Membranes provide an efficient method for treating flue gases to capture CO2 from various point sources, achieving high recovery and purity rates. However, the lack of systematic process-level design tools has limited the translation of advanced membrane materials into large-scale technical and economic metrics. Thus, in this study, we present a superstructure model for the design of membrane-based carbon capture, both from highly energy-intensive industries and from power plants. The superstructure model enables the flexible design and global optimization of multi-stage membrane systems. Multiple membranes are compared under technical performance indicators (specific energy and specific area), while the already commercialized polymeric membranes Polaris and PolyActive are taken into consideration for estimating their economic performance. The presented framework establishes a robust link between material innovation and optimal process design, providing a key tool for the large-scale d... [more]

This work aims at verifying the CO2 absorption capture model using monoethanolamine (MEA) solvent developed by the U.S. DOE's Carbon Capture Simulation Initiative (CCSI) and performing uncertainty propagation of mass transfer, liquid hold-up and reaction kinetics properties in the complete model, which includes absorber and stripper columns. The verification of the Aspen Plus CCSI model, based on pilot plant data from the National Carbon Capture Center (NCCC) for a CO2 flue gas concentration between 7 and 11% (mol) allowed uncertainty quantification (UQ) analysis for four different selected operational points using Monte Carlo Simulation (MCS), where low liquid mass transfer parameters exhibited an impact on calculation convergence. Gaussian Processes (GP) surrogate model was implemented, followed by a sensitivity analysis in order to correlate the most sensitive parameters with studied outputs.

In this study, we propose a novel trust-region funnel (TRF) optimisation framework for process systems that integrate external black-box models, such as rigorous models, within equation-oriented (EO) formulations. The framework is applied to optimise a synthetic natural gas production process combining direct air capture and catalytic CO2 conversion using dual-function material (DFM) technology, with the objective of minimising the total annualised cost. The problem is formulated in Pyomo and solved using IPOPT, treating the DFM reactor as an external black-box model. The TRF method achieves substantial improvements compared to published mixed-integer nonlinear programming and direct nonlinear programming approaches, reducing capture cost from 460 USD to 426 USD per tonne of CO2. Key design improvements include reducing the number of DFM units per train by one-third and achieving a 22% reduction in DFM capital costs. These results highlight the TRF framework's ability to overcome numer... [more]

Waste incineration with combined heat and power (CHP) supplies electricity and heat to cities and industrial clusters but remains a significant source of greenhouse gas emissions. This work develops an optimization-based, system-level decarbonization framework for an integrated waste-to-energy and chemical production cluster under operational, societal, and economic constraints. The framework is applied to a real-world case study including a municipal waste incineration plant, an energy utility system, and multiple chemical production units. A layered decarbonization strategy is implemented. First, energy efficiency is enhanced through waste heat valorization using heat pumps. Second, coordination between industrial actors is improved through solid waste storage management and operational alignment of heat and power supply with demand. Third, alternative feedstocks are introduced to reduce fossil-based inputs. Within the work material and heat-stream inventories are collected, and the... [more]

Environmental concerns caused by CO2 emissions has attracted much attention by researchers worldwide. CO2 can be captured from large single sources such as power plants to reduce the CO2 emission. Solvent-based post-combustion carbon capture (PCC) process for large scale biomass-fired power plant could achieve negative carbon emission. However, capture level is commonly set at 90% in many studies. The small fraction of residual CO2 is still a large amount due to the high flue gas flowrate. In this study, a piperazine-based PCC process at 95% capture level for biomass-fired power plant was studied. The process was simulated in Aspen Plus® V11, validated and scaled up. The energy performance results showed that when the capture level is increased to 95%, the reboiler duty rises to 4.07 GJ/tCO2, corresponding to an increase of approximately 13.7% compared to the 90% case. This additional regeneration energy demand is offset by the reduction in residual CO2 emissions from flue gas or 0.23... [more]

The present work aims to demonstrate the synergy achieved through the integration of biomass gasification with a direct air capture (DAC) system to maximize overall CO2 removal capacity, while simultaneously converting waste into value-added products (hydrogen) and supplying the energy required for DAC operation (BG-H2P-DAC). The proposed configuration is modeled using Aspen Plus to investigate the synergistic interactions and key performance indicators of the BG-H2P-DAC system. Parametric analyses are conducted by varying gasification temperature, air inlet flow rate, and amine concentration and flow rate. The results indicate that increasing the monoethanolamine (MEA) concentration from 10% to 40% leads to a gradual decline in CO2 capture efficiency, accompanied by a reduction in CO2 slip. The system achieves a net specific electricity consumption of 0.0293 MWh/t CO2, confirming that the electricity generated from the integrated steam power cycle is sufficient to fully offset the ele... [more]

Magnetic Inductive Swing Adsorption (MISA) is a carbon dioxide capture process similar to Temperature Swing Adsorption that uses direct electromagnetic heating instead of classic heating systems for the regeneration step of the process. However, the lack of validated dynamic models hinders process optimization. This work introduces an open-source MISA model in the IDAES framework, incorporating Specific Absorption Rate (SAR) physics (SAR ? B²) to capture electromagnetic heating. Binary Sips isotherm parameters for Fe3O4@HKUST-1 were fitted to experimental data, achieving high statistical agreement (R2 > 0.996, RMSE < 0.022 mol/kg). Comprehensive validation was performed against adsorption isotherms, dynamic breakthrough curves, and desorption profiles. The model predicts breakthrough time with only 9% error and saturation time with 6% error. Crucially, the coupled thermal transport and SAR heating model capture temperature evolution during desorption within 5% error across all field st... [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]

The integration of industrial symbiosis (IS) and carbon capture utilization (CCU) is recognized as a key strategy for achieving net-zero emissions in industrial parks (IPs). However, the optimization of these processes in combination remains an undeveloped research area. This work presents a multi-objective optimization framework implemented in Pyomo and linked with OpenLCA to simultaneously maximize material exchanges and minimize operational costs while evaluating CCU deployment. Applied to Portugal's largest industrial park, the model identified 26 feasible symbiotic exchange routes involving 14 enterprises and 7 potential CCU technologies. Maximum material exchange optimization yields 3,042,107 ton/year across 26 symbiotic routes and 7 CCU units, achieving 89.8 % reduction in climate change impact (from 13.5 to 1.76 million CO2eq/year); Cost minimization achieves 2,223,298 ton/year with 27 % fewer exchanges, delivering 87.0 % environmental reduction and net revenue of €65.5M/year v... [more]

Model simulation flowsheet of biomass gasification combined cycle system for simultaneous power and hydrogen production coupled with direct air capture in Aspen Plus.

Isotherm data for CO2 and N2 adsorption for Fe3O4@HKUST1 (MOF) and Mass and Energy balance equations for Magnetic Inductive Swing Adsorption system.

The escalating urgency to address climate change has driven carbon capture (CC) technologies into the spotlight, particularly for large-scale emitters, which benefit from economies of scale. However, small-scale emitters account for a significant share of CO2 emissions, yet such applications remain largely overlooked in the literature. While CC cost is often used as a key performance indicator (KPI) for CC technologies, the lack of standardized cost estimation methods leads to inconsistencies, complicating comparisons, and hindering the deployment of CC systems. This study addresses these challenges by developing flexible short-cut correlations for selected CC technologies, providing estimates of the total equipment cost (TEC) and energy consumption specific to small-scale applications across various CO2 inlet concentrations (mol%) and capture scales (10 – 100 kt/y). The flexibility of the correlations enables the integration of various cost estimation methods available in the literatu... [more]

Algal biomass production, mineralization, and chemical conversion as promising carbon dioxide utilization processes are compared with regard to economic as well as environmental factors. The production of the chemicals methanol, dimethyl ether, and dimethyl carbonate is selected as the most viable alternative among all options. The integrated production of the proposed chemicals is evaluated for a wide range of trade-offs between economic potential and environmental impact by applying multi-objective superstructure optimization. The results indicate that direct hydrogenation of CO2 to methanol with subsequent dehydration to dimethyl ether is on the verge of profitability (including capture cost) while achieving a positive net CO2 consumption of ca. 68% of supplied CO2 when direct and indirect emissions are accounted for; and 85% when only direct emissions are considered.

A technical evaluation on the production of sustainable formaldehyde was presented in this report, including process design, advanced simulation, economic analysis, and environmental analysis. Three process configurations to produce formaldehyde were developed: a base-case with no capture of carbon, a post-combustion capture (PCC) process, which utilized 14 wt.% MEA solution-based process, and a direct air capture (DAC) route which used NaOH. Sequestered CO₂ was used as a major feedstock for methanol production via an electrocatalytic reactor (ECR), after which was converted into formaldehyde via a FORMOX process. Large-scale simulations were carried out, demonstrating a yearly methanol production capacity of approximately 62 million kilograms, with a fixed formaldehyde-to-methanol conversion ratio of 1.4 kg per kg of methanol. Economic models were developed using Aspen Process Economic Analyser, indicating that the base-case option (without capture) would involve a capital expenditure... [more]

Aspen Plus simulations for the conversion of CO2 into Formaldehyde and related processes.

GAMS models and supporting spreadsheets for Innovative Strategies in Sustainable Formaldehyde Production in Belgium: Integrating Process Optimisation, Carbon Capture, and a comprehensive Environmental Assessment.

This is the OpenLCA Database for Innovative Strategies in Sustainable Formaldehyde Production in Belgium: Integrating Process Optimisation, Carbon Capture, and a comprehensive Environmental Assessment.

Decarbonizing industries could significantly increase electricity demand, necessitating strategic grid expansion. This study evaluates the impact of decarbonizing the Pulp and Paper Sector under four 2050 scenarios: carbon capture, biomass-based, direct electrification, and indirect electrification. A bottom-up approach is employed to estimate 2020 final energy demand by heat grade and subsector. Both final and primary energy demand systems are modeled, accounting for the efficiencies of end-use technologies and primary energy transformation processes. The analysis compares primary renewable energy demand (electricity and biomass) normalized per ton of equivalent CO2 avoided against a business-as-usual scenario. It also considers the requirements for wood residues, organic waste, and CO2 storage. The carbon capture scenario, while low in electricity demand, requires significant organic waste for renewable natural gas production and 2.6 Mt of CO2 storage to offset direct and indirect em... [more]

Energy storage is essential for transitioning to a renewable system based on renewable sources. To meet this challenge, Power-to-X technologies are attracting more attention. This work explores converting the excess of electric energy obtained from wind or solar sources into hydrogen and then into methane leveraging existing natural gas infrastructure for easier storage and transport. The process involves two stages: Firstly, the methane production step using Power-to-X technologies during excess renewable energy periods and, secondly, the electricity generation step during high demand with CO2 capture for reuse in methane synthesis, forming a closed carbon loop. In this way the Power-to-X process is integrated with repurposed combined cycle power plants (CCPPs) creating a Power-to-methane-to-power system. Two approaches are evaluated: oxy-combustion, which simplifies process CO2 purification and air combustion, which needs a more complex CO2 purification, such as amine absorption or P... [more]

Anthropogenic carbon-dioxide emissions, exceeding 51 billion tons annually, are a major driver of global climate impacts. Aqueous amine scrubbing offers an effective carbon-capture solution, but the energy-intensive thermal regeneration step of the process significantly increases costs, limiting large-scale adoption. To address these challenges, computational optimization of process and molecular design is promising but often too resource-intensive, emphasizing the need for efficient surrogate models. Specifically, we develop a surrogate model based on an artificial neural network (ANN) that is employed to replace rigorous phase-equilibrium computations performed with the SAFT-? Mie group contribution method within a steady-state aqueous amine carbon-capture process model. Our ANN is trained on 32,768 vapour–liquid equilibrium data points of a quaternary mixture of water, monoethanolamine, carbon dioxide, and nitrogen over industrially relevant temperature, pressure, and composition ra... [more]

By 2050 around 12% of cumulative emissions reductions will come from Carbon Capture, Utilisation and Storage (CCUS) making it an essential component in the path towards net zero [1]. Focus will initially be on the retrofitting of fossil fuel power plants, which will shift to hard-to-decarbonise industries such as iron, steel, and concrete [1]. Such industries are often grouped together in industrial clusters. Comprising both large and small point sources concentrated over a defined geographical area, industrial clusters offer an opportunity to maximise the impact of CCUS whilst also improving economic feasibility [2]. The North Sea Port (NSP) cluster an example of this. Within the NSP cluster an initial set of five emitters are to join a capture, conditioning, and transport network by 2030. From there other emitters within the area will be able to join incrementally to 2050 [3]. However, the emitters who join and the timing of their connection will have a significant effect on the evo... [more]

In response to global efforts to reduce carbon emissions, the oil refining sector, a major source of industrial emissions, has set ambitious decarbonization targets. This study analyzes trade-offs between minimizing CO2 emissions and costs through the use of Pareto optimal solutions. A superstructure optimization framework evaluates various technological pathways and timelines, employing a bi-criterion optimization approach using the ?-constraint method. Results show that cost-effective, higher-emission solutions often involve natural gas-based technologies with carbon capture, while expensive, low-emission solutions favor electric power-based technologies. The analysis incorporates detailed assumptions about grid carbon intensity of varying degrees and accounts for varying national policies. Comparative case studies across locations highlight how grid carbon profiles influence optimal strategies, providing insights to inform local policies and incentivize technologies.

This study presents a gate-to-gate Life Cycle Assessment (LCA) evaluating the sustainability and environmental impacts of utilising CO2 for Enhanced Oil Recovery (EOR) in Dukhan Field. The assessment employs a detailed model that encompasses CO2 capturing, transportation, injection, and oil production processes. Utilising Gabi software, the study assesses CO2 emissions across different stages of the EOR process and evaluates the environmental efficiency using two functional units: '1 kg of CO2 captured' and '1 kg of oil produced'. Results indicate that Post-Combustion Capture (PCC) contributes the highest emissions, accounting for 76% of the total Global Warming Potential (GWP), while transportation pipelines and separators contribute only 2% and 4%, respectively. By Year 21, emissions drop by over 98%, with a corresponding GWP reduction from 4.73 billion kgCO2e in Year 1 to 94.97 million kgCO2e. Emission rates for CO2 capture and oil production also decrease significantly, reaching 0.... [more]

Integrated Carbon Capture and Conversion (ICCC) technologies offer an efficient alternative to conventional Carbon Capture, Utilization, and Storage (CCUS) methods by simultaneously capturing and converting CO2 into value-added chemicals. Dual-function materials (DFMs) are particularly promising due to their capability to integrate adsorption and catalysis in a single step, thereby reducing both energy consumption and associated costs. This study models the dynamic behavior of CO2 adsorption within a laboratory-scale packed-bed reactor employing DFMs. The mathematical model incorporates momentum, mass, and heat transfer equations, implemented using COMSOL Multiphysics v5.6, and evaluates various axial dispersion models (ADMs) and mass transfer coefficients (MTCs). The results indicate that the Rastegar-Gu ADM, combined with an MTC of 8.3 × 10-2 s-1, provides the most accurate representation of breakthrough and saturation times, as well as the total quantity adsorbed. Furthermore, relat... [more]

The escalating urgency to address climate change has driven carbon capture (CC) technologies into the spotlight, particularly for large-scale emitters, which benefit from economies of scale. However, small-scale emitters account for a significant share of CO2 emissions, yet such applica-tions remain largely overlooked in the literature. While CC cost is often used as a key perfor-mance indicator (KPI) for CC technologies, the lack of standardized cost estimation methods leads to inconsistencies, complicating comparisons, and hindering the deployment of CC sys-tems. This study addresses these challenges by developing flexible short-cut correlations for selected CC technologies, providing estimates of the total equipment cost (TEC) and energy consumption specific to small-scale applications across various CO2 inlet concentrations (mol%) and capture scales (10 – 100 kt/y). The flexibility of the correlations enables the integration of various cost estimation methods available in the liter... [more]