scholarly journals Spatial variation in bicycling: a retrospective review of travel survey data from Greater Melbourne, Australia

2021 ◽  
Author(s):  
Ben Beck ◽  
Meghan Winters ◽  
Jason Thompson ◽  
Mark Stevenson ◽  
Christopher Pettit

Understanding spatial variation in bicycling within cities is necessary to identify and address inequities. We aimed to explore spatial variation in bicycling and explore how bicycling rates vary across population sub-groups. We conducted a retrospective analysis of household travel survey data in Greater Melbourne, Australia. We present a descriptive analysis of bicycling behaviour across local government areas (LGAs; n=31), with a focus on quantifying spatial variation in the number and proportion of trips made by bike, and by age, sex and trip distance. Associations between the proportion of infrastructure that had provision for biking and the proportion of all trips made by bike were analysed using linear regression. Overall, 1.7% of all trips were made by bike. While more than half (53.2%) of all trips were less than 5km, only 2% of these trips were by bike. Across LGAs, there was considerable variation in the proportion of trips made by bike (range: 0.1% to 5.7%). Mode share by females was 35.0%, and this varied across LGAs from 0% to 49%. Tor each percentage increase in the proportion of infrastructure that had provision for biking, there was an associated 0.2% increase in the proportion of trips made by bike (coefficient = 0.20; SE = 0.05; adjusted R2 = 0.38). While we observed a low bicycle mode share, more than half of all trips were less than 5 km, demonstrating substantial opportunity to increase the number of trips taken by bike.

2019 ◽  
Vol 11 (6) ◽  
pp. 1684 ◽  
Author(s):  
Chengcheng Xu ◽  
Shuyue Wu

This study aimed to investigate the effects of household characteristics on household traffic emissions. The household travel survey data conducted in the Jiangning District of Nanjing City, China were used. The vehicle emissions of household members’ trips were calculated using average emission factors by average speed and vehicle category. Descriptive statistics analysis showed that the average daily traffic emissions of CO, NOx and PM2.5 per household are 8.66 g, 0.55 g and 0.04 g respectively. The household traffic emissions of these three pollutants were found to have imbalanced distributions across households. The top 20% highest-emission households accounted for nearly two thirds of the total emissions. Based on the one-way ANOVA tests, the means of CO, NOx and PM2.5 emissions were found to be significantly different over households with different member numbers, automobile numbers, annual income and access to the subway. Finally, the household daily traffic emissions were linked with household characteristics based on multiple linear regressions. The contributing factors are slightly different among the three different emissions. The number of private vehicles, number of motorcycles, and household income significantly affect all three emissions. More specifically, the number of private vehicles has positive effects on CO and PM2.5 emissions, but negative effect on NOx emissions. The number of motorcycles and the household income have positive effects on all three emissions.


2016 ◽  
Vol 3 (2) ◽  
pp. 154-160 ◽  
Author(s):  
Casey P. Durand ◽  
Xiaohui Tang ◽  
Kelley P. Gabriel ◽  
Ipek N. Sener ◽  
Abiodun O. Oluyomi ◽  
...  

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