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Journal Article

Ride-pooling adoption model for CO2 emission estimation

Authors
/persons/resource/milli.keil

Keil,  Milli
Potsdam Institute for Climate Impact Research;

/persons/resource/Felix.Creutzig

Creutzig,  Felix       
Potsdam Institute for Climate Impact Research;

/persons/resource/molkenthin.nora

Molkenthin,  Nora       
Potsdam Institute for Climate Impact Research;

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Keil_2025_J._Phys._Complex._6_035013.pdf
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Citation

Keil, M., Creutzig, F., Molkenthin, N. (2025): Ride-pooling adoption model for CO2 emission estimation. - Journal of Physics: Complexity, 6, 3, 035013.
https://doi.org/10.1088/2632-072X/adffd4


Cite as: https://publications.pik-potsdam.de/pubman/item/item_33185
Abstract
With the climate emergency and growing challenges ranging from pollution to congestion, ride-pooling (rp) has been floated as a potential solution for less congested, low-carbon and more space-efficient urban transportation. However, it is unclear which system configurations will enable an economically viable case for shared pooled mobility. To develop a more profound comprehension of the mechanisms underlying this subject, we here develop a simplified model to analyze the switching potential and emissions of rp systems for a specified number of transport users, road network topology, and other system parameter values. This analysis is conducted across a broad range of switching probability functions (defined as the probability that a car or public transport user switches to rp) between an upper and lower bound of switching behavior assumptions. Based on current Berlin parameters and the basic switching probability function, we find that rp can reduce the carbon emissions resulting from local transportation in Berlin by approximately 39%. Policies that reduce the time factor—such as the provision of priority lanes—have the greatest effect in encouraging rp. For the system to be efficient and achieve measurable reductions in carbon emissions, the fleet size must be large enough. Across the range of switching probability functions, our results demonstrate that a fleet of 6000 to 23 000 minibuses would be optimal to serve Berlin and reduce system-wide emissions.