Based on our results, we classified a wide range of chemical substances based on
their respective characteristics and continued research and verification, accumulating
data that can be scientifically supported. To establish a practical ecological impact
assessment method for the OECD international standardization of the microcosm
test, the following specific issues were addressed: (1) confirmation of the reproducibility of the test methods using a blind test performed by three independent
organizations targeting the same substance, (2) verification of versatility using a
ring test (performed by five organizations) in domestic organizations, (3) building a
practical foundation for the microcosm NOEC database, (4) building the foundation
for a public test method through the completion of this test manual, and (5) verification of the utility of the test method by constructing an environmental NOEC
prediction method. These steps were deemed necessary, and the findings of previous
studies have been clarified through the application of this approach.
For steps 1–4, based on the characteristics of the chemical substances, a comparative analysis of reproducibility when a substance was added at the beginning of
culturing and during the steady state was performed as necessary. The aims of
generalization are to examine and strengthen the efficiency of the experiment with
respect to the timing of substance addition, the concentration range, and the precision of the appropriate settings. The aim of step 5 was to expand the database of the
1
17
22
NOAEC IN MICROCOSMS (µg·L -1 )
NOEC IN ECOSYSTEMS (µg·L
-1
)
23
14
19, 25
8
6
4
11
24
15
16
13
12
21
3
5
10,18
20
C o n fi d e n c e
in te
r v a l
S a fe
ty
fa
c to
r 2 0 0 :r e g r e s s io n
li n e
–
( A + B )
C o n fi d e n c e
in te
r v a l: r e g r e s s io n
li n e
+
( A + B )
2
7
9
10
4
10 4
10
3
10 3
Upper of dotted line
Between dotted line
and red line
Lower of red line
not protected
protected
protected
Upper zone of red line:
Scatter of ecosystem difference = S.D.B
Scatter of chemicals difference = S.D.A
NOEC eco
log NOEC eco = 1.08 ×
log NOEC eco = 1.08 ×
A
B
log m-NOAEC – 1.22 – (A+ B)
log m-NOAEC – 1.22 – (A)
m-NOAEC
200
Safety factor
(Almost all ecosystem will be protected)
(standard deviation A=0.57, standard deviation B=0.51)
m-NOAEC/200 < NOEC eco
10
2
10 2
10
-2
10 -1
10
1
10
log NOEC eco = 1.08·log m-NOAEC –1.22
Fig. 8.4 Relationship between m-NOEC and NOEC in ecosystem
●, mean of NOECs; ―, regression line; . . ., upper limit of confidence range; , lower limit of
confidence range; 1, Cd
2+ ; 2, atrazine; 3, PCP; 4, Cu
2+ ; 5, Zn
2+ ; 6, ammonia; 7, LAS; 8, 3,4-DCA;
9, phenol; 10, nonylphenol; 11, Mancozeb; 12, 2,3,4,6-tetrachlorophenol; 13, TMAC; 14, alachlor;
15, AE; 16, SDS; 17, DCMU; 18, linuron; 19, carbendazim; 20, paraquat; 21, 4-chlorophenol;
22, chlorpyrifos; 23, methoxychlor; 24, dibutyl phthalate; 25, 2,4-dichlorophenol; standard
deviationA, variation of chemicals; standard deviationB, variation of natural ecosystem
164
K. Kakazu et al.
their respective characteristics and continued research and verification, accumulating
data that can be scientifically supported. To establish a practical ecological impact
assessment method for the OECD international standardization of the microcosm
test, the following specific issues were addressed: (1) confirmation of the reproducibility of the test methods using a blind test performed by three independent
organizations targeting the same substance, (2) verification of versatility using a
ring test (performed by five organizations) in domestic organizations, (3) building a
practical foundation for the microcosm NOEC database, (4) building the foundation
for a public test method through the completion of this test manual, and (5) verification of the utility of the test method by constructing an environmental NOEC
prediction method. These steps were deemed necessary, and the findings of previous
studies have been clarified through the application of this approach.
For steps 1–4, based on the characteristics of the chemical substances, a comparative analysis of reproducibility when a substance was added at the beginning of
culturing and during the steady state was performed as necessary. The aims of
generalization are to examine and strengthen the efficiency of the experiment with
respect to the timing of substance addition, the concentration range, and the precision of the appropriate settings. The aim of step 5 was to expand the database of the
1
17
22
NOAEC IN MICROCOSMS (µg·L -1 )
NOEC IN ECOSYSTEMS (µg·L
-1
)
23
14
19, 25
8
6
4
11
24
15
16
13
12
21
3
5
10,18
20
C o n fi d e n c e
in te
r v a l
S a fe
ty
fa
c to
r 2 0 0 :r e g r e s s io n
li n e
–
( A + B )
C o n fi d e n c e
in te
r v a l: r e g r e s s io n
li n e
+
( A + B )
2
7
9
10
4
10 4
10
3
10 3
Upper of dotted line
Between dotted line
and red line
Lower of red line
not protected
protected
protected
Upper zone of red line:
Scatter of ecosystem difference = S.D.B
Scatter of chemicals difference = S.D.A
NOEC eco
log NOEC eco = 1.08 ×
log NOEC eco = 1.08 ×
A
B
log m-NOAEC – 1.22 – (A+ B)
log m-NOAEC – 1.22 – (A)
m-NOAEC
200
Safety factor
(Almost all ecosystem will be protected)
(standard deviation A=0.57, standard deviation B=0.51)
m-NOAEC/200 < NOEC eco
10
2
10 2
10
-2
10 -1
10
1
10
log NOEC eco = 1.08·log m-NOAEC –1.22
Fig. 8.4 Relationship between m-NOEC and NOEC in ecosystem
●, mean of NOECs; ―, regression line; . . ., upper limit of confidence range; , lower limit of
confidence range; 1, Cd
2+ ; 2, atrazine; 3, PCP; 4, Cu
2+ ; 5, Zn
2+ ; 6, ammonia; 7, LAS; 8, 3,4-DCA;
9, phenol; 10, nonylphenol; 11, Mancozeb; 12, 2,3,4,6-tetrachlorophenol; 13, TMAC; 14, alachlor;
15, AE; 16, SDS; 17, DCMU; 18, linuron; 19, carbendazim; 20, paraquat; 21, 4-chlorophenol;
22, chlorpyrifos; 23, methoxychlor; 24, dibutyl phthalate; 25, 2,4-dichlorophenol; standard
deviationA, variation of chemicals; standard deviationB, variation of natural ecosystem
164
K. Kakazu et al.