A new study in Case Studies on Transport Policy by Annette Rondaij, Bram Kin, Hans Quak, and colleagues (LiLS partners: Dutch TNO, HAN, and BUAS) offers a timely corrective to the electrification-first narrative that dominates urban freight policy. While battery electric vehicles remain the default answer to decarbonizing city logistics, the authors argue that measures aimed at reducing or reorganizing vehicle movements deserve equal attention, and their new model, Decamod, shows why.
Decamod decomposes urban logistics traffic into six segments (construction, facility/services, general cargo and retail, parcels and express, temperature-controlled, and waste) by combining ANPR camera data, RDW vehicle registrations, and traffic models. This decomposition matters because policy attention is skewed: parcel deliveries dominate the public debate, yet construction logistics generates up to six times more vehicles and emissions in Dutch cities.
Applied to a case study of Utrecht, the model tested three scenarios building on McKinnon’s decarbonization framework: (I) reducing freight demand only, (II) adding modal shift, and (III) adding shared use of fleets and assets (consolidation centers, microhubs, horizontal collaboration).
Against a 2030 business-as-usual baseline, which already delivers a 14% emissions cut through fleet electrification and EU/national policy, the additional scenarios added modest but meaningful gains: +3% from demand reduction, +5% from modal shift, and a striking +22% once consolidation and asset-sharing measures were included. The kilometer-reduction effect was even more pronounced, with Scenario III cutting vehicle-km by 21% versus BAU.
Two findings stand out for practitioners. First, shared-use measures (urban consolidation centers, microhubs, coordinated time windows) consistently outperform demand-reduction and modal-shift measures on both emissions and kilometers, suggesting these deserve more prominent placement in municipal logistics strategies. Second, roughly half of total urban logistics emissions originate from construction and service-related trips — segments that are largely invisible in current policy because the companies involved don’t see themselves as “logistics” operators at all. This is as much a governance and communication challenge as a technical one.
The authors are candid about Decamod’s limitations: it’s a proprietary tool built on expert judgment and literature-derived assumptions rather than empirical pilots; it doesn’t yet model interaction effects between measures; and it excludes spatial occupancy. This is an increasingly relevant metric, as EVs still occupy scarce curb and road space.
Still, the core message is a useful one for practitioners: electrification alone won’t get cities to their climate targets, and the sharing economy of urban freight, not just the powertrain, may be where the next real gains lie. For cities without Utrecht’s data richness, the authors note the approach is transferable using proxy relationships from comparable urban areas.
Also read: City logistics data: the holy grail for policymakers