The infrastructure of a city can influence inequality on multiple axes. In this work we aim to create a generalizable, open source methodology to analyse inequalities in transport accessibility which, paired with a thorough analysis of building energy efficiency, can lead us to pinpoint urban areas where both heating and transport needs lead to a high economical impact for many households. Real micro-data extracted from mobility questionnaires and cell phone data is used to compute and adjust a multi-agent transport simulation based on utility and cost functions for both travel and destination activities, which provides us with modes, times and fees for each transport demand. This mobility analysis performed on the whole street and public transport network of Madrid is paired with energy efficiency data of housing to give a multidimensional approach to inequality inherent to the spatial distribution and quality of infrastructure in Madrid.
