Alessandro Dal Pozzo1*
Anna Björklund2
Michael Carbajales-Dale3
Roland Hischier4
Dwarakanath Ravikumar5
Serena Righi6- 1Laboratory of Industrial Safety and Environmental Sustainability, Alma Mater Studiorum - Università di Bologna, Bologna, Italy
- 2Department of Sustainable Development, Environmental Sciences and Engineering (SEED), KTH Royal Institute of Technology, Stockholm, Sweden
- 3Environmental Engineering & Earth Sciences, Clemson University, Clemson, SC, United States
- 4Technology and Society Laboratory, Empa - Swiss Federal Laboratories for Material Science and Technology, St. Gallen, Switzerland
- 5Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada
- 6Department of Physics and Astronomy and Inter-Departmental Research Centre for Environmental Science, Alma Mater Studiorum - Università di Bologna, Ravenna, Italy
Editorial on the Research Topic
Early-stage quantitative sustainability assessment: Approaches for policy, processes and materials
Quantitative sustainability assessment methods, such as life cycle assessment (LCA) evaluate the potential impacts of products, processes and services. ISO standards and further technical guidelines such as, e.g., PEF1 or EPD2 related category rule documents provide guidance to practitioners on carrying out LCA studies on existing products, processes and services, which are retrospective (ex-post) in nature.
A key limitation of quantitative sustainability assessment lies in its prospective (ex-ante) application, i.e., in the analysis of new products, technologies, and projects at low technology readiness levels (TRL). At the early development stages, the potential to improve environmental performance is the greatest, while the organizational effort and the financial cost to change the course of a project might still be relatively low. However, the lack of direct information and the uncertainty in forecasting technology development and market evolution makes this kind of anticipatory studies particularly challenging.
In recent years, the research community has started a fruitful discussion on the methodological advances required by an ex-ante and anticipatory application of quantitative sustainability assessment (Wender et al., 2014; Cucurachi et al., 2018; Ravikumar et al., 2018; Buyle et al., 2019; Bergerson et al., 2020; Adrianto et al., 2021). The 5 articles that form this Research Topic continue this discussion by offering methodological contributions on the development of prospective assessment frameworks.
Main differences of a prospective LCA compared to its retrospective counterpart are the inclusion of future time considerations in the choice of emerging technological options, the projection of background systems, and the upscaling of foreground systems (Arvidsson et al., 2018). The work by Lai et al. exemplifies approaches to address those three aspects with reference to the assessment of alternative technology pathways to sustainable aviation fuels (SAF) in Sweden. The selection of alternative feedstocks for SAF was performed by applying a socio-technical system (STS) approach. The STS model traces the interdependencies between feedstocks, markets, and institutions in order to systematically identify relevant feedstock types for SAF by considering constraints to supply, the competition in the demand of feedstocks by different markets, and trends in availability of certain feedstocks owing to policy changes. Advanced biofuels obtained from forest residues and black liquor, and e-fuels derived from green hydrogen and biomass-enhanced CO2 capture were recognized as potential SAF feedstocks in the Swedish context. A filter based on TRL and economic considerations allowed screening of the technological options for the production of biofuels and e-fuels down to a selected number of processes, which were modeled prospectively using the upscaling framework proposed by Tsoy et al. (2020). Future background systems were modeled by adapting the approach by Steubing and de Koning (2021), i.e., by modifying the Ecoinvent database with information from integrated assessment modeling (IAM) scenarios.
Ventura discusses the prospective application of LCA at a more fundamental level, focusing on the broader issue of transition. Her article describes a novel conceptual framework, called transition LCA (Tr-LCA). Tr-LCA aims at studying transition scenarios for entire geographical contexts, rather than focusing on single products or organizations. As such, a methodological implication is that, differently from conventional LCAs, in Tr-LCA multiple functional units can be included and they can vary, as a consequence of the deep structural changes to the economy that transitions might realize. The modeling of substitution is another crucial aspect. Ventura extensively discusses integration with material flow analysis as a way to solve this issue at the level of the broad system boundaries of Tr-LCA.
Key for prospective LCA is its use as decision-support tool and, thus, its inclusion into multi-criteria decision-making frameworks. The most simple and widespread decision-support framework is the combination of LCA and techno-economic analysis (TEA). However, the lack of dedicated tools makes early-stage assessments a daunting task for technologists and practitioners. Faber et al. address this issue in the context of carbon capture and utilization (CCU), by presenting a series of ready-to-use, customizable, spreadsheet-based templates for the LCA/TEA of high-priority CCU pathways such as direct air capture, concrete/aggregates carbonation, chemical synthesis, and algae products. This streamlined approach enables an accelerated and standardized screening of CCU pathways, by providing reliable, order-of-magnitude estimates that allow discarding the less promising options and limiting the number of alternatives for which performing a comprehensive assessment.
Another relevant area for early-stage LCA together with decarbonization technologies is the transition toward circular economy (CE). Maximizing recirculation of materials does not necessarily result in a greater sustainability. Thus, solid assessment is needed to certify the soundness of CE projects (Blum et al., 2020). Küpfer et al. touch upon this relevant issue with reference to the building sector. They propose a decision-making framework for reuse of structural components in new construction projects. The proposed approach identifies the optimal rate of reused components by generating design alternatives and evaluating them on a combination of criteria, including environmental (LCA), economic and technical (procurement risk and project complexity) considerations.
More generally, the analysis of “end-of-life” scenarios is particularly critical in the context of novel products and emerging technologies, as very limited or no data are available on the potential impacts (see, e.g., the issues of microplastics and nanomaterials, or the dismantling of PV modules). Atabay et al. propose a top-down approach for the accounting of cradle-to-grave impacts of plastics based on the economic input-output life cycle assessment (EIO-LCA) method. The proposed model, named “Polluter Pays LCA”, aims at covering all the direct and indirect impacts of the plastics value chain, taking a monetization approach akin to life cycle costing with social perspective and including in the system boundaries also the negative externalities in terms of additional burdens to the healthcare and social assistance sector. The mechanism considered to account for the damages of plastics EoL on human health combines emission factors of different toxic compounds from plastic waste management scenarios with a simplified quantification of the effect of micro-plastics (MPs) in enhancing the bioaccumulation of polycyclic aromatic compounds.
The body of work presented in this Research Topic testifies the extensive and prolific activity currently devoted by the scientific community toward early-stage sustainability assessment. By proposing innovative frameworks and informative case studies, articles in this collection contribute to the ongoing development of quantitative methods for the anticipatory analysis of the impacts of emerging technologies and provide suggestions for future work.
Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.
Acknowledgments
We would like to express our gratitude to all the authors who proposed their work and all the researchers who reviewed the submissions to this Research Topic.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
1. ^Product Environmental Footprint: LCA-based method introduced in the EU by the Recommendation 2013/179/EC to regulate the calculation, assessment, third party validation and communication to all stakeholders of the environmental impacts of products and services.
2. ^Environmental Product Declaration: statement that quantifies the environmental information on the life cycle of a product to enable comparisons between products fulfilling the same function, as defined by ISO 14025.
References
Adrianto, L. R., van der Hulst, M. K., Tokaya, J. P., Arvidsson, R., Blanco, C. F., Caldeira, C., et al. (2021). How can LCA include prospective elements to assess emerging technologies and system transitions? The 76th LCA Discussion Forum on Life Cycle Assessment, 19 November 2020. Int. J. Life Cycle Assess. 26, 1541–1544. doi: 10.1007/s11367-021-01934-w
Arvidsson, R., Tillman, A.-M., Sandén, B. A., Janssen, M., Nordelöf, A., Kushnir, D., et al. (2018). Environmental assessment of emerging technologies: recommendations for prospective LCA. J. Indust. Ecol. 22, 1286–1294. doi: 10.1111/jiec.12690
Bergerson, J. A., Brandt, A., Cresko, J., Carbajales-Dale, M., MacLean, H. L., Matthews, H. S., et al. (2020). Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity. J. Indust. Ecol. 24, 11–25. doi: 10.1111/jiec.12954
Blum, N. U., Haupt, M., and Bening, C. R. (2020). Why “Circular” doesn't always mean “Sustainable”. Resour. Conserv. Recycl. 162, 105042. doi: 10.1016/j.resconrec.2020.105042
Buyle, M., Audenaert, A., Billen, P., Boonen, K., and Van Passel, S. (2019). The future of ex-ante LCA? Lessons learned and practical recommendations. Sustainability 11, 5456. doi: 10.3390/su11195456
Cucurachi, S., van der Giesen, C., and Guinée, J. (2018). Ex-ante LCA of emerging technologies. Procedia CIRP 69, 463–468. doi: 10.1016/j.procir.2017.11.005
Ravikumar, D., Seager, T. P., Cucurachi, S., Prado, V., and Mutel, C. (2018). Novel method of sensitivity analysis improves the prioritization of research in anticipatory life cycle assessment of emerging technologies. Environ. Sci. Technol. 52, 6534–6543. doi: 10.1021/acs.est.7b04517
Steubing, B., and de Koning, D. (2021). Making the use of scenarios in LCA easier: the superstructure approach. Int. J. Life Cycle Assess. 26, 2248–2262. doi: 10.1007/s11367-021-01974-2
Tsoy, N., Steubing, B., van der Giesen, C., and Guinée, J. (2020). Upscaling methods used in ex ante life cycle assessment of emerging technologies: a review. Int. J. Life Cycle Assess. 25, 1680–1692. doi: 10.1007/s11367-020-01796-8
Keywords: life cycle assessment (LCA), prospective LCA, anticipatory LCA, ex-ante LCA, transition, upscaling, scenario — analysis
Citation: Dal Pozzo A, Björklund A, Carbajales-Dale M, Hischier R, Ravikumar D and Righi S (2023) Editorial: Early-stage quantitative sustainability assessment: Approaches for policy, processes and materials. Front. Sustain. 4:1125016. doi: 10.3389/frsus.2023.1125016
Received: 15 December 2022; Accepted: 09 January 2023;
Published: 23 January 2023.
Edited and reviewed by: Maria Molinos-Senante, Pontificia Universidad Católica de Chile, Chile
Copyright © 2023 Dal Pozzo, Björklund, Carbajales-Dale, Hischier, Ravikumar and Righi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alessandro Dal Pozzo, 
a.dalpozzo@unibo.it