Pyrolysis reactions at different temperature [28].
\r\n\t
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At the moment he is the head of the red palm weevil research program, King Faisal University.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"192142",title:"Dr.",name:"Hamadttu",middleName:null,surname:"El-Shafie",slug:"hamadttu-el-shafie",fullName:"Hamadttu El-Shafie",profilePictureURL:"https://mts.intechopen.com/storage/users/192142/images/system/192142.jpg",biography:"Hamadttu Abdel Farag El-Shafie is an associate professor of entomology and senior research entomologist at the Date Palm Research Center of Excellence, King Faisal University, Saudi Arabia. He is the head of IPM research program in date palm. El-Shafie obtained his B.Sc. and M.Sc. degrees from the University of Khartoum, Sudan in 1988 and 1993, respectively. He received his Ph.D. degree from University of Giessen, Germany in 2001. He was appointed head of Crop Protection Department at University of Khartoum in 2008, and then deputy dean for academic affairs at Faculty of Agriculture, University of Khartoum. He supervised 25 M.Sc. students and 5 Ph.D. students at University of Khartoum. His research interest focuses on management of field crop pests using neem biopesticides, and biology and ecology of date palm pests including mites. He also has interest in control of red palm weevil using semiochemicals. He published 60 research papers in international peer-reviewed journals and 10 book chapters with international publishers such as Springer, John Wiley and IntechOpen, in addition to more than 25 international conferences in the field of entomology. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"56034",title:"Pyrolysis: A Sustainable Way to Generate Energy from Waste",doi:"10.5772/intechopen.69036",slug:"pyrolysis-a-sustainable-way-to-generate-energy-from-waste",body:'Lignocellulosic biomass is considered as a promising environmentally friendly substitute resource for carbon‐based fuels and chemicals. Existing global supply of energy depends on non‐renewable fuels such as oil, gas and coal formed naturally beneath the earth crust. However, the amount of fossil fuel is limited now. Due to the growing population of world, the consumption of energy per capita is increasing. Thus the inevitability for continuing alternative to generate the possible sources of energy is evident. Utilization of biomass to produce value‐added products is receiving great attention by researchers. Furthermore, the inorganic constituent of biomass is negligible and it contains minor quantity of nitrogen, sulphur and ash. Therefore, combustion of biopmass is advantageous as it produces less toxic gas such as nitrogen oxides (NO
Different types of thermochemical even biological processes have been adopted to convert biomass into value‐added products. Among those processes, pyrolysis is more convenient since it has several advantages of storing, transportation and flexibility in solicitation such as turbines, combustion appliances, boilers, engines, etc. In some cases, solid biomass and waste are precisely challenging to process for pyrolysis research. It is until now at a preliminary stage in terms of expansion and yet requires resolving numerous practical obstacles to contend with conventional fossil fuel–centred procedures [2, 3]. The preparation of liquid biofuels including other products like solid char and gas by pyrolysis of various lignocellulosic residues has been comprehensively explored earlier. Some of these biomass species are beechwood [4], bagasse [5] woody biomass [6, 7], straws [8], seedcakes [9] and municipal solid waste (MSW) [10, 11]. Figure 1 illustrates different types of existing biomass conversion process with their respective output.
Biomass conversion process to obtain value‐added products.
Pyrolysis is defined as the thermal decomposition of lignocellulosic derivatives under inert condition in oxygen‐deficient environment. The word is resulting from two Greek words: ‘pyro’, which means fire, and ‘lysis’, which means disintegration into integral parts. Pyrolysis technology is very old and earlier it was first used for preparation of charcoal in Middle East and Southern Europe before 5500 years ago [12]. Egyptian people used this technique to produce tar for sealing boats [13]. Subsequently then, practice of pyrolysis processes have been growing and are extensively carried out for charcoal and coke fabrication. Burning of charcoal can produce intensively high temperature to melt tin with copper to obtain bronze. Consequently, pyrolysis has been getting further consideration as an effective technique for transforming biomass into bio‐oil throughout the modern eras [14]. The eventual objective of pyrolysis is to yield high‐value energy products for contending with and gradually supplanting non‐renewable fossil fuels. Nevertheless, the expansion of progressive know‐hows is the ensuing challenge for the investigators to accomplish the objectives. It is required to transform biomass into bio fuels for uninterrupted usage in vehicles, trains, ships and aero‐planes to substitute diesel and petrol [15, 16]. Additional improvement of pyrolysis technology is enduring to produce solid fuel like char or carbonaceous materials, syngas, etc. Typically a pyrolysis system unit contains the equipment for lignocellulosic residues pre‐processing, the pyrolysis reactor, and subsequent unit for downstream processing. Mainly it can be classified as units that produces only heat and biochar (using slow pyrolysis) or units that produce biochar and bio‐oils (using fast pyrolysis). Figure 2 shows simple layout of pyrolysis units with its main products.
Simplified flow diagram for typical pyrolysis unit. (a) Biochar and bio‐oil production. (b) Biochar and heat production.
Extensive amount of research has been conducted in recent years for thermochemical conversion of biomass into biofuels (bio‐oil, biochar and biogas) using pyrolysis technology. Compared to other thermochemical conversion technologies, pyrolysis process has lot of advantages based on process parameter optimization. However, this technology still needs to be updated with respect to its commercial applications. In this chapter, emphasis has been given to discuss the current status of pyrolysis technology and its prospective for commercial applications for biofuel, syngas and biochar production. Aspects of pyrolysis technology such as types of pyrolysis, pyrolysis principles, biomass compositions and characteristics, pyrolysis reactor design, pyrolysis products and their physiochemical properties and economics of biofuel production are presented. We have pointed out some of the inherent properties of bio‐oil that cause complications for the end use of the products. Finally, we take a brief look at some processes including catalytic pyrolysis process that aim to valorize bio‐oil by conversion to higher value liquid fuel products.
The thermal decomposition process of pyrolysis using lignocellulosic biomass takes place in the absence of oxygen under inert atmosphere. As an inert atmosphere argon or nitrogen gas flow is usually needed. The fundamental chemical reaction is very complex and consists of several steps. The end products of biomass pyrolysis consist of biochar, bio‐oil and gases. Pyrolysis process emits mainly methane, hydrogen, carbon monoxide and carbon dioxide. The organic materials present in the biomass substrate starts to decompose around 350–550°C and it can proceed until 700–800°C without the presence of air/oxygen [17, 18]. Biomass is mainly composed of long polymeric chain of cellulose, lignin, hemicellulose, pectin and others. The larger molecules of organic materials start to decompose to yield smaller molecules, which are released from the process stream as gases, condensable vapours (tars and oils) and solid char during pyrolysis process. The proportion of each end product depends on the temperature, time, heating rate, and pressure, types of precursors and reactor design and configuration. Figure 3 illustrates the decomposition process of main lignocellulosic residues at different temperature. The moisture content of biomass also plays a vital role in pyrolysis processes. The moisture content of the feedstock should be around 10% during fast pyrolysis process [18]. Due to high moisture content, major products become liquids and if there is low level of water, there is high risk that the process produces huge amount of dust instead of oil. Thus sludge derived from waste stream and meat‐processing wastes require drying before exposing them finally to pyrolysis environment. Less than 450°C when the heating rate is slow, the main yield is biochar. However at higher temperature that is more than 800°C when the heating rate is high then larger fraction of ash and gaseous products are produced. Bio‐oil can be produced applying intermediate temperature using relatively high heating rates. During the beginning of the process around temperature 250–300°C, volatile materials are released at almost 10 times quicker than the subsequent step [20].
Decomposition behaviour of biomass constituents at different temperature [
Woody biomass was initially used to produce charcoal. The charcoal based on wood during heating produces negligible amount of smoke. Earlier it was extensively used for melting of ore to extract iron. However, the process had drawbacks of less yield percentages, less energy and excessive air pollution. After that, modern technology was developed to extract maximum possible energy from biomass using combustion (exothermic), gasification (exothermic) and pyrolysis (endothermic) [21]. Combustion deals with the burning of biomass in presence of oxygen to produce heat. The competence of this practice is not satisfactory [22, 23]. Gasification also takes place under oxygenated atmosphere which will yield gaseous fuels. Nevertheless, pyrolysis is the leading phase for both gasification and combustion processes [24, 25]. Consequently pyrolysis can be considered as part of gasification and combustion [26]. The decomposition products yield of biomass during pyrolysis is provided by following Figure 4 [27].
The decomposition products of pyrolysis of biomass [
Table 1 summarizes the list of main pyrolysis reactions at different temperature.
Temperature | Type of reaction | End products |
---|---|---|
Less than 350°C | Moisture loss, depolymerization, free radical generation | carbonyl and carboxyl group production, CO and CO2 gas liberation, biochar formation |
Between 350°C and 450°C | Substitution for breaking of glycoside chain of polysaccharide | Tar production containing levoglucosan, anhydrides and oligosaccharides |
Above 450°C | Dehydration, rearrangement and fission of sugar units | acetaldehyde, glyoxalin and acrolein production |
Above 500°C | A mixture of all above processes | A mixture of all above products |
Condensation | Unsaturated products condense and cleave to the char | A highly reactive char residue containing trapped free radicals |
Pyrolysis reactions at different temperature [28].
The structure of biomass is complex and usually composed of three main natural biomacromolecules: Cellulose, hemicellulose and lignin. Besides that it also has extractives and some minerals. The proportion and these basic constituents vary from biomass to biomass [11, 29, 30]. During pyrolysis, cellulose and hemicellulose yield condensable vapours or liquids and gas. Lignin decomposes to give liquid, gas and solid char. Extractives also produce liquid and gas due to simple volatilization or decomposition. The ash fraction inside the char matrix contains minerals. This distribution of components into products is shown schematically in Figure 5.
Product distribution during pyrolysis [
The vapours produced from initial decomposition of biomass undergoes for secondary reactions to yield soot which also varies due to slow and fast pyrolysis process. Alkali metals act like catalyst by enhancing the char yield. The presence of minerals affects the ignition properties of biochar matrix [11]. It was observed that bio‐oil mainly derived from cellulosic substrate around 500°C [31] whereas biochar may be extracted from lignin. Thus the biomass substrate which contains greater proportion of lignin derivatives can yield more bio‐oils yield. Table 2 shows a list of selected biomass containing different proportion of cellulose, hemicellulose and lignin substrate [11, 32–37].
Feedstock | Lignin (%) | Cellulose (%) | Hemicellulose (%) |
---|---|---|---|
Wood | 25–30 | 35–50 | 20–30 |
Wheat straw | 15–20 | 33–40 | 20–25 |
Switch grass | 5–20 | 30–50 | 10–40 |
Sugarcane bagasse | 23–32 | 19–24 | 32–48 |
Miscanthus | 17 | 24 | 44 |
Corn stover | 16–21 | 28 | 35 |
Hazelnut shell | 42.9 | 28.8 | 30.4 |
Olive husk | 48.4 | 24 | 23.6 |
Corncob | 15 | 50.5 | 31 |
Tea waste | 40 | 30.20 | 19.9 |
Walnut shell | 52.3 | 25.6 | 22.7 |
Almond shell | 20.4 | 50.7 | 28.9 |
Sunflower shell | 17 | 48.4 | 34.6 |
Nut Shell | 30–40 | 25–30 | 25–30 |
Paper | 0–15 | 85–99 | 0 |
Rice straw | 18 | 32.1 | 24 |
Stored refuse | 20 | 60 | 20 |
Leaves | 0 | 15–20 | 80–85 |
Cotton seed hairs | 0 | 80–95 | 5–20 |
Barley straw | 14–15 | 31–34 | 24–29 |
Oat straw | 16–19 | 31–37 | 24–29 |
Bamboo | 21–31 | 26–43 | 15–26 |
Rye straw | 16–19 | 33–35 | 27–30 |
Coastal Bermuda grass | 6.4 | 25 | 35.7 |
Jute fibre | 21–26 | 45–53 | 18–21 |
Banana waste | 14 | 13.2 | 14.8 |
Chemical constituent of selected biomass.
Based on process parameters and design of the reactor, presence of moisture can have significant effect on products yield [11]. The charcoal‐making process proceeds through two distinct steps: drying and pyrolysis steps. During the initial phase of drying, combined water in the pores represented as free water is expelled around 110°C. As much as water is present, it takes more energy to evaporate. After that between temperatures 150 and 200°C combined water present inside the cellulosic chain of wood will be reduced. In the early stage of carbonization, water evaporates as white smoke from charcoal kiln. Fast pyrolysis process is effective to dry the feed, so that the rate of temperature rise is not restricted by evaporation of water [38]. Typically 15–20% moisture is present in wood [11]. During producing the activated carbon also, moisture can significantly affect the properties of final carbon sample [39]. The particle size of the biomass matrix will have greater influence between char and liquid yield. Larger proportion of char is formed when particle sizes are big. Larger particles restrict the rate of disintegration, resulting in the increased scope of secondary char forming reaction [11]. Thus larger particle size is good to get more carbon yield whereas smaller particles are required to maximize liquid fractions during fast pyrolysis process. Higher proportion of lignin and fixed carbon also can contribute in better yield of biochar substrate if pyrolysis is carried out at medium temperature of 500°C whereas higher percentages of volatile materials can generate higher yield of bio‐oil and syngas (Table 3) [28]. Therefore, the precursors like hazel nut shell, olive stone, walnut shell is better to produce good quality biochar due to their lignin content (Table 2). The biomass like cereal straw, grasses, energy crops like woody biomass that die to their low mineral and nitrogen content are suitable for bio‐oil and syngas production (Table 4) [40].
Feedstock | Density (Kg/m3) | Moisture content (%) | Ash content (%) | Volatile matter (%) | Fixed carbon (%) |
---|---|---|---|---|---|
Wood | 1186 | 20 | 0.4–1 | 82 | 17 |
Bituminous coal | 11 | 8–11 | 35 | 45 | |
Hybrid polar | 150 | 45 | 0.5–2 | – | – |
Switchgrass | 108 | 13–15 | 4.5–5.8 | – | – |
Miscanthus | 70–100 | 11.5 | 1.5–4.5 | 66.8 | 15.9 |
Sugarcane baggage | 1198 | 3.2–5.5 | – | – | |
Barley straw | 210 | 30 | 6 | 46 | 18 |
Wheat straw | 1233 | 16 | 4 | 59 | 21 |
Danish pine | 8 | 1.6 | 71.6 | 19 | |
Rice straw | 200 | 6 4.3 | 79 | 10.7 | |
Fire wood | – | 7.74 | 1.98 | 80.86 | 17.16 |
Grateloupia filicina | – | 4.93 | 22.37 | 55.93 | 17.01 |
Birch | 125 | 18.9 | 0.004 | – | 20 |
Pine | 124 | 17 | 0.03 | – | 16 |
Polar | 120 | 16.8 | 0.007 | – | – |
Feedstock | Carbon (%) | Hydrogen (%) | Oxygen (%) | Nitrogen (%) | Ash (%) |
---|---|---|---|---|---|
Wood | 51.6 | 6.3 | 41.5 | 0.1 | 1 |
Cypress | 55 | 6.5 | 38.1 | – | 0.4 |
Olive baggage | 66.9 | 9.2 | 21.9 | – | 2 |
Wheat straw | 48.5 | 5.5 | 3.9 | 0.3 | 4 |
Barley straw | 45.7 | 6.1 | 38.3 | 0.4 | 6 |
Scots | 56.4 | 6.3 | – | 0.1 | 0.09 |
Birch | 44 | 6.9 | 49 | 0.1 | 0.004 |
Pine | 45.7 | 7 | 47 | 0.1 | 0.03 |
Polar | 48.1 | 5.30 | 46.10 | 0.14 | 0.007 |
Willow | 47.78 | 5.90 | 46.10 | 0.31 | 1.30 |
Switchgrass | 44.77 | 5.79 | 49.13 | 0.31 | 4.30 |
Reed canary grass | 45.36 | 5.81 | 48.49 | 0.34 | 5.10 |
Dactylis lomarata | 42.96 | 5.70 | 49.44 | 1.90 | 7.50 |
Festuca arundinacea | 42.22 | 5.64 | 50.65 | 1.50 | 7.30 |
Lolium perenne | 43.12 | 5.80 | 49.80 | 1.28 | 6.20 |
Based on composition, physiochemical properties as well as transformation mechanism, lignocellulosic residues can yield different value‐added products as illustrated by Figure 6.
Biomass transformation to value‐added products.
To optimize the product yield, controlling the temperature profile is the most important factor as it can partially influence the pressure, heating rate, peak temperature and contact time between solid and gaseous phases. Rapid heating and cooling rate is required for minimizing the extent of secondary reactions during fast pyrolysis. This will reduce liquid yield but product quality will be less. Even it will give a more complex mixture having higher viscosity [38]. On the other hand, the slow pyrolysis process uses slow heating rates which lead to higher char yields, but this is not consistent [11]. Higher temperature can ensure release of more volatile fractions to increase the carbon content of the char. However, longer residence time at higher temperature will significantly drop the product yield. The effect of temperature on liquid and gaseous fraction is far more complex. When the pyrolysis temperature reaches up to 400–550°C, liquid yields are higher. Above this temperature, secondary reactions take place by decomposing the condensable vapour, which finally gives lesser liquid fractions. For fast pyrolysis, maximum liquid is obtained around 500°C [18]. It was reported also that the liquid yields was 28–41% at temperatures between 377 and 577°C, depending on feedstock during the slow pyrolysis process [13]. Around 42–45% liquid fractions were obtained around temperature of 385–400°C using different straw feeds [45].
Gas flow rate during the pyrolysis process affects the degree of secondary char formation. Lower flow rate is favourable for char formation during slow pyrolysis process whereas higher gas flows are provided during fast pyrolysis process to effectively strip off the vapours as soon as they are formed. Higher pressure intensifies the activity of vapours within the reactor and at the surfaces of char particles to increase the secondary char formation. Conversely, pyrolysis under vacuum gives little char and gives more liquid fractions. For pyrolysis under pressure, moisture in the vapour phase can systematically upsurge the production of carbon. Because, in that case water is acting as catalyst by reducing the activation energy for pyrolysis reactions [46].The gas flow rate significantly influences the thermodynamics of the process. At higher pressure, the reaction is more exothermic using lower gas flow rates. Higher char yields can be ensured when pyrolysis process is exothermic and such conditions will favour the overall energy balance of the processes pursuing the carbon or char as main product. Thus it can be concluded that, any factor of pyrolysis conditions that increases the contact between primary vapours and hot char surface, including high pressure, lower flow rate of gas, larger particles size or slow heating is expected to favour the char formation with lower liquid yield.
Pyrolysis, especially pyrolysis of coal, is an age‐long activity but biomass pyrolysis is a completely new entrant. The process is aimed to produce biofuel. In the garret process, solid waste (Biomass) is allowed to mix with hot char and hot recycle gas in a specially designed chamber. This is then followed by pyrolysis at high temperature, usually above 800°C, and at a holding time of about 10 s. After pyrolysis, the char is the removed while the liquid portion is collected. The resulting formed tar is then separated and further processed to produce the process heat as well as the char feed for further pyrolysis. The process is generally expected to lead to production of at least 40% liquid yield but has been found to produce more of gas at the carbonization temperature and time, thereby making the process uneconomical [47]. The whole process can be summarized into three main steps: The formation of turbulent gaseous stream by intermixing the carrier gas, the solid biomass and the hot char using a designed mixing zone, passing the gaseous steam into the pyrolysis chamber and allowing to go through pyrolysis at temperature of about 800°C for about 10 s, and finally removing the pyrolyzed gaseous stream from the pyrolysis chamber [47].
In this process, the main feed (biomass) is crushed and sieved into about 1 mm particle size. The precursor is then dried to about 10% moisture content and fed into the reactor where it is pyrolyzed using a preheated inert gas. At pyrolysis temperature of about 500°C, a maximum yield of about 50% liquid and 30% gas is expected. The holding carbonization time is usually calculated based on the reactor height and the gas flow rates but usually made of several seconds [48]. One major problem of this technique is the low heat produced by the entraining gas which usually leads to low liquid yield since biomass requires high heat for a high liquid yield. Another problem is that fresh solid waste exerts a catalytic effect on bio‐oil cracking leading to production of more char and gas [49].
The fluidized bed pyrolysis process possesses highly excellent mass transfer characteristics as it offers an effective and highly positive means of heating of finely chopped biomass in a rapid manner to achieve the pyrolysis temperature to the desired level. It is a well‐established pyrolysis technique that can be used on a large‐scale pyrolysis process as it is capable of processing hundred tons of biomass per day. The advantages of this technique over conventional pyrolysis technique include improved performance of the system as well as lower viscosity coupled with higher energy content of the produced bio‐oil.
The Waterloo flash pyrolysis process involves the production of organic liquids from biomass materials using continuous atmospheric pressure in the absence of oxygen. Generally, it is a carefully controlled process that produces a high liquid yield. The process has been widely demonstrated using hardwood solid waste to produce organic liquid yield as high as 70% of the feed material [50]. It is a process in which the pyrolysis reactor works on a very unique principle in which the char is not allowed to accumulate in the bed while the treatment of the sand may not be necessary. One big advantage of the process is that the liquid product obtained is usually acid and pours easily with relative stability [51].
In order to satisfy certain criteria which have been left unsatisfied by other fast pyrolysis techniques, the RTI process was developed. This involves the use of deep fluid bed using very low temperatures with moderate heating rates and relatively long holding pyrolysis time. Satisfactory results have been obtained from pyrolysis of most biomass using this technology which effectively leads to high liquid yields at temperature range of between 400 and 450°C with volatile holding time of about 0.8 s [52]. Fine sand is usually employed as the bed heat carrier. This allows a very low gas flow rate and this coupled with indirect heat applied results in a highly effective thermal efficiency. This is a very big advantage from economic point of view when capital and operating costs are considered [52].
This technology, incorporated in 1991 aimed at producing value‐added products from bio‐oil especially to produce biolime. The pyrolyzer operating heat usually comes from the gas or char, that is, the by‐products of the pyrolysis, while the fluidizing gas comes off from the pyrolysis gas [53]. The liquid product obtained is then utilized in the production of materials such as biolime, slaked lime and in the control of SO
This process involves the utilization of wood and other lignocellulosic materials for the production of fermentable sugar. The process involves the following notable steps: subjecting the biomass material to dilute acid treatment (usually dilute sulphuric acid is used to dissolve the hemicellulose while cellulose content is unaffected), separation of the solid residue containing the cellulose, pyrolyzing the separated solid residue at a controlled temperature (400–600°C), atmospheric pressure with short vapour holding time in a fluidized bed reactor, formation of aqueous phase through controlled adjustment of the content of the crude product and finally the separation of the aqueous phase follows [53].
Overall the pyrolysis process can be classified as slow and fast depending on the heating rate. In slow pyrolysis process, the time of heating the biomass substrate to pyrolysis temperature is longer than the time of retention of the substrate at characteristic pyrolysis reaction temperature. However in fast pyrolysis, the initial heating time of the precursors is smaller than the final retention time at pyrolysis peak temperature. Based on medium, pyrolysis can be of another two types namely hydrous pyrolysis and hydro‐pyrolysis. Slow and fast pyrolysis is usually carried out in inert atmosphere whereas hydrous pyrolysis is carried out in presence of water and hydro‐pyrolysis is carried out in presence of hydrogen. The residence time of vapour in the pyrolysis medium is longer for slow pyrolysis process. This process is mainly used to produce char production. It can be further classified as Carbonization and Conventional. On the contrary, the vapour residence time is only for seconds or milliseconds. This type of pyrolysis, used primarily for the production of bio‐oil and gas, is of two main types: (1) flash and (2) ultra‐rapid. Table 5 summarizes some basic characteristics of different types of pyrolysis process.
During the fast pyrolysis process, biomass residues are heated in absence of oxygen at high temperature using higher heating rate. Based on the initial weight of the biomass, fast pyrolysis can provide 60–75% of liquid biofuels with 15–25% of biochar residues [54]. It can also yield 10–20% of gaseous phase depending on the biomass used [54]. The process is characterized by small vapour retention time. However, quick chilling of vapours and aerosol can ensure higher bio‐oil yield [54]. It can provide liquid biofuel for turbine, boiler, engine, power supplies for industrial applications. Fast pyrolysis technology is getting implausible acceptance for producing liquid fuels due to certain technical advantages [55–57]:
It can ensure preliminary disintegration of the simple oligomer and lignin portions from lignocellulosic biomass with successive upgrading.
The scaling up of this process is economically feasible.
It can utilize second generation bio‐oil feed stocks such as forest residues, municipal and industrial wastes.
It provides easy storability and transportability of liquid fuels.
It can ensure secondary transformation of motor fuels, additives or special chemicals.
The flash pyrolysis process of biomass can give solid, liquid and gaseous products. The bio‐oil production can go up to 75% using flash pyrolysis [58]. This procedure is carried out by speedy devolatilization under inert atmosphere using higher heating rate with high pyrolysis temperatures around 450 and 1000°C. In this process, the gas residence time (less than 1 s) is too little [59]. Nevertheless, this process has poor thermal stability. Due to catalytic effect of the char, the oil becomes viscous and sometimes it contains some solid residues also [60].
Slow pyrolysis can yield good quality charcoal using low temperature and low heating rates. The vapour residence time can be around 5–30 min in this process. The volatile organic fractions present in vapour phase continue to react with each other to yield char and some liquid fractions [61]. The quality of bio‐oil produce in this process is very low. Longer residence time initiates further cracking to reduce the yield of bio‐oil. The process suffers from low heat transfer values with longer retention time leading to enhance the expenditure by higher input of energy [62, 63]. The stoichiometric equation for production of charcoal is shown by [11].
Table 6 below gives the theoretical equilibrium yield of cellulose at different temperatures using slow pyrolysis [11].
Pyrolysis types | Retention time | Rate of heating | Final temperature (°C) | Products |
---|---|---|---|---|
Fast | <2 s | Very high | 500 | Bio‐oil |
Flash | <1 s | High | <650 | Bio‐oil, chemicals and gas |
Ultra‐rapid | <0.5 s | Very high | 1000 | Chemical and gas |
Vacuum | 2–30 s | Medium | 400 | Bio‐oil |
Hydro‐pyrolysis | <10 s | High | <500 | Bio‐oil |
Carbonization | days | Very low | 400 | Charcoal |
Conventional | 5–30 min | Low | 600 | Char, bio‐oil and gas |
Different types of pyrolysis process.
% of products | Temperature (°C) | ||||
---|---|---|---|---|---|
200 | 300 | 400 | 500 | 600 | |
C | 32 | 28 | 27 | 27 | 25.2 |
H2O | 36.5 | 32.5 | 27 | 27 | 22.5 |
CH4 | 8.5 | 10 | 10 | 10 | 9 |
CO2 | 23.9 | 28 | 35 | 35 | 36 |
CO | 0 | 0 | 1.2 | 1.2 | 4.5 |
Equilibrium concentration of gaseous products at different temperature.
A mixture of hydrocarbon was produced earlier from methanol over zeolites like ZSM‐5 [64]. Another patent suggested passing the vapours from pyrolyzer over the bed of zeolite ZSM‐5 to produce short chain hydrocarbon [65]. It was reported that the catalyst of ZSM‐5 can convert bio‐oils generated from the pyrolyzer to alkylated benzene [66]. The disadvantage of using ZSM‐5 as catalyst was coke formation [66]. The researchers concluded that low H/C ratio of bio‐oil caused rapid catalyst deactivation resulting in considerable amount of coke as waste materials [66]. However these disadvantages can be overcome by using circulating fluid bed technology where the fluidized bed can be prepared using different types of catalyst instead of sand [53]. A small‐scale pilot plant level (0.1 to 0.35 kg/h) has also been developed by RTI international [53]. This plant can successfully carry out the pyrolysis of locally available pine biomass to produce bio‐oil. This plant is also trying to carry out the catalytic pyrolysis of wooden chips where by 1 ton of biomass residues can yield 60 gallons of pyrolytic oil per day [53]. Recently other attempts have been made to produce aromatic compound specially benzene, xylene and toluene from biomass substrate [53]. Recently
Recently attempt has been taken to develop catalyst from renewable sources. The ash generated from gasified biomass contains 70–87% of silica in amorphous form which has been used by researchers to produce ZSM‐5 and ZSM‐48 catalyst for bio‐oil upgrading [67]. The biochar derived from duckweed showed excellent catalytic activity for reforming of CH4‐CO2 around 800°C [68]. Catalysts can be mixed with the lignocellulosic substrate earlier to pyrolysis process or separately with the gaseous reactants to obtain desired products. It was revealed that parting of the catalyst and biomass was more operative for the transformation of the required products [69]. This research used chromite (FeCr2O4) as catalyst and it demonstrated favourable outcomes in terms of restricted water production. Table 7 provides summary of zeolite‐based catalyst used for upgrading the lignocellulosic residues until now.
Catalyst | Temp. (°C) | Feedstock | Catalyst effects | Refs. |
---|---|---|---|---|
HZSM‐5 with varying Si/Al2O3 ratios | 500–764 | Kraft lignin | Decreasing the SiO2/Al2O3 ratio from 200/1 to 25/1 and increasing the catalyst‐to‐lignin ratio from 1:1 to 20:1 decreased the oxygenates and increased the aromatics. Aromatics yield increased from 500 to 650°C and then decreased at higher temperatures. Under optimal reaction conditions, the aromatic yields were 2.0% (EHI 0.08) and 5.2% (EHI 0.35). | [70] |
HZSM‐5, Na/ZSM5, HBeta, and H‐USY | 650 | Alkaline lignin | H‐USY had the largest pore size and lowest Si/Al ratio (7) and had the best liquid yield of 75% and aromatic yield of 40%. | [71] |
ZSM‐5, Al/MCM‐41, Al‐MSU‐F, ZnO, ZrO2, CeO2, Cu2Cr2O5, Criterion‐534, alumina‐stabilized ceria MI‐575, slate, char and ashes derived from char and biomass | 500 | Cassava rhizome | ZSM‐5, Al/MCM‐41, Al‐MSU‐F type, Criterion‐534, alumina‐stabilized ceria‐MI‐575, Cu2Cr2O5, and biomass‐derived ash were selective to the reduction of most oxygenated lignin derivatives. ZSM‐5, Criterion‐534, and Al‐MSU‐F catalysts enhanced the formation of aromatic hydrocarbons and phenols. No single catalyst was found to reduce all carbonyl products but ZSM‐5, Criterion‐534 and MI‐575 could reduce most of the carbonyl products that contained hydroxyl groups. ZSM‐5, Criterion‐534, Al/MCM‐41, Al‐MSU‐F, copper chromite, char and ashes increased acetic, formic, and lactic acid. MI‐575 did not increase acids. | [72] |
Dolomite | 500–800 | Waste olive husks | Dolomite increased cracking and gas production. | [73] |
HZSM‐5, Al/MCM‐41, Al‐MSU‐F, and alumina‐stabilized ceria MI‐575, pore sizes 5.5, 31, 15, and NA, respectively | 500 | Cassava rhizome | HZSM‐5 was the most effective catalyst for the production of aromatic hydrocarbons, phenols, and acetic acid and the reduction of oxygenated lignin‐derived compounds and carbonyls containing side chain hydroxyl groups. Only MI‐575 showed a decrease in acetic acid yields. MI‐575 also showed the most increase in methanol with HZSM‐5 a close second. | [74] |
Summary of zeolite‐based catalysts used for biomass upgrading.
Catalytic hydro‐pyrolysis is a kind of catalytic pyrolysis where the pyrolysis is carried out using fluidized bed reactor under the flow of hydrogen. In this process the fluidized bed is replaced by a transition metal catalyst. It was reported that the replacement inert sand with Ni‐based catalyst under atmospheric pressure can convert the bio‐oil into low molecular weight hydrocarbons within short contact time [75].
The importance of appropriate reactor in any process involving pyrolysis cannot be underestimated. Reactors have been designed in such a way as to satisfy specific conditions giving considerations to parameters such as heating temperature, vapour product residence time and required pressure, for a high bio‐oil yield. In considerations of the above, many types of reactors have been developed by researchers for specific assignments. These reactors include the following:
This is a very simple technology that gives priority to the production of bio‐oils, which are relatively uniform in size with low fines content [42]. It is made up of two basic components, that is, the gas cooling compartment and the cleaning system by filtering through cyclone, wet scrubbers and dry filters. During reaction, the solid sample is allowed to pass through a vertical shaft where it encounters an upwardly moving counter current gas stream product. This reactor can be made using either steel, firebricks or concrete and composed of the feeding unit (fuel), a unit for removing the ash and the gas escape unit [77]. The reactor, which has its priority for applications involving small‐scale heat and power, has high ability to conserve carbon and can operate for long time for solid residence, low gas velocity and of course with a low ash carry‐over. It has its limitation in the problem usually encountered during tar removal [78].
This reactor consists of a mixture of two phases, the solid and the liquid and usually accomplished by passing a pressurized fluid through the solid material. It is very popular for fast pyrolysis as it has the following advantages [79]:
The provision of heat transfer is rapid.
It has a good grip of pyrolysis reaction and vapour holding time control.
It has a sufficiently high surface area for contact between the two phases in the mixture.
The heat transfer in the system is exemplary, and
The relative velocity between the phases is very high.
There are different types of fluidized bed reactors, which include bubbling fluidized, circulating fluidized, ablative reactor, vortex reactor, rotating‐disk reactor, vacuum pyrolysis reactor, rotating cone reactor, PyRos reactor, auger reactor, plasma reactor, microwave reactor and solar reactor with each designed with different operating systems and for specific applications.
The construction and operation of this reactor is very simple and is illustrated by Figure 7 [80]. The high presence of solid density in the bed ensures a better temperature control, smooth contact between gas and solid, good transfer of heat and excellent storage capacity. The biomass is heated in an environment devoid of oxygen and decomposed into gas, vapour, aerosols and char and these components are finally collected from the reactor. While the charcoal is collected using the cyclone separator and stored, the vapour is cooled rapidly and condensed into high‐quality bio‐oil and stored with about 70% yield of biomass weight (dry weight) [80].
Bubbling fluidized bed reactor [
The features of this reactor is similar to that of a bubbling fluidized bed reactor described above except the fact that the residence time for the vapours and char is shorter. This makes the gas velocity and the content of char in the bio‐oil to be higher. However, it has a large throughputs advantage. Single and double types of this reactor are available [81]. The basic layout of this reactor is shown by Figure 8 [80].
Recirculating fluidized bed reactor [
In this reactor, heating is done through a molten layer on the surface of the hot reactor and in the absence of fluidizing gas. Biomass melting is done by pressing mechanically the biomass against the wall of a heated reactor and as the melted sample is moved, the pyrolysis vapours evaporate as oil. While this reactor allows for a large biomass particle size (up to 20 mm), the materials does not require excessive grinding [82]. However, the configuration of the reactor is a bit complex owing to the process nature which is mechanical. The reactor does not benefit from the same scale of economy as other reactors due to the fact that scaling functions linearly as heat transfer since it is surface area‐controlled. Two types of this reactor, that is, ablative vortex and ablative rotating disk are used commonly [82].
This is a slow pyrolysis reactor with heat transfer rate very low. This results in a lower bio‐oil yield usually in the range of 35–50 wt% [83]. The design is highly complicated and requirement for investment and maintenance is always high thereby making the technology uneconomically suitable. The biomass is conveyed into the vacuum chamber with a high temperature with the aid of a conveyor metal belt with periodical stirring of the biomass by mechanical agitation [83]. The heat carrier is usually made of a burner while the biomass is melted by heating inductively using molten salts. It has the ability to process larger particle size biomass but requires special solids feeds special discharging devices in order to have an effective seal all the time [83]. The basic lay out of this type of reactor is shown by Figure 9 [83].
Vacuum reactor [
Unlike the fluidized bed reactor, the rotating cone reactor requires the mixing of biomass and hot sand is done mechanically and does not require the use of inert gas. The operating feature is shown by Figure 10 [74]. The feed and the hot sand are fed in from the bottom of the cone while they are transported to the lip of the cone during spinning using centrifugal force and as they get to the tip, the vapour generated is condensed by the condenser [74]. The char and the sand are combusted with the sand being heated up again and reintroduced to remix with fresh feedstock at the bottom of the cone. Though the design of this reactor might be complex, its high bio‐oil yield makes it desirable.
Rotating cone reactor [
The aim of this reactor is to produce a bio‐oil that will not contain any particle. It uses a reactor that is cyclone in nature integrated with hot gas filter. Both the biomass feedstock and the inert heat are fed into the cyclone as particles while the vapours that are recycled are made to transport the solids during the process. The particles move down to the bottom of the cyclone through a centrifugal force, during which time drying, heating up and devolatilization take place simultaneously. The heating temperature is usually 450–550°C with residence time of 0.5–1 s. The reactor is highly economical in terms of investment and bio‐oil yield [84].
This reactor makes use of auger to move the sample feed through a cylindrical tube that is heated up and devoid of oxygen. During this process, the feedstock is pyrolyzed, devolatilized and gasified at a temperature between 400 and 800°C, leading to production of char and condensation of gases into bio‐oil [30].
This reactor is made up of a quartz tube that is cylindrical and fitted with two electrodes made of copper. Feeding of the feedstock is done at the middle using screw with variable speed screw at the top of the tube [85]. The gas flows in the tube is powered by thermal energy produced by the electrodes connected to electrical power source. Inert gas is used to remove oxygen from the compartment as well as producing plasma. Apart from its high consumption of energy, it exhibits the ability to guide against the generation of tar as could be witnessed in slow pyrolysis [86].
This is one of the latest developments in pyrolysis. Here, transfer of energy occurs as a result of interaction between the molecules and atoms using microwave. The whole process of drying and pyrolysis are carried out in a microwave oven chamber connected to electricity source. The carrier gas is inert and is also used to create oxygen‐free chamber. The reactor has proven to be highly effective in chemical recovery from biomass [87]. Among its advantages include effectiveness in heat transfer, ability to effectively control the heating process as well as ability to guide against the formation of undesirable by‐products. It can be used effectively on industrial basis [87].
With this technology, provision has been made for storage of solar energy as chemical energy. It is made up of quartz tube with external wall that is opaque, usually exposed to high concentration of solar radiation, capable of high temperature (>700°C) generation in the reactor [88, 89]. Pollution is reduced with this reactor as the feedstock is never tampered with during heating process unlike the slow pyrolysis where the process heat is generated by a part of the feedstock. Start up and shut down time is also very fast.
Table 8 illustrates the advantages and disadvantages of different types of reactors.
Reactor type | Advantages | Disadvantages |
---|---|---|
Fixed bed | Simplicity in design Reliable results Biomass size independent | High carbon conservation Long solid residence time Low ash carry over Difficult to remove char |
Bubbling fluidized bed | Simple design Easy operational procedures | Good temperature control Suitable for large‐scale application Small particle sizes are needed |
Circulating fluidized bed | Well‐understood technology Better Thermal control Larger particle sizes can be processed | Large‐scale production difficult Complex hydrodynamics Char is too finer |
Rotating cone | Centrifugal force circulates hot sand and biomass substrate No carrier gas required | Difficult operational process Smaller particle sizes needed Large‐scale application is difficult |
Vacuum | The oil is clean Can process larger particles of 3–5 cm No carrier gas required Lower temperature required Condensation of liquid product is easier | Slow process Solid residence time is too high Require large‐scale equipment Poor heat and mass transfer rate Generates more water |
Ablative | Inert gas is not required Larger particles can be processed | System is more intensive Moderate temperature required Reactor is costly Lower reaction rate |
Auger compact | No carrier gas required | Lower process temperature Moving parts in hot zone Heat transfer in larger scale is not appropriate |
PyRos | Compact and low cost Efficient heat transfer Short gas residence time | Complex design Solids in the oil Alkali dissolved in the oil High temperature required |
Plasma | High energy density High heat transfer Effective Process control High electrical power consumption | High operating costs Small particle sizes required |
Microwave | Efficient heat transfer Exponential control Compact structure Higher heating rate Large‐size biomass can be processed Uniform temperature distribution | High temperature High electrical power consumption High operating costs |
Solar | Use renewable energy Higher heating rate | High temperature High costs Weather dependent |
Biochar is solid amorphous carbonaceous materials obtained from thermal degradation of lignin and hemicellulose polymer during the pyrolysis process. The physiochemical properties of biocar matrix greatly vary with reactor type and design, biomass composition, particle size and extent of drying, chemical activation, heating rate, reaction time, pressure, flow rate of inert gas,
Based on biomass composition and process parameters of pyrolysis, the composition of syngas varies. Usually gaseous products obtained after pyrolysis mostly comprises of H2 and CO. It also contains negligible fraction of CO2, N2, H2O, mixture of alkanes, alkenes and alkynes, such as CH4, C2H4, C2H6, tar, ash, etc. [104]. Higher pyrolysis temperature leads to endothermic reaction. With the increase of pyrolysis, the vaporization of moisture from the biomass takes place initially. After that, thermal degradation and devolatilization take place. At this stage, tar is produced and volatile species are released. A series of secondary reactions such as decarboxylation, decarbonylation, dehydrogenetaion, deoxygenation and cracking takes place to produce mixture of syngas. Therefore, higher temperature initiates the tar decomposition, which results in the production of syngas with decreased yield of oil and char. For a given temperature, dry biomass yields the highest amount of gas at the early stage of pyrolysis, whereas with wet biomass the production of the maximum quantity happens later in the process. This is evident and expected as increase in humidity results in increase in drying time. The cracking of hydrocarbon produces hydrogen at higher temperature. Due to presence of oxygen in biomass, CO and CO2 are produced. The presence of oxygenated polymer that is cellulose determines the evolution of carbonated oxides produced [105]. The lighter hydrocarbons such as CH4, C2H4, C2H6, etc. is formed due to reforming and cracking of heavier hydrocarbons and tar in the vapour phase [106]. Plasma reactor using radio frequency can produce up to 76.64% syngas [85]. The advantages of using syngas are that it produces a considerably minor quantity of unburnt hydrocarbon (HC) and carbon monoxide (CO) with higher emissions of nitrogen oxides (NO
The oil extracted after pyrolysis is a mixture of about 300–400 compounds [111]. The oil obtained after pyrolysis has tendency to become viscous due to ageing as numerous physical and chemical changes with subsequent loss of volatile matters take place. However, the ageing process can be slowed down by storing them in cool places [35]. Previously it was found that energy crops can yield oil with high ash/metal content and water [112]. The presence of water will lower the heating values as well as it will make the phase separation difficult [112]. Thus for commercial application, presence of ash and lignin inside the biomass substrate should be carefully monitored. Earlier thermal efficiency of the pyrolysis oils was compared with diesel, but they demonstrated unwarranted delay in ignition [113]. On the other hand, the quantity, quality and constancy of pyrolysis oil can also be improved by method variables such as heating rate, temperature and retention times [114]. Type of different reactors (ablative and fixed), particle size and char accretion can disturb the amount and feature of the pyrolysis oil. Till currently, there is no inclusive research to diminish these things. Therefore, additional research is obligatory in order to achieve a complete representation of thermochemical transformation processes to yield superior quality pyrolysis oil. Bio‐oil which should be used commercially should preserve its chemical and physical properties such as constancy and viscosity. If the oil contains low molecular weight compound, it is possible. The oil contains high molecular weight compounds if the starting biomass contains larger proportion of lignin.
The utilization of food crops such as soybean, maize and sugarcane for producing ethanol and biodiesel may not endure for long since these crops are primarily cultivated for consumption. The need therefore arise for a more sustainable means of generating these materials from other sources such as biomass materials in addition to others already being researched into. However, none of these has proven to be feasible economically yet, but there is great hope on utilizing lignocellulosic biomass for this purpose through pyrolysis process even though it is still faced by some teething challenges. Some tangible efforts have been made by Ensyn and Dyna Motive companies to commercialize the utilization of biomass materials and other agricultural wastes in the generation of biofuels through fast pyrolysis process. These materials are readily available at little or no cost thereby making their utilization highly economical. While Dyna Motive concentrates on how to make energy systems from the fuels produced more environmentally friendly, Ensyn on the other hand is looking towards utilizing the chemicals that may be produced from the system as co‐products for other usage such as food smoking. These efforts have since led to production of biofuels from biomass materials. Other notable pyrolysis companies that have been involved in these activities are Pyrovac and Renewable Oil International which use vacuum pyrolysis technique in addition to other smaller pyrolysis plants which are available worldwide. From available data, it clear that fluidized bed reactor are mostly in use for production of bio‐oil using biomass while this is followed by other technologies.
The perusal of the literature showed that the transformation of biomass to value‐added products still needs to resolve some trials such as determining the relation between the starting precursors or feedstock and the overall operation of the pyrolysis plant, upgrading the consistency of the pyrolysis reactions in terms of complete energy and material balances to become sustainable for profitable applications. This chapter elaborately described about the principle of pyrolysis technology including the choice of effective parameters for pyrolysis, types of reactor,
The major challenge of pyrolysis process is to improve the process by enhancing the product quality and quantity as well as lessening the costs and reduce hazardous environmental impact.
Appropriate selection of biomass is a crucial factor to obtain high bio‐oil yields. Biomass containing high cellulose content can be selected, as bio‐oils are mostly derived from it whereas lignin‐based biomass can be used for biochar production. Furthermore, biomass with low moisture content is appropriate to decrease the drying costs and enhance the quality of the extracted oil.
The kinetics of pyrolysis of biomass can proceed by several parallel paths. However, application of low temperature would produce lower activation energy to yield mainly char and gas. On the contrary, an enhanced temperature will lead higher activation energy to produce mainly condensable vapours, oils and liquid aerosols. In order to obtain maximum liquid fuels, it is required to heat the biomass speedily at a suitable elevated temperature. Nevertheless, rapid heating of biomass needs smaller particle sizes of the precursors which can initiate constant particle heating. In this regard, fluidized beds are frequently used as efficient reactor type. The disadvantages of fluidized reactor have been overcome by using ablative pyrolysis and auger pyrolysis methods. These types of novel approaches can endure a wider range of variable sizes of the particles.
The separation process of the biochar should be effective and fast to reduce contamination of the bio‐oil.
Amendments should be done for upgrading the engine, turbine and boiler combustion systems for proper utilization of pyrolysis bio‐oil while the effect of physiochemical properties of the oil, emission of small particles, combustion efficiency and slag and carbon deposition during the burning process should be taken under considerations.
Until recently, sustainable industrial‐scale catalytic pyrolysis systems are not identified. Only some transition metal catalysts have been developed and studied for lab‐scale approach to improve gas production.
Though a lot of studies have been done on pyrolysis economy but most of those were restricted for small‐ or pilot‐scale production. Detail calculation for industrial‐scale pyrolysis plant is essential to inaugurate this technology up to a larger extent for practical phase applications.
The usage of bio‐oil as a renewable liquid fuel is hindered due to its underprivileged physicochemical properties. Presently, commercial projections for liquid fuel uses are dependent on its successful alteration to gasoline, diesel or kerosene, or chemicals such as olefins or aromatics. However, these techniques are still in emerging stage.
It has become increasingly common to see people interacting with their smartphones while performing other activities at any time and place. There are millions of applications that can be used to keep in contact with family and friends, order food, take a taxi, book a hotel, set up a blind date, or simply to be reachable at work. However, despite this wide variety of applications and content to be created and visited, it is not surprising that most of the time spent on the phone is destined to the use of social networks. According to [1], smartphone, along with its cousin, tablet and a fast-expanding family of wearables and other smart devices are transforming the way people live, work, play, connect, and interact. Martin [2] suggests that the time spent in the digital world on mobile devices such as smartphones and tablets is longer than the time spent on traditional devices such as computers and laptops, in some countries like Indonesia or India, where the use of smartphones and tablets accounts for 90% of the time spent on digital media. Undoubtedly, this is due to a greater access to these devices, with increasingly cheaper purchasing options and better features, to the extent that today these technologies can perfectly replace laptops for many people. Additionally, another factor that indeed played an important role in the increased use of mobile devices is mobile apps. In this sense, we can confirm that mobile devices definitely changed digital entertainment.
\nThe influence of mobile apps is evidenced by the fact that their use represents more than 90% of the time spent on smartphones and tablets, with Latin American countries on the top of the list: Argentina (94%), Mexico (92%), and Brazil (89%). In addition, mobile devices are used more than traditional devices like computers to access the digital world. This behavior is common in users of all ages, but it is more concentrated in women [2]. Regarding the reach of mobile apps, the app universe is dominated by a small group, with 96% of the time spent on no more than 10 apps [2], most of them corresponding to social networks such as Facebook, Instagram, and WhatsApp.
\nIn connection, according to Smith [3], Facebook has more than 2.234 billion active users per month. Sixty-six percent of these users use the app daily, out of which 51% visit it several times per day, which translates to more than 2 trillion posts and 1.13 trillion likes since the launch of the app.
\nAnother popular social network is Instagram. This app has 1 billion active users per month. Twenty-two percent of them use it daily, out of which 38% check the app multiple times during the day [3].
\nFor its part, WhatsApp, a free app that offers messaging and calls in a simple, safe, and reliable way to phones all over the world, has more than 1.8 billion active users. Seventy percent of them use the app daily, which translates into 65 billion messages sent, 100 million voice calls, and 55 million video calls per day [3].
\nThese data seem to indicate that the use of WhatsApp is more intensive than other popular social networks, even though it is not the most popular social network, and some people could categorize it as a messaging application instead of a social network. In view of this, the research question that arises is what makes users prefer this social network? Is an attractive proposal and design enough to capture a large quantity of people, or there is something else in play? Is it only on the users to decide what social networks will be used? This study seeks to answer these questions, specifically regarding the intention to use WhatsApp and using an adaptation of the technology acceptance model known as UTAUT2 to achieve this goal [4].
\nCreated as an extension to the world of the theory of reasoned action [5], the technology acceptance model [6] corresponds to one of the most renowned, analyzed, and studied models in the literature. This model seeks to understand how and why users accept and use a technology, using perceived ease of use and perceived usefulness as prediction variables of the intention to use. TAM2 was created after TAM and explains the intentions to use a specific technology in terms of social influence and cognitive processes [7]. To this end, the model incorporates constructs such as subjective norm, image, job relevance, output quality, result demonstrability, experience, and voluntariness. Three years later, the unified theory of acceptance and use of technology come to the fore [8]. This theory seeks to predict the intention to use through the variable performance expectancy, effort expectancy, and social influence, which are defined in a way very similar to perceived usefulness, perceived ease of use, and subjective norm, respectively. This set of variables adds up to facilitating conditions, which have a direct effect on usage behavior, and is defined as the extent to which the individual believes that certain organizational and technical infrastructures exist to support the use of a system [8]. Two new variables incorporated into the model correspond to gender and age, which are moderating variables, as well as experience and voluntariness. The UTAUT2 emerged more recently, as an extension of the UTAUT and to study the acceptance and use of technologies in a consumption context [4]. This model incorporates three new variables, namely, hedonic motivation, price value, and habit.
\nAs for social networks, several authors attempt to explain the use of online social networks (OSNs). According to Schneider et al. [9], users commonly spend more than half an hour interacting with OSNs, and the byte contributions per OSN session are relatively small. From this result, we could assume that most users are consumers and not content creators. In the case of Facebook, Ellison et al. [10] propose that this network might provide greater benefits for users experiencing low self-esteem and low life satisfaction. As for Twitter, Java et al. [11] suggest that people use microblogging to talk about their daily activities and to seek or share information. With respect to Instagram, motives were positively associated with both usage and self-presentation [12]. People use social networks such as Facebook, Twitter, and Instagram for the sole purpose of entertainment and maintaining contacts with their friends’ list [13]. As may be seen, the motivations to use social networks are varied. According to Brandtzæg and Heim [14], people use social networks to get in contact with new people, to keep in touch with their friends, and general socializing, and this could be closely related to the variable social influence proposed as a latent exogenous variable in the UTAUT2 [4]. Xu et al. [15] also suggested that user utilitarian gratifications of immediate access and coordination; hedonic gratifications of affection and leisure—which could be related to perceived usefulness and perceived ease of use, respectively; and website social presence were three positive predictors of social network site usage.
\nRegarding WhatsApp, there are specific motivators linked to cost, sense of community, and immediacy [16], as well as to unlocking new opportunities for intimate communication [17]; addictive behaviors have even been detected toward the application [18]. A number of studies about the use of this innovative technology have been conducted [19], which have detected a series of factors that positively or negatively influence the use of WhatsApp, such as the importance of family groups [20], the use of status within the application [21], interactions with the education field [22, 23], and concerns about privacy [24], among others. This study intends to analyze WhatsApp consumer behavior from the perspective of the variables that influence the intention to use this technology and to determine what these variables are and how they articulate to affect the intention to use WhatsApp, using the variables proposed in the UTAUT2 model [4].
\nThe proposed model considers the following latent exogenous variables that explain the intention to use WhatsApp. The model proposes that the following four variables positively influence the latent endogenous variable behavior.
\nH1: Hedonic motivation is defined as the pleasure individuals feel when they behave in a certain way or perform a specific activity [25].
\nH2: Performance expectancy is the extent to which using a technology will provide benefits to consumers in performing certain activities [4].
\nH3: Effort expectancy is the degree of ease associated with the consumers’ use of technology [4].
\nH4: Social influence is the extent to which consumers perceive that importantly others believe that they should use a particular technology [4]. This social influence or subjective norm is closely related to the intention to use a social network [26, 27, 28].
\nBehavioral intention is defined as the set of motivational factors that indicate how willing people are to try or how much effort people intend to put forth to develop a particular behavior [29].
\nThe structural model with the latent variables and their proposed relationships is shown in Figure 1.
\nProposed model.
In relation to the latent variables included in the structural model, Table 1 shows the observable variables measured in the questionnaire. It must be noted that these variables were measured through a Likert scale that ranged from 1 to 5, where 1 means “totally disagree” and 5 “totally agree.”
\nI find WhatsApp useful in my daily life | \n
Using WhatsApp increases my chances of achieving things that are important to me | \n
Using WhatsApp helps me accomplish things more quickly | \n
Using WhatsApp increases my productivity | \n
Learning how to use WhatsApp is easy for me | \n
My interaction with WhatsApp is clear and understandable | \n
I find WhatsApp easy to use | \n
It is easy for me to become skillful at using WhatsApp | \n
Using WhatsApp is fun | \n
Using WhatsApp is enjoyable | \n
Using WhatsApp is very entertaining | \n
People who are important to me think that I should use WhatsApp | \n
People who influence my behavior think that I should use WhatsApp | \n
People whose opinions that I value prefer that I use WhatsApp | \n
I intend to continue using WhatsApp in the future | \n
I will always try to use WhatsApp in my daily life | \n
I plan to continue to use WhatsApp frequently | \n
Observed variables.
The first four variables refer to performance expectancy, while the four next questions refer to effort expectancy. Then, the following three variables refer to hedonic motivation and the next three to social influence. Finally, the last three questions refer to the behavioral intention of using WhatsApp. The questionnaire also contains variables to measure demographic information such as sex, age, and level of education completed, as well as questions to measure behavioral variables such as the number of hours per day spent using WhatsApp and the number of times per day that respondents use this application.
\nTo conduct this study, a questionnaire was applied that contained the observable variables described above, as well as the questions for demographic characterization. The instrument was applied to 579 people through SurveyMonkey. Sampling was non-probabilistic and by convenience and targeted young people who use the Internet and social networks. The survey was sent through these two channels.
\nOnce answers were collected, a univariate analysis was conducted to obtain the respondents’ profile. Afterward, the reliability and internal consistency of each proposed construct were assessed by a Cronbach’s alpha test. Finally, the structural analysis proposed in Figure 1 was carried out using the software IBM SPSS Amos, taking care to obtain adequate absolute, incremental, and parsimony adjustments. Once the structural equation model analysis was completed, a cluster segmentation analysis was executed to determine the different profiles of WhatsApp users based on the answers of the attitude variables proposed in the model.
\nFirst, with respect to the descriptive analysis of the questionnaire answers and as mentioned above, 579 questionnaires were filled out. Fifty-seven percent of respondents are women, 60% of the sample are university students, and 25% completed higher education. In terms of age, the sample is concentrated in an age range from 20 to 40 years, with a mean age of 25.6 years.
\nRegarding the total of respondents, as shown in Figure 2, 62.3% express using WhatsApp for leisure, followed by 23.4% that use it for informative purposes.
\nMain reason why WhatsApp is used.
When comparing the motives to use WhatsApp by sex, the trend remains constant, with 62.4% of men using WhatsApp for leisure, against 57.5% of women. No significant differences are observed by age and educational level.
\nRegarding frequency of use, most people report using WhatsApp several times per day (89%): 90.4% for women and 87.1% for men. In this same line, with respect to the observable variables of intention to use, 58.4% of men and 63.6% of women declare totally agreeing that they will continue to use WhatsApp in the future (I intend to continue using WhatsApp in the future), 36.4% of men and 40.0% of women totally agree that they use WhatsApp in their daily life (I will always try to use WhatsApp in my daily life), and 48.0% of men and 53.5% of women declare total agreement with using WhatsApp frequently (I plan to continue to use WhatsApp frequently). In sum, for the three observable variables of the factor intention to use, the percentage of women who totally agree is slightly higher than that of men, and therefore, we can assume that women are more likely to keep using WhatsApp in the future. As seen in the first section, women tend to use mobile devices to access online content more than men, and this trend evidently replicates itself in the use of a mobile app like WhatsApp.
\nContinuing with the analysis, a Cronbach’s alpha reliability test is conducted. Results for each of the four factors proposed in the model from Figure 1 as latent exogenous variables and the latent endogenous variable behavioral intention are shown in Table 2.
\nPerformance expectancy | \n0.736 | \n
Effort expectancy | \n0.801 | \n
Social influence | \n0.867 | \n
Hedonic motivation | \n0.725 | \n
Behavioral intention | \n0.812 | \n
Cronbach’s α reliability analysis.
All five structural variables yielded satisfactory results in terms of construct reliability, with results over 0.700 in all cases.
\nSubsequently, the structural model was analyzed using IBM SPSS Amos, obtaining adequate absolute, incremental, and parsimony adjustment. Figure 3 shows the structural equation modeling, in which all relations proposed are significant (p value < 0.001).
\nResult model.
As shown in Figure 3, the model reaches R2 = 0.52 to model behavioral intention. In this sense, the most influencing variable is hedonic motivation, with a standardized regression weight of 0.499. Consequently, people use WhatsApp mainly motivated by pleasure, entertainment, and leisure. This is also related to the 62.3% of the sample that stated using WhatsApp for leisure. The other variables that explain the behavioral intention to use this instant messaging application are social influence with a standardized estimate of 0.333, followed by performance expectancy (0.305) and effort expectancy (0.256).
\nRevising observable variables, it must be noted first that for the factor hedonic motivation, the variable “using WhatsApp is fun” obtains a very high mean of 4.37, while the mode is 5, that is, “totally agree.” Indeed, people find that using this app is fun (Table 3).
\n\n | Mean | \nStd. deviation | \n
---|---|---|
Using WhatsApp is fun | \n4.37 | \n0.84 | \n
Using WhatsApp is enjoyable | \n4.28 | \n0.89 | \n
Using WhatsApp is very entertaining | \n4.28 | \n0.83 | \n
Observable variables of hedonic motivation.
Additionally, it is interesting to observe social influence, in which the variable “people who are important to me think that I should use WhatsApp” obtains a mean of 3.57 and a mode of 3, which implies a certain degree of indifference to social influence. In fact, if the three observable variables of social influence are considered, the mean obtained is 3.75. This might be explained by the fact that individuals do not consider others’ opinions to be very relevant when using WhatsApp. This is supported by the standardized regression coefficient 0.333 for this latent exogenous variable in the structural equation model, which albeit statistically significantly does not represent a high impact. A second reading of these results shows that people who are important to the respondent might not approve of the use of WhatsApp by the respondent, shedding some light on a control problem related to this behavior or perhaps an addiction, as mentioned in the literature review. A third reading leads us to conclude that as WhatsApp is widely used, the opinion of people important to the individual is not absolutely important to him, and what would probably matter would be whether those people use the app. Regardless of the underlying reason, the result is relevant because WhatsApp is an application that allows people to communicate with family and friends, and therefore, a high valuation was expected (between 4 and 5) for the social influence factor (Table 4).
\n\n | Mean | \nStd. deviation | \n
---|---|---|
People who are important to me think that I should use WhatsApp | \n3.85 | \n1.07 | \n
People who influence my behavior think that I should use WhatsApp | \n3.57 | \n1.09 | \n
People whose opinions that I value prefer that I use WhatsApp | \n3.84 | \n1.08 | \n
Observable variables of social influence.
Regarding the observable variables of effort expectancy, Table 5 shows that all have a rather high mean, between 4 and 5, with a standard deviation lower than 0.80 in all cases. In fact, WhatsApp is perceived as easy to use, which, according to the structural equation model, positively contributes to the intention to use the application but to a lesser extent than the other latent variables proposed in the model.
\n\n | Mean | \nStd. deviation | \n
---|---|---|
Learning how to use WhatsApp is easy for me | \n4.66 | \n0.74 | \n
My interaction with WhatsApp is clear and understandable | \n4.54 | \n0.74 | \n
I find WhatsApp easy to use | \n4.68 | \n0.71 | \n
It is easy for me to become skillful at using WhatsApp | \n4.58 | \n0.80 | \n
Observable variables of effort expectancy.
In the case of performance expectancy, it is noteworthy that the observable variable “using WhatsApp increases my productivity” has a high dispersion, with a standard deviation of 1.366 and a mean of 3.07. This casts some doubts on the applicability of the variable to a technology of these characteristics. However, if this variable is removed from the study, the scale of performance expectancy maintains a Cronbach’s α of 0.783; therefore, it should not be eliminated. Considering the high dispersion of the answers represented in the standard deviation, we will delve into this point by means of a cluster analysis, since the existence of different segments could help understand this result (Table 6).
\n\n | Mean | \nStd. deviation | \n
---|---|---|
I find WhatsApp useful in my daily life | \n4.47 | \n0.86 | \n
Using WhatsApp increases my chances of achieving things that are important to me | \n3.72 | \n1.21 | \n
Using WhatsApp helps me accomplish things more quickly | \n4.02 | \n1.12 | \n
Using WhatsApp increases my productivity | \n3.07 | \n1.37 | \n
Observable variables of performance expectancy.
With the aim of elaborating on the results, a cluster analysis is conducted based on the observable variables of the proposed model. Two segments were found, which do not differ in sex or age but in the usefulness perception of WhatsApp. The values of the four observable variables of performance expectancy are presented in Table 7.
\n\n | Cluster 1 | \nCluster 2 | \n
---|---|---|
I find WhatsApp useful in my daily life | \n4.01 | \n4.83 | \n
Using WhatsApp increases my chances of achieving things that are important to me | \n2.8 | \n4.21 | \n
Using WhatsApp helps me accomplish things more quickly | \n3.22 | \n4.54 | \n
Using WhatsApp increases my productivity | \n2.3 | \n3.55 | \n
Cluster analysis and performance expectancy.
A very low valuation by users from Cluster 1 is observed for the variables “using WhatsApp increases my chances of achieving things that are important to me,” “using WhatsApp increases my productivity,” and “using WhatsApp helps me accomplish things more quickly.” This seems to point to the existence of a certain degree of indifference and even disagreement with the contribution of WhatsApp in terms of productivity and utility for the user. In other words, although people from Cluster 1 perceive WhatsApp as useful for their daily routine, this usefulness is not understood as a contribution to their productivity and performance in matters important to them but as a self-referential usefulness. This is completely in agreement with the results, which indicate that people use WhatsApp motivated mainly by leisure, as observed in the first part of the analysis. In addition, individuals from Cluster 1 declare that WhatsApp is a useful app, but it does not help them in their tasks. From this, the following question arises: what is it useful for? Probably this answer has to do with certain degree of causality over other variables, for example, WhatsApp is useful to reach friends or to entertain yourself. But, it is definitely useful in contexts linked to leisure and unrelated to the user’s productivity and duties.
\nIt must be also noted that the highest educational level completed by people from Cluster 1 is concentrated in university education and secondary education, while Cluster 2 users have university education and postgraduate studies. This can help explain the differences in performance expectancy, since Cluster 1, represented by university students, does not perceive WhatsApp as a support to its tasks and duties, while Cluster 2, represented by people already in the world of work, does see WhatsApp as a supporting tool for their activities and obligations. This leads us to believe that albeit not the focus of this study, WhatsApp could have a positioning associated with social network and leisure for Cluster 1 and one associated with a messaging app for Cluster 2.
\nWhen analyzing the main motive that each cluster has for using WhatsApp, the trend remains constant, with leisure as the dominant motive for Cluster 1 (72.5%) and Cluster 2 (56.4%), although the percentage is slightly lower in the latter, as shown in Table 8.
\n\n | Cluster 1 (%) | \nCluster 2 (%) | \n
---|---|---|
Work | \n7.0 | \n10.7 | \n
Leisure | \n72.5 | \n56.4 | \n
Academic | \n4.2 | \n11.4 | \n
Informative | \n16.2 | \n21.4 | \n
Cluster analysis and motivation.
Even when in both cases the major motivation is leisure, it must be noted that differences exist in terms of the distribution of the same. In the case of Cluster 2, the other motives become important, particularly the motive “informative” (21.4%). Moreover, if we had a dichotomy between leisure and non-leisure, in which non-leisure comprises work, study, and information, Cluster 2 would be totally balanced between people who use WhatsApp for leisure and people who use it for other reasons. This obviously helps understand the differences between both segments with respect to the latent exogenous variable “performance expectancy.”
\nThen, an analysis of structural equations is performed seeking to test the proposed model through the samples of the two separate clusters. In this regard, although model fit indices are not optimal, it is necessary to emphasize that the relative weight of each latent exogenous variable on the intention to use WhatsApp responds to the differences shown by both clusters in the previous descriptive analysis. Figures 4 and 5 show the results of each analysis of structural equations for each cluster.
\nCluster 1 result model.
Cluster 2 result model.
As shown in Figure 4, the most influencing variable is hedonic motivation, with a standardized regression weight of 0.448. Consequently, Cluster 1 uses WhatsApp mainly motivated by pleasure, entertainment, and leisure. This is also related to the 72.5% of the cluster that stated using WhatsApp for leisure. The other variables that explain the behavioral intention to use this instant messaging application are social influence with a standardized estimate of 0.311, followed by performance expectancy (0.386) and effort expectancy (0.261). As can be seen, Cluster 1 highlights the importance of hedonic motivation against the other variables with respect to the total sample.
\nAs shown in Figure 5, the most influencing variable is hedonic motivation, with a standardized regression weight of 0.442. Consequently, Cluster 2 also uses WhatsApp mainly motivated by pleasure, entertainment, and leisure. This is also related to more than a half of the cluster stated using WhatsApp for leisure. The other variables that explain the behavioral intention to use this instant messaging application are social influence with a standardized estimate of 0.272, followed by performance expectancy (0.351) and effort expectancy (0.321). As can be seen, this cluster also highlights the importance of hedonic motivation against the other variables with respect to the total sample, but there is an increase in the relative weight of the effort expectancy.
\nTo close this point, the results obtained invite us to revise whether the observable variables proposed for performance expectancy can be applied to a technology that is perceived as pertaining to leisure and entertainment.
\nBased on the results of this study, we observe that the most influential variable for the intention to use WhatsApp is hedonic motivation, i.e., people use WhatsApp because it is fun, enjoyable, and very entertaining. This adds up to what is expressed by respondents, who report that their main motivation to use WhatsApp is leisure, which lead us to think that this application is seen more as an entertainment than a communication tool or, in other words, people use this app to communicate with people they are close to and seek entertainment in that interaction, as well as new opportunities for intimate communication [17].
\nAlthough all the variables are significant in the proposed model, the low impact of the variable social influence must be highlighted, as this was expected to be much more influential, considering that WhatsApp is an instant messaging application that does not work if people important to the user are not using it. This may indicate that social influence, in the case of an application already in use, translates into whether or not people important to the user’s decision-making process use the app and is not related to the opinion these people have regarding the user’s conduct.
\nFurthermore, the variability of the responses in the observable variables of the dimension performance expectancy seems to indicate that WhatsApp may have use drivers that vary among groups of people. To support this hypothesis, the cluster analysis yields two groups of users, whose main difference is related to the valuation of the observable variables of the dimension performance expectancy as well as the main motivation to use this application. As mentioned above, people in general use WhatsApp for leisure and entertainment; however, a great part of Cluster 2 declares that they use the app for motives other than leisure. Consequently, Cluster 1 presents valuations of indifference and disagreement regarding the usefulness of WhatsApp for their activities and duties. Consequently, there are at least two different segments of WhatsApp users motivated by different reasons, even though cross-cutting leisure and entertainment is the main motivation to continue using this technology.
\nFrom an AI/ML perspective, this study helps to guide the way in which the software behind WhatsApp should conduct their different learning processes about the user. Indeed, if we consider the results described above where hedonic motivation and social influence are the variables with the greatest influence on behavioral intention, WhatsApp should aim to develop its ML in the sense of generating updates that allow greater fun and entertainment to its users, with virtual reality features, camera filters, new emojis, photo effects and filters, and even games. In summary, WhatsApp could guide their ML to know in a better way how the user enjoys using WhatsApp, making it an increasingly entertaining mobile application.
\nLikewise, considering the social influence, WhatsApp should guide its AI toward a greater social role as a messaging application, similar to Facebook and other social networks, where the user can connect with new “recommended friends,” for example, according to their common interests and according to the number of contacts in common. In summary, the development of AI in WhatsApp could be oriented to a social network role over a simple instant messaging application.
\nFinally, the present chapter helps to understand what variables are involved in the behavior of users of these applications, information that can be used for the development of AI/ML ability of this application, making it adaptive to the needs of the user that can vary according to the context and the expected benefit, as our cluster analysis shows, ergo, to find ways to present the right service at the right time and with the right quality [30]. As stated before, this study also evidences the existence of consumer clusters in which users satisfy different needs with this mobile application, which indeed represents new opportunities for similar applications that aim to challenge the dominance of WhatsApp on the instant messaging field.
\nWhatsApp, Instagram, and Facebook are registered trademarks, and the author only uses them as a reference in his study due to the high level of use by the world population.
\n"I work with IntechOpen for a number of reasons: their professionalism, their mission in support of Open Access publishing, and the quality of their peer-reviewed publications, but also because they believe in equality. Throughout the world, we are seeing progress in attracting, retaining, and promoting women in STEMM. IntechOpen are certainly supporting this work globally by empowering all scientists and ensuring that women are encouraged and enabled to publish and take leading roles within the scientific community." Dr. Catrin Rutland, University of Nottingham, UK
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