Perspectives and Progress in Bioethanol Processing and Social Economic Impacts

Abstract

The liquid biofuel bioethanol is widely produced worldwide via fermenting sugars extracted from a variety of raw materials, including lignocellulose biomass, one of the world’s most abundant renewable resources. Due to its recalcitrant character, lignocellulose is usually pretreated by mechanical, chemical, and biological methods to maximize sugar recovery. Pretreated lignocellulose biomass undergoes a fermentation process performed sequentially or simultaneously to saccharification. The different fermentation strategies (e.g., separate or simultaneous hydrolysis and fermentation or co-fermentation) and conditions (e.g., inoculum type load, agitation, temperature, and pH) affect ethanol yield. Genetic modification of the inoculum has been focused recently to improve ethanol tolerance and as well as to use different sugars to enhance the performance of the microorganisms involved in fermentation. Nonetheless, these improvements result in a substantial increase in costs and have certain environmental costs. This review offers an overview of advancements in bioethanol production, with a primary focus on lignocellulosic feedstock, while also considering other feedstocks. Furthermore, it provides insights into the economic, social, and environmental impacts associated with bioethanol production.

1. Introduction

The global population has grown massively over the last century, increasing from 2.7 billion people in 1955 to over 7.8 billion in 2022, resulting in a greater demand for energy resources that has been fulfilled by fossil fuels (FFs) [1]. FFs are nonrenewable energy sources that pose a threat to the environment as well as the global economy, being the primary contributors of greenhouse gas (GHG) emissions. The use of FFs in the transportation sector is responsible for 24% of global CO₂ emissions [2,3]. To combat climate change, several countries are shifting towards renewable fuels such as bioethanol, biodiesel, and bio-hydrogen as alternatives to conventional fuels like oil, coal, and natural gas [4,5]. Biofuels are increasingly seen as a way to improve energy security, supply, GHG mitigation, and transport sector development [6]. According to the Renewable Fuels Association (RFA), bioethanol is the most widely produced liquid biofuel in the world, with 142.6 billion liters generated from vegetable biomass and algae, making it a crucial player in the transport sector [7]. Bioethanol is an alcohol that is produced by the microbial fermentation of carbohydrates. During this process, microorganisms break down organic molecules into simpler products, including ethanol, carbon dioxide, and other by-products. Currently, the focus of bioethanol production centers on its application within the transportation sector. Governmental regulations have played a pivotal role in incentivizing the ethanol market to reduce dependency on fossil fuels [8]. Notably, the USA and Brazil have emerged as major contributors, generating 61.54 and 29.85 billion liters of ethanol, respectively, predominantly derived from food crops such as corn and sugarcane. However, the adverse environmental impacts associated with waste disposal have spurred intensive research into technologies aimed at integrating waste materials into the biofuel conversion process, with a primary emphasis on bioethanol [9]. In the case of Mexico, as reported by Carillo-Nieves et al. [10], the country leads global production in 71 agro-food products and holds the top position in a total of 181. Consequently, diverse scenarios are under evaluation to enhance the efficient production of second-generation (2G) ethanol, employing consolidated bioprocessing methods. Brazil has been at the forefront of integrated biorefinery research, focusing on both first-generation (1G) and second-generation (2G) sugarcane processes. This involves the predominant production of bioethanol and advancements in upgrading for jet fuel applications [11]. The production of bioethanol not only plays a crucial role in reducing carbon emissions but also contributes significantly to fuel security. In general, the bioethanol production process is categorized into four generations based on the raw materials used and the associated processing technologies [12,13,14].

First-generation bioethanol is produced using crops intended for food consumption as raw materials. These crops can be divided into two groups: the first includes sugarcane, sugar beet, sweet sorghum, and fruit, as well as sugar refinery residues. The second group includes starch sources such as cereals, tubers, and roots, legumes, and green and unripe fruits, with maize, sorghum grains, wheat, cassava, potatoes, and barley being commonly used [14,15]. In 2019, Brazil and the USA were the largest bioethanol producers, using corn and sugarcane as their main raw materials, and together accounting for 84% of total world production. In the USA, 94% of bioethanol is produced from corn starch, whereas in Brazil, 99% is obtained from sugarcane [16]. The use of first-generation feedstocks for bioethanol production raises a contentious issue as these crops are primarily intended for food or feed purposes, and their use in biofuels production can cause significant market price increases due to the use of chemical fertilizers to improve yields.

Second-generation bioethanol comes from lignocellulosic biomass (LCB). Due to its high annual production of 170 billion metric tons [15], lignocellulose is a readily available and easily accessible bioresource, which makes it an attractive option for bioethanol production [17]. LCB can be derived from various sources, such as agricultural residues (straws, stover, leaves, bagasse, etc.), forest residues (sawdust, pruning’s, chips, etc.), wood (soft and hardwoods, such as pine, spruce, and aspen), energy crops (alternative feedstocks relieving the food vs. fuel competition) such as Switchgrass or Miscanthus (i.e., Miscanthus giganteus, Miscanthus sacchariflorus, Miscanthus sinensis), and municipal solid waste [18,19]. Additionally, the use of lignocellulosic wastes for bioethanol production significantly reduces environmental contamination [20,21]. Bioethanol production from lignocellulosic biomass has the advantage of using non-edible feedstock, which does not compete with the food industry [13,22]. However, a drawback associated with the use of lignocellulosic biomass (LCB) lies in the elevated production costs, as the substrates require a pretreatment with or without an enzymatic hydrolysis process before fermentation can occur. Additionally, biofuels derived from LCB require careful consideration due to the environmental impact, energy consumption, and maintenance involved throughout the entire process. All these aspects are evaluated through a life cycle assessment (LCA), which will be discussed, although focusing mainly on the second generation of bioethanol production [23].

Third-generation bioethanol comes from algal biomass. Algal biomass is sustainable and abundant since both macroalgae and microalgae can be used [24,25]. They are photosynthetic organisms that utilize carbon dioxide (CO₂) and are made up of carbohydrates, proteins, and lipids, and the content of each component varies between species [24]. Macroalgae, which are typically sourced from salty marine waters, are of three types: brown (Phaeophyceae), red (Rhodophyceae), and green (Chlorophyceae) [26,27].

Freshwater macroalgae such as Oedogonium, Rhizoclonium, Ulothrix, and Microspora also offer significant potential for biofuel production [28]. Compared to traditional raw materials that require longer production times, macroalgae can produce significantly higher amounts of bioethanol, with a yield of 0.43 g/g of substrate, making their use more profitable and viable [29]. It has been reported that the use of macroalgae biomass for bioethanol production is more cost-effective and practical than microalgal biomass [27,28,29]. However, microalgae are ideal for wastewater treatment since they are a good source of nitrogen, phosphorus, and other nutrients necessary for their growth [30,31].

Obtaining microalgae biomass and treating wastewater helps to reduce CO₂ emissions through sequestration and decrease the cost of bioethanol production [27]. CO₂ sequestration and yield depend on the growth rate of the microalgae, which in turn is influenced by the species, nutrient ratio, light intensity, pH, and temperature [31]. Certain oleaginous microalgae, such as Scenedesmus sp., Chlorella sp., Chlamydomonas sp., and Desmodesmus sp., can store more than 70% of lipids and increase their carbohydrate content up to 50% by weight of dry biomass under favorable growth conditions. As a result of their high sugar content, these microalgae are a suitable feedstock for bioethanol production [28,30]. In addition, algal biomass needs to be pretreated to make it suitable for the chemical conversion of intracellular compounds into value-added products [25,32]. Since the pretreatments used are diverse and specific, they will be described in the pretreatment section of this chapter due to their complexity. The utilization of algal biomass can serve as an excellent alternative to replace nonrenewable sources and promote environmentally friendly practices through sustainable bioethanol production.

The fourth generation of biofuels relies on genetic modification of the feedstocks (crops)/microorganisms to enhance the uptake and storage of high concentrations of carbon dioxide (CO₂) in feedstocks and as well to improve the metabolic efficiency of microorganisms used in the fermentation process [33,34,35]. By creating a synthetic carbon sink, this approach helps to minimize CO₂ emissions into the environment, resulting in a 50% reduction in GHG emissions and contributing to mitigating global warming [34,36]. Genetic engineering can also improve the growth rate of organisms, increase efficiency by boosting bioethanol yield, and lower production costs [33,37]. However, there are potential drawbacks associated with genetically modified organisms, including their potential impact on the environment due to the intentional or unintentional release of transgenic agents, which can alter natural habitats [38]. Despite this, the use of genetically modified organisms in biofuel production has the potential to significantly contribute to sustainable energy production and environmental preservation [38]. The fourth generation of biofuels has been viewed as a promising solution to the limitations of previous generations, which involved the use of crops intended for human consumption and/ or expensive and time-consuming pretreatment processes [36]. However, it is still in the development phase, due to certain limitations that need to be addressed through extensive research, before it can be implemented on an industrial scale. Failure to do so could result in reduced profitability of bioethanol production [35,36]. Despite these challenges, the potential benefits of fourth-generation biofuels make it a worthwhile area of exploration and investment for sustainable energy production in the future. Figure 1 summarizes the difference between generations for bioethanol production.

This review article deals with the recent advancements in different processes involved in the production of second-generation bioethanol such as pretreatment steps for LCB, process operating conditions, and genetic approaches to improve the ethanol yield. Additionally, this review presents a summary of the socio-economic and environmental impacts of bioethanol production based on the analyses reported in the literature.

2. Breakdown of Lignocellulosic Substrates to Fermentable Sugars

2.1. Lignocellulosic Biomass Composition

The large-scale availability of LCB has led to interest in its use as feedstock for ethanol production. Typically, LCB consists of three main components: cellulose (40–60%), hemicellulose (25–40%), and lignin (15–25%) [39]. The relative proportions of these components can vary depending on the source of the biomass. The composition of LCB of different feedstocks is presented in

Table 1. Lignocellulosic biomass composition.

Lignocellulosic Biomass	Cellulose, %	Hemicellulose, %	Lignin, %	Reference
Bamboo	47	23	28	[40]
Banana waste	28.92	25.23	10.56	[41]
Barley straw	38.43	28.55	16.26	[42]
Corn cobs	33.6	37.2	19.3	[43]
Corn stover	35–40	17–35	7–18	[44]
Corn stalk	34.5	27.6	8.7	[45]
Grass	25–40	35–50	10–30	[46]
Hardwood stems	40–55	24–40	18–25	[47]
Miscanthus	38.38	24.23	17.66	[48]
Municipal solid waste	33–49	9–16	10–14	[21]
Oat straw	31–37	27–38	14–19	[49]
Pinewood	40	28.5	27.7	[50]
Rice straw	28–36	23–28	12–15	[44]
Rye straw	30.9	21.5	22.1	[51]
Softwood stems	45–50	25–35	25–35	[41]
Sugarcane bagasse	42–48	19–25	20–42	[41]
Sunflower stalk	34.6	21	30	[52]
Sweet sorghum bagasse	34–45	18–27	14–21	[44]
Wheat straw	33–38	26–32	17–19	[43]

.

Cellulose is the most abundant lignocellulosic polymer on Earth, found in plant cell walls consisting of about 10,000–15,000 glucose units linked by β-(1,4) glycosidic bonds [53,54]. The organized microfibrils in cellulose establish multiple hydrogen bonds and van der Waals forces between hydroxyl groups, creating a rigid, resistant, and strong structure. The chains tend to form a crystalline structure, with various polymorphs, including the abundant polymorph I that is divided into cellulose Iα (algae and bacteria) and Iβ (main form in plants) [55]. Cellulose is present in various materials, including cotton, wood, bast fibers, grasses, algae, and bacteria [56,57].

Hemicellulose is a complex polymer composed of different sugars like pentoses (D-xylose, D-arabinose), hexoses (D-glucose, D-galactose, and D-mannose), and sugar acids (D-galacturonic and D-glucuronic acids) [14]. These sugars are connected by β-1,4-glycosidic bonds and, in some cases, β-1,3-glycosidic bonds. It can be degraded more easily by enzymes than cellulose [58]. Different hemicellulose structures can be found in softwood and hardwood. Within hardwoods, xylans and glucomannans are prevalent, while softwoods encompass galactoglucomannans, glucomannans, xylans, and arabinogalactans. Galactoglucomannans are compounds comprising glucose and mannose, interconnected by β-1,4 bonds, while galactose units are linked through α-1,6 bonds. Glucomannans are characterized by β-1,4-linked D-glucose and D-mannose. In softwood xylans, the predominant structure involves xylose residues linked by β-1,4 bonds, accompanied by α-1,3-linked arabinose and glucuronic acids in the side chains. In contrast, hardwoods display side branches of 4-o-methyl glucuronic acid connected via α-1,2 bonds. Arabinogalactans exhibit poly-β-(3-1,3)-galactose featuring side chains of 1,6 arabinose and galactose [59]. Several studies have demonstrated that the removal of hemicellulose through pretreatment processes can enhance cellulose conversion and facilitate enzyme access to cellulose [57].

In the realm of bioethanol production, the primary focus for conversion into ethanol during the fermentation process lies predominantly on sugars, such as cellulose and hemicellulose. However, the presence of lignin presents a formidable challenge. Acting as a recalcitrant constituent, lignin serves as a substantial physical barrier that curtails both enzymatic hydrolysis and microbial degradation [60]. Lignin is a complex heteropolymer formed by phenylpropanoid monomers (monolignols) such as p-coumaryl alcohol (hydroxyphenyl), coniferyl alcohol (guaiacyl), and sinapyl alcohol (syringyl) [61]. It is found in grasses and straws containing the three lignifying monomers, in softwoods composed of coniferyl alcohol, and in hardwoods, which have coniferyl alcohol and sinapyl alcohol in their composition [62]. Monolignols are joined by different bonds, the most common being β-O-4, β-5, 5-5, 4-O-5, β-β, and β-1. The main linkage that is present is β-O-4, which is weak compared to others and plays an important role in limiting the access of enzymes to cellulose [62,63]. Lignin is considered a physical barrier that limits enzymatic hydrolysis for ethanol due to the unproductive binding of cellulose to lignin [64]. Lignin is widely used when it is fractionated from cellulose and hemicellulose, and as a result of fermentation, it produces biopolymers and phenolic compounds [62]. The phenolic compounds, such as vanillin, syringaldehyde, and 4-hydroxybenzaldehyde, inhibit the fermentation of lignocellulosic hydrolysates, mostly despite low concentrations [65]. Moreover, lignin works as an adhesive because these phenolic compounds hold the fibers and keep cellulose and hemicellulose together [57]. Other inhibitors such as organic acids (acetic acid, formic acid, and levulinic acid), hydroxymethylfurfural (HMF), and furfurals exist, which affect the fermentation process, causing a negative impact on microbial viability [66].

2.2. Pretreatment Methods

Pretreatment processes aim to break down the complex structure of raw materials, facilitating access for hydrolytic enzymes to primarily target the carbohydrates fraction from second- and third-generation sources, converting them into fermentable sugars [4,67]. The effectiveness of pretreatment methods depends on the number of fermentable sugars released. Different technologies such as mechanical, physical, chemical, and biological methods have been successfully used to break down LCB [68,69]. A summary of the advancements on different pretreatment methods used for both lignocellulosic and algal biomass as raw materials and their resulting ethanol yield is presented in

Table 2. Summary on the efficiency of different pretreatments on bioethanol production from different second-generation feedstocks.

Pretreatment	Feedstocks	Pretreatment Conditions	Pretreatment Results	Limitations	Bioethanol Yield	Reference
Mechanical	Rice straw	Dry ball milling Loading charge biomass 50 g 60 min 1700 rpm	Sugar yields: Glucose (331 mg/g rice straw) Xylose (74 mg/g rice straw) Arabinose (14 mg/g rice straw)	High consumption of energy. No solubilization of lignin.	*	[70]
	Oil palm biomass	Ball milling Loading charge biomass 20 g 50 min 250 rpm	Size reduction (88.2%) Crystallinity reduction (46.6%) Sugar yield: Glucose 36.1% Xylose 56.4%	Inhibitors produced as acetic acid (1.3 mg/ g of biomass). High energy consumption.	*	[71]
Physical	Wood biomass	Microwave treatment/DES Choline chloride/oxalic acid 80 °C 800 W 3 min	Lignin removed 80% Glucose yield 22.3%.	Inhibitors such as HMF are produced.	*	[72]
	Sweet lime peel	2% v/v H2SO4 Loading charge of 6% 60 min 750 W 20 kHz.	181.5 mg sugars/g biomass	Relative low loading biomass charge High biomass content increases viscosity resulting in low chemical reaction.	64% in acidic pH	[73]
	Switchgrass	Steam explosion 200 °C 10 min	Sugar yield: Glucose 50.9% Xylose 28% Lignin removed 50%	Inhibitors such as formic acid, acetic acid, HMF, and furfural.	*	[74]
Chemical	Sugarcane bagasse	Alkaline 15% NaOH 140 °C 1 h	Reducing sugars 5.29 g/L Lignin removed 90%	Glucose released is negatively affected by the amount of hemicellulose and lignin present.	0.1 g ethanol/g biomass and 0.88 g/Lh
	Sugarcane bagasse	Organosolv Glycerol–acid 15% 130 °C 60 min	Glucan 65.8%	High concentration of glycerol–acid is required to improve hydrolysis. No significant influence on the lignin content.	0.38 g ethanol/g biomass and 0.57 g/Lh	[75]
	Rice straw	Acid 1%H2SO4 10%(w/v) rice straw 100 °C 2 h	Reducing sugars 14 g/L Lignin removed 11.7% Xylose 83%	More recycling times for acid treatment hydrolysate decrease xylose yield.	Concentration of 40.6 g/L yield of 86.4%	[76]
	Rice straw	DES: choline chloride-ethylene glycol 150 °C 24 h Biomass loading 5% w/w	Lignin removed 74% Glucan digestibility 87%	Residual DES decreases the enzymatic hydrolysis of cellulose.	*	[77]
	Wheat straw	Alkaline-Microwave 2.75% NaOH Solid loading 10% (w/v) 23 min 100 °C	Lignin removed 60% Total carbohydrates 82%	High energy consumption. Rapid oxidation of carbohydrates in alkaline conditions.	48 g ethanol/g sugar consumed	[78]
	Wheat straw	Ultrasound-assisted ionic liquid Triethylamine hydrogen sulfate ([TBA][H2SO4]) Sonicated at 24 kHz 130 °C 30 min	Saccharification yield 76.1% Lignin removed 74.9%	Sodium azide is used and represents a metabolic inhibitor. Ultrasound is not effective on a bigger scale.	42 g/L	[79]
	Corn stalks	Ionic liquid 150 °C 11.5 h 2.5% arginine 420 MPa	Lignin removed 92% Purity of cellulose reach 85%	Arginine can inhibit cellulose degradation. Good method for fabrication of cellulose fiber but not ethanol.	*	[80]
	Green coconut shells	Organosolv 80% (w/w) glycerol 1%(w/w) sulfuric acid 121 °C	Glucose 49 g/L Lignin removed 60%	Inhibitors such as furfural and HMF are formed.	29.6 g/L	[81]
	Olive tree biomass	Combined acid–alkaline 2.4% H2SO4 130 °C 84 min Peroxide: 7% H2O2 80 °C 90 min NaOH until 11.5 pH	Solubilization of hemicellulose 71% Lignin removed 80% Cellulose highly accessible 72%	Overliming method is needed for removing degradation products from lignocellulosic hydrolysates. Presence of acetic acid and furfural as potential inhibitors.	15 g ethanol/100 g biomass	[82]
	Oil palm trunk	Alkaline Peroxide 3% H2O2 70 °C 30 min	Lignin removed 58% Cellulose extraction 74%.	High phenolic compounds released. Black liquor released with high amounts of tannins and gallic acid.	*	[83]
	Corn stover	Ammonia Recycle Percolation Process 170 °C 10% ammonia (v/w) 1 h	Lignin removed 70% Xylan removed 47%	High temperature and energy required to improve pretreatment performance. High operation cost.	19.4 g/L	[83]
	Miscanthus (Miscanthus giganteus)	Acid diluted; 1% H2SO4 (v/v), 1:10 solid ratio (w/v), 121 °C for 30 min.	Xylose 24 g/L	Presence of furfural and HMF.	13.58 g/L; 0.148 g bioethanol/g dry biomass	[84]
Biological	Paddy straw	White rot fungi Pleurotus florida 5% inoculum 25–29 °C Biomass loading 10% (w/v) 28 days	Saccharification efficiency of 75%	High time required. No convenience in an industrial stage. Fungal residues limit enzymatic hydrolysis.	*	[85]
	Chlorella sp. KR-1	Polygalacturonase, amyloglucosidase, cellulase, and β-glucanase (simultaneous) pH 5.5; and 45 °C; 0.3 N HCl.	28.5 g of sugar released/L of hydrolysate	Inhibitors such as furfurals, HMF, and formic acid might be produced.	Ethanol yield of 0.4 g/g of fermentable sugar	[86]
	Scenedesmus abundans	H2SO4/amyloglucosidase, α-amylase (simultaneous)	10.752 g of total sugars/L and 5.730 g of glucose/L of the hydrolysate	Sugar content released depends on cultivation and pretreatment performance.	Ethanol yield of 0.1 g/g of algal biomass.	[87]

* Not reported. HMF: hydroxymethylfurfural. DES: deep eutectic solvent.

.

It can be observed from Table 2 that most of the reported physicochemical pretreatment methods are effective in increasing LCB’s degradability for enzymatic hydrolysis and bioconversion to bioethanol in sugar recovery. The formation of inhibitory compounds throughout the process has many limitations for smooth adaptation at a larger scale, primarily due to the adverse environmental effects [72,74,82]. Among these inhibitory compounds are furan aldehydes, organic acids, pseudo-lignins, small lignin units, extractives, and phenolic compounds [88]. Additionally, the lingering chemical reagents further aggravate inhibition of both enzymatic and microbial activity. Yet another significant challenge arises from the substantial volume of water required for rinsing the residues after the pretreatment process. This water, which contains chemical residues, is frequently discarded [89]. In this regard, biological methods are more sustainable as they break down the complex polysaccharides into simple fermentable sugars without much environmental impact [86,90,91,92].

3. Sugar Recovery from Pretreated Biomass through Hydrolysis

After the removal of lignin through pretreatment methods, cellulose remains on the medium, and cellulose is broken down by a chemical or enzymatic hydrolysis to obtain the sugar monomers [87,90,93]. In chemical hydrolysis, acids such as HCl and H₂SO₄ are used to break the β-1,4 linkages in cellulose, releasing sugar monomers or oligomers. In chemical hydrolysis compounds such as furfural, hydroxymethylfurfural (HMF), phenol, vanillin, vanillic acid, and other phenolic compounds can be released, which decreases ethanol yield [94]. In enzymatic hydrolysis cellulases, β-1,4-endoglucanase, exoglycanase, and β-glucosidase are used to hydrolyze cellulose into glucose monomers [44]. β-1,4-endoglucanase initiates the saccharification process by randomly cleaving the β-1,4 glycosidic linkages, producing cellodextrins with both reducing and non-reducing ends. Exoglucanase acts on the non-reducing ends of the molecule, releasing cellobiose. Finally, β-glucosidase breaks down small chains of glucose, cleaving the β-1,4 linkages in cellobiose and releasing sugar monomers [95]. Cellulases have been reported to exhibit their highest enzymatic activity in the range of 45 °C to 50 °C, a pH level of 4.5 to 5.5, and at atmospheric pressure. However, the specific conditions mentioned can exhibit variations contingent upon the enzymatic source, which includes microorganisms, as well as the substrate [96].

Other factors affecting cellulose hydrolysis are crystallinity of cellulose and its particle size [97]. Crystallinity is a property of cellulose structure where its fibers are linked by non-covalent hydrogen bonds making it more resistant to hydrolysis than the amorphous parts. Alkali pretreatments have a higher degree of conserving the crystalline structure of cellulose compared with other pretreatments previously mentioned [98]. Particle size plays an important role in enzymatic hydrolysis since it affects the reaction rate between cellulose and enzymes. Small particle size of biomass is preferred for a higher conversion rate; however, they are harder to process while bigger LCB particles tend to not hydrolyze completely and have a slower conversion rate [98]. A study conducted by Kapoor et al. [99] compared glucose recovery from glucan with 10, 15, and 20 mm particle size resulted in a 65.6, 80, and 60% sugar recovery using 5 FPU/mL of hydrolytic enzymes complex.

Enzymatic hydrolysis is widely studied for the purpose of increasing the fermentable sugars released from LCB. Its efficiency is intricately linked to the initial substrate concentrations. Maintaining an optimal balance is imperative for achieving a higher yield of fermentable sugars, thereby maximizing overall biofuel production. Controlling and optimizing these concentrations is key to enhancing the cost-effectiveness and sustainability of the entire process. Gao et al. [100] and Mondebach [101] emphasized that most optimization efforts for cellulose and hemicellulose degradation occur at low solid loading (<5% w/v). However, this low concentration often results in a diminished yield of fermentable sugars and lower end-product concentrations.

Furthermore, additional substrate and enzyme loading significantly influence enzymatic hydrolysis efficiency. Carefully adjusting these parameters impacts reaction kinetics, enabling the extraction of a higher quantity of fermentable sugars from lignocellulosic material [100]. Achieving the right balance in substrate and enzyme loading is vital for the economic feasibility of biofuel production, as reported by Amândio et al. [102], who employed a fed-batch operation starting with 11% (w/v) substrate and achieved an impressive concentration of 161 g/L of sugars with an enzymatic hydrolysis conversion efficiency of 76%.

Different modifications to enzymatic hydrolysis have been studied to increase sugar yield. For example, a study by Lee et al. [86] employed an enzymatic complex comprising cellulase, β-glucosidase, and amyloglucosidase, which yielded 28 g of sugar per liter, accompanied by an efficient ethanol conversion rate of 40% from the produced fermentable sugars. Furthermore, there are several studies that have combined pretreatment with enzymatic hydrolysis. For instance, Constantino et al. [103] adopted a chemo-enzymatic hydrolysis approach, utilizing α-amylase and a diluted acid treatment for biomass autoclaving with 4% H₂SO₄ v/v at 121 °C for 30 min. They employed microalgae as feedstock and obtained 34 ± 1 g of reducing sugars per 100 g of dry biomass. Wang et al. [104] elevated the maximum efficiency to reach 91.7% through enzymatic hydrolysis after the combination of alkaline and ozone pretreatment. Meanwhile, Ostadjoo et al. [105] employed Xylanase from Thermomyces lanuginosus for the hydrolysis of xylans from hemicellulose and recorded a yield surpassing 70%.

4. Metabolic Pathways, Settings, and Factors of Fermentation Process

Ethanol synthesis is carried out by microorganisms through the fermentation of reducing sugars. Glucose monomers are oxidized in the glycolysis process, forming two pyruvic acid molecules and a pair of NADH molecules from two NAD⁺ molecules. Pyruvic acid is then transformed into acetaldehyde by the enzyme pyruvate decarboxylase, while releasing carbon dioxide. One molecule of acetaldehyde is converted into a molecule of ethanol by the enzyme alcohol dehydrogenase, using the previous pair of NADH and regenerating the NAD⁺ molecules [106].

Five-carbon molecules such as xylose and mannose can remain in the medium when using substrates containing hexoses and pentoses. Saccharomyces cerevisiae cannot ferment pentose by itself; thus, pentose-fermenting microorganisms (PFMs) can be added to produce ethanol from five-carbon sugars. Zymomonas mobilis, Pichia stipitis, and Candida shehatae are the most common PFMs used in pentose fermentation. Pentose fermentation is carried out through the pentose phosphoketolase (PPK) pathway and is commonly seen in lactic-acid-producing bacteria. The PPK pathway begins with the same five steps as the pentose phosphate pathway (PPP), in which glucose is transformed into ribulose-5-phosphate (R5P) and xylulose-5-phosphate (X5P). Exogenous five-carbon sugars enter the microorganism and are phosphorylated by the 6-phosphogluconate dehydrogenase enzyme to be converted into R5P or X5P. R5P is used by microorganisms to produce ribose for nucleic acids or coenzymes, whereas X5P enters the PPK pathway and is catabolized into acetyl phosphate by pentose phosphoketolase. The acetyl phosphate then acts with phosphotransacetylase and aldehyde dehydrogenase to produce acetaldehyde, which is converted to ethanol by alcohol dehydrogenase [107]. A scheme on the fermentation of hexoses and pentoses into bioethanol is given in Figure 2.

4.1. Stress Factors and Inhibitors Affecting Ethanol Yield

Most of the factors that directly affect ethanol production are associated with the optimal growing conditions of the strain, which depends on the yeast or microbe used for fermentation. S. cerevisiae growth conditions may vary from 30 to 40 °C and pH 4 to 6. Disturbing these conditions lowers ethanol production by causing stress in microorganisms or inhibiting their metabolism [108].

Osmotic stress, heat stress, and chaotropic stress are the main stress factors affecting ethanol yield during fermentation. Osmotic stress occurs due to the high concentration of fermentable sugars or ethanol present in the medium. Concentrations of 150 mg of sugars/L have been reported for the Crabtree effect [83]. Osmotic stress also results in the formation of reactive oxygen species, resulting in oxidative stress by altering the redox state of key fermenting molecules. Heat stress occurs in most organisms and is characterized by denaturalization of proteins, nucleic acids, and membrane phospholipids [109].

Chaperone proteins help to fold both nascent proteins and unfolded proteins that were denatured due to heat stress [109]. Another consequence of high temperatures in the reactor is an increase in rigidity in yeasts’ cell membrane. Yeast starts replacing the short and unsaturated fatty acid chains in phospholipids with long and less saturated fatty acid chains, which have higher heat tolerance. Ergosterol is the predominant sterol found in yeast membranes; it oversees maintaining membrane stability [110]. Chaotropes are chemical compounds such as n-butanol or ethanol that promote disorder in macromolecules by disrupting the hydrogen bonds between them, inhibiting their role. Other factors that directly affect yeast fermentation are induced by the previously mentioned stress factors. Oxidative stress is the result of both osmotic and chaotropic stress by the production of reactive oxygen species [111]. Chaotropic stress occurs due to the accumulation of chaotropes which are compounds that disorder proteins and nucleic acids as well as disrupt the cell membrane. Ethanol itself is considered a chaotrope; thus, a high concentration of it inside the reactor results in chaotropic stress [112].

One of the key factors for ethanol production is the substrate concentration. Theoretically, a higher substrate concentration will result in higher production of ethanol. However, practically, increasing the number of substrate derivatives inhibits ethanol production. Wild-type strains of S. cerevisiae tolerate around 150 g/L of sugars. Going over this concentration starts inhibiting the fermentation process [112]. Ethanol is an antimicrobial compound that can diffuse through the cell membrane and directly reduce the activity of enzymes that act in glycolysis or even denature them [111].

Also, the presence of ethanol lowers water activity. A concentration of 20% (w/v) reduces water activity by 5% and reduces intracellular pH. Some inhibitors are carried in the liquid fraction after chemical hydrolysis such as furfural. The presence of 1 g/L of furfural lowers the activity of different growth enzymes, and dehydrogenases are found to be more sensitive to furfurals. The formation of carboxylic acids occurs by the deacetylation of hemicellulose. It decreases the yeast’s pH, causing acidic stress. Lignin degradation releases a wide range of phenolic compounds that commonly inhibit microbial growth by directly affecting membrane activity. Phenolic compounds seem to affect the rate of ethanol production but not the overall ethanol yield [112].

4.2. Different Setups and Optimal Conditions of the Fermentation Process

Selecting a method for bioethanol production comes with advantages and disadvantages depending on the configuration chosen. In this discussion, various fermentation setups and their respective pros and cons will be presented. Liquid-state fermentation (LSF), also known as submerged fermentation, is the most common way to obtain bioethanol. During LSF, the substrate is solubilized in a liquid medium where the microbes will grow to perform fermentation. Advantages of submerged fermentation include high homogeneity and short periods of fermentation. Nonetheless, LSF has several disadvantages such as high overall energy and water usage, high waste generation, high cost for culture medium, and a large space requirement for bioreactors [113].

Solid-state fermentation (SSF) utilizes solid wastes as a substrate to obtain various value-added products, including ethanol. SSF has been shown to offer high substrate concentrations, resulting in a high ethanol yield. The SSF process has no free water or low concentrations of it inside the reactor. SSF is paired with simultaneous saccharification, where enzymes are added to solid pretreated biomass to release the sugars inside it [114]. The enzymes act on the surface and then go down to the bottom of the biomass, hydrolyzing it.

The resulting solid-state hydrolysate acts as the same natural environment of different filamentous fungi, such as Trichoderma and Aspergillus. However, SSF allows the growth of single-cell fermentative organisms like yeast or bacteria. The most important condition in solid-state fermentation is moisture; high moisture promotes agglomeration of particles, reducing heat dissipation and gas transfer. On the other hand, low moisture decreases substrate solubility, thereby reducing substrate availability [113]. Different advantages of SSF include the reduction in catabolite repression and substrate inhibition, low energy consumption, higher ethanol concentration, no discharge of wastewater, and better enzymatic reaction with the substrate. Nonetheless, to date, solid-state fermentation still faces several challenges to be implemented on an industrial level, such as controlling pH and temperature, uneven distribution of enzymes and microorganisms, varying moisture content inside the biomass, difficulty in the purification process, long fermentation time, and limited availability of bioreactors [115].

Both SSF and LSF can be utilized synergistically. Chu et al. [115] used biomass from corn stover to produce ethanol. They centrifuged the hydrolysate from enzymatic hydrolysis and fermented the supernatant in a submerged fermentation, as well as the pellet using solid-state fermentation. The ethanol yield for LSF was 94.98%, with a total of 91.31 g/L of ethanol from 216.7 g/L of sugars. On the other hand, SSF was performed on hydrolysate residue containing 5.89% (w/w) of cellulose. After 24 h, cellulose was reduced to 3.78% (w/w), indicating simultaneous saccharification and fermentation occurred during the process. This resulted in the production of 1.51 g of glucose after 64 h, presenting an ethanol yield of 0.195 g/g.

The concentration of sugar for ethanol production can be categorized as normal gravity (<180 g/L of sugars), high gravity (180–240 g/L of sugars), and very high gravity (VHG) (>240 g/L of sugars). VHG fermentation can produce more than 15% (v/v) of ethanol, in contrast to the 10–12% (v/v) found in most processes. During VHG, microorganisms are put under several stress due to the increase in nutrients, metals, and sodium ions, as well as elevated temperatures, pH, osmotic stress, and ethanol concentration. After VHG, yeast produces other by-products such as trehalose, glycogen, succinic acid, and glycerol, which function as coping mechanisms for the stress factors. Various yeast strains have been shown to tolerate high ethanol concentrations without requiring adaptation or genetic modification [116]. Cruz et al. [117] inoculated an industrial strain of S. cerevisiae Y-904 into a broth containing 300 g/L of sugars for up to 30 h and reported an ethanol yield of 90% with a final concentration of 135 g/L of ethanol.

In addition to strain robustness, temperature and nutrient supplementation are crucial factors that prevent the implementation of VHG fermentation in industries. High temperatures directly affect the stress-coping mechanisms of yeast against ethanol tolerance. A decrease in temperature from 30 to 27 °C during VHG fermentation has been reported to increase the ethanol yield by 2.1%. Nutrient supplementation involves the addition of key components needed by cells besides the carbon source. Increasing substrate concentration often results in an imbalance of other nutrients, which lowers microbial growth and therefore reduces ethanol yield. Another drawback of VHG fermentation is the requirement of molasses addition to the medium, and the use of molasses in VHG competes with the food industry [116].

Optimizing both the enzymatic hydrolysis and fermentation processes results in increased ethanol yield. To achieve this, different parameters need to be considered. Going over or under a pH of 4.5–5.5 and a temperature of 45–50 °C can negatively affect enzymatic hydrolysis. Stoichiometrically, a molecule of glucose results in two molecules of ethanol; thus, 1 g of glucose produces 0.511 g of ethanol. Not all sugars are transformed by microorganisms during fermentation; around 10% are utilized for new biomass generation and other metabolic needs. Nevertheless, there are no fixed ideal conditions for cellulases to achieve maximum efficiency [118].

Optimization of enzymatic hydrolysis and fermentation involves the use of statistical analysis to determine the ideal parameters that approach 0.511 g of ethanol in a bioprocess. Response surface methodology (RSM) is the most reported analysis for optimization. RSM involves factorial analysis from the results of different factorial levels, with three-level analysis being the most efficient [119]. For instance, Assabjeu et al. [120] optimized the hydrolysis of pretreated sawdust from Triplochiton scleroxylon using RSM. The pretreated biomass contained 53.2 ± 0.3% cellulose. The researchers found that loading 9.07% of the substrate and using 21.36 FPU/gDM of the enzyme for 72 h were the most efficient parameters for ethanol fermentation, resulting in an ethanol yield of 21.88 mg/mL.

Another study aimed to optimize the fermentation of microalgae biomass for ethanol production. El-Mekkawi et al. [121] found that the best ethanol yield for the microalgal biomass was 18.57 g/L. To achieve this, they supplied 98.7 g/L of microalgal biomass to 15.09% of immobilized yeast for 43.6 h. The disadvantage of using response surface methodology is that a large number of experiments are required to find the optimal parameters. Microfluid reactions (MFRs) have recently been studied as a solution to this issue. MFRs simulate bioreactor conditions under microliter scales, allowing for a large screening of different conditions and the ability to scale up the results [122]. Beltrán et al. [123] used MFRs to test the impact of particle size during enzymatic hydrolysis. To optimize the conditions of the hydrolysis, they tested three levels of pH (4.5, 5, and 5.5) and temperature (45, 50, and 55 °C) and four levels of enzyme loading (1.0, 3.0, 5.0, and 7.0 μL/0.015 g-biomass), resulting in a total of 108 experiments. They concluded that the optimal conditions for the hydrolysis were an enzyme loading of 7 μL/0.015 g-biomass, a pH of 5.5, and a temperature of 46.31 °C.

Consolidated bioprocessing refers to the integration of various steps in bioprocessing, including the production of hydrolytic enzymes, saccharification of biomass, and fermentation of five- and six-carbon sugars. While there is no single microorganism capable of performing all these bioprocess steps, both fungi and bacteria have useful properties that can be exploited. Clostridium bacteria possess a highly efficient enzymatic complex capable of hydrolyzing cellulose, while fungi such as Fusarium and Trichoderma have demonstrated a large complex of cellulolytic enzymes [124]. However, the anaerobic microorganisms mentioned above also produce several by-products that directly reduce ethanol yield [125]. To date, there is no naturally viable method for consolidating bioethanol production. Nevertheless, there are different configurations that reduce the number of steps in the process.

One such configuration is simultaneous hydrolysis and fermentation (SHF), which involves the integration of biological saccharification and the fermentation process. This allows for the fermentation of sugar monomers by hexose-fermenting microorganisms (HFMs) as soon as cellulose is transformed, resulting in reduced production time and less material used for the bioprocess. However, optimizing this process can be challenging since the cellulase complex and fermenting microorganisms have different parameters where they work best. High efficiency thermo-tolerant strains must be used to achieve both enzyme and strain optimum parameters [114].

Another configuration used to lower the cost of ethanol production and utilize all sugars produced during pretreatment is co-fermentation (CF). Co-fermentation involves the use of different strains in the same medium that can ferment both hexose and pentose. This method is often combined with simultaneous hydrolysis to maintain a constant production of pentose and hexose sugars. Hexose fermentation is performed first in the bioreactor, and then ethanol is separated from the medium. The medium without ethanol is then inoculated with PFMs to ferment five-carbon sugars. By adding both hexose- and pentose-fermenting microorganisms, ethanol production increases and substrates are better leveraged, which speeds up the process and results in fewer reactors used for saccharification and both fermentations [114].

There are two major obstacles to co-fermentation. The first limiting factor is the same as that for simultaneous hydrolysis and fermentation, where the optimal conditions for different microorganisms and enzymes are not the same, resulting in less efficient ethanol yield. The second obstacle is the difference in microbial growth between pentose-utilizing microorganisms and hexose-utilizing microorganisms; HFMs grow considerably faster than PFMs and utilize most of the nutrients in the medium. A solution that has been widely studied is the implementation of a strain that can ferment both five- and six-carbon sugars. However, this solution does not address the problem of different optimal points, but it does help to improve microbial growth. Nonetheless, microorganisms capable of fermenting both pentoses and hexoses use five-carbon sugars when a six-carbon one is not present in the medium. This presents a disadvantage for continuous fermentations where ethanol production increases the time needed to produce it [126].

Response surface methodology (RSM) is widely employed to identify the optimal parameters for co-fermentation and simultaneous saccharification and co-fermentation process. Based on RSM, Derman et al. [127] employed the simultaneous saccharification and fermentation process of empty fruit bunches (EFBs) by employing a microbial consortium consisting of Trichoderma harzianum with S. cerevisiae. The highest bioethanol yield of 0.29 g/g of EFB was achieved with 4% (w/v) of biomass at 30 °C for 72 h. The parameters for ethanol production in different fermentation processes are summarized in

Table 3. Summary of varying process and parameter conditions for different types of fermentation.

Fermentation	Microorganism/Enzyme	Substrate	Substrate Concentration	Inoculum Volume	Parameters	Ethanol Yield	Total Ethanol	Reference
LSF	S.cerevisiae X19G2	Corn Stalk	5% (w/v)	1% (w/v)	30 °C, 0 rpm, 96 h	-	16.48 g/L	[128]
LSF	S.cerevisiae NRRLY-2034	Defatted Nannochloropsis oculate biomass	100% (v/v)	2% (v/v)	30 °C, 0 rpm, 96 h	64.5%	5.70–6.64 g/L	[129]
SScF	S.cerevisiae BY4743; cellulase (Celluclast 1.5 L)	Sugarcane bagasse	10% (w/v)	100 (U/g) cellulases 10% (v/v) S.cerevisiae	40 °C, 120 rpm, 4.8 pH	0.49 g/g	4.88 g/L	[130]
SSCF	S.cerevisiae X19G2; glucoamylase	Potato peel wastes	12.25% (w/v)	10% (v/v)	41.5 °C, 120 rpm, 5.5 pH, 24 h	0.26–0.33%	23.09–29.86 g/L	[131]
SSCF	S.cerevisiae (YSCII), T.harzianum, cellulase, β-glucosidase	Empty fruit bunches from palm	45 (w/v)	6.79%(v/v)	30 °C, pH 4.8, 150 rpm, 72 h	0.46 (g/g)	9.65 g/L	[125]
SSCF and SSF	S.cerevisiae MTCC173, soil inoculum	Apple waste	-	1% (w/v) S.cerevisiae; 1% (w/v) inoculum	30 °C, 6 pH, 72 h, 70.89% (w/w) moisture	49.64 g/L	-	[132]
SSF and SSCF	S.cerevisiae; A.niger	Pineapple waste	15 g/mL	1.64 × 105 (spores/mL) A.niger; 1.9 × 108 (cells/mL) S.cerevisiae	30 °C, 4.1 pH, 7 days	11.20%	-	[133]
SSF and SSCF	F.oxyspurum; C.cerevisiae; glucoamylase	Food waste		0.1% (w/w) F.oxyspurum; 15 mg/g S.cerevisiae	30 °C, 80 rpm, 94 h	-	30.8 g/L	[134]
VHG	S.cerevisiae C2/00	Sugarcane molasses	250.34 g/L	30% (v/v)	32 °C, 4.5 pH	63.91%	87.37 g/L	[135]
VHG; SSCF	L. sacchari LP175; Kluyveromyces marxianus DMKU-KS07; glucoamylases	Sugarcane bagasse	250 g/L	15% (v/v) L.sacchari and K.marxianus	50 °C, 200 rpm, 6 h	98.6 g/L	118 g/L	[130]

Liquid-state fermentation (LSF); simultaneous saccharification and fermentation (SScF); simultaneous saccharification and co-fermentation (SSCF); solid-state fermentation (SSF); very-high-gravity fermentation (VHG).

.

4.3. Downstream Process: Ethanol Upgrading

The final crucial step in ethanol production is downstream processing. Ethanol recovery from the fermentation broth involves three different steps: solid-liquid separation, primary purification, and fine purification. While centrifugation is a well-established technique for solid–liquid separation, other techniques such as membrane filtration can also be employed. In membrane filtration, the broth is pressurized through a membrane with small pores, allowing solubilized compounds to pass through while retaining bigger molecules like biomass. However, membrane technologies have a disadvantage compared to centrifugation as the membranes need to be changed after several uses and require frequent maintenance, adding extra costs to the process [136]. For primary purification, the aqueous part of the centrifugation is distilled using two columns: a crude column that removes non-volatile molecules and most of the water and a polishing column that produces an azeotropic mixture of ethanol and remaining water. Fine purification separates the ethanol and water azeotrope, and this can be achieved using molecular sieves, which have fine porosity, allowing ethanol molecules to pass through but blocking the flow of water molecules. Another method to purify the azeotrope is by pressure-swing distillation, where the polishing column operates under high vacuum conditions to separate the mixture between water and ethanol. The azeotrope point of water and ethanol can also be displaced by adding an extra compound like toluene or cyclohexane, allowing the mixture to be traditionally distilled [137].

5. Genetic Engineering Approaches to Improve Bioethanol Yield

To ensure efficient bioethanol production, the selection of microorganisms that can grow and develop under stressful conditions is a crucial step. These microorganisms must have good tolerance to ethanol and be capable of utilizing a variety of sugar-rich substrates to obtain a high yield of biofuel [138]. Normally, S. cerevisiae only ferments glucose to ethanol and produces carbon dioxide by repressing unnecessary metabolic pathways [139,140]. Although, the fermentation process is well understood for metabolizing glucose as the main substrate. However, when other sugars such as xylose, a pentose sugar derived from lignocellulosic materials, are present, ethanol production can become challenging. Therefore, it is essential to consider some aspects of ethanol production from lignocellulosic materials, as the bioconversion process may result in a high release of xylose [141]. Moreover, xylose can only be naturally fermented by other yeasts, such as Scheffersomyces stipitis and Spathaspora passalidarum, for conversion to ethanol [140]. Hence, genetic engineering of microorganisms is a promising approach for improving bioethanol production, as it can reduce raw material usage and associated costs. Several strains of S. cerevisiae have been genetically modified to convert xylose to ethanol, resulting in improved metabolic flux for efficient utilization of this substrate (see Table 4).

In recent years, studies have been carried out to construct recombinant S. cerevisiae that use xylose transporters through the XR-XDH (xylose reductase-xylitol dehydrogenase) or XI (xylose isomerase), pentose phosphate, and glycolysis pathways to produce pyruvate, which is then converted to ethanol with the introduction of Xyl (xyloglucokinase) and PPP (pentose phosphate pathway) genes [142,143]. It has been reported that in the diploid wild-type strain S. cerevisiae BSIF, two heterologous genes were integrated into the genome, the MGT05196N360F mutant of Meyerozyma guilliermondii, which encodes a xylose-specific and glucose-insensitive transporter, and Ru-xylA, which encodes a xylose isomerase (XI), resulting in the final strain S. cerevisiae LF1, with excellent fermentation of xylose as the sole carbon source and an ethanol yield of 0.475 g⁻¹ in 12 h, which is more than 93% of the theoretical yield [144]. Demeke et al. [143] studied the robust strain S. cerevisiae GS1.11-26, in which an expression cassette containing 13 genes, including Clostridium phytofermentans XylA, encoding D-xylose isomerase (XI), and enzymes of the pentose phosphate pathway (PPP), was inserted into its genome in two copies, resulting in their ability to ferment D-xylose and tolerate inhibitors for bioethanol production from lignocellulose hydrolysates showing a maximum specific consumption rate of 1.1 g/g DW/h in a synthetic medium with a complete attenuation of 35 g/L of D-xylose in about 17 h. On the other hand, metabolic and evolutionary engineering was also performed in S. cerevisiae WXY74, an acetate-tolerant strain for the rapid utilization of xylose from wheat straw residues. In this study, a six-gene expression cluster was optimized to obtain better ethanol yields from mixtures consisting of 80 g/L glucose and 40 g/L xylose with the presence of 3 g/L acetate in the medium, which approached 99% of the theoretical yield. The genetically modified strain achieved an ethanol of 58.4 g/L [144].

Table 4. Engineered yeast strains for hexose and pentose fermentation for bioethanol production.

Gene	Gene Source	Modified Strain	Substrate	Bioethanol Concentration, g/L	Bioethanol Yield, g/g	Reference
XYL1, XYL2, XKS1, TAL1	Scheffersomyce stipitis	S. cerevisiae MEC1122	Glucose, xylose	2.5	0.12	[145]
PPP genes (TAL1, TKL1, RKI1, RPE1)	S. cerevisiae and Kluyveromyces marxianus	S. cerevisiae YK246	Glucose, xylose	48.6	0.45	[146]
BvuXylA, XIqXylA, TAAXylA, araA, araB, araD	S. cerevisiae JUK36α	S. cerevisiae 36aS1.10.4	Glucose, xylose	54.11	0.44	[141]
HXK2, and RSP5	S. cerevisiae	S. cerevisiae IMS0629	Glucose, xylose	-	0.18	[147]
PHO4	S. cerevisiae MC15	S. cerevisiae MF01-PHO4	Glucose	114.71	-	[148]
PMA1, VMA1, VMA2, VMA4-8, VMA22	S. cerevisiae	S. cerevisiae XUSAE57	Glucose, xylose	-	0.49	[149]
GPD2, FPS1, ADH2, DLD3	S. cerevisiae	S. cerevisiae SCGFAD	Glucose	23,29	-	[150]
SESTC	Ampullaria gigas Spix	S. cerevisiae wild type	Glucose	7.53	0.377	[151]
ADH2 and hyg	S. cerevisiae	S. cerevisiae ΔADH2 As2.4	Glucose	14.6	-	[152]
noxE	Lactococcus lactiswas	S. cerevisiae JX123_noxE	Glucose, xylose	55.5	0.433	[153]
EG1, CBH1, Bglc	Trichoderma reesei	S. cerevisiae BY4743-4A	Glucose, xylose	32.6	0.42	[154]
EGII, CBHII, XynII, BGL, XylA	Trichoderma reesei, Aspergillus aculeatus and Aspergillus oryzae	S. cerevisiae Y5	Xylose	1.61	0.33	[155]
BGL1, XYLA, XYN	Aspergillus aculeatus, Aspergillus oryzae and Trichoderma reesei	S. cerevisiae industrial strain	Glucose, xylose	11.1	0.328	[156]
XylA and Xyn	Aspergillus niger, Saccharophagus degradans	S. cerevisiae	Xylose	6.0	-	[157]
XYNII, XylA, BGL1	Aspergillus aculeatus	S. cerevisiae MN8140/XBXX	Glucose, xylose	8.2	0.32	[158]

Table 4. Engineered yeast strains for hexose and pentose fermentation for bioethanol production.

Gene	Gene Source	Modified Strain	Substrate	Bioethanol Concentration, g/L	Bioethanol Yield, g/g	Reference
XYL1, XYL2, XKS1, TAL1	Scheffersomyce stipitis	S. cerevisiae MEC1122	Glucose, xylose	2.5	0.12	[145]
PPP genes (TAL1, TKL1, RKI1, RPE1)	S. cerevisiae and Kluyveromyces marxianus	S. cerevisiae YK246	Glucose, xylose	48.6	0.45	[146]
BvuXylA, XIqXylA, TAAXylA, araA, araB, araD	S. cerevisiae JUK36α	S. cerevisiae 36aS1.10.4	Glucose, xylose	54.11	0.44	[141]
HXK2, and RSP5	S. cerevisiae	S. cerevisiae IMS0629	Glucose, xylose	-	0.18	[147]
PHO4	S. cerevisiae MC15	S. cerevisiae MF01-PHO4	Glucose	114.71	-	[148]
PMA1, VMA1, VMA2, VMA4-8, VMA22	S. cerevisiae	S. cerevisiae XUSAE57	Glucose, xylose	-	0.49	[149]
GPD2, FPS1, ADH2, DLD3	S. cerevisiae	S. cerevisiae SCGFAD	Glucose	23,29	-	[150]
SESTC	Ampullaria gigas Spix	S. cerevisiae wild type	Glucose	7.53	0.377	[151]
ADH2 and hyg	S. cerevisiae	S. cerevisiae ΔADH2 As2.4	Glucose	14.6	-	[152]
noxE	Lactococcus lactiswas	S. cerevisiae JX123_noxE	Glucose, xylose	55.5	0.433	[153]
EG1, CBH1, Bglc	Trichoderma reesei	S. cerevisiae BY4743-4A	Glucose, xylose	32.6	0.42	[154]
EGII, CBHII, XynII, BGL, XylA	Trichoderma reesei, Aspergillus aculeatus and Aspergillus oryzae	S. cerevisiae Y5	Xylose	1.61	0.33	[155]
BGL1, XYLA, XYN	Aspergillus aculeatus, Aspergillus oryzae and Trichoderma reesei	S. cerevisiae industrial strain	Glucose, xylose	11.1	0.328	[156]
XylA and Xyn	Aspergillus niger, Saccharophagus degradans	S. cerevisiae	Xylose	6.0	-	[157]
XYNII, XylA, BGL1	Aspergillus aculeatus	S. cerevisiae MN8140/XBXX	Glucose, xylose	8.2	0.32	[158]

Genetic tools play an important role in the modification of the metabolism of different strains for the improvement of biofuel production. Through gene editing based on CRISPR/cas9 technology, genes can be modified to improve the tolerance and activity of yeast strains to obtain better ethanol production [159]. For example, in S. cerevisiae Y1H, a wild-type strain, the ADH2 gene was first disrupted and completely deleted using CRISPR-Cas9-mediated double-strand breaks (DSBs), resulting in a significant improvement in ethanol yield by 74.7% [160]. Meanwhile, Liu et al. [161] studied the mutant strain S. cerevisiae YS-6 from wild-type Y1H to alter ADH2 and, for the first time, ALD4 genes in ethanol fermentation. Y1H used 33.779 g/L of glucose and produced 15.431 g/L of ethanol, while strain YS-6 consumed 45.790 g/L of glucose to produce 21.711 g/L of ethanol, obtaining high productivity and yield. Moreover, this genetic tool has also demonstrated that the regulation of gene expression improves tolerance to multiple stresses.

In S. cerevisiae KF-7 and E-158, overexpression of the ENA5 gene of E. coli DH5α significantly improved multiple stress tolerance. The E-158-ENA5 engineered strain resulting from S. cerevisiae E-158 achieved higher ethanol accumulation with a concentration of 138.43 g/L when cassava was used as raw material [162]. Moreover, the simultaneous knockdown of GPD2, FPS1, and ADH2 genes indicated that S. cerevisiae SCGFA produced 23.1 g/L of ethanol compared to the wild-type strain that obtained 19.6 g/L with 50 g/L of glucose as substrate at 72 h and showed the highest ethanol conversion rate of 0.462 g/g of glucose [163].

The CRISPR/Cas9 technology that assisted with determining the genes for α-amylase (amyA) and glucoamylase (glaA) from Aspergillus tubingensis was cloned and expressed in a multicopy plasmid in the S. cerevisiae L20 strain, from which its recombinant strain L20 dT8 produced an ethanol concentration of 0.67 g/L; therefore, it obtained great potential for application in the industry of corn starch transformation into bioethanol [164].

In addition to evaluating the conventional yeast S. cerevisiae, several studies have considered other microorganisms as good candidates for bioethanol production based on their genetic modifications. Such is the case of Zymomonas mobilis, a bacterium that has been considered a model for bioethanol production due to its high sugar uptake, yield, and tolerance in which CRISPR/Cas9 technology has been used to facilitate the characterization of important genes and to construct new metabolic pathways. For example, a comparative transcriptome analysis between two ZM4 and ZM1 strains of Z. mobilis identified four highly expressed green fluorescent proteins (ORFs) potentially related to higher rates of glucose uptake and thus high bioethanol production [165].

On the other hand, Bacillus subtilis has an innate ability to grow on a diversity of carbohydrates and produce bioethanol from plant biomass. In the study conducted by Maleki et al. [125], the genes encoding alcohol dehydrogenases, adhZ and adhS from Z. mobilis and S. cerevisiae, respectively, along with the pdcZ gene (pyruvate decarboxylase from Z. mobilis) were used to create ethanol operons in a lactate-deficient B. subtilis, giving rise to strains NZ, NZS, and the recombinant NS:Z, where ethanol production by NZS and NS:Z using potatoes resulted in 16.3 g/L and 21.5 g/L during 96 h of fermentation, respectively. Another bacterium that has high potential to be a biocatalyst in ethanol production is Lactiplantibacillus casei, which is distinguished by its strong carbohydrate metabolism capacity and high tolerance to ethanol.

In a study, the feasibility of producing bioethanol using the ethanologenic engineered strain L. casei E1 as a starter culture and sugarcane molasses as a substrate medium was evaluated, and the results showed an ethanol yield of 13.77 g/L in 36 h and a carbohydrate percentage of 78.60% [166]. Moreover, the unconventional yeast Kluyveromyces marxianus is a promising eukaryotic microbe for bioethanol production and other environmental applications. Similarly, the modified K. marxianus strain expresses the major cellulosome complex OlpB of H. thermocellum on its cell surface, producing an ethanol concentration of 8.61 g/L [167]. Although various strains of different microorganisms have been modified by genetic tools to improve performance and tolerance to ethanol, it has not yet been reported if any are commercially viable. Therefore, S. cerevisiae is the model yeast that has been studied the most to be able to ferment hexoses and pentoses to produce bioethanol.

Genetic tools can also be used to develop feedstock for enhancing bioethanol yield. Modification of specific genes is essential to either increase or decrease the amount of plant cell wall components, making it an effective strategy to increase productivity, improve biomass yields, and reduce the high costs of bioethanol production [168]. Genetic engineering, coupled with pretreatment and fermentation methods, can optimize the process for increasing the mobility of degrading enzymes and achieving higher saccharification yield [169].

It is well known that in all lignocellulosic crops, lignin is one of the main targets in transgenic studies due to its complex structural characteristics [170]. Therefore, in vitro techniques and gene manipulation using DNA mutations have been used to reduce the degree of lignification in transgenic plants, achieving a reduction in lignin content by 10–50% [171]. Some studies have used RNA interference (RNAi), a mechanism that helps to tailor endogenous gene expression in plants to target genes of pests and pathogens [172]. Bewg et al. [170] used RNAi to individually knock down the expression of key genes in the lignin biosynthetic pathway in sugarcane (Saccharum officinarum L.): caffeoyl-CoA O-methyltransferase (CCoAOMT), ferulate 5-hydroxylase (F5H), and caffeic acid O-methyltransferase (COMT), respectively. The CCoAOMT gene transgenic lines did not have a reduction in lignin content but showed a significant release of glucose in one plant. The same occurred with the F5H gene lines. In contrast, for COMT, only one line reduced lignin content and obtained the highest levels of glucose during enzymatic hydrolysis.

Likewise, to improve sugarcane straw saccharification, it is possible to perform genetic RNAi silencing of the BAHD01 gene, which is responsible for the feruloylation of the cell walls of grasses. Research by de Souza et al. [173] identified six BAHD genes in the sugarcane genome (Saccharum officinarum L.) (SacBAHDs) and generated five lines with decreased expression of BAHD01. However, only three lines showed an improvement in saccharification efficiency of 24% and obtained a lower cell wall ferulate content but without any significant change in cellulose, hemicellulose, and lignin composition. On the other hand, in the study carried out by Poovaiah et al. [174], MYB31 and MYB42 genes from a maize plant (Zea mays) were cloned and expressed in sugarcane (Saccharum officinarum L.). MYB31 expression decreased lignin content in some plants, while all plants expressed with MYB42 had significant increases in glucose release by enzymatic hydrolysis, which makes MYB42 a transcription factor of interest for improving the production of second-generation bioethanol from sugarcane bagasse.

Besides sugarcane genetic modification to improve the amount of ethanol produced, other types of plants have been modified, such as rice (Oryza sativa L.). Huang et al. [168], who studied two GH9B subclass genes (OsGH9B1 and OsGH9B3) and analyzed cell wall changes and biomass saccharification in transgenic rice plants, demonstrated that the transgenic plants showed little alteration in cell wall composition (cellulose, hemicellulose, and lignin), stem mechanical strength, and biomass yield, resulting in high sugar efficiency after alkaline pretreatments and subsequent enzymatic hydrolysis, yielding 22.5% dry matter bioethanol yield. The RNAi approach was also used for the knockdown of OsSEX4 gene expression in rice straw, which caused a large accumulation of starch, resulting in a 50% increase in bioethanol production yield compared to that of wild-type straw [175]. In a study by Ai et al. [176], they worked with transgenic rice lines overexpressing AtCesA6, a gene involved in cellulose biosynthesis of primary cell walls in Arabidopsis thaliana. Enzymatic saccharification was significantly improved and was almost complete; thus, the transgenic rice samples achieved bioethanol yields of over 20% dry matter and bioethanol concentrations of 18.3 and 19.1 g/L. It has been suggested that, in rice and maize crops, overexpression of GA20-OX1, a key gene in gibberellic acid (GA) biosynthesis, is responsible for differences in plant growth rates. Voorend et al. [177] examined the biomass yield and quality characteristics of maize plants overexpressing GA20-OX1 and determined that the stalks of these plants were longer but also thinner, revealing that cellulose and lignin were deposited earlier in stalk development.

Furthermore, high saccharification efficiency per unit dry weight was obtained when the biomass was pretreated with NaOH. Therefore, the stem biomass yields as well as the conversion efficiency of cell wall polysaccharides into fermentable sugars are important for bioethanol production. Thus, genetic modification of different crops promises to incorporate desired characteristics to make the process more cost-effective in obtaining renewable fuels.

6. Challenges in Ethanol Conversion: Social, Economic, and Environmental Aspects

Regardless of bioethanol’s energetic potential, every process must be analyzed and verified to approach sustainable production and development. As new strategies for environmental assessment emerge, a methodology has been developed to assess the performance of products and services considering their environmental impacts over their life cycle, called life cycle assessment (LCA).

LCAs are tools that help develop and test environmentally and socio-economically improved scenarios. Furthermore, generated emissions and discharges are quantified, which represent environmental challenges such as global warming potential, eutrophication, and acidification [178,179]. According to Soleymani Angili [180], in a compilation of several studies on bioethanol production, 80% of studies revealed a reduction in global warming potential due to bioethanol production. It was also observed that an increase in acidification, eutrophication, and photochemical oxidation formation was due to feedstocks. They concluded that LCA studies should consider agrochemicals used in feedstock production and processing into the bioethanol process, giving importance to the chemicals generated, such as fertilizers and pesticides that increase acidification, eutrophication, and land change. New strategies are suggested to generate feedstock with fewer amounts of chemicals. However, even if LCA studies demonstrated the effectiveness of bioethanol to reduce GHG emissions, they have failed to report the impact of land usage.

Institutions like FAO suggest deep analysis of land usage, meaning that land should be categorized and utilized for specific crops for increased sustainability. To achieve this, benefits and input must be considered to assess its productive potential. The analysis requires a multi-disciplinary approach, studying it through biophysical, economic, social, and political aspects [181]. Using the LCA tool prevents the burden shifting between the production stages, originates from efforts to reduce environmental impact, and unintentionally creates impacts in other processes [182]. This procedure involves a meticulously planned supply chain system to ensure the quality and the efficient flow of materials, information, and finances. It is suggested that having croplands near the operation helps with supply chain optimization and cost reduction. Rural zones are suggested to avoid space limitations and to generate social impact, generating employment and development in these areas, which lead to academic improvement, so people from rural zones can match the demands and abilities required for the new job market. Additionally, this functions as a favorable factor to gain social acceptance and make the installation of the operation smoother.

Furthermore, the technical aspects must be studied further, especially pretreatment technologies, because they represent economic and environmental concerns; also, the inputs and outputs in bioethanol production must be considered. Wang et al. [183] conducted an LCA analysis in China comparing first- and second-generation bioethanol. The first generation of bioethanol production has a water-use intensity of 2545 m³/10⁴ CNY (USD 1460), with 73% green and 27% blue water, and a farmland-use and CO₂ emission intensity of 0.34 ha/10⁴ CNY and 1.86 t/10⁴ CNY, respectively. In contrast, second-generation bioethanol production has a water-use intensity of 1281 m³/10⁴ CNY, farmland-use intensity of 0.13 ha/10⁴ CNY, and a CO₂ emission intensity of 1.21 t/10⁴ CNY. On the other hand, Hossain et al. [184] used algal biomass as feedstock and produced 110 tons per year of algal biomass, which resulted in a bioethanol production of 57,087.5 gallons/year, with an annual CO₂ consumption of 366.66 tons (1.83 CO₂ kg consumed per kg of biomass) and an annual CO₂ emission of 147.8 tons. Therefore, the annual net CO₂ balance is 218.86 tons. However, due to energy needed throughout the process, there is an energy balance of -2749.6 GJ per year, despite generating 1290 GJ per year.

A circular economy (CE) is another concept used to evaluate the impact of the entire process, not only the main product generated in biofuels (e.g., ethanol, methane, diesel) but also the by-products generated and their application in real-life scenarios [185]. The CE approach for bioethanol production involves obtaining value-added products other than fuel products under a biorefinery approach. Although these products can inhibit fermentation, their management is crucial for effectively converting biomass into ethanol and other income sources, such as furfural, HMF, and lignin residues. HMF is the result of the dehydration of sugar monomers, mainly hexoses, and is used as a key intermediate in the synthesis of polymers from biomass, while furfural is obtained from xylose sugar and has industrial applications, such as making plastics, fertilizers, adhesives, fungicides, and antacids as shown in Figure 3. Moreover, furfural has been reported as a precursor for D-proline, which is used as a precursor in pharmaceuticals [186,187]. On the other hand, lignin is a natural raw material with higher aromatic content that can be used to produce dispersants, adhesives, and surfactants. Furthermore, lignin residues have been used in the rubber industry [188].

Some countries have evaluated the economic and environmental aspects of bioethanol production to predict suitable scenarios by considering several factors that play an important role in ethanol production, such as Lopez-Ortega et al. [189]. They proposed a scenario for Mexico in which a sugarcane factory is transformed into a biorefinery to estimate a techno-economic analysis.

Table 5. Techno-economic analysis and main inputs and outputs in Mexico of bioethanol production.

Parameter	Collected Data	Reference
Plan lifetime	25 years	[190]
Income tax rate	30%	[190]
Sugarcane price	34.5USD/TC (metric ton)	[190]
Ethanol price	0.52 USD/L	[191]
Electricity price	67.8 USD/MWh	[191]
Investment	139 USD × 106	[192]
Return of investment	16% per year	[189]
Net present value	66 USD × 106	[190]
Co-products sold (sugar in a concept of biorefinery)	0.49 USD/ kg	[190]
Greenhouse gases emitted	1.67 × 105 gCO2 eq/ TC (metric ton of sugarcane)	[190]

summarizes several parameters in a techno-economic analysis and lists the inputs and outputs under a scenario of bioethanol production from the sugarcane industry under a biorefinery concept with 1G bioethanol production. Table 5 shows the techno-economic analysis and the main inputs and outputs of bioethanol production in Mexico.

On the other hand,

Table 6. Comparison of inputs and outputs of bioethanol production in different countries.

Parameter	1G Mexico	2G China	3G Brunei	Reference
Feedstock type	Sugarcane	Wheat straw	Algal biomass (Chlorella vulgaris)	[183,184,189]
Bioethanol produced	77 L/metric ton of sugarcane	-	57,087.5805 gallons per year/210 tons biomass per year	[184,189]
CO2 emitted	1.67 × 102 kgCO2 eq/metric ton of sugarcane (GHG not only CO2)	1.21 tons/USD 1420 of ethanol produced	2.59 kg/gallon of bioethanol	[183,184,189]
Energy input	16 kWh/metric ton of sugarcane	-	3822 GJ per year	[183,184]
Water usage	55.6 L/metric ton of sugarcane	1281 m3/USD 1420 of ethanol produced	2 m3/GJ−1	[183,184,189,190]
Land usage	-	0.13 ha/USD 1420 of ethanol produced	2 m2/GJ−1	[183,184]

provides a comparison of 1G, 2G, and 3G bioethanol production in different countries, analyzing inputs and outputs throughout the process. While 3G has some environmental advantages compared to 1G and 2G, such as CO₂ capture during biomass cultivation and the use of wastewater to cultivate microalgae, as well as a relatively lower water and land footprint compared to other feedstocks such as sorghum, cassava, and sugarcane [184], there are also some factors that are not as favorable for 3G, as can be seen in Table 6 below.

7. Future Perspectives

The present challenges in bioethanol technologies for 1G environmental issues include unfavorable climate conditions such as droughts that lead to a decrease in food crop production and interfere with feed and food chains around the world. Additionally, the use of fertilizers and pesticides results in an increase in air, water, and soil pollution. Low government investment and an increase in taxes may cause some bioethanol plants to disappear [15]. Meanwhile, 2G faces problems in the pretreatment and hydrolysis processes that may not be suitable on an industrial scale. In 3G, microalgae cultivation (including strain selection and cultivation conditions) and cell collection are critical steps that influence bioethanol production. A large volume of water and nutrients are required, but this can be resolved by using wastewater. Biomass represents 40% to 70% of the total production cost in both 1G and 2G bioethanol production, making it an important economic consideration. Further, in the case of 1G, biomass is obtained directly, while in 2G, additional steps such as pretreatment are required for the biomass used in the process. In some cases, biological hydrolysis represents 20% to 40% of the total cost in the second generation of bioethanol, which is the main challenge in the 1G and 2G bioethanol production process [193].

Biorefineries require high investments, which is why businesses look for stakeholders. Stakeholders could be individuals or a group of people that hold rightful interest in the operation. They can provide financial support or human resources. Stakeholders may be governmental or non-governmental, and they play crucial roles in economic and social aspects. Non-governmental stakeholders help to increase the social acceptance of these kinds of projects and obtain funding and resources. Governmental stakeholders fasten the land-use approval, provide subsidies, and facilitate the generation of policies [194]. Policies for biofuels around the world dictate that global governments should promote initiatives to enhance the development of the biofuels market.

The most important initiatives include creating a global partnership to support the production of biofuels from biomass, especially in developing countries, taking into consideration the predominant use of biomass. Global actions to fight climate change and reduce carbon footprint are also necessary, along with boosting the development of clean energy and innovating strategies to accelerate development in energy. Several countries aspire to grow their production of biofuels, such as some Latin American countries, specifically Brazil, which is projected to increase its biofuel production by 18% by 2030. Additionally, the use of genetic engineering to improve strain yield and manipulate biosynthesis has shown promising advances. Moreover, genetic engineering can manipulate cellulose and hemicellulose content, leading to advances in bioethanol production. On the other hand, the use of modified crops has raised ethical debates about their employment due to concerns about changes in nature and plant integrity [195,196]. To conclude, though various strategies are being developed to improve biofuel yield by employing sustainable practices, there is an urgent need to focus on the evaluation of the sustainability and the impact of new technologies on the environment or on society in the mid- and long-term before adopting them at a large scale.

8. Conclusions

The effective conversion of LCB raw materials into bioethanol depends on appropriate pretreatment (if required) and adequate operation conditions that maximize fermentable sugar content and the purification of final products. New technologies, such as genetic engineering, offer tools for developing microorganisms that are more competent in the direct conversion of fermentable sugars into ethanol, thereby improving the bioethanol process. It is critical to ensure the availability of raw materials without interfering with society’s development and necessities.

Effective pretreatment is necessary to prepare feedstock for convenient conversion into bioethanol. Furthermore, conditions during hydrolysis and fermentation play a key role in the conversion of substances from which ethanol can actually be obtained, and in subsequent downstream processes ultimately improve the quality of final products. Different technological perspectives, such as genetic tools, are enhancing bioethanol production through various metabolic pathways and developing robust strains that can be applied in the industrial sector, not just at the laboratory scale. Although bioethanol is an attractive alternative for combating the global energy crisis and climate change, life cycle assessment (LCA) evaluates the environmental risks that could be associated with bioethanol production, such as greenhouse gas emissions and energy consumption. LCA, in combination with the circular economy concept under a biorefinery approach, assesses the inputs required to obtain all final products (outputs) and their utilization in different industrial sectors and economic perspectives for the sustainable development society.