Chemistry Reference
In-Depth Information
5.6 PHYSICOCHEMICAL PROPERTIES USED TO
PREDICT CATION BIOCONCENTRATION
Van Kolck et al.
(2008) developed 4 QSARs to predict the bioconcentration factors
(BCF) of cations to the mussel
Mytilus edulis
, and 4 QSARs to predict the BCFs of
developed for 8 cations and the QSARs with highest
r
2
values were obtained using
the ionic index (Z
2
/r) and the covalent index
X
r
m
( )
(
Table 5.18
). The BCFs for
Perna
viridis
were developed for 7 cations and the QSARs with highest
r
2
values were
obtained using the Pearson and Mawby softness parameter (σ
p
) and the covalent
index
X
r
m
(
)
(Table 5.18).
2
5.7 PHYSICOCHEMICAL PROPERTIES USED TO
PREDICT CATION BIOSORPTION
Can and Jianlong (2007), Chen and Wang (2007), and Zamil et al.
(2009) developed
54 QSARs to predict the maximum biosorption capacity (
q
max
) of cations to either
the yeast
Saccharomyces cerevisiae
or the bacterium
Staphylococcus saprophyticus
BMSZ711 (Table 5.4). Can and Jianlong (2007) used the t test to evaluate the contri-
bution of each physicochemical property to the QSAR and set a level of significance
as α = 0.05. The QSARs that did not meet this level of significance are indicated with
the superscript “b” in Table 5.23 and are not discussed further. Can and Jianlong
(2007) (labeled C&J in
Table 5.23
) used 7 physicochemical properties to develop
QSARs for predicting the biosorption capacity of 6 borderline cations (Cd
2+
, Co
2+
,
Cr
3+
, Cu
2+
, Ni
2+
, and Zn
2+
) and 2 hard cations (Cs
+
, Sr
2+
) (Table 5.23). For these 8 cat-
ions, the QSARs developed with the ionic index (Z
2
/r) and the absolute value of the
logarithm of the first hydrolysis constant (|log
K
OH
|) were the most statistically sig-
nificant (Table 5.23). Can and Jianlong (2007) removed Ni
2+
from the 8 cations listed
above and developed 10 QSARs with α = 0.05 to predict their biosorption capacity.
While the QSAR developed with ionization potential (IP) and atomic number (AN)/
the difference of the ionization potential in volts between its oxidation number (OX)
and the next lower one (OX - 1) (ΔIP) was the most robust, those developed with
Z
2
/r, and ionic potential (Z/r) were also highly statistically significant (Table 5.23).
Can and Jianlong (2007) developed 5 QSARs to predict the biosorption capacity
of 6 borderline cations (Cd
2+
, Co
2+
, Cr
3+
, Cu
2+
, Ni
2+
, and Zn
2+
) and 2 soft cations
(Ag
+
, Pb
2+
), but none were very statistically significant (Table 5.23). Can and Jianlong
(2007) also developed 7 QSARs to predict the biosorption capacity of 6 borderline
cations. Only the QSAR developed with |log
K
OH
| was highly statistically significant
(Table 5.23).
Chen and Wang (2007) (labeled C&W in Table 5.23) developed 3 QSARs to pre-
dict the
q
max
of 10 cations to
Saccharomyces cerevisiae
; the QSAR developed with
the covalent index
X
r
m
( )
was the most statistically significant (Table 5.23). Chen and
Wang (2007) also developed 6 QSARs to predict the biosorption capacity of 8 cat-
ions and again the QSAR developed with
X
r
m
2
was the most statistically significant
(Table 5.23). Only the Chen and Wang (2007) QSAR based on
X
r
m
2
and AN/∆IP
did not meet the level of significance as α = 0.05 (Table 5.23).
