Table 5. Non-linear multi-variable regression models with and without spatial autocorrelation for total concentrations of six PAH speciesa.
| Season | Predictors (variance explained) | R2 : RMSE with (without) spatial autocorrelation | LOOCV R2 : RMSE with (without) spatial autocorrelation |
|---|---|---|---|
| Summer | Spatial autocorrelation effect (19.1%); proportion of commercial cooking facilities (2.1%); ambient temperature (7.1%); ambient wind speed (2.1%); population density (15.2%); roadway length within a 700-m buffer (21.4%) | 0.67 : 6.95 ng/m3 (0.57:7.90 ng/m3) | 0.66: 7.00 ng/m3 (0.57: 7.90 ng/m3) |
| Winter | Spatial autocorrelation effect (55.6%); traffic density (15.7%); ambient temperature (2.4%); ambient wind speed (9.3%) | 0.83:6.61 ng/m3 (0.67: 9.14 ng/m3) | 0.77: 7.76 ng/m3 (0.59: 10.16 ng/m3) |
| Annual average | Spatial autocorrelation effect (11.6%); season (38.5%); proportion of park and recreational land-use (1.2%); traffic density (2.8%) | 0.54: 10.81 ng/m3 (0.33: 12.99 ng/m3) | 0.53: 10.90 ng/m3 (0.33: 13.00 ng/m3) |
a
Total PAH included fluorene, phenanthrene, anthracene, acenaphthene, fluoranthene, and pyrene