Effective use of elderberry (Sambucus nigra) pomace in biosorption processes of Fe(III) ions

Chemosphere 246 (2020) 125744

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Effective use of elderberry (Sambucus nigra) pomace in biosorption processes of Fe(III) ions Tomasz Kalak a, *, Joanna Dudczak-Hałabuda a, Yu Tachibana b, Ryszard Cierpiszewski a
University of Economics and Business, Niepodległo
sci 10, Department of Industrial Products and Packaging Quality, Institute of Quality Science, Poznan
, Poland 61-875, Poznan b Department of Nuclear System Safety Engineering, Graduate School of Engineering, Nagaoka University of Technology, 1603-1, Kamitomioka, Nagaoka, Niigata, 940-2188, Japan a

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


Elderberry residues were generated as a result of processing in the food industry.
Various parameters have an impact on the biosorption of Fe(III) ions.
The maximum Fe(III) biosorption efficiency of elderberry is estimated at 99.5%.
The maximum Fe(III) biosorption capacity is estimated at 33.25 mg/g.
The pseudo-second-order and Langmuir models fit better to the sorption process.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 11 September 2019 Received in revised form 20 December 2019 Accepted 23 December 2019 Available online 2 January 2020

Elderberry (Sambucus nigra) pomace obtained as a result of processing in the food industry was examined for the bioremoval of Fe(III) ions from aqueous solutions in batch experiments. Several physicochemical properties of the biomass were analyzed using a variety of analytical methods, such as particle size distribution, elemental composition (SEM-EDS), X-ray diffraction analysis (XRD), thermogravimetry (TGA, DTG), specific surface area and average pore diameter (BET adsorption isotherms), volume of pores and pore volume distribution (BJH), morphology (SEM), mid-infrared analysis FT-IR. The impact of adsorbent dosage, initial concentration, pH and contact time on the process efficiency was studied. The calculated maximum adsorption efficiency and capacity was estimated at 99.5% and 33.25 mg/g, respectively. The biosorption kinetic analysis indicated that the removal process fits better to the pseudosecond order equation and the Langmuir model. Summing up, the biosorbent is a promising low-cost material for the highly effective iron recovery from effluents and improvement of water quality. © 2020 Elsevier Ltd. All rights reserved.

Handling Editor: T Cutright Keywords: Water quality Biosorption capacity Elderberry pomace Fe(III) ions

1. Introduction Currently, the development of civilization brings not only

* Corresponding author. E-mail address: [email protected] (T. Kalak). https://doi.org/10.1016/j.chemosphere.2019.125744 0045-6535/© 2020 Elsevier Ltd. All rights reserved.

benefits for humanity, but also many serious threats. Some of their effects are investigated and appropriate preventive actions are taken. However, some threats may cause unpredictable consequences in the future. An example may be the presence of inorganic impurities, such as metal ions in the ecosystem, causing a serious environmental threat. Toxic metal compounds released into the environment as a result of human activity pollute not only surface

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T. Kalak et al. / Chemosphere 246 (2020) 125744

waters, including oceans, seas, lakes, ponds, rivers, reservoirs, but also can groundwater by penetrating the soil after snow and rain (Kalak et al., 2019). According to World Health Organization (WHO), Cu, Cr, Cd, Hg, Ni and Pb are classified as metals that are the most toxic and dangerous to the environment (WHO, 2006). One of the metals whose too high concentration in water is undesirable and even harmful is iron. It is mainly found in groundwater in the soluble or insoluble form. Water containing iron completely dissolved in the ionic form is transparent and colorless. When the water is in contact with oxygen-rich air, it becomes cloudy and a reddish-brown substance begins to form. This precipitate is an oxidized hydroxide iron that is not soluble in water (Das et al., 2007). This phenomenon causes many problems, including mainly aesthetic, indirect health problems, as well as economic problems. The metal is harmful to aquatic organisms, but the degree of toxicity can be reduced by binding iron ions with other anionic water components. The insoluble form creates iron deposits, which are eaten with food by fish and other aquatic organisms (Spellman, 2001). Iron is present in drinking water, as it is necessary for proper functioning of humans. Both its deficiency and excess are harmful to health. Permanent use of too much iron increases the risk of heart disease and cancer. According to the Environmental Protection Agency (EPA), the secondary standard maximum contaminant level (MCLs) for iron is 0.3 mg/L in drinking water (The Environmental Protection Agency website, 2019). However, the European Drinking Water Directive established a mandatory limit value of 200 mg/L Fe (The Drinking Water Directive, 1998). The concentration of metals and other impurities must be controlled to ensure adequate drinking water quality. Therefore, many physical, chemical and biological water purification methods are developed, for example the conventional techniques, including membrane technology, filtration, ion exchange, chemical precipitation, electrochemical treatment and many others (Ince and Ince, 2017). Their downside is that they are often very expensive and inefficient. An alternative method may be biosorption, which is very effective and much cheaper than the conventional ones. Many types of biosorbents exhibit binding properties to metal ions, however the efficiency of their removal depends on many factors, including the composition of adsorbents and types of metals. This is one of the reasons why research on biosorption has now become one of the most active and frequently undertaken works by scientists. In particular, cheap biosorbents obtained from agricultural, animal and industrial waste are of great interest. However, choosing a biosorbent for a given metal is not easy and requires many experiments and in-depth research (Kalak and Strus, 2014; Kalak et al., 2015; Kalak and Cierpiszewski, 2018). Elderberry waste generated in the food industry can be a promising material for conducting appropriate research on biosorption phenomena to effectively remove metal ions. This biomass is rich in ingredients, such as dietary fiber, anthocyanins (pelargonidin-3-sambubioside, cyanidin-3-sambubioside, cyanidin-3-glucoside, cyanidin-3,5diglucoside, pelargonidin-3-glucoside, cyanidin-3-rutinoside, cyanidin-3-sambubioside-5-glucoside), flavonoids (quercetin-3rutinoside, quercetin-3-glucoside), hyperoside, lectin, lupeol, bsitosterol, holocalin, prunasin, zierin, rutin, sambu-nigrin, tannin, choline, beltulin, vitamins A, B1, B2, B3, B5, B6, B9, C and P, minerals (Zafra-Stone et al., 2007; Wu et al., 2004). These substances contain polar functional groups, such as carboxyl, phenolic, hydroxyl, sulfo and amino groups that are capable of binding metal ions. The binding mechanism may involve ion exchange, complexation and chelation reactions. In addition, physical adsorption, redox reactions or micro-precipitation may take place. This process can also include all these reaction mechanisms (Das et al., 2008). The aim of the studies was to examine the physicochemical

properties of elderberry (Sambucus nigra L.) pomace generated from the processing in the food industry. Furthermore, the purpose was to study the efficiency of bioremoval of Fe(III) ions from aqueous solutions by the biomass under different conditions of adsorbent dosage, initial concentration, pH and contact time. Additionally, the biosorption kinetics, equilibrium and the Langmuir and Freundlich isotherms were analyzed. 2. Experimental procedure 2.1. Materials and methods 2.1.1. Elderberry preparation Elderberry (Sambucus nigra L.) pomace was obtained from processing in the food industry in one of companies located in Poland and used in these studies. The material was crumbled, sieved and separated into particular fractions. Then, it was dried at a temperature of 60  C and next kept in a desiccator before analysis. All measurements were repeated three times, chemical reagents were pure for analysis and distilled water was used. 2.1.2. Elderberry residues characterization The biomass fractions with a diameter of less than 0.212 mm were used in the experiments. Furthermore, physical and chemical properties of the material were characterized using various analytical methods, such as: 1) particle size distribution analyzed by the laser diffraction method using a Zetasizer Nano ZS (Malvern Instruments Ltd., UK); 2) the elemental composition and mapping using a scanning electron microscope (SEM) Hitachi S-3700 N with an attached a Noran SIX energy dispersive X-ray spectrometer (EDS) microanalyser (ultra-dry silicon drift type with resolution (FWHM) 129 eV, accelerating voltage: 20.0 kV); 3) X-ray diffraction analysis using Bruker AXS D8 Advance (Germany); 4) thermogravimetry analyzed by Setsup DTG, DTA 1200 (Setram; temperature range 30  Ce600  C; the rate of temperature increase 10  C/min; gas flow rate of nitrogen 20 mL/min); 5) the specific surface area and the average pore diameter by the BET method using Autosorb iQ Station 2 (Quantachrome Instruments, USA); 6) the pore volume by the BJH method using Autosorb iQ Station 2 (Quantachrome Instruments, USA); 7) the morphology by a scanning electron microscope (SEM) EVO-40 (Carl Zeiss, Germany); 8) the surface structure analysis by a Fourier transform attenuated total reflection (FT-IR ATR) Spectrum 100 (PerkinElmer, Waltham, USA). 2.1.3. Fe(III) adsorption Determination of the adsorption efficiency of Fe(III) on elderberry pomace was performed in batch experiments at room temperature (T ¼ 23 ± 1  C). Fe(III) ions with analytical purity (standard for AAS 1 g/L, Sigma-Aldrich (Germany)) were used. The elderberry (2.5e100 g/L) and a portion of Fe(III) solution (2.5e20 mg/L) at pH range 2e5 were shaken in conical flasks at 150 rpm during 1 h until equilibrium was reached. The pH of Fe(III) solutions were adjusted using 0.1 M HCl and NaOH. Next, the solutions were centrifuged for 15 min at 4000 rpm for phase separation. Finally, the Fe(III) ions concentration after biosorption was determined by the atomic absorption spectrophotometer (F-AAS, at a wavelength l ¼ 248.3 nm for iron) SpectrAA 800 (Varian, Palo Alto, USA). The measurements were carried out in triplicate and average results were depicted. 3. Results and discussion 3.1. Characterization of the adsorbent The particle size distribution affects several properties of

T. Kalak et al. / Chemosphere 246 (2020) 125744

materials, such as granules, powders, suspensions, emulsions, aerosols as well as it is an important indicator of particle quality and efficiency. This analysis affects the speed and strength of hydration. Smaller particles dissolve faster, they get higher viscosity of suspension than larger ones. Smaller drop sizes and a larger surface charge usually improve the stability of suspension and emulsion. In addition, smaller particle sizes affect the better performance of adsorption processes (Shanthi et al., 2014). In these studies, particle size distribution of elderberry residues was determined by laser diffraction and only one peak was revealed at 77.0 nm. It should be explained that the analysis was somewhat limited, i.e. not all biomass particles formed a slurry in a solution (larger particles fell to the bottom of the solution). Therefore, only the particles suspended in the solution could be analyzed. The SEM-EDS method was applied to determine elemental composition (Fig. 1). The peaks visible in the spectrum correspond to the following elements: C (41.26%), O (26.45%), Si (7.39%), P (5.45%), Al (5.29%), K (4.28%), S (3.5%), Mg (2.33%), Ca (1.71%), Na (1.55%) and Fe (0.78%). Due to the fact that elderberry is organic biomass, the presence of the largest amount of carbon and oxygen atoms was observed during the analysis. The content of elements was estimated by the number of counts in the EDS microanalysis. It is characteristic that the biomass material is not homogeneous, hence the quantitative and qualitative composition will be slightly different depending on the position of the measuring point on the sample using the SEM-EDS method. Qualitative analysis was carried out by X-ray diffraction (the diffractograms of mineralogical composition are attached as supplementary material). Thanks to this analysis, it is possible to estimate and provide approximate content of individual phases based on the intensity of reflexes. In accordance with the measurements, the primary crystalline phases of elderberry are as follows: quartz (SiO2, 48.28%), weddellite (syn. CaC2O4$2H2O, 20.05%), whewellite (CaC2O4$H2O, 16.35%), whewellite (syn. CaC2O4$H2O, 15.32%). Thermogravimetric analysis was performed at a temperature range of 29e600  C. In general, it can be noted that as the temperature rises, the material mass loss occurs. The TGA and DTG curves showed the two stages of decomposition of elderberry biomass. The first one occurred between 30 and 110  C and the second at around 160 and 480  C. The first stage represents a small weight loss (3%) caused by evaporation of adsorbed water from the biomass sample. The pyrolysis process caused a greater loss of mass (about 34.6%) in the second stage, where most volatiles are emitted from the sample. This visible strong peak (DTG) refers to the decomposition of lipids, carbohydrates and proteins (Peng et al.,

3

2001). The BET analysis was carried out and the results of the specific surface area (SBET), volume of the pores (Vp) and average pore diameter (Apd) are shown in Table 1. The adsorption and desorption isotherm is characteristic of Type II adsorption behaviour. Its intermediate flat area concerns the formation of a monolayer. In accordance with the IUPAC classification (Sing, 1982), pores present in elderberry are classified as mesopores (2.0e50 nm). Pore volume distribution for adsorption and desorption was carried out by the BJH method that is associated with capillary condensation taking place in mesopores. In addition, examples of the specific surface area values of other commercial adsorbents are summarized in Table 2. Generally, after the literature analysis, adding up and averaging, the values ranges are as follows: commercial activated carbon 500e2000 m2/g, bentonite 47e73 m2/g, silica gel 150e900 m2/g, banana peel and orange peel 20.6e23.5 m2/g, wood 3.8e6.4 m2/g. 3.2. Adsorption studies of Fe(III) removal by the use of elderberry 3.2.1. Impact of adsorbent dosage The influence of adsorbent dosage on the adsorption of Fe(III) in the pH range 2e5 is presented in Fig. 2. In general, the efficiency increased with the rise in the elderberry dosage up to 50 g/L. The dose can be regarded as optimal, where maximum adsorption efficiency is estimated at 97.1%. The best results were achieved at pH 4 and 5. Further increase in the amount of the adsorbent does make any sense, because no essential changes are observed and the adsorption is kept constant. Additionally, the experimental adsorption capacity decreased from 3.2 to 0.98 mg/g at pH 5. Thanks to this phenomenon, active sites are fully utilized during interaction between the adsorbent and Fe(III) ions at low mass _ _ 2014). It is assumed that the active surface (Paliulis and Bubenait e, sites of biomass available for iron ions were not fully utilized at the higher weight of the adsorbent. The increase in efficiency can be attributed to the greater number of free sites for metal ions and their high availability to the binding sites as the weight increases. Therefore, the decrease in adsorption capacity is observed (Karthikeyan et al., 2007; Lata et al., 2008; Nuhoglu and Malkoc, 2009). 3.2.2. Impact of initial concentration of Fe(III) The effect of the initial concentration of Fe(III) ions (2.5e20 mg/ L) at the optimal adsorbent dosage of 50 g/L was studied and results are shown in Fig. 3. As it is seen, the removal efficiency of elderberry suddenly increased with an increase in initial iron concentration up to 2.5 g/L. A further increase in concentration from 2.5 to 20 mg/L caused only a slight increase in the adsorption efficiency from 93.6 to 97.1%. Due to the specificity of biosorption, the saturation of the elderberry surface depends on the initial concentration of iron ions. At higher concentrations, Fe(III) ions are supposed to diffuse to the surface of elderberry by intraparticle diffusion. The hydrolyzed ions may occur at acidic pH that can lead to much more slow diffusion (Radnia et al., 2012; Langeroodi et al., 2018; Mînzatu et al., 2019). The initial concentration of Fe(III) was a sufficient driving force to initiate transfer between the aqueous phase and the

Table 1 Summary of BET adsorption and desorption parameters.

Fig. 1. EDS spectrum of elderberry.

BJH parameter

Values

Specific surface area (SBET) [m2/g] Pore volume (Vp) [cm3/g] Pore diameter (Apd) [nm]

2.642 0.0025 3.85

4

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Table 2 Specific surface area of various adsorbents.

Table 2 (continued ) Adsorbents

Adsorbents

Specific surface area Reference [m2/g]

Elderberry (Sambucus nigra L.) pomace Soy meal hull Sunflower stalk Anodonta shell CFBC slag (Poland) Fly ash (Slovakia) Wood Sepia pens Beer brewery waste Crude sewage sludge

2.64

(these studies)

0.7623 1.2054 1.42 1.87 3.26 3.8e6.4 4.11 4.5 5.28

High lime fly ash Fly ash (Czech Republic) Fly ash (treated with H2SO4) Squid pens Mixture almond shells

5.35 5.47 6.236 8.82 10.5

Modified zeolite CFBC fly ash (Poland) Fly ash, zeolite, unburned carbon Banana peel (raw) Orange peel (raw) Diatomite Bentonite

11.8 11.98 15.6, 16.0, 224 20.6e23.5 20.6e23.5 27.8 28

Blast furnace sludge Yellow passion fruit Charred dolomite Calcined alunite

28 30 36 42.8

Modified sepiolite Clay

50.5 71

Pyrolysed sewage sludge AC from cotton seed shell

80 124.35

Modified silica CAC Merck AC from gingelly seed shell

187 222.22 229.65

AC sludge based Coir pith carbonized

253 259

Rice husk carbon AC from pongam seed shell

272.5 324.79

AC Rice husk Carbonaceous adsorbent Activated sewage sludge Sawdust carbon Cane pith AC-Bagasse Cane (bagasse) pith Carbonaceous material AC from biomass Euphorbia rigida DTMA-bentonite AC-Walnut shell AC-Apricot shell AC-Sugarcane bagasse AC-Hazelnut shell AC-Pinewood AC-Corncob CAC fiber FE400 (Toho Rayon Co.) PAC Chemviron GW GAC Filtrasorb 400 (Chemviron Carbon UK) AC-groundnut shell CAC granular Wako (Wako pure chemicals) AC-Plum kernel AC from pine sawdust

352 380 390 516.3 606.8 607 606.8 629 741e21

Arami et al. (2006) Sun and Xu (1997) Figueiredo et al. (2000) Kalak (2019) Janos et al. (2003) Poots et al. (1976) Figueiredo et al. (2000) Tsai et al. (2008) Dhaouadi and M’Henni (2008) Eren and Acar (2007) Janos et al. (2003) Lin et al. (2008) Figueiredo et al. (2000) Doulati Ardejani et al. (2008) Ozdemir et al. (2004) Kalak et al. (2019) Wang et al. (2005) Annadurai et al. (2002) Annadurai et al. (2002) Al-Ghouti et al. (2003) Ozacar and Sengil (2006) Jain et al. (2003) Pavan et al. (2008) Walker et al. (2003) Ozacar and Sengil (2002) Ozdemir et al. (2004) Bagane and Guiza (2000) Otero et al. (2003) Thinakaran et al. (2008) Phan et al. (2000) Malik et al. (2007) Thinakaran et al. (2008) Martin et al. (2003) Namasivayam et al. (2001) Malik (2003) Thinakaran et al. (2008) Mohamed (2004) Jain et al. (2003) Otero et al. (2003) Malik (2003) Juang et al. (2001) Juang et al. (2002) Juang et al. (2002) Gupta et al. (1997) Gercel et al. (2008)

767 774 783 790 793 902 943 1010 1026 1100 1114 1150 1162 1390

Ozcan et al. (2004) Aygun et al. (2003) Aygun et al. (2003) Tsai et al. (2001) Aygun et al. (2003) Tseng et al. (2003) Juang et al. (2002) Okada et al. (2003) Martin et al. (2003) Ozacar and Sengil (2002) Malik et al. (2007) Okada et al. (2003) Juang et al. (2002)

CAC felt KF1500 (Toyobo Co.) AC-Waste newspaper

Specific surface area Reference [m2/g]

1480 1740

Akmil-Basar et al. (2005) Okada et al. (2003) Okada et al. (2003)

AC e activated carbon; GAC e granular activated carbon; PAC e powdered activated carbon; CAC e commercial activated carbon; DTMA e dodecyltrimethylammonium bromidemodified.

Fig. 2. The impact of adsorbent dosage on removal efficiency of Fe(III) ions in different pH (Fe(III) initial concentration 10.6 mg/L; contact time 60 min).

Fig. 3. The impact of initial concentration on the Fe(III) removal efficiency (initial pH 4; contact time 60 min; adsorbent dosage 50 g/L).

solid phase. It is estimated that the greater driving force of mass transfer, the lower resistance to metal uptake and, consequently, the greater removal of metal ions (Nouri et al., 2007). In accordance with literature, the ionic radius of Fe3þ is 65 pm (Marcus, 1988). It is estimated that the smaller the ionic radius, the greater the tendency to exhibit a hydrolysis reaction causing a decrease in biosorption efficiency (Vinod and Anirudhan, 2001). 3.2.3. Impact of initial pH The effect of initial pH on the adsorption was examined and presented in Fig. 4. As it is seen, the process efficiency strongly depends on pH and adsorbent dosage. At pH 2e5, Fe(III) adsorption increased thanks to more favorable adsorption conditions and greater affinity for active sites. Based on the results presented in Fig. 4, the adsorption efficiency increased with an increase in elderberry dosage and pH. Maximum values are observed in the

T. Kalak et al. / Chemosphere 246 (2020) 125744

Fig. 4. The impact of pH on the Fe(III) removal efficiency (initial concentration of Fe(III) 10.6 mg/L; contact time 60 min; initial pH range 2e5) at adsorbent dosage 2.5e100 g/L.

range between 95% and 99% at pH 2e5 (dosage range between 40 and 100 g/L) and no further significant changes were noticed. The lowest efficiency was observed with an adsorbent dose of 2.5 g/L (A ¼ 21.8% at pH 2; A ¼ 66.6% at pH 5). There is a high probability that these iron ions are absorbed by the cation exchange mechanism. The excess hydrogen ions caused the protonation of various functional groups present on the surface of elderberry and lead to the reduction of the number of negatively charged sites. With an increase in pH to 3e5, the acid groups of biomass were deprotonated and the possibility of adsorption of positively charged iron ions increased. Fe(III) occurs in the ionic form at pH 2e5, so it can be explained that the maximum sorption capacity was in the form of the ionic metal up to pH 5. The phenomena may be also explained by the example of binding reaction with amine groups present in the biomass. At lower pH, the biosorption of Fe(III) decreases due to the protonation of amine groups to eNHþ 3 form. This reduces the number of binding sites available for the biosorption. When the experimental conditions are changed and pH value is increased up to 3e5, the Fe(III) adsorption efficiency is increased because of the decreasing number of protonated amine groups, which results in the increase in the number of binding sites. At pH above 2 a slight decrease in the efficiency of Fe(III) adsorption from 99.5% to 95% (in the biomass dose range 50e100 mg/L) can be explained by the competition of hydroxyl ions in the adsorption centers (Li et al., 2008; Feng et al., 2009; Lu et al., 2009; Vaghetti et al., 2009; Janos et al., 2006; Benaisa et al., 2016). 3.2.4. Kinetic studies on adsorption 3.2.4.1. Impact of contact time. The impact of contact time on the biosorption was examined and results are presented in Fig. 5. This parameter is of great importance and has a significant impact on the practical and effective use of biosorbents in industry (Amini et al., 2008; Inbaraj and Sulochana, 2006; Ilhan et al., 2008). Such a measurement factor as the contact time can be used to determine the amount of solutions in adsorption processes and their design lu and Arıca, 2005). The maximum sorption capacity was (Bayramog obtained in the first 5 min of the process (55.9%) and there were no meaningful changes up to 300 min (56.2%). A rapid initial increase in adsorption may be caused by the availability of a larger number of free active sites on the biomass surface and a high concentration of Fe(III) ions at the adsorbent-solution interface. Biosorption equilibrium was gradually obtained by occupying active centers by cations, however, the reaction mechanism can take various forms (Kavitha and Namasivayam, 2007). This biosorption process could be slowed down probably by the potential formation of other forms

5

Fig. 5. The impact of contact time on the Fe(III) removal efficiency (Fe(III) initial concentration 10 mg/L; elderberry dosage 50 g/L; initial pH 3.4; T ¼ 23 ± 1  C).

of metal compounds, including Fe(OH)2þ, Fe(OH)þ 2 and Fe(OH)3. 3.2.4.2. Pseudo-first-order and pseudo-second-order kinetic models. In order to present kinetics of Fe(III) bisorption on elderberry, pseudo-first-order and pseudo-second-order models were applied and the parameters are shown in Table 3. The calculated correlation coefficient R2 for the pseudo-first-order kinetic model is not high, hence it suggests that the biosorption mechanism does not fit to the reaction. Therefore, pseudo-second-order model was used for next studies. Based on the calculated data, it is seen that the higher correlation coefficient was achieved. The result suggests that the pseudo-second-order model better describes the adsorption process kinetics. Thus, probably chemisorption took place at the biomass surface in the process and chemical bonds were formed with Fe(III) ions (Ho and McKay, 1999). 3.2.5. Adsorption isotherms The biosorption process was characterized by the Langmuir and Freundlich isotherm models. Based on the data shown in Table 4, it can be concluded that the isotherm parameters mainly fit to the Langmuir equation model. The constant KL is associated with the adsorbent and the solute-binding energy, which is proportional to the spontaneity of the adsorption process. The higher the KL value, the greater the spontaneity of the biosorption reaction. This relationship refers to a more stable product and greater adsorption efficiency (Wang and Ariyanto, 2007). On the other hand, the Freundlich isotherm equation is associated with the dependence between the concentration of metal ions at equilibrium (Ce) and the ions concentration per unit mass of a biosorbent (qe). The Kf and n values are the indicator of the adsorption capacity of the biosorbent and adsorption intensity, respectively (Kumar et al., 2010). The calculated Freundlich isotherm parameters (Kf ¼ 1.035, 1/n ¼ 1.138) suggest that it is not difficult to separate iron ions from the solution. The maximum adsorption capacity of Fe(III) on different biosorbents has been compared with literature data and the results are

Table 3 The adsorption rate constants, qe and correlation coefficients related to pseudo-firstorder and the pseudo-second-order rate equations. Adsorbent dosage [g/L] Pseudo-first-order kinetic model

Pseudo-second-order kinetic model

kad qe R2 [min1] [mg/g] 25

0.0937

1.832

K qe R2 [g/mg min] [mg/g]

0.918 161.5

0.172

0.998

6

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Table 4 Isotherm model constants and correlation coefficients for adsorption of Fe(III) onto elderberry. Adsorbent dosage [g/L]

25

Langmuir isotherm

Freundlich isotherm

Calculated qm [mg/g]

KL [L/mg]

R2

Kf [mg/g] [L/mg](1/n)

n

R2

33.25

0.025

0.960

1.035

0.879

0.921

Table 5 A comparison of adsorption capacity of Fe(III) ions onto various adsorbents. Type of adsorbent/reference

qm [mg/g]

Elderberry Sambucus nigra (these studies) The husk of Cicer arientinum (Ahalya et al., 2006) Brown algae Sargassum Vulgare (Benaisa et al., 2016) Olive Cake (Al-Anber and Al-Anber, 2008) Microbial biomass Rhizopus arrhizus (Sag and Kutsal, 1996) Padina sanctae crucis algae (Keshtkar et al., 2016) Pretreated orange peel (Lugo-Lugo et al., 2012) Hazelnut hull (Sheibani et al., 2012)

33.25 72.16 63.67 58.479 34.73 34.65 18.19 13.59

presented in Table 5. It is clear that the elderberry samples tested in this research work have an adsorption capacity comparable to other biosorbents. 3.3. Characterization of elderberry morphology Morphology of the surface of elderberry was assessed using SEM images. Biomass micrographs before and after interaction with iron are shown in Fig. 6. Generally, elderberry before adsorption is characterized by irregular shape of the organic material with numerous cavities. The shapes are oval, longitudinal and gentle without sharp edges. The forms have a developed surface and their structure is not homogeneous. Furthermore, larger particles show greater irregularity compared to smaller ones. After the biosorption process the morphology of the biomass surface became rough, stomata are closed and agglomeration of particles occurred. The surface appears more irregular with a lot of small agglomerates attached to larger parts of the material. These photographs show changes in texture, which are likely to confirm phenomena of Fe(III) ions adsorption on the surface of elderberry. The Fe(III) distribution on the elderberry surface was examined by SEM-EDS mapping analysis (attached supplementary material). In general, the iron signal is quite intensive on the sample and a homogeneous distribution of the ions is revealed in this image. Higher metal concentration was observed only in one place, which may result from the presence of more anionic groups binding iron ions. The FT-IR analysis of elderberry before and after Fe(III) ions adsorption was carried out. Details of the mid-infrared bands are

Table 6 FT-IR peaks of elderberry and their assignment. FT-IR band [cm1]

Assignment (vibrations, species)

3302, 3297

stretching OeH from water and other hydroxylated molecules (alcohols, phenols) asymmetric stretching CeH, eCH3 and eCH2- groups (carboxylic acids) stretching CeH, eCH3 groups stretching C]O (esters) stretching CeO bending NeH; stretching C]C (aromatic ring) bending OeH, bending CeH (-CH2 group from proteins) stretching CeOeC deformation vibration C-H, C-O, bending C-C (carbohydrates) bending C-O (polysaccharides)

2925 2854 1737 1658, 1514, 1457, 1159 1098 1033,

1652 1513 1456

1031

shown and explained in Table 6. A comparison of the elderberry biomass spectrum before and after Fe(III) adsorption was carried out, taking into account the differences in frequency, band shape and intensity or possible interactions with iron ions. As it is seen in Fig. 7, the intensity of peaks decreased after biosorption and their positions remained in the same places. A significant change in the

Fig. 7. FT-IR spectrum of elderberry before and after Fe(III) ions adsorption (initial concentration 10.6 mg/L; adsorbent dosage 100 g/L; initial pH 2.0).

Fig. 6. (A, B). The SEM image of elderberry (x10000) before (A) and after (B) Fe(III) adsorption.

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intensity of 1159 and 1031 cm1 bands was noticed. The peaks are assigned to stretching C-O-C and bending C-O, respectively. Other changes occurred at 3297 (shift to 3302 cm1), 2925.25 (shift to 2925.14 cm1), 2854.68 (shift to 2854.98 cm1), 1736.96 (shift to 1737.49 cm1), 1652.84 (shift to 1658.02 cm1), 1514.83 (shift to 1513.34 cm1), 1455.92 (shift to 1457.01 cm1), 1131.13 (shift to 1132.82 cm1) wave numbers. The phenomena can be explain in such a way that chemisorption could take place in the process due to the interaction between iron ions with the functional groups of compounds present in the biomass. 4. Conclusions In these research studies, elderberry waste (Sambucus nigra L.) generated during processing in the food industry was examined for the possibility of removing Fe(III) ions from aqueous solutions in biosorption processes. To begin with, the physicochemical properties of the biomass were characterized using several analytical methods. Secondly, the influence of adsorbent dosage, initial concentration, pH and contact time on the effectiveness of the biosorption process was tested in batch experiments. The results showed that the maximum adsorption efficiency of 99.5% (dosage 100 g/L, pH 2, initial C0 ¼ 10.6 mg/L) and the calculated maximum adsorption capacity of 33.25 mg/g were achieved. Thirdly, the biosorption kinetics was studied and specific parameters for isotherms were calculated and analyzed. Based on the results, the pseudo-second-order kinetic model and the Langmuir model better described the processes. In conclusion, the studies indicated that elderberry waste effectively removes Fe(III) ions from aqueous solutions due to beneficial organic components and appropriate physical and chemical properties. Hence, this achievement outlines new horizons in the use of this biosorbent to improve the quality of water coming from various sources. CRediT authorship contribution statement Tomasz Kalak: Conceptualization, Methodology, Software, Formal analysis, Data curation, Writing - original draft, Writing review & editing, Visualization, Supervision, Project administration. Joanna Dudczak-Hałabuda: Investigation. Yu Tachibana: Writing - review & editing. Ryszard Cierpiszewski: Supervision, Project administration. Acknowledgements This research did not receive a specific grant from any a funding agency in the public, commercial or not-for-profit sectors. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.chemosphere.2019.125744. References Ahalya, N., Kanamadi, R.D., Ramachandra, T.V., 2006. Biosorption of iron(III) from aqueous solutions using the husk of Cicer arientinum. Indian J. Chem. Technol. 13, 122e127. Akmil-Basar, C., Onal, Y., Kilicer, T., Eren, D., 2005. Adsorptions of high concentration malachite green by two activated carbons having different porous structures. J. Hazard Mater. 127, 73e80. Al-Anber, Z.A., Al-Anber, M.A.S., 2008. Thermodynamics and kinetic studies of iron(III) adsorption by olive cake in a batch system. J. Mex. Chem. Soc. 52, 108e115. Al-Ghouti, M.A., Khraisheh, M.A.M., Allen, S.J., Ahmad, M.N., 2003. The removal of dyes from textile wastewater: a study of the physical characteristics and

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