in section J1 exhibited a mean aggradation rate of at least 0.4 cm/y. This estimate is in agreement with the mean sedimentation rate of floodplain fines of the Morava River, 0.3 to 0.4 cm/y (Matys Grygar et al., 2011). The A horizon in floodplain soils is typically 20–30 cm thick. This agreement suggests a possible biogeochemical contribution to element depth profiles (pedogenic bias, pollutant bonding to sorbents accumulated in the A horizons, element accumulation related to nutrient recycling). In the Jizera floodplain, Pb and Zn depth profiles coincide with Ca depth profiles (Fig. 2). However, we do not consider Ca to be an anthropogenic pollutant (unlike Bain et al., 2012), but rather a marker of the A horizon. In an ideal case of merely adding anthropogenic components to an invariant natural sediment “matrix”, the definition of EF by Eq. (1) can be rewritten as: EF ¼ ð½pollution þ ½naturalÞ=½natural

ð2Þ

where [pollution] is an anthropogenic component (from artificial particles) and [natural] stands for sediment, which would have been deposited if there had been no pollution, assuming that the sediment is otherwise unaffected by human activities. This ideal relation is, in practice, approximated by Eq. (1). The difference between Eqs. (1) and (2) draws attention to the assumption that background levels from reference sediments are applicable to polluted strata, which is not valid for polygenetic soils and sediments, where the “matrix” has been altered by river engineering or fluvial dynamics. On the other hand, Eq. (2) is compatible with the concept that floodplain sediments have been continuously reworked (i.e., their “matrix” is invariant) and recently spiked with pollutants. Such an assumption is not valid for soils, and this assumption must be taken into account when calculating EF (Reimann and Garret, 2005; Desaules, 2012). However, pedogenesis is able to enrich some elements in topsoil, even without human interference. Reimann and de Caritat (2005) assumed that at least some part of Zn EF ~ 1.4 and Pb EF ~ 1.6 in soils far from pollution sources could be attributed to natural processes. While Cu and Zn belong to biogenic elements, the natural enrichment of these elements in topsoil (together with other nutrients) is to be expected. Natural surface enrichment of soils is also apparent for Pb (Sucharova et al., 2011; Reimann et al., 2012), which is an unexplained phenomenon. Natural enrichment due to biogeochemical processes (pedogenesis) prompts us to replace Eq. (2) by: EF ¼ ð½pollution þ ½natural enrichment þ ½as depositedÞ

ð3Þ

=ð½as deposited−½diagenesisÞ where [natural enrichment] is the post-depositional accumulation of elements in an A (or O) horizon, [as deposited] is the original background not affected by any post-depositional processes and [diagenesis] stands for the partial removal of the most labile portion of elements due to their mobilization by early diagenesis. Thus, the EF should be > 1 also for anthropogenically unaffected sediments subjected to pedogenic processes and diagenesis in floodplains for sufficiently long periods of time. For negligible [natural enrichment]

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and [diagenesis], i.e., without post-depositional migrations, Eq. (3) changes to Eq. (2). Although we cannot offer a way to distinguish all components in Eq. (3), it is useful to show the crudeness of Eqs. (1) and (2). While biogeochemical cycling (and evaporation of groundwater in floodplains) will probably tend to shift elements upward, bioturbation, plowing and other artificial mechanical actions tend to homogenize the top strata and cause an apparent downward transport of pollutants from topsoil. We examined depth profiles of 137Cs and 210Pb in one sediment profile from the Jizera floodplain (results not shown), but it has not allowed dating, apparently due to homogenized 137Cs signals in the top 15 cm of the soil. Although historical maps do not record other land use in the floodplains we sampled, occasional cultivation of meadows cannot be excluded with absolute certainty. Unfortunately, it is not feasible to experimentally evaluate the extent of all disturbing phenomena that tend to distort original deposition patterns for each study site. Examination of downstream variations of EFs (Fig. 7) seems to be the simplest and most robust way to show that pollution indications are not erased by these disturbances (above). In this study, all five heavy metals were significantly enriched immediately downstream of the industrial city of Mladá Boleslav. The total heavy metal concentrations (and also concentrations of Cd and Sb) obtained by ICP-MS of selected samples are listed in Table 3. In the most heavily polluted samples, concentrations of Cd, Cu, Cr, Ni, Pb and Zn are near the upper limits of negligible risks in European countries listed by Desaules (2012). The stable lead isotope ratio 206Pb/207Pb in the background is larger than 1.18 in deep layers, while this ratio is about 1.17 in the polluted top layer, which is comparable with isotope shifts observed in middle Labe (Elbe) floodplain sediments in Germany (from 1.19 to 1.17 since about 1900 to the present, Krüger et al., 2006). The elements Cr, Cu and Ni can be attributed to metal plating and battery production. These three elements are considerably more enriched in Jizera distal floodplain sediments downstream of Mladá Boleslav than elsewhere in the Jizera floodplain. In the Morava watershed, there are no such industrial activities and, correspondingly, no statistically significant EFs were found in floodplain fines (Matys Grygar et al., 2011, 2012; Nováková et al., 2013). We assume that floodplain sediments of the Jizera and the Morava rivers have been subjected to similarly intense pedogenesis due to similar settings (climate and land cover), but the industrial impact is smaller in the Morava watershed. Pollution from Ni is rarely reported in mapping surveys unless there are specific industrial pollution sources (smelting, metal plating). The lowest EFs in the Jizera floodplain were found in sites upstream of Mladá Boleslav and downstream sites J6 and J4. The site J4 is close to wells near Káraný (Fig. 1), one of three sources of drinking water for Prague and its surrounding areas. Only Cu and Pb are enriched in the topmost strata in J4, but EFs are close to 1.5. The VLJ7 profile upstream from Mladá Boleslav has EFs of Zn, Cu and Pb that are also close to 1.5. It is questionable whether these profiles are contaminated (by diffuse sources or recycling of more polluted sediments from upstream sites) or whether they represent natural enrichment (Reimann and de Caritat, 2005). In the Strážnice area in the Morava floodplain, profiles outside flood defenses erected in 1930s have maximal top EFs of 1.3 for Zn and 1.2 for Pb (Matys Grygar et al., 2012), which consist of natural

Table 3 ICP MS analyses of metal concentrations (mg/kg) and 206Pb/207Pb isotope ratios in most polluted top strata (in bold font) and underlying unpolluted background sediments (normal font) in two cores downstream of Mladá Boleslav. VLJ3B is a parallel core to VLJ3. Sample

Al

Ti

Cr

Ni

Cu

Zn

Rb

Cd

Sb

Pb

206

Pb/207Pb

VLJ 3B, 10–12 cm VLJ 3B, 21–24 cm VLJ 3B, 36–40 cm VLJ 3B, 45–50 cm J1/106, 3–6 cm J1/106, 15–19 cm J1/106, 58–64 cm

45591 45071 41906 40201 53483 59742 47036

2470 2528 2332 2366 2781 2966 2498

78.3 51.2 39.6 38.0 66.6 80.3 48.8

66.7 37.1 16.0 15.0 31.9 37.3 22.4

74.3 35.6 14.8 12.5 63.6 68.6 23.8

169 109 59 54 209 243 74

82.0 82.3 78.8 78.4 93.4 99.6 86.7

1.2 0.7 0.3 0.3 2.1 2.7 0.5

4.9 3.5 1.6 1.2 8.9 17.6 2.1

77.2 54.6 30.3 26.8 100.2 149.4 38.0

1.171 1.174 1.182 1.184 1.169 1.167 1.183

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enrichment plus pre-1930s pollution. These values in the Strážnice area represent another estimate of an upper limit of natural enrichment (as mentioned above, these upper estimates for Zn and Pb are 1.4 and 1.6, respectively, Reimann and de Caritat, 2005). However, the Pb EFs between 1.7 and 2.3 in profiles VLJ7, J5, J2 and J8 (upstream of Mladá Boleslav) exceed both of these two upper estimates of EF. This enrichment can be attributed to diffuse pollution sources, such as the E65 motorway, which is nearly parallel to the Jizera floodplain (the red line in Fig. 1). The Cu enrichment > 1.4 in all Jizera floodplain profiles also indicates diffuse pollution sources and not natural enrichment, as no statistically significant enrichments were found in comparable Morava floodplain sediments.

Conflict of interest statement There is no actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations involved in our work.

5. Conclusions Distal floodplain sediments are useful archives of past heavy metal pollution and pollutant point sources. Particular attention must be paid to moderate pollution with EFs around 1.5 that resembles possible natural enrichment in topsoil due to biogeochemical processes. Natural enrichment of Pb in floodplain soils can be 1.2–1.6 for Pb and 1.3–1.4 for Zn. Evaluation of such moderate levels of contamination requires an evaluation of geogenic uniformity of study areas. To evaluate geogenic uniformity, we used the correlation plots of matrix elements above reductimorphic sediment layers and the characterization of clay assemblage by ΔCu. Only geochemically uniform sediments above the reductimorphic zone should be used to estimate background levels in floodplains with ancient contamination, slow net aggradation or high water levels where such sediments could be missing. This selection of sediments must be done individually for each sediment core. The EFs depend on facies due to the hydraulic sorting of riverborn solids and the chemical interactions of sediments with river water in permeable (coarse) strata. Thus, identification of sediment facies is necessary to obtain temporal and/or spatial functions of pollution. The assignment of facies is conveniently accomplished by a combination of geophysical measurements, map processing and coring followed by the laboratory analyses of sediments. In the Jizera floodplain, the facies bias of EFs is principally twofold: 1) sediment sorting by hydraulic transport that causes larger concentrations of Cu, Ni and Pb in laterally deposited sediments than in distal floodplain sediments (for example, Figs. 5 and 6); and 2) sediments in direct contact with river water that acquire secondary pollution with anomalous depth profiles (downward increasing EFs, Fig. 6). The topmost enriched strata in the distal floodplain of the Jizera River are definitively polluted by recent anthropogenic activities, in particular by industries operating in the city of Mladá Boleslav. Local industrial enterprises in the Jizera floodplain produced Ni and Cr pollutants, enhanced Cu and Pb EFs, and only weakly contributed to Zn EF.

Acknowledgment Laboratory sample processing and analyses were mostly performed by P. Vorm, J. Dörflová, R. Barochová and Z. Hájková (IIC Řež) and L. Plotnárek (University in Ústí n.L.). Institutional funding in IIC (RVO 61388980) was essential for this work. The work with geoinformatic data and a part of ICP analyses were funded by the OPVK project ENVIMOD (CZ.1.07/2.2.00/28.0205) and ERT profiling by the Czech Science Foundation project P210/12/0573 (GAČR). We thank the 4 reviewers for their very careful work.

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