Management of missing air pollution data within urban environments using machine learning regressions: a case study for Delhi, India
An iterative, multi-model machine learning workflow to reconstruct missing daily pollution data for all six pollutants across 45 stations from 2014–2024 supports the usefulness of the approach for long-term regional reconstruction while also highlighting its limitations for pollutants with strong local emission signatu...