The dataset was created using a supervised machine-learning pipeline. The pipeline generates air pollution concentration predictions across a 1 km^2^ grid over England, subsequently aggregated to form representative "typical" hourly cycles for each day of the week and month. This approach simplifies downstream use cases such as policy assessment and public communication. The underlying methodology is implemented in the accompanying open-source Python package Environmental Insights, available at https://github.com/berrli/Environmental-Insights