Conference Agenda

The Net Zero target accelerates the energy transition, leading to the rapid development of technologies employing renewable energy. Hydrogen, as a popular energy carrier from renewable energy storage for alleviating the intermittency of renewables, can be further converted to ammonia for the advantages of cost-effective transportation and storage and well-established infrastructure of ammonia. Moreover, ammonia itself is a valuable chemicals as a vital raw material for fertiliser production, refrigerant in cryogenic technologies, solvent for carbon capture process, etc. We have designed a green ammonia production system driven by renewable energy. This system integrated a hydrogen generation process employing PEM water electrolysis, a nitrogen generation process from flue gas recovery, and an ammonia synthesis by the Haber-Bosch Process. In particular, flue gas was treated by an amine-based carbon capture process for nitrogen enrichment and further carbon reduction. The integrated processes were simulated and optimised in Aspen Plus in both sequential modular and equation-oriented modes for optimal operating conditions. However, the convergence difficulty limited the optimised variables. In this work, we will develop a mathematical model for further optimisation in GAMS. The objective is to minimise the levelized cost of ammonia while considering the heat exchanger networks. The resulting outputs will be sent to the model in Aspen Plus for validation.

The growing concern over climate change and increasing carbon dioxide (CO₂) emissions has driven the development of advanced strategies for mitigating greenhouse gases in the atmosphere. One promising avenue is the synthesis of green methanol (CH₃OH) through the catalytic hydrogenation of captured CO₂ using renewable hydrogen (H₂). This process not only provides a valuable chemical feedstock with diverse applications in fuel production and industrial processes but also contributes to the reduction of atmospheric CO₂ levels. Recent advancements in CO₂ capture technologies allow for the extraction of CO₂ with purities ranging from 70% to 98% (Raganati et al., 2021). Integrating efficient CO₂ capture technologies with the use of green hydrogen establishes the production of green methanol as a practical and sustainable solution for addressing the challenges posed by climate change.

However, while previous studies have predominantly focused on CO₂ compositions greater than 96% in the synthesis of methanol (Djettene et al., 2024; Pérez-Fortes et al., 2015; Jeong et al., 2022), these high-purity models fail to account for the more variable and lower purity CO₂ streams often encountered in real industrial carbon capture applications. This gap highlights the need for a more comprehensive analysis that reflects actual conditions.

The novelty of this study lies in its det ailed exploration of the economic implications of CO₂ purity within the methanol production process. By modeling and simulating the hydrogenation process to methanol using Aspen Hysys V14, this study analyzes the effects of differing CO₂ purities on key performance indicators such as operational cost, yield, and overall profitability. This approach provides a more realistic assessment of methanol production under varying CO₂ conditions, which has not been thoroughly investigated in previous literature.

The findings demonstrate that even small variations in CO₂ purity can significantly impact both operational costs and profitability, underscoring the necessity of optimizing CO₂ capture technologies for methanol production. This study contributes to the existing body of knowledge by quantifying the relationship between CO₂ purity and economic performance, offering critical insights for future optimization strategies. As such, it emphasizes the crucial role that CO₂ purity plays in enhancing both the sustainability and economic viability of green methanol production within the broader context of climate change mitigation.

References:

Raganati, F., Miccio, F., & Ammendola, P. (2021). Adsorption of carbon dioxide for post-combustion capture: A review. Energy & Fuels, 35(16), 12845–12868. https://doi.org/10.1021/acs.energyfuels.1c01618

Djettene, R., Dubois, L., Duprez, M., De Weireld, G., & Thomas, D. (2024). Integrated CO2 capture and conversion into methanol units: Assessing techno-economic and environmental aspects compared to CO2 into SNG alternative. Journal of CO2 Utilization, 85, 102879. https://doi.org/10.1016/j.jcou.2024.102879

Pérez-Fortes, M., Schöneberger, J. C., Boulamanti, A., & Tzimas, E. (2015). Methanol synthesis using captured CO2 as raw material: Techno-economic and environmental assessment. Applied Energy, 161, 718–732. https://doi.org/10.1016/j.apenergy.2015.07.067

Jeong, J. H., Kim, Y., Oh, S., Park, M., & Lee, W. B. (2022). Modeling of a methanol synthesis process to utilize CO2 in the exhaust gas from an engine plant. Korean Journal of Chemical Engineering, 39(8), 1989–1998. https://doi.org/10.1007/s11814-022-1124-1

Current environmental challenges necessitate the mitigation of CO2 emissions. However, CO2 emissions from certain industries are projected to remain significant in the foreseeable future. CO2 utilization is a promising approach to reduce atmospheric CO2 by using it as a feedstock to produce valuable products¹. Process intensification by in-situ water separation is a promising concept that enables the development of novel CO2 utilization pathways, as most CO2 utilization processes produce water as a byproduct. Packed bed membrane reactors (PBMRs) combine catalytic reactions of CO2 with selective separation through permeable membranes, based on zeolites, such as LTA, carbon or other materials.

Among the various CO2 utilization pathways, the reverse water gas shift (RWGS) reaction is crucial as it produces syngas, which can further be used to synthesize various products such as methanol, DME and aviation fuels. Despite its importance, the RWGS reaction remains underexplored by rigorous modeling, simulation and optimization. Some of RWGS-PBMR models exist, but they often oversimplify membrane characteristics (i.e. assume constant permeance) and overlook some practical aspects (e.g. use nitrogen as sweep).

In this work we have developed a multi-scale model to study the potential of LTA-membrane reactors for CO2 utilization processes. A detailed microscale membrane permeance model is combined with a reactor-scale model and used as a block in a fully integrated process-scale model. The permeance model predicts the impact of operating temperature, pressure and gas phase composition on water permeance and the perm-selectivity to other relevant species, based on the trans-membrane flux described as the sum of gas translation and surface adsorption diffusion². Simulations reveal significant changes in membrane permeance under different gas compositions and operating temperatures, highlighting the necessity of incorporating the membrane permeance model into the reactor design.

The effect of various design and operational parameters is evaluated, including membrane perm-selectivity for different species, pressure and flow rate ratios between the retentate and permeate sides, and sweep gases. It is concluded that high pressure and flow rate ratios generally have a positive effect on reactor performance, but assuming excessively high ratios is not always ideal due to diminishing returns. An optimal value for the membrane selectivity is revealed for some configuration, i.e., a higher value is not necessarily better. The membrane reactor model is linked to Aspen Hysys process simulation to evaluate the energy efficiency, yield and other integrated process attributes. A process configuration, which involves recycling the dried retentate flow as sweep gas through the permeate side, is proposed and compared to other process configurations suggested in the literature. These process considerations will be analyzed and discussed.

Reference:

1. M. Patrascu, Process intensification for decentralized production, Chem. Eng. Process. - Process Intensif. 184 (2023) 109291, http://dx.doi.org/10.1016/j.cep.2023.109291.
2. Zito, P. F., Brunetti, A., Caravella, A., Drioli, E., & Barbieri, G. (2019). Water vapor permeation and its influence on gases through a zeolite-4A membrane. Journal of Membrane Science, 574, 154–163. https://doi.org/10.1016/j.memsci.2018.12.065.

Global efforts to adopt cleaner-burning, low-CO2 fuels have accelerated, with hydrogen (H2) emerging as a promising option since its only byproduct is water vapor. Green hydrogen, produced via water electrolysis powered by renewable energy sources like solar or wind, has gained significant focus [1]. However, large-scale hydrogen storage faces major challenges due to its limitations. Gaseous compression and liquefaction are both energy-intensive and costly, while compressed hydrogen storage presents safety risks. For hydrogen to become a mainstream fuel, technical hurdles related to safe, energy-efficient storage for both stationary and mobile applications must be overcome.

This contribution introduces a solid-state hydrogen storage and release system based on the reversible iron oxide/iron thermochemical redox mechanism. In this process, magnetite (Fe3O4) undergoes an endothermic reduction with hydrogen, producing pure iron and water vapor. The reaction is reversible, allowing hydrogen recovery when iron reacts with steam to reform magnetite and release H2. Iron oxide/iron is an attractive candidate for large-scale hydrogen storage due to its abundance, low cost, non-toxicity, and lower energy requirements compared to other metal oxides [2]. Despite its potential, the system's high operating temperature (≥ 420°C), low storage density, and slow charging/discharging rates limit its suitability for mobile applications like hydrogen fuel cell vehicles (FCVs) [3].

To address these challenges, a custom thermochemical equilibrium model was developed using NIST thermochemistry data. This model predicted the equilibrium conversion of hydrogen to steam and the corresponding heat input required as a function of reaction temperature. Simulation results revealed a trade-off between the two main objectives: maximising equilibrium conversion and minimising heat input during the forward reaction. A multi-objective optimisation study demonstrated a preference for prioritising energy efficiency. Overall, the findings provided invaluable insights on setting the optimal process conditions and configuration of this thermochemical storage approach.

REFERENCES

[1] Raghu Raman, Vinith Kumar Nair, Veda Prakash, Anand Patwardhan, Prema Nedungadi, Green-hydrogen research: What have we achieved, and where are we going? Bibliometrics analysis, Energy Reports, 2022, 8, 9242–9260.

[2] L. Brinkman, B. Bulfin, and A. Steinfeld, Thermochemical Hydrogen Storage via the Reversible Reduction and Oxidation of Metal Oxides, Energy Fuels, 2021, 35, 18756-18767.

[3] K. Otsuka, C. Yamada, T. Kaburagi, S. Takenaka, Hydrogen storage and production by redox of iron oxide for polymer electrolyte fuel cell vehicles, International Journal of Hydrogen Energy 2003, 28, 335-342.

Abstract

The chemical industry has the highest energy demand across industrial sectors, primarily due to its heavy reliance on fossil fuels for both feedstock and utilities. Specifically, the industry consumes ca. 14% and 8% of the global oil and gas supply, respectively, contributing to 5.6 Gt CO₂e emissions annually (including both direct and indirect emissions), which accounts for 10% of global greenhouse gas emissions (Bauer et al., 2023). To meet the ambitious targets set by the Paris Climate Agreement, numerous studies in recent years have focused on reducing CO₂ emissions from chemical production. Techno‑economic and environmental studies, in particular, have gained wide attention in identifying more sustainable production pathways, with life cycle assessment emerging as the prevalent tool for environmental impact assessments. However, most of the studies consider fixed background data, neglecting the effects that the future evolution of socio‑economic systems could have on the chemical sector.

Propanol is a platform chemical with an annual demand of 4 Mt and a growth rate of 5%. Currently, propanol production relies on syngas and ethylene derived from fossil fuels, specifically from natural gas and naphtha, respectively (Vo et al., 2021). Consequently, the fossil‑based production route for propanol results in significant environmental burdens. An alternative to the fossil‑based route relies on using syngas from captured CO₂ and renewable‑powered electrolytic hydrogen via the reverse water‑gas shift reaction. Alternatively, renewable carbon feedstocks such as biomass, biomethane, and plastics could also be used to produce syngas for propanol production. To date, the economic and environmental benefits of these alternative propanol production routes remain unexplored.

To fill this critical research gap, we analyse sustainable routes for producing propanol by conducting a techno‑economic and prospective life cycle assessment to evaluate both their current and future environmental impacts. To this end, we develop detailed process simulations using Aspen HYSYS® v12.1 to quantify the process’s economic and environmental performance. For the environmental assessment, foreground data are extracted from the process simulation, while background inventories are obtained from Ecoinvent v3.10 using Brightway2.5 v1.0.6. Moreover, to perform a prospective life cycle assessment, we employ the premise v2.1.2 framework to model future background data using the IMAGE Integrated Assessment Model, following the shared socioeconomic pathway SSP2 (i.e., ‘middle‑of‑the‑road’) under different representative concentration pathways (RCPs). Overall, our results indicate that the biomass‑based alternatives demonstrate the best economic and environmental performance. Furthermore, we find that using prospective LCA data can greatly affect the outcome of the analysis, reinforcing the need to accompany standard LCAs with prospective studies to obtain a more comprehensive picture of the process’s potential.

References

Bauer, F., Tilsted, J.P., Pfister, S., Oberschelp, C., Kulionis, V., 2023. Mapping GHG emissions and prospects for renewable energy in the chemical industry. Curr. Opin. Chem. Eng. 39, 100881. https://doi.org/10.1016/j.coche.2022.100881

Vo, C.H., Mondelli, C., Hamedi, H., Pérez-Ramírez, J., Farooq, S., Karimi, I.A., 2021. Sustainability Assessment of Thermocatalytic Conversion of CO₂ to Transportation Fuels, Methanol, and 1-Propanol. ACS Sustain. Chem. Eng. 9, 10591–10600. https://doi.org/10.1021/acssuschemeng.1c02805

Plastics are indispensable in modern commerce and industry, with their consumption projected to double in the next 20 years, according to the European Environmental Agency (EEA) [1]. However, the environmental persistence of plastics and associated greenhouse gas (GHG) emissions are escalating concerns.

Currently, most plastic recycling in Europe is mechanical, which is energy-intensive, inefficient at removing contaminants, and produces secondary-grade outputs. Solvent-based polymer dissolution is emerging as a promising solution, potentially reducing CO₂ emissions by 65-75% per ton of plastic waste compared to incineration [2].

In this study we present a novel computer-aided molecular design (CAMD) formulation for selecting optimal solvents for polymer recycling via dissolution and precipitation. Polyethylene, which is found in heavily contaminated multilayer plastic films, is chosen as a case study polymer as it is well-suited to recycling using the dissolution and precipitation method. A mixed-integer nonlinear programming (MINLP) model is proposed to minimise the heat of dissolution for commercial polyethylene while considering solvent properties such as latent heat and toxicity.

Solubility plays a key role in determining the performance of the process but literature data are only available for a limited number of solvents. We employ the predictive SAFT-γ Mie [3] equation of state for the first time to describe polymer-solvent mixtures in the context of plastic recycling. This thermodynamic model, with its group contribution approach, can accurately model various solvent systems with a minimal number of parameters and experimental data. SAFT- Mie is used to predict polyethylene solubility in numerous solvents and assess polymer-solvent miscibility. We extend the current development of our model to consider green solvents such as cymene and deep eutectic solvents. Our SAFT-γ Mie predictions of polyethylene solubility show good agreement with experimental data.

In the CAMD, we consider a range of organic solvents with diverse molecular structures, including aromatic molecules like toluene and p-xylene, bi-cyclic compounds, such as decalin and ketones methyl ethyl ketone (MEK), and ethyl acetate, which are associating molecules. Additionally, bioderived solvents such as cymene and dibutoxymethane are included in the design space.

The MINLP is solved to generate a ranked list of potential solvents and associated process conditions for dissolving low-density polyethylene, one of the most prevalent polymers in industrial and municipal plastic waste. This study provides valuable insights into the selection of optimal solvents for polyethylene dissolution, advancing the design of more efficient recycling processes.

[1] European Environment Agency, Reichel, A., Trier, X., Fernandez, R. et al. (2021) Plastics, the circular economy and Europe's environment : a priority for action. Publications Office. https://data.europa.eu/doi/10.2800/5847

[2] I. Vollmer et al., ‘Beyond Mechanical Recycling: Giving New Life to Plastic Waste’, Angew. Chem. Int. Ed., vol. 59, no. 36, pp. 15402–15423, 2020, doi: 10.1002/anie.201915651.

[3] A. J. Haslam et al., ‘Expanding the Applications of the SAFT-γ Mie Group-Contribution Equation of State: Prediction of Thermodynamic Properties and Phase Behavior of Mixtures’, J. Chem. Eng. Data, vol. 65, no. 12, pp. 5862–5890, Dec. 2020, doi: 10.1021/acs.jced.0c00746.