Spatially Disaggregated Energy Consumption and Emissions in End-use Sectors for Germany and Spain
Abstract
High-resolution energy consumption and emissions datasets are essential for localized policy-making, resource optimization, and climate action planning. They enable municipalities to monitor mitigation strategies and foster engagement among governments, businesses, and communities. However, smaller municipalities often face data limitations that hinder tailored climate strategies. This study generates detailed final energy consumption and emissions data at the local administrative level for Germany and Spain. Using national datasets, we apply spatial disaggregation techniques with open data sources. A key innovation is the application of XGBoost for imputing missing data, combined with a stepwise spatial disaggregation process incorporating district- and province-level statistics. Prioritizing reproducibility, our open-data approach provides a scalable framework for municipalities to develop actionable climate plans. To ensure transparency, we assess the reliability of imputed values and assign confidence ratings to the disaggregated data.