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]

Herein, the Aspen models to the paper "Chemical recycling of plastic waste via production of ethylene from gasification syngas" are published. The model starts at syngas, as gasification was not modeled in Aspen Plus. Syngas is treated and fed into a methanation reactor. Ethylene is then produced via oxidative coupling of methane. The fractionation involves cryogenic distillation as well as CO2 capture. Latter one was modeled in a separate file.

The overarching goal of process design (Figure 1) is to find technologically feasible, operable, economically attractive, safe and sustainable processing pathways and process configurations with specifications for the connectivity and design of unit operations that perform a set of tasks using selected functional materials (e.g., catalysts, solvents, sorbents, etc.) to convert a set of feed-stocks or raw materials into a set of products with desired quality at a scale that satisfies the demand. Process synthesis and integration can further screen, optimize and improve these pathways for given techno-econo-environmental targets or objectives. These objectives may include, but are not limited to, minimizing the overall investment and processing costs, minimizing the energy consumption, minimizing the emissions or wastes, maxim-zing the profit, and enhancing the safety, operability, controllability, flexibility, circularity, and sustainability, among others... (ABSTRACT ABBREVIATED)

We present the implementation of combined junior course projects encompassing three core courses: reaction engineering, separations, and process simulation and design. The combined project aims to enhance the vertical integration of process design learning through all levels of the curriculum. We design the projects to utilize novel modular process technologies (e.g., membrane separation) and to emphasize new process design goals (e.g., sustainability, decarbonization). Two example projects, respectively on green methanol synthesis and ethylene oxide production, are showcased for project implementation. Feedback from junior and senior students is also presented to motivate the development of such joint project in CHE curriculum. We will also discuss the challenges we hope to address to maximize student learning from this unique project.

Carbon capture is a promising option to mitigate CO2 emissions from existing coal-fired power plants, cement and steel industries, and petrochemical complexes. Among the available technologies, membrane-based carbon capture presents the lowest energy consumption, operating costs, and carbon footprint. In addition, membrane processes have important operational flexibility and response times. On the other hand, the major challenges to widespread application of this technology are related to reducing capital costs and improving membrane stability and durability. To upscale the technology into stacked flat sheet configurations, high-fidelity computational fluid dynamics (CFD) that describes the separation process accurately are required. High-fidelity simulations are effective in studying the complex transport phenomena in membrane systems. In addition, obtaining high CO2 recovery percentages and product purity requires a multi-stage membrane process, where the optimal network configuratio... [more]

In response to the global imperative to address climate change, this research focuses on enhancing the transparency and efficiency of the Carbon Capture Utilization and Storage (CCUS) supply chain under carbon tax. We propose a decision-making framework that integrates the CCUS supply chain's optimization model, emphasizing carbon tax policies, with a blockchain network. Smart contracts play a pivotal role in automating the exchange and utilization of carbon emissions, enhancing the digitalization of the CCUS supply chain from source to sink. This automation facilitates seamless matching of carbon sources with sinks, efficient transfer of emissions and funds besides record-keeping of transactions. Consequently, it improves the monitoring, reporting, and verification processes within the CCUS framework, thereby simplifying compliance with regulatory mandates for net emission reductions and carbon taxation policies. By eliminating reliance on third-party verifiers, our blockchain-based... [more]

Inspired by Nature, we propose that synergies between biorefinery and mineral refinery can be exploited so that at least a part of the carbon is captured before being released to the atmosphere. In doing so, carbon is captured not only from CO2 but also from biomass and developing more such processes may be the cornerstone for controlling CO2 emissions. A comparison of circular economy in traditional biorefineries and bio-mineral refineries is done by using general chemical formulas and it is shown that the bio-mineral refinery captures carbon. In this work, we have shown that Serpentine may be used to partially neutralise biomass pyrolysis oil. The extracted oil may be used as feedstock to produce downstream chemicals and further studies are required to produce the same.

Some of the most highly trusted and ubiquitous process simulators have solution methods that are incompatible with algorithms designed for equation-oriented optimization. The natively unconstrained Efficient Global Optimization (EGO) algorithm approximates a black-box simulation with kriging surrogate models to convert the simulation results into a reduced-order model more suitable for optimization. This work evaluates several established constraint-handling approaches for EGO to compare their accuracy, computational efficiency, and reliability using an example simulation of an amine post-combustion carbon capture process. While each approach returned a feasible operating point in the number of iterations provided, none of them effectively converged to a solution, exploring the search space without effectively exploiting promising regions. Using the product of expected improvement and probability of feasibility as next point selection criteria resulted in the best solution value and re... [more]

Aiming to mitigate the environmental impact derived from fossil fuels, we propose an integrated carbon capture-biomass gasification process is proposed to produce low-carbon hydrogen as an alternative energy carrier. The process begins with the pre-treatment of empty fruit bunches (EFB), involving grinding, drying, torrefaction, and pelletization. The resulting EFB pellet is then fed into a dual gasifier, followed by a catalytic cracking of tar and water gas shift reaction to produce syngas, aiming to increase its H2 to CO ratio. Subsequently, we explore two alternatives (DEPG and MEA) for syngas upgrading by removing CO2. Finally, a PSA system is modeled to obtain H2 at 99.9% purity. The pre-treatment stage densifies the biomass from an initial composition (%C 46.47, %H 6.22, %O 42.25) to (%C 54.10, %H 6.09, %O 28.67). The dual gasifier operates at 800°C, using steam as a gasifying agent. The resulting syngas has a volume concentration (%CO 20.0, %CO2 28.2, %H2 42.2, %CH4 5.9). Next s... [more]

The transition to net-zero greenhouse gas emissions requires a rapid redesign of energy systems. However, the redesign may shift environmental impacts to other categories than climate change. To assess the sustainability of the resulting impacts, the planetary boundaries framework provides absolute limits for environmental sustainability. This study uses the planetary boundaries framework to assess net-zero sector-coupled energy system designs for absolute environmental sustainability. Considering Germany as a case study, we extend the common focus on climate change in sustainable energy system design to seven additional Earth-system processes crucial for maintaining conditions favorable to human well-being. Our assessment reveals that transitioning to net-zero greenhouse gas emissions reduces many environmental impacts but is not equivalent to sustainability, as all net-zero designs transgress at least one planetary boundary. However, the environmental impacts vary substantially betwe... [more]

An important measure to achieve global reduction in CO2 emissions is CO2 capture, transport, and storage. The deployment of CO2 capture requires the development of a shared CO2 transport infrastructure, where CO2 can be transported with different transport modes. Furthermore, the cost of CO2 transport can be subject to significant economies of scale effects with respect to the amount of CO2 transported, also mentioned as clustering effects. Therefore, optimizing the shared infrastructure of multiple CO2 sources can lead to significant reductions in infrastructure costs. This paper presents a novel formulation of the clustered CO2 transport network. The Markov Decision Process formulation defined here allows for more detailed modeling of non-linear, discrete transport costs and increased geographical resolution. The clustering effects are modeled through cooperative multi-agent interactions. A multi-agent, reinforcement learning-based algorithm is proposed to optimize the shared transpo... [more]

Post-combustion carbon capture technologies have the potential to contribute significantly to achieving the environmental goals of reducing CO2 emissions in the short term. However, these technologies are energy and cost-intensive, and the variability of flue gas represents important challenges. The optimal design and optimization of such systems are critical to reaching the net zero and net negative goals, in this context, the use of computer-aided process design can be very effective in overcoming these issues. In this study, we explore the implementation of carbon capture technologies within an industrial complex, by considering the pooling of CO2 streams. We present an optimization formulation to design carbon capture plants with the goal of enhancing efficiency and minimizing the capture costs. Capital and operating costs are represented via surrogate models (SMs) that are trained using rigorous process models in Aspen Plus, each data point is obtained by solving an optimization p... [more]