


By Dr. Beatriz Royo
Around the world, cities and conurbations are urgently addressing the need to reduce greenhouse gas (GHG) emissions, and with transport accounting for around 15% of total emissions, and the demand for freight transport rising as cities continue to grow, the emissions from urban freight logistics are a priority target.
But there is also a growing awareness that simply mandating change — for example, requiring that all vehicles no longer be propelled by fossil fuels by a certain date —not only fails to take into account the particular characteristics (economic, geographic, topographic and other) of a given urban area, but without other complementary strategies may not even achieve significant reductions when a wider view of GHG emissions is taken.
Ecologistics’ is a tool that was developed as a decision support system to help city governments track urban freight transport emissions and evaluate the likely impacts of different decarbonisation strategies despite the problems posed by data limitations, multiple stakeholders and evolving circumstances. We tested the Ecologistics tool in a real-life setting in Bogotá, Colombia, in collaboration with colleagues from Germany and the Netherlands.
The tool builds on the integration of two established frameworks: the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC), tailored for cities, and the Global Logistics Emissions Council (GLEC) Framework, developed for the logistics industry. Since logistics service providers are the primary data holders, aligning these frameworks was essential to ensure cities could access and use reliable emissions data.
This alignment was translated into a practical tool that supports emissions tracking across varying levels of data availability and granularity. It bridges the gap between corporate and municipal climate reporting and enables cities to incorporate industry-standard data into their GHG inventories. EcoLogistics was developed through a co-creation process involving local government representatives (as primary users), environmental experts, logistics practitioners, and software developers.
In particular participants in the co-creation process had to consider how to bridge data gaps, which exist for various reasons – the geographic basis for existing data collection, which may for example be at a regional rather than city level, high collection costs (for local government and for logistics operators), confidentiality and regulatory constraints, the small scale and fragmentary nature of much urban logistics, and the absence of advanced analytical tools.
While default values are available to fill data gaps, they may not reflect the real-world complexity of urban logistics. In practice, local factors significantly influence fuel consumption, efficiency, and emissions. For example, fuel use in a hilly city with a medieval street layout is likely to be less efficient than in a city with wide boulevards on flat terrain. Similarly, freight logistics in a manufacturing hub or port city may differ substantially from those in a service-oriented urban area.
Therefore, the Ecologistics tool allows the evolution toward city-specific emissions factor calculations, developed in collaboration with logistics companies, to improve accuracy and relevance in urban climate action planning.
In Bogotá, around 70% of freight operations are carried out by road, with a large share serving small and often informal business units. These operations tend to follow fragmented and complex patterns of transport and delivery, which makes emissions tracking particularly challenging. Using the Ecologistics approach, a baseline for freight-related emissions was established for the year 2019, prior to the COVID-19 pandemic. This baseline enabled the evaluation of various strategies aimed at reducing emissions in future target years—2025, 2030, and 2050—while accounting for projected urban growth and increased freight demand. The analysis considered interventions such as reducing travel distances, switching fuel types, adjusting delivery hours, and promoting eco-driving practices. It also assessed the impact of electrifying different vehicle classes, from motorcycles to rigid trucks. Due to the low prevalence of heavy goods vehicles over 12 tonnes in the city, these were excluded from the analysis.
In the final step of the analysis, we examined the impact of electrifying freight transport by 2030 or 2050 by varying two key parameters: the carbon intensity of the electricity grid and the percentage of tonne-kilometres shifted to electric power. For simplicity, we assumed that lighter vehicle types would be electrified first, and that gasoline-powered vehicles would convert before diesel, followed by CNG.
This approach highlights the trade-offs between fleet electrification and decarbonising the electricity grid. For instance, if the grid’s carbon intensity remains unchanged, achieving a 50% reduction in greenhouse gas emissions by 2030 would require electrifying approximately 44% of the vehicle fleet. However, if the grid’s carbon intensity improves to 141 gCO₂/kWh—down from 203 gCO₂/kWh in 2019—only a 9% fleet conversion would be needed to reach the same target.
Although the analysis required several assumptions and the data representation may be limited, it successfully demonstrated the importance of collaboration between industry and public administration in urban decarbonisation. This collaboration should begin with data collection and monitoring, and extend to strategic decision-making and the development of public-private partnerships. The harmonization process not only supports consistent reporting but also facilitates data sharing between stakeholders. Ultimately, collaboration and data-driven decision-making will help cities innovate and simulate the potential impacts of interventions before committing to large investments—paving the way for more efficient and low-carbon urban freight mobility.
This article is based on findings from the open access publication:
Royo, B., Zhang, Y., Lewis, A., & Dehdari, P. (2025). CO₂ emissions in urban freight transport: Developing and testing the EcoLogistics tool. Case Studies on Transport Policy, 20, 101415. https://doi.org/10.1016/j.cstp.2025.101415