The government has committed to end the sale of new petrol and diesel cars and vans by 2035. Using DfT uptake trajectories, there is predicted to be a critical mass of 40% Battery Electric Vehicles (BEVs) on the roads in 2035. However, effectively benchmarking policy interventions which could reduce emissions from the last mile sector is hindered by a lack of relevant data on emissions generated by last mile deliveries and travel patterns derived from logistic activities. There is a risk this lack of data could delay the uptake of zero emissions vehicles, modal shift and demand consolidation among logistics firms which would support the decarbonisation of the sector. Freight travel patterns are usually considered commercially sensitive and require a considerable effort in anonymisation and aggregation, which often hinders data sharing.
The Rural Innovation for Sustainable Environments (RISE) for Decarbonising Last Mile Road Freight project, jointly funded by SciTech and the Decarbonisation Strategy team at the Department for Transport, looked at ways to decarbonise road freight using 2021 mobile phone data to derive anonymised and aggregated travel patterns for last mile deliveries. It used this data to develop an integrated agent-based and emissions modelling tool to quantify emissions reduction from different interventions. The advantage of using MND is that it allows users to overcome the silos present in the Freight industry with logistic activities derived from all supply chains and for all last mile operators.
The RISE agent-based model represents a multimodal, transport model of the North East, where movements of people and goods are modelled. The model highlights bottlenecks and hot-spots with higher carbon emissions, which could help cities and towns develop strategies to meet their own transport decarbonisation targets. Scenarios were modelled for years 2021, 2031 and 2035 to explore the impact electrification, shipment consolidation and mode shift had on emissions generated from the last mile sector.