An Applied Assessment of Multi-Source Data Fusion by Machine Learning for PM2.5 Daily Concentration Prediction
This study evaluates a machine learning data fusion approach that integrates daily federal regulatory observations, daily low-cost community sensor measurements, and monthly satellite-derived aerosol products to improve PM2.5 prediction across under-monitored environments.