Worksheet A04 [HK]
: Estimated pesticide residues on various types of
vegetation shortly after an
application of 1 lb/acre.
Concentration (mg chemical/kg vegetation)
Type of Vegetation
Typical
Upper Limit
ID
Value
ID
Value
The following values are from Hoerger and Kenaga (1972).
Range grass
RGT
125
RGU
240
Grass
GST
92
GSU
110
Leaves and leafy crops
LVT
35
LVU
125
Forage crops
FCT
33
FCU
58
Pods containing seeds
PDT
3
PDU
12
Grain
GNT
3
GNU
10
Fruit
FRT
1.5
FRU
7
The following values are from Fletcher et al. (1994)
Short grass
SGT
85
SGU
240
Tall grass
TGT
36
TGU
110
Broadleaf/forage
plants and
BLT
45
BLU
135
small insects
Fruits, pods, seeds, and large
FRT2
7
FRU2
15
insects
Worksheet A05 [FRUIT]
: Concentration of a chemical on spheres of various sizes at an application rate of 1
lb/acre.
Diameter (cm)
Planar Surface
Area (cm
2
)
a
Amount
deposited
(mg)
b
Weight of sphere
( kg)
c
Concentration
(mg/kg)
d
1
0.78540
0.00880
0.00052
16.8
5
19.63495
0.21991
0.06545
3.36
10
78.53982
0.87965
0.52360
1.68
Application rate
1 lb/acre =
0.0112
mg/cm
2
a
b
c
d
Planar surface area of a sphere =
B
r
2
where r is the radius in cm.
Amount deposited is calculated as the application rate in mg/cm
2
multiplied by the planar
surface area.
Assumes a density of 1 g/cm
3
for the fruit. The volume of a sphere is(1÷6)×
B
× d
3
where
d is the diameter in cm. Assuming a density of 1 g/cm
3
, the weight of the sphere in kg is
equal to:
kg= (1÷6)×
B
× d
3
÷ 1000
Amount of chemical in mg divided by the weight of the sphere in kg.
WS-8
Worksheet A06 [OFFSITE
]: Central estimates of off-site drift (expressed
as fraction of application
rate) associated with ground applications of pesticides
1
(from AgDRIFT Version 1.16, Teske et al.
2001)
Distance Down Wind (feet)
Low Boom
High Boom
Orchard Airblast
(Normal)
25
0.0187
0.1034
0.0057
50
0.0101
0.0515
0.0029
100
0.0058
0.0262
0.0007
300
0.0024
0.0078
0.0001
500
0.0015
0.0038
0.0000403
900
0.0008
0.0015
0.000013
990
0.0007
0.0013
<0.0000108
1
Estimates based on very fine to fine spray. This will over-estimate drift for applications involving
larger droplets.
WS-9
Worksheet A07a [KAMODEL]: Estimate of first-order absorption rate (k
a
in hour
-1
) and 95%
confidence intervals (from SERA 1997).
Model
parameters
ID
Value
Coefficient for k
o/w
C_KOW
0.233255
Coefficient for MW
C_MW
0.005657
Model Constant
C
1.49615
Number of data points
DP
29
Degrees of Freedom (d.f.)
DF
26
Critical value of
t
0.025
with 26 d.f.
1
CRIT
2.056
Standard
error of the estimate
SEE
16.1125
Mean square error or model variance
MDLV
0.619712
Standard deviation of model (s)
MSD
0.787218
MDLV
0.5
X
N
X, cross products matrix
0.307537
-0.00103089
0.00822769
-0.00103089
0.000004377
-0.0000944359
0.0082
-0.0000944359
0.0085286
1
Mendenhall and Scheaffer 1973, Appendix 3, 4, p. A31.
Central (maximum likelihood ) estimate:
log
10
k
a
= 0.233255 log
10
(
k
o/w
) - 0.005657
MW - 1.49615
95% Confidence intervals for log
10
k
a
log
10
k
a
±
t
0.025
×
s × (
a
NN
X
NN
X a)
0.5
where
a is a column vector of {1, MW, log
10
(
k
o/w
)}.
NB: Although the equation for the central
estimate is presented with k
o/w
appearing before MW to be consistent
with the way a similar equation is presented by EPA, MW must appear first in column vector
a because of the way
the statistical analysis
was conducted to derive X
N
X .
See following page for details of calculating
a
NN
X
NN
X a without using matrix arithmetic.
WS-10
Worksheet Worksheet A07a (continued)
Details of calculating a
NN
X
NN
X a
The term
a'
A
(
X'X)
-1
A
a requires matrix multiplication. While this is most easily accomplished using a program that
does
matrix arithmetic, the calculation can be done with a standard calculator.
Letting
a = {a_1, a_2, a_3}
and
(
X'X)
-1
=
{
{b_1, b_2, b_3},
{c_1, c_2, c_3},
{d_1, d_2, d_3}
},
a'
A
(
X'X)
-1
A
a is equal to
Term 1: {a_1 ×([a_1×b_1] + [a_2×c_1] + [a_3×d_1])} +
Term 2: {a_2 ×([a_1×b_2] + [a_2×c_2] + [a_3×d_2])} +
Term 3: {a_3 ×([a_1×b_3] + [a_2×c_3] + [a_3×d_3])}.
WS-11