T Fix
email: tfix@unistra.fr

G Schmerber

H Wang

J.-L Rehspringer

C Leuvrey

S Roques

M Lenertz

D Muller

A Slaoui

Investigation of KBiFe 2 O 5 as a Photovoltaic Absorber

Keywords: thin film, oxide, pulsed laser deposition, solar cell, photovoltaics

KBiFe 2 O 5 (KBFO) was grown by pulsed laser deposition (PLD) on SrTiO 3 (001) (STO), 1 at% Nb-SrTiO 3 (001) (Nb-STO) and MgAl 2 O 4 (001) (MAO). In the case of MAO substrate, epitaxial growth is obtained.

As its bandgap is relatively low (1.6 eV in the bulk), KBFO is a promising candidate for oxide photovoltaics. In this work we examine the growth of KBFO by PLD by looking at its structure and composition and we investigate the optical properties of the films obtained. A photovoltaic architecture based on KBFO films is proposed and a solar cell behaviour based on KBFO absorber is obtained.

Introduction

Thin film solar cells in industry are mainly based on CdTe, amorphous Si and CuInGa(Se,S) 2 (CIGS). In recent times research on hybrid perovskites expanded exponentially, with solar cell power conversion efficiencies above 21%. This proves that research on novel materials for solar cells can be quite successful and should be maintained. Standard solar cells are based on a pn-junction, however ferroelectric solar cells have emerged with a record conversion efficiency in Bi 2 FeCrO 6 of 8.1% [START_REF] Nechache | Bandgap tuning of multiferroic oxide solar cells[END_REF][START_REF] Quattropani | Tuning photovoltaic response in Bi 2 FeCrO 6 films by ferroelectric poling[END_REF][START_REF] Quattropani | Band-gap tuning in ferroelectric Bi 2 FeCrO 6 double perovskite thin films[END_REF].

In this type of solar cell, there is no need for a pn-junction and the charge separation can originate from the polarization due to the ferroelectricity [START_REF] Yuan | Arising applications of ferroelectric materials in photovoltaic devices[END_REF]. The most studied ferroelectric material for its photoelectric properties is BiFeO 3 [START_REF] Paillard | Photovoltaics with Ferroelectrics: Current Status and Beyond[END_REF]. It was discovered that open circuit voltages of more than a dozen volts could be obtained with this material, and that it is linked to the ferroelectric domain walls [START_REF] Yang | Above-bandgap voltages from ferroelectric photovoltaic devices[END_REF]. Still, ferroelectric solar cell efficiencies with BiFeO 3 are generally much below 1% and the BiFeO 3 bandgap of around 2.6 eV is not ideal for the solar spectrum [START_REF] Basu | Photoconductivity in BiFeO 3 thin films[END_REF]. In fact, oxides with a bandgap suitable for the solar spectrum around 1.3 eV are scarce. Examples of such oxides are 1.1 eV for LaVO 3 [START_REF] Jellite | Investigation of LaVO 3 based compounds as a photovoltaic absorber[END_REF], 1.2 eV for BiMnO 3 [START_REF] Chakrabartty | Photovoltaic effect in multiphase Bi-Mn-O thin films[END_REF], 1.2 eV for CuO (10) and 1.5 eV for Co 3 O 4 [START_REF] Kupfer | Thin Film Co 3 O 4 /TiO 2 Heterojunction Solar Cells[END_REF], but these examples provided low solar cell conversion efficiencies pointing out that other parameters than the bandgap must be taken into account to provide efficient solar cells, such as carrier density and carrier diffusion length. Therefore alternative materials are welcome.

In this perspective, KBiFe 2 O 5 (KBFO) was reported in 2013 as a new ferroelectric compound with a bandgap of 1.6 eV and a high Curie temperature of 780 K [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF]. Measurements on single crystal KBFO contacted with Ag electrodes led to a high open circuit voltage (V oc ) of 9.1 V and a short-circuit current density (J sc ) of around 15 µA/cm² [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF]. Other studies on bulk KBFO exhibited a photoresponse with V oc =2.04 V, J sc =20.7 µA/cm² [START_REF] Jalaja | Switchable photovoltaic properties of multiferroic KBiFe 2 O 5[END_REF], and V oc =-0.5 V and a short circuit current of 20 nA [START_REF] Zhang | Investigation on a new multiferroic compound KBiFe 2 O 5 : Structural, optical, electrical and magnetic properties[END_REF]. It was argued that the short-circuit current density was limited due to the fact that measurements were made on single crystal KBFO. Thus, the synthesis of KBFO layers using a sol-gel process and spincoating has been reported [START_REF] Zhai | Optical and magnetic properties of KBiFe 2 O 5 thin films fabricated by chemical solution deposition[END_REF][START_REF] Jalaja | Ferroelectric, ferromagnetic and optical properties of KBiFe 2 O 5 thin film: a structure property relationship[END_REF]. KBFO has a brownmillerite type-structure A 2 B 2 O 5 with lattice parameters a=0.7984 nm, b=1.1819 nm, c=0.5739 nm with an orthorhombic space group P2 1 cn [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF].

In addition, magnetoelectric and photovoltaic (PV) effects in KBFO were studied theoretically in [START_REF] Mettout | photovoltaic, and magnetophotovoltaic effects in KBiFe 2 O 5[END_REF].

In the present work, we investigate the growth of KBFO in the form of thin films using the pulsed laser deposition (PLD) method. PLD is known to result in high quality materials, in particular in the case of an expitaxial process. The structural and optical properties of the deposited KBFO films are reported.

Experimental procedure

The KBFO target used for the PLD process was prepared as follows. First potassium nitrate (4.936 g), bismuth (III) nitrate pentahydrate (26.973 g), and iron (III) nitrate nonahydrate (27.234 g) are poured in deionized water (~100 ml). Films deposited from a stoichiometric composition were shown to be largely K and Bi deficient. Therefore targets were made with an excess of K and Bi in the following proportions: K 1.45:Bi 1.65:Fe 2. Citric acid (14 g) is dissolved in the solution together with ethylene glycol (30 ml, the Pecchini method is used). The excess of water is evaporated and a viscous liquid without precipitate appears. This compound is pre-calcinated in a furnace at 350 °C for two hours, mechanically ground in a mortar, and further calcinated at 700 °C for 1 h in air. The obtained powder is ground again, pressed into a pellet and sintered at 700°C for 1 h in air. The target is thoroughly polished, as Rutherford Backscattering (RBS) has indicated that the surface of the target after sintering is mainly composed of K. It was checked that the composition of the polished target matches the stoichiometry of the precursors.

The PLD process was performed using a KrF laser with 10 Hz repetition rate and a laser fluence of around 2 J/cm 2 on the target. The substrates used for deposition were SrTiO 3 (001) (STO) (insulating, thickness 0.5 mm), 1 at% Nb-SrTiO 3 (001) (Nb-STO) (resistivity 0.003 Ω•cm, thickness 0.5 mm) and MgAl 2 O 4 (001) (MAO) (insulating, thickness 0.5 mm). The deposition was carried out at 700 °C under an oxygen pressure of 10 -2 mbar. KBFO film thicknesses were in the 50-100 nm range. The as-grown film was cooled down under the same atmosphere at a rate of 10°C/min until 300°C, below this temperature it was naturally cooled down until room temperature. Around 30 samples were deposited for the study.

The crystalline structure of the KBFO films was analyzed by X-ray diffraction using a Rigaku SmartLab diffractometer equipped with a monochromatic source delivering a Cu K α1 incident beam (45 kV, 200 mA, 0.154056 nm). X-ray θ-2θ and reflectivity were performed in order to look for the film structure, check the presence of spurious phases, and determine the film thickness. Scanning electron microscopy (SEM) was performed with a Gemini 500-ZEISS apparatus. Rutherford backscattering was used to determine atomic composition and thickness of the layers, using 1.5 MeV He + particles provided by the Van De Graaff Accelerator (HVEE KN4000) facility of ICube. Transmission electron microscopy (TEM) was performed with a FEI TALOS F200X TEM/STEM with ChemiSTEM technology (X-FEG and SuperX EDS with four silicon drift detectors) operated at 200 kV. It was used for microstructure characterization and energy-dispersive X-ray spectroscopy (EDS) chemical mapping.

The optical measurements of the KBFO films were investigated using a Perkin-Elmer Lambda 950 spectrophotometer using a 150 mm integrating sphere. Their ferroelectric properties were investigated by the Piezoresponse Force Microscopy (PFM) technique using a Bruker Icon QNM microscope. For PV measurements, I-V characteristics were carried out at room temperature using an Oriel Solar Simulator in AM1.5G conditions and a Keithley 2461 SourceMeter.

Results

Firstly KBFO was deposited by PLD on SrTiO 3 (001) (STO). The XRD θ-2θ pattern was recorded as shown in Fig. 1a). STO is cubic with a lattice parameter of 0.3905 nm. Because there is no direct match between the STO substrate and KBFO, two different orientations are observed, (020) and (400). In the search for more suitable substrates, MgAl 2 O 4 (001) (MAO) was used. It is also cubic but with a lattice parameter of 0.8083 nm. Fig. 1b) shows the corresponding XRD θ-2θ pattern. The two film peaks observed can be attributed to KBFO (400) and (800) and no other parasitic peaks are observed within the limits of the technique available. The possible epitaxial relationship is KBFO

[010](100) // MAO [110](001), confirmed by TEM observation (see Supporting Information (SI) Fig. S1). In this situation the KBFO b and c lattice parameters are compressed in plane by 3.4% and 0.5% respectively compared to the bulk, which generates an extension of the a lattice parameter. Hence according to XRD the KBFO a lattice parameter is 0.8321 nm which is about 4.2% larger than the bulk.

It should be noted that the KBFO (200) and (600) reflections are absent, which could originate from strain or defects, and indicates that the film deviates from the P2 1 cn space group of the bulk [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF].

SEM analysis performed on KBFO on STO (001) revealed a growth with elongated rectangular shapes while smoother films could be obtained on MAO (001) (see SI Fig. S2). Analysis of the stoichiometry by EDS showed that the sample is composed of K 1 Bi 1 Fe 3.3 O y (SI Fig. S3). However, the measurement of stoichiometry in this case is not very accurate. This is due to the overlap with Sr and Ti signal from the substrate and also due to the small thickness of the sample (60 nm). Inaccuracy of the EDS analysis has been previously observed in similar materials based on Bi [START_REF] Quattropani | Band-gap tuning in ferroelectric Bi 2 FeCrO 6 double perovskite thin films[END_REF][START_REF] Choi | Room temperature Ferrimagnetism and Ferroelectricity in Strained, Thin Films of BiFe 0.5 Mn 0.5 O 3[END_REF]. In order to better account for the stoichiometry we performed RBS analysis on a KBFO//STO (001) film as shown in Fig. 2. The analysis for the spectrum using the SIMNRA tool indicated a stoichiometry of K x Bi 1 Fe 2.2 O y while the stoichiometry of K and O could not be determined in this analysis. The uncertainty of the values obtained for stoichiometry by RBS is 5 % for each element. Therefore we are confident that the stoichiometry obtained in Fe is not far from the desired K 1 Bi 1 Fe 2 O 5 material.

In order to better understand the growth of KBFO, TEM was performed. Figure 3 shows TEM observations of a KBFO thin film on MAO (001) along the MAO [100] zone axis. High epitaxial quality thin film is observed by TEM (Figure 3c, SI Figure S4,S5). The electron diffraction pattern (DP) (Figure 3b) and high-resolution TEM (HR-TEM) image show the great lattice matching between film and substrate and confirm the epitaxial relationship proposed above. However, further work will be to accurately determine atomic positions for comparison with the proposed bulk structure in [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF].The EDS mapping shows Bi segregation in the film (Figure 3d, SI Figure S6), while K and Fe are evenly distributed in the film.

We now focus on the optical properties of the films. Figure 4 shows the optical absorption properties of the MAO (001) substrate and a 60 nm thick KBFO film on MAO (001). The absorbance was not corrected for reflection. It shows that despite the low thickness the film is absorbing well in the 200-600 nm region. The Tauc plot is shown in the inset of Figure 4, showing a direct bandgap of around 2.3±0.1 eV. This value is larger than the value obtained for bulk KBFO (1.6 eV) [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF] but slightly lower than KBFO thin films fabricated by chemical solution deposition (2.5 eV) [START_REF] Zhai | Optical and magnetic properties of KBiFe 2 O 5 thin films fabricated by chemical solution deposition[END_REF]. The absorption coefficient was found to be 3.3•10 4 cm -1 at 600 nm which is comparable to the absorption coefficient of amorphous Si.

After having confirmed the structure and optical properties of the KBFO films, electrical properties were looked into. It was found that the in-plane resistivity or carrier properties could not be determined in the films grown on STO (001) or MAO (001) because they were found to be insulating. PFM measurements did not exhibit any sign of ferroelectricity or piezoelectricity with KBFO films grown on Nb-STO in order to have a conductive substrate. Such KBFO films on Nb-STO were found to be of better surface quality than with the STO substrate, with a root-mean-square roughness of 6 nm over 1 µm². The same KBFO on Nb-STO configuration was further covered with indium tin oxide (ITO) 1 mm² pads deposited by magnetron sputtering through a mask. A tungsten tip was applied on top of the pad and the backside was contacted with silver paste. Figure 5 shows the current-voltage characteristics obtained in dark and under 1 sun. The inset of Figure 5 shows that a rectifying behaviour is observed. When focussing on PV properties the short-circuit current density, open circuit voltage and fill factor were 2.8 µA/cm², 155 mV and 42% respectively. This short-circuit current density is about 5-7 times lower than references [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF] and [START_REF] Jalaja | Switchable photovoltaic properties of multiferroic KBiFe 2 O 5[END_REF]. It should be noted that the active area defined to convert the short-circuit current into a short-circuit current density has been taken as 1 mm², which is reasonable as the BFKO film is highly resistive and therefore the areas outside the ITO pad cannot contribute to the current. The power conversion efficiency is 1.8•10 -4 %.

While previous solar cells based on KBFO were obtained in bulk KBFO, here we demonstrate that similar performance in terms of short-circuit current density is obtained in KBFO thin films, which are more practical for possible applications. KBFO single crystal in Ref. [START_REF] Zhang | New high T c multiferroics KBiFe 2 O 5 with narrow band gap and promising photovoltaic effect[END_REF] allowed a high V oc of 9.1 V while here it is only 155 mV. We believe that this is directly due to the structure of the KBFO film on Nb-STO that provides multiple orientations of KBFO. The PV properties are low but encouraging because KBFO grown on Nb-STO did not provide epitaxy or high quality deposition. The short-circuit current remained the same after applying pulses of ±8 V between Nb-STO and ITO. This was expected because no ferroelectricity of KFBO films could be demonstrated. We attempted growing KBFO/SrRuO 3 //MAO (001) stacks. The aim was to obtain epitaxy of KBFO as in the case of KBFO//MAO (001), but this time with a SrRuO 3 conductive electrode instead of the electrode of Nb-STO (001). However no peaks of SrRuO 3 or KBFO could be observed by XRD. Alternative contact materials on top and bottom of KBFO must therefore be investigated.

Conclusions

We attempted to grow KBFO by PLD and obtained epitaxial films, showing high quality deposition as evidenced by XRD and TEM. To our knowledge this is the first time that epitaxy of KBFO is obtained.

Previous work on KBFO films obtained by sol-gel and spin coating were polycrystalline [START_REF] Zhai | Optical and magnetic properties of KBiFe 2 O 5 thin films fabricated by chemical solution deposition[END_REF][START_REF] Jalaja | Ferroelectric, ferromagnetic and optical properties of KBiFe 2 O 5 thin film: a structure property relationship[END_REF]. If the bandgap found of 2.2 eV is relatively high compared to the optimum for the solar spectrum for a single bandgap solar cell, the photoactive properties of KBFO have been clearly demonstrated which is a further step in polar functional materials. In order to further investigate the photovoltaic properties of the material, a suitable epitaxial conductive buffer layer on MAO (001) should be found in order to provide an electrode for KBFO. Our results are encouraging for future implementation of such oxide absorber in photovoltaic technology.

Figure 1 :Figure 2 :

 12 Figure 1: XRD θ-2θ pattern of a 60 nm thick KBFO thin film grown on STO (001) (a) and MAO (001) (b) substrates.

Figure 3 :Figure 4 :

 34 Figure 3: TEM of KBFO film on MAO (001) in the MAO [010] zone axis: a) low-magnification TEM image, b) selected area diffraction patterns (SAED) of thin film and substrate, and c) highmagnification TEM image, d) EDS mapping showing Bi, Fe and Mg.

Figure 5 :

 5 Figure 5: Current density vs. voltage of a KBFO solar cell measured in dark and under 1 sun.

Acknowledgments

This research was carried out under the framework of the FERROPV project supported by the French Agence Nationale de la Recherche (ANR) under the reference ANR-16-CE05-0002-01. We thank S. Colis for ITO deposition, M. V. Rastei for PFM measurements. Han W. and H. W. acknowledge the support from the US Office of Naval Research (ONR, N00014-16-01-2465). The TEM work at Purdue University was supported by the U.S. National Science Foundation (NSF, DMR-1565822).

Supporting Information

Sketch showing epitaxial relationship, SEM images, SEM EDX analysis, low magnification TEM images, high magnification TEM images, TEM EDS mappings.


João Teodor Stoichev
email: tstoichevbg@yahoo.com

Pedro Coelho

Alberto De Diego

Maria Gabriela

Lobos Valenzuela

Maria Eduarda Pereira

Aubin Thibault De Chanvalon

David Amouroux

João Pedro Coelho

P P L'

Pp

Multiple regression analysis to assess the contamination with metals and metalloids in surface sediments

Keywords: Metals, Coastal lagoon, Sediments, Multiple regression model, Contamination, Enrichment factor 1

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Estuarine catchments have been strategic settings throughout human history, either as places of navigation, agricultural abundance or as locations of the biggest cities in the World [START_REF] Kennish | Practical Handbook of Estuarine and Marine Pollution[END_REF][START_REF] Mclusky | The Estuarine Ecosystem (ecology, threats and management)[END_REF]. Usually used as repositories of industrial and domestic effluents, estuaries are the end-point of numerous contaminants, the vast majority of which tend to settle and are thus stored in estuarine and marine sediments [START_REF] Laurier | Mercury transformations and exchanges in a high turbidity estuary: The role of organic matter and amorphous oxyhydroxides[END_REF][START_REF] Prego | Twentieth century overview of heavy metals in the Galician Rias (NW Iberian Peninsula)[END_REF][START_REF] Kim | The effect of resuspension on the fate of total mercury and methyl mercury in a shallow estuarine ecosystem: a mesocosm study[END_REF]). Due to their toxicity to organisms and persistence in the environment, growing international consciousness has developed with regards to assessing the contamination status and protecting these ecosystems.

Traditionally, the dynamic of metals/metalloids in sediments is evaluated through the utilization of enrichment factors (EFs) [START_REF] Abrahim | Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand[END_REF], but recently, novel methodologies have been developed to evaluate the composition and dynamics of sediment characteristics. For example, artificial neural networks combined with residual kriging has been used to predict the spatial distribution of Cr in soil [START_REF] Tarasov | High variation topsoil pollution forecasting in the Russian Subarctic: Using artificial neural networks combined with residual kriging[END_REF].

Multiple regression analysis allows for the verification of simple and higher order effects of several explanatory variables and their interactions. Upon simplification of the starting models, only a few significant explanatory variables will remain. It has been applied recently to evaluate biogeochemical processes in estuarine water [START_REF] Stoichev | Multiple regression analysis to assess the role of plankton on the distribution and speciation of mercury in water of a contaminated lagoon[END_REF][START_REF] Stoichev | Modeling phaeopigment concentrations in water from a shallow mesotrophic lagoon[END_REF]. Multiple regression was used to quantify major components of lake sediments by near infrared spectra [START_REF] Russell | NIRS quantification of lake sediment composition by multiple regression using end-member spectra[END_REF] or to find out the relative importance of hydrous iron and manganese oxides on the retention of trace metals in estuarine sediments [START_REF] Turner | Trace metals contamination in sediments from UK estuaries: an empirical evaluation on the role of hydrous iron and manganese oxides[END_REF].

Multiple regression analysis has been successfully applied to study the behavior of Hg species in surface sediments from the Aveiro Lagoon [START_REF] Stoichev | Multiple regression analysis to assess the spatial distribution and speciation of mercury in surface sediments of a contaminated lagoon[END_REF]. A relatively small area of the lagoon, the Laranjo Bay, suffered from chlor-alkali mercury pollution coming from a single upstream source [START_REF] Pereira | Mercury pollution in Ria de Aveiro (Portugal): a review of the system assessment[END_REF][START_REF] Stoichev | Multiple regression analysis to assess the spatial distribution and speciation of mercury in surface sediments of a contaminated lagoon[END_REF]. However, sediment contamination in the system is not restricted to mercury, with reports of significant concentrations of other metals and metalloids, such as As, Pb, Zn [START_REF] Costa | Site investigation on heavy metal contaminated ground in Estarreja -Portugal[END_REF].

The aim of this work was to evaluate the effectiveness of multiple regression analysis to study spatial variations in heavy metal/metalloid concentrations in surface sediments from contaminated shallow tidal environments. One type of explanatory variables depended on geographical distances. Another type of variables was related to sediment geochemistry, which, in coastal environments, should include indicators of both terrestrial (e.g. Al or Fe) and oceanic (e.g. Ca) influence [START_REF] Perez | Variability in terrigenous sediment supply offshore of the Río de la Plata (Uruguay) recording the continental climatic history over the past 1200 years[END_REF]Gredilla et al. 2015a;[START_REF] Crawley | Suspended Particulate Matter Sources and Residence Time in a Mesotidal Lagoon[END_REF]). An attempt was made to separate and quantitatively evaluate the effects of contaminant dispersion from a point source from those of geochemical processes as a potential influence for spatial distribution of contamination. This is possible if additive statistical effects of some explanatory variables (responsible for metal/metalloid dispersion and for the geochemistry of the sediments) on the dependent variables (e.g. concentration of contaminant) are found. For this purpose, equations were developed modelling metal/metalloid concentrations depending on different distance variables or geochemical explanatory variables.

Experimental

Study area

Aveiro Lagoon is a coastal lagoon in the North of Portugal (Fig. 1) comprised of a network of channels, opening into the Atlantic Ocean by way of a single narrow channel. The lagoon covers an area of 83 km 2 at high tide (HT) and 66 km 2 at low tide (LT) and has an average depth of 1 m. The tidal range is minimum 0.6 m during neap tide; maximum 3.2 m during spring tide. The water residence time in the lagoon is approximately 2 days, however, it is more than two weeks in the contaminated area (Laranjo Bay, Fig. 1c)) [START_REF] Dias | A numerical system to study the transport properties in the Ria de Aveiro lagoon[END_REF]. The particle residence time is approximately 2-3 days in the lower areas of the lagoon and up to 14 days in the upper ends [START_REF] Crawley | Suspended Particulate Matter Sources and Residence Time in a Mesotidal Lagoon[END_REF]. The Laranjo Bay is contaminated, not only with mercury [START_REF] Pereira | Mercury pollution in Ria de Aveiro (Portugal): a review of the system assessment[END_REF]) but also with other metals/metalloids, like As, Pb, Zn coming from pyrite solid waste [START_REF] Costa | Site investigation on heavy metal contaminated ground in Estarreja -Portugal[END_REF].

The Vouga River is the largest freshwater source to the Aveiro Lagoon. It covers a catchment area of around 3362 km 2 and the main land uses, occupying 4/5 of the total area, being agriculture and forests [START_REF] Stoichev | Simple statistical models for relating river discharge with precipitation and air temperaturescase study of River Vouga (Portugal)[END_REF]. Acidic soil types have developed in the drainage area: mainly Umbrisol in the north and west and Umbrisol/Podzol in the south-west [START_REF] Esbn | European Soil Bureau Network, Soil Atlas of Europe, European Commission, Office for Official Publications of the European Communities[END_REF]. The small and relatively homogeneous drainage area means the Aveiro Lagoon is probably not influenced by multiple terrestrial sources.

The annual air temperatures in the drainage area are relatively low and precipitation is high compared to other parts of Iberian Peninsula (AEMET-IM 2011). This microclimate leads to quite important average river discharge of Vouga (50 m 3 s -1 ) in spite of the small catchment area [START_REF] Stoichev | Simple statistical models for relating river discharge with precipitation and air temperaturescase study of River Vouga (Portugal)[END_REF]. The Antuã River, suppling freshwater to Laranjo Bay, is the second largest freshwater source to the lagoon (average flow of only 5 m 3 s -1 ). It is of primary importance for the export of contaminants from Laranjo Bay to the rest of the lagoon [START_REF] Stoichev | Flux model to estimate the transport of mercury species in a contaminated lagoon (Ria de Aveiro, Portugal)[END_REF].

Sampling

The sediment samples named from 1 to 14 were collected in the summer of 2010, the remaining samples being collected during two further campaigns (February 2012 andAugust 2012) in order to estimate eventual seasonal change. Sites were located close to the lagoon entrance, in the main channels, near the main freshwater input and in the central area of the lagoon. Special emphasis was given to the Laranjo Bay, being near the contamination source. Samples were taken from intertidal flats, at low tide and during daylight from the top 5 cm layer with acid washed plastic utensils, stored in plastic bags and kept cool until arrival at the laboratory.

Each sampling point is characterized by geographical coordinates and falls within a simplified (in order to facilitate distance calculations) polygon border, marked with hyphen line (Fig. 1). For the spatial distribution of the contaminants, each point is characterized by the distances through water d S to suspected contamination source (S) and d M to mouth of the lagoon (M), obtained within the simplified polygon border (Fig. 1b). Alternatively; each sampling point may be described by the distance ratio . Each point was additionally characterized using distance d R to the reference point R (instead of d M ) obtained within the simplified polygon border or by reference distance ratio . More information can be found elsewhere [START_REF] Stoichev | Multiple regression analysis to assess the spatial distribution and speciation of mercury in surface sediments of a contaminated lagoon[END_REF].

Chemical analysis

At the laboratory, samples were freeze-dried (Unicryo MC-4L-60ºC) then disaggregated and macrodetritus removed by dry sieving through a 2 mm mesh. Fine fraction (FF) content (<63 µm) was quantified by wet sieving of sample aliquots under running water. Sediment organic matter (OM) was analyzed through loss on ignition (6 h at 500 ºC).

Each sample was then grinded with agate mortar and sieved (300 µm) before storage in darkness until analysis. Total carbon (TC), was quantified in a CHNS analyzer (Leco Truspec Micro). Organic Carbon (OC) was quantified with the same method, after carbonate removal according to the ISO 10694 standard. Sediment digestions for metal determination were performed according to US EPA 3051 protocol using microwave digestion with a mixture (3/1, v/v) of hydrochloric (37%, Sigma-Aldrich, p.a.) and nitric acids (69%, Sigma-Aldrich, p.a.). The metals (Ca, Al, Mn, Fe, Co, Li, Cu, Cd, Zn, Ni, Pb, Ba, V and Cr) were measured using inductively coupled plasma optical emission spectrometry (ICP-OES;

Perkin-Elmer, model ICP Optima 2000 DV). The accuracy was checked using BCSS-1 marine sediment with measured values being between 98% and 102% of the certified ones.

The concentration of As in sediments (US EPA 3051A) was determined after microwave digestion with a mixture (3/1, v/v) of nitric acid (69%, Sigma-Aldrich, p.a.) and hydrofluoric acid (40%, Sigma-Aldrich, p.a.). Determinations of As were carried out using a quadrupole inductively coupled plasma mass spectroscopy (ICP-MS, Thermo Elemental, X-Series) equipped with a Peltier cooled impact bead spray chamber and a concentric Meinhard nebulizer. Parallel digestion and analyses of certified reference material MESS-3

were consistent with the certified value, with extraction efficiencies ranging from 93% to 109%.

Statistical treatment

Model building

Cadmium was detected only in Laranjo Bay (5.78 4.09 2.49 μ l k -1 at samples 1, 2 and 5, respectively) and was not included in the statistical treatment. Statistical data treatment was carried out using R software (R Core Team 2014). The dependent variables Y (concentrations of Co, Li, As, Cu, Zn, Ni, Pb, Ba, V, Cr), were represented as functions of q explanatory variables X i. One type of explanatory variable is related to geographical coordinates (either both distances d S , d M or their ratio DR M ). Additionally, other distances (d S , d R ) or their ratio DR R were used. A second set of explanatory variables represent the geochemical characteristics of the samples (FF, concentrations of OM, OC, TC, Al, Mn, Ca).

The set of geochemical variables was selected after a preliminary inspection of the data. The concentrations of Al in sediments are an indicator of terrestrial processes [START_REF] Perez | Variability in terrigenous sediment supply offshore of the Río de la Plata (Uruguay) recording the continental climatic history over the past 1200 years[END_REF]Gredilla et al. 2015a). The levels of Ca could be used as proxy for ocean contribution in sediments from the Aveiro Lagoon [START_REF] Crawley | Suspended Particulate Matter Sources and Residence Time in a Mesotidal Lagoon[END_REF]). The concentrations of Ca in sediments are anticorrelated with d M (r=-0.40, p<0.05). The concentration of Mn are correlated mainly with those of Fe (r=0.58, p<0.001), less correlated with Al (r=0.48, p<0.01), TC (r=0.45, p<0.02) and OC (r=0.40, p<0.05) and not correlated with the carbonates (difference TC-OC).

Sulfide phases commonly occurred in sediments from Aveiro Lagoon a few millimeters bellow the sediment surface and were associated with metals, like Fe, Mn, Ni and Zn [START_REF] Martins | Early diagenesis and clay mineral adsorption as driving factors of metal pollution in sediments: the case of Aveiro Lagoon (Portugal)[END_REF]. Therefore, Mn would be an indicator of Mn(IV) oxo-hydroxides (related to Fe(III) oxo-hydroxides) or sulfides in sediments from the Aveiro Lagoon. Manganese was preferred to Fe as an explanatory variable to avoid co-linearity with Al (Fe was highly correlated with Al, r=0.82). Organic matter, sulfides and oxo-hydroxides of Mn are recognized as scavengers of toxic metals in Aveiro Lagoon [START_REF] Martins | Early diagenesis and clay mineral adsorption as driving factors of metal pollution in sediments: the case of Aveiro Lagoon (Portugal)[END_REF].

Both Y and X i were normalized, when necessary, using density function graphical visualization and Box-Cox transformations [START_REF] Bellanger | Data Exploration and Statistical Methods: Data Analysis and Data Mining Using R[END_REF] to give variables Y T and X T,i . Some of the explanatory variables (Al, Mn, TC, d S , d M , d R ) and some of the dependent variables (Co, Li, Ba, V, Cr) were not altered (identical transformation (

)), only the following transformations finally being selected:

(1)

The relationship between the explanatory variables is expressed by L 1 , L 2 or L 3 , the index representing the highest interaction order, described in the starting model:

for Al -TC (r=0.92) and Al -OC T (r=0.89). Therefore, the variables Al, OC and TC were never considered together in order to avoid problems with co-linearity [START_REF] Stoichev | Multiple regression analysis to assess the spatial distribution and speciation of mercury in surface sediments of a contaminated lagoon[END_REF].

Model simplification and selection

The coefficients a 0 (intercept), a i , a ij , a ijk were determined using multiple regression analysis [START_REF] Crawley | Suspended Particulate Matter Sources and Residence Time in a Mesotidal Lagoon[END_REF]. The models were simplified by leaving only the coefficients significantly different from 0 (p<0.05 for the interaction terms and p<0.1 for the simple effects). The number of the considered coefficients in the starting equations never exceeded 11 in order to avoid overparametrization.

Firstly, the minimal adequate model was developed using all available data (n=32).

Secondly, the applicability of the obtained model was checked after removing values of Y higher than 95th percentile (P 0.95 ) of all data and the regression coefficients for the minimal adequate model were determined again with the remaining dataset (short data, n=30). The obtained regression equation, using the short data, were extrapolated for data removed (extrapolated data, n=2). The minimal adequate model was considered further only if robust, meaning the same significant terms were obtained for all data and for short data. The extrapolated data includes only sites, sampled in summer 2010, and are mainly situated in Laranjo Bay: samples 1, 5 (for As, Cu); samples 1, 3 (for Cr, Ni, V); samples 1, 2 (Zn); 1, 11 (Pb); 1, 10 (Co); 3, 13 (Ba) and 3, 7 (Li).

All models were compared using graphical representation of model values Y M against experimental ones Y E and by root mean square deviation (RMSD) criteria (for all data, short data and extrapolated data) representing how far the model values differ when compared with n experimental data of Y:

(14)

Among the best models (for the dependence slope close to 1, intercept close to 0) the simplest ones were selected, especially those lacking interaction terms between distance and geochemical explanatory variables:

(15)

Effect of geochemistry

For models with additive effects of distance and geochemical variables, the effect of geochemistry on the spatial distribution of a contaminant away from a point source could be estimated using enrichment indexes (EI). Those indexes are defined, for each sample and for each dependent variable Y, as ratios between experimental values Y E (which presumably depend both on geographical distances and on geochemistry) and geochemical component Y Geo (Eq. 15), the last being obtained upon inverse transformation (Eq. 1) of Y Geo,T .

(

The results obtained from the EI are compared with enrichment factors (EF) in which concentrations of a chemical element Me are normalized with Al concentrations, both for the sample and for the local background levels (LBL):

(17)

LBLs were calculated using 3s and 4s methods, where s is the standard deviation from concentrations (Gredilla et al. 2015b). The LBLs are calculated as 90 th percentiles from data contained within average±3s intervals, or as averages from data contained within average±4s intervals, for 3s and 4s methods, respectively. Further, average EF from 3s and 4s methods will be used. Calculations were carried out using LBL as reference because usually the global values, such as metal/metalloid concentration in the upper continental crust (UCC), do not reflect local conditions [START_REF] Birch | Determination of sediment metal background concentrations and enrichment in marine environments: A critical review[END_REF].

Results and discussion

Potential existence of seasonal trends

Analysis of covariance ANCOVA (season, geochemical variables) for surface sediments from the Aveiro Lagoon (nine samples taken in February and August 2012) demonstrated that seasonal trends for Y E (metal/metalloid concentrations) were not observed (results not shown). When, for some sampling sites, winter / summer differences existed, they followed concentration changes observed for geochemical variables X i . For example, the concentrations of As could be expressed by a combination of TC and the product TC x Ca.

The concentrations of Zn depended on Al, Mn and Al x Mn and those of Cuon Al, Ca and Al x Ca. The concentrations of Li and Pb were determined only by Al. The rest of Y E (V, Co, Ba, Ni, Cr) depended on Al and Ca. Therefore, for subsequent treatment of the spatial variation, no seasonal differences were considered.

Modelling spatial distribution of metals and metalloids

Average values (bold), standard deviations and ranges (italic) for FF and concentrations of OC, TC, OM and metals/metalloids in surface sediments from Laranjo Bay and from the rest of the Aveiro Lagoon, as well as LBLs, are shown in Table 1. The average values of the dependent variables Y (concentrations of Co, Li, As, Cu, Zn, Ni, Pb, Ba, V and Cr) are always higher in Laranjo Bay compared to the rest of the lagoon. This difference was between 1.57 and 2.14 times for Co, Li, Ni, V, Ba, Cr and between 3.46 and 5.06 times for As, Cu, Zn, Pb. The concentrations of metals tend to decrease with d S (Fig. 2), the coefficients of correlation always being negative, between r=-0.45 (p<0.02) for Pb and Ba and r=-0.61 (p<0.001) for Zn and Li. It is suspected that some of the elements might come from a point anthropogenic source (both geochemical and geographical distance variables being important) while for others only geochemical explanatory variables will finally be included in the minimal adequate models.

Only minimal adequate models that show the same significant terms for all data and short data are considered. However, among the obtained robust models, some were generally worse than others and were not considered further geochemistry could be studied with the proposed robust equations using all sampling campaigns and are independent of site replication. The extrapolation was clearly seen for As, Cu, Pb, Ni, Zn and Cr, where the models for short data could be applied for concentrations at least 1.5-2.2 times higher than the maximum values. Similar approach, applied to other contaminants in sediments from the Aveiro Lagoon has led to even higher extrapolation of concentration: at least 8.0 and 3.0 times for inorganic mercury and methylmercury, respectively [START_REF] Stoichev | Multiple regression analysis to assess the spatial distribution and speciation of mercury in surface sediments of a contaminated lagoon[END_REF]).

The best models, described with the following equations, were selected based on their simplicity, especially the lack of interactions between geochemical and distance variables. For the sake of brevity, when, in some of the equations, appears, this stands for:

(18) For example, the slopes of for all data were between 0.92 and 1.03 for all studied elements, except Pb, and the origins were indistinguishable from 0 (online resources). Lower slope (0.80, all data) was obtained for Pb (Eq. 25, Fig. ESM 3b). A possible reason is the existence of other contamination sources in the lagoon downstream of Laranjo Bay.

Relatively high concentrations of Pb were found in sample 11 (0.106 mmol kg -1 ) as well as in GAF in summer and winter (0.026 and 0.050 mmol kg -1 , respectively). In that zone, higher concentrations of Pb have been measured in sediments, compared to the central area of the lagoon [START_REF] Velez | Bioaccumulation Patterns, Element Partitioning and Biochemical Performance of Venerupis corrugata from a Low Contaminated System[END_REF]). These samples are situated close to seafood processing industry / port activities that can eventually be a source of metal contamination. Alternatively, they may suffer influence from the Aveiro city channels, recognized as a source of Pb for the sediments [START_REF] Martins | Assessment of the health quality of Ria de Aveiro (Portugal): heavy metals and benthic foraminifera[END_REF][START_REF] Martins | Early diagenesis and clay mineral adsorption as driving factors of metal pollution in sediments: the case of Aveiro Lagoon (Portugal)[END_REF]. An attempt to improve the model, accounting for another Pb source, was undertaken by introducing into the starting models (Eqs. 6-12) an additional cubic term, (DR R ) 3 , without interaction of this term with the other explanatory variables (Table ESM 7 dispersed compared with the EI. For Ni, V, Ba and Cr, the EIs are close to 1 and do not depend on d S (Fig. 5a). Thus, despite their higher concentrations in sediments from Laranjo Bay, compared to the rest of the Aveiro Lagoon (Table 1), the influence of a potential point source upstream could not be proven for these metals. Only for As, Cu and Zn could the influence of an upstream contamination source be suspected from EIs (Fig. 5b). The EIs for Pb were not calculated but the existence of a strong contamination source upstream of Laranjo Bay was demonstrated from the contour plots (Fig. 4 a,b) as well as from the calculation of the EFs (Fig. 5d). Therefore, for As, Cu, Zn and Pb, the results from the Laranjo Bay (samples 1-5, LAR, Fig. 1c) were excluded from further consideration of the EFs, thus eliminating the influence of spatial distribution of contaminants away from the point source, from the geochemical results.

Effect of geochemical variables

The multiple regression analysis demonstrated that, for some of the elements (e.g. V and Ni)

Al was the geochemical variable present in almost all final equations. Terrestrial processes with simultaneous erosion of Al and Fe are involved in the transport of these metals, as indicated by the high correlation between Al and Fe concentrations (r=0.82). Participation of oxo-hydroxides of Fe, obtained after chemical erosion, in the retention of those metals is another possibility. Additional processes are possible, as demonstrated by the additive effects of Mn concentration on the behavior of Co (Eq. 19) and Cr (Eq. 29) in the sediments.

The terrestrial and marine influence could be involved in the case of Cu and Ba since additive effects of Al and Ca concentrations were observed in the minimal adequate models (Eqs. 22,28).

While OC has concentrating effects on metals/metalloids, the influence of TC is more ambiguous. In coastal sediments, some metals, such as Mn, sometimes co-precipitate with carbonates [START_REF] Ho | Distribution and contamination status of heavy metals in estuarine sediments near Cua Ong Harbor, Ha Long Bay, Vietnam[END_REF]) but more frequently carbonates exhibit dilution effect [START_REF] Basaham | Sharm Obshur: Environmental consequences of 20 years of uncontrolled coastal urbanization[END_REF][START_REF] Yücesoy | Heavy metal geochemistry of surface sediments from the southern Black Sea shelf and upper slope[END_REF]. Positive additive effect of TC (a 5 >0) was observed in [START_REF] Martinez-Ruiz | Paleoclimate and paleoceanography over the past 20,000 yr in the Mediterranean Sea Basins as indicated by sediment elemental proxies[END_REF]) and sedimentary rocks [START_REF] Rimmer | Geochemical paleoredox indicators in Devonian-Mississippian black shales, Central Appalachian Basin (USA)[END_REF]). Among other redox sensitive elements, V is particularly responsive to changes in sediment redox properties [START_REF] Martinez-Ruiz | Paleoclimate and paleoceanography over the past 20,000 yr in the Mediterranean Sea Basins as indicated by sediment elemental proxies[END_REF]. The molar ratio V/Cr was dependent neither on OC nor on V/Co, while Ni/Co ratio increased with V/Co (r=0.52, p<0.01, Fig. ESM 4 c,d). For the surface sediments of the Aveiro Lagoon, the relationships between Me/Mn molar ratios (Me is the studied metal/metalloid) and V/Co had higher R 2 compared with similar dependencies of Me/Mn with Ni/Co ratios (results not shown). Therefore, for the studied samples, V/Co has similar significance to Ni/Co, but is preferred to Ni/Co due to better relationships with the Me/Mn ratios.

In sediments, metals/metalloids could be bound to Mn oxohydroxides, as demonstrated for As [START_REF] Mil-Homens | Characterization of Heavy-Metal Contamination in Surface Sediments of the Minho River Estuary by way of Factor Analysis[END_REF][START_REF] Telfeyan | Arsenic, vanadium, iron, and manganese biogeochemistry in a deltaic wetland, southern Louisiana, USA[END_REF]), V [START_REF] Huang | Vanadium: Global (bio)geochemistry[END_REF][START_REF] Tribovillard | Trace metals as paleoredox and paleoproductivity proxies: An update[END_REF]), Ni, Co, Cu, Zn, Cr [START_REF] Tribovillard | Trace metals as paleoredox and paleoproductivity proxies: An update[END_REF]). In oxic conditions, Ba can precipitate as BaSO 4 and demonstrates similar behavior to that of Mn [START_REF] Tribovillard | Trace metals as paleoredox and paleoproductivity proxies: An update[END_REF]). The sediments whose contamination was related to their proximity to the point source have no correlation between EF of the studied elements and EF of Mn. In contrast, the others samples from Aveiro Lagoon show a strong correlation of EF for some elements with EF of Mn. The dependence is especially strong for As, Ba and Co (Fig. 6 a,c, r=0.94 for Ba and As, 0.90 for Co, 0.62 for Cr, 0.58 for V). Similar dependences, as those in Fig. 6, occur for EF Me Al as a function of EF Ca Al (shown on Fig. ESM 5) but with lower correlation coefficients for the case of Ba, As and Co. Generally, the EFs of As, Ba, Co, Cr and V were inversely related with OC (Fig. 6 b,d). Starting from the continental source (at EF Mn <0.8, n=12), the EF of As increased 16 times, from 0.47±0.10 to 7.5. For Ba and Co, the increase was from 0.98±0.08 and 0.92±0.07, respectively, to approximately 2.9. The effect was less significant for Cr and V: from 0.97±0.08 for both to 1.6 and 1.5, respectively.

Me: As, Ba, Co, Cr, V

The values for the intercept and the slope (Eq. 34a) for As, Ba, Co, Cr and V are given in Table 3. The intercept for As was 0 due to non-linear effects of the slower increase of EF of As at low EF of Mn (Fig. 6 c).

Therefore, the contamination of sediment can occur through two different pathways.

First, the relationship with distance indicates direct deposition of contaminated slurry.

Second, the correlation supports an intense scavenging of As, Ba and Co during estuarine Mn recycling. Hence, the linear relationship between EF (Eq. 34) suggests a mixing of a terrigeneous endmember with an endogenous Mn oxo-hydroxide precipitate endmember, probably produced during the reoxidation of efflux of dissolved Mn, coming from the reducing part of the sediment (Thibault de [START_REF] Thibault De Chanvalon | Particles transformation in estuaries: Fe, Mn and REE signatures through the Loire Estuary[END_REF]. This mechanism represents a credible opportunity for As, Ba and Co to co-precipitate in the newly formed Mn oxyhydroxide. Note that this second pathway of contamination, based on our dataset, results in more contaminated sediment, situated relatively far from the contamination source (EF of As up to 7.5 versus 2.6 for slurry deposition, Fig. 5 b,d). Moreover, the importance of the redox dynamic is underlined by the lower correlation of the EF of the two redox elements analyzed (Cr and V) with the EF of Mn. These redox elements are not contaminants of the point source and their EFs are highly correlated (EFs for Cr and V, r=0.85).

For the concentrations of As in the sediments, the geochemical component Y Geo (Eq. 16) included Mn, TC and FF rather than Al (Eq. 21). The enrichment of sediments with As is determined by EF Mn but not by other conditions (e.g. V/Co ratio). Indeed, the behavior of As is different from that of the other elements since the concentration ratio As/Mn does not depend on V/Co ratio, while for all other studied elements (Cu, Zn, Pb, Ba, Cr, Co, Ni, V)

there was an increasing trend of Me/Mn with V/Co ratio (Fig. 7). Strong correlations were found between V/Co ratio and V/Mn (r=0.82), Ba/Mn (r=0.81), Cr/Mn (r=0.75), Cu/Mn (r=0.73), Co/Mn (r=0.70), Ni/Mn (r=0.64), Pb/Mn (r=0.58) and Zn/Mn (r=0.51, p<0.02). Similar to As, in the oxic water, V is present as vanadate anion [START_REF] Huang | Vanadium: Global (bio)geochemistry[END_REF] but, in surface sediments from the Aveiro Lagoon, V demonstrates similar behavior to some metallic cations. While the adsorption of vanadate would increase the binding of metal cations, the binding of other oxoanions, such as arsenate, will be hindered [START_REF] Huang | Vanadium: Global (bio)geochemistry[END_REF].

Conclusions

The metal/metalloids, coming from a single upstream source, were suspected of contaminating surface sediments from a shallow coastal lagoon. Multiple regression analysis demonstrated that, from the studied chemical elements, only As, Cu, Zn and Pb were influenced both by geochemical and geographical distance variables, the latter representing the anthropogenic influence and the extent of transport of contaminants away from the upstream source. It is possible that for Pb, an additional source within the lagoon exists. The concentrations for the rest of the metals (Ni, Li, V, Ba, Cr, Co) were determined by geochemical variables, the geographical distance being less significant or even non-existent in the final equations. By multiple regression analysis, specific geochemistry effects of one or more explanatory variables were found for the studied elements. The usefulness of enrichment indexes to study the spatial distribution of contaminants away from a point source was demonstrated. The proposed approach is supplementary to the traditional utilization of enrichment factors in order to study the dynamic of metals/metalloids in sediments. Enrichment of the sediment with Ba, As, Co, Cr and V was determined mainly by enrichment with Mn, whose sediment recycling favors As scavenging and could represent an overlooked but more intense pathway for As contamination.

Additionally, the binding of Ba, Co, Cr and V was increased at higher V/Co molar ratios in sediments. Enrichment with Cu, Ni, Pb and Zn were higher in sediments with high V/Co molar ratio but were rather independent of enrichment with Mn.

Figure captions

  ). As a result, the slope of the dependence increased from 0.80 to0.85 (all data, Eq. 26, Fig. ESM 3f) and this dependence was used further to study the influence of DR R and geochemical variables on Pb concentration. However, the EIs for Pb were not calculated because the model values tend to be slightly lower than the experimental values. Contour plots of model and experimental values of As, Cu, Zn and Ni concentrations (Eqs 21-24) are shown in Fig. 3 and of Pb, V, Ba and Cr (Eqs. 26-29)in Fig. 4. For each element, the effect of specific geochemical function f geo (on y axis) are separated from distance function (on x axis). The behavior of As, Cu, Zn and Pb depended on both geochemical and distance functions. Although a slight increase in Ni concentration was observed near the contamination source, the isolines tended to be parallel to the x axis and therefore Ni was mainly determined by geochemical variables. The effect of the distances on V, Ba and Cr is negligible (despite the presence of d S and d R in Eqs. 27-29). As confirmation, for Ni, V, Ba and Cr, there were also good models describing the concentrations as functions of only geochemical variables (Figs. ESM 3c,g, ESM 2a,e): standard errors of the regression coefficients for Eqs. 19-33 are presented in online resources, showing similarity of the regression coefficients for all data and short data models. The calculation of EIs (Eqs. 15, 16) is intended to distinguish between geochemical and distance explanatory variables. The dependence of EI (a, b) and EF (c, d) on the d S for metals/metalloids in surface sediments is shown in Fig. 5. The results for the EF are more

Fig. 1 .

 1 Fig. 1. Map of (a) Localization of the Aveiro Lagoon (Atlantic coast, Portugal) (b)

Fig. 2 .

 2 Fig. 2. Dependence of concentrations of metals [Me] in surface sediments from the

Fig. 3 .

 3 Fig. 3. Contour plot (mmol kg -1 ) of (a, c, e, g) model values and (b, d, f, h)

Fig. 4 .

 4 Fig. 4. Contour plot (mmol kg -1 ) of (a, c, e, g) model values and (b, d, f, h)

Fig. 5 .

 5 Fig. 5. Dependence of (a, b) enrichment index (EI) and (c, d) enrichment factor (EF)

Fig. 6 .

 6 Fig. 6. Dependence of the enrichment factor (EF) for metals/metalloids (Me) on (a, c)

Fig. 7 .

 7 Fig. 7. Dependence of the ratio between concentrations of metals/metalloids [Me]

  (a) Samples 1-5 and LAR are excluded (Fig.1c);(b) LBL calculated according toGredilla et al. (2015b);Fe in sample BAR in summer could not be quantified (<LOQ).

Fig. 1

 1 Fig. 1

Figure 1 Fig. 2

 12 Figure 1

Figure 2 Fig. 3

 23 Figure 2

Figure 3 Fig. 4

 34 Figure 3

  Figure 4

  Figure 5

  Figure 6

Figure 7

 7 Figure 7

  . Such examples include all equations where distances d S or d were present, or where there was only one of the geochemical variables FF, OC, TC, OM, Ca, Mn. Generally, a model in which DR M was present produced similar results, or worse, than a model that used DR R as the explanatory variable. The minimal adequate models with RMSD values for Co, Li, As, Cu, Zn, Ni, Pb, V, Ba, Cr using all data, short data and extrapolated data are presented in online resources. Models with the lowest RMSD values (marked in bold in Tables ESM 1 to ESM 10, online resources) are further considered. The model values Y M are graphically compared with the experimental values Y E in Figs. ESM 1, ESM 2, ESM 3, the slope and intercept of and the models adjusted R 2 values also being given in the online resources. Only robust models (the same for all data and short data) that can extrapolate the concentrations of metals/metalloids (Figs. ESM 1, ESM2, ESM3) are further considered. Since extrapolated data concerns only sites sampled once in summer 2010, the effects of distances and

Table 1

 1 Average values (bold), standard deviations and ranges (italic) for fine fraction (<0.63 m, FF, %) and concentrations of organic carbon (OC, %), total carbon (TC, %), organic matter (OM, %, loss on ignition) and metals/metalloids (mmol kg -1 ) in surface sediments from

	Laranjo Bay (n=7) and from the other part of the Aveiro Lagoon (n=25 for FF, OC, TC, OM
	and As; n=24 for the other elements). Local background levels (LBL) were calculated using
	3s and 4s criteria
		Laranjo Bay	Aveiro Lagoon (a)	LBL (3s) (b)	LBL (4s) (b)
	FF 26.1 ± 16.8 (11.7-56.2)	23.5 ± 23.7 (0-90.7)	51.4	24.1
	OC 3.0 ± 1.3 (1.3-4.5)	1.4 ± 1.1 (0.05-3.7)	3.8	1.8
	TC 3.2 ± 1.0 (1.8-4.3)	1.7 ± 1.1 (0.07-3.4)	3.6	2.0
	OM 3.7 ± 2.1 (1.2-6.0)	3.0 ± 2.6 (0.4-11.2)	5.6	3.1
	Ca 46.7 ± 13.1 (33.7-72.9)	71.8 ± 42.9 (23.7-202.7)	100.0	66.1
	Al	1689 ± 433 (1111-2296)	875 ± 553 (52-1815)	1811	1059
	Mn 2.68 ± 0.41 (2.28-3.42)	2.49 ± 0.84 (0.87-4.55)	3.41	2.53
	Fe 382 ± 126 (206-589)	219 ± 144 (<LOQ-555)	449	256
	Co 0.11 ± 0.02 (0.08-0.14)	0.07 ± 0.03 (0.01-0.13)	0.12	0.075
	Li	20.5 ± 3.4 (14.3-24.0)	10.0 ± 6.5 (0.50-24.6)	21.2	12.4
	As 0.86 ± 0.49 (0.42-1.79)	0.17 ± 0.07 (0.10-0.40)	0.65	0.27
	Cu 0.57 ± 0.30 (0.28-1.18)	0.15 ± 0.10 (0.005-0.39)	0.47	0.25
	Zn 2.89 ± 1.28 (1.47-5.34)	0.77 ± 0.52 (0.03-2.66)	2.69	1.25
	Ni	0.30 ± 0.13 (0.16-0.55)	0.14 ± 0.08 (0.003-0.27)	0.27	0.18
	Pb 0.083 ± 0.050 (0.034-0.187) 0.024 ± 0.024 (0.002-0.106)	0.076	0.038
	V	0.73 ± 0.18 (0.49-0.96)	0.44 ± 0.26 (0.04-0.88)	0.82	0.51
	Ba 0.87 ± 0.19 (0.63-1.15)	0.55 ± 0.30 (0.08-1.07)	0.95	0.62
	Cr 0.64 ± 0.20 (0.42-1.00)	0.35 ± 0.19 (0.03-0.68)	0.67	0.41

Table 1

 1

Table 2

 2 Comparison of local background levels (LBL, mmol kg -1 ) of metals/metalloids in marine and estuarine sediments a) this study; range of LBL determined by 3s and 4s methods according toGredilla et al. 2015b (b) calculated fromGredilla et al. 2015a; range of LBL determined by 3s and 4s methods according toGredilla et al. 2015b (c) Corredeira et al. 2008 (d) Carballeira et al. 2000 (e) Coynel et al. 2016 (f) Birch 2017; mean and range of LBL in coastal and marine sediments (g) Rudnick and Gao 2003; UCC: upper continental crust

		Aveiro Lagoon (a) Cávado estuary	Shelf,	Galicia estuaries	Loire estuary	World (f)	UCC (g)
			(Portugal) (b)	SW Iberian (c)	NW Iberian (d)	(France) (e)
	Co 0.075 -0.12	0.078 -0.13		0.20 -0.22		0.27 (0.17 -0.66)	0.29
	Li 12.4 -21.2						3.46
	As 0.27 -0.65	0.067 -0.10			0.26	0.21 (0.16 -0.27)	0.064
	Cu 0.25 -0.47	0.96 -1.47	0.33	0.31 -0.55	0.31	0.43 (0.14 -1.81)	0.44
	Zn 1.25 -2.69	1.56 -2.17	0.99	1.84 -2.08	1.43	1.48 (0.61 -2.68)	1.02
	Ni 0.18 -0.27	0.18 -0.27		0.53 -0.65	0.66	0.51 (0.20 -1.35)	0.80
	Pb 0.038 -0.076	0.15 -0.19	0.13	0.24 -0.38	0.17	0.16 (0.053 -0.35) 0.082
	V	0.51 -0.82	0.18 -0.25			2.39		1.90
	Ba 0.62 -0.95						4.57
	Cr 0.41 -0.67	0.44 -0.64		0.58 -1.04	1.91	0.77 (0.15 -1.67)	1.77

(

Table 2

 2

Table 3

 3 Values for the intercept and the slope and the coefficient of determination R 2for As, Ba, Co, Cr and V (Eq. 34a). Data from Laranjo Bay (Fig.1c) for As were removed

	Me

Table 3

 3

(2)The regression coefficients a i represent the simple terms for variable X i . The coefficients a ij and a ijk , account for the double and triple interactions, respectively. The starting models, used to describe element concentrations, can be written with the equations:X i : Mn, Al, Ca, TC, OC(3)X i : Al, TC, OC(4)X i : Al, TC, OC(5)X i : Mn, Al, Ca, TC, OC(6)X i : Al, TC, OC(7) (8)X i : OC, TC(9)X i : OC, TC (10)X i : Al, TC, OC(11)X i : Al, TC, OC(12)X i : Al, TC, OC, OM(13)Eqs. 3-5 searched Y as a function of d S and d (either d M or d R ) while Eqs 6-12 used DR(either DR M or DR R ). Numerous geochemical characteristics were checked simultaneously without accounting for interaction effects (Eqs. 4, 7). Some of the starting equations accounted for interactions between distances (Eqs. 3-5), between geochemical variables(Eqs. 5, 8, 9, 11, 12 13) or between DR and geochemical variables (Eqs 6, 10). Quadratic effects of distances and of DR were checked in all starting models, except in Eq. 13, where distance variables were not present. Moderate correlations were found (all data) between Al and FF T (r=0.44) or between Mn and FF T (r=0.40) but very high correlations were observed

Acknowledgement

This research was supported by national funds through FCT (Foundation for Science and Technology (Portugal) within the scope of UIDB/04423/2020 and UIDP/04423/2020. The

Aveiro Lagoon sediments for Co, Li, Cu, Ni, Pb, V, Ba, Cr (Tables ESM 1, ESM 2, ESM4, ESM 6 -ESM 10, respectively) and therefore, TC in Aveiro Lagoon has the same carrier effect as OC. The difference TC-OC representing carbonates (negative values for samples 4,5,6,8,9 and BAR (winter) replaced by 0) was not correlated with concentrations of any of the metals/metalloids considered. In Aveiro Lagoon, carbonates (average 0.30 %C, maximum 0.86 %C) had negligible contribution to TC (Table 1) and no effects of carbonates on metal/metalloid concentrations in sediments could be observed.

Values of LBL for metals/metalloids in sediments from the Aveiro Lagoon are compared (Table 2) with LBLs in sediments from Atlantic coast of Europe but mostly from Iberian Peninsula (Gredilla et al. 2015a;[START_REF] Corredeira | Copper, zinc and lead impact in SW Iberian shelf sediments: An assessment of recent historical changes in Guadiana river basin[END_REF][START_REF] Carballeira | Regional-scale monitoring of coastal contamination. Nutrients and heavy metals in estuarine sediments and organisms on the coast of Galicia (northwest Spain)[END_REF][START_REF] Coynel | Spatial distribution of trace elements in the surface sediments of a major European estuary (Loire Estuary, France): Source identification and evaluation of anthropogenic contribution[END_REF]. For sediments from Cávado estuary (situated only 100 km north from Aveiro), the LBLs were estimated, by the same 3s and 4s methods as in the present study, using available data (Gredilla et al. 2015a). For Cr, Co, Zn and Ni, the LBLs for Aveiro Lagoon and for Cávado sediments are very similar. The sediments from Aveiro Lagoon compared with those from Cávado were naturally more enriched with As and V (about 5.3 and 3.1 times, respectively). On the contrary, Cávado sediments have LBL values of Cu and Pb about 3.5 and 3.2 times higher, compared to Aveiro Lagoon. The mean values and ranges of LBL for Co, As, Cu, Zn, Ni, Pb and Cr in marine sediments worldwide were also summarized in Table 2 [START_REF] Birch | Determination of sediment metal background concentrations and enrichment in marine environments: A critical review[END_REF]. The LBLs in Aveiro Lagoon are similar to the values reported in the world marine sediments but for Co, Ni, Pb are situated in the lower part of the world range.

The EFs for Mn and Ca showed similar behavior, decreasing with both OC and with V/Co molar ratio, especially rapid decrease being observed at low OC contents (Fig. ESM 4 a, b, online resources). The average values (ranges) for molar ratios of redox sensitive elements Ni/Co and V/Cr were 2.22 (0.32-3.96) and 1.22 (0.92-1.53), respectively, and possibly the surface sediments from the Aveiro Lagoon are oxic. Dissolved O 2 usually remains high in the lagoon waters even during summer [START_REF] Lopes | Temporal and spatial distribution of dissolved oxygen in the Ría de Aveiro lagoon[END_REF]