Systems thinking-informed and data-driven urban decarbonisation framework for individual, community and urban scale climate action

There is an urgent need to rapidly reduce greenhouse gas (GHG) emissions and, although human activity is a primary driver of emissions, a knowledge gap remains in terms of the key individual and collective drivers of emissions, and on how to harmonise citizen-led climate action with top-down emissions mitigation policy. In response to this, an urban decarbonisation framework which was informed by systems thinking was developed to support multi-level climate action and decision making. Another aim was to demonstrate the integration of a data-driven and activity-based GHG emissions model for individuals into the framework to enable decarbonisation. This model was populated using individual activity and lifestyle data which were collected for 172 people using a smartphone application. The resulting emissions drivers were identified as well as their interaction with the overarching urban decarbonisation framework. The research will have important implications in terms of informing emissions mitigation efforts at individual, community and urban scales. By applying the framework, individual data and GHG emissions modelled at scale can inform citizen and population-level actions and high-level emissions mitigation policy for accelerating the sustainability transition that our societies and cities must urgently undergo.