Life Cycle Assessment of Motor Bike and Electric Bike in Urban Areas of China

Motor bikes (m-bike) and electric bikes (e-bike) are widely used in urban areas of China. Life cycle assessment of m-bike and e-bike are presented to compare their energy use and environmental emission in a life cycle span. An m-bike and an e-bike are disassembled to collect material composition data for the life cycle assessment. The results show that e-bike consumes less energy and has less global warming potential (GWP), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), dissolved solids (DS), hydrocarbons (HC) than m-bike during life cycle. But e-bike generates more solid wastes, and more acidification potential (AP), heavy metal (HM) than m-bike. Advanced batteries and clean coal fired power plant technologies are recommended to promote e-bike use in urban area.

Electric scooter injuries:Incidence and injury patterns at a level I trauma center

Purpose:Electric scooters(e-scooters)have become an increasingly popular mode of public transportation in recent years.As the incidence of related injuries rises,it is important to understand specific fracture patterns unique to e-scooters and electric bikes(e-bikes)to help guide management.The purpose of this study was to review the prevalence and describe specific fracture patterns of e-scooter and ebike related injuries at the busiest level 1 trauma center in the borough of Manhattan.Methods:Chart review to determine mechanism of injury was performed on all patients for whom an orthopedic consult was requested from 1/1/2021 to 12/31/2021.All patients whose injuries were sustained due to an e-scooter or e-bike were further reviewed for demographics,injury characteristics including fracture pattern,and definitive injury management.Any patients who had an orthopedic consult placed for a reason other than an acute injury were excluded.Descriptive statistics are reported as frequency(percentage)for categorical variables and means for continuous variables.Results:Of the 1815 orthopedic consults requested,1357(74.8%)were for acute injury management.Of those with acute injuries,119(8.8%)sustained 136 e-scooter or e-bike related injuries.There were 92(77.3%)males at an average age of(33.8±15.7)years.Approximately one-fifth of all patients presented in June 2021(26,21.8%).There was a 9.2%rate of open fractures.The 136 injuries were evenly split between the upper and lower extremities,with 57(47.9%)upper extremity,57(47.9%)lower extremity injuries,and 5(4.2%)concomitant upper and lower extremity injuries.The most common fracture patterns were ankle fractures(16,11.7%),followed by tibial shaft(14,10.2%),tibial plateau(13,9.5%),and radial head fractures(11,8.0%).There was a 33.3%incidence of associated posterior malleolar fractures in the spiral tibial shaft fractures,31.0%of posterior malleolar involvement and 18.8%of isolated vertical medial malleolar fractures in the ankle fractures,and 61.5%of posterior comminution in the tibial plateau fractures.Conclusion:E-scooter and e-bike related injuries have a high incidence of tibial shaft fractures,ankle fractures,tibial plateau fractures,and radial head fractures.There should be a high index of suspicion for posterior and medial involvement in lower extremity fractures sustained due to e-scooter or e-bikes.Identifying specific fracture patterns seen in e-scooter and e-bike related mechanisms will help guide management of these injuries.

Injury severity analysis of electric bike crashes in Changsha, Hunan Province: taking different lighting conditions into consideration

With the increasing use of electric bikes, electric bike crashes occur frequently. Analysing the influencing factors of electric bikecrashes is an effective way to reduce mortality and improve road safety. In this paper, spatial analysis is performed by geographicinformation system (GIS) to present the hot spots of electric bike crashes during daylight and darkness in Changsha, Hunan Province,China. Based on the Ordered Probit (OP) model, we studied the risk factors that led to different severities of electric bike crashes.The results show that the main influencing variables include age, illegal behaviour, collision type and road factors. During daylightand darkness, elderly electric bike riders over the age of 65 years have a higher probability of fatal crashes. Not following trafficsignals and reverse driving are significantly related to the severity of riders’ injuries. In darkness, frontal collisions are significantfactors causing rider injury. In daylight, more serious crashes will be caused in bend and slope road segments. In darkness, roadswith no physically separated bicycle lanes increases the risk of riders being injured. Electric bike crashes are mainly concentratedin the commercial, public service and residential areas in the main urban area. In suburbs at darkness, electric bike riders are morelikely to be seriously injured. Adding protectionmeasures, such as improved lighting, non-motorized lane facilities and interventionstargeting illegal behaviour in the hot spot areas can effectively reduce the number of electric bike crashes in complex traffic.