Prospective consequential Life Cycle Assessment: Identifying the future marginal suppliers using Integrated Assessment Models

Abstract

While previous research has focused on developing prospective LCI databases that build upon projections from integrated assessment models (IAMs), until now only attributional databases have been developed. To construct consequential LCI databases, a novel approach is required that can be applied consistently on a large scale. To this end, the heuristic approach from Bo Weidema was selected as a basis for this study. This approach has been validated before with historical data and was adapted in this study to identify the marginal suppliers in a prospective context. The different steps within the approach were analyzed and alternative techniques for each step within the heuristic method were proposed. The techniques were tested out on the future electricity sector using projections from two IAMs (IMAGE and REMIND). Results showed how sensitive the results are to which technique is selected in each step. The most sensitive step is the selection of the time interval, with even small changes resulting in a noticeable difference. In addition the results also showed a substantial difference between the IAM projections. The relevance and goals of the alternative techniques for each step were discussed to guide users on forming the heuristic method for their study.

Prospective environmental mitigation potential of deploying waste-to-nutrition pathways

“…Twelve of these were modelled as "marginal" mix, where only unconstrained suppliers are able to respond to changes in demand are included 33 : power, domestic heat, industrial heat, N-fertilizing, Pfertilizing, K-fertilizing, protein feed, lipids feed, energy (carbohydrates) feed, roughage feed, meatequivalent and our-equivalent (see Table 1). Apart from being a key component of consequential LCA modeling, the marginal suppliers mixes were explicitly modeled because these depend on future background markets trends and technological developments, both linked to the underlying prospective scenario rationale 34 (see last section). The rest of the background inventory was assumed xed and modeled directly with existing ecoinvent 3.8 consequential system model 35 .…”

“…These forecasts disagree on two aspects, leading to the de nition of two contrasted future energy systems scenarios for France (see last section). modeling granularity was limited to capture the main technology groups, and the marginal mix of suppliers was estimated following the heuristic approach commonly used in the eld of consequential LCA 34 . Fertilizing markets were considered as global, and the marginal suppliers limited to mineral/synthetic fertilizers 37 .…”

“…Albeit some technical uncertainties remain (for example, regarding the large deployment of electri ed thermal processes), most of the uncertainty is political and societal (relocation of heavy industries, nuclear power acceptability, etc.). Two cornerstone future energy systems scenarios for France were derived: "towards renewable energies" which extrapolates past French trends and planning, and "towards high electri cation" which illustrates a situation of unconstrained power capacities with nuclear power (yet neglecting the lead time required to install new capacities 34 ). As both scenarios led to power and heat production environmentally more e cient than current average situation (mostly renewable or nuclear power, heat-pumps technologies for heat, moderated share of natural gas, etc.…”