Quantifying Transport Energy Resilience

Abstract

A reduction in the energy intensity of private transport is the least cost-feasible approach to mitigate the uncertainties of future oil supplies, given the impending peak in world conventional oil production. The built environment and transport infrastructure of an urban form determine the extent to which low-impact adaptations to these constraints are possible and hence the resilience of residents to fuel price shocks and constraints. This paper introduces the concept of active mode accessibility (AMA), defined as the proportion of activities that can be reached by active modes alone, given the population demographics of the study area. AMA is characterized by the underlying geographic form of an urban area and its transport networks. High AMA means that the resident transport activity system can be served with minimal energy input; consequently resilience to fuel shocks and constraints is greater. The AMA method is based on accessibility analysis and extends the depth of the analysis with energy-based activity modeling and defines a measure of energy accessibility. The paper introduces a spatial method for calculating the AMA within a selected study area and a geographic information system–based tool for applying the method, and presents two case studies. Central Christchurch, New Zealand, gives an AMA of 100% because the city has a high density of destinations and a wide range of local facilities available for every activity. The satellite township of Rolleston gives a significantly lower AMA of 59%, principally because of a lack of local preschool and high school facilities and an insufficient diversity of destinations for some activities.

Greening passenger transport: a review

“…Steep rises in car travel costs would thus heavily penalize them. (Similarly for the New Zealand city of Christchurch, Rendall et al (2011) showed that, compared to a central city location, their outer suburban study area was less resilient to fuel price rises, since far fewer destinations could be accessed by active modes.) These same disadvantages also apply to non-urban populations.…”

Estimating individual physical capability (IPC) to make journeys by bicycle

“…On the other hand, there exists a number of studies that have explicitly modeled some aspects of IPC, such as physical capabilities (British Medical Association & Hillman, 1992;Parkin & Rotheram, 2010); variation in fitness across populations (Dickinson, Kingham, Copsey, & Hougie, 2003;McArdle, 2010;Menghini, Carrasco, Sch€ ussler, & Axhausen, 2010;Rendall, Page, Reitsma, Van Houten, & Krumdieck, 2011;Rietveld, 2000); environmental factors affecting cycling (Keay, 1992;Milakis & Athanasopoulos, 2014;Phung & Rose, 2007); and the impact of topographic factors on walkability (Klein, Guti errez, & Escobar, 2015). In addition, recent work has considered the interaction between distance, environmental factors, and perceptions (Yang & Zacharias, 2016).…”

“…The IPC measures could be refined to consider whether an individual's maximum cumulative energy expenditure (MCEE) is sufficient to fulfill their daily activity requirement. This would build on the Active Mode Accessibility (AMA) work of Rendall et al (2011) or be applied in a largescale agent-based travel simulation such as MATSIM (http:// www.matsim.org).…”

Voila! A New Measure of Oil Vulnerability for Cities

“…The Minimum Energy Travel Activity Access characterisation (METAA) is an estimation of the minimum transport energy required by households to meet their day-to-day activity requirements [26,28]. The model is summarised here, a full description can be found in Rendall [26].…”