PMF Coupled With Random Forest Method Reveals Detailed PM2.5 Sources and Their Synergistic Effects on Air Pollution Control
Understanding the sources of emerging PM2.5 pollution is crucial for developing effective air quality management strategies. This study combines positive matrix factorization (PMF) with random forest (RF) classification to reveal a detailed PM2.5 source identification for both day and night samples collected in Tianjin...