Abstract
Light weighting by material substitution is a key to reducing GHG emissions during vehicle operation. The GHG benefits are a salient factor in selecting lightweight materials for vehicles. Although the literature has performed lightweight material selections using GHG benefits under product- and fleet-based life-cycle inventory (LCI) analyses, recycling effects have therein been accounted for by arbitrarily selecting allocation methods for recycling, as the consensus on their selection is absent. Furthermore, studies have mistreated the temporal variations of the LCI parameters (the dynamic inventory (DI)), though that could be an important factor affecting the overall LCI results when allocation methods for recycling are in place. Therefore, to investigate their influence on greenhouse gas (GHG) benefit evaluations, an LCI case study was conducted, centered on aluminum- and magnesium-substituted internal combustion engine vehicles (ICEVs) at the product- and fleet- levels. “CO2 savings” and the “CO2 payback time”, as well as four allocation methods for recycling, were considered to represent the GHG benefits and address the recycling effects, respectively. The dynamic inventory was based on the world average electricity grid mix change. The results indicate that changing the conditions of the DI and the allocation methods for recycling could alter the better performing material under fleet-based analyses. Therefore, we ascertained that the choice of the allocation method for recycling and conducting fleet-scale dynamic LCI analyses in the presence of the DI is pivotal for material selections.
Highlights
2, the2,use-phase phase emissions dominated the overall emissions of baseline, aluminum, magneemissions dominated the overall emissions of baseline, aluminum, and and magnesiumsium-intensive the recovery assumed for carbon, flat carbon, special intensive cars. cars
internal combustion engine vehicles (ICEVs) always performed better than the magnesium-intensive in the respective allocation methods for recycling, whil magnesium-intensive ICEV in the respective allocation methods for recycling, while the dynamic inventory was highly sensitive to the savings and payback times calcu dynamic inventory was highly sensitive to the CO2 savings and payback times calculated under the under the fleet-based
We identified that a dynamic inventory capturing more aspects could make magnesium-intensive ICEVs perform better than others in certain allocation method(s) for recycling under the same
Summary
The transportation sector is an important industrial sector in any economy that deals with the movement of people and products [1]. It includes air freight and logistics, airlines, and marine, road, rail, and transportation infrastructure [2]. Despite its importance to society, the transportation sector has become one of the major sources of global greenhouse gas (GHG) emissions caused by the burning of fossil fuels [3,4]. In 2020, about 16% of the global GHG emissions were from the transportation sector [5]. More than two-thirds of transportation-related emissions are derived from automobiles [5,6]
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