The challenge of assessing emerging technologies with life cycle assessment (LCA) has been increasingly discussed in the LCA field. In this article, we propose a definition of prospective LCA: An LCA is prospective when the (emerging) technology studied is in an early phase of development (e.g., small-scale production), but the technology is modeled at a future, more-developed phase (e.g., large-scale production). Methodological choices in prospective LCA must be adapted to reflect this goal of assessing environmental impacts of emerging technologies, which deviates from the typical goals of conventional LCA studies. The aim of the article is to provide a number of recommendations for how to conduct such prospective assessments in a relevant manner. The recommendations are based on a detailed review of selected prospective LCA case studies, mainly from the areas of nanomaterials, biomaterials, and energy technologies. We find that it is important to include technology alternatives that are relevant for the future in prospective LCA studies. Predictive scenarios and scenario ranges are two general approaches to prospective inventory modeling of both foreground and background systems. Many different data sources are available for prospective modeling of the foreground system: scientific articles; patents; expert interviews; unpublished experimental data; and process modeling. However, we caution against temporal mismatches between foreground and background systems, and recommend that foreground and background system impacts be reported separately in order to increase the usefulness of the results in other prospective studies.

/pdf/environmental-assessment-of-emerging-technologies-59wuj6ewgc.pdf

Environmental Assessment of Emerging Technologies - Recommendations for Prospective LCA

Manufacturing of nanomaterials is an interdisciplinary field covering physics, chemistry, biology, materials science and engineering. The interaction between scientists with different disciplines will undoubtedly lead to the production of novel materials with tailored properties. The success of nanomanufacturing depends on the strong cooperation between academia and industry in order to be informed about current needs and future challenges, to design products directly transferred into the industrial sector. It is of paramount importance the selection of the appropriate method combining synthesis of nanomaterials with required properties and limited impurities as well as scalability of the technique. Their industrial use faces many obstacles as there is no suitable regulatory framework and guidance on safety requirements; specific provisions have yet to be established in EU legislation. Moreover, regulations related to the right of intellectual properties as well as the absence of an appropriate framework for patent registration are issues delaying the process of products’ industrial application. The utilization of high-quality nanomaterials is now growing and coming to the industrial arena rendering them as the next generation attractive resources with promising applications. Undoubtedly, the existing gap between basic research relating nanomaterials and their application in real life will be overcome in the coming decade.

/pdf/manufacturing-nanomaterials-from-research-to-industry-3z5ux62nrz.pdf

Manufacturing nanomaterials: from research to industry

https://scholarlypublications.universiteitleiden.nl/access/item%3A3076636/view

A critical view on the current application of LCA for new technologies and recommendations for improved practice

Emerging technologies are expected to contribute to environmental sustainable development. However, throughout the development of novel technologies, it is unknown whether emerging technologies can lead to reduced environmental impacts compared to a potentially displaced mature technology. Additionally, process steps suspected to be environmental hotspots can be improved by process engineers early in the development of the emerging technology. In order to determine the environmental impacts of emerging technologies at an early stage of development, prospective life cycle assessment (LCA) should be performed. However, consistency in prospective LCA methodology is lacking. Therefore, this article develops a framework for a prospective LCA in order to overcome the methodological inconsistencies regarding prospective LCAs. The methodological framework was developed using literature on prospective LCAs of emerging technologies, and therefore, a literature review on prospective LCAs was conducted. We found 44 case studies, four review papers, and 17 papers on methodological guidance. Three main challenges for conducting prospective LCAs are identified: Comparability, data, and uncertainty challenges. The issues in defining the aim, functionality, and system boundaries of the prospective LCAs, as well as problems with specifying LCIA methodologies, comprise the comparability challenge. Data availability, quality, and scaling are issues within the data challenge. Finally, uncertainty exists as an overarching challenge when applying a prospective LCA. These three challenges are especially crucial for the prospective assessment of emerging technologies. However, this review also shows that within the methodological papers and case studies, several approaches exist to tackle these challenges. These approaches were systematically summarized within a framework to give guidance on how to overcome the issues when conducting prospective LCAs of emerging technologies. Accordingly, this framework is useful for LCA practitioners who are analyzing early-stage technologies. Nevertheless, further research is needed to develop appropriate scale-up schemes and to include uncertainty analyses for a more in-depth interpretation of results.

How to Conduct Prospective Life Cycle Assessment for Emerging Technologies? A Systematic Review and Methodological Guidance

In recent literature, prospective application of life cycle assessment (LCA) at low technology readiness levels (TRL) has gained immense interest for its potential to enable development of emerging technologies with improved environmental performances. However, limited data, uncertain functionality, scale up issues and uncertainties make it very challenging for the standard LCA guidelines to evaluate emerging technologies and requires methodological advances in the current LCA framework. In this paper, we review published literature to identify major methodological challenges and key research efforts to resolve these issues with a focus on recent developments in five major areas: cross‐study comparability, data availability and quality, scale‐up issues, uncertainty and uncertainty communication, and assessment time. We also provide a number of recommendations for future research to support the evaluation of emerging technologies at low technology readiness levels: (a) the development of a consistent framework and reporting methods for LCA of emerging technologies; (b) the integration of other tools with LCA, such as multicriteria decision analysis, risk analysis, technoeconomic analysis; and (c) the development of a data repository for emerging materials, processes, and technologies.

Life cycle assessment of emerging technologies: A review

The aim of this paper is to highlight the challenges that face the use of life cycle assessment (LCA) for the development of emerging technologies. LCA has great potential for driving the development of products and processes with improved environmental credentials when used at the early research stage, not only to compare novel processing with existing commercial alternatives but to help identify environmental hotspots. Its use in this way does however provide methodological and practical difficulties, often exacerbated by the speed of analysis required to enable development decisions to be made. Awareness and understanding of the difficulties in such cases is vital for all involved with the development cycle. This paper employs three case studies across the diverse sectors of nanotechnology, lignocellulosic ethanol (biofuel), and novel food processes demonstrating both the synergy of issues across different sectors and highlighting the challenges when applying LCA for early research. Whilst several researchers have previously highlighted some of the issues with use of LCA techniques at an early stage, most have focused on a specific product, process development, or sector. The use of the three case studies here is specifically designed to highlight conclusively that such issues are prevalent to use of LCA in early research irrespective of the technology being assessed. The four focus areas for the paper are system boundaries, scaling issues, data availability, and uncertainty. Whilst some of the issues identified will be familiar to all LCA practitioners as problems shared with standard LCAs, their importance and difficulty is compounded by factors distinct to novel processes as emerging technology is often associated with unknown future applications, unknown industrial scales, and wider data gaps that contribute to the level of LCA uncertainty. These issues, in addition with others that are distinct to novel applications, such as the challenges of comparing laboratory scale data with well-established commercial processing, are exacerbated by the requirement for rapid analysis to enable development decisions to be made. Based on the challenges and issues highlighted via illustration through the three case studies, it is clear that whilst transparency of information is paramount for standard LCAs, the sensitivities, complexities, and uncertainties surrounding LCAs for early research are critical. Full reporting and understanding of these must be established prior to utilising such data as part of the development cycle.

/pdf/use-of-lca-as-a-development-tool-within-early-research-15iyro4tnw.pdf

Use of LCA as a development tool within early research:Challenges and issues across different sectors

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Use of LCA as a development tool within early research:Challenges and issues across different sectors