Mapping and Modeling CO2 traffic emissions within local climate zones in Helsinki

Quantifying road traffic CO2 emissions is critical for urban climate and sustainability studies. However, detailed modeling often requires high-resolution input data that is unavailable in many regions. To address this gap, we present a simplified regression-based model that quantifies traffic-related CO2 emissions within Local Climate Zones (LCZs) using readily available data such as building surface area, asphalt surface area, population, traffic lights, and road type. This approach minimizes computational requirements and circumvents the need for traffic data, offering a practical alternative for regions with limited resources.
Our results show that road type and asphalt surface area are the most influential variables in describing CO2 emissions. Median CO2 emissions from built LCZs are 1.8 times higher than those from land cover LCZs. The generalized model can explain up to 69% of the emissions for some LCZ. Based on this model, we introduce a look-up table for LCZ-specific traffic CO2 emissions, providing a user-friendly tool to estimate emissions in data-scarce regions. This simplified methodology emphasizes accessibility and efficiency while maintaining robust results, making it an invaluable resource for urban emission studies.