In the pursuit of sustainable urbanization,Bike-Sharing Services(BSS)emerge as a pivotal instrument for promoting green,low-carbon transit.While BSS is often commended for its environmental benefits,we offer a more nu...In the pursuit of sustainable urbanization,Bike-Sharing Services(BSS)emerge as a pivotal instrument for promoting green,low-carbon transit.While BSS is often commended for its environmental benefits,we offer a more nuanced analysis that elucidates previously neglected aspects.Through the Dominant Travel Distance Model(DTDM),we evaluate the potential of BSS to replace other transportation modes for specific journey based on travel distance.Utilizing multiscale geographically weighted regression(MGWR),we illuminate the relationship between BSS’s environmental benefits and built-environment attributes.The life cycle analysis(LCA)quantifies greenhouse gas(GHG)emissions from production to operation,providing a deeper understanding of BSS’s environmental benefits.Notably,our study focuses on Xiamen Island,a Chinese“Type Ⅱ large-sized city”(1–3 million population),contrasting with the predominantly studied“super large-sized cities”(over 10 million population).Our findings highlight:(1)A single BSS trip in Xiamen Island reduces GHG emissions by an average of 19.97 g CO_(2)-eq,accumulating monthly savings of 144.477 t CO_(2)-eq.(2)Areas in the southwest,northeast,and southeast of Xiamen Island,characterized by high population densities,register significant BSS environmental benefits.(3)At a global level,the stepwise regression model identifies five key built environment factors influencing BSS’s GHG mitigation.(4)Regionally,MGWR enhances model precision,indicating that these five factors function at diverse spatial scales,affecting BSS’s environmental benefits variably.展开更多
Shared electric scooters(e-scooter)are booming across the world and widely regarded as a sustainable mobility service.An increasing number of studies have investigated the e-scooter trip patterns,safety risks,and envi...Shared electric scooters(e-scooter)are booming across the world and widely regarded as a sustainable mobility service.An increasing number of studies have investigated the e-scooter trip patterns,safety risks,and environmental impacts,but few considered the energy efficiency of e-scooters.In this research,we collected the operational data of e-scooters from a major provider in Gothenburg to shed light on the energy efficiency performance of e-scooters in real cases.We first develop a multiple logarithmic regression model to examine the energy consumption of single trips and influencing factors.With the regression model,a Monte Carlo simulation framework is proposed to estimate the fleet energy consumption in various scenarios,taking into account both trip-related energy usage and energy loss in idle status.The results indicate that 40%of e-scooter battery energy was wasted in idle status in the current practice,mainly due to the relatively low usage rate(0.83)of e-scooters.If the average usage rate drops below 0.5,the wasted energy could reach up to 53%.In the end,we present a field example to showcase how to optimally integrate public transport with e-scooters from the perspective of energy efficiency.We hope the findings of this study could help understand and resolve the current and future challenges regarding the ever-growing e-scooter services.展开更多
Daily commuting constitutes a major part of urban mobility.Personalized transport modes for daily commuting have been adopted increasingly,such as car driving,shared mobility,etc.In general,this trend is against the S...Daily commuting constitutes a major part of urban mobility.Personalized transport modes for daily commuting have been adopted increasingly,such as car driving,shared mobility,etc.In general,this trend is against the Sustainable Development Goals'aim of reducing emissions from the transport sector and improving urban ecosystem sustainability.We show the related statistics and advocate the use of nonmotor vehicles to mitigate greenhouse gas emissions and adverse environmental impacts of personalized daily commuting.展开更多
基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011174)the National Natural Science Foundation of China(Grant No.42101351).
文摘In the pursuit of sustainable urbanization,Bike-Sharing Services(BSS)emerge as a pivotal instrument for promoting green,low-carbon transit.While BSS is often commended for its environmental benefits,we offer a more nuanced analysis that elucidates previously neglected aspects.Through the Dominant Travel Distance Model(DTDM),we evaluate the potential of BSS to replace other transportation modes for specific journey based on travel distance.Utilizing multiscale geographically weighted regression(MGWR),we illuminate the relationship between BSS’s environmental benefits and built-environment attributes.The life cycle analysis(LCA)quantifies greenhouse gas(GHG)emissions from production to operation,providing a deeper understanding of BSS’s environmental benefits.Notably,our study focuses on Xiamen Island,a Chinese“Type Ⅱ large-sized city”(1–3 million population),contrasting with the predominantly studied“super large-sized cities”(over 10 million population).Our findings highlight:(1)A single BSS trip in Xiamen Island reduces GHG emissions by an average of 19.97 g CO_(2)-eq,accumulating monthly savings of 144.477 t CO_(2)-eq.(2)Areas in the southwest,northeast,and southeast of Xiamen Island,characterized by high population densities,register significant BSS environmental benefits.(3)At a global level,the stepwise regression model identifies five key built environment factors influencing BSS’s GHG mitigation.(4)Regionally,MGWR enhances model precision,indicating that these five factors function at diverse spatial scales,affecting BSS’s environmental benefits variably.
文摘Shared electric scooters(e-scooter)are booming across the world and widely regarded as a sustainable mobility service.An increasing number of studies have investigated the e-scooter trip patterns,safety risks,and environmental impacts,but few considered the energy efficiency of e-scooters.In this research,we collected the operational data of e-scooters from a major provider in Gothenburg to shed light on the energy efficiency performance of e-scooters in real cases.We first develop a multiple logarithmic regression model to examine the energy consumption of single trips and influencing factors.With the regression model,a Monte Carlo simulation framework is proposed to estimate the fleet energy consumption in various scenarios,taking into account both trip-related energy usage and energy loss in idle status.The results indicate that 40%of e-scooter battery energy was wasted in idle status in the current practice,mainly due to the relatively low usage rate(0.83)of e-scooters.If the average usage rate drops below 0.5,the wasted energy could reach up to 53%.In the end,we present a field example to showcase how to optimally integrate public transport with e-scooters from the perspective of energy efficiency.We hope the findings of this study could help understand and resolve the current and future challenges regarding the ever-growing e-scooter services.
基金supported by the National Natural Science Foundation of China(grant numbers 72171210 and 72350710798)China Postdoctoral Science Foundation(grant number 2021M702819)+1 种基金Zhejiang Provincial Natural Science Foundation of China(grant number LZ23E080002)the Smart Urban Future(SURF)Laboratory,Zhejiang Province
文摘Daily commuting constitutes a major part of urban mobility.Personalized transport modes for daily commuting have been adopted increasingly,such as car driving,shared mobility,etc.In general,this trend is against the Sustainable Development Goals'aim of reducing emissions from the transport sector and improving urban ecosystem sustainability.We show the related statistics and advocate the use of nonmotor vehicles to mitigate greenhouse gas emissions and adverse environmental impacts of personalized daily commuting.
