Table 23 CONTINUED. RESULTS OF LABORATORY ASSAYS OF THE ANNUAL RATES OF
DECAY TO CO2, DcOz, AND THE EFFECT OF ENVIRONMENTAL
VARIABLES ON THE PROCESS.

Conditions Concentration | Deo, Mean 8.0.

5 x 10°4% Na Acetate | DDT 10 ppm 0028
1 ppm 0030 .00297 + 00015
100 ppb .0031

5 x 105% Na Acetate | DDT 10 ppm 0027
1 ppm 0030 00287 + 00015
100 ppb 0029

5x 10% Na Acetate | DDT 10 ppm | .0025

tppm | .0027 .00270 + 00020
100 ppb .0029
5x 107%Na Acetate | DDT 10ppm | .0028
1 ppm | .0030 00277 + 00025
100 ppb .0025
Anaerobic, 10°C
5 x 10°'% Ethanol DDT 10ppm | .0007
Tppm | .0005 .00043 + 00031
100 ppb 0001
5 x 10°2% Ethanol DDT 10ppm | .0027
1ppm | 0028 00273 + 00006
100 ppb 0027 :
5 x 10°3% Ethanol DDT 10ppm | .0034
1ppm | .0031 00307 + 00035
100 ppb 0027
5 x 10°4% Ethanol ODT 10ppm | .0029
1ppm | .0030 .00297 + 00006
100 ppb .0030
5 x 10°% Ethanol DDT 10ppm | .0034
tppm | 0032 .00320 + 00020
100 ppb .0030
5 x 10°6% Ethanol DDT 10 ppm. .0022
1ppm | 0023 .00230 + 00010
100 ppb 0024
5 x 107% Ethanol DDT 10ppm | 0023
tppm | ..0022 .00233 + 00015
100 ppb 0025
Aerobic, 10°C DDD 100 ppm | 0016
10 ppm | .0015 +
tppm | 0015 00173 + 00000

100 ppb .0023

Aerobic, 10°C DDE 100 ppm | .0030
10'ppm | .0028
1ppm | .0031
100 ppb .0041

00325 t .00058

54


1KM

eh FATHOMS

Figure 3. DDD as a percent of the total concentration of DDT, DDD, and DDE plotted for data
obtained in 1970 and 1971. Circled numbers indicate actual percents in excess of 50%.

20


RESEARCH REPORTING SERIES

Research reports of the Office of Research and Development,

U.S. Environmental Protection Agency, have been grouped into
five series. These five broad categories were established to
facilitate further development and application of environmental
technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in
related fields. The five series are:

Environmental Health Effects Research
Environmental Protection Technology
Ecological Research

Environmental Monitoring
Socioeconomic Environmental Studies

APwWnN—

This report has been assigned to the ECOLOGICAL RESEARCH STUDIES
series. This series describes research on the effects of pollution

on humans, plant and animal species, and materials. Problems are
assessed for their long- and short-term influences. Investigations
include formation, transport, and pathway studies to determine the
fate of pollutants and their effects. This work provides the technical
basis for setting standards to minimize undesirable changes in living
organisms in the aquatic, terrestrial and atmospheric environments.

EPA REVIEW NOTICE

This report has been reviewed by the Office of Research and
Development, EPA, and approved for publication. Approval does
not signify that the contents necessarily reflect the views and
policies of the Environmental Protection Agency, nor does mention
of trade names or commercial products constitute endorsement or
recommendation for use.


0980
0081

0082
0083

0084

0085

0086 -

0087
0088

0089
0090

0091
0092

0093
0094
0095
0096
0097
0098

0099

0100
0101
0102
0103
0104
0105

aAnNA

aANADA

a

aaAaaAAN

DO 12 K=1,ID
TOT(5,K)=0.

DO 11 J=1,IA
11 TOT(5,K)=TOT(5,K)+X(5,J,K)

12 M(5,K)=TOT(5,K)/AI

DO 14 K=1,ID
V=0.0

DO 13 J=1,IA
13 V=(M(5,K)-X(5,J,K))**2+V

STD(5,K)=SQRT(V/(AI-1.0))
14 CALL STDEV2 (STD(5,K),STE(5,K),CL95(5,K))

CALCULATE K VALUES.

DO 15 K=1,ID
SUM1(K)=0.0

DO 15 J=1,1A
IF (X(1,J,K).EQ.0) X(1,J,K)=.004
IF (X(2,J,K).EQ.0) X(2,J,K)=.004
V=(DLOG10(X(2,J,K))-DLOG10(X(1,J,K)))/(X(5,J,K))
V2(J,K)=10.**V—1.0

15 SUM1(K)=SUM1(K)+V2(J,K)

SORT K VALUES.

DO 17 K=1,ID

DO 17 J=1,1A

IF (V2(J,K).GT.0) GO TO 16
X(7,J,K)=V2(J,K)

GOTO 17

16 X(6,J,K)+V2(J,K)
17 X(8,J,K)=X(7,J,K)+X(6,J,K)

CALCULATE K-NET.

63


0001

0002
0003
0004
0005
0006
0007

0008

0009

0010
0011
0012
0013
0014
0015
0016
0017
0018
0019
0020
0021
0022
0023
0024
0025
0026
0027
0028
0029
0030
0031
0032
0033
0034

aaAnA

fo}

SUBROUTINE FOR PROGRAM FOR ESTIMATING SYSTEM RATES
BASED ON REAL PAIRED SAMPLE VALUES.
SUBROUTINE FACTOR
DIMENSION TABLE (30), MONTH(12), ALOC(2,60,6), TOT(10,8), STD(23,8)
1,STE(23,8), CL95(23,8), VAR1(7), VAR2(7), VAR3(7), SUM1(7), SUM2(
27), SUM3(7), SUM4(7), COV1(7), COV2(7)
REAL *4MEAN,M(17,8),MR(7)
REAL *8X(10,60,7),V2(60,7);NAME(23),V1(7)
INTEGER CST(2,60),CDATE(2,60,3)
COMMON X,TABLE,IA,1,K,KD,ID
COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L
COMMON /BLK2/ MR

CALCULATE CORRECTION FACTOR FOR STANDARD DEVIATION
AI=IA
DO 14 K=1,ID

IF (M(8,K)) 1,4,5

JX=(AI*M(7,K)—AI*M(10,K))/M(8,K)

VJ=JX

V=(((AI*M(10,K))/VJ)**2)*VJ

IF ((M(8,K)+((AI*M(10,K))/VJ))*VJ—(AI*M(7,K))) 3,3,2

2. V=V+(AI*M(7,K)—VJ*(M(8,K)+((AI*M(10,K))/VJ))—M(8,K)) **2
V=V+(((AI*M(6,K))/(AI-VJ—1.0))—M(8,K))**2*(AI-VJ-1.0)
GO TO 8

3 V=V+(((AI*M(6,K))/(AI-VJ))—M(8,K))**2*(AI-VJ)
GO TO8

_

4 JX=AI/2.0

VJ=JX
V=((AI*M(6,K)/VJ)**2)*VJ
V=V+((AI*M(7,K)/VJ)**2°VJ
GO TO 8
5 JX=(AI*M(6,K)—AI*M(9,K))/M(8,K)
VJ=JX ~
V=(((AI*M(9,K))/VJ)**2)*VJ
IF ((M(8,K)+((AI*M(9,K))/VJ))*VJ—(AI*M(6,K))) 6,7,7
6 V=V+(AI*M(6,K)—VJ*(M(8,K)+((AI*M(9,K))/VJ))—M(8,K))**2
V=V+(((AI*M(7,K))/(AI-VJ—1.0))—M(8,K))**2*(AI—VJ—1.0)
GO TO 8
7 V=V+(((AI*M(7,K))/(AI-VJ))—M(8,K))**2*(AI-VJ)
8 V=V(AI-1.0)
W=0.0

74


determination. A volume of the slurried sediment equivalent to 24 grams dry weight
is delivered to a sterile Hypovial and seawater, with or without additional nutrients,
is added to give a volume of 98 mi total. One ml each of !2¢ and 14C substrate ad-
sorbed to sterile sediment is added giving a final volume of 100 ml. The preparation
may be gassed with nitrogen to produce an anaerobic environment prior to sealing.
All incubators are in the dark for periods of generally twelve weeks. All preparations
are set up in quintuplicate. A typical protocol is presented in Table 2.

12¢ Substrate Preparation—2.4 grams of either, 1,1-bis-(p-chlorophenyl)-2,2,2-tri-
chloro ethane, p-p’DDT 99+% No. 10, 002-1; 2,2-bis-(p-chlorophenyl)-1,1-dichloro
ethylene, No. 12, 289-7 (B 3964); or 2,2-bis-(p-chlorophenyl)-1,1-dichloroethane,
puriss B 3959 Aldrich Chemical Co. Inc., Milwaukee, Wisconsin, were dissolved in
10 ml of acetone. To 10 grams of dried sterile sediment 1 ml of acetone solution
was added and the sediment wet with an additional 3 ml of acetone. The acetone
was evaporated off at room temperature and 96 ml of distilled water added to slurry
the sediment and its adsorbed substrate. One ml contains 2.4 x 103 ug of substrate
on 0.1 gram of sediment per ml. Similar preparations were made giving 2.4 x 102 ug
and 21.6 ug of substrate on 0.1 gram of sediment per ml.

14¢.DDT Substrate Preparation—Uniformly ring labelled DDT, Amersham/Searle Corp.,
63.9 u Ci/mg in benzene was used for preparation of the substrate. The original 250 u Ci
preparation was diluted with acetone and 240 ug in 4 ml was added to 10 grams of dried
sterile sediment. The acetone was removed by evaporation at room temperature and 96
ml of distilled water added to give 2.4 ug 1M4c.ppT and 0.1 gram of sediment per ml.

A similar preparation was made giving 0.24 ug 14¢-DDT and 0.1 gram of sediment per ml.

14¢.DDD Substrate Preparation—!4C-DDT was converted to 14¢-DDD by the method
of Murphy (1970) and purity of the product confirmed by gas chromatography. The
resulting material was used to prepare substrate as described above for !4C-DDT.

14¢-DDE Substrate Preparation—!4C-DDT was converted to !4c-DDE by the method
of Gunther and Blinn (1950) and purity of the product confirmed by gas chromatography.
The resulting material was used to prepare substrate as described above for !4¢-DDT.

Analysis of Decay Assays—After incubation for generally 12 weeks 14co, was trapped
by the addition of 1.5 ml of 5 N NaOH to the Hypovial. The base was introduced by
syringe and the ampoule resealed with tape. Syringe delivered 5 ml aliquots of the

basic slurried sediment were transfered to 25 ml Erlenmeyer flasks containing magnetic
stirring bars. The flasks were stoppered with Top stoppers, K-882310, fitted with plastic
center wells, K-882320, both from Kontes Glass Co., Vineland, N.J. The center wells
contained an accordian pleated Whatman No. 1 filter paper wick, 2.5x5 cm. B-phenyl-
ethylamine, 0.15 ml, was delivered to the well and wick by syringe through the stopper.
While the sediment in the flask was gently stirred on a magnetic stirrer 0.25 ml of 5 N
H2SO4 was added to the sediment. The flasks were then held for 24 hours at room
temperature after which time the wicks were removed to scintillation vials to which
was added 15 ml of Toluene-omnifluror. Appropriate preparations for background

10


0001
0062

0003
0004
0005
0006
0007

0008
0009

0010

0011
0012

0013

0014
0015
0016

0001
0002

0003
0004
0005
0006
0007
0008
0009
0010
0011
0012
0013

0014
0015
0016
0017
0018
0019

SUBROUTINE PRINT
DIMENSION TABLE(30), MONTH(12),ALOC(2,60,6),TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8)
REAL *4MEAN,M(17,8)
REAL *8X(10,60,7),NAME(23)
INTEGER CST(2,60),CDATE(2,60,3)
COMMON X,TABLE,JA,I,K,KD,ID
COMMON /BLW1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L

DO 1J=1,A
1 WRITE (6,3) CST(L,J), (ALOC(L,J,K),K=1,6),(CDATE(L,J,K),K=1,3),(X(1
1,J,K),K=1,L1)

SKIP TO BOTTOM OF PAGE
N=(68-(IA+6))/2

DO 2 J=1,N
2 WRITE (6,4)

RETURN

3 FORMAT (5X,12,5X,2A4,A2,2X,2A4,A2,2X,12,2(‘-’,12),8F 11.2)
4 FORMAT (/)
END

SUBROUTINE PRINT2

DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8)

REAL *4MEAN,M(17,8)

REAL *8X(10,60,7),NAME(23)

INTEGER CST(2,60),CDATE(2,60,3)

COMMON X,TABLE,IA,I,K,KD,ID

COMMON /BLK1/ NAME, TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L

WRITE (6,1) (TOT(I,J),J=1,L1)

WRITE (6,2) (M(1,J),J=1,L1)

WRITE (6,3) (STD(I,J),J=1,L1)

WRITE (6,4) (STE(I,J),J=1,L1)

WRITE (6,5) (CL95(I,J),J=1,L1)

RETURN

1 FORMAT (34X, ‘TOTALS’ ,6X,7F 10.4)

2 FORMAT (/34X,‘MEAN’ 8X,7F 10.4)

3 FORMAT (/34X,‘S.D.’,8X,7F 10.4)

4 FORMAT (/34X,'S.E.’,8X,7F 10.4)

5 FORMAT (/34X,‘95% CL’,6X,7F 10.4)
END

69


Table 8. THIRD PAGE OF COMPUTER OUTPUT SHOWING PERCENT OF TOTAL OF
EACH OF THE THREE COMPOUNDS IN SEDIMENTS FROM SAMPLE STATIONS
AT THE FIRST SAMPLING TIME. C, IDENTIFIES AS DATA FOR TIME ONE.

cy
j SS SSG =F
|
LOCATION DDT DDD DDE
Station Latitude Longitude Date (%) (%) (%)
1 36 47.25 121 48.90 8-23-70 46.99 20.63 32.38
2 36 46.85 121 53.50 11-15-70 7.06 29.28 63.66
3 36 46.35 121 49.00 2-20-70 76.75 9.54 13.71
4 36 46.05 121 51.00 11-15-70 19.82 30.62 49.56
10 36 45.10 121 50.00 5-29-70 29.05 39.23 31.72
11 36 45.00 121 49.00 2-20-70 81.19 8.85 9.96
14 36 44.20 121 52.25 8-23-70 18.44 26.60 54.96
16 36 44.00 121 49.50 2-20-70 19.27 3.91 76.82
7 36 43.75 121 54.45 11-15-70 48.57 18.10 33.33
19 36 43.35 121 56.25 8-23-70 55.45 12.38 32.18
20 36 43.18 121 57.00 2- 8-70 0.0 19.61 80.39
22 36 42.90 121 58.00 2-20-70 0.0 15.42 84.58
23 36 42.55 121 53.30 8-23-70 41.34 17.95 40.71
25 36 41.70 121 55.00 2-20-70 29.40 12.77 57.83
26 36 41.55 121 55.50 2- 870 0.0 25.11 74.89
29 36 40.90 121 56.40 2-20-70 11.05 13.47 75.48
34 36 39.10 121 53.08 2- 8-70 44.36 12.00 43.64
36 36 37.95 121 52.50 2-20-70 17.16 18.07 64.77
37 36 37.77 121 51.83 2- 8-70 40.83 17.50 41.67
TOTALS 586.7412 351.0149 962.2397
Mean 30.8811 18.4745 50.6442
Standard Deviation + 24.2998 + 86373 + 22.2953
Standard Error + 55748 + 1.9815 + 5.1149
95% Confidence Limits + 11.7126 + 4.1632 + 10.7464

27


0079 WRITE (6,24) NAME(K),M(11,K),STD(20,K),STE(20,K),CL95(20,K)

0080 WRITE (6,25) NAME(K),M(12,K),STD(21,K),STE(21,K),CL95(21,K)
0081 WRITE (6,26) NAME(K),M(13,K),STD(22,K),STE(22,K),CL95(22,K)
0082 WRITE (6,27)
0083 WRITE (6,26) NAME(K),M(14,K),STD(23,K),STE(23,K),CL95(23,K)
0084 WRITE (6,28)
0085 15 CONTINUE

Cc

Cc
0086 16 FORMAT (’1’,40X,‘CORRECTED STANDARD DEVIATIONS’//,2X, ‘RATES OF CHA

1NGE FOR; A8,30X,‘S.D.’,7X,‘S.E.’,4X,‘95% LIMIT’//)

0087 17 FORMAT (2X,‘MEAN OF K’,13X,‘=NET’,3X,A8,‘=’,3X,4F11.4/)
0088 18 FORMAT (2X,‘MEAN OF + ( K — NET ) = T’,5X,A8,‘=’,3X,4F11.4)
0089 19 FORMAT (27X,‘I’/)
0090 20 FORMAT (2X,‘MEAN: OF — ( K — NET ) = T’,5X,A8,‘=’,3X,4F11.4)
0091 21 FORMAT (27X,‘0’/)
0092 22 FORMAT (2X,‘MEAN OF + K’,11X,‘= 1’,5X,A8,‘=’,3X,4F11.4//)
0093 23 FORMAT (2X,‘MEAN OF ~ K’,11X,‘= 0+D’,1X,A8,‘=’,3X,4F11.4//)
0094 24 FORMAT (26X,‘0',5X,A8,‘=’,3X,4F11.4/)
0095 25 FORMAT (26X,‘D’,5X,A8,‘=",3X,4F11.4/)
0096 26 FORMAT (26X,'T’,5X,A8,‘=’,3X,4F11.4)
0097 27 FORMAT (27X,’L’/)
0098 28 FORMAT (27X,‘R’)

Cc
0099 RETURN
0100 END

98


0 = Ty (O+D) ()
I

D = (1.0 - Ty) (O+D) or D = (O+D) -O (6)
I

The residence time, Tp, and lifetime, TL, in years, are calculated as the corresponding
reciprocals.

Tp = 1.0/(0+D) (7)
TL =1.0/D (8)

The last three pages of computer output present a summary of these estimations and
are presented in Tables 13, 14, and 15.

The effect of substitution of’a minimal value for zero concentrations was investigated
by reducing the set of sample stations to sixteen and elimination of all stations showing
a zero concentration of DDT at timie one. While there was some effect upon the esti-
mates of rates as the system was reduced in size, only the estimates of Tg for DDT
were significantly different when tested by the “test of equality of the means of two
samples whose variances are assumed to be unequal” (Sokol and Rohlf, 1969). The
difference between the other estimates was very small compared to the standard
deviation of these estimates. Table 16 presents for comparison the set of rates for

the nineteen and sixteen station data sets.

The approach to analysis of the data which provided these estimates of system rates
requires sampling at the same stations at two different times. However, as presented
in Table 3, there is additional data available with respect to the south bay system at
time one. This additional data can not be used by the approach to analysis presented
so far. More stations were sampled in the first sampling period than were sampled in
the second, and the approach requires pairs of samples identical except for time of
sampling. An additional program was written to permit analysis of a system where
sampling does not meet the requirements of the first approach. This second program
treats all samples as unpaired and. evaluates the rate of change, K, at the different
sample locations by comparison of the actual measurement at that station at time
one or time two with the mean concentrations of the system at either time one or
time two. That is, a measurement at time one is paired with the mean concentration
at time two and vice versa for the evaluation of K. Further the time interval, N, is
evaluated as the interval between the time of actual sample of one sampling time

and the mean time of the other sampling period. Equation 1 becomes,

Cp =Cy eKN 9.
with N=T)-Ty

34


APPENDIX A

PROGRAM FOR ESTIMATING SYSTEM RATES BASED ON REAL PAIRED SAMPLE VALUES.

This program for calculation of estimates of rates of input, output, translocation, and decay
was written in Fortran IV level G, and was run on an IBM 360/67. In our experience 112k
was used and the program required approximately 40 seconds per run. A maximum of 60
stations, 7 chemical compounds, and 2 sample times is permitted with the program as written.

The time interval is calculated in the subroutine, LEAPYR, through use of a calendar table
described below. K values are calculated using double precision, and confidence intervals are
estimated through use of a table of “‘t values.”

There are eight cards which precede the data deck. Their formats and content are as follows:

First three cards, FORMAT (1X,13F6.3/13F6.3/4F6.3), contain the table of t values.
The following numbers are punched using the indicated format:
First card, 12.706 4.303 3.182 2.776 2.571 2.447 2.365 2.306 2.262 2.228 2.201
2.179 2.160
Second card, 2.145 2.131 2.120 2.110 2.101 2.093 2.086 2.080 2.074 2.069 2.064
2.060 2.056
Third card, 2.052 2.048 2.045 2.042.

Fourth card, FORMAT (1214), contains numbers for calculation of time intervals.
The following numbers are punched using the indicated format:
0 31 59 90 120 151 181 212 243 273 304 334.

Fifth card, FORMAT (215), contains the number of stations followed by the number
of chemical compounds in the data set.

Sixth through eighth cards, FORMAT (10A8), contain the names of the chemical
compounds entered, left justified, followed by the word TOTAL, followed by the
concentration level repeated once for each chemical compound. Any remaining
portion of the three cards is left blank. The set of name cards used with the data
analyzed in the present case was as follows:

First Card
DDT DDD DDE TOTAL PPB PPB PPB PPB PERCENT PERCENT

Second Card
PERCENT

The third card was left blank.

The data is organized using FORMAT (1X,12,2(A4,A2),12,2(1X,12),7F7.2). The first variable
is the station number. The next six fields store the location in terms of latitude and longitude.
The next three variables store the month, day, and year, and the remaining fields store the
measured concentrations of each chemical compound.

An optional subroutine FACTOR may be called by placing a card before the END card with CALL

FACTOR.
59


Therefore, for the estimation of the overall rate of change in a compartment, ie., the
resultant of the various rates affecting concentration, the following expression was
solved for K,

C2 =CyeKN qa)

Cy and C2 are the concentrations within the compartment at time one and time two,
N is the length of the time interval in years, and e is the natural logarithm base. K is a
nominal percentage rate in the form of a decimal fraction resulting in continuous com-
pounding, and is converted to an annual rate for the expression,

C2 = Cy (1+K)N (2)

The results of these calculations for the three compounds are presented as the fifth, sixth,
and seventh pages of computer output in Tables 10, 11, and 12. In these tables the values
of K are sorted into positive and negative values for purposes discussed below. Compart-
ments which showed a zero concentration at time one were adjusted by substitution of
0.004 ppb, a value generally just below the level of detection in the analyses.

The standard deviation of these estimates was approximated through the use of the ex-
pression for the standard deviation of a function of two random variables (Papoulis, 1965),
aK? G2  @K?2 g?s 22k K
~ (SE) O1 +) OL+ 2277 GB)
K(Cy,Cp) — “VCy ~C," Cy “C, “AC, WC, “CC,
For ease in computation only two variables at a time were used in developing this ap-
proximation to the standard deviation.

If we assume that the rate of change within the system can be approximated by the mean
rate of change of its separate compartments, the mean of the K values becomes an esti-
mate of the rate of net change of the system.

Net rate of change = I - (O+D) (4)

This net rate of change is unaffected by the rates of internal translocation, Tj and To,
which are equal in magnitude and opposite in sign. The net rate of change is the sum of
“two other mean rates. One is the rate of input, I, which can be estimated by the mean
of the positive K’s, and the other is obtained as the mean of the negative K’s and may
be taken as an estimate of (O+D) in equation 4.

The mean of the differences between each K and the net rate of change, that is the mean
deviation from the mean of K, becomes an estimate of To and Ty. The results of these
calculations are included in Tables 10, 11, and 12.

The separation of the rate O and D is more difficult and several approaches have been
attempted. The decimal fraction of the input rate that is translocated within the system,
Ty/I, differs from compound to compound: DDT, 0.665; DDD, 0.882; and DDE, 0.860.
One explanation for this difference is that they reflect differences in the rates of decom-
position within the sediments. Based upon this assumption the rate O and D have been
estimated by the following equations,

30


0049
0050
0051
0052
0053
0054
0055

0056

0057
0058

0059
0060
0061
0062
0063
0064
0065

0066
0067
0068
0069
0070
0071

0072

0073
0074
0075
0076

0077
0078
0079

aaanNAa

DO 8 I=3,4

Li=ID

L=I-2

WRITE (6,51) L

WRITE (6,53) (NAME(N),N=1,ID)

WRITE (6,52) (NAME(N),N=12TP3,13TP2)
WRITE (6,54)

DO 6 K=1,ID

DO 6 J=1,1A
6 X(1J,K)=X(L,J,K)/X(L,J,IP1)* 100.

DO 7 K=1,3
CALL STDEV (TOTAL,MEAN,SD,SE,CL)
TOT(I,K)=TOTAL
M(I,K)=MEAN
STD(I,K)=SD
STE(I,K)=SE
7 CL9S(I,K)=CL

CALL PRINT
WRITE (6,53) (NAME(N),N=1,ID)
WRITE (6,52) (NAME(N),N=12TP3,13TP2)
WRITE (6,54)
CALL PRINT2
8 CONTINUE

DO 10J=1,1A
DO 10 L=1,IA
IF (CST(1,J).EQ.CST(2,L)) GO TO 9
GO TO 10
9 CALL LEAPYR (J)
DO 10 K=1,ID

X(5,J,K)=YR
10 CONTINUE

CALCULATE TOTAL AND MEAN OF N.

62


i TECHNICAL REPORT DATA

(Please read Instructions on the reverse before completing)
Traitor NO, ? 3. RECIPIENT'S ACCESSION NO.
EPA-660/3-75-013 ee
ATPL AND SUGTUILE Is. REPORT DATE
"An Analysis of the Dynamics of DDT in Marine 5 scare de mw out
Sediments." :
VROTHORIT 8. PERFORMING ORGANIZATION REPORT NO.

Phillips, John H., Eugene E. Haderlie, and Welton L. Lee

IG. rR OHMING ORGANIZATION NAME ANO ADDRESS 10. PROGRAM ELEMENT NO.
Hopkins Marine Station = —_—
Stanford University : .

Pacific Grove, CA 93950

17, SPONSORING AGENCY NAME ANO ADDRESS 13. TYPE OF REPORT AND PERIOD COVERED
Environmental Protection Agency 7a SPONSORING AGENCY CODE
200 S. W. 35th St.

Corvallis, OR 97330

10, GUPPLLEMENTARY NOTES:

[TABeHACT “The concentrations of DDT, DDD and DDE were measured in sediments at 57

stations in Monterey Bay on the Central California coast during 1970-1971. Mean
concentrations in parts per billion were DDT 3.1, DDD 2.3, and DDE 5.4. During

1973 nineteen of the original stations were sampled. Mean concentrations were
DDT 15.5, DDD 2.3, and DDE 5.4 PPB. :

Two approaches to ‘the estimation of annual system rates for input, I, output,
0, decay, D, and internal translocation, T, and Tg expressed as decimal fractions
of existing concentraticns were developed, and fraction programs that permit
rapid estimations were written. The mean annual rates in South Monterey Bay
obtained were for DDT, I +1.30, 0 -0.059, D -0.036 Ty and To +0.80 with a residence
time of 11 years and life time of 29 years. An I of 1.30 means the amount of input
is 130% of the existing concentration per year. Rates for DDD were, I +0.25, 0
-0.11, D -0.025, Tz and To +0.20 with residence time of 7 years and life time of 44
years. Rates for DDE were I +0.28, 0 -0.10, D -0.027, To and Ty +0.22 with residence
time of 8 years and life time of 39 years.

Laboratory assays were developed to determine the relative rate of decomposition
in sediment under conditions selective for various physiologically different kinds of
microorganisms. Decay under aerobic conditions was greater than under anaerobic con-

ditions. Nitrate increased the rate Of decomposition under anaerobic conditions.
The QJQ for decay was 2.5.

17,

KEY WORDS AND DOCUMENT ANALYSIS

q Desc ‘S b. 1OENTIFIERS/OPEN ENDED TERMS |c. COSATI Field/Group
Degradation, DDT, DDD, DDE, Coastal, Microbial degradation, 12 and 33
Pollution chemical degradation,

rates of change,
pesticide residues,
chlorinated hydrocarbon

pesticides
organic pesticides

VE. UIS FAIRUTION STATEMENT 19. SECURITY CLASS (This Report) 21, NO. OF PAGES
20. SECURITY CLASS (This page) 22. PRICE

EPA Porm 2220-1 (8-73) 4 U.S, GOVERNMENT PRINTING OFFICE: 1975~698- 259/118 REGION 10


Table 17. COMPARISON OF ESTIMATES OBTAINED FROM THE 49 AND 57 STATION DATA SETS AND

USING SAMPLE ANALYSES PAIRED WITH MEAN CONCENTRATION LEVELS. STANDARD

DEVIATIONS [S.D.] AND COEFFICIENTS OF VARIATION [C.V.] ARE INCLUDED.

49 SAMPLE DATA SET

57 SAMPLE DATA SET

Estimate S.D. Cv. Estimate S.D. Cv.
(%) (%)
DOT
Cy (ppb) 3.9576 + 4.1746 105.4 3.1019 t 4.0336 130.0
C2 (ppb) 15.4975 + 26.5034 171.0 15.4975 + 26.5034 171.0
-Net + 0.5905 + 1.0000 169.3 + 2.2567 + 1.0000 44.3
| + 0.6819 t 0.6374 93.5 + 2.3233 + 0.9204 39.6
O+D 0.0913 £ 0.3626 397.2 0.0667 + 0.0796 119.3
To 0.3234 t 0.3966 122.6 > 1.4256 t 0.1513 10.6
Ty + 0.3234 t 0.6034 186.6 + 1.4256 + 0.8487 59.5
fe) - 0.0433 + 0.1720 397.2 - 0.0409 + 0.0488 119.3
is) 0.0480 t 0.1906 397.1 0.0258 + 0.0307 119.0
TL (years) 20.8292 t 82.7111 397.1 38.8090 t 46.2947 119.3
TR (years) 10.9502 £ 43.4823 397.1 14.9951 t+ 17.8875 119.3
ODD
Cy (ppb) 2.4107 + 2.5354 105.2 2.2743 t 2.3532 103.5
C2 (ppb) 2.3435 t 2.8415 121.3 2.3435 t 2.8415 121.3
Net + 0.1283 + 1.0000 779.4 + 0.1587 + 1.0000 630.1
1 + 0.2703 + 0.6357 235.2 + 0.2813 t 0.6329 225.0
O+0 0.1420 + 0.3643 256.5 - 0.1226 + 0.3671 299.4
To - 0.2095 t 0.3653 174.4 > 0.2039 + 0.3698 180.9
Ty + 0.2095 +t 0.6347 303.0 + 0.2039 t 0.6311 309.5
fe) 0.1101 + 0.2823 256.4 0.0889 + 0.2662 299.4
Oo - 0.0319 + 0.0820 257.1 0.0337 + 0.1010 299.7
TL (years) 31.3031 + 80.3119 256.6 29.6518 t 88.7883 299.4
TR (years) 7.0424 + 18.0682 256.6 8.1558 + 24.4216 299.4
DDE
Cy (ppb) 5.1138 + 4.4111 86.3 5.3681 + 4.8069 89.5
C2 (ppb) 6.1575 + 5.6469 91.7 6.1575 + 5.6469 91.7
Net + 0.1748 + 1.0010 572.7 + 0.1793 t 1.0009 558.2
| + 0.2802 + 0.6628 236.5 + 0.2785 t 0.6787 243.7
O+D 0.1054 t 0.3382 320.9 + 0.0993 t 0.3222 324.5
To - 0.1946 t 0.3466 178.1 - 0.1906 t 0.3311 173.7
an + 0.1946 + 0.6544 336.3 + 0.1906 t 0.6697 351.4
fe) - 0.0732 + 0.2348 320.8 - 0.0679 t 0.2204 324.6
D + 0.0322 t 0.1033 320.8 0.0314 + 0.1018 324.2
Tr (years) 31.0400 + 99.5728 320.8 31.8905 + 103.4957 324.5
TR (years) 9.4853 t+ 30.4277 320.8 10.0735 + 32.6922 324.5

40



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aAaNAAN

aaaa

a

aaa

DO 21 J=1,1A3
21 V=(M(5,K)-X(5,J,K))**2+V

STD(5,K)=SQRT(V/(AI3-1.0))
22 CALL STDEV2 (STD(5,K),STE(5,K),CL95(5,K))

CALCULATE K VALUES.
DATA IN TWO SETS ARRANGED CHRONOLOGICALLY
CALCULATE K VALUES

DO 24 K=1,ID
SUM1(K)=0.0
IB=1A(2)

DO 23 J=1,IB
IF (X(2,J,K).EQ.O.) X(2,J,K)=.004
V=(DLOG10(X(2,J,K))-ALOG10(M(1,K)))/(X(5,J,K))
V2(J,K)=10.**V—1.0

23 SUM1(K)=SUM1(K)+V2(J,K)

IB=IA(1)

DO 24 J=1,1B
IF (X(1,J,K).EQ.0.) X(1,J,K)=.004
V=ALOG10(M(2,K))-DLOG10(X(1,J,K)))/X(5,J+IA(2),K)*.43429)
V2(J+1A(2),K)=10.* *(V*.43429)—1.0

24 SUM1(K)=SUM1(K)+V2(J+IA(2),K)

SORT VALUES
DO 26 K=1,ID
DO 26 J=1,J2T
IF (V2(J,K).GT.0.) GO TO 25
X(7,J,K)=V2(,K)
GO TO 26
25 X(6,J,K)=V20],K)
26 X(8,J,K)=X(7,J,K)+X(6,J,K)
CALCULATE K-NET

DO 28 K=1,ID

82


SECTION III

INTRODUCTION

Although the accumulation of chlorinated hydrocarbons in the marine ecosystem has
been a matter of concern for some time, methods for assessing the rates of accumula-
tion, decay, and translocation have been lacking. The problem is not unique to the ma-
rine environment, and methods for assessment of the dynamics of chemical pollutants
in general are needed for meaningful analysis of the residue measurements tabulated in
most investigations. Without an assessment of rates such tabulations generally permit
only the detection of some general trend of increase or decrease in concentration during
the period of study. In many cases, however, the amount of variability is so great that
the number of samples required to show such general trends is prohibitive. Yet we have
both the data available and a need to use these data for meaningful assessment. In addi-
tion, before any feasible monitoring activity geared to control and regulatory strategies
are designed and implemented, a means of assessing any new tabulations is required as
a determinant in the design of such activities. Whatever systems of assessment may be
developed in the future it cannot be expected that they will overcome the variability
that plagues environmental sampling. Rather, such systems should be expected to pro-
vide an estimate of this variability and a confidence interval for any derived parameter
of environmental change.

Several models stressing one or another aspect of the dynamics of pesticides in the en-
vironment have been presented (Hamaker 1966, Robinson 1967, Woodwell 1967, Har-
tison et al. 1970, and Eberhardt et al. 1971), but there still appears to be a need for a
general approach that provides a means of estimating rates of input, decay, and trans-
location from some minimal number of analyses. The study presented here is an attempt
to fill this need.

The data used here for these estimations consists of analyses of marine sediment samples
for 1,1,2-trichloro-2,2-bis (p-chlorophenyl) ethane, DDT; 1,1-dichloro-2,2-bis (p-chloro-
phenyl) ethane, DDD; and 1,1-dichloro-2,2-bis (p-chlorophenyl) ethylene, DDE. The

rates of decay at a sampling site and translocation away from a sampling site are difficult
to separate through the approach to estimation presented. Laboratory measurements of
the rate of !4C ring labelled DDT in marine sediments held under a variety of conditions
are also presented. These measurements reflect decay to the point of M4coy release rather
than conversion to any one of a variety of other metabolites including DDD and DDE,
but are useful in assessing the method of estimation based upon environmental samples
alone.

The analysis of DDT residue levels in marine sediments reported herein is only a part of
a larger study correlating the levels of pollutants with density and composition of benthic
populations. Other results of this study will be reported elsewhere.


GFIAI- FF Cit

Abstract
List of Figures

List of Tables

Acknowledgements

Sections

I Conclusions

Il Recommendations

I Introduction

IV Methods

v Results and Discussion

VI References

VII Appendices

CONTENTS

iii

13

58

59


Table 15. TENTH PAGE OF COMPUTER OUTPUT SHOWING A SUMMARY OF THE ANNUAL
SYSTEM RATES EXPRESSED AS DECIMAL FRACTIONS OF THE MEAN CONCEN-
TRATION OF DDE PRESENT IN THE SYSTEM.

95%

System of Rates for DDE S.D. S.E. Limit
Net rate of change =Net = + 0.1177 t 1.0024 + 0.2300 + 0.4831
Translocation into

compartments =T =+ 0.2343 + 0.7761 * 0.1781 * 0.3741
Translocation out of

compartments =Tg =- 0.2343 + 0.2262 * 0.0519 + 0.1091
Input =| =+ 0.2725 ¢t 07781 + 0.1785 + 0.3750
Output and Decay =O+D = 0.1548 ¢ 0.2243 + 0.0515 +¢ 0.1081
Output from System = = 0.1331 + 0.1929 + 0.0442 + 0.0930
Decay = = 0.0217 + 0.0314 + 0.0072 *¢ 0.0151
Lifetime in years =TL = 46.1286 + 66.8453 + 15.3354 + 32.2196
Residence time in years =TR = 6.4611 + 93629 + 2.1480 + 4.5129
Summary Equation for the System—

DDE Mean Cy Mean Cy | a To ie) OD N
6.3384 = 6.6310 (1.0 + 0.2725 + 0.2343 - 0.2343 - 0.1331 - 0.0217) 3-1628

37


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*0233
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0241
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0250
0251

0252

Cc

DO 43 L=1,3
43 WRITE (6,54)

WRITE (6,68)
WRITE (6,69) M(5,K)
WRITE (6,70) NAME(K),M(2,K),M(1,K),M(6,K),M(9,K),M(10,K),M(11,K),M
1(12,K)
44 CONTINUE

CALL FACTOR
STOP

45. FORMAT (1X,13F6.3/13F6.3/4F6.3)

46 FORMAT (1214)

47, FORMAT (215)

48 FORMAT (10A8)

49 FORMAT (1X,12,2(2A4,A2),12,2(1X,12),7F7.2)

50 FORMAT(‘1’)

51 FORMAT(‘1’,'C'/2X,11,/3X, ‘STATION ’,3X,‘LATITUDE’,3X,‘LONGITUDE’,
-5X,‘DATE’)

52 FORMAT(48X,8(3X,A8))

53 FORMAT(‘+’,47X,8(3X,A8))

54 FORMAT(/)

55 FORMAT(‘1’,1X,'RATES OF CHANGE FOR ‘,A8,30X,'S.D.’,7X,'S.E.’,4X,
~*95% LIMIT’//) .

56 FORMAT(2X,MEAN OF K’,13X,'= NET’,3X,A8,‘=",3X,4F 11.4/)

57 FORMAT(2X, ‘MEAN OF + ( K - NET ) = T’,5X,A8,‘=",3X,4F 11.4)

58 FORMAT(27X,'I’/)

59 FORMAT(2X,'MEAN OF - ( K - NET ) = T’,5X,A8,‘=",3X,4F 11.4)

60 FORMAT(27X,‘0’/)

61 FORMAT(2X,'MEAN OF + K’,11X,'= I',5X,A8,'=’,3X,4F11.4//)

62 FORMAT(2X,‘MEAN OF - K’,11X,'= O + D’,1X,A8,‘=’,3X,4F 11.4//)

63 FORMAT(26X,‘0’,5X,A8,‘=",3X,4F11.4/)

64 FORMAT(26X,'D’,5X,A8,‘=",3X,4F11.4/)

65 FORMAT(26X,‘T’,5X,A8,‘=’,3X,4F 11.4)

66 FORMAT(27X,'L"/)

67 FORMAT(27X,'R’)

68 FORMAT(13X,‘MEAN C’,6X,‘MEAN C’,16X,‘I’,10X,'T’ 6X, -’,4X,'T’,6X,
“,5X,‘0" 5X,” 5X,'D’,9X,'N'/19X,'2", 11X,'1,27X, 7,1 1X,'0"/)

69 FORMAT(/97X,F11.4)

70 FORMAT(2X,A8,F10.4,' =",F10.4,' (1.0 +,F10.4,' +’,F10.4,3(F 12.4)
)’)

_ END

68


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WRITE (6,21)
WRITE (6,22) NAME(K),M(6,K),STD(15,K),STE(15,K),CL95(15,K)
WRITE (6,23) NAME(K),M(7,K),STD(16,K),STE(16,K),CL95(16,K)
WRITE (6,24) NAME(K),M(11,K),STD(20,K),STE(20,K),CL95(20,K)
WRITE (6,25) NAME(K),M(12,K),STD(21,K),STE(21,K),CL95(21,K)
WRITE (6,26) NAME(K),M(13,K),STD(22,K),STE(22,K),CL95(22,K)
WRITE (6,27)
WRITE (6,26) NAME(K),M(14,K),STD(23,K),STE(23,K),CL95(23,K)
WRITE (6,28)

15 CONTINUE

16 FORMAT (‘1’,40X,‘CORRECTED STANDARD DEVIATIONS’//,2X,‘RATES OF CHA
1NGE FOR ‘,A8,30X,‘S.D.’,7X,'S.E.’,4X,‘95% LIMIT’//)

17 FORMAT (2X,‘MEAN OF K’,13X,‘= NET’,3X,A8,‘=’,3X,4F11.4/)

18 FORMAT (2X,‘MEAN OF + ( K — NET ) = T’,5X,A8,‘=’,3X,4F 11.4)

19 FORMAT (27X,‘I’/)

20 FORMAT (2X,‘MEAN OF — ( K — NET ) = T’,5X,A8,‘=",3X,4F 11.4)

21 FORMAT (27X,‘0'/)

22 FORMAT (2X,‘MEAN OF + K’,11X,‘= I’,5X,A8,‘=,3X,4F11.4//)

23 FORMAT (2X,‘MEAN OF — K’,11X,‘= O + D’,1X,A8,‘=’,3X,4F11.4//)

24 FORMAT (26X,‘0’,5X,A8,‘=’,3X,4F11.4/)

25 FORMAT (26X,‘D’,5X,A8,‘=’,3X,4F11.4/):

26 FORMAT (26X,‘T’,5X,A8,‘=’,3X,4F11.4)

27 FORMAT (27X,'L’/)

28 FORMAT (27X,‘R’)

RETURN
END

77


EPA-660/3-75-013
MAY 1975

Ecological Research Series

An Analysis of the Dynamics of DDT
in Marine Sediments

ted S%

fr
wy

7

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(@)
NW agenct

2
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3
Zz
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vp, é
AL pror®

National Environmental Research Center
Office of Research and Development
U.S. Environmental Protection Agency

Corvallis, Oregon 97330


ABSTRACT

The concentration of the three chlorinated hydrocarbons, DDT, DDD, and DDE, were
measured in sediments at 57 stations in Monterey Bay on the Central California coast
during 1970 and 1971. Mean concentration in parts per billion was DDT 3.1, DDD 2.3,
and DDE 5.4, Maximum concentrations were DDT 19.3, DDD 8.7, DDE, 20.5 parts per
billion. The distribution of the three compounds within South Monterey Bay was
charted. During 1973 nineteen of the original stations, representing locations that were
low, intermediate, and high concentrations in the original survey, were resampled. The
mean concentration approximately three years later were DDT 15.5, DDD 2.3, and DDE
5.4 parts per billion with maximum levels of DDT 83.1, DDD 11.4, and DDE 17.5 parts
per billion. A chart of the concentrations in South Monterey Bay revealed essentially
the same distribution of chlorinated hydrocarbons.

Two approaches to the estimation of annual system rates for input, I, output, O, decay,
D, and internal translocation, Ty and To, expressed as decimal fractions of the existing
concentration were developed, and Fortran programs that permit rapid estimations were
written. The mean annual system rates obtained were for DDT, 1+1.30, O-.059, D-.036,
Ty and Tg + .80 with a residence time of 11 years and life time of 29 years. An I of 1.30
means the amount of input is 130% of the existing concentration per year. The mean
annual rates obtained for DDD were, I + 0.25, O - 0.11, D - 0.025, Ty and Tg + 0.20 with
residence time of 7 years and life time of 44 years. The rates for DDE were | + 0.28,

O - 0.10, D - 0.027, To and Ty + 0.22 with residence time of 8 years and life time of 39
years. The approaches to these estimates are dependent upon variability in net rates of
change at the various stations and an approach to evaluation of the standard deviation

of the estimated rates relative to distributions of net rates with minimal variance is pre-
sented.

Laboratory assays were developed to determine the relative rate of decomposition in
sediment placed under conditions selective for various physiologically different kinds
of microorganisms. 14¢ ting labelled substrates were used in all assays. Decay of the
three chlorinated hydrocarbons under aerobic conditions without additional nutrients
was greater than decay under anaerobic conditions. The addition of accessory energy
and carbon sources such as sodium acetate did not increase the rate of decay under
anaerobic conditions. There was some decay under anaerobic conditions suggesting
mechanisms of ring cleavage not involving incorporation or oxygen prior to ring split.
Nitrate as an accessory electron acceptor increased the rate of decomposition under
anaerobic conditions. Degradation products formed from the parent compounds in-
cluded water soluble intermediates as well as carbon dioxide.

The Qj for the decay process as determined by laboratory assays incubated at 10° and
20° C. is 2.5.

This report was submitted in fulfillment of Grant No. R 800365 by Hopkins Marine Station.
Work was completed under sponsorship of the Environmental Protection Agency as of 1974.

ENVTROW

PROTECTION AGENOY


Table 6. FIRST PAGE OF COMPUTER OUTPUT.SHOWING CONCENTRATION OF

POLLUTANT COMPOUNDS IN SEDIMENT FROM SAMPLE STATIONS

AT FIRST SAMPLING TIME. Cy IDENTIFIES AS CONCENTRATIONS AT

TIME ONE.
Cy
|
H LOCATION DDT | DDD| DDE

Station | Latitude Longitude Date (ppb) (ppb) (ppb) TOTAL
1 36 47.25 121 48.90 8-23-70 | 8.36 | 3.67 5.76 17.79
2 36 46.85 121 53.50 11-15-70 | 1.63 | 676 | 14.70 | 23.09
3 36 46.35 121 49.00 2-20-70 | 5.71 071 1.02 7.44
4 36 46.05 121 51.00 11-15-70 | 4.28 | 6.61 | 10.70 | 21.59
10 36 45.10 121 50.00 5-29-70 | 642 | 8.67 7.01 22.10
" 36 45.00 121 49.00 2-20-70 | 367 | 040 | 0.45 4.52
14 36 44.20 121 52.25 8-23-70 | 5.20 | 7.50 | 15.50 | 28.20
16 36 44.00 121 49.50 2-20-70 | 069 | 0.14 | 2.75 3.58
17 36 43.75 121 54.45 11-15-70 | 1.02 | 038 | 0.70 2.10
19 36 43.35 121 56.25 8-23-70 | 1.12 | 0.25 | 065 2.02
20 36 43.18 121 57.00 2870 | 0.0 5.00 | 20.50 | 25.50
22 36 42.90 121 58.00 2-20-70 | 0.0 0.35 1.92 2.27
23 36 42.55 121 53.30 8-23-70 | 13.20 | 5.73 | 13.00 | 31.93
25 36 41.70 121 55.00 2-20-70 | 1.22 | 053 | 240 4.15
26 36 41.55 121 55.50 2. 8-70 | 0.0 2.35 | 7.01 9.36
29 36 40.90 121 56.40 2-20-70 | 1.32 1.61 9.02 11.95
34 36 39.10 121 53.08 2.870 | 244 | 066 | 2.40 5.50
36 36 37.95 121 52.50 2-20-70 | 265 | 2.79 | 10.00 15.44
37 36 37.77 121 51.83 2870 | 049 | 0.21 0.50 1.20

TOTALS 59.4199 54.3199 125.9899 239.7298

Mean 3.1274 2.8589 6.6310 12.6174

Standard Deviation + 3.4385 t 2.9296 6.0673 t 10.1773

Standard Error + 0.7889 0.6721 + 1.3919 + 2.3348

95% Confidence Limits + 1.6574 + 1.4121 + 2.9245 + 4.9055

25



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aan

aan

VAR1(K)=(.43429/M(1,K))**2*SUM3(K)/(AI3-1.0)+(-.43429/M(2,K))**2
1*SUM4(K)/(AI3-1.0)
34 V1(K)=SUM2(K)/AI3

DO 36 K=1,ID
VAR2(K)=((1.0/M(5,K))**2*VAR1(K))+(-V1(K)/M(5,K)* *2))**2*STD(5,K)
1**2
VAR2(K)=10.0** VAR2(K)
STD(8,K)=SQRT(VAR2(K))
36 CALL STDEV2(STD(8,K),STE(8,K),CL95(8,K))

CALCULATE THE DISTRIBUTION OF VARIANCE BETWEEN +K AND-K.

DO 41 K=1,ID
Vv=0.0

DO 38 J=1,J2T
IF (X(6,J,K))38,38,37

37 V=(X(6,J,K)-M(8,K))**2+V

38 CONTINUE

V=V/AI3-1.0
W=0.0

DO 40 J=1,J2T
IF (X(7,J,K)) 39,40,40
39 W=(X(7,J,K)-M(8,K))**24+W
40 CONTINUE

W=W/AI3-1.0)

U=V+W

V=STD(8,K)**2*(V/U)**2

STD(6,K)=SQRT(V)

W=STD(8,K)**2*(W/U)**2

STD(7,K)=SQRT(W)

CALL STDEV2(STD(6,K),STE(6,K),CL95(6,K))
41 CALL STDEV2(STD(7,K),STE(7,K),CL95(7,K))

CALCULATION OF STANDARD DEVIATION K-NET AND ITS DISTRIBUTION.

DO 46 K=1,ID
V=0.0
W=0.0

DO 45 J=1,J2T

IF(X(9,J,K))43,43,42
42 V=V+(X(9,J,K))**2)
43 IF(X(10,J,K))44,45,45
44 W=W+(X(10,J,K)**2)
45 CONTINUE

84


0013
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0022

0023

0024

0025
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0027

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0034

AANAAANAAAA

aaa

aaa

CALCULATE INDEXES.

Al NUMBER OF STATIONS CONVERTED TO A REAL NUMBER.
AL3 AI(1) + AI(2)

1A3 TA(1) + 1A(2)

Pi ID+1

1P2 ID+2

12TP2 2*ID+2

12TP3 2*ID+3

13TP2 3*ID+2

jot TA(1) + TA(2)

AI(1)=1A(1)
AI(2)=1A(2)
AI3=AI(1)+AI(2)
1A3=IA(1)+1A(2)
IP1=ID+1
IP2=ID+2
12TP2=2*ID+2
12TP3=2*ID+3
13TP2=3*ID+2
J2T=1A(1)+1A(2)

CLEAR X ARRAY.
DO 4 1=1,10
DO 4 J=1,J2T

DO 4 K=1,IP1
4 X(IJ,K)=0.0

WRITE (6,9)
READ IN DERIVATIVE NAMES AND CONCENTRATION LEVEL ON UP TO 3 CARDS.
READ (5,5) NAME

5 FORMAT (10A8)

READ IN DATA.
6 FORMAT (1X,12,2(2A4,A2),12,2(1X,12),7F7.2)

DO 7 I=1,2
IB=IA(I)

DO 7 J=1,IB
7 READ (5,6) CST(I,J),(ALOC(,J,L),L=1,6),(CDATE(I,J,L),L=1,3),(X(,
1J,K),K=1,ID)
COMPUTE TOTAL OF EACH STATION.

79


RATIONALE OF DESCRIBED WORK

Selection of Study Site and Source of Marine Sediments for Decay Assays—For the
estimation of rates governing the dynamics of a chlorinated hydrocarbon pollutant

in marine sediments an area with the following characteristics appeared most desirable.
(1) The marine area should be adjacent to a land area for which there exists an account-
ing of input to the environment through normal use. The use of DDT and DDD within
the State of California has been subject to such accounting on a square mile section
basis since 1970 (Calif. Dept. of Agriculture 1970). Such accounting is available only
for normal agricultural and related uses. Therefore, areas which receive or have received
less well determined inputs from chlorinated hydrocarbon manufacture, such as the ocean
adjacent to Los Angeles, are less desirable for this type of study. (2) In order to assess
translocation within the study area it would appear desirable to select a marine area
with a limited number of point sources of input rather than one subject to diffuse in-
put by way of the atmosphere. (3) The area should be one open to general oceanic in-
fluence rather than a closed system so that translocation of the pollutant out of the
system by dilution or dissemination can be assessed. (4) As a source of materials for
laboratory assays of decay the area should be one which has had a long exposure to

the pollutant, thus insuring the establishment of microbial systems with the capacity
for decomposition of the pollutant. (5) The area should be known to be contaminated
with the pollutant. (6) The area should be accessible to sampling and close to the re-
quired analytical capability.

Monterey Bay, and in particular the southern portion of Monterey Bay, has these char-
acteristics and was selected as the study site and source of materials for the development
of laboratory assays for the rate of decay of DDT, DDD, and DDE.

Survey of Residue Levels in Monterey Bay Sediments—In order to assess the variability
in concentration and distribution of the three compounds in the sediments of Monterey
Bay thirty-seven sample sites were selected for analysis in the southern portion of the
bay which receives water and sediments from the agricultural area of Monterey County
by way of the Salinas River. An additional eleven sample sites in the northern portion
of the bay were selected in order to assess any augmenting effect of additional river
input sources such as the San Lorenzo and Pajaro Rivers that drain areas of Santa Cruz
and San Benitio Counties lying adjacent to Monterey County and Monterey Bay.

Determination of the Amount of Change in Residue Levels with Time—In order to as-
sess the magnitude of change in the concentration of DDT and related compounds a
subset of the original survey sampling stations was resampled and analyzed after ap-
proximately three years. Nineteen of the original sample stations were selected as this
subset. The selection was made on a basis of accessibility and representations of stations
showing a broad range of residue concentrations as determined in the original survey.

Determination of the Variance of Sampling—One additional sample station, number 38,
which had never before been sampled was added to the resampled subset and sampled
three times on the same day. Three aliquots from each of these samples were analyzed
for the three compounds to provide an estimate of the variability of sampling.


CIRCULATION OF DDT DERIVATIVES

Figure 8. Composite chart of the translocation of DDT compounds based upon the rates
of change, K, at individual stations in the southern portion of Monterey Bay.

49


0010
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0013

0014
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0017
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0019
0020
0021

0022
0023

0024
0025
0026
0027

0028
0029
0030
0031
0032
0033
0034
0035
0036
0037
0038

0039

DO 13 I=1,2

K=0

SUMDA(I)=0

ITOTDA(1)=0

STORE INITIAL TIME

MO1=CDATE(I,1,1)

IDA1=CDATE(I,1,2)

TYR1=CDATE(I,1,3)

TYRVAL(1)=365

A=IYR1

IZ=A/4. .
IF (IZ*4.EQ.1TYR1.AND.MO1.GT.2) IYRVAL(1)=366
INT1=MONTH(MO1)+IDA1L ,

FIND TIME INTERVAL OF FIRST DATE TO END OF FIRST YEAR
INT2=IYRVAL(1)-INT1

IB=IA(I)

DO 4 J=1,1B
MO2=CDATE(1J,1)

IDA2=CDATE(LJ,2)

IYR2=CDATE(LJ,3)

COMPUTE YEAR VALUES-365 OR 366

IF (IYRL.EQ.1YR2) TO TO 3

K STORES NUMBER OF INTERVENING YEARS
K=IYR24YR1

DO 1 L=1,K

TYRVAL(L+1)=365

A-TYR1+L

IZ=A/4.

IF (1Z*4.EQ.IYR1+L) ILYRVAL(L+1)=366
1 CONTINUE

COMPUTE INTERVAL OF LAST YEAR
LAST1=MONTH(MO2)+IDA2

CHECK FOR LEAPYR OF LAST YEAR

IF (IYRVAL(K).EQ.366.AND.MO2.GT.2) LAST=LAST+1
LAST2=IYRVAL(K)-LASTI

COMPUTE TOTAL DAYS OF DATA SET

INT=FIRST YEAR

K=K+1

K= NUMBER OF YEARS

91


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0003
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0009
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0014

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0016

0017
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0031
0032
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0034

0035
0036

0037
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0039
0040

SUBROUTINE PRINT3
DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8)
REAL *8X(10,60,7)
REAL *8NAME(23)
REAL *4MEAN,M(17,8)
INTEGER CST(2,60),CDATE(2,60,3)
COMMON X,TABLE,IA,LK,KD,ID
COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L

DO 2 K=1,ID
WRITE (6,3)

WRITE (6,4)

WRITE (6,5) NAME(K),NAME(K)
WRITE (6,6)

WRITE (6,8)

DO 1J=1,IA
1 WRITE (6,7) CST(1,J),X(2,J,K),X(1,J,K),X(5,J,K),(X(X,J,K),1X=6,10
1)

WRITE (6,8)
WRITE (6,17) TOT(2,K), TOT(1,K), TOT(5,1),(TOT(L,K),L=6,10)
WRITE (6,16)
WRITE (6,14) NAME(K)
WRITE (6,17) M(2,K),M(1,K),M(5,1),(M(L,K),L=6, 10)
WRITE (6,9)
WRITE (6,14) NAME(K)
WRITE (6,17) STD(2,K),STD(1,K),STD(5,1),(STD(L,K),L=6,10)
WRITE (6,10)
WRITE (6,13) NAME(K)
WRITE (6,17) STE(2,K),STE(1,K),STE(5,1),(STE(L,K),L=6,10)
WRITE (6,11)
WRITE (6,13) NAME(K)
WRITE (6,17) CL95(2,K),CL95(1,K),CL95(5,1),(CL95(L,K),L=6, 10)
WRITE (6,12)
WRITE (6,15) NAME(K)
2 CONTINUE

RETURN

3 FORMAT (‘1’,1X,‘STATION’)

4 FORMAT (12X,‘C’,9X,‘C’,11X,‘N’,8X,‘+ K’,7X,‘- K’,6X,‘+K + -K’,
1 4X,‘+K - NET’,3X,'-K - NET’)

5 FORMAT (‘+’,15X,A8,2X,A8)

6 FORMAT (13X,‘2’,9X,‘1’,52X,‘R’,10X,‘R’/)

7 FORMAT (4X,12,1X,2F 10.2,2X,3F 10.4,3F 11.4)

8 FORMAT (/)
70


Table 10. FIFTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,

FOR DDT IN EACH SEDIMENT COMPARTMENT.

——- =
Station] Cy DDT} Cy DDT} N +K K tk 4K [4K Net | -K Net
1 1.06 | 836 | 28795 | 0.0 0.5119 | 05119 | 00 -2.0906
2 9.50 | 1.63 | 26493 | 09452 | 0.0 0.9452 | 0.0 -0.6336
3 110 | 5.71 | 33836 | 00 0.3854 | -0.3854 | 0.0 -1,9641
4 363 | 4.28 | 26493 | 00 0.0603 | -0.0603 | 00 1.6390
10 092 | 642 | 30959 | 00 0.4661 | -0.4661 | 0.0 -2.0449
" 218 | 367 | 33644 | 00 0.1434 | -0.1434 | 00 1.7222
14 | 3060 | 5.20 | 28301 | 08706 | 00 0.8708 | 0.0 -0.7082
16 096 | o69 | 3.3644 | 0.1031 | 00 0.1031 | 0.0 1.4756
17 5.41 | 1.02 | 2.7342 | 08408 | 0.0 0.8408 | 0.0 -0.7380
19 | 7270 | 1.12 | 29644 | 3.0866 | 00 3.0866 | 15079 | 0.0
20 | 6310 | a0 | 3.3671 | 16.6503 | 0.0 16.6503 | 15.0715 | 0.0
22 093 | 00 | 34685 | 38113 | 0.0 38113 | 2.2325 | 00 .
23 | 29.90 | 1320 | 28301 | 03350 | 0.0 0.3350 | 0.0 1.2438
25 114 | 1.22 | 3.4027 | 00 0.0197 | -0.0197 | 0.0 1.5985
26 o68 | 00 | 34356 | 3.4588 | 00 3.4588 | 1.8800 | 0.0
29 0.70 | 1.32 | 3.4027 | 00 0.1701 | -0.1701 | 00 “1.7488
34 118 | 244 | 35014 | 00 0.1874 | -0.1874 | a0 1.7661
36 | 8310 | 265 | 3.3342 | 1.8105 | 00 1.8105 | 0.2317 | 0.0
37 054 | 049 | 34356 | 0.0287 | 0.0 0.0287 | 0.0 1.5501
Totals 309.3296 59.4199 60.0930 31.9407 -1.9442 29.9964 20.9236 -20.9235
Mean 16.2805 3.1274 3.1628 = 1.6811. -0.1023, 1.5788 = 1.1012—-1.1012
S.D. 26.9909 +3.4385 +0.3100 + 0.9016 + 0.0984 + 1.0000 + 0.8738 + 0.1262
SE. + 6.1921 0.7889 +0.0711 + 0.2068 + 0.0226 + 0.2294 + 0.2005 + 0.0289
95% C.L. + 13.0097 + 1.6574 +0.1494 + 0.4346 + 0.0474 + 0.4820 + 0.4212 + 0.0608

31


Table 18. STANDARD DEVIATIONS AND STANDARD ERRORS OF DISTRIBUTIONS OF K WITH MINIMAL
VARIANCE FOR GIVEN VALUES OF I, T; AND To, (O+D) AND n,

n=5 n= 10 n=20
\ T, | O+D |} Net SD. SE. 8D. SE. SD. S.E.

2.00] 1.20] -0.15 | 185 | t 2.7524 t 25965 t 2.5338

+ 1.2309 + 082i t 0.5666
1.75} 1.20 | -0.15 | 1.60 | * 3.4084 t 2.7758 + 2.7107

t 15243 t 089778 t 0.6061
150] 1.20 | -0.15 | 1.35 | * 3.3586 + 3.1663 + 3.0831

t 1.5020 t 1.0013 t 06804
150| 1.20 | -030 | 1.20 | t 3.3719 t 3.1785 t 28433

t 1.5080 t 1.0051 t 0.6358
1.50] 1.20 | -060 | 090 | * 3.4249 * 3.2267 * 2.7077

t 15317 t 1.0204 t 0.6055
1.50} 090 | -0.15 | 1.35 | t 2.0724 t 1.9568 t 1.9124

t 0.9268 t 0.6185 t 0.4276
150] 0.60 | -0.15 | 1.35 | * 1.4335 + 1.3528 t 1.3063

* 0641 + 0.4278 | t 0.2921

:

43


Table 21. TOTAL AMOUNTS OF DDT, DOD, AND ODE IN THE SOUTH MONTEREY BAY STUDY
AREA BASED ON THE MEAN CONCENTRATIONS AT THE TWO SAMPLE TIMES, AND
EXPECTED AMOUNTS AFFECTED BY THE MEAN OF THE ESTIMATES OF SYSTEM RATES

Kilograms Pounds Pounds/Acre
Amount at Sample Time 1 ODT 128 284 0.004
DDD 97 213 0.003
DDE 214 472 0.007
TOTAL 439 969 0.014
Amount at Sample Time 2, DDT 579 1276 0.018
3 years later DDD 91 200 0.003
DDE 232 $11 0.007
TOTAL 932 1987 0.028
Expected input for next DDT 753 1659 0.024
year interval DDD 23 50 0.001
DDE 65 143 0.002
TOTAL 841 1852 0.027
Expected loss for next DDT 58 128 0.0018
year interval DDD 12 26 0.0004
ODE 30 66 0.0010
TOTAL 100 220 0.0032
Expected amounts due to Net DDT 1274 2807 0.041
change for next year interval DDD 102 224 0.003
DDE 267 588 0.008,
TOTAL 1643 3619 0.052
Expected amount translocated DDT 463 1020 0.015
within the system in next ODD 18 40 0.001
year interval DDE 51 112 0.002
TOTAL 532 1172 0.018
Expected amount Output to DDT 35 7 0.0011
other systems in next year DDD 7 22 0.0003
interval DDE 23 51 0.0007
TOTAL 65 150 0.0021
Expected amount Decayed DOT 21 46 0.0007
in next time interval 00D 2 5 0.0001
DDE 6 14 0.0002
TOTAL 29 65 0.0010

48


: Table 19. COMPARISON OF UNCORRECTED AND CORRECTED STANDARD DEVIATIONS OF
SYSTEM ESTIMATES

=—=
16 Sample Set 19 Sample Set 49 Sample Set 57 Sample Set
Uncorrected} Corrected | Uncorrected {Corrected | Uncorrected|Corrected | Uncorrected} Corrected
DOT
Net + 1.0000 |+ 0.2751 | + 1.0000 |+ 0.5986 + 1.0000 |+ 0.3366 | + 1.0000} + 0.5379
I + 0.7556 |+ 0.2806 | + 0.9016 |+ 0.5397 + 0.6374 |+ 0.2145 | + 0.9204} + 0.4951
O+D & 0.2444 |+ 0.0907 | + 0.0984 |+ 0.0589 + 0.3626 |+ 0.1221 | + 0.0796 | + 0.0428
To + 0.2591 |+ 0.0962 | + 0.1262 /+ 0.0755 + 0.3966 |+ 0.1335 | + 0.1513} + 0.0814
TT + 0.7409 |+ 0.2751 | + 0.8738 |+ 0.5231 + 0.6034 |+ 0.2031 | + 0.8487 | + 0.4565
oO + 0.1723 |+ 0.0640 | + 0.0644 |+ 0.0386 + 0.1720 |+ 0.0579 | + 0.0488 | + 0.0263
19) + 0.0721 |+ 0.0268 | + 0.0339 |+ 0.0203 + 0.1906 |+ 0.0642 | + 0.0307 | + 0.0165
Te + 56.1105 |+20.8365 | + 27.2386 |+16.3047 +82.7111 |+27.8380 | + 46.2947 | 424.9713
TR + 16.5496 |+ 6.1457 | + 9.3952 |+ 5.6239 443.4823 /414.6348 | + 17.8875 | + 9.6215
DDD
Net + 1,0000 | + 0.3604 | + 1.0000 |+ 0.3860 + 1.0000 |+ 0.3419 | + 1.0000 | + 0.3521
' + 0.7279 |+ 0.2623 | + 0.7233 |+ 0.2792 + 0.6357 |+ 0.2174 | + 0.6329 | + 0.2228
O+D + 0.2721 |+ 0.0981 | + 0.2767 |+ 0.1068 + 0.3643 {+ 0.1246 | + 0.3671 | + 0.1293
To + 0.2721 |+ 0.0981 | + 0.2767 |+ 0.1068 + 0.3653 |+ 0.1249 | + 0.3689 | + 0.1299
TT + 0.7279 |+ 0.2623 | + 0.7233 |+ 0.2792 + 0.6347 |+ 0.2170 | + 0.6311 | + 0.2222
fe} + 0.2350 |+ 0.0847 | + 0.2441 |+ 0.0942 + 0.2823 |+ 0.0965 | + 0.2662 | + 0.0937
D + 0.0371 |+ 0.0134 | + 0.0326 |+ 0.0126 + 0.0820 |+ 0.0280 | + 0.1010 | + 0.0356
Th +107.4660 |+38.7279 | +123.4241 [447.6463 +#80.3119 [427.4603 | + 88.7883 | +31.2619
Tr + 14,6462 |+ 5.2781 | + 14.5330 |+ 5.6103 £18.0682 |+ 6.1779 | + 24.4216 | + 8.5987
ODE
Net + 1.0030 }+ 0.3602 | + 1.0024 |+ 0.4716 + 1.0010 |+ 0.4379 | + 1.0009 | + 0.4545
i} + 0.7843 |+ 0.2817 | + 0.7781 }+ 0.3661 + 0.6628 |+ 0.2900 | + 0.6787 | + 0.3082
O+D + 0.2186 |+ 0.0785 | + 0.2243 |+ 0.1055 + 0.3382 |4 0.1479 | + 0.3222 | + 0.1463
To *# 0.2211 {+ 0.0794 | + 0.2262 [+ 0.1064 + 0.3466 |+ 0.1516 | + 0.3311 | + 0.1504
an + 0.7818 |+ 0.2808 | + 0.7761 |+ 0.3651 + 0.6544 |+ 0.2863 | + 0.6697 | + 0.3041
fo + 0.1899 |+ 0.0682 | + 0.1929 + 0.0907 + 0.2348 |+ 0.1027 | + 0.2204 | + 0.1001
ie) + 0.0287 |+ 0.0103 | + 0.0314 |+ 0.0148 + 0.1033 [+ 0.0452 | + 0.1018 | + 0.0462
Th + 66.4924 |+23.8815 | + 66.8543 [+31.4484 +99.5728 |+43.5593 | +103.4957 | +46.9942
Tr + 8.7347 |+ 3.1372 | + 9.3629 |+ 4.4049 430.4277 |+13.3109 | + 32.6922 | +14.8445



0001
0002
0003
0004
0005
0006

0007
0008

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0010

0011
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0013

0014
0015
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0017
0018

0001
0002
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0005
0006
0007
0008
0009
0010

SUBROUTINE STDEV (SUMX,XBAR,STD,STE,CL$)
REAL *8X(10,60,7)

DIMENSION TABLE(30)

COMMON X,TABLE,IA,I,K,KD,ID

DEV=0.

SUMX=0.

DO 1 J=1,JA
1 SUMX=SUMX+X(I,J,K)

AIsIA
XBAR=SUMX/AI

DO 2 J=1,1A
DEV=(XBAR-X(I,J,K))**2+DEV
2 CONTINUE

STD=SQRT(DEV/(AI-1.))
STE=STD/SQRT(AI)
CALL TDIST (T)
CL$=T*STE

END

SUBROUTINE STDEV2 (STD,STE,CL$)
REAL *8X(10,60,7)

DIMENSION TABLE(30)

COMMON X,TABLE,IA,I,K,KD,ID
AIsIA

STE=STD/SQRT(AI)

CALL TDIST (T)

CL$=T*STE

RETURN

END

73


0124
0125
0126
0127
0128
0129
0130

0131

0132
0133

0134
0135

0136
0137

0138

0139
0140
0141
0142

0144
0145
0146
0147
0148
0149

0150
0151
0152
0153
0154

0155

anna

aan

DO 28 J=1,J2T
V=X(8,J,K)-SUM1(K)/AI3
IF (V.GT.0) GO TO 27
X(10,J,K)=V
GO TO 28

27 X(9,J,K)=V

28 CONTINUE

COMPUTE SUM & MEAN FOR K VALUES
DO 30 K=1,ID

DO 30 I=6,10
Vv=0.0

DO 29 J=1,J2T
29 V=V+X(LJ,K)

TOT(I,K)=V
30 M(I,K)=V/AI3

DO 31 I=6,10

DO 31 K=1,7

STD(I,K)=0.0

STE(I,K)=0.0
31 CL95(I,K)=0.0

CALCULATE STANDARD DEVIATION, STANDARD ERROR, AND 95% CONFIDENCE
LIMITS OF K VALUES.
DO 32 K=1,ID
SUM1(K)=0.0
SUM2(K)=0.0
SUM3(K)=0.0
32 SUM4(K)=0.0
IB=IA(2)

DO 33 J=1,1B

V2(J,K)=DLOG(X(2,J,K))-DLOG(X(1,J;K))

SUM2(K)=V2(J,K)+SUM2(K)

SUM3(K)=(DLOG(X(1,J,K))-ALOG(M(1,K)))**2+SUM3(K)
33 SUM4(K)=(DLOG(X(2,J,K))-ALOG(M(2,K)))**2+SUM4(K)

DO 34 K=1,ID

83


Table 16. COMPARISON OF ESTIMATES OBTAINED FROM THE 16 AND 19 STATION DATA SETS AND
USING ACTUAL PAIRED SAMPLE ANALYSES STANDARD DEVIATIONS [S.D.] AND COEF-
FICIENTS OF VARIATION [C.V.] ARE INCLUDED.

16 STATION DATA SET

19 STATION DATA SET

Estimate S.D. cv. Estimate S.D. Cv.
(*) (*)

ODT
C, (ppb) 3.7137 + 3.4446 92.8 3.1274 + 3.4385 109.9
Co (ppb) 15.2887 + 26.3645 172.4 16.2805 t 26.9909 165.8
Net . + 0.3798 + 1.0000 263.3 + 1.5788 + 1.0000 63.3
( + 0.5013 + 0.7556 150.7 + 1.6811 + 0.9016 53.6
O+D 0.1215 + 0.2444 138.2 + 0.1023 + 0.0984 96.2
To 0.3534 + 0.2591 73.3 - 1.1012 + 0.1262 11.5
Ty + 0.3534 + 0.7409 209.6 + 1.1012 t 0.8738 79.3
oO 0.0857 + 0.1723 201.1 - 0.0670 + 0.0644 96.1
1?) 0.0358 + 0.0721 201.4 0.0353 + 0.0339 96.0
TL (years) 27.9014 t+ 56.1105 201.1 28.3322 + 24.2386 96.1
TR (years) 8.2294 + 16.5496 201.1 9.7724 £ 9.3952 96.1

DDD
Cy (ppb) 2.9137 + 3.0908 106.1 2.8589 t 2.9296 102.5
C2 (ppb) 2.6625 + 3.0921 116.1 2.4468 + 2.8805 117.7
Net + 0.1054 +  1,0000 948.8 + 0.0820 + 1.0000 1219.5
t + 0.2417 + 0.7279 301.2 + 0.2200 t 0.7233 328.8
O+D - 0.1363 + (0.2721 199.6 > 0.1380 t 0.2767 200.5
To - 0.2088 + 0.2721 130.3 - 0.1941 t 0.2767 142.6
Ty + 0.2088 + 0.7279 348.6 + 0.1941 + 0.7233 5009.4
fe) - 0.1177 + 0.2350 199.7 + 0.1217 + 0.2441 200.6
D - 0.0186 + 0.0371 199.5 - 0.0162 + 0.0326 201.2
TL (years) 53.8306 + 107.4660 199.6 61.5459 123.4241 200.5
TR (years) 7.3364 - £ 14.6462 199.6 7.2469 + 14.5330 200.5

DDE
Cy (ppb) 6.0350 5.4299 90.0 6.6310 6.0673 91.5
C2 (ppb) 6.3887 + 6.2166 97.3 6.3384 + 5.7417 90.6
Net + 0.1368 + 1.0030 733.2 + 0.1177 + 1.0024 851.7
' + 0.2950 t 0.7843 265.9 + 0.2725 + 0.7781 285.5
O+D 0.1582 + 0.2186 138.2 - 0.1548 + 0.2243 144.9
To 0.2563 + 0.2211 86.3 - 0.2343 + 0.2262 96.5
an + 0.2563 t 0.7818 305.0 + 0.2343 t 0.7761 332.1
te) 0.1374 + 0.1899 138.2 - 0.1331 + 0.1929 144.9
1?) - 0.0208 + 0.0287 138.0 0.0217 t 0.0314 144.7
TL (years) 48.1189 + 66.4924 138.2 « 46.1286 + 66.8543 144.9
TR (vears) 6.3211 + 8.7347 138.2 6.4611 + 9.3629 144.9

38



EPA-660/3-75-013
MAY 1975

AN ANALYSIS OF THE DYNAMICS OF DDT IN MARINE SEDIMENTS

By

John H. Phillips
Hopkins Marine Station
Pacific Grove, California 93950

Eugene E. Haderlie
Naval Postgraduate School
Monterey, California 93940

Welton L. Lee
California Academy of Sciences
San Francisco, California 94118

Grant No. R800365
Program Element IBA025
21AIS, Task No. 08

Project Officer
Dr. Milton H. Feldman

Coastal Pollution Branch
Pacific Northwest Environmental Research Laboratoi
National Environmental Research Center
Corvallis, Oregon 97330

NATIONAL ENVIRONMENTAL RESEARCH CENTER
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CORVALLIS, OREGON 97330

For Sale by the National Technical Information Service
U.S. Department of Commerce, Springfield, VA 22151


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a aANAA

a

aanaan

aaAnNAa

aaana

DO 2 I=1,2

DO 2 J=1,IA
2 READ (5,49) CST(I,J),(ALOC(LJ,L),L=1,6),(CDATE(1,J,L),L=1,3),(X(
1,J,K),K=1,1D)

COMPUTE TOTAL OF EACH STATION.
DO 3 I=1,2
DO 3 J=1,IA

DO 3 L=1,ID
3 X(LJ,IP1)=X(LJ,L)+X(1,J,IP1)

WRITE HEADING OF FIRST TWO PAGES.

DO 5 [=1,2

L=I

WRITE (6,51) 1

WRITE (6,53) (NAME(N),N=1,IP 1)
WRITE (6,52) (NAME(N),N=IP2,12TP2)
WRITE (6,54)

DO 4 K=1,IP1
CALL STDEV (TOTAL,MEAN,SD,SE,CL)
TOT(I,K)=TOTAL
M(I,K)=MEAN
STD(I,K)=SD
STE(I,K)=SE
4 CL95(I,K)=CL

L1=NUMBER OF SETS COMPUTED.

WRITE FIRST TWO PAGES.
L1sIP1
CALL PRINT
WRITE (6,53) (NAME(N),N=1,IP1)
WRITE (6,52) (NAME(N),N=IP2,12TP2)
WRITE (6,54)
CALL PRINT2
5 CONTINUE

COMPUTE PERCENTS.
61


. Table 20. MEAN OF THE ESTIMATES FOR THE SOUTH MONTEREY BAY SYSTEM AND
ASSOCIATED DESCRIPTIVE STATISTICS.

——$_—
Mean S.D. SE. 95% C.L. cv.

(%)

C, DOT (ppb) 3.4752 * 0.4281 * o2141 t 0.6812 12.3
DDD (ppb) 2.6144 t 03196 t 0.1598 0.5086 12.2

DDE (ppb) 5.7870 + 0.6837 t 03419 + 1.0878 118

Cy DDT (ppb) 15.6411 * 0.4375 * 0.2188 * 06961 28
DDD (ppb) 2.4491 t 0.1504 t 0.0752 t 0.2393 6.1

DDE (ppb) 6.2605 t 0.1207 t 0.0604 * 0.1921 1.9

Net DDT + 1.2015 t 08764 t 0.4382 t 1.3044 72.9
DDD + 0.1186 t 0.0327 t o.0o16a t 0.0521 27.6

DDE + 0.1522 t 0.0298 t oo149 t 0.0475 19.6

\ DDT. + 1.2969 t 0.8587 * 0.4294 + 1.3663 66.2
DDD + 0.2533 t 0.0278 t 0.0139 t 0.0442 11.0

DDE + 0.2816 t 0.0096 * 0.0048 * 0.0152 3.4

0+D DDT 0.0955 t 0.0096 t 0.0114 t 0.0364 24.0
DDD 0.1347 t 0.0229 t 0.0042 * 0.0134 6.2

DDE - 0.1294 t 0.0084 t 0.0157 t 0.0499 27.3

To &T, DOT t osoog + 0.5604 + 0.2752 t 08756 68.7
DDD t 0.2041 * 0.0071 t 0.0036 t 0.0113 3.5

DDE t 0.2190 t 0.0318 t 0.0159 * 0.0505 145

° DDT 0.0592 t 0.0212 t 0.0106 t 0.0338 35.8
DoD 0.1096 t 0.0146 t 0.0073 * 0.0233 13,3

DDE 0.1029 t 0.0375 t 0.0187 t 0.0596 36.4

D DDT 0.0362 t 0.0091 t 0.0045 t 0.0145 25.1
DDD 0.0251 * 0.0090 * 0.0143 t 0.0143 35.9

DDE 0.0265 + 0.0061 * 0.0031 t 0.0097 23.0

TL DDT (years) 28.9680 + 7.4078 + 3.7039 111.7858 25.6
DDD (years) 44.0829 16.0370 t 8.0185 25.5148 36.4

DDE (years) 39.2945 t 9.0835 t 45418 114.4519 23.1

Ta DOT (years) 10.9868 * 2.8952 + 1.4476 + 46062 26.4
DDD (years) 7.4454 t 0.4893 t 0.2447 t 0.7785 6.6

DDE (years) 8.0853 + 1.9717 t 0.9859 + 3.1371 24.4

47



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aaan an

aan

aan

aaa

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12
13

DO 9 J=1,1A3
W=W+(X(8,J,K)—M(8,K))**2

W=W/(AI3—1.0)
C=( (W—V)/W)**2

CALCULATE CORRECTED STD,6,7,AND 8
STD(15,K) IS CORRECTED STD(6,K)

STD(15,K)=SQRT(C*STD(6,K)**2)
CALL STDEV2 (STD(15,K),STE(15,K),CL95(15,K))

STD(16,K)IS CORRECTED STE(7,K)

STD(16,K)=SQRT(C*STD(7,K)**2)
CALL STDEV2 (STD(16,K),STE(16,K),CL95(16,K))

STD(17,K) IS CORRECTED STD(8,K)

STD(17,K)=SQRT(C*STD(8,K)**2)
CALL STDEV2 (STD(17,K),STE(17,K),CL95(17,K))

CALCULATE CORRECTED STD(9,K) AND STD(10,K)

v=0.0

DO 11 J=1,1A3
IF (X(9,J,K)) 11,11,10

V=V+X(9,J,K)**2
CONTINUE

V=V/(A13—1.0)
W=0.0

DO 13 J=1,1A3

IF (X(10,J,K)) 12,13,13

W=W+(X(10,J,K))**2
CONTINUE

96


=
\ 1 KM

Vas FATHOMS

g
%DDE 1970 & 1971

200 Ea

Figure 4. DDE as a percent of the total concentration of DDT, DDD, and DDE plotted for data
obtained in 1970 and 1971. Circled numbers indicate actual percents in excess of 50%

21


Table 4. (continued) LEVELS OF DDT, DDD, AND DDE AS PERCENT OF TOTAL
RESIDUES IN MARINE SEDIMENT SAMPLES FROM MONTEREY

BAY.
LOCATION DDT DDD ODE
Station Latitude Longitude Date (%) (%) (%)

39 36 54.80 122 01.00 11-24-71 13.33 . 42.22 44.44
40 36 57.10 121 56.20 11-1071; 10.58 53.23 36.19
41 36 56.70 121 59.20 11-24-71 | 11.40 33.70 54.90
42 36 55.50 121 52.60 11-10-71; = 27.51 51.13 21.36
43 36 55.10 121 56.70 11-10-71 12.52 47.45 40.03
44 36 53.60 121 57.50 11-24-71 18.40 41.37 40.23
45 36 53.00 121 55.00 11-10-71! 23.73 39.41 36.86
46 36 52.30 121 59.80 11-24-71' 12.52 37.57 49.90
47 36 51.00 121 49.80 11-10-71 | 32.58 35.67 31.74
48 36 50.80 121 53.60 11-24-71) 11.61 40.22 48.17
49 36 50.20 121 50.20 11-10-71 21.97 41.69 36.34

1 36 47.25 121 48.90 T- 973 49.30 24.65 26.05

2 36 46.85 121 53.50 7- 9-73 24.74 29.69 45.57

3 36 46.35 121 49.00 7- 9-73 48.67 23.45 27.88

4 36 46.05 121 51.00 7- 9-73 22.73 34.00 43.27
10 36 45.10 121 50.00 7- 2-73 50.27 21.31 28.42
11 36 45.00 121 49.00 7- 2-73 58.45 19.30 22.25
14 36 44.20 121 52.25 6-21-73 63.92 12.68 23.40
16 36 44.00 121 49.50 7- 2-73 76.80 4.80 18.40
7 36 43.75 121 54.45 8 9-73 19.85 16.66 63.49
19 36 43.35 121 56.25 8- 9-73 82.72 3.63 13.65
20 36 43.18 121 57.00 6-21-73 93.66 1.17 5.17
22 36 42.90 121 58.00 8- 9-73 11.79” 11.41 76.81
23 36 42.55 121 53.30 6-21-73 64.41 9.31 26.28
25 36 41.70 121 55.00 7-16-73 7.93 19.07 73.00
26 36 41.55 121 55.50 7-16-73 5.89 19.05 75.06
29 36 40.90 121 56.40 7-16-73 9.36 14.84 75.80
34 36 39.10 121 53.08 8 973 29.21 10.40 60.40
36 36 37.95 121 52.50 6-21-73 95.09 1.09 3.82
37 36 37.77 121 51.83 7-16-73 47.37 17.54 35.09
38 36 38.47 121 51.68 9-21-73 16.67 10.22 73.12

17


OTHER SYSTEMS
SYSTEM
COMPARTMENT
c
+T, -Ty
-O—+-> +1 -O—+-> +1
-Th ty
c
COMPARTMENT
=C—DC
SYSTEMS
Cy=C,(1+I-O0-D)% Ty=Ty
COMPARTMENTS

Ca=C\(IFI4+T,-T>-0-DN Th#
C,=CONCENTRATION OF RESIDUE AT TIME |

Cy=CONCENTRATION OF RESIDUE AT TIME 2

I=RATE OF tNPUT OF RESIDUE

O=RATE OF OUTPUT OF RESIDUE

D=RATE OF DECAY

To= RATE OF TRANSLOCATION OUT OF A COMPARTMENT

T,=RATE OF TRANSLOCATION INTO A COMPARTMENT

Figure 7. Model of the system of sediment compartments and this system’s relation to other
systems.

29


Table 23 CONTINUED. RESULTS OF LABORATORY ASSAYS OF THE ANNUAL RATES OF
DECAY TO CO2, Dco2, AND THE EFFECT OF ENVIRONMENTAL
VARIABLES ON THE PROCESS.

Conditions Concentration 2co4 Mean S.D.

Anaerobic, 10°C,
5 x 10°1% Na NO3

5x 101% Na Acetate} DDT 10 ppm 0011

1ppm | .0008 .00090 + 00017
100 ppb .0008
5 x 102% Na Acetate} DDT 10 ppm .0008
1ppm | .0008 .00087 + 00012
100 ppb .0010

5x 103% Na Acetate}. DDT 10ppm | .0022
1ppm | .0022 00223 + 00006
100 ppb 0023

5x 10°4% Na Acetate| DDT 10 ppm 0022

1ppm | .0025 .00237 + 00015

100 ppb 0024

5x 105% Na Acetate} DDT 10ppm | .0022
: 1ppm | .0023 .00227 + 00006

100 ppb .0023

5 x 10°6% Na Acetate| DDT 10 ppm .0019
1ppm | .0022 .00213 + 00021

100 ppb .0023

5x 107%Na Acetate) DDT 10ppm | .0024
1ppm | .0024 .00240 + 00000

100 ppb 0024

Aerobic, 10°C
5x 101% Na Acetate} DDT 10ppm | .0031

1ppm | .0033 .00317 + 00012

100 ppb 0031

5 x 10°2% Na Acetate] DDT 10 ppm .0034
Tppm | .0031 .00307 + 00035

100 ppb .0027

5x 10°3% Na Acetate} DDT 10ppm | .0025
1ppm | .0023 00237 + 00012

100 ppb .0023

53


0041
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9 FORMAT (‘+’,94X,‘MEANS’)
10 FORMAT (‘#’,94X,‘S.D.’)
11 FORMAT (‘+’,94X,‘S.E.’)
12 FORMAT (‘+’,94X,'95% CONFIDENCE LIMITS’)
13 FORMAT (‘+’, 99X,A8)
14 FORMAT (‘+’,102X,A8)
15 FORMAT (‘+’,116X,A8)
16 FORMAT (‘+?,94X,‘TOTALS’)
17 FORMAT(/9X,5F10.4,3F 11.4)
END

SUBROUTINE LEAPYR (J)

DIMENSION TABLE(30), MONTH(12), ALOC(2,60,6), TOT(10,8), STD(23,8)
1, STE(23,8),CL95(23,8)

REAL *4MEAN,M(17,8)

REAL *8X(10,60,7)

REAL *8NAME(23)

INTEGER TOT, YR1,YR2,DA1,DA2,DAYS

INTEGER CST(2,60),CDATE(2,60,3)

COMMON /BLK1/ NAME, TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L
COMMON X,TABLE,IA,L,K,KD,ID

DAYS=0

NT=0

MO1=CDATE(1,J,1)

DA1=CDATE(1,J,2)

YR1=CDATE(1,J,3)

DA2=CDATE(2,L,2)

YR2=CDATE(2,L,3)

MO2=CDATE(2,L,1)

AMO=MO1

DO 4 I=YR1,YR2
A=I
LEAP=0
IZ=A/4.
Z51Z
Z=Z*4
IF (1LEQ.YR1) GOTO 1
GO TO2
1 DAYS=365-(MONTH(MO1)+DA1)
IF (Z.EQ.A.AND.AMO.LT.3.) LEAP=1
GO TO 3
2 IF (Z.EQ.A) LEAP=1
3 NT=DAYS+LEAP+NT
4 DAYS=365

71


Figure 6. Total concentration in parts per billion of DDT, DDD, and DDE from data obtained in
1973. The blank portions of the area were not sampled. Circled numbers indicate actual
concentrations in excess of 50 ppb.

23


0047 11 FORMAT (‘+’,94X,‘95% CONFIDENCE LIMITS’)

0048 12 FORMAT (‘+’, 99X,A8)
0049 13 FORMAT (‘+’,102X,A8)
0050 14 FORMAT (‘+’,116X,A8)
0051 15 FORMAT (‘+’,94X,‘TOTALS’)
0052 16 FORMAT (/9X,5F10.4,3F 11.4)
0053 17 FORMAT (4X,12,1X,F10.2,12X,3F 10.4,3F11.4)
0054 18 FORMAT(4X,12,1X,10X,F10.2,2X,3F 10.4,3F11.4)
0055 END
Cc
Cc
0001 SUBROUTINE TDIST (KA,T)
0002 REAL *8X(10,60,7)
0003 DIMENSION TABLE(30), IA(2), AI(2)
0004 COMMON X, TABLE JA,IB,I,K,KD,ID
0005 11=KA-1
0006 AK=11
0007 IF (I1) 1,1,2
0008 1 WRITE (6,11) 1
0009 GOTO 10
0010 2 IF (11.LT.31) GO TO 9
0011 IF (I1.LT.41) GO TO 3
0012 GO TO 4
0013 3 TINT=((2.042-2.021)/10.)*(AK-30.)
0014 T=TINT+2.042
0015 GO TO 10
0016 4 IF (I1.Lt.61) GO TO 5
0017 GO TO 6
0018 5 TINT=((2.021-2.000)/20.)*(AK-40.)
0019 T=TINT+2.021
0020 GO TO 10
0021 6 IF (11.LT.121) GO TO7
0022 GOTO 8
0023 7 TINT=((2.000-1.980)/40.)*(AK-60.)
0024 T=TINT+2.000
0025 GO TO 10
0026 8 T=1.960
0027 GO TO 10
0028 9 T=TABLE(I1)
0029 10 RETURN
c
0030 11 FORMAT (‘1’,T IN T TABLE =",13)
0031 END
c
c

89


THE STUDY AREA

This study was carried out in Monterey Bay located in the central coastal region of
California. Figure 1 shows the study area and the location of the forty-nine Stations
from which sediment samples were obtained. The figure also shows several geographical
features pertinent to this investigation. The bottom of Monterey Bay is divided by a
major submarine canyon over 3800 meters in depth at its deepest point. The sampling
effort was concentrated in the southern portion of the bay with no sampling beyond
the 200 fathom, 365 meter, line. Residue levels of DDT, DDD, and DDE were first
measured in samples from this southern portion of the bay during 1970 and nineteen
of these stations were resampled in 1973. A small number of stations were sampled in
the northern part of the bay during 1971.

Monterey Bay is the recipient of drainage from a major agricultural area, the Salinas
Valley, where DDT was used in large amounts for a period of twenty years. Usage of
this pesticide and DDD has decreased sharply since 1969. A tabulation of use was
started in 1970 when 33,931 pounds was applied to 19,387 acres in Monterey County.
This input level was further reduced in 1971 to 4,697 pounds, and in 1972 to

10 pounds on 20 acres (Calif. Dept. of Agriculture 1970, 1971, 1972). Final tabulations
for 1973 will probably show levels of input similar to those of 1972. Although the use
of DDT in the area adjacent to Monterey Bay has declined sharply since 1970, the level
of DDT in marine sediments appears to be increasing as more of this pesticide finds its
way to the sea via the drainage system of the neighboring agricultural area. The decrease
in usage on adjacent land and apparent increase in concentration in the marine sediments
of the area suggests that continued study of the Monterey area is of particular interest
in determining the time lag between terrestrial input and marine accumulation of persis-
tent chemical pollutants.

Although in the past, when DDT was being regularly applied on the adjacent lands, the
atmosphere was an important source of input to the bay; at the present time the major
source of input appears to be the Salinas River which drains the inland agricultural areas.
This river flows directly into the bay only intermittently. Most of the time the mouth

of the river is blocked by a bar of sand that is removed only at times of heavy rainfall

to prevent flooding. During this investigation this event occurred Jan. 13, 1970, Nov. 30,
1970, Dec. 29, 1971, Nov. 16, 1972, Nov. 17, 1972, and Nov. 20, 1973. Input directly
by the river has, therefore, not been continuous.

Analyses of the sediment samples from the river bed along its course in 1972 (State of
California, 1974) showed considerable variation in the relative abundance and concen-
tration of the three compounds. Table 1 gives the results of these analyses and the ap-
proximate location of the samples relative to the mouth of the river.

During the periods when the mouth of the river is blocked, there is a sluggish flow north
to Elkhorn Slough which served as the mouth of the river until 1908. This flow is joined
by drainage from Trembladero Slough which receives water and sediments from the Re-
clamation Canal that flows through the City of Salinas to the east and beyond the right-
hand margin of the figures. The Reclamation Canal receives effluents from food proces-
sing plants and other industries, and analyses of its sediment in 1972 (State of Calif.,
1974) revealed the levels also listed in Table 1.


0033
0034
0035
0036
0037
0038
0039

0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
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0017
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0021
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0023
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0027
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0029

0030
0031

IF (LEAP.EQ.1) GO TO 5
GO TO6
5 IF (MO2.LT.3) NT=NT-1
6 YR=NT-365+MONTH(MO2)+DA2
YR=YR/365.
RETURN
END

SUBROUTINE TDIST (T)
REAL *8X(10,60,7)
DIMENSION TABLE(30)
COMMON X,TABLE,IA,I,K,KD,ID
1151A-1
Al=I1
IF (11) 1,1,2

1 WRITE (6,11) 1
GO TO 10

2 IF (11.LT.31) GO TO 9
IF (11.LT.41) GO TO 3
GO TO4

3 TINT=((2.042-2.021)/10.)*(AI-30.)
T=TINT+2.042
GO TO 10

4 IF (11.LT.61) GO TO 5
GO TO6

5 TINT=((2.021-2.000)/20.)*(AI-40.)
T=TINT+2.021
GO TO 10

6 IF (11.LT.121) GO TO7
GO TO 8

7 TINT=((2.000-1.980)/40.)*(AI-60.)
T=TINT+2.000
GO TO 10

8 T=1.960
GO TO 10

9 T=TABLE(11)

10 RETURN

11 FORMAT (‘1’,‘ IN T TABLE =’,13)
END

72


APPENDIX B

PROGRAM FOR ESTIMATING SYSTEM RATES BASED ON SAMPLE VALUES PAIRED TO MEANWALUES

This program for calculation of estimates of input, output, translocation, and decay was written in
Fortran IV level G, and was run on an IBM 360/67. In our experience 112k was used and the pro-
gram required approximately 40 seconds per run. A maximum of 60 stations, 7 chemical compounds,
and 2 sample times is permitted with the program as written.

The time interval is calculated in the subroutine, NCOMP, which calls the subroutine, LEAPYR. K
values are calculated using double precision, and confidence intervals are estimated through use of
a table of “‘t values.”

There are eight cards which precede the data deck. Their formats and content are as follows:

First four cards, as in preceding program.

Fifth card, Format (315), contains the number of stations at time one, followed by the
number of stations at time two, followed by the number of chemical com-
pounds in the data set.

Sixth through eighth cards, Format (10A8), as in preceding program.

The data is organized as in the preceding program but is sorted chronologically.

An optional subroutine FACTOR may be called by placing a card before the END card with CALL
FACTOR.

Cc PROGRAM FOR ESTIMATING SYSTEM RATES BASED ON
Cc SAMPLE VALUES PAIRED TO MEAN VALUES.
Cc
Cc
0001 DIMENSION TABLE(30), MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8),
1, STE(23,8),CL95(23,8),VAR1(7),VAR2(7),VAR3(7),SUM1(7),SUM 2(
27), SUM3(7), SUM4(7), COV1(7), COV2(7), IA(2), AI(2)
0002 REAL *4MEAN,M(17,8),MR(7)
0003 REAL *8X(10,60,7),V2(60,7), NAME(23),V1(7).
0004 INTEGER CST(2,60),CDATE(2,60,3)
0005 COMMON X,TABLE,JA,IB,I,K,KD,ID
0006 COMMON /BLK2/MR
0006 1 FORMAT (1X,13F6.3/13F6.3/4F6.3)
0007 READ (5,1) TABLE
0008 2 FORMAT (1214)
0009 READ (5,2) MONTH
0010 READ (5,3) IA(1)‘IA(2),ID
0011 3 FORMAT (315)
0012 Cc

78


ACKNOWLEDGEMENTS

The financial support of the U.S. Environmental Protection Agency and interest of
Dr. Milton H. Feldman are gratefully acknowledged.

A gift from the Forest Park Foundation permitted the acquisition of equipment es-
sential to this project and other studies on chlorinated hydrocarbons in our laboratories.
This support and interest in environmental problems has been greatly appreciated.

Finally, the authors would like to acknowledge Philip Murphy, Will McCarthy, Barbara

Cunningham, Anne Edwards, and Charles Bates for their technical assistance in this
project.

vii


0056

0057
0058

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0060

0061

0062

0063
0064

0065
0066

0067
0068

0069

0070

0071
0072
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0074
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anNAA aaa

aaa

aaa

aaa

14

W=W/(AI-1.0)

STD(18,K) IS CORRECTED STD(9,K)
STD(18,K)=SQRT((V/(V+W))**2*C*(STD(8,K)**2))
CALL STDEV2 (STD(18,K),STE(18,K),CL95(18,K))
STD(19,K) IS CORRECTED STD(10,K)

STD(19,K)=SQRT((W/(V+W))**2*C*(STD(8,K)**2))
CALL STDEV2 (STD(19,K),STE(19,K),CL95(19,K))

CALCULATE CORRECTED STD(20,K) CORRECTED STD(11,K)
STD(20;K)=SQRT(STD(16,K)**2*(M(9,K)/M(6,K))**2)

CALL STDEV2 (STD(20,K),STE(20,K),CL95(20,K))
CALCULATE STD(21,K) CORRECTED STD(12,K)
STD(21,K)=SQRT(STD(16,K)**2*(1.0—M(9,K)/M(6,K))**2)
CALL STDEV2 (STD(21,K),STE(21,K),CL95(21,K))

CALCULATE STD(22,K) CORRECTED STD(13,K)

STD(22,K)=SQRT(STD(21,K)**2*(1.0/M(12,K)**2)**2)
CALL STDEV2 (STD(22,K),STE(22,K),CL95(22,K))

CALCULATE STD(23,K) CORRECTED STD(14,K)
STD(23,K)=SQRT(STD(16,K)* *2"(1.0/M(7,K)**2)**2)
CALL STDEV2 (STD(23,K),STE(23,K),CL95(23,K))

CONTINUE

DO 15 K=1,D

WRITE (6,16) NAME(K)

WRITE (6,17) NAME(K),M(8,K),STD(17,K),STE(17,K),CL95(17,K)
WRITE (6,18) NAME(K),M(9,K),STD(18,K),STE(18,K),CL95(18,K)
WRITE (6,19)

WRITE (6,20) NAME(K),M(10,K),STD(19,K),STE(19,K),CL95(19,K)

76


0008
0009.

0010

0011
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0013

0014
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0002

0003
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0005
0006
0007
0008
0009
0010
0011
0012
0013

0014
0015
0016
0017
0018
0019

0001
0002

0003
0004
0005
0006

DO 1 J=1,IB
1 WRITE (6,3) CST(L,J),(ALOC(L,J,K),K=1,6),(CDATE(L,J,K), K=1,3),(X(I
1,),K),K=1,L1)

SKIP TO BOTTOM OF PAGE
N=(68-(IB+6))/2

DO 2 J=1,N
2 WRITE (6,4)

RETURN

3 FORMAT (5X,12,5X,2A4,A2,2X,2A4,A2,2X,12,2(‘-’,12),8F 11.2)
4 FORMAT (/)
END

SUBROUTINE PRINT2

DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8).
1, STE(23,8),CL95(23,8), IA(2),A1(2)

REAL *MEAN,M(17,8)

REAL *8X(10,60,7),V2(60,7), NAME(23),V1(7)

INTEGER CST(2,60),CDATE(2,60,3)

COMMON X,TABLE,IA,IB,I,K,KD,ID

COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L

WRITE (6,1) (TOT(I,J),J=1,L1)

WRITE (6,2) (M(1,J),J=1,L1)

WRITE (6,3) (STD(1,J),J=1,L1)

WRITE (6,4) (STE(I,J),J=1,L1)

WRITE (6,5) (CL95(1,J),J=1,L1)

RETURN

1 FORMAT (34X,‘TOTALS’,6X,7F 10.4)

2 FORMAT (/34X,‘MEAN’ 8X,7F 10.4)

3 FORMAT (/34X,‘S.D.’,8X,7F 10.4)

4 FORMAT (/34X,‘S.E.’,8X,7F 10.4)

5 FORMAT (/34X,‘95% CL’ ,6X,7F 10.4)
END

SUBROUTINE PRINT3

DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8),IA(2),Al(2)

REAL *4MEAN,M(17,8)

REAL *8X(10,60,7),V2(60,7),NAME(23),V1(7)

INTEGER CST(2,60),CDATE(2,60,3)

COMMON X,TABLE,IA,IB,I,K,KD,ID

87


Table 24. RATES OF DECAY TO WATER SOLUBLE COMPOUNDS AND CO9 DETERMINED

BY LABORATORY ASSAYS.

DOT DDD DDE
Laboratory Assays
S.D. S.D. S.D.
Deco 00529 + .00023 | .00173 + 00036 | .00325 + .00058
Ows 01539 + .000817 | .00309 + .00052 | .00459 + .00074
Laboratory Assays
Corrected by Q49
Dco2 00600 + 00026 | 00196 + .00041 .00369 + .00066
Dws 01746 + 00093 | .00351 + 00059 | .00521 + .00084
Estimations from
Field Data
iD) .0362 .0251 0265

55



Table 22. RESULTS OF A LABORATORY ASSAY OF ANNUAL RATE OF DECAY OF DDT
TO C09, 2co2, EXPRESSED AS A DECIMAL FRACTION OF THE INITIAL CONCEN-

TRATION OF DDT MAINTAINED AT 10°C. UNDER AEROBIC CONDITIONS.

DDT Prepar, 2coy Means S.D. Means S.D. Mean S.D.

100 ppm 1 0046

1 0045 00455 + .000071

2 0048

2 0042 .00450 + 000424

3 0059

3 0056 00575 + 000212

4 -0060

4 0045 00475 000354

5 -0046

5 .0053 00495 + .000495 | .00490 + 000544
10 ppm 1 0050

1 0052 00510 + 000141

2 .0058

2 0048 -00530 + 000707

3 0045

3 0056 -00505 + .000778

4 0056

4 0057 -00565 + .000071

5 0051

5 0056 00535 + 000354 | .00529 t 000436

1 ppm 1 .0050

1 .0059 00545 + 000636

2 0045

2 0046 00455 + 000071

3 0062

3 .0057 00595 + 000354

4 0058

4 0052 00550 + 000424

5 0063

5 0058 00605 + .000354 .00550 + .000638
100 ppb 1 .0057

1 .0057 .00570 + .0000

2 0045

2 0047 .00460 + 000141

3 0051

3 0051 00510 + 0000

4 0055

4 .0058 -00565 + 000212

5 .0063

5 0053 -00580 + 000707 | .00537 + 000542 | .00527 + .000570

Si



SECTION V

RESULTS AND DISCUSSION

SURVEYS OF RESIDUE LEVELS IN MONTEREY BAY SEDIMENTS

The concentration in parts per billion of the three compounds, DDT, DDD, and DDE

in sediment samples collected during the three sampling periods are presented in Table 3.
Table 4 presents the same set of analyses in terms of the percent of total residues for
each of the three compounds.

The variance of sampling at Station 38 can be assessed from the data presented in
Table 5. The greatest variation in results can be observed with respect to DDT, the
compound also showing the greatest loss during the extraction, concentration, and
cleanup procedures as mentioned in the section on methods.

The data obtained in the 1970 and 1971 samplings is presented in Figures 2, 3, and 4,
where the distribution of DDT and its two derivatives is displayed in terms of percent
of the concentration of total DDT derivatives. Figures 5 and 6 show the distribution in
terms of the total concentration of DDT and its two derivatives in parts per billion.
Figure 5 shows the distribution in 1970 and 1971, and Figure 6 shows the distribution
as indicated by the analyses of the smaller number of samples obtained in 1973.

The small number of sample stations in the northern portion of the bay did not reveal

any unusual augmentation in concentrations of the three compounds due to input from the
San Lorenzo and Pajaro Rivers although the percent composition of DDT derivatives

does indicate differences between the northern and southern portions of the bay.

If particular attention is paid to the southern portion of the bay for which there is the
greatest information, the distributions suggest a number of characteristics of the system.
After input with sediments from the Salinas River, and perhaps also through Elkhorn
Slough, these materials are subjected to considerable translocation due to the currents
operating within the south bay. The highest concentration of DDT derivatives is to be
found at a considerable distance from the mouth of the river. Close to the mouth of
the river, however, the sediments show a high percentage of DDT which is characteristic
of some of the sediments within the drainage system. These high DDT percentages are
also found at the more distant points where the highest concentrations of derivatives
are found as well. Over much of the area in terms of percent, however, DDE represents
the major compound.

These plots of distribution reflect input over a considerable period of time. During this
time the major routes of input may have changed considerably as has the relative con-
centrations of the three derivatives in these input sources. Nevertheless, the apparent
constancy of location of major basins of deposition is remarkable. Areas with high
concentrations in 1970 have become even more heavily contaminated in 1973.

13


j
If > K £n(O+D)

1
n(O+D) - Ky = Kj +1 (22)
aL = Kjg2 Kjag Kp (23)
nj-1

j
If > K = (04D)

1
n(l) = Kis Kjnar- Kn (24)
nj

The variances of such distributions are the minimal variances that will permit the estima-
tions of I, T and Tg, and (O+D) with a given number of samples. This variance is less af-
fected by the number of samples than it is by the difference between the values of I, Ty

and To, and (O+D) as can be seen in Table 18. The lowest standard deviations are observed
where Ty is low. Where I is increased relative to Ty, the standard deviation is reduced as well
but not to the same extent. For example, I = 2.0, Tj = 1.2 has a ratio of 0.6 as does 1 = 1.5,
Ty = 0.9, however, the latter has the lower standard deviation. The unavoidable variance
related to any series of values of I, Tj and Tq, O+D, and n has significance to survey design.
The greater the amount of internal translocation due to Ty and Tg the greater the unavoid-
able variance of the estimation of K. Increasing the number of sampling points has only a
minor effect upon the variance although it has a marked effect upon the standard error and
95% confidence limits of the estimates.

The corrected standard deviations with associated standard errors and 95% confidence
limits can be calculated using Subroutine FACTOR which will be found in the Appendix.
The.correction is imposed following the calculation of the standard deviation of K using
equation 3, but only with respect to first moment as is true for the other estimations of
standard deviations.

The variance is corrected as follows,
2 2 2 2 2
Sk calc. “Min. | °k ~ 5K corr.
2
‘kK calc.

(25)

Where 2 is the variance calculgted by equation 3, ein is the variance of the distribution
of K’s with minimal variance, K calc. is the variance of the distribution of K’s calculated
by equation 3, and sk (;; is the corrected variance of K. This correction appears to be
justifified because the variance of interest is that which is related to the variance of a sys-
tem with particular characteristics as compared to a similar system with minimal unavoid-
able variance. Table 19 presents a comparison of uncorrected standard deviations from
Tables 16 and 17 and the corresponding corrected values. The system estimates for

42


pointing from more negative to less negative K values and ending in basins with positive
K values. The result is a kinematic graph representing the movement of these materials
within the system. It is composite with respect to the time interval under consideration
and would appear to represent the result of several events of translocation. Figure 8
presents such a graph developed for the 19 station data set. The large double arrows in-
dicate the main offshore forces that drive the inshore circulation and correlated with the
kinematic expression of circulation within the system.

46


9035
0036

0037
0038

0039
0040

0041
0042

0043
0044

0045

0046

0047
0048
0049

0050
0051

0052
0053

0054
0055

aaa aaan a0

aaa

ann

aaa

9

10
ll

12
13

DO 9 J=1,IA
W=W+(X(8,J,K)—M(8,K))**2

W=W/(AI—1.0)
C=((W—V)/W)**2

CALCULATE CORRECTED STD,6,7,AND 8
STD(15,K) IS CORRECTED STD(6,K)

STD(15,K)=SQRT(C*STD(6,K)**2)
CALL STDEV2 (STD(15,K),STE(15,K),CL95(15,K))

STD(16,K)IS CORRECTED STE(7,K)

STD(16,K)=SQRT(C*STD(7,K)**2)
CALL STDEV2 (STD(16,K),STE(16,K),CL95(16,K))

STD(17,K)IS CORRECTED STD(8,K)

STD(17,K)=SQRT(C*STD(8,K)**2)
CALL STDEV2 (STD(17,K),STE(17,K),CL95(17,K))

CALCULATE CORRECTED STD(9,K) AND STD(10,K)

Vv=0.0

DO 11 J=1,JA
IF (X(9,J,K)) 11,11,10

V=V+X(9,J,K)**2
CONTINUE

V=V(AI-1.0)

W=0.0

DO 13 J=1,IA

IF (X(10,J,K)) 12,13,13

W=W+(X(10,J,K))**2
CONTINUE

“75


Approaches to the estimation of rates and Dynamics of the compounds in Sediments—
Using the tabulated data obtained from the sampling programs various approaches to
the estimation of the rates of input, translocation, and decay were developed for the
system of sample sites. Considerable attention was directed to estimation of variance
of these derived rates.

Development of Laboratory Assay Methods for the Determination of Decay Rate—
Measurement of decay rate based on changes in residue level observed by repeated
sampling from the environment are subject to error due to translocation to or away
from the sample site. Therefore, a means of estimating decay rate in a closed system
not susceptible to such error would be desirable. A variety of preparations using 14c
ring labelled compounds were established for such estimations.

Effect of Environmental Variables on Decay Rate—Any closed system preparation is

by its very nature selective for one or another metabolic type of microorganism. The
initial conditions and conditions which subsequently develop may have a marked ef-
fect upon the observed rate of decomposition through the election of particular micro-
bial populations. Therefore, it was necessary to study the process of decay as influenced
by a number of environmental variables chosen to encourage one or another of the ma-
jor metabolic types of microorganisms.


DEVELOPMENT OF LABORATORY ASSAY METHODS FOR DETERMINATION OF
DECAY RATE

Of the various preparations tested for the assay of decay rate, the sealed hypovial prepar-
ations described in the Methods section have best met the following desired criteria.

(1) Preparations must be capable of being sealed to prevent loss of the chlorinated hydro-
carbon and its degradation products including CO2. (2) The containers must be readily
sterilized and of materials that prevent contamination by other chlorinated hydrocarbons.
(3) The preparations must be easily manipulated with respect to the establishment of
aerobic and anaerobic conditions. (4) The preparation must be susceptible to replication
both in terms of individual preparations and aliquots from the same preparation.

The most convenient estimate of decay cari be obtained by measurement of the amount
of 14CQ2 produced from ring labelled substrate after an interval of time. Knowing the
initial concentrations of substrate the decay to carbon dioxide can be expressed as a deci-
mal fraction of this initial concentration. The decimal fraction is the Deo: Table 22

presents the results of an assay of DDT to CO2 under aerobic conditions at 10°C. Two
aliquots from each of five preparations at four concentrations of DDT were analysed for
their 14CO content. There is no significant difference between the Deo, measurements
at the four concentrations of DDT. Therefore, over the range from 100 parts per billion
to 100 parts per million there was neither a stimulation of the decay process nor a satura-
tion of the decay process by substrate. Table 23 presents the results of assays for Deo,
of DDT, DDD, and DDE. This Table also includes the results of assays in which the effect
of environmental variables on the Dcg, was determined.

The Qy9 for Deg, of DDT calculated from the aerobic 10° and 20° assays is 2.50. The
remaining assays where DDT is the substrate were designed to determine the participation
of various physiologically different microbiol populations in the decay process. Aerobic
conditions without additional nutrients gave the maximum Dy. The decay process was
inhibited by anaerobiosis, but a rate 27% of the aerobic rate remained. The addition of
nitrate as an additional electron acceptor under anaerobic conditions permitted an in-
crease in the anaerobic rate. The three highest concentrations of nitrate, 5 X 10°!% to

5 X 10°3% were inhibitory but below these concentrations the anaerobic rate becomes
68% of the aerobic rate at 5 X 10°5% sodium nitrate.

The addition of a possible cometabolite, sodium acetate, somewhat removes the inhibi-
tory effect of 5 X 10°!% sodium nitrate probably by its lowering of the nitrate level
through denitrification. However, at none of the levels of sodium acetate tested did the
anaerobic rate reach the level with 5 X 10°5% sodium nitrate alone. The effect of the
addition of cometabolites on decay in the presence of nitrate reducing systems must be
tested at lower concentrations of nitrate.

Sulfate, present in the seawater, was available as an electron acceptor under anaerobic
conditions, Attempts to stimulate sulfate reduction systems by the addition of ethanol
under anaerobic conditions were successful. However, the anaerobic decay of DDT was
not increased over the rate observed with optimum nitrate concentrations and in the
absence of added electron donors such as sodium acetate,

50


FIGURES

The study area, Monterey Bay. Sampling stations are indicated
by number.

DDT as a percent of the total concentration of DDT, DDD, and
DDE plotted for data obtained in 1970 and 1971. Circled numbers
indicate actual percents in excess of 50%.

DDD as a percent of the total concentration of DDT, DDD, and
DDE plotted for data obtained in 1970 and 1971. Circled numbers
indicate actual percents in excess of 50%.

DDE as a percent of the total concentration of DDT, DDD, and
DDE plotted for data obtained in 1970 and 1971. Circled numbers
indicate actual percents in excess of 50%.

Total concentration in parts per billion of DDT, DDD, and DDE
from data obtained in 1970 and 1971. Circled numbers indicate
actual concentrations in excess of 50 ppb.

Total concentration in parts per billion of DDT, DDD, and DDE
from data obtained in 1973. The blank portions of the area were
not sampled. Circled numbers indicate actual concentrations in
excess of 50 ppb.

Model of the system of sediment compartments and this system’s
relation to other systems.

Composite chart of the translocation of DDT compounds based
upon the rates of change, K, at individual stations in the
southern portion of Monterey Bay.

iv

22

23

29

49


0192

0193
0194

0196
0197
0198

0199
0200
0201
0202

0203
0204
0205
0206
0207
0208
0209
0210
0211
0212
0213
0214
0215
0216
0217

an

aAaanaAA aaAnn

aaaa

M(12,K)=M(7,K)—M(11,K)

CALCULATION OF STANDARD DEVIATION OF D

STD(12,K)=SQRT(STD(7,K)**2*(1.—M(9,K)/M(6,K))**2)
CALL STDEV2 (STD(12,K),STE(12,K),CL95(12,K))

CALCULATE TL.

M(13,K)=-1.0*(1.0/M(12,K))
STD(13,K)=SQRT(STD(12,K)**2*(1.0/M(12,K)**2)**2)
41 CALL STDEV2 (STD(13,K),STE(13,K),CL95(13,K))

CALCULATE TR.

DO 42 K=1,ID

M(14,K)=-1.0*(1.0/M(7,K))

STD(14,K)=SQRT(STD(7,K)**2*(1.0/M(7,K)**2)**2)
42 CALL STDEV2 (STD(14,K),STE(14,K),CL95(14,K))

DO 44 K=1,ID
WRITE (6,55) NAME (K)

WRITE (6,56) NAME (K),M(8,K),STD(8,K),STE(8,K),CL95(8,K)
WRITE (6,57) NAME (K),M(9,K),STD(9,K),STE(9,K),CL95(9,K)

WRITE (6,58)

WRITE (6,59) NAME (K),M(10,K),STD(10,K),STE(10,K),CL95(10,K)

WRITE (6,60)

WRITE (6,61) NAME (K),M(6,K),STD(6,K),STE(6,K),CL95(6,K)
WRITE (6,62) NAME (K),M(7,K),STD(7,K),STE(7,K),CL95(7,K)
WRITE (6,63) NAME (K),M(11,K),STD(11,K),STE(11,K),CL95(11,K)
WRITE (6,64) NAME (K),M(12,K),STD(12,K),STE(12,K),CL95(12,K)
WRITE (6,65) NAME (K),M(13,K),STD(13,K),STE(13,K),CL95(13,K)

WRITE (6,66)

WRITE (6,65) NAME (K),M(14,K),STD(14,K),STE(14,K),CL95(14,K)

WRITE (6,67)

67


KM

|

sof FATHOMS

NY

TOTAL DDT DERIVATIVES
PPB 1970 & I97I

= |
7
7

7

J

Figure 5. Total concentration in parts per billion of DDT, DDD, and DDE from data obtained in
1970 and 1971. Circled numbers indicate actual concentrations in excess of 50 ppb.

22


0131

0132
0133

0134
0135
0136

0137
0138
0139

0142
0143

0144
0145
0146
0147

0148
0149

0150
0151
0152
0153

0154
0155
0156

23 SUM 4 (K)=(DLOG(X(2,J,K))-ALOG(M(2,K)))* *2+SUM4(K)

Cc
Cc
DO 24 K=1,ID
VAR 1(K)=(.43429/M(1,K))**2*SUM3(K)/(AI—1.0)+(—.43429/M(2,K))**2
1*SUM4 (K)/(AI-1.0)
24 V1(K)=SUM2(K)/AI
DO 25 K=1,ID
VAR2(K)=((1.0/M(5,K))**2* VAR1(K))+(—V1(K)/(M(5,K)**2))**2*STD(5,K)
1**2 .
VAR2(K)=10.0**VAR2(K)
STD(8,K)=SQRT(VAR2(K))
25 CALL STDEV2 (STD(8,K),STE(8,K),CL95(8,K))
Cc
Cc
Cc
Cc CALCULATE THE DISTRIBUTION OF VARIANCE BETWEEN +K AND -K
Cc
DO 30 K=1,ID
V=0.0
Cc
DO 27 J=1,1A
IF (X(6,J,K)) 27,27,26
26 V=(X(6,J,K)-M(8,K))**2+V
27 CONTINUE
Cc
Cc
V=V/(AI-1.0)
W=0.0
Cc
Cc
DO 29 J=1,JA
IF (X(7,J,K)) 28,29,29
28 W=(X(7,J,K)-M(8,K))**2+W
29 CONTINUE
Cc
W=W/(AI-1.0)
U=V+W

V=STD(8,K)**2*(V/U)**2

65


SECTION VI
REFERENCES
Calif. Dept. of Agriculture, 1970, 1971, 1972, 1973. Pesticide Use Report. Data Proces-

sing Center, Calif. Dept. of Agri., Sacramento.

Eberhardt, L. L., R. L. Meeks, and T. J. Peterle. Food chain model for DDT kinetics in a
freshwater marsh. Nature. 230:60-62. 1971.

Gunther, A., and R. C. Blinn. The DDT-type compound as source material in organic syn-
thesis. J. Chem. Educ. 27:654-658. 1950.

Hamaker, J. W. Mathematical prediction of cumulative levels of pesticides in soil. Adv. in
Chem. Sci. 60. Amer. Chem. Soc., Wash., D.C. 1966.

Harrison, H. L., O. L. Louchs, J. W. Mitchell, D. F. Parkhurst, C. R. Tracy, D. G. Watts,
and V. J. Yannacone, Jr. System studies on DDT transport. Sci. 170:503-508. 1970.

Murphy, P. G. Effects of salinity on uptake of DDT, DDE and DDD by fish. Bull. Envir.
Cont. and Tox. 5:404-407. 1970.

Papoulis, A. Probability, random variables, and stochastic processes. McGraw-Hill Book
Co., N. ¥. 1965.

Robinson, J. Dynamics of organochlorine insecticides in vertebrates and ecosystems.
Nature. 215:33-35. 1967.

Sokal, R. R. and F. J. Rolf. Biometry. W. H. Freeman and Co., San Francisco. 1969. .
State of California. Monterey basin pilot monitoring project. To be released in 1974.

Woodwell, G. M. Toxic substances and ecological cycles. Sci. Amer. 216:24-31. 1967.

58


Table 3. (continued) CONCENTRATIONS OF DDT, DDD, AND DDE IN MARINE
SEDIMENT SAMPLES FROM MONTEREY BAY.

poo
LOCATION DDT DDD DDE
Station Latitude Longitude Date (ppb) (ppb) (ppb) TOTAL

39 36 54.80 122 01.00 11-24-71 0.60 1.90 2.00 4.50
40 36 57.10 121 56.20 11-10-71 1.62 8.15 5.54 15.31
41 36 56.70 121 59.20 11-24-71 0.93 2.75 4.48 8.16
42 36 55.50 121 52.60 11-10-71 0.85 1.58 0.66 | 3.09
43 36 55.10 121 56.70 11-10-71 0.81 3.07 2.59 6.47
44 36 53.60 121 57.50 11-24-71 1.13 2.54 2.47 6.14
45 36 53.00 121 55.00 11-10-71 1.21 2.01 1.88 5.10
46 36 52.30 121 59.80 11-24-71 1.27 3.81 5.06 10.14
47 36 51.00 121 49.80 11-10-71 1.16 1.27 1.13 3.56
48 36 50.80 121 53.60 11-24-71 1.62 5.61 6.72 13.95
49 36 50.20 121 50.20 11-10-71 0.78 1.48 1.29 3.55

1 36 47.25 121 48.90 7- 973 1.06 0.53 0.56 2.15

2 36 46.85 121 53.50 7- 9-73 9.50 11.40 17.50 38.40

3 36 46.35 121 49.00 7- 9-73 1.10 0.53 0.63 2.26

4 36 46.05 121 51.00 7- 9-73 3.63 5.43 6.91 15.97
10 36 45.10 121 50.00 7- 2-73 0.92 0.39 0.52 1.83
11 36 45.00 121 49.00 7- 2-73 2.18 0.72 0.83 3.73
14 36 44.20 121 52.25 6-21-73 | 30.60 6.07 11.20 47.87
16 36 44.00 121 49.50 7- 2-73 0.96 0.06 0.23 1.25
17 36 43.75 121 54.45 8- 9-73 5.41 4.54 17.30 27.25
19 36 43.35 121 56.25 8- 9-73. | 72.70 3.19 12.00 87.89
20 36 43.18 121 57.00 6-21-73 | 63.10 0.79 3.48 67.37
22 36 42.90 121 58.00 8 9-73 0.93 0.90 6.06 7.89
23 36 42.55 121 53.30 6-21-73 | 29.90 4.32 12.20 46.42
25 36 41.70 121 55.00 7-16-73 1.14 2.74 10.49 14.37
26 36 41.55 121 55.50 7-16-73 0.68 2.20 8.67 11.55
29 36 40.90 121 56.40 7-16-73 0.70 1.11 5.67 7.48
34 36 39.10 121 53.08 8 9-73 1.18 0.42 2.44 4.04
36 36 37.95 121 52.50 6-21-73 | 83.10 0.95 3.34 87.39
37 36 37.77 121 51.83 7-16-73 0.54 0.20 0.40 1.14
38 36 38.47 121 51.68 9-21-73 0.62 0.38 2.72 3.72

15


Table 11. SIXTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,
FOR DDD IN EACH SEDIMENT COMPARTMENT.

T ==
Station | C2DODD |C, DDD N +K -K +K +-K | +K aNet “K vet
1 0.53 3.67 2.8795 0.0 -0.4893 -0.4893 0.0 -0.5714
2 11.40 6.76 2.6493 0.2181 0.0 0.2181 0.1360 0.0
3 0.53 0.71 3.3836 0.0 -0.0828 -0.0828 0.0 -0.1648
4 5.43 6.61 2.6493 0.0 -0.0715 -0.0715 0.0 -0.1536
10 0.39 8.67 3.0959 0.0 -0.6328 -0.6328 0.0 -0.7148
1 0.72 0.40 3.3644 0.1909 0.0 0.1909 0.1089 0.0
14 6.07 7.50 2.8301 0.0 -0.0720 -0.0720 0.0 -0.1541
16 0.06 0.14 3.3644 0.0 -0,2226 -0.2226 0.0 -0.3047
7 4.54 0.38 2.7342 1.4774 0.0 1.4774 1,3953 0.0
19 3.19 0.25 2.9644 1.3607 0.0 1.3607 1.2787 0.0
20 0.79 5.00 3.3671 0.0 -0.4219 -0,.4219 0.0 -0.5039
22 0.90 0.35 3.4685 0.3130 0.0 0.3130 0.2309 0.0
23 4.32 5.73 2.8301 0.0 -0.0950 -0.0950 0.0 -0.1770
25 2.74 0.53 3.4027 0.6206 0.0 0.6206 0.5386 0.0
26 2.20 2.35 3.4356 0.0 -0.0190 -0.0190 0.0 -0.1011
29 1.11 1.61 3.4027 0.0 -0.1035 -0.1035 0.0 -0.1856
34 0.42 0.66 3.5014 0.0 0.1211 -0.1211 0.0 -0.2031
36 0.95 2.79 3.3342 0.0 -0.2761 -0.2761 0.0 -0.3582
37 i 0.20 0.21 3.4356 0.0 -0.0141 -0.0141 0.0 -0.0961

Totals 46.4899 54.3199 60.0930 4.1806 -2.6218 1.5588 3.6884 -3.6884
Mean 2.4468 2.8589 3.1628 0.2200 -0.1380 0.0820 0.1941 -0.1941
S.D. + 2.8805 + 2.9296 +0.3100 +0.7233 +0.2767 + 1.0000 +0.7233 + 0.2767
S.E. + 0.6608 + 0.6721 +0.0711 +0.1659 +0.0635 +0.2294 +0.1659 + 0.0635

95% C.L. + 1.3884 + 1.4121 +0.1494 +0.3486 +0.1334 +0.4820 +0.3486 +0.1334

32


Table 23. RESULTS OF LABORATORY ASSAYS OF THE ANNUAL RATES OF DECAY TO C02,
Dco2 AND THE EFFECT OF ENVIRONMENTAL VARIABLES ON THE PROCESS.

Conditions Substrate Deo. Mean S.0.
Aerobic, 10°C DDT 100 ppm -0050
10 ppm .0053
00529 + 00023
1 ppm .0055
100 ppb 0054
Aerobic, 20°C DDT 100 ppm 0100
10 ppm 0111
01320 + 00335
1 ppm 0167
100 ppb 0154
Qip 2.50
Anaerobic, 10°C DDT 100 ppm 0012
10 ppm 0013
00145 + .00027
1 ppm 0015,
100 ppb 0018
Anaerobic, 10°C DDT 10 ppm .0013
5x 101% NaNO3 1 ppm 0016 00150 + 00017
100 ppb 0016
5x 102% NaNO3 ODT 10 ppm 0017
ppm 0018 00183 + 00015
100 ppb 0020
5 x 10°3% NaNO3 DDT 10ppm | .0024
ppm 0024 00250 + 00017
100 ppb .0027
5 x 104% NaNO3 DDT 10ppm | .0030
1 ppm .0036 00340 + 00035
100 ppb 0036
5 x 10°5% NaNO DDT 10ppm | .0037
. T ppm 0034 00360 + 00017
100 ppb .0037
5 x 10°6% NaNO DDT 10ppm | .0036
ppm 0025 00310 + .00056
100 ppb .0032
5 x 107% NaNOg DDT 10ppm | .0031
1 ppm 0032 00313 + ,00006
100 ppb 0031

52


Table 5. VARIANCE OF SAMPLING MEASURED AT STATION 38.

DDT DDD DDE TOTAL

Sample Subsample (ppb) (ppb) (ppb) (ppb)

1 1 687 430 3.01 4.13

2 772 470 2.90 4.14

3 550 370 2.85 3.77

2 1 561 345 2.89 3.80

2 .706 333 2.38 3.42

3 801 .280 2.57 3.65

3 1 663 439 2.63 3.73

2 .398 .315 2.96 3.67

3 405 A18 2.32 3.14
Mean 6159 3778 2.7233 3.7167
Variance .02167 .00416 .06574 .09841
Standard Deviation +1472 +0645 + .2564 + 3137
Standard Error * 0491 +0215 7 .0855 t 1046
95% Confidence Limits +1131 t.o495 * 1971 + 2411

18


0197 V=V/(AI3-1.0)
0198 W=W/(AI3-1.0)
0199 STD(9,K)=SQRT(((V/(V+W))* *2*(STD(8,K)**2))
0200 CALL STDEV2(STD(9,K),STE(9,K),CL95(9,K))
0201 STD(10,K)=SQRT(((W/(V+W))**2*(STD(8,K)**2))
Cc
0202 46 CALL STDEV2(STD(10,K),STE(10,K),CL95(10,K))
0203 CALL PRINT3
Cc
Cc CALCULATE O AND ITS STANDARD DEVIATION
Cc
0203 DO 52 K=1,ID
0204 M(11,K)=(M(9,K)/M(6,K))*M(7,K)
0205 STD(11,K)=SQRT(STD(7,K)**2*((M(9,K)/M(6,K))* *2))
0206 CALL STDEV2 (STD(11,K),STE(11,K),CL95(11,K))
Cc
Cc
Cc CALCULATION OF D
0207 M(12,K)=M(7,K),—M(11,K)
Cc
Cc CALCULATION OF STANDARD DEVIATION OF D
Cc
0208 STD(12,K)=SQRT(STD(7,K)**2*(1.-M(9,K)/M(6,K))**2)
0209 CALL STDEV2 (STD(12,K),STE(12,K),CL95(12,K))
Cc
Cc CALCULATE TL.
Cc
0222 M(13,K)=-1.0*(1.0/M(12,K))
0223 STD(13,K)=DSQRT(STD(12,K)**2*(1.0/M(12,K)**2)**2)
0224 52 CALL STDEV2(STD(13,K),STE(13,K),CL95(13,K))
Cc
Cc CALCULATE TR.
Cc
0225 DO 53 K=1,ID
0226 M(14,K)=-1.0*(1.0/M(7,K))
0227 STD(14,K)=SQRT(STD(7,K)**2*(1.0/M(7,K)**2)**2)
0228 53 CALL STDEV2 (STD(14,K),STE(14,K),CL95(14,K))
Cc
0229 DO 71 K=1,ID
0230 WRITE (6,54) NAME(K)
0231 54 FORMAT (‘1’,1X,‘RATES OF CHANGE FOR’,A8,30X,'S.D.’,7X,‘S.E.’,4X,
1 ‘95%LIMIT’//)
0232 WRITE (6,55) NAME (K),M(8,K),STD(8,K),STE(8,K),CL95(8,K)
0233 55 FORMAT (2X,‘MEAN OF K’,13X,‘=NET’,3X,A8,‘=’,3X,4F11.4/)
0234 WRITE (6,56) NAME(K),M(9,K)STD(9,K),STE(9,K),CL95(9,K)
0235 56 FORMAT (2X, ‘MEAN OF + ( K-NET ) = T’ ,5X,A8,‘=’,3X,4F11.4)
0236 WRITE (6,57)

85


T2 = mean time of second sampling period

Ty = time of actual sampling in first sampling period
and Cy = Cy eKN (10)
with N=T3-Ty

T2 = time of actual sampling in second sampling period

T1 = mean time of first sampling period.

Table 17 presents the estimates of the system obtained using this pairing with means
approach. Once again the effect of substitution of a minimal value for zero concentra-
tions was explored by eliminating stations with zero concentration thus providing the
subset of 49 samples from the complete set of 57. Except for the estimates of Tg for
DDT, there was no significant difference between the two sets of estimates once again,
nor are these estimates significantly different from either of the sets of estimates based
on the 16 and 19 station data sets. The principal effect of inclusion or exclusion of the
zero level values with substitution of a minimal value is upon the estimates of the rates
of input, 1, translocation, Tj and To, and the net rate. The stations showing a zero
concentration of DDT at time one show high positive rates of change, and therefore,
have a particularly marked effect on the positive rate estimates as well as those based
to at least some extent upon these positive rate estimates.

The second approach which uses sample values paired to mean values should find use
in the analysis of systems where real paired values are impossible to obtain. Animals
which are sacrificed at the time of sampling obviously can not be resampled at another
point in time. The use of sample values at one sample time paired to the mean value
of another permits estimation of system rates for the population. The comparison be-
tween the two approaches to these estimates that is presented here indicates that the
use of mean values in pairing gives a close approximation of rate estimates obtained
with real paired values. ;

Both of these approaches to the estimation of system rates are dependent upon vari-
ability in concentration level and rate of caange within compartments. It is essential
to these methods of analysis that individual compartments show the effect of the
various processes to different degrees. If all the concentration levels and rates of
change within compartments were the same, it would be possible to gain an estimate
of net rate of change only. Therefore, these approaches to estimation of system rates
are dependent upon variability in environmental samples of the system and make use
of this variability for estimating the rates of the various processes.

39


0035 DO 8 I=1,2
0036 IB=IA(1)
c
0037 DO 8 J=1,1B
c
0038 DO 8 L=1,ID
0039 8 X(LJ,IP1)=X(1,J,L)+X(1J,IP1)
c
c
c WRITE HEADING OF FIRST TWO PAGES.
c
0040 DO 15 1=1,2
0041 IB=IA(1)
0042 L=I
0043 9 FORMAT (‘1’)
0044 10 FORMAT (‘1',‘C’/2X,11,/3X, ‘STATION’ 3X,‘LATITUDE’,3X,‘LONGITUDE’,
1 5X,‘DATE’)
0045 WRITE (6,10) I
0046 11 FORMAT (48X,8(3X.A8))
0047 12 FORMAT (‘+’,47X,8(3X,A8))
0048 WRITE (6,12) (NAME(N),N=1,IP 1)
0049 13 FORMAT (/)
0050 WRITE (6,11) (NAME(N),N=IP2,12TP2)
0051 WRITE (6,13)
c
0052 DO 14 K=1,IPi
0053 CALL STDEV (TOTAL,MEAN,SD,SE,CL)
0054 TOT(I,K)=TOTAL
0055 M(,K)=MEAN
0056 STD(I,K)=SD
0057 STE(I,K)=SE
0058 14 CL95(I,K)=CL
c
c L1=NUMBER OF SETS COMPUTED.
c
Cc WRITE FIRST TWO PAGES.
0059 L1=IP1
0060 CALL PRINT
0061 WRITE (6,12) (NAME(N),N=1,IP1)
0062 WRITE (6,11) (NAME(N),N=IP2,12TP2)
0063 WRITE (6,13)
0064 CALL PRINT2
0065 15 CONTINUE
c
c
c COMPUTE PERCENTS.

80


estimation of field rates. If we take the difference between the values of Dws obtained
from laboratory assays and D obtained from field estimations the rates of decay of the
parent compounds to lipid soluble breakdown products, Dig, are .0187 for DDT, .0216
for DDD, and .0213 for DDE under aerobic conditions at 11°C, the mean temperature
of the sediments. It should be noted that although every precaution was taken to ensure
purity of starting materials in laboratory assays, the amounts of decomposition in three
month periods is extremely small and trace contaminants containing labell could have a
large effect upon the results. In addition it must be emphasized that conditions in labora-
tory preparations poorly approximate conditions in the field. Therefore, their value is
more in terms of results obtained by comparisons between preparations rather than com-
parisons between laboratory preparation and field observation.

57


0066
0067
0068
0069
0070
0071
0072
0073

0074

0075
0076

0077
0078
0079
0080
0081
0082
0083

0084
0085
0086
0087
0088
0089

0090

0091
0092

0093
0094

0095

0096
0097

Cc

aan

DO 18 1=3,4
IB=IA(I-2)

L1=ID

L=I-2

WRITE (6,10) L

WRITE (6,12) (NAME(N),N=1,ID)

WRITE (6,11) (NAME(N),N=12TP3,13TP2)
WRITE (6,13)

DO 16 K=1,ID

DO 16 J=1,1B
16 X(I,J,K)=X(L,J,K)/X(L,J,IP1)*100.

DO 17 K=1,3
CALL STDEV (TOTAL,MEAN,SD,SE,CL)
TOT(I,K)=TOTAL
M(1,K)=MEAN
STD(I,K)=SD
STE(I.K)=SE
17 CL95(1,K)=CL

CALL PRINT
WRITE (6,12) (NAME(N),N=1,ID)
WRITE (6,11) (NAME(N),N=I2TP3,I3TP2)
WRITE (6,13)
CALL PRINT2
18 CONTINUE
CALL NCOMP
CALCULATE TOTAL AND MEAN OF N.

DO 20 K=1,ID
TOT(5,K)=0.

DO 19 J=1,1A3
19 TOT(5,K)=TOT(5,K)+X(5,J,K)

20 M(5,K)=TOT(5,K)/AI13
DO 22 K=1,ID
V=0.0

81


Table 7. SECOND PAGE OF COMPUTER OUTPUT SHOWING CONCENTRATION OF
POLLUTANT COMPOUNDS IN SEDIMENT FROM SAMPLE STATIONS AT
THE SECOND SAMPLING TIME. Co IDENTIFIES AS CONCENTRATIONS AT

TIME TWO.
Co
LOCATION DDT DDD DDE

Station Latitude Longitude Date (ppb) (ppb) (ppb) | TOTAL
1 36 47.25 121 48.90 7-973 | 1.06 0.53 0.56 2.15
2 36 46.85 121 53.50 7-973 | 9.50 11.40 17.50 38.40
3 36 46.35 121 49.00 79-73 | 1.10 0.53 0.63 2.26
4 36 46.05 121 51.00 7-973 | 3.63 5.43 6.91 15.97
10 36 45.10 121 50.00 7- 2-73 | 0.92 0.39 0.52 1.83
1 36 45.00 121 49.00 7- 2-73 | 2.18 0.72 0.83 3.73
14 36 44.20 121 52.25 6-21-73 | 30.60 6.07 11.20 47.87
16 36 44.00 121 49.50 7- 2-73 | 0.96 0.06 0.23 1.25
17 36 43.75 121 54.45 8 973 | 5.41 4.54 17.30 27.25
19 36 43.35 121 56.25 8 9-73 | 72.70 3.19 12.00 87.89
20 36 43.18 121 57.00 6-21-73 | 63.10 0.79 3.48 67.37
22 36 42.90 121 58.00 8 973 | 0.93 0.90 6.06 7.89
23 36 42.55 121 53.30 6-21-73 | 29.90 4.32 12.20 46.42
25 36 41.70 121 55.00 7-16-73 | 1.14 2.74 10.49 14.37
26 36 41.55 121 55.50 7-16-73 | 0.68 2.20 8.67 11.55
29 36 40.90 121 56.40 7-16-73 | 0.70 111 5.67 7.48
34 36 39.10 121 53.08 89-73 | 1.18 0.42 2.44 4.04
36 36 37.95 12152.50 | 6-21-73 | 83.10 0.95 3.34 87.39
37 36 37.77 12151.83 ° 7-16-73 : 0.54 0.20 0.40 1.14

i

TOTALS 309.3296 46.4899 120.4299 476.2488

Mean 16.2805 2.4468 6.3384 25.0657

Standard Deviation + 26.9909 +2.8805 + 5.7417 + 29.2362

Standard Error + 61921 +06608 + 1.3172 + 6.7072

95% Confidence Limits + 13.0097 + 1.3884 + 2.7675 + 14.0919

26



SECTION II
RECOMMENDATIONS

The complexities of the dynamics of coastal pollution by chlorinated hydrocarbons
necessitates an initial survey of the concentration of these environmental contaminants at
a large number of stations. Once basins of accumulation are established and principal
translocation paths established a much smaller number of stations require surveillance at
later points in time. It doesn’t appear to be essential to monitor exactly the same stations
in any surveillance program as long as the set of surveillance stations includes established
basins and positions along translocation pathways.

It is recommended that initial intensive surveys be carried out in the coastal marine envi-
ronment adjacent to major agricultural and industrial areas which are known to produce
or utilize poorly degraded environmental contaminants such as the chlorinated hydro-
carbons.

Monterey Bay is a very useful model coastal marine environment for the establishment
and testing of approaches to system rate estimation. Continued surveillance of this area is
recommended.

It is also recommended that work be done on extending the approach to estimation of
system rates explored with respect to sediments to other environmental systems including
populations of organisms. It would appear desirable to concentrate initially upon abun-
dant and useful indicator organisms rather than commercially desirable or affected species.

Finally, it is recommended that additional effort be expended on the study of laboratory
assays of decay not only as approximations of the environment but as useful preparations
for elucidating the conditions inhibitory and stimulatory to the decay process.


For any set of estimates of I, (O+D), Ty and To, based on a number of samples, n,
there is a distribution of K’s with a minimal variance. The members of the distribu-
tion can be determined through one of the following sets of equations:

Where the net rate of change, I + (O+D), is positive,

j= nl-nTy and j is an integer obtained without rounding. (11)
1+ (O+D)
1+ (O+D) + nTy = Ky, Ky..-Kj (12)
J

If >* Lal

1
nl -jKy =Kj +1 (13)
m(O+D) = Kj+2,Kj+3...Ky (14)
n-j-1
j
If >
K =nl
1

mO+D) = Kj+1,Kj+2...K, (15)

n-j

Where the net rate of change, I + (O+D), is zero,

J “S and j is an integer obtained without rounding. (16)
aty = Ky, Ky... Kj (17)

J
nTg = K+ i Kje2 Kj (18)

J
If 2j Ln,
K, = 0.0 (19)

Where the net rate of change, I + (O+D), is negative,
j=n(O+D) -nTo (20)
1+ (O+D)
1+ O+D) + Tg = Ky, Kp, .. Kj (21)
J

41


SECTION I

CONCLUSIONS

Chlorinated hydrocarbons associated with sediment particles tend to concentrate in
sedimentation basins which may be at some distance from the input source.

Although the use of chlorinated hydrocarbon pesticides has declined sharply the levels
of three materials has continued to increase in marine sediments. The principal source
of this additional pollutant load in this instance appears to be more related to translo-
cation of these materials absorbed to sediments of adjacent land drainage systems.

The dynamics of chlorinated hydrocarbons in the coastal marine environment, although
complex, are susceptible to study. Approaches to the estimation of rates of input, decay,
and translocation can be developed and assessed by continued analysis of environmental
samples.

The measurement of decay rate by laboratory assay appears to have its greatest utility

in the determination of the effect of environmental conditions on the process of decay.
Duplication of conditions existing in situ in the laboratory can only be approximated
and then only for a limited time. The laboratory work, short term in its execution, serves
only as a guide to what is happening in the environment.


Table 13. EIGHTH PAGE OF COMPUTER OUTPUT SHOWING A SUMMARY OF THE ANNUAL,
SYSTEM RATES EXPRESSED AS DECIMAL FRACTIONS OF THE MEAN CONCEN-

TRATION OF DDT PRESENT IN THE SYSTEM.

95%
System of Rates for DDT S.D. S.E. Limit
Net rate of change = Net = 1.5788 + 1.0000 0.2294 * 0.4820
Translocation into compartments = T; = 1.1012 + 0.8738 0.2008 ¢ 0.4212
Translocation out of compart- 4 +
ments =To9 = 1.1012 + 0.1262 0.0289 * 0.0608
Input els 1.6811 * 0.9016 0.2068 + 0.4346
Output and Decay =O#D=- 0.1023 +t 0.0984 0.0226 +t 0.0474
Output from System =O = 0.0670 + 0.0644 0.0148 + 0.0311
Decay =D = 0.0353 + 0.0339 0.0078 + 0.0164
Lifetime in years =TL = 283322 + 27,2386 6.2490 + 13.1291
Residence time in years =TR = 9.7724 + 9.3952 2.1554 + 4.5285 |
Summary Equation for the System—
pot MeanCo = Mean Cy | an To fe) ie) N

16.2805 = 3.1274 (1.0 + 1.6811 + 1.1012- 1.1012 - 0,0670 - 0.0353) 3-1628

35


Table 3. CONCENTRATIONS OF DDT, DDD, AND DDE IN MARINE SEDIMENT
SAMPLES FROM MONTEREY BAY.

I

LOCATION DDT DDD DDE
Station Latitude Longitude Date (ppb) | (ppb)} = (ppb)}| TOTAL

36 47.25 121 48.90 8-23-70 8.36 3.67 5.76 17.79
36 46.85 12153.50 | 11-15-70 1.63 6.76 14.70 23.09
36 46.35 121 49.00 2-20-70 5.71 0.71 1.02 7.44
36 46.05 12157.00 | 11-15-70 4.28 6.61 10.70 21.59
36 46.00 121 57.00 5-29-70 2.14 0.93 4.00 7.07
36 45.45 12150.00 ) 11-15-70 2.04 1.17 1.80 5.01
36 45.30 121 54.00 5-29-70 00. 2.50 4.51 7.01
36 45.20 121:54.00 5-29-70 2.65 4.26 6.51 13.42
36 45.10 121 52.00 5-29-70 4.48 5.14 4.51 14.13
36 45.10 121 50.00 5-29-70 6.42 8.67 7.01 22.10
36 45.00 121 49.00 2-20-70 3.67 0.40 0.45 4.52
36 44.60 121 50.50 2-20-70 0.52 0.18 0.28 0.98
36 44.25 12150.35 | 11-15-70 0.26 0.19 0.45 0.90
36 44.20 121 52.25 8-23-70 5.20 7.50 | 15.50 28.20
36 44.00 1217 50.00 5-29-70 0.0 0.19 0.35 0.54
36 44.00 121 49.50 2-20-70 0.69 0.14 2.75 3.58
36 43.75 121 54.45 11-15-70 1.02 0.38 0.70 2.10
36 43.50 121 51.80 2-20-70 1.73 2.64 2.40 6.77
36 43.35 121 56.25 8-23-70 1.12 0.25 0.65 2.02
36 43.18 121 57.00 2- 8-70 0.0 5.00 | 20.50 25.50
36 43.00 121 51.00 5-29-70 6.12 1.30 6.01 13.43
36 42.90 121 58.00 2-20-70 0.0 0.35 1.92 2.27
36 42.55 121 53.30 8-23-70 | 13.20 5.73 13.00 31.93
36 42.50 121 50.30 8-23-70 | 19.30 0.65 2.75 22.70
36 41.70 121 55.00 2-20-70 1.22 0.53 2.40 4.15
36 41.55 121 55.50 2- 8-70 0.0 2.35 7.01 9.36
36 41.50 121 52.00 5-29-70 2.85 2.50 |. 8.01 13.36
36 41.00 12151.00 } 11-15-70 0.0 1.61 4,26 5.87
36 40.90 121 56.40 2-20-70 1.32 1.61 9.02 11.95
36 40.50 121 53.50 5-29-70 2.55 1.76 6.76 11.07
36 40.08 121 54.05 2 8-70 0.0 0.82 3.25 4.07
36 39.80 121 54.50 5-29-70 2.04 1.91 5.26 9.21
36 39.80 121 57.50 2- 9-70 0.0 1.42 8.52 9.94
36 39.10 121 53.08 2- 8-70 2.44 0.66 2.40 5.50
36 39.10 121 53,08 2- 8-70 8.67 0.66 3.00 12.33
36 37.95 121 52.50 2-20-70 2.65 2.79 10.00 15.44
36 37.77 121 51.83 2- 8-70 0.49 0.21 0.50 1.20

WYOOWWOWNRNUNRNNYNNNN SSA Saoaeaons
NOANBWNHNAFOODIYDHMRWNSOODYDTMABNS-OWDYHAMAWN=

14


SECTION IV

METHODS

ANALYSIS OF SEDIMENT SAMPLES

Samples of sediment were collected by Shipek grab or shallow dredge. Between 50
and 70 grams of wet sediment were placed in a 250 ml bottle and mixed with 30-50
grams of granular anhydrous sodium sulfate. The sediment was extracted with 50 ml
of acetone:hexane, 1:1, by shaking for four hours. The acetone, hexane was decanted
and filtered through a fritted glass filter or silicon-treated phase separation paper into
a separatory funnel. Three additional 50 ml portions of hexane were used to wash the
sediment and added to the original extractant.

The extract was washed with three 200 ml portions of water followed by dehydration
of the extract by passage through a 2x5 cm column of anhydrous sodium sulfate and
concentration in a Kuderna-Danish concentrator to less than 10 ml. The extract was
then cleaned by shaking first with 1 ml of concentrated sulfuric acid and finally with
approximately 0,1 ml of mercury. The analysis was performed in a Beckman GC-4 Gas
Chromatograph with electron capture detector, using a mixed bed column of Chromo-
sorb W, 80-100 mesh, DMCS treated, and acid washed, containing 5% DC-200 and 5%
QF1.

Although the efficiency of extraction is difficult to assess, the effect of concentration
and clean-up procedures can be measured by the use of 14C labelled materials added
just prior to extraction with acetone, hexane. Recovery was 73.9% for DDT, 94.4%
for DDD, and 84.8% for DDE, and these figures were used to correct the results of
analyses.

LABORATORY DECAY ASSAYS

A variety of preparations have been investigated for their applicability to decay assay
preparations. These preparations have included sealed stationary aliquots of sediment
and 14C labelled substrate as well as ones in which the sediment with labelled substrate
was subjected to continuous percolation or periodic gas flow. Maintenance of percolat-
ing systems for the length of time required to measure the very slow rates of decay is
not feasible, and it is difficult to maintain a large number of preparations under condi-
tions whereby they may be subjected to periodic gas flow and trapping of metabolic CO.
Therefore, sealed stationary preparations have proved to be the only feasible type of
preparation so far developed. The most convenient container for such preparations has
been 125 ml Hypovials, Pierce, Rockford, Illinois, No. 12995, fitted with Teflon liners.
The preparation of decay assays is as follows. Sediment is collected as for samples for
residue analysis, packed in ice, and brought to the laboratory within a few hours. The
sediment is rinsed through screen with 16 mesh to the inch to remove macroscopic in-
fauna and refrigerated. Aliquots of the slurried sediment are removed for dry weight


10

11

12

13

TABLES

Concentration of DDT, DDD, and DDE in sediments
of the Monterey area land drainage system in 1972
(State of Calif., 1974).

Typical decay assay protocol.

Concentrations of DDT, DDD, and DDE in marine sediment
samples from Monterey Bay.

Levels of DDT, DDD, and DDE as percent of total residues
in marine sediment samples from Monterey Bay.

Variance of sampling measured at Station 38.

First page of computer output showing concentration of
pollutant compounds in sediment from sample stations at
first sampling time. Cj identifies as concentrations at time one.

Second page of computer output showing concentration of
pollutant compounds in sediment from sample stations at the

second sampling time. C2 identifies as concentrations at time two.

Third page of computer output showing percent of total of each
of the three compounds in sediments from sample stations at the
first sampling time. Cy identifies as data for time one.

Fourth page of computer output showing percent of total of each
of the three compounds in sediments from sample stations at the
second sampling time. C2 identifies as data for time two.

Fifth page of computer output showing the rate of change, K,
for DDT in each sediment compartment.

Sixth page of computer output showing the rate of change, K,
for DDD in each sediment compartment.

Seventh page of computer output showing the rate of change, K,
for DDE in each sediment compartment.

Eighth page of computer output showing a summary of the
annual system rates expressed as decimal fractions of the mean
concentration of DDT present in the system.

Page

11
14

16

18

25

26

27

28

31
32
33

35


0106

0107
0108
0109
0110
0111
0112
0113

0114

0115
0116

0117
0118

0119
0120

0121
0122
0123
0124
0125
0127
0128
0129
0130

ananaaan

a

aaaaa

DO 19 K=1,ID

DO 19 J=1,1A
V=X(8,J,K)-SUM1(K)/AI
IF (V.GT.0) GO TO 18
X(10,J,K)=V
GOTO 19

18 X(9,],K)=V

19 CONTINUE

COMPUTE SUM AND MEAN FOR K VALUES.

DO 21 K=1,ID

DO 21 I=6,10
V=0.0

DO 20 J=1,1A
20 V=V+X(I,J,K)

TOT(I,K)=V
21 M(I,K)=V/AI

CALCUALTE STANDARD DEVIATION, STANDARD ERROR, AND 95% CONFIDE:
LIMITS OF K VALUES.

DO 22 K=1,ID
SUM 1 (K)=0.0
SUM 2 (K)=0.0
SUM 3 (K)=0.0
22 SUM 4 (K)=0.0
DO 23 J=1,IA
V2(J,K)=DLOG(X(2,J,K))—DLOG(X(1,J,K))
SUM2(K)=V2(J,K)+SUM2(K)
SUM 3 (K)=(DLOG(X(1,J,K))—ALOG(M(1,K))) **2+SUM3(K)


—
KM

Uo

ae FATHOMS

200

Figure 2. DDT as a percent of the total concentration of DDT, DDD, and DDE plotted for data
obtained in 1970 and 1971. Circled numbers indicate actual percents in excess of 50%.

19


\SAN LORENZO

KM

N
WATSONVILLE
‘50 FATHOMS
100
SLOUGH
CASTROVILLE
TREMBLADERO
SLOUGH

GROVE ¥.- SEASIDE
MONTEREY

= CARMEL RIVER

Figure 1. The study area, Monterey Bay. Sampling stations are indicated by number.

5


ANALYSIS OF DYNAMICS

An approach to the analysis of the dynamics of sediment systems has been developed
and has led to the development of Fortran programs permitting the rapid evaluation of
data. The discussion of the approach to analysis will refer to output from these programs.
The programs themselves with explanatory documentation are to be found in an appen-
dix at the end of this report.

The first program requires sampling at the same set of stations at two points in time.
The residue levels measured in sediments from the 19 stations sampled in both 1970
and 1973 constitute the data set used by this program. These data are presented as the
first two pages of output, see Tables 6 and 7, followed by two pages showing the per-
cent composition of total derivatives, see Tables 8 and 9. From the sums and means in
Tables 6 and 7 it would appear that while DDT has shown an increase of several-fold
the concentrations of DDD and DDE have changed very little. With respect to these
latter two compounds input must be rather closely balanced with respect to output
and decay. The changes in levels detected at individual stations must be a reflection

of the rates of input of new material, output or removal both geographically and into
other parts of the ecosystem, decay or decomposition within the sediment, and finally
a shifting about of the material from sampling station to sampling station due primarily
to the action of currents. The obvious complexity of the effect of these various rates
has made the analysis of such a system extremely difficult. The approach presented
here has necessitated the making of several simplifying assumptions. The utility of the
method and the validity of the assumptions must await further evaluation, and the
approach is intended more as a beginning than a final answer to the needs for methods
of data analysis.

Figure 7 presents a diagram of the essential features of the system as it is envisaged.
The individual stations where sediment samples were obtained are considered as com-
partments within the system of sediments in the southern portion of Monterey Bay.
The diagram indicates that this system has a relationship to all other systems both
geographical and of other kinds where the three compounds occur. Systems of dif-
ferent kinds would include the water above the sediment, the atmosphere above the
water, organisms, etc. The effect of the rate of input, I, the rate of output, O, the rate
of decay, D, and the rates of internal translocation, Tj and To, on the concentration
within the system and within compartments is indicated.

A comparison of Figures 5 and 6 suggests that with continued input areas with the
higher concentrations tend to increase in concentration due to the movement of the
compounds within the system to these sinks or basins. Therefore, the amount of in-
crease within any sediment compartment would appear to be related to the concen-
tration already existing in that compartment. A similar relationship between the
amount of decrease and concentration is less easily deduced from these Figures.
However, the results of laboratory assays to be discussed in a later section have not
revealed either a saturation of the decay process nor a stimulation by induction and
selection of microbial populations that can be related to the concentration of these
compounds. Instead the amount of decomposition appears to be a function of con-
centration. That the amount of translocation would be similarly related to concen-
tration seems apparent.

24


0073 DO 11 K=1,ID

on74 X(5,1J,K)=YR
0075 11 CONTINUE
c
0076 12 CONTINUE
Cc
0077 13 CONTINUE
Cc
0078 RETURN
0079 END
Cc
Cc
0001 SUBROUTINE LEAPYR (J,IMON,IDAY YR)
0002 DIMENSION TABLE(30), MONTH(12), ALOC(2,60,6), TOT(10,8), STD(23,8)
1,STE(23,8), CL95(23,8), [A(2), Al(2)
0003 REAL *4MEAN, M(17,8)
0004 REAL *8X(10,60,7),NAME(23)
0005 INTEGER YR1,YR2,DA1,DA2,DAYS
0006 INTEGER CST(2,60),CDATE(2,60,3) ;
0007 COMMON /BLK1/ NAME,TOT M,STD,STE,CL95,ALOC,YR,CST,CDATE MONTH, L1,L
0008 COMMON X,TABLE,IA,IB,1,K,KD,ID
0009 DAYS=0
0010 NT=0
0011 IF (1.EQ.2) GO TO 1
0012 MO1=IMON
0013 DA1=IDAY
0014 YRI=IYR
_ 0015 MO2=CDATE(2,J,1)
0016 DA2=CDATE(2,J,2)
0017 YR2=CDATE(2,J,3)
0018 GOTO2
0019 1 MO2=IMON
0020 DA2=IDAY
0021 YR2=IYR
0022 MO1=CDATE(1,J,1)
0023 DA1=CDATE(1,J,2)
0024 YR1=CDATE(1,J,3)
0025 2 AMO=MO1
Cc
0026 DO 6 1Y=YR1,YR2
0027 A=IY
0028 LEAP=0
0029 IZ=A/4.
0030 ZeIZ
0031 Z=Z*4.
0032 IF (IY.EQ.YR1) GO TO 3
0033 GOTO4

93


0237 57 FORMAT (27X,‘T’/)

0238 WRITE (6,58) NAME(K),M(10,K),STD(10,K),STE(10,K),CL95(10,K)
0239 58 FORMAT (2X,‘MEAN OF - ( K - NET ) = T’,5X,A8,'=’,3X,4F 11.4)
0240 WRITE (6,59)
0241 59 FORMAT (27X,‘0/)
0242 WRITE (6,60) NAME(K),M(6,K),STD(6,K),STE(6,K),CL95(6,K)
0243 60 FORMAT (2X,‘MEAN OF + K’,11X,‘= I’,5X,A8,‘=",3X,4F11.4//)
0244 WRITE (6,61) NAME(K),M(7,K),STD(7,K),STE(7,K),CL95(7,K)
0245 61 FORMAT (2X,‘MEAN OF - K’,11X,'= O + D’,1X,A8,‘=’,3X,4F11.4//)
0246 * WRITE (6,62) NAME(K),M(11,K),STD(11,K),STE(11,K),CL95(11,K)
0247 62 FORMAT (26X,'0’,5X,A8,‘=’,3X,4F11.4/)
0248 WRITE (6,63) NAME(K),M(12,K),STD(12,K),STE(12,K),CL95(12,K)
0249 63 FORMAT (26X,'D’,5X,A8,‘=",3X,4F11.4/)
0250 WRITE (6,64) NAME(K),M(13,K),STD(13,K),STE(13,K),CL95(13,K)
0251 64 FORMAT (26X,'T’,5X,A8,'=’,3X,4F 11.4)
0252 WRITE(6,65)
0253 65 FORMAT(27X,‘L"/)
0254 WRITE(6,64) NAME(K),M(14,K),STD(14,K),STE(14,K),CL95(14,K)
0255 WRITE(6,66)
0256 66 FORMAT(27X,'R’)
0257 DO 67 L=1,3
0258 67 WRITE(6,13)
0259 WRITE(6,68)
0260 68 FORMAT(13X,‘MEAN C’,6X,'MEAN C’,16X,‘I’,10X,'T’,6X,'",4X,'T’,6X,
“,5X,'0",5X,"~',5X,'D’,9X,'N'/19X, ‘2’, 11X,‘1",27X,'1,11X,'0/)
0261 69 FORMAT(/97X,F11.4)
0262 WRITE(6,69) _M(5,K)
0263 WRITE(6,70) NAME(K),M(2,K),M(1,K),M(6,K),M(9,K),M(10,K),M(11,K),
-M(12,K)
0264 70 FORMAT(2X,A8,F10.4,' =’,F10.4,‘ (1.0 +,F10.4, +’,F10.4,3(F12.4)
ee)
0265 71 CONTINUE
0266 CALL FACTOR
0267 STOP
0268 END
Cc
Cc
0001 SUBROUTINE PRINT
0002 DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6),TOT(10,8),STD(23,8).
1, STE (23,8),CL95(23,8),1A(2),Al(2)
0003 REAL *4MEAN,M(17,8)
0004 REAL *8X(10,60,7),V2(60,7),NAME(23),V1(7)
0005 INTEGER CST(2,60),CDATE(2,60,3)
0006 COMMON X,TABLE,IA,IB,1,K,KD,ID
0007 COMMON /BLK1/ NAME, TOT M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,1
c

86


Table 1. CONCENTRATION OF DDT, DDD, AND DDE IN SEDIMENTS OF THE
MONTEREY AREA LAND DRAINAGE SYSTEM IN 1972 (STATE OF

CALIF., 1974)
Salinas River
distance from mouth {ppb)
(kilometers) DDT ODD DDE
42 1.0 1.3
25 120. + 20.
8 150. 1000. 360.
16. 620.
3 0.12 30.
Reclamation Canal
distance from mouth
lof Elkhorn Slough
(kilometers)
20 7,000. 45,000. 10,000.
21,000. 150,000.



0040 DO 2 L=1,K

0041 2 ITOTDA(I)=ITOTDA(I)YRVAL(L)
c :
C SUM ALL DAYS OF YEARS INVOLVED
0042 ITOTDA(I)=ITOTDA(I)-INT1-LAST2
0043 SUMDA(I)=SUMDA(I)+ITOTDA()
0044 GOTO4
0045 3 INT2=MONTH(MO2)HDA2
0046 ITOTDA(1)=INT2-INT1
0047 SUMDA(I)-SUMDA(I)+ITOTDA(I)
0048 4 CONTINUE
Cc
C COMPUTE MEAN OF TIME
0049 MEANT=SUMDA(I)/IA(1)
C SUBTRACT FIRST YEAR
0050 IX=MEANT+INT1
0051 IF (K.EQ.0) GO TO7
Cc
0052 DO 5 L=1,K
0053 IF (IX.LT.IYRVAL(L)) GO TO 6
0054 IF (IX.EQ.IYRVAL(L)) TO TO 6
0055 IX=IX-IYRVAL(L)
0056 5 CONTINUE
Cc
C ‘COMPUTE YEAR
0057 6 IYR=L-14+1YR1
0058 IF (IYRVAL(L).EQ.366.AND.IX.GT.59) IX=IX-1
0059 GO TO8
0060 7 IF (IYRVAL(1).EQ.366.AND.IX.GT.59) IX=IX-1
0061 IYR=CDATE(I,1,3)
c
0062 8 DO 9 N=1,12
C LOCATE MONTH
0063 IF (IX.LT.MONTH(N+1)) GO TO 10
0064 IF (IX.EQ.MONTH(N)) GO TO 10
0065 9 CONTINUE
c
0066 10 IMON=N
0067 IDAY=1X-MONTH(N)
0068 IF (.EQ.1) IC=1A(2)
0069 IF (1.EQ.2) IC=IA(1)
Cc
0070 DO 12 J=1,IC
0071 W=lj+1
0072 CALL LEAPYR (J,IMON,IDAY,IYR)
Cc

92


0056 W=W/(A13—1.0)

Cc
Cc STD(18,K) IS CORRECTED STD (9,K)
Cc
0057 STD(18,K)=SQRT((V/(V+W))**2*C*(STD(8,K)**2))
0058 CALL STDEV2 (STD(18,K),STE(18,K),CL95(18,K))
Cc
Cc
Cc STD(19,K) IS CORRECTED STD(10,K)
Cc
0059 STD(19,K)=SQRT((W/(V+W))**2*C*(STD(8,K)**2))
0060 CALL STDEV2 (STD(19,K),STE(19,K),CL95(19,K))
Cc
Cc CALCULATE CORRECTED STD(20,K) CORRECTED STD(11,K)
Cc
0061 STD(20,K)=SQRT(STD(16,K)**2*(M(9,K)/M(6,K))**2)
Cc
Cc
0062 CALL STDEV2 (STD(20,K),STE(20,K),CL95(20,K))
Cc CALCULATE STD(21,K) CORRECTED STD(12,K)
0063 STD(21,K)=SQRT(STD(16,K)**2*(1.0—M(9,K)/M(6,K))**2)
0064 CALL STDEV2 (STD(21,K),STE(21,K),CL95(21,K))
Cc
Cc CALCULATE STD(22,K) CORRECTED STD(13,K)
Cc
0065 STD(22,K)=SQRT(STD(21,K)**2*(1.0/M(12,K)**2)**2)
0066 CALL STDEV2 (STD(22,K),STE(22,K),CL95(22,K))
Cc
Cc CALCULATE STD(23,K) CORRECTED STD(14,K)
Cc
0067 STD(23,K)=SQRT(STD(16,K)* *2*(1.0/M(7,K)**2)**2)
0068 CALL STDEV2 (STD(23,K),STE(23,K),CL95(23,K))
Cc
Cc
0069 14 CONTINUE
Cc
Cc
0070 DO 15 K=1,ID
Cc
0071 WRITE (6,16) NAME(K)
0072 WRITE (6,17) NAME(K),M(8,K),STD(17,K),STE(17,K),CL95(17,K)
0073 WRITE (6,18) NAME(K),M(9,K),STD(18,K),STE(18,K),CL95(18,K)
0074 WRITE (6,19)
0075 WRITE (6,20) NAME(K),M(10,K),STD(19,K),STE(19,K),CL95(19,K)
0076 WRITE (6,21) .
0077 WRITE (6,22) NAME(K),M(6,K),STD(15,K),STE(15,K),CL95(15,K)
0078 WRITE (6,23) NAME(K),M(7,K),STD(16,K),STE(16,K),CL95(16,K)

97


0001

0002
0003
0004
0005
0006
0006
0007
0008
0009

0010
0011
0012
0013
0014
0015

0016

0017

0018
0019

0020

0021

Cc
Cc

aNANAAAANAN

aaa

PROGRAM FOR ESTIMATING SYSTEM RATES BASED ON
REAL PAIRED SAMPLE VALUES.

DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8),VAR1(7), VAR2(7),VAR3(7),SUM1(7),SUM2(
27),SUM3(7),SUM4(7),COV1(7),COV2(7)

REAL *4MEAN,MR(7),M(17,8)

REAL *8X(10,60,7),V2(60,7),NAME(23),V1(7)

INTEGER CST(2,60),CDATE(2,60,3)

COMMON X, TABLE,JA,I,K,KD,ID

COMMON/BLK1/NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1,L

COMMON/BLK2/MR

READ (5,45) TABLE

READ (5,46) MONTH

READ (5,47) IA,ID

CALCULATE INDEXES.

Al NUMBER OF STATIONS CONVERTED TO A REAL NUMBER
IP1 ID+1

IP2 ID+2

I2TP2 2*ID+2

I2TP3 2*ID+3

13TP2 3*ID+2

AI=IA

IP1=ID+1

IP2=ID+2

12TP2=2*ID+2
12TP3=2*1D+3
13TP2=3*ID+2
CLEAR X ARRAY.
DO 1 I=1,10

DO 1J=1,1A

DO 1 K=1,IP1
1 X(1,J,K)=0.0

WRITE (6,50)

READ IN DERIVATIVE NAMES AND CONCENTRATION LEVEL ON UP TO 3 CAR
READ (5,48) NAME

READ IN DATA.

60


0157 STD(6,K)=SQRT(V)

0158 W=STD(8,K)**2*(W/U)**2
0159 STD(7,K)=SQRT(W)
0160 CALL STDEV2(STD(6,K),STE(6,K),CL95(6,K))
0160 30 CALL STDEV2 (STD(7,K),STE(7,K),CL95(7,K))
Cc
Cc
C CALCULATION OF STANDARD DEVIATION K-NET AND ITS DISTRIBUTION.
Cc
c
Cc
0161 DO 35 K=1,ID
0161 V=0.0
0162 . W=0.0
0163 DO 34 J=1,1A
0164 IF(X(9,J,K)) 32,32,31
0165 31 V=V+(X(9,J,K)**2)
0166 32 IF(X(10,J,K)) 33,34,34
0167 33 W=W+(X(10,J,K)**2)
0168 34 CONTINUE
Cc
Cc
0169 V=V(AI-1.0)
0170 W=W/(AI-1.0)
0171 STD(9,K)=SQRT((V/(V+W))**2*(STD(8,K)**2))
0172 CALL STDEV2(STD(9,K),STE(9,K),CL95(9,K))
0173 STD(10,K)=SQRT((W/(V+W))**2*(STD(8,K)**2))
0174 35 CALL STDEV2(STD(10,K),STE(10,K),CL95(10,K))
Cc
Cc
Cc
0175 CALL PRINT3
Cc
CALCULATE 0 AND ITS STANDARD DEVIATION
c
0176 DO 41 K=1,ID
0177 M(11,K)=(M(9,K)/M(6,K))*M(7,K)
0178 STD(11,K)=SQRT(STD(7,K)**2*((M(9,K)/M(6,K))**2))
0179 CALL STDEV2(STD(11,K),STE(11,K),CL95(11,K))
c
Cc
Cc
c
C CALCULATION OF D
Cc

66


Table 2. TYPICAL DECAY ASSAY PROTOCOL.

f=
Seawater
Hypovial plus 12¢ 14¢ Total Total
No. Slurried Sediment} nutrients} Substrate | Substrate {Substrate | volume
(grams) (ml) (ml) | (ug) (mt) (ug) _(mt)|__ (ppm) (ml)
1-5 24 59 39 2400 1 2.4 1 100 100
6-10 24 59 39 240 1 24 1 10 100
11-15 24 59 39° 21.6] 1 2.4 1 1 100
16-20 24 59 39 0 0 2.4 1 0.1 100
21-25 24 59 39 0 0 0.24 1 0.01 100

11



0034
0035
0036
0037
0038
0039

0040
0041
0042
0043
0044
0045
0046

3 DAYS=365-MONTH(MO1)+DA1)
IF (Z.EQ.A.AND.AMO.LT.3.) LEAP=1
GOTO 5

4 IF (Z.EQ.A) LEAP=1

5 NT=DAYS+LEAP+NT

6 DAYS=365

IF (LEAP.EQ.1) GO TO 7
GO TO 8
7 IF (MO2.LT.3) NT=NT-1
8 YR=NT-365+MONTH(MO2)+DA2
YR=YR/365.
RETURN
END

94


Table 4. LEVELS OF DDT, DDD, AND DDE AS PERCENT OF TOTAL RESIDUES IN

MARINE SEDIMENT SAMPLES FROM MONTEREY BAY.

LOCATION ODT DDD DDE
Station Latitude Longitude Date (%) (%) (%)
1 36 47.25 121 48.90 8-23-70 46.99 20.63 32.38
2 36 46.85 121 53.50 11-15-70 7.06 29.28 63.66
3 36 46.35 121 49.00 2-20-70 76.75 9.54 13.71
4 36 46.05 121 51.00 11-15-70 19.82 30.62 49.56
5 36 46.00 121 57.00 5-29-70 30.27 13.15 56.58
6 36 45.45 121 50.00 11-15-70 40.72 23.35 35.93
7 36 45.30 121 54.00 5-29-70 0.0 35.66 64.34
8 36 45.20 121 54.00 5-29-70 19.75 31.74 48.51 |
9 36 45.10 121 52.00 5-29-70 31.71 36.38 31.92
10 36 45.20 121 50.00 5-29-70 29.05 39.23 31.72
11 36 45.00 121 49.00 2-20-70 81.19 8.85 9.96
12 36 44.60 121 50.50 2-20-70 53.06 18.37 28.57
13 36 44.25 121 50.35 11-15-70 28.89 21.11 50.00
14 36 44.20 121 52.25 8-23-70 18.44 26.60 54.96
15 36 44.00 121 50.00 5-29-70 0.0 35.19 64.81
16 36 44.00 121 49.50 2-20-70 19.27 3.91 76.82
17 36 43.75 121 54.45 11-15-70 48.57 18.10 33.33
18 36 43.50 121 51.80 2-20-70 25.55 39.00 35.45
19 36 43.35 121 56.25 8-23-70 55.45 12.38 32.18
20 36 43.18 121 57.00 2- 8-70 0.0 19.61 80.39
21 36 43.00 121 51.00 5-29-70 45.57 9.68 44.75
22 36 42.90 121 58.00 2-20-70 0.0 15.42 84.58
23 36 42.55 121 53.30 8-23-70 41.34 17.95 40.71
24 36 42.50 121 50.30 8-23-70 85.02 2.86 12.11
25 36 41.70 121 55.00 2-20-70 29.40 12.77 57.83
26 36 41.55 121 55.50 2- 8-70 0.0 25.11 * 74.89
27 36 41.50 121 52.00 5-29-70 21.33 18.71 59.96
28 36 41.00 121 51.00 11-15-70 0.0 27.43 72.57
29 36 40.90 121 56.40 2-20-70 11.05 13.47 75.48
30 36 40.50 121 53.50 5-29-70 23.04 15.90 61.07
31 36 40.08 121 54.05 2. 8-70 0.0 20.15 79.85
32 36 39.80 121 54.50 5-29-70 22.15 20.74 57.11
33 36 39.80 121 51.50 2- 9-70 0.0 14.29 85.71
34 36 39.10 121 53.08 2. 8-70 44.36 12.00 43.64
35 36 39.10 121 53.08 2- 870 70.32 5.35 24.33
36 36 37.95 121 52.50 2-20-70 17.16 18.07 64.77
37 36 37.77 121 51.83 2- 8-70 40.83 17.50 41.67

16



DDT obtained from the four data sets did show some significant differences when
compared using these corrected estimates of the standard deviation. The estimates
obtained with the 49 and 57 sample sets were significantly different at the .05 level
for Net, I, To, and Ty. The estimates obtained with the 16 and 57 sample sets were
significantly different for Net, I, and To, and the estimates of To for the 19 and 57
data sets were also significantly different. These differences would appear to be
primarily the result of inclusion or exclusion from the system of sites where there are
major increases in the concentration of DDT rather than the effect of substitution of
a minimal value for the concentration at time one. The estimation of Tg in systems
showing a positive Net rate of change are particularly sensitive to significance testing
due to their relatively low standard deviations that result from the distribution of
variance between T] and Tg.

If we keep in mind the limitations imposed by the variability of the data, the estimates
can be used to gain a picture of the flux of these pollutants in the study area. The area
of south Monterey Bay is approximately 280 square kilometers, or 69,190 acres in size.
The density of the sediments on a dry weight basis averages 1.32 grams per cm3. Table
20 gives the mean of the estimates for system concentrations and rates that were ob-
tained by the two approaches to analysis and the four data sets. Standard deviations,
standard errors, 95% confidence limits, and coefficients of variation for these means are
included. These latter descriptive statistics refer only to the variation of the estimates
and do not include the effect of compartment variability discussed above.

Table 21 uses the mean of the estimates and gives the total amounts of these chlorinated
hydrocarbons in the area and the.concentration in pounds per acre based upon the mean
concentrations at the two times of sampling. These total amounts are estimated as being
present in the top 10 cm of sediment, a depth generally sampled with the collecting gear
used. Considering that the usual level of application on land is 2 pounds to the acre the
total level of these compounds per acre has reached somewhat more than 1/100 of the
land applications level.

The estimated annual rates of input, I, as seen in Table 20, average 130% for DDT, 25%
for DDD, and 28% for DDE. The corresponding amounts of these materials expected in
the next year are indicated in Table 21. Expected loss due to translocation, output, and
decay based on the estimated annual rates, O+D, 10% for DDT, 13% for DDD, and 13%
for DDE, are also shown. The resulting net effect for the year period following the last
sample time in 1973 gives the expected values shown, Table 21. The expected change in
the amount of the total chlorinated hydrocarbons derived from DDT amounts to an in-
crease of 182%. The amounts translocated within the system are presented in Table 21
along with a separation of the expected loss into that expected from output and decay.
All of the projections, of course, assume that the estimated rates reflecting flux of these
materials in the past three years will persist for the next year period.

The K values for the individual compartments can also be used to present a composite

view of the translocation of the three compounds within the system and principal points

of geographical exit. The stations at their geographical location are connected with arrows
45


0001 SUBROUTINE STDEV (SUMX,XBAR,STD,STE,CL$)

0002 REAL *8X(10,60,7)
0003 DIMENSION TABLE(30), IA(2), AI(2)
0004 COMMON X,TABLEJA,IB,K,KD,ID
0005 DEV=0.
0006 SUMX=0.
Cc
0007 DO 1 J=1,1B
0008 1 SUMX=SUMX+X(I,J,K)
Cc
0009 AI(I)=IA(I)
0010 XBAR=SUMX/AI(I)
Cc
0011 DO 2 J=1,1B
0012 DEV=(XBAR-X(I,J,K))**2+DEV
0013 2 CONTINUE
Cc
0014 STD=SQRT(DEV/AK(1)-1.))
0015 STE=STD/SQRT(AI(1))
0016 KA=IB
0017 CALL TDIST (KA,T)
0018 CL$=T*STE
0019 END
Cc
Cc
0001 SUBROUTINE STDEV2 (STD,STE,CL$)
0002 REAL *8X(10,60,7)
0003 DIMENSION TABLE(30), [A(2), AI(2)-
0004 COMMON X,TABLE,IA,IB,1,K,KD,ID
0005 AI3=1A(1)41A(2)
0006 STE-STD/SQRT(AI3)
0007 KA=IA(1)+1A(2)
0008 CALL TDIST (KA,T)
0009 CL$=T*STE
0010 RETURN
0011 END
Cc
Cc
0001 SUBROUTINE NCOMP
0002 DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6), TOT(10,8),STD(23,8)
1, STE(23,8),CL95(23,8),1A(2), AI(2)
0003 DIMENSION IYRVAL(5),ITOTDA(5)
0003 REAL *4M(17,8)
0004 REAL *8X(10,60,7),NAME(23)
0005 INTEGER CST(2,60),CDATE(2,60,3)
0006 INTEGER SUMDA(2)
0007 COMMON X,TABLE,IA,IB,I,K,KD,ID
0008 COMMON /BLK1/ NAME, TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1
0009 1J=0

90


Table 9. FOURTH PAGE OF COMPUTER OUTPUT SHOWING PERCENT OF TOTAL
OF EACH‘OF THE THREE COMPOUNDS IN SEDIMENT FROM SAMPLE
STATIONS AT THE SECOND SAMPLING TIME. Co IDENTIFIES AS DATA

FOR TIME TWO.
C2
— —
LOCATION DDT DDD DDE
Station | Latitude Longitude Date (%) (%) (%)

1 36 47.25 121 48.90 7- 9-73 49.30 24.65 26.05
2 36 46.85 121 53.50 7- 973 24.74 29.69 45.57
3 36 46.35 121 49.00 7- 9-73 48.67 23.45 27.88
4 36 46.05 121 51.00 7- 9-73 22.73 34.00 43.27
10 36 45.10 121 50.00 7- 2-73 50.27 21.31 28.42
11 36 45.00 121 49.00 7- 2-73 58.45 19.30 22.25
14 36 44.20 121 52.25 6-21-73 63.92 12.68 23.40
16 36 44.00 121 49.50 7- 2-73 76.80 4.80 18.40
17 36 43.75 121 54.45 8- 9-73 19.85 16.66 63.49
19 36 43.35 121 56.25 8- 9-73 82.72 3.63 13.65
20 36 43.18 121 57.00 6-21-73 93.66 1.17 5.17
22 36 42.90 121 58.00 8- 9-73 11.79 11.41 76.81
23 36 42.55 121 53.30 6-21-73 64.41 9.31 26.28
25 36 41.70 121 55.00 7-16-73 7.93 19.07 73.00
26 36 41.55 121 55.50 7-16-73 5.89 19.05 75.06
29 36 40.90 121 56.40 7-16-73 9.36 14.84 75.80
34 36 39.10 121 53.08 8- 9-73 29.21 10.40 60.40
36 36 37.95 121 52.50 6-21-73 95.09 1.09 3.82
37 36 37.77 121 51.83 7-16-73 47.37 17.54 35.09

TOTALS 862.1616 294.0427 743.7920

Mean 45.3769 15.4759 39.1469

Standard Deviation + 29.2068 + 9.2122 + 24.6220

Standard Error + 6.7005 + 2.1134 + 5.6487

95% Confidence Limits + 14.0777 + 4.4403 + 11.8679

28



measurement were also made. The amount of l4co, was determined in a Nuclear
Chicago Corp. Unilux II. Diffusion time and trapping volume of B-phenylethylamine
were established through tests using a standard preparation of Na Mco3.

DECAY AS AFFECTED BY ENVIRONMENTAL VARIABLES

The effect of temperature was determined by comparing the amount of decomposition
at 10° and 20°C, and the effect of oxygen, nitrate, and sulfate as terminal electron ac-
ceptors in the presence and absence of cometabolizable sodium acetate and ethanol was
determined by appropriate additions to the Hypovials.

12


The addition of sodium acetate as an extra electron donor under aerobic conditions was

inhibitory to the aerobic decay process. However, since there was hydrogen sulfate pro-

duced in these preparations the inhibition may have been due to the competition for the
available oxygen and the production of anaerobic conditions.

In summary, decay to CO? appears to be primarily due to the activity of aerobic micro-
organisms. The process attains the greatest rate where there is no unusual competition for
oxygen. Since the known mechanisms for splitting aromatic rings involve the addition of
oxygen to the aromatic nucleus prior to splitting, these observations are not unexpected.
However, some considerable activity remains under anaerobic conditions even where an
additional oxidizable substrate such as sodium acetate or ethanol is present to remove
any traces of residual oxygen. The results also indicate that nitrate and sulfate may be
acceptable electron acceptors in the oxidation of aromatic compounds under anaerobic
conditions. The mechanisms for anaerobic ring split have not been elucidated. Finally,
The Qj for the decay process under aerobic conditions presents no surprise as to its
magnitude.

A comparison of the Deco, for DDT, DDD, and DDE reveals a similar relationship to the
total decay rates, D, estimated for South Monterey Bay in that DppT,cO, > DDDE,CO2>

DppD, CO, just as DppT > PppE >Dppp- See Table 24.

For purposes of analysis the process of decay can be divided into a series of steps as follows,

D D,

pot 2 its 2S ws 2 co,
D D

ppp E> ts YS ws 25% co,

D, Dy
DoE —%s 1s 28S, ws 92 coy

where LS represents lipid soluble degradation products of the starting compound and WS
represents water soluble degradation products of the starting compound.

Water soluble degradation products were measured as water soluble !4C after high speed
centrifugation of samples from the initial preparations followed by acidification to remove
14¢co.

2°

Dws values presented in Table 24 are based on the sum of the 14¢ present in water solu-
ble form plus that present as 14CO4. Attempts at determining the amount of lipid soluble
degradation products were unsuccessful. The high levels of the starting compound still
present in the preparations made quantification by gas chromatography difficult. Thin
layer chromatography was more successful but revealed that the sodium hydroxide added
to stop further biological breakdown and to absorb 14CO2 from the gas phase caused
conversion of a considerable amount of the DDT to DDD.

While laboratory assays of decay rate have revealed rates compatible with the field esti-
mation, it has not been possible to use this approach for full appraisal of the method of

56


14

15

16

17

18

19

20

21

22

23

24

Ninth page of computer output showing a summary of the
annual system rates expressed as decimal fractions of the mean
concentration of DDD present in the system.

Tenth page of computer output showing a summary of the
annual system rates expressed as decimal fractions of the mean
concentration of DDE present in the system.

Comparison of estimates obtained from the 16 and 19 station
data sets and using actual paired sample analyses. Standard
deviations and coefficients of variation are included.

Comparison of estimates obtained from 49 and 57 station
data sets and using sample analyses paired with mean concentration
levels. Standard deviations and coefficients of variation are included.

Standard deviations and standard errors of distributions of K
with minimal variance for given values of I, Tj and To, (O+D),
and n.

Comparison of uncorrected and corrected standard deviations of
system estimates.

Mean of the estimates for the South Monterey Bay system and
associated descriptive statistics.

Total amounts of DDT, DDD, and DDE in the South Monterey
Bay study area based on the mean concentrations at the two
sample times, and expected amounts affected by the mean of the
estimates of system rates.

Results of a laboratory assay of annual rate of decay of DDT to CO,
Deo: expressed as a decimal fraction of the initial concentration
of DDT maintained at 10°C under aerobic conditions.

Results of laboratory assays of the annual rates of decay to CO2,
Dcop: and the effect of environmental variables on the process.

Rates of decay to water soluble compounds and CO2 determined
by laboratory assays.

i)
bs
iB

37

38

40

43

47

48

51

52

55


0007
0008
0009
0010
0011
0012
0013
0014

0015
0016

0017
0018

0019
0020
0021

0022
0023
0024
0025
0026
0027
0028
0029
0030
0031
0032
0033
0034
0035
0036
0037
0038

0039
0040

0041
0042
0043
0044
0045
0046

COMMON /BLK1i/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE ,MONTH,L1,L
DO 19 K=1,ID

WRITE (6,3)

WRITE (6,4)

WRITE (6,5) NAME(K),NAME(K)

WRITE (6,6)

WRITE (6,7)

IB=IA(2)

DO 1 J=1,1B
1 WRITE (6,17) CST(2,J),X(2,J,K),X(5,J,K),(X(IX,J,K),IX=6,10)

JPIA=IA(2)
IB=1A(1)

DO 2 J=1,1B
JPIA=JPIA+1
2 WRITE (6,18) CST(1,J),X(1,J,K),X(5,JPIA,K),(X(IX,JPIA,K),IX=6,10)

WRITE (6,7)
WRITE (6,16) TOT(2,K), TOT(1,K),TOT(5,1),(TOT(N,K),N=6,10)
WRITE (6,15)

WRITE (6,13) NAME(K)

WRITE (6,16) M(2,K),M(1,K),M(5,1),(M(N,K),N=6,10)

WRITE (6,8)

WRITE (6,13) NAME(K)

WRITE (6,16) STD(2,K),STD(1,K),STD(5,1),(STD(N,K),N=6,10)
WRITE (6,9)

WRITE (6,12) NAME(K)

WRITE (6,16) STE(2,K),STE(1,K),STE(5,1),(STE(N,K),N=6,10)
WRITE (6,10)

WRITE (6,12) NAME(K)

WRITE (6,16) CL95(2,K),CL95(1,K),CL95(5,1),(CL95(N,K),N=6,10)
WRITE (6,11)

19 WRITE (6,14) NAME(K)

RETURN

3 FORMAT (‘1’,1X,‘STATION’)

4 FORMAT (12X,‘C’,9X,‘C’,11X,‘N’,8X,‘+ K’,7X,‘- K’,6X,‘+K + -K’,
1 4X,‘+K - NET’ 3X,‘-K - NET’)

5 FORMAT (‘+’,15X,A8,2X,A8)

6 FORMAT (13X,'‘2’,9X,‘1’,52X,‘R’,10X,'R’/)

7 FORMAT (/) .

8 FORMAT (‘+’,94X,‘MEANS’)

9 FORMAT (‘+’,94X,'S.D.’)

10 FORMAT (‘+’,94X,‘S.E.’)

88


Table 12. SEVENTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,
FOR DDE IN EACH SEDIMENT COMPARTMENT.

Station | Cp DDE | C, DDE N +K -K t+K+-K | +K-Net | -K- Net
R R
1 0.56 5.76 2.8795 0.0 -0,.5549 -0.5549 0.0 -0.6726
2 17.50 | 14.70 2.6493 0.0680 0.0 0.0680 0.0 -0.0497
3 0.63 1.02 3.3836 0.0 -0,1327 -0.1327 0.0 -0.2505
4 6.91 10.70 2.6493 0.0 -0.1522 -0.1522 0.0 -0.2699
10 0.52 7.01 3.0959 0.0 -0.5684 -0.5684 0.0 -0.6861
11 0.83 0.45 3.3644 0.1996 0.0 0.1996 0.0818 0.0
14 11.20 | 15.50 2.8301 0.0 -0.1085 -0.1085 0.0 -0.2262
16 0.23 2.75 3.3644 0.0 -0.5217 0.5217 0.0 -0.6394
17 17.30 0.70 2.7342 2.2318 0.0 2.2318 2.1141 0.0
19 12.00 0.65 2.9644 1.6740 0.0 1.6740 1.5563 0.0
20 3.48 | 20.50 3.3671 0.0 -0.4094 -0.4094 0.0 -0.5272
22 6.06 1.92 3.4685 0.3929 0.0 0.3929 0.2752 0.0
23 12.20 | 13.00 2.8301 0.0 -0.0222 -0.0222 0.0 -0.1399
25 10.49 2.40 3.4027 0.5426 0.0 0.5426 0.4249 0.0
26 8.67 7.01 3.4356 0.0638 0.0 0.0638 0.0 -0.0539
29 5.67 9.02 3.4027 0.0 -0.1275 -0.1275 0.0 -0,2453
34 2.44 2.40 3.5014 0.0047 0.0 0.0047 0.0 -0.1130
36 3.34 | 10.00 3.3342 0.0 -0.2803 -0.2803 0.0 -0.3980
37 0.40 0.50 3.4356 0.0 -0.0629 -0,0629 0.0 -0,.1806
Totals 120.4299 125.9899 60.0930 5.1774 -2.9407 2.2367 4.4522 -4.4522
Mean 6.3384 6.6310 3.1628 0.2725 -0.1548 0.1177 0.2343 -0.2343
S.D. + 5.7417 +6.0673 +0.3100 +0.7781, +0.2243 +1.0024 +0.7761 +0.2262
S.E. + 1.3172 + 1.3919 +0.0711 +0.1785 +0.0515 +0.2300 +0.1781 + 0.0519
95% C.L. + 2.7675 + 2.9245 +0.1494 + 0.3750 + 0.1081 +0.4831 +0.3741 + 0.1091

33


Cc SUBROUTINE FOR PROGRAM FOR ESTIMATING SYSTEM RATES
Cc BASED ON SAMPLE VALUES PAIRED TO MEAN VALUES.

SUBROUTINE FACTOR

0001 DIMENSION TABLE(30), MONTH(12), ALOC(2,60,6), TOT(10,8), STD(23,8)
0002 1, STE(23,8), CL95(23,8), VAR1(7), VAR2(7), VAR3(7), SUM1(7), SUM2(
0003 27), SUM3(7), SUM4(7), COV1(7), COV2(7), IA(2), AI(2)
0002 REAL *4MEAN,M(17,8),MR(7)
0003 REAL *8X(10,60,7),V2(60,7), NAME(23),V1(7)
0004 INTEGER CST(2,60),CDATE(2,60,3)
0005 COMMON X,TABLE,IA,1B,I,K,KD,ID
0006 COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,LI,L
0007 COMMON /BLK2/ MR

Cc

Cc

c CALCULATE CORRECTION FACTOR FOR STANDARD DEVIATION

c
0008 1A3=1A(1)+1A(2)
0009 AI3=1A3

c
0010 DO 14 K=1, ID

c
0011 IF (M(8,K)) 1,4,5
0012 1 JX=(AI3*M(7,K)—AI3*M(10,K))/M(8,K)
0013 VJ=JX
0014 V=( ((AI3*M(10,K) )/VJ)**2)*VJ
0015 IF ((M(8,K)+( (AI3*M(10,K))/VJ))*VJ-(AI3"M(7,K)) ) 3,3,2
0016 2. V=V+(AI3*M(7,K)—VJ*(M(8,K)+( (AI3*M(10,K) )/VJ))—M(8,K))**2
0017 V=V+( ((AI3*M(6,K))/AI3—VJ—1.0))—M(8,K))**2*(AI3—VJ—1.0)
0018 GO TO8
0019 3. V=V+( ((AI3 *M(6,K))/(AI3—VJ))—M(8,K))**2*(AI3—VJ)
0020 GOTO 8
0021 4 JX-AI3/2.0
0022 VJ=JX
0023 V=( (AI3*M(6,K)/VJ)**2)*VJ
0024 V=V+( (AI3*M(7,K)/VJ)**2)*VJ
0025 GO TO8
0026 5 JX=(AI3*M(6,K)—AI3*M(9,K))/M(8,K)
0027 VJ=JX
0028 V=(((AI3*M(9,K))/VJ)**2)*VJ
0029 IF ((M(8,K)+((AI3*M(9,K))/VJ))*VJ—(AI3*M(6,K))) 6,7,7
0030 6 V=V+(AI3*M(6,K)—VJ*(M(8,K)+((AI3*M(9,K))/VJ))—M(8,K))**2
0031 V=V+(((AI3*M(7,K))/(AI3—VJ—1.0))—M(8,K))**2*(AI3—VJ—1.0)
0032 GOTO8
0033 7 V=V+( ((AI3*M(7,K))(AI3—VJ))—M(8,K))**2*(AI3—VJ)
0034 8 V=V/(AI3—1.0)

W=0.0
c
c

95


Table 14. NINTH PAGE OF COMPUTER OUTPUT SHOWING A SUMMARY OF THE ANNUAL
SYSTEM RATES EXPRESSED AS DECIMAL FRACTIONS OF THE MEAN CONCEN-
TRATION OF DDD PRESENT IN THE SYSTEM.

95%

System of Rates for DDD S.D. S.E. Limit

Net rate of change =Net =+ 0.0820 ¢ 1.0000 + 0.2294 + 0.4820
Translocation into + +

compartments =T, =+ 0.1941 + 0.7233 ¢ 0.1659 * 0.3486

Translocation out of

compartments =To =- 0.1941 + 0.2767 * 0.0635 * 0.1334
Input =| =+ 0.2200 t 0.7233 ¢ 0.1659 + 0.3486
Output and Decay =O+D = 0.1380 + 0.2767 +t 0.0635 ¢ 0.1334
Output from System =O = 0.1217 + 0.2441 +t 0.0560 ¢ 0.1177
Decay =D = 0.0162 + 0.0326 + 0.0075 + 0.0157
Lifetime in years =TL = 61.5459 + 123.4241 + 28.3154 * 59.4907
Residence time in years =TR = 7.2469 + 14.5330 + 3.3341 + 7.0049
Summary Equation for the System—

DDD Mean Cy = Mean Cy I Ty To ie) D N

2.4468 = 2.8589 (1.0 + 0.2200 + 0.1941 - 0.1941 - 0.1217 - 0.0162) 3:1628

36