Projecting traffic flows for road-based passenger transport in Europe for the analysis of climate impact
Nina Thomsen, Angelika Schulz · 2024 · 2 citationsRead the paper
Abstract Road-based transport is a significant contributor to global transport emissions of greenhouse gases and local pollutants, thus contributing to the environmental impact of the mobility of people and goods. In order to develop strategies to mitigate this impact, it is necessary to build reliable emission inventories that include sector-specific emissions. Furthermore, the methods for creating these inventories should be applicable for forecasts and scenario calculations to facilitate the evaluation of pathways towards a more sustainable transport system. The study at hand proposes a model-based framework to predict travel demand and its spatial distribution for a bottom-up calculation of road transport emissions in Europe. With this framework, it is possible to calculate emissions based on the road network structure, traffic flows and vehicle types. In order to demonstrate the applicability of the framework for scenario calculations, it is applied to three exemplary scenarios where population data is modified. With the developed methodology, a tool for the large-scale assessment of emissions from road transport is provided, which is able to simulate the impact of socio-economic and economic changes on these emissions.
What the full text shows
Working prototype- The framework successfully calculates spatially disaggregated road transport emissions for Europe based on socio-economic inputs and road network structure. (Applied to Europe using open data (OSM, Eurostat, OECD))
- The model demonstrates scenario readiness by reacting to modifications in population and GDP data. (Tested across three exemplary scenarios with modified population data)
- Road type distribution of CO2e emissions remains relatively stable across population-based scenarios. — Motorways: 30-31%, Outside settlements: 46%, Urban: 23-24% (Across Baseline, Higher population, and Higher population in cities scenarios)
- Computation time for a single scenario is efficient on standard hardware. — < 60 min on Intel Core i7 (1.90 GHz), 16 GB RAM (Example scenario for Europe)
- Setup
- Large-scale assessment of road-based passenger transport in Europe using open-source data (OSM) and socio-economic datasets (Eurostat, OECD).
- How
- A bottom-up modelling framework that derives national travel volumes (PKT) from GDP and population using a Gompertz function for motorisation rates, then distributes these volumes across a road network model to calculate emissions using emission factors.
- Limitations
- Trip distribution model is currently calibrated and validated using German data only. · Cannot currently simulate changes in mode choice or monetary-based travel costs. · Network design changes (e.g., speed regulations) cannot be accurately calculated. · Computing time for network creation depends on internet connection speed for OSM downloads.
Summarized by Gemma 4 from the open-access full text · 9 Oct 2026. Read it