Woodcock James, Aldred Rachel, Lovelace Robin, Strain Tessa, Goodman Anna
University of Cambridge, UK.
University of Westminster, UK.
J Transp Health. 2021 Sep;22:101066. doi: 10.1016/j.jth.2021.101066.
The Propensity to Cycle Tool (PCT) is a widely used free, open source and publicly available tool for modelling cycling uptake and corresponding health and carbon impacts in England and Wales. In this paper we present the methods for our new individual-level modelling representing all commuters in England and Wales.
Scenario commuter cycling potential in the PCT is modelled as a function of route distance and hilliness between home and work. Our new individual-level approach has allowed us to create an additional "Near Market" scenario where age, gender, ethnicity, car ownership and area level deprivation also affect an individual's likelihood of switching to cycling. For this and other scenarios, we calculate the carbon benefits of cycling uptake based on the trip distance and previous mode, while health benefits are additionally affected by hilliness and baseline average mortality risk. This allows the estimation of how health and carbon benefits differ by demographic group as well as by scenario.
While cycle commuting in England and Wales is demographically skewed towards men and white people, women and people from ethnic minorities have greater cycling potential based on route distance and hilliness. Benefits from cycling uptake are distributed differently again. For example, while increasing female cycling mode share is good for equity, each additional female cyclist generates a smaller average health and carbon benefit than a male cyclist. This is based on women's lower baseline mortality risk, shorter commute travel distances, and lower propensity to commute by car than men.
We have demonstrated a new approach to modelling that allows for more sophisticated and nuanced assessment of cycling uptake and subsequent benefits, under different scenarios. Health and carbon are increasingly incorporated into appraisal of active travel schemes, valuing important outcomes. However, especially with better representation of demographic factors, this can act as a barrier to equity goals.
骑行倾向工具(PCT)是一款广泛使用的免费、开源且公开可用的工具,用于模拟英格兰和威尔士的骑行普及率以及相应的健康和碳影响。在本文中,我们介绍了针对英格兰和威尔士所有通勤者的新个体层面建模方法。
PCT中的情景通勤者骑行潜力被建模为家和工作地点之间路线距离和坡度的函数。我们新的个体层面方法使我们能够创建一个额外的“接近市场”情景,其中年龄、性别、种族、汽车拥有情况和地区层面的贫困程度也会影响个人转向骑行的可能性。对于此情景及其他情景,我们根据出行距离和先前的出行方式计算骑行普及率的碳效益,而健康效益还会受到坡度和基线平均死亡率风险的影响。这使得能够估计不同人口群体以及不同情景下健康和碳效益的差异。
虽然在英格兰和威尔士,骑行通勤在人口统计学上偏向男性和白人,但基于路线距离和坡度,女性和少数族裔群体具有更大的骑行潜力。骑行普及率带来的效益分布也有所不同。例如,虽然增加女性骑行模式份额有利于公平,但每增加一名女性骑行者所产生的平均健康和碳效益比男性骑行者要小。这是基于女性较低的基线死亡率风险、较短的通勤出行距离以及比男性更低的开车通勤倾向。
我们展示了一种新的建模方法,该方法能够在不同情景下对骑行普及率及其后续效益进行更精细和细致入微的评估。健康和碳因素越来越多地被纳入对积极出行计划的评估中,重视重要成果。然而,特别是在更好地体现人口因素的情况下,这可能会成为实现公平目标的障碍。