Uptake of Organic Contaminants from Soil into Vegetables and Fruits - Dealing with Contaminated Sites: From Theory Towards Practical Application - page 374

Fig. 9.2 Calculation of BCF
from the slope of the
regression between
concentrations in soil and
plant root; calculation of
background concentration
due to uptake from air from
the y-axis intercept of the
regression. Example from
(Mikes et al. 2009 ), p,p -DDT
in roots and soil

9.3.2 Regression Equations

BCF s for neutral organic contaminants are related to contaminant properties. This is
applied in regression equations where physico-chemical properties like lipophilicity
of the contaminants are correlated to the BCF s. These regressions based on mea-
sured data allow us to estimate concentrations of contaminants in plant tissue from
the octanol-water partitioning coefficient, K OW , in case of uptake from soil (e.g.
(Travis and Arms 1988 )) or from the octanol-air partitioning coefficient, K OA ,in
case of uptake from air (Kömp and McLachlan 1997 ).
A frequently applied regression for the uptake of organic contaminants from soil
into above-ground plants stems from Travis and Arms ( 1988 ):

29, r 2

log BCF V = 1.588 − 0.578 × log K OW ( n = = 0.53) (9.3)

where BCF v is the bioconcentration factor of vegetation to soil (kg kg dw -1 ) and K OW
(L L -1 ) expresses the lipophilicity of the contaminant. The curve was fitted with 29
data points in the range 1.15

≤

log K OW ≤ 9.35. A limitation of the regression is

that the uptake from air remains unknown. This may lead to false predictions.

9.3.3 Root Concentration Factor

Phase equilibrium is the endpoint of diffusion and is achieved when the activity of
the contaminant in the root tissue is equal to the activity of the contaminant in the
external solution (Lewis 1907 ). The concentration ratio between root and aqueous
solution in phase equilibrium is called the root concentration factor RCF (L kg -1 )
(Shone and Wood 1974 ).

Concentration in root (mg g − 1 )
Concentration in solution (mg mL − 1 )

RCF = (9.4)

The most widely applied regression for the RCF is from Briggs et al. ( 1982 ). It
has been fitted to data derived from experiments with intact and macerated barley