Abstract
This study explored spatiotemporal patterns of e-bike usage. The carbon emissions of electric bike-sharing systems in Chicago were estimated, and their spatial distribution was characterized. Customers preferred e-bikes as a transportation mode for trips that took less than 20 min, indicating that the use of e-bikes for short trips could reduce traffic congestion. This finding has an important implication for urban planning studies. It would be more reasonable to calculate the potential reduction of carbon emissions from substituting e-bike rides for short trips by car or other transportation modes rather than for all trips. This study also identified hotspots and corresponding peak periods. Recommendations were made for strategically dispatching e-bikes around the central business district to meet customer needs during weekday peak commuting hours. E-bike trips produced the least amount of carbon in January. Emissions gradually climbed until April, when they almost tripled the January emissions. Throughout these 4 months, e-bike trips generated 1624.4 kg of carbon emissions, with weekday emissions accounting for the majority. The spatial patterns of carbon emissions were visualized based on street networks. The method used in this study for exploring carbon emissions can be applied to future research after adjusting the model parameters to fit particular scenarios.
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Funding
This work was supported by the Natural Science Foundation of Fujian Province (grant number: 2023J05162), the Science and Technology Project of the Education Department of Fujian Province (grant number: JAT200282), and the Scientific Research Foundation of Jimei University, China (grant number: ZQ2019025).
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Xie, J., Xiao, Z. Spatiotemporal Patterns and Carbon Emissions of Shared-Electric-Bike Trips in Chicago. J geovis spat anal 8, 13 (2024). https://doi.org/10.1007/s41651-024-00171-7
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DOI: https://doi.org/10.1007/s41651-024-00171-7