Authors: Claire Shadbolt*, Leeds Institute for Data Analytics, Ian Philips, Institute for Transport Studies, University of Leeds
Topics: Transportation Geography, Spatial Analysis & Modeling
Keywords: Transport geography, GIS, Energy geography, Climate change, Equitable decarbonisation.
Session Type: Poster
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There is a vital need to decarbonise the transport sector. Technologies, such as electric cars and app-based mobility services, are promoted as sustainable transport solutions. The climate science shows this alone is not enough. Policies that create a greater shift to active travel and to constrain travel demand are also required.
We aim to identify the demand for travel for various purposes and place it in the context of socio-demographic data, for example car ownership, economic status and location. From this we can estimate small area indicators of where different policies and technologies can have the greatest impact on CO2 emissions reductions. We also consider the social vulnerabilities that might occur through such initiatives. Individuals have different capabilities in terms of adapting to a new transport mode or reducing demand. Hence a blanket policy, for instance, a fuel tax or a congestion charge, might not have equal levels of success across a population due to these differences. It is also indicates where possible excess demand exists. Insights from geographic data science inform the governance of place-based decarbonisation.
We carried out a spatial microsimulation at the individual and household level. To avoid relying on out of date census data we apply microsimulation based population projections and make use of recent travel survey data.
The results describe small area spatial patterns of the capability to lower transport emissions, contextualised by the effects on a population’s vulnerability. It provides urgently needed insights to policymakers aiming to identify equitable solutions for specific locations
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