While freight transportation is a necessary activity to sustain cities’ social and economic life—enabling the movement and deployment of goods and services in urbanized areas—it also accounts for a significant portion of carbon dioxide (CO₂) emissions. The urban freight ecosystem is a complex network of agents, both public and private. Reducing CO₂ emissions from urban freight requires the collaboration and coordination between those agents, but the motivations behind their goals, strategies for achieving those goals, and the challenges faced by each agent may differ. In this paper, we document the strategies aimed at reducing CO₂ emissions considered by cities and private companies with the goal of understanding the challenges to progress faced by each. To accomplish this, we interviewed officials from purposefully sampled city departments in North America and private companies involved in city logistics. We found that cities face challenges related to a lack of strong leadership, resources, and policy tools. Companies must consider technological challenges, costs, and their workforce before reducing emissions. Cities and companies are challenged by the disaggregated nature of the urban freight “system”—a system that is not organized at the municipal scale and that is driven by performance and customer expectations.

This work applies an unsupervised clustering algorithm to blockface zoning data to identify typical curb configurations in a city. Data is obtained via the city of Seattle’s (Washington, USA) open data portal. To compare the distribution of blockfaces of varying length, all blockfaces are normalized where each zone type is presented as a percentage of the total blockface length in an order-preserving format. Common zone sequences are identified via k-modes clustering, where an optimal choice of k is cross-validated, quantifying the number of curb configurations to represent the majority of Seattle’s blockfaces. All documented code and data are open source and available at https://github.com/pnnl/curbclustering.

Inefficient curb space allocation increases congestion and emissions at airports. Variable message signs (VMS) can alleviate this issue, guiding vehicles from congested to underutilized curbs. However, VMS effectiveness hinges on the right activation and deactivation timing. Using a microsimulation model of the Seattle-Tacoma International Airport, we analyzed the impacts of implementing VMS and determined the best time to turn the sign on and off. We simulated sixteen VMS management scenarios and compared the results against those of a baseline where there was no VMS. We found that strategic and timely management of the VMS is crucial to achieving improvements in congestion and curb performance. Specifically, activating VMS before congestion started on the sending link and deactivating it before congestion began on the receiving link substantially improved curb productivity and accessibility, vehicle delay, and CO ₂ emissions. On the other hand, if not managed correctly, VMS may lead to little to no improvements, or even negative impacts on traffic conditions and curb performance. For instance, late activation or deactivation can worsen curb accessibility and vehicle delay. Our framework provides valuable insights into how airports could successfully manage VMS technologies.