Open access peer-reviewed chapter

Biological and Chemical Wastewater Treatment Processes

Written By

Mohamed Samer

Submitted: December 2nd, 2014 Reviewed: July 23rd, 2015 Published: October 14th, 2015

DOI: 10.5772/61250

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Abstract

This chapter elucidates the technologies of biological and chemical wastewater treatment processes. The presented biological wastewater treatment processes include: (1) bioremediation of wastewater that includes aerobic treatment (oxidation ponds, aeration lagoons, aerobic bioreactors, activated sludge, percolating or trickling filters, biological filters, rotating biological contactors, biological removal of nutrients) and anaerobic treatment (anaerobic bioreactors, anaerobic lagoons); (2) phytoremediation of wastewater that includes constructed wetlands, rhizofiltration, rhizodegradation, phytodegradation, phytoaccumulation, phytotransformation, and hyperaccumulators; and (3) mycoremediation of wastewater. The discussed chemical wastewater treatment processes include chemical precipitation (coagulation, flocculation), ion exchange, neutralization, adsorption, and disinfection (chlorination/dechlorination, ozone, UV light). Additionally, this chapter elucidates and illustrates the wastewater treatment plants in terms of plant sizing, plant layout, plant design, and plant location.

Keywords

  • Wastewater treatment
  • biological treatment
  • chemical treatment
  • bioremediation
  • phytoremediation
  • mycoremediation
  • vermifiltration
  • treatment plant

1. Introduction

The chapter concerns with wastewater treatment engineering, with focus on the biological and chemical treatment processes. It aims at providing a brief and obvious description of the treatment methods, designs, schematics, and specifications. The chapter also answers an important question on how the different processes are interrelated and the correct order of these processes in relation to each other. The main objective of this work was to summarize the work of the eminent scientists in this field in order to provide a clear but concise chapter that can be used as a quick reference for environmental engineers and researchers, and to be effectively implemented in higher education teaching undergraduate and graduate students, as well as extension and outreach.

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2. Chapter description and contents overview

The chapter describes the biological and chemical wastewater treatment processes that include:

  1. Bioremediation of wastewater using oxidation ponds, aeration lagoons, anaerobic lagoons, aerobic and anaerobic bioreactors, activated sludge, percolating or trickling filters, biological filters, rotating biological contactors, and biological removal of nutrients;

  2. Mycoremediation of wastewater using bioreactors;

  3. Phytoremediation of wastewater that includes: constructed wetlands, rhizofiltration, rhizodegradation, phytodegradation, phytoaccumulation, phytotransformation, and hyperaccumulators;

  4. Vermifiltration and vermicomposting;

  5. Microbial fuel cells for electricity production from wastewater;

  6. Chemical wastewater treatment processes that include: chemical precipitation, ion exchange, neutralization, adsorption and disinfection (chlorination/dechlorination, ozone, ultraviolet radiation);

  7. Wastewater treatment plants. The chapter elucidates and illustrates the plant sizing, plant layout, plant design, and plant location.

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3. Overview

3.1. Wastewater treatment techniques

Wastewater, or sewage, originates from human and home wastewaters, industrial wastes, animal wastes, rain runoff, and groundwater infiltration. Generally, wastewater is the flow of used water from a neighborhood. The wastewater consists of 99.9% water by weight, where the remaining 0.1% is suspended or dissolved material. This solid material is a mixture of excrements, detergents, food leftovers, grease, oils, salts, plastics, heavy metals, sands, and grits [1, 2]. Types of wastewaters include: municipal wastewater, industrial wastewaters, mixtures of industrial/domestic wastewaters, and agricultural wastewaters. Typical agricultural industries include: dairy processing industries, meat processing factories, juice and beverage industries, slaughterhouses, vegetable processing facilities, rendering plants, and drainage water of irrigation systems.

Subsequent to primary treatment of wastewater, i.e., physical treatment of wastewater, it still contains large amounts of dissolved and colloidal material that must be removed before discharge. The issue is how to transform the dissolved materials or particulate matters that are too little for sedimentation into larger particles to allow the separation processes to eliminate them. This can be accomplished by secondary treatment, i.e., biological treatment. The treatment of wastewater subsequent to the removal of suspended solids by microorganisms such as algae, fungi, or bacteria under aerobic or anaerobic conditions during which organic matter in wastewater is oxidized or incorporated into cells that can be eliminated by removal process or sedimentation is termed biological treatment. Biological treatment is termed secondary treatment. Chemical treatment, or tertiary treatment, using chemical materials will react with a portion of the undesired chemicals and heavy metals, but a portion of the polluting material will remain unaffected. Additionally, the cost of chemical additives and the environmental problem of disposing large amounts of chemical sludge make this treatment process deficient [1]. Alternatively, the biological treatment must be implemented. This treatment process implements naturally occurring microorganisms to transform the dissolved organic matter into a dense biomass that can be separated from the treated wastewater by the sedimentation process. In fact, the microorganisms utilize the dissolved organic matter as food for themselves, where the generated sludge will be far less for chemical treatment. In practice, therefore, secondary treatment tends to be a biological process with chemical treatment implemented for the removal of toxic compounds.

3.2. Aims of wastewater treatment

The goals of treating the wastewaters are:

  1. Transforming the materials available in the wastewater into secure end products that are able to be safely disposed off into domestic water devoid of any negative environmental effects;

  2. Protecting public health;

  3. Ensuring that wastewaters are efficiently handled on a trustworthy basis without annoyance or offense;

  4. Recycling and recovering the valuable components available in wastewaters;

  5. Affording feasible treatment processes and disposal techniques;

  6. Complying with the legislations, acts and legal standards, and approval conditions of discharge and disposal.

3.3. Biological treatment processes

The secondary treatment can be defined as “treatment of wastewater by a process involving biological treatment with a secondary sedimentation”. In other words, the secondary treatment is a biological process. The settled wastewater is introduced into a specially designed bioreactor where under aerobic or anaerobic conditions the organic matter is utilized by microorganisms such as bacteria (aerobically or anaerobically), algae, and fungi (aerobically). The bioreactor affords appropriate bioenvironmental conditions for the microorganisms to reproduce and use the dissolved organic matter as energy for themselves. Provided that oxygen and food, in the form of settled wastewater, are supplied to the microorganisms, the biological oxidation process of dissolved organic matter will be maintained. The biological process is mostly carried out bacteria that form the basic trophic level (the level of an organism is the position it occupies in a food chain) of the food chain inside the bioreactor. The bioconversion of dissolved organic matter into thick bacterial biomass can fundamentally purify the wastewater. Subsequently, it is crucial to separate the microbial biomass from the treated wastewater though sedimentation. This secondary sedimentation is basically similar to primary sedimentation except that the sludge contains bacterial cells rather than fecal solids. The biological removal of organic matter from settled wastewater is conducted by microorganisms, mainly heterotrophic bacteria but also occasionally fungi. The microorganisms are able to decompose the organic matter through two different biological processes: biological oxidation and biosynthesis [1]. The biological oxidation forms some end-products, such as minerals, that remain in the solution and are discharged with the effluent (Eq. 1). The biosynthesis transforms the colloidal and dissolved organic matter into new cells that form in turn the dense biomass that can be then removed by sedimentation (Eq. 2). Figure 1 summarizes these processes. On the other hand, algal photosynthesis plays an important role in some cases (Figure 2).

Oxidation:COHNS+O2(Organicmatter)+BacteriaCO2+NH3+Energy+OtherendproductsE1
Biosynthesis:COHNS+O2(Organicmatter)+BacteriaC5H7NO2(Newcells)E2

3.3.1. Useful terms

The following terms are the most used in biological treatment processes [2]:

  1. DO: Dissolved Oxygen (mg L-1)

  2. BOD: Biochemical Oxygen Demand (mg L-1)

  3. BOD5: BOD (mg L-1), incubation at 15°C for 5 days

  4. COD: Chemical Oxygen Demand (mg L-1)

  5. CBOD: Carbonaceous BOD (mg L-1)

  6. NBOD: Nitrogenous (mg L-1)

  7. SOD: Sediment Oxygen Demand (mg L-1)

  8. TBOD: Total BOD (mg L-1)

Figure 1.

Biological synthesis and oxidation [3].

Figure 2.

Photosynthesis and oxidation [2].

3.4. Chemical treatment processes

In early wastewater treatment technologies, chemical treatment has preceded biological treatment. Recently, the biological treatment precedes chemical treatment in the treatment process. Chemical treatment is now considered as a tertiary treatment that can be more broadly defined as “treatment of wastewater by a process involving chemical treatment”. The mostly implemented chemical treatment processes are: chemical precipitation, neutralization, adsorption, disinfection (chlorine, ozone, ultraviolet light), and ion exchange.

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4. Biological treatment of wastewater

4.1. Biological growth equation

The biological growth can be described according to the Monod equation:

μ=(λS)/(KS+S)BB1

Where, μis the specific growth rate coefficient; λis the maximum growth rate coefficient that occurs at 0.5 μmax; Sis the concentration of limiting nutrient, that is BOD and COD; and KSis the Monod coefficient [3].

Generally, the bacterial growth can be explained by the following simplified figure:

Organics+Bacteria+Nutrients+OxygenNewBacteria+CO2+H2O+ResidualOrganics+InorganicsBB2

Several bioenvironmental factors affect the activity of bacteria and the rate of biochemical reactions. The most important factors are: temperature, pH, dissolved oxygen, nutrient concentration, and toxic materials. All these factors can be controlled within a biological treatment system and/or a bioreactor in order to ensure that the microbial growth is maintained under optimum bioenvironmental conditions. The majority of biological treatment systems operate in the mesophilic temperature range, where the optimal temperature ranges from 20°C to 40°C. Aeration tanks and percolating filters operate at the temperature of the wastewater that ranges from 12°C to 25°C; although in percolating filters, the air temperature and the ventilation rate may have a significant effect on heat loss. The higher temperatures increase the biological activity and metabolism, which result in increasing the substrate removal rate. However, the increased metabolism at the higher temperatures may lead to problems of oxygen limitations.

4.2. Bacterial kinetics

The bacterial kinetics can be shown in Figures 3 and 4. The microbial growth curve that shows bacterial density and specific growth rate at the different growth phases is shown in Figure 3. The microbial growth curves that compare the total biomass and the variable biomass are shown in Figure 4.

Figure 3.

Microbial growth curve [1].

Figure 4.

Microbial growth curves [1].

4.3. Principles of biological treatment

The principles of biological treatment of wastewater were stated by [3]. The following is a summary of the principles:

  1. The biological systems are very sensitive for extreme variations in hydraulic loads. Diurnal variations of greater than 250% are problematic because they will create biomass loss in the clarifiers.

  2. The growth rate of microorganisms is highly dependent on temperature. A 10°C reduction in wastewater temperature dramatically decreases the biological reaction rates to half.

  3. BOD is efficiently treated in the range of 60 to 500 mg L-1. Wastewaters in excess of 500 mg L-1 BODs have been treated successfully if sufficient dilution is applied in the treatment process, or if an anaerobic process was implemented as a pretreatment process.

  4. The biological treatment is effective in removing up to 95% of the BOD. Large tanks are required in order to eliminate the entire BOD, which is not feasible.

  5. The biological treatment systems are unable to handle “shock loads” efficiently. Equalization is necessary if the variation in strength of the wastewater is more than 150% or if that wastewater at its peak concentration is in excess of 1,000 mg L-1 BOD.

  6. The carbon:nitrogen:phosphorus (C:N:P) ratio of wastewater is usually ideal. The C:N:P ratio of industrial wastewaters should range from 100:20:1 to 100:5:1 for a most advantageous biological process.

  7. If the C:N:P ratio of the wastewater is strong in an element in comparison to the other elements, then poor treatment will result. This is especially true if the wastewater is very strong in carbon. The wastewater should also be neither very weak nor very strong in an element; although very weak is acceptable, it is difficult to treat.

  8. Oils and solids cannot be handled in a biological treatment system because they negatively affect the treatment process. These wastes should be pretreated to remove solids and oils.

  9. Toxic and biological-resistant materials require special consideration and may require pretreatment before being introduced into a biological treatment system.

  10. Although the capacity of the wastewater to utilize oxygen is unlimited, the capacity of any aeration system is limited in terms of oxygen transfer.

4.4. Bioremediation of wastewater

Bioremediation is a treatment process that involves the implementation of microorganisms to remove pollutants from a contaminated setting. Bioremediation can be defined as “treatment that implements natural organisms to decompose hazardous materials into less toxic or nontoxic materials”. Some examples of bioremediation-related technologies are phytoremediation, bioaugmentation, rhizofiltration, and biostimulation. The microorganisms implemented to carry out the bioremediation are called bioremediators. However, some pollutants are not easily removed or decomposed by bioremediation. For example, heavy metals such as lead and cadmium are not eagerly captured by bioremediators. Example of bioremediation: fish bone char has been shown to bioremediate small amounts of cadmium, copper, and zinc.

The bioremediation of wastewater can be achieved by autotrophs or heterotrophs. A heterotroph is an organism that is unable to fix carbon and utilizes organic carbon for its growth. Heterotrophs are divided based on their source of energy. If the heterotroph utilizes light as its source of energy, then it is considered a photoheterotroph. If the heterotroph utilizes organic and/or inorganic compounds as energy sources, it is then considered a chemoheterotroph. Autotrophs, such as plants and algae, that are able to utilize energy from sunlight are called photoautotrophs. Autotrophs that utilize inorganic compounds to produce organic compounds such as carbohydrates, fats, and proteins from inorganic carbon dioxide are called lithoautotrophs. These reduced carbon compounds can be utilized as energy sources by autotrophs and provide the energy in food consumed by heterotrophs. Over 95% of all organisms are heterotrophic.

4.4.1. Aerobic treatment

Aeration has been used to remove trace organic volatile compounds (VOCs) in water. It has also been employed to transfer a substance, such as oxygen, from air or a gas phase into water in a process called “gas adsorption” or “oxidation”, i.e., to oxidize iron and/or manganese. Aeration also provides the escape of dissolved gases, such as CO2 and H2S. Air stripping has been also utilized effectively to remove NH3 from wastewater and to remove volatile tastes and other such substances in water [2]. Samer [4] and Samer et al. [5] mentioned that aerobic treatment with biowastes is effective in reducing harmful gaseous emissions as greenhouse gases (CH4 and N2O) and ammonia.

4.4.1.1. Oxidation ponds

Oxidation ponds (Figure 5) are aerobic systems where the oxygen required by the heterotrophic bacteria (a heterotroph is an organism that cannot fix carbon and uses organic carbon for growth) is provided not only by transfer from the atmosphere but also by photosynthetic algae. The algae are restricted to the euphotic zone (sunlight zone), which is often only a few centimeters deep. Ponds are constructed to a depth of between 1.2 and 1.8 m to ensure maximum penetration of sunlight, and appear dark green in color due to dense algal development. Samer [6] and Samer et al. [7] illustrated the structures and constructions of the aerobic treatment tanks and the used building materials.

Figure 5.

Aerobic system/oxidation pond [1].

In oxidation ponds, the algae use the inorganic compounds (N, P, CO2) released by aerobic bacteria for growth using sunlight for energy. They release oxygen into the solution that in turn is utilized by the bacteria, completing the symbiotic cycle. There are two distinct zones in facultative ponds: the upper aerobic zone where bacterial (facultative) activity occurs and a lower anaerobic zone where solids settle out of suspension to form a sludge that is degraded anaerobically.

4.4.1.2. Aeration lagoons

Aeration lagoons are profound (3–4 m) compared to oxidation ponds, where oxygen is provided by aerators but not by the photosynthetic activity of algae as in the oxidation ponds. The aerators keep the microbial biomass suspended and provide sufficient dissolved oxygen that allows maximal aerobic activity. On the other hand, bubble aeration is commonly used where the bubbles are generated by compressed air pumped through plastic tubing laid through the base of the lagoon. A predominately bacterial biomass develops and, whereas there is neither sedimentation nor sludge return, this procedure counts on adequate mixed liquor formed in the tank/lagoon. Therefore, the aeration lagoons are suitable for strong but degradable wastewater such as wastewaters of food industries. The hydraulic retention time (HRT) ranges from 3 to 8 days based on treatment level, strength, and temperature of the influent. Generally, HRT of about 5 days at 20°C achieves 85% removal of BOD in household wastewater. However, if the temperature falls by 10°C, then the BOD removal will decrease to 65% [1].

4.4.2. Anaerobic treatment

The anaerobic treatments are implemented to treat wastewaters rich in biodegradable organic matter (BOD >500 mg L-1) and for further treatment of sedimentation sludges. Strong organic wastewaters containing large amounts of biodegradable materials are discharged mainly by agricultural and food processing industries. These wastewaters are difficult to be treated aerobically due to the troubles and expenses of fulfillment of the elevated oxygen demand to preserve the aerobic conditions [1]. In contrast, anaerobic degradation occurs in the absence of oxygen. Although the anaerobic treatment is time-consuming, it has a multitude of advantages in treating strong organic wastewaters. These advantages include elevated levels of purification, aptitude to handle high organic loads, generating small amounts of sludges that are usually very stable, and production of methane (inert combustible gas) as end-product.

Anaerobic digestion is a complex multistep process in terms of chemistry and microbiology. Organic materials are degraded into basic constituents, finally to methane gas under the absence of an electron acceptor such as oxygen [8]. The basic metabolic pathway of anaerobic digestion is shown in Figures 6 and 7. To achieve this pathway, the presence of very different and closely dependent microbial population is required.

Figure 6.

Steps of the anaerobic digestion process [8].

Figure 7.

Major steps in anaerobic decomposition [1].

Suitable wastewaters include livestock manure, food processing effluents, petroleum wastes (if the toxicity is controlled), and canning and dyestuff wastes where soluble organic matters are implemented in the treatment. Most anaerobic processes (solids fermentation) occur in two predetermined temperature ranges: mesophilic or thermophilic. The temperature ranges are 30–38oC and 38–50oC, respectively [3]. In contrast to aerobic systems, absolute stabilization of organic matter is not achievable under anaerobic conditions. Therefore, subsequent aerobic treatment of the anaerobic effluents is usually essential. The final waste matter discharged by the anaerobic treatment includes solubilized organic matter that is acquiescent to aerobic treatment demonstrating the possibility of installing collective anaerobic and aerobic units in series [1].

4.4.2.1. Anaerobic digesters

Samer [9] elucidated and illustrated the structures and constructions of the anaerobic digesters and the used building materials. Samer [10] developed an expert system for planning and designing biogas plants. Figures 8 to 13 show different types of anaerobic digesters. While Figures 14 and 15 show some industrial applications. Table 1 shows the advantages and disadvantages of anaerobic treatment compared to aerobic treatment.

Figure 8.

Most commonly used anaerobic reactor types: (A) Completely mixed anaerobic digester, (B) UASB reactor, (C) AFB or EGSB reactor, and (D) Upflow AF [8].

Figure 9.

Single-stage conventional anaerobic digester [3].

Figure 10.

Dual-stage high rate digester [3].

Figure 11.

Schematic representation of digester types. Flow-through (A–B) and contact systems (C–F) [1].

Figure 12.

The upper scheme shows a two-stage anaerobic sludge digester, while the lower scheme shows the conventional sludge digestion plant [1].

Figure 13.

Primary digestion tank with screw mixing pump and external heater [1].

Figure 14.

Wastewater treatment plant for corn processing industry [8].

Figure 15.

Mass balance study for a wastewater treatment plant of the baker’s yeast industry [8].

By definition, the anaerobic treatment is conducted without oxygen. It is different from an anoxic process, which is a reduced environment in contrast to an environment without oxygen. Both processes are anoxic, but anaerobic is an environment beyond anoxic where the oxidation reduction potential (ORP) values are highly negative. In the anaerobic process, nitrate is reduced to ammonia and nitrogen gas, and sulfate (SO32-) is reduced to hydrogen sulfide (H2S). Phosphate is also reduced because it is often transformed through the ADP–ATP chain [3].

Table 1.

The advantages and disadvantages of anaerobic treatment compared to aerobic treatment [1].

4.4.2.2. Anaerobic lagoons

An anaerobic lagoon is a deep lagoon, fundamentally without dissolved oxygen, that enforces anaerobic conditions. The anaerobic process occurs in deep ground ponds, and such basins are implemented for anaerobic pretreatment. The anaerobic lagoons are not aerated, heated, or mixed. The depth of an anaerobic lagoon should be typically deeper than 2.5 m, where deeper lagoons are more efficient. Such depths diminish the amount of oxygen diffused from the surface, allowing anaerobic conditions to prevail (U.S. EPA, 2002). Figures 16 to 18 show different types of anaerobic lagoons.

Figure 16.

Anaerobic lagoon for strong wastewater treatment, such as meat processing wastewater [1].

Figure 17.

Schematic of volume fractions in anaerobic lagoon design [11].

Figure 18.

Anaerobic wastewater treatment lagoon [12].

4.4.3. Bioreactors

A bioreactor can be defined as “engineered or manufactured apparatus or system that controls the embraced or encompassed bioenvironment”. Precisely, the bioreactor is a vessel in which a biochemical process is conducted, where it involves microorganisms (e.g., bacteria, algae, fungi) or biochemical substances (e.g., enzymes) derived from such microorganisms. The treatment can be conducted under either aerobic or anaerobic conditions. The bioreactors are commonly made of stainless steel, usually cylindrical in shape and range in size from liters to cubic meters. The bioreactors are classified as batch, plug, or continuous flow reactors (e.g., continuous stirred-tank bioreactor).

Mycoremediation is a type of bioremediation where fungi are implemented to break down the contaminants. The term “mycoremediation” refers particularly to the implementation of fungal “mycelia” in bioremediation. The principal role of fungi in the ecological system is the breakdown of pollutants, which is performed by the mycelium. The mycelium, the vegetative part of a fungus, secretes enzymes and acids that biodegrade lignin and cellulose that are the main components of vegetative fibers. Lignin and cellulose are organic compounds composed of long chains of carbon and hydrogen, and therefore they are structurally similar to several organic pollutants. One key issue is specifying the right fungus to break down a determined pollutant. Similarly, mycofiltration is a process that uses fungal mycelia to filter toxic compounds from wastewater. In an experiment, wastewater contaminated with diesel oil was inoculated with mycelia of oyster mushrooms. One month later, more than 93% of many of the polycyclic aromatic hydrocarbons (PAH) had been reduced to non-toxic components in the mycelial-inoculated samples. The natural microbial community participates with the fungi to break down contaminants, eventually into CO2 and H2O. Wood-degrading fungi are particularly effective in breaking down aromatic pollutants (toxic components of petroleum), as well as chlorinated compounds (certain persistent pesticides). Figures 19 to 22 show different types and designs of bioreactors.

Figure 19.

A bioreactor for fungal degradation: trickle bed bioreactor [13].

Figure 20.

A bioreactor for fungal degradation: rotating disc bioreactor [13].

Figure 21.

Fluidized bed bioreactor [14].

Figure 22.

Typical design of fluidized bed reactor system [1].

4.4.4. Activated sludge

The activated sludge process is based on a mixture of thick bacterial population suspended in the wastewater under aerobic conditions. With unlimited nutrients and oxygen, high rates of bacterial growth and respiration can be attained, which results in the consumption of the available organic matter to either oxidized end-products (e.g., CO2, NO3-, SO42-, and PO43-) or biosynthesis of new microorganisms. The activated sludge process is based on five interdependent elements, which are: bioreactor, activated sludge, aeration and mixing system, sedimentation tank, and returned sludge [1]. The biological process using activated sludge is a commonly used method for the treatment of wastewater, where the running costs are inexpensive (Figure 23). However, a huge quantity of surplus sludge is produced in wastewater treatment plants (WWTPs) which is an enormous burden in both economical and environmental aspects. The excess sludge contains a lot of moisture and is not easy to treat. The byproducts of WWTPs are dewatered, dried, and finally burnt into ashes. Some are used in farm lands as compost fertilizer [15]. However, it is suggested that the dried byproducts of WWTPs are fed into the pyrolysis process rather than the burning process.

The sludge volume index (SVI) is an estimation that specifies the tendency of aerated solids, i.e., activated sludge solids, to become dense or concentrated through the thickening process. SVI can be computed as follows: (a) allowing a mixed liquor sample from the aeration tank to sediment in 30 min; (b) determining the concentration of the suspended solids for a sample of the same mixed liquor; (c) SVI is then computed as ratio of the measured wet volume (mL/L) of the settled sludge to the dry weight concentration of MLSS in g/L (Source: Office of Water Programs, Sacramento State, USA).

During the treatment of wastewater in aeration tanks through the activated sludge process (Table 2) there are suspended solids, where the concentration of the suspended solids is termed as mixed liquor suspended solids (MLSS), which is measured in milligrams per liter (mg L-1). Mixed liquor is a mixture of raw wastewater and activated sludge in an aeration tank. MLSS consists mainly of microorganisms and non-biodegradable suspended solids. MLSS is the effective and active portion of the activated sludge process that ensures that there is adequate quantity of viable biomass available to degrade the supplied quantity of organic pollutants at any time. This is termed as Food to Microorganism Ratio (F/M Ratio) or food to mass ratio. If this ratio is kept at the suitable level, then the biomass will be able to consume high quantities of the food, which reduces the loss of residual food in the discharge. In other words, the more the biomass consumes food the lower the BOD will be in the treated effluent. It is important that MLSS eliminates BOD in order to purify the wastewater for further usage and hygiene. Raw sewage is introduced into the wastewater treatment process with a concentration of several hundred mg L-1 of BOD. The concentration of BOD in wastewater is reduced to less than 2 mg L-1 after being treated with MLSS and other treatment methods, which is considered to be safe water to use.

Figure 23.

Activated sludge [15].

Specification Value Unit
BOD-Sludge Loading 0.40 mg L-1
BOD-Volume Loading 0.20 mg L-1
MLSS 2000 mg L-1
COD of Influent 300 mg L-1
Amount of Influent 4.48 L d-1
Aeration Rate 3.00 L min-1

Table 2.

Conventional activated sludge [15].

The biological treatment process is the most commonly implemented method for the treatment of domestic sewage. This method implements bacterial populations that possess superior sedimentation characteristics. The living microorganisms break down the organic matter in the wastewater and consequently purify the wastewater from biological waste [15].

According to [1], the main components of all activated sludge systems are:

  1. The bioreactor: it can be a lagoon, tank, or ditch. The main characteristic of a bioreactor is that it contains sufficiently aerated and mixed contents. The bioreactor is also known as the aeration tank.

  2. Activated sludge: it is the bacterial biomass inside the bioreactor that consists mostly of bacteria and other flora and microfauna. The sludge is a flocculent suspension of these microorganisms and is usually termed as the mixed liquor suspended solids (MLSS) that ranges between 2,000 and 5,000 mg L-1.

  3. Aeration and mixing system: the aeration and mixing of the activated sludge and the raw influent are necessary. While these processes can be accomplished separately, they are usually conducted using a single system of either surface aeration or diffused air.

  4. Sedimentation tank: clarification or settlement of the activated sludge discharged from the aeration tank is essential. This separates the bacterial biomass from the treated wastewater.

  5. Returned sludge: the settled activated sludge in the sedimentation tank is returned to the bioreactor to maintain the microbial population at a required concentration to guarantee persistence of treatment process.

Several parameters should be considered while operating activated sludge plants. The most important parameters are: (1) biomass control, (2) plant loading, (3) sludge settleability, and (4) sludge activity. The main operational variable is the aeration, where its major functions are: (1) ensuring a sufficient and continuous supply of dissolved oxygen (DO) for the bacterial population, (2) keeping the bacteria and the biomass suspended, and (3) mixing the influent wastewater with the biomass and removing from the solution the excessive CO2 resulting from oxidation of organic matter [1].

There are several types of activated sludge processes, e.g., conventional activated sludge plant (Figure 24), complete mix plant (Figure 25), contact stabilization plant (Figure 26), and step aeration plant (Figure 27). Figure 28 shows the food pyramid that represents the feeding relationships within the activated sludge process.

Figure 24.

Conventional activated sludge plant [3].

Figure 25.

Complete mix plant [3].

Figure 26.

Contact stabilization plant [3].

Figure 27.

Step aeration plant [3].

Figure 28.

Food pyramid illustrating the feeding relationships within the activated sludge process [1].

4.4.5. Biological filters

The main systems of operation of biological filters are: (a) single filtration, (b) recirculation, (c) ADF, and (d) two-stage filtration with high-rate primary biotower (Figure 29). There are several types of biological filters, for example, submerged aerated filters that are widely known as biological aerated filters (BAFs) and are the commonly implemented design (Figure 30), and the percolating (trickling) filters (Figure 31). The BAFs implement either the sunken granular media with upward (Figure 30a) or download (Figure 30b) flows, or floating granular media with upward flow (Figure 30c), which is the most common design of BAFs. In order to compare the biological filters and the activated sludge systems (Figures 31 and 32), the comparison is based on the oxidation that can be accomplished by three processes:

  1. Spreading the wastewater into a thin film of liquid with a large surface area, consequently the required oxygen can be supplied by gaseous diffusion, which is the case of the percolating filters.

  2. Aerating the wastewater by pumping air in the form of bubbles or stirring forcefully, which is the case of the activated sludge process.

  3. Implementing algae to produce oxygen by photosynthesis, which is the case of the stabilization ponds.

Figure 29.

The main systems of operation of biological filters [1].

Figure 30.

Biological aerated filters [1].

Figure 31.

Relationship between the natural bacterial populations in rivers and the development of (A) trickling (percolating) filter and (B) activated sludge system [1].

Figure 32.

Comparison of the food chain pyramids for biological filters and activated sludge systems [1].

4.4.6. Rotating biological contactors

The rotating biological contactors (RBC) system (Figure 33) can be implemented to amend and improve the available treatment processes as the secondary or tertiary treatment processes. The RBC is successfully implemented in all three steps of the biological treatment, which are BOD5 removal, nitrification, and denitrification. The process is a fixed-biofilm of either aerobic or anaerobic biological treatment system for removal of nitrogenous and carbonaceous compounds from wastewater (Figure 34). The RBC installations (Figure 35) were designed for removal of BOD5 or ammonia nitrogen (NH3-N), or both, from wastewater [1, 2].

Figure 33.

Schematic diagram of air-drive RBC [2].

The RBC consists of media, shaft, drive, bearings, and cover (Figure 34). The RBC hardware consists of a large diameter and closely spaced circular plastic media that is mounted on a horizontal shaft supported by bearings and is slowly rotated by an electric motor. The plastic media are made of corrugated polystyrene or polyethylene material with different designs, dimensions, and densities. The model designs are based on increasing surface area and firmness, allowing a winding wastewater flow path and stimulating air turbulence [1, 2].

Figure 34.

Mechanism of attached growth media in an RBC system [2].

Figure 35.

RBC system [1].

4.4.7. Biological removal of nutrients

4.4.7.1. Biological phosphorous removal

It is widely agreed that microorganisms utilize acetate and fatty acids to accumulate polyphosphates as poly-β-hydroxybutyrate, which is an acid polymer. The precise mechanism is based on the production and regeneration of adenosine diphosphate (ADP) within the bacteria, and it involves the adenosine triphosphate (ATP). Phosphate removal requires true anaerobic conditions, which occur only when there is no other oxygen donor [3]. Figure 36 shows a phosphate removal process. This process needs long narrow tanks for maintenance of plug flow.

Figure 36.

Phosphate removal process [3].

4.4.7.2. Biological removal of nitrogen

The nitrification and denitrification processes are responsible for N2O production (Figure 37). Figure 38 shows a nitrification/denitrification system for biological removal of nitrogen.

Figure 37.

Schematic illustration of nitrification and denitrification processes that are responsible for N2O release [16].

Figure 38.

Nitrification/denitrification system for biological removal of nitrogen [3].

4.4.8. Phytoremediation

Phytoremediation is a treatment process that solves environmental problems by implementing plants that abate environmental pollution without excavating the pollutants and disposing them elsewhere. Phytoremediation is the abatement of pollutant concentrations in contaminated soils or water using plants that are able to accumulate, degrade, or eliminate heavy metals, pesticides, solvents, explosives, crude oils and its derivatives, and a multitude of other contaminants and pollutants from water and soils. Figures 39 through 44 show the designs of constructed wetlands where the phytoremediation takes place.

Figure 39.

Cross-sectional view of a typical subsurface flow constructed wetland [17].

Figure 40.

Components of a horizontal flow reed bed: (1) drainage zone consisting of large rocks, (2) drainage tube of treated effluent, (3) root zone, (4) impermeable liner, (5) soil or gravel, (6) wastewater distribution system, and (7) reeds [1].

Figure 41.

Free water surface system [18].

Figure 42.

Sub-surface flow system [18].

Figure 43.

Components of a free water surface constructed wetland [2].

Figure 44.

Components of a vegetated submerged bed system [2].

The incorporation of heavy metals, such as mercury, into the food chain may be a deteriorating matter. Phytoremediation is useful in these situations, where natural plants or transgenic plants are able to phytodegrade and phytoaccumulate these toxic contaminants in their above-ground parts, which will be then harvested for extraction. The heavy metals in the harvested biomass can be further concentrated by incineration and recycled for industrial implementation. Rhizofiltration is a sort of phytoremediation that involves filtering wastewater through a mass of roots to remove toxic substances or excess nutrients. Phytoaccumulation or phytoextraction implements plants or algae to remove pollutants and contaminants from wastewater into plant biomass that can be harvested. Organisms that accumulate over than usual amounts of pollutants from soils are termed hyperaccumulators, where a multitude of tables that show the different hyperaccumulators are available and should be referred to. In the case of organic pollutants, such as pesticides, explosives, solvents, industrial chemicals, and other xenobiotic substances, certain plants render these substances non-toxic by their metabolism and this process is called phytotransformation. In other cases, microorganisms that live in symbiosis with plant roots are able to metabolize these pollutants in wastewater. Figure 45 shows the tissues where the rhizofiltration, phytodegradation, and phytoaccumulation take place.

Figure 45.

Rhizofiltration, phytodegradation, and phytoaccumulation [19].

4.4.9. Vermifiltration

Vermiculture, or worm farming, is the implementation of some species of earthworm, such as Eisenia fetida(known as red wiggler, brandling, or manure worm) and Lumbricus rubellus, to make vermicompost, also known as worm compost, vermicast, worm castings, worm humus, or worm manure, which is the end-product of the breakdown of organic matter and considered to be a nutrient-rich biofertilizer and soil conditioner. Vermiculture can be implemented to transform livestock manure, food leftovers, and organic matters into a nutrient-rich biofertilizer.

The potential use of earthworms to break down and manage sewage sludge began in the late 1970s [20] and was termed vermicomposting. The introduction of earthworms to the filtration systems, termed vermifiltration systems, was advocated by José Toha in 1992 [21]. Vermifilter is widely used to treat wastewater, and appeared to have high treatment efficiency, including synchronous stabilization of wastewater and sludge [22, 23, 24]. Vermifiltration is a feasible treatment method to reduce and stabilize liquid-state sewage sludge under optimal conditions [24, 25, 26]. Vermicomposting involves the joint action of earthworms and microorganisms [24, 27, 28], and significantly enhances the breakdown of sludge. Earthworms operate as mechanical blenders and by comminuting the organic matter they modify its physical and chemical composition, steadily decreasing the C:N ratio, increasing the surface area exposed to microorganisms, and making it much more suitable for bacterial activity and further breakdown. Throughout the passageway is the earthworm gut, they move fragments and bacteria-rich excrements, consequently homogenizing the organic matter [29]. An intensified bacterial diversity was found in vermifilter, compared with conventional biofilter without earthworms [25]. The principle of using earthworms to treat sewage sludge is based on the perception that there is a net loss of biomass and energy when the food chain is extended [25]. Compared to other technologies of liquid-state sludge stabilization, such as anaerobic digestion and aerobic digestion [30], vermifiltration is a low-cost and an ecologically sound technique, and more suitable for sewage sludge treatment of small or developing-countries' WWTPs [23, 24, 25, 26, 31]. Figure 46 illustrates schematic diagram of a vermifilter, where the earthworms are in the filter bed.

Figure 46.

Schematic diagram of a vermifilter [24].

An important application is in livestock manure treatment as shown in Figure 47, where manure is flushed out from the livestock building to a raw effluent tank then the raw effluent is screened to separate the solid waste from manure. The screened effluent is then introduced to the vermifilter to produce the vermicompost. The vermifiltered effluent is then stored in a sedimentation tank. Afterwards, the vermifiltered effluent is introduced to constructed wetlands where the phytoremediation process takes place. The purified water can be then used to flush the water from the livestock building.

Figure 47.

Schematic diagram of a manure treatment system containing vermifiltration and phytoremediation processes (Amended and redrawn from Morand et al. [32]).

4.4.10. Microbial fuel cells

The microbial fuel cells (MFCs) allow bacteria to grow on the anode by oxidizing the organic matter that result in releasing electrons. The cathode is sparked with air to provide dissolved oxygen for the reaction of electrons, protons, and oxygen on the cathode, which result in completing the electrical circuit and producing electrical energy (Figure 48).

Figure 48.

Schematic diagram of the essential components of an MFC [33].

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5. Chemical treatment of wastewater

5.1. Chemical precipitation

The dissolved inorganic components can be removed by adding an acid or alkali, by changing the temperature, or by precipitation as a solid. The precipitate can be removed by sedimentation, flotation, or other solid removal processes [1]. Although chemical precipitation (coagulation, flocculation) is still implemented, it is highly recommended to substitute the chemical precipitation process by phytoremediation (see previous section), where the trend is to ramp up the implementation of bioremediation and phytoremediation to reduce the use of chemicals, which is in line with the “Green Development”.

5.2. Neutralization

Neutralization is controlling the pH of the wastewater whether it is acidic or alkaline to keep the pH around 7. The lack of sufficient alkalinity will require the addition of a base (Table 3) to adjust the pH to the acceptable range. Lime (CaO), calcium hydroxide (Ca(OH)2), sodium hydroxide (NaOH), and sodium carbonate (Na2CO3), also known as soda ash, are the most common chemicals used to adjust the pH [34]. The lack of sufficient acidity will require the addition of an acid to adjust the pH to the acceptable range. Sulfuric acid (H2SO4) and carbonic acid (H2CO3) are the most common chemicals used to adjust the pH.

Table 3.

Neutralization: Case of acidic wastewater [34].

Note: a stoichiometric reaction will yield a pH of 7.0


5.3. Adsorption

Adsorption is a physical process where soluble molecules (adsorbate) are removed by attachment to the surface of a solid substrate (adsorbent). Adsorbents should have an extremely high specific surface area. Examples of adsorbents include activated alumina, clay colloids, hydroxides, resins, and activated carbon. The surface of the adsorbent should be free of adsorbate. Therefore, the adsorbent should be activated before use. A wide range of organic materials can be removed by adsorption, including detergents and toxic compounds. The most widely used adsorbent is activated carbon, which can be produced by pyrolytic carbonization of biomass [1]. Figure 49 illustrates the difference between absorption and adsorption. Activated carbon is the most implemented adsorbent and is a sort of carbon processed to be riddled with small, low-volume pores that enlarge the surface area available for adsorption. Owing to its high level of microporosity, 1 g of activated carbon has a surface area larger than 500 m2, which was determined by gas adsorption. Figure 50 shows a bed carbon adsorption unit. Note that the carbon can be regenerated by thermal oxidation or steam oxidation and reused. The adsorption capacity, one of the most important characteristics of an adsorbent, can be calculated as follows:

AdsorptionCapacitymg/g=Adsorbatemg/AdsorbentgBB3

The factors that affect adsorption are [3]:

  1. Particle diameter: the adsorption is inversely proportional to the particle size of the adsorbent, and directly proportional to surface area.

  2. Adsorbate concentration: the adsorption is directly proportional to adsorbate concentration.

  3. Temperature: the adsorption is directly proportional to temperature.

  4. Molecular weight: generally, the adsorption is inversely proportional to molecular weight depending upon the compound weight and configuration of pores diffusion control.

  5. pH: the adsorption is inversely proportional to pH due to surface charge.

  6. Individual properties of adsorbate and adsorbent are difficult to compare.

  7. Iodine number: is the mass of iodine (g) that is consumed by 100 g of a substance.

Figure 49.

A comparison between absorption and adsorption.

Figure 50.

A bed carbon adsorption unit [35].

5.4. Disinfection

The disinfection of wastewater is the last treatment step of the tertiary treatment process. Disinfection is a chemical treatment process conducted by treating the effluent with the selected disinfectant to exterminate or at least inactivate the pathogens. The rationales behind effluent disinfection are to protect public health by exterminating or inactivating the pathogens such as microbes, viruses, and protozoan, and to meet the wastewater discharge standards. The purpose of disinfection is the protection of the microbial wastewater quality. The ideal disinfectant should have bacterial toxicity, is inexpensive, not dangerous to handle, and should have reliable means of detecting the presence of a residual. The chemical disinfection agents include chlorine, ozone, ultraviolet radiation, chlorine dioxide, and bromine [3].

5.4.1. Chlorine

Chlorine is one of the oldest disinfection agents used, which is one of the safest and most reliable. It has extremely good properties, which conform to the aspects of the ideal disinfectant. Effective chlorine disinfection depends upon its chemical form in wastewater. The influencing factors are pH, temperature, and organic content in the wastewater [3]. When chlorine gas is dissolved in wastewater, it rapidly hydrolyzes to hydrochloric acid (HCl) and hypochlorous acid (HOCl) as shown in the following chemical equation:

Cl2+H2OH++Cl-+HOClBB4

Free ammonia combines with the HOCl form of chlorine to form chloramines in a three-step reaction, as follows:

NH3+HOClNH2Cl+H2ONH2Cl+HOClNHCl2+H2ONHCL2+HOClNCl3+H2OBB5

Figure 51 illustrates the chlorination curve, where the formation of chloramines occurs at the breakpoint. The free chlorine residual first rises then falls until the reaction with ammonia has been completed. As additional chlorine is applied and ammonia is consumed, the chlorine residual rises again.

Figure 51.

Chlorination curve [3].

Dechlorination is a very important process, where activated carbon, sulfur compounds, hydrogen sulfide, and ammonia can be implemented to minimize the residual chlorine in a disinfected effluent prior to discharge. Activated carbon and sulfur compounds are the most widely used [3]. The commonly used sulfur compounds are sulfur dioxide (SO2), sodium metabisulfite (NaS2O5), sodium bisulfate (NaHSO3), and sodium sulfite (Na2SO3). The dechlorination reactions with the abovementioned compounds are described in the following equations:

SO2+2H2O+Cl2H2SO4+2HClSO2+H2O+HOCl3H++Cl-+SO42-Na2S2O5+2Cl2+3H2O2NaHSO4+4HClNaHSO3+H2O+Cl2NaHSO4+2HClBB6

5.4.2. Ozone

Ozone (O3) is a very strong oxidant typically used in wastewater treatment. Ozone is able to oxidize a multitude of organic and inorganic compounds in wastewater. These reactions cause an ozone demand in the treated wastewater, which should be fulfilled throughout wastewater ozonation prior to developing an assessable residual. Ozone should be generated at the point of application for use in wastewater treatment as ozone is an unstable molecule [3]. Figure 52 illustrates the corona discharge method for making ozone. Ozone is generally formed by combining an oxygen atom with an oxygen molecule (O2) as follows:

Figure 52.

Schematic drawing of corona discharge method for making ozone [3].

5.4.3. Ultraviolet light

Ultraviolet (UV) radiation is a microbial disinfectant that leaves no residual. It requires clear, un-turbid, and non-colored water for its implementation. The commercial UV disinfection systems use low- to medium-powered UV lamps with a wavelength of 354 nm [3]. The UV dosage can be calculated as follows:

D=ItBB7

where, Dis the UV dose (mW. s/cm2); Iis the intensity (mW/cm2); and tis the exposure time (s).

The advantages of UV radiation are: (1) directly effective against the DNA of many microorganisms, (2) not reactive with other forms of carbonaceous demand, and (3) provides superior bactericidal kill values while not leaving any residues. The advantage is often the disadvantage, because power fluctuations, variations in hydraulic flow rates, and color or turbidity can cause the treatment to be ineffective [3]. Additionally, cell recovery and re-growth of the damaged organisms because of the inactivation of their predators and competitors has come to light.

5.5. Ion exchange

Ion exchange (IX) is a reversible reaction in which a charged ion in a solution is exchanged with a similarly charged ion which is electrostatically attached to an immobile solid particle. The most common implementation of ion exchange method in wastewater treatment is for softening, where polyvalent cations (e.g., calcium and magnesium) are exchanged with sodium [36]. Practically, wastewater is introduced into a bed of resin. The resin is manufactured by converting a polymerization of organic compounds into a porous matrix. Typically, sodium is exchanged with cations in the solution [34]. The bed is shut down when it becomes saturated with the exchanged ions, where it should be regenerated by passing a concentrated solution of sodium back through the bed. Figure 53 shows the schematic illustration of organic cation-exchange bead. Figure 54 shows a typical ion exchange resin column. Table 4 shows the ion preference and affinity for some selected compounds.

Figure 53.

Schematic illustration of organic cation-exchange bead [34].

Figure 54.

Typical ion exchange resin column [37].

Table 4.

Ion preference and affinity for some selected compounds [3].

5.6. Physicochemical treatment processes

The principal advanced physicochemical wastewater treatment processes are elucidated in Table 5.

Table 5.

Principal advanced physicochemical wastewater treatment processes [1].

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6. Wastewater treatment plants

This section shows some examples of WWTPs as shown in Figure 55 (a, b, and c) and Figure 56. On the other hand, there are some computer programs for planning and designing WWTPs (Figures 57, 58, and 59).

Figure 55.

WWTP showing: (a) layout of the plant, (b) wastewater process flow diagrams, and (c) sludge process flow diagram.Wastewater treatment: 1. Storm water overflow; 2. screening; 3. grit removal; 4. primary sedimentation; 5. aeration tanks; 6. Secondary sedimentation; 7. emergency chlorination; 8. filtration; 9. effluent outfall.Sludge treatment: 10. raw sludge thickeners; 11. digestion tanks; 12. digested sludge thickeners; 13. power house; 14. biogas storage; 15. filter press house; 16. transformer station. A and B are administrative areas [1].

Figure 56.

Summary of the main process options commonly employed at both domestic and industrial WWTPs. Not all of these unit processes may be selected, but the order of their use remains the same [1].

Figure 57.

Screenshot of the STEADY program [3].

Figure 58.

WEST software typical plant configuration [3].

Figure 59.

WEST configuration for multitank system [3].

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7. Conclusions

According to this study, it can be conclude that:

  1. The trend is to ramp up the implementation of bioremediation, phytoremediation, and mycoremediation to reduce the use of chemicals, which is in line with the “Green Development”.

  2. The recent developments elucidate that subsequent to the physical treatment processes (the primary treatment) the biological treatment processes come in turn as secondary treatment and precede the chemical treatment processes, which constitute the tertiary treatment.

  3. Microbial fuel cells, phytoremediation, and mycoremediation are the focus of the future development in this field.

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Written By

Mohamed Samer

Submitted: December 2nd, 2014 Reviewed: July 23rd, 2015 Published: October 14th, 2015

2. Chapter description and contents overview

The chapter describes the biological and chemical wastewater treatment processes that include:

  1. Bioremediation of wastewater using oxidation ponds, aeration lagoons, anaerobic lagoons, aerobic and anaerobic bioreactors, activated sludge, percolating or trickling filters, biological filters, rotating biological contactors, and biological removal of nutrients;

  2. Mycoremediation of wastewater using bioreactors;

  3. Phytoremediation of wastewater that includes: constructed wetlands, rhizofiltration, rhizodegradation, phytodegradation, phytoaccumulation, phytotransformation, and hyperaccumulators;

  4. Vermifiltration and vermicomposting;

  5. Microbial fuel cells for electricity production from wastewater;

  6. Chemical wastewater treatment processes that include: chemical precipitation, ion exchange, neutralization, adsorption and disinfection (chlorination/dechlorination, ozone, ultraviolet radiation);

  7. Wastewater treatment plants. The chapter elucidates and illustrates the plant sizing, plant layout, plant design, and plant location.

3. Overview

3.1. Wastewater treatment techniques

Wastewater, or sewage, originates from human and home wastewaters, industrial wastes, animal wastes, rain runoff, and groundwater infiltration. Generally, wastewater is the flow of used water from a neighborhood. The wastewater consists of 99.9% water by weight, where the remaining 0.1% is suspended or dissolved material. This solid material is a mixture of excrements, detergents, food leftovers, grease, oils, salts, plastics, heavy metals, sands, and grits [1, 2]. Types of wastewaters include: municipal wastewater, industrial wastewaters, mixtures of industrial/domestic wastewaters, and agricultural wastewaters. Typical agricultural industries include: dairy processing industries, meat processing factories, juice and beverage industries, slaughterhouses, vegetable processing facilities, rendering plants, and drainage water of irrigation systems.

Subsequent to primary treatment of wastewater, i.e., physical treatment of wastewater, it still contains large amounts of dissolved and colloidal material that must be removed before discharge. The issue is how to transform the dissolved materials or particulate matters that are too little for sedimentation into larger particles to allow the separation processes to eliminate them. This can be accomplished by secondary treatment, i.e., biological treatment. The treatment of wastewater subsequent to the removal of suspended solids by microorganisms such as algae, fungi, or bacteria under aerobic or anaerobic conditions during which organic matter in wastewater is oxidized or incorporated into cells that can be eliminated by removal process or sedimentation is termed biological treatment. Biological treatment is termed secondary treatment. Chemical treatment, or tertiary treatment, using chemical materials will react with a portion of the undesired chemicals and heavy metals, but a portion of the polluting material will remain unaffected. Additionally, the cost of chemical additives and the environmental problem of disposing large amounts of chemical sludge make this treatment process deficient [1]. Alternatively, the biological treatment must be implemented. This treatment process implements naturally occurring microorganisms to transform the dissolved organic matter into a dense biomass that can be separated from the treated wastewater by the sedimentation process. In fact, the microorganisms utilize the dissolved organic matter as food for themselves, where the generated sludge will be far less for chemical treatment. In practice, therefore, secondary treatment tends to be a biological process with chemical treatment implemented for the removal of toxic compounds.

3.2. Aims of wastewater treatment

The goals of treating the wastewaters are:

  1. Transforming the materials available in the wastewater into secure end products that are able to be safely disposed off into domestic water devoid of any negative environmental effects;

  2. Protecting public health;

  3. Ensuring that wastewaters are efficiently handled on a trustworthy basis without annoyance or offense;

  4. Recycling and recovering the valuable components available in wastewaters;

  5. Affording feasible treatment processes and disposal techniques;

  6. Complying with the legislations, acts and legal standards, and approval conditions of discharge and disposal.

3.3. Biological treatment processes

The secondary treatment can be defined as “treatment of wastewater by a process involving biological treatment with a secondary sedimentation”. In other words, the secondary treatment is a biological process. The settled wastewater is introduced into a specially designed bioreactor where under aerobic or anaerobic conditions the organic matter is utilized by microorganisms such as bacteria (aerobically or anaerobically), algae, and fungi (aerobically). The bioreactor affords appropriate bioenvironmental conditions for the microorganisms to reproduce and use the dissolved organic matter as energy for themselves. Provided that oxygen and food, in the form of settled wastewater, are supplied to the microorganisms, the biological oxidation process of dissolved organic matter will be maintained. The biological process is mostly carried out bacteria that form the basic trophic level (the level of an organism is the position it occupies in a food chain) of the food chain inside the bioreactor. The bioconversion of dissolved organic matter into thick bacterial biomass can fundamentally purify the wastewater. Subsequently, it is crucial to separate the microbial biomass from the treated wastewater though sedimentation. This secondary sedimentation is basically similar to primary sedimentation except that the sludge contains bacterial cells rather than fecal solids. The biological removal of organic matter from settled wastewater is conducted by microorganisms, mainly heterotrophic bacteria but also occasionally fungi. The microorganisms are able to decompose the organic matter through two different biological processes: biological oxidation and biosynthesis [1]. The biological oxidation forms some end-products, such as minerals, that remain in the solution and are discharged with the effluent (Eq. 1). The biosynthesis transforms the colloidal and dissolved organic matter into new cells that form in turn the dense biomass that can be then removed by sedimentation (Eq. 2). Figure 1 summarizes these processes. On the other hand, algal photosynthesis plays an important role in some cases (Figure 2).

Oxidation:COHNS+O2(Organicmatter)+BacteriaCO2+NH3+Energy+OtherendproductsE1
Biosynthesis:COHNS+O2(Organicmatter)+BacteriaC5H7NO2(Newcells)E2

3.3.1. Useful terms

The following terms are the most used in biological treatment processes [2]:

  1. DO: Dissolved Oxygen (mg L-1)

  2. BOD: Biochemical Oxygen Demand (mg L-1)

  3. BOD5: BOD (mg L-1), incubation at 15°C for 5 days

  4. COD: Chemical Oxygen Demand (mg L-1)

  5. CBOD: Carbonaceous BOD (mg L-1)

  6. NBOD: Nitrogenous (mg L-1)

  7. SOD: Sediment Oxygen Demand (mg L-1)

  8. TBOD: Total BOD (mg L-1)

Figure 1.

Biological synthesis and oxidation [3].

Figure 2.

Photosynthesis and oxidation [2].

3.4. Chemical treatment processes

In early wastewater treatment technologies, chemical treatment has preceded biological treatment. Recently, the biological treatment precedes chemical treatment in the treatment process. Chemical treatment is now considered as a tertiary treatment that can be more broadly defined as “treatment of wastewater by a process involving chemical treatment”. The mostly implemented chemical treatment processes are: chemical precipitation, neutralization, adsorption, disinfection (chlorine, ozone, ultraviolet light), and ion exchange.

4. Biological treatment of wastewater

4.1. Biological growth equation

The biological growth can be described according to the Monod equation:

μ=(λS)/(KS+S)BB1
\n\t\t\t\t

Where, μ is the specific growth rate coefficient; λ is the maximum growth rate coefficient that occurs at 0.5 μmax; S is the concentration of limiting nutrient, that is BOD and COD; and KS is the Monod coefficient [3].

Generally, the bacterial growth can be explained by the following simplified figure:

Organics+Bacteria+Nutrients+OxygenNewBacteria+CO2+H2O+ResidualOrganics+InorganicsBB2
\n\t\t\t\t

Several bioenvironmental factors affect the activity of bacteria and the rate of biochemical reactions. The most important factors are: temperature, pH, dissolved oxygen, nutrient concentration, and toxic materials. All these factors can be controlled within a biological treatment system and/or a bioreactor in order to ensure that the microbial growth is maintained under optimum bioenvironmental conditions. The majority of biological treatment systems operate in the mesophilic temperature range, where the optimal temperature ranges from 20°C to 40°C. Aeration tanks and percolating filters operate at the temperature of the wastewater that ranges from 12°C to 25°C; although in percolating filters, the air temperature and the ventilation rate may have a significant effect on heat loss. The higher temperatures increase the biological activity and metabolism, which result in increasing the substrate removal rate. However, the increased metabolism at the higher temperatures may lead to problems of oxygen limitations.

4.2. Bacterial kinetics

The bacterial kinetics can be shown in Figures 3 and 4. The microbial growth curve that shows bacterial density and specific growth rate at the different growth phases is shown in Figure 3. The microbial growth curves that compare the total biomass and the variable biomass are shown in Figure 4.

Figure 3.

Microbial growth curve [1].

Figure 4.

Microbial growth curves [1].

4.3. Principles of biological treatment

The principles of biological treatment of wastewater were stated by [3]. The following is a summary of the principles:

  1. The biological systems are very sensitive for extreme variations in hydraulic loads. Diurnal variations of greater than 250% are problematic because they will create biomass loss in the clarifiers.

  2. The growth rate of microorganisms is highly dependent on temperature. A 10°C reduction in wastewater temperature dramatically decreases the biological reaction rates to half.

  3. BOD is efficiently treated in the range of 60 to 500 mg L-1. Wastewaters in excess of 500 mg L-1 BODs have been treated successfully if sufficient dilution is applied in the treatment process, or if an anaerobic process was implemented as a pretreatment process.

  4. The biological treatment is effective in removing up to 95% of the BOD. Large tanks are required in order to eliminate the entire BOD, which is not feasible.

  5. The biological treatment systems are unable to handle “shock loads” efficiently. Equalization is necessary if the variation in strength of the wastewater is more than 150% or if that wastewater at its peak concentration is in excess of 1,000 mg L-1 BOD.

  6. The carbon:nitrogen:phosphorus (C:N:P) ratio of wastewater is usually ideal. The C:N:P ratio of industrial wastewaters should range from 100:20:1 to 100:5:1 for a most advantageous biological process.

  7. If the C:N:P ratio of the wastewater is strong in an element in comparison to the other elements, then poor treatment will result. This is especially true if the wastewater is very strong in carbon. The wastewater should also be neither very weak nor very strong in an element; although very weak is acceptable, it is difficult to treat.

  8. Oils and solids cannot be handled in a biological treatment system because they negatively affect the treatment process. These wastes should be pretreated to remove solids and oils.

  9. Toxic and biological-resistant materials require special consideration and may require pretreatment before being introduced into a biological treatment system.

  10. Although the capacity of the wastewater to utilize oxygen is unlimited, the capacity of any aeration system is limited in terms of oxygen transfer.

4.4. Bioremediation of wastewater

Bioremediation is a treatment process that involves the implementation of microorganisms to remove pollutants from a contaminated setting. Bioremediation can be defined as “treatment that implements natural organisms to decompose hazardous materials into less toxic or nontoxic materials”. Some examples of bioremediation-related technologies are phytoremediation, bioaugmentation, rhizofiltration, and biostimulation. The microorganisms implemented to carry out the bioremediation are called bioremediators. However, some pollutants are not easily removed or decomposed by bioremediation. For example, heavy metals such as lead and cadmium are not eagerly captured by bioremediators. Example of bioremediation: fish bone char has been shown to bioremediate small amounts of cadmium, copper, and zinc.

The bioremediation of wastewater can be achieved by autotrophs or heterotrophs. A heterotroph is an organism that is unable to fix carbon and utilizes organic carbon for its growth. Heterotrophs are divided based on their source of energy. If the heterotroph utilizes light as its source of energy, then it is considered a photoheterotroph. If the heterotroph utilizes organic and/or inorganic compounds as energy sources, it is then considered a chemoheterotroph. Autotrophs, such as plants and algae, that are able to utilize energy from sunlight are called photoautotrophs. Autotrophs that utilize inorganic compounds to produce organic compounds such as carbohydrates, fats, and proteins from inorganic carbon dioxide are called lithoautotrophs. These reduced carbon compounds can be utilized as energy sources by autotrophs and provide the energy in food consumed by heterotrophs. Over 95% of all organisms are heterotrophic.

4.4.1. Aerobic treatment

Aeration has been used to remove trace organic volatile compounds (VOCs) in water. It has also been employed to transfer a substance, such as oxygen, from air or a gas phase into water in a process called “gas adsorption” or “oxidation”, i.e., to oxidize iron and/or manganese. Aeration also provides the escape of dissolved gases, such as CO2 and H2S. Air stripping has been also utilized effectively to remove NH3 from wastewater and to remove volatile tastes and other such substances in water [2]. Samer [4] and Samer et al. [5] mentioned that aerobic treatment with biowastes is effective in reducing harmful gaseous emissions as greenhouse gases (CH4 and N2O) and ammonia.

4.4.1.1. Oxidation ponds

Oxidation ponds (Figure 5) are aerobic systems where the oxygen required by the heterotrophic bacteria (a heterotroph is an organism that cannot fix carbon and uses organic carbon for growth) is provided not only by transfer from the atmosphere but also by photosynthetic algae. The algae are restricted to the euphotic zone (sunlight zone), which is often only a few centimeters deep. Ponds are constructed to a depth of between 1.2 and 1.8 m to ensure maximum penetration of sunlight, and appear dark green in color due to dense algal development. Samer [6] and Samer et al. [7] illustrated the structures and constructions of the aerobic treatment tanks and the used building materials.

Figure 5.

Aerobic system/oxidation pond [1].

In oxidation ponds, the algae use the inorganic compounds (N, P, CO2) released by aerobic bacteria for growth using sunlight for energy. They release oxygen into the solution that in turn is utilized by the bacteria, completing the symbiotic cycle. There are two distinct zones in facultative ponds: the upper aerobic zone where bacterial (facultative) activity occurs and a lower anaerobic zone where solids settle out of suspension to form a sludge that is degraded anaerobically.

4.4.1.2. Aeration lagoons

Aeration lagoons are profound (3–4 m) compared to oxidation ponds, where oxygen is provided by aerators but not by the photosynthetic activity of algae as in the oxidation ponds. The aerators keep the microbial biomass suspended and provide sufficient dissolved oxygen that allows maximal aerobic activity. On the other hand, bubble aeration is commonly used where the bubbles are generated by compressed air pumped through plastic tubing laid through the base of the lagoon. A predominately bacterial biomass develops and, whereas there is neither sedimentation nor sludge return, this procedure counts on adequate mixed liquor formed in the tank/lagoon. Therefore, the aeration lagoons are suitable for strong but degradable wastewater such as wastewaters of food industries. The hydraulic retention time (HRT) ranges from 3 to 8 days based on treatment level, strength, and temperature of the influent. Generally, HRT of about 5 days at 20°C achieves 85% removal of BOD in household wastewater. However, if the temperature falls by 10°C, then the BOD removal will decrease to 65% [1].

4.4.2. Anaerobic treatment

The anaerobic treatments are implemented to treat wastewaters rich in biodegradable organic matter (BOD >500 mg L-1) and for further treatment of sedimentation sludges. Strong organic wastewaters containing large amounts of biodegradable materials are discharged mainly by agricultural and food processing industries. These wastewaters are difficult to be treated aerobically due to the troubles and expenses of fulfillment of the elevated oxygen demand to preserve the aerobic conditions [1]. In contrast, anaerobic degradation occurs in the absence of oxygen. Although the anaerobic treatment is time-consuming, it has a multitude of advantages in treating strong organic wastewaters. These advantages include elevated levels of purification, aptitude to handle high organic loads, generating small amounts of sludges that are usually very stable, and production of methane (inert combustible gas) as end-product.

Anaerobic digestion is a complex multistep process in terms of chemistry and microbiology. Organic materials are degraded into basic constituents, finally to methane gas under the absence of an electron acceptor such as oxygen [8]. The basic metabolic pathway of anaerobic digestion is shown in Figures 6 and 7. To achieve this pathway, the presence of very different and closely dependent microbial population is required.

Figure 6.

Steps of the anaerobic digestion process [8].

Figure 7.

Major steps in anaerobic decomposition [1].

Suitable wastewaters include livestock manure, food processing effluents, petroleum wastes (if the toxicity is controlled), and canning and dyestuff wastes where soluble organic matters are implemented in the treatment. Most anaerobic processes (solids fermentation) occur in two predetermined temperature ranges: mesophilic or thermophilic. The temperature ranges are 30–38oC and 38–50oC, respectively [3]. In contrast to aerobic systems, absolute stabilization of organic matter is not achievable under anaerobic conditions. Therefore, subsequent aerobic treatment of the anaerobic effluents is usually essential. The final waste matter discharged by the anaerobic treatment includes solubilized organic matter that is acquiescent to aerobic treatment demonstrating the possibility of installing collective anaerobic and aerobic units in series [1].

4.4.2.1. Anaerobic digesters

Samer [9] elucidated and illustrated the structures and constructions of the anaerobic digesters and the used building materials. Samer [10] developed an expert system for planning and designing biogas plants. Figures 8 to 13 show different types of anaerobic digesters. While Figures 14 and 15 show some industrial applications. Table 1 shows the advantages and disadvantages of anaerobic treatment compared to aerobic treatment.

Figure 8.

Most commonly used anaerobic reactor types: (A) Completely mixed anaerobic digester, (B) UASB reactor, (C) AFB or EGSB reactor, and (D) Upflow AF [8].

Figure 9.

Single-stage conventional anaerobic digester [3].

Figure 10.

Dual-stage high rate digester [3].

Figure 11.

Schematic representation of digester types. Flow-through (A–B) and contact systems (C–F) [1].

Figure 12.

The upper scheme shows a two-stage anaerobic sludge digester, while the lower scheme shows the conventional sludge digestion plant [1].

Figure 13.

Primary digestion tank with screw mixing pump and external heater [1].

Figure 14.

Wastewater treatment plant for corn processing industry [8].

Figure 15.

Mass balance study for a wastewater treatment plant of the baker’s yeast industry [8].

By definition, the anaerobic treatment is conducted without oxygen. It is different from an anoxic process, which is a reduced environment in contrast to an environment without oxygen. Both processes are anoxic, but anaerobic is an environment beyond anoxic where the oxidation reduction potential (ORP) values are highly negative. In the anaerobic process, nitrate is reduced to ammonia and nitrogen gas, and sulfate (SO32-) is reduced to hydrogen sulfide (H2S). Phosphate is also reduced because it is often transformed through the ADP–ATP chain [3].

\n\t\t\n\t\t\n\t\t\t\n\t\t\n\t
\n\t\t\t\t\n\t\t\t

Table 1.

The advantages and disadvantages of anaerobic treatment compared to aerobic treatment [1].

4.4.2.2. Anaerobic lagoons

An anaerobic lagoon is a deep lagoon, fundamentally without dissolved oxygen, that enforces anaerobic conditions. The anaerobic process occurs in deep ground ponds, and such basins are implemented for anaerobic pretreatment. The anaerobic lagoons are not aerated, heated, or mixed. The depth of an anaerobic lagoon should be typically deeper than 2.5 m, where deeper lagoons are more efficient. Such depths diminish the amount of oxygen diffused from the surface, allowing anaerobic conditions to prevail (U.S. EPA, 2002). Figures 16 to 18 show different types of anaerobic lagoons.

Figure 16.

Anaerobic lagoon for strong wastewater treatment, such as meat processing wastewater [1].

Figure 17.

Schematic of volume fractions in anaerobic lagoon design [11].

Figure 18.

Anaerobic wastewater treatment lagoon [12].

4.4.3. Bioreactors

A bioreactor can be defined as “engineered or manufactured apparatus or system that controls the embraced or encompassed bioenvironment”. Precisely, the bioreactor is a vessel in which a biochemical process is conducted, where it involves microorganisms (e.g., bacteria, algae, fungi) or biochemical substances (e.g., enzymes) derived from such microorganisms. The treatment can be conducted under either aerobic or anaerobic conditions. The bioreactors are commonly made of stainless steel, usually cylindrical in shape and range in size from liters to cubic meters. The bioreactors are classified as batch, plug, or continuous flow reactors (e.g., continuous stirred-tank bioreactor).

Mycoremediation is a type of bioremediation where fungi are implemented to break down the contaminants. The term “mycoremediation” refers particularly to the implementation of fungal “mycelia” in bioremediation. The principal role of fungi in the ecological system is the breakdown of pollutants, which is performed by the mycelium. The mycelium, the vegetative part of a fungus, secretes enzymes and acids that biodegrade lignin and cellulose that are the main components of vegetative fibers. Lignin and cellulose are organic compounds composed of long chains of carbon and hydrogen, and therefore they are structurally similar to several organic pollutants. One key issue is specifying the right fungus to break down a determined pollutant. Similarly, mycofiltration is a process that uses fungal mycelia to filter toxic compounds from wastewater. In an experiment, wastewater contaminated with diesel oil was inoculated with mycelia of oyster mushrooms. One month later, more than 93% of many of the polycyclic aromatic hydrocarbons (PAH) had been reduced to non-toxic components in the mycelial-inoculated samples. The natural microbial community participates with the fungi to break down contaminants, eventually into CO2 and H2O. Wood-degrading fungi are particularly effective in breaking down aromatic pollutants (toxic components of petroleum), as well as chlorinated compounds (certain persistent pesticides). Figures 19 to 22 show different types and designs of bioreactors.

Figure 19.

A bioreactor for fungal degradation: trickle bed bioreactor [13].

Figure 20.

A bioreactor for fungal degradation: rotating disc bioreactor [13].

Figure 21.

Fluidized bed bioreactor [14].

Figure 22.

Typical design of fluidized bed reactor system [1].

4.4.4. Activated sludge

The activated sludge process is based on a mixture of thick bacterial population suspended in the wastewater under aerobic conditions. With unlimited nutrients and oxygen, high rates of bacterial growth and respiration can be attained, which results in the consumption of the available organic matter to either oxidized end-products (e.g., CO2, NO3-, SO42-, and PO43-) or biosynthesis of new microorganisms. The activated sludge process is based on five interdependent elements, which are: bioreactor, activated sludge, aeration and mixing system, sedimentation tank, and returned sludge [1]. The biological process using activated sludge is a commonly used method for the treatment of wastewater, where the running costs are inexpensive (Figure 23). However, a huge quantity of surplus sludge is produced in wastewater treatment plants (WWTPs) which is an enormous burden in both economical and environmental aspects. The excess sludge contains a lot of moisture and is not easy to treat. The byproducts of WWTPs are dewatered, dried, and finally burnt into ashes. Some are used in farm lands as compost fertilizer [15]. However, it is suggested that the dried byproducts of WWTPs are fed into the pyrolysis process rather than the burning process.

The sludge volume index (SVI) is an estimation that specifies the tendency of aerated solids, i.e., activated sludge solids, to become dense or concentrated through the thickening process. SVI can be computed as follows: (a) allowing a mixed liquor sample from the aeration tank to sediment in 30 min; (b) determining the concentration of the suspended solids for a sample of the same mixed liquor; (c) SVI is then computed as ratio of the measured wet volume (mL/L) of the settled sludge to the dry weight concentration of MLSS in g/L (Source: Office of Water Programs, Sacramento State, USA).

During the treatment of wastewater in aeration tanks through the activated sludge process (Table 2) there are suspended solids, where the concentration of the suspended solids is termed as mixed liquor suspended solids (MLSS), which is measured in milligrams per liter (mg L-1). Mixed liquor is a mixture of raw wastewater and activated sludge in an aeration tank. MLSS consists mainly of microorganisms and non-biodegradable suspended solids. MLSS is the effective and active portion of the activated sludge process that ensures that there is adequate quantity of viable biomass available to degrade the supplied quantity of organic pollutants at any time. This is termed as Food to Microorganism Ratio (F/M Ratio) or food to mass ratio. If this ratio is kept at the suitable level, then the biomass will be able to consume high quantities of the food, which reduces the loss of residual food in the discharge. In other words, the more the biomass consumes food the lower the BOD will be in the treated effluent. It is important that MLSS eliminates BOD in order to purify the wastewater for further usage and hygiene. Raw sewage is introduced into the wastewater treatment process with a concentration of several hundred mg L-1 of BOD. The concentration of BOD in wastewater is reduced to less than 2 mg L-1 after being treated with MLSS and other treatment methods, which is considered to be safe water to use.

Figure 23.

Activated sludge [15].

\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t
\n\t\t\t\tSpecification\n\t\t\t\n\t\t\t\tValue\n\t\t\t\n\t\t\t\tUnit\n\t\t\t
BOD-Sludge Loading0.40mg L-1\n\t\t\t
BOD-Volume Loading0.20mg L-1\n\t\t\t
MLSS2000mg L-1\n\t\t\t
COD of Influent300mg L-1\n\t\t\t
Amount of Influent4.48L d-1\n\t\t\t
Aeration Rate3.00L min-1\n\t\t\t

Table 2.

Conventional activated sludge [15].

The biological treatment process is the most commonly implemented method for the treatment of domestic sewage. This method implements bacterial populations that possess superior sedimentation characteristics. The living microorganisms break down the organic matter in the wastewater and consequently purify the wastewater from biological waste [15].

According to [1], the main components of all activated sludge systems are:

  1. The bioreactor: it can be a lagoon, tank, or ditch. The main characteristic of a bioreactor is that it contains sufficiently aerated and mixed contents. The bioreactor is also known as the aeration tank.

  2. Activated sludge: it is the bacterial biomass inside the bioreactor that consists mostly of bacteria and other flora and microfauna. The sludge is a flocculent suspension of these microorganisms and is usually termed as the mixed liquor suspended solids (MLSS) that ranges between 2,000 and 5,000 mg L-1.

  3. Aeration and mixing system: the aeration and mixing of the activated sludge and the raw influent are necessary. While these processes can be accomplished separately, they are usually conducted using a single system of either surface aeration or diffused air.

  4. Sedimentation tank: clarification or settlement of the activated sludge discharged from the aeration tank is essential. This separates the bacterial biomass from the treated wastewater.

  5. Returned sludge: the settled activated sludge in the sedimentation tank is returned to the bioreactor to maintain the microbial population at a required concentration to guarantee persistence of treatment process.

Several parameters should be considered while operating activated sludge plants. The most important parameters are: (1) biomass control, (2) plant loading, (3) sludge settleability, and (4) sludge activity. The main operational variable is the aeration, where its major functions are: (1) ensuring a sufficient and continuous supply of dissolved oxygen (DO) for the bacterial population, (2) keeping the bacteria and the biomass suspended, and (3) mixing the influent wastewater with the biomass and removing from the solution the excessive CO2 resulting from oxidation of organic matter [1].

There are several types of activated sludge processes, e.g., conventional activated sludge plant (Figure 24), complete mix plant (Figure 25), contact stabilization plant (Figure 26), and step aeration plant (Figure 27). Figure 28 shows the food pyramid that represents the feeding relationships within the activated sludge process.

Figure 24.

Conventional activated sludge plant [3].

Figure 25.

Complete mix plant [3].

Figure 26.

Contact stabilization plant [3].

Figure 27.

Step aeration plant [3].

Figure 28.

Food pyramid illustrating the feeding relationships within the activated sludge process [1].

4.4.5. Biological filters

The main systems of operation of biological filters are: (a) single filtration, (b) recirculation, (c) ADF, and (d) two-stage filtration with high-rate primary biotower (Figure 29). There are several types of biological filters, for example, submerged aerated filters that are widely known as biological aerated filters (BAFs) and are the commonly implemented design (Figure 30), and the percolating (trickling) filters (Figure 31). The BAFs implement either the sunken granular media with upward (Figure 30a) or download (Figure 30b) flows, or floating granular media with upward flow (Figure 30c), which is the most common design of BAFs. In order to compare the biological filters and the activated sludge systems (Figures 31 and 32), the comparison is based on the oxidation that can be accomplished by three processes:

  1. Spreading the wastewater into a thin film of liquid with a large surface area, consequently the required oxygen can be supplied by gaseous diffusion, which is the case of the percolating filters.

  2. Aerating the wastewater by pumping air in the form of bubbles or stirring forcefully, which is the case of the activated sludge process.

  3. Implementing algae to produce oxygen by photosynthesis, which is the case of the stabilization ponds.

Figure 29.

The main systems of operation of biological filters [1].

Figure 30.

Biological aerated filters [1].

Figure 31.

Relationship between the natural bacterial populations in rivers and the development of (A) trickling (percolating) filter and (B) activated sludge system [1].

Figure 32.

Comparison of the food chain pyramids for biological filters and activated sludge systems [1].

4.4.6. Rotating biological contactors

The rotating biological contactors (RBC) system (Figure 33) can be implemented to amend and improve the available treatment processes as the secondary or tertiary treatment processes. The RBC is successfully implemented in all three steps of the biological treatment, which are BOD5 removal, nitrification, and denitrification. The process is a fixed-biofilm of either aerobic or anaerobic biological treatment system for removal of nitrogenous and carbonaceous compounds from wastewater (Figure 34). The RBC installations (Figure 35) were designed for removal of BOD5 or ammonia nitrogen (NH3-N), or both, from wastewater [1, 2].

Figure 33.

Schematic diagram of air-drive RBC [2].

The RBC consists of media, shaft, drive, bearings, and cover (Figure 34). The RBC hardware consists of a large diameter and closely spaced circular plastic media that is mounted on a horizontal shaft supported by bearings and is slowly rotated by an electric motor. The plastic media are made of corrugated polystyrene or polyethylene material with different designs, dimensions, and densities. The model designs are based on increasing surface area and firmness, allowing a winding wastewater flow path and stimulating air turbulence [1, 2].

Figure 34.

Mechanism of attached growth media in an RBC system [2].

Figure 35.

RBC system [1].

4.4.7. Biological removal of nutrients

4.4.7.1. Biological phosphorous removal

It is widely agreed that microorganisms utilize acetate and fatty acids to accumulate polyphosphates as poly-β-hydroxybutyrate, which is an acid polymer. The precise mechanism is based on the production and regeneration of adenosine diphosphate (ADP) within the bacteria, and it involves the adenosine triphosphate (ATP). Phosphate removal requires true anaerobic conditions, which occur only when there is no other oxygen donor [3]. Figure 36 shows a phosphate removal process. This process needs long narrow tanks for maintenance of plug flow.

Figure 36.

Phosphate removal process [3].

4.4.7.2. Biological removal of nitrogen

The nitrification and denitrification processes are responsible for N2O production (Figure 37). Figure 38 shows a nitrification/denitrification system for biological removal of nitrogen.

Figure 37.

Schematic illustration of nitrification and denitrification processes that are responsible for N2O release [16].

Figure 38.

Nitrification/denitrification system for biological removal of nitrogen [3].

4.4.8. Phytoremediation

Phytoremediation is a treatment process that solves environmental problems by implementing plants that abate environmental pollution without excavating the pollutants and disposing them elsewhere. Phytoremediation is the abatement of pollutant concentrations in contaminated soils or water using plants that are able to accumulate, degrade, or eliminate heavy metals, pesticides, solvents, explosives, crude oils and its derivatives, and a multitude of other contaminants and pollutants from water and soils. Figures 39 through 44 show the designs of constructed wetlands where the phytoremediation takes place.

Figure 39.

Cross-sectional view of a typical subsurface flow constructed wetland [17].

Figure 40.

Components of a horizontal flow reed bed: (1) drainage zone consisting of large rocks, (2) drainage tube of treated effluent, (3) root zone, (4) impermeable liner, (5) soil or gravel, (6) wastewater distribution system, and (7) reeds [1].

Figure 41.

Free water surface system [18].

Figure 42.

Sub-surface flow system [18].

Figure 43.

Components of a free water surface constructed wetland [2].

Figure 44.

Components of a vegetated submerged bed system [2].

The incorporation of heavy metals, such as mercury, into the food chain may be a deteriorating matter. Phytoremediation is useful in these situations, where natural plants or transgenic plants are able to phytodegrade and phytoaccumulate these toxic contaminants in their above-ground parts, which will be then harvested for extraction. The heavy metals in the harvested biomass can be further concentrated by incineration and recycled for industrial implementation. Rhizofiltration is a sort of phytoremediation that involves filtering wastewater through a mass of roots to remove toxic substances or excess nutrients. Phytoaccumulation or phytoextraction implements plants or algae to remove pollutants and contaminants from wastewater into plant biomass that can be harvested. Organisms that accumulate over than usual amounts of pollutants from soils are termed hyperaccumulators, where a multitude of tables that show the different hyperaccumulators are available and should be referred to. In the case of organic pollutants, such as pesticides, explosives, solvents, industrial chemicals, and other xenobiotic substances, certain plants render these substances non-toxic by their metabolism and this process is called phytotransformation. In other cases, microorganisms that live in symbiosis with plant roots are able to metabolize these pollutants in wastewater. Figure 45 shows the tissues where the rhizofiltration, phytodegradation, and phytoaccumulation take place.

Figure 45.

Rhizofiltration, phytodegradation, and phytoaccumulation [19].

4.4.9. Vermifiltration

Vermiculture, or worm farming, is the implementation of some species of earthworm, such as Eisenia fetida (known as red wiggler, brandling, or manure worm) and Lumbricus rubellus, to make vermicompost, also known as worm compost, vermicast, worm castings, worm humus, or worm manure, which is the end-product of the breakdown of organic matter and considered to be a nutrient-rich biofertilizer and soil conditioner. Vermiculture can be implemented to transform livestock manure, food leftovers, and organic matters into a nutrient-rich biofertilizer.

The potential use of earthworms to break down and manage sewage sludge began in the late 1970s [20] and was termed vermicomposting. The introduction of earthworms to the filtration systems, termed vermifiltration systems, was advocated by José Toha in 1992 [21]. Vermifilter is widely used to treat wastewater, and appeared to have high treatment efficiency, including synchronous stabilization of wastewater and sludge [22, 23, 24]. Vermifiltration is a feasible treatment method to reduce and stabilize liquid-state sewage sludge under optimal conditions [24, 25, 26]. Vermicomposting involves the joint action of earthworms and microorganisms [24, 27, 28], and significantly enhances the breakdown of sludge. Earthworms operate as mechanical blenders and by comminuting the organic matter they modify its physical and chemical composition, steadily decreasing the C:N ratio, increasing the surface area exposed to microorganisms, and making it much more suitable for bacterial activity and further breakdown. Throughout the passageway is the earthworm gut, they move fragments and bacteria-rich excrements, consequently homogenizing the organic matter [29]. An intensified bacterial diversity was found in vermifilter, compared with conventional biofilter without earthworms [25]. The principle of using earthworms to treat sewage sludge is based on the perception that there is a net loss of biomass and energy when the food chain is extended [25]. Compared to other technologies of liquid-state sludge stabilization, such as anaerobic digestion and aerobic digestion [30], vermifiltration is a low-cost and an ecologically sound technique, and more suitable for sewage sludge treatment of small or developing-countries\' WWTPs [23, 24, 25, 26, 31]. Figure 46 illustrates schematic diagram of a vermifilter, where the earthworms are in the filter bed.

Figure 46.

Schematic diagram of a vermifilter [24].

An important application is in livestock manure treatment as shown in Figure 47, where manure is flushed out from the livestock building to a raw effluent tank then the raw effluent is screened to separate the solid waste from manure. The screened effluent is then introduced to the vermifilter to produce the vermicompost. The vermifiltered effluent is then stored in a sedimentation tank. Afterwards, the vermifiltered effluent is introduced to constructed wetlands where the phytoremediation process takes place. The purified water can be then used to flush the water from the livestock building.

Figure 47.

Schematic diagram of a manure treatment system containing vermifiltration and phytoremediation processes (Amended and redrawn from Morand et al. [32]).

4.4.10. Microbial fuel cells

The microbial fuel cells (MFCs) allow bacteria to grow on the anode by oxidizing the organic matter that result in releasing electrons. The cathode is sparked with air to provide dissolved oxygen for the reaction of electrons, protons, and oxygen on the cathode, which result in completing the electrical circuit and producing electrical energy (Figure 48).

Figure 48.

Schematic diagram of the essential components of an MFC [33].

5. Chemical treatment of wastewater

5.1. Chemical precipitation

The dissolved inorganic components can be removed by adding an acid or alkali, by changing the temperature, or by precipitation as a solid. The precipitate can be removed by sedimentation, flotation, or other solid removal processes [1]. Although chemical precipitation (coagulation, flocculation) is still implemented, it is highly recommended to substitute the chemical precipitation process by phytoremediation (see previous section), where the trend is to ramp up the implementation of bioremediation and phytoremediation to reduce the use of chemicals, which is in line with the “Green Development”.

5.2. Neutralization

Neutralization is controlling the pH of the wastewater whether it is acidic or alkaline to keep the pH around 7. The lack of sufficient alkalinity will require the addition of a base (Table 3) to adjust the pH to the acceptable range. Lime (CaO), calcium hydroxide (Ca(OH)2), sodium hydroxide (NaOH), and sodium carbonate (Na2CO3), also known as soda ash, are the most common chemicals used to adjust the pH [34]. The lack of sufficient acidity will require the addition of an acid to adjust the pH to the acceptable range. Sulfuric acid (H2SO4) and carbonic acid (H2CO3) are the most common chemicals used to adjust the pH.

\n\t\t\n\t\t\n\t\t\t\n\t\t\n\t
\n\t\t\t\t\n\t\t\t

Table 3.

Neutralization: Case of acidic wastewater [34].

Note: a stoichiometric reaction will yield a pH of 7.0


5.3. Adsorption

Adsorption is a physical process where soluble molecules (adsorbate) are removed by attachment to the surface of a solid substrate (adsorbent). Adsorbents should have an extremely high specific surface area. Examples of adsorbents include activated alumina, clay colloids, hydroxides, resins, and activated carbon. The surface of the adsorbent should be free of adsorbate. Therefore, the adsorbent should be activated before use. A wide range of organic materials can be removed by adsorption, including detergents and toxic compounds. The most widely used adsorbent is activated carbon, which can be produced by pyrolytic carbonization of biomass [1]. Figure 49 illustrates the difference between absorption and adsorption. Activated carbon is the most implemented adsorbent and is a sort of carbon processed to be riddled with small, low-volume pores that enlarge the surface area available for adsorption. Owing to its high level of microporosity, 1 g of activated carbon has a surface area larger than 500 m2, which was determined by gas adsorption. Figure 50 shows a bed carbon adsorption unit. Note that the carbon can be regenerated by thermal oxidation or steam oxidation and reused. The adsorption capacity, one of the most important characteristics of an adsorbent, can be calculated as follows:

AdsorptionCapacitymg/g=Adsorbatemg/AdsorbentgBB3
\n\t\t\t\t

The factors that affect adsorption are [3]:

  1. Particle diameter: the adsorption is inversely proportional to the particle size of the adsorbent, and directly proportional to surface area.

  2. Adsorbate concentration: the adsorption is directly proportional to adsorbate concentration.

  3. Temperature: the adsorption is directly proportional to temperature.

  4. Molecular weight: generally, the adsorption is inversely proportional to molecular weight depending upon the compound weight and configuration of pores diffusion control.

  5. pH: the adsorption is inversely proportional to pH due to surface charge.

  6. Individual properties of adsorbate and adsorbent are difficult to compare.

  7. Iodine number: is the mass of iodine (g) that is consumed by 100 g of a substance.

Figure 49.

A comparison between absorption and adsorption.

Figure 50.

A bed carbon adsorption unit [35].

5.4. Disinfection

The disinfection of wastewater is the last treatment step of the tertiary treatment process. Disinfection is a chemical treatment process conducted by treating the effluent with the selected disinfectant to exterminate or at least inactivate the pathogens. The rationales behind effluent disinfection are to protect public health by exterminating or inactivating the pathogens such as microbes, viruses, and protozoan, and to meet the wastewater discharge standards. The purpose of disinfection is the protection of the microbial wastewater quality. The ideal disinfectant should have bacterial toxicity, is inexpensive, not dangerous to handle, and should have reliable means of detecting the presence of a residual. The chemical disinfection agents include chlorine, ozone, ultraviolet radiation, chlorine dioxide, and bromine [3].

5.4.1. Chlorine

Chlorine is one of the oldest disinfection agents used, which is one of the safest and most reliable. It has extremely good properties, which conform to the aspects of the ideal disinfectant. Effective chlorine disinfection depends upon its chemical form in wastewater. The influencing factors are pH, temperature, and organic content in the wastewater [3]. When chlorine gas is dissolved in wastewater, it rapidly hydrolyzes to hydrochloric acid (HCl) and hypochlorous acid (HOCl) as shown in the following chemical equation:

Cl2+H2OH++Cl-+HOClBB4
\n\t\t\t\t\t

Free ammonia combines with the HOCl form of chlorine to form chloramines in a three-step reaction, as follows:

NH3+HOClNH2Cl+H2ONH2Cl+HOClNHCl2+H2ONHCL2+HOClNCl3+H2OBB5
\n\t\t\t\t\t

Figure 51 illustrates the chlorination curve, where the formation of chloramines occurs at the breakpoint. The free chlorine residual first rises then falls until the reaction with ammonia has been completed. As additional chlorine is applied and ammonia is consumed, the chlorine residual rises again.

Figure 51.

Chlorination curve [3].

Dechlorination is a very important process, where activated carbon, sulfur compounds, hydrogen sulfide, and ammonia can be implemented to minimize the residual chlorine in a disinfected effluent prior to discharge. Activated carbon and sulfur compounds are the most widely used [3]. The commonly used sulfur compounds are sulfur dioxide (SO2), sodium metabisulfite (NaS2O5), sodium bisulfate (NaHSO3), and sodium sulfite (Na2SO3). The dechlorination reactions with the abovementioned compounds are described in the following equations:

SO2+2H2O+Cl2H2SO4+2HClSO2+H2O+HOCl3H++Cl-+SO42-Na2S2O5+2Cl2+3H2O2NaHSO4+4HClNaHSO3+H2O+Cl2NaHSO4+2HClBB6
\n\t\t\t\t

5.4.2. Ozone

Ozone (O3) is a very strong oxidant typically used in wastewater treatment. Ozone is able to oxidize a multitude of organic and inorganic compounds in wastewater. These reactions cause an ozone demand in the treated wastewater, which should be fulfilled throughout wastewater ozonation prior to developing an assessable residual. Ozone should be generated at the point of application for use in wastewater treatment as ozone is an unstable molecule [3]. Figure 52 illustrates the corona discharge method for making ozone. Ozone is generally formed by combining an oxygen atom with an oxygen molecule (O2) as follows:

Figure 52.

Schematic drawing of corona discharge method for making ozone [3].

5.4.3. Ultraviolet light

Ultraviolet (UV) radiation is a microbial disinfectant that leaves no residual. It requires clear, un-turbid, and non-colored water for its implementation. The commercial UV disinfection systems use low- to medium-powered UV lamps with a wavelength of 354 nm [3]. The UV dosage can be calculated as follows:

D=ItBB7
\n\t\t\t\t\t

where, D is the UV dose (mW. s/cm2); I is the intensity (mW/cm2); and t is the exposure time (s).

The advantages of UV radiation are: (1) directly effective against the DNA of many microorganisms, (2) not reactive with other forms of carbonaceous demand, and (3) provides superior bactericidal kill values while not leaving any residues. The advantage is often the disadvantage, because power fluctuations, variations in hydraulic flow rates, and color or turbidity can cause the treatment to be ineffective [3]. Additionally, cell recovery and re-growth of the damaged organisms because of the inactivation of their predators and competitors has come to light.

5.5. Ion exchange

Ion exchange (IX) is a reversible reaction in which a charged ion in a solution is exchanged with a similarly charged ion which is electrostatically attached to an immobile solid particle. The most common implementation of ion exchange method in wastewater treatment is for softening, where polyvalent cations (e.g., calcium and magnesium) are exchanged with sodium [36]. Practically, wastewater is introduced into a bed of resin. The resin is manufactured by converting a polymerization of organic compounds into a porous matrix. Typically, sodium is exchanged with cations in the solution [34]. The bed is shut down when it becomes saturated with the exchanged ions, where it should be regenerated by passing a concentrated solution of sodium back through the bed. Figure 53 shows the schematic illustration of organic cation-exchange bead. Figure 54 shows a typical ion exchange resin column. Table 4 shows the ion preference and affinity for some selected compounds.

Figure 53.

Schematic illustration of organic cation-exchange bead [34].

Figure 54.

Typical ion exchange resin column [37].

\n\t\t\n\t\t\n\t\t\t\n\t\t\n\t
\n\t\t\t\t\n\t\t\t

Table 4.

Ion preference and affinity for some selected compounds [3].

5.6. Physicochemical treatment processes

The principal advanced physicochemical wastewater treatment processes are elucidated in Table 5.

\n\t\t\n\t\t\n\t\t\t\n\t\t\n\t
\n\t\t\t\t\n\t\t\t

Table 5.

Principal advanced physicochemical wastewater treatment processes [1].

6. Wastewater treatment plants

This section shows some examples of WWTPs as shown in Figure 55 (a, b, and c) and Figure 56. On the other hand, there are some computer programs for planning and designing WWTPs (Figures 57, 58, and 59).

Figure 55.

WWTP showing: (a) layout of the plant, (b) wastewater process flow diagrams, and (c) sludge process flow diagram. Wastewater treatment: 1. Storm water overflow; 2. screening; 3. grit removal; 4. primary sedimentation; 5. aeration tanks; 6. Secondary sedimentation; 7. emergency chlorination; 8. filtration; 9. effluent outfall. Sludge treatment: 10. raw sludge thickeners; 11. digestion tanks; 12. digested sludge thickeners; 13. power house; 14. biogas storage; 15. filter press house; 16. transformer station. A and B are administrative areas [1].

Figure 56.

Summary of the main process options commonly employed at both domestic and industrial WWTPs. Not all of these unit processes may be selected, but the order of their use remains the same [1].

Figure 57.

Screenshot of the STEADY program [3].

Figure 58.

WEST software typical plant configuration [3].

Figure 59.

WEST configuration for multitank system [3].

7. Conclusions

According to this study, it can be conclude that:

  1. The trend is to ramp up the implementation of bioremediation, phytoremediation, and mycoremediation to reduce the use of chemicals, which is in line with the “Green Development”.

  2. The recent developments elucidate that subsequent to the physical treatment processes (the primary treatment) the biological treatment processes come in turn as secondary treatment and precede the chemical treatment processes, which constitute the tertiary treatment.

  3. Microbial fuel cells, phytoremediation, and mycoremediation are the focus of the future development in this field.

\n',keywords:"Wastewater treatment, biological treatment, chemical treatment, bioremediation, phytoremediation, mycoremediation, vermifiltration, treatment plant",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/49024.pdf",chapterXML:"https://mts.intechopen.com/source/xml/49024.xml",downloadPdfUrl:"/chapter/pdf-download/49024",previewPdfUrl:"/chapter/pdf-preview/49024",totalDownloads:27734,totalViews:16725,totalCrossrefCites:55,totalDimensionsCites:103,totalAltmetricsMentions:1,impactScore:37,impactScorePercentile:100,impactScoreQuartile:4,hasAltmetrics:1,dateSubmitted:"December 2nd 2014",dateReviewed:"July 23rd 2015",datePrePublished:null,datePublished:"October 14th 2015",dateFinished:"August 25th 2015",readingETA:"0",abstract:"This chapter elucidates the technologies of biological and chemical wastewater treatment processes. The presented biological wastewater treatment processes include: (1) bioremediation of wastewater that includes aerobic treatment (oxidation ponds, aeration lagoons, aerobic bioreactors, activated sludge, percolating or trickling filters, biological filters, rotating biological contactors, biological removal of nutrients) and anaerobic treatment (anaerobic bioreactors, anaerobic lagoons); (2) phytoremediation of wastewater that includes constructed wetlands, rhizofiltration, rhizodegradation, phytodegradation, phytoaccumulation, phytotransformation, and hyperaccumulators; and (3) mycoremediation of wastewater. The discussed chemical wastewater treatment processes include chemical precipitation (coagulation, flocculation), ion exchange, neutralization, adsorption, and disinfection (chlorination/dechlorination, ozone, UV light). Additionally, this chapter elucidates and illustrates the wastewater treatment plants in terms of plant sizing, plant layout, plant design, and plant location.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/49024",risUrl:"/chapter/ris/49024",book:{id:"4619",slug:"wastewater-treatment-engineering"},signatures:"Mohamed Samer",authors:[{id:"175050",title:"Prof.",name:"Mohamed",middleName:null,surname:"Samer",fullName:"Mohamed Samer",slug:"mohamed-samer",email:"msamer@agr.cu.edu.eg",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/175050/images/system/175050.jpeg",institution:{name:"Cairo University",institutionURL:null,country:{name:"Egypt"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Chapter description and contents overview",level:"1"},{id:"sec_3",title:"3. Overview",level:"1"},{id:"sec_3_2",title:"3.1. Wastewater treatment techniques",level:"2"},{id:"sec_4_2",title:"3.2. Aims of wastewater treatment",level:"2"},{id:"sec_5_2",title:"3.3. Biological treatment processes",level:"2"},{id:"sec_5_3",title:"3.3.1. Useful terms",level:"3"},{id:"sec_7_2",title:"3.4. Chemical treatment processes",level:"2"},{id:"sec_9",title:"4. Biological treatment of wastewater",level:"1"},{id:"sec_9_2",title:"4.1. Biological growth equation",level:"2"},{id:"sec_10_2",title:"4.2. Bacterial kinetics",level:"2"},{id:"sec_11_2",title:"4.3. Principles of biological treatment",level:"2"},{id:"sec_12_2",title:"4.4. Bioremediation of wastewater",level:"2"},{id:"sec_12_3",title:"4.4.1. Aerobic treatment",level:"3"},{id:"sec_12_4",title:"4.4.1.1. Oxidation ponds",level:"4"},{id:"sec_13_4",title:"4.4.1.2. Aeration lagoons",level:"4"},{id:"sec_15_3",title:"Table 1.",level:"3"},{id:"sec_15_4",title:"Table 1.",level:"4"},{id:"sec_16_4",title:"4.4.2.2. Anaerobic lagoons",level:"4"},{id:"sec_18_3",title:"4.4.3. Bioreactors",level:"3"},{id:"sec_19_3",title:"Table 2.",level:"3"},{id:"sec_20_3",title:"4.4.5. Biological filters",level:"3"},{id:"sec_21_3",title:"4.4.6. Rotating biological contactors",level:"3"},{id:"sec_22_3",title:"4.4.7. Biological removal of nutrients",level:"3"},{id:"sec_22_4",title:"4.4.7.1. Biological phosphorous removal",level:"4"},{id:"sec_23_4",title:"4.4.7.2. Biological removal of nitrogen",level:"4"},{id:"sec_25_3",title:"4.4.8. Phytoremediation",level:"3"},{id:"sec_26_3",title:"4.4.9. Vermifiltration",level:"3"},{id:"sec_27_3",title:"4.4.10. Microbial fuel cells",level:"3"},{id:"sec_30",title:"5. Chemical treatment of wastewater",level:"1"},{id:"sec_30_2",title:"5.1. Chemical precipitation",level:"2"},{id:"sec_31_2",title:"5.2. Neutralization",level:"2"},{id:"sec_32_2",title:"5.3. Adsorption",level:"2"},{id:"sec_33_2",title:"5.4. Disinfection",level:"2"},{id:"sec_33_3",title:"5.4.1. Chlorine",level:"3"},{id:"sec_34_3",title:"5.4.2. Ozone",level:"3"},{id:"sec_35_3",title:"5.4.3. Ultraviolet light",level:"3"},{id:"sec_37_2",title:"5.5. Ion exchange",level:"2"},{id:"sec_38_2",title:"5.6. Physicochemical treatment processes",level:"2"},{id:"sec_40",title:"6. Wastewater treatment plants",level:"1"},{id:"sec_41",title:"7. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Gray N. F. (2005). Water Technology: An Introduction for Environmental Scientists and Engineers (2nd\n\t\t\t\t\tEdition), Elsevier Science & Technology Books, ISBN 0750666331, Amsterdam, The Netherlands.'},{id:"B2",body:'Lin, S. D. (2007). Water and Wastewater Calculations Manual (2nd\n\t\t\t\t\tEdition), McGraw-Hill Companies, Inc., ISBN 0-07-154266-3, New York, USA.'},{id:"B3",body:'Russell D. L. (2006). Practical Wastewater Treatment, John Wiley & Sons, Inc., ISBN-13: 978-0-471-78044-1, Hoboken, New Jersey, USA.'},{id:"B4",body:'Samer M. (2015). 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1. Introduction

Photonics, a field that aims at the study of generation, manipulation, and detection of light, has become essential in modern life. Photonic devices as all-optical switches and modulators play a key role in worldwide data optical communications or optical computing. Since the invention of lasers in the 1960s, there has been a huge increase in the use of devices that use photons (light) instead of electrons. In 1985, a research group of the Southampton University showed the potential of silica glass fibers doped with Er3+ ions for applications in long optical transmission systems, at the wavelength region of 1.55 μm, without the need of electronic repeaters [1]. The invention of the erbium-doped fiber amplifier (EDFA) was a key factor in enabling the transmission of long-distance data through silica fiber. The 1.55 μm optical waveband falls in the low-loss transmission window of silica fiber and the amplification band of EDFA’s. Sadly, they are still restricted to amplification in the C and L bands. Therefore, optical fibers using linear near-infrared light transmission are only a small fraction of what can be exploited by extending the operating region to the mid- and far-infrared. In fact, silica optical fibers have a non-negligible attenuation of the emitted signal, so if the range of transparency were extended to longer wavelengths, it would have less attenuation. Hence, transparent glasses in the mid and far-infrared wavelength range are well suited to long-distance communication systems due to the Rayleigh dispersion attenuation coefficient varying with λ−4. Nowadays, almost all data flow, including internet, phone calls, etc., goes through fiber optic transmission lines [2] and the field of communications continues to expand to higher data rates and shorter delays to allow more capacity. The demands of the modern world are looking for high-speed communication and therefore it is expected that an overload of data traffic may occur in the telecommunications window that currently operates in the C and L bands. Therefore, an expansion to a wider bandwidth is required which would facilitate data transmission and new amplification materials are needed beyond EDFA’s to provide amplification over the optical fiber. This requires overcoming the limitation of peak water absorption around 1.4 μm. All wave fiber was the first to be designed for optical transmission across the entire telecommunications window from 1.3 μm to 1.67 μm (Figure 1) [3]. On the other hand, rare-earth (RE) have low solubility in silica glass which limits the interaction length of active devices based on RE doped silica [4]. Besides, silica has high phonon energy which implies that the RE ions transitions will decay non-radiatively; also exhibit a low nonlinear refractive index and so, nonlinear devices based on silica will require high intensities to operate. Finally, silica has a high transmission loss at wavelengths above 2 μm [3].

Figure 1.

Loss of standard and all wave silica fibers showing the region of minimum attenuation and the six conventional bands of optical telecommunications [3].

The necessary increase in the bandwidth excludes the use of EDFA’s, leaving fiber Raman amplifiers as the main devices used for that proposes [5]. In fact, amplifiers based on stimulated Raman scattering and four-wave mixing offer additional advantages over EDFAs [6], operate without the need for doping, and can be used at any spectral region [7]. Moreover, the wavelength of the pump laser can be chosen to give a maximum gain at any wavelength range (S, C, or L-band), and the gain bandwidth is higher than that offered by EDFA’s (> 100 nm versus 35 nm), which can be enlarged by an appropriate choice of the material [6]. On the other hand, fiber Raman lasers are excellent options for high-power fiber lasers, mainly because of their high output power and broad gain bandwidth, especially in the near-infrared region.

Although silica is widely used in the near-infrared, it limits the wavelength operating range. To overcome these limitations new glasses for optical device applications and photonics have been investigated. These include heavy metal oxide, fluoride, and chalcogenide glasses.

Glasses containing chalcogenides are the basis for the manufacture of devices operating in the mid-infrared region. In addition, glasses based on heavy metal oxides, such as Sb, Bi, Pb, W, Ga, Ge, Te, allow applications such as optical switches, due to their characteristics of low linear and nonlinear loss, large Kerr nonlinearity, and ultra-fast response. Fluoride-based glasses are used as optical amplifiers in telecommunication as well as in the manufacture of lasers.

Photonics is also used in medical applications, such as lasers used for LASIK surgery, and biomedical diagnostics exploit optical components for bioimaging. Integrated photonics also enables the advance of computing, information technology, sensing, and communications. The integration on a simply planar substrate of several photonic devices (optical sources, beam splitters, couplers, waveguides, detectors, etc.), as proposed by Miller in 1964 [8], enables the control of light on a significantly reduced scale where components are expected to exhibit a very reduced size and achieving a multiplicity of functions, including splitting, combining, switching, amplifying, and modulating signals. Many of these functions are nonlinear. For example, fiber nonlinearities are the basis of several devices such as amplifiers and switching. These nonlinear effects can be divided into two types. The first type is owing to the Kerr-effect (or intensity dependence of the refractive index of the material), which in turn can display phase modulation and wave mixing, depending upon the type of input signal. The second type is related to the inelastic-scattering phenomenon, which can induce stimulating effects such as stimulated Brillouin-Scattering and stimulated Raman-Scattering [9].

NLO is an important issue of advanced photonics and enables technical development in many fields including optical signal processing and quantum optics. It refers to the study of phenomena that occur due to modifications in the optical properties of a material in the presence of light. However, only laser light has sufficient intensity to promote these changes. Indeed, nonlinear optical phenomena (e.g. multiphoton absorption, harmonic generation, self-focusing, self-phase modulation, optical bistability, stimulated Brillouin scattering, and stimulated Raman scattering) require high electromagnetic field intensities to manifest.

2. Basic principles of NLO

In the linear optical domain, photons interact with the glass structure leading to various optical effects, such as dispersion, refraction, reflection, absorption, diffraction, and scattering. For example, the linear refractive index of a material, n, describes how light propagates through it, and the index defines how much light is bent, or refracted when it across the material. However, these properties may become nonlinear if the intensity is high enough to modify the glass optical properties, resulting in the creation of new beam lights of different wavelengths.

A nonlinear optical behavior is a deviation from the linear interaction between a material’s polarization response and the electric component of an applied electromagnetic field [10]. This phenomenon involves various optical exchanges such as frequency doubling, conversion, data transformation, etc. Because the magnetic component of light can be ignored in a glass (photons and magnetic fields usually do not interact), the electric component (E) becomes the main field that interacts with the medium. The polarization (P) induced by this interaction produces nonlinear responses that can be explained due to the distortion/deflection of the electronic structure of any atom or molecule (deformation of the electron cloud) due to the application of the electric field, thus producing a resulting dipole moment (vector that separates the positive and negative charges).

Once an external E field is applied to the material the positive charges tend to move in the opposite direction of the electrons. This interaction causes a charge separation that gives rise to microscopic dipole moments within the material. Under the influence of an electric field, these dipoles oscillate at the same frequency (ω) of the incident light. The sum of all the microscopic dipoles of the medium oscillating with time gives rise to material polarization. At low light intensities, Hook’s law is valid and the deformation of the electrons cloud is proportional to the applied field strength of the incident light: the light waves and excited electrons oscillate sinusoidally. The induced polarization is also oscillatory and is directly proportional to the incident electric field, as described by:

P=ε0χ1EE1

where ε0 is the vacuum permittivity and χ1 (or χ) is the linear susceptibility, which, in this case, depends on the frequency, and thus is directly linked to the linear refractive index, but does not depend on the amplitude of the electric field, which implies that the frequency of light does not change as it passes through matter. However, at high intensities, the electrons are extremely deflected from their orbit, and their movements become distorted giving rise to important deviation from harmonic oscillation. As a result, the amplitude of dipoles oscillation increases, and they emit light not only at the wavelength that excites them but in other frequencies (new color!!!) (Figure 2) [11]. At large intensities, P is a nonlinear function of E whereas, at low intensities, the interaction is a linear function. So, for materials with nonlinear characteristics, in which the polarization given by the Eq. (1) is no longer valid, P must be written in a more general form, as a power series of E:

Figure 2.

(a) Linear optics, a light wave acts on the material constituents, which vibrates and then emits its own light wave that interferes with the original light wave, (b) nonlinear optics. Adapted from [11].

P=ε0χ1E1+χ2E2+χ3E3+E2

where the values of χ(2) and χ(3), are, respectively, the second-order and third-order susceptibilities which appear due to the nonlinear response of charged particles and are determined by the symmetry properties of the medium. Consequently, nonlinear refractive index (n2), second (𝜒 (2)), and third-order (𝜒 (3)) nonlinear susceptibilities can be measured. In isotropic, nondispersive, and homogeneous mediums, the material susceptibilities can be considered constants. However, in anisotropic media where properties are directionally dependent, the susceptibilities of the material are tensor quantities and therefore, depend on the microscopic structure (electronic e nuclear) of the material [12].

Considering the relations n2=1+χ1, c=1ε0μ0, and n=cc0, where n represents the linear refractive index, c is the speed of light in vacuum, c0 the speed of light in the material, and μ0 the vacuum permeability; Maxwell’s equations can be used to obtain the wave equations in a nonlinear material:

2E1+χε0μ0t2E=1ε0c2t2PE3

where the term t2P, represents a measure of the acceleration of the charges that constitute the material, which plays a fundamental role in the theory of nonlinear optics. This term acts as a source in the generation of new radiation field components, producing oscillating electric fields within a linear medium of refractive index n.

Assuming an external electric field of the type E(t) = Eexp(−iωt) + c.c, where c.c. denotes “complex conjugate”, the term related to second order polarization is given by:

P2=ε0χ2E2=2ε0χ2E2+ε0χ2E2exp2iωt+c.cE4

being responsible for the generation of a field with twice the frequency of the incident radiation (2ω), taking the designation of the second harmonic generation process. However, in centrosymmetric materials, or isotropic materials like glass, which have macroscopic inversion symmetry, the polarization must reverse when the optical electric field is reversed, which implies that χ(2) must be zero, i.e., all second-order components of the susceptibility tensor are null and GSH does not manifest unless the glass has been poled. It is possible to induce GSH in glasses to break its centrosymmetry, using heat treatments or high energy excitation in the UV [13]. But, without the use of this strategy to eliminate glass’s isotropy, only a χ(3) is ≠0 and may lead to NLO character in glass [10] and the dominant term in (2) is then the third order:

P3=ε0χ3E3E5

which will give rise to frequency tripled light, called third-harmonic generation (THG). According to (5) this nonlinear polarization contains a component of frequency ω and an additional one at 3ω:

P3=3ε0χ3E2EPω+ε0χ3EP3ωE6

The term P (3ω) shows that the THG of light is produced while the term P (ω) denotes an incremental change of the susceptibility (Δχ) at the frequency ω, given by:

ε0Δχ=PωE=3χ3E2=6nε0cχ3IE7

Where I is the intensity of the incident light that become significantly the value of χ(3). The χ(3), which gives the dependence of refraction on the intensity of the propagated optical beam, is responsible for the lowest order nonlinear effects in the glass as self-phase modulation and other parametric effects.

Since n2 = 1+ χ, Δχ is equivalent to an incremental change in the refractive index, Δn is an increase (or decrease) of the total refractive index due to nonlinear effects:

Δn=χn1Δχ=Δχ2n=3n2ε02cχ3I=n2IE8

where n2 is the nonlinear refractive. This change of the linear refractive index, n, is proportional to the light intensity, and therefore it becomes a linear function of I:

nI=n+n2IE9
n2=3n2ε02cχ3E10

The intensity-dependent refractive index is generally given as:

nI=n+n1E+n2E2E11

where n1 is the Pockel’s coefficient (insignificant for isotropic materials as glasses) and n2 is known as the Kerr coefficient (from the optical Kerr effect) [10]. However, the classical wave theory says that the intensity of the electric field of the light is equal to the square of its amplitude, and thus one can also write n(I) in the form of Eq. (9). The optical Kerr effect is very sensitive to the operating wavelength and polarization dependence and so the prevalent non-linearity occurs at a frequency well below the glass band gap and this effect is called non-resonant [10].

Typical values of the Kerr coefficient (in cm2/W) are 10−16 to 10−14 in transparent crystals and glasses. Silica glass (e.g. silica fibers), has an n2 index of 2.7 × 10−16 cm2/W at the wavelength of 1500 nm, whereas most of the chalcogenide glasses exhibit higher values, about several orders of magnitude larger than silica [14]. Since the values of the nonlinear refractive index in glasses are very small, resulting in a slight change of ∆n = n2I, the effect is measurable only for very intense light beams (lasers) of the order of 1GWcm−2. From Figure 3, it can be noted that n and n2 are usually directly correlated, such that high index (n) glasses, like chalcogenides, have also high n2 [16] and exhibit ultrahigh n2 greater than silica, as plotted in Figure 3.

Figure 3.

Nonlinear refractive index, n2, versus refractive index, n, for various glasses, and silica glasses. Adapted from [15].

For all-optical signal processing and switching devices, glasses with large n (hence a large n2) are very attractive. Figure 4 shows the relationship between the linear refractive index (n), and the third-order nonlinear optical susceptibility χ(3) of various types of glass. High index (n) glasses, like chalcogenide ones, have also high n2, which seem to have the largest non-resonant third-order optical non-linearities related so far. As previously mentioned, χ(3) arises from light-induced changes in the refraction index that result in the Kerr effect or in parametric interactions (mixing of optical beams). In a glass fiber, the third-order susceptibility is related to n2 by Eq. (10) and the magnitude of the corresponding nonlinear effect is given by:

Figure 4.

Relationship between linear refractive index and third-order optical susceptibility. Adapted from [17].

γ=2πλAeffn2E12

where λ is the free-space wavelength and Aeff is the efficient core area [6]. Since 1999, single-mode silica fibers with γ of 20 W−1 km−1 were fabricated [18] with a core that was only 10.7 μm2, but typical Aeff values in silica fibers can reach 50 μm2 for 1.5 μm wavelengths. The self-phase modulation is a phenomenon arising from the dependence between the refractive index of a nonlinear medium and the strength of the electric field, which induces a phase shift of the propagating light, φNL(z):

ϕNLz=γP0z=zLNLE13

where P0 is the input power and LNL is the non-linear length that corresponds to the propagation distance at which the phase modulation becomes relevant, being defined by:

LNL=γP01E14

If the input power is only 1 mW at λ =1.55 μm, and the Aeff = 50 μm2, the LNL is ∼500 m [6]. As the refractive index in silica is weakly dependent on power, nonlinearities are introduced into the signal propagation and significantly increase in optical networks over relevant distances.

The various nonlinearities can be expressed in terms of the real and imaginary parts of each of the nonlinear susceptibilities χ(1), χ(2), χ(3), … that appear in (2). The real part is associated with the refractive index and the imaginary part with a time or phase delay in the reply of the material, giving rise to loss or gain. Table 1 exhibits the principal third-order NLO effects usually showed by dielectric materials like most glasses. For example, the nuclear contribution to stimulated Raman scattering (resulting in loss or gain) can be expressed in terms of the imaginary part of a χ(3) susceptibility, while the four-wave mixing, which is only of electronic nature and almost an instantaneous effect, result in frequency conversion and in related to the real part of the χ(3) susceptibility [6]. The imaginary part of χ(3) provides a change in the absorption coefficient, α, as a function of light intensity:

Order Tensor Effect Description
3 χ(3)(−ω;ω,-0,0) Kerr’s effect Under the action of two electric fields, there is a change of the refractive index in the NLO medium.
3 χ(3)(−ω;ω,-ω,ω) Nonlinear refractive index also called Kerr’s effect, self-phase modulation. The refractive index of the medium changes with intensity according to the formula: n = n0 + n2I. Self-focusing and self-defocusing of a laser beam are special cases.
3 χ(3)(−3ω,ω,ω,ω) Third harmonic generation. There is an emission of light with triple frequency under the illumination of the medium.
3 χ(3)(−ω4123) Multiwave mixing. When illuminated with three light sources with different frequencies a generation of light occurs whose frequency equals the sum of the three excitation frequencies.

Table 1.

Third-order NLO effects are usually shown by dielectric materials. Adapted from [19].

αI=α0+βIE15

where α is the linear absorption, and β is the non-linear absorption coefficient. As a result, occurs a prevalence of non-linearities at frequencies above the electronic absorption edge is known as resonant. The third-order non-linearity may be analyzed in phase conjugate mirrors, like in Mach-Zehnder interferometer pulse selectors or in Fabry-Perot interferometers filled with a nonlinear medium.

The χ(3) susceptibility is often measured by degenerate four-wave mixing, by the maker fringe method (THG method), or by the Z-scan method. The latter is by far the most used and meticulous method involving the analysis of third-order nonlinear optical properties arising from pulsed laser or CW irradiation at a given wavelength [20].

3. Nonlinear optical properties of glass

Glass is defined as a solid material of amorphous (non-crystalline) structure while crystals possess long-range order, the amorphous materials only possess short-range order. Therefore, glasses are typically brittle and optically transparent because they lack internal structure. The silica-based glass was undoubtedly the most studied given its multiple applications. Glasses that do not include silica as a main constituent exhibit other properties that make them useful for various applications, for example in optical fibers that work in different frequency domains than SiO2 fibers. These include fluoride glasses, tellurite glasses, aluminosilicates, phosphate glasses, borate glasses, and chalcogenide glasses. Common glasses are transparent materials in the spectral range of the visible and near-infrared region, although opaque in the far IR and UV region. The visible transparency threshold ends, for high wavelengths (λ), with UV absorption, due to electronic transitions between valence band levels and unfilled conduction band levels. For applications in photonics, there are two main categories of special glasses: chalcogenide glasses (CGs) and heavy metal oxide glasses. Chalcogenide glasses are based on the chalcogen elements S, Se, and Te. These glasses are formed by the addition of other elements such as Ge, As, Sb, Ga, etc. Heavy metal oxide and chalcogenide glasses offer the largest nonlinear response.

Most of the glasses are prepared by the melt of precursors. In solid form, glass is a non-crystalline (or amorphous) material. The deposition from a liquid solution (sol–gel method) is an alternative approach to obtain glass, especially in films form. Some compositions may otherwise be rather difficult to prepare by melt and that’s why in practice this method is limited to a relatively small number of compositions. Therefore, the sol–gel processes allow the synthesis of glasses of extended composition ranges, allowing the fabrication of multiple oxide composition, but also non-oxide glasses, with a high degree of homogeneity, because reagents are mixed at the molecular level at temperatures lower than those required for conventional melting. However, the OH content of the sol–gel glasses is high and OH absorptions usually limit transmission at 1.4 μm.

Optical glasses are optically homogeneous glass that are applied in several optical functionalities. The first optical quality (flint) glasses were created at the end of the 19 century by Otto Schott, who also invented Ba crown glass, allowing the production of adjusted lenses for chromatic aberration [21]. X-ray diffraction (XRD) allows distinguishing a glass from a crystalline material. The pattern of SiO2 glass contains only a few, very broad peaks, which cannot be correlated by the Bragg law with planar distances (as in the case of crystals). SiO2 consists of a matrix of SiO4 tetrahedra (Figure 5) [22].

Figure 5.

A schematic representation of the structure of vitreous silica. The tetrahedral SiO4 units in silica are represented by triangular units [22].

The presence of a glass modifier together with the glass formers (SiO2 or P2O5) breaks up the oxide network M–O–M (M = Si, P) and drives the transformation of the bridging oxygens (BO) into nonbridging oxygens (NBOs). The structural unit of SiO2 has Si-O atomic bonds whose electronic transitions occur in the UV range. For high λ, the transparency threshold ends due to the vibrations of the ions in the network (in resonance with the incident radiation). The amorphous character of the glass explains the absence of grain boundaries in its structure and, therefore, the absence of internal dispersion and reflection phenomena, which are always present in crystalline materials. Glasses are dielectric materials and therefore exhibit a large energy gap between the valence band and the conduction band in accordance with the band theory of solids. Their optical transmission is limited by electronic transitions (Urbach tail) for low wavelength, and multiphonon absorption at high wavelength, in the IR spectrum. The multiphonon absorption process is related to the fundamental vibration frequencies of the glass.

The transmittance spectrum varies from glass to glass, but the main differences are observed outside the transparency range (Figure 6). The glass has an optical transparent window which strongly depends on the compositions. Glasses made for use in the visible region have high transmittance across the entire wavelength range of ∼400 nm–800 nm. However, the structure of silicate glasses limits its transmission in the infrared region to above 3 μm. They have strongly bound electrons but non-bridging oxygens, with their weakly bound electrons, reduce transmission. Chalcogenide glasses, heavy metal fluoride glasses, and heavy metal oxide glasses extend this transmission to higher wavelengths. The telluride glasses have larger atoms and weaker bonds than oxide glasses and so its vibrational resonance occurs at a lower frequency, shifting the fundamental absorption cut-off to longer wavelengths (Figure 6).

Figure 6.

Typical transmittance spectra of silica, fluorides, sulfide, selenide, and telluride glasses [23].

The interest in chalcogenide glasses backs from 1950s when was reported high infrared transparency of the As2S glass, up to 12 μm [24]. The structure of chalcogenide glasses such as Ge-Sb-Se consists of covalently bonded atoms, like amorphous SiO2, with lacking periodicity. They include sulfide, selenide, and telluride-based glasses. As dielectric materials, their optical transparent window is dependent on electronic absorption at low wavelengths and multiphonon absorption at high wavelengths. They have a band gap (Eg) that is dependent on the composition and decreases according to Sulfides < Selenides < Tellurides. A specificity of tellurides that differentiates it from the sulfides and selenides in its crystalline structure and physical properties is the large atomic number of Te. The energy gap may be taken from the glass absorption spectrum α(ħω) by extrapolating the linearized Tauc equation:

αħωħωEg1/2E16

The absorption coefficient, α, varies exponentially with the photon energy, ħω in the Urbach tail.

It is interesting to note that n and n2 and are usually directly correlated, such that low index (n) glasses, like certain fluorides and phosphates, have also low n2. On the other hand, a relationship between the material band gap and the n2 was also established. For example, the n2 value obtained for pure As2S3 was about 2.9 x 10−18 m2/W while for fused SiO2 was about 2.8 x 10−19 m2/W [25], which is comparatively about 10 times lower. So, materials with lower band gap seam to exhibit an increase in the nonlinear optical behavior; SiO2 has a gap of about 9 eV while that of As2S3 is 2.3 eV [19].

The increase of the nonlinear absorption coefficient (β), third-order nonlinear optical susceptibility (χ(3)), and nonlinear refractive index (n2) and decreasing the optical band gap (Eg) can be attributed to the formation of BO bonds and ions of higher polarizability in the glass matrix. It has been recognized the effect of the glass composition on the dependency of χ(3). In most multicomponent oxide glasses, there are both BO and NBO oxygens in the glass network (e.g. for a silicate glass, Si-O+Na). The NBO bonds possess larger n2 than the BO of the more covalent Si-O-Si bonds [26]. It was also established that third-order nonlinear optical susceptibility of the glasses increases with increasing optical basicity and tendency for metallization of the glasses. This fact is associated with the polarizability of the anions (F < O2− < S2− < Se2−) and the small optical band gap [19], which is related to the increasing metallicity of the oxides [27]. The theory of metallization of the condensed matter says that in the Lorentz–Lorenz equation, the refractive index becomes infinite when metallization of covalent solid materials occurs [27]. SiO2, B2O3, and GeO2 based glasses exhibit low refractive index and have low polarizability, large metallization tendency, and small χ(3). Tellurite and TiO2 based glasses, as well as B2O3 glasses containing a large amount of Sb2O3 and Bi2O3 with high refractive index, show large polarizability, small metallization tendency, and large χ(3) (Figure 7). Consequently, under the point of view of polarizability, high-refractive-index glasses with an increased tendency for metallization are promising materials for application as components of nonlinear optical devices.

Figure 7.

Line-up of the Kerr effect among various glass compositions [19].

Glass materials are excellent non-linear optical materials, being isotropic and transparent in a wide spectral range, combining low cost of fabrication with high optical quality, manufacturable not only as bulk shapes, or fibers, but also as thin films (e.g. nonlinear planar waveguides). Furthermore, when compared to polymers, glass is more stable and has the advantage over crystals since its atomic composition is easily tailored: a nonlinear optical glass can be obtained with any refractive index in a wide range [28]. Its properties can be adjusted through doping and compositional changes to fit the specified requests of each application. Its disordered structure allows light propagation inside that medium like no other material. They also exhibit good compatibility with silica-based systems and waveguide production in which high optical intensities and long interaction lengths can be achieved [28], giving rise to nonlinear structures in integrated optical devices [29].

For the fabrication of all-optical systems in information technology and integrated photonics, the chosen materials should exhibit high nonlinearities. Rather, low nonlinearities are essential for fibers in optical communications to avoid phenomena of self-focusing, self-phase modulation, Raman and Brillouin scatterings. NLO was considered the threshold to the total of information that can be transmitted in a single optical fiber. As laser power levels increase, NLO limits data rates, transmission lengths, and the number of wavelengths that can be transmitted simultaneously. Optical nonlinearities give rise to many “secondary” effects in optical fibers. These effects can be damaging in optical communications, but they find other applications, especially for the integration of all-optical functionalities in optical networks. The optical nonlinearities can give rise to gain or amplification, the conversion between wavelengths, the generation of new wavelengths or frequencies, the control of the temporal and spectral shape of pulses, and switching [6]. Thus, they can be distinguished in two types: that from scattering (stimulated Brillouin and stimulated Raman) and that from optically induced changes in the refractive index, resulting either in phase modulation or in the mixing of several waves and the generation of new frequencies (modulation instability and parametric processes, such as four-wave mixing). So, the nonlinear refractive index, also referred optical Kerr nonlinearity (n2), offers a means to achieve switching and amplifying functions in photonic devices and produces nonlinear effects, namely self-phase modulation, and four-wave mixing. Self-phase modulation implies changes in the phase and rising frequency of a pulse, which can cause spectral broadening. Four-wave mixing is a kind of nonlinear frequency conversion generated by the Kerr nonlinearity which enables, for example, high-speed communications, frequency conversion, sensing, and quantum photonics. The effect of ultrafast response time (10 s−15 s) provides broad bandwidths, that can pull actual GHz electronic computing forward to PHz (1015) rates using all-optical signal processing [30]. In addition, spectral broadening, produced by changes in phase from the nonlinear refractive index, can enable the production of short-pulsed sources [30]. Four-wave mixing, on the other hand, can be used to generate optical frequency combs [30], which can measure precise frequencies of light and span spectral ranges useful for spectroscopic investigations.

Although these applications are of great practical interest, the Kerr effect (n2) is often small for common optical glasses (∼10−20 to 10−19 m2/W) [30], leading to high thresholds for nonlinear effects and requiring special sources of high-power excitation.

Transparent optical glasses exhibiting nonlinearities, e. g. large nonlinear refractive index and nonlinear absorption coefficient are good candidates for fiber telecommunication and for nonlinear optical devices such as optical switches, self-focusing, and white-light continuum generation. Glasses that exhibit significant nonlinearity are good candidates as Raman gains media to provide enhanced Raman gain over an extended wavelength range. Chalcogenide (As–Se) glasses and fibers are examples of good candidates as well tellurite fibers because of the high refractive index of TeO2 (2.3–2.4) [6] compared to the SiO2 (1.46). An As2S3 fiber exhibit a Raman coefficient is 300 times greater than that of silica fiber [6]. However, chalcogenide fibers have lesser chemical stability. In spite of that, chalcogenide glass has wide transparency transmission from 0.5 to 25 μm [31], enhancing their potential applications on the mid-IR. As shown in Figure 8, the long-wavelength cut-off edges of chalcogenide glasses depend on the mass of anionic elements and are extended between 12 and 20 μm. Their nonlinearity (Kerr effect) is 200–1000 times larger than that of the silica glass at a wavelength of 1.55 μm [32].

Figure 8.

Typical infrared (IR) transmission spectra of S-, Se-, and Te-based chalcogenide (ChG) glass [32].

The nonlinear optical properties of glasses have been considered of great interest for photonic devices to be used in several technological applications with a broad spectrum of phenomena, such as optical frequency conversion, optical solitons, phase conjugation, and Raman dispersion. Most of the previous investigations were devoted to crystalline materials such as Quartz, LiNbO3, KTiOPO4, and α-BaB2O4 [19]. Nevertheless, recently the development of special glass compositions exhibiting NLO properties have extended the research into practical applications of glass transparent materials for a wide range of effects, such as fast intensity-dependent index, third-harmonic generation (THG), stimulated emission (or stimulated Raman scattering), second harmonic generation (SHG) and the multiphoton absorption [29]. Nonlinear phenomena in glasses, such as nonlinear refractive index, multiphoton absorption, and Raman and Brillouin scattering, depend on the glass itself, its nature (composition and structure), which is responsible for the nonlinearity. On the other hand, in glasses doped with RE ions or semiconductor nanoparticles, in which the glass assumes the role of host, the nonlinearity is produced by interactions between dopant ions, domains, and different phases (such as in glass-ceramics).

The first nonlinear effect in history is often associated with the beginning of the NLO [33], had occurred in 1875, when J. Kerr observed changes in the refractive index of a liquid (CS2) in the presence of an electric field. The Kerr effect or quadratic electro-optic effect is directly related to the third-order nonlinearity, χ(3). Pockels, 20 years later, observed another phenomena, the linear electro-optic effect [34], through the modification of the index of refraction of light in a non-centrosymmetric crystal (Quartz) placed by an electric field. For a long time thereafter, these phenomena were little studied and found of non-practical applications. However, the decisive prerequisite for work out such effects demands high laser pump intensities and suitable phase-matching conditions. Significant effects of NLO (e.g., frequency conversion by taking advantage of second and third harmonic generation) only began to be observed experimentally in the early 60s, after laser invention, due to the fact that such NLO effects require high electromagnetic field intensities to manifest, which was only possible using high-power lasers. P. Franken reported the first observation of the SHG in 1961 after focusing a pulsed ruby laser (λ = 694 nm) into a Quartz crystal; the red incident beam generated an emitted blue light (λ = 347 nm) [35]. THG was soon experimentally reported in 1965 [36]. Since the late of the 80s the interest in NLO properties in glass began to increase [19]. As already mentioned, the nonlinear optical response of glasses is closely related to their anionic polarizability [29, 37] which is described as the deformation of electron clouds (dipoles) when the electromagnetic field is applied. The selection of suitable glass structure and composition can contribute to efficiently optical Kerr effect, self-focusing, intensity-dependent refractive index, and other χ(3) -related effects. In the literature, several reports have shown that the Kerr effect of non-conventional glass compositions is a viable option for self-phase modulation and broadband light generation in the near-infrared [29]. The χ(3) in resonant mode is an additional possibility. Due to the bandwidth requirements for transmitting information for both long-haul and local area networks, Raman amplification is considered a good option to face out the recent developments in the telecommunications fiber industry and diode laser technology. Compared, for instance, with Er3+-doped silica fiber amplifiers, in which the wavelength is fixed at 1550 nm, Raman gain bandwidths are larger, and the operational range only varies with the pump wavelength and the bandwidth of the Raman active medium (the glass nature) [29]. It is well known that the Kerr effect and Raman gain follow the polarity of the glass medium and are deeply impacted by the structure of some specific glasses, such as TeO2 glass, which have large electronic polarizability. Additionality the small length of Te–O bond (2.01 Å) [37, 38] is considered responsible for the large third-order nonlinear optical susceptibility of these kinds of glass [38]. It χ(3) value was as high as 1.4 × 10−12 esu about 50 times as large as that of SiO2 glass [38].

The field of nonlinear optics of glasses has been mainly focused on two main groups: resonant and non-resonant [28]. Non-resonant interactions occur when the light excitation falls in the transparent wavelengths range of the glass longer than its electronic absorption edge. As no electronic transitions take place, the process can be seen as lossless and so an ultrafast glass response due to third-order electronic polarization is assured. Examples are, in general, high refractive index and high dispersion glasses like heavy flint optical glasses, or heavy metal oxide glasses, or chalcogenide glasses.

The resonant ones include semiconductor (quantum dots), or metallic nanoparticles doped glasses [10, 28] and the interaction occurs when the optical field’s frequencies are near the electronic absorption edge so that its high resonant nonlinearity can be exploited. However, the isotropic structure glass and its amorphous state have inversion symmetry and do not exhibit second-order nonlinearity, χ(2), or Pockels effect which is necessary for applications such as electro-optic switching and modulation or wavelength conversion in photonic technology. Indeed, glass is a good example of optically isotropic material (as well cubic crystals) that does not exhibit (in principle) any behavior that arises from that condition (e.g. optical birefringence). However, this is not always the case because second-order nonlinearity can be achieved in glass upon appropriate modification. For example, the application of both heat and electric fields (thermal poling) gives rise to SHG. Since χ(2) is not physically possible in a centrosymmetric material, the creation of an axial symmetry under thermal poling has been demonstrated to be effective to introduce second-order nonlinearity properties [29]. Another route to create an optical SHG is by the introduction of optical non-linear nanocrystals within a glass matrix. Although thermal poling is an efficient way to induce SHG in silicate glasses, χ(2) also appeared after glass heat treatments to precipitate crystallites of non-centrosymmetric compounds [39]. This strategy gives rise to transparent crystallized glasses (glass-ceramics). Nevertheless, more research is necessary to clarify some aspects, for instance, whether the thermal poling approach is effectively the best choice for raising SHG.

In the glass transparency region, which is found between the ionic (vibrational) and the electronic excitation interactions and where no permanent electric dipoles are present, the light frequency is too high for the ionic polarizability to follow the E field oscillations and too low to resonate with the electronic excitations [10]. Still, multiphoton processes may occur. For example, the probability of two-photon absorption is proportional to the square of the E field intensity [10].

4. Quantum dots doped glasses

Intensity-dependent nonlinear optical effects, such as the optical Kerr one, are very significant for all-optical data processing. Glasses with large nonlinear refractive index and nonlinear absorption coefficient are suitable materials for fiber telecommunication and nonlinear optical devices such as ultrafast optical switches and several photonic applications. Since silica and silicate glasses exhibit a small third-order nonlinear susceptibility χ(3), the strategy of combining different materials to obtain composite systems, such as glass doped with semiconductor nanocrystals (quantum dots), allowed to obtain optimized nonlinear optical properties because semiconductors exhibit larger susceptibility. Glasses doped with semiconductors nanocrystals (quantum dots, QDs) such as CdS, CdSe, CdTe, PbS, CuCl, etc., are suitable materials for resonant NLO devices with response times on the ps domain. They can be prepared through the dispersion of a nanocrystalline phase in a glass matrix. This approach, through the reduction of bulk size to nanometric scale or quasi-zero-dimensional quantum dots, allow to change the electronic properties of glasses accordingly with enhanced nonlinearity compared with the corresponding bulk semiconductors [40]. Whenever the absorption of a photon of enough energy (hν is greater than the band gap, Eg) excites an electron from the valence band to the conduction band in semiconducting materials, a free electron–hole pair may be formed. The hole and electron are attracted by Coulombic forces to keep them in a stable orbit as a bound electron–hole pair, called exciton [10]. Due to electrons and holes being confined in a small volume of radius, the radius of the exciton (distance between the electron and hole in an exciton), will change the available energy levels and the interaction with the photons. As the size of nanoparticles becomes progressively smaller, the quantum size effects of excitons confined in all three dimensions give rise to a series of discrete energy levels [10], and therefore the energy associated with them will depend on the relationship between the crystal size (R) and the exciton Bohr radius. Quantum confinement effects are quite significant in the range of a ≪R ∼ aB, where a is the lattice constant of the semiconductors, i.e. when R is similar to Bohr radius of exciton in bulk crystal (aB). In QDs doped glasses these effects give rise to the so-called blue shift of the linear optical absorption edge. The shift regarding to the bulk Eg varies with R as ∼1/R2. Smaller R gives rise to larger blue-shift.

The size of semiconductor particles can be calculated by [41]:

Eg=h2/8R21/me+1/mh
1.8e2/4πε0εαR0.124e4/ħ4πε0εα21/me+1/mh1E17

where ΔEg is the shift of the band gap energy (due to the confinement), R is the particle size (radius), me and mh are respectively the reduced effective masses of the electron (e) and hole (h). It is interesting to note that the second term, related to the kinetic energy of the electron and hole [41] exhibits a 1/R2 dependence while the third term, the Coulomb interaction between the electron and hole, has a 1/R dependence. Although the kinetic energy of the exciton for nanoparticles of R ∼ aB seems to be predominant, the Coulomb interaction must also be considered [42]. Figure 9 shown that the shift of the exciton resonances to higher energy (blue shift) is a consequence of the increasing quantum confinement as R decreases [43].

Figure 9.

Absorption spectra of CuCI-doped quantum dot glasses: 22 Å (solid); 27 Å (dot); 34 Å (dash) [43].

The changes in absorption also lead to refractive index changes, through the Kramers-Kronig transformation:

Δnω=cπ0αωω2ω2E18

where c is the speed of light and ω is the light frequency.

The method allows to correlate the determined change Δα in the absorption coefficient to the change Δn in the refractive index [43]. The nonlinear refractive index is then obtained by n2 = Δn/I (Eq. (8)). The value of χ(3) will be proportional to the reciprocal of the confinement volume and will increase with decreasing R [10]. Is then expected that larger non-linearities are obtained for glasses containing smaller particles and larger volume fractions of QDs [10].

5. Metal-doped glasses

Metal doped glass possesses linear and nonlinear optical properties. Great interest has driven the study of the third-order nonlinear susceptibility of metal particles embedded in dielectric matrices, like glasses [44], which are influenced not only by the type and size of the metal particles but also by the metal-dielectric constant. The most significant effect of the confinement of metal particles in optical properties of nanocomposite glasses is the appearance of the surface plasmon resonance, which deeply enhances the glass χ(3) responses with picosecond temporal responses. For example, the optical absorption spectrum of Ag-doped silica sol–gel glass shows the presence of an absorption band of surface plasmon resonance due to Ag nanoparticles at ∼420 nm (Figure 10).

Figure 10.

Absorption spectra of Ag-SiO2 cermet (at a concentration of 8% Ag) and SiO2 matrix (without Ag).

Plasmons deals with a coherent interaction between the free-electron gas surrounding metal and the incident radiation. The motion of these free electrons can be described by the plasma Drude model, along with a plasma frequency of the bulk metal ωp. In accordance with the Drude free-electron model, the dielectric constant of metal particles is given by [45]:

εm=εmiεm=1ωP2/ωωi/τE19

Where τ is the time between collisions among electrons. The real (ε’) and imaginary (ε”) parts of the complex dielectric constant are expressed as [45]:

εm=n2k2=1ωP2τ2/1+ωτ2E20
εm=2nk=ωP2τ/ω1+ωτ2E21

From the above equations is possible to infer the existence of an interaction between the free-electron gas and the incident electromagnetic field, which gives rise to an excitation of the electrons at the metal surface, associated with collective oscillations of electrons in the metal nanoparticles, called surface plasmon. The large value of χ(3) of metal-doped glasses arises predominantly from the local electric field enhancement near the surface of the metal nanoparticles (Ag, Cu, Ni, or other metal nanoparticles) due to their surface plasma resonance, leading to a variety of optical effects.

When the diameter (d) of metal particles is much lower than the wavelength of light (λ), scattering is negligible. As well, the total collisional impacts of the electrons with the particle surfaces become significant and a new-found relaxation time, τeff, appeared, given by [45]:

1/τeff=1/τb+2vF/dE22

where τb is the bulk value and vF is the electron velocity at the Fermi energy. Spherical metal nanoparticles embedded in a glass matrix with a real dielectric constant εd exhibit NLO properties. Figure 11 exhibits homogeneous size distribution of spherical Au nanoparticles in a SiO2 thin film on a metal substrate [46]. For the conditions.

Figure 11.

Transmission electron microscopy micrographs of Au-SiO2 thin films: a) cross section view of a film with Au volume fraction p = 23%, and b) plan view of a film of Au volume fraction p = 8% [46].

The equation usually considered to obtain the χ(3) of metal/glass composites, is given by [45]:

χ3=3pf4χm3E23

Where χm3 is the bulk metal third-order susceptibility, f is the local electric field near the metal particles and p is the metal volume fraction. The optical response of metal particle/glass composites can be determined by the local field enhancement inside the nanoparticles (dielectric confinement):

f=EE0=3εdεm+2εdE24

f is given by the ratio between the field E inside a metal particle and the applied field E0, with εd the dielectric constant of the glass matrix and εm the one of the metal.

So, if one assumes χm3independent of particle size, then χ(3) will increase as the volume fraction of metal particles and their size increases [45].

6. Conclusions

In the last decades, the development of optics, as the science that deals with light and its applications, has had an enormous growth not only through new or recognized theoretical concepts but also in new optical techniques and new instruments. Several factors contributed to this, namely: 1) the emergence of new light sources, such as lasers, which allowed the advent of new applications associated with light manipulation, such as those based on the nonlinear optical properties of materials; and 2) the development of new glasses or the modification/optimization of others through the addition of dopants (e.g., metallic nanoparticles or QDs), also allowed the creation of new photonic devices (light sources, all-optical switches, modulators, etc.) and new technologies associated with them. These developments also gave rise to the so-called integrated optics, which allowed a reduction in the size of optical systems, while maintaining their high nonlinear optical performance. Many of these technologies are used in the field of communications and other sectors of activity, such as health and information. In terms of materials, NLO glasses have grown as indicated by the numerous scientific publications on the subject. Glasses have great versatility and offer great flexibility to modify their nonlinear responses by manipulating their composition, refractive index, gap, etc. Because of their structural inversion symmetry, glasses do not possess second-order optical nonlinearity. Yet, it is possible to induce this optical response in the glass by thermal electric poling.

Conflict of interest

The author declares no conflict of interest.

\n',keywords:"glass, photonics, nonlinear optical (NLO), Kerr effect (third-order nonlinearity)",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80452.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80452.xml",downloadPdfUrl:"/chapter/pdf-download/80452",previewPdfUrl:"/chapter/pdf-preview/80452",totalDownloads:65,totalViews:0,totalCrossrefCites:0,dateSubmitted:"November 6th 2021",dateReviewed:"November 25th 2021",datePrePublished:"February 13th 2022",datePublished:"March 30th 2022",dateFinished:"February 13th 2022",readingETA:"0",abstract:"The field of photonics has been the target of constant innovations based on a deep knowledge of the nonlinear optical (NLO) properties of materials and especially on information/data technologies. This chapter compiles some of the main physical aspects needed to understand NLO responses, especially in glasses. Any deviation from the linear correlation between a material’s polarization response and the electric component of an applied electromagnetic field is an example of nonlinear optic behavior. Heavy metal oxide and chalcogenide glasses offer the largest nonlinear response. For example, high refractive index and high dispersion glasses fall in the type of non-resonant devices, while the resonant ones comprise metal nanoparticle doped glasses. Metal nanoparticles’ doped glasses can be pre- pared by the sol-gel method. The optical absorption spectrum of Ag-doped silica glass shows the presence of an absorption band of surface Plasmon Resonance due to Ag nanoparticles at 420 nm and Z-scan has been used to study the NLO properties. This chapter contains a brief discussion of the basic principles of nonlinear optics, the review of the nonlinear optical of glass in general, and two separate sections concerning the nonlinear optical effects in the glasses doped with quantum dots and metals, respectively.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80452",risUrl:"/chapter/ris/80452",signatures:"Helena Cristina Vasconcelos",book:{id:"10672",type:"book",title:"Nonlinear Optics",subtitle:"Nonlinear Nanophotonics and Novel Materials for Nonlinear Optics",fullTitle:"Nonlinear Optics - Nonlinear Nanophotonics and Novel Materials for Nonlinear Optics",slug:"nonlinear-optics-nonlinear-nanophotonics-and-novel-materials-for-nonlinear-optics",publishedDate:"March 30th 2022",bookSignature:"Boris I. Lembrikov",coverURL:"https://cdn.intechopen.com/books/images_new/10672.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83962-836-8",printIsbn:"978-1-83962-835-1",pdfIsbn:"978-1-83962-890-0",isAvailableForWebshopOrdering:!0,editors:[{id:"2359",title:"Dr.",name:"Boris I.",middleName:"I.",surname:"Lembrikov",slug:"boris-i.-lembrikov",fullName:"Boris I. Lembrikov"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"93646",title:"Prof.",name:"Helena",middleName:"Cristina",surname:"Cristina Vasconcelos",fullName:"Helena Cristina Vasconcelos",slug:"helena-cristina-vasconcelos",email:"helena.cs.vasconcelos@uac.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of the Azores",institutionURL:null,country:{name:"Portugal"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Basic principles of NLO",level:"1"},{id:"sec_3",title:"3. Nonlinear optical properties of glass",level:"1"},{id:"sec_4",title:"4. Quantum dots doped glasses",level:"1"},{id:"sec_5",title:"5. Metal-doped glasses",level:"1"},{id:"sec_6",title:"6. Conclusions",level:"1"},{id:"sec_10",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Poole SB, Payne DN, Fermann ME. Fabrication of low-loss optical fibres containing rare-earth ions. Electronics Letters. The Institution of Engineering and Technology. 1985;21:737-738. DOI: 10.1049/el:19850520'},{id:"B2",body:'Refi JJ. Optical fibers for optical networking. Bell Labs Technical Journal. 1999;4(1):246-261. DOI: 10.1002/bltj.2156'},{id:"B3",body:'Hughes M. Modified Chalcogenide Glasses for Optical Device Applications. 2007'},{id:"B4",body:'Vasconcelos HC, Pinto AS. Fluorescence properties of rare-earth-doped sol-gel glasses. In: Chandra U, editor. Recent Applications in Sol-Gel Synthesis. Rijeka: IntechOpen; 2017. 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Exoplanet characteristics and their comparison to Solar System planets are provided as well as general detection methods and planned probes to gather additional data.",book:{id:"10210",slug:"solar-system-planets-and-exoplanets",title:"Solar System Planets and Exoplanets",fullTitle:"Solar System Planets and Exoplanets"},signatures:"Joseph Bevelacqua",authors:[{id:"115462",title:"Dr.",name:"Joseph",middleName:"John",surname:"Bevelacqua",slug:"joseph-bevelacqua",fullName:"Joseph Bevelacqua"}]},{id:"65725",title:"On the Deviation of the Lunar Center of Mass to the East: Two Possible Mechanisms Based on Evolution of the Orbit and Rounding Off the Shape of the Moon",slug:"on-the-deviation-of-the-lunar-center-of-mass-to-the-east-two-possible-mechanisms-based-on-evolution-",totalDownloads:984,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"It is known that the Moon’s center of mass (COM) does not coincide with the geometric center of figure (COF) and the line “COF/COM” is not directed to the center of the Earth, but deviates from it to the South-East. Here, we discuss two mechanisms to explain the deviation of the lunar COM to the East from the mean direction to Earth. The first mechanism considers the secular evolution of the Moon’s orbit, using the effect of the preferred orientation of the satellite with synchronous rotation to the second (empty) orbital focus. It is established that only the scenario with an increase in the orbital eccentricity e leads to the required displacement of the lunar COM to the East. It is important that high-precision calculations confirm an increase e in our era. In order to fully explain the shift of the lunar COM to the East, a second mechanism was developed that takes into account the influence of tidal changes in the shape of the Moon at its gradual removal from the Earth. The second mechanism predicts that the elongation of the lunar figure in the early era was significant. As a result, it was found that the Moon could have been formed in the annular zone at a distance of 3–4 radii of the modern Earth.",book:{id:"8444",slug:"lunar-science",title:"Lunar Science",fullTitle:"Lunar Science"},signatures:"Boris P. Kondratyev",authors:[{id:"277909",title:"Prof.",name:"Boris",middleName:"Petrovich",surname:"Kondratyev",slug:"boris-kondratyev",fullName:"Boris Kondratyev"}]},{id:"68357",title:"Solar System Exploration Augmented by In Situ Resource Utilization: System Analyses, Vehicles, and Moon Bases for Saturn Exploration",slug:"solar-system-exploration-augmented-by-in-situ-resource-utilization-system-analyses-vehicles-and-moon",totalDownloads:824,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Human and robotic missions to Saturn are presented and analyzed with a range of propulsion options. Historical studies of space exploration, planetary spacecraft and astronomy, in situ resource utilization (ISRU), and industrialization all point to the vastness of natural resources in the solar system. Advanced propulsion is benefitted from these resources in many ways. While advanced propulsion systems were proposed in these historical studies, further investigation of nuclear options using high-power nuclear electric and nuclear pulse propulsion as well as advanced chemical propulsion can significantly enhance these scenarios. Updated analyses based on these historical visions are presented. At Saturn, nuclear pulse propulsion with alternate propellant feed systems and Saturn moon exploration with chemical propulsion and nuclear electric propulsion options are discussed. Issues with using in situ resource utilization on Saturn’s moons are discussed. At Saturn, the best locations for exploration and the use of the moons as central locations for Saturn moon exploration are assessed. 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Saxena",hash:"d92a4085627bab25ddc7942fbf44cf05",volumeInSeries:2,fullTitle:"Current Perspectives in Human Papillomavirus",editors:[{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:148,paginationItems:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of ​​Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of ​​Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. 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Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"July 5th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:320,numberOfPublishedBooks:32,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. 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