| Bicycle rebalancing activities are a major source of carbon emissions in the operation phase of shared bikes.Due to the difficulty in obtaining the actual data of the rebalancing activity and the complexity of its process,there is no good method to quantify its carbon emissions at present.Studies on carbon emission accounting of bike sharing systems（BSS）also rarely consider the bike rebalancing process,resulting in an incomplete accounting of the overall carbon emissions of the system.In addition,there are few comparative studies on carbon emissions of different bike rebalancing modes,especially on the carbon emissions of tricycles,which play an important role in short-distance logistics distribution currently.In all,how much carbon emissions do BSSs generate from bicycle rebalancing activities?Are urban BSSs really carbon-reducing?What is the impact of different rebalancing modes on carbon emissions of the system?These remaining scientific problems need more in-depth research.To full fill up the gap,we select the BSS of New York City,a world-class cycling city,as a case study to carry out the following research.First,big data analysis was used to describe the basic characteristics of urban BSS and spatial-temporal patterns of cycling activities.Second,a Bike Sharing System-Rebalancing Emission Quantitive Model（BSS-REQM）is proposed,in which,based on the historical cycling raw big data,data mining method was used to reverse-extract historical bike-rebalancing activity record and the vehicle routing problem model was used to restore the vehicle optimal daily rebalancing route and estimate the conservative rebalancing distance.Through this model,the temporal and spatial patterns of urban shared bike rebalancing activities were revealed,the correlation between cycling activity level and rebalancing activity level was also analyzed,and the carbon emissions of the historical bike rebalancing in the system was estimated.Third,the carbon emissions of different rebalancing modes of urban BSSs were compared,and the life cycle carbon emissions accounting work of electric tricycles and human tricycles,which were rarely studied,was carried out to evaluate the potential carbon emission reduction benefits of using tricycles to assist diesel trucks in dispatching bikes in some urban areas.Finally,the carbon footprint assessment framework of the BSS is proposed,which combines the carbon emission assessment results of the bike rebalancing process,i.e.the output of BSS-REQM model,with the life-cycle carbon footprint of the infrastructure（including bikes,docks and stations）and the carbon emission reduction from replacing other energy-intensive transportation modes by cycling,to evaluate the carbon emission structure and reduction benefit of urban bike-sharing system in its life cycle from the system level.The main results are as follows:（1）Based on the analysis of cycling activity big data,it is found that the cycling activity of Citi Bike-sharing project in New York City in 2020 fluctuates greatly in a year.Winter and spring were the low season,summer and autumn were the peak season,and March and April witnessed the low season due to the epidemic.On weekdays,cycling activities showed double peaks in the morning and evening,and single peak on weekends.The overall scale of bike stations and cycling activity level of the system are significantly higher than before,and Manhattan is the most active region.（2）Combined with data mining algorithms,a Bike sharing system-Rebalancing Emission Quantitive Model（BSS-REQM）was proposed and tested on the New York City bike sharing study case.It is found that the fluctuation pattern of New York City’s bike-sharing activity throughout the year was similar to that of cycling activity,with low season in spring and winter,high season in summer and fall,and low season in March and April due to the epidemic.80%of the top 20 chains with the highest number of dispatched bikes are short-distance dispatch routes（road network distance less than 200m）.There is a good positive relationship between the total number of daily rebalance waves and daily cycling activity.The user-side incentive mechanism promotes 43.88%of bike dispatching by the user side through riding.（3）Dispatch pattern scenario simulation was carried out to identify the vehicle types for dispatching waves.Life cycle carbon footprint accounting was carried out for human-powered and electric tricycles,and it was found that both types of tricycles are sensitive to life cycle riding kilometers,so that making full use of carriers and rationalizing transportation schemes will help improve resource utilization.By constructing the vehicle path problem（VRP）sub-model of the BSS-REQM model,20 sample days with different riding activity are sampled as representatives,and the city’s approximate global optimal dispatch route with all historical dispatch wave tasks completed daily is obtained.Comparing the different dispatch mode scenarios,it is thus found that tricycle assistance to diesel trucks in localized areas of Manhattan in New York City contributed to an overall annual dispatch carbon reduction of about 7%.The correlation law between the historical necessary dispatch distance values and the rebalance wave number,the number of dispatched bicycles and the riding heat under different riding heat is analyzed,and the overall dispatch distance of the system is inferred.The system dispatching efficiency has been improved in recent years.（4）The carbon emssions assessment framework of the BSS is proposed to comprehensively assess the carbon footprint of the Citi Bike Sharing System,in which the results of the carbon emission assessment of the bike rebalancing process are combined with the life-cycle carbon footprint of the system’s infrastructure（including bicycle fleet,docks and stations）,and the carbon emission reduction generated by the cycling end in lieu of other energy-intensive transportation modes.Result showed that the carbon emissions reduction from the Citi Bike Share system has been found to be extremely high,with the carbon emissions reduction from cycling substitution for other transportation modes,totaling14,333.4 t CO2-eq in 2020,being 1.8 times the total carbon expenditure of the system infrastructure and dispatching process over 10 years.The carbon emissions from the bicycle-rebalancing process estimated by this study account for at least 11.8%of the overall system emissions.Except for the cycling activity,the system carbon footprint is most sensitive to the life-cycle carbon footprint of docks,followed by stations.Quantifying environmental impact of the rebalance process promotes the systematic and comprehensive evaluation of bike sharing systems,providing a scientific guidance for the fine operation,sustainable development and management of the bike-sharing industry. |
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