This study presents the modeling and operation optimization of an adsorption heat storage to improve the supply of renewable heat to a house. The system configuration is an open system with water being carried by an air flow and adsorbed on zeolite 13X beads in a packed bed. A numerical model is developed based on mass and energy balances, using a Langmuir adsorption isotherm and a Linear Driving Force (LDF) mass transfer equation. The model is implemented in Pyomo and solved with the NLP solver IPOPT. A sensitivity analysis on the discretization parameters is performed to choose a good compromise between accuracy and computational time. The chosen model is then validated against experimental data from the literature, with a mean absolute percentage error less than 5%. The dynamic optimization of the operation of the system to satisfy a heat demand is then performed. The trajectory for the inlet fluid velocity is optimized in several heat demand scenarios. The results show that this nu... [more]

Direct Air Capture (DAC) is a negative emissions technology whose performance is inherently linked to ambient conditions, which directly affect its primary feed stream (air). A common simplification in DAC model simulations is the use of fixed weather conditions, which can bias the predicted performance under weather variability. In response, this study quantifies the impact of local meteorological variability and temporal weather aggregation on the performance of DAC units. Building on a previously developed and validated 1D mechanistic model of a fixed-bed Steam-assisted Temperature Vacuum Swing Adsorption (S-TVSA) DAC process, we simulate its operation using weather data from the Met Office station at Buchan (UK), near the Saint Fergus terminal - a strategic hub for Carbon Capture and Storage (CCS) activities in Scotland. A two-branch methodological framework is developed combining optimization and forward simulations. Operating conditions are optimized using a multi-objective genet... [more]

Behind-the-meter generation from variable renewable energy is a potential pathway for new data centers to obtain power more quickly and more sustainably than interconnecting to existing electrical grids. Energy storage is needed to accommodate the variability of wind and solar energy across multiple timescales. Hydrogen from electrolysis and ammonia made from this hydrogen can be used as fuel for dispatchable power generation while offering lower $/MWh storage costs than batteries. In this work, we analyze the economics of using hydrogen, and/or ammonia along with batteries in hybrid energy storage systems to enable data centers to be powered by 100% renewables. We perform this analysis using an optimization model for the selection, sizing, and coordinated hourly operation of constituent energy storage technologies toward minimizing the levelized cost of energy (LCOE). The model uses an hourly resolution scheduling horizon of five years to account for hourly, seasonal, and interannual... [more]

Flexible, electrified systems for chemical and energy production are promising alternatives to traditional, hydrocarbon-based processes. Flexible systems have the potential to reduce costs and emissions, but the interconnection between design and operation makes these systems challenging to implement. We use an operation-informed design framework to model a flexible, electrified ammonia synthesis system. We examine the levelized cost and carbon intensity of ammonia in response to different grid emissions (0-420 kg/MWh). We find levelized costs from 700-1200 $/ton-NH3 and observe non-monotonicity in carbon-intensity with respect to grid emissions. We rationalize this trend as a design transition from large, grid-reliant systems to smaller, flexible designs that are grid independent. We then study how synergies in demand and unit-operation flexibility can lower both the price and carbon-intensity of ammonia production. We find that for seasonal, or yearly demand (rather than hourly), a f... [more]

The objective of this paper is to present a single equation format for quantifying the net carbon balance (NCB) in the evaluation of CO2 capture technologies, and to discuss the benefits of this approach. The equation must take into account indirect emissions, especially the contributions from utility generation systems (heating, cooling and electricity), making use of efficiency values and emission factors. The idea is to synthesize, in a single expression, the quantification of the environmental footprint of a technology, in a practical way so that it could be used as an efficient metric in technical evaluation studies, or as objective function/constraint in optimization problems. It also facilitates demonstrating the relationship between capture efficiency and environmental performance, as well as the contribution of each term to total emissions, and to compare different technologies in terms of time, location and available energy sources. To illustrate the application of the propos... [more]

Green hydrogen constitutes a strategic energy vector for achieving the Sustainable Development Goals (SDGs 7, 9, 12, and 13) due to its high energy density, flexibility for renewable energy storage, and direct emission-free operation. However, its production critically depends on the supply of high-purity water, which is unsustainable in the context of a projected 40% global water deficit by 2030. Given that more than 97% of available water is saline, integrating desalination processes with electrolysis constitutes an essential strategy for transitioning toward circular economy models in water resource management. This work presents the conceptual design, detailed modeling, and optimization of an integrated process for the sustainable production of green hydrogen from saline water. The system couples a desalination technology (Solar Distillation) with two electrolysis technologies (AEL and SOEC), modeled through physicochemical, electrochemical, and thermodynamic principles. The object... [more]

When designing and planning Green Hydrogen Supply Chains (GHSCs), sustainability considerations are increasingly recognized as essential, particularly in light of decarbonization goals and climate policy targets. Existing research has largely focused on economic and environmental however, social sustainability aspects remain significantly underexplored. This work aims to develop a mathematical programming model to design a GHSC, considering simultaneously economic and social aspects. Solar PV, wind power, and PPA (wind) as energy sources are integrated, while transportation options include the construction of new pipelines, compared to the use of existing highways for trucks carrying liquefied or compressed hydrogen to deliver hydrogen to an oil refinery. The model is applied to a case study conducted in the Brazilian state of Bahia, where different social indicators will be explored, characterizing the case study context while allowing generalization to other contexts. Results allow u... [more]

In the urgent effort to reduce greenhouse gas (GHG) emissions in the industrial sector, biogas-derived green hydrogen and power co-generation represents a promising solution. Biogas, a renewable and carbon-neutral resource, provides a flexible feedstock for decentralized energy systems, particularly in regions with well-developed agricultural or waste biomass infrastructure. This approach allows the deployment of cost-efficient systems aligned with climate targets and industrial decarbonization roadmaps. Compared to steam methane reforming (SMR), sorbent-enhanced SMR (SE-SMR) with integrated calcium looping (CaL) CO2 capture reduces process emissions while enhancing hydrogen yield. This study investigates the economic and exergy-based implications of partially splitting hydrogen from a SE-SMR-CaL system producing 50, 000 Nm³/h of H2 from desulfurized biogas. Following heat integration using the PINCH methodology, an electrically self-sufficient base case was established. Economic and e... [more]

Hydrogen from biomass gasification combined with carbon capture and storage (CCS) can lead to negative emissions and support Europe's energy transition. This study presents a mixed-integer bilinear optimization model for the cost-optimal design of a Northern European hydrogen supply chain with integrated CCS, focusing on exports from Norway to Germany and CO2 sequestration in Norway. The model is formulated as a superstructure problem and implemented in Pyomo, considering multiple locations for infrastructure nodes and transport options for hydrogen, wood chips, and CO2. The results show that shipping wood chips and CO2 is generally more cost-effective than shipping compressed hydrogen. Supply chain costs range from 35-55 NOK/kg H2, and net-negative emissions (scope 1 and scope 2) are achieved at CO2 capture rates above approximately 30%.

Biodiesel production from sustainably cultivated plant sources holds extremely high promise globally [6]. Microalgae have been intensely explored as a next-generation source for transport fuel production [9], as they combine attractive characteristics: rapid growth, high lipid content, and environmental benefits. Nevertheless, technical challenges abound regarding the feedstock potential, cultivation process, and its fatty acid mono-alkyl ester (FAME) properties. Performance evaluations for specific microalgal strains [2, 4, 10, 15] are thus of particular interest. The case of Indonesia is particularly significant due to the country's large size, population, biodiversity of terrestrial and marine plant species, and the variety of microalgae that can be harvested and used on an industrial scale for biodiesel production, especially in different media and cultivation methods. Many strains, such as Botryococcus braunii, Chlorella sp., Chlamydomonas sp., and Nannochloropsis sp., have a high... [more]

The reliable identification of feasible and optimal operating conditions is a key challenge in the design and optimization of thermochemical conversion processes, where kinetics, limited data availability, and strict physical constraints coexist. In this work, a novel data-driven strategy based on Physics-Informed Neural Networks (PINNs) is proposed to explore the operability space of a bubbling fluidized bed (BFB) plastic pyrolysis process. The approach integrates mechanistic knowledge through explicit mass balance constraints with data-driven learning, enabling accurate prediction of and feasibility boundaries. An adaptive sampling framework is employed to iteratively augment the training dataset. The trained PINN surrogate is then used to predict feasible regions and perform constrained optimization aimed at minimizing tar production, which is one of the most problematic byproducts in plastic pyrolysis processes. Beyond classical optimality, a robustness-oriented uncertainty quantif... [more]

The increasing deployment of lithium-ion batteries (LIBs) requires effective recycling strategies to reduce environmental impacts and dependence on critical raw materials. In this study, a comparative life cycle assessment (LCA) of two LIB recycling routes, a pyrometallurgical process (Pyro) and a hydrometallurgical process with co-precipitation (Hydro), was performed using a Python-based process modeling framework. The LCA was carried out using an attributional approach, with impacts referred to 1 kg of spent LIBs treated at the recycling facility inlet, considering a representative mix of battery formats and cathode chemistries. Results showed that, when normalized per kilogram of treated batteries, the Hydro route is more impactful than the Pyro one, particularly in terms of global warming potential. The Pyro process does not enable direct cathode regeneration but allows the recovery of high-purity metal salts, whereas the Hydro route enables the production of re-formed NMC-111 cath... [more]

The ecological transition demands innovative frameworks to reduce industrial resource consumption and environmental impacts. Industrial ecology, particularly through Eco-Industrial Parks (EIPs), provides a promising pathway by enabling exchanges of materials, energy, and water between firms. However, the deployment of EIPs is limited by the lack of standardized industrial profiles and transferable modeling approaches. This study develops a generic framework for representing industrial actors as standardized input-output black-box models, consolidating data on resource consumption, energy demand, by-products, and waste streams. These profiles are structured into a harmonized database to support resource-exchange analysis and scalable optimization across diverse contexts. Complementary mappings of processes and resources, as well as energy and heat demand profiles, enhance the feasibility of identifying synergies such as heat cascading and material reuse. The framework is designed to int... [more]

Sustainable aviation fuel (SAF) is a key pathway for mitigating greenhouse gas emissions in aviation, yet its large-scale deployment is constrained by high energy demand and production costs. Among available conversion routes, the hydroprocessed esters and fatty acids (HEFA) pathway is the most commercially mature, but it requires substantial hydrogen input and high-temperature heat, affecting both economic and environmental performance. This study presents a decision-support framework for SAF production via integrated biorefineries, using rapeseed oil extraction coupled with HEFA conversion as a case study. Detailed process simulations are combined with energy integration and mixed-integer linear programming optimization to enable system-level analysis. Material integration strategies include internal hydrogen generation via glycerol steam reforming and valorization of rapeseed meal through gasification for syngas production. Heat integration considers cross-process heat recovery and... [more]

China's cement industry accounts for over half of global production and contributes 8% of global CO2 emissions, making its decarbonization critical for achieving climate targets. While carbon capture and storage (CCS) and carbon capture and utilization (CCU) are essential deep decarbonization technologies, existing research has not adequately addressed the regional and temporal variations needed for optimal pathway selection across China's diverse provinces. This study develops a comprehensive whole-systems optimization model to design provincial-scale decarbonization pathways for China's cement industry from 2025 to 2060. The model reveals significant spatial and temporal heterogeneity in optimal technology combinations. Before 2050, traditional cement processes integrated with CCS (TCP-CCS) represent the dominant bridging technology for low-carbon transition. However, reaching carbon neutrality by 2060 necessitates an eventual shift toward widespread deployment of novel chemical proc... [more]

Plastic pyrolysis is widely promoted as a techno-economic industrial scale recycling strategy. Nevertheless, the fate and reactivity of plastic chemical additives during pyrolysis are mostly overlooked in product quality and environmental release assessments. Here, we present an integrated modeling framework to elucidate the role of additives in plastic pyrolysis and evaluate the implications of their transformation products and environmental releases. Using high-density polyethylene (HDPE) as a case study, chemical additives of concern are selected based on occurrence, concentration data, and potential risk to human health and the environment. Bond dissociation energies are predicted using a machine learning model to identify dominant radical species formed under pyrolytic conditions. These additive-derived radicals are incorporated into an automatic chemical reaction mechanism generator that constructs kinetic models composed of elementary chemical reaction steps. These kinetic model... [more]

Palm oil mill effluent (POME) represents a major environmental burden in the palm oil industry while offering opportunities for resource recovery. This study develops and applies a value-based assessment framework to examine how technological choice influences the integrated environmental-economic performance of POME valorization. Biomethane production and bio-hydrogen production are selected as representative mature and emerging technologies, respectively. Life-cycle environmental performance is quantified using greenhouse gas (GHG) emissions midpoint indicator and natural resources endpoint indicator, reflecting broader environmental damages. A techno-economic assessment is performed to show the economic performance. In addition to conventional return of investment (ROI), the benefits of mitigating environmental impacts are accounted using the return of value (ROV) methodology. The results indicate that the attractiveness of POME valorization pathways depends strongly on how environm... [more]

Achieving and sustaining net-zero greenhouse-gas emissions will require the long-term deployment of green hydrogen. Proton exchange membrane water electrolysers (PEMWEs) are attractive for variable renewable electricity (VRE) because of their fast dynamic response; however, they rely on iridium (Ir) anode catalysts, and Ir supply is severely constrained. Here, a Japan-specific dynamic material flow analysis (DMFA) model is developed for 2025-2100 to quantify Ir circularity in PEMWE deployment under a backcasting-oriented hydrogen production pathway. The model tracks Ir in anode catalysts only and represents: (i) Ir demand for new capacity additions and replacements, (ii) end-of-life (EoL) outflows governed by a Weibull lifetime distribution, and (iii) closed-loop recycling characterised by an overall recycling rate across collection, separation/pre-processing, and refining. Sensitivity analyses show that long-term primary Ir requirements are governed by the coupled effects of catalyst... [more]

Existing gas network infrastructure are important national energy assets, transporting mostly fossil-derived natural gas to end-users. Biomethane, methane derived from anaerobic digestion (AD) of organic matter, presents a potential route to replace fossil fuels with home-grown renewable gas. Combined with carbon capture and storage (CCS) of the CO2 in the biogas potentially results in carbon negative energy. This work seeks to understand the feasibility of operating a part of the gas network isolated from the main natural gas network fully on biomethane in Scotland. We present an integrated techno-economic optimisation framework for designing self-sufficient biomethane islands, applied to the Inverness network. The model, implemented as a nonlinear program (NLP), maximises annual net profit from biomethane sales and Green Gas Support Scheme (GGSS) tariffs subject to practical constraints such as GGSS-compliance of =50 % waste-derived biomethane, seasonal supply, land/scale, demand bal... [more]

This paper presents OpenAD-lib, an open-source Python framework for anaerobic digestion (AD) digital twins, unifying mechanistic models, machine learning (ML) surrogates, and model predictive control (MPC) within a modular ecosystem. OpenAD-lib addresses the critical fragmentation in AD digitalisation by bridging mechanistic and data-driven paradigms under explicit uncertainty. By integrating uncertainty-aware feedstock characterisation with robust process control, the platform enables the transition from isolated research tools to fully integrated digital twins, delivering economic and environmental value in AD systems.

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]

Regional deployment of bioenergy and bio-based products is often constrained by the seasonality, heterogeneity, and dispersed availability of lignocellulosic biomass. This work demonstrates a computer-aided process engineering (CAPE) workflow that integrates experimental characterization, process modeling, and life cycle assessment (LCA) to support regional symbiosis design using mixed feedstocks from agriculture and forestry. A case study is developed for Tanegashima, a remote Japanese island where unused woody residues and sugarcane bagasse are locally available but temporally mismatched. Torrefaction is modeled in an autothermal configuration: char is the main product, while torrefaction gas and condensables are recovered for internal heat supply and any excess is treated as an energy coproduct. Laboratory measurements (220-400°C, 20°C interval) provide temperature-dependent yields of char, tar, aqueous condensate, and gas, alongside ultimate analysis and heating values of solids an... [more]

Critical metals are indispensable in renewable, low-carbon, and hydrogen technologies due to their unique catalytic and electrochemical properties. They are primarily sourced through mining, which is associated with significant environmental impacts and geopolitical risks due to the uneven global distribution of ore deposits. As a result, efficient recovery of these metals from secondary sources such as electronic waste has become increasingly important. In this context, liquid-liquid extraction (LLE) has emerged as a promising separation technique due to its high selectivity and scalability. The development of intensified, continuous-flow LLE in small channels offers further advantages in terms of mass transfer efficiency, solvent utilization, and process sustainability, making it an attractive approach for the recovery of critical metals. A flow pattern known as segmented flow further enhances mass transfer in LLE in small channels. This work presents a hybrid modelling approach for... [more]

While the transition from traditional energy sources to renewable energy is necessary to reduce greenhouse gas (GHG) emissions, it introduces new challenges related to material use, both in quantity and type, potentially leading to resource scarcity, biodiversity loss, and waste accumulation. Therefore, incorporating circular economy (CE) principles into the design and planning of energy systems becomes essential. Despite the growing recognition of circularity, current assessments in energy systems focus on economic performance and GHG emissions. In this work, we propose a metric for quantifying circularity of energy systems based on the CE assessment framework MICRON, addressing the gap between CE metrics and energy systems planning. The framework is adapted to energy systems by accounting for the specific characteristics of energy technologies and by incorporating metrics associated with critical material use, scarcity, and durability. Its applicability is demonstrated through a case... [more]

The biopharmaceutical sector has traditionally focused on cost-efficient process design and capacity planning to meet rising demand. Recently, sustainability pressures have increased, driving efforts to reduce the environmental footprint of manufacturing and supply chains; however, strict quality and sterilization requirements can limit the implementation of fully circular resource-use strategies. In this space, adopting an industrial-cluster systems view could unlock opportunities to improve sustainability of industrial clusters through coordinated material and energy exchange, supporting resource efficiency at cluster level and still meet sector-specific quality/sterilization requirements. In this work, we present life cycle assessment (LCA)-based comparative analyses to investigate the potential of industrial symbiosis within monoclonal antibody (mAb) manufacturing, whereby LCA process models are based on comprehensive techno-economic analyses that quantify resource inputs and waste... [more]