By Himanshu Raj and Dana Vigran
Have you ever thought about the entire trip of an item that you order online or buy in a supermarket? Where did it come from, how was it transported from the factory, what type of vehicle was used, how many people were involved, how was it packed, how many kilometers did it travel and what emissions and air pollution did this trip cause?
Global freight demand is expected to triple between 2015 and 2050, and the ability to move goods efficiently has become the lifeblood of economic development, especially in cities that generate over 80 percent of global GDP and an estimated 75 percent of global emissions.
Freight accounts for an increasing percentage of transportation and emissions, but there is no common way to collect the data we need for urban freight to optimize deliveries and operations for sustainable cities. Urban goods transport is operated by a complex network of private and public actors, from shippers and forwarders to retailers and residents. The most comprehensive data available is often in the private sector, and there are rarely agreements that this data be shared.
City logistics solutions should be evidence-based and tailored to the needs of these different interest groups. In order for city planners and designers to identify these solutions, correct and complete data on urban freight transport is required. Only with comprehensive data from the entire supply chain can local authorities properly integrate freight transport into urban planning and serve goods vehicles better through improved design and use of facilities and infrastructure.
For the local authorities Collecting and updating urban freight data can be expensive and often lack the resources to acquire high quality data, which limits their ability to implement data-driven policies.
The data we have and the data we need
Traffic counts have traditionally been the most common method of surveying support for urban freight policies, as policymakers have the habit and experience of techniques that are already popular in personal travel planning.
According to Allen et al. (2012) Data on the movement of urban goods can be collected using three main techniques: general survey on the flow of goods and commercial traffic, specific stakeholder surveys among shippers, transport companies, retailers and vehicle-specific surveys on vehicle use and driver practices.
However, the lack of an established and accepted methodology means that the data gaps in urban freight transport are not only large, but also varied and variable.
In a recent collection of responses from two projects, freight data experts in 10 EU countries and three developing countries identified a number of data gaps in urban freight transport. These gaps affect both the understanding of the patterns of activity in urban freight transport and the development of urban freight transport models.
According to experts, here are some frequent data gaps and challenges:
- Little data is available on the activities of light commercial vehicles (gross vehicle weight <3.5 tons)
- The relationship and relationship between urban freight activity and freight activity higher up the supply chain is not well documented
- There is a lack of data on the logistics infrastructure from which urban freight deliveries differ
- There are not enough geographical details about truck journeys in urban areas
- There is a lack of data collection on journeys made by consumers for shopping (a form of urban freight transport, but which is often not defined as such for the collection of data on urban freight transport).
- There is insufficient data on the types of delivery outside the street
- The data collected is not always reliable
- In developing countries, the majority of urban freight traffic is often informal and difficult to record
Closing the gap
There are new techniques and ideas on how to close these gaps. New technologies offer the ability to collect significant amounts of urban freight data at a relatively low cost compared to previous technologies. Technology can also improve the visibility of freight flows and improve how and when goods are delivered. Companies rely on technology to improve efficient deliveries. Collecting and sharing data also offers opportunities to reduce freight journeys. Services such as route optimization and vehicle telematics can be used to design the scheme and inform local delivery schedules.
However, closer cooperation between the public sector and freight companies is needed to make important data sets broader and more freely available.
Above all, common methods have the potential to make data more accessible to local governments and policymakers. As part of the EcoLogistics project, ICLEI is working with local and regional authorities in Argentina, Colombia and India to identify the primary data gaps in urban freight transport and to develop a common data collection method to address these gaps. The results are used as a basis to understand the flow of goods in project cities and to precisely quantify the effects of urban freight transport.
Himanshu works as an officer in the EcoMobility team, is project officer of the EcoLogistics project funded by IKI and supports the city network of the EcoMobility Alliance. He has a background in infrastructure planning (M.Sc.) with a focus on climate resilience.
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