There is a growing need for the use of low-cost and ecofriendly adsorbents in water/wastewater treatment applications. Conventional adsorbents as well as biosorbents from different natural and agricultural sources have been extensively studied and reviewed. However, there is a lack of reviews on biosorption utilizing industrial wastes, particularly those of food processing and pharmaceuticals. The current review evaluates the potential of these wastes as biosorbents for the removal of some hazardous contaminants. Sources and applications of these biosorbents are presented, while factors affecting biosorption are discussed. Equilibrium, kinetics, and mechanisms of biosorption are also reviewed. In spite of the wide spread application of these biosorbents in the treatment of heavy metals and dyes, more research is required on other classes of pollutants. In addition, further work should be dedicated to studying scaling up of the process and its economic feasibility. More attention should also be given to enhancing mechanical strength, stability, life time, and reproducibility of the biosorbent. Environmental concerns regarding disposal of consumed biosorbents should be addressed by offering feasible biosorbent regeneration or pollutant immobilization options.
Increased industrial activities resulted in major environmental problems; one of the most challenging is water pollution and the subsequent scarcity in fresh and clean water resources available for current and future generations. Industrial wastewater contains various toxic compounds such as organics, heavy metals, and dyes which could have potential detrimental effect on human beings and aquatic lives. World Health Organization (WHO) recommended the maximum acceptable concentrations for these compounds in water streams. Dyes are one of the most polluted groups as their complex aromatic structure makes them difficult to be biologically degradable [
Removal of such pollutants from different industrial effluents may be achieved
Biosorption has become an attractive common technique for many reasons. Being a cost-effective, highly efficient, and easily implemented method made it a successful alternative for the conventional ones [
Disposal of different industrial wastes and by-products is considered a major environmental problem. The cost associated with the waste treatment or disposal, transport, and accumulation may sometimes be the most challenging problem in industry. Such problem increases especially in food industries which produce huge amount of wastes and by-products. Utilizing industrial wastes as low-cost effective biosorbents introduces a bifunctional solution from an environmental point of view. That is to say, treating wastewater effluents with these zero-cost waste materials adds value to these wastes while help solving an important environmental issue.
This paper reviews the state-of-the-art endeavors in utilizing industrial food processing and pharmaceutical wastes as effective low-cost biosorbents for water/wastewater treatment. The aim is to assess the potential of these wastes as biosorbents as well as highlight new options to be further explored and possibilities for improvement. To the best of the authors’ knowledge, research dedicated to these particular types of waste has not been reported elsewhere. A comprehensive critical review is presented on (i) the different biosorption techniques and mechanisms, (ii) controlling factors, (iii) equilibrium and kinetics studies, and (iv) recovery and/or pretreatment options. Moreover, concluding remarks will be given at the end along with some suggestions for future work.
Adsorption as a process gained much more attention recently after the use of low-cost adsorbents became so popular especially
A schematic flow diagram showing the different types of available adsorbents.
Biosorbents are a large subclass of low-cost adsorbents that can be subdivided into [
Less research has been done on industrial food processing and pharmaceutical wastes despite their huge annual worldwide production. Scarcity of relevant reviews was therefore the main motivation of this current work. Biosorbents from these origins are expected to grow by an annual rate of around 5% in the next few years [
Utilizing these wastes as biosorbents has been applied in the area of water purification and/or wastewater treatment; previous work in this regard is summarized in Table
Summary of the different industrial food processing and pharmaceutical waste biosorbents; their sources, applications, and the relevant biosorption parameters.
Type of biosorbent | Source of biosorbent | Feed solution | Sorbate | pH | Contact time, min | Temperature, °C | Initial concentration of sorbate, mg/L | Mode of operation | Maximum |
Biosorbent dose | Reference |
---|---|---|---|---|---|---|---|---|---|---|---|
Spent brewery grains (SBG) | Mohan breweries and distilleries Limited, Chennai, India | Synthetic dye solution | AG25 acid dye of commercial name Alizarin Cyanin Green G | 3.0 | 75 | 30 | 90 | Batch | 98 | 0.2 | [ |
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Tea industry waste | Local tea factory in China | Aqueous synthetic solution | Cd(II) | 7.0 | 180 | 25 | 20 | Batch | 90 | 5 | [ |
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Exhausted coffee waste | Soluble coffee manufacturer, Catalonia, Spain | Aqueous synthetic solution | Cr(VI) |
3.0 | 8640 | 25 | 1000 | Batch | — | 6.67 | [ |
|
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Sugarcane bagasse waste | From local alcohol and sugar | Aqueous synthetic solution | Methylene Blue (MB) | 7.0 | 600 | 25 | 200 | Batch | — | 0.2 |
[ |
Industries, City of Ouro Preto, Minas Gerais, Brazil | Gentian Violet | 900 | 300 | ||||||||
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Wine processing waste sludge (WPWS) | Ilan Wine-Processing Company, Ilan, Taiwan | Aqueous synthetic solution | Cr(III, IV) | 2.0 | 240 | 30 | 100 | Batch | 36 | 10 | [ |
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Wine processing waste sludge (WPWS) | Ilan |
Aqueous synthetic solution | Ni(II) | 5.5 | 120 | 50 | 30 | Batch | 75 | 12 | [ |
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Grape bagasse waste residue | Wine production process, Styria region, Austria | Effluent from research laboratory | Cd(II) |
7.0 |
45 | 25 | 100 | Batch | — | 0.67 | [ |
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Waste beer yeast | Aoke Beer Company in Zhengzhou, Henan province, China | Aqueous synthetic solution | Cu(II) |
5.0 | 30 | 20 | 9.14 |
Batch | — | — | [ |
|
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Waste beer yeast |
Beer fermentation industry, brewery located near Chennai, India | Electroplating effluents | Cr(VI) | 5.0 | 120 | — | — | Batch | — | 0.02 | [ |
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Suspended brewery yeast waste biomass |
Brewery waste biomass collected from CIUC brewery, Miercurea-Ciuc, Romania | Synthetic aqueous solution | Cd(II) | 5.5 | 40 | 50 | 6 | Batch | 99.83 | 9.78 | [ |
|
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Beer brewery diatomite waste (SDE) | Shan-Hua factory, Tobacco and Liquor Co., TainanTaiwan | Synthetic aqueous solution |
Methylene Blue (MB) basic dye | 7.0 | 1440 | 25 | 2.5 | Batch | — | 0.25 | [ |
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Spent waste beer yeast |
Fermentor at a brewery, Chennai, India | Battery manufacturing industrial effluent | Pb(II) | 5.0 | 120 | 30 | 100 | Batch | — | — | [ |
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Fresh malted sorghum mash waste | local malted sorghum beer (pito) brewer at Navrongo, Ghana | Synthetic aqueous solution | Methylene Blue (MB) basic dye | 7.0 | 18 |
|
50 | Batch | >90 | 4 | [ |
|
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Waste biomass from sugarcane aguardente | Brazilian alcoholic beverage production, (Lapinha, Bocaiana, Germana and Taboroa) State of Minas Gerais, Brazil | Stainless steel effluent | Cr(VI) |
4.0 | 180 | 25 | 50 |
Batch | 70 |
1 | [ |
|
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Waste biomass Cachaça Brazilian alcoholic beverage | the stillage generated by a liquor distillery (Germana), Minas Gerais, Brazil | Stainless steel industrial effluent from Acesita Co., Brazil | Fe(III) |
4.0 | 180 | 25 | 7.8 |
Batch | 94 |
2 | [ |
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|
Food processing wastewaters | Aqueous synthetic solution | Cu(II) | 5.0 | 120 | 30 | 100 | Batch | 70 | 1 | [ |
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Waste biomass of |
A residual biomass of a canned food factory in Bartin, Turkey | Aqueous synthetic solution | Pb(II) | 5.0 | 20 | 20 | 100 | Batch | 92 | 4 | [ |
|
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Waste biomass of |
A residual biomass of a local canned food plant, Turkey | Aqueous synthetic solution | Textile Reactive Red dye (RR 198) | 2.0 | 20 | 20 | 100–300 | Batch | 99.3 | 1.6 | [ |
|
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Cupuassu shell, |
Food residue from jelly industry, Belém-PA, Brazil | Aqueous synthetic solution | Reactive Red dye (RR 194) | 2.0 | 480 | 25 | 50 | Batch | — | 2.5 |
[ |
Direct Blue 53 | 1080 | ||||||||||
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Okra food industrial waste | Food waste from food canning processes | Aqueous synthetic solution | Cd(II) |
— | 90 | — | 20 | Batch | 96.4 |
1 | [ |
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Sugar industrial waste (bagasse waste) | Obtained from food canning processes | Aqueous synthetic solution | Cd(II) |
— | 90 | — | 20 | Batch | 96.4 |
1 | [ |
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Pineapple peel, an agricultural effluent | Food can processing industries | Aqueous synthetic solution | Methylene Blue (MB) cationic dye | 6.0 | 400 | 30 | 300 | Batch | 47 | 1.5 | [ |
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Waste baker’s yeast biomass | Pakmaya Yeast Company, Izmir, Turkey | Aqueous synthetic solution | Cd(II) |
6.0 |
180 | 30 | 25 | Batch | 60 |
1 | [ |
|
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Desiccated coconut waste sorbent (DCWS) | By-product of Coconut Milk Processing | Aqueous synthetic solution | Hg(II) | 7.4 | 2880 |
30 | 50 |
Batch Column | — | 1 |
[ |
|
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Pecan nut shells ( |
Biomass from food factories, Nuevo Leon, Mexico | Aqueous synthetic solution | Acid Blue 74 (AB74) | 6.5 | 500 | 30 | 100 |
Batch |
— |
10 |
[ |
Reactive Blue 4 (RB4) | 1000 | ||||||||||
Acid Blue 25 (AB25) | 500 | ||||||||||
|
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Orange peel | Solid waste from local fruit juice industries, Egypt | Aqueous synthetic solution | Pb(II) |
5.0 | 30 | 25 | 20 | Batch | 99.5 |
4 | [ |
|
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Orange ( |
Agrumexport, S.L., an orange juice manufacturing company |
Aqueous synthetic solution | Cr(III) | 4.0 |
4320 |
25 |
100 |
Batch Column | 81 |
4 | [ |
|
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Pectin-rich fruit wastes | Residues from fruit juice and wine production, from a citrus-juice producer (Sunkist), USA | Aqueous synthetic solution | Cd(II) | 5.0 | 50 | — | 60 | Batch | 46 | 2 | [ |
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Orange waste | From orange juice industry, Spain | Aqueous synthetic solution | Cd(II) | 6.0 | 60 | 25 | 100 | Batch | 98 | 4 | [ |
|
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Orange waste | From orange juice industry, Spain | Aqueous synthetic solution | Cd(II) |
4.0 | 180 |
20 | 15 |
Batch | 86 |
4 | [ |
|
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Peach and Apricot stones | Solid wastes of juice and jam industries, Egypt | Aqueous synthetic solution | Pb(II) | 7.0 | 180 |
— | 54.65 | Batch | 97.64 |
10 | [ |
|
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|
Local juice manufacturing industry | Aqueous synthetic solution | Methylene Blue (MB) cationic dye | 8.0 | 120 | 30 | 100 | Batch | 96.17 | 0.67 | [ |
|
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Mango seeds (MS) |
Juice producer, Ubá-MG, Brazil | Aqueous synthetic solution | Victazol Orange 3R dye (VO-3R) | 2.0 | 360 | 25 | 40 | Batch | — | 2.5 | [ |
|
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Waste cider yeast |
Fermentation Lab at the College of Food Science and Engineering of Northwest A & F University (Yangling, China) | Apple juice solution | Patulin (PAT) | 4.5 | 2160 | 25 | 0.1 |
Batch Column | 58.29 | 5 |
[ |
|
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Dairy sludge | Dairy plant, France | Aqueous synthetic solution | Pb(II) |
5.0 | 500 | 20 | 200 |
Batch | >90 | 0.5–4.0 | [ |
|
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The waste pomace of olive oil factory (WPOOF) | Turkish |
Aqueous synthetic solution | Cr(VI) | 2.0 | 120 | 60 | 50 |
Batch Column | 100 |
5 |
[ |
|
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Solid waste from |
The OS and OMS wastes were provided by the “Cooperativa Nuestra S |
Aqueous synthetic solution | Pb(II) | 5.0 | 120 | 25 | — | Batch | — | 10 | [ |
|
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Olive mill waste (OMW) two-phase decanter | Mixture of pulp and olive |
Aqueous synthetic solution | Pb(II) |
7.0 | 30 | 20 | 10 | Batch | 80 |
10 | [ |
|
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Olive mill residues (OMR) | Solid residues of oil production, provided by an olive mill in Abruzzo, Italy. | Aqueous synthetic solution | Cu(II) | 5.5 |
150–1440 | Room temperature | 40 |
Batch Column | 60% |
10 |
[ |
|
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Palm oil mill effluent (POME) sludge | Waste sludge from palm oil mill, Felda Taib Andak, Johor, Malaysia | Aqueous synthetic solution | Methylene Blue (MB) cationic dye | 7.5 | 4320 | 27 | 100 | Batch | — | 2 | [ |
|
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Sunflower oil |
Biomass obtained from a sunflower oil production |
Aqueous synthetic solution |
Pb(II) |
4.0 | — | — | 10 | Column | — |
|
[ |
|
|||||||||||
Crushed olive stone wastes | Supplied by an olive oil |
Aqueous |
Pb(II) |
5.5 | 60 | 20 | 18.86 |
Batch | 79 |
13.3 | [ |
|
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Waste olive cake (OC) | Supplied by “ProBeira” an olive oil producer, Envendos Portugal | Aqueous |
Zn(II) | 6.0-7.0 | 120 | 25 | 10 | Batch | 93 | 1 | [ |
|
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Olive stones |
From the orujo oil extraction plant ‘‘Orujera |
Aqueous |
Cd(II) | 11 | 360 | 40 | 10 | Batch | 90 | 0.01 | [ |
|
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Olive pomace | Supplied by an Italian olive oil production |
Aqueous |
Cu(II) |
5.0 | 60 | — | — | Batch | — | 10 | [ |
|
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Olive pomace |
Supplied by one of the olive oil production |
Aqueous |
Methylene Blue (MB) dye | — | 240 | 25 | 10 |
Batch Column | 80 |
2 |
[ |
|
|||||||||||
Olive pomace |
Solid by-products of olive oil processing mills, the island of Lesvos, Greece. | Oil mill waste water (OMWW) | Phenol | 10.0 | 120 | 20 | 50 |
Batch Column | >90 |
10 |
[ |
|
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Activated carbon derived from exhausted olive waste cake | Olive waste cake from oil factory “Agrozitex” Sfax, Tunisia | Synthetic aqueous solution |
Lanaset Grey G | 6.0 | 3000 | 25 | 150 | Batch | 93 | 1.67 | [ |
|
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Activated carbon derived from empty fruit bunch (EFB) | Industrial waste from united palm oil mill, Nibong, Tebal, Malaysia | Synthetic aqueous solution | Methylene Blue dye (MB) | 12 | — | 30 | 200 | Batch | — | 1 | [ |
|
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Activated carbon from tea industry waste (TIWAC) | Tea waste from tea processing plant, Black Sea region, Trabzon, Turkey | Real water samples | Cr(VI) |
6.0 | 30 | — | 0.2 | Batch | 0 |
2 | [ |
|
|||||||||||
Activated carbon from sago waste | Sago waste is collected from sago industry, Salem district, Tamilnadu, India | Synthetic aqueous solution |
Pb(II) |
|
180 | 27 | 10 | Batch | 87.34 | 2 | [ |
|
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|
Canned food factory | Aqueous synthetic solution | Acid Red 57 dye | 2.0 | 20 | 20 | 150 | Batch | — | 1.6 |
[ |
Textile wastewater | 1 (spiked wastewater sample) | 97.68 | |||||||||
|
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Industrial fungi |
Ascolor Biotec (Pardubice, Czech Republic) |
Aqueous synthetic solution | Pb(II) |
5.0 | — | 20 | 10 |
Batch | Up to 85 for Hg | 0.3 | [ |
|
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Fruit waste macrofungi |
Mushroom processing factory | Aqueous synthetic solution | Cd(II) |
6.0 | 60 | 25 | 10 | Batch | 75 |
18 | [ |
|
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|
Czech Industrial Partners | Aqueous synthetic solution | Cd(II) |
5.0 | 20 | — | 50 | Batch | — | 0.3 | [ |
|
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Antibiotic waste |
SAIDAL antibiotic |
Aqueous synthetic solution | Basic Blue 41, cationic dye | 8.0-9.0 | 60 | 30 | 50 | Batch | 75 | 0.5 | [ |
|
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Industrial waste of |
Antibiotic |
Aqueous synthetic solution | Cd(II) | 5.0 | 15 | 20 | 200 | Batch | 41 | 1 | [ |
|
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Fungal waste biomass | Pharmaceutical companies, Italy | Textile wastewater effluents | Dye mixtures | 3.0 | 30 | 25 | 60–5000 | Batch | 90 | 16.7 | [ |
|
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Nonliving biomass |
Fermentation industry, Artemis Pharmaceuticals Limited, HAD, Jeedimetla, Hyderabad, India | Aqueous synthetic solution | perse |
7.0 | 60 | — | 4.8 |
Batch | 70 |
20 |
[ |
|
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Nonliving biomass |
Industrial complex enzyme preparation | Aqueous synthetic solution | Cr(VI) | 2.0 | 40 | 1152 | 25 | Batch | 87 | 1 | [ |
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Nonliving biomass |
Industrial complex enzyme preparation | Aqueous synthetic solution | Cu(II) | 5.0 | 20 | 180 | 100 | Batch | — | 1 | [ |
|
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|
Fermentation industry |
Aqueous synthetic solution | Reactive Black 5 (RB5) | 1.0 | 35 | 500 | 500 | Batch | — | 2.5 | [ |
|
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Activated carbon from antibiotic waste | Industrial antibiotic production | Aqueous synthetic solution | Hg(II) | 5.5 | — | 30 | 40 | Batch | — | 0.2 | [ |
|
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Fennel biomass ( |
Medical herb, local Unani medicine manufacturing unit at Aligarh, India | Aqueous synthetic solution | Cd(II) |
4.3 | 50 |
50 | 100 | Batch Column | 92 |
10 |
[ |
A number of researchers in the Mediterranean countries (Turkey, Spain, Italy, etc.) were interested in olive oil wastes since these countries are among the world’s biggest olive producers. All types of wastes from olive oil industry such as pomace, pulp, stones, and milling sludge were used for the sorption of heavy metals and dyes from solutions [
Commercial activated carbon has been a very common method of adsorption for a long time. Research is now shifted toward using activated carbon derived from various agricultural as well as industrial sources. In the current review, only activated carbons manufactured from food processing wastes are reported. The method of deriving activated carbon (AC) from these wastes will be explained later in the pretreatment section. AC derived from different industrial waste sources such as olive waste cake [
As for pharmaceutical wastes, they are either fungal or bacterial biomass that could be dead or living. Examples of fungal biomass are
For the removal of dyes,
Holistically, the behavior and performance of biosorption are affected by the physical and chemical characteristics of each of the biosorbent and sorbate; in addition to the process operating conditions. Biosorbent and sorbate characteristics include composition, structure, type of charged and uncharged functional groups, and particle size. It was also reported that in biomass sorbents, the composition of the cell wall influences both sorption uptake capacity and selectivity [
Operating conditions are instrumental biosorption controlling parameters which include pH, temperature, initial sorbate concentration, biosorbent dose, contact time, agitation speed, sorbent particle size, mode of operation, and competition from coions. These operating parameters will be further discussed in more detail.
The pH of sorbate solution plays a vital role in the biosorption process since it influences the charge on the biosorbent functional groups and the dissociation of these groups on the active sites. It also affects sorbate solubility and its degree of ionization. The effect of pH on both uptake capacity and percentage removal was investigated by numerous workers. For heavy metal sorption, it was found that the increase in pH increases uptake capacity of heavy metals such as Cd, Pb, Ni, Cu, and Zn in both the acidic and the neutral range (pH 2–7). The rate of increase under highly acidic conditions (pH 2–4) was mostly higher than that observed at milder acidic conditions (pH 4–6) [
Very limited studies were conducted on the effect of ionic strength where the presence of NaCl [
The increase in the initial concentration of the sorbate acts as a driving force to overcome the mass transfer resistance and hence increase the uptake. This behavior was reported for both heavy metals and dyes [
The percentage removal, on the other hand, was found to decrease with increasing in concentration for the heavy metals Cd, Zn, and Ni onto tea, olive cake wastes, and wine processing sludge, respectively [
Generally as the biosorbent dose increases, the number of available active sites increases and thus consequently enhances the removal [
The effect of temperature becomes important when dealing with wastewater effluents that are discharged at high temperatures due to processing. For endothermic reactions, biosorption uptake capacity and removal efficiency increased with temperature due to increase in surface activity and hence availability of more active sites [
In most of the reported studies, the initial rate of sorption was rapid and it decreased gradually till it reached an approximately constant value [
The speed of agitation was found to enhance removal efficiency by reducing mass transfer resistances but only up to an optimal limit above which efficiency drops probably due to biomass fragmentation [
The operational mode influences uptake and % removal because dynamics of batch systems are different from column dynamics. In most studies, dynamic capacity was lower than its batch counterpart; and the same held true for % removal [
One additional factor affecting biosorption in multicomponent systems is competition and interference between ions in the sorbate mixture. As a result, the reported individual batch uptake and breakthrough capacities of ions in single-component systems were lower compared to their counterparts in multicomponent systems [
Food and pharmaceutical wastes contain organic compounds such as proteins, amino acids, polysaccharides, phenolics, and acids. These compounds have functional groups that bind to the sorbate cations. Groups include, but are not limited to, amines, hydroxyls, carbonyls, sulfonyls, thiols, and phosphates. Biosorption mechanisms include physical sorption by virtue of Van der Waals forces or by ion exchange electrostatic interactions, chemical sorption by chelation or complexation, and microprecipitation. Generally, a combination of these mechanisms is involved in biosorption [
There are several factors controlling sorption mechanisms, type of ligands or binding sites available on the sorbent; chemical structure and characteristics of the target ions/molecules, physicochemical conditions such as pH, ionic strength, and temperature. There are some general rules for metal binding particularly via complexation. Hard acids such as K+, Na+, Ca2+, and Mg2+ prefer to bind to oxygen ligands, whereas soft acids such as the precious metal ions of Ag, Au, Hg, and Cd preferentially bind covalently to the cell wall via ligands that contain nitrogen or sulfur [
Sorption onto biomass can generally occur via one or more of the following mechanisms: rapid surface reaction between the sorbate and the active functional groups existing in the cell wall, intracellular accumulation, or precipitation/extracellular accumulation. Surface reaction could be either physical adsorption or chemisorption and is nonmetabolism dependent. Intracellular accumulation takes place when the sorbate migrates across the cell wall. It is a metabolism-dependent process that is influenced by adverse environmental conditions such as lack of nutrients and toxicity. It is also a function of the regular metabolic activities that change the microenvironment surrounding the cell, such as nutrient uptake, metabolic release, and respiration. In living biomass, biosorption is metabolism-dependent and occurs by sorbent uptake across the cell membrane. Therefore, it has its limitations regarding toxicity and maintaining nutrient levels. Biosorption via dead biomass does not suffer from these limitations and occurs on the cell wall where the polysaccharides and proteins have binding sites. However, lower binding capacities and higher desorption tendencies are often encountered [
To elucidate the underlying biosorption mechanism, the functional groups involved in biosorption were determined by Fourier transform infrared spectroscopy (FTIR) analysis (Table
Suggested biosorption mechanisms based on interacting functional groups.
Biosorbent | Sorbate | Functional group | Mechanism | Reference |
---|---|---|---|---|
Orange peel | Pb(II) |
Carboxylic | IEX/H-bonding | [ |
|
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Orange waste | Cr(III) | Carboxyl/hydroxyl | Chemisorption | [ |
|
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Orange waste | Cd(II) | Carboxyl/hydroxyl | — | [ |
|
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Orange waste | Cd(II) |
Mainly carboxyl | — | [ |
|
||||
Desiccated coconut | Hg(II) | Hydroxyl/carboxyl/amine | Chelation | [ |
|
||||
Pecan nut shells |
Acid Blue |
Sulfonyl | — | [ |
|
||||
Cupuassu shell, |
Reactive red dye |
Hydroxyl/carboxylic | IEX | [ |
|
||||
Mango seeds (MS) |
Victazol orange | Sulfonyl | — | [ |
|
||||
Okra food industrial waste | Cd(II) |
Hydroxyl/carbonyl/amide | IEX/complexation | [ |
|
||||
Sugar industrial waste (bagasse waste) | Cd(II) |
Hydroxyl/carbonyl/amide | IEX/complexation | [ |
|
||||
Pineapple peel | MB dye | Hydroxyl/carboxyl/amine | — | [ |
|
||||
Olive pomace | Pb(II) |
Carboxylic/phenolic | Surface complexation | [ |
|
||||
Olive mill stone | Pb(II) | Carboxylic | IEX | [ |
|
||||
Palm oil mill effluent (POME) sludge | Methylene Blue | Carboxylic | — | [ |
|
||||
Wine processing sludge | Ni(II) | Amino/carboxyl | Physical adsorption/chemical complexation | [ |
|
||||
Spent waste beer yeast |
Pb(II) | Amine/carboxylic/ |
IEX/complexation | [ |
|
||||
Grape bagasse waste residue | Cd(II) |
Carbonyl/hydroxyl | — | [ |
|
||||
|
Pb(II) | Amino/hydroxyl | — | [ |
|
||||
Activated carbon from antibiotic waste | Hg(II) | Hydroxyl/carbonyl | Complexation | [ |
|
||||
Nonliving biomass |
Cr(VI) | Amine | — | [ |
|
||||
Nonliving biomass |
Cd (II) |
Hydroxyl/amine | Complexation | [ |
|
||||
Fennel biomass |
Cd(II) | Carboxylic/phenolic | IEX* | [ |
The change in pH during sorption could be indicative of the involved mechanism. For example, the decrease in pH during the sorption of heavy metals onto
Biosorption equilibrium is governed by isotherm models that are well-known and established in literature. Table
Main adsorption isotherm models involved in the present study.
Adsorption isotherm model | Model parameters |
---|---|
Freundlich |
|
|
|
Langmuir |
|
|
|
Sips |
|
|
|
Dubinin-Astakhov |
|
|
|
BET |
|
Equations of kinetic models involved in the current study.
Kinetic Model | Model Parameters |
---|---|
Pseudo-first order |
|
|
|
Pseudo-second order |
|
|
|
Elovich |
|
Table
Equilibrium parameters as predicted by the well-established sorption models.
Biosorbent | Target ion/compound | Equilibrium model | Maximum sorption capacity (mg/g) | Sorption constant* | pH/temperature (°C) | Reference |
---|---|---|---|---|---|---|
Local dairy sludge | Pb(II) |
Langmuir | 178.6 |
0.03 |
5/40 | [ |
|
||||||
Baker’s yeast biomass | Cd(II) |
Langmuir | 31.75 |
0.092 |
6.0/30 |
[ |
|
||||||
Cider yeast | Patulin | Langmuir | 0.0082 | 0.064 | 4.5/25 | [ |
|
||||||
Beer yeast | Cu(II) |
Langmuir | 0.66 |
0.314 |
5.0/20 | [ |
|
||||||
Spent waste beer yeast |
Pb(II) | Freundlich | — |
|
5.0/30 | [ |
|
||||||
Spent brewery grains (SBG) | AG25 dye | Langmuir | 212.76 | 0.036 | 3.0/30 | [ |
|
||||||
Wine processing sludge | Ni(II) | Langmuir | 3.91 | 0.113 | 5.5/50 | [ |
|
||||||
Antibiotic waste |
Cu(II) | Langmuir | 106.38 | 0.007 | — | [ |
|
||||||
Antibiotic waste |
Basic Blue 41 | Langmuir |
111.00 |
0.097 |
(8.0-9.0)/30 | [ |
|
||||||
|
Acid Red 57 dye | Langmuir | 215.13 | — | 2.0/20 | [ |
|
||||||
|
Reactive Red 198 | Freundlich |
|
[ | ||
|
||||||
Fruit waste macrofungi |
Cd(II) |
Langmuir | 8.43 |
— | 6.0/25 | [ |
|
||||||
Industrial fungi |
Cd(II) |
Langmuir | 35.90 |
0.05 |
5.0/20 | [ |
|
||||||
Industrial fungi |
Cd(II) |
Langmuir | 11.90 |
1.03 |
5.0/20 | [ |
|
||||||
industrial waste of |
Cd(II) | BET | 45.3 | 16 |
5.0/20 | [ |
|
||||||
Fungal waste biomass | Simulated acid bath for wool (SABW) dye | Langmuir | 289.5 | 0.0114 | 3.0/25 | [ |
|
||||||
biomass of |
Pb(II) | Langmuir | 19.93 | 0.498 | 5.0/50 | [ |
|
||||||
Fennel biomass (Foeniculum vulgare) | Cd(II) | Langmuir |
26.59 | 0.080 |
4.3/50 | [ |
|
||||||
Nonliving biomass |
Cu(II) | Langmuir | 35.97 | 0.136 | 5.0/20 | [ |
|
||||||
|
Reactive Black 5 |
Langmuir |
419 | 0.042 |
1.0/35 | [ |
|
||||||
|
Cu(II) | Langmuir | 79.37 | 0.282 | 5.0/30 | [ |
|
||||||
Pectin-rich fruit wastes (lemon peels) | Cd(II) | Langmuir | 22.32 | 0.015 | 5.0/— | [ |
|
||||||
Orange waste | Cd(II) | Sips | 20.64 | 0.038 ( |
6.0/25 | [ |
|
||||||
Orange waste | Cd(II) |
Langmuir | 17.66 |
0.004 |
4.0/20 | [ |
|
||||||
Orange ( |
Cr(III) | Langmuir | 36.48 | 0.403 | 5.0/25 | [ |
|
||||||
Pineapple peel, an agricultural effluent | Methylene Blue (MB) cationic dye | Langmuir | 97.09 | 0.074 | 6.0/30 | [ |
|
||||||
Peach stones |
Pb(II) | Freundlich | — |
|
7.0/— | [ |
|
||||||
|
Methylene Blue (MB) cationic dye | Langmuir | 153.846 | 0.8227 | 8.0/50 | [ |
|
||||||
Desiccated coconut | Hg(II) | Langmuir | 500.00 | — | 7.4/30 | [ |
|
||||||
Pecan nut shells ( |
Acid Blue 74 (AB74) | Langmuir | 4.851 | 0.001 | 6.5/30 |
[ |
Reactive Blue 4 (RB4) | Langmuir | 13.410 | 0.001 | |||
Acid Blue 25 (AB25) | Sips | 7.576 |
| |||
|
||||||
Crushed olive stone wastes | Pb(II) |
Freundlich | — | — | 5.5/20 |
[ |
Binary mixtures | Extended Langmuir | |||||
|
||||||
Olive pomace | Cu(II) |
Langmuir | 1.94 |
0.138 |
5.0/60 | [ |
|
||||||
Olive pomace | Phenols | Freudlich | — |
|
10.0/20 | [ |
|
||||||
Pomace from olive oil | Cr(IV) | Langmuir | 18.69 | 0.055 | 2.0/60 | [ |
|
||||||
olive mill residues (OMR) | Cu(II) | Langmuir | 13.50 | 0.080 | 5.0/23 | [ |
|
||||||
Solid olive stone | Pb(II) | Sips | 6.57 |
|
5.0/25 | [ |
|
||||||
Olive oil mill | Pb(II) | Dubinin-Astakhov | 23.69 | 5.0/25 | [ | |
|
||||||
Palm oil mill effluent (POME) sludge | Methylene Blue (MB) cationic dye | Langmuir | 23.50 | 0.208 | 7.6/27 | [ |
|
||||||
Sugarcane bagasse waste | Methylene Blue (MB) | Langmuir | 202.43 | 0.031 | 8.0/25 |
[ |
Gentian Violet (GV) | 327.83 | 0.047 | ||||
|
||||||
Fresh malted sorghum mash waste | Methylene Blue (MB) basic dye | Langmuir | 384.6 | 0.011 | 7.0/53 | [ |
|
||||||
Cupuassu shell, T |
Reactive Red dye (RR 194) | Sips | 64.1 |
|
2.0/25 |
[ |
Direct Blue 53 | 37.5 |
| ||||
|
||||||
Activated carbon derived from exhausted olive waste cake | Lanaset Grey G | Langmuir | 108.70 | 0.031 | 6.0/25 | [ |
|
||||||
Activated carbon derived from empty fruit bunch (EFB) | Methylene Blue dye (MB) | Langmuir | 344.83 | 0.060 | —/30 | [ |
|
||||||
Activated carbon from sago waste | Pb(II) | Langmuir | 14.35 | 0.095 | 3.5/27 | [ |
In most reported studies, the pseudo-second order model was found to be the most appropriate fitting model that describes biosorption of heavy metals and dyes onto food and pharmaceutical wastes (Table
Kinetic parameters as predicted by the well-established sorption models.
Biosorbent | Target ion/compound | Kinetic model |
|
Rate constant* | pH/temperature (°C)/time (min) | Co (mg/L) | Reference |
---|---|---|---|---|---|---|---|
Local dairy sludge | Pb(II) |
Pseudo-second order | 117.6 |
0.27 |
5.0/20°C/500 | 200 |
[ |
|
|||||||
Wine processing sludge | Cr(VI) | Pseudo-second order | 2.42 | 0.070 | 4.2/50/240 | 100 | [ |
|
|||||||
Wine processing sludge | Ni(II) | Pseudo-second order | 3.11 | 0.226 | 5.5/50/120 | 45 | [ |
|
|||||||
Desiccated coconut | Hg(II) | Pseudo-second order | 447.03 | — | 7.4/30/60 | 50 | [ |
|
|||||||
Pecan nut shells ( |
Acid Blue 74 (AB74) | Pseudo-first | 3.271 | 0.02 | 6.5/30/500 | 1000 |
[ |
Reactive Blue 4 (RB4) | Pseudo-second | 10.010 |
|
6.5/30/1000 | |||
Acid Blue 25 (AB25) | Pseudo-second-order | 4.892 |
|
6.5/30/500 | |||
|
|||||||
Spent brewery grains | AG25 dye | Pseudo-second order | 74.63 | 0.038 | 3.0/30/75 | 90 | [ |
|
|||||||
Beer brewery diatomite waste (SDE) | Methylene Blue basic dye | Pseudo-second order | 4.92 | 1.24 | 7.0/25/1440 | 2.5 | [ |
|
|||||||
Antibiotic waste |
Basic Blue 41 | Pseudo-second order | 90.91 | 0.0042 | 8.0-9.0/30/60 | 70 | [ |
|
|||||||
Macrofungal waste from antibiotics | Cd(II) | Pseudo-second order | 82.8 | 0.0014 | 5.0/20/15 | 200 | [ |
|
|||||||
Fennel biomass ( |
Cd(II) | Pseudo-second order | 9.30 | 0.476 | 5.0/30/50 | 100 | [ |
|
|||||||
|
Reactive Red 198 | Pseudo-second order | 81.97 | 0.036 | 2.0/20/20 | — | [ |
|
|||||||
Nonliving biomass |
Cu(II) | Pseudo-first order | 35.00 | 0.077 | 5.0/20/180 | 25 | [ |
|
|||||||
|
Reactive Black 5 |
Pseudo-second order | 370.00 |
|
1.0/25/500 | 2000 | [ |
|
|||||||
|
Acid Red 57 dye | Pseudo-second order | 89.49 | 0.21 | 2.0/20/20 | 150 | [ |
|
|||||||
Fruit waste macrofungi |
Cd(II) | Pseudo-first |
[ | ||||
Pb(II) | Pseudo-second order | 13.04 | 2.17 | 6.0/25/60 | 10 | ||
|
|||||||
Orange ( |
Cr(III) | Pseudo-second order | 10.97 | 0.002 | 5.0/25/4320 | 100 | [ |
|
|||||||
Pectin-rich fruit wastes (lemon peels) | Cd(II) | Pseudo-second order | 13.92 | 0.021 | 5.0/—/50 | 19.2 | [ |
|
|||||||
Orange waste | Cd(II) | Elovich | 333.33 (1/ |
0.004 (1/ |
6.0/25/60 | 100 | [ |
|
|||||||
|
Methylene Blue (MB) cationic dye | Pseudo-first order | 115 | 0.0461 | 8.0/30/120 | 175 | [ |
|
|||||||
|
Cu(II) | Pseudo-second order | 69.82 | 0.002 | 5.0/30/120 | 100 | [ |
|
|||||||
Crushed olive stone wastes | Pb(II) |
Pseudo-second |
1.12 | 0.141 | 5.5/20/60 | 18.86 |
[ |
Ni(II) | 0.25 | 3.000 | 4.48 | ||||
Cu(II) | 0.26 | 7.497 | 4.35 | ||||
Cd(II) | 0.72 | 0.121 | 10.56 | ||||
|
|||||||
Olive stones | Cd(II) | Pseudo-second order | 0.903 | 3.196 | 11.0/80/20 | 10 | [ |
|
|||||||
Palm oil mill effluent (POME) sludge | Methylene Blue (MB) cationic dye | Pseudo-second order | 5.54 | 0.0072 | 7.6/27/4320 | 10 | [ |
|
|||||||
Olive pomace | Methylene Blue (MB) dye | Pseudo-second order | — | 0.0906 | —/25/240 | 10 | [ |
|
|||||||
Tea industry waste | Cd(II) | Pseudo-second order | 10.6 | 0.02 | 7.0/25/180 | 100 | [ |
|
|||||||
Pineapple peel, an agricultural effluent | Methylene Blue (MB) cationic dye | Pseudo-second order | 104.17 |
|
6.0/30/400 | 300 | [ |
|
|||||||
Okra food waste | Cd(II) |
Pseudo-second order | 17.54 |
0.009 |
—/20/90 | 20 | [ |
|
|||||||
Activated carbon derived from exhausted olive waste cake | Lanaset Grey G | Pseudo-first order | 106.4 | 0.0019 | 6.0/25/3000 | 150 | [ |
|
|||||||
Activated carbon from tea industry waste (TIWAC) | Cr(III) | Pseudo-second order | 0.464 | 1.52 | 6.0/—/30 | 0.01 | [ |
|
|||||||
Sugar industry (waste bagasse) | Cd(II) |
Pseudo-first order | — |
|
—/20/90 | 20 | [ |
|
|||||||
Sugarcane bagasse waste | Methylene Blue (MB) | Pseudo-second |
192.31 | 0.0012 | 8.0/25/600 | 200 |
[ |
Gentian Violet | 357.14 | 0.00005 | 8.0/25/900 | 300 |
Wastes from most fruit sources are pectin-rich biosorbents of potentially high metal binding abilities. Many studies that involved the use of such biosorbents have undertaken prior chemical pretreatment known as protonation. This process aims at removing excess cations such as Ca2+, Na+, or K+ from the biosorbent before carrying out biosorption experiments to reduce the competition of these elements with targeted heavy metals. Moreover, it leads to the creation of negative active sites on the biosorbent surface (at specific pH values) which leads to higher metal uptake capacity [
H2O2 along with thermal treatment was used to treat wine processing sludge in order to remove organic matter before using the biosorbent for the removal of Cr (VI) [
A combined chemical and physical treatment was performed for baker’s yeast waste used for Cd (II) and Pb (II) removal [
Other different chemical treatments either acidic or caustic were employed by other workers in their biosorption studies. Zinc chloride and potassium hydroxide were employed as chemical activating agents for palm oil sludge in a study on the removal of Methylene Blue dye [
To test the effect of different functional groups on the removal of some heavy metals (Cd2+, Zn2+, and Cr3+), orange waste biomass was chemically modified by specific reagents [
Some researchers used chemical and physical methods for the preparation of activated carbons produced from different food processing wastes. Four studies were reported for the removal of dyes or heavy metals using AC prepared from exhausted olive waste cake [
As for pharmaceutical wastes,
Few researchers were interested in desorption processes for either regeneration of the biosorbent for reuse and/or for recovery of the sorbate material. Desorption can be performed by adding acids, bases, inorganic salts, or solvents [
In comparing HCl with other desorping agents, higher Pb (II) desorption rate using HCl as compared to EDTA was reported [
Industrial food processing and pharmaceutical wastes are promising biosorbents for treatment of wastewater effluents. They contain functional groups such as hydroxyl, carboxyl, and amine that allow them to interact with metal ions and dye pollutants via physical and/or chemical sorption. Sorption equilibrium in most of the previous studies was best described by Langmuir isotherm suggesting single-site binding. Sorption kinetics was generally fast and it predominantly followed the pseudo-second order model indicating a chemisorption mechanism. Surface reaction as well as film and pore diffusion processes were considered in the model.
Biosorption is influenced by the physical and chemical properties of the sorbent as well as various operating conditions. Numerous workers studied the effect of these parameters in batch systems. However, very few studies were conducted in continuous column systems. The latter is of paramount importance in scaled-up applications. Furthermore, most workers employed synthetic aqueous solutions rather that real wastewater effluents where competition and interference between ions in the mixture could significantly affect biosorption performance. One parameter that was overlooked is the physical, mechanical, and chemical stability of the sorbent. Mechanical strength of the biosorbent and its resistance to chemicals and microbial degradation are crucial parameters that ensure reproducibility of biosorbent, particularly in continuous operations where the biosorbent is regenerated and reused many times. Maintaining reproducibility for many subsequent cycles has both environmental and economic merits.
Desorption studies are relatively fewer compared to removal studies. The former is particularly important for both biosorbent regeneration and sorbate recovery if of value. Disposing of, landfilling and incineration could be alternatives to discarding the used biosorbent rather than regenerating it. However issues with cost and leaching of toxic compounds in the soil and ground water make them sometimes unfavorable options. Under very strong binding conditions, where the equilibrium binding constant is high, leaching and metal release are minimized.
Biosorbent performance could be enhanced by chemical, thermal, or chemical/thermal pretreatment and/or immobilization. Pretreatment could be performed to remove undesired organic compounds, proteins, or competing ions from the biosorbent and hence improve biosorption capacity and efficiency. In other cases, pretreatment is undertaken to add new functional groups to the biosorbent that can possibly enhance biosorption. However in some cases, pretreatment gave adverse effects. Prior characterization studies on the biosorbent may help in selecting the suitable treatment option.
Biosorption utilizing industrial food processing and pharmaceutical wastes could provide a cost-effective ecofriendly viable means of treating wastewater effluents, while making good use of waste materials. However, more work should focus on scaling up the proposed biosorption processes and studying their technoeconomic feasibility. Research should also be extended to using these biosorbents for treatment of different classes of contaminants such as phenolic compounds and mycotoxins.
The authors declare that there is no conflict of interests regarding the publication of this paper.