Unlocking the Potential of Biomass Resources: A Review on Sustainable Process Design and Intensification

Abstract

Biomass is a key renewable resource for advancing sustainable and circular energy systems. In contrast to prior reviews that predominantly emphasized well-established biomass types and conventional conversion technologies, this work offers a comparative synthesis that underscores underutilized feedstocks and emerging valorization pathways, providing a strategic perspective for sustainable process development. This review critically examines the current state of high-value-added bioproducts derived from biomass, focusing on their relevance to climate mitigation and resource efficiency. It explores sustainable process design strategies that enhance the environmental and economic performance of biomass conversion. Particular attention is given to recent advances in process intensification, including novel reactor configurations and heat integration techniques. The integration of sustainability assessment tools and multi-objective optimization approaches is analyzed to support data-driven decision-making. Multi-product biorefineries are discussed as central platforms for valorizing diverse feedstocks, supported by emerging models for supply chain integration. Present limitations such as feedstock heterogeneity, infrastructure constraints, and energy coupling challenges are reviewed, along with new opportunities in digitalization, modularization, and policy support. The novelty of this work lies in its cross-sectional synthesis of technologies, methodologies, and system-level strategies, offering a unified framework to unlock the full potential of biomass as a strategic vector for sustainable process development.

1. Introduction

The intensification of global climate change and energy insecurity has forced a historic reconsideration of current energy paradigms, particularly the continued reliance on fossil fuels, which still account for over 60% of global electricity generation as of 2020 [1]. Global warming, driven primarily by CO₂ emissions, threatens to raise global temperatures by up to 5.8 °C within the 21st century [2], with widespread implications for ecosystems, economies, and public health. In response, international frameworks such as the Paris Agreement and the EU Green Deal have called for urgent decarbonization and net-zero energy transitions, necessitating the development of scalable, flexible, and sustainable energy solutions [3,4].

Among renewable energy sources, biomass plays a unique and strategic role due to its dual capability to provide both energy and material products. Biomass currently supplies about 14% of total global energy, and up to 38% in emerging economies [5]. Its versatility enables applications across electricity generation, biofuels, heating, and industrial processes. For instance, in Germany, forest biomass and agricultural residues are widely used for combined heat and power production, contributing to grid stability [6]. In Asia, in Japan, wood residues and energy crops are integrated into distributed generation systems, supporting the transition toward renewable energy [7].

Notably, forest biomass accounts for the largest share of renewable energy use in the EU [3], and in countries such as Brazil and India, bioenergy contributes significantly to national energy mixes, 27% (160 TWh) and 12% (370 TWh), respectively [8]. Biomass not only supports national energy strategies but also contributes to rural development, industrial applications, and sustainable livelihoods [9,10]. In Latin America, the rural sector holds significant potential for biomass energy due to its diverse feedstocks. Key technologies include solar drying for biomass conditioning, thermochemical conversion via pyrolysis and hydrothermal methods for flexible biofuel production, and cogeneration systems for combined electricity and heat. Additionally, carbon fixation in forest plantations illustrates the potential for integrating energy production with climate mitigation. While implementation varies across the region, these approaches offer promising opportunities for sustainable energy and improved rural livelihoods [11]. In African countries such as South Africa, Ethiopia, and Nigeria, biomass remains a primary source of household energy while increasingly supporting small-scale industrial applications, with modern bioenergy pathways potentially supplying 20–30% of regional electricity demand [12]. These examples underscore the need to consider regional differences in feedstock availability, socio-economic conditions, and policy frameworks, which directly influence technology adoption, sustainability outcomes, and energy planning.

The role of biomass in climate change mitigation extends beyond energy substitution. It also involves integrated carbon management, waste valorization, and circular economy practices [5,13]. This is evident in initiatives like Indonesia’s biomass resource modeling, which projects that up to 312 Mt of biomass could fulfill 24% of national energy demand by 2050, particularly through waste-derived sources [14]. Similarly, in Switzerland, the technical biomass potential is estimated at 209 PJ/year, of which 50% can be sustainably harnessed [15].

However, exploiting biomass at scale requires reconciling technological, economic, and policy barriers. The transition remains uneven across regions: while some countries are advancing toward 100% renewable systems, as demonstrated by Pastore and de Santoli [16] in the Italian context using EnergyPLAN modeling, others have regressed due to geopolitical crises. For instance, the 2022 European energy crisis saw a temporary resurgence in fossil fuel use [17], highlighting the vulnerability of energy systems and the need for resilience-oriented planning [18].

From a technological standpoint, biomass can be processed through thermochemical (e.g., pyrolysis, gasification) or biochemical (e.g., fermentation, anaerobic digestion) routes to produce a wide range of energy carriers such as bioethanol, biogas, biohydrogen, bio-oil, and syngas [5,13]. Gasification, with efficiencies ranging from 70 to 85%, emerges as a leading pathway in terms of energy yield and reduced CO₂ emissions [6]. Yet, economic feasibility remains a challenge. Production costs for 2G ethanol vary between USD 0.78/L and USD 0.97/L, while 3G ethanol is still at pilot scale [13].

The biorefinery concept represents a systems-based solution to these challenges. By integrating process intensification (PI), material valorization, and environmental control, biorefineries enable multi-output configurations that optimize biomass use [19]. In Colombia, for example, palm oil residues processed through turbines and digestion systems could yield 61–227 MW of electricity and reduce greenhouse gas (GHG) emissions by up to 2.1% [20]. In Malaysia, palm oil waste-to-energy systems have progressed slowly despite policy incentives, constrained by biomass price volatility and policy implementation gaps [21].

Furthermore, biomass energy planning must consider both energy and non-energy demands, particularly for industrial feedstocks and chemicals [22]. These dual uses introduce resource competition, which must be addressed through integrated modeling approaches, such as those applied in Belgium, where 15% of the primary energy mix corresponds to non-energy biomass demand. Spatial analyses in China confirm that socioeconomic disparities and land use heterogeneity affect the viability of rural biomass transitions, with consumption saturation occurring around RMB 13,000 income threshold [23].

Beyond technology and economics, governance and policy frameworks are pivotal. The success of India’s RE pathway modeled with hourly resolution and integrating Power-to-X strategies hinges on targeted investment in storage and infrastructure, achieving levelized electricity costs of 42–52 €/MWh by 2050 [24]. Similarly, the sustainability guardrails proposed by Child et al. [25] advocate for embedding resilience, ethical criteria, and planetary boundaries into energy system modeling.

In terms of environmental performance, biomass offers tangible GHG reductions. In the Colombian palm oil sector, emissions range between 22.2 and 55.1 g CO₂ eq/kWh [20], while thermochemical processes for biofuel production exhibit lower NO_x and SO_x emissions [13]. However, biomass carbon neutrality remains debated due to methodological divergences in emissions accounting and land use assumptions [3].

Addressing the intermittent nature of renewables, biomass can contribute significantly to hybrid systems involving wind, solar, and hydro sources [26], supported by robust storage solutions such as batteries, thermal storage, and power-to-gas systems [27]. Sector coupling and integrated planning (especially under high-renewable penetration scenarios) are key to leveraging biomass flexibility across energy sectors [16].

Despite its promise, biomass still faces challenges in scale-up, land use competition, and policy coherence. The sustainability of biomass pathways must be evaluated not only by their carbon impact but also by their contributions to rural development, food security, and ecosystem services [28,29]. This review contributes to the existing literature by offering a comprehensive synthesis of sustainable process design and intensification strategies for biomass valorization, focusing on the integration of technological routes, spatial and socio-economic considerations, and energy system modeling. Unlike previous reviews that primarily focus on well-established biomass types and conventional conversion pathways, this work explicitly highlights underutilized feedstocks, emerging thermochemical and biochemical routes, and comparative assessments of process strategies. Beyond energy applications, particular attention is devoted to high-value-added bioproducts and their relevance to climate mitigation and resource efficiency, linking process design with broader sustainability goals. Recent advances in process intensification (such as innovative reactive distillation configurations, modular setups, and heat integration techniques) are critically examined, alongside the role of multi-product biorefineries as platforms for valorizing diverse feedstocks and supporting supply chain integration. The review further incorporates sustainability assessment tools and multi-objective optimization approaches to enable data-driven decision-making under real-world constraints. Present limitations, including feedstock heterogeneity, infrastructure gaps, and energy coupling challenges, are discussed together with emerging opportunities in digitalization, modularization, and policy support. The novelty of this work lies in bridging isolated advances across disciplines and scales, resulting in a unified framework that positions biomass valorization as a strategic enabler of circular, low-carbon, and resilient energy and resource systems.

2. Methodology

This review was conducted following a structured and systematic approach to ensure comprehensive coverage and critical evaluation of relevant literature on biomass valorization, sustainable process design, and intensification strategies. The scope of the review spans from the year 2000 to 2025, capturing both foundational and recent advancements within this 25-year period.

A targeted bibliographic search was carried out using scientific databases including Scopus, Web of Science, ScienceDirect, and Google Scholar. Keywords employed in the search strategy included combinations of: biomass conversion, bioenergy, biorefinery, process intensification, sustainability assessment, circular bioeconomy, renewable fuels, and supply chain integration. The selection criteria focused on peer-reviewed journal articles, book chapters, and official reports that provide quantitative data, techno-economic evaluations, methodological frameworks, or case studies relevant to biomass valorization.

The review is thematically organized into nine analytical sections: (1) introduction, (2) methodology, (3) high-value-added bioproducts derived from biomass, (4) sustainable process design for biomass conversion, (5) emerging strategies and technologies for process intensification, (6) sustainability assessment and process optimization, (7) multi-product biorefinery configurations and supply chain integration, (8) present limitations and emerging opportunities, and (9) final conclusions. Each section synthesizes insights from multiple disciplines, including chemical engineering, environmental science, policy, and industrial ecology, to provide an integrated perspective.

To ensure temporal relevance, particular attention was given to literature published in the last decade (2015–2025), while seminal studies from the early 2000s were included for historical context and foundational understanding. Priority was given to works that include quantitative assessments (e.g., life cycle analysis, energy and mass balances, cost analysis), model-based simulations (e.g., EnergyPLAN, techno-economic optimization), and policy-relevant discussions, ensuring a multidimensional examination of biomass-based sustainable transitions. Figure 1 illustrates the review process, the volume of literature analyzed, and the inclusion/exclusion criteria.

Building upon this structured methodology and comprehensive literature mapping, the following sections delve into the technical, economic, and environmental dimensions of biomass valorization. The analysis begins with an overview of high-value-added bioproducts derived from diverse biomass feedstocks, highlighting their conversion potential and strategic relevance in sustainable industrial systems.

3. High-Value-Added Bioproducts from Biomass

Biomass resources are highly diverse and include a wide array of feedstocks with potential for sustainable fuel and material production. These can be grouped into the following categories:

• Lignocellulosic biomass, encompassing agricultural residues, forestry residues, dedicated energy crops, and industrial residues. These materials are rich in cellulose, hemicellulose, and lignin, making them suitable for a variety of biochemical and thermochemical conversion processes [30,31].
• Lipid-rich wastes (fats, oils, and greases (FOG)), including yellow grease, brown grease from sewer lines, and palm oil by-products, representing low-cost feedstocks convertible into fuels via transesterification, pyrolysis, or thermal cracking [32,33].
• Algal biomass, both micro- and macroalgae, rich in lipids, proteins, and polysaccharides, with potential for biofuels, bioplastics, and nutraceuticals [34].
• Biogenic fraction of municipal solid waste (MSW), mainly food waste, paper, and cardboard, increasingly valorized via anaerobic digestion and thermochemical routes [35].
• Animal manure, traditionally used in biogas production and often co-digested to improve methane yield [36].
• Aquatic plants and invasive weeds, such as water hyacinth (Eichhornia crassipes), representing low-cost, underutilized biomass feedstock with potential for bioenergy and environmental remediation [37].

Biomass is a renewable source of compounds that can be transformed into a wide variety of bioproducts, ranging from basic bioblocks to high-value-added products. Depending on its composition, products can be obtained through different conversion routes, such as fermentation, enzymatic hydrolysis, pyrolysis, gasification, transesterification, and chemical extraction.

Table 1. Bioproducts and Conversion Pathways of Various Biomass Types.

Biomass Type	Bioblocks/Intermediates	High-Value-Added Products	Conversion Route	Applications
Lignocellulosic Biomass	Glucose, xylose, arabinose, mannose, galactose, glucuronides, phenolic monomers oligosaccharides, pectin, cellulose nanoparticles, lignin extractives	Bioethanol, xylitol, levulinic acid, 5-HMF, lactic acid, glucaric acid, sorbitol, mannitol, vanillin, guaiacol, bio-oil, bioplastics (PLA, PHA), glycols (EG, PG), phenolic resins, adhesives, biochar, activated carbon	Enzymatic or acid hydrolysis, fermentation, pyrolysis, gasification, chemical oxidation, depolymerization, extraction, mechanical milling	Biofuels, green chemicals, biodegradable materials, solvents, adhesives, cosmetics, advanced materials, fertilizers, filtration
Vegetable Oils/Fats (including FOG, brown grease, palm oil waste)	Fatty acids, triglycerides	Biodiesel, glycerol, biolubricants, surfactants, polyhydroxyalkanoates (PHA), soaps, waxes	Transesterification, fermentation, hydrolysis, polymerization	Fuels, cosmetics, detergents, bioplastics, personal care products
Organic residues (fruits, vegetables, manure, bagasse, urban food waste)	Sugars, amino acids, organic acids (citric, malic, lactic), proteins	Biogas (CH4), lactic acid, succinic acid, butyric acid, biofertilizers, enzymes, probiotics, bioethanol	Fermentation, anaerobic digestion, extraction, hydrolysis	Renewable energy, bioplastics, animal feed, agriculture, functional foods
Microalgae	Carbohydrates, lipids, proteins, pigments	Biodiesel, bioethanol, pigments (β-carotene, phycocyanin, astaxanthin), omega-3 fatty acids, biofertilizers, biopolymers	Lipid extraction, fermentation, transesterification, purification	Fuels, dietary supplements, cosmetics, functional foods, agriculture
Marine Biomass (red, brown, green algae)	Polysaccharides (alginate, carrageenan, agar), proteins, lipids	Bioplastics, edible gels, biofertilizers, antioxidants, purified carrageenans	Extraction, fermentation, polymerization	Food, cosmetics, agriculture, biomedicine

summarizes the main bioproducts derived from different types of biomass, specifying their intermediates, final products, conversion routes, and applications:

Among these diverse resources, lignocellulosic biomass stands out as particularly versatile and abundant in the context of a circular economy. Its composition, rich in cellulose, hemicellulose, and lignin, allows the production of a wide range of products (Figure 2), including advanced biofuels, platform chemicals, bioplastics, composite materials, and functional additives [38]. However, the efficient use of this raw material depends on a detailed understanding of its structural and compositional diversity.

3.1. Types of Lignocellulosic Biomass

From the point of view of its origin, lignocellulosic biomass can be classified into four large groups: agricultural waste (such as straw, husks, leaves and stems), forest waste (such as branches, sawdust and cutting waste), energy crops (such as switchgrass or miscanthus), and industrial waste (from the paper, textile, food industry, among others). Each type of biomass has a unique compositional profile that determines its suitability for different biochemical or thermochemical conversion pathways.

The variability in the proportion of cellulose, hemicellulose, and lignin directly influences the efficiency of processes such as enzymatic hydrolysis, fermentation, pyrolysis, or gasification. For example, residues such as sugar cane or coffee bagasse have a balanced balance between cellulose and hemicellulose, facilitating their transformation into fermentable sugars. In contrast, materials with high lignification, such as cotton stalks or pine wood, require more intensive pretreatments to break down the lignocellulosic matrix and allow access to structural carbohydrates.

Understanding this compositional heterogeneity is key to the design of efficient and sustainable recovery strategies.

Table 2. Composition of lignocellulose on a dry basis of lignocellulosic materials.

Lignocellulosic Materials	Cellulose (%)	Hemicellulose (%)	Lignin (%)
Softwood stalks	40–55	24–40	18–25
Hardwood stalks	45–50	25–35	25–35
Corn cobs	45	35	15
Barley husks	34	36	19
Barley straw	36–43	24–33	6.3–9.8
Bamboo	49–50	18–20	23
Banana waste	13	15	14
Corn stover	35.1–39.5	20.7–24.6	11.0–19.1
Cotton	85–95	5–15	0
Cotton stalk	31	11	30
Coffee pulp	33.7–36.9	44.2–47.5	15.6–19.1
Douglas fir	35–48	20–22	15–21
Eucalyptus	45–51	11–18	29
Softwood stems	45–50	24–40	25–35
Hardwood stems	45–55	23–25.	18–25
Rice husk	28.7–35.6	11.96–29.3	15.4–20
Wheat straw	35–39	22–30	12–16
Wheat bran	10.5–14.8	35.5–39.2	8.3–12.5
News paper	40–55	24–39	18–30
Paper	85–99	1–5	1–15
Waste paper from chemical pulps	60–70	10–20	5–10
Sugarcane bagasse	25–45	28–32	15–25
Sugarcane tops	35	32	14
Pine	42–49	13–25	23–29
Poplar wood	45–51	25–28	10–21
Olive tree biomass	25.2	15.8	19.1
Jute fibers	45–53	18–21	21–26
Switchgrass	35–40	25–30	15–20
Grasses	25–40	25–50	10–30
Winter rye	29–30	22–26	16.1
Oilseed rape	27.3	20.5	14.2
Softwood stem	45–50	24–40	18–25
Oat straw	31–35	20–26	10–15
Nut shells	25–30	22–28	30–40
Sorghum straw	32–35	24–27	15–21
Tamarind kernel Powder	10–15	55–65	20–35
Groundnut shells	25–30	25–30	30–40
Water hyacinth	18.2–22.1	48.7–50.1	3.5–5.4

summarizes a wide range of lignocellulosic materials reported in the literature, along with their approximate cellulose, hemicellulose, and lignin content on a dry basis [39].

3.2. Biomass Heterogeneity: Obstacle or Opportunity?

One of the main challenges in the valorization of lignocellulosic biomass is its heterogeneity. Variations in chemical composition, moisture, density, and physical structure between different sources make it difficult to standardize processes and design universal conversion technologies. This variability can affect the performance of thermochemical or biochemical processes, as well as the quality of the final product [40].

However, if properly managed, this heterogeneity can become a strategic advantage. The diversity of structural components allows flexibility in the production of multiple products (multiproduct biorefineries), favoring the integration of complementary chemical routes. In addition, the combined use of different types of biomass makes it possible to take better advantage of seasonality, reduce dependence on a single input, and promote decentralized biorefinery models [10,41].

It has been shown, for example, that the mixture of sugarcane bagasse and forest residues improves the efficiency of pre-treatments and hydrolysis processes in the production of fermentable sugars [42,43]. In this sense, the integration of multi-source logistics chains and predictive modeling tools is essential to transform variability into technological and economic resilience [9,10].

3.3. Value-Added Products

Through biochemical and thermochemical conversion pathways, lignocellulosic biomass can be transformed into a wide variety of compounds applicable in energy, chemical, food, biomedical, and advanced materials sectors.

Among the most relevant products are:

• Second-generation bioethanol, produced by enzymatic hydrolysis of cellulose and hemicellulose, followed by fermentation. This biofuel is key in the transition to renewable energy sources, especially when produced from agro-industrial waste [44].
• Platform acids such as lactic acid, levulinic acid, succinic acid, and itaconic acid, which act as chemical building blocks. These compounds enable the synthesis of green solvents, biodegradable plastics, and industrial additives, and have been identified as priorities by the U.S. Department of Energy for building a renewable bioeconomy [45,46,47].
• Modified lignin, used as a reinforcement of composite materials and as a partial substitute for phenolic resins, represents an efficient strategy to valorize a historically underutilized fraction of biomass [43].
• Biogas and biohydrogen, obtained through anaerobic digestion and gasification, are clean energy vectors that can be integrated into hybrid networks and sustainable industrial applications [36,37].
• Nanocellulose and bifunctional materials are used as biodegradable packaging, films, and in pharmacy [48,49].

These products can be functionally grouped into four main categories:

• Platform chemicals (building blocks): include lactic acid, succinic, itaconic acid, HMF (5-hydroxymethylfurfural), furfural, levulinic acid, and FDCA (furandicarboxylic acid), used in the synthesis of biopolymers, resins, and solvents. These building blocks are valuable within specialized markets, for example, succinic acid has an estimated market price between 2.0 and 3.0 USD/kg [50], while itaconic acid reaches 2 USD/kg [51]. HMF, of high purity, exceeds 6.0 USD/kg, due to its strategic role in obtaining bio-based monomers such as FDCA [52].
• Biopolymers: Polylactic acid (PLA), with strong growth in sectors such as packaging, medicine, and electronics due to its renewable origin and versatile properties, its global demand in 2019 was 400,000 tons, with projections to double every 3–4 years [53]. Other biopolymers with growth are those such as polyhydroxyalkanoates (PHAs), where their price ranges between 2.0 and 6.0 USD/kg, depending on the degree of purity and the production method [54].
• Bio-based materials: Nanocellulose and aromatic lignin derivatives stand out in this category, both with great potential in applications such as coatings, adhesives, paints, biodegradable packaging, and advanced composite materials. Nanocellulose, in particular, has established itself as a strategic material thanks to its high mechanical strength, biodegradability, barrier capacity, and functional versatility. In today’s market, its price is between USD 2000 and USD 3500 per tonne, reflecting its value in specialized technical applications. On the other hand, more conventional cellulosic materials such as microcrystalline cellulose (MCC) and powdered cellulose (PC) continue to be widely used due to their availability and low relative cost. MCC fetches prices of $4–5/kg in Asia and up to $6–7/kg in Europe and the US, while PC trades at $2.5–3/kg, making it a viable option for less demanding industrial applications. This diversity of bio-based materials allows technical solutions to be adjusted according to performance requirements and the economic production environment [55].
• Bioactive compounds: such as polyphenols, terpenoids, and flavonoids, present in plants and agro-industrial waste, they are valued for their antioxidant, anti-inflammatory, and therapeutic properties that make them useful in nutraceutical, cosmetic, and pharmaceutical applications. These compounds contribute to the prevention of chronic diseases, the development of anti-aging products, and the formulation of drugs with antimicrobial and anticancer activity [56].

The production of these compounds is based on technologies such as microbial fermentation, enzymatic catalysis, pyrolysis, chemical transformation, and hybrid processes that integrate biological and chemical stages. Lignocellulosic biomass and agro-industrial waste represent ideal raw materials due to their abundance and low cost. Notable examples include the commercial production of lactic acid from starch-rich residues and the industrial scale-up of FDCA from HMF.

Emerging trends point towards bioproducts with advanced functionalities, such as smart packaging, controlled release systems, and stimulus-sensitive biomaterials. These innovations are driven by advances in synthetic biology, metabolic engineering, and process intensification, along with digital simulation and optimization tools that enable the design of flexible and resilient biorefineries.

In short, the development of high-value bioproducts derived from biomass is essential to consolidate a sustainable bioeconomy. Its effective implementation depends on regionally adapted biorefinery models, which integrate technical, economic and environmental criteria to maximize the value of bio-based supply chains.

Having identified the key bioproducts derived from various biomass sources, the next section examines the principles and strategies for designing sustainable conversion processes. This includes evaluating configurations that balance technical performance with environmental and economic criteria.

4. Sustainable Process Design for Biomass Conversion

Biomass can be converted into fuels and chemicals through two primary pathways: thermochemical and biochemical processes. Thermochemical conversion (e.g., pyrolysis, gasification, hydrothermal liquefaction) utilizes heat, sometimes with catalysts or oxidants, to break down organic matter into energy-dense fuels, while biochemical conversion (e.g., fermentation, anaerobic digestion) relies on microorganisms or enzymes to transform biomass into desired products. Figure 3 provides a conceptual overview of these two conversion routes, including representative technologies and key evaluation criteria. These pathways are central to sustainable chemical production because they offer renewable alternatives to fossil resources and can utilize waste materials, thereby reducing greenhouse gas emissions and environmental impact. In assessing biomass conversion routes, several criteria are considered.

Energy efficiency is paramount—the goal is to maximize the usable energy output (fuel, heat, or electricity) per unit of biomass input while minimizing energy losses. Selectivity refers to how preferentially a process yields the target product over undesired by-products—for instance, a fermentation that cleanly produces mainly ethanol with few side-products, or a pyrolysis that yields a high fraction of liquid fuel oil. Product quality is crucial since fuel properties (e.g., calorific value, stability, purity) determine usability—for example, bio-oils may require upgrading to meet diesel or gasoline standards, and fermentation products like ethanol need purification to remove water. Finally, scalability and feasibility of the process determine its practical deployment: sustainable design must consider whether the conversion technology can be economically scaled up and integrated into existing infrastructure, and how it copes with feedstock variability and supply chain logistics. Thermochemical methods often have advantages in processing speed and feedstock flexibility, whereas biochemical methods operate under milder conditions with potentially higher specificity. A sustainable biomass conversion design will judiciously choose the pathway or combination of pathways that best fit the feedstock characteristics, energy requirements, and environmental goals.

4.1. Thermochemical Conversion Processes

Thermochemical conversion employs heat and sometimes chemical agents to deconstruct biomass into gas, liquid, and solid products. These processes occur at high temperatures and can achieve rapid conversion of even recalcitrant biomass like lignocellulose. The three major thermochemical techniques used in sustainable process design are pyrolysis, gasification, and hydrothermal processing. Each of these has distinct operating principles, reactor systems, and product slates, but all share the goal of maximizing energy recovery from biomass with minimal waste. In general, thermochemical routes can handle a wide range of feedstocks (including agricultural residues, wood, and wet waste) and have faster reaction times than biochemical routes. However, they often require extensive heat input and advanced materials to withstand harsh conditions, affecting their overall efficiency and economics. Below, each thermochemical process is discussed with an emphasis on operating conditions, reactor configurations, products, and performance metrics relevant to sustainable design.

To provide a clear overview of these processes,

Table 3. Comparative summary of thermochemical conversion routes, highlighting operating conditions, reactor types, main products, and sustainability relevance.

Process	Operating Conditions	Reactor Types	Main Products	Key Features/Sustainability Relevance
Pyrolysis	350–700 °C, absence of oxygen	Fixed-bed, fluidized-bed, rotary kiln, ablative, microwave-assisted	Bio-oil (60–75%), biochar, syngas	Fast reactions, flexible product distribution (slow/fast/catalytic), bio-oil needs upgrading
Gasification	800–1200 °C, partial oxidation with air/steam/O2	Fixed-bed (updraft/downdraft), fluidized-bed, entrained flow	Syngas (H2 + CO), char, tars, particulates	High efficiency (60–75%), syngas used for heat, power, or synthesis (FT fuels, methanol, H2, ammonia)
Hydrothermal Processing	180–374 °C, 10–25 MPa, aqueous medium (avoids drying)	Stirred reactors, continuous-flow systems (for HTL/HTC)	HTL: bio-crude oil, aqueous phase, hydrochar, CO2; HTC: hydrochar (coal-like, carbon-rich solid)	Direct use of wet biomass (algae, sludge, manure), nutrient recovery, potential integration in biorefineries

presents a comparative summary of the main thermochemical routes, their operating conditions, reactor configurations, primary products, and sustainability relevance.

Following this overview, each thermochemical route is discussed in greater detail.

4.1.1. Pyrolysis

Pyrolysis thermally decomposes biomass without oxygen to produce bio-oil, biochar, and non-condensable gases. Process class (slow/fast/flash/catalytic), heating rate, and vapor residence time determine yields; fast pyrolysis at ~500 °C can deliver ~60–75 wt% bio-oil (dry basis), with the remainder as char and gas. Reactor options include fixed-bed, fluidized-bed, auger/rotary kilns, and ablative or microwave-assisted designs. For scalability and economics, the central bottleneck is upgrading: raw bio-oil (acidic, oxygen-rich, unstable) typically requires hydrodeoxygenation and hydrogen supply, often favoring distributed pyrolysis + centralized upgrading hubs to exploit scale in hydrotreating and hydrogen management. Among the sustainability co-benefits of pyrolysis is the production of biochar, the solid residue of the process, which is rich in carbon and inorganic nutrients and exhibits high porosity and surface area [57,58]. It can serve as a solid fuel, a soil amendment to improve fertility and sequester carbon, or as an adsorbent for pollutants, heavy metals, and organic contaminants [59]. Its high stability allows long-term carbon storage in soils, contributing to climate change mitigation, while enhancing soil water retention, microbial activity, and nutrient availability [58]. Beyond being a byproduct, biochar is increasingly recognized as a valuable co-product of pyrolysis, with potential applications in water purification, compost enhancement, and as a precursor for activated carbon and catalyst supports [60]. Integrating biochar valorization into pyrolysis enhances both the economic and environmental performance of the process, promotes circular bioeconomy strategies, and supports sustainable land management and carbon-negative energy systems [61].

The combustible gases (CO, H₂, CH₄, light hydrocarbons, CO₂) released during pyrolysis (often 10–20% of the output) can be burned on-site to provide process heat or further processed (e.g., cleaned and used in gas engines) [57]. Pyrolysis is generally considered energy-efficient when integrated properly: the process can be self-sustaining by combusting a portion of the syngas/volatiles to maintain reactor heat, and fast pyrolysis in particular aims to maximize liquid fuel yield, which concentrates much of the biomass energy (up to ~70% of the feed’s energy content in the bio-oil product). However, achieving high efficiency and selectivity requires careful control to avoid excessive char (which locks up fuel carbon) or gas production, and catalytic or staged processes are often researched to improve oil quality and stability. Overall, pyrolysis offers a pathway to convert solid biomass into a transportable liquid fuel intermediate, with the trade-offs of needing dry feedstock and requiring downstream upgrading for high-quality biofuels.

4.1.2. Gasification

Gasification is a thermochemical process that converts biomass into a combustible synthesis gas (syngas) through partial oxidation at high temperatures. Unlike pyrolysis, gasification introduces a controlled amount of oxygen (or air/steam) to react with the biomass, but not enough to fully combust it. Operating temperatures are typically in the range of 800–1200 °C (and up to ~1500 °C in some systems), which ensures that the organic molecules break apart into primarily small gases. The syngas produced consists mainly of hydrogen (H₂) and carbon monoxide (CO)—the key combustible components—along with carbon dioxide, light hydrocarbons like methane (CH₄), water vapor, and minor tars and char particles. A representative composition from air-blown biomass gasifiers might be roughly 15–20% H₂, 15–20% CO, 8–15% CO₂, a few percent CH₄, and the rest N₂ (if air is used). The exact composition and heating value of the syngas depend on the gasification agent (air, pure oxygen, or steam), the temperature and pressure, and the feedstock properties. Using air yields a nitrogen-diluted syngas with a lower heating value (~4–7 MJ/m³), while oxygen or steam gasification produces a higher-calorific syngas (10–15 MJ/m³) more suitable for chemical synthesis. Scale-up hinges on reliable syngas cleanup (tars, particulates, NH₃, H₂S, HCl, trace metals) and capital intensity of downstream synthesis. Cold/hot gas cleanup and advanced filtration/catalytic reforming are active areas that directly affect capex/opex and plant availability. For sustainability, integrating CHP, heat recovery (e.g., for drying), and co-feeding residues improves net efficiency and GHG performance, while modular gasifiers can reduce logistics barriers for dispersed feedstocks [62].

The primary product, syngas, can be used directly for heat and power (for example, in internal combustion engines, gas turbines, or boilers) or serve as an intermediate for synthesizing fuels and chemicals. Notably, syngas can be catalytically converted via Fischer–Tropsch synthesis into liquid hydrocarbons or used to produce methanol, dimethyl ether, hydrogen, or ammonia. The quality of syngas is crucial: selectivity toward H₂ and CO (and minimal tar) is desired for chemical synthesis applications. Catalysts (often nickel-based or alkali metals) may be used inside the gasifier or in secondary reactors to crack tars and boost H₂ yields. A major challenge in biomass gasification is tar formation—complex hydrocarbons that can condense and foul downstream equipment. Thus, gas cleaning is a significant part of any gasification system. Tar mitigation strategies include high-temperature cracking or catalytic reforming in situ, as well as downstream measures like thermal or catalytic tar crackers and scrubbing systems. Particulates (ash, char fines) must also be removed, often by cyclones and filters, and if the gas is to be used in engines or turbines, removal of acid gases (H₂S, HCl) may be required to prevent corrosion. From an energy efficiency perspective, modern biomass gasifiers can be quite efficient at converting feedstock energy into chemical energy in syngas (often 60–75% cold gas efficiency, depending on heat recovery). Some heat is lost in the form of sensible heat in hot gas and in char/ash residues. Integrating gasifiers with combined heat and power (CHP) systems or using waste heat for biomass drying can improve overall efficiency. Selectivity can be tuned by process conditions: for instance, adding steam can enhance hydrogen production via water–gas shift, yielding a syngas with a higher H₂/CO ratio suitable for certain end-uses [63].

While pyrolysis is often associated with biochar production, gasification also generates a carbon-rich char fraction that can be valorized. Char from gasification typically has higher fixed carbon content and lower volatile matter than pyrolytic biochar due to the higher operating temperatures and partial oxidation environment [64]. This type of biochar can be used not only as a solid fuel but also for soil amendment, carbon sequestration, and as a precursor for advanced carbon materials. Its mineral content, including potassium, calcium, and phosphorus, makes it suitable for improving soil fertility, especially in degraded lands. Moreover, gasification biochar exhibits enhanced adsorption properties for removing heavy metals and organic pollutants from wastewater, due to its higher surface area and porosity compared to pyrolysis char [58]. Recovering and utilizing this biochar fraction adds value to gasification processes by promoting circular economy strategies, enhancing environmental performance, and providing additional revenue streams from byproducts, particularly when integrated with combined heat and power (CHP) systems [65].

4.1.3. Hydrothermal Processing (Liquefaction & Carbonization)

Hydrothermal processing utilizes water at elevated temperatures and pressures to convert wet biomass into fuels without the need for prior drying. In this approach, subcritical or supercritical water acts as both reactant and solvent to decompose biomass, taking advantage of the unique properties of water under these conditions (such as increased ionic product, altered solvation behavior, and catalyst-like activity of hot compressed water). Two main variants are usually highlighted: hydrothermal liquefaction (HTL), which operates in the subcritical water regime to maximize liquid oil production, and hydrothermal carbonization (HTC), which typically uses lower subcritical temperatures to produce a solid char product. In HTL, biomass (which can be algae, wet agricultural residues, sewage sludge, etc.) is treated at ~250–374 °C and 10–25 MPa for residence times on the order of minutes to an hour. These conditions keep water in liquid form (near or just below its critical point of 374 °C) and promote reactions that break down biopolymers into smaller, hydrophobic molecules that coalesce into an energy-dense bio-crude oil. HTC, by contrast, uses milder conditions (typically 180–250 °C, saturated pressure) for longer times (hours) to yield a hydrochar—a coal-like solid—by dehydration and decarboxylation reactions; HTC is essentially a “wet torrefaction” useful for solid fuel upgrading or soil amendment char production. The main products of hydrothermal liquefaction are: a viscous biocrude oil, an aqueous phase containing water-soluble organics (e.g., short-chain acids, alcohols, furans), a solid residue (hydrochar, which contains unreacted material and re-polymerized char), and gaseous products (mostly CO₂ with some H₂, CH₄ depending on conditions). Hydrothermal carbonization (at ~200 °C) primarily yields a solid hydrochar by enhancing polymerization and carbon condensation reactions—essentially concentrating carbon in the solid and expelling oxygen as CO₂ and water. The hydrochar is a porous, coal-like material that can be used as a solid fuel (with improved handling and energy density compared to raw biomass) or as a soil amendment/adsorbent. HTC typically achieves 60–70% solid yield and captures a large portion of feed carbon in the char, whereas HTL focuses on maximizing liquid yield at higher temperature and pressure. In terms of energy efficiency, hydrothermal processes can be very effective since they operate in a closed system where much of the sensible heat can be recovered, and they do not require drying energy [66].

4.2. Biochemical Conversion Processes

Biochemical conversion harnesses the capabilities of biological systems—microorganisms and enzymes—to transform biomass into fuels and chemicals under milder conditions (typically near-ambient temperatures and pressures). These processes tend to be highly selective for specific products and can achieve complete conversion of particular biomass components (like sugars), but generally require that the complex polymers in raw biomass (cellulose, hemicellulose, etc.) be broken down into fermentable substrates first. Biochemical routes are at the core of many established biofuel industries (e.g., ethanol from sugarcane or corn) and are essential for producing certain chemicals (like organic acids or biopolymers) from renewable feedstocks. In the context of sustainable process design, biochemical processes often have a lower energy input requirement than thermochemical processes (since they operate without extreme heat), but their overall efficiency depends on feedstock pretreatment and the efficiency of biological metabolism, as well as the energy needed for product recovery (e.g., distillation). Below, we discuss key biochemical conversion processes: fermentations for biofuels and biochemicals, anaerobic digestion for biogas, and the enzymatic hydrolysis steps and integrated configurations that enable these conversions. To illustrate the diversity of reactor technologies and their associated biochemical pathways, Figure 4 presents a comparative overview of reactor configurations, conversion processes, and the main bioproducts obtained through fermentation, anaerobic digestion, and enzymatic hydrolysis.

4.2.1. Fermentation-Based Processes

Substrates: Biochemical fermentation processes use sugars or other simple organic substrates derived from biomass. Lignocellulosic biomass (such as agricultural residues or wood) is composed mainly of cellulose (glucose polymers), hemicellulose (mixed sugars like xylose, arabinose, mannose), and lignin. Before fermentation, a pretreatment step is usually required to break the rigid structure, and an enzymatic hydrolysis (see Section 4.2.3) releases fermentable sugars (glucose, xylose, etc.) from cellulose and hemicellulose. In some cases, biomass that contains readily accessible sugars or starch (like sugarcane juice, corn starch, or algal starch) can be directly used after enzymatic or acid hydrolysis to monomer sugars. Emerging feedstocks include not only terrestrial plants but also algal biomass; some microalgae, for instance, accumulate starch or simple carbohydrates that can be fermented after cell disruption. Additionally, the organic fraction of municipal solid waste or food waste can be enzymatically saccharified to generate a fermentable broth. In all cases, effective pretreatment and hydrolysis are critical to maximizing sugar yield and minimizing inhibitors (such as furfural, HMF, or phenolics from harsh pretreatments) that could impair microbial fermentation. Reactor Types: Fermentations are typically carried out in stirred-tank bioreactors, which can operate in batch, fed-batch, or continuous modes. In batch fermentation, all substrates are added at the start, and the process runs to completion; this is simple and common for ethanol production. Fed-batch involves adding substrate gradually to control the fermentation rate or avoid inhibition—this is often used for high-density ethanol or butanol fermentations to achieve higher yields. Continuous fermentation (e.g., a chemostat) feeds substrate continuously and harvests product broth continuously at steady-state; it can have higher productivity and is used in some large-scale operations (like continuous fuel ethanol plants or industrial acid fermentations) [48].

Target Products: A range of bio-based products can be made via fermentation of biomass-derived sugars:

• Ethanol: The most established biofuel, produced typically by yeast (Saccharomyces cerevisiae) or bacteria (Zymomonas) fermenting glucose (and with engineered strains, also fermenting xylose from hemicellulose). Ethanol yields from glucose approach the theoretical maximum of 0.51 g ethanol per g sugar (since yeast fermentation yields 2 ethanol + 2 CO₂ per glucose). In practical terms, yields of 0.45–0.50 g/g are achieved, corresponding to conversion efficiencies around 88–98% of theoretical [67].
• Butanol (and Acetone-Butanol-Ethanol, ABE): Butanol is produced via fermentation by certain bacteria [67].
• Organic acids: Fermentation can produce organic acids such as lactic acid (by lactic acid bacteria) and succinic acid (by certain bacteria or fungi), among others. Lactic acid fermentation (used in the food industry) can achieve near-quantitative conversion of glucose to lactic acid (yield ~0.9 g/g for homofermentative pathways, since one glucose yields two lactic acid with no CO₂). Lactic acid is a building block for biodegradable plastics (PLA—polylactic acid). Succinic acid is another biomass-derived platform chemical used for polyesters and resins; some bacterial strains (e.g., engineered Actinobacillus or Basfia) can convert sugars and CO₂ into succinic acid with high yield (in some cases exceeding 1 g per g sugar by fixing carbon from CO₂) [67].
• Bioplastics and others: Besides monomeric acids, some fermentations allow direct production of polymeric materials. For example, certain bacteria (like Ralstonia eutropha) can accumulate PHAs, which are biodegradable polyesters, in their cells when fed sugars or volatile fatty acids under nutrient-limited conditions. While not a classical fermentation product (since it is intracellular and must be extracted), PHAs offer a direct route to bioplastics from renewable substrates.

4.2.2. Anaerobic Digestion and Biogas Production

Anaerobic digestion (AD) is a biochemical process in which consortia of microbes break down organic matter in the absence of oxygen, yielding biogas (a mixture of mostly methane and CO₂) and a nutrient-rich residue (digestate). AD is widely used for waste treatment (sewage sludge, animal manure, food waste) and renewable energy production in the form of biogas. The process occurs naturally in environments like swamps and landfills, but engineered anaerobic digesters optimize this to capture methane for use as fuel [68].

Process stages: AD proceeds through four key stages carried out by different microbial groups: (1) Hydrolysis—enzymes (often produced by bacteria or fungi) break down complex polymers (carbohydrates, proteins, fats) into soluble monomers like sugars, amino acids, and fatty acids. This is a crucial first step, especially for solid lignocellulosic substrates, and can be rate-limiting if the material is not easily hydrolysable (e.g., high lignin content can slow hydrolysis). (2) Acidogenesis—acidogenic (fermentative) bacteria consume the monomers from hydrolysis and ferment them into short-chain volatile fatty acids (VFAs such as acetic, propionic, butyric acids), alcohols, H₂, CO₂, and ammonia (from amino acids). This stage essentially produces a mixture of organic acids and gases. (3) Acetogenesis—acetogenic bacteria convert the higher organic acids and alcohols produced in acidogenesis into primarily acetic acid, H₂, and CO₂. For instance, propionate and butyrate are oxidized to acetate and H₂/CO₂. This stage is often dependent on syntrophic cooperation with hydrogen-consuming organisms because the reactions are thermodynamically favorable only when H₂ is kept at low partial pressure. (4) Methanogenesis—methanogenic archaea convert acetic acid to methane and CO₂ (aceticlastic methanogenesis) or use H₂ to reduce CO₂ to methane (hydrogenotrophic methanogenesis). Roughly 70% of biogas methane typically comes from acetate conversion and 30% from H₂/CO₂ conversion, though this can vary. The result is biogas with about 50–70% CH₄ and 30–50% CO₂, plus trace impurities like hydrogen sulfide (H₂S), ammonia, and water vapor. A common composition is ~60% CH₄, ~40% CO₂ for many substrates, giving a heating value of roughly 20–25 MJ per cubic meter of biogas. The leftover material, or digestate, contains the indigestible fraction (e.g., lignin, minerals) and microbial biomass, and is often used as a fertilizer since it retains most of the nutrients (N, P, K) from the feedstock in a [68].

Outputs and yields: The main output, biogas, is a versatile renewable fuel. It can be combusted directly in boilers for heat, used in CHP engines to produce electricity and heat, or upgraded to biomethane (by removing CO₂ and impurities) to pipeline quality for use as a natural gas substitute or vehicle fuel. Typical methane yields are often reported in terms of volume of methane per mass of volatile solids (VS) fed. For example, digestion of sewage sludge or manure might yield around 0.2–0.3 m³ CH₄ per kg VS, whereas more easily degradable substrates like food waste or grease can yield 0.4–0.6 m³ CH₄/kg VS. In terms of energy, if a biomass has, say, 18 MJ/kg dry and half of that energy is converted to methane in biogas, the process captures ~50% of the energy (some of the rest remains in the digestate, mainly in the form of residual carbon like lignin). Indeed, the literature indicates energy conversion efficiencies (feedstock to biogas energy) in the range of 20–40% of the biomass LHV for many waste substrates—this may sound low relative to thermochemical processes, but one must consider that the non-converted fraction is often the lignin and refractory portion, which could be separately combusted or processed. Selectivity issues: AD is generally less selective in the sense that its product is always a mixture of CH₄ and CO₂ regardless of feedstock, but there are issues of biogas purity. Notably, H₂S is generated from any sulfur in the feed (as microbes reduce sulfate or degrade sulfur-containing proteins), and even a few hundred ppm of H₂S can cause corrosion in engines and pipes and needs to be removed (by scrubbers or iron sponge absorbers) if the biogas is to be used extensively. CO₂ in biogas is not burned and dilutes the energy content; removing CO₂ (via water washing, amine scrubbing, membrane separation, etc.) yields biomethane (~98% CH₄) which can directly substitute for natural gas. For on-site heat or power generation, often the CO₂ is tolerated and the engine/genset simply handles a lower BTU gas. There is interest in biogas upgrading because biomethane injection into gas grids or use as CNG fuel greatly enhances its value. Another selectivity consideration is that AD typically mineralizes about half the carbon to CO₂ (the rest to CH₄); from a carbon utilization perspective, that CO₂ might be seen as a loss (though if the biogas is captured and CO₂ emitted, it is part of the short carbon cycle and not necessarily problematic for climate). Some systems try to capture that CO₂ or even feed external H₂ to the digester to react with CO₂ to form more CH₄ (a process known as biomethanation)—effectively upgrading the gas and storing renewable H₂ in CH₄ [68,69].

Operational constraints: The performance of anaerobic digesters is sensitive to several factors: (1) Temperature: Most digesters operate either in the mesophilic range (~35 °C) or thermophilic (~55 °C). Mesophilic digestion is more stable and robust to perturbations, whereas thermophilic digestion has faster kinetics and better pathogen kill but can be less stable and requires more heating input. Psychrophilic (ambient temperature) digestion is used in some lagoon or cold-climate applications, but has much slower gas production. (2) pH: The optimal pH is around neutral (6.5–7.5). If acid production (acidogenesis) outpaces methanogenesis, pH can drop and cause digester souring (inhibiting methanogens). Thus, maintaining buffering capacity (often provided by bicarbonate from CO₂ or added alkalinity) is important. Ammonia from protein degradation can raise pH and directly inhibit methanogens if too high; a balance is needed. (3) Nutrient balance (C/N ratio): Microbes in AD need an appropriate carbon to nitrogen ratio. A C/N around 20–30:1 is often cited as ideal. Too low C/N (excess nitrogen) leads to ammonia accumulation and inhibition; too high C/N (excess carbon relative to N) can lead to slow microbial growth and eventual nitrogen limitation for microbial protein synthesis. Co-digestion strategies (mixing high-nitrogen manure with carbon-rich crop residues, for example) are employed to achieve a good balance. (4) Organic loading rate (OLR) and retention time: Overloading a digester with too much feed too fast can result in acid buildup (because the fast acid-producers lower pH before methanogens can catch up) and washout of microbes in continuous systems. Each system has a maximum OLR it can handle (often measured in kg vs. per m³ reactor volume per day). If exceeded, performance drops. A related parameter is the hydraulic retention time (HRT)—if it is too short, the slow-growing methanogens are removed before they reproduce, leading to failure. Many digesters run at HRTs of ~20–30 days to ensure stability. (5) Toxicity/Inhibitors: Besides ammonia, other potential inhibitors include high concentrations of salts, heavy metals, or antibiotics/cleaning chemicals (if digesting industrial or municipal waste). The microbial community can adapt to some extent, but upsets can occur. Ensuring the feedstock does not contain persistent toxins (or diluting them) is part of sustainable operation. (6) Mixing: Adequate mixing in a digester prevents stratification, distributes heat and substrates, and releases biogas bubbles. However, excessive mixing can break microbial flocs or granules and reduce performance in some cases (especially in UASB). Usually, moderate mixing is maintained [68,69].

4.2.3. Enzymatic Hydrolysis and Combined Systems

To efficiently ferment or biologically convert lignocellulosic biomass, enzymatic hydrolysis is a crucial enabling step. Enzymatic hydrolysis uses specific enzymes to depolymerize biomass polymers (primarily cellulose and hemicellulose) into simple sugars that can be fermented. The enzymes employed are typically produced by microorganisms (fungal enzyme cocktails are common, e.g., from Trichoderma reesei) and include a synergistic mixture of: cellulases (which attack cellulose)—for instance, endoglucanases that cut internal bonds in cellulose chains, exoglucanases (cellobiohydrolases) that chew from the ends releasing cellobiose, and β-glucosidases that convert cellobiose to glucose; hemicellulases such as xylanases and β-xylosidases to break down hemicellulose into pentoses; and often accessory enzymes like pectinases, ligninases or laccases if needed to handle other components or alleviate lignin blocking. Each enzyme has a specific substrate and condition: for example, fungal cellulases typically work best around 50 °C and pH ~4.8–5.5. Substrate specificity is important—some enzymes target only amorphous cellulose regions while others can act on crystalline cellulose; some hemicellulases cut backbone xylan, others remove side groups. A robust enzyme cocktail is tailored to the biomass at hand (softwood vs. corn stover, which have a different hemicellulose composition) [42].

Process intensification: There are several configurations for integrating enzymatic hydrolysis with fermentation in a bioprocess, each with advantages and disadvantages:

• SHF (Separate Hydrolysis and Fermentation): In this traditional approach, biomass is first pretreated, then enzymatically hydrolyzed in a dedicated reactor. Once sugars are released (over 1–3 days of enzyme action), the resulting sugar solution is fed to a separate fermenter for conversion to ethanol or other products. The advantage of SHF is that each step can be optimized independently (e.g., hydrolysis at the enzyme’s optimal temperature, which might be around 50 °C, while fermentation occurs at 30 °C for yeast). Also, one can use different vessels, allowing longer hydrolysis if needed, without tying up fermenter volume. However, a major drawback is that released glucose can inhibit cellulase enzymes (end-product inhibition), slowing the hydrolysis as sugars accumulate to significant concentrations. Additionally, separate reactors and longer overall residence time can increase costs [70].
• SSF (Simultaneous Saccharification and Fermentation): This configuration combines enzymatic hydrolysis and fermentation in a single vessel—enzymes and microbes are both present, and as enzymes hydrolyze cellulose to sugars, the fermenting organism immediately consumes the sugars. This has two big advantages: it alleviates product inhibition of the enzymes (sugars do not build up, because they are converted to, e.g., ethanol, which typically does not inhibit cellulases strongly), and it reduces equipment (one vessel instead of two) thereby potentially lowering capital cost (estimates suggest a >20% reduction in equipment cost for SSF vs. SHF). Yields of ethanol in SSF are often higher or faster than in SHF due to the continuous removal of sugars. However, SSF has challenges: the conditions must be a compromise between what’s ideal for enzymes and what’s ideal for fermentative microbes [71].
• CBP (Consolidated Bioprocessing): This is an aspirational “all-in-one” process where one organism (or a consortium) both produces the enzymes needed to hydrolyze biomass and ferments the released sugars to product, in one step. In CBP, no added enzyme cocktail is needed—the microbes themselves secrete cellulases and hemicellulases. Ideal CBP microbes are often thought to be genetically engineered bacteria or fungi that combine high cellulolytic ability with high product yields. The promise of CBP is a significant reduction in cost, since dedicated enzyme production (which can account for a large portion of cellulosic biofuel cost) is eliminated or minimized. However, achieving a single organism that is excellent at both depolymerizing biomass and producing the target fuel is very challenging [72].

Despite technical advances, biochemical pathways face four persistent, system-level constraints. First, inhibitors generated during pretreatment (most notably furfural (often ≤ 3.5 g L⁻¹ in hydrolysates) and HMF, alongside phenolics) depress growth, extend lag phases, and reduce sugar uptake; even sub-gram-per-liter furfural can measurably impair pentose fermentation, necessitating milder pretreatments, detox strategies, and inhibitor-tolerant strains [73]. Second, enzyme costs remain a significant operating burden in lignocellulosic routes, driving efforts in on-site enzyme manufacture, enzyme recycling, and adoption of LPMO-containing cocktails to boost saccharification at high solids while safeguarding oxidative activity [74]. Third, scaling from pilot to commercial introduces viscosity/mass-transfer limits at high solids, end-product inhibition in SHF, and bioreactor integration trade-offs, hence the frequent preference for SSF to stabilize kinetics and reduce capital, and the continued R&D on CBP to simplify flowsheets [75].

Finally, adoption hinges on robust feedstock logistics, utility and upgrading infrastructure (e.g., for ethanol dehydration or biogas upgrading), and policy/market frameworks that reward low-carbon outputs; while unit operations are mature (e.g., PSA/membranes or water/amine scrubbing for biomethane), regional deployment still requires de-risked business models, reliable offtake, and capacity-building, particularly in resource-rich but infrastructure-constrained settings [76].

4.3. Comparative Analysis of Conversion Routes

In evaluating thermochemical vs. biochemical biomass conversion pathways, several comparative factors emerge that inform sustainable process design decisions:

Energy Efficiency: The fraction of feedstock energy converted into the desired energy product varies by route. Thermochemical processes like gasification and pyrolysis can convert a large portion of the biomass energy into combustible fuels (syngas, bio-oil) relatively quickly, but they require supplying significant process heat and often have thermal losses. For example, fast pyrolysis might achieve an energy yield of ~55–70% of the biomass energy in the liquid bio-oil, with the rest in char (some of which can be burned to provide process heat). Gasification, when coupled with efficient heat recovery and if syngas is used in a CHP system, can reach high overall energy efficiency (potentially > 70–80% of biomass energy utilized as combined electricity and heat). Biochemical processes, on the other hand, often operate close to ambient conditions (thus low process heat requirement), but not all biomass fractions are converted—e.g., fermentation leaves lignin energy unused (often burned for steam). Ethanol fermentation captures roughly 30–35% of the biomass energy in ethanol (since only the carbohydrate fraction is converted, and one-third of glucose energy is lost as fermentation heat and co-produced CO₂). However, when the lignin by-product is used for cogeneration, the total utilization can climb. Anaerobic digestion might capture about 20–50% of biomass energy in biogas, depending on degradability, but it excels with high-moisture substrates where other methods would waste energy in drying. Hydrothermal liquefaction can attain energy recoveries of ~60% in the biocrude, and if the aqueous phase is further processed (say by AD. In terms of MJ per kg biomass to useful fuel, thermochemical methods generally yield a higher immediate output, but one must subtract the energy needed to run them (for pyrolysis or HTL, energy for heating reactors and possibly for feed preparation; for gasification, energy to produce oxygen or to compress syngas if synthesizing fuels). Biochemical methods have lower energy overhead in the process but can require more time and larger reactors for the same throughput. From a sustainability perspective, integrated energy efficiency is key—often hybrid systems (fermentation + combustion of residues, gasification + Fischer-Tropsch, etc.) are evaluated for overall efficiency. One metric used is Energy Return on Investment (EROI) or net energy ratio. Cellulosic ethanol processes, for instance, have been reported to achieve net energy outputs several times the fossil energy input when lignin is used for power. Thermochemical Fischer-Tropsch fuel production has slightly lower EROI due to oxygen production and refining steps, but yields drop-in fuels. The choice can depend on whether heat/power or liquid fuel is the desired output: for electricity, biochemical (AD) with CHP can be as efficient as gasification-based CHP. For liquid fuels, fermentation (ethanol/butanol) vs. HTL/pyrolysis vs. syngas-to-liquids, each has different conversion efficiencies, but all are improving with technology [77].

Carbon and Atom Economy: This relates to how much of the biomass carbon is incorporated into final products versus lost (as CO₂ or char or other residues). Biochemical routes often have inherent carbon losses due to metabolism—e.g., ethanol fermentation converts 1/3 of sugar carbon to CO₂ (by stoichiometry). So, the carbon efficiency (carbon in product/carbon in feed) might be ~67% for that step. Anaerobic digestion converts roughly half the carbon to CO₂ (and half to CH₄), although if biogas CO₂ is vented, that carbon is “lost” to the atmosphere (but not wasted if one considers environmental cycling; however, it is not in the fuel). Thermochemical processes theoretically can convert nearly all carbon to some energetic form: gasification can convert ~75–90% of carbon to syngas (with the remainder in ash/char and CO₂ from partial oxidation). Fast pyrolysis typically converts ~50–65% of carbon to bio-oil, 20–30% to char (solid carbon), and the rest to gas. HTL might convert ~60% carbon to oil, 10–20% to gas, remainder to char/aqueous. In terms of atom economy, thermochemical processes tend to break more C–C bonds and produce more CO₂ directly in the process (especially gasification, which deliberately produces CO₂ as part of syngas). For instance, a biomass gasifier may output 15% of carbon as CO₂ in the raw syngas, which might be separated and lost. Fermentation yields concentrated CO₂ streams as a pure by-product (from yeast fermenters, nearly 1 kg CO₂ per kg ethanol is released), which can actually be captured or utilized (some ethanol plants sell CO₂ for carbonation, etc.). A sustainable design looks to maximize carbon usage: strategies include using fermentation off-gas CO₂ for algae growth or methanation, or gasification’s CO₂ can be recycled via shift reactions if hydrogen is added. Also, any process that yields solid char (pyrolysis, HTC) has to decide if that char will be considered a product (biochar for soil, which sequesters carbon—a positive from an environmental view but not an energy product) or if it will be combusted (emitting that carbon as CO₂ but recovering energy). Circular carbon economy principles favor utilizing or fixing as much carbon as possible—e.g., producing long-lived materials like bioplastics from part of the carbon while using the rest for energy. In direct fuel production terms, gasification and fermentation both leave some carbon unused (in ash or lignin), whereas pyrolysis/HTL keep more carbon in liquid/solid fuels but may need further conversion. So the “atom economy” of each route must be considered in the context of the entire system [78].

Product Quality and Purification Requirements: Thermochemical and biochemical processes yield products with very different characteristics and subsequent refining needs. Syngas from gasification, for example, is versatile but requires cleaning (tar removal, particulate filtration, sulfur/nitrogen removal) and often catalytic conditioning (water–gas shift to adjust H₂/CO for synthesis, or methanation to make SNG). If the end goal is power generation, syngas can be used in a gas engine or turbine after basic cleaning, but for liquid fuels, it must go through Fischer–Tropsch or similar synthesis, and then those synthetic liquids might need upgrading (hydrocracking, fractionation) similar to petroleum refining. This is a long process train, meaning high complexity, but also a drop-in final fuel (FT diesel, gasoline, etc., are high-quality). Pyrolysis bio-oil has undesirable properties (corrosive, unstable, high oxygen content). It typically requires catalytic hydrodeoxygenation (with hydrogen) to stabilize and reduce oxygen to produce a hydrocarbon oil that can be blended into refinery streams. That upgrading process is non-trivial and consumes hydrogen (which has to be generated, possibly from a portion of biomass via gasification or biogas reforming). HTL biocrude, by contrast, though still needing upgrading, is closer to crude oil quality—it has lower oxygen (~10–20%) and higher energy density, so hydroprocessing it to drop-in fuel is somewhat milder, and many studies show it can be co-processed in petroleum refineries after initial hydrotreating. On the biochemical side, ethanol is produced in aqueous solution and needs distillation and dehydration—an energy-intensive but well-established process (consuming roughly 12–15 MJ per kg of ethanol for distillation from ~10% beer to 99.5% fuel grade). Ethanol is already a high-quality fuel (for spark ignition engines) when pure, but it cannot directly substitute for diesel or jet fuel without chemical conversion (though it can be an intermediate to other fuels like ethylene or hydrocarbons via catalytic processes). Biogas quality depends on usage: raw biogas (~60% CH₄, 40% CO₂, traces H₂S) can be used for heat or electricity with minimal treatment (just H₂S scrubbing and moisture removal). To use in vehicles or pipelines, biogas must be upgraded to biomethane (removing most CO₂) and meet stringent standards for H₂S (<4 ppm often), siloxanes (if from waste), etc. Fortunately, biogas upgrading technology is mature (water wash, PSA, membranes, etc.), and the fact that CO₂ is already separated in this case means that carbon is removed (lowering yield but improving quality). Product purity is also an issue for chemicals: fermentation products like lactic or succinic acid often need multi-step crystallization or extraction to obtain a pure acid suitable for polymerization, which can be expensive. In contrast, petrochemical processes often produce more readily separable products. Thus, when comparing routes, one must consider the effort to go from crude product to usable fuel/chemical. Thermochemical routes can produce drop-in fuels but typically after substantial upgrading; biochemical routes produce functional fuels (ethanol, biogas) directly, but in diluted forms that require energy to isolate. In sustainable design, integrating heat for separations (using waste heat for distillation, etc.) and improving product selectivity (to reduce side streams to purify) are important [78].

Feedstock Flexibility: Thermochemical processes are generally more agnostic to feedstock composition. A gasifier or pyrolyzer can accept wood chips, straw, nutshells, even mixtures of biomass, albeit with adjustments (e.g., feed handling systems and bed materials might differ). They can also handle the lignin fraction of biomass, which fermentations cannot consume. Biochemical processes, however, often require specific components—e.g., fermentations need sugar or starch or other easily metabolized substrates, so highly lignified or cellulose-rich feedstocks need preprocessing. Additionally, microbial cultures might be sensitive to certain toxins (such as heavy metals or excessive phenolics), limiting the use of very heterogeneous municipal waste unless sorted/treated. Anaerobic digesters are flexible for organic wastes but cannot break down lignin either, and performance can vary widely with feed C/N ratio and digestibility. Scalability ties into this: if a process requires a uniform feed (like a particular crop residue), securing that at a large scale might be challenging. Gasification and pyrolysis have been tested on dozens of biomass types—from wheat straw to pine chips to sewage sludge—showing good adaptability. Ethanol fermentation technology, while originally developed for sugar/starch, has now been extended to many lignocellulosic feedstocks via pretreatment/hydrolysis (corn stover, bagasse, wood, etc.), but each feedstock may need tailored pretreatment conditions. HTL is extremely flexible with moisture and feed—it can even handle mixed wastes like a blend of manure and food waste, converting both to oil/char. However, inorganic content (like high ash or salts in feed) can pose problems in all processes: in gasifiers, causing slag or aerosol issues, in fermenters, potentially inhibiting microbes or requiring nutrient adjustment. Another aspect is decentralization: smaller-scale plants make sense for biochemical processes that can be built modularly (e.g., farm-scale biogas digesters or small ethanol plants for local crop residues). Thermochemical processes, like big FT synthesis, often need a large scale for economy (to justify an oxygen plant, etc.), meaning a large feedstock supply radius. But new approaches like small-scale modular pyrolysis units (that make bio-oil on-site, which is then transported) are being explored to improve feedstock logistics. The best route also depends on local factors: for instance, in a region with lots of wet manure, AD is the obvious choice; in a region with excess forestry slash, fast pyrolysis or gasification to power might be more attractive [77].

Environmental and Economic Considerations: Each route has a distinct environmental profile. Thermochemical processes operate at high temperatures and thus have concerns like air emissions (particulate, NOx if air is used, some tar/oil emissions if not contained). However, they can also achieve complete sterilization (important if the feedstock contains pathogens) and can potentially destroy contaminants. Biochemical processes are low-temperature and produce very low air emissions on-site (mostly CO₂ from fermentation, which is biogenic). They do produce liquid effluents—e.g., stillage from ethanol or liquid digestate—which must be managed (often used as fertilizer or animal feed in the case of stillage). The digestate from AD, if not managed, could cause nutrient runoff, but when used correctly, it recycles nutrients and reduces the need for synthetic fertilizer. Economically, thermochemical plants (like gasification with fuel synthesis) involve high capital costs and a lot of precision engineering (pressure vessels, etc.), whereas biochemical plants (like digesters or fermenters) can be simpler and potentially cheaper at smaller scales, but may incur high operational costs for enzymes, yeast, and purification. The co-products and how they are valued can swing the economics: pyrolysis yields biochar that, if used as a soil amendment with carbon credits, adds economic value; fermentation of sugars yields not just ethanol but also CO₂, which can be sold for beverages or dry ice in some cases. Lignin from biochemical processes can be a feedstock for bioproducts (research into lignin-based resins, carbon fibers is ongoing), which could improve carbon utilization and process economics. From an environmental view, one must consider life-cycle emissions: a well-run biomass conversion route can greatly reduce net CO₂ emissions compared to fossil fuel (often 50–100% reduction depending on feedstock and energy inputs). But if a process uses a lot of fossil energy (e.g., for enzyme production or for hydrogen in upgrading), it may erode the benefit. Hybrid systems often score well: for example, an integrated biorefinery making ethanol (renewable fuel) and burning lignin for electricity (offsetting grid fossil electricity) can even have net negative carbon emissions in some scenarios due to soil carbon benefits from not burning ag residues in the field, etc. Another consideration is effluent and waste: gasification leaves ash that can be used or must be disposed of (it is inorganic and often can be used as fertilizer if it is clean biomass ash rich in minerals). Fermentation leaves solid residues that might need disposal if not used (though often they are burned or used as animal feed if protein-rich, like distillers’ grains). AD digestate can be applied to land, but care must be taken to avoid nutrient runoff. So each route has environmental pros and cons—a comparative assessment might say: thermochemical is generally land (footprint) intensive and capital intensive, but yields versatile products; biochemical is water-intensive (for pretreatment, fermentation broths) and slower, but can be done in distributed fashion and is perceived as “natural” (public acceptance might be higher for an anaerobic digester than a high-temperature gasification plant, for instance). Economically, many of these processes still struggle to compete with fossil fuels on pure cost; however, policy support (carbon credits, renewable fuel standards) and selecting the right niche (like waste management + energy production via AD, which earns tipping fees for waste processing plus energy revenue) can make them viable. The optimal sustainable design might integrate multiple pathways to use each part of the biomass in the most efficient way—often termed an integrated biorefinery approach, where for example, sugars are fermented to high-value products while lignin is gasified for power or fuels, and any waste streams are anaerobically digested to biogas. In conclusion, no single conversion route is categorically “best”—the choice must be guided by feedstock type, scale, desired outputs, and local conditions, balancing energy efficiency, carbon efficiency, product requirements, and economic viability [77,78]. A distinctive contribution of this analysis is the explicit inclusion of Technology Readiness Levels (TRLs) across biomass conversion pathways. While well-established technologies such as ethanol fermentation from sugar/starch crops, biodiesel production, and biomethane upgrading are fully commercial (TRL 9), emerging processes like advanced biomass gasification with Fischer–Tropsch synthesis or hydrothermal liquefaction remain at demonstration or early commercial stages (TRL 5–7). In many emerging economies, particularly across Africa and Latin America, the primary barriers are not just technological efficacy but scalability, dependable feedstock supply chains, financing structures, and regulatory support. Sustainable process design must, therefore, navigate these bottlenecks with modularized, de-risked deployment strategies to transition TRL-anchored innovations toward viable, locally adopted solutions.

Table 4. Comparative TRLs and deployment hurdles per technology [79].

Conversion Pathway	Approximate TRL	Key Bottlenecks for Scale-Up & Adoption	De-Risking Strategies (Africa/Latin America Context)
Anaerobic Digestion (AD)	TRL 9 (commercial)	Feedstock heterogeneity; biogas purification infrastructure	Mobile modular digesters; micro-finance; local demand
Ethanol Fermentation (including 2G)	TRL 7–9 (demo–com’l)	High-cost pretreatment/enzyme recovery; scale-dependent logistics	Local feedstock aggregation; enzyme cost-sharing cooperatives
Pyrolysis (fast pyrolysis)	TRL 5–7 (pilot/pre-com’l)	Upgrading bio-oil (H2, catalysts); optimization of product quality	Mobile pyrolysis units; centralized upgrading hubs
Gasification + Fischer–Tropsch (FT)	TRL 5–7 (demo)	Syngas cleanup; capital cost of FT synthesis; feedstock supply reliability	Public–private partnerships; small modular gasifier units
Hydrothermal Liquefaction (HTL)	TRL 5–7 (pilot/demo)	High-pressure corrosion-resistant reactors; aqueous phase handling	Modular skid systems; heat recovery; local pilot plants

highlights TRLs and deployment hurdles per technology.

4.4. Design Considerations for Sustainable Implementation

Figure 5 provides a schematic overview of the design considerations for sustainable biomass conversion. The framework captures four complementary dimensions that shape process implementation: the choice of conversion route tailored to feedstock and context, the integration of hybrid and intensified schemes, the adoption of digitalization and advanced simulation tools, and the pursuit of modularity and circularity. Together, these dimensions establish a roadmap that links technical decision-making with broader sustainability objectives.

Designing a sustainable biomass conversion process involves a holistic analysis of feedstock supply, conversion technology, product end-use, and integration into existing systems. Some key considerations include:

• Selection of Process Route Based on Feedstock, Location, and End-Use: The characteristics of the available feedstock largely determine which conversion process is suitable. High-moisture feedstocks (like manure slurries, food waste, algae) favor biochemical routes such as anaerobic digestion or hydrothermal liquefaction, which can handle wet input, whereas trying to pyrolyze or gasify these would waste energy in drying. Lignocellulosic dry feedstocks (crop residues, wood chips) can be efficiently processed via pyrolysis, gasification, or fermentation after pretreatment. If the end goal is a gaseous fuel for heating or power in a local setting, a simple anaerobic digester might be the most appropriate technology (e.g., farm-based digesters for manure, producing biogas for a CHP unit on-site). For liquid transportation fuels like biodiesel or bio-jet, one might prefer routes that yield liquid hydrocarbons: pyrolysis + upgrading, HTL + upgrading, or Fischer–Tropsch synthesis from syngas. Local infrastructure and markets also play a role: a region with an existing ethanol distribution network might integrate a cellulosic ethanol plant more easily than a new Fischer–Tropsch facility. Conversely, a forestry community might opt for a gasification plant to feed syngas into a gas-to-liquids system if they aim to produce drop-in diesel for local use. Scale is critical: some technologies only make economic sense at large scale (a large gasification+FT plant needs a big refinery-like setup and steady feed supply, which might only be viable with hundreds of thousands of tons of biomass per year), while others are scalable down to small units (modular AD units, small pyrolysis units, etc.). A sustainable design often tries to minimize biomass transport distance—hauling bulky biomass too far erodes energy and carbon gains. Thus, one may consider decentralized processing: for example, mobile or satellite pyrolyzers that convert biomass to bio-oil on-site (densifying the energy), which is then centrally upgraded, reducing transportation of raw biomass. Similarly, small community-scale digesters or ethanol fermenters can serve local needs. The decision also depends on end-use requirements: If the product is meant for local rural electrification, a straightforward biogas or direct combustion in a boiler or engine might be simplest. If targeting aviation fuel, for example, one might lean towards Fischer–Tropsch or catalytic upgrading routes that yield hydrocarbons. Sustainability metrics like GHG reduction, land use, and social acceptance will guide these choices: using an agricultural residue in a way that also returns nutrients (digestate fertilizer from AD) might be favored in an agricultural community, whereas maximizing liquid biofuel yield might be a priority in a context aiming to displace imports of fuel [80].
• Hybrid Approaches and Process Integration: Increasingly, designs combine thermochemical and biochemical steps to optimize efficiency. These hybrid systems use each method for what it is best at. For instance, a process might ferment the sugar components of biomass to ethanol (high yield, specific product) and gasify the lignin residue to syngas for electricity or further fuel synthesis. This way, nearly all fractions of the biomass are utilized (sugars to ethanol, lignin to power or additional fuel). Similarly, there are concepts of two-stage liquefaction: first do HTL on wet biomass to get biocrude, then take the aqueous phase rich in small acids and feed it to an anaerobic digester to make biogas—thus capturing energy from both liquid and aqueous streams. Another example is pyrolysis + fermentation: pyrolysis can convert biomass into bio-crude and biochar, while the pyrolysis vapors can potentially be fermented by special microbes (in emerging gas fermentation setups) to products like alcohols. Or simply, gasification or combustion of fermentation residues can supply process heat, effectively integrating the systems energetically. Process integration can also occur in the form of cascades: for example, an integrated biorefinery might produce sugar for ethanol, and take a portion of the sugar or intermediate syrup to produce higher-value chemicals (like organic acids or bioplastics) fermentatively, which improves the economics (the ethanol covers volume fuel needs, the specialty product gives a profit margin). Thermochemical steps can also help manage wastes from biochemical steps: burning or gasifying distillation residues, treating wastewater by wet oxidation, etc. The overall philosophy is to move toward a circular, zero-waste system where outputs of one step are inputs to another. Nutrient recycling is a key aspect: processes like AD inherently recycle nutrients in digestate; thermochemical ash can be returned to fields if clean. Hybrid approaches can ensure nutrients and carbon that are not in the main product are returned to soil or re-used, closing loops. For instance, a hybrid plant could produce methanol from syngas (thermochemical) and use some methanol as a feedstock for biochemical syntheses or as a hydrogen carrier. Another innovative hybrid is electro-bio systems: using renewable electricity to produce hydrogen (via electrolysis) and feeding that H₂ into a bioreactor or even into a gasifier’s syngas (to boost hydrocarbon yields or methane yields, effectively storing renewable electricity in chemical form). This can turn a 60% carbon conversion into near 100% by “hydrogenating” all CO₂ to additional CH₄ or liquids—an approach being explored to increase the carbon efficiency of biogas upgrading and FT synthesis. Each hybrid concept aims to synergize: minimize waste heat, use by-products beneficially, and often to improve the economic viability by diversification (multiple revenue streams). Of course, integration adds complexity, so designers must ensure each component is compatible and that the added complexity does not outweigh the benefits [81].
• Role of Digitalization and Simulation in Process Design: Modern sustainable process design heavily employs process simulation tools (like Aspen Plus, SuperPro, etc.) and techno-economic analysis (TEA) models to evaluate different configurations quickly and optimize parameters. Simulation allows engineers to conduct heat and mass balance for the entire plant, identify energy integration opportunities (for example, using the exothermic heat of fermentation or FT synthesis to drive the endothermic pretreatment or gasifier air preheat), and size equipment appropriately. Digitalization goes further by incorporating real-time data and control: for instance, model predictive control of a gasifier or digester to handle feedstock variability can improve stability and efficiency. In development phases, computational models of reaction kinetics (for enzymatic hydrolysis or pyrolysis) and supply chain models for feedstock logistics help tune the design. Digital twins of biorefineries are sometimes created to test how the system will respond to changes or to optimize throughput. This reduces risk and helps in scaling up technologies while maintaining sustainability goals. Furthermore, life-cycle assessment (LCA) is integrated with process models to compute environmental impacts (GHGs, water use, etc.) for various design options, guiding choices that minimize negative impacts. As Industry 4.0 principles take hold, one can envision smart bio-conversion facilities that automatically adjust operation to maximize yield from a given batch of biomass (accounting for moisture, composition), or to switch products based on demand (e.g., producing more electricity vs. fuel depending on grid needs). Simulation has already been key in demonstrating the feasibility of concepts like co-locating processes (e.g., using waste heat from a nearby industry in a biomass plant). Ultimately, digital tools accelerate innovation and ensure that designs are robust, optimized, and validated virtually before concrete is poured. This helps in de-risking and attracting investment to new sustainable technologies by providing data-backed projections of performance and cost [82].
• Design for Modularity, Decentralization, and Circular Economy Principles: A trend in sustainable design is toward modular systems—smaller units that can be replicated and distributed rather than one massive complex. This is driven by the dispersed nature of biomass resources. For example, instead of one 2000 ton/day centralized plant, a design might employ ten 200 ton/day pyrolysis units spread across a region, each producing bio-oil that is then transported to a central refinery for upgrading. Modular designs lower feedstock transport burdens and can be factory-built (improving quality and lowering cost via mass production of unit skids). Decentralized production can also stimulate rural development (local jobs, energy autonomy) and reduce the environmental impact of hauling large volumes of raw biomass (which often is 30–50% water and bulk). However, decentralization can lose economies of scale; thus, the optimal size must be found via techno-economic analysis considering feedstock density. A key is flexibility—designing units that can handle variable feedstock or produce multiple outputs (polygeneration). For instance, a gasification plant might be run in fuel production mode or power mode depending on price signals. Or a fermenter could switch between producing ethanol and butanol if genetically flexible microbes are used. Incorporating circular economy principles means ensuring that wastes are minimized and outputs that cannot be used as products are recycled. This might include: utilizing CO₂ streams (from fermentation or syngas refining), perhaps in greenhouses or algae cultivation; recycling water in the plant (water from bio-oil upgrading could be cleaned and used for fermentation media, etc.); and using the solid residues like biochar or digestate to return carbon and nutrients to soil, improving soil health and closing the nutrient loop. Also, modular biorefineries could be moved or re-purposed as needs change—e.g., a skid-mounted pyrolizer could seasonally operate near rice husk during harvest, then be transported to corn stover regions later. While this is a bit speculative, designing equipment for mobility and flexibility is an interesting concept being considered. Additionally, community involvement and acceptance are part of sustainable design—smaller, safer-looking modular units might be more readily accepted in a community than a huge industrial complex, easing implementation and aligning with local sustainability goals (like managing local waste and providing local energy). Many current projects indeed focus on integrated value chains: for example, a sugarcane ethanol plant that also has an attached anaerobic digester for vinasse (wastewater) treatment to biogas, which powers the plant—demonstrating energy integration and circular use of waste, and now even exploring using surplus CO₂ and electricity to produce algal protein, truly using all outputs. The ideal sustainable biomass conversion facility will likely borrow concepts from both thermochemical and biochemical realms, be smart and adaptive via digital technologies, be appropriately scaled to its feedstock supply, and be deeply interwoven with local material cycles to ensure minimal waste and maximal efficiency. By carefully considering feedstock traits, combining processes, and employing advanced design tools, engineers can develop biomass conversion systems that are not only technically and economically sound, but also exemplary in their environmental stewardship and resource circularity [83].

4.5. Recent Advances in Co-Digestion and Hydrogen-Assisted Biomethanation

Recent developments in anaerobic digestion enhance both methane yield and system resilience through strategic substrate combinations and hydrogen supplementation. Two key advances are highlighted below.

4.5.1. Co-Digestion Enhancements

Co-digestion of complementary substrates improves nutrient balance, stabilizes digestion, and raises methane yields. For instance, Bidiko et al. [84] optimized co-digestion of cafeteria food waste (CFW) and cow dung (CD) using response surface methodology; they achieved a biogas yield of ~197 mL and methane content of ~62.5% under a 3:1 CFW-to-CD ratio at 37.5 °C and pH 7.0.

Similarly, Kriswantoro et al. [85] demonstrated co-digestion of Napier grass with hydrolyzed food waste in a two-stage system, resulting in methane yields of ~614 mL/g vs. and 67.3% methane, outperforming mono-digestion baseline rates.

These studies underscore that co-digestion of disparate organic wastes not only augments methane yield but also accelerates conversion kinetics and stabilizes reactor operation.

4.5.2. Hydrogen-Assisted Biomethanation (In Situ Bio-Methanation)

Injecting hydrogen (H₂) into anaerobic digesters facilitates hydrogenotrophic methanogenesis, improving methane purity and energy content. Akimoto et al. [86] conducted pilot-scale in situ biomethanation during co-digestion of sewage sludge, achieving high hydrogen conversion efficiencies and operational stability.

Complementing this, González et al. [87] reviewed hydrogen-enriched digestion strategies, including bioaugmentation and electron-conductive materials, highlighting significant biogas yield improvement and process economics gains.

While sustainable design provides the structural basis for biomass conversion, process intensification offers opportunities to enhance efficiency, reduce energy demands, and simplify operations. The following section reviews emerging technologies that enable these improvements.

5. Process Intensification: Emerging Strategies and Technologies

The concept of process intensification (PI) has evolved from a set of siloed engineering solutions to a systemic approach to redesigning chemical processes for greater efficiency, sustainability, and adaptability. In the context of biomass valorization, PI addresses the intrinsic limitations of conventional biorefinery processes, such as low reaction selectivity, energy-intensive separations, and the inherently variable nature of feedstock composition. The fundamental idea of PI is to be more efficient, producing more value with fewer resources, less energy, and a smaller environmental footprint [88]. In practice, PI comprises a set of strategies: miniaturization of equipment, integration of unit operations, alternative methods of energy input, and improved transport phenomena. These interventions not only intensify core processes but often lead to new process routes and increased economic viability. As biorefineries aim to move from centralized plants to agile, distributed production systems, PI enables the development of compact, modular units capable of responding to changing demands, feedstock availability, and regulatory pressures. Figure 6 illustrates the principal strategies of PI applied to bioproducts, distinguishing between emerging and mature technologies.

A critical analysis of recent literature reveals a growing interest in applying PI strategies to biomass valorization. However, many of these efforts remain fragmented, with reviews focused on individual technologies without an integrative vision articulating how these could converge into coherent and sustainable biorefinery systems. For example, Barrientos et al. [89] have made significant contributions to the state of the art of reactive distillation, highlighting its evolution as a central technology in the intensification of processes applied to the sustainable production of biofuels and biomass-derived chemicals. Their review highlights the operational advantages of this technology, such as the reduction in the number of equipment, lower energy consumption, and improved conversion of limited-equilibrium reactions. New designs, such as coated wall catalytic columns, are also examined, and the integration of this unit with membrane separation systems or pervaporation technologies is proposed to further enhance process efficiency.

Segovia-Hernández et al. [90,91] have made significant contributions to the intensification of processes for the sustainable production of bioproducts. These works emphasize that intensification should be understood as a holistic strategy that combines advanced separation and reaction technologies with robust sustainability criteria, such as life cycle analysis, exegetic assessment, and carbon footprint reduction. Concrete applications in the production of biofuels and chemical blocks such as succinic acid, HMF, and ethyl levulinate stand out, where the integration of thermally coupled processes, multifunctional reactors, and hybrid schemes has been shown to significantly improve energy efficiency and productivity, while minimizing environmental impact. These studies also underscore the importance of simulation and modeling tools to optimize flowcharts and assess economic and environmental feasibility, thus consolidating a comprehensive framework for the intensified and sustainable design of biorefineries. Although significant advances in intensified separation technologies have been reported, in most cases, treatment is limited to the unit of operation, without addressing its integration into complete flow schemes or its ability to adapt to the inherent variability of lignocellulosic feedstocks [90,92].

Reactors are a fundamental part of process design, which is why some authors have proposed a comprehensive approach to bioprocess intensification focused on biocatalytic transformations. Boodhoo et al. [93] have made a proposal based on the synergistic interaction of three technological pillars: intensified reactors, alternative energy sources, and advanced materials for catalytic support. Technologies such as hydrodynamic cavitation, ultrasound, and pulsed electric fields not only improve mass and energy transfer but also reduce residence time and energy consumption without compromising the stability of the biocatalyst. In addition, the use of functionalized materials, such as porous supports or modified polymers, increases the efficiency and reuse of enzymes or cells, contributing to the reduction in waste and the extension of the useful cycle of the biocatalyst.

Asghar et al. [94] highlight that PI not only represents a technological tool, but also a strategic way to overcome the bottlenecks that limit the operational efficiency and sustainability of conventional biorefineries. Their review underlines that many current biomass conversion processes suffer from multiple sequential steps, high thermal energy consumption, and low integration between reaction and separation. In view of this, the authors propose that intensified technologies such as ultrasound-assisted extraction, multifunctional reactors, separation by membranes coupled to catalytic reactions, and fermentation in continuous integrated systems offer promising routes to reduce the complexity of the process, improve yields, and reduce the energy footprint. In addition, they emphasize the need to redesign process flows to operate under principles of modularity and flexibility, allowing biorefineries to be adapted to variations in biomass quality and specific product requirements. This vision converges with other recent systemic approaches by pointing out that PI must be understood as a structural part of a modern bioeconomic model, capable of articulating technological efficiency, operational resilience, and environmental sustainability.

In contrast to these partial approaches, authors such as Hartmann et al. [95] emphasize that bioprocess intensification should be understood as a holistic redesign that goes beyond unit metrics, integrating principles of resource efficiency, adaptability, and digitalization. Other studies highlight that technological advances must be accompanied by a paradigm shift that simultaneously considers energy integration, compatibility with renewable sources, flexibility in the face of variable raw materials, and the comprehensive evaluation of environmental and economic performance [91,93].

On the other hand, López-Molina et al. [96] highlight the importance of incorporating modular and decentralized architectures as strategies to address the challenges of operational flexibility and geographic dispersion of biomass. However, these proposals still lack solid discussion on their convergence with automation technologies, artificial intelligence, or hybrid energy management systems.

In a transversal way to these investigations, the work of Ramírez-Márquez et al. [97] represents a valuable contribution by reframing PI as part of a broader industrial sustainability agenda. This review articulates how intensified technologies should not be analyzed in isolation, but as nodes within coupled systems with sustainability indicators, life cycle analysis, and new exegetical and environmental performance metrics. Through concrete examples and comparative cases, a systemic vision is promoted in which PI is connected to the goals of decarbonization, resource efficiency, and circularity, thus providing a conceptual platform to overcome the traditional technocratic vision of process design.

Finally, it is crucial to understand that PI is not limited to a series of techniques designed to improve performance or reduce energy consumption. Beyond its technical dimension, IP represents a true design philosophy that allows the biorefineries of the future to be conceived as dynamic, resilient, and profoundly efficient systems. This vision transcends the isolated analysis of unit operations and promotes an integrated architecture where advanced technologies, sustainability criteria, and adaptive capabilities are intertwined synergistically. In this context, intensification becomes a strategic platform to simultaneously respond to the technical, economic, and environmental challenges posed by the conversion of biomass on an industrial scale.

This paradigm shift requires overcoming the fragmentation of technical knowledge and consolidating a systemic perspective in which not only traditional thermodynamic foundations are considered, but also operational and strategic dimensions such as raw material variability, scalability, modularization, and compatibility with renewable sources. In this framework, multi-product biorefineries emerge as central platforms for the valorization of various biomasses, where the integration of sustainability assessment tools and multi-objective optimization methodologies allows data-driven decision-making, balancing economic, environmental, and social criteria. At the same time, digitalization, modular models, and articulation with flexible supply chains open up new opportunities to design resilient systems in the face of current constraints, such as resource heterogeneity, infrastructure constraints, and energy coupling challenges. In contrast to approaches that treat intensified technologies as isolated solutions, this review proposes a cross-cutting synthesis of strategies, tools, and scales of analysis, offering a unified framework to unlock the potential of biomass as a strategic vector in the sustainable development of industrial processes.

5.1. Integrated and Hybrid Systems for Process Intensification

PI has given rise to a new generation of technologies that merge reaction and separation into integrated systems, enabling higher efficiency, lower energy consumption, and more compact plant designs, essential features for sustainable biomass valorisation. These hybrid and intensified units play a crucial role in overcoming the traditional limitations of equilibrium-constrained reactions, high water content, and complex feedstock mixtures commonly found in biorefineries.

Technologies such as reactive distillation (RD) allow the reaction and separation steps to be performed simultaneously within a column, which favors higher conversions and an improvement in product selectivity by shifting the chemical equilibrium through continuous product removal. RD has been successfully used in the production of bioproducts such as ethyl levulinate, levulinic acid, and lactic acid [45,46,98,99], reducing energy consumption by 25–50% compared to conventional designs. Recent innovations in RD include catalytic columns with coated walls and configurations with internal thermal integration significantly reduce energy consumption and the number of equipment required [100].

The combination of RD with membrane separation techniques, such as pervaporation or membrane distillation, opens up new possibilities for improving efficiency in moisture-sensitive processes, including the esterification of biomass-derived carboxylic acids. On the other hand, membrane reactors have established themselves as multifunctional units that allow the selective retention of catalysts or the removal of inhibitory products in real time. These configurations are especially useful in dehydration, transesterification, and biotransformation reactions, by controlling product accumulation and thermodynamic conditions, which in turn reduces downstream separation steps and allows for more compact modular designs [101,102].

Unit miniaturization has also played a key role in intensification. Microscale reactors, such as microreactors and millireactors, offer precise control overheat and mass transfer, enabling fast kinetics and safe handling of reactive intermediates such as furfural or HMF. These systems are often integrated with online analytical tools to facilitate real-time process control and connection to advanced automation frameworks. Despite the challenges in scalability, parallel numbering strategies and 3D printed reactors are being explored to make their industrial application feasible [103].

Advanced thermal systems also play a central role. For example, microwave-assisted reactors offer volumetric and selective heating, ideal for lignocellulosic matrices where conventional thermal conduction is inefficient. Ultrasound-assisted processes, thanks to cavitation, improve mixing, reduce particle size, and increase enzymatic accessibility, being especially effective in the pretreatment stages before hydrolysis or fermentation. In addition, emerging technologies such as cold plasma and infrared irradiation are being explored for the selective breakdown and functionalization of lignin and other recalcitrant components of biomass, which could open new recovery routes with lower energy requirements and fewer by-products [104,105].

Thermal integration remains critical in the design of efficient biorefineries. Traditional techniques such as pinch analysis and heat exchange network (HEN) design are still in force in large-scale applications, such as multi-effect evaporation in the production of cellulosic bioethanol. Intensified configurations such as thermally coupled columns (TCDs) and dividing wall columns (DWCs) offer significant reductions in operating costs, especially useful in the separation of complex mixtures such as biobutanol, acetone, or organic acids. Hybrid separation schemes, such as the combination of distillation-pervaporation, adsorption-membranes, liquid–liquid extraction, reactive extraction, or electrochemical reactors coupled to separation modules, allow for a reduction in energy consumption and are better adapted to variations in the composition of the biomass [90,91,106,107,108].

Authors such as Ramírez-Márquez et al. [97] and Segovia-Hernández et al. [90,91] propose holistic frameworks that integrate these technologies with life cycle analysis, energy, and digital control, with the aim of optimizing not only the efficiency of each unit, but the overall performance of the biorefinery. Tools such as multi-objective optimization and data-driven approaches make it possible to design intensified flowcharts that are technically and environmentally robust, aligned with the changing demands of biomass resources, bioproduct markets, and environmental policies.

5.2. Digitalization and Modularization of Intensified Systems

PI not only involves the improvement of the physical–chemical performance of unit operations, but also their structural and operational transformation through digitalization and modularization. These two strategies, when synergistically integrated, make it possible to conceive systems that are highly adaptable, efficient, and capable of responding to the inherent variability of biomass and market demands in real time.

Modularization involves the development and assembly of compact, standardized, and easily transportable process units, which represent a significant advantage for decentralized biorefineries. According to Barron et al. [109], these modular units can be strategically located close to biomass sources, which contributes to reducing the costs associated with the transport and handling of raw materials, in addition to improving economic viability in regions where biomass is dispersed or seasonally available. In addition, its scalability facilitates the gradual implementation of productive capacities and reduces the risks associated with large initial investments [94].

On the other hand, digitalization brings an advanced level of operational intelligence to modular systems by implementing technologies such as advanced process control (APC), digital twins, and machine learning algorithms. The digital twin is an accurate and dynamic virtual representation of the physical process that allows real-time simulation of different operating scenarios, facilitating predictive diagnostics, preventive maintenance, and continuous optimization of critical parameters without the need for direct intervention in the plant [110]. For example, in a reactive distillation unit, a digital twin can anticipate problems such as column fouling, automatically adjust operating variables such as reflux ratio, and manage start-up protocols under varying conditions, helping to improve efficiency, reduce downtime, and increase process resilience to disturbances.

In addition, machine learning models can be trained on historical and operational data to predict variations in product yields, detect deviations in key variables, and recommend new operating points in response to process disturbances or changes in economic conditions, such as market prices or availability of raw materials. For example, advanced techniques, such as reinforcement learning, were used by Arun et al. [111] to optimize energy demand response in grids with high penetration of renewables, can be adapted to biorefinery environments to improve energy coordination between subsystems, reducing losses and stabilizing consumption. In turn, Abdullah et al. [112] highlight how artificial intelligence approaches geared towards microalgae biorefineries allow not only to optimize biomass productivity and bioproduct conversion, but also to adapt process flows in real time to maximize energy and economic efficiency under dynamic operating conditions.

The combination of these tools allows us to move towards autonomous decision-making systems, capable not only of maintaining optimal operating conditions, but also of dynamically reconfiguring process flow diagrams, enabling a new generation of smart, resilient biorefineries oriented towards integral sustainability. This technological evolution also opens new opportunities for the implementation of multi-objective schemes, where economic, energy, environmental, and social criteria are simultaneously optimized.

5.3. AI-Driven Adaptive Intensification Platforms

Building on these synergies, this review envisages a new paradigm: AI-powered adaptive intensification platforms for biomass valorization. These systems integrate high-performance equipment, real-time sensing technologies, and advanced machine learning, particularly reinforcement learning, to create self-optimizing, self-correcting processing units. The AI layer works as an intelligent orchestrator that continuously processes incoming data streams, such as temperature gradients, pressure fluctuations, and raw material composition, and issues precise control actions through actuators in real time. In the long term, the platform learns from process feedback to refine its operational strategy, maximizing reaction efficiency, selectivity, and energy savings.

This architecture is especially advantageous for multi-feedstock biorefineries, where variability in feed properties, such as moisture, cellulose-hemicellulose-lignin ratio, or contaminant profile, poses significant challenges to maintaining steady-state conditions. In such environments, AI-based models provide robustness and agility by dynamically adjusting parameters such as residence time, heating profile, or catalyst dosing based on real-time deviations from predicted performance baselines [110,112].

Reinforcement learning techniques, in the context of energy demand response systems, can be transferred to bioprocesses to develop adaptive supervisory control that learns optimal operating policies in uncertain and changing environments. These methods offer a clear advantage over conventional control strategies by enabling continuous online learning without the need for fully predefined process models [111]. In addition, the implementation of digital twins as part of these AI platforms enhances predictive capabilities, enabling virtual experimentation, fault diagnosis, and proactive maintenance planning [110]. These twins simulate transient and steady-state behaviors across a wide range of operational scenarios, supporting better-informed decision-making with minimal experimental downtime.

The convergence of PI with AI and automation is not only a technological breakthrough but also represents a systemic transformation in the way biomass is converted into valuable products. Such platforms embody the principles of Industry 4.0, paving the way for autonomous biorefineries that are modular, scalable, and capable of operating efficiently in decentralized environments with highly variable inflows. By closing the loop between sensing, computation, and actuation, AI-powered PI systems can reduce process variability, decrease energy consumption, minimize waste, and ensure consistent product quality, all critical factors for the economic and environmental sustainability of future biorefineries [109,112].

PI must be complemented by robust sustainability assessment frameworks to ensure that gains in efficiency do not compromise environmental or social outcomes. The next section introduces tools and methodologies for multi-criteria evaluation and optimization.

6. Sustainability Assessment and Process Optimization

6.1. Introduction to Sustainability in Biomass Conversion

Modern biomass conversion processes must be evaluated on more than just technical performance—they require an integrated sustainability assessment encompassing environmental, economic, and social factors. This holistic approach aligns with global sustainability frameworks such as the United Nations 2030 Agenda for Sustainable Development (with its 17 Sustainable Development Goals) [113]. Figure 7 illustrates the key dimensions of sustainability in the context of biomass utilization, highlighting their role in achieving net-zero emissions and circular economy targets.

In particular, climate objectives like the Paris Agreement’s call to limit warming to 1.5 °C demand net-zero greenhouse gas emissions by mid-century. Biomass utilization is seen as a key contributor to these goals, both as a carbon-neutral energy source and as part of a circular economy that valorizes waste streams and recycles carbon. Thus, evaluating biomass conversion technologies for sustainability means examining their life-cycle environmental impacts, economic viability, and societal benefits in tandem, ensuring they support global targets such as net-zero emissions and circular resource use [114]. This section outlines the key indicators in these dimensions and how they are integrated into multi-objective decision frameworks for sustainable process design.

6.2. Key Sustainability Indicators in Biomass-Based Processes

6.2.1. Environmental Indicators

Life Cycle Assessment (LCA). Environmental performance of biomass-based processes is typically quantified through LCA, which tallies impacts from cradle to grave. LCA measures indicators like GHG emissions—often expressed as Global Warming Potential (GWP in CO₂-equivalents)—as well as contributions to acidification, eutrophication, and ecotoxicity, among others. By accounting for inputs (e.g., energy, water, raw materials) and outputs (emissions, effluents, waste) across all stages, LCA provides a comprehensive view of a process’s environmental footprint. For example, in bioenergy production, LCA can identify the stages contributing most to GHG emissions or other impacts, thereby guiding improvements. Impact Categories and Metrics. Common impact categories in LCA of biomass processes include climate change (GWP), eutrophication potential (nutrient runoff effects), acidification potential (SO_x, NO_x emissions), photochemical smog formation, human and ecosystem toxicity potentials, among others. These are quantified using standard methods in life-cycle impact assessment (LCIA). Multiple LCIA methodologies exist—for instance, CML 2001, TRACI, Eco-Indicator 99, and ReCiPe—which convert inventory data into specific impact scores. The ReCiPe method in particular has become widely used for bio-based systems due to its comprehensive coverage of over 3000 substances and ability to report both midpoint indicators (e.g., GWP, acidification) and endpoint damage categories. Such methods can also apply weighting or single-score indices (e.g., Eco-Indicator 99’s aggregated eco-score) to summarize overall environmental burden. Furthermore, LCA tracks resource depletion (e.g., fossil fuel or water use) and waste generation. High energy or non-renewable resource consumption is flagged as unsustainable, prompting consideration of process efficiency and the use of renewables. In practice, environmental sustainability of a biomass conversion route is often judged by its life cycle GHG emissions (relative to a fossil baseline) and a suite of other impact metrics to ensure a reduction in one category (say, carbon footprint) is not offset by worse performance in another (such as water pollution). LCA, though powerful, has limitations—notably, current indicators often struggle to capture dynamic temporal effects (e.g., biogenic carbon uptake timing) or regional variations (local ecosystem sensitivity), which remains an area for methodological improvement [115].

6.2.2. Economic Indicators

Sustainability also demands economic feasibility. Key economic indicators for biomass processes are obtained through TEA of the capital and operating costs versus revenues. Capital Expenditure (CAPEX) represents an upfront investment in equipment and infrastructure, while Operating Expenditure (OPEX) covers ongoing costs for feedstock, utilities, labor, maintenance, etc. Combined, these determine the process’s Total Annual Cost (TAC). Minimization of TAC—without unduly compromising environmental or social goals—is a common objective in sustainable process design. Profitability metrics include the Net Present Value (NPV) of the project, the return on investment, and the payback period. NPV is calculated by discounting future net cash flows to present value and subtracting the initial investment. For instance, a TEA for a biomass-to-fuel plant will compute NPV from the after-tax cash flows over the plant’s lifetime at a given discount rate (target internal rate of return). If NPV ≥ 0, the project is financially viable. Another metric, Internal Rate of Return (IRR), is the discount rate that yields NPV = 0, which investors compare against hurdle rates. Profit margins and product selling price needed for breakeven (e.g., minimum fuel selling price) are also reported. In evaluating bio-based processes, sensitivity analysis is typically performed on economic parameters (e.g., ±20% variation in CAPEX, feedstock cost, or plant capacity) to test the robustness of profitability. This helps identify cost drivers and economic risks. A higher CAPEX process might still be favored if it yields significantly lower environmental impacts or has better long-term feedstock security, underscoring the need to balance economics with other pillars. Market factors (such as biofuel credit policies or carbon pricing) are also considered under economic sustainability, as they affect competitiveness. Ultimately, a biomass conversion pathway must demonstrate not only reduced emissions but also reasonable cost-effectiveness and ROI to be truly sustainable. Multi-criteria approaches (see Section 6.3) explicitly incorporate both economic and environmental objectives to find optimal trade-offs—for example, identifying a biodiesel production strategy that minimizes life-cycle GHG emissions with only a modest increase in unit cost [116,117].

6.2.3. Process Safety and Risk Indicators

Ensuring that biomass conversion processes are inherently safe and pose minimal risk is another sustainability facet, often under the social or institutional pillar (safety of workers and community). Process safety indicators quantify the potential for accidents, fires, explosions, or toxic releases. Traditional metrics include the venerable Dow Fire and Explosion Index (F&EI) and the Mond Index, which provide a relative hazard ranking based on material flammability/reactivity and process conditions. These indices condense complex hazard properties into a single score to guide engineers in identifying high-risk units that may require additional safeguards. Similarly, the Inherent Safety Index (ISI) method (originally by Heikkilä) scores process routes on inherent hazards (toxicity, operating pressure, temperature, etc.) to compare alternatives. Many derivatives have been developed—e.g., the Integrated Inherent Safety Index (I2SI) and other weighted indices—that allow early-stage safety evaluation of different process designs. For example, a recent study proposed a Comprehensive Inherent Safety Index to optimize chemical plant layouts by accounting for safety distances and inventory minimization alongside economics. Beyond indices, qualitative hazard analysis remains indispensable. Hazard and Operability (HAZOP) studies are systematically conducted, even at the conceptual design phase, to identify deviation scenarios (e.g., over-pressure, leak, unintended reactions) and their causes. Integrating HAZOP insights early can inspire inherently safer design decisions—such as eliminating a hazardous intermediate or simplifying a reaction pathway—before the plant is built. To quantify overall risk, one can use composite measures like the Risk Index (RI) (aggregating frequencies and consequences of potential accidents) or more specialized metrics like the Dow F&EI mentioned above [118]. Khan and Abbasi’s Accident Hazard Index (AHI) is an example of a composite risk index that accounts for multiple factors (toxic dispersion, fire damage, etc.) to rate the severity of potential accidents. AHI and similar tools enable rapid comparison of alternative processes or sites in terms of risk. In sustainable process optimization, safety metrics are increasingly treated as objective functions alongside cost and efficiency. A process route with superior economics may be rejected if it scores poorly on inherent safety. Conversely, a design with slightly higher cost might be preferable if it dramatically lowers explosion risk or toxic exposure. For instance, in a biomass-to-chemical process, one might evaluate alternative solvents or reaction pathways by scoring each on an inherent safety index and including that score in a multi-objective optimization. Such an approach was demonstrated in an extractive distillation case study: optimizing for both minimum Total Annual Cost and maximum inherent safety (via a hazard index) led to the selection of a safer solvent that reduced the inherent risk index by ~58% while also slightly lowering operating cost. This exemplifies risk-based optimization—ensuring the chosen process route is not only economically and environmentally sound but also fundamentally safer. Ultimately, sustainable design strives for processes that minimize the probability and impact of accidents (through smaller inventories, less hazardous reagents, milder conditions, etc.), thereby protecting workers, the public, and the environment [119].

6.2.4. Process Operability and Controllability Metrics

An often overlooked aspect of sustainability is operability—the ease with which a process can be controlled, adjusted, and kept stable under real conditions. A highly efficient biomass conversion process on paper may underperform or face safety/environmental upsets if it is difficult to control or lacks flexibility to handle feed and demand fluctuations. Thus, controllability and flexibility metrics are increasingly included in process assessment. For example, the Controllability Index and related measures derived from control theory (e.g., condition number of the system gain matrix) quantify how sensitive a process is to disturbances or setpoint changes. A low condition number indicates a well-conditioned process that responds predictably to control actions, whereas a high value signals potential control difficulty (small changes can cause large deviations). Likewise, a Flexibility Index can be defined (following Grossmann and colleagues) as the range of operating conditions (feedstock quality, throughput, etc.) over which the process can meet specifications without modification. A higher flexibility index means the process can accommodate variability (common in biomass feedstocks) and remain within environmental and performance constraints. These operability metrics are linked to sustainability: a process that frequently goes off-spec or must be shut down for troubleshooting will waste energy and materials, incur higher costs, and potentially cause safety or environmental incidents (e.g., flaring during upsets). Therefore, incorporating controllability into early design leads to more resilient and sustainable operations. Recent research has shown that there are synergies between inherent safety and controllability—processes designed with simpler flow sheets and fewer hazardous inventories tend to be easier to control. One study proposed using the condition number (controllability measure) as a surrogate for both operational flexibility and safety, demonstrating that a single indicator can capture a process’s ability to remain stable and inherently safe. In practice, engineers examine metrics like plantwide controllability, steady-state gain matrices, dynamic response times, and stability margins when comparing process alternatives. Tools such as dynamic simulations or linearized control analyses help quantify these. Additionally, operability indices like the Disturbance Cost or Expected Profit Loss due to Disturbances can merge economic and control performance. Another important concept is the Condition Number of the process steering matrix, which, if large, indicates significant interaction or ill-conditioning in control loops. For multi-product biorefineries, a Flexibility Index can be computed to ensure the design can handle seasonal feedstock variability or different product mix demands without extensive reconfiguration. Integrating control structure design into sustainability assessment means that, alongside LCA and TEA, one evaluates how easily the process can be automated and maintained at optimal conditions. A process with high inherent efficiency but poor controllability might, in reality, operate sub-optimally and negate some sustainability gains. Thus, the sustainable process is one that is not only “optimal” on paper but robust in operation. By quantifying controllability and flexibility in early design, engineers can make informed choices (e.g., adding a recycle for stability, choosing a different reactor type for easier control) that enhance long-term sustainability of the biomass conversion plant [120].

6.2.5. Social and Regional Impact Indicators

The social dimension of sustainability covers a broad range of indicators, from direct job creation to community well-being and equity. Biomass conversion projects, especially biorefineries or bioenergy plants, often tout local economic development benefits. Indeed, studies have found that bioenergy systems are among the most labor-intensive of renewable energy options, creating more employment per unit of energy produced than fossil systems or even other renewables. For example, utilizing agricultural residues in a biofuel plant can spur rural job creation not only within the facility but across the supply chain (feedstock collection, equipment maintenance, logistics). The number of jobs (measured in job-years or full-time equivalents) per PJ of energy or per million dollars invested is a common metric. A classic analysis by Domac et al. [121] showed that biomass energy projects generate significantly higher local employment than comparably sized fossil projects—making job creation a key social indicator of sustainability in bioenergy. This employment can help revitalize rural economies, increase household incomes, and improve social cohesion by providing stable jobs in areas like farming communities. Hence, regional development metrics (e.g., changes in local GDP or employment rate attributable to the project) are tracked. Another important social indicator is social acceptance or public perception of the biomass project. This can be gauged through surveys or stakeholder engagement processes—effectively a qualitative indicator, but crucial nonetheless [121]. Factors influencing acceptance include odor or traffic from the facility, concerns about feedstock (e.g., “food vs. fuel” debate for biofuels), and trust in the operating company. High social acceptance often correlates with proactive community engagement and demonstrable local benefits (like district heating or job opportunities). Social Life Cycle Assessment (S-LCA) has emerged as a methodological extension of LCA, aiming to evaluate social impacts of products and processes throughout their life cycle. S-LCA considers various stakeholder categories (workers, local community, consumers, society at large) and impact categories such as human rights, working conditions, health and safety, and cultural heritage. For instance, in an S-LCA of a biofuel supply chain, indicators might include the incidence of occupational injuries (for workers), wages relative to living wage, hours of training provided, or community impacts like displacement or infrastructure development. In a case study of a pilot biorefinery, S-LCA was combined with a Social Cost–Benefit Analysis to quantify social outcomes: experts weighted criteria and identified social benefit indicators (e.g., GHG reduction contributes to global welfare, but also local criteria like odor nuisance or traffic). The analysis found significant social benefits, such as reduced emissions (global benefit) and local job creation but also noted social “costs” like high upfront investment borne by the community or need for skilled labor migration. These insights help decision-makers balance social equity with other objectives. Other tools for social impact assessment include multi-criteria decision methods (considering social criteria alongside others) and frameworks like the Social Impact Assessment (SIA), commonly used in development projects. SIA qualitatively (and sometimes quantitatively) predicts the social consequences of a planned project—for example, how a new biomass power plant might affect property values, local services, or indigenous rights. Equity indicators are also considered: Does the project’s value creation reach marginalized groups? Are there provisions for benefit-sharing or community ownership? Such questions reflect the just transition aspect of sustainability—ensuring that the shift to bio-based processes also advances social justice. A challenge in this area is the standardization of social metrics. Unlike environmental LCA (which has relatively well-defined categories and units), social metrics can be more subjective or context dependent. Nevertheless, frameworks are converged by using UNEP/SETAC guidelines for S-LCA and creating databases of social risk factors by country/sector. For biomass projects, stakeholders increasingly demand evidence of positive socio-economic impact—governments may require estimates of jobs created or rural development indices improved. As Domac et al. [121] note, local employment and income gains are often the deciding factors for community support of bioenergy initiatives. Therefore, incorporating these social indicators into sustainability assessment ensures a more complete evaluation of biomass conversion processes, capturing the human dimension of sustainability alongside the technical metric [114].

6.3. Integration of Indicators into Multi-Criteria and Multi-Objective Frameworks

Because sustainability is inherently multi-dimensional, engineers employ multi-criteria decision-making (MCDM) and multi-objective optimization frameworks to balance trade-offs between competing indicators. In sustainable process design, it is rarely possible to minimize all impacts simultaneously—improving one aspect may worsen another. For example, a design that minimizes environmental impact might come at a higher cost or lower inherent safety. Multi-objective optimization acknowledges this by seeking Pareto-optimal solutions: a set of alternative designs where no one objective can be improved without worsening at least one other. Instead of a single “optimum,” the result is a Pareto frontier that illuminates the trade-off curve (e.g., cost vs. GHG emissions). Decision-makers can then choose a compromise solution from this set based on preferences or external priorities.

Pareto-Based Approaches. In practice, multi-objective optimization problems in this context might include minimizing environmental impacts (or a single-score eco-indicator) and minimizing cost simultaneously, or maximizing safety and maximizing efficiency, etc. Mathematical programming techniques (linear, non-linear, or mixed-integer multi-objective optimization) can generate Pareto fronts, often using methods like the ε-constraint method or weighted sum method to explore different trade-off weights. For instance, Caldeira et al. [117] optimized a biodiesel supply chain for minimum cost and minimum environmental impact, and obtained a set of solutions illustrating how a slight cost increase could dramatically cut GHG emissions. This helps policymakers visualize the cost–environment trade-off and select a strategy that best meets sustainability goals (e.g., a middle ground with 3% cost reduction and 30% emissions reduction). Similarly, in process development, a Pareto front might show trade-offs between energy efficiency and inherent safety index, allowing designers to avoid solutions that are extreme on one end (super-efficient but hazardous, or ultra-safe but very inefficient). To aid decision-making, multi-criteria decision analysis (MCDA) tools aggregate different indicators (often after obtaining a Pareto set or for discrete alternatives).

The Analytical Hierarchy Process (AHP) is one popular method where decision-makers compare the importance of criteria (environmental, economic, social, etc.) pairwise and alternatives are scored to determine an overall ranking. AHP was, for example, combined with TOPSIS in an evaluation of alternative fuels: experts weighted criteria like emissions, cost, and availability, and the hybrid AHP-TOPSIS analysis identified biofuels as the most sustainable option for maritime fuel among several alternatives [117]. In that study, the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method assigned a performance score to each fuel; biofuel scored highest (0.689) compared to hydrogen, ammonia, and LNG, indicating it achieved the best balance across criteria. Such MCDA techniques are invaluable for screening process alternatives or retrofit options using a mix of qualitative and quantitative criteria. Other MCDA methods commonly applied include PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), which provides a complete ranking of alternatives based on outranking relationships, and TOPSIS, which identifies the alternative closest to the ideal solution and farthest from a nadir solution in multi-criteria space. PROMETHEE has been used in combination with AHP for process selection problems to capitalize on AHP’s robust weighting and PROMETHEE’s clear ranking ability [12]. For instance, in selecting a biorefinery pathway for a region, PROMETHEE can rank options after criteria weights are set (perhaps via AHP or stakeholder input), highlighting which option has the most favorable trade-off profile. Decision-making under uncertainty can further be addressed with fuzzy extensions of these methods (fuzzy AHP, fuzzy TOPSIS) to account for imprecise judgments, as was performed in the maritime biofuel example [122]. Crucially, the integration of sustainability indicators into these frameworks makes the decision process transparent and traceable. Stakeholders can see how each alternative performs on each criterion and how the trade-offs were negotiated. This is particularly important when social or subjective criteria are involved—MCDA provides a structured way to include, say, “social acceptance” alongside numeric LCA results. Multi-objective evolutionary algorithms (like NSGA-II, a Non-dominated Sorting Genetic Algorithm) are also widely used to handle complex, non-linear process optimization with multiple objectives. They can efficiently approximate the Pareto frontier for large-scale problems such as biorefinery network design or supply chain optimization. For example, an NSGA-II approach was applied to a bioethanol supply chain design to simultaneously minimize total cost and GHG emissions, yielding a set of Pareto-optimal configurations under different feedstock mixes and transportation modes.

6.4. Case Studies and Applications

To illustrate the concepts, several case studies can be discussed where processes were assessed and optimized under sustainability metrics. Biocomposite Optimization: In materials engineering, biocomposites (e.g., natural fiber-reinforced polymers or mycelium-based composites) have been optimized for both performance and environmental impact. A recent study on mycelium-based construction composites used multi-objective optimization to maximize mechanical strength while minimizing ecological footprint [115].

By varying the substrate composition (agricultural waste fibers, nutrient content) and processing conditions, researchers identified an optimal blend that achieved high tensile strength with a significantly reduced environmental impact (in terms of energy use and carbon emissions). The optimization balanced a mechanical performance indicator (strength) against an LCA-based indicator (global warming impact), reflecting the trade-off between material functionality and sustainability. This approach can also apply to biocomposites like flax-fiber-reinforced plastics, where one might seek to maximize strength or stiffness per unit weight while minimizing GWP and toxicity (using, for example, ReCiPe single scores as the environmental objective). The Pareto front would show designs of varying fiber content and matrix type, from which an optimal point is chosen that modestly sacrifices peak strength to gain a large environmental improvement. Such studies demonstrate the feasibility of eco-design for biomaterials, yielding products that meet technical requirements with lower life-cycle burdens [123].

Biofuels—GHG vs. Profitability: Biofuel production processes have been a focal point of sustainability assessment, often revealing clear trade-offs between GHG emissions and economic profitability. As a case in point, consider a biodiesel production system using different feedstocks (e.g., virgin vegetable oil vs. waste cooking oil). A multi-objective analysis by Caldeira et al. optimized the feedstock blend to minimize both the total production cost and the life-cycle environmental impacts. The model allowed waste oil incorporation, which cuts GHG emissions (because waste-derived biodiesel has a lower carbon footprint) but can increase processing costs (due to pre-treatment needs). The Pareto-optimal solutions showed that by accepting a slightly higher unit cost, the producer could dramatically reduce GHG emissions (up to 30% reduction). In other words, there is a quantifiable cost-to-emission curve. Decision-makers could then choose an operating point—for example, a blend with 50% waste oil that yields a 20% emission cut at only 5% higher cost than the absolute minimum cost scenario. This kind of techno-ecological trade-off analysis is increasingly used in biofuel refinery design and policy. Similarly, bioethanol production from various biomass feedstocks (corn, sugarcane, and cellulosic biomass) has been evaluated on a yield vs. sustainability basis. Some designs maximize ethanol yield and revenue but involve energy-intensive steps that raise emissions, whereas others use more renewable energy or efficient integration at the expense of throughput. Multi-criteria ranking using, say, TOPSIS has been applied to pick the best configuration considering GHG emissions, energy return on investment, and production cost together [124]. Often the result is a balanced solution—e.g., an integrated biorefinery with combined heat and power that slightly lowers ethanol output but uses far less fossil energy, yielding better overall sustainability.

Biochemicals—Risk-Based Route Optimization: When producing bio-based chemicals (e.g., bioplastics, solvents, pharmaceuticals), process safety can be a decisive factor in route selection. A noteworthy example comes from the design of an extractive distillation process for a biomass-derived chemical, where a hazardous conventional solvent (like dimethyl sulfoxide, DMSO) was traditionally used. Researchers applied an inherently safer design framework: using computer-aided molecular design (CAMD) to find alternative entrainer solvents, then performing a multi-objective genetic algorithm optimization with two objectives—minimize total annual cost and minimize inherent safety risk (using a Global Inherent Safety Index) [125]. The Pareto analysis revealed how each candidate solvent and process setup traded off safety and economics. Notably, 1,3-propanediol emerged as an alternative entrainer that achieved both a lower TAC (by ~3.7%) and a dramatically lower GISI (58% lower hazard index) compared to DMSO. Although 1,3-propanediol required slightly different operating conditions, its higher flash point and thermal stability made the process much safer. This risk-based optimization led to a solution that improves safety without any economic penalty—an ideal sustainable outcome. More generally, in biochemical production, one can integrate reaction route selection with safety and environmental objectives. For instance, multiple pathways to synthesize a bio-based polymer might be considered; some may involve toxic intermediates or extreme pressures. By scoring each pathway on an inherent safety index and an LCA metric (alongside yield/cost), a multi-objective optimization or MCDA can rank the pathways. Such analyses have been performed for selecting pathways to bio-acrylonitrile and other platform chemicals, often finding that the route with the absolute highest yield may not be preferred once safety and emissions are accounted for. Stochastic optimization algorithms (like hybrid simulated annealing-genetic algorithms) have also been used in these problems to handle the complex search space of reaction networks [125].

Optimization Frameworks: The above cases employ different optimization frameworks—deterministic mathematical programming in the biodiesel example, stochastic evolutionary algorithms in the distillation solvent example, and hybrid methods (e.g., CAMD plus optimization plus experimental validation) in the bio composite example [123]. Deterministic approaches (e.g., linear programming, MILP) are useful when the problem can be well-formulated with continuous decision variables and the objectives/constraints are relatively smooth. Stochastic or metaheuristic approaches (genetic algorithms, particle swarm, etc.) excel when the design space is discontinuous, highly non-linear, or combinatorial—such as selecting among discrete process alternatives or molecular structures. Often, a hybrid strategy is adopted: for instance, using an evolutionary algorithm to generate Pareto-optimal process designs, then applying an MCDA method to choose a single design from the Pareto set using higher-level criteria or stakeholder preferences [123]. In all cases, these frameworks underscore how sustainability optimization differs from classical process optimization—instead of a single cost or yield objective, the goal is a set of objectives reflecting the triple (or quadruple) bottom line, and the solution is a set of compromise options rather than one “extreme” optimum.

To synthesize the diversity of applications and methodological approaches discussed,

Table 5. Summary of Sustainability-Oriented Optimization Case Studies.

Case Study Area	Optimization Focus	Indicators Used	Optimization Type	Key Outcomes and Trade-Offs
Biocomposites	Mechanical performance vs. environmental impact	Tensile strength, LCA (GWP), ReCiPe scores	Hybrid (CAMD + Genetic Algorithm + Experimental Validation)	Optimal fiber blend achieved high strength with reduced carbon footprint; eco-design enabled material functionality with lower life-cycle burden.
Biodiesel Production	Cost vs. GHG emissions	Production cost, GHG emissions (LCA), Pareto front	Deterministic (Mathematical Programming)	Waste oil reduced emissions by up to 30% with only 5% cost increase; trade-off curve supports informed decision-making.
Bioethanol Systems	Yield vs. sustainability	Ethanol output, energy return, GHG, TOPSIS ranking	Multi-Criteria Decision Analysis (TOPSIS)	Integrated biorefinery with CHP slightly reduced yield but improved overall sustainability via lower fossil energy use.
Biochemical Routes	Safety vs. economic performance	Total Annual Cost (TAC), Global Inherent Safety Index (GISI)	Stochastic (Genetic Algorithm)	1,3-propanediol replaced DMSO with 58% lower hazard and 3.7% lower cost; safer process achieved without economic penalty.
Reaction Pathways	Yield vs. safety and emissions	Yield, LCA, GISI, MCDA ranking	Hybrid (Stochastic + MCDA)	Highest-yield routes not always optimal; safer, cleaner pathways preferred after multi-criteria evaluation.
Optimization Frameworks	Methodological comparison	Deterministic (MILP), Stochastic (GA, PSO), Hybrid	Comparative Analysis	Hybrid strategies combine algorithmic design with MCDA to select compromise solutions aligned with sustainability goals.

provides a structured overview of representative case studies in sustainability-oriented process optimization. It highlights the optimization focus, performance, and sustainability indicators, the type of algorithmic framework employed, and the resulting trade-offs. This comparative summary reinforces the relevance of multi-objective strategies in advancing resilient, safe, and environmentally responsible bioprocesses.

Insights from sustainability assessments inform the development of integrated biorefinery architectures. Building upon the earlier discussion of process optimization and multi-objective strategies, the following section explores multi-product configurations and supply chain approaches that enhance biomass valorization and reinforce system resilience.

7. Multi-Product Biorefineries and Supply Chain Integration

The transition from mono-product biomass conversion facilities to multi-product biorefineries constitutes a central strategy for improving the economic and environmental performance of bio-based industries. Multi-product biorefineries are designed to valorize all major fractions of biomass (cellulose, hemicellulose, lignin, proteins, and lipids) into a diverse set of marketable outputs, including biofuels, platform chemicals, biomaterials, and energy. This diversification enhances value generation and resource efficiency, but also introduces complexity in terms of process design, supply chain integration, and environmental management. A comprehensive understanding of these dimensions is necessary for the rational development and deployment of multi-product biorefinery systems.

The conceptual basis for multi-product biorefineries has been systematized by Kamm and Kamm [126], who identified four dominant configurations: lignocellulosic biorefineries, green biorefineries, whole corn biorefineries, and two-platform systems. These typologies reflect the integration of biotechnological and chemical conversion steps, with a focus on transforming carbohydrates, lignin, oils, and proteins into intermediate and final products. Amidon et al. [127] demonstrated the commercial potential of this approach through the ABS Process™, which applies hot water extraction to woody biomass, generating fermentable sugars, acetic acid, furfural, and lignin derivatives without the use of mineral acids. This process emphasizes the importance of separating biomass into more homogeneous fractions to reduce energy requirements and improve downstream processability.

From a design perspective, Giuliano et al. [128] applied superstructure-based process synthesis to model a lignocellulosic biorefinery producing levulinic acid, succinic acid, and ethanol. Their optimization framework considered biomass seasonal variability and composition, revealing that variations in cellulose, hemicellulose, and lignin content significantly affect biomass allocation among product pathways and alter the optimal flowsheet. The incorporation of multiple biomass types throughout the year maintained a constant feed rate but induced shifts in product yield distribution, thereby underscoring the need for adaptive system design under dynamic input conditions.

Ulonska et al. [129] proposed an extension of Process Network Flux Analysis (PNFA) that integrates process optimization, biomass supply chain modeling, and market-based price fluctuations. Their analysis focused on ethanol and iso-butanol co-production, demonstrating that a maximum ethanol-to-isobutanol mass ratio of 1.9 is required to achieve economic breakeven. Their methodology enables early-stage performance ranking of processing routes under conditions of uncertainty, which is particularly useful for pre-commercial development stages.

Katakojwala and Mohan [49] developed an integrated biorefinery based on sugarcane bagasse, producing nanocrystalline cellulose (NCC), lignin, and biohydrogen. The system achieved NCC yields of 0.15 ± 0.02 g/g SCB and hydrogen yields of 0.15 L/g Chemical Oxygen Demand Removed (CODR). LCA demonstrated that the integrated process reduced global warming potential by approximately 24% compared to a standalone NCC system. This illustrates the environmental advantage of multi-product valorization, particularly when combined with zero liquid discharge (ZLD) strategies and circular chemistry principles.

The challenge of environmental burden allocation in systems with multiple outputs has been addressed by Cai et al. [130], who compared co-product handling methods in integrated biorefineries co-producing renewable diesel, succinic acid, and adipic acid. Their findings showed that displacement methods more accurately capture the emissions implications of diverse co-products, while mass- or energy-based allocations may introduce distortions. Similarly, Obydenkova et al. [31,131] used a matrix-based life cycle inventory (LCI) model to track environmental burdens across ethanol, crude lignin oil, and electricity value chains. They identified biomass pretreatment, lignin solvolysis, and lignin drying as critical environmental hotspots. Wastewater treatment infrastructure accounted for 58% of pretreatment-related costs and 75% of associated GHG emissions, whereas lignin drying depended heavily on CHP systems, which contributed 56% of emissions. These results point to the need for process-level innovations targeting these specific steps.

The integration of microalgae into multi-product biorefineries has also received attention. Wu and Chang [34] presented a systems engineering-based review of integrated algal biorefineries (IABRs), emphasizing the role of process simulation and multi-objective optimization. Slegers et al. [132] conducted techno-economic analysis of several microalgal value chains, demonstrating that multiproduct configurations could increase biomass conversion from 7–28% to over 97%. Although cascading extraction steps increased total production costs, the additional revenue from diversified products offset the investment. Kingsley et al. [133] validated several Spirulina-based biorefinery scenarios through pilot-scale demonstrations and Aspen Plus simulations. The integration of dried Spirulina food products with phycocyanin and biostimulants, along with biogas-based heat systems, improved economic feasibility, with product yields approaching 8.6 g/m²·day and phycocyanin recovery at 6%, compared to a theoretical maximum of 11%.

On the supply chain side, Dansereau et al. [134] and Sharma et al. [135] emphasized the importance of aligning product portfolios with logistics and market characteristics. The former proposed a supply chain screening methodology based on product type, biomass sourcing, and process responsiveness, while the latter developed a stakeholder-inclusive strategic optimization model incorporating input mix, technology selection, capital structure, and risk sharing. Rajabian et al. [136] expanded this to a multi-echelon model that considered five biomass types and four production stages, optimizing both cost and environmental performance through a bi-objective mixed-integer linear programming (MILP) approach.

The integration of process design with energy and environmental considerations is also reflected in the work of Kosamia et al. [137], who evaluated three biorefinery configurations for biosuccinic acid production from corn stover. Scenario 1 (biosuccinic acid and electricity) yielded the most favorable results, with a minimum selling price (MSP) of 2.28 USD/kg and an 8-year payback period. Scenario 2, which included furfural co-production, allowed greater heat recovery but incurred higher operating costs and a longer payback period (9 years, MSP = 3.33 USD/kg). Scenario 3 integrated biogas production, offering lower capital investment but reduced BioSA yields (MSP = 3.19 USD/kg). These findings highlight the trade-offs between product mix, energy integration, and economic returns.

Sánchez et al. [138] addressed the need for multi-scale analysis, linking reactor-level process modeling to macro-scale supply chain logistics. They identified biomass availability and distribution as major variables in supply chain design and emphasized the role of water and energy integration, crop selection, and geographic constraints. Ferrero et al. [139] combined MILP optimization with Data Envelopment Analysis (DEA) to balance economic, environmental, and social criteria, demonstrating the feasibility of biorefineries using sugarcane and lemon feedstocks in Argentina.

Finally, the long-term vision of a carbohydrate-based economy was articulated by Zhang [140], who calculated that effective lignocellulose fractionation and the sale of high-value co-products could improve profit margins up to 6.2-fold compared to ethanol-only systems. John et al. [141] further supported this perspective by integrating AI-based optimization, microbial engineering, and modular system design into a framework for next-generation biorefineries. They emphasized the alignment of such systems with energy security, circular economy principles, and climate goals.

Multi-product biorefineries represent a technologically and economically viable approach for maximizing the utility of biomass resources. Success depends on the integration of process synthesis, supply chain optimization, environmental assessment, and market-responsive design. Recent advances demonstrate that scalable and adaptable multi-product systems can play a transformative role in achieving sustainable industrial development.

To visually synthesize the systemic complexity and value potential of multi-product biorefineries, Figure 8 presents a conceptual framework linking biomass and energy inputs to high-value-added products through intermediate bioblocks and multi-objective optimization strategies. It highlights the role of conversion routes, supply chain dynamics, and performance indicators in guiding sustainable design and deployment.

Despite the advantages of integrated biorefineries, several limitations persist in real-world applications. The next section critically analyzes current barriers and emerging opportunities, with emphasis on technological, economic, and institutional factors.

8. Present Limitations and Emerging Opportunities

Due to the global energy transition, which seeks to integrate principles of sustainability, circular economy, and decarbonization, biorefineries emerge as a strategic alternative to progressively replace the model based on fossil sources of energy production, fuels, and chemical products [10]. These facilities, designed to transform various types of biomass into a wide range of value-added products, are emerging as key elements in the construction of circular economies based on renewable resources. One of the most promising areas of opportunity in the development of sustainable biorefineries lies in the synergistic integration of thermochemical, biological, and physicochemical processes within advanced hybrid configurations. This approach offers a high potential to maximize the use of the renewable carbon contained in biomass and minimize waste generation. The comprehensive valorization of cellulosic, lignin, and hemicellulose fractions, through coordinated conversion routes, would allow the establishment of functional synergies between platforms oriented to both energy and non-energy products. This integration, if implemented effectively, could not only improve the overall efficiency of the system, but also increase its environmental sustainability, economic viability, and social acceptance. Likewise, the diversification of products and technological routes represents a strategic way to strengthen resilience to market fluctuations and expand the range of viable industrial applications, thus consolidating new value chains based on bioeconomy [10]. However, despite these conceptual and technological advances, the large-scale implementation of biorefineries continues to face numerous structural challenges that limit their expansion and industrial consolidation [142].

Unlike crude oil, which can be processed using mature and well-defined technologies in conventional refineries, biomass presents substantial variations in its chemical composition, moisture, energy density, physical structure and impurity content, both between different types (e.g., agricultural residues, forestry, energy crops, algae, urban organic waste) and within the same type depending on the geographical origin. seasonality or agricultural practices applied [143]. This variability represents a considerable challenge for the design of efficient and stable processes, as conversion paths require specific operating conditions that are not always compatible with the variable characteristics of the biomass. For example, a high proportion of ash or moisture can negatively affect the efficiency of gasification or pyrolysis, while unbalanced lignocellulosic compositions can reduce fermentation yield or enzymatic hydrolysis efficiency [144]. As a result, many biorefineries face problems of operational instability, increased pretreatment costs, and difficulties in scaling laboratory technologies to real-world environments, where biomass supply cannot be as carefully controlled as in experimental environments. In addition, heterogeneity also negatively impacts the logistical and economic aspects of the system. The need to sort, pre-process, dry, crush, or even mix different types of biomasses before conversion implies the use of additional energy, higher infrastructure requirements, and higher operating costs [40,41]. This reality contrasts with the oil model, where the standardization of inputs has allowed the development of economies of scale, vertical integration, and highly optimized global supply chains. In the case of biomass, on the other hand, systems must be designed with operational flexibility, which increases the complexity of the plant design, the need for real-time monitoring, and the application of adaptive technologies (such as advanced sensors, automatic control, multivariate modeling, or artificial intelligence). Despite these challenges, the heterogeneity of biomass can also be seen as a strategic resource if properly managed, as it allows the generation of differentiated product portfolios adapted to local markets, promoting productive decentralization, rural economic diversification, and the resilience of the system in the face of supply interruptions [145]. To overcome this obstacle, it is necessary to see it from a comprehensive perspective, combining advances in biomass characterization (through spectroscopy, chromatography or thermogravimetric analysis), development of robust and adaptive technologies, implementation of smart logistics platforms, and the design of flexible contractual schemes that integrate biomass producers from early stages. In addition, the integration of digital technologies such as blockchain for traceability and IoT for real-time monitoring can allow for more accurate and efficient management of variability, moving towards a smart and flexible biorefinery model.

Another challenge is associated with the logistical limitations of transporting, handling, and storing biomass. Unlike fossil fuels, which can be efficiently moved by pipelines or ships, biomass is bulky, low-energy dense, and susceptible to degradation. These characteristics significantly increase the costs of land transport, and limit the economic supply radius of the plants, making it difficult for them to be viable in regions with low resource density [9]. In response to this situation, some approaches have proposed logistics centralization through intermediate conditioning sites, while others suggest productive decentralization through modular plants located close to biomass sources [96]. This second option, although it requires changes in the industrial paradigm, can offer important advantages in terms of emission reductions, rural development, and territorial equity.

Process design and intensification are key strategies to optimize the production of bioproducts in biorefineries, by improving efficiency, reducing operating costs, and accelerating technological development towards more sustainable schemes. In this context, multiple intensified technologies have demonstrated their potential to maximize the use of lignocellulosic raw materials, allowing a more efficient conversion and integrated purification of value-added products. Among the most outstanding technologies are reactive distillation, which allows reaction and separation to be combined in a single unit, improving overall performance and reducing energy consumption, as well as membrane reactors, which integrate reaction and selective separation, favoring the displacement of equilibrium and the efficient use of catalysts. Likewise, thermally coupled systems and hybrid processes such as extractive distillation have been developed. These technologies have been successfully applied in the production of bio-based building blocks such as succinic acid, levulinic acid, HMF, and ethyl fatty acid esters (FAEE), as well as in advanced biofuels such as bioethanol or biodiesel [90,91]. The integration of these intensified schemes has not only proven to be technically feasible, but also more favorable in terms of sustainability analysis and LCA, thanks to the reduction in the number of equipment, lower energy requirements, and a decrease in the generation of waste and by-products. In addition, these strategies allow processes to be modulated to adapt to the heterogeneity of the biomass and the decentralized size of the plants, making their implementation feasible in rural contexts or regions with limited resources. In this way, the PI not only represents a technical improvement, but also a way to promote circular, resilient production models that are adaptable to different socio-economic contexts. In addition, intensification facilitates the implementation of modular and flexible units, suitable for operating on a smaller scale in decentralized contexts. This flexibility is essential when working with variable raw materials and in environments where industrial infrastructure is limited. It also allows for dynamic adaptation to market developments, as intensified systems can be more easily modified to change products or conversion paths. Ultimately, the intensified approach contributes to reducing both the capital required and operating costs, improving the overall profitability of the system.

Despite technological advances in biomass conversion, one of the least consolidated aspects in the implementation of biorefineries is the effective integration of sustainability criteria from the early stages of process design. In many cases, decisions on technological configuration, raw material selection, and scaling are made based on purely technical or economic criteria, leaving environmental or social considerations in the background. This vision represents a critical limitation, as it can lead to solutions that, although technically feasible, are not sustainable in the long term or competitive with other energy alternatives [146]. Likewise, the poor integration of renewable energy sources in the operation of biorefineries implies a partial dependence on fossil inputs that reduces their added environmental value and compromises their legitimacy as truly green solutions [147]. However, this current limitation also opens a strategic opportunity for the future. The systematic incorporation of tools such as LCA, multi-objective assessments or eco-efficiency analysis can guide the design towards optimal configurations that maximize environmental, social, and economic benefits simultaneously. Similarly, the integration of renewable energies, such as solar thermal, cogeneration with residual biomass, or the integration of energy storage systems, allows reducing emissions, increasing the operational autonomy of plants, and generating synergies with other local value chains. This not only increases the resilience of the production system, but also enables more equitable territorial models, where sustainability is an inherent attribute from design to operation. In this sense, sustainability ceases to be an external constraint to become a structural criterion of innovation and future competitiveness for biorefineries in the 21st century.

On the other hand, the financial viability of many biorefineries is compromised by the lack of consolidated business models. Most projects require high capital investments, while financial returns are conditioned by external factors such as the price of crude oil, volatility in agricultural markets, and reliance on public incentives [148,149]. This combination of uncertainty and perceived risk hinders access to finance and discourages private sector participation. Added to this is the fact that many of the products obtained as bioplastics, chemical additives or advanced biofuels do not yet have mature markets that guarantee sustained demand [150]. In this context, consolidating control over different stages of the value chain from the procurement of raw materials to the commercialization of the final product, together with the establishment of strategic alliances and collaboration with other industries, becomes a key strategy to reduce risk exposure and diversify sources of income [151].

Despite their renewable nature, many biorefineries today still rely, in part, on fossil inputs and energy sources. This aspect has come under increasing scrutiny, as it compromises the environmental sustainability of processes. For example, operations such as gasification, fermentation, or thermal drying require energy inputs that often come from natural gas or electricity from the grid, which may be predominantly fossil in origin. Overcoming this dependence involves effectively integrating renewable energy sources such as solar thermal, photovoltaic, wind, or residual biomass into the design and operation of plants. In this way, not only would the carbon footprint of the system be reduced, but progress would be made towards greater energy autonomy and operational resilience [10].

In this sense, the decentralized biorefinery model, based on small or modular plants strategically distributed in rural or peri-urban areas, is particularly relevant. This approach reduces logistics costs, leverages local resources, and creates employment in communities where economic opportunities are often scarce [96]. At the territorial level, decentralized biorefineries can be integrated into regional bioeconomy schemes, where agricultural producers, cooperatives, local governments, and downstream companies collaborate on fairer, more inclusive, and sustainable value chains [152].

The role of digitalization and smart technologies in this new paradigm is equally central. The incorporation of advanced control systems, real-time sensors, artificial intelligence, and digital platforms makes it possible to optimize process yields, reduce losses, anticipate failures, and manage biomass variability more efficiently [153]. Technologies such as blockchain can bring transparency and traceability to supply chains, ensuring the sustainability of products throughout their entire life cycle. This digital transformation is a necessity to manage the inherent complexity of modern biorefineries.

However, none of these technology solutions can thrive without the right policy and regulatory environment [154]. The consolidation of biorefineries requires coherent, stable, and ambitious public policies that encourage both the sustainable production of biomass and its local transformation into high-value products. It is crucial to have mechanisms such as guaranteed purchase contracts, preferential tariffs, tax incentives, and carbon prices that reflect the environmental benefits of the bioeconomy. Likewise, public–private cooperation must be strengthened through territorial governance schemes, where universities, technology centers, companies, and communities work together in capacity building, project design, and impact assessment.

As described in Figure 9, together these elements make up a unique opportunity scenario for biorefineries. Overcoming current challenges requires a systemic vision that transcends the technical and embraces economic, social, and territorial dimensions. The integration of renewable energy sources, intensified process design, productive decentralization, smart digitalization, and coordinated institutional support will not only unlock the true potential of biomass, but will also contribute to shaping a fairer, more resilient, and sustainable energy and production system.

9. Conclusions

This review proposes an interdisciplinary framework to unlock the potential of biomass as a strategic resource in the transition towards sustainable and resilient industrial systems. Through a systematic analysis of conversion routes, the intensification of processes, sustainability assessment tools, and territorial integration models, a design architecture that responds to the technical–environmental challenges of the 21st century is proposed. Biomass has a versatile capacity to generate high-value-added bioproducts, including 2G bioethanol (USD 0.78–0.97/L), HMF (USD > 6/kg), PLA (400,000 tonnes in 2019), and nanocellulose (USD 2000–3500/tonnes). Thermochemical (e.g., gasification with efficiencies of 70–85%) and biochemical (e.g., fermentation, anaerobic digestion) routes are evaluated using the criteria of energy efficiency, atomic economy, and scalability. Hybrid configurations allow for the more complete use of cellulosic, hemicellulosic and ligninic fractions.

Technologies such as reactive distillation, membranes, hydrodynamic cavitation, and ultrasound have been shown to reduce energy consumption by up to 50%, simplify flowcharts, and facilitate plant decentralization. The integration of thermally coupled schemes and hybrid separation systems has improved the productivity of strategic compounds such as ethyl levulinate, HMF, and lactic acid.

The incorporation of environmental (GWP, eco-indicator 99), economic (CAPEX, MSP), security (ISI, AHI), and operational (flexibility, controllability) indicators and methodologies such as LCA, AHP-TOPSIS, and NSGA-II allows for the optimization of configurations under conflicting objectives. Studies show that it is possible to reduce emissions by 30% with only a 5% increase in unit costs. This strengthens the design approach based on optimal compromises.

Multi-product architecture allows more than 97% of the biomass content to be valorized, compared to only 28% in conventional configurations. The inclusion of co-products such as nanocellulose, biohydrogen, biogas and organic acids improves economic and environmental viability, especially in scenarios with internal energy recovery.

Resource variability, a lack of consolidated business models, and fossil energy dependence remain critical barriers. These challenges are especially pronounced in low- and middle-income countries, where limited access to advanced technologies, infrastructure constraints, and institutional fragmentation hinder the deployment of sustainable biomass-based solutions. To address these disparities, future research should prioritize modular and low-cost process designs tailored to decentralized and rural contexts, the development of open-source digital tools and AI-driven platforms for process simulation, control, and optimization, and capacity-building initiatives that support technology transfer and local innovation. Additionally, policy frameworks that incentivize circular bioeconomy models and inclusive infrastructure deployment are essential to ensure equitable access and long-term viability.

The convergence of technological intensification, multi-objective optimization, intelligent digitalization (digital twins, adaptive AI, and blockchain) and the territorialization of production systems offers a robust platform to accelerate the consolidation of the bioeconomy. This systemic approach reconceptualizes the role of process engineering as a catalyst for resilient, scalable, and climate-responsible solutions, grounded in equity and global applicability.