Future carbon footprints of batteries and passenger cars

: Prospective life cycle assessment using climate mitigation pathways from integrated assessment models. (Alternative Format Thesis)

Abstract

Human-induced greenhouse gas emissions have increased global temperatures by over 1.1 °C since pre-industrial times, leading to more extreme weather and ecological harm. Global temperature rise must avoid breaching 1.5–2.0°C to prevent the worst effects of climate change. Emissions from energy-intensive sectors such as transport must be rapidly reduced through the widespread adoption of low-carbon technologies such as electric vehicles (EV). However, such technologies also introduce new environmental challenges, such as high embodied carbon and the reliance on resource-intensive and toxic supply chains.

While life cycle assessment (LCA) can help measure these environmental impacts, it cannot account for future system changes such as those driven by global decarbonisation targets. For example, EVs may be manufactured today, but their use and end-of-life phases take place in the future. Moreover, peak manufacturing volumes of EVs will also be in the future. Given that material and energy systems are expected to evolve significantly over time and impact the EV life cycle, there is substantial uncertainty in existing LCAs regarding their current and future environmental impacts. A form of “Prospective” LCA (pLCA), enabled by a software tool called “Premise”, offers a solution to this challenge. Premise incorporates future decarbonisation pathways from integrated assessment models (IAMs) into LCA databases, providing a framework for exploring future environmental impacts.

This thesis advances pLCA methodologies to better represent the current and future environmental impacts of long-lived technologies, focusing on batteries and passenger cars. Previously, Premise included future scenarios from only two IAMs -REMIND and IMAGE - resulting in limited scenario availability for conducting pLCA. Therefore, four 1.5-3.0°C future scenarios from a third IAM – TIAM-UCL – are linked to Premise, which expands IAM scenarios, strengthening potential conclusions from pLCA (Chapter 5). Over 200 variables across 16 global regions were connected to over 300 LCA processes, representing future technological changes across seven major sectors, including electricity, fuels, and steel. A pLCA case study on decarbonising the global electricity mix compared equivalent scenarios from IMAGE, REMIND, and TIAM-UCL, revealing significant differences in the environmental co-benefits and trade-offs. These variations stem from differences in the low-carbon technologies adopted by each model, underscoring the importance of IAM selection and scenario diversity when interpreting pLCA outcomes.

The current and future carbon footprints of six lithium-ion battery production and four recycling routes were evaluated using pLCA, incorporating future electricity decarbonisation scenarios from IMAGE (Chapter 4). By 2050, if global electricity follows a 2.0°C decarbonisation trajectory, production carbon footprints could decrease by 57%. Thus, it is crucial to decarbonise upstream heat, fuels, and direct emissions to achieve zero-carbon batteries. Battery recycling, when assessed through the conventional LCA approach, appears effective in reducing net impacts by recovering high-impact raw materials, avoiding their primary production. However, when recycling is projected to occur post-production in future years using time-adjusted pLCA, recycling benefits can be up to 75% lower than expected. This is because materials recycled in the future replace lower-impact processes due to anticipated electricity decarbonisation. Therefore, greater emphasis should be placed on mitigating production impacts today rather than relying on the uncertain future recycling benefits.

Similarly, LCAs of passenger cars often overlook future energy system transitions, leading to misrepresented impacts of their use and end-of-life. Therefore, time-adjusted pLCA is applied to enhance passenger car carbon footprints under four 1.5–3.0°C decarbonisation pathways for electricity, diesel, and hydrogen from TIAM-UCL (Chapter 6). Using Monte Carlo and Global Sensitivity Analysis methods to evaluate 5,000 comparative cases, battery electric vehicles consistently deliver the lowest carbon footprints compared to hybrid combustion, plug-in hybrid electric, and hydrogen fuel-cell vehicles. The pLCA revealed distinct differences in vehicle results compared to conventional LCA. For instance, the average carbon footprint of battery electric vehicles was from 32% to 47% lower than that of hybrid combustion across all future scenarios in pLCA, compared to just 24% in a conventional LCA. Battery electric vehicles retained their advantage for mileages over 100,000 km, even in regions with carbon-intensive electricity, since these are anticipated to decarbonise the most. Applying future scenarios was a critical and determining factor in passenger car outcomes, further motivating the importance of pLCA.

Prospective LCA overcomes the limitations of conventional LCA by providing distinct insights and more robust findings. Incorporating IAM future scenarios into pLCA enables more accurate assessments of long-lived technologies, as presented for batteries and passenger cars in this thesis. This approach encourages practitioners and decision-makers to adopt pLCA methodologies and tools, such as Premise and IAMs, to better account for future uncertainties, improve environmental impact representation, and inform decisions that are crucial for securing a sustainable future.

Date of Award	26 Mar 2025
Original language	English
Awarding Institution	Institute of Sustainability and Climate Change Department of Mechanical Engineering EPSRC Centre for Doctoral Training in Advanced Automotive Propulsion Systems (AAPS CDT)
Supervisor	Stephen Allen (Supervisor), Rick Lupton (Supervisor) & Christopher Vagg (Supervisor)