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. 2015 Apr 29;26(4):365–376. doi: 10.1038/jes.2015.14

Table 4. Land use regression (LUR) covariates and model fits for inversion-focused and 24-h black carbon (BC).

  LUR Model
Covariates β (P-value) IQR conc. increasea Seq R2 b
Inversion focused summer BC (abs) c
 Intercept 2.18 (0.11)
 Weekly reference BC 2.53 (0.0007) 0.26
 Land use (industry) at 750 m 3.0 × 10−6 (0.01) 0.41 0.57
 Elevation at 1000 m −0.009 (0.01) −0.58 0.64
 
Inversion focused winter BC (abs)
 Intercept 3.10 (0.12)
 Weekly reference BC 0.60 (0.82) 0.04
 Land use (industry) at 750 m 1.9 × 10−6 (0.0006) 0.26 0.42
 Signaled intersections within 500 m 0.05 (0.01) 0.14 0.60
 Elevation at 1000 m −0.005 (0.02) −0.32 0.67
 Wind speed (m/s) −0.30 (0.001) −0.33 0.76
24-H summer BC (abs)
 Intercept −0.31 (0.36)
 Weekly reference BC 1.55 (0.01) 0.12
 IDW of PM2.5 emissions 0.36 (<0.0001) 0.15 0.52
 Land use (Com+Ind) at 200 m 4.5 × 10−6 (<0.0001) 0.13 0.64
 Wind direction      
  Blowing from NW/W 0.25 (0.001) 0.25
  Blowing from SW/S 0.74
 
24-H winter BC (abs)
 Intercept −0.09 (0.56)
 Weekly reference BC 1.31 (<0.0001) 0.28
 IDW of PM2.5 emissions 0.38 (0.001) 0.16 0.61
 Land use (industry) at 750 m 1.0 × 10−6 (0.02) 0.14 0.67
a

IQR concentration increase=β × IQR of source indicator.

b

Seq R2 is the sequential model fit for each additional term incorporated into the model.

c

One influential point removed for LUR modeling. Bold values are the percentages of explained pollutant variability according to final LUR models.