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Climate performance of shared e scooters in Dubai : An attributional life cycle assessment and scenario-based implications

Ibrahim, Haider ; Dias, Charitha ; Ilahi, Anugrah ; Alawadi, Khaled and Zhao, Pengxiang LU (2026) In Green Technologies and Sustainability 4(3).
Abstract

Shared electric scooters (e-scooters) are widely promoted as a low-carbon urban transport solution. However, their environmental impact depends on lifespan, operations, and modal shift. This study evaluates life cycle greenhouse gas emissions of shared e-scooters operating in Dubai, UAE. A cradle-to-grave life cycle assessment is conducted, considering manufacturing, transportation, use phase electricity, redistribution logistics, and end-of-life treatment through scenario analysis varying lifetime distance (500, 1500, and 5000 km), riding energy intensity (10, 15, and 20 Wh/km), redistribution rate (10% and 50%), and disposal pathways (landfill versus high-recovery recycling). Emissions are then combined with modal shift assumptions to... (More)

Shared electric scooters (e-scooters) are widely promoted as a low-carbon urban transport solution. However, their environmental impact depends on lifespan, operations, and modal shift. This study evaluates life cycle greenhouse gas emissions of shared e-scooters operating in Dubai, UAE. A cradle-to-grave life cycle assessment is conducted, considering manufacturing, transportation, use phase electricity, redistribution logistics, and end-of-life treatment through scenario analysis varying lifetime distance (500, 1500, and 5000 km), riding energy intensity (10, 15, and 20 Wh/km), redistribution rate (10% and 50%), and disposal pathways (landfill versus high-recovery recycling). Emissions are then combined with modal shift assumptions to estimate net impacts relative to replaced transport modes. Manufacturing dominates the carbon footprint, contributing 144 kg CO2e per-e-scooter. Lifetime distance is the key determinant of per-km emissions, ranging from 262–483 g CO2e/km at 500 km, decline at 1500 km, and dropping to 63 g CO2e/km at 5000 km, allowing meaningful reductions when replacing short car trips. Variation in riding electricity intensity changes emissions by 5–8 g CO2e/km, indicating a minor contribution. In contrast, intensive redistribution can increase emissions by 140–145 g CO2e/km, making it the dominant operational contributor. Scenario-based net impact analysis shows that shared e-scooters do not inherently reduce emissions. They increase transport emissions when service lifetimes are short and substitution is dominated by walking. Shared e-scooters are therefore conditionally low-carbon, and their climate benefits depend on extended service lifetimes, optimized fleet management, material recovery, and policies that ensure car trip replacement. Otherwise, they risk increasing overall transport-related emissions.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Carbon footprint, Dubai, Electric scooter, Greenhouse gas emissions, Life cycle assessment (LCA), Modal shift
in
Green Technologies and Sustainability
volume
4
issue
3
article number
100408
publisher
KeAi Publishing Communications Ltd.
external identifiers
  • scopus:105038333010
DOI
10.1016/j.grets.2026.100408
language
English
LU publication?
yes
id
7e4ae656-c5d0-4637-9f88-36cf1cbe545e
date added to LUP
2026-08-24 13:34:48
date last changed
2026-08-24 14:39:24
@article{7e4ae656-c5d0-4637-9f88-36cf1cbe545e,
  abstract     = {{<p>Shared electric scooters (e-scooters) are widely promoted as a low-carbon urban transport solution. However, their environmental impact depends on lifespan, operations, and modal shift. This study evaluates life cycle greenhouse gas emissions of shared e-scooters operating in Dubai, UAE. A cradle-to-grave life cycle assessment is conducted, considering manufacturing, transportation, use phase electricity, redistribution logistics, and end-of-life treatment through scenario analysis varying lifetime distance (500, 1500, and 5000 km), riding energy intensity (10, 15, and 20 Wh/km), redistribution rate (10% and 50%), and disposal pathways (landfill versus high-recovery recycling). Emissions are then combined with modal shift assumptions to estimate net impacts relative to replaced transport modes. Manufacturing dominates the carbon footprint, contributing 144 kg CO<sub>2</sub>e per-e-scooter. Lifetime distance is the key determinant of per-km emissions, ranging from 262–483 g CO<sub>2</sub>e/km at 500 km, decline at 1500 km, and dropping to 63 g CO<sub>2</sub>e/km at 5000 km, allowing meaningful reductions when replacing short car trips. Variation in riding electricity intensity changes emissions by 5–8 g CO<sub>2</sub>e/km, indicating a minor contribution. In contrast, intensive redistribution can increase emissions by 140–145 g CO<sub>2</sub>e/km, making it the dominant operational contributor. Scenario-based net impact analysis shows that shared e-scooters do not inherently reduce emissions. They increase transport emissions when service lifetimes are short and substitution is dominated by walking. Shared e-scooters are therefore conditionally low-carbon, and their climate benefits depend on extended service lifetimes, optimized fleet management, material recovery, and policies that ensure car trip replacement. Otherwise, they risk increasing overall transport-related emissions.</p>}},
  author       = {{Ibrahim, Haider and Dias, Charitha and Ilahi, Anugrah and Alawadi, Khaled and Zhao, Pengxiang}},
  keywords     = {{Carbon footprint; Dubai; Electric scooter; Greenhouse gas emissions; Life cycle assessment (LCA); Modal shift}},
  language     = {{eng}},
  number       = {{3}},
  publisher    = {{KeAi Publishing Communications Ltd.}},
  series       = {{Green Technologies and Sustainability}},
  title        = {{Climate performance of shared e scooters in Dubai : An attributional life cycle assessment and scenario-based implications}},
  url          = {{http://dx.doi.org/10.1016/j.grets.2026.100408}},
  doi          = {{10.1016/j.grets.2026.100408}},
  volume       = {{4}},
  year         = {{2026}},
}