Table 1 Statistical summary of NO2 prediction model performance
From: Nitrogen dioxide (NO2) Meteorology and predictability for air quality management using TROPOMI
Model | Savanna | Transition | Forest | Coastal | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
MPD | r | d | MPD | r | d | MPD | r | d | MPD | r | d | |
Linear | 28.84 | 0.89 | 0.91 | 31.77 | 0.88 | 0.93 | 14.74 | 0.83 | 0.88 | 17 | 0.71 | 0.81 |
Ridge | 28.59 | 0.89 | 0.92 | 33.02 | 0.87 | 0.91 | 13.96 | 0.86 | 0.89 | 13.84 | 0.75 | 0.77 |
Random Forest | 29.01 | 0.84 | 0.87 | 28.41 | 0.87 | 0.89 | 10.11 | 0.92 | 0.92 | 16.51 | 0.7 | 0.74 |
Gradient Boosting | 35.69 | 0.85 | 0.87 | 37.76 | 0.89 | 0.92 | 13.73 | 0.93 | 0.96 | 27.17 | 0.66 | 0.81 |
XGBoost | 28.86 | 0.86 | 0.89 | 28.65 | 0.81 | 0.85 | 9.87 | 0.91 | 0.91 | 15.35 | 0.71 | 0.73 |