**Application Research of Biochar for the Remediation of Soil Heavy Metals Contamination: A Review**

**Sheng Cheng 1,2,**† **, Tao Chen 1,2,\* ,**† **, Wenbin Xu <sup>3</sup> , Jian Huang 1,2, Shaojun Jiang 1,2 and Bo Yan 1,2**


Academic Editors: Chiara Bisio and Monica Pica Received: 16 June 2020; Accepted: 8 July 2020; Published: 10 July 2020

**Abstract:** Soil contamination by heavy metals threatens the quality of agricultural products and human health, so it is necessary to choose certain economic and effective remediation techniques to control the continuous deterioration of land quality. This paper is intended to present an overview on the application of biochar as an addition to the remediation of heavy-metal-contaminated soil, in terms of its preparation technologies and performance characteristics, remediation mechanisms and effects, and impacts on heavy metal bioavailability. Biochar is a carbon-neutral or carbon-negative product produced by the thermochemical transformation of plant- and animal-based biomass. Biochar shows numerous advantages in increasing soil pH value and organic carbon content, improving soil water-holding capacity, reducing the available fraction of heavy metals, increasing agricultural crop yield and inhibiting the uptake and accumulation of heavy metals. Different conditions, such as biomass type, pyrolysis temperature, heating rate and residence time are the pivotal factors governing the performance characteristics of biochar. Affected by the pH value and dissolved organic carbon and ash content of biochar, the interaction mechanisms between biochar and heavy metals mainly includes complexation, reduction, cation exchange, electrostatic attraction and precipitation. Finally, the potential risks of in-situ remediation strategy of biochar are expounded upon, which provides the directions for future research to ensure the safe production and sustainable utilization of biochar.

**Keywords:** biochar; pyrolysis; heavy metals; soil remediation; bioavailability

#### **1. Introduction**

Soil is the final destination of heavy metals (HMs) whether they are from natural or anthropogenic sources. Mineral resource exploiting and smelting [1], metal electroplating [2], paint and coating processing [3], electronic equipment manufacturing [4], farmland sewage irrigating [5] and pesticide and chemical fertilizer nonstandard applying [6] are the primary anthropogenic activities that aggravate HMs contamination in soil. For instance, more than 30,000 tons of chromium and 800,000 tons of lead have been released into the environment globally in the past half century, most of which eventually accumulates in soils [7]. It is reported that approximately one-sixth of the total agricultural land area in China and about 600,000 hectares of brown field sites in America have been contaminated by HMs [8]. Hitherto, cadmium, lead and arsenic pollution, and associated ecological health risks in southeast China, are more severe than those in northwest China; similarly, those in industrial regions are worse

than those in agricultural regions [7]. According to the results of a national soil survey [9] in 2014, the over-standard rates of cadmium, mercury, arsenic, copper, lead, chromium, zinc and nickel in soils of China are 7.0%, 1.6%, 2.7%, 2.1%, 1.5%, 1.1%, 0.9% and 4.8%, respectively. Soil HMs enter the food chain mainly through agricultural crops [10] and ultimately accumulate in organisms through diet, respiratory inhalation, skin contact and other exposure pathways, which directly or indirectly cause serious negative effects on human health [11,12]. The occurrence of cancer villages caused by HMs are the most immediate warning. Soil degradation and reduction of agricultural production land caused by HMs pollution brings an urgent need for the application of various efficient in-situ and ex-situ remediation techniques, to lessen the ecological risk of HMs and maximize the quality and security of agricultural land.

Over recent years, physical remediation (washing, thermal desorption, solidification and guest land methods), chemical remediation (vitrification, leaching, immobilization and electrokinetic methods), and biological remediation (microorganisms and plants) approaches have been applied to achieve this objective [13]. Nevertheless, these methods more or less exist with respective limitations i.e., complicated technique, inefficiency, poor feasibility, short duration, high economic cost, high secondary risk and so on [14]. At present, applying amendments to HM-contaminated soil is considered to be one of the most promising in-situ remediation techniques [15]. The frequently used soil additions include phosphate compounds, liming materials, clay minerals, coal fly ash, organic composts, metal oxides, and biochar [16,17]. In brief, the immobilization process of HMs can be achieved mainly through adsorption, complexation, reduction, and precipitation reactions, which cause the redistribution of HMs from soil liquid phases to solid phases, so as to reduce their mobility and bioavailability [16].

Biochar is a kind of carbon-rich, porous substance with abundant active organic functional groups and carbon aromatic structures with a neutral to alkaline pH value, relatively high cation exchange capacity, large specific surface area, and negative surface charge [18,19]. Numerous researchers report that the seed germination [20], plant growth [21–23], crop yields [23,24], and microbial activity and population [22,25,26] have been significantly increased in the HM-contaminated soil amended with biochars. Meanwhile, the effects of biochar on the immobilization/mobilization for different kinds of HMs have been confirmed in many pot experiments and field trials [21,27–29]. Furthermore, the production process of biochar is regarded as an efficient management method to dispose of a large number of organic wastes, which shows certain advantages in economic benefits and feasibility aspects. Remarkably, it cannot be completely ignored that there are still some potential risks in the field application of biochar, and these potential threats may hamper its further application. On this basis, the following aspects of biochar are reviewed: 1) preparation technologies, performance characteristics and influencing factors; 2) interaction mechanisms with different kinds of HMs; 3) effects on plant growth and HM bioavailability; and 4) potential risks in field engineering applications. In addition, the promotion and application of biochar in the future are also discussed.

#### **2. Preparation of Biochar**

The feedstock for biochar preparation mainly includes wood chips/branches [30–32], agricultural residues [21,33,34] and other woody biomass, as well as animal manure [35–38], sewage sludge [39–41] and other organic wastes. As shown in Table 1, thermochemical conversion technologies involved in the preparation process usually include fast pyrolysis, intermediate pyrolysis, slow pyrolysis, gasification, hydrothermal carbonization, torrefaction, etc. [42,43]. These technologies are mainly classified based on different heating rates, peak temperatures, residence times, reaction atmospheres and other parameters, where biochar, bio-oil and syngas are the main products. The yield of biochar is seriously affected by different operating conditions; several common thermochemical conversion technologies and their approximate product yields are discussed in Table 1.


**Table 1.**The reaction conditions and product distribution of various thermochemical conversion technologies.

Fast pyrolysis can be defined as the thermochemical decomposition process of biomass with low energy density at a moderate pyrolysis temperature in the presence of little or no oxygen. Due to the characteristics of higher heating rate (>200 K min–1) and shorter residence time (<2 s) in this process, bio-oil with high energy density, syngas with relatively low energy density and a small amount of biochar can be obtained (Table 1) [52]. On the contrary, slow pyrolysis is the common type of pyrolysis which is conducive to the formation of biochar rather than the generation of liquid and gaseous products. In this process, the biomass is pyrolyzed in a wide range of carbonization temperature with a heating rate of about 0.1~1 °C s –1 for a residence time between few hours and even days [52]. During slow pyrolysis, the fixed carbon content of biochar may increase with the rise of peak temperature, which is particularly prominent in the range of 400~500 ◦C [44]. The operating conditions of intermediate pyrolysis are between fast pyrolysis and slow pyrolysis, which better balances the distribution of solid–liquid product yield. The biochar produced by this pyrolysis mode has a brittle structure and does not contain a high quantity of reactive tar, which is suitable for the application of solid fuel, soil amendments and fertilizer [46].

Gasification is a process of direct contact oxidation of dry biomass with air, steam, oxygen, nitrogen, carbon dioxide or a mixture of these gases [43]. The primary product of gasification is a combustible gas which is packed with H2, CO and CH4, while the biochar with low yield contains a high amount of toxic substances such as polyaromatic hydrocarbons, and alkali and alkaline earth metals, that are attributed to the result of high-temperature reactions [51]. Hydrothermal carbonization is performed under a given pressure (2~6 MPa) and temperature (180~300 ◦C) that the feedstocks do not require for drying pretreatment, which is usually some wet biomass or dry biomass mixed with water. Compared to the pyrolysis and gasification processes, hydrothermal carbonization biochar (hydrochar) shows several advantages [51,53]. For instance, the hydrochar is characterized by high yield and high purity, and possesses a higher degree of aromatization and more surface functional groups. In addition, hydrochar contains a lower alkali and alkaline earth and heavy metal content, and a higher carbon content and heating value. Torrefaction, also referred to as mild pyrolysis, results in approximately 30% mass loss of biomass. The main products of torrefaction are organic carbon compounds with high specific energy density, but these cannot be referred to as a "biochar", because torrefaction is just the previous section of the pyrolysis process [43,51]. Consequently, the physicochemical properties of the torrefaction product is between that of biochar and biomass, and it also remains some volatile organic compounds.

Pyrolysis is a conventional process for the preparation of biochar. In this review paper, the properties of pyrolyzed biochar are preliminarily discussed, and the close connection between biochar performance characteristics and biomass feedstock species, pyrolysis temperature and residence time are clarified. According to the above factors (different preparation conditions), the performance characteristics of biochar are reviewed in detail in the next chapter, which provides a theoretical foundation for explaining the interaction mechanisms between biochar and soil HMs.

#### **3. Performance Characteristics of Biochar**

#### *3.1. Elemental Composition*

Element composition and content of biochar are a function of biomass species and pyrolysis temperature [54]. Generally, the content of total N, P, K, Ca, Mg and other nutrient elements in biochar prepared from poultry manure is higher than that of woody biomass, while the content of total C is the opposite [55]. Meanwhile, poultry manure is rich in mineral elements like K and P, which are important for plant growth, and thus the poultry-manure-derived biochar may be suitable as an ideal soil amendment instead of fertilizer [56].

The rise in pyrolysis temperature of biomass commonly results in the increase of ash and C content of biochar [50,57]. The N content of lignocellulosic type biochar increased slightly with the rise of pyrolysis temperature [58,59], while that of animal-manure- and sewage-sludge-derived

biochar shows a downward trend [35,60–62]. Furthermore, the pyrolysis conditions of biomass such as a higher temperature and longer residence time are beneficial to the accumulation of total P and K [50,63], the release of Ca, Mg and Si, and the retention of Fe, Mn and S [47]. Correspondingly, with the increase in reaction time and temperature, other unstable substances (containing H and O elements) of biomass are removed by deoxygenation, dehydration and decarboxylation reactions progressively, which leads to the loss of volatile organic compounds and the reduction of H/C–O/C ratio [51,57,64,65]. These results indicate that the high-temperature biochar more easily forms a very stable crystal graphite-like structure and possesses a higher carbonization degree and more aromatic structures [66–68]. For example, Jindo et al. [66] reported that the O/C ratio of biochar pyrolyzed in the temperature range of 400~500 ◦C changed according to the following order: rice straw > rice husk > wood chips of apple tree > wood chips of oak tree. Therefore, these results indicate that there is a higher content of lignin and a slower mineralization rate in woody biomass (i.e., apple tree, oak tree), compared with herbaceous biochar (i.e., rice straw, rice husk) and sewage sludge biochar; furthermore, it has a lower O/C ratio, making woody biochar's structure more stable [67].

#### *3.2. Functional Groups Abundance*

As mentioned in Section 3.1, a high pyrolysis temperature commonly results in the decrease of the H/C, O/C and N/C ratios in biochar, which immediately indicates the decrease of its abundance of hydroxyl, carboxylic and amino functional groups [18]. Chen et al. [57] summarized the variation of FTIR characterization of pine wood shaving derived biochar with pyrolysis temperature: 1) for 150 ◦C, biochar is rich in -OH groups, CH<sup>2</sup> units, C=O, C=C, aromatic CO-, and phenolic-OH; 2) for 250 ◦C, C=O and C=C stretching vibrations were enhanced; 3) for 350 ◦C, the band CH<sup>2</sup> units disappeared completely, and aromatic ring and C=C stretching vibration of lignin strengthened; 4) for 500 ◦C, C=O and C=C stretching vibrations were significantly weakened; 5) for 700 ◦C, merely C=C of lignin and aromatic C-H vibrations were spotted. During the whole heating process, the band C-O-C of cellulose and hemicellulose reduced with the rise of pyrolysis temperature, until it disappeared. Hence, these results show that hemicellulose with short side chains, thermally stable cellulose, and lignin with phenolic structures contained in lignocellulosic are generally decomposed at 200~350 ◦C, 305~375 ◦C and 250~500 ◦C, respectively [69]. In addition, Ding et al. [70] indicated that compared with 250 ◦C pyrolyzed sugarcane-derived biochar, C≡C and C=O in 500 ◦C pyrolyzed biochar were relatively reduced, while C-O completely disappeared.

Moreover, the abundant surface functional groups such as C-O, C=O, -COOH and -OH in biochar possess high modifiability, which is the foundation for the preparation of various functionalized carbon materials [52]. For instance, Yang et al. [71] incubated walnut-shell-derived biochar with Al, Ca, Fe minerals or kaolinite, and the modified biochar's relative content of C-C, C=C and C-H increased from 63.8% to 72.5~81.8%, while C-O, C=O, and -COOH decreased from 36.3% to 16.6~26.5%. This result means that the interaction between biochar and minerals (Al, Ca, Fe, or kaolinite) has prevented the oxidation of C-C, C=C, C-H into C-O, C=O or -COOH, which enhanced the oxidation resistance of biochar surface. This is related to the modification process of biochar, which has been reviewed by previous scholars in the following papers [18,31,72], and will not be further analyzed in this paper.

#### *3.3. Cation Exchange Capacity (CEC) and Specific Surface Area (SSA)*

With the pyrolysis processes conducting, the SSA (specific surface area) value of biochar has significantly increased compared to the feedstock, while the relatively low temperature pyrolyzed biochar has the highest CEC (cation exchange capacity) value [73]. Although high-temperature biochar cannot possess the highest CEC and SSA values simultaneously, there are adequate functional groups remaining in the biochar structures to provide negative charges. The low O/C atomic ratio of high-temperature biochar results in a decrease in the CEC value, which is mainly manifested by the reduction of volatile organic compounds and acidic functional groups [74]. In other words, the high SSA and pH value of biochar pyrolyzed at higher temperatures (>600 ◦C) may compensate for

the low CEC value to supply greater CEC provision to soil [54]. Thereby, biochar is a combination of charged surface functional groups and specific surface area, which can combine with HMs by adsorption and complexation reactions. For example, Yuan et al. [75] raised the pyrolysis temperature of sewage sludge from 300 ◦C to 700 ◦C, and found that the O/C ratio of biochar decreased from 0.33 to 0.05 and the volatile matter content reduced from 27.4% to 5.5%, but the SSA value increased from 14.37 m<sup>2</sup> g −1 to 26.70 m<sup>2</sup> g −1 . Similarly, Heitkötter et al. [76] used corn digestate (derived from maize silage) as feedstock, as the temperature increased from 400 ◦C to 600 ◦C, the CEC value decreased by 29.9%, but the SSA value increased by 50.7% which exactly made up for the deficiencies in the CEC value reduction. The cation exchange capacity of biochar was enhanced by the tendency of attracting positive charges through its surface functional groups, which is an important feature for the remediation of HM-contaminated soil [77]. Furthermore, the porosity and pore size of biochar still depend on pyrolysis temperature, because the release of volatile organic compounds at higher pyrolysis temperatures may promote the formation of micropores.

#### *3.4. pH Value*

The pH value of biochar is mostly alkaline, and normally increases with the rise of pyrolysis temperature, which means biochar possesses the abilities to improve soil pH and CEC value, and to reduce soil acidity and bioavailability of certain HMs [78–80]. Fidel et al. [81] summarized four broad categories of biochar alkalinity, including: (1) surface organic functional groups; (2) soluble organic compounds; (3) carbonates/bicarbonates; and (4) other inorganic alkalis such as oxides, hydroxides, sulfates, sulfides, and orthophosphates. Surface organic functional groups have a long-term effect on the amelioration of soil properties (e.g., pH and CEC value), while soluble organic and inorganic alkalis contribute to the short-term improvement of soil acidification [54,81]. The functional groups separated from the pyrolysis of biomass are predominantly acidic in essence, such as the carboxyl group, hydroxyl group, or formyl group [73]. For others, the alkalinity of remaining solid (includes ash) raised with the increase number of functional groups released by biomass, therefore, the increase of pH value of biochar is the direct result of the increasing degree of carbonization [73]. The carbonates formed by mineral elements were considered to be the primary alkaline substances in biochar, and especially the biochar pyrolyzed at high temperatures possesses a higher content of carbonates a stronger buffer capacity [80]. Shen et al. [34] reported that the pH value (7.94) of rice-straw-derived biochar pyrolyzed at 300 ◦C is alkalescence, while the biochars with higher pH values (10.40 and 10.68) can be obtained at higher pyrolysis temperatures (500 ◦C and 700 ◦C). The results are attributed to the decomposition of acidic functional groups such as the carboxyl group and phenolic hydroxyl group, and the formation of alkaline minerals like K2O in high-temperature pyrolyzed biochar. In addition, there is a high ash content in poultry manure and algae biomass, so the pH value of biochar pyrolyzed at the same temperature is higher than that of other woody biochar [82]. However, in some studies, the biochar produced by hydrothermal carbonization is typically acidic [83]. For example, the pH value of *Miscanthus*-derived hydrochar prepared by Gronwald et al. [84] at 200 ◦C is 3.8, and Cui et al. [85] found that the pH values of *Hydrocotyle verticillata*-, *Myriophyllum spicatum*- and *Canna indica*-derived hydrochar (200 ◦C) are 5.07, 4.97 and 6.48. Liu et al. [86] adjusted the pH value of the initial solution (pH = 2, 3, 5, 7, 9, 11, 12) of the hydrothermal carbonization process, so that the pH value of the prepared sewage-sludge-derived hydrochar was still weakly acidic or neutral (corresponding pH = 5.05, 6.11, 7.24, 6.60, 6.62, 6.74, 6.94). The presence of carboxyl functional groups on the surface of hydrochar as a result of formation of acetic and formic acids during the hydrothermal carbonization process could be the reason for the low pH value [87].

#### **4. Remediation of Soil HMs Contamination by Biochar**

#### *4.1. Interaction Mechanisms of Biochar and HMs in Soil*

The different sources of biomass feedstocks, and the diverse pyrolysis conditions applied in the preparation processes, lead to various biochar performance characteristics, which may in turn affect the interaction mechanisms between biochar and HMs. On the other hand, the greatest concerns of HMs have been focused on copper, arsenic, cadmium, lead, mercury, and chromium. Table 2 summarizes the research progress on biochar applications for the remediation of HM-contaminated soil, which included different types of biochar, different application conditions, and different HM treatment efficiencies. The various mechanisms proposed for the interaction of biochar with HMs are summarized in Figure 1. It shows that the abundant surface functional groups, mineral substances, alkaline metal ions, π-electrons, organic matters, and pore structures of micropores provided by biochar are the effective binding sites of HMs. Biochar is able to absorb or combine soil HMs through complexation, reduction, cation exchange, electrostatic attraction, and precipitation functions, or convert HMs from inorganic states into organic states, which changes HM mobility and bioavailability [14,88,89], and then improves soil agronomic benefits. Therefore, the interaction mechanisms between biochar and HMs are critical for the soil remediation and are discussed in detail in the following sections.

**Figure 1.** Interaction mechanism between biochar particles and HMs in soil.


**Table 2.**Remediation efficiency of biochar on HM (heavy metal)-contaminated soil.


**Table 2.** *Cont*.

aUnits explanation: d for days, w for weeks, m for months and y for years.

#### 4.1.1. Copper (Cu)

As described by Meier et al. [36], the functional groups (especially for -OH) and negative ζ-potential existing in chicken-manure-derived biochar has been proved with high affinity for Cu. The immobilization process of Cu is achieved by increasing soil pH value and inducing the liming effect, to stimulate the complexation of Cu(II) with biochar surface functional groups (e.g., C=O and phenolic-OH). Additionally, Rechberger et al. [30] found that carbonates and hydroxides in the ash of woodchip-derived biochar are the important adsorbents for Cu(II), which are able to promote the formation of CuCO<sup>3</sup> and Cu(OH)2, and this is also illustrated by the bamboo-derived biochar prepared by Zhang et al. [93]. Therefore, the essential point of Cu immobilization is to use the alkalinity of biochar to improve soil pH value [92]. On the other side of the shield, the mobility of Cu is highly affected by the content of soil-dissolved organic carbon (DOC). For instance, Park et al. [91] introduced chicken-manure-derived biochar to Cu-spiked soil, which led to the increase of soil DOC content and provoked the conversion of Cu(II) into Cu complexes with higher solubility. Wagner et al. [106] also reported that the *Miscanthus*-derived biochar can increase the Cu concentration in soil solution. In other words, the increase of Cu concentration in soil pore water is the proximate consequence of the Cu(II) desorption from soil with the form of organic complex. Hence, the immobilization/mobilization of Cu by biochar should be further studied according to the actual types of biochar.

#### 4.1.2. Arsenic (As)

Phosphorus (P) and As have similar chemical properties and the soil P content is a critical factor in controlling the mobility of As [25]. There is a significant positive correlation between phosphate content and arsenate content in As-contaminated soils. After the soils are treated with P-containing biochar, the competition between soluble phosphate and arsenate that occurred on the adsorption sites of soil particles promoted the desorption of As from soil solid phase, and increased the As concentration in pore water [45], such as soybean-stover-, pine-needle- [25], and rice-straw-derived biochar [94]. The role of soil DOC is similar to P [95], but DOC has another effect. For example, Wang et al. [26] indicated that the application of rice-straw-derived biochar under the anaerobic conditions increased the abundance of Fe-reducing bacteria (e.g., *Clostridum*, *Bacillus* and *Caloramator*) in paddy soil, promoted the reduction of As(V) adsorbed on the amorphous Fe/Al oxides. To be brief, the increase of DOC content in soils enhanced the microbial reduction effect of As(V), and finally stimulated the release of As (III) from paddy soil. Under the anoxic conditions, similar results were obtained in the application of oil palm fiber derived biochar prepared by Qiao et al. [96]. Biochar, with high aromaticity and alkalinity, and which can act as an electron shuttle, likes humus to promote the microbial reduction of Fe(III) and As(V) simultaneously [26,96]. In addition, Choppala et al. [27] reported that the π-electrons provided by the functional groups on the surface of chicken-manure-derived biochar could promote the reduction of As(V), which is another important factor to enhance the mobility of As. However, the Fe-biochar prepared by Yin et al. [94] and Mn-biochar prepared by Yu et al. [23] are able to adsorb As to the Fe/Mn oxides of biochar surface, thus commendably limiting the migration of As into soil solution, which proved the effectiveness of As immobilization by the modified biochar (not listed in Table 2).

#### 4.1.3. Cadmium (Cd)

The activity of Cd in soils strongly depends on soil pH value [99]. The alkaline substances such as CO<sup>3</sup> <sup>2</sup>−, PO<sup>4</sup> <sup>3</sup><sup>−</sup> and OH<sup>−</sup> contained in biochar commonly have strong adsorption and binding capacity to Cd in soils, which makes the free Cd(II) transform into Cd(OH)2, Cd3(PO4)<sup>2</sup> and CdCO<sup>3</sup> precipitates [30]. The high adsorption affinity produced by the cation exchange effects of soil calcite (CaCO3) with Cd(II) is the main factor to reduce the bioavailability of Cd; of course, the abundant functional groups and large specific surface area in biochar are also critical for Cd immobilization [29]. For instance, Yin et al. [94] used 1~2% rice-straw-derived biochar to treat farmland soil in a mining

area, and found that the Cd concentration in pore water of soil rhizosphere was significantly reduced, and the corn-straw-derived biochar prepared by Gao et al. [99] decreased 91% of the CaCl2-extractable Cd content in the farmland soil. Besides, Bian et al. [98] applied 40 t ha−<sup>1</sup> wheat-straw-derived biochar to paddy soil, and the CaCl2-extractable Cd and DTPA-extractable Cd was reduced by 59% and 24%, respectively, over the past three years. Thereby, the result of biochar in increasing soil pH value is extremely effective for the immobilization of Cd. It is worth mentioning that the basic substances in biochar can also stimulate the deprotonation of acid functional groups of biochar, and further enhance the adsorption capacity of Cd [107].

#### 4.1.4. Lead (Pb)

The immobilization process of Pb in soils by biochar is relatively simple. For example, Ahmad et al. [25] considered that the immobilization process of Pb stimulated by soybean-stover -derived biochar is attributed to the π-cation electron donor–acceptor interaction, which occurs by the π-electron-rich biochar graphene surface and π-electron-deficient positively charged Pb(II) ion. Furthermore, the cation exchange and precipitation reactions between basic substances (CO<sup>3</sup> 2−, OH<sup>−</sup> and other alkaline earth Ca2+, Mg2+) in biochar and Pb(II) are able to achieve a significant immobilization effect of Pb, such as the formation of Pb3(CO3)2(OH)<sup>2</sup> precipitation. In particular, the poultry-manure-derived biochar [38] and the sewage-sludge-derived biochar [39] contain abundant phosphates, which are able to form insoluble compounds, such as Pb5(PO4)3Cl, Pb5(PO4)3OH and β-Pb9(PO4)6, with Pb(II) to reduce the mobility of Pb [25,101]. The functional groups also have certain effects on the immobilization of Pb. Igalavithana et al. [100] reported that the vegetable-waste-derived biochar not only improved soil pH value, but also promoted the immobilization of Pb by the strong covalent bonding action of N-containing functional groups (especially for -NH2) on the biochar surface, thereby effectively decreasing the concentration of NH4OAc-extractable Pb.

#### 4.1.5. Mercury (Hg)

Hg, as a special metal, has great toxicity in soil, but biochar is an effective tool for soil remediation. As Wang et al. [31] remarked, the carboxyl group in a hardwood-derived biochar surface and soil Hg(II) ion develop a coordination reaction generating a complex of -COOHg<sup>+</sup> precipitate, thereby reducing the mobility of Hg and the thiol functionalities and sulfoxide groups are also able to react with Hg(II) ion to form -S(Hg)- and [Hg(OSR2)<sup>6</sup> <sup>2</sup>+] precipitates. Additionally, Xing et al. [28] found that rice-husk-derived biochar possesses a higher sulfate concentration compared with wheat-straw-derived biochar, which is more effective to promote the mercury–sulfur coordination reaction and to produce sulfides precipitation. It is extremely important to know that methylation of Hg is a special environmental biogeochemical behavior, and once the inorganic-Hg in soils is converted into methylmercury (MeHg), its toxicity and bioaccumulation will be enormously enhanced [108]. The release of rice root exudates reduced soil pH value, thereby enhancing the methylation of Hg, while the application of alkaline biochar increases soil pH value and effectively inhibits methylation. Zhang et al. [41] reported that sewage-sludge-derived biochar with high organic matter content can stimulate the growth and activity of heterotrophic microorganisms in Hg-contaminated acidic farmland soil, thus promoting the formation of MeHg. However, the utilization rate of MeHg in rice has been significantly decreased, which led to the inhibition of MeHg accumulation in rice and effectively reduced the bioavailability of organic-Hg [41].

#### 4.1.6. Chromium (Cr)

Firstly, it should be pointed out that Cr exists in soils in the form of two valence states, namely Cr(VI) and Cr(III). Therefore, the immobilization of Cr in soils is a complicated combination process of adsorption–reduction–precipitation. The interaction mechanism between biochar and Cr is mainly manifested in the surface adsorption effect of Cr(VI) by the oxygen-containing functional groups such as C-O, C=O, -COOH and -OH in biochar, as well as the reduction reaction of electrons provided by biochar [105]. Specifically, biochar transforms Cr(VI) into Cr(III) with lower toxicity and solubility by adsorption–reduction effects, and participates in the formation of Cr2O<sup>3</sup> and/or Cr(OH)<sup>3</sup> precipitation, so as to achieve the purpose of Cr immobilization [109,110]. On the other hand, Choppala et al. [27] applied chicken-manure-derived biochar to Cr-spiked soil with low organic matter content, which significantly increased the supply of soil organic carbon and nutrients, enhancing the soil respiration and microbial activity effectively and finally showing a superior microbial Cr(VI) reduction effect and reduced the Cr biotoxicity. Moreover, Mandal et al. [111] found that the Cr(VI) reduction effect of animal-manure-derived biochar in acidic soil was significantly higher than that in alkaline soil.

In summary, many HMs can be continuously immobilized in soil by biochar through specific or non-specific surface adsorption. It is noteworthy that not only the activity of Cu and As are affected by DOC content in soil, but also Pb and Cd. This phenomenon is attributed to the fact that the high-dose application of biochar in soil results in the sharp increase of DOC content, which leads to the complexation of Pb and Cd with DOC, and finally increases the mobility and bioavailability of Pb and Cd. In addition, the adsorption and cation exchange reactions between HMs and biochar ash (e.g., K+, Na+, Ca2+, Mg2<sup>+</sup> and other alkali metal ions) are also important factors for the immobilization of HMs.

#### *4.2. E*ff*ect of Biochar on Bioavailability of HMs in Soil*

Plants mainly absorb, transport, and accumulate HMs from contaminated soil by roots. Thus, the primary objectives of biochar soil remediation are limiting the migration and transformation rates of HMs in soil and reducing their bioavailability, so as to prevent HMs from entering organisms through the food chain and to eliminate their toxic effects. The ultimate goal of HM-contaminated soils remediation is to increase crop yields on the premise of ensuring food production safety.

On the one hand, the introduction of biochar provides a source of organic matter, N, P, K, Ca, Mg and other nutrients to the soil, which enhances soil enzyme and microbial activities. On the other hand, the plant root environment, soil water retention and saturated hydraulic conductivity [112] can be improved with the presence of biochar, and plant growth and nutrient absorption can be promoted. Finally, it increases the plants biomass, and dilutes the content of HMs in plant tissues to reduce their phytotoxicity. Meier et al. [36] indicated that 5% chicken-manure-derived biochar can reduce the uptake of Cu from 66.9 mg kg−<sup>1</sup> to 36.6 mg kg−<sup>1</sup> in the aboveground part of *Oenothera picensis* plants in copper-mine-polluted soil, and increase the biomass of shoots and roots by 3.5 times and 3.1 times respectively. Xing et al. [28] reported that after applying 24 t ha−<sup>1</sup> and 72 t ha−<sup>1</sup> rice-husk-derived biochar to mercury-contaminated farmland soils, the Hg content in rice grains reduced to 10 ng g−<sup>1</sup> and 7.2 ng g−<sup>1</sup> , which significantly inhibited the transportation of Hg from soil to rice grains, and successfully reached the national standard (below 20 ng g−<sup>1</sup> ). Similarly, Li et al. [97] applied 3% of soybean-straw-derived biochar (hydrothermal carbon at 350°C) to the arsenic and cadmium co-contaminated farmland soil, which reduced the bioaccumulation of As in rice plants by 88%. Besides, compared with the control group, As(III) content decreased from 3.47 mg kg−<sup>1</sup> to 0.29 mg kg−<sup>1</sup> , As(V) decreased from 715 µg kg−<sup>1</sup> to 150 µg kg−<sup>1</sup> , and the treatment effects on Cd were similar [97]. As for cadmium, a field trial studied by Zheng et al. [113] showed that, when the application rates of soybean-straw-derived biochar and rice-straw-derived biochar were 20 t ha−<sup>1</sup> , the content of Cd in rice roots, rice shoots, rice husks and rice grains decreased by 25.0~44.1% and 19.9~44.2%, and 46.2%~70.6% and 25.8%~70.9%, respectively. Furthermore, the effectiveness of rice-straw-derived biochar in reducing Cd accumulation in rice grains was also confirmed in the long-term field effects studied by Zhang et al. [29]. Cd contamination of farmland soil is particularly prominent in China, but it happens that China is a large agricultural country, which has a large output of agricultural waste with low cost. Considering the economic value of biochar application, using rice straw, wheat straw and other agricultural wastes to produce biochar and returning it to the field is the best choice.

In a word, the immobilization effects of soil HMs, the limitation of HM uptake and accumulation by plants, the enhancement of plant biomass, and the dilution effect of HMs in plant tissues are the four pivotal performances of biochar to reduce the bioavailability of HMs [114,115]. Although certain HMs can be combined with soil DOC and converted into organic complex forms, which are activated finally, these organic complexes commonly possess stability and are not readily or directly absorbed by plants, which has little impact on HM content in plant tissues.

#### **5. Potential Risks**

Applying biochar as an addition to soil in-situ remediation should not only consider the HM immobilization/mobilization effects, but also take into account the long-term stability and potential ecological risks of biochar, which similarly depend on the type and performance characteristics of biochar. Figure 2 briefly introduced the advantages and disadvantages of biochar in the remediation of soil HM contamination. Firstly, it is reported that biochar may be the carrier of HMs [116], volatile organic compounds (VOCs) [117], dioxin (PCDD/Fs) and polycyclic aromatic hydrocarbons (PAHs) [118,119] and other toxic substances, and the demands for remediation of HM contamination in soil varies from 1.5 to 72 t ha−<sup>1</sup> or even higher [24,28,98,113]. Therefore, the toxic substances may be released into the soil/air/water environment with the application of the double-edged biochar, which will pose a secondary pollution and ecological risk. So far, from the perspective of soil, biochar plays an important role in the carbon utilization and non-CO<sup>2</sup> greenhouse gases emission reduction [104]. However, the research on increasing greenhouse gas emissions by biochar has also been reported, i.e., under specific conditions, the application of biochar can promote the emissions of CO<sup>2</sup> [120], N2O [121], CH<sup>4</sup> [122] to a certain extent. For example, although biochar can reduce CH<sup>4</sup> emissions, it may also promote N2O emissions, and vice versa, and this depends on the diversity of biochar application conditions. Therefore, the emission reduction effect of biochar cannot be reflected in all types of greenhouse gases, and blind application may cause negative effects, so the biochar–greenhouse gas interaction should be considered in the field application of biochar. Meanwhile, other research has indicated that biochar can inhibit the efficacy of soil pesticides and their biodegradation effects [123], which makes the ability of agricultural weeding and insecticides unable to achieve the expected effects. The residue of pesticides may be related to the strong adsorption and binding capacity of biochar. Furthermore, although biochar can improve the biological activity of bacteria (e.g., *Geobacter*, *Anaeromyxobacter* and *Clostridium*) [26,96], it may bring about a negative impact on the survival, growth and diversity of, for example, acidophilic earthworm and fungi biological communities [124,125].

**Figure 2.** Advantages and disadvantages of biochar in the remediation of soil HM contamination.

#### **6. Summary and Future Perspectives**

It is a feasible strategy of green, economic and environmental protection to apply biochar to remediate the HM-contaminated soil. Several thermochemical conversion technologies have been used to prepare biochar, and the performance characteristics of biochar are highly affected by the type of feedstock materials, pyrolysis temperature, and residence time. The immobilization or mobilization mechanisms of HMs includes complexation, reduction, cation exchange, electrostatic attraction and precipitation reactions. The HM uptake and accumulation of plants can be suppressed by biochar through the variation in soil pH value, DOC content, and other alkaline mineral substances content, and achieve the goal of promoting plant growth, reducing HM bioavailability and improving soil quality in unison.

Modern soil environmental management and remediation technologies are beginning to pay attention to the long-term stability of biochar and the ecological responses of contaminants with the most toxicological fractions. Consequently, in order to meet demand and application-based results, the future application of biochar is predicted as follows:

(1) It is expected that the secondary ecological risks in the process of biochar production will still need to be focused on, i.e., the formation of HMs, VOCs, PCDD/Fs and PAHs. These pollutants are essentially derived from biomass, so it is necessary to screen and pretreat raw biomass materials to remove HMs. In addition, we must adjust the pyrolysis temperature, residence time, pyrolysis atmosphere, pressure conditions and other process parameters to minimize the generation of associated pollutants. Furthermore, it is necessary to establish and perfect the regulatory systems related to the application of biochar in practical engineering.

(2) With the passage of time, soil components will occur varying degrees of physicochemical and biochemical changes, including the properties of biochar (aged biochar) in the meantime. Although the research on soil HM immobilization by biochar has developed to laboratory pot experiments and short-term field trials, the ultimate goal is to extend it to large-scale engineering applications. Hence, carrying out long-term positioning tests in different types of HM-contaminated soil must be conducted, so as to further verify the long-term stability of biochar and its long-term effects on soil environment (such as aggregation, surface potential and density magnitude), and lastly to ensure the quality and safety of agricultural land.

(3) Biochar cannot completely remediate the heavy metals contaminated soil. Therefore, in order to improve the remediation/improvement effects of multi-heavy metals contaminated soil, the multifunctional biochar materials (e.g., biochar inoculated with microorganisms and biochar modified by chemicals and minerals) should be gradually put on the stage of engineering application.

(4) The advantages and disadvantages between the economic cost (production) and benefit value (application) of biochar need to be carefully measured. In order to enhance economic availability, easier production processes and cheaper sources of raw biomass materials need to be discovered, which could provide a platform for improving production efficiency and reducing economic burdens, i.e., to achieve the purpose of commercial practicality.

**Author Contributions:** Conceptualization, S.C. and T.C.; methodology, S.C.; software, S.C.; validation, J.H.; W.X. and S.J.; formal analysis, W.X.; investigation, S.C.; resources, T.C.; data curation, S.C.; writing—original draft preparation, S.C.; writing—review and editing, T.C.; visualization, S.J.; supervision, T.C.; project administration, T.C. and B.Y.; funding acquisition, B.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was financially supported by the National key research and development plan (2018YFC1802800), the Guangdong provincial science and technology program (2015B020237003), the Provincial Science and Technology Plan Project of Guangdong Province, Shao Guan (2018SG00118), and the Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety (2019B030301008).

**Acknowledgments:** The authors are very grateful to the anonymous reviewers for their revising suggestions.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Review* **Recent Developments in Chitosan-Based Adsorbents for the Removal of Pollutants from Aqueous Environments**

**Daniele C. da Silva Alves 1,2 , Bronach Healy <sup>1</sup> , Luiz A. de Almeida Pinto <sup>2</sup> , Tito R. Sant'Anna Cadaval, Jr. <sup>2</sup> and Carmel B. Breslin 1,\***

	- dqmpinto@furg.br (L.A.d.A.P.); titoeq@gmail.com (T.R.S.C.J.)

**Abstract:** The quality of water is continuously under threat as increasing concentrations of pollutants escape into the aquatic environment. However, these issues can be alleviated by adsorbing pollutants onto adsorbents. Chitosan and its composites are attracting considerable interest as environmentally acceptable adsorbents and have the potential to remove many of these contaminants. In this review the development of chitosan-based adsorbents is described and discussed. Following a short introduction to the extraction of chitin from seafood wastes, followed by its conversion to chitosan, the properties of chitosan are described. Then, the emerging chitosan/carbon-based materials, including magnetic chitosan and chitosan combined with graphene oxide, carbon nanotubes, biochar, and activated carbon and also chitosan-silica composites are introduced. The applications of these materials in the removal of various heavy metal ions, including Cr(VI), Pb(II), Cd(II), Cu(II), and different cationic and anionic dyes, phenol and other organic molecules, such as antibiotics, are reviewed, compared and discussed. Adsorption isotherms and adsorption kinetics are then highlighted and followed by details on the mechanisms of adsorption and the role of the chitosan and the carbon or silica supports. Based on the reviewed papers, it is clear, that while some challenges remain, chitosan-based materials are emerging as promising adsorbents.

**Keywords:** chitosan; adsorbent; carbon; graphene oxide; silica; magnetic separation; dyes; heavy metals; adsorption; Langmuir isotherm

#### **1. Introduction**

Improving water quality is one of the major environmental challenges worldwide to be solved, since water resources are increasingly scarce due to population growth, climate change and increased demand for water in industrial and agricultural activities [1]. In addition, the inappropriate disposal of organic and inorganic contaminants combined with disinformation and neglect in the treatment of these compounds can result in irreversible damage to the aquatic environment and, consequently, to humans [2,3]. Dyes, phenolic compounds, metallic ions and micropollutants, such as pesticides and drugs, have all been detected in wastewaters, surface and even drinking water, indicating that the conventional methods used in treatment plants are not optimised for their removal [4]. Consequently, the removal of these pollutants with high toxicity, even when present at low concentrations, has been increasingly studied in the scientific world [5,6].

Several techniques have been developed based on hybrid systems [7], membrane filtration [8] and biological degradation [9] to reduce the content of pollutants in water. However, the slow response, sensitivity and high energy demand are some of the disadvantages of such techniques. In addition, they are not very efficient when the effluent has a low content of suspended colloidal particle and a high load of organic matter. A promising alternative to the treatments mentioned is adsorption, due to its simplicity of operation and

**Citation:** da Silva Alves, D.C.; Healy, B.; Pinto, L.A.d.A.; Cadaval, T.R.S., Jr.; Breslin, C.B. Recent Developments in Chitosan-Based Adsorbents for the Removal of Pollutants from Aqueous Environments. *Molecules* **2021**, *26*, 594. https://doi.org/10.3390/ molecules26030594

Academic Editors: Chiara Bisio and Monica Pica Received: 7 December 2020 Accepted: 21 January 2021 Published: 23 January 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

effectiveness [10]. Therefore, the search for new adsorbent materials that can be used to remedy aquatic contamination has been stimulated. The biopolymer chitosan is attracting considerable interest as a matrix for adsorbent material development, since this biopolymer has a high density of hydroxyl groups (–OH) and primary amines (–NH2) that act as active adsorption sites, making it an efficient adsorbent [11].

Chitosan (β–(1–4)–D–glucosamine) is a polysaccharide that possesses two types of monomers, one containing an acetamido group (2–acetamido–2–deoxy–β–D–glucopyranose residues), and another containing an amino group (2–amino–2–deoxy–β–D–glucopyranose residues). Chitosan is not available directly in the environment, it is obtained from chitin (β–(1–4)–*N*–acetyl–D–glucosamine), usually by the alkaline or enzymatic *N*-deacetylation of chitin [12–14]. The characteristic that differentiates the structure of chitin and chitosan is the substitution of the acetamide group at position 2. This directly influences the solubility properties of these compounds, with chitin being insoluble and inert, and chitosan soluble in weak acids [13,15].

Currently, chitin and chitosan are produced commercially in Japan, United States, India, Poland, Australia, and Norway, and to a lesser extent, in Canada, Italy, Chile and Brazil [16,17]. The annual production of chitin in nature has been estimated to be as high as 1 × 10<sup>10</sup> to 1 × 10<sup>12</sup> tonnes [18], which makes this biopolymer a cheap and available resource. However, as the biodegradation rate of chitin is slow, the production of high amounts through shrimp and seafood processing creates an environmental problem, and the conversion of this waste material into high-value products, such as chitosan, can be an attractive solution [19].

During the past few decades, many researchers have focused on the development of chitosan-based materials to solve problems in environmental and biomedical engineering fields, and in the development of innovative products for other different applications [20–22]. From 2010 to 2015, more than 15,000 articles and about 20 books on chitosan were published worldwide. This ever increasing interest is connected with the attractive properties of chitosan, such as biodegradability, low toxicity and biocompatibility, coupled with the availability of natural resources required for its chemical and enzymatic modifications for specific end uses [19,23]. Chitosan has been used in many fields such as food, medicine, cosmetics and wastewater treatment [24]. In addition, the efficient utilisation of marine biomass resources has become an environmental priority that leads to intensified research on chitosan production and its applications [25].

In this review, the applications of chitosan-based materials as adsorbents for the removal of pollutants from aqueous environments are reviewed. Although there are a number of review articles that describe the environmental applications of chitosan [19,24,26,27], in this review we focus initially on the sources, properties and chemical modifications of chitosan and discuss the various factors that influence its properties as a material for the removal of pollutants. Next, we review the support materials utilised and combined with chitosan, including the emerging carbon and silicon supports, providing a more comprehensive account than previously published.

#### **2. Chitosan**

Chitin is the second most abundant natural polysaccharide (biopolymer) on Earth, following cellulose [26]. In 1811, the first chitin was extracted by Henri Bracon from mushrooms and was named initially as "fungine". In 1823, Odier [28] found the same material in the insect exoskeleton and called it chitin. Later, chitin was found in crab shells, confirming that it can be found in the crustacean exoskeleton. In 1859, Charles Roughet discovered that chitin could be transformed into a water-soluble form after chemical modification [19]. In 1894, this chemically modified chitin was called chitosan by Hoppe-Seyler [29,30]. Although chitin was discovered 30 years before cellulose, most of the research was focused on cellulose, due to the high investments made by the textile industries. Thus, chitin and chitosan remained restricted only to basic research during this period. Around 1970, interest in natural products increased and investigations directed at

exploring the potential applications of chitosan began to attract considerable attention [13]. In 1977, the "1st International Conference on Chitin and Chitosan" was organised in Boston, USA, where the scientific and industrial communities leveraged the world's interest in these biopolymers [23].

#### *2.1. Source and Production*

Chitosan is derived from chitin, usually obtained from natural sources such as the residues of shrimp, crab and lobster, fungal mycelia and green algae [15,31,32]. This biopolymer can also be found in the exoskeletons of insects and fungal cell walls, as shown in Figure 1a. Chitin content in fungi varies between 19% and 42%, compared to the exoskeleton, where chitin can reach up to 75% [29,33]. Not all shellfish wastes are good sources of chitin. The blue crab (*Callinectes*) contains 14% of chitin, while oyster and clam shells have chitin content in the range of 4–6% [29,34]. Chitin content can vary with the proportion of minerals, proteins, and carotenoids, depending on the species, reproductive cycle phase, nutritional status, age, and also the peeling conditions during the processing [13,17]. Chitosan can be obtained by deacetylation of chitin through enzymatic or alkaline methods (Figure 1b). However, the enzymatic method has been limited only to the laboratory scale, while the alkaline method has been more widely used on an industrial scale, due to its short processing time, simplicity, and low operational costs [29].

**Figure 1.** (**a**) Examples of chitin content from different sources, (**b**) Chitin deacetylation methods to produce chitosan.

#### 2.1.1. Enzymatic Methods

The first step in the production of chitosan is the extraction of chitin from the seafood waste and this can be achieved using both biological and chemical approaches. The biological process involves the use of bacteria, that produce organic acids, and enzymes for the demineralisation and deproteinisation of crustacean shells [35]. In the demineralisation step, the lactic acid produced by bacteria reacts with the calcium carbonate component in the crustacean biomass waste resulting in the formation of calcium lactate, which can be precipitated and removed by washing, while proteases from the bacteria eliminate proteins [35]. *Bacillus cereus* A21 has shown high activity with both the demineralisation and deproteinisation steps from shrimp shell wastes, 91% and 80%, respectively [36]. Likewise, the deproteinisation and demineralisation from natural crab shell wastes by *Bacillus pumilus*A1 were 94% and 80%, respectively [37]. These results suggest that the chitin production process by the enzymatic method of the seafood wastes could be applicable and become a friendly environmental alternative.

The deacetylation step that gives rise to the production of chitosan can be promoted by chitin deacetylase. This enzyme was first found in *Mucorrouxii* (*Zygomycetes*) in 1974, by Araki and Ito [38]. In 1984, Davis and Bartnicki-Garcia found evidence that changes in the culture medium during the fungi growth phase can directly influence the production of chitosan [39]. The reaction mechanism of the chitin deacetylase from *Mucorrouxii* is considered as a multipoint attack mode; specifically, the enzyme systematically hydrolyses acetyls from the non-reducing end of the binding site after it binds to a substrate chain, and then leaves the substrate and binds to another one [40]. Strains that produce a large amount of extracellular deacetylase with high activity are very valuable in the production of chitin deacetylase and the production of chitosan. Nevertheless, there are still some problems such as low enzyme activity and low yields of deacetylase-producing strains. Moreover, natural chitins are crystals, not a good substrate for deacetylase. Hence, many preparations still need to be carried out before the chitin deacetylase method can be used in the industrial production of chitosan [41].

Chitin deacetylase-producing bacteria, such as *Serritia* sp. and *Bacillus*sp, may replace the current fungal strains. This microorganism culture method is another possibility to obtain chitosan, removing the acetyl groups by catalysing the substrate with the enzymes produced by these microorganisms. Moreover, bacteria grow faster than fungi in largescale fermentation processes. Recently, research has concentrated on the breeding of microorganism strains and optimisation of the culture medium. Chitosan formed by this method has shown good ion adsorption capacity [41], making it suitable for environmental applications.

#### 2.1.2. Alkaline Methods

The traditional chemical methods to extract chitin from crustacean shell wastes involve three steps: demineralisation, deproteinisation and decolourisation. In the first step, crustacean shells are washed, dried, and grounded to smaller sizes [42]. In order to remove mineral constituents, mainly calcium carbonate, the powdered raw material is treated with dilute hydrochloric acid followed by the precipitation of calcium chloride. Alkali treatment is used for deproteinisation of the demineralised shells. Proteins are eliminated through solubilising with dilute aqueous sodium hydroxide and in the process, N-acetyl groups within the polymer backbone are hydrolysed. The recovery of protein may be obtained by lowering the pH to about 4.0. An additional decolourisation step can be incorporated when a colourless product is required. Acetone or organic solvent mixtures are used to remove the pigments such as carotenoids [15].

Chitosan is obtained by deacetylation of chitin in 40–45% sodium hydroxide, as shown in the sketch of Figure 2. The alkaline treatments hydrolyse the acetyl groups and transform the *N*–acetyl–D–glucosamine units into D–glucosamine units with free NH<sup>2</sup> groups [15]. Chitosan, with different degrees of deacetylation, is generated depending on the reaction temperature, time, and concentration of the alkaline solution [43]. An additional purification step can be performed to obtain high purity chitosan. For this, the deacetylated product is dissolved in acid, centrifuged or filtered, and the chitosan is precipitated through the addition of alkali generating pure chitosan (90–95%) in paste form. These steps can be repeated to obtain higher purity chitosan (purity >99.9%) [15,23].

**Figure 2.** Process of obtaining chitosan by the deacetylation alkaline treatment of chitin from shrimp shell wastes.

The drying of chitosan is an important step in its production. In general, after drying, the desired product should contain a moisture content lower than 10% (wet basis), to ensure good physicochemical and microbiological aspects during prolonged storage. Polymerisation and Maillard reactions are the main alterations that should be avoided during the drying operation [44]. Chitosan is composed mainly of carbohydrate monomer units that, at high temperatures, are capable of undergoing caramelisation of the polymer. Therefore, in this process, one of the key parameters is temperature [45,46]. Different techniques have been used to obtain good quality dried chitosan, such as spouted bed drying [47], spray drying [48], convective tray drying [49], oven drying and infrared drying [50], lyophilization [51] and low-pressure superheated steam drying [52]. All these techniques have shown that the most important factors are temperature and residence time, which must be controlled to obtain a high-quality product. For example, Dotto et al. [47] have shown that an increase in the temperature (from 90 to 100 and 110 ◦C), using a spouted bed drying technique, causes an increase in powder darkening, an increase in molecular weight (from 147 to 25 kDa) and increased particle size (from 100 to 200 µm). Hence, the best powder quality was obtained at 90 ◦C, which resulted in the final humidity content being within the commercial range (10%).

#### *2.2. Structure and Properties*

μ β β β Chitosan, a partially deacetylated product of chitin, is a biopolymer composed of β– (1–4)–D–glucosamine, as shown in Figure 3. This biopolymer is a glycosaminoglycan and consists of two common sugars, β–(1–4)–2–acetamido–D–glucose and β–(1–4)–2–amino– D–glucose, glucosamine, and *N*–acetylglucosamin, respectively. The proportion of each depends on the alkaline treatment, and usually deviates from an equal contribution. In terms of structure, chitosan is analogous to cellulose, in which the hydroxyl (in cellulose) has been replaced by acetamido or amino groups (in chitosan) at carbon-2 [53]. Thus, unlike other polysaccharides abundant in carbon, oxygen, and hydrogen; chitin and chitosan contain additional nitrogen (6.89%), making them interesting commercially [54].

**Figure 3.** Chemical structure of chitin and chitosan.

The physicochemical properties of chitin and chitosan strongly depend on molecular chain orientation and regular packing. The abundance of hydroxyl groups and highly reactive amino groups in chitosan or its N-acetyl counterpart with a strong tendency for intra- and inter-molecular hydrogen bonding, results in the formation of linear aggregates and rigid crystalline domains. However, chitosan is usually less crystalline than chitin, which presumably makes chitosan more accessible to reagents and, consequently, more soluble. Most of the aqueous acids dissolve chitosan whereas chitin is soluble in very few solvents. The protonation of amino groups by acids along the chitosan chain creates a multitude of cationic sites, which increases its solubility by increasing the polarity. This unique property expands the potential applications of chitosan, including its ability to adsorb different pollutants. Amine groups, for example, are strongly attracted to metal ions due to the lone pair of electrons on the nitrogen atoms [55,56]. The protonation of these amine groups may lead to the electrostatic attraction of anionic compounds, such as anionic dyes [57] and halogens [58]. Moreover, the existence of these free –NH<sup>2</sup> and −OH active groups allows the adsorption of other pollutants, such as, phenol [59,60], antibiotics [61,62] and pesticides [63]. Hence, the chitosan adsorption capacity depends on its crystallinity, affinity to water, and deacetylation percentage [64].

The main properties of chitosan are summarised in Table 1. Some of the intrinsic properties of chitosan, such as its polycationic character in acid media, its ability to form hydrogen bonds, van der Walls and electrostatic interactions, make it an efficient adsorbent material. Other characteristics, such as the degree of deacetylation (DD), crystallinity, molecular weight (MW), solubility, surface area and particle size will all influence the properties of the final chitosan-based material and its adsorption potential [23]. Therefore, these properties and their optimisation are central in the formation of efficient adsorbent materials.

−


**Table 1.** Main chitosan properties, according to the information reported in [13,27].

#### 2.2.1. Deacetylation Degree

The deacetylation degree (DD) of chitosan is one of the most important parameters as it defines the acetyl content in the biopolymer and it can be increased by repeating or prolonging the alkaline treatment step in the chitin deacetylation process [15]. It can be easily determined using several analytical tools, including UV spectrophotometry [65], X-ray diffraction [66], FTIR-spectroscopy [67,68] and titration methods [69–71]. Increases in DD lead to an increase in the number of free amino groups on the chitosan polymeric chain. These amino groups are responsible for differences in the physicochemical properties and structure of chitosan, due to intra- and inter-molecular hydrogen bonds. As a consequence, the chitosan solubility and polycationic character are increased, expanding the applications of chitosan [72].

The control and manipulation of the physicochemical properties of chitosan, such as the mechanical properties, crystallinity, swelling and thermal degradation, have been shown to correlate with the distribution of the acetyl groups along the main chain [73,74]. With an increase in the DD, the charge density along the chain increases and the chitosan chain becomes more flexible, tending to form a random coil with more inter- and intramolecular hydrogen bonds within the chain. In Table 2, the influence of DD on the physicochemical properties is shown, where it is seen that the DD % has a significant impact.


**Table 2.** Influence of deacetylation degree (DD) on physicochemical properties of chitosan in different forms.

In most cases, an increase in DD was shown to result in an increase in tensile strength and crystallinity and a decrease in the percentage of elongation of the materials. This effect of increasing tensile strength with increasing DD is usually attributed to an increase in crystallinity of the chitosan. Chitosan chains with higher DD have fewer acetyl side groups leading to a more efficient and regular packing of the polymer chains, which in turn, promotes crystallinity in the chitosan [77,85,86]. On the other hand, chitosan with lower DD presents more acetyl side groups that prevent regular packing of the chains due to steric hindrances leading to a reduced crystalline or an amorphous structure [77,86]. Despite the improved tensile strength and stiffness of the chitosan which is observed on increasing the crystallinity this also leads to an increase in the brittleness and a decrease in the percentage of elongation [86]. For example, Zhuang et al. [86] evaluated chitosan films with different DD (81.0%, 88.1% and 95.2%). They reported that the tensile strengths of chitosan films increased from 28.86 to 32.96 MPa and the elongation decreased from 54.31% to 41.66% as DD increased from 81.0% to 95.2%. In applications where film-formation properties of chitosan are important, chitosan with improved tensile strength is an advantage [81,87]. Liu et al. [88] developed composite films of gelatin and chitosan of different MW and DD, and evaluated the interactions between the two polymers in order to improve the films produced. It was verified that the tensile strengths of gelatine films were improved, especially when using chitosan of higher DD and MW. On the other hand, Moura et al. [89] reported a decrease in tensile strength and in elongation of chitosan films with increasing DD, while Nunthanide et al. [75] found both an increase and decrease in tensile strength and elongation, depending on the molecular weight, on increasing DD. These studies which account for the role of MW in the observed results are interesting and highlight the role of both MW and DD.

DD also influences the swelling and thermal degradation characteristics of chitosan [77,78,90,91]. These studies have shown that chitosan with higher DD exhibits faster thermal degradation rates and reduced swelling, as compared to lower DD chitosan. These characteristics may also depend on crystallinity. Chitosan with higher DD and crystallinity are expected to have a close-packed microstructure, which limits water permeation and thus reduced swelling [77]. Moreover, a decrease in the N-acetyl content results in a decrease in the thermal stability as the N-acetyl domains are more thermally stable than the deacetylated ones [92]. Khoulenjani et al. [90], in using chitosan with different DDs (56%, 64% and 74%), showed that the swelling index decreased from 216% to 115% with an increase in DD from 56% to 74%. Nunthanide et al. [75] also reported that the films become more brittle with a lower swelling index with an increase in DD. Wanjun et al. [93] verified that an increase in DD resulted in a decrease in the thermal stability of chitosan due to the decreased acetyl content. This relationship between thermal effects and the DD of chitosan has also been confirmed by Kittur et al. [76]. In another study, Tavares et al. [84] demonstrated that the DD of chitosan had a positive influence on the thermal degradation behaviour. They prepared genipin-crosslinked chitosan beads and evaluated the effect of the chitosan DD (83%, 94% and 96%) on their characteristics. It was verified that the chemical interactions between chitosan and genipin result in a material more thermally stable, especially when a higher chitosan DD (96%) was used. This behaviour was attributed to the decrease in the hydrophilic groups available to form hydrogen bonds with water molecules, resulting in a material more thermally stable.

However, the highly hydrophilic character of chitosan with high DD might be a disadvantage for its surface modification and hence limit the development of chitosanbased materials. Iamsamai et al. [94] have shown that the DD of chitosan plays a critical role in the dispersion of multiwall carbon nanotubes (MWCNTs) and their stability. They confirmed that the chitosan surface coverage on the MWCNTs was twice as high when modifying the surface of the nanotubes with the 61% DD than when using the 93% DD chitosan; suggesting that the dispersion of MWCNTs with chitosan might be improved when using chitosan having a lower DD level.

In addition to the above properties, DD also affects the adsorption properties of chitosan-based materials, since it is linked directly to its cationic properties. Piccin et al. [95] studied the adsorption of FD&C Red 40 dye by chitosan powder with different deacetylation degrees. It was shown that an increase in the DD from 42% to 84% caused an increase in the adsorption capacity from 266 to 373 mg g−<sup>1</sup> . Habiba et al. [96] prepared a chitosan/polyvinyl alcohol/TiO<sup>2</sup> composite with different DD for methyl orange adsorption. They have shown that the adsorption capacity was higher for the composite containing chitosan with higher DD. Furthermore, the composite containing chitosan with higher DD was more reusable and stable with good adsorption capacity even after 15 regenerations. Józwiaket al. [97] have developed chitosan adsorbents with different forms (flakes and hydrogel granules) and different DD (75%, 85% and 90%) to remove Reactive Black 5 (RB5) from aqueous solutions. The highest adsorption capacity (1559.7 mg g−<sup>1</sup> ) was obtained for the chitosan-hydrogel granules formed with 90% DD. Chitosan hydrogel granules reached up to 224% higher adsorption capacity (qDD75% = 1307.5 mg g−<sup>1</sup> ) than chitosan in the form of flakes (qDD75% = 403.4 mg g−<sup>1</sup> ), which indicated that the chitosan form is also important to the adsorption operation. Besides, the DD of chitosan had a particularly large impact on the RB5 adsorption effectiveness of chitosan in the form of flakes. The adsorption on the flakes with a 90% DD was 1049.6 mg g−<sup>1</sup> and was higher by 260% than on the flakes with 75% DD. All the authors of these studies concluded that the DD had influenced the physicochemical properties as well as the interactions of chitosan with the pollutants in the adsorption process. Therefore, DD is a major factor in matching chitosan to other materials to develop potential adsorbent materials [98].

#### 2.2.2. Molecular Weight

The molecular weight (MW) of chitosan is a characteristic associated with the number of monomeric units per polymer molecule (n). The deacetylation process brings about a change in MW and depending on the source and preparation procedure, the average MW of chitosan may range from 50 to 2000 kDa [99]. The MW of chitosan can be measured by light scattering, high-performance liquid chromatography (HPLC) and viscosimetric methods [23]. Chitosan can be classified as low molecular weight (LMW), medium molecular weight (MMW) and high molecular weight (HMW) [99]. Generally, the MW of chitosan can be modified by using depolymerisation techniques where the high MW chitosan is converted to a lower MW. These MW modifications are important as they can preserve the integral structure of chitosan [99,100].

The control, evaluation and modifications of this characteristic are fundamental since MW affects many of the physicochemical properties, including solubility, viscosity, crystallinity, tensile strength, adsorption and elasticity. Consequently, MW has a significant effect on the applications of chitosan. Zhou et al. [73] prepared hydrogels with different MW of chitosan and verified that the viscosity of the hydrogels increased with MW, increasing from 88 to 1360 kDa at 37 ◦C. Moreover, the increase of MW was favourable for sol-to-gel transition and high molecular chitosan was optimal for hydrogel preparation. In Table 3, the various molecular weights employed in chitosan-based materials are summarised. In all cases, the MW is a key factor that influences the tensile strength (TS) and elongation-at-break (EB) properties, as well as the different physical forms of chitosan.

Zhong et al. [101] studied the effect of MW on the properties of chitosan films and found that the conductivity, viscosity, surface tension, and crystallinity of the chitosan film were raised with increasing MW due to an increase in the proportion of amine-groups and degrees of chitosan chain entanglements. Moura et al. [89] verified that the tensile strength, elongation-at-break and water barrier properties of chitosan films were improved with an increase in MW. On the other hand, Ziani et al. [102] showed that the low MW films exhibited greater tensile strengths and percentage of elongation compared to the high MW films despite the high DD of the low MW chitosan. In this study, they verified that the MW had more influence on the mechanical properties than DD. These characteristics were attributed to the number of hetero-monomers, which form stronger films than the character of the acetylated or deacetylated monomers. In general, according to Tables 2 and 3, several studies have demonstrated that DD and MW can be used to manipulate the physical-mechanical and the thermal degradation properties of chitosan materials. However, these studies also highlight that there is a significant and complex interaction between DD and MW and this interaction can lead to conflicting results, e.g., tensile strengths have been shown to increase and decrease with an increase in DD, according to the MW, and increasing MW can both increase and decrease the percentage of elongation, depending on DD. It is also noted that the type or mode of fabrication of the chitosan (e.g., films, gels, membranes, etc.) may be further influenced by the DD and MW properties.


**Table 3.** Tensile strength (TS) and elongation-at-break (EB) properties of chitosan-materials with different molecular weight (MW) chitosan.

#### 2.2.3. Solubility

The solubility of chitosan is a fundamental property that is particularly important in the fabrication of chitosan-based materials [17,26,105]. The main factors that affect this property are DD and MW. It is known that due to the high degree of acetylation, chitin is hydrophobic making it insoluble in water and most organic solvents, decreasing its applications [13]. On the other hand, with higher DD levels, more amino groups in the molecular chain become protonated to give higher degrees of solubility [106,107]. However, an increase in the MW brings about an increase in the intra- and inter-molecular hydrogen bonds within the chains, giving rise to entanglement of the chains and a reduction in solubility [108].Chitosan is soluble in weak acids but insoluble above a pH of 7. The pH has a significant influence on the charged state and properties of chitosan due to the presence of the amino groups [74]. At low pH, the amino groups of chitosan are protonated and become positively charged which leads to a soluble cationic polyelectrolyte. However, as the pH increases to above 6, the amino groups of chitosan are deprotonated, the biopolymer loses its charge, and this gives an insoluble structure. The soluble-insoluble transition occurs at about a pH of 6.5 (p*K*a of the amino group). This characteristic makes chitosan a cationic polyelectrolyte (p*K*a ≈ 6.5), one of the few found in nature [19,27].

In addition to the properties mentioned previously, solubility depends also on the type of acid used [13]. Formic acid is one of the best solvents when aqueous solutions of chitosan are required and the formic acid concentrations can range from 0.2–100% [14]. Acetic acid (1%) has been the most used solvent for the solubilisation of chitosan [13]. However, acetic acid solutions with high concentrations and at elevated temperatures can give rise to the depolymerisation of chitosan [109]. Rinaudo et al. [109,110] observed that for acetic and hydrochloric acid, the chitosan solubility was entirely related to the pH and to the ionic strength, while Kurita et al. [111] verified that it was dependent on chain flexibility, degree of ionisation, crystallinity, solvation of the chain, and the presence of acetyl-glucosamine blocks. Shamov et al. [112] have observed that chitosan solubility is also influenced by interactions between the hydrocarbon chains of the carboxylic acids. There are many other factors that have vital effects on chitosan solubility. These factors can

include alkali concentration, temperature, time of deacetylation, prior treatments applied to chitin isolation, particle size, etc. [113]. In addition, these studies also highlight that solubility in acidic solution imparts the chitosan with excellent gel-forming properties and can expand the potential applications of chitosan-composite materials.

#### 2.2.4. Surface Area and Particle Size

Chitosan surface area and particle size are important characteristics which are related to the porosity, pore volume and pore size distribution of the chitosan. Surface area and particle size are fundamental for adsorption applications, since accessible sites and a porous structure are required [114,115]. It is known that chitosan powders or flakes are non-porous materials which present a low surface area (lower than 10 m<sup>2</sup> g −1 ) [23]. Thus, chemical and physical modifications of chitosan have been performed to increase the surface area and improve potential applications [17,27,58,59,116,117]. Phongying et al. [118] obtained chitosan directly from chitin and prepared chitosan nanoscaffolds in order to improve the surface area, particle size and pore volume. They verified that the surface area of their chitosan scaffolds (55.75 m<sup>2</sup> g −1 ) was approximately seven times higher than the commercial chitosan flakes (7.70 m<sup>2</sup> g –1). Moreover, the pore volume and pore size of the chitosan nanoscaffolds were higher. Esquerdo et al. [119] developed chitosan scaffolds and verified that the new material had a specific surface area, porosity and pore volume of 1135 m<sup>2</sup> g −1 , 92.2% and 0.0079 m<sup>3</sup> kg−<sup>1</sup> , respectively. These values are higher that other chitosan-based materials, such as chitosan powders (surface area of 4.2 m<sup>2</sup> g <sup>−</sup><sup>1</sup> and pore volume of 9.5×10−<sup>6</sup> m<sup>3</sup> kg−<sup>1</sup> ) [120], chitosan flakes (surface area range of 4–6 m<sup>2</sup> g −1 ), chitosan beads (surface area range of 30–40 m<sup>2</sup> g −1 ) [121], chitosan hydrogel beads (porosity of 85%) [122], and chitosan–graphene mesostructures (surface area of 603.2 m<sup>2</sup> g −1 ) [123]. These studies confirm that modification of chitosan leads to an improvement in the surface area and, consequently, in the porosity and pore volume.

Moreover, the particle size of the adsorbents has a significant effect on the final solute concentration, and hence on the overall performance of the adsorption process. Larger particle sizes reduce the uptake due to the lower specific surface area. Thus, an increase in surface area of adsorbent results in new active sites formed, thus allowing more binding of solute molecules [124]. Piccin et al. [120] investigated the effects of particle size, surface area and pore volume of chitosan on the adsorption of FD&C Red 40. The particle sizes used were 0.10, 0.18 and 0.26 mm, with surface areas of 4.2, 3.4 and 1.6 m<sup>2</sup> g −1 , respectively. The results showed that an increase in the surface area and a decrease in particle size doubled the adsorption capacity. Dotto et al. [57] evaluated chitin and chitosan as adsorbents for tartrazine dye. They verified that chitosan showed better adsorbent properties than chitin due to its higher deacetylation degree and higher surface area, pore volume and pore size. These characteristics are particularly important for adsorption applications because it provides access to large pollutant molecules, enabling them to reach the internal adsorption sites.

#### **3. Chitosan Supports**

Although chitosan is an effective adsorbent for a variety of pollutants (as illustrated in Section 2), it nevertheless suffers from poor mechanical properties and thermal stability combined with a relatively low surface area. Therefore, it is not surprising that it has been modified with a variety of other additives to form composites or hybrids. These additives include cellulose [125,126], starch [127], other biopolymers such as alginate [128], gelatin [129], clays, such as bentonite [130], zeolites [131], metal organic frameworks (MOFs) [132], conducting polymers, such as polypyrrole [133] and other polymeric systems comprising methacrylamide [134],polyacrylamide [135], polyurethane [136], poly(vinyl alcohol) [137] and lignosulfonate [138]. These additives are interesting because they can form interpenetrated polymers with chitosan.

#### *3.1. Chitosan Combined with Carbon-Based Materials*

In more recent times, there has been considerable interest in combining chitosan (CS) with carbon-based materials as many carbon-based materials have very good adsorption qualities and these materials can also be employed to enhance the surface area of the adsorbents. Shown in Figure 4 is a summary of the number of papers published in 2019 and 2020 that have employed chitosan combined with various carbon-based materials as adsorbents. It is clearly evident from this analysis that it is graphene and especially graphene oxide (GO) that is dominating the carbon-based materials, with a somewhat lower number of papers describing the use of activated carbon. In the following sections, these CS/carbon-based materials are introduced, highlighting their properties and abilities to facilitate adsorption.

**Figure 4.** Number of papers published in 2019 (open) and 2020 (solid) focussed on various CS/carbonbased materials, where the carbon materials are graphene oxide (GO), carbon nanotubes (CNT), biochar (BC) and activated carbon (AC). All data taken from Scopus.

#### 3.1.1. Chitosan/Graphene Composites

π π Since its discovery, graphene has been used in a wide variety of applications, ranging from sensors [139], batteries [140], electro-Fenton [141] to electronics [142]. It has also been recognised as an adsorbent material, as it possesses a large surface area and there is considerable evidence to show that π-π interactions occur between the aromatic rings of various organic pollutants and the basal planes of graphene [143]. These π-π interactions occur between aromatic pollutants and pristine graphene, but fortunately graphene oxide, which is considerably easier to synthesise and is more cost effective, is an especially promising adsorbent [144]. GO contains a number of oxygen containing functional groups, such as epoxides (C–O–C), hydroxyl (–OH), carboxylic (–COOH) and carbonyl groups (>C=O) [145], while other oxygen containing groups, such as ketones and quinones, have also been detected [146]. These functional groups can facilitate the binding of positively charged molecules through electrostatic interactions [147]. Indeed, numerous studies have demonstrated the excellent ability of GO to adsorb various planar aromatic molecules, such as dyes, through a combination of π–π stacking, electrostatic interaction and hydrogen bonding [148,149].

Graphene oxide (GO) is normally synthesised by oxidising graphite using the wellknown modified Hummers method [150]. The interlayer spacing increases as the graphite is oxidised to give GO sheets that can be exfoliated through a relatively simple liquid-phase exfoliation and/or ultrasonication. The GO sheets are stable in colloidal solutions and are easily combined with chitosan to give CS/GO composites. Typically, the chitosan is dissolved in acetic acid and the GO is added to form a homogeneous mixture. The CS/GO hydrogel can be easily formed, by a combination of violent shaking and sonication [144], adding NaOH [151], freeze drying [152], or by employing solvothermal reactions [153]. Chitosan is a positively charged polysaccharide at near neutral pH due to protonation of the amino groups and therefore it attracts the negatively charged GO sheets. These electrostatic interactions combined with hydrogen bonding facilitates the formation of

the CS/GO hydrogel to give stable composites with excellent thermal and mechanical properties [154], as illustrated in the schematic provided in Figure 5. Indeed, it has been shown by Fan et al. [155] using FTIR measurements, that the –NH groups on the chitosan chains react with the –COOH groups of GO to form a linking –NHCO– group. Using these approaches, CS/GO composites have been formed as beads [156], membranes [157,158] and columns [144,159] and employed successfully as adsorbents for the removal of pollutants from aqueous media.

**Figure 5.** Schematic representation of the interactions between chitosan and GO.

Several studies have been reported using CS/GO composites and these hydrogels have been employed to adsorb and remove various dyes from water [160], heavy metal ions [161], phenolic compounds [162] and pharmaceutical and personal care products [163]. In more recent years, other components have been added in an attempt to further enhance the adsorption capacity of the CS/GO composites, while three-dimensional GO and graphene based aerogels have also been developed and these are now described in turn.

#### Magnetic Chitosan/GO

Magnetic chitosan has emerged as an exciting new material in environmental applications and recently there has been much interest in the applications of magnetic CS/GO [164,165]. The introduction of magnetism facilitates the separation of the adsorbent from the aqueous medium through a simple magnetic process [166]. It is normally difficult to separate chitosan-based adsorbents, and indeed other adsorbents, from aqueous environments through conventional filtration and sedimentation techniques, as these adsorbents can block filters and are often lost, contributing to secondary pollution. The Fe3O4, a ferromagnetic black iron oxide, is the most widely employed, as it possesses good compatibility, low toxicity and also has high magnetic properties [167]. Furthermore, it contains both Fe(II) and Fe(III), and with the presence of Fe(II), which has the potential to act as an electron donor, oxidation of the pollutants can be achieved. Fe3O<sup>4</sup> can also be formed as rods, spheres, wires and nanoparticles and these can be combined with CS/GO. There has also been a report where FeO(OH) was utilised with CS/GO [168], while γ-Fe2O<sup>3</sup> has been combined with chitosan and employed as a magnetic adsorbent [169].

γ Magnetic CS/GO can be easily formed through both in-situ [170] and ex-situ methods [171] and variations of these two approaches. The GO/Fe3O<sup>4</sup> can be initially formed before being combined with chitosan [172], or the CS/Fe3O<sup>4</sup> can be firstly formed [173]. For example, Singh et al. [165] used the reactions between the carboxyl and epoxy groups on GO and the amine groups on chitosan to form amide and hydroxyl functionalised groups that facilitated the conversion of the iron ions to the iron oxide, enabling the in-situ preparation of the magnetic CS/GO. Alternatively, the Fe3O<sup>4</sup> nanoparticles can be initially synthesised using simple methods, such as co-precipitation using ferric and ferrous salts, as illustrated in the schematic provided in Figure 6a. The Fe3O<sup>4</sup> nanoparticles are then combined with the CS/GO hydrogel [174]. Using these approaches, Tran et al. [175] showed that a large number of the Fe3O<sup>4</sup> nanoparticles were immobilised onto the GO

sheets, Figure 6b, while Rebekah et al. [164] also concluded that the Fe3O<sup>4</sup> nanoparticles became attached to the edges and basal planes of GO.

**Figure 6.** (**a**) Schematic representation of the co-precipitation method used to prepare Fe3O<sup>4</sup> (**b**) SiO<sup>2</sup> coated Fe3O<sup>4</sup> nanoparticles deposited and dispersed on GO.

The dispersion and aggregation, size dispersion and shape of the Fe3O<sup>4</sup> nanoparticles within the hydrogels are all important characteristics in terms of their performance as adsorbents. In general, the Fe3O<sup>4</sup> nanoparticles appear aggregated, due to their magnetic nature [173]. Some authors have estimated the particle sizes or have observed some isolated particles among the clusters. Spherical Fe3O<sup>4</sup> clustered particles were observed by Gul et al. [167] with some isolated particles of approximately 90 nm. Shafaati et al. [176] have prepared spherical Fe3O<sup>4</sup> particles with an average size of 45 nm with evidence of some agglomeration, but when they were combined with chitosan an increase in the particle size was observed, indicating more extensive agglomeration during the reaction with chitosan or as the authors suggested, the chitosan polymer chains may provide links between the neighbouring Fe3O<sup>4</sup> particles. Again, Jiang et al. [177] have shown that the Fe3O<sup>4</sup> particles can become severely aggregated, but when the Fe3O<sup>4</sup> particles were coated with silica the aggregation was markedly reduced. TEM micrographs indicated that the GO sheets were decorated with the silica coated Fe3O<sup>4</sup> particles with the more wrinkled GO sheets providing more adsorption sites for the particles. A similar finding, highlighting the role of silica in reducing aggregation of the Fe3O<sup>4</sup> particles, was reported by Tang et al. [178]. This reduction in the aggregation was attributed to a decrease in the dipole-dipole interactions between the silica modified Fe3O<sup>4</sup> nanoparticles. Furthermore, the inert silica coating layers can protect the magnetic cores as the Fe3O<sup>4</sup> particles are susceptible to dissolution and corrosion in acidic solutions, which lead to the loss of magnetism [179], as illustrated in Figure 6b.

#### Chitosan/rGO

While GO is the main form of graphene employed with chitosan, there is also evidence to show that reduced GO, designated as rGO, can be employed to give CS/rGO hydrogel adsorbent materials. The rGO is formed through the reduction of GO and this can be achieved using various thermal approaches, where the GO is heated to high temperatures to transform the oxygen-containing groups to gaseous CO or CO<sup>2</sup> [180], reducing agents, such as borohydride or ascorbic acid [181], or through the electrochemical reduction of GO [182–184]. However, it is very difficult to completely reduce GO and maintain it in the fully reduced form

and therefore rGO will always contain some oxygen-containing functional groups. The rGO is considerably more conducting compared to GO, and therefore it can be easily decorated with various metals or metal oxide particles or single atoms. Indeed, Pradeep and co-workers [185] employed the conducting nature and properties of rGO to form well dispersed and uncapped silver, gold, platinum, palladium and manganese oxide decorated rGO, which was then supported within a chitosan hydrogel. The redox reaction between the metal ion precursors and rGO leads to the progressive oxidation of rGO back to GO, providing the metal decorated graphene sheets with functional groups, facilitating its incorporation within chitosan.

CS/rGO has also been combined with Fe3O<sup>4</sup> to give magnetic CS/rGO adsorbents and employed to give the effective adsorption of an antibiotic [186] and dyes [187]. While the conducting rGO can be beneficial in depositing well dispersed metal/metal oxide particles through reduction, there is evidence to show that CS/GO composites have a higher adsorption capacity when compared with the reduced GO counterparts. For example, Gu et al. [188] compared the performance of chitosan combined with GO and rGO in adsorbing and removing a dye from aqueous solutions and found that while adsorption was evident with both systems, the CS/GO was the more efficient adsorbent. This appears to be related to the presence of the functional groups providing a combination of π–π stacking, electrostatic interaction and hydrogen bonding with the pollutants [148,149].

#### Chitosan with 3D Graphene, Graphene Aerogels, Foams and Sponges

Although GO sheets can be well dispersed within chitosan, restacking of these sheets can occur over time to give GO aggregates and this, in turn, will reduce the surface area of the adsorbent, reducing its adsorption capacity. Consequently, there has been increasing interest in using three-dimensional (3D) GO or rGO hierarchical macrostructures for environmental applications [189,190]. The 3D GO structures can be fabricated as foams, sponges and as porous or macro-porous aerogels [191] and are based on the bending and wrinkling of the GO sheets to give a low mass density and very high specific surface areas [192]. These 3D materials have the potential to act as scaffolds with very good mechanical strength and a high specific surface area, facilitating adsorption. Moreover, they are easily recovered from the liquid phase following adsorption. However, 3D GO and rGO structures without any other additives can have relatively poor stability in water, but this stability can be enhanced considerably by combining the 3D GO network with biopolymers such as chitosan. Indeed, it was shown by Ma et al. [193], in studying the adsorption and removal of methylene blue, that the GO foam was susceptible to collapse, but its macroscopic morphology could be maintained over three repeated uses when combined with chitin. Similarly, 3D GO combined with high molecular weight chitosan was successfully applied in five repeated cycles of adsorption followed by regeneration, achieving a 90% adsorption capacity [152]. Very good stability and recyclability was also achieved with layered chitosan/GO sponges, with a regeneration efficiency greater than 80% over five cycles [194]. A number of CS/aerogel composites have been formed and these have been employed successfully in the removal of Cu(II) [195], tetracycline [196], azo dyes [197], anionic and cationic dyes [198], hexavalent chromium [199] and 4-nonylphenol [151].

#### Chitosan/GO with Other Additives

Other additives have been combined with CS/GO adsorbents and these have included β-cyclodextrins exploiting the hydrophobic properties of the β-cyclodextrin to enhance the adsorption of dyes. These β-cyclodextrin modified CS/GO composite materials have been fabricated and employed to adsorb methylene blue [200]. In this case the authors clearly showed that the extent of adsorption was enhanced on going from GO to CS/GO to CS/GO/β-cyclodextrin, illustrating the beneficial effects of incorporating the β-cyclodextrin. Yan et al. [201] employed a similar CS/GO/β-cyclodextrin composite to adsorb Mn(II), while Li et al. [202] found that the added β-cyclodextrin improved the adsorption of Cr(VI). Similar findings were reported in studying the adsorption of hydroquinone [203] and dye molecules [204].

Polypyrrole, a well-known conducting polymer, has also been combined with CS/GO by polymerising the corresponding pyrrole monomer within the CS/GO dispersion. This gives ternary hydrogel composites with a conducting polymer that has the ability to bind anionic and cationic species as dopants and these materials have been shown to give efficient adsorbents [205,206]. Moreover these hybrids can be further decorated with magnetic nanoparticles, enabling the removal of the adsorbent from water following the adsorption process [207]. Other polymeric systems that have been combined with CS/GO include polyacrylamide [208] and polyacrylate [209]. These high molecular weight polymers can improve the swelling and adsorption behaviour of the CS/GO hydrogels.

Although chitosan has a number of binding sites for metal ions, some of these are consumed in the crosslinking with the GO sheets. Consequently, additives that have additional binding sites have been added with the aim of enhancing the adsorption capacity. Particularly interesting additives include polydopamine, a mussel adhesive, that is easily formed through the oxidation and polymerisation of dopamine in slightly alkaline solutions [210]. It is a promising adsorbent material [211]. Polydopamine has a high density of amine and catechol groups and the combination of chitosan and polydopamine gives more binding groups and has been used to adsorb Cr(VI) [212] and Cu(II), Pb(II) and Cd(II) [213]. Other interesting materials are layered double hydroxides (LDHs) that have the general formula [M2+ 1–xM3+ <sup>x</sup>(OH)2] x+[(An–)x/nmH2O] where M2+ and M3+ are the divalent and trivalent cations, respectively, such as Fe2+ and Al3+, while An−<sup>1</sup> represents the intercalating anions. These layered materials have very good adsorption properties for metal ions and have been used extensively for the removal of heavy metal ions [214]. It is not surprising that LDHs have recently been combined with chitosan and GO to give efficient adsorbents with enhanced adsorption performances [215,216]. Recently, metal-organic frameworks (MOFs) have also been combined with CS/GO [217,218] to give good adsorption properties. MOFs have received considerable interest in environmental science and chemistry as these materials have high porosity and high specific surface areas, with tunable pore structures. Indeed they have been used for heavy metal adsorption and are attracting applications in wastewater treatment [219]. However, MOFs, which are typically powders, are difficult to separate from aqueous environments and this is limiting their environmental applications. The CS/GO hydrogel provides a matrix for encapsulating these powdered materials and as detailed earlier the GO sheets can be easily decorated with magnetic iron to introduce magnetic separation.

A number of other additives has been combined with CS/GO, such as kaolin as a filler to enhance the mechanical strength of the hydrogel composite [220], lignosulfonate for additional binding sites [221,222], triethylenetetramine providing amine groups to enhance adsorption [223], hydroxyapatite to enhance strength and adsorption capacity [224] and silica as it contains a number of silanol groups (Si–OH) [225] and it can be furthermore employed to aid the dispersion of GO within chitosan to give effective adsorbents [226]. Moreover, other biopolymers have been combined with chitosan to form blends which are then combined with GO to give high performing adsorbents. These comprise CS/GO/gelatin [227], CS/GO/alginate [228], CS/GO/heparin [229] and CS/GO/cellulose blends [230].

#### 3.1.2. Chitosan/Carbon Nanotubes

Carbon nanotubes (CNTs), like GO sheets, have high surface areas and excellent stability. Therefore, there has been considerable interest in combining these carbon-based materials with chitosan to give adsorbent materials. CNTs are now readily synthesised as single-walled (SWCNT) and multi-walled nanotubes (MWCNT), distinguished by the number or graphitic layers folded over to form the tubes, with very high aspect ratios. They can be well dispersed within chitosan minimising their agglomeration. For good dispersion, the CNTs are normally treated in nitric acid to generate –COOH groups [231] and these groups can also bind with the chitosan. More recently, the CNTs have been functionalised with valine and starch to aid their dispersion within chitosan and enhance their affinity

for the adsorption of heavy metal ions [232]. In addition, they have been coated with polydopamine thin films to aid dispersion and minimise aggregation within chitosan [233]. Similar to that employed in the formation of CS/GO, the CS/CNTs are formed by initially dissolving the chitosan in acetic acid, then the CNTs are added, dispersed and normally a crosslinking agent, such as glutaraldehyde [215], is used. These CS/CNT composites have been employed as adsorbents and used in the removal of Cr(VI) [234], V(V), Cr(VI), Cu(II), As(V) and Ag(I) from biological and environmental samples [235], Cu(II) [236], U(VI) [237], Pb(II) [238], phosphate [239], phenol [60], fluoride [58], diazinon [240], food dyes [241] and dyes [242].

Magnetic separation has also been developed and this provides a convenient method to remove the CS/CNT adsorbents from the aquatic environment. This is especially important for CNTs as there is considerable concern over the environmental and ecological risks associate with the release of CNTs into the environment [243,244]. For example, Zhou et al. [245] decorated CNTs with –NH<sup>2</sup> functionalised super paramagnetic CoFe2O<sup>4</sup> nanoparticles and combined these magnetic CNTs with chitosan and employed the resulting composites for the removal of Pb(II) and tetrabromobisphenol A. Magnetic Fe3O<sup>4</sup> nanoparticles have also been used to form magnetic CS/CNTs composites and employed to remove Pb(II) [246].

Multicomponent and multifunctional CS/CNTs have also been formed. For example, CS/CNT has been further modified with poly(acrylic acid) and poly(4–aminodiphenylamine). The resulting adsorbent enabled the removal of Cr(VI) through adsorption and reduction to the Cr(III) species. The partially oxidised poly(4–aminodiphenylamine) was transformed in the presence of Cr(VI) into its fully oxidised form with the corresponding reduction of Cr(VI) to Cr(III) [247]. Alsabagh et al. [248] have fabricated a multifunctional nanocomposite comprising chitosan, well dispersed silver and copper nanoparticles and CNTs for the adsorption of Cu(II), Cd(II) and Pb(II). Other components have been added to CS/CNT and these include a prussian blue analogue [249], while a cellulose acetate (CA) and chitosan solution were used as an electrospinning solution and employed to form multicomponent electrospun CA/CS/CNTs/Fe3O4/TiO<sup>2</sup> nanofibers [250].

CS/CNTs have also been formulated to give selective adsorption. While many adsorbents can give relatively high adsorption capacity, it is more challenging to obtain selective adsorption. One avenue that can be employed is imprinting technology. This has been used successfully with ion imprinted polymers, whereby the polymer is formed with a template molecule through a copolymerisation process. The template molecule is then removed leaving behind cavities in the polymer matrix with an affinity for that template, facilitating its rebinding. Li et al. [251] have used this approach to form CS/CNTs composites for the selective capture of Gd(III) by imprinting the chitosan with the Gd(III).

#### 3.1.3. Chitosan/Biochar

Biochar (BC) is a porous carbon rich material which is obtained through the pyrolysis of organic matter, in the presence of a limited concentration of oxygen. It has attracted much attention in environmental applications as it has a porous structure [252,253]. Moreover, it is a cost-effective material as it is fabricated from wastes, mainly agricultural and forestry waste materials. However, the adsorption capacity of biochar is limited and the density of the functional groups on its surface depend on the pyrolytic temperature with a general loss in these functional groups as the pyrolytic temperature is increased [253]. Accordingly, much attention has been paid to the modification of the biochar production process and modification of the surface through oxidation and/or functionalisation, to give more effective adsorbents [254,255]. Treatment of the BC with H2O<sup>2</sup> is an interesting modification that gives rise to an increase in the concentration of the oxygen-containing functional groups and aids the removal of heavy metal ions from water [254].

Chitosan has been coated onto biochar surfaces [256] and employed as a dispersing and stabilising reagent to form CS/BC composites [257,258]. The BC powders are difficult to retrieve from aqueous solutions, but when the BC is incorporated within the chitosan

hydrogel, it is more readily separated from the solution phase. Separation can be further facilitated by forming magnetic CS/BC hydrogels [259,260]. In addition, by using the chitosan solution phase, it is possible to add a number of other additives or reagents in addition to the BC, giving the composite more functional properties. For example, while CS/BC composites have a number of functional groups, such as amine and hydroxyl groups, other additives that increase the number of functional groups can be introduced within the hydrogel matrix. Using this approach, pyromellitic dianhydride (PMDA) has been employed as it can react with the amine groups of chitosan to give additional amides and carboxyl groups and this facilitates electrostatic interactions and complexation with heavy metal ions [261]. Indeed, it was found that the CS/PMDA modified BC exhibited selective adsorption for Cu(II) and this was attributed to the *N*-containing functional groups and carbonyl groups. Moreover, poly(acrylic acid), with carboxylate groups, was grafted to the chitosan modified BC to give not only additional functional groups, but also enhance chemical stability with stronger intermolecular forces [262]. Supramolecules, such as cyclodextrins, which have hydrophobic cavities and hydrophilic exteriors, and can form inclusion complexes with a wide range of organic molecules, have also been combined with CS/BC to give higher performing adsorbents [263]. These CS/BC composites have been employed as adsorbents in a number of studies to remove heavy metal ions from water [264], including Cr(VI) [265]. In addition, they have been utilised in the removal of phosphates [266], nitrates and phosphates [267], fluorides [268], benzoates [269] and various antibiotic and pharmaceutical molecules, such as diclofenac, ibuprofen and naproxen [270], ciprofloxacin [271,272] and ofloxacin [273].

#### 3.1.4. Chitosan/Activated Carbon

Activated carbon (AC) is well-known as an adsorbent material. It has been used in a number of environmental applications [274]. However, its relatively high cost is limiting its more widespread applications. One of the more commonly used starting materials in the synthesis of AC is coal [275], but given the depleted amounts of coal now available, this gives rise to an increase in the price of coal-based AC. Consequently, there is a recent focus on developing more environmentally acceptable synthesis and fabrication methods, using starting materials such as mandarin peel [276] and coconut shell [274]. Another avenue being exploited is the fabrication of multifunctional adsorbent materials that contain relatively small amounts of AC. Chitosan, with its high density of functional groups and good dispersion properties, is an ideal companion material. Indeed, there is evidence to suggest that this combination is effective as an adsorbent material. On comparing the maximum adsorption capacities of AC, chitosan and CS/AC for Cd(II), Hydari et al. [277] observed values of 10.3, 10.0, and 52.63 mg g−<sup>1</sup> for AC, chitosan and CS/AC, respectively. Likewise, Auta and Hameed [278] observed synergistic effects between AC and chitosan in the removal of cationic and anionic dyes, while Fatombi et al. [279] also concluded that the best performance was achieved with a CS/AC composite.

CS/AC composites have been formed using commercially available activated carbon, coconut shell charcoal/carbon [280,281], renewable waste tea [278], sapotaceae seed shells [282] *Typhalatifolia* leaves [283] and olive stones as the carbon source [284]. These composites can be formed through a surface modification process, where the surface of the AC is modified by chitosan [285]. Babel et al. [280] concluded that surface modification of coconut shell charcoal with chitosan significantly improved the adsorption of Cr(VI). They also found that the pre-treatment of the AC with acids gave rise to enhanced adsorption. Amuda et al. [281] arrived at a similar conclusion, and showed that chitosan coated acid treated coconut shell carbon was very effective in the removal of Zn(II). Alternatively, the chitosan can be dissolved in acid and then the AC can be added in the form of a powder to generate CS/AC [286,287]. Crosslinking agents, such as glutaraldehyde [288], genipin [289] or epichlorohydrin [290], can be added to generate the composite hydrogels. With this latter approach, the ratio of activated carbon to chitosan can be easily varied [291], while other additives can be introduced. For example, a CS/AC was formed with SiO2/Fe3O<sup>4</sup>

to give magnetic CS/AC [288], while CS/AC was combined with an anionic surfactant, sodium dodecyl sulphate (SDS), to adsorb a cationic dye [292]. In addition, chitosan has been blended with polyvinyl alcohol [293,294], and polyethylene glycol [295] and then combined with activated carbon, while CS/CA has also been combined with alginate to form CS/CA/alginate adsorbent beads [289].

Activated carbon fibres, regarded as the third generation of carbonaceous adsorbents, have also been employed with chitosan. These have been utilised as membranes [296] and have been decorated with iron oxides and modified with chitosan to remove arsenic, phenol and humic acid from water, with high adsorption capacity for As(V) [297]. Magnetic activated carbon nanofibers based on chitosan and cellulose acetate have also been fabricated for the adsorption of Cr(VI), Ni(II) and phenol from aqueous solutions [298]. In addition, a number of magnetic CS/AC composites has been formed with the majority involving Fe3O<sup>4</sup> [299,300], while others have employed CoFe2O<sup>4</sup> [301] and barium ferrite [302].

These CS/AC composites have been evaluated for the removal of phenols [303], parabens [304], dyes [305], food dyes [306], anti-inflammatory drugs [307], acetaminophen [308], organic molecules, such as aniline [309], and various heavy metal ions [289]. Generally, there is good agreement that the combination of chitosan and AC gives rise to enhanced adsorption, when compared to the individual chitosan and AC counterparts.

#### *3.2. Chitosan Combined with Inorganic Adsorbent Materials*

While chitosan has been combined with various carbon based materials, as illustrated in Section 3.1, there is growing interest in the use of inorganic components, such as activated alumina [310], mesoporous alumina [311], silica and ordered mesoporous silica-based materials, as the chitosan support materials [312,313]. Silica has very good physical, mechanical and thermal stability and can be easily functionalised due to its hydroxyl groups. In particular, mesoporous silica is a fascinating material, which first gained prominence in the 1990s with a regular mesostructure, with uniform pore distribution and tunable pore sizes, very high specific surface areas, combined with thermal and mechanical stability [314]. It is attracting considerable interest as an adsorbent material [315]. These materials can be formed by a simple sol–gel synthesis route comprising hydrolysis, condensation and polycondensation reactions using various templates or surfactant molecules [316]. In particular, the template-assisted mesoporous silica synthesis using surfactants is gaining considerable attention. Typically, liquid silicon alkoxide precursors, such as tetramethyoxysilane or tetraethoxysilane are used. The successive polymerisation, gelation, drying and aging steps can be tailored to control the microstructure of the final materials. The surfactant–silica assembly occurs simultaneously with condensation of the inorganic species to produce the mesoporous silica composite.

CS/silica composites have been formed using a variety of methods which can be broadly grouped into two main approaches, comprising silica supported chitosan, where the chitosan is coated or adsorbed onto the silica support, and secondly a CS/silica hybrid that is fabricated using the sol-gel methodology. Several reports have focussed on SiO<sup>2</sup> as a bead, particle, nanoparticle or powder, where the SiO<sup>2</sup> particles are added to the chitosan solution phase to give a chitosan coated particle [317]. The SiO<sup>2</sup> particles can also be functionalised with amine and carboxylic groups to give more efficient binding with the chitosan [318]. Silica layers have also been added to previously formed chitosan-based beads to give organic-inorganic (CS/silica) layered structures, with greater stability [319] and sol-gel synthesis has been employed to immobilise chitosan onto silica particles [320]. Sol-gel synthesis is more commonly used to form a CS/silica hybrid layer on silica bead/particle supports [321,322]. For example, Xu et al. [323] covalently linked chitosan with an epoxide containing siloxane through the sol-gel process to give a hybrid chitosan layer on silica particles. The CS/silica hybrid has been further modified with EDTA (ethylenediaminetetraacetic acid), which is very well known to form stable chelates with a number of metal ions [324], to give adsorbents for heavy metal ions [325]. While the sol-gel synthesis is very versatile, Blachnio et al. [326], on comparing three CS/silica

composites formed by the adsorption of chitosan on silica gel and fumed silica and by the sol-gel process, concluded that the adsorbed chitosan had a higher adsorption capacity for dye molecules, although the CS/silica fabricated using the sol-gel synthesis had a high surface area of 600 m<sup>2</sup> g −1 .

There has been considerable interest in combining mesoporous silica with chitosan to combine the good adsorption properties of chitosan with the large surface area and adjustable pore size of silica. Likewise, magnetic mesoporous silica, which has a magnetic Fe3O<sup>4</sup> core surrounded by the mesoporous silica is attracting a lot of attention in environmental applications [327]. These magnetic materials are environmentally acceptable with no toxicity, are biocompatible, have high surface area, very good stability and the outer mesoporous silica can be functionalised and modified by chitosan to add functional groups. The cross-linking method can be employed to decorate the mesoporous silica with the chitosan. Cross-linking agents, such as glutaraldehyde [328], formaldehyde [329] and epoxides [327], can be used, while in a recent study, He et al. [330] used thiol-ene click chemistry to achieve binding between chitosan and magnetic mesoporous silica. The surface areas, pore sizes and volumes of a number of these materials are summarised in Table 4. In general, the surface area, pore size and volume of the mesoporous silica are reduced as higher amounts of chitosan are added and partially fill the pores. However, these chitosan and mesoporous silica composites possess good surface areas with a high density of functional groups and with the potential to give magnetic separation.


**Table 4.** Surface area, pore diameter and pore volume of CS/mesoporous silica composites and hybrids.

#### **4. Adsorption and Removal of Pollutants**

The removal of pollutants from aquatic environments through adsorption is one of the more popular approaches in environmental applications. The aim in these technologies is to remove the maximum amount of pollutant and therefore adsorption isotherms have been used extensively to develop an understanding of the adsorption equilibria. In this section, these adsorption models are briefly introduced, followed by adsorption kinetics and finally a comparison of the performance of the various chitosan composites is made.

#### *4.1. Adsorption Models and Adsorption Kinetics*

Adsorption isotherms are frequently employed in the study of adsorption, facilitating a quantitative comparison of different adsorbent materials. In addition, they are often used to optimise the use of adsorbents, by observing the adsorption capacity as a function of the experimental conditions. Several different isotherm models have been employed to analyse experimental adsorption data and these include the Langmuir, Freundlich, Temkin, Frumkin, Redlich-Peterson (R-P), Halsey, Henderson and Dubinin-Radushkevich isotherms. However, the two most frequently used models with chitosan and chitosan-

based composite materials are the Langmuir [223,334] and to a lesser extent the Freundlich isotherms [335]. The Langmuir adsorption model is described in Equation (1) and the linear form commonly employed in fitting data in Equation (2). Here *q<sup>e</sup>* is the equilibrium concentration of the adsorbate, *q*<sup>m</sup> is the monolayer adsorption capacity, *C<sup>e</sup>* is the concentration of the adsorbate in the aqueous phase and *K* is a constant. In this model all sites are considered as energetically equivalent, to give monolayer adsorption with no interactions between adjacent adsorbates. In this analysis, the adsorbent has a finite capacity for the adsorbate and a saturation point is reached where no further adsorption occurs. The BiLangmuir model can also be applied with chitosan-based composites [317] and, in this case, the relationship is given in Equation (3), where *qm*<sup>1</sup> and *qm*<sup>2</sup> represent the maximum adsorption capacities of two different adsorption sites and *KL*<sup>1</sup> and *KL*<sup>2</sup> correspond to these two sites. The Freundlich model assumes multilayer adsorption on a heterogeneous surface and can be described by Equations (4) and (5), where *q<sup>e</sup>* represents the amount of adsorbent adsorbed at the surface, *C<sup>e</sup>* is the equilibrium concentration, and *n* and *K<sup>F</sup>* are the Freundlich constant and Freundlich exponent, respectively. The Freundlich constant, *KF*, provides a measure of the adsorption capacity and the magnitude of *n* is related to the extent of adsorption with *n* > 1, indicating favourable adsorption. An adsorption plot, using simulated data, is illustrated in Figure 7, where a schematic of monolayer and multilayer adsorption is also shown. In this example, the experimental data are more consistent with the Freundlich isotherm.

$$q\_{\ell} = \frac{q\_{m}K\_{L}\mathbf{C}\_{\varepsilon}}{1 + K\_{L}\mathbf{C}\_{\varepsilon}}\tag{1}$$

$$\frac{\mathbb{C}\_{\varepsilon}}{q\_{\varepsilon}} = \frac{1}{\mathbb{K}\_{L}q\_{m}} + \frac{\mathbb{C}\_{\varepsilon}}{q\_{m}} \tag{2}$$

$$q\_{\varepsilon} = \frac{q\_{m1}K\_{L1}\mathbf{C}\_{\varepsilon}}{1 + K\_{L1}\mathbf{C}\_{\varepsilon}} + \frac{q\_{m2}K\_{L2}\mathbf{C}\_{\varepsilon}}{1 + K\_{L2}\mathbf{C}\_{\varepsilon}}\tag{3}$$

$$\mathfrak{q}\_{\mathcal{E}} = \mathbb{K}\_{\mathcal{F}} \mathbb{C}\_{\mathcal{E}}^{1/n} \tag{4}$$

$$
\log q\_{\varepsilon} = \log K\_F + \frac{1}{n} \log \mathcal{C}\_{\varepsilon} \tag{5}
$$

− − − **Figure 7.** Schematic of an adsorption plot showing experimental data (symbols), with the —— Freundlich isotherm and − − − Langmuir isotherm fitting and the inset shows monolayer and multilayer adsorption processes.

lnሺ െ <sup>௧</sup>

 ௧ = 1 ௧ +

**−**

ሻ = െ <sup>ଵ</sup>

1 ଶ ଶ The kinetics of the adsorption process are important as these studies provide information on the rate of adsorption which is relevant in terms of the contact time required to remove the maximum amount of adsorbate. The Lagergren rate equation is one of the most widely used adsorption rate equations for the adsorption of adsorbates from a solution phase and this has been used with various chitosan composites [336]. The pseudo-first order (PFO) and pseudo second-order models (PSO) are described in Equations (6) and (7) where *q<sup>t</sup>* and *q<sup>e</sup>* represent the mass of the adsorbing molecule per unit mass of adsorbent at time *t* and at equilibrium, while *k*<sup>1</sup> and *k*<sup>2</sup> correspond to the first- and second-order rate constants and *t* is the time. Other kinetic models have been employed in the study of chitosan composite materials and these include a double-exponential kinetic model [337], and a generalised fractal kinetic model (Brouers-Sotolongo model) [338]. Generally, the adsorption kinetics are controlled by the (i) rate of diffusion of the adsorbate from the bulk solution to the adsorbent-solution boundary, (ii) diffusion form the boundary layer to the adsorbent surface, (iii) diffusion of the adsorbate within the adsorbent material, i.e., intraparticle diffusion and (iv) the rate of the adsorption step. Normally, the diffusion process in the bulk solution can be eliminated through agitation, while the adsorption is fast and the rate-determining step is typically intraparticle diffusion [200].

$$
\ln(q\_\varepsilon - q\_t) = \ln q\_\varepsilon - k\_1 t \tag{6}
$$

$$\frac{t}{q\_t} = \frac{1}{q\_t} + \frac{1}{k\_2 q\_\varepsilon^2} \tag{7}$$

#### *4.2. A Comparison of the Chitosan Supported Composites in the Adsorption of Pollutants*

The performance of the chitosan composites in the removal of heavy metal ions is summarised and illustrated in Tables 5–7, where the chitosan is combined with GO, CNTs, BC, AC and silica as support materials.

The Langmuir isotherm is based on the assumption that the surface of the absorbent is homogenous, and every adsorption site is equal. Although these chitosan-composites have various functional groups, which in turn, give rise to different affinities with the adsorbates, the Langmuir model and to a lesser extent, the Freundlich model, correlate well with most of the experimental studies. It is also evident in Tables 5–7, that many of the 3D or porous supports give higher adsorption capacity values, highlighting the influence of the more porous materials, while the magnetic chitosan materials, (MSC), with Fe3O<sup>4</sup> particles/nanoparticles, also perform well. It is difficult to make a direct comparison between the carbon-based materials and silica-based supports, as the adsorption capacity depends on the nature of the chitosan. However, some of the highest adsorption capacities are seen when chitosan is combined with GO.

It can be seen from these tables that a large variety of heavy metal ions have been adsorbed and removed. This is not surprising as these ions are toxic and pose a significant threat to both human beings and aquatic life. As illustrated, the adsorption capacity varies considerably from relatively low values of 9.4 mg g−<sup>1</sup> to much higher values in the vicinity of 957 mg g−<sup>1</sup> . These variations appear to be somewhat related to the nature of the heavy metal ions, with relatively high adsorption values for Pb(II) and lower values for Cr(VI). However, the nature and properties of the chitosan, including its DD levels, MW, porosity, particle size, solubility (Section 2), crosslinking agents and the ratio of chitosan to the carbon-based or silica supports are also important elements that will influence the extent of adsorption.


**Table 5.** Adsorption performance of CS/GO composites in the removal of heavy metal ions.

In terms of the experimental conditions employed in these studies, it is well documented that the pH plays a significant role in the adsorption process. It is well known that the –NH<sup>2</sup> and –OH groups on the chitosan chains have a strong association with metal cations and this facilitates the adsorption of various heavy metal ions at slightly acidic or near neutral pH values. This is clearly evident in Tables 5–7, where several of the studies are performed in slightly acidic solutions. As the chitosan becomes protonated, with the formation of NH<sup>3</sup> <sup>+</sup> at lower pH values, this protonated group repels the cationic heavy metal ions. Moreover, the chitosan becomes less stable and more soluble in highly acidic environments. Indeed, the pH of zero charge (pHpzc) has been determined as 6.0 for CS/GO composites, indicating that the surface of CS/GO is positively charged for pH values < 6.0 but for pH values > 6.0, the surface adopts a negative charge [365]. However, the speciation of the metal ions is also important, and this is illustrated in Figure 8, where the Pourbaix diagrams for various heavy metals, designated as M, and Cr are shown. In general, for heavy metals, such as Cu(II), the adsorption capacity increases gradually as the pH increases from about 2 to 7 and then it decreases rapidly as the pH is further increased. The rapid decrease at higher pH values is due to the formation of insoluble hydroxide species. While higher concentrations of the metal cations are present in the solution phase at low pH values, the adsorption capacity is poor, which can be attributed to the protonation of chitosan. As the pH is increased, the–NH<sup>2</sup> chelating groups become available and at these conditions the concentrations of the metal cations is still sufficiently high to facilitate chelation with the chitosan. The nature of the –COOH functional groups on GO and the other carbon-based materials is also pH dependent with the generation of –COO<sup>−</sup> at higher pH values and again this anionic group will bind with metal cations. Therefore, the maximum adsorption is seen at pH values from about 5 to 7, as illustrated in Tables 5–7, for a number of heavy metal ions. The Pourbaix diagram of Cr is somewhat

different with the generation of the anionic dichromate (Cr2O<sup>7</sup> <sup>2</sup>−) and chromate (HCrO<sup>4</sup> −) ions at the lower more acidic pH values and the insoluble oxide phases at higher pH values. In this case, the HCrO<sup>4</sup> <sup>−</sup> ions can be adsorbed at the chitosan through electrostatic interactions with the protonated chitosan, to give more favourable adsorption at pH values between approximately 2.0 and 4.0.

**Table 6.** Adsorption performance of CS/CNT, CS/BC and CS/AC composites in the removal heavy metal ions.


Abbreviations: PMDA: pyromellitic dianhydride; PAA: poly(acrylic acid); PVA: poly(vinyl alcohol); PEO: poly(ethylene oxide); PB: Prussian blue.


**Table 7.** Adsorption performance of CS/silica composites in the removal heavy metal ions from water.

Abbreviations: polyacrylamide (PAM).

**Figure 8.** Pourbaix diagrams illustrating the speciation of (**a**) heavy metals, M, and (**b**) Cr in aqueous solutions.

− tt π−π − Other conditions that can alter the adsorption capacity of the heavy metal ions are temperature and ionic strength. Generally, the adsorption capacity increases with higher temperatures [195], as ∆*G* becomes more negative, implying that the adsorption process becomes more favourable at higher temperatures, with ∆*G* ◦ < 0, ∆*H*◦ > 0 and ∆*S* ◦ > 0 for several adsorbents, however, adsorption can also be exothermic [337]. There have been relatively few studies devoted to the selectivity of the adsorption process at these chitosan composites. This is especially important in terms of the potential applications of the adsorbents, as the water samples or industrial effluents are likely to contain other cations and anions, such as Cl−, NO<sup>3</sup> <sup>−</sup>, SO<sup>4</sup> <sup>2</sup>−, Mg2+ and Na<sup>+</sup> . For example, it was found

π−π

−

that an increase in the ionic strength inhibited the adsorption of Cu(II) at CS/GO [195]. One approach that can be employed to enhance the binding of a particular heavy metal ion is templating [251]. This is generally successful provided the target metal ion is reasonably different to the size of the co-existing ions.

The adsorption capacity of the various supported chitosan composites in the removal of dye molecules and other organic molecules, including antibiotics, is summarised in Table 8. Various cationic and anionic dyes have been employed as model compounds and very impressive adsorption capacities have been obtained in a number of studies. In particular, the adsorption of methylene blue (MB), a cationic dye molecule, is very high at CS/GO composites reaching values > 1000 mg g−<sup>1</sup> in a number of studies, as illustrated in Table 8. This good adsorption is attributed mainly to the π−π interactions between the MB and GO layers. The electrostatic interactions between the –COO<sup>−</sup> groups on GO and the cationic MB can also facilitate adsorption, provided the solution pH is not acidic giving rise to the formation of the unionised –COOH groups. Therefore, it is the GO that is largely responsible for the adsorption of cationic dyes [144]. On the other hand, the chitosan plays a more significant role in the adsorption of anionic dye molecules. Although π−π interactions will exist between GO and the anionic dyes, the electrostatic repulsion between the –COO<sup>−</sup> groups and the anionic dye will inhibit its adsorption at higher pH values, where the COOH groups are ionised. The electrostatic interactions between the cationic centres in the chitosan chains and the anionic dyes will have a significant effect at low pH values, while a combination of electrostatic forces, van der Waals interactions and hydrogen bonding are likely to occur at higher pH values [366]. This explains the good adsorption of anionic dyes observed at near neutral pH values in Table 8. The concentrations of the dye molecules can also influence the adsorption process. Many of these dye molecules can form dimers and aggregates and this becomes more relevant as the concentrations of the dye molecules increase, with aggregates forming in solution and at the surface. Indeed, the impressive adsorption of rhodamine B [367] and its adsorption kinetics were questioned as the aggregation of rhodamine B in water was not taken into account in the original study [368].

Various antibiotics have also been adsorbed at the chitosan-based composites, as shown in Table 8. Again, many of these molecules have benzene rings which facilitate their adsorption onto the carbon surface through π-π electron donor-acceptor interactions. Furthermore, many of these organic molecules have –OH, >C=O and –NH<sup>2</sup> groups which can be involved in hydrogen bonding with the oxygen groups on the carbon surfaces in the chitosan composites [369]. Hydrophobic interactions may also be relevant [370]. These organic molecules tend to be hydrophobic making hydrophobic interaction between the antibiotics and the carbon surfaces possible. However, high numbers of oxygen-containing groups, such as –OH and –COOH on the carbon surfaces tend to make the surface more hydrophilic.

The CS/silica composites are only emerging as potential adsorbents and compared with the chitosan-carbon based systems, there are much fewer reports focused on the removal of dyes and organic molecules with these adsorbents. This may be due in part to the silanol groups, which are hydrophilic, and easily form hydrogen bonds with water, thus limiting the adsorption process. However, the mesoporous silica surfaces can be functionalised, and this provides the opportunity to design more hydrophobic surfaces that can be tailored to adsorb organic molecules. Indeed, there is clear evidence in Table 8 that the CS/silica composites can be employed in the removal of dyes.


**Table 8.** Adsorption performance of chitosan composites in the removal pharmaceuticals, organics and drug molecules from water. 


**Table 8.***Cont*.

#### **5. Conclusions and Future Perspectives**

It is clear from the reports reviewed and the growing number of publications, where chitosan and chitosan-based materials are employed as adsorbents, that these materials are emerging as interesting candidates in the formulation of adsorbents for environmental applications. Chitosan can be easily combined with different support materials, and while earlier studies were devoted to blending chitosan with other polymeric materials, many of the more recent reports are focused on combing chitosan with carbon-based materials with GO, and to a lesser extent activated carbon, attracting considerable attention. Likewise, there is increasing attention being focussed on merging chitosan and mesoporous silica. The CS/GO composites have shown impressive adsorption capacity with both dyes and heavy metal ions.

However, this research field is still in its infancy and a number of challenges exist and must be addressed before these chitosan-carbon based or chitosan-silica based materials can be employed as adsorbents for the removal of a variety of pollutants. One of the more challenging aspects, that has direct implications in terms of costs, is the regeneration of the adsorbents. Ideally, adsorbents should have the capacity to be regenerated and used multiple times. Regeneration is normally achieved using NaOH or acid treatments, where, for example, heavy metal ions are released from the chitosan. However, these treatments lead to a progressive hydrolysis of the polysaccharide on the chitosan. Consequently, the adsorption capacity decreases with each adsorption-regeneration cycle. New regeneration processes are required to give more longer lasting and cost-effective chitosan-based adsorbents. Other challenges are the introduction of selectivity in the adsorption process. Real water samples contain a number of ions that will compete with the removal of heavy metal ions, consuming the adsorption sites and reducing the uptake of the targeted pollutants. Furthermore, the removal of neutral pollutant molecules using these chitosan-based materials is more difficult to achieve, although the addition of GO provides two dimensional sheets that facilitate the adsorption of aromatic ring structures. In addition, the adsorbents need to be removed from the aquatic environment or employed in a continuous flow system. While the development of magnetic chitosan-based materials provides the opportunity to remove the adsorbents using magnetic separation, these magnetic materials are only emerging and it is not entirely clear if they can be sufficiently anchored within the chitosan composites to prevent their leaching over longer terms. However, the development of silica coated and protected magnetic iron-containing particles is promising. There are added concerns over the environmental impact of GO and CNTs, which if leached from the chitosan composites, can enter the aquatic system and have adverse effects on the aquatic ecosystem. Therefore, the CS-carbon and CS-silica composites must be stable and not prone to leaching of GO flakes, CNTs, or the magnetic iron oxide particles. Consequently, studies that monitor the leaching of the various carbon, silica and iron species from the chitosan composites are needed from an environmental perspective.

Fundamental studies on kinetics and intraparticle diffusion require further study. Most of the kinetic models employed are relatively simple pseudo-second order models while the impermeable nature of the GO sheets, CNTs, carbon and silica particles on the internal diffusion of the pollutants are not well developed. While the physical and chemical properties of chitosan can be tailored by varying its molecular weight, DD levels, particle sizes, etc, the complex relationships between some of these parameters and how they control the adsorption process and capacity are difficult to establish.

Nevertheless, these chitosan-based materials, and especially the emerging chitosancarbon and chitosan-silica based composites, have a promising future as adsorbent materials. While chitosan is currently unable to compete with activated carbon in commercial and industrial settings, it is nevertheless an attractive and viable material as it is derived from chitin, which can be found in abundance and extracted from seafood wastes. With further developments aimed at strengthening the mechanical properties of chitosan, the development of recovery protocols, scale-up of production using green solvents and implementation of nonthermal technologies, industrial exploitation can become a reality.

Moreover, there has been a recent explosion in the development of new two-dimensional materials. Some of these 2D layered materials, for example MXenes, MoS<sup>2</sup> and MoSe2, are potential adsorbents and could be easily combined with chitosan to generate a new family of high-performance materials.

**Author Contributions:** Conceptualization, D.C.d.S.A. and C.B.B.; writing—original draft preparation, D.C.d.S.A., B.H., L.A.d.A.P., T.R.S.C.J. and C.B.B.; writing—review and editing, D.C.d.S.A., B.H., L.A.d.A.P., T.R.S.C.J. and C.B.B.; supervision, L.A.d.A.P., T.R.S.C.J. and C.B.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)/Brazil, grant number 001 and by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)/Brazil. This research also was funded by Secretaria de Desenvolvimento, Ciência e Tecnologia/RS/Brazil, grant numbers DCIT 70/2015 and DCIT 77/2016.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


### *Review* **Extremophilic Microorganisms for the Treatment of Toxic Pollutants in the Environment**

### **Sun-Wook Jeong and Yong Jun Choi \***

School of Environmental Engineering, University of Seoul, Seoul 02504, Korea; jeongsunwook@gmail.com **\*** Correspondence: yongjun2165@uos.ac.kr; Tel.: +82-02-6490-2873; Fax: +82-02-6490-2859

Academic Editors: Chiara Bisio and Monica Pica Received: 17 September 2020; Accepted: 23 October 2020; Published: 23 October 2020

**Abstract:** As concerns about the substantial effect of various hazardous toxic pollutants on the environment and public health are increasing, the development of effective and sustainable treatment methods is urgently needed. In particular, the remediation of toxic components such as radioactive waste, toxic heavy metals, and other harmful substances under extreme conditions is quite difficult due to their restricted accessibility. Thus, novel treatment methods for the removal of toxic pollutants using extremophilic microorganisms that can thrive under extreme conditions have been investigated during the past several decades. In this review, recent trends in bioremediation using extremophilic microorganisms and related approaches to develop them are reviewed, with relevant examples and perspectives.

**Keywords:** bioremediation; toxic pollutants; extreme conditions; extremophilic microorganism

### **1. Introduction**

Due to the rapid industrial growth, the environment and public health are threatened by the huge amount of toxic pollutants that have accumulated in the environment. Therefore, maintaining and protecting the environment from toxic pollutants has become a great challenge for mankind over the past few decades. Recently, various strategies have been intensively exploited to protect the environment by preventing the dispersion of toxic pollutants into it. For example, physicochemical methods such as electrochemical treatments, excavation, ion exchange, precipitation, reverse osmosis, evaporation, and sorption have been developed for the removal of toxic substances [1–4]. However, many of these techniques are not yet commonly applied to the actual treatment of contamination due to critical drawbacks such as high cost and secondary contamination possibly associated with them [5–7]. As an alternative, microbial bioremediation has attracted much attention as a promising technology that can overcome the shortcomings of the currently used physicochemical methods (Figure 1) [8–10]. Specifically, extremophilic microorganisms offer the most suitable approach for the treatment of toxic pollutants [11–14] because not only can they detoxify toxic pollutants through microbial cellular metabolism but also they can withstand extremely harsh conditions [11,13–15]. Herein, we focus on recent trends in bioremediation processes for the treatment of toxic pollutants such as inorganic heavy metals, harmful organic substances, and radioactive elements using extremophilic microorganisms and on the perspectives of this approach in public health.

**Figure 1.** Current microbial bioremediation strategies for the removal of diverse toxic pollutants. Biosorption, a metabolically independent process based on ionic interactions between the extracellular surface of biomass and metal ions; bioaccumulation, a metabolically active process in which microorganisms use proteins to absorb metal ions inside their intracellular space; bioprecipitation, a process of immobilizing soluble metal ions through redox reactions, enzymes, and metabolites on the extracellular surface of microorganisms; bioreduction, a process of transformation of toxic metals/metalloids to non-toxic elements through a biological reduction and oxidation process; bioemulsification, a biological process of using proteins or metabolites to form emulsions in two immiscible liquid phases.

#### **2. Survival Strategies of Extremophilic Microorganisms under Extreme Conditions**

Extreme environments are defined as habitats that make the prospect of survival difficult for most organisms on earth. These are mostly natural conditions such as extreme temperatures, salinity, pH, and desiccation observed in environments such as deep sea, volcanoes, and deserts. However, these extreme conditions can also appear in polluted areas containing harmful organic substances [16], heavy metals [17], and/or radioactive waste [18]. Under extremely polluted conditions, the clean-up process of pollutants by using physicochemical methods is not always successful due to limited accessibility to the pollutants and secondary contamination. Thus, there is a need to combine microbial biotechnology and chemistry to advance the remediation processes. Over the past century, extremophilic microorganisms have adapted and evolved in various ways to thrive under extreme conditions through unique biological mechanisms. During the process of adaptation, extremophilic microorganisms have evolved not only to convert unstable toxic pollutants into sufficiently stable beneficial resources for their cellular metabolism but also to become highly tolerant to toxic matter. Thus, many studies have been attempted to develop sustainable bioremediation processes using the survival strategies of extremophilic microorganisms. Here, we briefly describe the adaptation and survival mechanisms that can be used for bioremediation.

#### *2.1. Acidophilic and Alkaliphilic Microorganisms*

Acidophilic microorganisms can survive under extremely low pH (less than pH 3) conditions, maintaining pH homeostasis by controlling proton permeation [19]. For example, microorganisms from the genera *Thermoplasma*, *Ferroplasma,* and *Sulfolobus* can regulate proton permeation under extremely low pH conditions due to a highly impermeable cell membrane mainly composed of tetraether lipids having a diverse array of polar head groups and a bulky isoprenoid core [20–23]. The modulation of the influx of protons through the proton pump system is important to survive at low pH, and putative proton pump proteins such as H+-ATPase, symporters, and antiporters from *Ferroplasma* type II and *Leptospirillium* group II are involved in maintaining pH homeostasis [21,24,25]. Moreover, F0F1-type adenosine triphosphate synthase in *Bacillus acidocaldarus*, *Thermoplasma acidophilum*, and *Leptospirillium ferriphilum* is known to play a critical role in regulating proton permeation [25]. In addition to these mechanisms, several other auxiliary mechanisms, involving for example, chaperone proteins and cytoplasmic buffering capacity contribute to survival strategies under extremely low pH conditions by protecting intracellular molecules such as DNA, RNA, and proteins [25].

Contrary to acidophilic microorganisms, alkaliphilic microorganisms can resistant high pH. To date, three key biological mechanisms have been identified as survival strategies in these microorganisms. First, under extremely high pH conditions, some alkaliphilic *Bacillus* spp. can increase the generation of proton motive force through synthesizing a secondary acidic cell membrane consisting primarily of peptidoglycan, teichuronic acid, and teichuronopeptide [26,27]. Increasing the proton motive force contributes to not only energy generation but also pH balance [28–30]. Second, sodium motive force can also promote pH balance under extremely high pH conditions [31,32]. Under high Na<sup>+</sup> ion conditions, Na+/H<sup>+</sup> antiporters extrude Na<sup>+</sup> ions and absorb a greater amount of extracellular H<sup>+</sup> ions than that of extruded Na<sup>+</sup> ions, thereby activating a bioenergetic process and regulating the internal pH [33]. Finally, the production of organic acids that can be used for pH calibration is known to be an important biological process in maintaining pH balance [34,35].

#### *2.2. Halophilic Microorganisms*

Halophilic microorganisms can thrive in a high-salt environment which hinders organisms' survival due to osmolar imbalance and metabolic problems [36,37]. Previous studies on halophilic microorganisms reported two fundamental adaptation strategies to survive under extremely high salt conditions. The first is to use a "salt-in" strategy that refers to the accumulation of inorganic osmoprotectants such as KCl inside the cell to maintain the osmotic balance both inside and outside the cell [37]. It has been demonstrated that *Halobacterium salinarum* can accumulate 3.97 M and 4.57 M of K<sup>+</sup> and Cl<sup>−</sup> ions, respectively, inside the cell using the ATP-dependent K<sup>+</sup> transport system (the KdpFABC complex and cationic amino acid transporter-3 (Cat3) and Na<sup>+</sup> efflux antiporters (NhaC) to balance the osmotic gradient under high-salt conditions [38–41]. Moreover, halophilic microorganisms have evolved an abundance of negatively charged aspartate and glutamate residues on protein surfaces that can interact with water molecules to form a water cage that prevents protein precipitation and dehydration [41–44].

As another adaptation strategy, some halophilic and halotolerant bacteria use the 'compatible solutes adaptation' strategy to maintain osmotic balance by using compatible organic solutes such as polyols, glucosylglycerol, sucrose, trehalose, ectoine, and betaine [45,46]. For example, the halophilic bacterium *Spiribacter salinus* M19-40 produces enhanced levels of compatible solutes such as ectoine and trehalose when they are exposed to a high NaCl concentration [45]. These organic solutes have a critical role in reducing the thermodynamic activity of water to compensate for the external osmotic pressure [47].

#### *2.3. Psychrophilic and Thermophilic Microorganisms*

Psychrophilic microorganisms usually have a preferred temperature range of 1–4 ◦C. Unlike mesophilic microorganisms, whose preferred temperature range is 30–37 ◦C, psychrophilic microorganisms can fully maintain cellular metabolism even at temperatures below 0 ◦C. To adapt to these harsh conditions, they have evolved several physiological adaptation mechanisms, including membrane fluidity control, molecular chaperones' action, and antifreeze molecules' synthesis [48,49]. For example, they can modulate membrane fluidity by altering its lipid composition, increasing the amount of polyunsaturated fatty acids and polar/non-polar carotenoids and decreasing the size of the lipid head groups [19,49]. A variety of temperature-induced enzymes such as cold-shock proteins

(Csps) and heat-shock proteins (Hsps) are also involved in cold-shock resistance by regulating signaling cascades that protect damaged proteins and cofactors [50]. Moreover, various antifreeze proteins and polysaccharides such as trehalose, mannitol, and exopolysaccharides, which are constituents of biofilm, can act as cryoprotectants [51].

Thermophilic microorganisms with a preferred temperature above 60 ◦C activate similar survival mechanisms to psychrophilic microorganisms. For example, *B. acidocalidus*, a thermophilic spore-forming bacterium, modulates membrane lipid fluidity by increasing hopanoids (a subclass of triterpenoids) to resist high temperatures [52]. The thermophilic archaeon *Metahnocaldococcus jannaschii* can resist high temperatures by regulating membrane lipid composition. When these microorganisms were exposed to high temperature, the diether lipids decreased from 80% to 20%, while the caldarchaeol-based and cyclic archaeol-based lipids increased from 10% to 40% [53,54]. In addition, thermophilic microorganisms have evolved various biomolecules to induce thermal stability, e.g., by increasing the guanine/cytosine content of DNA or developing a positive supercoiled DNA structure [55]. Moreover, they not only possess very rich ribosomal proteins but also have a well-developed heat-shock response to allow normal protein synthesis even at high temperatures [56,57].

#### *2.4. Radiophilic Microorganisms*

Radiophilic (radio-tolerant) microorganisms can thrive in environments with high levels of radiation, including ultraviolet light and gamma rays. Previous studies on how they can adapt and survive under high-dose radiation and oxidative stress conditions have revealed that they possess robust DNA repair systems and antioxidation mechanisms to withstand intensive irradiation stress [58–63]. For example, RecA proteins from *Deinococcus radiodurans* R1, which is a representative radiophilic microorganism, plays a crucial role in repairing damaged DNA under gamma ray irradiation [63,64]. When it is exposed to a high dose of irradiation, the expression levels of several novel proteins (PprA, PprM, PprI, and DdrABCDO) and of DNA damage response regulons are dramatically increased and contribute to DNA repair and damaged genome reconstruction [65–68].

Radiophilic microorganisms also have efficient antioxidant enzymes, such as catalase (CAT), superoxide dismutase (SOD), and peroxidase, which are responsible for the scavenging of reactive oxygen species (ROS) [63,69]. For example, CATs and SODs from *D. radiodurans* exhibit a 30-fold higher ROS scavenging activity than radiation-sensitive bacteria such as *Escherichia coli* and *Saccharomyces cerevisiae* [63]. Moreover, non-enzymatic factors such as relatively high intracellular manganese concentrations, polyphosphate granules, carotenoids, and pyrroloquinoline quinone are also involved in the efficient scavenging of various ROSs as well as in the protection against protein damage [70–73]. Other non-enzymatic factors protecting biomolecules from ionizing radiation are a high intracellular Mn/Fe concentration ratio, orthophosphates, large amounts of free amino acids, and small peptides that have been found in the polyextremophilic microorganism *H. salinarum* [74].

#### **3. Bioremediation Using Extremophiles**

#### *3.1. Treatment of Heavy Metal Pollutants*

Concerns about the toxicity of heavy metals have been drastically increasing because even a tiny amount can be dangerous for public health and the environment. Moreover, currently used chemical treatments of toxic heavy metals under extreme conditions is often hampered by their poor accessibility. Thus, the development of sustainable bioremediation methods using extremophilic microorganisms for the treatment of heavy metals has been investigated during the past several decades (Table 1). In the case of extremely acidic conditions, acidophilic microorganisms that can thrive under low pH conditions have been used as host strains for the detoxification of heavy metals through biomining processes such as bioleaching and bio-oxidation [75–78]. There have been several reports on the development of bioremediation processes using *Acidothiobacillus* strains, which are the most common acidophilic and chemolithotrophic microorganisms. For example, industrial-scale bioleaching has

been performed using *Acidothiobacillus ferrooxidans* [79–81]. Romero-González et al. [82] reported the bioremediation of 100 mg/L of U(IV) ex situ from polluted mine water using *At. ferrooxidans* NCIMB 8455, while Jameson et al. [83] demonstrated the utility of *At. ferrooxidans* and *Acidothiobacillus ferrivorans* strains for hydrogen sulfide (H2S)-assisted copper precipitation (>99%) under acidic conditions (pH 2.5–2.6). In other studies, the efficient reduction of vanadium ions [vanadate; V(V)] to V(IV) and the biosorption of cadmium cations were successfully achieved by *Acidocella aromatica* PFBC and *Acidiphilium symbioticum* H8, respectively, under highly acidic conditions [84,85].

More efficient decontamination of toxic heavy metals can be obtained using a microbial consortium, a major advantage of which is to synergize different enzymatic systems and metabolic pathways of individual microorganisms. Recently, the bioaugmentation of heavy metals using an acid mine drainage (AMD)-isolated acidophilic microorganism consortium was performed on polluted port sediment. The extraction of more than 90% Cu2+, Cd2+, Hg2+, and Zn2<sup>+</sup> was successfully achieved using an acidophilic microbial consortium consisting of *Acidothiobacillus thiooxidans, At. ferrooxidans, Acidiphilium cryptum,* and *Leptospirillum ferrooxidans* [86]. Another study also reported the in situ bioremediation of AMD soil defined as highly acidic (pH 3.21), sulfate (6285 mg/L), and heavy metals. The introduction of an enriched microbial consortium composed of acidophilic microorganisms and metal-resistant strains of *Chloroflexi* (29%), *Acidobacteria* (21%), *Proteobacteria* (16%), and *Firmicutes* (2%) into AMD soil enabled 97% reduction of dissolved sulfate and increased the pH to 7.5 [87].

Halophilic microorganisms offer great advantages in the treatment of toxic pollutants in high-salt environments. For example, bioremediation using marine bacteria is a promising solution for the decontamination of seawater from toxic heavy metals, as these bacteria can survive at high salt concentrations. There have been a few reports on the removal of toxic heavy metals using several marine bacteria. For instance, *Vibrio harveyi* showed a good capability to accumulate cadmium cations inside the cell with a high adsorption capacity (up to 23.3 mg Cd2+/g of dry cells) [88]. Another marine bacterium, *Enterobacter cloaceae*, can chelate Cd, Cu, and Co by up to 65%, 20%, and 8%, respectively, from mixed-salts solutions [89]. In addition to marine bacteria, some thermophilic microorganisms such as *Geobacillus thermantarcticus* and *Anoxybacillus amylolyticus* have considerable biosorption capacity for heavy metals, which suggests their applicability for the removal of heavy metals in polluted environments [90].

As the development of biotechnology progresses, more advanced bioremediation methods that are superior to traditional methods have been reported. Unlike conventional bioremediation methods whose principle is based on the microorganism itself, new methods present improved efficiency and specificity thanks to the use of biomolecular engineering approaches. For instance, S-layer proteins, which have high stability and activity toward various heavy metals, are produced by lactic acid bacteria and are promising biomolecules for toxic heavy metal decontamination under very low pH (pH 2) conditions [91]. The S-layer proteins from *Lactobacillus plantarum* YW11 showed 99.9% Pb adsorption capacity [92]; scanning electron microscopy–energy dispersive X-ray analysis demonstrated that the Pb2<sup>+</sup> ions were efficiently adsorbed and accumulated on the cell surface of *L. plantarum* YW11 in a process mediated via S-layer proteins. The interaction of S-layer proteins from two *Lactobacillus kefiri* strains (CIDCA 8348 and JCM 5818) has also been investigated for the adsorption of various metal ions such as Cd2+, Zn2+, Pb2+, and Ni2<sup>+</sup> [93].


**Table 1.** Extremophilic microorganisms used in the removal of heavy metals.

<sup>1</sup> Either the experimental conditions or the tolerance of the species. ND, not determined; MIC, minimum inhibitory concentration. <sup>2</sup> Initial concentration of contaminant in the test. <sup>3</sup> Bioleaching, a metal solubilization process mediated by sulfur-/iron-oxidizing bacteria.

#### *3.2. Biodegradation of Organic Pollutants*

A variety of microorganisms can transform toxic organic pollutants into non-toxic substances such as petroleum hydrocarbons, aromatic petrochemicals, and various halogenated compounds (Table 2). Such complete transformation requires not only strong resistance to toxic organic pollutant exposure but also the ability to utilize toxic organic contaminants for their cellular metabolism. Therefore, extremophilic microorganisms that have adapted to harsh environments such as extreme temperatures and high salt concentrations over a long time period can potentially be widely used for the treatment of organic toxic pollutants under the corresponding condition. For example, the decontamination of polycyclic aromatic hydrocarbons and long-chain alkanes (C<sup>10</sup> to C32) using thermophilic *Bacillus*, *Thermus*, and *Geobacillus* strains isolated from oil-contaminated areas has been reported [95–99]; a *Geobacillus* SH-1 strain isolated from a deep oil well was also able to degrade saturated alkanes ranging from C<sup>12</sup> to C<sup>33</sup> and naphthalene. In another study, C12–C<sup>21</sup> *n*-alkanes were completely decomposed within 8 days, and 100 ppm of naphthalene was almost degraded within 72 h [100]. Furthermore, bioaugmentation through introduction of various extremophilic microorganisms including *Geobacillus thermopara*ffi*nivorans* IR2, *Geobacillus stearothermophilus* IR4, and *Bacillus licheniformis* increased the decontamination of long alkyl (C<sup>32</sup> and C40) substances [101].

**Table 2.** Extremophilic microorganisms used in the removal of hydrocarbons.


In addition to thermophilic microorganisms, psychrotrophic and halophilic microorganisms have shown excellent performance in the treatment of organic hydrocarbon pollutants. Low-temperature-adapted *Pseudoalteromonas* sp. P29 and *Oleispira antarctica* RB-8<sup>T</sup> exhibited high efficiencies in the degradation of hydrocarbon mixtures composed of diesel, military jet fuel, and crude

oil [102,103], while the halotolerant microorganisms *Marinobacter sedimentalis*, *Marinobacter falvimaris*, and *Marinobacter nanhaiticus* D15-8W were able to transform biphenyl, phenanthrene, anthracene, and naphthalene into useful carbon sources in hypersaline environments (e.g., salt lakes, salt marshes, and highly saline soils) [104,105]. In particular, extracellular polymeric substances (EPSs), which are cellular components of halophilic microorganisms, play a critical role in the remediation of organic pollutants from hypersaline environments. Exopolysaccharides secreted by halophiles can act as biosurfactants that contribute toward aggregating oils and emulsifying hydrocarbons, as well as offer cellular resistance toward toxic heavy metals. Halophilic microorganism *Halobacillus* sp. EG1HP4QL develops the ability to utilize crude oil as the sole carbon source within 12 days and to degrade paraffin (34.5%), naphthalene (49.6%), mono- and bicyclic aromatic hydrocarbons (51.2%), polycyclic aromatic hydrocarbon (43.5%), and alcohol–benzene resins (25.5%) [106]. EPS-producing *Halomonas* strain TG39 was also used for bioremediation of a hydrocarbon-contaminated Deepwater Horizon spill site [107]; the extracted EPS was effective not only in increasing the solubilization of aromatic hydrocarbons but also in enhancing the degradation rate of phenanthrene. Hence, bioremediation using extremophilic microorganisms is a promising method for the treatment of organic contaminant-polluted areas under extreme conditions because the organic pollutants can be metabolized by the microorganisms.

#### *3.3. Microbial Treatment of Radioactive Waste*

Recent advances in synthetic chemistry and separation methods have led to the design of various adsorbent systems including surface-modified nanomaterials and/or hybrid composites for the treatment of radionuclides in soil or aqueous media. For example, surface-modified iron oxide (Fe3O4) nanoparticles have been applied to selectively adsorb toxic heavy metals such as Cr(III), Co(II), Ni(II), Cd(II), Pb(II), and As3<sup>+</sup> from aqueous media [108]. Furthermore, engineered Au nanomaterials have been developed that are excellent adsorbents for the desalination of non-radioactive and radioactive iodine anions [109–111]. However, there are still several problems in the practical application of these methods. First, a large volume of secondary radioelement-contaminated solid adsorbents is generated during the desalination procedure, and so the removal of unsettled adsorbents after the treatment requires an additional expensive step. Second, small- (nano- or micro-) sized adsorbents tend to lose their stability and properties under particularly harsh conditions such as high salt concentration and high radiation. Therefore, employing extremophilic microorganisms that can be used as a live cleaning agent offer a useful alternative for the treatment of radioactive waste (Table 3).

The microbial treatment of radioactive waste can be accomplished through the interactions between microorganisms and radioisotopes, such as biomineralization, biotransformation, and biosorption [112–115]. Among these, mineralization of the target element inside bacterial cells has been proposed as the main strategy for the removal of radionuclides from a contaminated area [116,117]. As an example, *Shewanella* and *Geobacter* strains can reduce some alpha nuclides such as U(VI), Pu(IV), Am(V), and Th(IV) to make them harmless [15,114,116,118,119]. Anderson et al. reported the removal of uranium from aqueous media by using acetate-stimulating *Geobacter* species, while enhanced removal efficiency was demonstrated by supplementation with glucose, ethanol, and acetate as an electron donor [120]. Since the 1990s, a variety of extremophilic microorganisms that can thrive under high levels of ionizing radiation conditions (>15 kGy) have been identified [121–123]. Among these, *D. radiodurans,* which is one of the most radio-resistant microorganisms, has received much attention as a biological material for on-site treatment of radionuclide-contaminated environments [124,125] (Table 3). Moreover, a variety of studies investigating the development of the bioremediation processes using *D. radiodurans* for the removal of radionuclides pollutants have been reported [123,126–129]. A genetically engineered *D. radiodurans* strain expressing a non-specific acid phosphatase from *Salmonella enterica* serovar Typhi [127–129] or bacterial Ni/Co transporter (NiCoT) [130] can precipitate the oxidized form of uranium pollutants and radioactive cobalt (60Co), respectively.

In recent years, the combination of extremophilic microorganisms with nanotechnology has emerged as a central strategy in efforts to treat polluted environments. A few case studies including the biosynthesis of various nanomaterials using extremophilic microorganisms have been reported [131–135]. With the advent of nano-biotechnology, the combination of extremophilic microorganisms with nanomaterials (nano-adsorbents and reductants) will be a promising technology for useful bioremediation applications. For example, a highly efficient and stable method for the removal of radioactive iodine (125I) using *D. radiodurans* with biogenic Au nanoparticles has been reported [131], in which more than 3.7 MBq of <sup>125</sup>I was efficiently removed (>99%) within 30 min. More recently, the thermo-acidophilic archeon *S. tokodaii* 7 T (NBRC 100140) capable of synthesizing biogenic Pd(0) nanoparticles (mean diameter: 8.7 nm) showed four-fold increased Cr(IV) reduction with 2.0 mg Cr(VI)/L/h/Pd(0) compared to a commercial Pd/C catalyst [(0.5 mg Cr(VI)/L/h/Pd(0)] [136]. Another study also demonstrated efficient Cr(IV) reduction using Pd(0) nanoparticles synthesized by the acidophilic Fe3+-reducing bacteria *Ac. aromatica* PFBCT and *Ap. cryptum* SJH via a one-step microbiological reaction [137].

**Table 3.** Extremophilic microorganisms used in radioactive waste bioremediation.


#### **4. The Future Direction**

Pollution, which has emerged as a side effect of the rapid growth of industrialization and urbanization, is a worldwide threat to the environment and public health. Thus, the development of highly efficient and stable methods for cleaning up polluted environments has become a major challenge. Although a variety of conventional methods to remove toxic pollutants have been developed over the past several decades, there are still many hurdles that need to be overcome to realize practical applications [138]. Hence, extremophilic microorganisms, which can thrive under harsh conditions, have been receiving particular interest as bioagents for the removal of toxic pollutants.

Although conventional microbial bioremediation processes have succeeded in the removal of various toxic pollutants, current methods still require much effort to overcome their limitations in terms of cost-effectiveness, removal efficiency, and practicality. *E. coli* and *Bacillus* spp. are commonly considered host strains for microbial bioremediation processes, being well known due to their broad use with well-established genetic engineering tools [139,140]. However, despite intensive genetic engineering, the practical use of these microorganisms for on-site remediation is extremely limited, owing to their relatively weak resistance to harsh conditions and low removal efficiency. Thus, to overcome these limitations, subsequent strategies based on the combination of extremophilic microorganisms with advanced biotechnology from fields such as systems metabolic engineering, synthetic biology, and nanotechnology have enhanced the performance of bioremediation through reprogramming the nature of wild-type microorganisms [141,142]. Several approaches based on biotechnology and nanotechnology are (**1**) screening and identification of microorganisms that have a strong tolerance for harsh conditions, (**2**) making microorganisms capable of degrading a variety of environmental toxic pollutants, (**3**) increasing the removal capacity and specificity of microorganisms toward target pollutants, and (**4**) expanding the removal spectrum of microorganisms using biogenic nanoparticles. Moreover, a variety of advanced tools in bioengineering, such as in silico flux analysis, biostatistics, and multi-omics analysis, will allow us to access the possibly infinite potential of extremophilic microorganisms for the treatment of environmental toxic pollutants.

### **5. Conclusions**

When considering all the aspects presented in this review, extremophilic microorganisms appear as attractive bioagents for the clean-up of toxic pollutants contaminating the environment, due to their unique characteristics such as toughness, adaptability, and strong resistance to extreme conditions. Although many challenges still need to be addressed, the adoption of extremophilic microorganisms for the development of bioremediation processes is an environmental imperative for us to meet the needs of global public health. Indeed, combining extremophilic microorganisms with biotechnology and nanotechnology will open new avenues toward developing highly efficient and eco-friendly methods for the treatment of toxic pollutants (Figure 2).

**Figure 2.** A schematic diagram of advanced bioremediation using extremophilic microorganisms combined with biotechnology and nanotechnology. Representative candidates that can be used as a host strain for the treatment of pollutants in the environment are shown.

**Author Contributions:** S.-W.J. and Y.J.C. conceived and designed the review concept. S.-W.J. contributed to data curation and analysis. S.-W.J. and Y.J.C. wrote the manuscript. Y.J.C. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2019R1A6A3A01092533) and the Korea government (MSIT) (2020R1A2C4001737). This work was also supported by the C1 Gas Refinery Program (NRF-2017M3D3A1A01037019).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

1. Muddemann, T.; Haupt, D.; Sievers, M.; Kunz, U. Electrochemical reactors for wastewater treatment. *ChemBioEng Rev.* **2019**, *6*, 142–156. [CrossRef]


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### *Article* **Highly Efficient Methylene Blue Dye Removal by Nickel Molybdate Nanosorbent**

**Souad Rakass 1,\*, Hicham Oudghiri Hassani <sup>2</sup> , Ahmed Mohmoud 3,4, Fethi Kooli <sup>5</sup> , Mostafa Abboudi <sup>4</sup> , Eman Assirey <sup>4</sup> and Fahd Al Wadaani <sup>4</sup>**


**Abstract:** Removing methylene blue (MB) dye from aqueous solutions was examined by the use of nickel molybdate (α-NiMoO<sup>4</sup> ) as an adsorbent produced by an uncomplicated, rapid, and costeffective method. Different results were produced by varying different parameters such as the pH, the adsorbent dose, the temperature, the contact time, and the initial dye concentration. Adsorbent dose and pH had a major removal effect on MB. Interestingly, a lower amount of adsorbent dose caused greater MB removal. The amount of removal gained was efficient and reached a 99% level with an initial methylene blue solution concentration of ≤160 ppm at pH 11. The kinetic studies indicated that the pseudo-second-order kinetic model relates very well with that of the obtained experimental results. The thermodynamic studies showed that removing the MB dye was favorable, spontaneous, and endothermic. Impressively, the highest quantity of removal amount of MB dye was 16,863 mg/g, as shown by the Langmuir model. The thermal regeneration tests revealed that the efficiency of removing MB (11,608 mg/g) was retained following three continuous rounds of recycled adsorbents. Adsorption of MB onto α-NiMoO<sup>4</sup> nanoparticles and its regeneration were confirmed by Fourier transform infrared spectroscopy (FTIR) analysis and scanning electron microscopy (SEM) analysis. The results indicated that α-NiMoO<sup>4</sup> nanosorbent is an outstanding and strong candidate that can be used for removing the maximum capacity of MB dye in wastewater.

**Keywords:** nanosorbent; regeneration; α-NiMoO<sup>4</sup> ; methylene blue; removal

### **1. Introduction**

Dyes have recently been extensively utilized in several industrial and manufacturing applications, e.g., printing, textile, paper, carpet, and cosmetics. Dyes are considered toxic, hazardous pollutants and require removal before their discharge into the environment [1–7].

Numerous methods have been developed for dye removal from wastewater and industrial waste matter, including adsorption, coagulation, photodegradation, flocculation, membrane separation, ion exchange, biological treatment, chemical oxidation, and extraction [8–15].

Adsorption application is extensively employed due to its ease of process and guarantee of superb minimal cost from among those above-mentioned methods [1,16–21]. Several natural adsorbents have been successful in the elimination of color from aqueous waste

**Citation:** Rakass, S.; Oudghiri Hassani, H.; Mohmoud, A.; Kooli, F.; Abboudi, M.; Assirey, E.; Al Wadaani, F. Highly Efficient Methylene Blue Dye Removal by Nickel Molybdate Nanosorbent. *Molecules* **2021**, *26*, 1378. https://doi.org/10.3390/ molecules26051378

Academic Editors: Chiara Bisio and Monica Pica

Received: 31 December 2020 Accepted: 27 February 2021 Published: 4 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

matter [22–25]. A universally used example is activated carbon owing to the presence of its large surface area [26,27]. There are still some difficulties that limit its use, such as its high cost of production, low-quality mechanical properties, regeneration issues, and phase separation strain [28]. The challenge faced by the researchers is to develop novel adsorbents with boundless adsorption capabilities that are capable of being regenerated for the recovery of reusable compounds.

In recent years, researchers have shown a great interest in binary metal oxides due to their potential performances for different materials [29]. In recent years, scientists have paid extensively studied the group of metal molybdates which has given the most favorable examples of mixed metal oxides [30–33]. Nickel molybdate (NiMoO4) has various applications in catalysis such as hydrodesulfurization and hydrodenitrogenation reactions [34,35], oxidative dehydrogenation of light alkanes [36–40], partial oxidation of hydrocarbons [41], and microwave applications [42]. It is also used in humidity sensors [43], supercapacitors [44,45], optical fibers, and military devices [46]. Nickel molybdate has attractive structures and electrochemical and magnetic properties [47,48], and it can be found in two crystalline forms, α-NiMoO<sup>4</sup> and β-NiMoO4.

Various methods of NiMoO<sup>4</sup> synthesis have been presented in the literature, including sonochemical [49,50], hydrothermal [46,51,52], precipitation [53,54], sol–gel [53], mechanochemical synthesis [55], solid state at high temperature [56,57], and microwaveassisted methods [58].

Recently, molybdate compounds have attracted great interest for their utilization in environmental applications such as the photocatalytic oxidation of dyes [59–62], the oxidation of methylene blue (MB) dye [63], and the sorption of water-soluble dyes [30,61].

In particular, α-NiMoO<sup>4</sup> synthesized by the microwave-assisted method has shown good photocatalytic activity for methylene blue photodegradation [58]. In addition, NiMoO<sup>4</sup> nanostructures synthesized by the coprecipitation method were efficiently used as a catalyst for methyl orange photooxidation under UV irradiation [64]. Furthermore, hydrothermally synthesized β-NiMoO<sup>4</sup> was recently used as a sono-photocatalyst for the degradation of methylene blue (MB) under diffused sunlight [65]. However, α-NiMoO<sup>4</sup> has not yet been explored for the removal of dyes by adsorption.

In the present work, nickel molybdate nanoparticles, synthesized using a facile and easy method without the use of any solvents, were evaluated for removing methylene blue dye (MB) as adsorbents. MB dye was utilized as an ideal dye owing to its extensive manufacturing uses as a food coloring agent and for cotton, wool, silk, and leather, to name a few examples [60]. The influence of diverse parameters, namely solution pH, initial concentration, adsorbent dose, and contact time, on the removal of methylene blue by synthesized α-NiMoO<sup>4</sup> nanosorbents was examined. The kinetics and adsorption isotherms were evaluated. In addition, after the nanosorbent had been regenerated by calcinating at high temperature, the removal efficiency was likewise investigated.

#### **2. Results and Discussion**

#### *2.1. Removal of MB*

#### 2.1.1. pH Point of Zero Charge (pHpzc)

The pH point of zero charge (pHpzc) can provide information regarding the surface charge of a material. The results found for this parameter are given in Figure 1. In fact, the pHpzc of nickel molybdate was determined from graphs where the initial pH is equal to the final pH (intersection of curves). As shown in Figure 1, the nickel molybdate presented a surface charged negatively (pHpzc = 8.96). The surface of nickel molybdate became negatively charged for a pH of solutions >8.96 and acquired a positive charge when the pH was lower than 8.96. According to the literature, the cation uptake is favorable at a pH > pHpzc, whereas the uptake of anions is encouraged at a pH < pHpzc of sorbent [66]. The obtained pH point of zero charge value is close to those obtained for some metal oxides such as CuO and NiO, which are in the range of 9–10 [67].

**Figure 1.** pHpzc for nickel molybdate.

#### 2.1.2. Effect of pH

pH is essential in terms of controlling the removal of dyes. It has no effect on altering the separation of the adsorbent site; nevertheless, it modifies the structure and the chemistry of the dye [68]. Moreover, the charge and surface potential of the oxide are primarily pHdependent. It is possible, in some cases, to adjust the pH conditions of the slurry in such a way that all the particles exhibit the same charge polarity [68]. Hence, the effect of pH on the removal of MB by nickel molybdate (α-NiMoO4) nanosorbent was assessed by varying pH values between 3 and 11 at a controlled temperature of 20 ◦C with the initial concentration of 100 ppm. Figure 2 demonstrates that methylene blue removal depended on the effect of pH. By increasing the pH from 3 to 7, the removal percentage did not substantially change and remained at about 29%. The further increase of pH to 9 slightly increased the removal percentage to 35%. The increase of pH to 11 led to the highly efficient removal of MB, as the removal percentage reached 93%. Moreover, there was an increase in the quantity of dye eliminated for every unit mass of the adsorbent at its equilibrium (qe) from 25 to 93 mg/g.

**Figure 2.** Effect of pH on dye removal performance of α-NiMoO<sup>4</sup> in a 100 ppm methylene blue solution (mads = 0.1 g, T = 20 ◦C, t = 30 min).

Strong electrostatic interactions took place between the charges of the MB dyes and those of α-NiMoO<sup>4</sup> adsorbent, as demonstrated by the increase in removal percentage obtained with the increase of the pH values. Furthermore, in the solution at pH 11, the hydroxyl group (OH−) favors the direction of the positively charged MB as the pKa equals 3.8 [69]. Nevertheless, the lower removal performance at acidic values may well be related to the extra proton ions within the solution which are in concurrency with those of the basic dye cations on the removal sites of α-NiMoO4. Comparable outcomes were reported by Kooli et al. in the examination of waste bricks utilized as favorable agents for the removal of basic blue 41 from liquid solutions [70].

On the other hand, these results can be explained by the point of zero charge value measured for nickel molybdate (pHpzc = 8.96). The literature reports that at lower pH (pH < pHpzc), the surface charge may become positive, thus allowing H<sup>+</sup> ions to compete effectively with dye cations and causing a decrease in the amount of dye adsorbed [71]. At higher pH (pH > pHpzc), the nickel molybdate may become negatively charged, which enhances the positively charged cationic dye through electrostatic forces of attraction.

Thus, pH 11 was found to be the best value for the removal of MB when employing α-NiMoO<sup>4</sup> nanosorbent.

#### 2.1.3. Effect of Adsorbent Dose

One crucial parameter in adsorption processes is the adsorbent dose [72]. The MB dye removal using α-NiMoO<sup>4</sup> was explored with varying adsorbent doses of 0.001 to 0.5 g/L with an initial dye concentration of 160 ppm. As can be seen clearly in Figure 3, the percentage (%) and the amount (mg/g) of MB removed were reduced as the nanosorbent dose increased from 0.001 to 0.5 g/L. The decrease in the removal effectiveness might be due to the performance of particle interaction (e.g., aggregation) as a result of the high dosage of the adsorbent. Such aggregation could increase diffusional path duration. Furthermore, the adsorption sites remain unsaturated throughout the course of sorption under these conditions. In fact, all of these factors can lead to a decrease in available particle size [73,74].

**Figure 3.** Effect of adsorbent dose on the dye removal performance of α-NiMoO<sup>4</sup> in a 160 ppm methylene blue solution (t = 30 min, T = 20 ◦C).

#### 2.1.4. Effects of Initial Concentration and Contact Time

Figure 4 presents the effects of initial MB dye concentration and contact time on dye removal. The removal of MB was enhanced with the increase in contact time, reaching the highest value of 98% at around 30 min for initial methylene blue concentrations of 100 ppm. For MB concentrations of 120, 140, and 160 ppm, a maximum value of 99% removal was reached at around 60 min. However, the removal percentage of MB decreased from 99% to 76% as the Ci value was increased from 160 to 200 ppm. The removal amount remarkably increased from 9993 mg/g to 15,900 mg/g when the initial dye concentration increased from 100 to 160 ppm and remained stable when the concentration was increased to 200 ppm. This showed that the concentration gradient is an essential factor that drives the overcoming of the mass transfer resistances within the solid and liquid phases. The ratio of the solution connected with the α-NiMoO<sup>4</sup> surface was higher at lower MB concentrations, which triggered a rise in removal efficiency. In contrast, at higher MB dye concentrations, the decrease in the adsorption percentage was affected by the saturation of active sites on the α-NiMoO<sup>4</sup> surface [75].

**Figure 4.** Impact of the initial dye concentration and contact time on the methylene blue (MB) dye removal performance of α-NiMoO<sup>4</sup> (madsorbent = 0.001 g, T = 20 ◦C, pH = 11).

#### 2.1.5. Temperature Effect

The temperature is an essential factor that greatly affects the removal of dyes [76]. The procedure for removing the methylene blue dye was examined from 20 to 70 ◦C, as shown in Figure 5. The outcome of temperature experiments shows that the removal percentage increased from 70% to 100% and the removal capacity increased from 14,047 to 19,990 mg/g at an initial MB dye concentration of 200 ppm. The efficiency progression of MB removal with a rise in temperature was due to the intensity of attractive forces between removal sites and the MB, which shows an endothermic process [70]. In addition, increasing the temperature improves the removal motion of the adsorbent sites and the dye molecule motion [76].

**Figure 5.** The effect of temperature on the dye removal capacity of NiMoO<sup>4</sup> in a 200 ppm methylene blue solution (t = 30 min, pH = 11).

Thermodynamic factors are also important factors in adsorption processes [77,78]. The probability and the mechanism of adsorption can be predicted by the thermodynamic factors [77]. The following equations are used to determine the thermodynamic parameters:

$$
\Delta \mathbf{G}^{\diamond} = -\text{RTL} \mathbf{n} \mathbf{K}\_{\mathsf{d}} \tag{1}
$$

$$\mathbf{K\_d} = \frac{\mathbf{C\_a}}{\mathbf{C\_e}} \tag{2}$$

$$\text{LnK}\_{\text{d}} = \frac{\Delta \text{S}^{\text{o}}}{\text{R}} - \frac{\text{H}^{\text{o}}}{\text{RT}} \tag{3}$$

where R is the gas constant (J mol <sup>−</sup><sup>1</sup> K −1 ), ∆G◦ is the free energy, K<sup>d</sup> is the distribution constant, T is absolute temperature (K), Ca is the quantity of dye adsorbed by the adsorbent at equilibrium (mol/L), C<sup>e</sup> is the equilibrium concentration, ∆H◦ is the standard enthalpy,

and ∆S ◦ is the standard entropy. ∆S ◦ and ∆H◦ values were obtained from the intercept and slope of the ln K<sup>d</sup> versus 1/T plot (Figure 6). ∆G◦ values were obtained from Equation (1) and are shown in Table 1. The adsorption is favorable and spontaneous, and this is revealed by the negative value obtained for ∆G◦ . In fact, Gibbs free energy change (∆*G* ◦ ) values can discern whether a process is spontaneous or not, and negative values of ∆*G* ◦ imply a spontaneous process. The enthalpy change (∆*H*◦ ) provides information about the exothermic or endothermic nature of the process and differentiates between physical and chemical adsorption processes. Therefore, the positive value of ∆H◦ (35.12 kJ mol −1 ) shows that methylene blue removal followed an exothermic process. In addition, the (∆H◦ ) value was found to be less than 40 kJ/ mol, which indicates that the adsorption of MB by nickel molybdate is physisorption [79]. The present results are similar to the results reported by Xia [80] for adsorption of congo red from aqueous solution by CTAB–hectorite and ODA– hectorite composites. The enhanced anarchy and uncertainty in the solid solution interface of methylene blue and α-NiMoO<sup>4</sup> are shown by the positive values of ∆S ◦ . The adsorbate molecules move the adsorbed water molecules; consequently, translational energy is gained rather than lost, which indicates that this approach takes place randomly [81].

**Figure 6.** Van't Hoff plot presenting the impact of temperature on methylene blue dye removal utilizing α-NiMoO<sup>4</sup> .



#### *2.2. Kinetic Study*

Kinetic study of removal of methylene blue dye has been conducted as it provides an indication regarding the adsorption system [82].

The data found from the kinetics of removing MB dye using α-NiMoO<sup>4</sup> nanosorbent were examined by pseudo-first-order, pseudo-second-order, and intraparticle diffusion models. Equations of the studied models are shown in Table 2.


**Table 2.** Kinetic model equations.

Three model parameters, namely pseudo-first-order, pseudo-second-order, and intraparticle diffusion, are presented in Table 3 and displayed in Figure 7, Figure 8, Figure 9 respectively. Regression correlation coefficients (R 2 ) of the three models vary. Intraparticle diffusion is 0.934 to 0.981, pseudo-first-order ranges from 0.952 to 0.988, and pseudo-second-order is 0.999 to 1.000, varying with their concentrations used. The R 2 for pseudo-second-order is equal to or near 1, and hence this model fits very well.

**Figure 7.** Pseudo-first-order model plot showing the impact of contact time and initial dye concentration on methylene blue removal utilizing α-NiMoO<sup>4</sup> .

**Figure 8.** Pseudo-second-order model plot showing the impact of contact time and initial dye concentration on methylene blue dye removal utilizing α-NiMoO<sup>4</sup> .

**Figure 9.** Intraparticle diffusion model plot showing the impact of contact time and initial dye concentration on methylene blue dye removal utilizing α-NiMoO<sup>4</sup> .

**Table 3.** Kinetic parameters for removal of methylene blue utilizing α-NiMoO<sup>4</sup> .


#### *2.3. Adsorption Isotherms*

When planning adsorption methods, adsorption isotherms, which are known to be essential, are taken into consideration due to their perfect explanation [84]. Four adsorption models have been examined, namely Dubinin–Radushkevich, Temkin, Freundlich, and Langmuir models. Equations of the four examined models are presented in Table 4.


**Table 4.** Adsorption isotherm models for the removal of methylene blue dye utilizing α-NiMoO<sup>4</sup> .

> The models employed to match the investigational data were Freundlich, Langmuir, Temkin, and D–R isotherm. Standards of regression correlation coefficients (R 2 ) and the model parameters are displayed in Figure 10 and contained in Table 5. Langmuir equation demonstrated the highest value of R 2 (0.999), and D–R model revealed the lowest value of R 2 (0.782), while intermediary values were attained for Temkin and Freundlich (0.960 and 0.948, respectively). The Langmuir model fits the experimental results well; the methylene blue removal occurred on a homogeneous surface, establishing a monolayer on the α-NiMoO<sup>4</sup> adsorbent, with a high adsorption capacity of 16,863 mg/g. Methylene blue dye removal by α-NiMoO<sup>4</sup> is favorable and is revealed by the RL separation factor ranging from 0.0004 to 0.0006.

**Figure 10.** Freundlich (**a**) and Langmuir (**b**) isotherm model plots presenting the results of initial dye concentration and the removal of methylene blue dye utilizing α-NiMoO<sup>4</sup> .


**Table 5.** Isotherm parameters for the removal of MB dye utilizing α-NiMoO<sup>4</sup> .

Table 6 presents previous reports of the maximum amount of methylene blue dye removed. When compared with many nanosorbents, Nickel-based nanosorbents NiO (Qmax = 10,585 mg/g) and α-NiMoO<sup>4</sup> (Qmax = 16,863.00 mg/g) show a considerably higher rate of adsorption for MB. The adsorption capacity of Fe2(MoO4)<sup>3</sup> (Qmax = 6173.00 mg/g) is lower than that obtained by α-NiMoO4, which can be related to the difference in their specific surface area (8.03 versus 29.86 m2/g). Thus, α-NiMoO<sup>4</sup> has the advantage of being able to be synthesized at a rather low temperature via a relatively cost-effective, very simple procedure for use in potential novel, more efficient decontamination processes aimed at the removal of methylene pollutants.

**Table 6.** Previous reports of the maximum amount of methylene blue dye removed (qm).


#### *2.4. Regeneration and Characterization of the α-NiMoO<sup>4</sup> Nanosorbent*

2.4.1. Regeneration Performance

The repeatability and regeneration of nanosorbents are quite important for their practical applications. Regeneration techniques suggested in the literature include chemical extraction, thermal treatment, supercritical regeneration, microwave irradiation, bioregeneration, etc. [25,88,93–95]. The thermal regeneration, which has been applied for molybdenum oxide nanosorbent, was described in our previously published work [88]. In this investigation, the thermal treatment technique was examined for purposes of regeneration testing, as the structure of the α-NiMoO<sup>4</sup> removal agent was steady. The adsorbed MB was completely oxidized and decomposed during the calcination process.

The results showed that α-NiMoO<sup>4</sup> could be re-stimulated through thermal treatment. Figure 11 indicates the reused performance of α-NiMoO<sup>4</sup> in the removal of MB in three cycles. As a matter of fact, the data show a decrease in dye removal from 99% to 73% with a decrease in removal capacity from 15,900 to 11,608mg/g. The maximum adsorption capacity obtained after four cycles of use (11,608 mg/g) was higher than that obtained by several nanosorbents [30,87–92]. The high level of removal efficiency showed that the adsorbent regeneration by way of calcination under atmospheric air at a temperature of 400 ◦C was extremely efficient and indicative of outstanding recycling capability.

**Figure 11.** Recycled performance of α-NiMoO<sup>4</sup> in the removal of MB dye.

#### 2.4.2. Fourier Transform Infrared Spectroscopy

To completely recognize the method by which α-NiMoO<sup>4</sup> nanosorbent removes MB dye, the components subjected to MB dye were examined by FT-IR spectroscopy. Figure 12 shows the FTIR spectra for the α-NiMoO<sup>4</sup> sample before and after the removal of methylene blue dye. As observed, the characteristics of flexing and stretching vibrations of the metal– oxygen bonds at 966 and 930 cm−<sup>1</sup> and the broad, centered bonds at 650 cm−<sup>1</sup> correspond to nickel molybdate [96]. The FTIR spectrum of the pure methylene blue displayed bands between 1700 and 1000 cm−<sup>1</sup> [97]. The FTIR spectrum of NiMoO<sup>4</sup> after adsorption of methylene blue (NiMoO4-MB) displayed further bands located at 1600 cm−<sup>1</sup> , related to the C=C stretching of methylene blue, because of the presence of the methylene blue attached to the active sites of NiMoO<sup>4</sup> [98]. The FTIR spectrum of the regenerated NiMoO<sup>4</sup> (NiMoO4- MB-Reg) after thermal treatment and the FTIR spectrum of fresh NiMoO<sup>4</sup> were alike, indicating thorough combustion of the attached methylene blue on the surface, and the resulting spectrum showed the cleanness and performance of the regenerated adsorbent.

**Figure 12.** Fourier transform infrared spectra of NiMoO<sup>4</sup> , NiMoO<sup>4</sup> -MB, NiMoO<sup>4</sup> -MB-Reg, and MB. *2.5. Removal Mechanism of MB*

The removal of MB by α-NiMoO<sup>4</sup> nanoparticles was discovered to be due to the adsorption mechanism. Moreover, FTIR spectroscopy revealed that the removed methylene blue cations were triggered by the adsorption method without any intermediate compounds produced due to the absence of MB decomposition. Additionally, by using α-NiMoO<sup>4</sup> nanoparticles, the effectiveness of MB dye removal increased with the increase in pH up to pH 11, and this may be credited to its basic media. A reasonable mechanism can be proposed (Figure 13) on the basis of these findings. Furthermore, the positive charge of the MB dye is sustained in the first step at pH 11 since the pKa is equal to 3.8 [69]. Additionally, α-NiMoO<sup>4</sup> reacts with the hydroxyl groups (OH−) in the solution to generate the ion nickel molybdate (NiMoO<sup>5</sup> <sup>2</sup>−) with no intermediate compounds present [99]. Hence, the adsorption is directed by the strong electrostatic interactions between the negatively charged surface of nickel molybdate (NiMoO<sup>5</sup> <sup>2</sup>−) and the positive charge of methylene blue cations [88].

**Figure 13.** Schematic mechanism of the methylene blue dye removal by α-NiMoO<sup>4</sup> nanosorbent.

It is important to adhere to the progression of the α-NiMoO<sup>4</sup> morphology at different phases of the adsorption study. The SEM micrograph in Figure 14A gives an idea about how the particles form aggregates, showing a good porosity that can allow the improved adsorption of the dye. Nevertheless, the micrographs in Figure 14B,D,F show much less porous powder after the adsorption experiments; the methylene blue molecules filled the pores present in the starting samples. Figure 14C,E,G shows that the morphology of the sample did not change after the regeneration or the first and second reuses. In all cases, the particles were less agglomerated, displaying exceptionally porous powder. The morphology of α-NiMoO<sup>4</sup> was not significantly altered, even after the second and third reuses (Figure 14E,G).

**Figure 14.** SEM micrographs: (**A**) the starting material, pure nickel molybdate (α-NiMoO<sup>4</sup> ); (**B**) the material after the MB dye had been removed; (**C**) the regenerated α-NiMoO<sup>4</sup> ; (**D**) the material after the second regeneration and/or removal cycle of the methylene blue dye; (**E**) the morphology of α-NiMoO<sup>4</sup> after the second regeneration process; (**F**) the material after the third regeneration/removal cycle of methylene blue dye; (**G**) the morphology of α-NiMoO<sup>4</sup> after the third regeneration.

#### **3. Materials and Methods**

#### *3.1. Nickel Molybdate Nanosorbent Preparation*

All synthetic compounds aside from the methylene blue (provided by Panreac, Barcelona, Spain) were purchased from Sigma-Aldrich (St. Louis, MO, USA) and utilized as received with no alterations.

Nickel molybdate (NiMoO4) was formed by thermal breakdown of a nickel molybdenum complex obtained from the reaction of oxalic acid dihydrate H2C2O4·2H2O, nickel nitrate Ni(NO3)2·6H2O, and ammonium molybdate (NH4)6Mo7O24·4H2O in its solid form, as defined previously in the literature [32]. Nickel nitrate, oxalic acid dihydrate, and ammonium molybdate were blended jointly together in a molar proportion of 1/10/0.143. The mixture was powdered homogeneously and placed on a hot plate at a temperature of 160 ◦C for heating. The obtained nickel molybdenum complex was then decomposed under the control with static air at 500 ◦C for 2 h inside a cylindrical furnace, which was open at the two ends.

#### *3.2. Adsorption Experiments*

Experimental adsorption batches were set up for the removal of the MB dye [75]. The elimination of MB dye by NiMoO<sup>4</sup> was undertaken by the constant stirring of a precise quantity of adsorbent into a 100 mL MB dye solution with known concentrations and varied temperatures (such as T = 20, 50, and 70 ◦C) with various contact times (such as 10, 30, 60, 90, and 120 min). Toward the end of prearranged time intervals, before examination with a UV-Visible spectrometer, 0.22 µm syringe filters (Whatman) were used for filtration. Using 0.01 N NaOH or 0.01 N HCl, the pH of the methylene blue solution was easily adjusted. The removed quantity and percentage (%) of methylene blue dye at its equilibrium q<sup>e</sup> (mg/g) were calculated by the following equations:

$$\text{Removal }\%= \frac{\text{C}\_0-\text{C}\_e}{\text{C}\_0} \times 100\tag{13}$$

$$\mathbf{q}\_{\mathbf{e}} = \frac{(\mathbf{C}\_0 - \mathbf{C}\_{\mathbf{e}})}{\mathbf{M}} \times \mathbf{V} \tag{14}$$

where M stands for the mass of α-NiMoO<sup>4</sup> (g) added; V is the quantity of solution used (L); and C<sup>e</sup> and C<sup>0</sup> are equilibrium and initial concentrations of MB (ppm), respectively. The results were tested three consecutive times, and the percentage uncertainty was found to be around 3%.

#### *3.3. Adsorbent Regeneration Method*

A solution of 160 ppm was used for regeneration experiments, and the removal equilibrium period was extended by 1 h. The fresh α-NiMoO<sup>4</sup> used was filtered and dried under a constant temperature of 100 ◦C and then calcined at 400 ◦C for 1 h under atmospheric air. The calcined α-NiMoO<sup>4</sup> was examined to assess the recycling objectives under conditions similar to those for the freshly used α-NiMoO4. Once the first recycling test worked well, the restoration process was replicated for three consecutive cycles under consistent conditions.

#### *3.4. pH Point of Zero Charge (pHpzc) Measure*

The pH point of zero charge (pHpzc) of the material was measured by the electrochemical method reported by Altenor et al. [100]. First, 50 mL of a 0.01 M NaCl solution was placed in a 100 mL beaker. Then, the pH was adjusted to successive initial values between 2 and 12 by using either NaOH or HCl (0.1 M), and 0.001 g of nickel molybdate was added to the solutions. After a contact time of 24 h, the final pH was measured and plotted against the initial pH.

#### *3.5. Characterization*

Analysis of XRD patterns (X-ray diffractometer 6000, Shimadzu, Tokyo, Japan, installed with <sup>λ</sup>Cu-K<sup>α</sup> = 1.5406 ´Å and Ni filter) was conducted to characterize the phase composition of the synthesized α-NiMoO<sup>4</sup> nanosorbent, as presented in Figure 15.

**Figure 15.** X-ray diffraction pattern of the synthesized NiMoO<sup>4</sup> nanoparticle powder. The Joint Committee on Powder Diffraction Standards (J.C.P.D.S) index file number is 31-0902.

The specific surface area characterization was completed by using nitrogen isotherm adsorption in the same way as stated in our previous research work [32]. The recorded specific surface area was 29.86 m2/g.

FTIR spectroscopy in the range of 400 to 4000 cm−<sup>1</sup> (IR Affinity-1S Shimadzu apparatus, Tokyo, Japan) using KBr pellets confirmed the existence of methylene blue dye on α-NiMoO<sup>4</sup> nanoparticles following the experimental adsorption and regeneration studies.

SEM analysis (Quanta Feg 250, Thermo Fisher Scientific, Hillsboro, OR, USA) was conducted. UV-Visible spectrophotometer (Thermo Scientific Genesys 10S, Madison, WI, USA) was used to determine the concentration at equilibrium.

#### **4. Conclusions**

α-NiMoO<sup>4</sup> nanosorbent was synthesized and investigated as a material for the removal of MB dye from aqueous solutions. Removal of MB was extremely reliant on the pH, and this resulted in the achievement of 99% removal efficiency for initial dye concentrations between 100 and 160 ppm at pH 11. The kinetic findings suggested that the removal of methylene blue followed the pseudo-second-order model, and the equilibrium adsorption results were best fitted with the Langmuir isotherm model. The highest removal amount achieved was 16,863 mg/g, as determined by the Langmuir model. Calcination at 400 ◦C was effectively sufficient to regenerate the adsorbent for further reuse. Even after three cycles of reusing the adsorbent, the MB removal efficiency of NiMoO<sup>4</sup> was still high. The data proved that α-NiMoO<sup>4</sup> could be an effective nanosorbent offering outstanding performance in removing MB dye even after being recycled.

**Author Contributions:** Conceptualization, S.R., H.O.H., and A.M.; Methodology, S.R., H.O.H., and A.M.; Validation, S.R., H.O.H., F.K., M.A., E.A., F.A.W. and A.M.; Formal Analysis, H.O.H., S.R., A.M., M.A., and F.K.; Investigation, S.R., H.O.H., A.M., F.K., M.A. and E.A.; Resources, H.O.H., M.A., F.K., F.A.W., E.A. and S.R.; Data Curation, H.O.H., S.R., A.M., M.A., F.K. and E.A.; Writing-Original Draft Preparation, S.R., H.O.H. and A.M.; Writing-Review & Editing, F.K., M.A, S.R., A.M. and H.O.H.; Visualization, S.R., H.O.H., F.K., A.M., M.A., E.A. and F.A.W.; Supervision, S.R., and H.O.H.; Project Administration, S.R. and H.O.H.; Funding Acquisition, E.A., F.A.W. and M.A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Data Availability Statement:** The data that support the findings of this study are available from the corresponding author upon reasonable request.

**Conflicts of Interest:** The authors declare no conflict of interest.

**Sample Availability:** Samples of the compounds NiMoO4 are available from the corresponding author.

#### **References**


### *Article* **Silica Monolith for the Removal of Pollutants from Gas and Aqueous Phases**

**Vanessa Miglio 1,2 , Chiara Zaccone 1,2, Chiara Vittoni 1,2, Ilaria Braschi 2,3,\*, Enrico Buscaroli <sup>3</sup> , Giovanni Golemme <sup>4</sup> , Leonardo Marchese 1,2 and Chiara Bisio 1,2,5,\***


**Abstract:** This study focused on the application of mesoporous silica monoliths for the removal of organic pollutants. The physico-chemical textural and surface properties of the monoliths were investigated. The homogeneity of the textural properties along the entire length of the monoliths was assessed, as well as the reproducibility of the synthesis method. The adsorption properties of the monoliths for gaseous toluene, as a model of Volatile Organic Compounds (VOCs), were evaluated and compared to those of a reference meso-structured silica powder (MCM-41) of commercial origin. Silica monoliths adsorbed comparable amounts of toluene with respect to MCM-41, with better performances at low pressure. Finally, considering their potential application in water phase, the adsorption properties of monoliths toward Rhodamine B, selected as a model molecule of water soluble pollutants, were studied together with their stability in water. After 24 h of contact, the silica monoliths were able to adsorb up to the 70% of 1.5 × 10−<sup>2</sup> mM Rhodamine B in water solution.

**Keywords:** adsorption; toluene; rhodamine B; water stability of monolith

#### **1. Introduction**

In recent years, chemical industries have been focusing on sustainable development approaches, promoting products and services that offer performance at lower costs, reducing significantly the environmental impact and improving the quality of life.

In connection to these approaches, mesoporous materials have been synthesized in the form of powder and extensively studied for various applications (i.e., catalysis, adsorption, etc.). Nevertheless, on an industrial level, the use of powders for environmental applications has been severely hindered due to their handling and recycling limitations. Therefore, in recent years, research has been focusing on developing materials on a macroscopic scale, aiming at facilitating their handling, recovery and reuse in order to expand the range of their applications to different fields [1].

To overcome problems related to the use of powders there are two possible options: (i) use pre-synthesized silica powders to form pellets, or (ii) directly synthesize silica monoliths. In the first case, it is often necessary to use one or different binders (such

**Citation:** Miglio, V.; Zaccone, C.; Vittoni, C.; Braschi, I.; Buscaroli, E.; Golemme, G.; Marchese, L.; Bisio, C. Silica Monolith for the Removal of Pollutants from Gas and Aqueous Phases. *Molecules* **2021**, *26*, 1316. https://doi.org/10.3390/ molecules26051316

Academic Editor: Teofil Jesionowski

Received: 25 January 2021 Accepted: 24 February 2021 Published: 1 March 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

as methylcellulose) and to press the materials even under heating. This multistep timeconsuming procedure could adversely affect the structure of mesoporous silica, thus causing performance alteration [2]. In the second case, the formation of silica monolith can be a convenient way to fully exploit the structural and functional properties of the material [3] by saving, at the same time, both reactants and time, in that a single-step synthesis is required.

Several studies have been carried out in the recent literature to obtain monolithic siliceous structures. Galarneau et al. synthetized macroporous silica monoliths with disordered mesoporosity, prepared by the spinodal decomposition method [4]. Nakanishi and coworkers synthesized silica gel monoliths with macro-mesoporous hierarchical structure via a spontaneous sol–gel process from silicon alkoxide using a structure-directing agent and a micellar swelling agent [5]. Kohns et al. obtained silica monoliths with submicrometric macropores, introducing urea as an agent to control the size of macropores, mesopores and skeleton thickness [6]. Fotoohi et al. prepared mesoporous silica monoliths using a simple one-pot sol–gel synthesis with subsequent atmospheric evaporation [1]. Roucher et al. synthesized self-supported macro-mesoporous SBA-15-Si (HIPE) monoliths by combining emulsion and cooperative templating mechanisms [7].

Silica monoliths have been used in applications mainly related to the field of chromatography for the preparation of columns [8]. However, recent examples report on their use for the removal of chemical compounds such as fatty acids, phenols, and sterols from wastewater effluents: in these cases, they are mainly exploited as composite [9] or biocomposite materials [10] after the inclusion of biomolecules or enzymes. Few examples of the use of silica monolith also concern the preparation of composite [5] or functionalized materials for CO<sup>2</sup> adsorption [4,11]. Organic-modified silica monoliths are also used for the sequestration of heavy metals and for the immobilization of enzymes [12,13].

VOCs (Volatile Organic Compounds) are a group of noxious organic compounds characterized by vapor pressure higher than 0.01 kPa at 293.15 K. The group includes some of the most common air pollutants released by chemical, petrochemical and allied industries [14] such as aliphatic, aromatic and chlorinated hydrocarbons, aldehydes, terpenes, alcohols, esters and ketones. Due to their toxicity, the removal of these compounds by means of adsorbent materials [15] is of environmental concern and a relevant issue for human health. Several recent studies focused on the use of mesoporous ordered silicas, functionalized with organic groups, for the adsorption of VOCs [16]. The toluene adsorption properties of different porous silicas (i.e., fumed silica, SBA-15 and commercial MCM-41) have been recently reported by our group [16] and we have shown that the porous architecture of different silicas have an important effect on the final adsorption properties. In the same conditions, we also tested the adsorption behaviour of siliceous zeolites and hypercross-linked polymers [17]. We derived that whereas siliceous zeolite adsorbs 21 Q% of toluene, HyperCross-linked Polymers (HCPS) with flexible structures are able to adsorb more than 140 Q% of toluene.

Soluble dyes, such as Rhodamine B, Methylene blue, Congo red, Methyl Orange, etc., have been increasingly used for applications in different fields (i.e., food, paper, textiles, paints, pharmaceuticals, cosmetics, etc.) [18]. Their occurrence in industrial wastewater is worrying because they are harmful for ecosystems as well as animals and humans [19]. Although there are many treatment methods for removing dyes from aqueous solutions (e.g., chemical oxidation, photodegradation, membrane filtration), adsorption has been found to be a high-efficient and low-cost technology [20] and several sorbent materials such as activated carbons [21], clays [22], zeolites [23], activated alumina [24], etc., have been tested for this purpose. Among these, ordered mesoporous silicas are promising candidates due to their high specific surface area, uniform pore size and high pore volume.

For example, Rasalingam et al. showed that mesoporous MCM-48 and MCM-41 are able to remove, respectively, 87% and 81% of Rhodamine B from an aqueous solution at the concentration of 10−<sup>5</sup> M [25]. They found that, in the used conditions, the MCM-41 sample (having a specific surface area of 1453 m<sup>2</sup> ·g −1 ) is able to retain 8.2 × 10−<sup>4</sup> mol·g <sup>−</sup><sup>1</sup> of Rhodamine B. Others used MCM-41 (specific surface area of 1300.5 m<sup>2</sup> ·g −1 ) to remove Rhodamine B at 25 ◦C and pH = 4 and in these conditions the solids absorb ca. 9.4 × 10−<sup>4</sup> mol·g −1 [26].

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In this work, for the first time, mesoporous silica monoliths without any surface functionalization are proposed for the removal of organic pollutants from water and for the reduction of volatile organic compounds (VOCs). Model molecules (i.e., Rhodamine B and toluene, respectively) are used to this purpose. Our aim is to study the adsorption capacities of a silica-based monolith intended as a possible candidate to overcome limitations related to the use of mesoporous silica in powder form (i.e., handling and recycling issues). We focused on the optimization of a synthesis procedure for the direct formation, in a single work phase, of cylindrical mesoporous silica monoliths and to the determination of their physico-chemical properties by using different experimental techniques. The spatial textural homogeneity of the synthesized monoliths and the reproducibility of the synthesis were assessed. Moreover, the monoliths were tested for the removal of toluene, chosen as a model molecule of aromatic hydrocarbons, from gas phase. A combination of FT-IR spectroscopy and volumetric analysis was adopted to study the adsorption process and gain knowledge on the interactions between adsorbent surface and toluene molecule. Finally, the ability of the same monoliths to remove Rhodamine B from aqueous solution was also studied by using UV-Visible spectroscopy. Fundamental parameters of the monoliths for real water applications (i.e., mechanical and textural stability under operating conditions) [27] were verified as well.

#### **2. Results and Discussion**

#### *2.1. Physico-Chemical Characterization of Silica Monoliths*

The morphology of the silica monoliths, named Mono-ICE (see Section 3.1), was studied by using scanning electron microscopy (SEM). The obtained micrographs of samples before (A) and after the calcination step (B) to remove the polyethylene oxide template (PEO, see Section 3.1), are reported in Figure 1.

**Figure 1.** SEM micrographs (20000×) of Mono-ICE before (**A**) and after calcination (**B**).

μ μ The Mono-ICE sample after the spinodal phase separation process (Figure 1A) is characterized by an irregular morphology, where the particle aggregation gives origin to interconnected macropores with a diameter of 4 µm and a skeleton thickness of 3 µm, on average, in accordance with what it has been reported in the reference article [4]. After the formation of the macroporous monoliths in acidic medium at low temperature, the ammonia treatment at 40 ◦C brings about the rearrangement of the weakly condensed silica network into denser nanodomains and the formation of larger mesopores, giving rise to the final hierarchical SBA-15 [4]. After the calcination of the organics (Figure 1B), the sample morphology appears deeply modified, with a strong reduction of macropore dimensions to 0.5–1 µm, on average.

μ

The surface properties of the calcined silica monolith were then monitored by infrared spectroscopy (Figure S1 from Supplementary Materials). The FT-IR spectrum of Mono-ICE sample (Figure S1 from Supplementary Materials) is characterized by the presence of an intense band at 3743 cm−<sup>1</sup> , due to the O-H stretching mode of isolated silanol groups present on the silica surface, and a broad band between 3700 and 3200 cm−<sup>1</sup> with a maximum at 3521 cm−<sup>1</sup> and a shoulder at ca. 3654 cm−<sup>1</sup> , due to different surface silanol groups interacting with each other through hydrogen bonds. In the low frequency region, the spectrum shows three bands at 1983, 1863 and 1637 cm−<sup>1</sup> , due to overtones and combination modes of the silica framework [28]. − − − − −

Textural properties of the monoliths were determined by N<sup>2</sup> adsorption–desorption isotherms at 77 K. In order to investigate whether the physico-chemical properties were homogeneous throughout the entire length of the cylindrical monoliths, several samples were singly divided into three parts of 1 cm in length each and of a weight of about 50 mg: the obtained samples were named Mono-ICE-Lateral A, Mono-ICE-Lateral B, Mono-ICE-Central C, respectively. Nitrogen adsorption and pore size distribution of the samples are shown in Figure 2A,B, respectively.

**Figure 2.** N<sup>2</sup> adsorption and desorption isotherms at 77K (**A**) and pores size distribution (**B**) of calcined Mono-ICE-Lateral A (a), Mono-ICE-Lateral B (b), and Mono-ICE-Central C (c).

Following the IUPAC classification, all the isotherms obtained (Figure 2A) are of type IVa, thus indicating a multilayer adsorption, which is typical of mesoporous solids. Hysteresis loops of type H2, due to disordered materials with a distribution of pore size and shape that is not well-defined, are found. All samples show a monomodal pore size distribution between 50 and 200 Å with maxima at around 110 Å (Figure 2B). The textural features of the three samples are similar, and this strongly suggests that the cylindrical monolith under investigation is structurally homogeneous along the entire length (Table 1).

− − − − To assess the reproducibility of the synthesis method, N<sup>2</sup> adsorption–desorption isotherms of monoliths from two different synthesis batches have been determined (Figure S2 from Supplementary Materials). The monoliths considered have similar textural properties, in terms of specific surface area and pore volume. In particular, Mono-ICE-1st repetition and Mono-ICE-2nd repetition have, on average, a surface area of 889 and 810 m<sup>2</sup> ·g −1 , respectively. By averaging the two values, the Mono-ICE monoliths have approximately a surface area of 850 m<sup>2</sup> ·g −1 , with a total pore volume of 1.2 cm<sup>3</sup> ·g −1 . Such values are quite close to those (700 m<sup>2</sup> ·g −1 , and pore size of 12 nm) reported by Galarneau et al. for the monoliths prepared with similar procedure [4].

#### *2.2. Effect of the Water Treatment*

The stability in water of the monolith samples (Mono-ICE-Lateral A, Mono-ICE-Lateral B and Mono-ICE-Central C) and the possible modifications on the textural properties after contacting with water were evaluated by N<sup>2</sup> physisorption analysis conducted at 77 K. To speed up the process, the three samples were soaked in warm water (T = 50 ◦C) for 36 h [29]. Samples will be hereafter named Mono-ICE-Lateral A-36h, Mono-ICE-Lateral B-36h and Mono-ICE-Central C-36h, respectively.

For the sake of brevity, only the results about Mono-ICE-Lateral A sample before and after the water treatment are shown in Figure 3. Similar results were obtained for Mono-ICE-Lateral B and Mono-ICE-Lateral C samples (Figure S3 from Supplementary Materials).

 **Figure 3.** N<sup>2</sup> adsorption and desorption isotherms at 77 K (**A**) and pores size distribution (**B**) of calcined Mono-ICE-Lateral A () and Mono-ICE-Lateral A-36h (•).

− − The isotherms of the material before and after treatment in water at 50 ◦C show similar shapes, but at low pressure (P/P<sup>0</sup> < 0.1) the N<sup>2</sup> adsorption reduced to around 50% after the treatment in water (Figure 3A) because of the strong reduction in the amount of micropores (Figure 3B). The textural properties of the soaked material are indeed modified: (i) the surface area decreases from 909 to 455 m<sup>2</sup> ·g −1 (Table 1); (ii) the pore size increases from 115 to 169 Å (Figure 3B); (iii) the total pore volume slightly decreases from 1.3 to 1.1 cm<sup>3</sup> ·g −1 (Table 1). These changes are probably the effect of the hydrolysis and condensation of those parts of silica surrounding the micropores and characterized by a small radius of curvature, leaving a smoother surface inside the pores and enlarging the pore size [30]. Similar effects were also evidenced for other silica samples [29,31].

**Table 1.** Specific Surface Area and Total Pore Volume of Calcined Mono-ICE-Lateral A, Mono-ICE-Lateral B and Mono-ICE-Central C Samples, Before and After 36 h of Water Treatment.


<sup>1</sup> Brunauer-Emmet-Teller (BET) specific surface area (SSA); <sup>2</sup> Total pore volume by Barrett, Joyner, and Halenda (BJH) method.

#### *2.3. Toluene Adsorption from the Gas Phase*

Toluene adsorption on silica monoliths was studied from qualitative and quantitative point of view by using FT-IR spectroscopy and volumetric analysis.

The adsorption has been carried out on the Mono-ICE central sample after calcination. The IR spectra obtained after the admission of 30 mbar of toluene on the sample and subsequent gradual decrease of the vapour pressure are reported in Figure 4A.

 **Figure 4.** (**A**) FT-IR spectra of calcined Mono-ICE sample after outgassing at RT for 1 h (curve a, green), after dosages of 5, 10, 15, 20 mbar up to 30 mbar of toluene (curve f, orange), and after evacuation of toluene at RT for 30 min (curve g). (**B**) Toluene volumetric adsorption (full symbols) and desorption (empty symbols) isotherms of toluene at 35 ◦C on calcined Mono-ICE (a, ), and MCM 41 (b, •) samples.

− − π The admission of increasing toluene pressure on Mono-ICE silica samples (central part) (Figure 4A, curves b–f) results in a progressive disappearance of the band at 3745 cm−<sup>1</sup> , due to isolated Si-OH species, and into the contemporary formation of a broad band centered at 3600 cm−<sup>1</sup> . The progressive disappearance of the band related to isolated silanol species and to the formation of the band at lower frequencies is likely due to O–H···π interactions between silica silanols and toluene molecule [16].

Moreover, bands due to vibrations of the aromatic ring and the methyl group of toluene are also visible at lower wavenumbers. The vibrational modes of toluene adsorbed on the silica surface are described in Table 2.


**Table 2.** IR Bands Formed after the Adsorption of Toluene on Mono-ICE.

**−**

At higher pressure (above 5 mbar), the adsorption is likely driven by van der Waals interactions between the silica walls and the toluene molecules (host–guest interactions) and among toluene molecules (guest–guest interactions), as already observed elsewhere [16].

After decreasing the toluene pressure and subsequent evacuation at RT, the toluene has been fully desorbed: the band due to isolated SiOH species is completely restored, while the bands of toluene disappear (Figure 4A, curve g).

To gain information on the toluene uptake by the silica monolith, volumetric adsorption measurements at 35 ◦C were performed (Figure 4B). The isotherm of Mono-ICE sample (curve a) presents a complex shape where three regimes of adsorption are visible. In the

adsorption branch, three different plateau are visible between: 5 and 10, 20 and 25, 30 and 35 mbar (with a toluene uptake of ca. 25, 40 and 50%, respectively). This interpretation is confirmed by the almost disappearing signal of the isolated silanol groups at 3745 cm−<sup>1</sup> in the IR spectrum of Mono-ICE with toluene at 10 mbar (Figure 4A). On increasing the toluene pressure three adsorption steps are found, with a final toluene uptake of 85 Q%, or 1.00 cm<sup>3</sup> ·g <sup>−</sup><sup>1</sup> of liquid toluene. The desorption isotherm forms three shallow hysteresis loops in the ranges 10–25, 25–35 and 35–40 mbar are due to a capillary condensation of the toluene molecules inside the pores. This complex behavior could be associated with the filling of the heterogeneous porosity of Mono-ICE sample. Although the calcined monolith showed a monomodal pore size distribution, pores with diameters ranging from 50 to 200 Å are visible, as described before (vide Figure 2).

The maximum toluene uptake is 85 *Q*% at 41 mbar, where

$$Q\% = \frac{m \text{ adsorbed tolerance (mg)}}{100 \text{ mg of sample}} \tag{1}$$

The volumetric adsorption of toluene on silica monoliths has been compared to that of the reference mesoporous silica MCM-41 in the form of powder (Figure 4B, curve b) and already discussed in our recent publication [16]. For the sake of clarity, textural data of this sample are reported as supporting information (Table S1). Similarly to the Mono-ICE sample, the volumetric isotherm of toluene adsorbed on MCM-41 (Figure 4B, curve b) present three regimes of adsorption, however, only two hysteresis loops in the range 9–25 and 25–40 mbar, due to the toluene capillary condensation inside the pores, can be distinguished. The curve appears rapid until 9 mbar, and then the slope increases up to ca. 15 mbar, when the adsorption curve gradually tends to a first plateau at ca. 25 mbar with an uptake of ca. 59 Q%, which is associated with the filling of the fraction of mesopores with diameter lower than 40 Å (see pore size distribution, Figure S3B from Supplementary Materials). At pressures higher than 25 mbar, the slope increases again and progressively until 45 mbar, where the overall toluene uptake is ca. 78 Q%: the filling of the fraction of mesopores with dimensions from 40 to 80 Å likely occurs at this pressure.

It is here worth noticing that the overall toluene uptake for the two samples is similar, reaching 80–85 Q%, however the monolith adsorbs more at low pressure (<10 mbar). This effect should be correlated to the presence of micropores and narrow mesopores (ca. 20–30 Å) in Mono-ICE.

#### *2.4. Rhodamine B Adsorption*

The adsorption capacity of 1.5 × 10−<sup>2</sup> mM Rhodamine B by the monoliths was studied by UV-Vis spectroscopy, at room temperature. In particular, the characteristic absorption band at 553 nm of Rhodamine B, due to the π→π\* transition of the chromophore unit [32], was observed after contact with the monolith (Figure 5) at increasing times (1 to 24 h).

Figure S6 from Supplementary Materials shows the adsorbed amount of Rhodamine B as a function of concentration of Rhodamine B solution over time.

Rhodamine B is a weak acid (pKa 4.2) with good solubility (34 g·L −1 ) in water. Its organic part is a cation in which the positive charge is shared by the two N atoms. At pH values larger than 4.2, the carboxylic group is predominantly deprotonated and the prevalent form of Rhodamine B is a Zwitterion (Figure S7 from Supplementary Materials). As reported in the literature, Rhodamine B molecules adsorb on the mesoporous silica materials through electrostatic, hydrogen, nonpolar and n–π bonding interaction. The effective adsorption sites on the silica surface are composed mainly of OH and/or oxygen bridges. At a pH between 5 and 6, Zeta potential of silica was negative, and the surfaces of the adsorbent was negatively charged. The positive moieties in the Rhodamine B zwitterion are attracted onto the surface silanolate groups present in silica materials through electrostatic forces. In addition, the residual surface hydroxyls of the mesoporous materials may also form H-bonds with the COO<sup>−</sup> group present in the Rhodamine B zwitterion [25].

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− **Figure 5.** UV-Vis spectra, showing the intensity decrease of the maximum characteristic peak at 553 nm of 1.5 × 10−<sup>2</sup> mM Rhodamine B in water solution (**a**), after 1 (**b**), 2 (**c**), 3 (**d**), 4 (**e**), 5 (**f**), 6 (**g**) and 24 (**h**) hours of contact with the calcined Mono-ICE, at room temperature.

π

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π→π

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% = ௗ௦ௗ ௧௨ () ଵ ௦

−

It is reasonable to think that the Mono-ICE monolith, being entirely composed of silica, having a pH of 5.5 and a Zeta potential of −24 mV, behaves exactly in the same way. −

Figure 6 shows the relative concentration of the Rhodamine B in aqueous solution after contact with Mono-ICE sample at room temperature, before and after it has undergone water treatment, over the time. The measurements have been replicated three times and average values and relative standard deviations are reported in the figure.

− **Figure 6.** Concentration (%) decrease over time of 1.5 × 10−<sup>2</sup> mM Rhodamine B water solution in the presence of calcined Mono-ICE before () and after water treatment (•). Error bars represent standard deviations calculated on averaging results collected from three replicated experiments.

The concentration of the Rhodamine B solution decreases over time: 70% of the dye is removed from the solution after 24 h of contact with Mono-ICE before the water treatment (Figure 6, black squares).

The adsorption of Rhodamine B on calcined silica monoliths was compared with that on MCM-41 silica powder, before and after water treatment (Figure S5 from Supplementary Materials). MCM-41 powder (before water treatment) absorbs 58% of Rhodamine B after the first hour of contact, and 92% after 24 h. Rhodamine B adsorbs more rapidly in MCM-41, compared to the Mono-ICE monolith, probably because it is a powder; in the Mono-ICE monolith Rhodamine B has to diffuse in the macropore system before it may reach the mesopores.

After 24 h of contact with Mono-ICE after the water treatment (Figure 6, black circles), the adsorbed amount of Rhodamine B solution decreased by 50%, due to the modification of textural properties (i.e., surface area decrease, the pore size increase, total pore volume decrease) already described (Figure S4B from Supplementary Materials and Table S1).

Similar changes of textural properties are reported for the MCM-41 powder after treatment in water at 50 ◦C for 36 h (Figure S4 from Supplementary Materials).

MCM-41 silica powder has better performance than the monolith due to the faster diffusion of the pollutant in the pores and having a larger specific surface area; however, the monolith shows excellent adsorption properties and, above all, since it is not synthesized in the form of powder, it is more usable from a technological point of view. As reported in the work of Rasalingam et al. the adsorption capacity of Rhodamine B on MCM-41 silica synthesized by them (having an SSA of 1453 m<sup>2</sup> ·g −1 ) is 8.2 × 10−<sup>4</sup> mol·g −1 [25]. The Mono-ICE monolith has an adsorption capacity of 1.07 × 10−<sup>6</sup> mol·g −1 . Moreover, unlike MCM-41 silica which is not stable in water, the monolith possesses perfect stability.

MCM-41 is adsorbing more Rhodamine B than Mono-ICE basically for two reasons: (i) the SSA of MCM-41 is larger; (ii) the reduced radius of curvature of the MCM-41 pores favours a stronger interaction with Rhodamine B. In addition, since MCM-41 has a larger tendency to dissolve in water than Mono-ICE because of its thinner walls [16,30], MCM-41 may develop a larger amount of silanol groups per unit surface.

Owing to its instability in water, together with the difficult handing of the powder, the advantages in the use of the MonoICE monolith become evident.

#### **3. Materials and Methods**

#### *3.1. Materials*

Silica monoliths were obtained by adapting the procedure described by Galarneau et al. [4]. In detail, a mixture of nitric acid (2.31 g, HNO<sup>3</sup> 68 % *w*/*w*, Sigma-Aldrich 7697372, M.W. = 63.01 g·mol−<sup>1</sup> ), polyethylene oxide-PEO (2.5 g, Sigma-Aldrich 25322683, M.W. > 20 kDa) and deionized water (24.5 g) was prepared and refrigerated at −19 ◦C for 1 h. Then, tetraethylorthosilicate-TEOS (20 g, Si(OC2H5)4, Sigma-Aldrich 131903, M.W. = 208.33 g·mol−<sup>1</sup> ), previously cooled at −19 ◦C for 1 h, was added to the mixture (molar ratios of the optimized final composition: 1 Si/0.60 PEO/0.26 HNO3/14.21 H2O).

Polyvinylchloride tubes (five of 8 mm in diameter and seven of 6 mm in diameter and 10 cm length) were then filled with the mixture and closed with a cap, paying particular attention to keep everything cold throughout the whole process by means of an ice bath. Following, the filled tubes were put in a vertical position, held in place by an appropriate support, in a 4 L water bath at 40 ◦C for 3 days.

The formed monoliths were then removed from the tubes and placed in a water bath at room temperature (RT). The water bath was regenerated every 30 min until neutral pH. The monoliths were then immersed in 1 L of 0.1 M ammonia aqueous solution (NH4OH, Sigma-Aldrich 7664417, M.W. = 17.03 g·mol−<sup>1</sup> ) in a Teflon bottle, and placed in an oven at 40 ◦C for 1 day, to catalyze the Ostwald ripening of the weakly condensed silica. Finally, the monoliths were recovered, further washed in a water bath until pH neutrality, dried at RT for 4 days and then calcined in O<sup>2</sup> flow at 550 ◦C for 6 h to remove the PEO still present. The obtained silica monoliths were named Mono-ICE (Figure 7).

A monolith was divided into 3 parts of 1 cm in length each, and weighed about 50 mg: 48.9 mg for Mono-ICE-Lateral A, 50.4 mg for Mono-ICE-Lateral B and 55.5 mg for Mono-ICE-Central C.

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<sup>−</sup> −

**Figure 7.** Mono-ICE samples.

#### *3.2. Stability in Water Treatments*

Considering that silica monoliths are soaked in water during their usage as pollutants removers from aqueous phase, the stability in water is as an important characteristic that the adsorbent must have.

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To study the stability in water of silica monoliths (and the reference MCM41 silica powder), the solids (50 mg) were dispersed in 5 mL of water and the dispersion was heated at 50 ◦C for 36 h to speed possible degradation processes. Samples were then recovered and dried at 60 ◦C for 24 h.

#### *3.3. Characterization Techniques*

#### 3.3.1. Scanning Electron Microscopy (SEM)

SEM images were acquired on a Quanta 200 scanning electron microscope (FEI, Eindhoven, The Netherlands) equipped with tungsten filament as electron source. Before the analysis, a conductive coating of gold was deposited on the monoliths by low-pressure plasma to avoid that insulating particles are electronically charged under the electron beam.

#### 3.3.2. Infrared Spectra

Infrared spectra were collected by using a Thermo Electron Corporation (Whaltham, MA, USA) FT Nicolet 5700 spectrometer with 4 cm−<sup>1</sup> resolution. Self-supporting pellets of Mono-ICE samples were obtained by grinding a piece of silica monolith and compressing the obtained powder with a mechanical press at ca. 7 tons·cm−<sup>2</sup> . To perform the analysis, the obtained pellets were placed into an IR cell equipped with KBr windows permanently attached to a vacuum line (residual pressure ≤ 1 × 10−<sup>3</sup> mbar), allowing all treatments (and toluene adsorption/desorption experiments) to be carried out in situ. All the spectra were collected at beam temperature (ca. 35 ◦C) on samples previously dehydrated at RT for 30 min to completely remove the adsorbed water.

#### 3.3.3. Nitrogen Adsorption Measurements

Nitrogen Adsorption Measurements were conducted at AlfatestLAB S.R.L (Cinisello Balsamo, Italy). Experiments were performed at 77 K in the pressure range between 0.01 and 1 P/P<sup>0</sup> of relative pressure using a 3Flex instrument (Micromeritics, Norcross, GA, USA). Prior to adsorption, the samples were outgassed and thermally treated as follows: 3 h at RT, 30 min at 50 ◦C, 30 min at 80 ◦C, 2 h at 110 ◦C and 3 h at 220 ◦C. The specific surface area of the samples was determined by the Brunauer−Emmett−Teller (BET) multipoint method in the range between 0.05 and 0.25 P/P0. The pore size distribution was also calculated by applying the BJH (Barrett, Joyner, and Halenda) method on the adsorption branch (Thickness Curve: Halsey, Correction: Standard).

#### *3.4. Toluene Adsorption*

Volumetric Analysis. Toluene adsorption isotherms by gas phase were obtained at 35 ◦C by volumetric analysis of vapor sorption employing an Autosorb-iQ instrument (Quantachrome Instruments, Boynton Beach, FL, USA). Prior to adsorption, the samples were outgassed (final pressure 7 × 10−<sup>4</sup> mbar) and thermally treated as follows: 30 min at 50 ◦C, 30 min at 80 ◦C, 2 h at 120 ◦C, 2 h at 150 ◦C and, finally, 12 h at 220 ◦C in order to remove completely adsorbed water.

#### *3.5. Rhodamine B Adsorption*

The Rhodamine B adsorption experiments were conducted by using a Lambda 900 UV-Visible spectrometer (Perkin Elmer, Waltham, MA, USA). Rhodamine B (CAS Number: 81-88-9, IUPAC name: [9-(2-carboxy phenyl)-6-diethylamino-3-xanthenylidene] diethylammonium chloride, was purchased from Sigma Aldrich, St. Louis, MO, USA, (Analytical Standard). Before the experiment, a calibration line was obtained from five Rhodamine B standard solutions (2 × 10−<sup>2</sup> , 5 × 10−<sup>3</sup> , 2.5 × 10−<sup>3</sup> , 1.25 × 10−<sup>3</sup> , and 6 × 10−<sup>4</sup> mM), resulting in the equation A = 85.702 × C, with *R <sup>2</sup>* = 0.99995.

For the contact tests, 317 mg of sample was placed in a sealable glass vial with 63.4 mL of Rhodamine B solution 1.46 × 10−<sup>2</sup> mM (pH = 5.5). The bottles have been subsequently sealed with teflon-lined caps and placed on a mechanical stirrer (300 rpm) at RT. At different interval times (i.e., 1, 2, 3, 4, 5, 6, 24 h), an aliquot of each solution (ca. 1 mL) was then withdrawn and directly analyzed. Each experiment was repeated 3 times, every time using a fresh monolith.

Z potential of the monolith at the pH value of the Rhodamine B solution (pH = 5.5) was −24.6 mV.

#### **4. Conclusions**

In this work a synthesis procedure of mesoporous silica monoliths suitable for being used as adsorbents of organic pollutants in water (Rhodamine B), or in the gaseous phase (toluene, as a model of VOCs), was adopted.

Textural properties were found to be homogeneous over the entire length of the monolith, which has an average surface area of ca. 850 m<sup>2</sup> ·g <sup>−</sup><sup>1</sup> and a total pore volume of 1.2 cm<sup>3</sup> ·g −1 . After a water treatment (36 h at 50 ◦C), the specific surface area remained approximately 500 m<sup>2</sup> ·g −1 , and the total pore volume 1.1 cm<sup>3</sup> ·g −1 .

From a comparison between Mono-ICE and MCM-41 silica powder, it was found that both samples adsorb comparable amounts of toluene, and that the silica monolith performs better at low pressure (<10 mbar).

Monoliths before and after the water treatment were tested as adsorbents for Rodamine B in aqueous solution. Although the water treatment reduced the specific surface area, the treated material was still able to adsorb 50% of the Rhodamine B with respect to 70% of the control sample.

The silica monolith prepared in this study shows slightly worse performances in the adsorption of Rhodamine B when compared to the silica MCM-41 powder, however it displays several advantages including greater ease in handling and recovering.

**Supplementary Materials:** The following are available online: Figure S1. FT-IR spectra of selfsupported pellets of Mono-ICE calcined sample after treatment in vacuum at beam temperature (b.t.) for 30 min; Figure S2. Comparison between the first repetition (Frame A) and the second repetition (Frame B) of N2 adsorption and desorption isotherms of Mono-ICE-A (a), Mono-ICE-B (b) and Mono-ICE-C (c); Figure S3. N2 adsorption and desorption isotherms (Frame A) and pore size distribution (Frame B) of Mono-ICE-A-36h (a), Mono-ICE-B-36h (b) and Mono-ICE-C-36h (c). Figure S4. N<sup>2</sup> adsorption and desorption isotherms (Frame A) and pores size distribution (Frame B) of MCM-41 -before and after water treatment at 50 ◦C for 36 h; Figure S5. Concentration (%) decrease over time of 1.5 × 10−<sup>2</sup> mM Rhodamine Rhodamine B in water solution in the presence of commercial MCM-41 powder. Table S1. Main textural features of MCM-41 silica.

**Author Contributions:** Conceptualization, V.M., C.Z. and C.B.; methodology, C.Z.; validation, C.V., and V.M.; investigation, V.M., C.V., C.Z.; resources, C.B.; data curation, V.M., C.V. and C.Z.; writing original draft preparation, V.M., C.V., and C.Z.; writing—review and editing, C.B., E.B., I.B., G.G. and L.M.; supervision, C.B. and L.M.; project administration, C.B.; funding acquisition, C.B. and L.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the University of Bologna *"2*◦ *Bando "Proof of Concept d'Ateneo" (PoC UNIBO)—Finanziamento a supporto dello sviluppo di invenzioni brevettate" and by the Italian Ministry of the Economic Development "Bando per la realizzazione di programmi di valorizzazione dei brevetti tramite il finanziamento di progetti di Proof of Concept (PoC) delle Università italiane, degli Enti Pubblici di Ricerca (EPR) italiani e degli Istituti di ricovero e cura a carattere scientifico (IRCCS)."* Decreto direttoriale del 27 settembre 2019, registrato alla Corte dei Conti il 10 ottobre 2019, Reg. n. 1-968.

**Data Availability Statement:** Not available.

**Conflicts of Interest:** The authors declare no conflict of interest.

**Sample Availability:** Samples of the compounds are available from the authors.

#### **References**


### *Article* **Volcanic Rock Materials for Defluoridation of Water in Fixed-Bed Column Systems**

**Wondwosen Sime Geleta 1,2 , Esayas Alemayehu 3,4,\* and Bernd Lennartz 2,\***

	- Tel.: +251-91-701-7002 (E.A.); +49-381-498-3180 (B.L.)

**Abstract:** Consumption of drinking water with a high concentration of fluoride (>1.5 mg/L) causes detrimental health problems and is a challenging issue in various regions around the globe. In this study, a continuous fixed-bed column adsorption system was employed for defluoridation of water using volcanic rocks, virgin pumice (VPum) and virgin scoria (VSco), as adsorbents. The XRD, SEM, FTIR, BET, XRF, ICP-OES, and pH Point of Zero Charges (pHPZC) analysis were performed for both adsorbents to elucidate the adsorption mechanisms and the suitability for fluoride removal. The effects of particle size of adsorbents, solution pH, and flow rate on the adsorption performance of the column were assessed at room temperature, constant initial concentration, and bed depth. The maximum removal capacity of 110 mg/kg for VPum and 22 mg/kg for VSco were achieved at particle sizes of 0.075–0.425 mm and <0.075 mm, respectively, at a low solution pH (2.00) and flow rate (1.25 mL/min). The fluoride breakthrough occurred late and the treated water volume was higher at a low pH and flow rate for both adsorbents. The Thomas and Adams–Bohart models were utilized and fitted well with the experimental kinetic data and the entire breakthrough curves for both adsorbents. Overall, the results revealed that the developed column is effective in handling water containing excess fluoride. Additional testing of the adsorbents including regeneration options is, however, required to confirm that the defluoridation of groundwater employing volcanic rocks is a safe and sustainable method.

**Keywords:** adsorption; breakthrough curve; defluoridation; up-flow mode; volcanic rocks

#### **1. Introduction**

Credible evidence from scientific literature substantiates both beneficial and detrimental effects of fluoride on human health with only a narrow range between intake associated with these effects [1,2]. Consumptions of fluoride in low concentrations (<1.0 mg/L) is an essential micronutrient for the healthy development of bone and dental enamel [3]; however, it leads to the development of fluorosis if it is consumed beyond the permissible limit (>1.5 mg/L) [4].

In many parts of the world, groundwater sources are the single largest supply of drinking water. For many rift communities, it may be the only economically viable option for drinking water. In the Ethiopian rift valley, about 40% of deep and shallow wells are contaminated with up to 26 mg/L of fluoride [5,6]. The weathering of primary rocks and leaching of fluoride-containing minerals in soils yield fluoride-rich groundwater in the Ethiopian Rift, which is generally associated with a low calcium content and high bicarbonate concentrations [7,8].

**Citation:** Geleta, W.S.; Alemayehu, E.; Lennartz, B. Volcanic Rock Materials for Defluoridation of Water in Fixed-Bed Column Systems. *Molecules* **2021**, *26*, 977. https:// doi.org/10.3390/molecules26040977

Academic Editor: Giorgio Vilardi Received: 7 December 2020 Accepted: 8 February 2021 Published: 12 February 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Globally, more than 200 million people, including Ethiopia, rely on groundwater with a fluoride concentration above the permissible level [3,4,9]. According to the Central Statistical Agency of Ethiopia report [10], 3.8% of the population is affected by high-level fluoride concentrations (>1.5 mg/L) in groundwater, which is used for drinking purposes. In general, fluorosis turns out to be the most widespread geochemical-based disease in the East African rift, affecting more than 80 million people [11–14]. Thus, due to the health effect of high fluoride in groundwater, it is essential to reduce excess fluoride concentrations to the allowable limit (<1.5 mg/L).

So far, various technologies such as coagulation/precipitation, electro-coagulation, membrane separations, ion exchange, and adsorption had been attempted for efficient defluoridation of groundwater [15–18]. Some of the shortfalls of these techniques include expensiveness, fouling issues, regular maintenance, and complicated operational procedures. In comparison to the techniques mentioned above, the adsorption methodology is still one of the most widely applied methods, taking the lead of high removal efficiency, cost-effectiveness, ease of operation, simplicity of design, and availability of large varieties of adsorbents [19,20].

Various adsorbents have been investigated and reported for the removal of excess fluoride from water in an effective manner. Some of the widely employed adsorbents are La (III)-Al (III)-activated carbon modified by chemical route [21], biomaterial functionalized cerium nanocomposite [22], Quaternized Palm Kernel Shell (QPKS) [23], bone char and activated alumina [24], bone char [25], renewable biowaste [26], MgFe2O4–chitosan–CaAl nanohybrid [27], carbon nanotube composite [15], Neem Oil-Phenolic Resin Treated Biosorbent [17], etc. However, many of these suffer from either time-consuming synthesis procedure, high processing costs, availability of raw materials, or short lifespan, which makes them impractical to be applied in the rift valleys that are essentially impacted by high fluoride concentration in water [1]. Consequently, efforts have been made to obtain easily accessible and long-lasting, low-cost, and efficient adsorbents that may be applied for the purification of water in low-income countries such as Ethiopia.

In recent years, volcanic rocks (VPum and VSco) have received significant interest for pollutant removal due to their valuable properties such as high surface area, low-cost, easy accessibility, good mechanical resistance, and availability in large quantities [28]. The source of these rocks is volcanic magma that formed during volcanic eruptions. Pumice (VPum) is a finely porous rock frothy with air bubbles; Scoria (VSco) is a rough rock that seems like furnace slag [28]. VPum is often formed from rhyolite magma [28], it can also develop from trachytic or dacitic magma. Due to its high porosity and low specific gravity, it has been used for water and wastewater treatment processes [29]. VSco is a vesicular pyroclastic rock with basaltic compositions, reddish-brown to black, denser than VPum, somewhat porous with high surface area and strength. Both volcanic rocks are found in abundance in Europe (Italy, etc.), Central America, Southeast Asia (Indonesia, etc.), and East Africa (Ethiopia, Eritrea, etc.) [28,29]. Although several studies have been conducted on the application of volcanic rocks for pollutants-laden wastewaters [28–31], very little research has been directed to the defluoridation of groundwater using volcanic rocks.

Previously, defluoridation research has been conducted on batch experiments using natural adsorbents [6,32]. The sorption capacity of adsorbents gained from batch equilibrium is valuable in giving basic information about the effectiveness of the adsorbents. Nevertheless, the data obtained from batch studies may not be appropriate for continuous processes where the contact time for the achievement of an equilibrium might be insufficient [33]. Consequently, studies by different authors [34–36] reveal that continuous processes mode (fixed-bed column set-up) yields reliable information about the breakthrough time, appropriate adsorption conditions, and the stability of the adsorption performance which can then be used to evaluate the potential of prepared adsorbents for industrial applications [1]. Therefore, there is an interest to conduct adsorption studies in a flow-through system.

The primary objectives of the current work were to (i) investigate the fluoride sorption capacity of VPum and VSco in fixed-bed column set-up, (ii) compare the adsorption properties of both adsorbents with each other, (iii) assess the fluoride adsorption mechanisms with respect to varying solution pH, adsorbent particle size, and flow rate, (iv) deeper analyze the adsorption processes employing mathematical models such as the Adams–Bohart and Thomas model, and (v) finally verify the suitability of the models for the design of flow-through systems for the removal of fluoride from aqueous solutions.

#### **2. Results and Discussions**

#### *2.1. Characterization of Adsorbents*

#### 2.1.1. Crystalline Structures and Material Properties and Experimental Conditions

The crystalline phases of VPum and VSco were characterized using the X-ray diffraction (XRD) instrumental technique. The mineralogical composition of the adsorbents was characterized by matching the X-ray diffractogram (Figure 1a (VPum), b (VSco)) with the database of the X'pert HighScore Plus software package (Version: 2.2b (2.2.2)). The results showed that the main crystalline phases in VSco were Silicon Oxide (SiO2), Albite low (Na(AlSi3O8)), whereas Hematite (Fe2O3) and Silicon Oxide (SiO2) and Albite high (Na(AlSi3O8)) are the dominant components of VPum. The presence of crystalline phases in VPum samples can be ascribed to the peaks at 2*θ* = 24.9◦ , 27.6◦ , 27.7◦ , 37.7◦ , 41.9◦ , 58.0◦ , 64.9◦and 65.0◦ , while that of VSco sample appeared at 2*θ* = 22.2◦ , 23.9◦ , 23.9◦ , 23.9◦ , 28.2◦ , 30.0◦ , 33.9◦ , and 35.8◦ . The detected dome in both samples between 2*θ* = 10◦ and 40◦ is an indication of amorphous material. The amorphous phase(s) present in the adsorbents was estimated by the calibration method. This method makes use of the integrated counts associated with the amorphous and crystalline fraction (Equation (1)) [37].

$$\mathbf{C\_m(\%)} = \left[\frac{\mathbf{C\_{pa}}}{\mathbf{A\_{pa}} + \mathbf{C\_{pa}}}\right] \times 100\tag{1}$$

where C<sup>m</sup> is the measured crystallinity, Cpa and Apa are the integrated peak areas for the crystalline and amorphous components, respectively. The results revealed that the presence of the amorphous phase (s) in VPum and VSco is 89% and 68%, respectively.

**Figure 1.** XRD patterns for (**a**) virgin pumice (VPum) and (**b**) virgin scoria (VSco).

The greater fraction of amorphous phase(s) in VPum compared with VSco possibly origins from simultaneous rapid cooling and depressurization of high-temperature volcano lava. The depressurization produces bubbles by lowering the boiling point of the lava. The simultaneous cooling then freezes the bubbles in the matrix of VPum. Due to rapid cooling, crystals do not have enough time to grow. A similar observation has been reported from the XRD analysis of pumice in previous studies [38,39].

Additionally, the results of material properties and experimental conditions were summarized in Table 1 as shown below.


**Table 1.** Material properties and experimental conditions.

#### 2.1.2. Chemical Composition

The chemical analysis revealed that the major elements in VPum and VSco, as determined by ICP-OES (Table S1), are Si, Al, and Fe. Other elements were present in comparatively smaller quantities or below the detection limit of the instrument. In our previous study [28], the XRF measurement (Table S1) indicated that the oxides of Si, Fe, and Al were the major constituents of both VPum and VSco.

However, the chemical composition of the adsorbents might changes in time due to weathering processes. Consequently, representative samples have to be checked for possible changes induced due to weathering.

#### 2.1.3. Fourier Transform Infrared (FTIR) Analysis

The FTIR spectrums of VPum (Figure 2a) and VSco (Figure 2b) at wavelengths ranging from 4000 to 400 cm−<sup>1</sup> are shown in Figure 2. Due to the symmetric stretching vibration of Si-O-Si, the absorption band at ∼1045.75 cm−<sup>1</sup> can be assigned to the characteristic peak of (SiO4) <sup>2</sup><sup>−</sup> groups in the FTIR spectrum of VPum [39], whereas the band located at ∼1011.5 in the FTIR spectrum of VSco can be belongs to the asymmetric stretching vibration of T-O-Si, T = Si or Al [40]. In the FTIR spectrum of VPum, the peaks at ∼781 and ∼695.25 belong to bending vibrations of Si-O-Si bond [38], whereas the band shown in the FTIR spectrum of VSco at ∼759 is related to the stretching vibration of 6-fold coordinated Al(VI)-OH and 6-fold coordinated Al(VI)-O [41]. The small peaks shown in the FTIR spectrum of VSco at ∼572 and ∼539.25 can be attributed to the symmetric stretching of Si-O-Si and Al-O-Si [40,42], whereas the small band at ∼465 belongs to bending vibrations of Si-O-Si and O-Si-O [42]. Certain peaks like the broadening peak at ∼3602.5 cm−<sup>1</sup> in the FTIR spectrum of VPum and sharper peak at ∼2369.75 cm−<sup>1</sup> in the FTIR spectrum of VSco belongs to the asymmetric stretching vibration of -OH bond can be allocated to adsorbed water molecules, whereas the peak at ∼1645.75 cm−<sup>1</sup> in VPum can be allocated to the bending vibration of H-O-H bond [38,39,42]. The most characteristic difference observed between the FTIR spectrum of VPum and FTIR spectra of VSco concerning the band attributed to the asymmetric stretching vibration of -OH bond. This band that is appeared as a broad band at about ∼3602.5 cm−<sup>1</sup> in the FTIR spectrum of VPum becomes sharper and shifts to lower frequencies (∼2369.75 cm−<sup>1</sup> ) in the FTIR spectrum of VSco indicating that there is a high water content in VPum and could be correlated with less mechanical strength than VSco. Similar observations have been reported for a different system [42].

**Figure 2.** Fourier-transform infrared (FTIR) for (**a**) VPum and (**b**) VSco.

#### 2.1.4. Scanning Electron Microscope (SEM) Analysis

The VPum (Figure 3a) and VSco (Figure 3b) SEM micrographs allowed direct observation of the surface morphology of the adsorbents with a magnification of ×100. The structure of VPum showed that the surface of VPum had an interconnected porous surface [38,43], while VSco had an irregular shape and fibrous cavities (or pores). In addition, it may be said that these pores in VSco were either closed or in open forms (pores) [44]. As seen from the micrographs of the adsorbents, VPum had an interconnected inner porous surface (as indicated in Figure 3a, red-colored), while VSco (Figure 3b) is dominated by the dead-end pores. Consequently, the interconnected internal pore structure in VPum allows for better fluoride accessibility and, hence, better adsorption capacity than VSco.

**Figure 3.** SEM micrographs for (**a**) VPum and (**b**) VSco.

#### 2.1.5. pH and Point of Zero Charges (pHPZC)

The pH of the rock samples in water was found to be 6.65 and 7.20 for VPum and VSco, respectively. The point of zero charges (pHPZC) of the adsorbents was identified as 6.85 for VPum and 6.98 for VSco at the intersection of the graph of the initial pH vs. the final pH (Figure 4). The slight difference observed in the adsorbents pHpzc is related to their different characteristics. As can be seen from Table S1, the two volcanic rocks

(VPum and VSco) have different chemical compositions, which also influence the surface charge of the adsorbents. This is in agreement with previous studies [30,45], showing the effect of chemical composition on the zeta-potential of different materials. Below these values (pH < 6.85 for VPum and <6.98 for VSco), the surface of the adsorbents is positively charged. Thus, if the pH < pHPZC, fluoride could possibly be adsorbed onto the surface of the adsorbents by coulombic attraction [6,46,47]. In addition, the curve for the blank experiment (for blank electrolyte solution 0.01 M NaCl) of both adsorbents is shown in Figure 4. As seen from the blank curve (Figure 4), a pH change without adding the adsorbents was obtained, which confirmed the sorbent dosing is not the only factor to fluctuate the pH of the solution.

**Figure 4.** Determination of pH point of zero charges (pHPzC) for (**a**) VPum and (**b**) VSco.

#### *2.2. Effect of Adsorbents Particle Size*

The effect of the particles size on the breakthrough behavior of fluoride was investigated for both VSco and VPum with grain size classes of silt to medium sand (<0.075, 0.075–0.425, 0.425–2.00 mm), while maintaining the same initial fluoride concentration (10 mg/L), bed depth (10cm), initial flow rate (1.25 mL/min), as well as solution pH (2.00) (Figure 5a (VPum), b (VSco)). As seen from Figure 5a (VPum) and b (VSco), on reducing the particle size from medium (0.425–2.00 mm) to silt (<0.075 mm) the breakthrough and exhaustion time noticeably increased for VSco, while the breakthrough and exhaustion time was high for VPum at a fine particle size (0.075–0.425 mm). The resulting breakthrough and removal of fluoride parameters are tabulated in Table 2. As can also be seen from Table 2, the amount of total adsorbed fluoride (qtot) and the uptake of fluoride was high at silt (<0.075 mm) and fine (0.075–0425 mm) particle size for VSco and VPum, respectively. The smaller particle sizes provide large surface areas and/or sorption sites are more readily available. The results showed that the reduction of particle size of an adsorbent is a significant controlling factor in the fluoride–VSco system (at a particle size of <0.075 mm the fluoride uptake was high). A similar effect was observed for VPum (at a particle size of 0.075–0.425 mm the fluoride sorption capacity was high). However, the effect of particle size on the adsorption capacity is more pronounced for VSco than VPum. That means the pore spaces are more readily available in VPum as compared to VSco, showing that the pore space of VPum is a continuum (skeletal structure) while the pore space of VSco is dominated by dead-end pores. This infers VPum loses its internal porosity at the smallest particle size (<0.075 mm) since the continuum pore space (skeletal structure) is damaged when compared to the fine particle size (0.075–0425 mm) and resulting in smaller internal

pore surface areas; consequently, the removal capacity of the adsorbent decreased. On the other hand, the pore space is not readily available in VSco (i.e., the internal pore space of VSco is dominated by dead-end pores). VSco at the smallest particle size (<0.075 mm) is, therefore, expected to have a large surface area, which leads to higher removal capacity compared to the fine particle size (0.075–0425 mm). A similar observation was reported for both adsorbents based on a batch adsorption experiment [28], and a similar remark was also drawn for pumice in the previous study [38]. Moreover, the BET specific surface area (SBET) of the adsorbents was determined. As expected, VPum (3.50 m2/g) has a larger surface area than VSco (2.49 m2/g). Thus, all experiments other than the effect of particle sizes were conducted at a particle size of <0.075 mm for VSco and 0.075–0.425 mm for VPum.

**Figure 5.** Effect of particle sizes on the breakthrough behavior of fluoride in (**a**) VPum and (**b**) VSco at (pH 2.00; influent fluoride concentration 10 mg/L (CO: 10 mg/L); flow rate 1.25 mL/min (QO: 1.25 mL/min; bed depth 10 cm).


**Table 2.** Fixed-bed column parameters obtained for fluoride adsorption onto VPum and VSco.

t<sup>b</sup> = breakthrough time, t<sup>e</sup> = exhaustion time, V<sup>b</sup> = total effluent volume at breakthrough time, V<sup>e</sup> = total effluent volume at exhaustion time MTZ = Mass Transfer Zone, EBCT = Empty Bed Contact Time, qtotal = total amount of fluoride adsorbed from the column, q<sup>e</sup> = equilibrium fluoride uptake per kg of adsorbent.

#### *2.3. Effect of Influent pH*

The influent solution's pH can noticeably affect the anions sorption on the adsorbents by changing the degree of ionization, the ion speciation, and the adsorbent's surface charge. Therefore, the effect of solution pH on adsorption of fluoride using VPum and VSco was investigated at different pH (2.00, 4.00, and 6.00) by a separate set of fixed-bed adsorption columns. The breakthrough curves obtained for both adsorbents are shown in Figure 6a,b for a fixed inlet flow rate of 1.25 mL/min, influent fluoride concentration of 10 mg/L, column bed depth of 10 cm, and a particle size of <0.075 mm for VSco and 0.075–0.425 mm for VPum.

**Figure 6.** Effect of pH on the breakthrough behavior of fluoride in (**a**) VPum: 0.075–0.425 mm and (**b**) VSco: <0.075 mm (CO: 10 mg/L; QO: 1.25 mL/min; bed depth 10 cm).

As can generally be observed from Figure 6a, b, the adsorption capacity of the adsorbents noticeably increased with decreasing pH. As can also be seen from Table 2 (VPum and VSco), the total amount of fluoride adsorbed (qtot) was high for VPum (29.24 mg) and 16.08 mg for VSco at lower pH of 2, and the breakthrough time decreased from 1206 to 135 min for VPum and 415 to 227 min for VSco with an increase in pH from 2 to 6. The volume of water treated at the breakthrough time was higher at pH of 2.00 (1507.5 mL for VPum and 518.03 mL for VSco) than 4.00 (347.5 mL for VPum and 370 mL for VSco) and 6.00 (168.75 mL for VPum and 283.75 mL for VSco). This concludes the occurrence of the breakthrough time was longer, the amount of fluoride adsorbed, and treated water volume was high for a pH of 2.00. As pH varies, surface charge also varies; the sorption of charged species is affected. Therefore, the performance of adsorbents for better adsorption at low pH may be the result of the presence of a large number of H<sup>+</sup> ions at low pH values, and hence neutralize the negatively charged adsorbent surface [48], consequently dropping the interference of the adsorption of fluoride. In addition, this reality can be elucidated based on the pH value at the point of zero charges of the adsorbents (pHPZC = 6.85 (VPum) and 6.98 (VSco)).

Moreover, the decrease in the adsorption of fluoride at pH 4.00 and 6.00 could also be due to the decrease in the number of H<sup>+</sup> or electrostatic repulsion of fluoride by negatively charged adsorbent surface [47,49].

Hence, the sorption of fluoride ions is due to an electrostatic phenomenon and surface complexation that perform independently or together for the adsorption of fluoride ions on the adsorbents. The removal mechanism at pH < pHPZC is presumably due to columbic attraction of fluoride by positive surface charges (Equation (2)) and/or ligand exchange reactions of fluoride with surface hydroxyl groups (Equation (3)).

$$\rm{MOH\_2^+} + \rm{F^-} \leftrightarrow \rm{MOH\_2^+} - - - \rm{F^-} \tag{2}$$

$$\rm MOH\_2^+ + F^- \leftrightarrow \rm MF + H\_2O \tag{3}$$

where, M represents Fe, Al, Si, Ca, Mg, etc.

In this study, an increment in the final pH (pH ∼7.20) was observed after the completion of the adsorption experiment, which is consistent with the columbic or ligand exchange type adsorption mechanism shown in Equations (2) and (3) [47]. This can be further explained by the capacity of the adsorbents to maintain a neutral pH after adsorption [6,50]. The capacity to maintain neutral effluent solution pH could be from the amphoteric nature of oxides in both adsorbents (Al2O3, Fe2O3, TiO2, etc.) when compared with the effect of basic metallic oxides (Table S1). This type of observations were reported for the removal of pollutant in a previous study [6]. Furthermore, the elemental compositions of exchangeable cations also play a critical role in fluoride uptake during defluoridation [51]. There might be a slight increase in electro conductivities of the final solutions, which might not influence the adsorption process [52]. However, additional testing of the effluent solution for various compounds may be required to draw definite conclusions.

It is noted that the effect of pH on the adsorption capacity may be due to the shared impact of pH on the nature of the adsorbent surface, the existence of the adsorbed pollutant (fluoride ion), and the added acid and base to the working solution to adjust its pH. In this study, the optimum and effective removal of fluoride takes place at a pH of 2.00; hence, all experiments other than the effect of pH were conducted at a pH of 2.00 for both adsorbents.

#### *2.4. Effect of Flow Rate*

The effect of flow rate on the adsorption of fluoride using VPum and VSco was examined at the flow rates of 1.25, 2.50, and 3.75 mL/min whereas the bed depth (10 cm), influent solution pH (2.00), initial fluoride concentration (10 mg/L), and adsorbents particle size (<0.075 mm (Vsco) and 0.075–0.425 mm (VPum)) were held constant. As indicated in Figure 7a (VPum) and b (VSco), the breakthrough curves become steeper and shifted to the origin with an increasing flow rate while the breakthrough time decreased. The use of a high flow rate decreases the contact time of fluoride in the solution with the adsorbents, thereby allowing earlier breakthroughs to occur. Additionally, increasing the flow rate from 1.25 to 3.75 mL/min decreased the volume of water treated from 1507.5 to 282.69 mL and 518.03 to 256.03 mL for VPum and VSco, respectively (Table 2).

**Figure 7.** Effect of influent flow rate on the breakthrough behavior of fluoride in (**a**) VPum: 0.075–0.425 mm and (**b**) VSco: <0.075 mm (pH 2; CO: 10 mg/L; bed depth 10 cm).

This was further supported by Mass Transfer Zone (MTZ) (Table 2) which increased with increasing flow rate. The total fluoride adsorbed (qtot) increased from 4.49 mg to 29.24 mg for VPum and from 3.10 mg to 16.08 mg for VSco (Table 2) as the flow rate decrease

from 3.75 to 1.25 mL/min. This results in the increase of the adsorption performance of the column from 17 to 110 mg/kg and 4.2 to 22 mg/kg for VPum and VSco, respectively (Table 2). The increase in sorption efficiency at a low flow rate shows that the adsorbates have sufficient time to penetrate and diffuse deeply into the pores of the adsorbents; hence, intraparticle mass transfer controls the sorption process. This was also verified by MTZ (Table 2) or unused bed, which decreased with decreasing flow rate. In general, at the lower flow rate, the contact time between the adsorbent and the fluoride was higher, resulting in an increased breakthrough time and treated water volume for the continuous column adsorption system. A similar type of observation was reported by various authors for fixed-bed column systems [53–55]. In this study, the optimum and effective removal of fluoride takes place at a flow rate of 1.25 mL/min; so, all experiments other than the effect of flow rate were performed at a flow rate of 1.25 mL/min.

#### *2.5. Application of the Thomas Model*

The values of the Thomas model parameters, K<sup>T</sup> and q<sup>o</sup> for both adsorbents shown in Table 3 for different experimental parameters were found from the non-linear optimization techniques according to Equation (18). The non-linear plots of the experimental (designated as exp.) and simulated (designated as cal.) breakthrough curves based on the Thomas model for VPum (a) and VSco (b) at different particle sizes (Figure S1), influent pH (Figure S2), and influent volumetric flow rate (Figure S3) were provided in Supplementary Materials. The results of KT, qo, and correlation coefficient (R<sup>2</sup> ) are shown in Table 3 for VPum and VSco. From the results, it can be seen that the values of R<sup>2</sup> range from 0.897 to 0.993 for VPum and 0.901 to 0.973 for VSco.

**Table 3.** Thomas model parameters for fluoride adsorption onto VPum and VSco.


The high values of R<sup>2</sup> indicate there were no significant disparities between the experimental data points and calculated data by the Thomas model for all particle sizes, influent solution pH, and influent volumetric flow rate. The observed differences between the experimental data and calculated data from the Thomas model may be due to the characteristic attribute weakness in the model. The Thomas model does not consider the external (film) and intra-particle diffusions in the adsorption system and, therefore, proposes adsorbate–adsorbent surface reactions to control the adsorption rate, hence the breakthrough. However, nearly all adsorption operations are typically not limited to surface reaction kinetics, but are also controlled by external and/or intra-particle diffusion [56,57]. Thus, the perceived disparities in this study indicate external and/or intra-particle mass transfer may be the rate-controlling steps in fluoride adsorption in a fixed-bed column

onto the adsorbents. Similar observations were drawn with the kinetic study of fluoride under fixed-bed conditions onto modified pumice [57]. As shown in Table 3, the value of the Thomas rate constant (KT) increased as the influent flow rate increased but the value of the maximum solid-phase concentration (qo) decreased. A related type of investigation on Thomas constants for different systems was reported by various authors [58,59].

*2.6. Application of the Adams–Bohart Model*

The parameter values of the Adams–Bohart model, KAB and NO, as depicted in Table 4 for Vpum and Vsco were similarly determined by non-linear regression analysis according to Equation (19).


**Table 4.** Adams–Bohart model parameters for fluoride adsorption onto VPum and VSco.

From the results presented in Table 4, it can be realized that the values of R<sup>2</sup> range from 0.911 to 0.993 for Vpum and 0.886 to 0.969 for VSco. The high values of R<sup>2</sup> designate the applicability of the Adams–Bohart model for describing the entire sorption mechanisms of fluoride onto VPum and VSco under a continuous fixed-bed flow process.

In a similar fashion with the Thomas model, the comparison of the non-linear plots of the experimental and calculated breakthrough curve, based on the Adams–Bohart model, are generally in good agreement for VPum (a) and VSco (b) at different particle sizes (Figure S4), influent solution pH (Figure S5), and influent flow rate (Figure S6) respectively. Only minor disparities were noticed at lower pH (2.00) and particle sizes of 0.075–0.425 mm and <0.075 mm for VPum and VSco, respectively. As seen in Table 4, the values of the kinetic constants were affected by the influent flow rate and increased with increasing flow rate. This presented that external mass transfer in the entire fluoride adsorption mechanisms in the fixed-bed column dominates the overall system kinetics [57,60]. In general, both the Adams–Bohart and the Thomas models could predict very well the entire region of the breakthrough curves for the fluoride-VSco and fluoride-VPum systems. In addition, both the Adams–Bohart model (Equation (19)) and the Thomas model (Equation (18)) are mathematically the same and, therefore, gave similar fit quality.

#### *2.7. Comparison of Different Adsorbents on Fluoride Removal*

A comparison has been made between volcanic rocks (VPum and VSco) used in this study and previously reported adsorbents for fluoride removal in a fixed-bed column system. The results for some adsorbents are presented in Table 5.


**Table 5.** Comparison of other adsorbents with VPum and VSco.

NA\*: Not available.

As can be seen from these results in Table 5, the natural VPum used is comparable to cement paste and aluminum modified iron oxide in terms of defluoridation capacity. Values of adsorption capacity per unit surface area are, however, higher for VPum than those of acid-treated bentonite (GHB), kanuma mud, and activated alumina; and higher for VSco than acid-treated bentonite (GHB) and activated alumina (Grade OA-25) (Table 5). Both adsorbents are available in abundance in all parts of the world and are readily available in approximately 1/3 of Ethiopia's total area and are, hence, favored adsorption materials because of very low supply costs. The adsorbents used are primarily part of the natural environment. However, to improve the specific surface area and hence the defluoridation capacity, surface modification of the natural volcanic rocks may be appropriate.

#### **3. Materials and Methods**

#### *3.1. Materials*

In this study, rock samples were collected from volcanic cones (VPum: 8◦10′ N 39◦50′ E; VSco: 8◦33′ N 39◦16′ E) of the Main Rift Valley area of Oromia Regional State, East Showa Zone, Ethiopia, around 50–100 km East of Addis Ababa. The rocks are readily available in approximately 1/3 of the country's total area and are, thus, a preferred adsorption material because of very low supply costs [29,48,66].

#### *3.2. Preparations of Adsorbents*

The rock samples (VPum and VSco) were washed repeatedly with deionized water until all water-soluble compounds and dust were removed, and thereafter dried at 55 ◦C for 48 h [30,67]. After cooling samples down to room temperature, they were crushed with a mortar and sieved using different mesh sizes: silt (<0.075 mm), fine sand (0.075–0.425 mm), and medium sand (0.425–2.00 mm) [28,68]. All prepared samples were packed in air-tight plastic bags and stored at a cool and dry place for further use.

#### *3.3. Preparations of Adsorbate*

All glassware and bottles were thoroughly washed and rinsed with deionized water before usage. Chemicals used were analytical grade reagents and a fluoride stock solution (1000 mg/L) was prepared freshly by dissolving 2.21 g of anhydrous NaF (Merck KGaA, Darmstadt, Germany) in 1000 mL of deionized water. The synthetic fluoride solution of desired concentrations was made by diluting the stock solution. 0.1 M of NaOH and/or 0.1 M HCl solutions were used to adjust the pH values of the fluoride solution utilized in the column experimental experiments.

#### *3.4. Adsorbent Characterizations*

#### 3.4.1. Crystalline Structures

The crystalline structures of the adsorbents were analyzed by an X-ray diffractometer (XRD-7000, Drawell, Shanghai, China) with Cu Kα as a radiation source (1.54056 Å) generated at 30 kV and 25 mA instrument. The diffractograms were gained with a step width of 2θ and a scan rate of 0.04◦/min.

#### 3.4.2. Chemical Composition

The elemental composition of the adsorbents was analyzed using inductively coupled plasma-optical emission spectroscopy (ICP-OES). X-ray fluorescence (XRF) spectroscopy was used to obtain information on the oxide contents of the adsorbents.

#### 3.4.3. Fourier Transform Infrared (FTIR) Analysis

FTIR spectra of the samples were run on KBr pellets. The spectra were recorded over a range of 5000 to 400 cm−<sup>1</sup> at a resolution of 0.1 cm−<sup>1</sup> in a PerkinElmer spectrometer (UNSW Sydney, Australia) using a lithium tantalite (LiTaO3) detector.

#### 3.4.4. Scanning Electron Microscope (SEM) Analysis

A scanning electron microscope (SEM) (JCM-6000plus, Version 0.2, Peabody, MA, USA), operated at 15 kV, was used to determine the morphologies of VPum and VSco. The characteristics of the adsorbents were compared.

#### 3.4.5. Determination of pH and Point of Zero Charges (pHPZC)

The pH of the adsorbents was determined using a pH meter in a 1:10 adsorbent/water ratio as per the standard method [6]. The pH at the point of zero charges (pHPZC) of the adsorbents was examined based on the standard method. For this effect, 250 mL of 0.01 M NaCl solution as an electrolyte was positioned in a vessel, thermostated at 298 K, and N<sup>2</sup> was bubbled through the solution to stabilize the pH by preventing the dissolving of CO<sup>2</sup> from the air. In 6 Erlenmeyer flasks, 25 mL of the electrolyte was introduced and the pH was adjusted to the required value (2.00, 4.00, 6.00, 8.00, 10.00, and 12.00) by adding 0.1 M NaOH or 0.1 M HCl. The same procedure and method were performed for blank electrolyte solution (0.01 M NaCl). In each beaker, 0.25 g of the rock samples were added and shaken for 48 h. The suspension was subsequently filtrated and the final pH was determined. The point of zero charges (pHPZC) was found at the intersection point by plotting the initial pH versus the final pH.

#### 3.4.6. BET Analysis

The specific surface area (*SBET*) of the adsorbents was measured using a nitrogen gas adsorption-desorption technique at 77k using surface analyzer equipment (Micrometrics/ Gemini-2372). The samples were degassed at 300 ◦C under vacuum for at least 6 h before analysis. The Brunauer-Emmett-Teller (BET) equation was used to obtain a specific surface area (*SBET*). The *SBET* values of the two adsorbents (VPum and VSco) are compared.

#### *3.5. Column Adsorption Experimental Set-Up and Procedures*

Continuous fixed-bed column adsorption studies were carried out to assess the dynamic behavior of fluoride removal by using VPum and VSco. Continuous flow adsorption experiments were conducted in a small-scale cylindrical column of 8.1 cm internal diameter and 10 cm height with an empty bed volume of 515 cm<sup>3</sup> . The column was filled with a weighted amount of adsorbent of different particle sizes (silt: <0.075 mm, fine sand: 0.075–0.425 mm, and medium sand: 0.425–2.00 mm). The same particle size was used if controlling parameters such as pH and flow rate were tested. The bed was conditioned with deionized water (pH: 7.00–7.30) for 12 h (overnight) to ensure a closely packed adsorbent and to avoid the potential occurrence of voids, channeling, or cracking, which can significantly affect the performance of the column.

A synthetic fluoride solution with a concentration of 10 mg/L was pumped to a packed bed column in up-flow mode to avoid channeling caused by gravity. The influent volumetric flow rate varied between experiments but was held constant in a given experiment using an adjustable peristaltic pump (MS-REGLO, Labortechnik-Analytic, Zürich, Switzerland). The experiments were conducted at room temperature (25 ± 2 ◦C). The effluent column sample was collected using an automatic fraction collector (RFI, MA-RON GmbH, Germany). The constant flow rate was verified by collecting and quantifying the effluent solution at regular time intervals. The column operation was stopped when the concentrations of the fluoride in the effluent exceeded 90% of its initial concentrations. Ion chromatography (930 Compact IC Flex, Metrohm, Switzerland) was used to quantify fluoride concentrations. The instrument uses 3.2 mmol/L Na2CO3/1.0 mmol/L NaHCO<sup>3</sup> as eluent, Metrosep A Supp 5–150/4.0 column, and a standard conductivity detector to measure the conductivity of the effluent solutions. The fluoride concentration was measured in the calibration range of 0.2–200 mg/L, contains inline dilution, inline dialysis, eluent degasser, CO<sup>2</sup> suppressor, and chemical suppressor. Suppression in IC maximizes the detection sensitivity of fluoride ions while reducing the background conductivity of the eluent.

The maximum tolerable breakthrough concentration (Cb) was 1.5 mg/L (15% of the influent initial concentration of 10 mg/L), which is recommended by WHO [4] as a maximum acceptable level for drinking water.

The effect of experimental parameters such as particles size (silt: <0.075 mm, fine sand: 0.075–0.425 mm, and medium sand: 0.075–0.425 mm), influent solution pH (2.00, 4.00, and 6.00), and influent volumetric flow rate (1.25, 2.50, and 3.75 mL/min) on breakthrough behavior and amount of fluoride removed were examined.

#### *3.6. Modeling and Analysis of Fixed-Bed Column Data*

A fixed-bed column adsorption performance is well described through the breakthrough curve concept [53]. The time of solute breakthrough and the shape of the breakthrough curve are important indicators for the operational adsorption processes; the breakthrough curve is directly linked to the viability and economics of the adsorption process [54,69]. The breakthrough patterns and according parameters are dependent on the operating conditions of the fixed-bed column such as adsorbent particle size, influent flow rate, and pH of the influent solution. Nevertheless, the pH value may not influence the breakthrough curve in a situation such as when using strongly basic anion exchangers. The primary and significant attribute is the sorbent selectivity to the pollutant, as well as the dynamic exchange capacity and full dynamic capacity of the column [70]. To investigate the performance of the column and to scale-up, the determination of breakthrough parameters is crucial. The breakthrough curves expressed in terms of the ratio of effluent to influent adsorbate concentration (Ct/Co) as a function of time or effluent volume for a given height of the bed reflects the absorbed fluoride from the solution. Time equivalent to stoichiometric capacity (exhaustion time) and time equivalent to usable capacity (breakthrough time) is shown in Equations (4) and (5), respectively [54,59].

$$\mathbf{t}\_{\mathbf{e}} = \int\_{t=0}^{t=t\_{\text{total}}} \left( 1 - \frac{\mathbf{C}\_{\mathbf{t}}}{\mathbf{C}\_{\mathbf{o}}} \right) \mathbf{d} \mathbf{t} \tag{4}$$

$$\mathbf{t}\_{\mathbf{b}} = \int\_{t=0}^{t\_{\mathbf{b}}} \left( 1 - \frac{\mathbf{C}\_{\mathbf{b}}}{\mathbf{C}\_{\mathbf{o}}} \right) \mathbf{d}\mathbf{t} \tag{5}$$

where t<sup>e</sup> is exhaustion time (min), t<sup>b</sup> is the breakthrough time (min) at which C<sup>t</sup> = C<sup>b</sup> (mg/L) (for the present system, C<sup>b</sup> = 1.5 mg/L).

The total value of fluoride adsorbed (qtotal: mg) from the column for a given feed concentration and the flow rate was obtained from the area (A) under the breakthrough

curve by integrating the adsorbed fluoride concentration Cad (Cad = Co−Ct) (mgL−<sup>1</sup> ) versus t (min) and can be obtained from Equation (6) [55,71].

$$\mathbf{q}\_{\text{total}} = \frac{\mathbf{Q} \mathbf{A}}{1000} = \frac{\mathbf{Q}}{1000} \int\_{\mathbf{t}=0}^{\mathbf{t}=\mathbf{t}\_{\text{total}}} \mathbf{C}\_{\text{ad}} \mathbf{d} \mathbf{t} \tag{6}$$

where ttotal, and Q are the total flow time until saturation of the bed (min), and volumetric flow rate (mL/min), respectively.

Equilibrium fluoride uptake (qe: mg kg−<sup>1</sup> ) (maximum capacity of the column) in the column is calculated by Equation (7) as the total amount of fluoride adsorbed (qtotal) per kilogram of dry adsorbent mass (m) at the end of the total flow time [71].

$$\mathbf{q}\_{\rm eq} = \frac{\mathbf{q}\_{\rm total}}{\mathbf{m}} \tag{7}$$

The effluent volume (Ve) and treated effluent volume or breakthrough volume (Vb) of solution can be found from Equations (8) and (9), respectively.

$$\mathbf{V\_e = Qt\_e} \tag{8}$$

$$\mathbf{V\_b = Qt\_b} \tag{9}$$

where, V<sup>e</sup> is the total effluent volume at exhaustion time (mL), Vb, total effluent volume at the breakthrough time (mL), Q is the volumetric flow rate (mL/min), t<sup>e</sup> and t<sup>b</sup> are exhaustion and breakthrough time (min), respectively.

The Mass Transfer Zone (MTZ) or unused bed length (HUNB) can be obtained from Equation (10) [54,59].

$$\text{MTZ} = \text{H}\_{\text{T}} \left( \frac{\text{t}\_{\text{e}} - \text{t}\_{\text{b}}}{\text{t}\_{\text{e}}} \right) \tag{10}$$

where H<sup>T</sup> is total bed height (cm), t<sup>e</sup> (min) is exhaustion time, and t<sup>b</sup> is breakthrough time (min).

The Empty Bed Contact Time (EBCT), which measures the critical depth and the contact time between the solid phase adsorbent and the liquid phase, can be obtained from Equation (11).

$$\text{EBCT} = \frac{\text{V}\_{\text{B}}}{\text{Q}} \tag{11}$$

where V<sup>B</sup> is the volume of a fixed bed (mL) and Q is the flow rate (mL/min).

The bulk density (ρb: gm.cm−<sup>3</sup> ), which measures the adsorbent compaction status, and the particle density (ρp: gm.cm−<sup>3</sup> ) of the adsorbent can be obtained from Equations (12) and (13), respectively [72].

$$
\rho\_{\rm b} = \frac{\mathbf{m}\_{\rm ads}}{\mathbf{V}\_{\rm t}} \tag{12}
$$

$$\rho\_{\rm p} = \frac{\mathbf{m\_{ads}}}{\mathbf{V\_t - V\_v}} \tag{13}$$

where mads is the dry mass of adsorbent (mg), and V<sup>t</sup> is the bulk volume (cm<sup>3</sup> ) which includes the volume of adsorbent (VB:cm<sup>3</sup> ) and the pore space between the adsorbent particles or void volume (Vv:cm<sup>3</sup> ).

The void volume (Vv:cm<sup>3</sup> ) of the adsorbent can be found from Equation (14) [72].

$$\mathbf{W\_{v}} = \frac{\mathbf{W\_{Sat}} - \mathbf{W\_{dry}}}{\rho\_{\mathbf{w}}} \tag{14}$$

where Wdry is the weight of dry adsorbent (g), Wsat is the weight of saturated adsorbent (g), and ρ<sup>w</sup> is the density of water (g cm−<sup>3</sup> ).

The total porosity of the adsorbent (εb) can be obtained from Equation (15) [72].

$$
\varepsilon\_{\mathbf{b}} = 1 - \frac{\rho\_b}{\rho\_p} \tag{15}
$$

The filter (superficial) velocity (V<sup>f</sup> :cm min−<sup>1</sup> ) and effective (interstitial) velocity (V<sup>I</sup> :cm min−<sup>1</sup> ) can be found from Equations (16) and (17), respectively [72].

$$\mathbf{V\_{f}} = \frac{\mathbf{Q}}{\mathbf{A}}\tag{16}$$

$$\mathbf{V\_{I}} = \frac{\mathbf{Q}}{\mathbf{A} \times \boldsymbol{\varepsilon\_{b}}} \tag{17}$$

where A is the cross-sectional area of the fixed-bed (cm<sup>2</sup> ) and Q is the flow rate (cm3min−<sup>1</sup> ).

#### *3.7. Fixed–Bed Column Breakthrough Curve Modeling*

The successive operation of a small scale column towards industrial applications can be well elucidated with the help of some models. Various models have been reported for predicting the breakthrough performance in fixed-bed adsorption [57,73]. In this study, the two most important and widely used mathematical models, the Thomas model and Adams– Bohart model, have been applied to the column experimental data for describing the dynamic behavior of fluoride adsorption using VPum and VSco in a fixed-bed column filter.

#### 3.7.1. Thomas Model

The Thomas model [74] is one of the most extensively employed kinetic models to predict fixed-bed column performance. In addition to the prediction of the breakthrough curve for the effluent, the model can be used to determine the maximum uptake of adsorbate and adsorption rate constant [74]. The non-linear form of the Thomas model can be described as follows Equation (18), [75].

$$\frac{\mathbf{C\_t}}{\mathbf{C\_o}} = \frac{1}{1 + \exp\left[\mathbf{K\_T q\_o} \frac{\mathbf{m}}{\mathbf{Q}} - \mathbf{K\_T C\_o} t\right]}\tag{18}$$

where C<sup>o</sup> (mg/L) is the initial solute concentration, C<sup>t</sup> (mg/L) is the solute concentration at the time, t, Q (L/min) is the volumetric flow rate, q<sup>o</sup> (mg/kg) is the maximum solid-phase concentration of solute (maximum column adsorption capacity), K<sup>T</sup> is the Thomas rate constant (L/min mg), and m (kg) is the packed dry mass of the adsorbent in a fixed-bed.

#### 3.7.2. Adams–Bohart Model

The Adams–Bohart model [76] was developed for the analysis of the dynamics of fixed-bed based on the assumption that the adsorption rate is proportional to both the residual adsorbent and adsorbate concentration. The nonlinear form of the Adams–Bohart model (Equation (19)) [77], was used for the prediction of breakthrough curves and model parameters.

$$\frac{\mathbf{C}\_{\text{t}}}{\mathbf{C}\_{\text{o}}} = \frac{1}{1 + \exp\left[\mathbf{K}\_{\text{AB}} \mathbf{N}\_{\text{o}} \frac{\mathbf{Z}}{\upsilon} - \mathbf{K}\_{\text{AB}} \mathbf{C}\_{\text{o}} \mathbf{t}\right]}\tag{19}$$

Where KAB (L/mg min) is the kinetic constant, *v* (mL/min) is the linear flow rate, Z (cm) is a column bed depth, and N<sup>O</sup> (mg/L) is the saturation concentration (adsorption capacity of the adsorbent per unit volume of the bed), and time t (min) ranges from the start to fluoride breakthrough point. The linear flow rate was determined by Equation (20).

$$v = \frac{\mathbf{Q}}{\mathbf{A}}\tag{20}$$

where Q (cm3/min) is the volumetric flow rate, and A (cm<sup>2</sup> ) is the cross-sectional area of the bed [60,62,78].

#### **4. Conclusions**

In this study, the removal of fluoride from aqueous solutions was examined in a continuous fixed-bed adsorption column system using VPum and VSco. The characterizations investigations were performed using XRD, SEM, FTIR, BET, XRF, and ICP-OES equipment to reveal the mechanisms of adsorption and the suitability of the adsorbents for fluoride removal. The pHPZC is 6.98 for VSco and 6.85 for VPum. The effects of process parameters such as adsorbent particle size, influent pH, and influent volumetric flow-rate on the performance of the adsorption process in a column were evaluated. The maximum removal capacity of 110 mg/kg for VPum and 22 mg/kg for VSco were achieved at a particle size of 0.075–0.425 mm and <0.075 mm, respectively, at lower solution pH (2.00) and flow rate (1.25 mL/min). The increase in adsorbent particle size, solution pH, and flow rate decreases the breakthrough and saturation time of the column bed and, consequently, lowers the amount of fluoride removal by VSco. The breakthrough and exhaustion time on VPum was high at a particle size of 0.075–0.425 mm, at lower solution pH and flow rate similar to that of VSco. Thus, in order to attain optimum performance, suitable experimental parameters are significant for the operation of the adsorption column. The Thomas and Adams–Bohart models were applied to the experimental data to estimate the breakthrough curves and to determine fixed-bed column kinetic parameters. Both the Adam–Bohart and the Thomas models could predict very well the entire region of the breakthrough curves for the fluoride-VSco and fluoride-VPum system. The results show that VPum and VSco could be used in a fixed-bed adsorption column for the removal of excess fluoride from water. The supply cost of the two adsorbents is very low; nevertheless, an overall cost analysis of the purification system is very important as it has implications for the feasibility (technical and economic) of the adsorption method. Additional testing of the adsorbents including representative samples test for possible compositional, mineralogical, and textural changes in time due to weathering, leaching test, competitive ions effects, and regeneration options is required to confirm that the defluoridation of groundwater employing volcanic rocks is a safe and sustainable method.

**Supplementary Materials:** Table S1: Elemental composition and oxides content of VPum and VSco, Figure S1: Experimental (exp.) and simulated (cal.; Thomas model) breakthrough curves of fluoride at different particle sizes for (a) VPum and (b) VSco (pH 2.00; CO: 10 mg/L; QO: 1.25 mL/min; bed depth 10 cm), Figure S2: Experimental and simulated (Thomas model) breakthrough curves of fluoride at different pH for (a) VPum: 0.075–0.425 mm (b) VSco: <0.075 mm (CO: 10 mg/L; QO: 1.25 mL/min; bed depth 10 cm), Figure S3: Experimental and simulated (Thomas model) breakthrough curves of fluoride at different influent flow rate for (a) VPum: 0.075–0.425 mm and (b) VSco: <0.075 mm (pH 2.00; CO: 10 mg/L; bed depth 10 cm), Figure S4: Experimental (exp.) and simulated (cal.; Adams–Bohart model) breakthrough curves of fluoride at different particle sizes for (a) VPum and (b) VSco (pH 2.00; CO: 10 mg/L; QO: 1.25 mL/min; bed depth 10 cm), Figure S5: Experimental and simulated (Adams–Bohart model) breakthrough curves of fluoride at different pH for (a) VPum: 0.075–0.425 mm and (b) VSco: <0.075 mm (CO: 10 mg/L; QO: 1.25 mL/min; bed depth 10 cm), Figure S6: Experimental and simulated (Adams–Bohart model) breakthrough curves of fluoride at different flow rate for (a) VPum: 0.075–0.425 mm and (b) VSco: <0.075 mm (pH 2.00; CO: 10 mg/L; bed depth 10 cm).

**Author Contributions:** W.S.G. prepared the adsorbents, designed and conducted the adsorption experiments, analyzed the data, and prepared the manuscript; E.A. supervised the research work, updated and reviewed the manuscript; B.L. supervised the research work, reviewed and edited the article. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data used in this study can be available from the authors on reasonable request.

**Acknowledgments:** The first author is greatly thankful to the German Academic Exchange Service (DAAD) for providing the scholarship during the study.

**Conflicts of Interest:** The authors declare no conflict of interest.

**Sample Availability:** Samples of the adsorbents (VPum and VSco) are available from the authors.

#### **References**


### *Article* **Application of Natural Clinoptilolite for Ammonium Removal from Sludge Water**

**Stephan Wasielewski 1,\*, Eduard Rott <sup>1</sup> , Ralf Minke <sup>1</sup> and Heidrun Steinmetz <sup>2</sup>**


**\*** Correspondence: stephan.wasielewski@iswa.uni-stuttgart.de; Tel.: +49-711-685-65425

**Abstract:** Sludge water (SW) arising from the dewatering of anaerobic digested sludge causes high back loads of ammonium, leading to high stress (inhibition of the activity of microorganisms by an oversupply of nitrogen compounds (substrate inhibition)) for wastewater treatment plants (WWTP). On the other hand, ammonium is a valuable resource to substitute ammonia from the energy intensive Haber-Bosch process for fertilizer production. Within this work, it was investigated to what extent and under which conditions Carpathian clinoptilolite powder (CCP 20) can be used to remove ammonium from SW and to recover it. Two different SW, originating from municipal WWTPs were investigated (SW1: *c*<sup>0</sup> = 967 mg/L NH<sup>4</sup> -N, municipal wastewater; SW2: *c*<sup>0</sup> = 718–927 mg/L NH<sup>4</sup> -N, large industrial wastewater share). The highest loading was achieved at 307 K with 16.1 mg/g (SW1) and 15.3 mg/g (SW2) at 295 K. Kinetic studies with different specific dosages (0.05 gCLI/mgNH4-N), temperatures (283–307 K) and pre-loaded CCP 20 (0–11.4 mg/g) were conducted. At a higher temperature a higher load was achieved. Already after 30 min contact time, regardless of the sludge water, a high load up to 7.15 mg/g at 307 K was reached, achieving equilibrium after 120 min. Pre-loaded sorbent could be further loaded with ammonium when it was recontacted with the SW.

**Keywords:** ammonia; ammonium recovery; Freundlich; intraparticle diffusion; isoelectric state; Langmuir; pseudo-second-order; Temkin; zeolite; high-strength wastewater; sludge liquor

#### **1. Introduction**

In view of the world's population growing from 7.6 billion in 2017 to estimated 9.4–10.2 billion people by 2050, but also in consideration of rising living standards, correlating with increasing meat consumption, an increase of food requirements by 50% between 2012 and 2050 is to be expected [1]. This increased demand cannot be satisfied by the utilization of new farmland alone, since most of it is not developed, too remote from potential markets, susceptible to pest infestation or new cultivated would compete with the conservation of important ecosystems. Furthermore, potential arable land is limited to a small number of countries. Rather, increasing productivity and efficiency in agricultural production must contribute to meet the increased demand [2], resulting in a greater need for nutrients, especially nitrogen fertilizers.

Nowadays, the nutrition of half the world's population is ensured by the Haber-Bosch process, which enables the synthesis of ammonia (NH3) for fertilizer production [3]. However, the production of NH<sup>3</sup> requires a high amount of energy (10 kWh/kg NH3) [4]. Dawson and Hilton [5] calculated that 1.1% of the world's energy consumption can be attributed to the production of fertilizers; 90% of it due to the production of nitrogen fertilizers.

On the other hand, ammonium has severe negative environmental impacts. Because of its eutrophication potential, ammonium contributes to the growth of biomass in water

**Citation:** Wasielewski, S.; Rott, E.; Minke, R.; Steinmetz, H. Application of Natural Clinoptilolite for Ammonium Removal from Sludge Water. *Molecules* **2021**, *26*, 114. https://doi.org/10.3390/ molecules26010114

Academic Editors: Chiara Bisio and Monica Pica Received: 1 December 2020 Accepted: 23 December 2020 Published: 29 December 2020

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

bodies. Under alkaline conditions, which can occur during the day if intensive photosynthesis takes place, ammonium dissociates to ammonia, which has a toxic effect on aquatic fauna even in low concentrations.

In wastewater treatment rejected sludge water from the dewatering process of anaerobically treated sludge causes significant additional ammonium loads for the biological treatment step [6], resulting in additional need for energy and space. Additionally, external carbon sources might be necessary for a stable nitrogen elimination process. Instead of elimination and high-energy expenditure, the ammonium should be recovered to partially substitute the increasing worldwide demand for NH3.

Recovery methods such as air stripping, bioelectrochemical systems, membrane separation, and ion exchange have been thoroughly investigated. However, these methods require additional chemicals as well as energy, and ammonia losses due to volatilization can occur [7].

The zeolite clinoptilolite (CLI) is known to be a very good ion exchanger, as it consists of a three-dimensional tetrahedral structure formed of AlO<sup>4</sup> <sup>−</sup> and SiO4, connected by a shared oxygen atom. The micropores formed by this structure are fine enough to allow entry and exchange of cations and water molecules [8]. This ability is based on the substitution of SiO<sup>4</sup> by AlO<sup>4</sup> <sup>−</sup>, leading to a negative charge in the structure, which has to be compensated by exchangeable cations such as Na<sup>+</sup> , K<sup>+</sup> , Ca2+, and Mg2+ [9]. In a previous study with carpathian Clinoptilolite powder (CCP 20), 21.0 meq/100 g Na<sup>+</sup> , 49.3 meq/100 g K<sup>+</sup> , 65.6 meq/100 g Ca2+, and 3.3 meq/100 g Mg2+ were exchanged with 136.9 meq/100 g NH<sup>4</sup> + [10].

As soon as the exchange capability for ammonium is exhausted, CLI is proposed to be utilized as a slow-release fertilizer in agriculture [11] or regenerated by the use of sodium chloride, sodium carbonate, sodium bicarbonate, or sodium hydroxide solutions [12–15].

In a study investigating the adsorption of ammonium from different highly concentrated wastewaters, it was shown that elimination from leachate of a sewage sludge landfill (*c*<sup>0</sup> = 11.12–115.16 mg/L NH4-N) was 10–20% lower than from a matrix-free solution [16]. It has been demonstrated, that ammonium from swine manure (*c*<sup>0</sup> = 0.43 M/L NH<sup>4</sup> <sup>+</sup> ≈ 6150 mg/L NH4-N) can be removed by means of CLI, but the load is reduced from 10 mg/g (matrix-free ammonium solution) to 2 mg/g (manure) due to the cations contained [17]. Furthermore, dilution of leachate from a municipal landfill (*c*<sup>0</sup> = 2292 mg/L NH4-N) does not improve ammonium adsorption [18]. In addition, organic compounds that are not removed by activated carbon interfere with the sorption of ammonium from leachate (*c*<sup>0</sup> = 820 mg/L NH<sup>4</sup> <sup>+</sup> = 637 mg/L NH4-N) at CLI; the load increases when leachate is pretreated with activated carbon [19]. The results of these studies show that the composition of the medium to which CLI is applied might be decisive for the adsorption effect. Since the adsorption of ammonium from sludge water, has not been sufficiently investigated, the adsorption process in this complex medium is not well understood and the technical implementation is uncertain.

The objective of this study was to develop a deeper understanding of the factors influencing the sorption of ammonium from sludge water on powdered natural clinoptilolite.

#### **2. Materials and Methods**

#### *2.1. Zeolite Samples and Chemicals*

Since preliminary studied Slovakian CLI CCP 20 (CCP = Carpathian clinoptilolite powder) showed favorable sorption properties [10], it was employed for this study. It was obtained from the supplier Labradorit GmbH (Berlin, Germany), in a ground and sieved form (particle size smaller than 20 µm). The CLI was dried at 378 K for 24 h before use. No other pretreatment was conducted. The CCP 20 mainly consisted of Si (35.5% (*wt*/*wt*)), Al (5.4%), K (2.0%), Ca (1.6%), Fe (1.0%), Na (0.4%), Mg (0.3%), Ti (0.1%), Ba (0.08%), and Pb (0.001%), whereas Cr, Ni, As, Rb, Cd, Cs, Ba, Hg, and Tl were below the limit of detection.

NH4Cl (p.a.), NaOH (p.a.) and HCl (32%, p.a.) were obtained from VWR International (Radnor, PA, USA).

#### *2.2. Sludge Water and Matrix-Free Solution*

Sludge water from two different WWTPs with high concentrations of ammonium nitrogen (see Table 1) were investigated. The sludge water originated from the dewatering process of anaerobically stabilized sludge by means of a chamber filter press. During normal operation, this sludge water is recycled to the main treatment process.


**Table 1.** Physical properties and constituents of the examined sludge waters.

n.d.: not detected.

SW1 originated from a WWTP treating mainly municipal wastewater using the activated sludge process with upstream denitrification. Iron chloride sulphate is employed for phosphate precipitation. Primary sludge from mechanical treatment, secondary sludge from the biological stage and precipitated sludge from phosphorus elimination are admixed and anaerobically digested. Before dewatering, the digested sludge is pre-thickened and subsequently dewatered by means of a chamber filter press. For the investigations, the sludge water was taken from the outlet of the chamber filter press.

SW2 originated from a WWTP with a high industrial wastewater share. The wastewater is treated by trickling filters and a downstream denitrification. A mixture of aluminum and iron salts is employed as precipitant for phosphate elimination. Sludge from primary and secondary treatment as well as from phosphate elimination are pre-thickened and subsequently anaerobically digested. Afterwards, the digested sludge is dewatered with a chamber filter press, the outlet of which was sampled to gain SW2 for the investigations. From SW2, several samples were examined, which were taken at different times.

Matrix-free ammonium chloride solution (*c*<sup>0</sup> = 1000 mg/L NH4-N) was prepared by dissolving NH4Cl in distilled water.

Table 1 summarizes the physical properties and constituents of the examined sludge waters.

Both sludge waters showed only minor differences in composition except of COD (chemical oxygen demand) and PO4-P. The COD concentration in SW1 was about twice as high as in SW2, but the dissolved COD concentration (filtered by 0.45 µm nylon membrane) was similar. Presumably, the retention of COD-causing particles in the sludge dewatering of SW1 was less efficient than in SW2. In addition, the concentration of PO4-P in SW1 was considerably higher (factor 10).

In Table 2 the elementary composition of the examined sludge waters is listed.


**Table 2.** Elementary composition of the examined slugde waters.

n.d.: not detected.

The investigated sludge waters contained very low concentrations of heavy metals. They differed in their concentration of potassium and calcium, whereas the sodium and magnesium concentrations were almost identical.

Cations competing with ammonium ions for sorption sites such as K<sup>+</sup> and Na<sup>+</sup> were present in lower concentrations (K<sup>+</sup> : SW1: 234 mg/L = 6.0 mmol/L; SW2: 87.5–91.0 mg/L = 2.2–2.3 mmol/L; Na<sup>+</sup> : SW1: 126 mg/L = 10.3 mmol/L; SW2: 129– 132 mg/L = 5.6–5.7 mmol/L) as ammonium (SW1: 967 mg/L NH4-N = 67.7 mmol/L; SW2: 718–913 mg/L NH4-N = 51.3–65.2 mmol/L). Accordingly, ammonium was present in multiple excess (SW1: [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 5; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 10; SW2: [NH<sup>4</sup> + ]/ [K<sup>+</sup> ] ≈ 234–30; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 9–12).

The ion ratios of ammonium to potassium and sodium were more favorable (high ammonium surplus) than in leachate from a sewage sludge landfill ([NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 2.7; [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 14.6 [16]) and leachate ([NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 2.2; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 0.9 [19]), whereas a larger ammonium surplus was set in synthetic wastewater ([NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 17.3; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 6.9 [20]).

#### *2.3. Experimental Design*

#### 2.3.1. Isoelectric State of CLI and pH-Dependent Adsorption

Both sludge waters were adjusted to pH values ranging from 2 to 12 by HCl or NaOH prior to the experiment. A fixed specific sorbent mass at a ratio of 0.1 g CLI per mg NH4-N was employed. Sorbent (20 g) and solution (200 mL) were stirred for 20 h on a magnetic stirrer (400 rpm) at room temperature (295 K) in closed bottles, subsequently membranefiltered (0.45 µm pore size), and then the pH value as well as the ammonium concentration were determined. The initial pH values of the solutions were compared with those of the filtrates. The isoelectric state is the point at which both pH values are identical.

Sodium ions, which are added to the sample by NaOH to adjust the pH, compete with ammonium for the sorption sites in the CLI. In order to show the influence of the sodium ions without additionally pH value, equimolar NaCl was added. All experiments were conducted as triplicates. The titration curves of NH4Cl solution, SW1 and SW2 are also depicted in Appendix A.

#### 2.3.2. Isothermal Adsorption

Since sludge water originates from the digestion tower, operated moistly at mesophilic conditions, the influence of temperature on CLI loading was investigated. For this purpose, temperatures of 307 K (34 ◦C, mesophilic conditions in the digestion tower, considering small heat losses), 295 K (22 ◦C, room temperature) and 283 K (10 ◦C) were tested.

Since the ammonium concentration in the sludge water could not be changed, the amount of sorbent mass *m* (g) was varied instead. Thus, different quantities ranging from 2 g to 48 g sorbent were mixed with 200 mL sludge water *V<sup>p</sup>* (mL) and stirred at a constant temperature (283 K, 295 K, and 307 K) on a magnetic stirrer at 400 rpm. After 20 h, the residual ammonium concentration *ceq* (mg/L) as well as the pH in the filtrate were determined. Since the pH barely varied between the different dosages and a competing adsorption by Na<sup>+</sup> or H3O<sup>+</sup> cations as well as a dilution due to the pH adjustment was to be avoided, a pH correction was not conducted. One experimental approach without sorbent for each examined pH was used to determine unwanted ammonium elimination, e.g., by stripping or adsorption onto parts of the glass apparatus. All experiments were conducted as triplicates. The ammonium concentration in the filtrate of that approach is expressed as *c<sup>B</sup>* (mg/L). The loading *qeq* (mg/g) of the sorbent mass was determined by Equation (1).

$$q\_{eq} = \frac{(c\_0 - (c\_0 - c\_B) - c\_{eq}) \times (\frac{V\_P}{1000})}{m} \tag{1}$$

#### 2.3.3. Adsorption Kinetics

The influence of temperature (283 K–307 K; constant specific sorbent ratio of 0.1 gCLI/mgNH4-N; non pre-loaded CLI), the influence of the specific sorbent ratio (0.05–0.2 g CLI per mg NH4-N; constant temperature 295 K; non pre-loaded CLI), as well as the influence of pre-load (0–11.4 mgNH4-N/gCLI; constant sorbent ratio 0.1 gCLI/mgNH4-N; constant temperature 307 K) were investigated in kinetic experiments. Furthermore, a matrix-free ammonium chloride solution (*c*<sup>0</sup> = 1000 mg/L NH4- N) was examined as well. The sorption properties of CCP 20, including isoelectric state, pH-dependent elimination, isothermal adsorption, and thermodynamic properties were already investigated with similar matrix-free solution by Wasielewski et al. [10].

CCP 20 was mixed with the sample (1.5 L) on a magnetic stirrer. All experiments were conducted as triplicates. At periodic intervals, an aliquot (10 mL) was taken and immediately membrane-filtered (nylon membrane, 0.45 µm pore size) to prevent further contact between sorbent (CLI) and sample (NH4Cl solution or sludge water). Subsequently, the ammonium concentration was measured in the filtrate and the time-dependent loading of the sorbent *q*(*t*) (mg/g) was calculated. Since it is known from published studies that the adsorption kinetics strongly depend on the stirring speed [21–23], a high rotation frequency of 800 rpm was chosen to determine the maximum possible adsorption kinetic values. Due to sampling during the test, the total volume was continuously reduced. However, it can be assumed that during the sampling no change in the ratio of the sorbent mass to the volume of the solution occurred due to the homogeneously mixed conditions.

#### *2.4. Adsorption Models*

#### 2.4.1. Freundlich Model

The nonideal, reversible adsorption of a heterogenous surface is described by the empirical Freundlich model [24]. It is not possible to calculate a complete loading, as the sorbent sites can be occupied in several layers. The loading of the sorbent *qeq,F* (mg/g) can be calculated by exponentiation of the corresponding equilibrium concentration *ceq* (mg/L) with the factor *1/n* (–), as described by Equation (2).

$$\mathfrak{q}\_{\text{eq},\text{F}} = \mathcal{K}\_{\text{F}} \mathfrak{c}\_{\text{eq}}^{\frac{1}{n}} \tag{2}$$

Calculation methods for determining the constants *K<sup>F</sup>* and *1/n* with the help of nonlinear regression or linearization are given, e.g., by Ho et al. [25]. In this study, the linearization was done by plotting log *qeq* versus log *ceq*. The gradient of the graph corresponds to *n*, while the tenth power of the intercept represents *KF*.

#### 2.4.2. Langmuir Model

A monomolecular layer of adsorbate on the available sorption sites is assumed according to the adsorption model of Langmuir [26]. Thus, the properties of the sorbent sites are identical and equivalent, so that a determination of the maximum adsorption capacity is possible. The loading of sorbent is calculated according to Equation (3), where *K<sup>L</sup>* (L/mg) is the Langmuir constant and *qmax* (mg/g) the maximum capacity.

$$q\_{\epsilon q,L} = \frac{q\_{\max} K\_L c\_{\epsilon q}}{1 + K\_L c\_{\epsilon q}} \tag{3}$$

The constants can either be deduced from linear or nonlinear regression based on measurement results. By plotting *ceq/qeq* vs. *ceq*, *1/qeq* vs. *1/ceq*, *qeq* vs. *qeq/ceq*, or *qeq/ceq* vs. *qeq*, a linear relationship for Equation (3) can be deduced [27]. Table 3 lists the four possible linear forms for determining Langmuir constants. In this study, only the type of isotherm with the highest coefficient of determination *r* 2 is listed. The coefficient of determination *r* 2 of the nonlinear form of the Langmuir isotherm and the experimentally determined loads *qeq* and the arithmetical average loads *qeq* were calculated according to Equation (4).

$$r^2 = \frac{\sum \left(q\_{eq,L} - \overline{q\_{eq}}\right)^2}{\sum \left(q\_{eq,L} - \overline{q\_{eq}}\right)^2 + \sum \left(q\_{eq,L} - q\_{eq}\right)^2} \tag{4}$$


**Table 3.** Linear forms of the Langmuir isotherm (according to [28]).

#### 2.4.3. Temkin Model

The isothermal loading of sorbents according to Temkin ([29] in [30]) is extended by the temperature parameter. Accordingly, the adsorption enthalpy is linearly proportional to the loading on the sorbent [31]. The form of the isotherm used in this work is taken from Ho et al. [25] (Equation (5)), where *R* is the universal gas constant (8.314459 J/(mol K)), *T* the temperature (K), *b<sup>T</sup>* (1/mol), and *A<sup>T</sup>* (L/mg) the Temkin isothermal constants.

$$q\_{eq,T} = \frac{RT}{b\_T} \ln\left(A\_T c\_{eq}\right) \tag{5}$$

The linearized form of the Temkin isotherm is shown in Equation (6).

$$q\_{eq,T} = \frac{RT}{b\_T} \ln(A\_T) + \frac{RT}{b\_T} \ln(c\_{eq}) \tag{6}$$

In a plot of ln *ceq* vs. *qeq*, the term *RT/b<sup>T</sup>* is represented by the slope, whereas the intersection with the ordinate represents the term *RT ln(AT)/bT*. Subsequently, *b<sup>T</sup>* and *A<sup>T</sup>* can be deduced.

#### 2.4.4. Thermodynamic Calculations

Energy adsorption or release, i.e., temperature increase or decrease, can be observed during the adsorption process. The standard free energy ∆*G* 0 (kJ/mol) can be calculated according to the following Equation (7)

$$
\Delta \mathbf{G}^0 = -RT \ln(\mathbf{K}\_d) \tag{7}
$$

where *K<sup>d</sup>* is the thermodynamic equilibrium constant, here the Freundlich constant (L/g). According to Milonjic [32], it should be noted that *K<sup>d</sup>* must be dimensionless. Therefore, the use of the temperature-dependent equilibrium constant *K<sup>F</sup>* must be corrected by a factor of 1000 g/L (density of water) into its dimensionless form. The relationship of the other thermodynamic parameters such as change in enthalpy ∆*H*<sup>0</sup> (kJ/mol) and change in standard entropy ∆*S* 0 (J/(mol K)) can be derived by means of the Gibbs–Helmholtz Equation (8).

$$
\Delta G^0 = \Delta H^0 - T\Delta S^0 \tag{8}
$$

From the plot of the logarithmic equilibrium constant *K<sup>d</sup>* against the reciprocal value of the temperature *1/T* (Van't–Hoff diagram), a linear correlation can be derived. Here, the gradient corresponds to the quotient of the negative change in the free standard enthalpy ∆*H*<sup>0</sup> and the universal gas constant *R*. Furthermore, the quotient of the change of the free molar standard entropy ∆*S* <sup>0</sup> and the universal gas constant can be derived from the axis section.

Endothermic adsorption is described by a positive value of ∆*H*<sup>0</sup> , meaning energy is absorbed by the adsorption process. A negative value indicates exothermic adsorption, meaning energy is being released. A spontaneous (exergonic) adsorption is expressed by negative ∆*G* 0 , while negative ∆*S* 0 indicates a random adsorption behavior.

#### *2.5. Kinetic Models*

#### 2.5.1. Intraparticle Diffusion

A mathematical description of the diffusion process is provided by the intraparticle diffusion model (ID). It presumes a correlation between the loading rate *kID* (mg/(min0.5 g)) and the square root of the contact time *t* (min) ([33] in [34]). However, McKay et al. [35] extended this model by the constant *C* (mg/g), which is proportional to the thickness of the boundary layer as well as the initial adsorption by it. The time-dependent loading of the sorbent *q*(*t*)*ID* (mg/g) can be calculated by Equation (9).

$$q(t)\_{ID} = k\_{ID}t^{0.5} + \mathcal{C} \tag{9}$$

To determine the loading rate *kID*, *q*(*t*) versus *t* 0.5 is plotted. The slope of the resulting graph corresponds to *kID* while the intersection with the ordinate corresponds to *C*. Sole intraparticle diffusion occurs when the graph intersects the origin (*C* = 0). If a multistage diffusion process is present, two or more partial lines passing into each other can be approximated to the existing empirical measuring points of *q*(*t*).

#### 2.5.2. Pseudo-Second-Order

The time-dependent loading of the sorbent can be described by the pseudo-secondorder (PSO) model according to Ho and McKay [36]. However, it is not possible to deduce the prevailing adsorption kinetic processes when using this model. It offers a macroscopic view of the adsorption process, based on the assumption that the adsorption rate is dependent on the loading of the ion exchange material at a certain point in time and its equilibrium state. The differential form of the PSO, i.e., as the differential of the load *q*(*t*) (mg/g) at any time *t,* is given in Equation (10)

$$\frac{dq\_{\rm t,PSO}}{dt} = \left. k\_2 (q\_e - q\_t)^2 \right. \tag{10}$$

where *k*<sup>2</sup> is the pseudo-second-order rate (mg/(g min)) and *q<sup>e</sup>* (mg/g) the load at equilibrium. From the integration of Equation (10) with the boundary conditions *q*(*t*) = 0 at *t* = 0 and *q*(*t*) = *q*(*t*) at *t* = *t*, four different linear forms of the PSO model can be obtained (Table 4).


**Table 4.** Linear forms of PSO model (according to [37]).

In this study, only the type with the highest coefficient of determination *r* 2 (Equation (4)) is listed. All calculations in this study were conducted using Microsoft Excel 2019.

#### *2.6. Analytical Methods*

Ammonium was measured according to German standard DIN 38406-5 [38]. At a pH of about 12.6, ammonium cations and ammonia contained in the sample react with hypochlorite ions and salicylate ions in the presence of sodium pentacyanonitrosylferrate (2-)(nitroprusside sodium) as a catalyst to form a blue dye. The required hypochlorite ions are formed in the alkaline medium by hydrolysis of the dichloroisocyanuric acid ions. The spectral absorbance of the blue dye at 655 nm wavelength is linearly proportional to the ammonium concentration.

For determination of pH, probes (SenTix 950 + Multi 3430, WTW, Weilheim, Germany) were used.

F - , Cl- , NO2-N, NO3-N, Br- , SO<sup>4</sup> 2-, and PO4-P were analyzed according to ISO 10304- 1 [39] using the Dionec ICS-110 ion chromatograph (Thermo Fischer Scientific, Waltham, MA USA). Before the determination, the sample was filtered through a C18 cartridge (Strata C18-E (55 µm, 70 Å), Phenomenex, Torrance, USA) and diluted if necessary.

To determine the elementary composition of the sludge waters, 44 mL of sample were admixed with 2 mL HCl (32%), 3 mL HNO<sup>3</sup> (65%), 1 mL H2O<sup>2</sup> (30%) and digested by a microwave (Start, MLS GmbH, Leutkirch, Germany) with a selected program run of 10 min at 443 K and a subsequent cooling phase of 20 min.

To determine the chemical elements of the zeolite, 0.3 to 0.5 g of the CLI were weighed and mixed with 6 mL HNO<sup>3</sup> (65%), 4 mL HF (48%), and 2 mL HCl (32%). The mixture was digested by microwave with a selected program run of 10 min at 383 K, then 5 min at 413 K, and finally 9 min at 463 K. Together with the cooling phase, the digestion lasted 64 min.

Heavy metals were analyzed by inductively coupled plasma mass spectrometry (Nexion 2000, Perkin Elmer, Waltham, MA, USA).

#### **3. Results and Discussion**

#### *3.1. Isoelectric State of CLI and pH-Dependent Adsorption*

In Figure 1 the final pH of SW1 and SW2 filtrates are plotted as a function of the initial pH after contact with CCP 20. The arbitrary pH value of SW1 was 7.9 and that of SW2 was 8.0. In the alkaline range, no considerable change in the pH was observed. This can be attributed to the decrease in ammonium uptake, as uncharged NH<sup>3</sup> is formed at pH >8, which is not adsorbed by the CCP 20. As a result, no cations are eluted that could lead to a change in the pH.

**Figure 1.** Final pH of the filtrates after 20 h contact with CCP 20 (SW1: *c*<sup>0</sup> = 967 mg/L NH<sup>4</sup> -N; SW2: *c*<sup>0</sup> = 927 mg/L NH<sup>4</sup> -N; *T* = 295 K; sorbent ratio 0.1 gCLI/mgNH4-N) as a function of the initial pH (adjusted pH of the solution before contact with CLI).

The pH increased in the acidic range (2–6), which can be attributed to the removal of NH<sup>4</sup> <sup>+</sup> and the elution of cations (e.g., Na<sup>+</sup> , K<sup>+</sup> , Ca2+, and Mg2+). The isoelectric state (pHISO) of CCP 20 with both sludge waters occurred at pH values of 8 and 10. The same values of pHISO were also determined after contact of CCP 20 with matrix-free NH4Cl solution [10]. Hence, an influence of the sludge water matrix on the pHISO is not detectable. Furthermore, Figure 1 shows the pH after spiking SW1 with equimolar NaCl instead of NaOH; the latter was added to the sample to adjust the pH. When spiked with NaCl (23–168 mmol/L), the pH remained at approx. 8.

α Figure 2 depicts the elimination of ammonium from SW1 and SW2 by CCP 20 as a function of the initial pH. Furthermore, the degree of dissociation α of the NH<sup>4</sup> <sup>+</sup>/NH<sup>3</sup> system is plotted over the initial pH. α

**Figure 2.** Elimination of ammonium from sludge water by CCP 20 (SW1: *c*<sup>0</sup> = 967 mg/L NH<sup>4</sup> -N; SW2: *c*<sup>0</sup> = 927 mg/L NH<sup>4</sup> -N; *T* = 295 K; sorbent ration 0.1 gCLI/mgNH4-N) after 20 h contact time as a function of different initial pH of the sludge water (adjusted pH before contact with CCP 20); in addition, the influence of an equimolar amount of Na<sup>+</sup> (from NaCl instead of NaOH to raise the pH) on the elimination is shown; degree of dissociation of ammonium in grey.

In the pH-range from 2 to 8 a consistent elimination between 66% and 81% was determined. A decrease in the elimination could be observed with pH values above 8. For SW1, the elimination decreased from 79% at pH 8 to 58% at pH 9 (59% at pH 10) and dropped to 24% at pH 12.2. At the same pH, the elimination from SW2 decreased from 81% to 55% (57% at pH 10) and finally to 19% (at pH 12). The batches with NaCl instead of NaOH indicate that the influence of sodium ions competing for sorption sites on the elimination is inferior to the influence of the pH. Although the elimination already declined

from 79% to 62% due to the addition of Na<sup>+</sup> (from NaCl), the equimolar amount of NaOH, which increased the pH to 12.2, led to an even lower elimination of only 24%.

When comparing these results with results from similar experiments with matrix-free solution (pH 9: 73% elimination; pH 12.2: 20% elimination [10]), only a slightly negative influence of the SW matrix becomes apparent. Table 2 shows that both SW1 and SW2 had constituents (e. g., K<sup>+</sup> , Na<sup>+</sup> ) that compete with ammonium for adsorption sites

Comparable studies with leachate have reported an elimination of 68% at pH 7 [22]. At pH 7 a higher loading (*q* = 17.7 mg/g) was achieved from swine liquid manure as compared to the arbitrary pH 8.2 (*q* = 12.5 mg/g) [17]. Furthermore, investigations with artificial swine wastewater stated that most ammonium was removed at pH 7, also showing a strong decrease in sorption with increasing pH [39]. On the contrary, the sorption of ammonium from drinking water was not affected by pH in the range of 5–9 [40].

The results here reveal that at a pH of 7, ammonium is eliminated to a high degree. In contrast to the literature results, a high degree of elimination could be realized with CCP 20 at arbitrary pH (7.9 or 8.0). A higher pH, however, should be avoided.

#### *3.2. Isothermal Adsorption*

Figure 3 displays the equilibrium loading *qeq* of CCP 20 and the corresponding equilibrium concentration *ceq* after 20 h contact time with SW1 and SW2 at different temperatures (283 K, 295 K, and 307 K). The lines represent the Freundlich equation, which gained the highest degree of determination of all tested isothermal equations (Freundlich, Langmuir, Temkin). The coefficients of the isothermal equations and their coefficient of determination are listed in Table 5. From the high concordance with the Freundlich isotherm, it can be deduced, that CLI has a heterogeneous surface, resulting in non-ideal sorption. Furthermore, the sorption process from sludge water is non-ideal, e.g., possible multiple occupancy of a sorption site as well as not all sorption sites are occupied.

**Figure 3.** Equilibrium load *qeq* and equilibrium concentration *ceq* of CCP 20 and Freundlich isotherm of CCP 20 after 20 h contact time with SW1 or SW2 at different temperatures (SW1: *c*<sup>0</sup> = 967 mg/L NH<sup>4</sup> -N; initial pH 8.1; final pH 7.6–8.6. SW2: *c*<sup>0</sup> = 866–913 mg/L NH<sup>4</sup> -N; initial pH 7.9; final pH 7.2– 8.0).

≈

≈ ≈

≈

≈ ≈


**Table 5.** Coefficients of isothermal adaptation according to Freundlich, Langmuir and Temkin for CCP 20 after 20 h contact time with SW1 or SW2 at different temperatures (SW1: *c*<sup>0</sup> = 967 mg/L NH<sup>4</sup> -N; initial pH 8.1; final pH 7.6–8.6. SW2: *c*<sup>0</sup> = 866–913 mg/L NH<sup>4</sup> -N; initial pH 7.9; final pH 7.2–8.0).

The pH of the filtrate of SW1 (initial pH 8.1) changed independently to values between 7.6 and 8.6 during contact, and to 7.2 to 8.0 for SW2 (initial pH 7.9), whereby the former occurred with low sorbent masses and the latter was determined in a blind test without sorbent. As a result, the pH value dropped slightly due to the sorption process.

The highest equilibrium load of CCP 20 with ammonium from SW1 was 16.1 mg/g at 307 K. However, this was considerably lower by 13% than observed for matrix-free solution (NH4Cl) with a similar concentration of 1000 mg/L NH4-N (*qeq* = 18.8 mg/g [10]). From SW2, the highest equilibrium load was 15.3 mg/g at 295 K (18% lower than from matrixfree solution). The load was lower at 307 K, but this was probably due to an alteration in the ammonium concentration in SW2 between the tests.

The minor loading of CCP 20 compared to matrix-free solution could be ascribed to the constituents in the sludge water, which interfere with the sorption process and thus lead to a reduction of the adsorption capacity. In particular, the deeper sorption sites in the framework of the CLI are probably more difficult to access. Access pores may be blocked or sorption sites may be occupied by other constituents in the sludge water. Furthermore, blocking of zeolite pores could be caused e.g., by solids. In addition, the viscosity of the sludge water changes depending on the temperature, which could also influence the loading of the CLI.

A decrease in the adsorption capacity of zeolite due to the wastewater matrix has been reported in several publications [16,17]. By using swine manure (*c*<sup>0</sup> = 7700 mg/L NH<sup>4</sup> + ) instead of NH4Cl solution (*c*<sup>0</sup> = 7700 mg/L NH<sup>4</sup> + ), the uptake capacity of the tested CLI decreased from 10 mg/g to 2 mg/g [17]. To a similar extent as was found in this paper, a decrease of 10–20% of the adsorption capacity when using leachate from a sewage sludge landfill (*c*<sup>0</sup> = 115.16 mg/L NH4-N) instead of NH4Cl solution (*c*<sup>0</sup> = 119.48 mg/L NH4-N) was reported [16]. The authors attributed this to ions such as Na<sup>+</sup> , K<sup>+</sup> , Mg2+, and Ca2+ with ion ratios of ammonium to potassium of [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 14.6 and sodium of [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 2.7 in the leachate. However, in both sludge waters investigated ammonium was present in multiple excess (SW1: [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 5; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 10; SW2: [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 24–30; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 10–12) and thus ammonium dominated the sorption process.

The determined ion ratio of ammonium to potassium and sodium in SW1 and SW2 was higher than reported by Wang et al. [16], but the difference in load between sludge water and matrix-free solution [10] was within the same magnitude. Obviously, the capacity of CCP 20 is influenced by both, the cations contained in the sludge water and by the matrix of the sludge water.

#### *3.3. Thermodynamic Properties*

Table 6 lists the determined thermodynamic state variables free reactivity enthalpy ∆*G* 0 , free standard enthalpy ∆*H<sup>0</sup> ,* and molar standard entropy ∆*S* <sup>0</sup> after 20 h contact time of CCP 20 with SW1 and SW2.

**Table 6.** Thermodynamic properties of CCP 20 after 20 h contact time with SW1 or SW2 (SW1: *c*<sup>0</sup> = 967 mg L−<sup>1</sup> NH<sup>4</sup> -N; Initial pH 8.1; Final pH 7.6–8.6. SW2: *c*<sup>0</sup> = 866–913 mg L−<sup>1</sup> NH<sup>4</sup> -N; Initial pH 7.9; Final pH 7.2–8.0).


In the examined temperature range (283–307 K), an exergonic, i.e., voluntary sorption process of ammonium to CLI, can be deduced from to the negative free reaction enthalpy ∆*G* 0 . The free standard enthalpy ∆*H*<sup>0</sup> was positive for SW1, i.e., an endothermic reaction was present. In contrast to this, an exothermic reaction was observed for SW2. The positive molar standard entropy ∆*S* 0 indicates a directed process. Independent of the matrix, the reaction of ammonium with CLI is voluntary and directed.

From experiments with CLI and matrix-free solution, an exergonic reaction was also reported with ∆*G* 0 ranging from −2.8662 to 0.22 kJ/mol [41], −0.79 to 1.63 kJ/mol [42], and −0.22 to 1.60 kJ/mol [43]. In this study, the values of ∆*G* 0 ranged from −15 to −17 kJ/mol. The much lower values regarding ∆*G* <sup>0</sup> of this study can be attributed to the smaller particle size and therefore short diffusion pathways of cations into the CLI. For their experiments, Alshameri et al. [41], Gunay [42], and Karadag et al. [43] used zeolites with larger particle sizes such as 0.063–0.074 mm, 0.3–0.6 mm, and 1.0–1.4 mm.

On the contrary to the results published by other researchers (∆*H*<sup>0</sup> : −49.384, −22.34, −5.43, −15.38 kJ/mol [41–44]), which indicate that adsorption of ammonium is exothermic, a slightly endothermic adsorption from SW1 (∆*H*<sup>0</sup> : 8.5 kJ/mol (SW1)) was found. However, adsorption from SW2 was exothermic (∆*H*<sup>0</sup> : −15.5 kJ/mol).

Furthermore, results reported with negative values of ∆*S* 0 (−0.1561, −43.03, −49.34, −74.42 kJ/(mol K) [41–44]) indicate decreasing ammonium uptake due to increasing randomness. In contrast to this, a strongly directed adsorption process, as indicated by positive ∆*S* <sup>0</sup> values ranging between 2.6 J/(K mol)−<sup>1</sup> (SW2) and 84.3 J/(K mol)−<sup>1</sup> (SW1), was achieved.

#### *3.4. Kinetic Studies*

3.4.1. Influence of Temperature on Kinetics

In Figure 4, the loading of CCP 20 with ammonium from sludge water at various temperatures (283 K to 307 K) after different contact times (up to 180 min) is depicted. The sorption kinetics at the investigated temperatures are fit to the ID model.

− **Figure 4.** Loading *q*(*t*) of CCP 20 as a function of contact time *t* at different temperatures (283–307 K) and fit to the ID model (specific sorbent ratio: 0.1 gCLI/mgNH4−N; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.3–7.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.6; final pH 7.4–8.3; SW2: *c*<sup>0</sup> = 913 mg/L NH4-N; initial pH 7.6; final pH 6.5–8.2).

Over the entire temperature range, a rapid adsorption of ammonium by CCP 20 was observed. Within the first five minutes, a high loading occurred, independently of the sludge water matrix.

Table 7 shows the coefficients of the kinetic fit according to both, PSO and ID model, the latter of which achieved a higher coefficient of determination.


**Table 7.** Coefficients of the sorption kinetics according to the PSO and ID models of CCP 20 at different temperatures (283–307 K, specific sorbent ratio: 0.1 gCLI/mgNH4−N; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.3–7.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.6; final pH 7.4–8.3; SW2: *c*<sup>0</sup> = 913 mg/L NH4-N; initial pH 7.6; final pH 6.5–8.2).

From the PSO model, an increase of *k*<sup>2</sup> from 0.065 g/(mg min) to 0.090 g/(mg min) could be derived with increasing temperature of the matrix-free NH4Cl solution. For SW1, *k*<sup>2</sup> first decreased with increasing temperature from 0.056 g/(mg min) (at 283 K) to 0.043 g/(mg min) (295 K), but then increased to 0.070 g/(mg min) (307 K). With SW2, *k*<sup>2</sup> remained almost unchanged with 0.041 g/(mg min) (at 295 K) and 0.037 g/(mg min) (at 307 K). Thus, the sludge-water matrix caused a reduction of the sorption rate *k*2. Temperature only had a minor effect on the sorption rate in the range of 283–295 K. The equilibrium load *q<sup>e</sup>* was similar for all samples, with a higher value for *q<sup>e</sup>* being obtained with increasing temperature.

For all three matrices, an increase in the initial sorption *C* was observed with increasing temperature, whereas the sorption rate *kID* was only slightly affected. In the case of the matrix-free solution, *kID* decreased from 0.159 mg/(min0.5 g) at 283 K to 0.129 mg/(min0.5 g) at 307 K. In contrast, *kID* increased slightly with SW1 between 283 K and 295 K. This low coefficient of determination of the sorption kinetics at 283 K indicates that no ID was present at low temperatures. Nevertheless, it was also shown that the kinetics at 295 K slowed down. Here, *kID* decreased from 0.208 mg/(min0.5 g) to 0.161 mg/(min0.5 g).

Regardless of the sorption kinetics, it should be recognized that ammonium uptake was mainly affected by initial sorption, which in turn was greater at higher temperatures. After the CCP 20 was in contact with the matrix-free solution or sludge waters for 30 min at 307 K, a load between 6.88 mg/g (SW2) and 7.15 mg/g (SW1) of was determined.

Similar conclusions regarding a decrease of the sorption rate as a result of an increase in temperature were described according to the PSO model (NH4Cl solution) [43]. Furthermore, it was concluded that this was an exothermic process, which was slower due to increased temperatures. On the other hand, it was found that *k*<sup>2</sup> was reduced and *kID* increased due to increased temperature [23]. Consequently, the equilibrium was reached later. However, the values reported by Erdo ˘gan and Ülkü [23] for *<sup>k</sup>ID* with 4.8 10−<sup>3</sup> mg/(min0.5 g) at 298 K and 5.4 10−<sup>3</sup> mg/(min0.5'g) at 313 K were about a factor of 30 lower than the values obtained with CCP 20. This is probably ascribed to the larger particle sizes of the CLI (0.85–2.00 mm [23]) investigated.

#### 3.4.2. Influence of the Specific Dosage on Kinetics

Figure 5 displays the loading *q*(*t*) as a function of the contact time *t* of CCP 20 at different specific sorbent dosages (0.05–0.2 gCLI/mgNH4N) after contact with NH4Cl solution as well as SW1 and SW2. In addition, the fit of the ID model, which had gained the highest coefficient of determination, is shown. A load between 3.07 mg/g and 7.25 mg/g was realized after only 5 min, regardless of the matrix. After 30 min contact time, depending on the specific sorbent addition (0.05–0.2 gCLI/mgNH4N), a loading of between 4.15 mg/g

**Figure 5.** Loading *q*(*t*) of CCP 20 as a function of the contact time *t* after different specific sorbent ratios (0.05–0.2 gCLI/mgNH4-N) aligned with the ID model (*T* = 295 K; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.3–7.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.6; final pH 7.5–8.5; SW2: *c*<sup>0</sup> = 718–913 mg/L NH4-N; initial pH 7.6; final pH 7.7–8.2).

Table 8 displays the coefficients of the sorption kinetics according to the PSO model and the ID model. The high coefficients of determination of the ID model indicate the limitation of the sorption rate by intraparticle diffusion.

− −


**Table 8.** Coefficients of the sorption kinetics according to the PSO and ID models of CCP 20 after different sorbent loads (*T* = 295 K; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.3–7.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.6; final pH 7.5–8.5; SW2: *c*<sup>0</sup> = 718–913 mg/L NH4-N; initial pH 7.6; final pH 7.7–8.2.

The coefficients of the PSO model and the ID model indicate that the sorbent dosage has a decisive influence on the rate of ammonium uptake. In the investigated samples, *k*<sup>2</sup> increased with increasing sorbent dosage, i.e., the sorption equilibrium was achieved earlier. With the lowest specific sorbent dosage of 0.05 gCLI/mgNH4-N, *k*<sup>2</sup> was between 0.008 g/(mg min) (SW2) and 0.048 g/(mg min) (SW1) and rose disproportionately with a specific dosage of 0.2 gCLI/mgNH4-N to 0.062 g/(mg min) (SW2), 0.154 g/(mg min) (NH4Cl) or even up to 0.188 g/(mg min) (SW1). In contrast, the load *q<sup>e</sup>* decreased from 9.26 mg/g (SW2) to 4.35 mg/g (SW1) with increasing sorbent dosage. The values for *kID* became smaller with increasing sorbent loading, i.e., the sorption equilibrium was achieved earlier. Thus, *kID* values of 0.410 mg/(min0.5 g) (SW2), 0.202 mg/(min0.5 g) (SW1), and 0.225 mg/(min0.5 g) (NH4Cl) where reached at a dosage of 0.05 gCLI/mgNH4-N, which then decreased to 0.135 mg/(min0.5 g) (SW2) and 0.063 mg/(min0.5 g) (SW1) and 0.058 mg/(min0.5 g) (NH4Cl), respectively, at a dosage of 0.2 gCLI/mgNH4-N. The constant *C*, which is proportional to the thickness of the boundary layer and represents the initial sorption, was also reduced from 6.31 mg/g to 3.78 mg/g (NH4Cl), from 7.00 mg/g to 3.77 mg/g (SW1), and from 4.19 mg/g to 2.84 mg/g (SW2) when a larger sorbent dosage (0.05–0.2 gCLI/mgNH4-N) was applied. This can be ascribed to the fact that with higher specific dosage, more sorption sites are provided, resulting in a rapid sorbent equilibrium but lower load.

During the contact time investigated, only a slight influence of the sample matrix on the load has been observed. Neither was the uptake rate *k*<sup>2</sup> or *kID* influenced (except for SW2 at a specific dosage of 0.05 gCLI/mgNH4-N). However, regardless of the matrix, CCP 20 was in equilibrium after 120 min. In contrast, it was reported that for ammonium from matrix-free sorption solution one hour of contact time, but for that from the leachate 2.5 h were needed to achieve equilibrium [16]. The authors ascribed this to interfering cations such as Na<sup>+</sup> , K<sup>+</sup> , Mg2+, and Ca2+ ([NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 2.7; [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 14.6) in the leachate investigated. However, the high stoichiometric excess of ammonium in the sludge waters investigated in this work was larger (SW1: [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 5; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 10; SW2: [NH<sup>4</sup> + ]/[K<sup>+</sup> ] ≈ 24–30; [NH<sup>4</sup> + ]/[Na<sup>+</sup> ] ≈ 10–12). Hence, the interfering of competing cations can be assumed as low. Therefore, no significant difference between matrix-free solution and sludge water could be determined in this experiment.

#### 3.4.3. Influence of the Pre-load on Sorption Kinetics

During one sorption process, the CCP 20 may not be completely loaded, e.g., if the lowest possible residual concentration is to be achieved by a higher dosage of sorbent. In a process cascade, this partially pre-loaded sorbent could be returned and recontacted with sludge water. Similarly, a partial regeneration of the sorbent can result in partially loaded sorbent.

Figure 6 shows the loading *q*(*t*) of partially loaded CCP 20 after contact with NH4Cl solution, SW1, and SW2 as a function of the contact time *t*. For pre-loading, the sorbent was brought into contact with the sample for 30 min (*q*1) or 60 min (*q*2) at 307 K (based on the results from Section 3.4.1). In addition, the fit of the ID model is shown, which achieved the highest coefficient of determination (Table 9).

**Figure 6.** Loading *q*(*t*) of CCP 20 as a function of the contact time *t* of differently pre-loaded CCP 20 (*q0–q*<sup>2</sup> = 0–11.4 mg/g) and fit with the ID model (specific sorbent dosage: 0.1 gCLI/mgNH4-N; *T* = 307 K; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.9; final pH 7.6; SW2: *c*<sup>0</sup> = 775–913 mg/L NH4-N; initial pH 7.6; final pH 6.5–8.4).


**Table 9.** Coefficients of the sorption kinetics according to the PSO and ID models of CCP 20 with different pre-loads (specific sorbent dosage: 0.1 gCLI/mgNH4-N; *T* = 307 K; NH4Cl solution: *c*<sup>0</sup> = 1000 mg/L NH4-N; initial pH 5.3; final pH 6.0; SW1: *c*<sup>0</sup> = 967 mg/L NH4-N; initial pH 7.9; final pH 7.6; SW2: *c*<sup>0</sup> = 775–913 mg/L NH4-N; initial pH 7.6; final pH 6.5–8.4).

As Figure 6 shows, the loading of CCP 20 increased with increasing contact time. Unloaded sorbent is marked as *q*0, pre-loaded sorbent as *q*<sup>1</sup> and *q*2, respectively. Preloaded CCP 20 (*q*<sup>1</sup> and *q*2) adsorbed additional ammonium on contact with the sample. A considerable change in the load *q*(*t*) occurred for the matrix-free NH4Cl solution. However, CCP 20 pre-loaded with 11.4 mg/g was already close to the sorption equilibrium, so that no significant increase in loading could be determined.

In contrast, with both wastewater matrices of the sludge waters SW1 and SW2 even at the highest pre-load (*q2(SW1)* = 9.9 mg/g and *q2(SW2)* = 7.3 mg/g), an increase of loading was achieved.

Table 9 shows the coefficients of the kinetic fit according to the PSO and ID models, the latter achieving higher coefficients of determination.

Within 5 min contact time, a high initial loading (*C* = 5.12–6.16 mg/g) of the unloaded sorbent (*q*0) was achieved, independent of the sample matrix. When partially pre-loaded (*q*1), the loading of the sorbent was considerably increased in all tests; depending on the pre-loading (approx. 80% for NH4Cl, almost 100% for SW1 and approx. 60% for SW2). In the first pre-loading step (*q*1), the initial loading *C* of NH4Cl increased significantly from 6.16 mg/g (*q*0) by about 80% to 11.07 mg/g (*q*1). For SW1, it also increased considerably from 6.16 mg/g (*q*0) to 9.30 mg/g (*q*1), but for SW2 only slightly from 5.12 mg/g (*q*0) to 5.46 mg/g (*q*1). In case of the highest preload (*q*2), the initial load *C* of matrix-free NH4Cl was lower (10.69 mg/g), but in case of sludge water it increased (SW1: 12.11 mg/g; SW2: 8.25 mg/g). The decreasing values for *kID* of SW1 (*q*1–*q*2: 0.243–0.182 mg/(min0.5 g)) and SW2 (*q*1–*q*2: 0.316–0.229 mg/(min0.5 g)) indicate that the sorbent reached equilibrium faster due to the partial pre-loading. After 30 min, preloaded (*q*2) CCP 20 was loaded to an extend between 9.45 mg/g (SW2) and 13.63 mg/g (SW1).

The fit of the sorption kinetics from matrix-free NH4Cl solution by means of the PSO model reveals that *k*<sup>2</sup> increased with increasing pre-load of the sorbent, i.e., the sorbent achieved equilibrium faster. However, *k*<sup>2</sup> of unloaded CCP 20 (*q*0) attained 0.090 g/(mg min), which increased to 0.135 g/(mg min) when partially loaded (*q*1) and finally to 0.161 g/(mg min) with the highest pre-load (*q*2), which was almost in equilibrium. On the contrary, the *k*<sup>2</sup> values for SW1 (*q*0–*q*2: 0.042–0.070 g/(mg min)) and SW2 (*q*0–*q*2: 0.027–0.043 g/(mg min)) do not allow clear conclusions due to their wide variation.

Nevertheless, it has been ascertained that the sorption equilibrium is achieved faster from matrix-free NH4Cl solution than from sludge water. This can be ascribed to cations competing for sorption sites, but also to organic matter or particles contained in the sludge water and the slower diffusion of ammonium to deeper sorption sites. In a process cascade, in which a high CLI dosage has to achieve the lowest possible residual concentration, the

partially loaded CLI could be brought into contact with sludge water again in order to use its capacity to the full extent. In order to achieve the highest possible loading of the sorbent, up to three sorption phases should be carried out, each lasting a maximum of 30 min.

#### **4. Conclusions**

From experiments with high strength sludge waters with ammonium concentrations from 718 mg/L NH4-N to 967 mg/L NH4-N by means of Carpathian clinoptilolite, the following boundary conditions can be derived with which the highest possible loading of the sorbent CCP 20 can be achieved:


However, other boundary conditions may be relevant, depending on the objectives of the treatment, e.g., high loading of the sorbent, shortest possible contact time, low effluent concentrations. For the design as well as the implementation of the process, the required contact time is of major importance. In the experiments it could be shown that a high loading of the clinoptilolite can be achieved already after 30 min. Therefore, it can be deduced that the necessary equipment for the treatment of the relatively small partial flow of the sludge water compared to the main wastewater flow would only require minor construction and plant engineering upgrades.

Based on the found conditions, it is of interest for future investigations under which parameters the clinoptilolite can be regenerated and possibly reused. Furthermore, it should not be omitted that the liquid resulting from the regeneration is still usable or the recovered ammonium is available in a usable form.

**Author Contributions:** Conceptualization, S.W.; Investigation, S.W.; Methodology, S.W.; Visualization, S.W.; Writing—original draft, S.W.; Writing—review & editing, E.R., R.M. and H.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Federal Ministry of Economic Affairs and Energy following a resolution of the German Parliament.

**Data Availability Statement:** All data comes from the author.

**Acknowledgments:** We thank the Federal Ministry of Economic Affairs and Energy following a resolution of the German Parliament for sponsoring this research work (ZF4045511). The CLI was provided by Fluidtec, Kempenich, Germany.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Appendix A Titration Curve of SW1, SW2, and NH4Cl Solution**

During anaerobic digestion, large quantities of methane and CO<sup>2</sup> are formed, resulting in high concentrations of hydrogen carbonate in the sludge water. By lowering the pH, the hydrogen carbonate is converted into CO2, which then outgasses.

The base capacity, i.e., the amount of OH<sup>−</sup> required to adjust the pH to 8.2, corresponds to the amount of free CO<sup>2</sup> in the solution. The acid capacity, i.e., the amount of H3O<sup>+</sup> necessary to adjust the pH to 4.3, corresponds to the amount of HCO<sup>3</sup> <sup>−</sup>. In addition, other compounds such as ammonium, borate, phosphate, sulfate, nitrate, etc. may react, therefore the titration method can only be applied to sludge water to a limited extent [45].

The amounts of OH−or H3O<sup>+</sup> required to adjust the pH of SW1, SW2 and NH4Cl solution are shown in Figure A1.

−

−

−

**Figure A1.** Quantity of OH<sup>−</sup> (NaOH) and H3O<sup>+</sup> (HCl) to adjust the pH of SW1, SW2, and NH4Cl solution as well as the degree of dissociation of ammonium depending on the pH.

Only a small amount of H3O<sup>+</sup> (pH 4: 0.09 mmol/L; pH 3: 1.2 mmol/L; pH 2: 12.7 mmol/L) was required to lower the pH of NH4Cl (arbitrary pH 5.3), as no hydrogen carbonate was present. For an increase of the pH, a larger amount of OH<sup>−</sup> was required due to the conversion of NH<sup>4</sup> + into NH<sup>3</sup> (pH 7: 0.3 mmol/L; pH 8: 15.8 mmol/L; pH 12: 90 mmol/L). Since no other substances were present in the matrix-free solution, a stoichiometric transformation of OH<sup>−</sup> for the conversion of NH<sup>4</sup> + into NH<sup>3</sup> can be assumed when adjusting the pH value.

For both sludge waters SW1 and SW2, almost the same amount of H3O<sup>+</sup> and OH<sup>−</sup> was required. However, the amount of H3O<sup>+</sup> and OH<sup>−</sup> required for pH adjustment of NH4Cl solution was much lower. Obviously, a large amount of hydrogen carbonate buffering the pH was present. For example, 74.5 mmol/L of H3O<sup>+</sup> was needed to set up a pH of 5 for SW1 and 73.8 mmol/L of H3O<sup>+</sup> for SW2. To adjust a pH of 10, 90.9 mmol/L and 85 mmol/L OH−, respectively, were required. Due to the high concentration of interfering ions, it is not possible to determine the exact acid/base capacity and hydrogen carbonate concentration in the sludge waters. Based on the data, it can be estimated at approx. 75–80 mmol/L. The hydrogen carbonate is opposed by a sufficiently large amount of ammonium cations (55–69 mmol/L) as counter ion.

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