Conference Agenda

To achieve the ambitious goals set through various international agreements for climate change mitigation, it has become imperative for the chemical industry to transition to more sustainable production routes. Thus, life cycle assessment (LCA) has emerged as a tool to compare the environmental performance of alternative production pathways. However, traditional LCA methodologies (such as the Environmental Footprint (EF) impact assessment method (European Commission, 2017)) provide limited insights on the sustainability performance of a process in absolute terms. Recently, it was proposed to overcome this limitation by capitalizing on the planetary boundaries (PBs) framework, which defines a set of thresholds on nine Earth system processes delimiting the Earth’s ‘safe operating space’ (SOS). Transgressing the SOS could lead to detrimental effects that could shift the current equilibrium state of the Earth (Rockström et al., 2009). Building on this concept, Sala et al. (2020) recently developed a framework linking the PBs and the EF method to five Sustainable Development Goals (SDGs). While the SDGs were adopted in 2015 to assist policymakers in addressing key challenges facing humanity, their inclusion in process design has not been explored yet. Further, while LCAs are often carried out assuming that socio-economic systems will remain the same in future, they may greatly change due to learning curves and ongoing efforts to meet climate goals. In this regard, prospective LCAs leveraging the outcomes of integrated assessment models (IAMs) have recently emerged to assess the sustainability performance of industrial systems in future.

Here, capitalizing on the framework developed by Sala et al. (2020) and our previous work on hybrid modeling using Bayesian symbolic regression (Jog et al., 2024), we develop a process design framework accounting for the environmental process performance in terms of the contribution to attaining the SDGs. This approach is applied to the bi-objective optimization of the CO₂ hydrogenation to methanol process, considering economic and SDGs-based performance as the objective functions. Comparing with the business‑as‑usual process, we find that while the CO_­2­ hydrogenation process stays within the SOS linked to SDG 13 (i.e., climate action), burden-shifting leads to worsening of other impact categories. However, a prospective process design for the year 2050 shows that this collateral damage is drastically reduced due to expected improvements across economic sectors. Overall, this work emphasizes the need to evaluate environmental impacts beyond climate change in the transition to sustainable chemicals production, also showcasing the advantages of using hybrid modeling for efficient computation of the Pareto frontier.

References

European Commission (EC). PEFCR Guidance Document - Guidance for the Development of Product Environmental Footprint Category Rules (PEFCRs), version 6.3; European Commission, 2017, http://ec.europa.eu/environment/eussd/smgp/pdf/PEFCR_guidance_v6.3.pdf. (accessed July 28, 2024).

Jog, S., Vázquez, D., Santos, L.F., Caballero, J.A., Guillén-Gosálbez, G., 2024. Hybrid analytical surrogate-based process optimization via Bayesian symbolic regression. Comput. Chem. Eng. 182, 108563. https://doi.org/10.1016/j.compchemeng.2023.108563

Rockström, J. et al., 2009. A safe operating space for humanity. Nature 461, 472–475. https://doi.org/10.1038/461472a

Sala, S., Crenna, E., Secchi, M., Sanyé-Mengual, E., 2020. Environmental sustainability of European production and consumption assessed against planetary boundaries. J. Environ. Manage. 269, 110686. https://doi.org/10.1016/j.jenvman.2020.110686

The transition towards climate-neutral societies demands innovative solutions to mitigate carbon emissions, particularly in energy-intensive industries. This study explores sustainable-by-design approaches to clinker production and Power-to-X (PtX) technologies by applying learning effects to forecast their environmental impacts through prospective life cycle assessments (pLCA). Incumbent clinker production practices fall short of meeting carbon-neutral targets, pressing the need to implement waste valorization and CO₂ utilization strategies. Yet, knowledge gaps persist on the future environmental performance of alternative clinker manufacturing and emerging PtX solutions.

To address these gaps, this study examines the prospective life cycle impacts of (1) solid recovered fuel (SRF) utilization as a substitute for fossil fuels in clinker production and (2) Power-to-Methanol (PtM) technology, which converts renewable electricity and captured CO₂ into methanol. By applying environmental learning effects, the environmental impacts of these systems are projected between 2025 and 2050, considering shared socioeconomic pathways (SSP1, SSP2) and the 1.9 W m⁻² representative concentration pathway (SSP2-RCP1.9). First-of-a-kind (FOAK) and n^th-of-a-kind (NOAK) PtM plants are modeled using the ASPEN Plus V14 software, capturing environmental learning effects through process optimization and scale-up. SimaPro 9.3.0.3 and the ReCiPe 2016 method are used to conduct life cycle impact assessments. Environmental learning rates, ranging from 4% to 34%, indicate substantial opportunities for improved environmental performance, with NOAK configurations achieving lower energy consumption and reduced production costs. This highlights the importance of integrating technological advancements in both the foreground and background life cycle inventories. The highest decarbonization progress is observed under the SSP2-RCP1.9 trajectory, driven by emissions avoided from waste management systems, the conversion of biogenic carbon-rich municipal solid waste, and CO₂ upgrading. The results also highlight the potential for burden-shifting, such as land transformation and eutrophication (+26.9% and +5.1% by 2050), pointing to the need to adjust emission mitigation strategies.

The combined findings from these prospective assessments emphasize the critical role of environmental learning effects in driving sustainability performance in early-stage design and process engineering. By incorporating quantified learning rates into pLCA, this study provides essential insights for decision-makers, underscoring the value of continuous innovation and scale-up to achieve climate goals in cement manufacturing and methanol production. Together, these advancements represent a significant step toward a more sustainable and carbon-neutral industrial future.

Trichlorosilane (TCS) is a key platform chemical used in the manufacture of silicon metals, silicones, and functional silanes. Despite this, very little information is available on the environmental impact (EI) associated with TCS manufacture. This is highly undesirable given the production volume of TCS and the manufacturing supply chains dependent upon it.

One reason for the lack of information on the EI of TCS is its variable production history¹. For instance, technical grade TCS (TG-TCS, ~98wt%) can be produced from a direct chlorination (DC) process, or as a co-product of the Siemens process². Though EI information is not available for production by either of these processes, a significant amount of process design information is¹; thus, process modelling could be used to accurately predict the EI of TG-TCS via Life Cycle Assessment (LCA)³.

This study addresses gaps in understanding for the EI of TG-TCS. An LCA model has been developed to quantify this impact in terms of the Global Warming Potential (ReCiPe 2016 ‘H’ method⁴) associated with producing TG-TCS; both the direct (DC) and indirect (Siemens) process approaches are considered. The functional unit used is one kilogram of TG-TCS.

To produce robust research findings, a combination of process modelling (Aspen Plus V11) and technoeconomic analysis is used to identify economic operating conditions at which TG-TCS is likely produced. This is coupled with LCA and a bi-objective optimization method (NSGA-II algorithm⁵) to simultaneously identify minimal EI possible for manufacturing TG-TCS.

Findings demonstrate the ability to manufacture TG-TCS profitably with GWP in the range of 1.5 to 2.3 kg_CO2-eq per year. Moreover, from results of bi-objective optimization, pareto frontiers are used to highlight how the minimum achievable process impact varies as a function of process profitability. Finally, a comparison of impact associated with production according to direct (DC) and indirect (Siemens) processing routes are then used to discuss the effect of processing history on overall environmental impact of the TCS product. Results are of interest to the EI of any field relying on TG-TCS manufacture.

References

[1] Simmler, W. 2000. “Silicon Compounds, Inorganic”. In Ullmann's Encyclopedia of Industrial Chemistry.

[2] Ramírez-Márquez, César, et al. "Process design and intensification for the production of solar grade silicon." Journal of Cleaner Production 170 (2018): 1579-1593.

[3] Parvatker, A.G. and Eckelman, M.J. 2018. Comparative evaluation of chemical life cycle inventory generation methods and implications for life cycle assessment results. ACS Sustainable Chemistry & Engineering 7.1, pp. 350-367.

[4] Huijbregts, M. A.J., et al. 2016. ReCiPe 2016: a harmonized life cycle impact assessment method at midpoint and endpoint level report I: characterization.

[5] Deb, Kalyanmoy, et al. "A fast and elitist multiobjective genetic algorithm: NSGA-II." IEEE transactions on evolutionary computation 6.2 (2002): 182-197.

Plastics are indispensable materials in modern society, primarily used in packaging, textiles, and the transportation industries. The building blocks of plastics, olefins, are currently produced using fossil fuels, with naphtha—a refinery product—as the main feedstock. The most common process, steam naphtha cracking, demands significant energy inputs, which are supplied by the combustion of natural gas. Consequently, the process is vulnerable to fluctuations in the supply of crude oil and is responsible of 30% of the total CO₂ emissions in the chemicals industry. One possible alternative to naphtha cracking is the waste gasification, which produces syngas that can then be used for methanol synthesis and further through the methanol-to-olefins (MTO) process to produce olefins. Specifically, carbon-rich plastic waste can serve as the feedstock, supporting a circular economy and providing a solution for both plastic waste treatment and olefin production. Plastics can be co-gasified with biomass within autothermal or plasma configuration gasifiers. In addition, other strategies aiming at improving the efficiency and sustainability of this alternative process, such as CO₂ capture, and storage technologies are investigated. Seasonal CO₂ storage can enable cost-effective production, allowing for increased capacity during periods when renewable energy is abundant, and electricity is cheaper. CO₂ can be valorized in various ways, such as through injection, methanation, or syngas production via the rWGS reaction or co-electrolysis with water. Each of these options requires different processing conditions leading to distinct overall process performance. The hydrogen needed for methanation and rWGS reactions can be supplied by integrating a SOEC. Gasification is also a high energy demand process, after which the waste heat could be recovered for electricity generation trough steam cycles. Those configurations were compared in light of thermodynamic, economic and environmental key performance indicators. As a result, with the integrated energy systems and CO₂ valorization methods, the overall process efficiency can reach up to 99%, nearly doubling the production capacity from the same feedstock amount while eliminating direct CO₂ emissions. The specific energy requirement of the suggested configurations has increased by 2 to 2.5 times compared to traditional SNC, with the entire energy demand shifted to electricity requirements, making the process independent from fossil fuels. This shift underscores the critical importance of renewable energy sources, as the process depends on the widespread availability of clean electricity to fully realize its environmental benefits. The proposed configurations establish a circular economy with no additional CO₂ emissions with maximized efficiency, being a promising solution in future scenarios of high renewable energy availability.