Link-based European road transport emissions for CAMS-REG v8.1 and a comparison to city inventories

Abstract

Spatially resolved estimates of road transport emissions are fundamental for tackling challenges of air pollution and greenhouse gas emissions. Emission estimates at 0.05° × 0.1° resolution are provided in the widely used CAMS-REG regional European emissions inventory. Building on previous work by for the road transport sector, several improvement opportunities were identified: Firstly (1) an underestimation of ca. 35 % of NOx emissions in comparison to 8 independent urban inventories; secondly (2), artefacts in the spatial distribution in Eastern European non-EU countries; thirdly (3), the necessity of labour-intense downscaling methodologies to create high-resolution urban inventories from the fixed resolution dataset. To overcome these, emissions for most road links in the domain (n = 59 710 490) were estimated using gap-filled activity data (AADT) from OpenTransportMap, targetting NOx for the base year 2018. Gap filling was performed with random forest models trained on land-use and road information data and with a spatial method for small roads. For non-EU countries, model performance was R2: 0.63, MAE(AADT): 2028, for EU countries it was R2: 0.74, MAE(AADT): 1570, with better performance for larger roads. Up-to-date emission factors for NOx were applied on road links using a novel maximum-speed–based classification. To generate the CAMS-REG v8.1 inventory, the resulting spatial distribution was used as a proxy map, together with national totals. The new dataset is based on OpenStreetMap geometries and lowered the difference to city inventories to 18 % for absolute NOx emissions. It can be flexibly gridded to high resolutions. Some non-EU cities see large increases (Kiev, +84 %, Istanbul, +360 %) in attributed emissions due to the updated spatial distribution. Two case studies (London and Milan) show an increased spatial correlation, from R2≈0.3 using CAMS-REG v4.2 to R2≈0.6, with CAMS-REG v8.1 against the local inventory. Vector and gridded versions of the emission dataset and spatial distribution are available at https://doi.org/10.5281/zenodo.15688722.