Summary: 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are available for prospective modeling of the foreground system: scientific articles; patents; expert interviews; unpublished experimental data; and process modeling.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.

One promising future bulk application of graphene is as composite additive. Therefore, we compare two production routes for in-solution graphene using a cradle-to-gate lifecycle assessment focusing on potential differences in energy use, blue water footprint, human toxicity, and ecotoxicity. The data used for the assessment is based on information in scientific papers and patents. Considering the prospective nature of this study, environmental impacts from background systems such as energy production were not included. The production routes are either based on ultrasonication or chemical reduction. The results show that the ultrasonication route has lower energy and water use, but higher human and ecotoxicity impacts, compared to the chemical reduction route. However, a sensitivity analysis showed that solvent recovery in the ultrasonication process gives lower impacts for all included impact categories. The sensitivity analysis also showed that solvent recovery is important to lower the blue water footprint of the chemical reduction route as well. The results demonstrate the possibility to conduct a life cycle assessment study based mainly on information from patents and scientific articles, enabling prospective life cycle assessment studies of products at early stages of technological development.

The authors hypothesize that pollution-induced community tolerance (PICT) is direct evidence that a community is disturbed by a pollutant and, furthermore, that the agent or agents causing the effects can be identified, because induced tolerance will be observed only for those compounds that have exerted selection pressure on the community. A similar concept has been formulated for population tolerance, but we suggest that the concept is more useful when applied at the community level. Our examination of some crucial points behind PICT, using arsenate and periphyton communities, demonstrates that (1) the tolerance increase can be determined in short-term photosynthesis experiments, (2) PICT correctly indicates changes in species composition and net production, and (3) the selection pressure of arsenate is specific—that is, a tolerance increase for one compound is not followed by co-tolerance to other compounds unless they are closely related chemically or in their mode of action. These results support the idea of using PICT as an ecotoxicological tool. If further corroborated, PICT can be applied in both laboratory and field studies. PICT might be used retrospecitively in the field to detect minor disturbances and to identify the causing agent. In a laboratory test system, PICT can be used to estimate the no-effect concentration for the community under study. The authors argue that test systems based on PICT will be sensitive and yield ecologically relevant information.