In the field of biochemical process design, the accurate modeling of microbial growth is essential for the development and optimization of biological reactors used in the production of high-value compounds. Achieving this objective requires a detailed understanding of how environmental factors-such as pH and nutrient availability-influence microbial dynamics across the four distinct growth phases: lag, exponential, stationary, and death. Traditionally, reactor design relies heavily on the Monod model, which provides a simplified representation of microbial growth, focusing primarily on the exponential phase under constant operating conditions (1). However, this model presents substantial limitations when applied to dynamic environments where key parameters vary over time. To overcome these constraints, the present study proposes a data-driven modeling approach using a multilayer perceptron (MLP) artificial neural network for the prediction of microbial growth trajectories under varying... [more]

The energy recovery of agro-industrial residual biomass offers a pathway to reduce fossil fuel emissions in thermal processes while valorizing waste. In practice, however, the primary bottleneck is logistical: feedstocks are geographically dispersed, with low bulk density and high moisture content, driving up collection, pretreatment, and transport costs. This work combines geospatial processing with mathematical optimization to design a multi-stage logistics network. The model incorporates intermediate densification options and technology selection (chipping, pelletizing, or briquetting) to supply one or more final waste-to-energy plants. The case study focuses on Northeastern Uruguay, considering forestry residues, meat-processing waste, and rice husks. We formulate a multi-period Mixed-Integer Linear Programming (MILP) model aimed at minimizing the total annualized cost, encompassing transportation, logistical operations, capital investment, and plant O&M, subject to supply constrai... [more]

Anaerobic digestion (AD) across Europe and the UK faces increasing economic and operational pressure from volatile feedstock supply under climate extremes. Existing stochastic programming (SP) approaches for feedstock planning often rely on limited historical observations and/or simplify yield uncertainty in ways that miss the joint, non-linear response of crops to weather variability, thereby understating downside supply risk. We develop an integrated decision-support framework that links climate uncertainty to AD procurement planning by coupling mechanistic crop simulation, generative surrogate modelling, and stochastic optimization. First, APSIM is used offline to generate a mechanistic yield knowledge base across weather trajectories and discrete planting-density choices. Then, a conditional GAN (CGAN) is trained to produce non-parametric joint yield samples for multi crops conditioned on scenario features and management, enabling fast Monte Carlo evaluation. At last, these samples... [more]

Understanding the relationships between operating conditions and product formation pathways in biomass pyrolysis remains challenging due to the complex interactions among temperature, catalytic effects, and feedstock composition. In this work, principal component analysis (PCA) was applied to investigate the combined influence of temperature and catalyst-to-biomass ratio on the pyrolysis of sugarcane bagasse and Salicornia. To preserve mechanistic interpretability, two complementary analyses were performed: one considering only catalytic experiments and a second integrating both thermal and catalytic conditions. Separate PCA were conducted for product yields, gas and liquid compositions, and solid-phase FTIR features. The results reveal that thermal conditions promote severe cracking and solid carbonization, whereas catalytic operation favors secondary pathways associated with controlled dehydration and partial stabilization of liquid products. Distinct patterns between the two feedsto... [more]

The climate crisis and dependence on fossil fuels make the transition to renewable energy sources imperative, with biomass standing out for promoting decarbonization and circular economy. In this context, fluidized bed gasification emerges as an efficient route for converting waste into syngas, applicable to power and hydrogen generation. Given the variability of real operating conditions, dynamic models are essential to represent coupled fluid dynamic, thermal, and kinetic phenomena over time. In this work, a dynamic phenomenological model was developed using a lumped 0D approach, in which the reactor is divided into two interacting zones represented as continuous stirred-tank reactors (CSTRs): a dense bed, where drying, devolatilization, and heterogeneous reactions occur, and a freeboard, dominated by homogeneous gas-phase reactions. The model was validated against experimental data from a bubbling fluidized bed gasifier, showing good agreement for major syngas species (CO and H2, me... [more]

The valorization of lignocellulosic biomass represents a key pathway toward sustainable chemical production, as it enables the development of circular economy products with reduced dependence on fossil resources. Among the platform molecules derived from biomass, furfural stands out as a versatile intermediate that can be transformed into several high-value chemicals, such as furfuryl alcohol, 2-methylfuran, tetrahydrofurfuryl alcohol, furan, tetrahydrofuran, and maleic anhydride. In this work, an integrated biorefinery scheme for producing the main furfural derivatives is proposed and evaluated through process simulation and sustainability metrics. The process was modeled in Aspen Plus V14, using furfural obtained from lignocellulosic biomass (corn stover) as raw material, following hydrogenation and oxidation routes. The process is multi-product, meaning that the main furfural derivatives are produced simultaneously within the same plant. This was achieved by implementing splitters t... [more]

Reliable data for the standard enthalpies and Gibbs free energies of formation, DHf° and DGf° are essential for process synthesis, energy integration, and lost-work analysis. However, many biomass-derived compounds lack reliable thermodynamic property data, limiting optimization of energy and carbon utilization in biomass conversion processes. This study proposes a composition-based method to estimate DHf° and DGf° for compounds containing carbon, hydrogen, and oxygen. The method exploits widely available heats of combustion data and establishes a linear correlation between the enthalpy and Gibbs free energy of combustion, DHC and DGC using tabulated organic compounds. The applicability of this relationship to biomass-derived compounds is tested using published data for cellulose, starch, and glucose. Thornton's correlation between heat of combustion and oxygen demand is then incorporated to derive simple expressions for estimating formation properties directly from elemental compositi... [more]

Single-cell protein (SCP) fermentation efficiently converts carbohydrates into high-protein food products but typically relies on purified glucose. Better understanding of SCP growth on mixed sugar substrates could allow for use of lower-cost, less processed sugars and waste-derived feedstocks. Glucose-fructose mixtures are particularly relevant, as these are the main sugars in sucrose hydrolysates and are also common in many food and beverage waste streams. In this study, the growth of Fusarium venenatum on glucose-fructose mixtures was investigated experimentally and modelled using a lagged dual-substrate Monod framework incorporating inhibition of fructose growth by glucose. Batch fermentations were conducted at a fixed total sugar concentration (15 g/L) with four different initial substrate compositions. Model parameters were estimated using both single-experiment and multi-experiment fitting strategies using differential evolution and wild bootstrap uncertainty analysis. A shared... [more]

Decarbonization of hydrogen-intensive industrial clusters is essential to meet the European Union's net-zero targets. Although hydrogen can replace fossil-based feedstocks and fuels in refineries and chemical industries, its production remains largely dependent on natural gas. Therefore, cost-effective and low-emission supply routes require a system-level approach that integrates regional resources, technologies, and industrial demand. This study applies a multi-objective optimization framework to design a low-carbon hydrogen supply system for Galicia (northwestern Spain), addressing two gaps in regional energy system modeling: model transferability across regions and integration of social criteria beyond techno-economic assessment. The model quantifies trade-offs between total system cost and greenhouse gas emissions, and an employment indicator is integrated via post-processing using TOPSIS. The results show that meeting 100% of the projected 2030 demand (105 kt H2/a) yields a single... [more]

This study conducted a life cycle assessment to assess and design regional symbiosis at plant-oil production. These industries face challenges including dependence on fossil fuels and the generation of underutilized by-products, while effective regional symbiosis requires the selection of diverse regional unused resources and assessment based on process models that consider future technological prospects. Mathematical models for plant-oil production were developed using industrial data from literature to calculate inventory data. The case study showed that introducing woody biomass combined heat and power reduced GHG emissions by 8% in the Cradle-to-Grave system boundary, while recycling technology for soap stock using Kolbe electrolysis achieved a 3% reduction. Regional analysis indicated that 33 prefectures in Japan could meet woody biomass demand through sustainable forestry management, potentially reducing GHG emissions in Japan by approximately 0.041%. These results suggest that r... [more]

The transition from a linear, fossil-based polymer economy to a circular bio-economy is critical for mitigating resource depletion and greenhouse gas emissions. This study provides a rigorous comparison of two biomass-to-plastic pathways: a biochemical route (PLA via enzymatic hydrolysis) and a thermochemical route (bio-PE via gasification and MTO). Based on Aspen Plus simulations and a "lifetime-adjusted" lifecycle assessment framework, we evaluate the environmental performance of these routes in the transition from linear to circular systems. Unlike standard "cut-off" methods, the lifetime-adjusted model accounts for virgin make-up and molecular retention across multiple recycling cycles. Results indicate that at current 15% recycling rates, PLA exhibits the lowest global warming potential due to significant biogenic carbon sequestration. However, as recycling rates reach 75%, process efficiency becomes the dominant factor; the precise biochemical recycling of PLA continues to outper... [more]

This document provides supplementary material supporting the Conference Paper “A Multi-Objective Optimisation and Superstructure-Based Decision-Support Tool for Regional Low-Carbon Hydrogen Roadmaps: Methodology and Application to a region of Spain”.

It includes additional methodological details, input data, model assumptions, and extended results that complement the analyses presented in the main manuscript.

Supplementary Material for Estimation of Thermodynamic Properties for Cellulosic Biomass-Derived Compounds: Application to Heat and Work Balances in Process Simulation that will be submitted to Escape36.

The climate crisis and dependence on fossil fuels make the transition to renewable energy sources imperative, with biomass standing out for promoting decarbonization and circular economy. In this context, fluidized bed gasification emerges as an efficient route for converting waste into syngas, applicable to power and hydrogen generation. Given the variability of real operating conditions, dynamic models are essential to represent coupled fluid dynamic, thermal, and kinetic phenomena over time. In this work, a dynamic phenomenological model was developed using a lumped 0D ap-proach, in which the reactor is divided into two interacting zones represented as continuous stirred-tank reactors (CSTRs): a dense bed, where drying, devolatilization, and heterogeneous re-actions occur, and a freeboard, dominated by homogeneous gas-phase reactions. The model was validated against experimental data from a bubbling fluidized bed gasifier, showing good agree-ment for major syngas species (CO and H₂,... [more]

This supplementary material provides additional process descriptions, process flowsheets and life-cycle inventories in order to reproduce the work presented in the manuscript. Further, more detailed derivations of the impact calculation model are given.

This study provides standardized models for the chemical characterization of complex streams, ensuring the necessary adaptations while considering the differences in biomass types and forms. Several datasets are compiled and examined to establish a valid representation of the mixture, according to industry accepted standards and laboratory protocols. For reliable property estimation, correlations of key biomass properties are obtained from both computational models and experimental measurements. Existing data are used to create datasets for the biomass and the biocrude streams. This model builds upon existing knowledge and data technologies with emphasis on hydrothermal liquefaction (HTL). The proposed approach shows potential as a starting point for the design and modelling of more biorefinery-associated technologies. Sludge and pine wood are used as case studies for biomass feedstocks. Two biocrude samples are employed for biocrude characterization. The performance of the developed o... [more]

Soybean is a highly valuable global commodity due to its versatility and numerous derivative products. During harvest, all non-seed materials become “straw”. Currently, this waste is primarily used for low-value purposes such as animal feed, landfilling, and incineration. To address this, the present work proposes a conceptual biorefinery aimed at converting soybean straw into higher-value products. The study began with data collection to identify potential conversion routes. Based on this information, a superstructure was developed, comprising seven conversion routes: four thermochemical routes (pyrolysis, combustion, hydrothermal gasification, and liquefaction), two biological routes (fermentation and anaerobic fermentation), and one chemical route (alkaline extraction). Each process was evaluated based on product yields, conversion times, and associated capital and operating costs. Using this data, an MILP (Mixed-Integer Linear Programming) optimization model was built in Pyomo usin... [more]

The global reliance on fossil-based solvents has driven the search for sustainable alternatives. This study employs the IBSS® CAMD tool to evaluate building blocks derived, directly or indirectly, from agricultural residues - specifically orange and coffee wastes-, to replace toluene in furfural extraction. A three-stage methodology was implemented: (1) identification of potential building blocks from residues, (2) multi-objective optimization using genetic algorithms and group contribution models for properties calculation, and (3) analysis of the resulting candidates based on performance indicators. A total of 13 families were evaluated, generating millions of candidates. Target properties included minimization of Hansen Solubility Parameters (HSP) distance, boiling point above 250°C, melting point below 10°C, flash point above 61°C, and octanol-water partition coefficient (log(kow)) below 3. The most promising candidates were derivatives of glycerol (performance: 0.9986), limonene (... [more]

Sugarcane bioenergy is a reality in Brazil, comprising the production of ethanol and bioelectricity. Sugarcane bioenergy can reduce greenhouse gas (GHG) emissions as compared to fossil fuels. However, there are concerns about the possible implications caused by the expansion of sugarcane production, the displacement of mainly pastureland, but also other croplands, and the potential for indirect land use changes. A promising strategy to enlarge sugarcane bioenergy in Brazil without compromising the cattle industry is to integrate both activities, converting extensive livestock production systems into more intensive ones. The objective of this study is to model and evaluate the socioeconomic impacts and land use change considering the expansion of ethanol production in two scenarios. The first scenario, referred to Business as Usual (BAU), comprises of sugarcane bioenergy and extensive livestock production, without any integration between the two. The second scenario, Integrated Sugarcan... [more]

This study optimizes the Sustainable Aviation Fuel Supply Chain Network (SAFSCN) in the Czech Republic, using wheat straw as feedstock. It integrates geospatial data, transportation logistics, and economic feasibility, applying mixed-integer linear programming (MILP) to optimize pyrolysis plant locations and minimize costs. Sensitivity analysis varied wheat production growth by ±0.1% and ±0.2%. Results confirm Sustainable Aviation Fuel (SAF) production is technically and economically viable, with costs projected to decline up to 30.64% and revenues rising 49.07% from 2030 to 2050 due to technological advancements, improved logistics, and economies of scale. The findings underscore the critical role of SAF in achieving EU aviation decarbonization targets and highlight the importance of efficient supply chain planning for scaling SAF production.

Uncertainty plays a crucial role in strategic supply chain design. In this study, we explore robust approaches to model uncertainty when the non-deterministic parameters are placed in the independent term, on the right-hand side (RHS) of the constraints. We consider the "disjunctive adjustable column-wise robust optimization" (DACWRO), a disjunctive formulation introduced previously in our group, and compare it with the adjustable column-wise robust optimization (ACWRO) formulation, a specific technique for solving robust optimization problems when the original robust optimization approach may assume too-conservative results. Given that the proposed method is based on the generalized disjunctive programming (GDP) technique, it is a higher lever modelling approach that represents the discrete nature of the decision process. In addition, it provides alternative MILP representations that can be further tested and compared. The analysis assesses the computational performance and reformulat... [more]

This study introduces a mathematical programming approach to optimize biomass-to-hydrocarbon supply chain design and planning, aiming to balance economic and environmental outcomes. The model incorporates a range of residual biomass types from forestry, sawmills, and the pulp and paper industry, with the option to establish various processing facilities and technologies over a multi-period planning horizon. The analysis involves selecting forest areas, identifying biomass sources, and determining the optimal locations, technologies, and capacities for facilities converting wood-based residues into methanol and pyrolysis oil, which can be further refined into biodiesel and drop-in fuels. Using Life Cycle Assessment (LCA) in a gate-to-gate analysis, forest supply chain carbon emissions are estimated and integrated into the optimization model, extending previous research. A multi-objective framework is employed to minimize CO2-equivalent emissions while minimizing present costs, with effi... [more]

Biomass gasification is a promising technology for sustainable energy production. To date, extensive research has been conducted on biomass gasification, particularly focusing on the reaction models of the process. However, existing models are too complex to apply to the control system or to optimize the process operating conditions effectively, limiting their practical use for industrial applications. To address this, a simple reaction model for biomass gasification was developed and validated. A steady state simulation of the biomass gasification process is conducted to analyze gasifier behavior and provide insights into reaction dynamic. The findings in this study align well with existing literature, confirming the reliability of the approach. This simulation serves as a foundation for further study in process control and optimization. Future work will include experimental validation to enhance model accuracy and applicability.

By-product fuel gases from refinery operations are a major heat source in fossil refineries and their availability poses a challenge to the deployment of low-carbon heat sources. This study evaluates the valorization of refinery fuel gases (RFG) into low-carbon methanol via co-processing with residual biogenic gas streams from biomass thermochemical conversion. Results from techno-economic analysis indicate that up to 44 wt.% of biogenic blend is possible without the need for external hydrogen supply, while electricity and heat requirements per tonne of methanol change by -4 % and + 80% respectively. Nevertheless, at the 44 wt.% blend, the estimated methanol cost increases only by 2.4 % (0.43 EUR/kg), while the reduction in methanol carbon intensity is approximately 40 %. This highlights promising benefits that can contribute to the integration of bio-oils producing technologies within fossil refineries.

Oxidation of arabinose to arabinoic acid is an innovative way to valorize local biomass to a high add value product. Previously done experiments on oxidation of arabinose to arabinoic acid with molecular oxygen were used to determine the optimum reaction conditions, scale-up the process and analyse the techno-economic aspects. These results were utilized to analyse the environmental impact of the scaled-up process during its lifetime using the life cycle assessment (LCA) methodology. SimaPro software combined with the impact assessment method IMPACT 2002+ were applied. The results revealed that heating seems to be the largest contributor to the environmental impact even if the reaction is performed under rather mild conditions (70oC). This highlights the importance of reducing the energy consumption via efficient heat integration.