13.1 Introduction

Algae are everywhere on the earth like in rivers, lakes, seas, on soil and walls, in plants and animals (as symbionts-partners collaborating together), or can say every place where lights are present to carry out photosynthesis (El Gamal 2010). The primary producer of the marine food chain is marine microalgae which show the toxic impact on a higher level when the toxicants are consumed by the same (Purbonegoro et al. 2018). Alga is considered to be an abundant and vastly accessible natural resource in a tropical ecosystem. It is observed that the brown algae have better uptake capacity as compared to red and green and considered to be one of the best biosorbents for the retrieval of the heavy metals. Alginic acid and fucoidan are present in their cell wall, and at neutral pH, the alginic acid yields sulfate ion as well as carbohydrates (Sweetly 2014). Marine algae like Sargassum constitute of diverse multifunctional groups which are present on the surface and have even distribution of binding sites on the cell surface. There are many advantages of marine algae as biosorbent like the requirement of minimal preparatory steps, retention capacity is excellent and truly renewable, recyclable, and simply available all year around.

As biosorption is a passive mechanism, hence this process is faster than that of active or bioaccumulation (Bilal et al. 2018). Algal biosorption attributes the cell wall where complexation, as well as static attraction, plays a major role. Carboxyl group is considered to be the dominating binding groups in brown algae. Brown algae possess alginic acid and fucoidan in the cell wall matrix as well as in intercellular material. Seaweed is considered to be better than that of microbial biomasses because of the less variability in seawater than that of fermentation media. Marine algae carry a large number of biopolymers that are helpful in the metal binding.

Seaweeds are larger enough so that there is no need for any complicated or costly immobilization required (Schiewer and Volesky 2000). Seaweeds are accountable for recovery of heavy metals due to macroscopic structures which provides a basis for the formation of biosorbent particle. The brown alga Sargassum consists of gel materials in their call wall termed as alginates that are very porous in nature, are responsible for metal binding, and are also easily permeable to small ionic species. Volesky et al. reported Sargassum (brown algae) seaweeds as the best biomass for recovery of heavy metals (Vieira and Volesky 2000). In marine macroalgae, removal of heavy metals is done either by ion exchange on the surface of the cell or by means of intracellular transport of heavy metals (Sweetly 2014). Biosorption by marine algae is considered to be very effective as the marine algae are found in diverse size and are having better efficiency in removing heavy metals from wastewater which is one of the most critical problems nowadays. Numerous micro- and macroalgae are accountable for the recovery of different heavy metals. Marine algae or seaweeds like brown, red, and green have the highest sorption capacity or higher rate of bioaccumulation for the heavy metal ion. Out of these three seaweeds, brown algae are considered more proficient in biosorption. Marine algae are fast-growing algae and can perform relatively better as it requires a small amount of nutrients, CO2, and sunlight for its survival.

Figure 13.1 shows three types of marine algae (also known as macroalgae) that are responsible for the removal of heavy metals, and Table 13.1 shows the classification of marine algae on the basis of their different characteristics.

Fig. 13.1
figure 1

Types of marine algae

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Table 13.1 Characteristics of brown, red, and green algae
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13.2 Brown Algae

Brown algae are suitable for removing heavy metals as a consequence of its polysaccharide content (Volesky and Holan 1995). They have the capability to absorb heavy metals owing to chemical groups present on the surface, for instance, sulfonate, amino, carboxyl as well as sulfhydryl (Umar Mustapha and Halimoon 2015). It is one of the most important plant groups that are successfully studied for the biosorption of heavy metals from industrialized wastes.

Owing to the existence of large amounts of carotenoid fucoxanthin that are located in the chloroplast of brown algae, the color becomes brown; these brown algae are grown in marine environments. There are about 13 divisions of Phaeophyta (a division of brown algae); out of which 2 orders called Laminariales and Fucales are most important that are abundantly available in nature. The order Laminariales are known as “kelp” and commercially applicable in the production of syrups, dessert gels, ceramics (for stabilizing property), cleanser, welding rods, and so on. The order Fucales is vast; therefore some of its species are mainly studied for the properties of their biosorption or metal binding ability. Carboxylic groups are abundantly present in brown algae that are important in the biosorption process by reducing the cadmium and lead uptake (Fourest and Volesky 1996). After the carboxylic group, sulfonic acid plays a secondary role in metal binding at lower pH value.

Brown seaweed Sargassum baculari are useful for the biosorption of copper. Large amounts of seaweeds are harvested from oceans and can be further cultured for phycocolloid or food production. Lots of seaweeds are used for the testing of its biosorptive properties in the laboratory as well as on large-scale operations that can be easily conducted by the help of well-established activated carbon fixed-bed system. The process equipments and design procedure are already available, that’s why it is beneficial to implement the operations on fixed-bed configurations. The investigation on biosorption of copper with brown seaweeds Sargassum baccularia immobilized onto polyvinyl alcohol (PVA) gel beads in fixed-bed experiment (Chu and Hashim 2007). The immobilization of seaweeds by PVA is done as it is easily accessible and inexpensive and possesses the best abrasion resistance properties. Chu et al. concluded that the immobilization process of seaweed biomass in PVA gel was suited for removal of toxic metals like that of copper in fixed-bed column operations as biosorbent exhibited favorable regeneration conditions and also the biosorption capacity remains unchanged all through three cycles of biosorption-desorption successfully (Chu and Hashim 2007).

In the recent years, detection of a huge number of heavy metal and low-cost sorbents but brown algae is recognized as the most promising as well as the most effective substrate for remediation of M+ (metal ion) (Davis et al. 2003). The marine environment is considered to be the available source of the antimicrobial compounds as numerous sea organisms yield bioactive metabolites on the development of the chemical strategy and in response to the environmental stress (Maadane et al. 2017). The binding of M+ on the surface of algae depends upon many factors like algal species and ionic charge of metal ions (Sulaymon 2014). Brown algae are most effective macroalgae because it contains a higher amount of alginate and on the other side, a carboxylic group that is responsible for capturing the cations present in the solution (Manuel et al. 2016). Figure 13.2 depicts the process of removal of heavy metals by metabolite-dependent as well as metabolite-independent phenomena. As we know that for the recovery of heavy metal, functional groups are responsible for binding as commonly the ion-exchange process is done by algae during biosorption. On the other side, bioaccumulation of heavy metals is either transformed or accumulates in the vacuoles or cytoplast of the algae.

Fig. 13.2
figure 2

Different binding groups of brown macroalgae

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Figure 13.3 depicts algin or alginate and fucoidan are mainly present in the outer layer, as well as the inner layer of brown algae due to which it is unique in comparison to the red and green and sorption efficiency and is also better than other ones. Alginic acid is a polymer of guluronic acid, mannuronic acid, salts of sodium, potassium, magnesium, calcium, and sulfated polysaccharides (Davis et al. 2003; Sweetly 2014) that offers sulfate ions and anionic carbohydrate at neutral pH.

Fig. 13.3
figure 3

Metal sorption by brown algae

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13.3 Metabolic Pathway

The production of metabolites in brown algae was discussed by the help of “amino acid derivatives” and peptides metabolism and “energy and carbohydrate metabolism.”

13.3.1 Amino Acid Derivatives and Peptides

A study was conducted by Belghit et al. in which 70 compounds possess significant difference in relative abundance among 139 compounds related to amino acid derivatives (Fig. 13.4).

Fig. 13.4
figure 4

Typical metabolic pathway for the formation of metabolites possessed by brown algae (glutamate, ornithine, and citrulline) that are involved in the urea cycle

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Many of these compounds ascribed to the stress response. Seaweeds are subjected to a variety of biotic and abiotic stress factors, and simultaneously they respond against this by regulating their physiological profile, especially carbon (C) and nitrogen (N) metabolism. N-enriched amino acids such as ornithine, glutamate, and citrulline are found in brown algae that help them to tolerate stress in different stress conditions (Belghit et al. 2017).

13.3.2 Energy and Carbohydrate Metabolism

Metabolites produced during glycolysis except glucose were more abundantly found in brown algae in comparison to red. Several Krebs cycle intermediates (citrate, succinate, cis-aconitate, and isocitrate) are highly concentrated in brown algae that protect them against oxidative stress. The metabolic pathway of their production is demonstrated in Fig. 13.5 (Belghit et al. 2017).

Fig. 13.5
figure 5

Metabolic pathway of formation of Krebs cycle intermediates abundantly found in brown algae

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13.4 Heavy Metals and their Toxicity

Nowadays, toxicity of heavy metals is a serious concern that causes a lot of problems. The sources of such metals are mining industries, battery industries, fertilizer and chemical industries, and nuclear power plant. To overcome this serious problem, several methods were conducted like biosorption, bioaccumulation which are responsible for recovery of these toxic metals from industrial runoffs by using numerous biosorbents (Manuel et al. 2016).

Heavy metals like lead (Pb), zinc (Zn), arsenic (As), copper (Cu), mercury (Hg), boron (B), manganese (Mn), aluminum (Al), and nickel (Ni) have density that is five times higher than that of water. As a limited amount of metal is essential for human health but if consumes in more amount, it causes hazardous effects on living beings (Table 13.2). Copper is considered to be a component of several enzymes and proteins that participate in a different metabolic pathways in algae (Purbonegoro et al. 2018).

Table 13.2 Sources and toxicity of heavy metals
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13.5 Biosorption

The term biosorption is a subclass of adsorption wherein the biological matrix is sorbent. This process provides an economical, eco-friendly, reversible, and rapid binding of M+ from solution against functional groups available on the biomass surface. It is not dependent on cellular metabolism. It was found that among all the biosorbents, algae were found to be most appreciable (Michalal et al. 2013). Biosorption is responsible for removal of heavy metals and precious metals (Sweetly 2014). There are several conventional methods like precipitation, coagulation, ion exchange, and membrane separation for removal of heavy metals but consist of several disadvantages like requirements of higher energy, reagents, expensive, toxic waste product generation, and not effective at low metal concentration. The adsorption mediated through activated carbon is considered to be the most effective method, but it also carries some disadvantages like high cost and non-recyclable in nature (Ramezani et al. 2013). The brown algae are considered to be one of the best biosorbents for recovery of heavy metals (Aziz 2004). It was reported that the green marine macroalgae possess the potential for removal of heavy metals such as Pb, Hg, and Cd from the aqueous solution. It was found that the highest Cd and Pb uptake is done by Chaetomorpha species and for Hg, C. sertularioides (Kumar and Goyal 2009). The excellent recovery of gold is shown by Sargassum natans (a brown alga) as reported in US Patent no. 4,769,223 (Volesky and Kuyucak 1988).

Table 13.3 shows different authors who have investigated different aspects like the usage of free/immobilized biomass in continuous/batch column experiment and includes parameters affecting the process (pH, temperature, and functional group). Thus, marine algae have a carboxylic group that is responsible for the heavy metal recovery.

Table 13.3 Factors affecting biosorption of heavy metals using marine algae
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13.6 Bioaccumulation

As soon as a portion of metal is taken by microorganism, then the process of bioaccumulation takes place. It is an active process wherein metal is metabolically controlled like energy production and transformation (Arunakumara and Zhang 2008). Brown algae show higher accumulation of heavy metals in comparison to green and red algae mainly because of the presence of polysaccharides and polyphenolic substances that constitute their cellular wall (Wallenstein et al. 2009). Brown algae are considered to be one of the better bioaccumulators of heavy metals and can also be used as a universal bioaccumulator (Sweetly 2014). Bioaccumulation is a complex process where metal level must be checked in the tissues from two adjacent tropical levels in animals (Jakimska et al. 2011). Cladophora herpestica (green algae) is considered as one of the dominating and abundantly growing on the Maruit lake surface can accumulate residual nutrients in addition to heavy metal ions from both atmospheric and aquatic environments (Al Maghraby and Hassan 2017). It was found that the accumulation of Hg, Cd, Zn, and Ag is done by various marine algae successfully (Fisher et al. 1984). Marine microalgae are considered to be a promising indicator species for inorganic as well as organic pollutants because of their abundance in the marine ecosystem that occupies the base of the food chain (Torres et al. 2008).

Table 13.4 depicts the bioaccumulation of various heavy metals by marine algae. In a report, it was found that the capacity of metal recovery like Hg has been checked by taking three algae, i.e., Ulva lactuca (green), Gracilaria gracilis (red), and Fucus vesiculosus (brown), and the result shows that the green algae have displayed the best performance in the recovery of Hg (Henriques et al. 2015). In a report, it was found that the green algae, i.e., Ulva lactuca, has the capability to remove Fe, Mn, Zn, Pb, Cr, and Cd metals except for Cu (Swaleh et al. 2016).

Table 13.4 Bioaccumulation of heavy metals from wastewater using marine algae
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13.7 Advantages of Algal Biomass Over Conventional Methods

There are numerous advantages of algal biomass as a biosorbent such as used in the wastewater with high metal concentration, unlike the membrane process. Metal uptake capacity and efficiency of metal removal are also high. In addition to this, regeneration of biomass takes place and is cost-effective. These biomasses can be easily reused in different adsorption/desorption cycles. These biomasses can be used all year around. No generation of toxic chemicals takes place. Macroalgal biomass does not need to be immobilized. Few chemicals for the regeneration and desorption of biosorbent are needed. It is suitable for anaerobic as well as aerobic effluent treatment units used in continuous as well as in discontinuous regime for the selectivity of heavy metal ions. During acid treatment of algal biomass, the polysaccharides that are present on the cell wall can dissolve up to some extent, thus able to form additional binding sites generally the amino acids (González et al. 2011). As compared to the microbial biomasses that require immobilization for industrial-scale application, algal biomass can be used without any pretreatment (e.g., biosorption column) (Schiewer and Volesky 2000).

There are a lot of conventional methods used in the recovery of heavy metals like ion exchange, reverse osmosis, precipitation, membrane filtration, filtration, and coagulation, but each and every method has their own drawbacks like higher cost and time-consuming. To overcome all these drawbacks, here comes the process of biosorption. Biosorption poses numerous advantages over conventional methods together with efficiency, cost-effectiveness, regeneration of biosorbent with the possibility of metal recovery, and requirements of additional nutrients minimization of biological/chemical sludge (Alluri et al. 2007).

13.8 Isotherm Models Used in the Biosorption Process

13.8.1 Langmuir Isotherm

This isotherm assumes a surface having equivalent sorption energies, homogeneous binding sites also, and no interactions between species that are sorbed. In this isotherm, once a site gets filled, then there will be no other sorption at that site (Langmuir 1916).

$$ \frac{C_q}{Q_{eq}}=\frac{1}{bQ_{max}}+\frac{C_{eq}}{Q_{max}} $$
(15.1)

where

  • Qmax= Maximum amount of metal ions per unit weight of a bio sorbent(mg/g)

  • b = Langmuir constant that relates to the energy of adsorption

Langmuir isotherm can also be calculated in terms of separation parameters (dimensionless), i.e.,

$$ {R}_L=1/\left(1+b{C}_0\right) $$
(15.2)

Equation 13.2 indicates the shape of isotherm that helps to predict whether adsorption is favorable or not.

Conditions:

  1. 1.

    Favorable when 0 <RL< 1

  2. 2.

    Unfavorable when RL> 1

  3. 3.

    Linear when RL= 1

  4. 4.

    Irreversible when RL= 0

13.8.2 Freundlich Isotherm

These isotherms are applicable to adsorption on the surface that is heterogeneous with the interaction between the molecules that are adsorbed. On the basis of sorption on the heterogeneous surface, the equation is as under:

$$ \log Q=\mathit{\log}{K}_f+\frac{1}{n}\ \mathit{\log}{C}_e $$
(15.3)

where.

  • Kfand n = Freundlich constant

  • n = indicator of the degree of nonlinearity between adsorption and concentration of the solution.

Freundlich equilibrium constants are determined by the plots of log Qeqvs. log Ceq.

Conditions:

  1. 1.

    Linear adsorption occurs when n = 1

  2. 2.

    Physical process adsorption occurs when n > 1

  3. 3.

    Chemical process adsorption occurs when n < 1

13.8.3 Redlich-Peterson Isotherm

It is considered to be a special case of Langmuir when constant g becomes unity. It can be applied on the homogeneous surface or on a heterogeneous surface/system (Abdel-Ghani et al. 2015).

$$ \mathrm{Linear}\ \mathrm{form}\ \mathit{\ln}\left[\left(\frac{A{C}_e}{q_e}\right)-1\right]=g\ \mathit{\ln}\left({C}_e\right)+\mathit{\ln}(B) $$
(15.4)

where A, B, and g(0 < g < 1) that are represented are isotherm constant

At higher concentration, the isotherm equation reduced to form Freundlich isotherm, and when g = 1, then it reduced to Langmuir isotherm.

13.8.4 Sip Isotherm

An empirical formula was proposed by Sip and also termed as Langmuir-Freundlich isotherm, which is often represented as (Abdel-Ghani et al. 2015):

$$ {q}_e=\frac{K_s{C}_e^{n_s}}{1+{a}_s{C}_e^{n_s}} $$
(15.5)

where

  • Ks = Sip’s constant /affinity constant (Lmg−1)

  • ns = heterogeneity coefficient

At higher concentration of sorbate, Sip isotherm predicts as Langmuir isotherm.

At lower concentration of sorbate, Sip isotherm reduced to Freundlich isotherm and did not obeys Henry law.

13.8.5 Temkin Isotherm

This isotherm provides an equal distribution of binding energies on various exchange sites on the surface (Abdel-Ghani et al. 2015).

$$ \mathrm{Linear}\ \mathrm{Temkin}\ \mathrm{isotherm}\kern1.00em {q}_e=B\ \mathit{\ln}\ A+b\ \mathit{\ln}\ {C}_e $$
(15.6)

where

  • B = RT/b

  • R = universal gas constant (8.314 Lmol−1 K−1)

  • T = absolute temperature in Kelvin

  • B = heat of sorption

  • A = equilibrium binding constant

13.8.6 Dubinin-Radushkevich (D-R) Isotherm

This isotherm is a semi-empirical equation under which the adsorption follows a mechanism of pore filling. It is applicable to the process of physical adsorption and consists of van der Waals forces (Abdel-Ghani et al. 2015).

$$ \mathrm{Linear}\ \mathrm{form}\kern1.25em \mathit{\ln}\ {q}_e=\mathit{\ln}\ {q}_d-\beta {\epsilon}^2 $$
(15.7)

Where,

  • qd= D-R constant (mg g−1)

  • β = constant related to free energy

  • T = absolute temperature in Kelvin

  • ϵ = Polanyi potential

$$ \epsilon = RT\ \mathit{\ln}\left[1+1/{C}_e\right] $$
(15.8)

13.9 Estimation of Equilibrium in Biosorption

The equilibrium in biosorption process is estimated by sorption isotherms which are beneficial in evaluating the relationship between equilibrium concentration (Ce) of the metal ions and the mass of metal ions bounded per (qe) unit mass of biosorbent. Most of the time, the equilibrium between solid and liquid is done by Langmuir isotherm (Michalak et al. 2013). A chemical speciation computer program termed as PHREEQCI 6.2 was used to calculate data corresponding to equilibrium condition and compared with experimental data. At equilibrium, the data of M+ concentration remaining in the solution is entered, and software is useful for calculating both the number of unoccupied sites at equilibrium (qmax − q) and the amount of metal that is taken up by biomass (availability of number of active sites for the occupied metal in this condition). And finally, the program database was uploaded. This program excellently reproduces the experimental results, with a better correlation between calculated data and experimental data. Hence, PHREEQCI program has proven as one of the important means for predicting the behavior of biomass after equilibrium has attained (Romera et al. 2007).

13.10 Kinetics of Biosorption

Pseudo-first-order and pseudo-second-order kinetic model are utilized to study the kinetics of heavy metals (Tálos et al. 2012). The kinetic study of the biosorption process is done as it is useful in the determination of the time of contact that is helpful in assessing sorption equilibrium and for the analysis of process parameters like temperature, and pH that are helpful for the identification of the sorptive properties of the given biosorbents (Michalak et al. 2013).

The spirulina biomass can be proficiently utilized for removal of rhenium from the industrial effluent as well as batch solution. The biosorption of rhenium with the help of spirulina biomass fits better in pseudo-second-order kinetic model (Zinicovscaia et al. 2018). Different models related to kinetics are mentioned in Table 13.5.

Table 13.5 Kinetic models for biosorption
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Spirulina platensis has the maximum attainable biosorption that is 97.1%, and the equilibrium adsorption capacities of the adsorbent which are used for zinc ions were investigated using the two isotherms that are Langmuir and Freundlich isotherms, and Langmuir isotherm was found as a better correlation (Gaur and Dehankhar 2009). The term pseudo-second order has reaction constant K2 and was introduced in the mid-1980s, but it was not very popular until 1999 when McKay and Ho performed numerous experiments and concluded result. They analyzed that pseudo-second-order kinetics offers excellent correlation of experimental data (Liu and Shen 2008; Simonin and Bouté 2016). It was investigated successfully that the adsorption of metals like Cd2+ and Cu2+ has been defined more efficiently by pseudo-second order (Dang et al. 2008).

13.11 Discussion

In this chapter, marine algae are considered as an appropriate biosorbent for removal of heavy metals attributable because of the presence of rich polysaccharides in their cell wall. To support this, various models have been discussed. The utilization of brown algae is mainly because of the reason that it possesses the best biosorptive as well as bioaccumulative properties in comparison to red and green algae. It is concluded that the carboxylic group is the most abundant and dominant acidic functional group followed by fucoidan. Due to the abundance in the extracellular polymers and cell wall matrix polysaccharides, brown algae are most useful in the removal of heavy metals from the industrial effluents.