Albert Olioso
email: albert.olioso@inra.fr

Marie Weiss

IRST EVALUATION OF LAND SURFACE EMISSIVITY SPECTRA SIMULATED WITH THE SAIL-THERMIQUE MODEL

Keywords: Emissivity, thermal infrared, radiative transfer model, vegetation canopy, SAIL-Thermique

The SAIL-Thermique model was developed to simulate land surface emissivity. It is adapted from the original SAIL model. A specific experiment was set-up over a soybean canopy for evaluating spectral emissivity simulations. Multispectral data were obtained thanks to a CIMEL CE 312-2 radiometer and emissivities calculated using the TES method. Comparison of multispectral emissivity simulations and measurements at various leaf area index levels were comparable in terms of emissivity values and spectral behavior.

INTRODUCTION

Spectral Land Surface Emissivity (LSE) is required for deriving surface temperature from thermal infrared (TIR) radiances as acquired by space sensors such as MODIS, ASTER or the sensors on board of the LANDSAT platforms. Surface temperature is an essential input to surface energy balance analysis, for example to map evapotranspiration [START_REF] Olioso | Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into SVAT models[END_REF][2][3] [START_REF] Lagouarde | Energy Balance of Continental Surfaces and the Use of Surface Temperature[END_REF]. The determination of emissivity from remote sensing data is not straightforward, while accurate values are required for surface temperature estimation procedures. [START_REF] Olioso | Estimating the difference between brightness and surface temperatures for a vegetal canopy[END_REF] showed that an error of +/-0.01 in spectral emissivity resulted in surface temperature error between 0.5 K and 1 K depending on the atmospheric conditions and the temperature level.

It is recognized that LSE varies according to many factors such as soil type, surface soil moisture and roughness, amount of vegetation cover and plant species. There is no exhaustive knowledge of the variations of LSE because in situ measurements of LSE are complex to implement. There are also only very few modelling studies [START_REF] Olioso | Simulating the relationship between thermal emissivity and the normalized difference vegetation index[END_REF] [7] [START_REF] Verhoef | Unified Optical-Thermal Four-Stream Radiative Transfer Theory for Homogeneous Vegetation Canopies[END_REF] and almost no evaluation of LSE model against LSE measurements [START_REF] Olioso | SAIL-thermique, a model to simulate land surface emissivity[END_REF]. In this study we present the evaluation of multispectral simulation with the SAIL -Thermique model [START_REF] Olioso | Simulating the relationship between thermal emissivity and the normalized difference vegetation index[END_REF] of LSE against multispectral measurements over a soybean canopy. LSE measurements were performed using a multispectral radiometer and the TES method (see [START_REF] Mira | Comparison of Thermal Infrared Emissivities Retrieved With the Two-Lid Box and the TES Methods With Laboratory Spectra[END_REF]).

MATERIEL ET METHODE

The SAIL-Thermique model

The SAIL model was originally developed by [START_REF] Verhoef | Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model[END_REF] for simulating bi-directional spectral reflectances in the solar domain. It was adapted for simulating radiative transfers in the thermal infrared, and particularly for simulating land surface emissivity by [START_REF] Olioso | Estimation of evapotranspiration and photosynthesis by assimilation of remote sensing data into SVAT models[END_REF] [START_REF] Olioso | Simulating the relationship between thermal emissivity and the normalized difference vegetation index[END_REF]. Considering the Kirchhoff's relation, the LSE in the direction of the measurement is calculated as the absorptivity of an incident directional radiation. Specific values of model parameters have to be prescribed including leaf reflectance, leaf transmittance, soil reflectance, Leaf Area Index (LAI) and Leaf Angle Distribution (LAD). The geometry of the measurement is set by considering a direction of observation equivalent to the direction of incident radiation (azimuth and zenith) and a diffuse fraction in the incident radiation set to zero.

A first evaluation of the model against broadband LSE data compiled from various databases was given by [START_REF] Olioso | SAIL-thermique, a model to simulate land surface emissivity[END_REF]. Compiled land surface emissivities for the 8-14 μm spectral band ranged between 0.92 and 0.99. A root mean square error around 0.006 was obtained. When considering only herbaceous species, the root mean square error was 0.004.

Experimental setup

An irrigated soybean crop was grown on the 'Flux and Remote Sensing' experimental site at INRA Avignon (South East France) during summer 2007. When the crop reached the flowering phenological stage it was almost fully covering the ground with a Leaf Area Index (LAI) close to 4. A part of the crop (10 m2) was progressively thinned out in order to generate a spatial gradient of LAI from bare soil to maximum LAI value.

Radiances were measured at nadir using the multispectral TIR radiometer CIMEL Electronique CE 312-2 [START_REF] Brogniez | A high-accuracy multiwavelength radiometer for in situ measurements in the thermal infrared. Part II: Behavior in field experiments[END_REF] in 5 channels equivalent to the channels of the ASTER sensor (on board of the TERRA platform) and one broad channel between 8 and 14 μm (Table 1). The radiometer had a field of view of 10°. It was calibrated before the field measurements. The measurement in each channel lasts for around 20 s, so that the full acquisition takes 2 min. The measurements were performed in order to cover the full LAI gradient with around 10 measurements. Every two or three measurements, a set of measurements was performed over an Infragold reference plate in order to characterize atmospheric downwelling irradiance in each channel. The acquisitions were performed under cloudless sky starting half an hour after solar noon so that time variations in temperature were limited. The full measurement sequence was repeated 3 times in order to control the residual temperature variations.

Table 1. Effective wavelengths (λeff) and full width at half-maximum (Δλ) for the bands of the CE 312-2 radiometer ([10])

Emissivity calculation from radiance measurements

Emissivities in the five ASTER channels were retrieved on the basis of the Temperature-Emissivity Separation (TES) algorithm proposed for ASTER by [13][14]. It can be applied to any multispectral sensors as far as at least 3 TIR channels are available [START_REF] Jacob | Reassessment of the temperature -emissivity separation from multispectral thermal infrared data: Introducing the impact of vegetation canopy by simulating the cavity effect with the SAIL-Thermique model[END_REF]. The determination of emissivity requires additional information as radiances depends on surface temperature and emissivity. For a multispectral TIR sensor with n-channels, there are n + 1 unknowns (n spectral emissivities plus one surface temperature) but only n available radiance measurements. TES uses the spectral contrast between the different channels to provide an additional equation that relates the minimum emissivity εmin to the Maximum-Minimum Difference (MMD) calculated over the n channels. MMD is the ratio of the difference between the maximum and the minimum emissivity values (εmax -εmin) to the mean emissivity value εmean. The equation that was derived empirically from laboratory measurements of spectra from rocks, soils, vegetation, snow and water samples by [START_REF] Gillespie | A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images[END_REF][14] is expressed as:

The TES algorithm requires the sky irradiance in each channel in order to account for the reflected radiation. We used the average of the two closest sky irradiance measurements obtained over the reference plate before and after each radiance measurements over the soybean canopy.

Simulations

Simulations of LSE with the SAIL-Thermique model were done by considering similar conditions as the experimental conditions. LAI was varied between 0 and 4 and the LAD set to planophile. Leaf reflectance spectrum (Figure 1) was obtained from measurements done using a SOC400T portable FTIR reflectometer [START_REF] Jaworske | Portable Infrared Reflectometer for Evaluating Emittance[END_REF] on soybean leaves harvested in the experimental field (3 leaf samples). An experimental protocol similar to [START_REF] Fabre | Influence of water content on spectral reflectance of leaves in the in the 0.4 -15 μm domain[END_REF] was used. Leaf transmittance was assumed equal to zero as [START_REF] Gerber | Modeling directional-hemispherical reflectance and transmittance of fresh and dry leaves from 0.4 μm to 5.7 μm with the PROSPECT-VISIR model[END_REF] showed that leaf transmittance is usually very low for fresh herbaceous plant leaves. Soil reflectance spectra (Figure 1) were obtained on soil samples from the experimental field by [START_REF] Lesaignoux | Influence of soil moisture content on spectral reflectance of bare soils in the 0.4-14 μm domain[END_REF]. LSE in the five radiometer channels were obtained by convoluting simulated LSE spectra by the spectral response function of each channel. Simulated emissivities were eventually compared to measured emissivities by considering measurements obtained over LAI close to the one used for the simulation.

Figure 1. Soybean leaf (mean and 3 samples) and soil reflectance spectra acquired in Avignon, together with the soil reflectances derived in the CE 312-2 channels from TES emissivity estimates.

RESULTS AND DISCUSSION

Soil reflectances retrieved using TES were slightly different from the values obtained in the laboratory by [START_REF] Lesaignoux | Influence of soil moisture content on spectral reflectance of bare soils in the 0.4-14 μm domain[END_REF] over soil samples (Figure 1). However, the differences were not too large as compared to other studies (e.g. [START_REF] Mira | Comparison of Thermal Infrared Emissivities Retrieved With the Two-Lid Box and the TES Methods With Laboratory Spectra[END_REF]) and the spectral behavior was globally respected. The difference might be explained by several factors as spatial variations in soil composition, differences in soil aspect between laboratory measurements (powder), and/or uncertainties associated to the TES method.

Simulations of LSE spectra at LAI 0.125, 0.25, 0.5, 1, 2 and 4 are presented in Figure 2 and the simulated values obtained in the five radiometer channels in Figure 3. These last simulations were performed assuming soil reflectance equivalent to the measurements obtained over bare soil with TES. Figure 4 shows the LSE obtained from the CIMEL measurements and the TES method over the in situ LAI gradient (~10 points with LAI increasing from 0 to 4). Spectra simulations in Fig. 2 show a rapid increase with LAI from bare soil values to saturation values obtained for LAI about 2 or 3. This is in general agreement with previous modelling [START_REF] Olioso | Simulating the relationship between thermal emissivity and the normalized difference vegetation index[END_REF][7][8] [START_REF] Olioso | SAIL-thermique, a model to simulate land surface emissivity[END_REF] and experimental [START_REF] Van De Griend | On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces[END_REF][21] studies. Spectra at LAI above 2 present features in accordance with soybean leaf spectra (e.g., leaf reflectance bump at 9.85 μm resulting in emissivity decrease) with no more visible impact of soil spectra features (e.g. soil absorption peak at 10.7 μm and high soil reflectivity at 8.2 μm).

When considering simulated LSE in the radiometer channels (Fig 3 .), the saturation of LSE at the higher LAI is of course still visible, but spectral features appeared only partially. The spectral behavior of soil surface is well captured by the 5 channels: impact of high soil reflectance in the first channel at 8.4 μm; local minimum values at 9.1 μm and 11.3 μm; higher values at 8.7 μm and 10.6 μm. Conversely, the main spectral feature of vegetation, around 9.9 μm is not seen as no channel covers this part of the spectra.

Simulations show a general agreement with LSE measurements (comparing Figures 3 and4). The spectral behavior related to soil and vegetation properties is globally similar even if TES estimates appeared more variable and slightly higher than SAIL-Thermique simulations (e.g., see saturated values between 0.985 and 0.990 in the simulation and between 0.990 and 0.992 in the TES estimates). This may be related to the uncertainties related to the TES methods and its application to the CIMEL Electronique CE 312-2 radiometer. The sensitivity analysis performed in [START_REF] Mira | Comparison of Thermal Infrared Emissivities Retrieved With the Two-Lid Box and the TES Methods With Laboratory Spectra[END_REF] showed that the uncertainty in TES results may be larger than 0.01 while the uncertainties related to the non-simultaneity of the measurements in each channel was significantly lower (less than 0.2%). However, this may depend on meteorological conditions at the time of the measurements. The difference between simulations and measurements may be also related to the representativity of the leaf reflectance spectrum used for the simulation (average of only 3 leaf samples with a standard deviation close to 0.005). Model hypothesis as considering isothermal and homogeneous plant canopies may also be in cause.

CONCLUSION

We presented a preliminary evaluation of multispectral simulations of emissivity with the SAIL-Thermique model. The results are encouraging as simulations are globally in agreement with the measurements. However, we still have to provide a more exhaustive evaluation, including numerical evaluation of the differences between simulations and measurements, over a larger number of situations and plant canopies. We also have to keep in mind that emissivity simulations considered isothermal canopies while the variation of temperature within plant canopies can be large and can generate large directional effects [START_REF] Luquet | Using directional TIR measurements and 3D simulations to assess the limitations and opportunities of water stress indices[END_REF][23].

ACKNOWLEDGEMENT

Figure 2 .

 2 Figure 2. LSE spectra between 8 and 14 μm simulated with SAIL-Thermique at LAI values of 0, 0.125, 0.25, 0.5, 1, 2 and 4.

Figure 3 .

 3 Figure 3. LSE in the 5 radiometer channels simulated with SAIL-Thermique at LAI values of 0, 0.125, 0.25, 0.5, 1, 2 and 4. LSE values are given at the central wavelength of each channel.

Figure 4 .

 4 Figure 4. LSE obtained from the application of the TES method to the radiance measurements in the 5 radiometer channels. LSE values are given at the central wavelength of each channel. Each line corresponds to measurements obtained at specific position over the 0 to 4 LAI gradient.

This work was made possible thanks to the financial support of CNES (Centre National d'Etudes Spatiales) through the TOSCA program (EVASPA v3.0 and E2IRT) and of PNTS (Programme National de Télédétection Spatiale) program (contract 06CV101, Potentialité des mesures ASTER pour l'estimation de la température de surface).


Amina Lissaneddine

Mounir Laila Mandi

Mounir El Achaby

Emmanuel Mousset

Eldon R Rene

Naaila Ouazzani

Marie-Noëlle Pons

Faissal Aziz

Performance and dynamic modeling of a continuously operated pomace olive packed bed for olive mill wastewater treatment and phenol recovery

Keywords: Olive pomace, Olive mill wastewater, Phenolic compounds, Activated carbonbeads, Adsorption, Regeneration

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Oil mills generating olive oil in the Mediterranean region have a significant economic position, representing 98% of global olive oil production [START_REF] Bampalioutas | Detoxification and methane production kinetics from three-phase olive mill wastewater using Fenton's reagent followed by anaerobic digestion[END_REF][START_REF] Al-Bsoul | Optimal conditions for olive mill wastewater treatment using ultrasound and advanced oxidation processes[END_REF]. Olive oil extraction is achieved via modern or traditional processes. Generally, two waste fractions are produced regardless of the extraction technique [START_REF] Kaleh | Selective isolation of valuable biophenols from olive mill wastewater[END_REF] in seasonal time intervals [START_REF] Annab | A proposal for the sustainable treatment and valorisation of olive mill wastes[END_REF]: solid waste (OP) and liquid effluent (OMWW). Unfortunately, OMWW has a high polluting power due to a high chemical and biochemical oxygen demand after 5 days (COD and BOD5) (Ji et al., 2019). Furthermore, they are saturated by phenolic and aromatic compounds that are toxic and extremely difficult to biodegrade (Baierle et al., 2019).

Environmental legislation in Morocco requires that the discharge from olive mills have a pH ranging between 6 and 9, a concentration of PCs of 0.5 mg L -1 , an electrical conductivity that does not exceed 3 mS cm -1 , a BOD5 that does not surpass 0.1 g-O2 L -1 and a COD that does not go over 0.5 g-O2 L -1 [START_REF] Pinto | Strategies for recovering phenol from wastewater: thermodynamic evaluation and environmental concerns[END_REF][START_REF] El Moudden | Effect of filtration of olive mill wastewater on the phenolic composition and its influence on antioxidant activity[END_REF].

Tyrosol, hydroxytyrosol, vanillic acid, gallic acid, p-hydroxyphenyl acetic acid, caffeic acid and p-coumaric acid are considered the dominant PCs in OMWW (Bressan et al., 2004). The toxicity of OMWW is largely attributed to these phenolic compounds. In addition to their high cost, traditional physicochemical and biological systems applied for OMWW treatment have limited effectiveness. Thus, possible treatment techniques are necessary to reach a suitable solution for the elimination of these compounds [START_REF] Kilic | Photochemical treatment of tyrosol, a model phenolic compound present in olive mill wastewater, by hydroxyl and sulfate radical-based advanced oxidation processes (AOPs[END_REF][START_REF] El Ghadraoui | Treatment of olive mill and municipal wastewater mixture by pilot scale vertical flow constructed wetland[END_REF][START_REF] Elmansour | Effect of polyphenols on activated sludge biomass during the treatment of highly diluted olive mill wastewaters: biomass dynamics and purifying performances[END_REF]). However, many technologies have recently been investigated for recovery of PCs from OMWW, such as physical, thermal, physicochemical and biological technologies (Rahmanian et al., 2013). [START_REF] Azzam | Olive mill wastewater treatment and valorization by extraction/concentration of hydroxytyrosol and other natural phenols[END_REF] used liquid-liquid extraction to recover PCs from OMWW using ethyl acetate as a solvent; [START_REF] Zagklis | Purification of olive mill wastewater phenols through membrane filtration and resin adsorption/desorption[END_REF] used resin adsorption/desorption for the recovery of hydroxytyrosol from OMWW, and [START_REF] Achak | Low cost biosorbent "banana peel" for the removal of PCs from olive mill wastewater: Kinetic and equilibrium studies[END_REF] used adsorption followed by desorption for the recovery of total PCs from OMWW using banana peel as a biosorbent.

Adsorption is the most widely used and effective technique for removing environmental pollutants [START_REF] Sun | Insight into the mechanism of adsorption of phenol and resorcinol on activated carbons with different oxidation degrees[END_REF]. In recent years, many adsorbents, such as activated carbons (ACs), have been used to eliminate PCs [START_REF] Annab | A proposal for the sustainable treatment and valorisation of olive mill wastes[END_REF]. AC is commonly used because of its microporous texture, high surface reactivity, consistency in the distribution of pore size, wide spectrum of functional surface groups and thermal steadiness [START_REF] Shim | Removal of pcresol and tylosin from water using a novel composite of alginate, recycled MnO2 and activated carbon[END_REF].

A column reactor is a practical and simple device that reduces the costs of and energy needed for water treatment by exploiting the concentration gradient between the adsorbent and pollutants, producing high-quality treated effluents with a minimum pollutant concentration on an ongoing basis [START_REF] Basu | Adsorption of lead on lentil husk in fixed bed column bioreactor[END_REF]. However, due to the small particle size of AC, its application in continuous flow adsorption systems has some disadvantages, such as bed compaction and a high-pressure drop in fixed bed column systems [START_REF] Aziz | Composites with alginate beads: A novel design of nano-adsorbents impregnation for large-scale continuous flow wastewater treatment pilots[END_REF]. To avoid such drawbacks, the encapsulation of AC in alginate hydrogels is an attractive alternative with high applicability for continuous flow adsorption processes [START_REF] Aziz | Composites with alginate beads: A novel design of nano-adsorbents impregnation for large-scale continuous flow wastewater treatment pilots[END_REF][START_REF] Quesada | Chitosan, alginate and other macromolecules as activated carbon immobilizing agents: A review on composite adsorbents for the removal of water contaminants[END_REF]. Alginate gels are highly permeable due to their porous texture and hydrophilicity, providing important advantages due to their high affinity and adsorption potential for several micropollutants, such as heavy metal ions and dyes [START_REF] Arenales-Sierra | Calcium alginate beads loaded with Mg(OH)2 improve L. casei viability under simulated gastric condition[END_REF][START_REF] Quesada | Chitosan, alginate and other macromolecules as activated carbon immobilizing agents: A review on composite adsorbents for the removal of water contaminants[END_REF]. The wastewater treatment operation at the real scale requires granular materials of controlled size, which numerous researchers had to generate those materials by the encapsulation of diverse adsorbents in the alginate composite to improve their potentials [START_REF] Aziz | Composites with alginate beads: A novel design of nano-adsorbents impregnation for large-scale continuous flow wastewater treatment pilots[END_REF].

Currently, many researchers use beads with alginate coatings on several kinds of sorbent materials or functionalize them to be more efficient and teste the obtained composites for OMWW PCs or synthetic effluent (Jodra and Mijangos 2007;[START_REF] Kim | Adsorption equilibrium of copper ion and phenol by powdered activated carbon, alginate bead and alginate-activated carbon bead[END_REF]Siva Kumar et al., 2009;[START_REF] Duarte | Removal of PCs in olive mill wastewater by silica-alginate-fungi biocomposites[END_REF]. [START_REF] Duarte | Removal of PCs in olive mill wastewater by silica-alginate-fungi biocomposites[END_REF] The objective of this study is to carry out a cycle of olive mill waste treatment in which OP is first converted into a highly porous AC to be used for the treatment of OMWW by adsorption.

The kinetics, mechanism and adsorption isotherms of PC adsorption were investigated. The experiments were carried out under different operational conditions (time, concentration, pH, temperature) to determine the adsorbent behavior in stirred batch and fixed-bed reactors. PC recovery and the process reusability of SA-AC beads were carried out in fixed-bed reactors.

Materials and methods

Sample collection and characterization

OMWW was sampled from modern and traditional oil mills located in the region of Marrakech in Morocco during the olive oil extraction season from December to March during the 2019/2020 campaign. The collected samples were subjected to various physicochemical analyses according to the methods of analysis as indicated in Table S1 (in the Supplementary material). The pH, temperature, TDS (total dissolved solids), salinity and EC (electrical conductivity) were measured by a Hanna HI 9829 probe (Kallang Road, Singapore). The COD, suspended matter and volatile matter in suspension, ammonium and total phosphorus and orthophosphates were analyzed according to AFNOR standards. The PCs were measured using the Folin-Ciocalteu method (Singleton and Rossi, 1965) using caffeic acid as a standard.

Preparation of activated carbon

OP was collected from modern oil mills located in the region of Marrakech in Morocco. It was dried at 105°C overnight and then ground to a coarse aggregate. The activation process was performed using chemical activation. Ten grams of precursor (olive pomace) was physically mixed with 5 M sodium hydroxide (98-100.5% purity, Sigma-Aldrich) at a weight ratio (activator/precursor) of 1:1 by stirring for 1 h. The material was thoroughly washed and filtered using deionized ultrapure water until a pH of 7 was obtained. Finally, the material was placed in a furnace at room temperature. The adsorbent was heated to 700°C with a temperature increase rate of 10°C per minute. The material was then kept in the furnace (SF7/S Stuart, United Kingdom) at 700°C for 30 min.

Preparation of beads

Composite beads (sodium alginate (SA) -AC) were prepared via the crosslinking process. The process for preparing the composite beads consists of first producing a primary mixture of the hydrogel of sodium alginate (BioChemica) (1%) at 25°C. The AC powder (1%) was then added to the alginate hydrogel under constant stirring to prepare a homogeneous dispersion (24 h).

The second step was to pour the secondary mixture dropwise into a crosslinking solution of iron 20 g L -1 (iron(III) chloride hexahydrate, 99%, ACROS Organics). Bead solidification was performed for 24 h. Finally, the aggregated SA-AC beads were thoroughly washed with ultrapure water and stored in ultrapure water.

Characterization

FTIR was used to assess the functional groups on the surface of the AC and beads. The FTIR spectra were obtained by ALPHA FT-IR Spectrometer (ALPHA-P, Germany) in the wavelength range of 400 to 4000 cm -1 . Each spectrogram consisted of an average of 60 scans.

Morphological examination of the SA-AC beads was performed by using SEM measurements, which were taken with a TESCAN™ VEGA3 scanning electron microscope (Fuveau, France).

An EDS analyzer (TEAM™ EDS) enabled the analysis of elements on the micro-scale and element distribution on the SA-AC beads. The BET method was used to calculate the specific surface area (SBET) and the total volume (VT) of AC and SA-AC beads that had been previously outgassed and assessed by nitrogen adsorption at -196°C (via a Micromeritics ASAP 2020 surface analyzer system).

The average pore radius (r -) was calculated from Eq. 1 [START_REF] Lagergren | One-step steam pyrolysis for the production of mesoporous biochar from oil palm frond to effectively remove phenol in facultatively treated palm oil mill effluent[END_REF]:

𝑟 (𝑛𝑚) = 2𝑉 𝑇 𝑆 𝐵𝐸𝑇
× 10 3 (Eq. 1)

2.5. Experimental setup and procedure

Stirred batch sorption experiments

Batch tests were achieved by adding 5 g of SA-AC beads to a 5 mL OMWW sample for the optimal time in tubes in a rotary mixer under continuous stirring (KS 3000 i control, Germany) at 200 rpm. Isotherm studies were performed on the prepared SA-AC with OMWW of various concentrations (20,40,80,100,250,800, 1,000, 1,500, 2,000, 2,500, 3,000, 3,500 and 4,000 mg L -1 ) for 24 h and at pH 4, which corresponds to the pH of the real effluent. In a subset of experiments, the pH of the OMWW solution was adjusted from 4 to 10 using 1.0 M NaOH or HCl. The control tests samples were agitated without SA-AC beads under the same conditions.

All experiments were performed at ambient temperature (19 °C) and were performed in duplicate.

Column sorption experiments

The continuous system assays were performed with a column with a 4 cm interior diameter and a height of 30 cm. The SA-AC beads (140 g) were introduced into the column. The OMWW was introduced in ascending flow using a peristaltic pump (Antlia -3C Dutscher, France) at a constant flow rate of 2 mL min -1 . At the outlet of the column, the OMWW was sampled at regular time intervals, and the PC concentration was measured. All tests were carried out in duplicate.

To assess the reusability of this newly generated material, PC desorption from SA-AC beads in the liquid phase was examined in fixed-bed reactors. After the adsorption experiment, the SA-AC beads were rinsed with distilled water three times to eliminate PCs on the surface, targeting the adsorbed fraction. The desorption tests were then performed with ethanol due to the selectivity of this solvent for PCs (Zagklis et al., 2018). Desorption was performed with 5 mL ethanol per g of SA-AC beads. At a constant temperature, ethanol was pumped into the column at a fixed flow rate of 2 mL min -1 for 3 h. The PCs concentrations were determined at various time intervals from the beginning of the desorption operation.

Analytical method

The phenolic extracts were analyzed by high-performance liquid chromatography (HPLC).

AKnauer-HPLC chromatograph equipped with a diode array detector and accompanied by software for processing the data was used. The column had a reversed-phase polarity (Eurospher II 100-5 C-18, 250x4.6). The mobile phase was a gradient of acetonitrile and bidistilled water acidified to pH 2.6 with O-phosphoric acid. The separation lasted 1 h according to a linear gradient program of acetonitrile/water and was performed at a temperature of 25°C, a pressure of 400 bar and a flow rate of 1 mL min -1 .

Batch and fixed-bed column data analysis

To understand and explain the adsorption process of PCs onto beads, Langmuir and Freundlich adsorption isotherm models were presented in this study; according to many references [START_REF] Badawi | Adsorption of aluminum and lead from wastewater by chitosan-tannic acid modified biopolymers: Isotherms, kinetics, thermodynamics and process mechanism[END_REF][START_REF] Olusegun | Enhancement of adsorption capacity of clay through spray drying and surface modification process for wastewater treatment[END_REF][START_REF] Es-Sahbany | Removal of heavy metals (nickel) contained in wastewater-models by the adsorption technique on natural clay[END_REF], these two models are considered compatible models to describe the sorption phenomena.

The Langmuir isotherm equation (Eq. 2) shows an adsorption model of a homogeneous system with a single layer and is expressed as (Langmuir, 1916):

= × + (Eq. 2)
where qe (mg g -1 ) is the PCs amount adsorbed at equilibrium; Ce (g L -1 ) is the equilibrium concentration of PCs in solution; KL is the Langmuir constant related to the energy of adsorption (L g -1 ); and qm (mg g -1 ) is the maximum PCs adsorption capacity.

The Freundlich adsorption isotherm model is applied for multiple layer adsorption founded on a heterogeneous process. The Freundlich adsorption isotherm equation (Eq. 3) is (Freundlich, 1906):

𝑙𝑛𝑞 = 𝑙𝑛𝐾 + × 𝑙𝑛𝐶 (Eq. 3)
where Kf is a Freundlich constant that presents the adsorption capacity of the adsorbent and n is a constant that presents the greatness of the relationship between PCs and SA-AC beads.

To further explain the elimination process of PCs onto SA-AC beads, two kinetic models were investigated. The adsorption kinetics data have been compared with the pseudo-first order and pseudo-second order rate equations; according to many references, these two models are used to define the sorption mechanisms [START_REF] Lagergren | One-step steam pyrolysis for the production of mesoporous biochar from oil palm frond to effectively remove phenol in facultatively treated palm oil mill effluent[END_REF][START_REF] Ho | Pseudo-second order model for sorption processes[END_REF]:

𝑙𝑜𝑔(𝑞 -𝑞 ) = 𝑙𝑜𝑔 (𝑞 ) - . × 𝑡 (Eq. 4) = × + (Eq. 5)
Where qe and qt are the amounts of PCs adsorption onto SA-AC beads at equilibrium and time t, respectively, and k1 and k2 are the pseudo-first order and pseudo-second order rate constants, respectively.

A temperature study on the adsorption of PCs on alginate beads at various temperatures (19-35°C) was performed. The thermodynamic parameters, i.e., the Gibbs energy (Δ𝐺 in kJ mol -1 ), standard entropy (ΔS in J mol -1 K -1 ) change, and standard enthalpy (Δ𝐻 in kJ mol -1 ) change, of the adsorption process were calculated from the following equations (Eqs. 6-9) [START_REF] Li | Synergistic effect of mesoporous feroxyhyte nanoparticles and Fe (II) on phosphate immobilization: Adsorption and chemical precipitation[END_REF]):

∆𝐺 = -𝑅 × 𝑇 × 𝑙𝑛𝐾 (Eq. 6) ∆𝐺 = ∆𝐻 -𝑇 × ∆𝑆 (Eq. 7) 𝑙𝑛𝐾 = - ∆ × + ∆ (Eq. 8)
where𝐾𝑐 is the thermodynamic distribution coefficient calculated by Eq. 9:

𝐾 = (Eq. 9)

where qe and Ce are equilibrium concentrations (g L -1 ) of adsorbate on the adsorbent and the solution, respectively.

The values of the important design parameters of the breakthrough curves of the column for PCs adsorption onto the SA-AC beads were calculated. The volume of the effluent, Vef (mL), was calculated with the following equation:

𝑉 = 𝑄 × 𝑡 (Eq. 10)
Where ttotal is the total time (min) and Q is the flow rate that circulates through the column (mL min -1 ).

The pic area of the breakthrough curve signifies the total mass of PCs biosorbed, qtotal (mg), for a specific feed concentration and flow rate and can be calculated by integration as follows:

𝑞 = × ∫ 𝐶 × 𝑑𝑡 (Eq. 11)
where CR is the concentration of PCs removal (mg L -1 ).

The total amount of PCs sent to the column (mg) can be determined from the equation below:

𝑚 = × ×
(Eq. 12)

and the total metal removal (%) can be determined from the ratio of PCs mass adsorbed (qtotal)

to the total amount of PCs sent to the column (mtotal) as:

%𝑅 = × 100
(Eq. 13)

The amount of PCs adsorbed at equilibrium or adsorption capacity, qe (mg of adsorbed phenolic compounds/g of SA-AC beads), and the equilibrium PCs concentration, Ce (mg L -1 ), can be determined from the following equations:

𝑞 = (Eq. 14) 𝐶 = × 1000 (Eq. 15)
where m total amount of PCs sent to the column (g), and Vef (mL) volume of the effluent.

The dynamic behavior of the column is approached by the following models: Thomas and Yoon-Nelson.

 Thomas model

The Thomas model is one of the most extensively used breakthrough models in fixed-bed column performance theory. It assumes Langmuir kinetics for adsorption and desorption with no axial dispersion. The model expression can be presented as (Thomas, 1994):

= × × × × (Eq. 16)
Where kTH (mL min -1 mg -1 ) is the Thomas rate constant, q0 (mg g -1 ) is the adsorption capacity, m total amount of PCs sent to the column (g), and Q is the flow rate that circulates through the column (mL min -1 ).

 Yoon-Nelson model

The Yoon-Nelson model involves no detailed data about the physical properties of the adsorbent in the fixed-bed column (Yoon and Nelson, 1984). It is expressed as:

= ( × × ) ( × × )
(Eq. 17)

where is the time required for 50% adsorbate breakthrough (min) and kYN is a rate constant that is related to the diffusion characteristics of the mass transfer zone (min -1 ).

Results and discussion

3.1. Physicochemical properties of the effluent for traditional oil mills). Inorganic loads such as sodium (0.13 g L -1 ), potassium (5.9 g L -1 ), calcium (0.24 g L -1 ) and chloride (3.5 g L -1 ) are high for modern oil mills. These high organic and inorganic loads can make biological treatment extremely difficult and justify the need to implement alternative physicochemical processes such as adsorption. In addition, the concentration of total solids is relatively high (128 g L -1 ).

The analysis of the phenolic composition of this effluent by HPLC (Fig. A1 in Supplementary material) revealed the presence of a varied phenolic pool composed mainly of gallic acid, tyrosol, ferulic acid, caffeic acid, cinnamic acid, and coumaric acid. [START_REF] Magdich | A yearly spraying of olive mill wastewater on agricultural soil over six successive years: impact of different application rates on olive production, phenolic compounds, phytotoxicity and microbial counts[END_REF] found protocatechuic acid, tyrosol, benzoic acid, ferulic acid and p-coumaric acid. In addition, Tafesh et al. (2014) showed the presence of hydroxytyrosol, acetic acid, 3,4-dihydroxyphenyl, tyrosol, protocatechuic acid, vanillic acid, verbascoside, caffeic acid, p-coumaric acid and ferulic acid.

However, [START_REF] Leouifoudi | Identification and characterisation of PCs extracted from Moroccan olive mill wastewater[END_REF] identified tyrosol and hydroxytyrosol as the main PCs in OMWW, which is similar to the results reported by [START_REF] Achak | Low cost biosorbent "banana peel" for the removal of PCs from olive mill wastewater: Kinetic and equilibrium studies[END_REF]. PCs do not have the same organic functions; therefore, the adsorption mechanism should not be selective for the organic structure of only one type of PC.

Characterization of the adsorbent

FTIR spectra of AC and SA-AC beads before and after adsorption are displayed in Fig. A2 (a, b & c) (Supplementary material). FTIR spectra were obtained in the wavelength range of 4000 -400 cm -1 . The peaks of the FTIR spectrum of AC (Fig. A2 a) at 3457 cm -1 could be the -OH stretching vibration mode of hydroxyl functional groups. The band at approximately 3032 cm -1 corresponds to the stretching mode of aromatic unsaturated hydrocarbon groups [START_REF] Iwanow | Activated carbon as catalyst support: precursors, preparation, modification and characterization[END_REF]. The symmetrical stretching vibrations of -CH2-and -C=O groups are represented by the bands at1435 cm -1 and 1683 cm -1 , respectively [START_REF] Wang | De-intercalation of the intercalated potassium in the preparation of activated carbons by KOH activation[END_REF]. In the FTIR spectrum of the SA-AC beads (Fig. A2 b), the band at approximately 3308 cm -1 corresponds to the hydroxyl group (-OH group). The stretching vibration of the carbonyl (-C=O) group appears at 1590 cm - 1 ; the symmetrical stretching vibration of -CH2-is located at 1402 cm -1 [START_REF] Allwar | Preparation and characterizations of activated carbon from banana fruit bunch with chemical treatments using hydrothermal processes[END_REF].

The absorption band at 1037 cm -1 is attributed to the bending vibration of the O-H group [START_REF] Nasrullah | High surface area mesoporous activated carbon-alginate beads for efficient removal of methylene blue[END_REF]. There were no significant differences in FTIR spectra between SA-AC beads after adsorption of phenolic compounds and SA-AC beads before adsorption. This result is in accordance with the work previously reported by Shim et al. (2018). These researchers speculated that weak electrostatic interactions and ionic adsorption are prevalent among the studied contaminants and beads.

The textural characteristics of AC and SA-AC beads were evaluated by SEM, and images at the same magnifications are shown in Fig. 1 (a &b). In the SEM photograph, the AC surface has a porous morphology caused by the effect of sodium hydroxide as an activating agent at higher temperatures, and the surface of SA-AC beads has a porosity less than that of a pure AC sample. However, SA-AC beads still have a rough and porous surface. The textural characteristics of the raw AC and SA-AC beads are shown in Table S2 (in the Supplementary material). The specific surface areas (SBET) of AC and SA-AC were 758 and 523 m 2 g -1 , respectively. In addition, the total pore volume (VT) values were 0.805 cm 3 g -1 for AC and 0.308 cm 3 g -1 for SA-AC beads, which are almost analogous to those reported by other researchers. [START_REF] Kwak | Sericin-derived activated carbon-loaded alginate bead: An effective and recyclable natural polymer-based adsorbent for methylene blue removal[END_REF] reported VT values of 0.710 cm 3 g -1 for AC and 0.358 cm 3 g -1 for composite beads.

The average r -values were 2.124 nm and 1.179 nm for the AC and SA-AC beads, respectively.

The decrease in the r -of AC when mixed with sodium alginate polymer to generate SA-AC beads indicates pore encapsulation by sodium alginate.

These results show the achievement of the feasibility of agglomerating the adsorbent (powder) into macroparticles (beads) by keeping these higher adsorption capacity potentials in order to avoid clogging during the column treatment process. Clogging overcame increase the process life cycle, which decrease the treatment fees. This new design promotes the industrial-scale application to treat effluents in a continuous flow which is the best practical way in the real application [START_REF] Aziz | Composites with alginate beads: A novel design of nano-adsorbents impregnation for large-scale continuous flow wastewater treatment pilots[END_REF].

Adsorption efficiency

Fig. 2a presents the effect of contact time on the removal PCs capacity onto SA-AC beads. The results show that the removal potential increased rapidly at the initial stage until 120 min.

Afterwards, the PCs adsorption potential did not change meaningfully until equilibrium was reached.

The initial rapid uptake is caused by the existence of a greater number of active sites on the SA-AC beads in the starting stage, and after a lapse of time, the accumulation of PCs in the active sites could be the cause of the decrease in the adsorption of more compounds [START_REF] Braghiroli | Production, characterization, and potential of activated biochar as adsorbent for PCs from leachates in a lumber industry site[END_REF].

Adsorption equilibrium study

The adsorption isotherms were analyzed to describe the PCs distribution between the liquid and solid phases when the adsorption process attained equilibrium [START_REF] Sun | Insight into the mechanism of adsorption of phenol and resorcinol on activated carbons with different oxidation degrees[END_REF]. Fig. 2b shows the PCs adsorption isotherms onto SA-AC beads. The amount of adsorbed PCs increased with the PCs concentration in solution until it reached 95 mg g -1 at 1000 mg L -1 . The increasing amount of PCs in solution causes a rise in the mass transfer driving force [START_REF] Li | Synergistic effect of mesoporous feroxyhyte nanoparticles and Fe (II) on phosphate immobilization: Adsorption and chemical precipitation[END_REF].

The fitting results of the adsorption isotherms are shown in Fig. 2 (c &d) and the parameters are provided in Table S3 (in the Supplementary material). The Langmuir isotherm provided the highest correlation (R 2 = 0.9975) for PCs adsorption, indicating that adsorption sites are assumed to be energetically homogeneous, and significant PCs monolayer coverage on the outer bead surface is formed without any interaction between the PCs (adsorbed molecules) [START_REF] Mojoudi | Removal of phenol and phosphate from aqueous solutions using activated carbons prepared from oily sludge through physical and chemical activation[END_REF]. Therefore, the monolayer saturation capacity is 114 mg g -1 beyond which no further adsorption can take place, but full-scale, supplementary experiments (adsorption kinetics) are needed to accurately predict the adsorption capacity of phenolic compounds.

Modeling of adsorption kinetics

The rate constants and R 2 values were calculated from the linearized plots shown in Fig. 3 and are also summarized in Table S4 (in the Supplementary material). Considering the reported R 2 values, PCs adsorption onto SA-AC beads followed pseudo-second order kinetics, and the correlation coefficients were higher (0.9973) than those of pseudo-first order kinetics (0.7009).

The amount of PCs adsorption for pseudo-first order kinetics was 28 mg g -1 , whereas that of pseudo-second order kinetics was 68 mg g -1 . The calculated qe(calc) values using the pseudosecond order kinetic model are much closer to the experimental qe(exp)values, further suggesting that the adsorption of PCs onto SA-AC beads best fits pseudo-second order kinetics. This model supposes that PCs adsorption is principally controlled by chemisorption, which includes valency changes through sharing or exchange of electrons between the SA-AC beads and the PCs, and external adsorption occurs more often than micropore adsorption [START_REF] Abdelhay | Kinetic and thermodynamic study of phosphate removal from water by adsorption onto (Arundodonax) reeds[END_REF]Tao et al., 2017). Analogous results have also been reported for biochars prepared from olive oil processing waste, CuO-coated olive cake nanocomposites, granular and powdered AC encapsulated in calcium alginate (beads), and shrimp shell chitin [START_REF] Elayadi | Factorial Design for Optimizing and Modeling the Removal of Organic Pollutants from Olive Mill Wastewater Using a Novel Low-Cost Bioadsorbent[END_REF][START_REF] El Hanandeh | Modification of biochar prepared from olive oil processing waste to enhance phenol removal from synthetic and olive mill wastewater[END_REF][START_REF] Yuney | CuO coated olive cake nanocomposites for rapid phenol removal and effective discoloration of high strength olive mill wastewater[END_REF][START_REF] Annab | A proposal for the sustainable treatment and valorisation of olive mill wastes[END_REF]. The SA-AC beads used in the present study for PCs removal from a batch test, which were able to remove 68 mg g -1 phenolic compounds, yielded more promising results than other reported adsorbents. In comparison to biochar prepared from olive oil processing waste (51.3 mg g -1 ), granular and powdered AC encapsulated in calcium alginate beads (14.32 and 35.8 mg g -1 , respectively), SA-AC composite beads showed a higher removal capacity. However, in the case of using shrimp shell chitin (1.045 g g -1 ), the adsorption potential was higher than that of the adsorbent used in our study because the initial phenol concentration tested was also higher (10-12 g L -1 ). In addition, information on the kinetics of PCs adsorption is necessary to determine the optimum conditions for full-scale PC removal procedures.

Effect of pH

The PCs adsorption ability of the SA-AC beads at different pH values is shown in Fig. 4a. The adsorption capacity of PCs declined from 65 to 12 mg g -1 as the pH increased from 2 to 10. This is due to the solubility of PCs that increases when the pH values decrease. Thus, there was an inverse relationship between the adsorption and solubility of phenolic compounds. However, pH values influenced the augmentation of oxygen-containing functional groups of SA-AC beads, inducing the effects of pH on the zeta potentials of SA-AC beads [START_REF] Tahermansouri | Phenol adsorption from aqueous solutions by functionalized multiwalled carbon nanotubes with a pyrazoline derivative in the presence of ultrasound[END_REF][START_REF] Sun | Insight into the mechanism of adsorption of phenol and resorcinol on activated carbons with different oxidation degrees[END_REF]Al Bsoul et al., 2020). These authors studied the effect of pH on phenol adsorption using carboxylated multi-walled carbon nanotubes, activated carbons, and ziziphus leaves, respectively. The same results were also reported for the effect of pH.

The main PCs identified in the effluent are mentioned in section 3.1. The pKa of PCs vary from around 3-4 to 10-11, while for most of them it is around 10. Thus, the protonated forms of PCs are predominant from acidic to neutral pH. This form is more prone to be adsorbed on SA-AC beads than the unprotonated form. That is why the adsorption capacity increase when the pH decrease. The adsorption capacity is higher at an acidic pH than at a basic pH, which is advantageous in our case since the pH of real effluent is acidic and thus pH adjustment would not be required during the treatment. Therefore, in full-scale systems, OMWW can be used directly, which will minimize costs during treatment. [START_REF] Alwan | PH Control Problems of a Wastewater Treatment Plant[END_REF] showed pH-control problems of industrial wastewater treatment plants, which induct technical issues affecting the treatment efficiency, that increase the cost of each treated volume.

Effect of temperature

The thermodynamic parameters, i.e., ΔG°, ΔS° and ΔH° values, were obtained from the plot of ln (KD) versus 1/T (Fig. 4b and Table S5 in the Supplementary material). The positive values of ΔH° suggest an endothermic reaction. In addition, the value of ΔH° was 29 kJ mol -1 (higher than 20 kJ mol -1 ), suggesting that PCs adsorption onto SA-AC beads involves some chemisorption. The ΔG° values for different temperatures were found to be negative and decreased as the temperature decreased; the negative values of ΔG° (19°C: -255; 25°C: -1183; 30°C: -1460; 35°C: -1946 J mol -1 ) indicate a spontaneous reaction. The positive value of ΔS° (74 J mol -1 K -1 ) corresponds to a dissociative mechanism. Moreover, the positive value of ΔS° also indicates an increased degree of freedom of the PCs in the solution and randomness at the solid/solution interface with some structural variations in the PCs and SA-AC beads during the PCs adsorption process, while the adsorbed molecules of water can be displaced by the PCs molecules [START_REF] Srivastava | Adsorptive removal of phenol by bagasse fly ash and activated carbon: equilibrium, kinetics and thermodynamics[END_REF][START_REF] Cheng | Phenol adsorption equilibrium and kinetics on zeolite X/activated carbon composite[END_REF].

Fixed-bed column modeling

During the first 40 min, all the PCs were adsorbed, resulting in a PCs concentration of zero in the outlet water (treated water). As adsorption proceeded, the PCs concentration in the treated water gradually increased. In the up-flow mode, as PCs water is inserted at the bottom of a clean bed of the SA-AC bead medium, most of the PCs are first eliminated in a closed layer at the bottom. As the adsorption proceeded, the lower compartment of the SA-AC beads became saturated with PCs, and the adsorption area advanced vertically through the column (Kundu et al., 2016). Finally, the adsorption area reached the top of the column, and the PCs concentration in the treated water began to increase. A breakthrough curve was generated by plotting the PCs concentration (in mg L -1 ) in the treated water against time (in min). The values of the important design parameters of the breakthrough curves of the bed column for PCs adsorption onto the SA-AC beads were calculated and are shown in Table S6 (in the Supplementary material). As shown in this table, for Ci = 4,700 mg L -1 and Q = 2 mL min -1 , the value of qe reached 159 mg g -1 , while the R was 41.6%.

The SA-AC beads used in the present study for PCs removal from a fixed-bed column yielded more promising results than other reported adsorbents [START_REF] Kumar | Removal of methylene blue and phenol onto prepared activated carbon from Fox nutshell by chemical activation in batch and fixed-bed column[END_REF][START_REF] Víctor-Ortega | Performance and modeling of continuous ion exchange processes for phenols recovery from olive mill wastewater[END_REF][START_REF] Annab | A proposal for the sustainable treatment and valorisation of olive mill wastes[END_REF]. The adsorbent SA-AC beads were able to remove 159 mg g -1

PCs. In comparison to Amberlyst A26 exchange resin (148 mg g -1 ), activated carbon (76 mg g - 1 ) and bead-activated carbons, calcium alginate (16 mg g -1 ), SA-AC beads showed higher removal capacity. Furthermore, the adsorbent (SA-AC beads) used in the present study was easily prepared at a low cost.

Data from HPLC analysis of PCs adsorption onto the SA-AC beads before and after treatment in a fixed-bed column are depicted in Fig. A4 (in the Supplementary material). HPLC analysis of the PCs of OMWW after adsorption on the SA-AC beads at 10 min of treatment (Fig. A4a)

showed the removal of 100% tyrosol (361.08 mg L -1 ), caffeic acid (99.24 mg L -1 ), ferulic acid (8.44 mg L -1 ), coumaric acid (9.12 mg L -1 ), and cinnamic acid (264.90 mg L -1 ). It can be noted that the adsorption capacity of tyrosol, caffeic acid, coumaric acid, ferulic acid and cinnamic acid is greater than that of gallic acid (40.50 mg L -1 ). This could be due to the effect of the structure and pKa (acid dissociation constant at logarithmic scale) of PCs of the OMWW.

OMWW contains a considerable quantity of mineral ions and organic matter. The physicochemical parameters of the OMWW before and after treatment in a fixed-bed column are described in Table 2. In addition to removing PCs, the SA-AC beads were able to adsorb several ions and colloidal and soluble organic particles with an average of approximately 50%.

These contaminants can compete for the adsorption sites and interfere with the removal efficiency. This finding indicates that the surface of the SA-AC bead is highly attractive to multiple elements of OMWW contaminants, which was confirmed by the greater decrease in electrical conductivity (EC) after treatment. SA-AC was also efficient in raising the pH from 4.79 to 6.12, so after treatment, we could use it directly without pH adjustment.

The parameters given by modeling the experimental breakthrough curves with the Thomas and Yoon-Nelson models for PCs adsorption into SA-AC are presented in well, meaning that the results followed the kinetics of Langmuir with the hypothesis applicable in a system with a constant flow and a negligible axial dispersion in the adsorption of the column because the motive force of speed follows the reversible reaction of the second-order (Chue, 2010). These results are consistent with those obtained previously in batch experiments.

These data, in addition to their utility in terms of kinetics and isotherms obtained with real effluents, will allow us to design an OMWW treatment system by simulating a full-scale process. In fact, to accurately design a full-scale SA-AC bead adsorption system, in several cases, pilot-scale tests are still required. These modeling results facilitate implementation and offer promising results on PCs breakthroughs in a short period of time. Consequently, the time and cost of a full-scale design are significantly reduced [START_REF] Merle | Assessment of the breakthrough of micropollutants in full-scale granular activated carbon adsorbers by rapid small-scale column tests and a novel pilot-scale sampling approach[END_REF].

Desorption studies will serve to recover precious PCs from OMWW to regenerate SA-AC beads and to understand the adsorption process. As we showed, PCs adsorption on SA-AC beads is ensured by chemisorption, so desorption experiments were carried out with ethanol according to the procedure described in Section 2.5.2. This was due to the high solubility of PCs in ethanol. The results showed that ethanol recovered almost 43% of the PCs adsorbed.

This indicates that ethanol could access SA-AC bead micropores. A similar desorption investigation was also performed and examined for the desorption of phenol using 30% (v/v) ethanol solution by neem leaves (Azadirachta indica). Maximum desorption of phenol was achieved (58.5%) with the batch system [START_REF] Mandal | Phenol removal from wastewater using low-cost natural bioadsorbent neem (Azadirachtaindica) leaves: Adsorption study and MLR modeling[END_REF]. [START_REF] Shim | Simultaneous removal of phenol, Cu and Cd from water with corn cob silica-alginate beads[END_REF] worked with actual Ca-alginate beads containing corn cob silica, immobilized Pseudomonas putida YNSI, and reported successful phenol desorption using 0.05 M HCl. These studies showed that recovery of phenol from beads was substantial (69%) and that optimization of the desorption step in the continuous process is still needed (Mandal et al., 2014).

Solvent regeneration has numerous advantages for SA-AC bead regeneration since it requires less energy, enables the recovery of PCs and SA-AC beads, and avoids the loss of SA-AC beads. Adsorbent regeneration allows the feasibility of recycling beads for several cycles of OMWW treatment and phenol recovery.

However, adsorbents regeneration is affected by some physical parameters such as the pressure. [START_REF] Shen | Capture of CO2 from flue gas by vacuum pressure swing adsorption using activated carbon beads[END_REF] highlighted that an increase of feed pressure from 131.32 to 202.65 kPa, make increases the adsorbate recovery rate from 48.6 to 78.2%. The pressure drop is impacted by the beads bed thickness (i.e. column height), the bed porosity, as well as the frictional at the surface of the beads [START_REF] Franchin | Removal of Ammonium from Wastewater with Geopolymer Sorbents Fabricated via Additive Manufacturing[END_REF]. This pressure drop across the column increases approximately linearly with breakthrough time [START_REF] Kratochvil | Biosorption of Cu from ferruginous wastewater by algal biomass[END_REF]. For this reason and in order to reduce the pressure drop across the bed, it is necessary to periodically backwash the column (Cooney et al., 1998).

To selectively desorb phenolic compounds, electrosorption/desorption experiments will be carried out using a column reactor with a fixed-bed and upward flow. Specific attention will be given to the influence of the acidity constants of PCs on the efficiency of electrosorption to selectively desorb phenolic compounds.

Conclusions

New composite beads based on olive pomace with alginate hydrogel were formulated successfully for PC elimination from OMWW. The structure and porous morphology of SA-AC beads was confirmed by FTIR, SEM and EDS, which revealed the feasibility of SA-AC beads as potential and low-cost biosorbents. The adsorption of PCs by the SA-AC bead composite fit second-order kinetics and Langmuir isotherms. The results indicated that PC adsorption on SA-AC beads is strongly dependent on pH and phenol solubility.

Thermodynamic analysis indicated that PCs adsorption was spontaneous and endothermic.

Thomas and Yoon-Nelson models were selected to fit the experimental data, and the modified Thomas model was better at predicting PCs column adsorption. Finally, the regeneration investigation of SA-AC beads showed that the recovery of phenols from OMWW can be carried out with ethanol.

  Fig. A3 (a & b) (in Supplementary material) shows the EDS spectra of AC and SA-AC beads.

  Fig. 5 shows the breakthrough curve of the adsorption of the phenolic compound onto SA-AC beads. The instant breakthrough time observed was 40 min, and the exhaustion time was 25 min. Different column parameters were determined.

  used silica-alginate-fungi biocomposites; Siva Kumar et al. (2009) investigated chitosan-calcium (CS/Ca) alginate blended beads; Kim et al. (2008) used an alginate-activated carbon (AAC) bead and Jodra and Mijangos (2007) used a calcium alginate-AC composite bead. Although numerous studies exist on the application of alginate composite beads for the treatment of PCs of OMWW or synthetic phenol from water exist, this is the first work on the combined use of olive mill wastes and alginate for the adsorption and recovery of PCs from real OMWW.

In a similar work,

[START_REF] Annab | A proposal for the sustainable treatment and valorisation of olive mill wastes[END_REF]

investigated beads based on AC encapsulated in calcium alginate to adsorb polyphenols from OMWW. This work succeeded in attaining a high level of adsorption capacity of their synthesized material for polyphenols. In addition, the activation of the pomace used in this work was accomplished with KOH. Furthermore, these beads were tested under batch and column conditions on only synthetic effluent and OMWW diluted in ultrapure water, i.e., without the high concentrations that are characteristic of real effluents. All these reasons make their results not easily applicable to industrial applications. Therefore, it is suggested in the present work to use raw effluent and AC treated with NaOH before transforming it into beads for the first time and to characterize the PCs adsorbed from OMWW by liquid chromatography.

  Table1presents the physicochemical properties of the studied OMWW. The results showed that OMWW has acidic pH values equal to 4.8 and 4.7 for modern oil mills and traditional oil mills, respectively, due to the presence of organic acids and PCs. The latter constitute a large proportion of OMWW (4 and 10 g L -1 for modern oil mills and traditional oil mills, respectively). This high content of PCs leads to toxicity of this effluent. It is further associated with a high concentration of organic matter, indicated by a very high COD value (110 g-O2 L -1

Table 3 .

 3 The R 2 values (0.9771) demonstrated that the Yoon-Nelson model were compatible and could be used to describe the PCs in SA-AC continuous mode. Furthermore, it is shown in Table3 thatthe 50% breakthrough time () for 50% adsorbate breakthrough from the Yoon-Nelson model complies with the experimental values ((exp) = 141 min). Moreover, error analysis was based on obtaining the best model among the models used for this study. The mean absolute error (MAE) values equaled 0.0619 and 0.0710 for the Thomas model and Yoon-Nelson model, respectively, as shown in Table 3, while the root-mean-square error (RMSE) values for both models were calculated as 0.0727 and 0.0902, respectively. The MAE and RMSE for the Thomas model were lower than those for the Yoon-Nelson model. The Thomas model fit the experimental data

Acknowledgments

This work was financed by the PHC TOUBKAL 2019 Project (French-Morocco bilateral program) grant number: 41525VG. The authors would like to thank the National Center for Studies and Research on Water and Energy (Cadi Ayyad University_Morocco) and Laboratoire Réactions et Génie des Procédés (LRGP), CNRS/Université de Lorraine (France) for the technical and scientific support to this work.