Table 2:
Prediction of indoor exposure for NO2, NOx, SHS and PM2.5
| NO2 (ppb) | NOx (ppb) | Nicotine (SHS) (μg/m3) | PM2.5 (μg/m3)† | ||
|---|---|---|---|---|---|
| Range of concentration (min, max of measured) | Indoor | (1.01, 115.91) | (1.27, 477.68) | (0.01, 19.92) | (1.19, 58.80) |
| Outdoor | (0.99, 29.79) | (0.15, 143.29) | − | (1.66, 29.18) | |
| Correlation of indoor to outdoor | Pearson’s r (p-value) | r=0.34 (p<0.001) | r=0.41 (p<0.001) | - | r=0.01 (p=0.92) |
| Model A1‡: best linear | R2/adj. R2 | 0.40/0.35 | 0.38/0.33 | 0.40/0.30 | 0.52/0.45 |
| CV R2 (RMSE) | 0.21 (8.88) | 0.14 (38.36) | −0.12 (1.93) | 0.30 (10.67) | |
| Model A2‡: best logarithmic | R2/adj. R2 | 0.60/0.55 | 0.57/0.51 | 0.59/0.54 | - |
| CV R2 (RMSE) | 0.46 (0.51) | 0.39 (0.72) | 0.45 (1.41) | - | |
| Model A2‡: squared root with interactions | R2/adj. R2 | - | - | - | 0.58/0.52 |
| CV R2 (RMSE) | - | - | - | 0.44 (1.09) | |
| Model A3‡: removing outliers from Model A2 | R2/adj. R2 | 0.63/0.57 | 0.58/0.53 | 0.61/0.56 | 0.60/0.54 |
| CV R2 (RMSE) | 0.48 (0.47) | 0.43 (0.69) | 0.45 (1.37) | 0.45 (1.06) | |
| Model B4‡: correlation with residuals | R2/adj. R2 | 0.63/0.58 | - | - | 0.65/0.56 |
| CV R2 (RMSE) | 0.49 (0.491) | - | - | 0.42 (1.11) | |
| Model B5‡: removing outliers from Model B4‡ | R2/adj. R2 | 0.65/0.59 | - | - | 0.66/0.58 |
| CV R2 (RMSE) | 0.51 (0.46) | - | - | 0.45 (1.06) | |
Note:
†
- For PM2.5, all models (except the first one) are in square root function: Model A1 - is a model with linear function without interactions; Model A2 - square root function with interactions; Model A3 - removing outliers from Model A2; Model B4 - testing residuals; Model B5- removing outliers from Model B4;
‡
Letter “A” represents models that were built using the first “A” approach, while letter “B” represents models that were built using the second “B” approach (see subsection 2.3.2)