Accurate maps of nitrogen dioxide pollution at fine scales are essential for assessing air quality and protecting public health. We developed a machine learning model that produces daily high-resolution 3D nitrogen dioxide fields across Western Europe by combining large-scale atmospheric simulations with ground-based measurements. This approach outperforms traditional methods, especially over cities and complex terrain, and can enhance satellite-based air quality monitoring.