SAB: An open-access Python-based integrated platform for fully automated emergent sustainability assessment of biorefineries

• Published in: The international journal of life cycle assessment Vol. 29; no. 4; pp. 632 - 651
• Main Authors: Zarafshani, Hanie, Watjanatepin, Ponnapat, Navare, Kranti, Sauve, Giovanna, Van Acker, Karel
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024; Springer Nature B.V
• Subjects: Algorithms; Automation; biomass; Biorefineries; biorefining; Circular economy; computer software; Data simulation; Decision making; decision support systems; Earth and Environmental Science; economic analysis; Economics; energy; Environment; Environmental Chemistry; Environmental Economics; Environmental Engineering/Biotechnology; Lca for Agriculture Practices and Biobased Industrial Products; Life cycle analysis; Life cycle assessment; life cycle costing; Life cycle costs; life cycle inventory; Life cycles; Lignocellulose; Parameter sensitivity; Parameter uncertainty; Performance evaluation; Refining; risk; Risk assessment; Sensitivity analysis; Sustainability; Sustainable development; Tradeoffs; uncertainty; Life cycle assessment; Python-based platform; Biorefinery; Trade-off-based decision-making tool; Risk-based analysis; Life cycle cost
• ISSN: 0948-3349; 1614-7502
• DOI: 10.1007/s11367-023-02271-w

Purpose The ability of biorefineries to simultaneously produce energy and materials from biomass is a key factor in their role as a fundamental solution for enabling the circular economy. Research in this field is primarily focused on measuring and improving the sustainability of biorefineries. Nevertheless, the evaluation of biorefineries’ sustainability faces a significant challenge due to their emergent nature. This challenge stems from inadequate data availability or the presence of data that is fraught with uncertainties and risks, which hampers the assessment process. Consequently, it becomes imperative to undertake comprehensive and extensive analyses of risks and uncertainties to tackle this issue effectively. In addition to this, data simulation also requires subsequent manual steps to transfer these data into assessment software. All these requirements for a comprehensive sustainability assessment combined can accumulate into a resource-demanding, time-consuming, and energy-intensive task. Furthermore, most studies neglect the trade-off between different sustainability aspects and fully comprehend the relative relevance of input elements impacting sustainability. The aforementioned issues reduce the accuracy of biorefinery sustainability assessments. Research methodology To overcome these challenges, an automated open-access python-based integrated modular platform, named SAB (Sustainability Assessment of Biorefineries), was developed to perform the environmental and economic assessment of biorefineries. SAB extracts the data required for building the life cycle inventory from the ASPEN model. It performs life cycle assessment (LCA) and life cycle cost (LCC) while taking the input parameters’ uncertainty into account. It also determines the impact of input parameters on LCA and LCC results by carrying out a Global Sensitivity Analysis. In addition, SAB evaluates the sustainability performance of a variety of scenarios based on a trade-off decision-making algorithm to determine the scenario with the least environmental and economic risk. To illustrate the capability of SAB, three case studies for lignocellulose-based biorefinery are presented in this paper. Results and conclusion Overall, the SAB tool enables the evaluation of LCA and LCC of biorefineries transparently in an automated manner. It can be employed as a decision-making tool that gives information about the environmental and economic risks of multiple scenarios. SAB also supports the development of a more sustainable biorefinery concept by giving information about the effects of different variables on LCA and LCC results.