Research Article
Evaluation of Key Parameters Using Deep Convolutional Neural Networks for Airborne Pollution (PM10) Prediction
Table 1
Selected variables and description.
| | Variable | Metric | Minimum | Maximum |
| | PM10 | Microgram/cubic meter (μg/m3) | 2 | 234 |
| | Temperature (TMP) | Degrees celsius (°C) | 2 | 31.6 |
| | Wind direction (WDR) | Degrees Azimuth (AZM) | 0 | 360 |
| | Wind speed (WSP) | Meters/second (m/s) | 0.2 | 6.5 |
| | Relative humidity (RH) | Percentage (%) | 3 | 94 |
| | Solar ultraviolet radiation type A (UVA) | Milliwatt/squared centimeter (mW/cm2) | 0 | 6.067 |
| | Solar ultraviolet radiation type B (UVB) | Minimum dose of erythema/hour (MDE/h) | 0 | 5.558 |
|
|
