When the Background Matters: Using Scenarios from Integrated Assessment Models in Prospective Life Cycle Assessment

Abstract

Summary Prospective life cycle assessment (LCA) needs to deal with the large epistemological uncertainty about the future to support more robust future environmental impact assessments of technologies. This study proposes a novel approach that systematically changes the background processes in a prospective LCA based on scenarios of an integrated assessment model (IAM), the IMAGE model. Consistent worldwide scenarios from IMAGE are evaluated in the life cycle inventory using ecoinvent v3.3. To test the approach, only the electricity sector was changed in a prospective LCA of an internal combustion engine vehicle (ICEV) and an electric vehicle (EV) using six baseline and mitigation climate scenarios until 2050. This case study shows that changes in the electricity background can be very important for the environmental impacts of EV. Also, the approach demonstrates that the relative environmental performance of EV and ICEV over time is more complex and multifaceted than previously assumed. Uncertainty due to future developments manifests in different impacts depending on the product (EV or ICEV), the impact category, and the scenario and year considered. More robust prospective LCAs can be achieved, particularly for emerging technologies, by expanding this approach to other economic sectors beyond electricity background changes and mobility applications as well as by including uncertainty and changes in foreground parameters. A more systematic and structured composition of future inventory databases driven by IAM scenarios helps to acknowledge epistemological uncertainty and to increase the temporal consistency of foreground and background systems in LCAs of emerging technologies.

Bringing a life cycle perspective to emerging technology development

“…Two papers focus on advancing methods for the specific purpose of assessing emerging technologies. The first is titled “When the background matters: Using scenarios from integrated assessment models in prospective life cycle assessment” (Mendoza Beltran et al., ). This study focuses on prospective LCA where the uncertainty in background processes such as future electricity grid intensity is important.…”

Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity

“…Accounting for uncertainty is critical in LCAs of both commercial technologies (discussed in Gregory et al., ; Igos, Benetto, Meyer, Baustert, & Othoniel, ; Mendoza Beltran et al., ; Lloyd and Ries, ) as well as emerging technologies. Some studies (Lacirignola, Blanc, Girard, Pérez‐López, & Blanc, ; Ravikumar et al., ) have proposed new methods for accounting for uncertainty in LCA of emerging technologies using sensitivity analyses to aid in identifying key parameters affecting a technology's environmental impacts.…”

“…Some studies (Lacirignola, Blanc, Girard, Pérez‐López, & Blanc, ; Ravikumar et al., ) have proposed new methods for accounting for uncertainty in LCA of emerging technologies using sensitivity analyses to aid in identifying key parameters affecting a technology's environmental impacts. Integrated Assessment Models have been used to develop future demand scenarios to account for market conditions surrounding demand for current technologies (Mendoza Beltran et al., ) or deployment of emerging technologies (Cucurachi, Borgonovo, & Heijungs, ; Steubing, Reinhard, Zah, & Ludwig, ). Others have employed consequential modeling approaches to assess the net environmental effects of future increases in demand for a product such as renewable fuels (Reinhard & Zah, ; Reinhard & Zah, ).…”

“…Vehicle ownership rates in sub‐Saharan Africa are among the lowest in the world, yet are expected to increase as income levels rise (Dargay & Gately, ). Many LCAs have quantified associated materials and energy use of the technology by itself or as an incumbent technology for a comparison with emerging design, fuel, and engine options (Hawkins, Singh, Majeau‐Bettez, & Strømman, ; Kaniut, Cetiner, & Franzeck, ; MacLean & Lave, , ; Mendoza Beltran et al., ; Sullivan & Cobas‐Flores, ). A common metric for measuring life cycle performance of the automobile is kg CO 2 eq/passenger‐mile (or km).…”

“…The literature on LCA of emerging technologies includes many case studies, variously using terms such as prospective (Mendoza Beltran et al., ; Cooper & Gutowski, ; Raugei & Winfield, ; Sathre et al., ; Wender & Seager, ), early stage (Cramer, ; Hetherington et al., ; Hung, Ellingsen, & Majeau‐Bettez, ), ex ante (Hesser, ; Villares, Işıldar, Van der Giesen, & Guinée, ; Zhou et al., ), anticipatory (Gifford, Chester, Hristovski, & Westerhoff, ; Kendall & Yuan, ; Mattick, Landis, Allenby, & Genovese, ; Ravikumar, Seager, Cucurachi, Prado, & Mutel, ; Tsang, Philippot, Aymonier, & Sonnemann, ; Wender et al., ; Wender, Foley, Guston, Seager, & Wiek, ), explorative (Steubing, Mutel, Suter, & Hellweg, ), and scenario‐based (Arvidsson et al., ) LCA. The diversity of terms mirrors the wide range of available methods and disparate language employed across the LCA community.…”