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1. Ride Substitution Using Electric Bike Sharing: Feasibility, Cost, and Carbon Analysis

   https://doi.org/10.1145/3448081  

   Wamburu, John ; Lee, Stephen ; Hajiesmaili, Mohammad H. ; Irwin, David ; Shenoy, Prashant ( March 2021 , Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies)

   null (Ed.)

   While ride-sharing has emerged as a popular form of transportation in urban areas due to its on-demand convenience, it has become a major contributor to carbon emissions, with recent studies suggesting it is 47% more carbon-intensive than personal car trips. In this paper, we examine the feasibility, costs, and carbon benefits of using electric bike-sharing---a low carbon form of ride-sharing---as a potential substitute for shorter ride-sharing trips, with the overall goal of greening the ride-sharing ecosystem. Using public datasets from New York City, our analysis shows that nearly half of the taxi and rideshare trips in New York are shorts trips of less than 3.5km, and that biking is actually faster than using a car for ultra-short trips of 2km or less. We analyze the cost and carbon benefits of different levels of ride substitution under various scenarios. We find that the additional bikes required to satisfy increased demand from ride substitution increases sub-linearly and results in 6.6% carbon emission reduction for 10% taxi ride substitution. Moreover, this reduction can be achieved through a hybrid mix that requires only a quarter of the bikes to be electric bikes, which reduces system costs. We also find that expanding bike-share systems to new areas that lack bike-share coverage requires additional investments due to the need for new bike stations and bike capacity to satisfy demand but also provides substantial carbon emission reductions. Finally, frequent station repositioning can reduce the number of bikes needed in the system by up to a third for a minimal increase in carbon emissions of 2% from the trucks required to perform repositioning, providing an interesting tradeoff between capital costs and carbon emissions. 

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2. Ride Substitution Using Electric Bike Sharing: Feasibility, Cost and Carbon Analysis

   Wambouru, John ; Lee, Stephen ; Hajiesmaili, Mohammad ; Irwin, David ; Shenoy, Prashant ( March 2021 , Proceedings of the ACM on interactive mobile wearable and ubiquitous technologies)

   null (Ed.)

   While ride-sharing has emerged as a popular form of transportation in urban areas due to its on-demand convenience, it has become a major contributor to carbon emissions, with recent studies suggesting it is 47% more carbon-intensive than personal car trips. In this paper, we examine the feasibility, costs, and carbon benefits of using electric bike-sharing—a low carbon form of ride-sharing—as a potential substitute for shorter ride-sharing trips, with the overall goal of greening the ride-sharing ecosystem. Using public datasets from New York City, our analysis shows that nearly half of the taxi and rideshare trips in New York are shorts trips of less than 3.5km, and that biking is actually faster than using a car for ultra-short trips of 2km or less. We analyze the cost and carbon benefits of different levels of ride substitution under various scenarios. We find that the additional bikes required to satisfy increased demand from ride substitution increases sub-linearly and results in 6.6% carbon emission reduction for 10% taxi ride substitution. Moreover, this reduction can be achieved through a hybrid mix that requires only a quarter of the bikes to be electric bikes, which reduces system costs. We also find that expanding bike-share systems to new areas that lack bike-share coverage requires additional investments due to the need for new bike stations and bike capacity to satisfy demand but also provides substantial carbon emission reductions. Finally, frequent station repositioning can reduce the number of bikes needed in the system by up to a third for a minimal increase in carbon emissions of 2% from the trucks required to perform repositioning, providing an interesting tradeoff between capital costs and carbon emissions. 

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3. Greening Electric Bike Sharing Using Solar Charging Stations

   https://doi.org/10.1145/3408308.3427621  

   Wamburu, John ; Raff, Christopher ; Irwin, David ; Shenoy, Prashant ( November 2020 , Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys))

   null (Ed.)

   Electric bikes have emerged as a popular form of transportation for short trips in dense urban areas and are being increasingly adopted by bike share programs for easy accessibility to riders. Motivated by the rising popularity of electric bikes, a form of an electric vehicle, we study the research question of how to design a zero-carbon electric bike share system. Specifically we study the challenges in designing solar charging stations for electric bike systems that enable either net-zero or a fully zero-carbon operation. We design a prototype two bike solar charging station to demonstrate the feasibility of our approach. Using insights and data from our prototype solar charging station, we then conduct a data driven analysis of the costs and benefits of converting an entire bike system into one powered using solar charging stations. Using empirical analysis, we determine the panel and battery capacity for each station, and perform a feasibility evaluation of the system using 8 months of ridership data. Our results show that equipping each bike station with a single grid-tied solar panel is adequate to meet the annual charging demand from electric bikes and achieve net-zero operation using net-metering. For an off-grid setup, our analysis shows that a bike station needs twice as many solar panels, on average, along with a 1.8kWh battery, with the busiest bike station needing 6× more solar capacity than in the net-metering case. Our analysis also reveals a tradeoff between the array size and the battery size needed to achieve true-zero carbon operation for the electric bike share system. 

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4. Exploring Patterns of Demand in Bike Sharing Systems Via Replicated Point Process Models

   https://doi.org/10.1111/rssc.12322  

   Gervini, Daniel ; Khanal, Manoj ( November 2018 , Journal of the Royal Statistical Society Series C: Applied Statistics)

   Understanding patterns of demand is fundamental for fleet management of bike sharing systems. We analyse data from the Divvy system of the city of Chicago. We show that the demand for bicycles can be modelled as a multivariate temporal point process, with each dimension corresponding to a bike station in the network. The availability of daily replications of the process enables non-parametric estimation of the intensity functions, even for stations with low daily counts, and straightforward estimation of pairwise correlations between stations. These correlations are then used for clustering, revealing different patterns of bike usage.

    

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5. Hydrogen Station Location Planning via Geodesign in Connecticut: Comparing Optimization Models and Structured Stakeholder Collaboration

   https://doi.org/10.3390/en14227747  

   Lopez Jaramillo, Oscar ; Rinebold, Joel ; Kuby, Michael ; Kelley, Scott ; Ruddell, Darren ; Stotts, Rhian ; Krafft, Aimee ; Wentz, Elizabeth ( November 2021 , Energies)

   Geodesign is a participatory planning approach in which stakeholders use geographic information systems to develop and vet alternative design scenarios in a collaborative and iterative process. This study is based on a 2019 geodesign workshop in which 17 participants from industry, government, university, and non-profit sectors worked together to design an initial network of hydrogen refueling stations in the Hartford, Connecticut, metropolitan area. The workshop involved identifying relevant location factors, rapid prototyping of station network designs, and developing consensus on a final design. The geodesign platform, which was designed specifically for facility location problems, enables breakout groups to add or delete stations with a simple point-and-click operation, view and overlay different map layers, compute performance metrics, and compare their designs to those of other groups. By using these sources of information and their own expert local knowledge, participants recommended six locations for hydrogen refueling stations over two distinct phases of station installation. We quantitatively and qualitatively compared workshop recommendations to solutions of three optimal station location models that have been used to recommend station locations, which minimize travel times from stations to population and traffic or maximize trips that can be refueled on origin–destination routes. In a post-workshop survey, participants rated the workshop highly for facilitating mutual understanding and information sharing among stakeholders. To our knowledge, this workshop represents the first application of geodesign for hydrogen refueling station infrastructure planning. 

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