Unlocking Large-Scale, Long-Term Capital for Sustainable Mobility

The report identifies significant financial and operational barriers to the adoption of zero-emission vehicles (ZEVs), particularly the high upfront capital expenditure (capex) and the 'chicken-and-egg' problem of infrastructure versus vehicle demand. To overcome these, the World Economic Forum and McKinsey & Company propose six investment archetypes—covering city buses, school buses, passenger fleets, heavy-duty trucks, last-mile delivery, and hydrogen refuelling—that shift the financial burden from capex to operating expenditure (opex) through leasing models backed by long-term institutional investors and government guarantees.

• The transition to net-zero emissions in the 27 European Union member states by 2050 is estimated to require €28 trillion in investments, with the domestic transportation sector accounting for 40% of this need, totaling €12 trillion.
• The domestic transport sector in the EU 27 requires an incremental capex of approximately €180 billion by 2030 to achieve a zero-emission transition, though it is projected to break even by 2050.
• A primary barrier to ZEV adoption is the 'chicken-and-egg' problem, where charging infrastructure investment depends on ZEV demand, while ZEV adoption is hindered by a lack of available charging and refuelling stations.
• The report proposes using Special Purpose Vehicles (SPVs) to shift the financial burden from capital expenditure (capex) to operating expenditure (opex) by having the SPV own the assets and lease them to operators.
• For city buses, the report suggests a leasing model where an SPV acquires buses and charging infrastructure, which is particularly viable because battery electric buses (BEVs) often offer a lower total cost of ownership (TCO) than diesel or compressed natural gas alternatives.
• School bus electrification in the US faces challenges due to fragmented operator landscapes and low vehicle utilization, which can be mitigated by Vehicle-to-Grid (V2G) technology to create additional revenue streams during idle times.
• Ride-hailing and taxi fleets offer a high-impact opportunity for CO2 reduction because they are bundled under platform operators, allowing for demand aggregation despite the vehicles being owned by individual drivers.
• Heavy-duty truck transition is proposed via joint ventures between OEMs, infrastructure providers, and investors, targeting specific freight corridors in Europe (such as the Trans-European Transport Network) or urban areas.
• Last-mile delivery electrification can be accelerated through a 'Transport-as-a-Service' (TaaS) model, which is especially beneficial for smaller fleet operators and subcontractors who lack the financial strength for high upfront costs.
• Hydrogen refuelling station (HRS) build-out is essential for fuel cell electric vehicles (FCEVs), with current capital costs as high as $3.5 million per station, though economies of scale could reduce this by 40% by 2030.

APA

World Economic Forum (2021). Unlocking Large-Scale, Long-Term Capital for Sustainable Mobility. http://www3.weforum.org/docs/WEF_Unlocking_Large_Scale_Long_Term_Capital_for_Sustainable_Mobility_2021.pdf

Chicago

World Economic Forum. Unlocking Large-Scale, Long-Term Capital for Sustainable Mobility. 2021. http://www3.weforum.org/docs/WEF_Unlocking_Large_Scale_Long_Term_Capital_for_Sustainable_Mobility_2021.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Unlocking Large-Scale, Long-Term Capital for Sustainable Mobility |date=September 2021 |url=http://www3.weforum.org/docs/WEF_Unlocking_Large_Scale_Long_Term_Capital_for_Sustainable_Mobility_2021.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2021unlocking, author = {{World Economic Forum}}, title = {{Unlocking Large-Scale, Long-Term Capital for Sustainable Mobility}}, institution = {World Economic Forum}, year = {2021}, month = sep, url = {http://www3.weforum.org/docs/WEF_Unlocking_Large_Scale_Long_Term_Capital_for_Sustainable_Mobility_2021.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }