Data for N2O Emissions across European Coastal Systems

The project compiles ~8,500 in-situ N₂O flux measurements from European coastal waters (1993–2023), harmonizes them into a single dataset, and applies machine-learning models (Random Forest and XGBoost) to: • Predict spatial distributions of coastal N₂O fluxes • Identify dominant environmental drivers • Benchmark against global ensemble estimates • Conduct warming, oxygen decline, and nutrient perturbation scenarios • Quantify prediction uncertainty • Produce high-resolution (0.25°) gridded maps of coastal emissionsThis repository ensures transparency and reproducibility for all analyses presented in the thesis and manuscript.Environmental predictors (all long-term climatologies): • World Ocean Atlas 2018/2023 – temperature, salinity, oxygen, nitrate, phosphate, density • Copernicus Marine Service (CMEMS) – chlorophyll-a hindcast (1993–2025) • GEBCO 2025 Grid – bathymetry • Yang et al. (2020) global N₂O flux dataset – external benchmark