Biology Reference
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where
Α is the dimensionless sticking efficiency of column slice
i
,
d
is the median of the
grain size weight distribution (m),
Η
is the single collector contact efficiency (-) ,
Θ
is the total
porosity of the sand (-),
L
is the height of the column slice
i
, i.e. the distance (m) between two
sampling ports,
M
−
is the total number of cells entering slice
i
, obtained from the breakthrough
curve determined at the upper sampling port of slice
i
and
M
is the total number of cells,
obtained from the breakthrough curve determined at the lower sampling port of slice
i
. The total
number of cells
1
in the fluid phase at a sampling port was obtained from (Kretzschmar et al.,
M
1997)
t
=
∫
(4.2)
M
q
c t dt
( )
0
where
q
is the volumetric flow rate (mL/min),
C
is the cell concentration in the suspension (#
cells/mL) and
t
is time (min). The Tufenkji-Elimelech correlation equation (Tufenkji and
Elimelech, 2004a) was used to compute Η. For this, we assumed that the bacteria density was
1055 kg/m
3
, and the Hamaker constant was 6.5×10
-21
J (Walker et al., 2004).
4.2.3 Retained bacteria as fraction of total input
For the assessment of the sticking efficiency distribution, not only the sticking efficiencies in all
column slices need to be determined, but also the number of retained bacteria in a slice, as a
fraction of the total number of bacteria cells injected in the column. This fraction,
F
, in each
segment was calculated as
M
−
M
(4.3)
F
=
i
i
−
1
i
M
0
where
M
is the total number of cells in the influent.
4.2.4 Data analysis
Various types of distributions (logarithmic, exponential, power law) were used to assess the
relation between the fraction of cells retained,
F
, and their corresponding sticking efficiency per
column slice,
Α
, thereby assessing the nature of the sticking efficiency distributions of the
E.
coli
strains we used. To evaluate the goodness of fit, we employed the coefficient of
determination,
R
2
>
0.9
0.8
≤
R
2
≤
0.9
2
. In case
, the fit was considered excellent. For
, the fit
R
R
< , the fit was considered weak. All regression curve
fitting were performed using SPSS 14 (SPSS, 2005).
2
0.8
was considered good, and when
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