Supporting a transition towards sustainable circular economy: sensitivity analysis for the interpretation of LCA for the recovery of electric and electronic waste

Purpose

The interpretation is a fundamental phase of life cycle assessment (LCA). It ensures the robustness and the reliability of the overall study. Moving towards more circular economy requires that different waste management options are systematically scrutinized to assess the environmental impacts and benefits associated to them. The present work aims at illustrating how a sensitivity analysis could be applied to the impact assessment step supporting the interpretation of a LCA study applied to a waste management system that includes material recovering. The focus is on toxicity-related and resource-related potential impacts as they are considered among the most critical ones, which may affect the way the final benefit from material recovery is evaluated.

Methods

Possible alternatives in terms of impact assessment assumptions and modelling are tested by performing a sensitivity analysis on a case study on electric and electronic waste. For the toxicity-related impact categories, first, a sensitivity analysis is performed using different sets of characterization factors for metals aiming at identifying how they are affecting the final results. Then, an analysis of the relative contribution of long-term emissions in upstream processes is carried out aiming at unveiling critical issues associated to their inclusion or exclusion. For the resource depletion impact category, a sensitivity analysis has been performed, adopting different sets of characterization factors based on existing models for minerals and metals as well as recently proposed sets accounting for critical raw materials.

Results and discussion

The indicator of the ecotoxicity impact category obtained by applying the updated characterization factors is about three times higher than the corresponding obtained by the USEtox model. The long-term emission result is responsible for the major part of all the toxicity impact indicators. Moreover, for the ecotoxicity indicator, excluding the long-term emissions changes the total results from being negative into positive. The sensitivity analysis for the resource depletion impact category shows that all the models applied result in a total avoided impact. A quantitative comparison among all the results is not possible as the different models use different units of measure.

Conclusions

The application of LCA is crucial for assessing avoided impacts and uncovers potential impacts due to recycling. However, contrasting results may stem from the application of different assumptions and models for characterization. A robust interpretation of the results should be based on systematic assessment of the differences highlighted by the sensitivity, as guidance for delving into further analysis of the drivers of impacts and/or to steer ecoinnovation to reduce those impacts.