Environmental sustainability is increasingly recognized as a critical consideration in pharmaceutical development, yet it is rarely incorporated at the scale of molecular-level design. This study introduces a strategy to predict cradle-to-gate indicators that can be flexibly incorporated into multiple early-stage molecular prioritization scenarios. A dataset of 150 pharmaceutical-relevant molecules was compiled, with each molecule described by structural descriptors, thermophysical properties, and ReCiPe endpoint indicators representing human health, ecosystem quality, and resource scarcity. A dual-branch multi-task model combining graph-based and descriptor-based representations was trained to predict these three endpoint indicators. Model performance was evaluated through validation metrics, local sensitivity analysis, and SHAP-based interpretability. A case study with solubility-based feasibility constraints was then used to illustrate how different sustainability weighting schemes... [more]

Accurate life cycle assessment (LCA) depends on robust characterization factors (CFs), which quantify impacts such as ecotoxicity through the integration of fate (FF), exposure (XF), and effect (EF) factors. While databases such as USEtox and Ecoinvent provide essential CFs, significant data gaps remain, particularly in ecotoxicity endpoints like hazardous concentration 50% (HC_50), which directly inform effect factor calculations. Existing machine learning models can predict such values, but they often lack interpretability, which limits trust and transparency in environmental modeling. To address this, a machine learning framework is applied that utilizes symbolic regression (SR) and genetic programming (GP) to predict missing HC_50 values from physicochemical descriptors. A dataset with 14 descriptors was used to train SR models capable of generating interpretable mathematical expressions that link chemical properties to HC_50 values. SR models were benchmarked against prominent bla... [more]

Direct air capture is gaining significant interest due to its potential to achieve carbon-negative emissions. With the aim to reduce the energy consumption and in line with the electrification of chemical processes, the absorption direct air capture system is integrated into a bipolar membrane electrodialysis cell stack for solvent regeneration and carbon dioxide release. The scheme solution is characterized by carbon dioxide bubbles inside the cell reducing efficiency so that other regeneration schemes have been proposed in the literature. A direct comparison of those is missing in the existing state of the art: the present work wants to fill this gap. In addition to the above process, the reaction of the rich solution with a weak organic acid and the use of both nanofiltration and reverse osmosis membranes are considered in other process schemes. The three case studies are modelled in Aspen Plus software with the aim to compare the energy consumption and total cost while the environm... [more]

Recent advances in computer-aided retrosynthesis (CAR), flow chemistry, and continuous manufacturing collectively offer new opportunities to enable environmentally sustainable development and manufacturing practices across the pharmaceutical development and manufacturing value chain. However, the implementation of these methods and technologies remains scattered and fragmented, preventing full realization of their potential to address one of the most urgent needs in the pharmaceutical and related sectors. This work introduces a holistic digital framework for the design and optimization of an end-to-end manufacturing process for paracetamol (acetaminophen). The framework integrates Green-by-Design synthetic and purification routes of the active pharmaceutical ingredient (API) aims to deliver cost efficiency and robust quality, safety, and environmental sustainability assurance. The approach integrates AI-driven CAR with plant wide modelling, Techno-Economic Analysis (TEA), and prospecti... [more]

Early-stage system-level assessment of emerging technologies is essential for achieving climate neutrality and a circular economy; however, such assessments are often constrained by the lack of representative life cycle inventory data. In thermal energy systems, performance strongly depends on scale, making direct application of laboratory- or bench-scale experimental data potentially misleading in life cycle assessment (LCA). This study investigates the influence of experimental scale on system-level evaluation using a zeolite-based thermal energy storage (TES) system as a case study.LCAs were conducted using performance data from laboratory-, bench-, and pilot-scale experiments and compared with predicted commercial-scale performance derived from numerical simulations. The TES system stores waste heat via water vapor desorption from zeolite and generates pressurized steam using a moving-bed with indirect heat exchanging system. Heat recovery ratios of 36%, 50%, and 61% were obtained... [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]

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]

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]

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]

The transition from a linear, fossil-based polymer economy to a circular bio-economy is critical for mitigating resource depletion and greenhouse gas emissions. This study provides a rigorous comparison of two biomass-to-plastic pathways: a biochemical route (PLA via enzymatic hydrolysis) and a thermochemical route (bio-PE via gasification and MTO). Based on Aspen Plus simulations and a "lifetime-adjusted" lifecycle assessment framework, we evaluate the environmental performance of these routes in the transition from linear to circular systems. Unlike standard "cut-off" methods, the lifetime-adjusted model accounts for virgin make-up and molecular retention across multiple recycling cycles. Results indicate that at current 15% recycling rates, PLA exhibits the lowest global warming potential due to significant biogenic carbon sequestration. However, as recycling rates reach 75%, process efficiency becomes the dominant factor; the precise biochemical recycling of PLA continues to outper... [more]

Conventional urea production is a centralized and fossilintensive process associated with significant greenhousegas (GHG) emissions and limited flexibility for deep decarbonization. As an alternative, the Integrated COnversion of NItrate and Carbonate steams (ICONIC) project is developing innovative electrochemical urea (eurea), via the co-electroreduction of nitrogen and carbon sources using renewable power. While recent research advances in electrocatalysis have demonstrated promising Faradaic efficiencies (FE) toward urea, the design of electrochemical systems involves inherent tradeoffs between key performance indicators (KPIs) such as current density, cell voltage, and FE. Crucially, the implications of electrolyzerlevel performance on plantlevel economics and environmental impacts remain poorly understood. To address this gap, we integrate process modelling with technoeconomic and lifecycle assessment (TEA-LCA) to evaluate the trade-offs of KPIs from a process systems per... [more]

This supplementary material provides additional process descriptions, process flowsheets and life-cycle inventories in order to reproduce the work presented in the manuscript. Further, more detailed derivations of the impact calculation model are given.

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

The environmental impacts of pharmaceutical production underscore the need for comprehensive life cycle assessments (LCAs). Offshoring manufacturing, a common cost-saving strategy in the pharmaceutical industry, increases supply chain complexity and reliance on countries like India and China for active pharmaceutical ingredients (APIs). The COVID-19 pandemic exposed Europe’s vulnerability to global crises, prompting initiatives such as the French government’s re-industrialization plan to relocate the production of fifty critical drugs. Paracetamol production has been prioritized, with recent shortages highlighting the urgency to address supply chain risks while considering environmental impacts. This study uses process engineering to generate life cycle inventory (LCI) data for paracetamol production, offering an eco-design perspective. Aspen Plus was employed to model the API manufacturing process, integrating mass and energy balances to address the scarcity of LCI data. The results h... [more]

This study presents a comprehensive comparison of the three alternative downstream manufacturing technologies for pharmaceuticals: i) Dry Granulation (DG) through roller compaction, ii) Direct Compaction (DC), and iii) Wet Granulation (WG) based on the economic, environmental and product quality performances. Firstly, the integrated dynamic mathematical models of the different downstream (drug product) processes were developed using gPROMS formulated products based on data from the literature or/and our recent experimental work. The process models were developed and simulated to reliably capture the impact of the different design options, process parameters, and material attributes. Uncertainty analysis was conducted using global sensitivity analysis to identify the set of critical process parameters (CPP) and critical material attributes (CMA) that mostly influence the quality and performance of the final pharmaceutical tablets in each case, captured by the critical quality attribute... [more]

This work introduces a Python-based interface that couples cradle-to-gate Life Cycle Assessment (LCA) with advanced process simulations in continuous biomanufacturing, resulting in dynamic process inventories and thus to dynamic LCA (dLCA). The open-source Brightway2.5 framework is used to dynamically track environmental inventories of the foreground process and LCA indicators (e.g. damage to ecosystems according to ReCiPE 2016) from the v3.10 cut-off ecoinvent database. The framework is applied to KTB1, a dynamic MATLAB–Simulink benchmark model of continuous Lovastatin production. 580 data points are computed across four different 24-hour scenarios. The difference between the hourly and the averaged foreground scenario is between 20-30%; a more pronounced deviation is observed when both background and foreground are averaged. The dLCA framework precisely identifies optimal periods for cleaner electricity usage, enabling future work on direct environmental feedback into process control... [more]

In 2022, Uruguay launched its green hydrogen roadmap, due to its renewable energy potential, water availability, and favorable logistics to position itself as an exporter of green hydrogen and derivatives. The energy source for water electrolysis is a key factor in both the final cost and the environmental impact of hydrogen production. In this context, this study evaluates the environmental impact of hydrogen production via water electrolysis, powered by 150 MW of new power sources (solar, wind, and hybrid farms) in Uruguay, all connected to the national grid. A life cycle assessment (LCA) was conducted using OpenLCA software and the Ecoinvent database, with 1 kg of hydrogen as the functional unit and the system boundaries included power generation and the electrolysis system. The analysis focused on global warming potential (GWP), considering different scenarios for the grid energy mix and the inclusion or exclusion of surplus energy as carbon credits. The wind plant is the option th... [more]

This study evaluates the environmental impact of carbon capture technology in the context of reducing industrial CO2 emissions within Eco-Industrial Parks (EIP). The primary focus is on the post-combustion absorption process, which uses solvents like monoethanolamine (MOA) to capture CO2 before it is released into the atmosphere. The captured CO2 is either stored or utilized to prevent further contribution to climate change. The study employs a Life Cycle Assessment (LCA) methodology to compare the environmental impacts of two scenarios: one with CO2 capture and the other with the direct release of CO2 into the atmosphere. The LCA considers inputs, outputs, energy requirements, and materials needed for the CO2 absorption process. The functional unit of the assessment is 1000 tons of CO2, to standardize comparisons between both scenarios. Results show that the CO2 absorption process significantly reduces the impact on climate change, capturing over 80% of the CO2 from the stream. In ter... [more]

Hydrogen is increasingly recognized as a key player in future energy systems. However, its production technologies—Steam Methane Reforming (SMR) and electrolysis—present trade-offs. SMR, the dominant method, is cost-effective but has a significant carbon footprint, emitting substantial greenhouse gases (GHGs). In contrast, electrolysis, powered by renewable energy sources, offers a cleaner alternative, albeit at a higher cost. While current hydrogen system optimizations primarily focus on cost reduction and GHG mitigation, they often neglect broader environmental impacts. This paper addresses the challenge of modeling a hydrogen supply chain (HSC) that achieves strong environmental performance at a relatively affordable cost. To this end, a supply chain design optimization is coupled with Life Cycle Assessment (LCA). The novelty of this work lies in the integration of multiple LCA indicators in the supply chain design optimization, rather than focusing solely on costs and Global Warmin... [more]

Endpoint indicators provide a concise representation of environmental impacts by aggregating multiple midpoint indicators into a single value. Traditional endpoint weighting systems, however, are often limited by biases introduced through panel reviews and a lack of robustness in scientific process models. Additionally, they typically fail to account for the preferences of key stakeholders, including industry, government, and the public. This work addresses these limitations by developing an endpoint indicator that incorporates stakeholder preferences and minimizes dissatisfaction. A multi-stakeholder optimization framework was formulated to achieve this goal, employing distance, downside risk, and conditional value at risk as objective functions. Stakeholder preferences were derived from emissions data for industry, federal spending on environmental issues for government, and public surveys for societal input. Results highlight regional variations in midpoint indicator weightings acro... [more]

The reduction and recovery of organic fraction of municipal solid waste is a major challenge for contemporary society. It requires the establishment of regional strategies with minimized environmental impact. This study employs life cycle assessment to evaluate the respective environmental performances of the current French system based on incineration, and those of alternative systems including (i) anaerobic digestion with composting and (ii) composting for biowaste treatment under different energy scenarios. The environmental impacts of Parisian biowaste are calculated by considering incineration technologies in the area, the French energy mix in 2022, the average European energy mix in 2022 and the projected French energy mix for 2030. The results show that the proportion of fossil-based sources in the energy mixes significantly influences the environmental performance of waste management systems. Energy mixes based in high-carbon fossil sources dependency tend to favour incineratio... [more]

Hydrogen is increasingly recognized as a crucial energy carrier for a low-carbon future. However, most studies on clean hydrogen production devote limited attention to the entire supply chain. This study evaluates the sustainability of 800 combinations of hydrogen production and transportation methods, comparing their environmental impacts against the geophysical limits defined by the Planetary Boundaries framework. Findings reveal that no supply chain alone can make the current economy sustainable, yet powering water electrolysis with bioenergy and carbon capture and storage can meet the CO2-based planetary boundaries. The analysis also underscores the need for decarbonization efforts in the hydrogen transportation sector, as certain options could offset the benefits of clean hydrogen production.

In this work, we propose a mixed-integer linear programming (MILP) model that optimizes economic and environmental objectives by retrofitting fuel stations for the case study of Spain. The model contains set-covering constraints that ensure that there is at least one retrofitted fuel station within a radius of 20 kilometers of each retrofitted fuel station. The results indicate that by retrofitting fuel stations to allow for electric vehicles, both economic and environmental objectives improve, while showing which power plants would be tasked with the increase in electricity production to satisfy the increased electric demand.

Detailed assessment of fuel production processes at an early stage of a project is crucial to identify potential technical challenges, optimize efficiency and minimize costs and environmental impact. While process simulations often are either very rigid and accurate or very flexible and unprecise, informed decision making can only be maintained by establishing a detailed process model as early as possible within the project lifecycle while keeping relevant aspects of the process flexible enough. In this work, we present the development of a framework based on a dynamic interface between AspenPlus® process simulations and Python, enabling enhanced flexibility and automation for process modeling and optimization. This integration leverages the powerful simulation capabilities of AspenPlus® with the versatility of Python for data analysis and optimization, delivering significant improvements in workflow efficiency and process control. By utilizing the dynamic simulation data exchange with... [more]