Commuting is a daily ritual for a large proportion of the world's population. It is important materially, consuming large amounts of time, money and natural resources. As with many routine activities travel to work is often taken for granted but its energy consumption is of particular interest due to its heavy reliance on fossil fuels and the inflexibility of the demand for commuting. This understudied area of knowledge, the energy costs of travel to work, forms the basis of the thesis. There is much research into commuting and transport energy use as separate fields, but they have rarely been combined in the same analysis, let alone at high levels of geographical resolution. The well-established field of spatial microsimulation offers tools for investigating commuting patterns in detail at local and individual levels, with major potential benefits for transport planning. For the first time this method is deployed to investigate variability in commuter energy use both between and within small administrative zones. The maps of commuter energy use presented in this thesis illustrate this variability at national, regional and local levels. Supporting previous research, the results suggest that a range of geographical factors influence energy use for travel. This has important policy implications: when high transport energy use in commuting is due to lack of jobs in the vicinity, for example, modal shift (e.g.~from cars to bicycles) on its own has a limited potential to reduce energy costs. Such insights are quantified using existing aggregate data. The main methodological contribution of this work, however, is to add individual-level factors to the analysis - creating the potential for policy makers to also assess the distributional impacts of their interventions and target specific types of commuters having high transport energy costs, rather than treat areas as homogeneous blocks. This potential is demonstrated with a case study of South Yorkshire, where commuting energy use is cross-tabulated by socio-economic variables and disaggregated over geographical space. The areas where commuting energy use is less evenly distributed across the population, for example in urban centres, are likely to benefit most from policies that target the specific groups. Areas where commuter energy use is more even, such as Stocksbridge (in Northwest Sheffield), will benefit from more universal policies. The thesis contributes to human knowledge new information about the energy costs of commuting, its variability at various levels and insight into the implications. New methods of generating and analysing individual-level data for the analysis of commuter energy use have also been developed. These are reproducible (see the GitHub repository https://github.com/Robinlovelace/thesis-reproducible for example code and data) and will be of interest to researchers and policy makers investigating the energy security, resource efficiency and potential welfare impacts of interventions in personal travel systems
