Table 2. Spatial Regression Models for Drinking Water PFAS Concentrations as a Function of the Abundance of Point Sources.
| compound | major industrial sitesa | MFTAsb | AFFF-certified airports | WWTPsc | λd | R2 |
|---|---|---|---|---|---|---|
| PFHxS | ||||||
| coefficiente | 24% | 20% | –13% | 1% | 94% | 0.62 |
| p-valuef | 0.249 | 0.002 | 0.073 | 0.045 | <0.001 | |
| PFHpA | ||||||
| coefficient | 10% | 10% | –2% | 0.5% | 72% | 0.40 |
| p-value | 0.569 | 0.155 | 0.761 | 0.436 | <0.001 | |
| PFOA | ||||||
| coefficient | 81% | 10% | –6% | 2% | 52% | 0.38 |
| p-value | <0.001 | 0.111 | 0.353 | 0.006 | <0.001 | |
| PFOS | ||||||
| coefficient | 46% | 35% | –6% | 2% | 79% | 0.46 |
| p-value | 0.124 | <0.001 | 0.512 | 0.007 | <0.001 |
a
Only the major industrial sites participating in US EPA’s 2010/2015 PFOA Stewardship Program were included.
b
MFTA = military fire training area.
c
WWTP = wastewater treatment plant.
d
Coefficient for the spatial error term characterizing spatial influence.
e
Results have been transformed to reflect expected changes in drinking water concentrations per increase in the abundance of different sources. Positive coefficients in the results indicate increasing concentrations with an increasing abundance of point sources within the same hydrologic unit.
f
p-values for the spatial error regression model. The spatial error term is used to incorporate spatial autocorrelation structures into a linear regression model.