Uncertainty communication in the environmental life cycle assessment of carbon nanotubes

Abstract

Amidst the great technological progress being made in the field of nanotechnology, we are confronted by both conventional and novel environmental challenges and opportunities. Several gaps exist in the present state of knowledge or experience with nanomaterials. Understanding and managing the uncertainties that these gaps cause in LCAs is essential. Traditionally used for more established technology systems, environmental LCA is now being applied to nanomaterials by policy-makers, researchers and industry. However, the aleatory (variability) and epistemic (system process) uncertainties in LCAs of nanomaterials need to be handled correctly and communicated in the analysis. Otherwise, the results risk being misinterpreted, misguiding decision-making processes and could lead to significant detrimental effects for industry, research and policy-making. Here, we review current life cycle assessment literature for carbon nanotubes, and identify the key sources of uncertainty that need to be taken into consideration. These include: the potential for non-equivalency between mass and toxicity (potentially requiring inventory and impact models to be adjusted); the use of proxy data to bridge gaps in inventory data; and the often very wide ranges in material performance, process energy and product lifetimes quoted.

A Content Review of Life Cycle Assessment of Nanomaterials: Current Practices, Challenges, and Future Prospects

“…There are a variety of limitations in LCA studies on NMs associated with their uncertainties. These uncertainties can be defined in various ways, but generally, uncertainty and variability are distinguished by model structure, parameter, spatial, temporal, and nature of uncertainty [93,108]. Identified uncertainties are characterized in Figure 7.…”

“…Parameters in LCA are vital; that is why some may have selected non-representative and non-inconclusive parameters. However, it can be improved by tackling the technology scale-up, processing, performance, and fate models in the environment and toxicity assessment, making it more representative in terms of emission values and potential impacts [108][109][110]. Uncertainties may come from the choices of models and frameworks while modelling, which leads to a lack of correlation between the mathematical models.…”