This study presents a comprehensive comparison of the three alternative downstream manufacturing technologies for pharmaceuticals: i) Dry Granulation (DG) through roller compaction, ii) Direct Compaction (DC), and iii) Wet Granulation (WG) based on the economic, environmental and product quality performances. Firstly, the integrated dynamic mathematical models of the different downstream (drug product) processes were developed using gPROMS formulated products based on data from the literature or/and our recent experimental work. The process models were developed and simulated to reliably capture the impact of the different design options, process parameters, and material attributes. Uncertainty analysis was conducted using global sensitivity analysis to identify the set of critical process parameters (CPP) and critical material attributes (CMA) that mostly influence the quality and performance of the final pharmaceutical tablets in each case, captured by the critical quality attribute... [more]

This work introduces a Python-based interface that couples cradle-to-gate Life Cycle Assessment (LCA) with advanced process simulations in continuous biomanufacturing, resulting in dynamic process inventories and thus to dynamic LCA (dLCA). The open-source Brightway2.5 framework is used to dynamically track environmental inventories of the foreground process and LCA indicators (e.g. damage to ecosystems according to ReCiPE 2016) from the v3.10 cut-off ecoinvent database. The framework is applied to KTB1, a dynamic MATLAB–Simulink benchmark model of continuous Lovastatin production. 580 data points are computed across four different 24-hour scenarios. The difference between the hourly and the averaged foreground scenario is between 20-30%; a more pronounced deviation is observed when both background and foreground are averaged. The dLCA framework precisely identifies optimal periods for cleaner electricity usage, enabling future work on direct environmental feedback into process control... [more]

Microalgae cultivation on liquid digestate from the anaerobic co-digestion of agricultural feedstocks is an interesting option for digestate nutrient removal and resource recovery coupled to value-added biomass production. In this paper, a first-principle plant-wide modelling of the process is described. Two well-established models for anaerobic digestion (IWA – ADM1) and algae-based bioremediation processes (ALBA) were considered and modified with necessary equations and extensions to develop a coherent interface between the state variables of the two models. The resulting system is composed by highly non-linear and non-smooth DAEs. Open-loop scenario analysis for different upstream co-digester design and operating conditions was carried out to assess the impacts on the downstream microalgae outputs. It highlighted the importance of a proper biorefinery design and yet a noteworthy robustness of the system performance. The exploitation of the model can facilitate: a more realistic asse... [more]

In 2022, Uruguay launched its green hydrogen roadmap, due to its renewable energy potential, water availability, and favorable logistics to position itself as an exporter of green hydrogen and derivatives. The energy source for water electrolysis is a key factor in both the final cost and the environmental impact of hydrogen production. In this context, this study evaluates the environmental impact of hydrogen production via water electrolysis, powered by 150 MW of new power sources (solar, wind, and hybrid farms) in Uruguay, all connected to the national grid. A life cycle assessment (LCA) was conducted using OpenLCA software and the Ecoinvent database, with 1 kg of hydrogen as the functional unit and the system boundaries included power generation and the electrolysis system. The analysis focused on global warming potential (GWP), considering different scenarios for the grid energy mix and the inclusion or exclusion of surplus energy as carbon credits. The wind plant is the option th... [more]

To achieve carbon neutrality, the installation of variable renewable energy (VRE) has been accelerated. However, the inherent variability of VRE can be mitigated through the installation of energy storage. This study aims to evaluate life cycle impacts of energy storage systems utilizing batteries, hydrogen storage, or thermal energy storage. A model of the energy storage systems with VRE was developed, and the annual energy flow simulations were conducted. The energy storage system targeted in this study assumed that all energy derived from VRE was stored in the energy storage and supplied to consumers. The amount of electricity to-be-sold from the energy storage system, based on the capacity of VRE and the installed energy storage, was calculated. A life cycle assessment was performed to evaluate the greenhouse gas (GHG) emissions, abiotic resource depletion (ARD), and intensity of GHG and ARD as life cycle impacts. The smallest life cycle impacts varied depending on the type and sca... [more]

This study evaluates the environmental impact of carbon capture technology in the context of reducing industrial CO2 emissions within Eco-Industrial Parks (EIP). The primary focus is on the post-combustion absorption process, which uses solvents like monoethanolamine (MOA) to capture CO2 before it is released into the atmosphere. The captured CO2 is either stored or utilized to prevent further contribution to climate change. The study employs a Life Cycle Assessment (LCA) methodology to compare the environmental impacts of two scenarios: one with CO2 capture and the other with the direct release of CO2 into the atmosphere. The LCA considers inputs, outputs, energy requirements, and materials needed for the CO2 absorption process. The functional unit of the assessment is 1000 tons of CO2, to standardize comparisons between both scenarios. Results show that the CO2 absorption process significantly reduces the impact on climate change, capturing over 80% of the CO2 from the stream. In ter... [more]

Industrial ecology appears to be a significant means of reducing carbon dioxide emissions from industry. However, beyond flow management, eco-industrial parks can also contribute to a socio-economic transition on a regional scale. Usually, multi-criteria optimization models use economic and environmental criteria in the decision-making process. This article looks at the integration of social criteria in these models, and more broadly at the issues involved in measuring the social impact of an eco-industrial park. The aim of this article is to take a different approach to social indicators, by highlighting the key success factors of an eco-industrial park, such as cooperation within a collective but also between the different scales making up the system. This work is based on bibliographical research and semi-structured interviews with stakeholders in the field. What's more, the process of developing social indicators, particularly participatory ones, seems to be a strong catalyst in th... [more]

Hydrogen is increasingly recognized as a key player in future energy systems. However, its production technologies—Steam Methane Reforming (SMR) and electrolysis—present trade-offs. SMR, the dominant method, is cost-effective but has a significant carbon footprint, emitting substantial greenhouse gases (GHGs). In contrast, electrolysis, powered by renewable energy sources, offers a cleaner alternative, albeit at a higher cost. While current hydrogen system optimizations primarily focus on cost reduction and GHG mitigation, they often neglect broader environmental impacts. This paper addresses the challenge of modeling a hydrogen supply chain (HSC) that achieves strong environmental performance at a relatively affordable cost. To this end, a supply chain design optimization is coupled with Life Cycle Assessment (LCA). The novelty of this work lies in the integration of multiple LCA indicators in the supply chain design optimization, rather than focusing solely on costs and Global Warmin... [more]

One of the proposed strategies to reach net-zero goals is the diversification of a country’s energy mix and transition to technologies that favour the mitigation of greenhouse gas emissions, while decreasing dependency on conventional fuels. This work presents a mathematical model that describes key production routes for two proposed energy transition vectors, biomethane and hydrogen, expressed as a Mixed-Integer Linear Problem (MILP). The supply chain is optimized with the objective of maximizing the profits from the global supply chain. The problem is formulated as an allocation problem, with production distributed between biomethane and hydrogen markets. The case study focuses on a region in Mexico where second-generation biomass for biogas production is abundant, while hydrogen is produced from biomethane using steam methane reforming. The results highlight the importance of balancing resource allocation in shared supply chains. With a production ratio of 60% biomethane and 40% hyd... [more]

Hydrogen is a key element in the global transition toward a low-carbon economy, with green hydrogen offering significant potential to decarbonize industries and energy systems. This study focuses on designing and optimizing a green hydrogen supply chain (HSC) for the state of Bahia, Brazil, using a deterministic Mixed-Integer Linear Programming (MILP) model. The model evaluates 24 scenarios combining production sites, storage technologies, transportation methods, and energy sources, minimizing the Total Sustainable Cost (TSC). The TSC integrates financial and environmental costs, monetizing CO2 emissions using international carbon pricing. Results indicate that economies of scale play a critical role allowing the minimization of the financial costs while achieving lower greenhouse gas (GHG) emissions compared to other scenarios. The study emphasizes the importance of aligning production strategies with regional renewable energy resources to enhance both cost-effectiveness and sustainab... [more]

Hydrothermal liquefaction (HTL) has proven to be an appropriate technology for converting sewage sludge into a valuable resource for renewable energy generation. This study focuses on a prospective analysis of various technological scenarios for sewage sludge-to-fuel pathways via HTL, co-located with a wastewater treatment plant, in support of a circular economy perspective. Four technological foreground scenarios and three prospective background scenarios aligned with the Paris agreement’s climate targets REMIND-SSP2-Base (projecting a 3.5°C temperature rise by the end of the century), PKBudg1150 (aiming to limit the rise to below 2°C), and PKBudg500 (targeting a cap below 1.5°C) are analyzed for sewage sludge-to-fuel conversion in 2030, 2040, and 2050. The superstructure problem of the possible combinations of the developed scenarios is solved using the P-graph studio which is based on the branch and bound approach. The goal of this study is to maximize the objective function (OF) by... [more]

The reduction and recovery of organic fraction of municipal solid waste is a major challenge for contemporary society. It requires the establishment of regional strategies with minimized environmental impact. This study employs life cycle assessment to evaluate the respective environmental performances of the current French system based on incineration, and those of alternative systems including (i) anaerobic digestion with composting and (ii) composting for biowaste treatment under different energy scenarios. The environmental impacts of Parisian biowaste are calculated by considering incineration technologies in the area, the French energy mix in 2022, the average European energy mix in 2022 and the projected French energy mix for 2030. The results show that the proportion of fossil-based sources in the energy mixes significantly influences the environmental performance of waste management systems. Energy mixes based in high-carbon fossil sources dependency tend to favour incineratio... [more]

Hydrogen is increasingly recognized as a crucial energy carrier for a low-carbon future. However, most studies on clean hydrogen production devote limited attention to the entire supply chain. This study evaluates the sustainability of 800 combinations of hydrogen production and transportation methods, comparing their environmental impacts against the geophysical limits defined by the Planetary Boundaries framework. Findings reveal that no supply chain alone can make the current economy sustainable, yet powering water electrolysis with bioenergy and carbon capture and storage can meet the CO2-based planetary boundaries. The analysis also underscores the need for decarbonization efforts in the hydrogen transportation sector, as certain options could offset the benefits of clean hydrogen production.

In this work, we propose a mixed-integer linear programming (MILP) model that optimizes economic and environmental objectives by retrofitting fuel stations for the case study of Spain. The model contains set-covering constraints that ensure that there is at least one retrofitted fuel station within a radius of 20 kilometers of each retrofitted fuel station. The results indicate that by retrofitting fuel stations to allow for electric vehicles, both economic and environmental objectives improve, while showing which power plants would be tasked with the increase in electricity production to satisfy the increased electric demand.

Photochemical monolith reactors offer advantages over microreactors by providing high mixing efficiency and surface area to volume ratio while being scalable. However, optimizing monolith design parameters like channel number, shape, and stacking is critical to maximizing light usage and reactor efficiency. This work proposes using Bayesian optimization and COMSOL Multiphysics simulations to automatically design translucent monoliths for photochemical reactions. The goal is to maximize both photochemical space-time yield and space-time yield. Ray tracing simulations were performed while evaluating five different channel geometries (circular, elliptical, triangular, square, and pentagonal) and optimizing parameters, including channel diameter, vertical stacking, shape rotation, and ellipse axis ratio. Results showed a clear trade-off between Space-Time Yield (STY) and Photochemical Space-Time Yield (PSTY), with optimized elliptical channels achieving up to 15.3% improvement in STY with... [more]

Accurate yet interpretable prediction of Global Warming Potential (GWP) is essential for the sustainable design of chemical products and processes. However, existing studies that utilize molecular structure and physicochemical properties for GWP prediction often suffer from low interpretability, relying on black-box models that obscure the underlying relationships between molecular descriptors and environmental impact. To address this limitation, this study employs a Kolmogorov–Arnold Network (KAN) to derive symbolic equations that establish explicit relationships between molecular properties and GWP. By extracting interpretable mathematical expressions, our approach provides a transparent foundation for decision-making in chemical processes and reaction development. Our comparative analysis of machine learning models—including Random Forest, XGBoost, Deep Neural Networks (DNN), and KAN—reveals that Mordred descriptors outperform MACCS keys in GWP prediction, emphasizing the importance... [more]

This work approaches a detailed characterization of the aspects inherent to the innovative paradigm of Water and Energy Integration Systems (WEIS). These consists in conceptual physical systems which consider all potential energy-using and water-using processes in a site, all potential recirculation of material and energy streams between these and the integration of several categories of state-of-the-art technologies. The WEIS have the ultimate aim to promote the sustainability character associated to existing installations (through the reduction of energy and water input and contaminants output). The specific characteristics of WEIS are compared to existing similar process integration methodologies and a set of performance indicators are determined, having as a basis two previous case-studies approached for the Engineering project of WEIS. The performed analysis in this work revealed that the innovative paradigm is able to constitute Engineering projects with associated sustainability... [more]

Efficient temperature control in greenhouses is essential for optimal plant growth, especially in arid regions where the harsh environment poses significant challenges to maintaining a stable microclimate. Maintaining the optimum temperature range directly influences healthy plant development and overall agricultural productivity, impacting crop yields and financial outcomes. However, the greenhouse in the present case study fails to maintain the optimum temperature as it operates based on predefined settings, limiting its ability to adapt to dynamic climate conditions. To maintain an ideal temperature range within the greenhouse while dynamically adapting to fluctuating external conditions, this study introduces a control framework using Deep Deterministic Policy Gradient, a model-free deep reinforcement learning algorithm, to optimize temperature control in the closed greenhouse. A deep neural network is trained using historical data collected from the greenhouse to accurately repre... [more]

Circular economy is recognized as one of the most effective strategies for promoting plastic sustainability. However, its implementation requires to enhance consumer engagement, which remains a primary target of regulatory initiatives designed to promote plastic circular economy. To ensure sustained consumer participation, it is essential to evaluate and optimize various incentives, including regulatory policies, voluntary programs, and market-related mechanisms. This study applies Stackelberg Game Approach to quantitatively capture the strategic interactions between the authorities (as the leader) and consumers (as followers). The model incorporates key consumer behaviors, i.e., "use less," "use longer," and "recycling", to reflect their role in advancing plastic circular economy goals. By integrating factors such as governmental utility (gains of benefits), consumer utility (welfare), and plastic waste reduction, the model identifies the optimal intensities of various public initiati... [more]

Renewable carbon sources, such as biomass and waste, are being explored as alternatives for sustainable plastic production. However, the significant uncertainties surrounding the environmental impact of biomass supply processes raise questions about whether these plastics positively contribute to society. Furthermore, the lack of systematic knowledge about plastics and incomplete understanding among stakeholders pose challenges to conducting comprehensive assessments and designing effective plastic life cycle systems. This study aims to clarify the carbon flow within the life cycle of biomass- and recycled-derived plastics and to design a plastic life cycle that enables the introduction of renewable carbon sources. To this end, the study analyzed the structure of plastics containing renewable carbon and conducted a flow analysis of packaging plastics in Japan. The flow analysis was conducted in the form of an optimization problem. Greenhouse gas (GHG) emissions and the proportion of re... [more]

Data-driven decision-making is crucial in the transition to a low-carbon economy, especially as global industries strive to meet stringent sustainability goals. Traditional life cycle assessments often rely on static emission factors, overlooking the dynamic nature of the energy grid. As renewable energy penetration increases, grid carbon intensity fluctuates significantly across time and regions, due to the inherent intermittency of renewable sources like wind and solar. This variability introduces discrepancies in emission estimations if time-averaged factors are applied, leading to sub-optimal process operations and unintended environmental consequences. To this end, we present a real-time emission-aware optimization framework, which is implemented through a mixed-integer linear programming formulation that can determine optimal design configurations and operation schedules while simultaneously mitigating emissions by utilizing electricity price forecasts, time-varying emission fact... [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]

The integration of carbon capture and storage (CCS) into coal and biomass co-firing systems (CBCCS) offers a promising solution for reducing carbon emissions in electricity generation. This study evaluates hypothetical scenarios in Malaysia and Indonesia, focusing on techno-economic-environmental transparency. The analysis shows a negligible change in plant net efficiency (~1%) across biomass co-firing ratios of 5-20% in both countries. The capture penalty increases at higher biomass ratios, particularly at 20% co-firing, due to higher auxiliary power demands and steam extraction. As biomass share increases, net CO2 emissions decrease by an average of 43% in Malaysia and 34% in Indonesia. Economic evaluations show a positive revenue increase for Malaysia at a 20% co-firing ratio, while Indonesia faces a revenue deficit (0.6%) under the same condition, mainly due to an unattractive carbon price and feed-in tariff from 2027 onward. Malaysia faces a higher risk of stranded assets due to e... [more]

A generally applicable framework for the evaluation of the sustainability of distillation processes is proposed by aligning indicators directly to selected sustainable development goals (SDGs) created by the United Nations. The indicators are related to the goals good health and well-being (SDG 3), clear water and sanitation (SDG 6), affordable and clean energy (SDG 7), decent work and economic growth (SDG 8), industry, innovation and infrastructure (SDG 9), responsible consumption and production (SDG 12), climate action (SDG 13) and life below water (SDG 14). A total of 12 sustainability indicators, including human toxicity potential, wastewater generation, water consumption, renewable energy share, energy demand, material footprint, profit, waste generation, recycling ratio of waste, greenhouse gas emission, eutrophication potential and acidification potential are assigned to selected SDGs. The application of the indicators is illustrated by two case studies: a batch (BD) and a conti... [more]

The Life Cycle Assessment (LCA) of a solid oxide electrolyser (SOE) has been performed using publicly available data. The system for producing 1 kg of hydrogen at 25bar and 99.9% purity is represented by a modular structure, which includes the 20-kW solid oxide stack manufacturing, balance of plant equipment, operation consumables, and end-of-life processes. A parametrized life cycle inventory modeling approach was developed. The results illustrate that SOE performs better than steam methane reforming only if supplied by electricity from renewable or nuclear sources. The operation consumables have been identified as the most contributive life stage (67%-89% of potential impacts), followed by equipment manufacturing (7%-22%) and stack manufacturing (4%-11%). Considering the predominant contribution of electricity supply in the consumables, no compromise should be made on ensuring clean electricity sourcing and on the stack energy conversion efficiency. The lifetime of the stack and the... [more]