AN ANALYSIS OF THE DYNAMICS OF DDT AND ITS
DERIVATIVES, DDD AND DDE, 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
Project R 800 365
Project Officer
Dr. Milton H. Feldman
Coastal Pollution Branch
Pacific Northwest Environmental Research Laboratory
National Environmental Research Center
Corvallis, Oregon 97330
Prepared for
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
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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 resarnpled. 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, Tj and Tq, 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,
Tj and Tq ± .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, 1 + 0.25, 0 - 0.11, D - 0.025, Tj a.nd Tq t 0.20 with
residence time of 7 years and life time of 44 years. The rates for DDE were I + 0.28,
O - 0.10, D - 0.027, Tq and Tj t 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. ^C ring 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 Qio 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 project R 800 365 under sponsorship of the
Environmental Protection Agency.
ii
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Abstract
List of Figures
List of Tables
Acknowledgements
I Conclusions
II Recommendations
III Introduction
IV Methods
V Results and Discussion
VI References
VII Appendix
CONTENTS
Page
ii
iv
v
vii
1
2
3
9
13
58
59
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FIGURES
No. Page
1 The study area, Monterey Bay. Sampling stations are indicated 5
by number.
2 DDT as a percent of the total concentration of DDT, DDD, and 19
DDE plotted for data obtained in 1970 for the southern and 1971
for the northern portions of Monterey Bay.
3 DDD as a percent of the total concentration of DDT, DDD, and 20
DDE plotted for data obtained in 1970 and 1971. Circled numbers
indicate actual percents in excess of 50%.
4 DDE as a percent of the total concentration of DDT, DDD, and 21
DDE plotted for data obtained in 1970 and 1971. Circled numbers
indicate actual percents in excess of 50%.
5 Total concentration in parts per billion of DDT, DDD, and DDE 22
from data obtained in 1970 and 1971. Circled numbers indicate
actual concentrations in excess of 50 ppb.
6 Total concentration in parts per billion of DDT, DDD, and DDE 23
from data obtained in 1973. The blank portions of the area were
not sampled. Circled numbers indicate actual concentrations in
excess of 50 ppb.
7 Model of the system of sediment compartments and this system's 29
relation to other systems.
8 Composite chart of the translocation of DDT compounds based 49
upon the rates of change, K, at individual stations in the
southern portion of Monterey Bay.
IV
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TABLES
No. Page
1 Concentration of DDT, DDD, and DDE in sediments 6
of the Monterey area land drainage system in 1972
(State of Calif., 1974).
2 Typical decay assay protocol. 11
3 Concentrations of DDT, DDD, and DDE in marine sediment 14
samples from Monterey Bay.
4 Levels of DDT, DDD, and DDE as percent of total residues 16
in marine sediment samples from Monterey Bay.
5 Variance of sampling measured at Station 38. 18
6 First page of computer output showing concentration of 25
pollutant compounds in sediment from sample stations at
first sampling time. Cj identifies as concentrations at time one.
7 Second page of computer output showing concentration of 26
pollutant compounds in sediment from sample stations at the
second sampling time. C2 identifies as concentrations at time two.
8 Third page of computer output showing percent of total of each 27
of the three compounds in sediments from sample stations at the
first sampling time. Cj identifies as data for time one.
9 Fourth page of computer output showing percent of total of each 28
of the three compounds in sediments from sample stations at the
second sampling time. C2 identifies as data for time two.
10 Fifth page of computer output showing the rate of change, K, 31
for DDT in each sediment compartment.
i 1 Sixth page of computer output showing the rate of change, K, 32
for DDD in each sediment compartment.
12 Seventh page of computer output showing the rate of change, K, 33
for DDE in each sediment compartment.
13 Eighth page of computer output showing a summary of the 35
annual system rates expressed as decimal fractions of the mean
concentration of DDT in the system.
v
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No. Page
14 Ninth page of computer output showing a summary of the 36
annual system rates expressed as decimal fractions of the mean
concentration of DDD in the system.
15 Tenth page of computer output showing a summary of the 37
annual system rates expressed as decimal fractions of the mean
concentration of DDE in the system.
16 Comparison of estimates obtained from the 16 and 19 station 38
data sets and using actud paired sample analyses. Standard
deviations and coefficients of variation are included.
17 Comparison of estimates obtained from 49 and 57 station 40
data sets and using sample analyses paired with mean concentration
levels. Standard deviations and coefficients of variation are included.
18 Standard deviations and standard errors of distributions of K 43
with minimal variance of given values of I, Tj and Tq, (O+D),
and n.
19 Comparison of uncorrected and corrected standard deviations of 44
system estimates.
20 Mean of the estimates for the South Monterey Bay system and 47
associated descriptive statistics.
21 Total amounts of DDT, DDD, and DDE in the South Monterey 48
Bay study area based on the mean concentrations at the two
sample times, and expected amounts effected by the mean of the
estimates of system rates.
22 Results of a laboratory assay of annual rate of decay of DDT to CO2, 51
DCO2' expressed as a decimal fraction of the initial concentration
of DDT maintained at 10° C under aerobic conditions.
23 Results of laboratory assays of the annual rates of decay to CO2, 52
Dco2> and the effect of environmental variables on the process.
24 Rates of decay to water soluble compounds and CO2 determined 5 5
by laboratory assays.
VI
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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
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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.
1
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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
latier 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.
2
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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-
rison 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 l,l,2-trichloro-2,2-bis (p-chlorophenyl) ethane, DDT; l,l-dichloro-2,2-bis (p-chloro-
phenyl) ethane, DDD; and l,l-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 ^C ring labelled DDT in marine sediments held under a variety of conditions
are also presented. These measurements reflect decay to the point of *4C02 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.
3
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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.
4
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I i'/O
"VKi'
.V. xN r
WATSON VILLE
PAJARO
RIVKR
130 FATHOMS
^£lOO
ELKIIORN
SLOUGH
CASTROVILLE
fREMBLADERO
SLOUGH
SALINAS
RIVER
w51
PACIFIC
GR0VE ^ *
MONTEREY
SEASIDE
ItCARMEL
CARMEL RIVER
riGURE 1. The study area, Monterey Bay. Sampling stations are indicated by number.
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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
(kilometers)
(ppb)
DDT
DDD
DDE
42
1.0
1.3
25
120.
20.
8
150.
16.
1000.
620.
360.
3
0.12
30.
Reclamation Canal .
distance from mouth
of Elkhorn Slough
(kilometers)
20
7,000.
21,000.
45,000.
150,000.
10,000.
6
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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.Cniz
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 arid 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.
7
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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
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.
8
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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 l^C labelled materials added
just prior to extraction with acetone, hexane. Recovery was 73.9% for DDT, 94.4%
for DDD, and 84.8% for E>DE, 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 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 isystems 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 CO2.
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
9
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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 ml total. One ml each of and 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.
^C Substrate Preparation—2.4 grams of either, l,l-bis-(p-chlorophenyl)-2,2,2-tri-
chloro ethane, p-p'DDT 99+% No. 10, 002-1; 2,2-bis-(p-chlorophenyl)-l,l-dichloro
ethylene, No. 12, 289-7 (B 3964); or 2,2-bis-(p-chlorophenyl)-l,l-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 10^ ug of substrate
on 0.1 gram of sediment per ml. Similar preparations were made giving 2.4 x 10 ug
and 21.6 ug of substrate on 0.1 gram of sediment per ml.
l^C-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 ^C-DDT and 0.1 gram of sediment per ml.
A similar preparation was made giving 0.24 ug ^C-DDT and 0.1 gram of sediment per ml.
l^C-DDD Substrate Preparation—^C-DDT was converted to ^C-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 ^C-DDT.
l^C-DDE Substrate Preparation— ^C-DDT was converted to ^C-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 ^C-DDT.
Analysis of Decay Assays—After incubation for generally 12 weeks ^C02 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. jJ^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
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Table 2. TYPICAL DECAY ASSAY PROTOCOL.
Hypovial
No.
Slurried
(qrams)
Sediment
(ml)
Seawater
plus
nutrients
(ml)
12C
Substrate
(ug) (ml)
14c
Substrate
(up) (ml)
Total
Substrate
(ppm)
Total
volume
(ml)
1-5
24
59
39
2400
1
2.4
1
100
100
6-10
24
59
39
240
1
2.4
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
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measurement were also made. The amount of ^CC>2 was determined in a Nuclear
Chicago Corp. Unilux II. Diffusion time and trapping volume of |3-phenylethylamine
were established through tests using a standard preparation of Na ^COj.
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
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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 m 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
-------
Table 3. CONCENTRATIONS OF DDT, DDD, AND DDE IN MARINE SEDIMENT
SAMPLES FROM MONTEREY BAY.
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
6.76
14.70
23.09
3
36 46.35121 49.00
2-20-70
5.71
0.71
1.02
7.44
4
36 46.05 121 5T.00
11-15-70
4.28
6.61
10.70
21.59
5
36 46.00 121 57.00
5-29-70
2.14
0.93
4.00
7.07
6
36 45.45 121 50.00
11-15-70
2.04
1.17
1.80
5.01
7
36 45.30 121 54.00
5-29-70
0.0
2.50
4.51
7.01
8
36 45.20 121 54.00
5-29-70
2.65
4.26
6.51
13.42
9
36 45.10 121 52.00
5-29-70
4.48
5.14
4.51
14.13
10
36 45.10 121 50.00
5-29-70
6.42
8.67
7.01
22.10
11
36 45.00 121 49.00
2-20-70
3.67
0.40
0.45
4.52
12
36 44.60121 50.50
2-20-70
0.52
0.18
0.28
0.98
13
36 44.25 121 50.35
11-15-70
0.26
0.19
0.45
0.90
14
36 44.20 121 52.25
8-23-70
5.20
7.50
15.50
28.20
15
36 44.00 121 50.00
5-29-70
0.0
0.19
0.35
0.54
16
36 44.00 121 49.50
2-20-70
0.69
0.14
2.75
3.58
17
36 43.75 121 54.45
1M5-70
1.02
0.38
0.70
2.10
18
36 43.50 121 51.80
2-20-70
1.73
2.64
, 2.40
6.77
19
36 43.35 121 56.25
8-23-70
1.12
0.25
0.65
2.02
20
36 43.18 121 57.00
2- 8-70
0.0
5.00
20.50
25.50
21
36 43.00121 51.00
5-29-70
6.12
1.30
6.01
13.43
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
24
36 42.50 121 50.30
8-23-70
19.30
0.65
2.75
22.70
25
36 41.70 121 55.00
2-20-70
1.22
0.53
2.40
4.15
26
36 41.55 121 55.50
2- 8-70
0.0
2.35
7.01
9.36
27
3641.50121 52.00
5-29-70
2.85
2.50
8.01
13.36
28
36 41.00121 51.00
11-15-70
0.0
1.61
4.26
5.87
29
36 40.90121 56.40
2-20-70
1.32
1.61
9.02
11.95
30
36 40.50121 53.50
5-29-70
2.55
1.76
6.76
11.07
31
36 40.08 121 54.05
2- 8-70
0.0
0.82
3.25
4.07
32
36 39.80 121 54.50
5-29-70
2.04
1.91
5.26
9.21
33
36 39.80 121 51.50
2- 9-70
0.0
1.42
8.52
9.94
34
36 39.10 121 53.08
2- 8-70
2.44
0.66
2.40
5.50
35
36 39.10 121 53.08
2- 8-70
8.67
0.66
3.00
12.33
36
36 37.95 121 52.50
2-20-70
2.65
2.79
10.00
15.44
37
3637.77 121 51.83
2- 8-70
0.49
0.21
0.50
1.20
Cont'd...
14
-------
Table 3. (continued) CONCENTRATIONS OF DDT, DDD, AND DDE IN MARINE
SEDIMENT SAMPLES FROM MONTEREY BAY.
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 53.60121 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 50.80121 53.60
11-24-71
1.62
5.61
6.72
13.95
49
36 50.20121 50.20
11-10-71
0.78
1.48
1.29
3.55
1
36 47.25 121 48.90
7- 9-73
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 45.00121 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 1?1 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 4. LEVELS OF DDT, DDD, AND DDE AS PERCENT OF TOTAL RESIDUES IN
MARINE SEDIMENT SAMPLES FROM MONTEREY BAY.
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
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.T0 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 41.00121 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
3639.80 121 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- 8-70
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
Cont'd..
-------
Table 4. (continued)
LEVELS OF DDT, DDD, AND DDE AS PERCENT OF TOTAL
RESIDUES IN MARINE SEDIMENT SAMPLES FROM MONTEREY
BAY.
LOCATION
DDT
DDD
DDE
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
11-10-71
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 50.20121 50.20
11-10-71
21.97
41.69
36.34
1
36 47.25 121 48.90
7- 9-73
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 44.20121 52.25
6-2 1*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
3643.18 121 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 39.10121 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
38
36 38.47 121 51.68
9-21-73
16.67
10.22
73.12
17
-------
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
.418
2.32
3.14
Mean
.6159
.3778
2.7233
3.7167
Variance
.02167
.00416
.06574
.09841
Standard Deviation
+ .1472 t .0645 + .2564
t .3137
Standard Error
* .0491 + .0215 .+ .0855
* .104 6
95% Confidence Limits
+ .1131 t .0495 t .1971
+ 2411
18
-------
I I
I I I
I I II 11
„ I I I T I O
i r i ro
il i u
"I i
SiBiBE
-WJA<
''/I/iTi/i. J
'a>:0~''>7 r z
_ SlAih ^
' 7i yf vi >l>»v /
% DDT 1970 & 1971
::: 0-10
>10-20
>20-30
>30-40
^>40-50
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%.
-------
'¦ ,V j/|/
i ' f /; ?'(./I y i sH sO
'>7\7\7
.•sisfsjfih'j.ytsjs i7
\/ is (/')/• l / * s
'J7')7i7i V'j/j/jsi'S
' i /'!/(/i sl.s>
1. - .•
.¦7j/'7i's\si/\7)s.
2}?j7^ ii/J.O- <;7\7„
J
TZtsfSJsJ.^J
S\s)s\.
?.GO FATHOMS
)2iliZsZ
''L^d7j?-\Z\
U4_JZI2Z(ZL7|/Ii _.
mls\y\<>H>i /'i _ _
Jl /iyi/'7|
rTTr'/'i Ti "Vi i
Ijfrb:.i ~ ~
jx,„
UJ
11 i i
I m i
uj i
• u.. i
Vo DDD 1970 a 1971
>10-20
m >2°-30
£§>30-40
>40-50
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%.
-------
21
\
i/»'i
IM.1
l .-'''/ !/ :/ I I.. .
I\/\s'f. is' y I/ OV |
s'}./\yi S'i S\" \
>¦)! I .'I,.-1 /i/l/VVv'l | |
Vj/I, | I 'I "f
.•:V;i/yi/'!/(/!/i ii'i if
i s'\ r\/) A /' / '/ II j j j j j"
I I I I I I
'\>y\/\7S7\/\7\/W\A I T I I I I
• •iyi/i/'/VI/i/l/i^', I. I | I I I I l,\
iV~\Sto'W^
!./1 ~'1/ l/'i /171 /»/ i/ i 717f 7| 7 !/ [A / j/1 /
< •.: i; i.' !./ I / !/l/'i 71 7'! 7\/\/\/\/\/\A ' i 7 i /i 7i /i>
<. ;VI l/l >1/1
•••••y" * '}X?\/!/17l 7'l/i/1/ (/'!>* |/ I/I /i'
y/\/\7\7\A7\?y-j7\/\7'\/\?'V\7\'A7\., ,
/i/i/l/i/l/i.y¦.>•!/ i/j/1/17!/|/171/iVr
'I '.I''
"j"..-'-
y
i ¦ v; s <».;v j/1a/;/•/ i/i/i
i.-l/i/i/l/l/i
t r-i 10-20
•j-|-t >20-30
U >30-40
%% >40-50
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 pcrcents in excess of 50%.
-------
I I I
Mill
I III M I
I III II I
III I III I
T i rrrn
oxmj
' i < G_l
' j". i A.j__
1 J-Li
S\'\/
?.00 FATHOMS
«r--?!*tV.
. I I
J TV IJ
i" I I I I I I 'i -'
i.r. ...cq~o "i -n..'v^ i
32> :'3cq~az:
TO IAL DDT DtRI VATIVES
PPQ 1970 & 1971
L.i'i .I. I J
>1-10
iPJ >10-15
Jjj| >15-20
?¦ t > 20-25
PIGURE 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.
-------
\
200 FATHOMS
I T I J I III
i rr i t i ¦' r
p-corpi?;
.cod:
TOTAL DDT DERIVATIVES
1973
?.oo
0-1
>1-10
l:IGUUT: 6.
Total concentration in parts per billion of DDT, DDD, and DDE from data obtained
in 1973. The blank portions of tiie area were not sampled. Circled numbers indicate
actual concentrations in excess of 50 ppb.
-------
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 Tq, on die 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
-------
Table 6. FIRST PAGE OF COMPUTER OUTPUT SHOWING CONCENTRATION OF
POLLUTANT COMPOUNDS IN SEDIMENTS FROM SAMPLE STATIONS
AT FIRST SAMPLING TIME. Cj IDENTIFIES AS CONCENTRATIONS AT
TIME ONE.
C1
LOCATION
DDT
DDD
DrE
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
6.76
14.70
23.09
3
36 46.35 121 49.00
2-20-70
5.71
0.71
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
6.42
8.67
7.01
22.10
11
36 45.00121 49.00
2-20-70
3.67
0.40
0.45
4.52
14
36 44.20 121 52.25
8-23-70
5.20
7.50
15.50
28.20
16
36 44.00121 49.50
2-20-70
0.69
0.14
2.75
3.58
17
36 43.75 121 54.45
11-15-70
1.02
0.38
0.70
2.10
19
36 43.35 121 56.25
8-23-70
1.12
0.25
0.65
2.02
20
36 43.18 121 57.00
2- 8-70 .
0.0
5.00
20.50
25.50
22
36 42.90121 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
0.53
2.40
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- 8-70
2.44
0.66
2.40
5.50
36
36 37.95 121 52.50
2-20-70
2.65
2.79
10.00
15.44
37
36 37.77 121 51.83
2- 8-70
0.49
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
+ 2.9296
"*¦ 6.0673
+ 10.1773
Standard Error
t 0.7889
+ 0.6721
+ 1.3919
+ 2.3348
95% Confidence Limits
+ 1.6574
+ 1.4121
+ 2.9245
+ 4.9055
25
-------
Table 7. 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.
C2
LOCATION
DDT
DDD
DDE
Station
Latitude Longitude
Date
(ppb)
(ppb)
(ppb)
TOTAL
1
36 47.25 121 48.90
7- 9-73
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 45.10121 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 44.20121 52.25
6-21-73
30.60
6.07
11.20
47.87
16
36 44.00121 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 41.70121 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 40.90121 56.40
7-16-73
0.70
l!l1
5.67
7.48
34
36 39.10121 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
TOTALS ¦
309.3296
46.4899
120.4299
476.2488
Mean
16.2805
2.4468
6.3384
25.0657
Standard Deviation
+
26.9909
t 2.8805
t 5.7417
t 29.2362
Standard Error
+
6.1921
+ 0;6608
+ 1.3172
t 6.7072
95% Confidence Limits
+
13.0097
+ 1.3884
t 2.7675
+ 14.0919
26
-------
Table 8. THIRD PAGE OF COMPUTER OUTPUT SHOWING PERCENT OF TOTAL OF
EACH OF THE THREE COMPOUNDS IN SEDIMENTS FFIOM SAMPLE STATIONS
AT THE FIRST SAMPLING TIME, q IDENTIFIES AS DATA FOR TIME ONE.
Cl
i
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 45.00121 49.00
2-20-70
81.19
8.85
9.96
14
36 44.20121 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
17
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 43.18121 57.00
2- 8-70
0.0
19.61
80.39
22
36 42.90121 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- 8-70
0.0
25.11
74.89
29
36 40.90121 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
t 8,6373
t 22.2953
Standard Error
+ 5.5748
t 1.9815
t 5.1149
95% Confidence Limits
+ 11.7126
t 4.1632
t 10.7464
27
-------
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. C2 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- 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 44.00121 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 40.90121 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
t 6.7005
t 2.1134
t 5.6487
95% Confidence Limits
+ 14.0777
+ 4.4403
+ 11.8679
28
-------
I ...
O . i m i") n / o i » • q
I | ,'/ i \ O I - 1 I i lO
I 1i.l
¦0-
~~£> -f-1
COMPARTMENT
: li -To
A
V
-To J''Ti
COMPARTMENT
"0 ~
¦> + 1
>:c~dc
SYSTEMS
C2=C,(l-l-I-0-D)M Jq-Tj
COMPARTMENTS
C2- C, (M- M-Tj-Tq— 0 - - D)N T0 f Tz
C, = CONCENTRATION OP RESIDUE AT TIME I
C2=C0NC.ENTRATI0N OF RESIDUE AT TIME 2
I = RATE OF INPUT OF RESIDUE
0 = RATE OF OUTPUT OF RESIDUE
D = RATE OF DECAY
T0= RATE OF TRANSLOCATION OUT OF A COMPARTMENT
JX-RATE OF TRANSLOCATION INTO A COMPARTMENT
FIGURE 7. Model of the system of sediment compartments and this system's relation to other
systems.
29
-------
Therefore, for the estimation of the overall rate of change in a compartment, i.e., the
resultant of the various rates affecting concentration, the following expression was
solved for K,
C2 = C1eKN 1.
Cj 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 = C1(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),
rj2 -v (1L)2 cr2 + (^)2 cr2 + 2— — cr 3
°K(CltC2) - ¦ dC{ C1 3G2 C2 <^^2 C-C2.
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 Tq,
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 Tq and Tj. 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,
Ti/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
-------
Table 10. FIFTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,
FOR DDT IN EACH SEDIMENT COMPARTMENT.
Station
C2 DDT
C-j DDT
N
+K
-K
+K + -K
+K - Net
.. R
-K - Net
R
1
1.06
8.36
2.8795
0.0
-0.5119
-0.5119
0.0
-2.0906
2
9.50
1.63
2.6493
0.9452
0.0
0.9452
0.0
-0.6336
3
1.10
5.71
3.3836
0.0
-0.3854
-0.3854
0.0
-1.9641
4
3.63
4.28
2.6493
0.0
-0.0603
-0.0603
0,0
-1.6390
10
0.92
6.42
3.0959
0.0
-0.4661
-0.4661
0.0
-2.0449
11
2.18
3.67
3.3644
0.0
-0.1434
-0.1434
0.0
-1.7222
14
30.60
5.20
2.8301
0.8706
0.0
0.8706
0.0
-0.7082
16
0.96
0.69
3.3644
0.1031
0.0
0.1031
0.0
-1.4756
17
5.41
1.02
2.7342
0.8408
0.0
0.8408
0.0
-0.7380
19
72.70
1.12
2.9644
3.0866
o!o
3.0866
1.5079
0.0
20
63.10
0.0
3.3671
16.6503
0.0
16.6503
15.0715
- 0.0
22
0.93
0.0
3.4685
3.8113
0.0
3.8113
2.2325
0.0
23
29.90
13.20
2.8301
0.3350
0.0
0.3350
0.0
-1.2438
25
1.14
1.22
3.4027
0.0
-0.0197
-0.0197
0.0
-1.5985
26
0.68
0.0
3.4356
3.4588
0.0
3.4588
1.8800
0.0
29
0.70
1.32
3.4027
0.0
-0.1701
-0.1701
0.0
-1.7488
34
1.18
2.44
3.5014
0.0
-0.1874
-0.1874
0.0
-1.7661
36
83.10
2.65
3.3342
1.8105
0.0
1.8105
0.2317
0.0
37
0.54
0.49
3.4356
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
t 0.8738
+ 0.1262
S.E
+ 6.1921
+ 0.7889 +0.0711 + 0.2068
+ 0.0226
+ 0.2294 + 0.2005
+ 0.0289
95% C.L
. 113.0097
+ 1.6574
t0.1494 t 0.4346
+ 0.0474
+ 0.4820 + 0.4212
+ 0.0608
SST/n^onmental Research Center
200 S. W. 33th
3 j Corvallis, Oregon 9733a
-------
Table 11. SIXTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,
FOR DDD IN EACH SEDIMENT COMPARTMENT.
Station
C9 DDD
Ci DDD
N
+K
-K
+K + -K
+K - Net
-K - Net
£
1 .
R
R
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
11
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
17
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
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.
t 2.8805 + 2.9296 10.3100
t 0.7233
+ 0.2767
+ 1.0000
+ 0J233
+ 0^2767
S.E.
+ 0.6608 + 0.6721 t
0.0711
t 0.1659
+ 0.0635
+ 0.2294
+ 0.1659
+ 0.0635
95% C.L. + 1,3884 + 1.4121 + 0.1494,
t 0.3486
+ 0.1334
+ 0.4820
+ 0.3486
+ 0.1334
32
-------
Table 12. SEVENTH PAGE OF COMPUTER OUTPUT SHOWING THE RATE OF CHANGE, K,
FOR DDE IN EACH SEDIMENT COMPARTMENT.
Station
C2DDE
C! DDE
N
+K
-K
+K + -K
+K - Net
R
-K - Net
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
t.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
12(14299 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
t 0.3100
+ 0.7781
+ 0.2243
+ 1.0024
+ 0.7761
+ 0.2262
S.E.
t 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
f 0.3741
+ 0.1091
33
-------
O = Tj (0+D)
I
5.
D = (1.0 - Tj) (O+D) or D = (O+D) - O
6.
The residence time, Tr, and lifetime, Tl, in years, are calculated as the corresponding
reciprocals.
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 time one. While there was some effect upon the esti-
mates of rates as the system was reduced in size, only the estimates of Tq 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,
TR = 1.0/(O+D)
7.
Tl = 1.0/D
8.
C2 = CieKN
with N = T2 - Tj
9.
34
-------
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.
System of Rates for DDT
S.D.
S.E.
95%
Limit
Net rate of change = Net = +
1.5788
+
1.0000
+
0.2294
+
1
0.4820
Translocation into compartments = T| = +
1.1012
+
0.8738
+
0.2005
+
0.4212
Translocation out of compart-
ments = Tq =¦ -
1.1012
+
0.1262
+
0.0289
+
0.0608
Input = 1 = +
1.6811
+
0.9016
+
0.2068
+
0.4346
Output and Decay = O+D = -
0.1023
+
0.0984
+
0.0226
+
- 0.0474
Output from System = 0 = -
0.0670
+
0.0644
+
0.0148
+
0.0311
Decay = D
0.0353
+
0.0339
+
0.0078
+
0.0164
Lifetime in years = T[_ =
28.3322
+
27.2386
+
6.2490
+
13.1291
Residence time in years = Tr =
9.7724
+
9.3952
+
2.1554
+
4.5285
Summary Equation for the System-
DDT Mean C2 Mean C-| 1 , T|
16.2805 = 3.1274 (1.0 + 1.6811 + 1.1012
T0 0
- 1.1012 - 0.0670-
D N
0.0353) 3 1628
35
-------
Table 14. NINETH 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.
System of Rates for DDD
S.D.
S.E.
95%
Limit
Net rate of change
= Net = +
0.0820
+
1.0000
+
0.2294
+
0.4820
Translocation into
compartments
+
ii
II
0.1941
+
0.7233
+
0.1659
+
0.3486
Translocation out of
compartments
11
O
I-
II
0.1941
+
0.2767
+
0.0635
+
0.1334
Input
= l = +
0.2200
+
0.7233
+
0.1659
+
0.3486
Output and Decay
= 0+D = -
0.1380
+
0.2767
+
0.0635
+
0.1334
Output from System
= 0 = -
0.1217
+
0.2441
+
0.0560
+
0.1177
Decay
= D = -
0.0162
+
0.0326
+
0.0075
+
0.0157
Lifetime in years
ii
_i
l-
11
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 C2
Mean
' T,
T0
O
D
N
2.4468 =
I
2.8589 (1.0 + 0.2200 + 0.1941 -
0.1941-0.1217
- 0.0162)
3.1628
36
-------
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.
System of Rates for DDE
S.D.
S.E.
95%
Limit
Net rate of change
Net = +
0.1177
+
1.0024
+
0.2300
+
0.4831
Translocation into
compartments
T| = +
0.2343
+
0.7761
+
0.1781
+
0.3741
Translocation out of
compartments, =
11
O
t-
0.2343
+
0.2262
+
0.0519
+
0.1091
Input
I = +
0.2725
+
0.7781
+
0.1785
+
0.3750
Output and Decay =
0+D = -
0.1548
+
0.2243
+
0.0515
+
0.1081
Output from System
0 = -
0.1331
+
0.1929
+
0.0442
+
0.0930
Decay
D = -
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
+
9.3629
+
2.1480
+
4.5129
Summary Equation for the System-
DDE Mean C2 Mean Ci 1 Tj
6.3384 = 6.6310 (1.0 + 0.2725 + 0.2343-
¦T0 O
0.2343 - 0.1331
0D N
-0.0217) 31628
37
-------
Table 16.
COMPARISON OF ESTIMATES OBTAINED FROM THE 16 AND 19 STATION DATA SETS AND
USING ACTUAL PAI RED SAMPLE ANALYSES, STANDARD DEVIATIONS [S.DJ AND COEF-
FICIENTS OF VARIATIONS [C.V.] ARE INCLUDED.
16 STATION DATA SET
19 STATION DATA SET
Estimate
S.D.
C.V.
Estimate
S.D.
C.V.
I
. %
%
DDT
C1 (ppb)
3.7137
+ 3.4446
92.8
3.1274
+ 3.4385
109.9
,C2 (ppb)
15.2887
+ 26.3645
172.4
16.2805
+ 26.9909
165.8
Net
+ 0.3798
+ 1.0000
263.3
+ 1.5788
+ 1.0000
63.3
I
+ 0.5013
+ 0.7556
150.7
+ 1.6811
+ 0.9016
53.6
0+ 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
T,
+ 0.3534
+ 0.7409
209.6
+ 1.1012
+ 0.8738
79.3
0
- 0.0857
+ 0.1723
201.1
0.0670
+ 0.0644
96.1
D
0.0358
+ 0.0721
201.4
0.0353
+ 0.0339
96.0
T|_ (years)
27.9014
+ 56.1105
201.1
28.3322
f 24.2386
96.1
Tp (years)
8.2294
+ 16.5496
201.1
9.7724
i 9.3952
96.1
DDD
Ci (ppb)
2.9137
+ 3.0908
106.1
2.8589
+ 2.9296
102.5
C2 (ppb)
2.6625
± 3.0921
116.1
2.4468
v 2.8805
117.7
Net
+ 0.1054
+ 1.0000
948.8
+ 0.0820
i 1.0000
1219.5
1
+ 0.2417
± 0.7279
301.2
+ 0.2200
+ 0.7233
328.8
0+ D
- 0.1363
+ 0.2721
. 199.6
0.1380
± 0.2767
200.5
T0
- 0.2088
+ 0.2721
130.3
0.1941
+ 0.2767
142.6
T|
+ 0.2088
± 0.7279
348.6
+ 0.1941
+ 0.7233
5009.4
0
- 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
Tp (years)
7.3364
+ 14.6462
199.6
7.2469
+ 14.5330
200.5
DDE
i
Ci (ppb)
6.0350
i 5.4299 ,
90.0
6,6310
i 6.0673
91.5
C2 (ppb)
6.3887
,+ 6.2166
97.3
6.3384
+ 5.7417
90.6
Net
+ 0.1368
i 1.0030
733.2
+ 0.1177
+ 1.0024
851.7
I
+ 0.2950
+ 0.7843
265.9
+ 0.2725
+ 0.7781
285.5
0+ D
- 0.1582
± 0.2186
138.2
- 0.1548
± 0.2243
144.9
T0
- 0.2563
+ 0.2211
86.3
0.2343
+ 0.2262
96.5
T|
+ 0.2563
+ 0.7818
305.0
+ 0.2343
+ 0.7761
332.1
0
- 0.1374
+ 0.1899
138.2
0.1331
+ 0.1929
144.9
D
- 0.0208
+ 0.0287
138.0
0.0217
+ 0.0314
144.7
Tl (years)
48.1189
+ 66.4924
138.2
46:1286
t 66.8543
144.9
Tr (years)
6.3211
+ 8.7347
138.2
6.4611
+ 9.3629
144.9
38
-------
T2 = mean time of second sampling period
Tj = time of actual sampling in first sampling period
and C2 = Ci e^N 10.
with N = T2 -Ti
T2 = time of actual sampling in second sampling period
Ti = 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 Tq 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, I, translocation, Tj and Tq, 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 change 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
-------
Table 17. COMPARISON OF ESTIMATES OBTAINED FROM THE 49 AND 57 SAMPLE DATA SETS AND
USING SAMPLE ANALYSES PAIRED TO MEAN CONCENTRATION LEVELS. STANDARD
DEVIATIONS [S.D.] AND COEFFICIENTS OF VARIATIONS [C.V.] ARE INCLUDED.
49 SAMPLE DATA SET
57 SAMPLE DATA SET
Estimate
s.d!
C.V.
%
Estimate
S.D.
C.V.
%
DDT
C1 (ppb)
C2 (ppb)
Net
1
0+ D
T0
T,
0
D
TL (years)
Tr (years)
DDD
Cj (ppb)
C2 (ppb)
Net
1
0 + D
T0
T|
0
D
T|_ (years)
Tp (years)
DDE
C1 (ppb)
C2 (ppb)
Net
1
0+ D
T0
T|
0
D
T|_ (years)
Tr (years)
3.9576
15.4975
+ 0.5905
+ 0.6819
0.0913
- 0.3234
+ 0.3234
- 0.0433
- 0.0480
20.8292
10.9502
2.4107
2.3435
+ 0.1283
..+ 0.2703
- 0.1420
• 0.2095
+ 0.2095
• 0.1101
¦ 0.0319
31.3031
7.0424
5.1138
6.1575
+ 0.1748
+ 0.2802
- 0.1054
- 0.1946
+ 0.1946
- 0.0732
• 0.0322
31.0400
9.4853
+ 4.1746
+ 26.5034
± 1.0000
+ 0.6374
1 0.3626
+ 0.3966
± 0.6034
+ 0.1720
+ 0.1906
± 82.7111
± 43.4823
+ 2.5354
+ 2.8415
+ 1.0000
± 0.6357
+ 0.3643
+ 0.3653
+ 0.6347
+ 0.2823
+ 0.0820
+ 80.3119
+ 18.0682
+ 4.4111
+ 5.6469
+ 1.0010
+ 0.6628
+ 0.3382
+ 0.3466
+ 0.6544
+ 0.2348
± 0.1033
± 99.5728
± 30.4277
105.4
171.0
169.3
93.5
397.2
122.6
186.6
397.2
397.1
397.1
397.1
105.2
121.3
779.4
235.2
256.5
174.4
303.0
256.4
257.1
256.6
256.6
86.3
91.7
572.7
236.5
320.9
178.1
336.3
320.8
320.8
320.8
320.8
3.1019
15.4975
+ 2.2567
+ 2.3233
0.0667
1.4256
+ 1.4256
0.0409
0.0258
38.8090
14.9951
2.2743
2.3435
+ 0.1587
+ 0.2813
0.1226
- 0.2039
+ 0.2039
0.0889
0.0337
29.6518
8.1558
5.3681
6.1575
+ 0.1793
+ 0.2785
0.0993
- 0.1906
+ 0.1906
- 0.0679
0.0314
31.8905
10.0735
± 4.0336
± 26.5034
+ 1.0000
+ 0.9204
+ 0.0796
± 0.1513
+ 0.8487
+ 0.0488
+ 0.0307
± 46.2947
± 17.8875
± 2.3532
± 2.8415
+ 1.0000
+ 0.6329
+ 0.3671
+ 0.3698
+ 0.6311
+ 0.2662
+ 0.1010
± 88.7883
+ 24.4216
+ 4.8069
+ 5.6469
± 1.0009
± 0.6787
± 0.3222
± 0.3311
± 0.6697
+ 0.2204
± 0.1018
+ 103.4957
± 32.6922
130.0
171.0
44.3
39.6
119.3
10.6
59.5
119.3
119.0
119.3
119.3
103.5
121.3
630.1
225.0
299.4
180.9
309.5
299.4
299.7
299.4
299.4
89.5
91.7
558.2
243.7
324.5
173.7
351.4
324.6
324.2
324.5
324.5
40
-------
For any set of estimates of I, (O+D), Tj and Tq, 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 - nTj and j is an integer obtained without rounding.
I + (O+D)
I + (O+D) + nTj =K1,K2 . . .Kj
j 1
If K L nl
1
nl - jKx = Kj + 1
n(Q+D) = Kj + 2, Kj + 3 . . , Kn
n-j-1
j
If
K = nl
1
n(Q+D) = Kj + l,Kj + 2 . . .Kn
n-j
Where the net rate of change, I + (O+D), is zero,
^ | and j is an integer obtained without rounding.
nTt = K1,K2'...Kj
j
nT0 = Kj + 1, Kj + 2 . . . K2j
j
If 2j L n,
K 'n ~ 0 0
Where the net rate of change, I + (O+D), is negative,
j = n(0+D) - nTQ
1 + (O+D)
I + (0+D) + nT0 = K1)K2)...Kj
j
41
-------
j
If ^ K Ln(0+D)
1
n(0+D)-.11^ = 1^ + 1 22.
_nl_ = Kj+2' ^j+3 • • ¦ Kn
n-j-1
J
If ^ K = n(0+D)
1
n(I^= Kj+1, Kj+2, . . . Kn 24.
n-j
The variances of such distributions are the minimal variances that will permit the estima-
tions of I, Tj and T0- and (0+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, Tj
and Tq, and (O+D) as can be seen in Table 18. The lowest standard deviations are observed
where Tj is low. Where I is increased relative to Tj, 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 I = 1.5,
Tj = 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 Tj and Tq 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 _ _
s - s V s 25.
K calc. Min. I K K corr.
K calc.
2 2
Where s^ is the variance calculated by equation 3, smjn is the variance of the distribution
of K's with minimal variance, s^-cajc is the variance of the distribution of K's calculated
by equation 3, and s^ corr 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
-------
Table 18. STANDARD DEVIATIONS AND STANDARD ERRORS OF DISTRIBUTIONS OF K WITH MINIMAL
VARIANCE FOR GIVEN VALUES OF I, T, AND TQf (O+D) AND n.
I
Tl
O+D
Net
n
= 5
n
= 10
n
= 20
S.D.
S.E.
S.D.
S.E.
S.D.
S.E.
2.00
1.20
-0.15
1.85
+ 2.7524
+ 2.5965
* 2.5338
* 1.2309
* 0.8211
+ 0.5666
1.75
1.20
-0.15
1.60
+ 3.4084
+ 2.7758
+ 2.7107
+- 1.5243
* 0.8778
* 0.6061
1.50
1.20
-0.15
1.35
+ 3.3586
+ 3.1663
* 3.0831
+ 1.5020
* 1.0013
+ 0.6894
1.50
1.20
-0.30
1.20
* 3.3719
+ 3.1785
* 2.8433
+ 1.5080
* 1.0051
+ 0.6358
1.50
1.20
-0.60
0.90
+ 3.4249
+ 3.2267
+ 2.7077
+ 1.5317
+- 1.0204
+ 0.6055
1.50
0.90
-0.15
1.35
+- 2.0724
+ 1.9558
* 1.9124
+- 0.9268
t 0.6185
+ 0.4276
1.50
0.60
-0.15
1.35
+- 1.4335
+ 1.3528
+- 1.3063
+ 0.6411
+ 0.4278
0.2921
43
-------
Table 19.
COMPARISON OF UNCORRECTED AND CORRECTED STANDARD DEVIATIONS OF
SYSTEM ESTIMATES
<
16 Sam
ale Set
19 Sample Set
49 Sam
Die Set -
57 Sam
pie Set
Uncorrected
Corrected
Uncorrected
Corrected
Uncorrected
Corrected
Uncorrected
Corrected
DDT
I
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
T0
± 0.2591
± 0.0962
± 0.1262
± 0.0755
± 0.3966
± 0.1335
± 0.1513
± 0.0814
T|
± 0.7409
± 0.2751
± 0.8738
± 0.5231
± 0.6034
± 0.2031
± 0.8487
± 0.4565
0
± 0.1723
± 0.0640
+ 0,0644
+ 0.0386
± 0.1720
± 0.0579
± 0.0488
+ 0.0263
D
± 0.0721
± 0.0268
± 0.0339
± 0.0203
± 0.1906
± 0.0642
± 0.0307
+ 0.0165
V
± 56.1105
±20.8365
± 27.2386
±16.3047
±82.7111
±27.8380
± 46.2947
±24.9713
Tr
± 16.5496
± 6.1457
± 9.3952
± 5.6239
±43.4823
£14.6348
+ 17.8875
+ 9.6215
DDD
Net
± 1.0000
± 0.3604
± 1.0000
+ 0.3860
± 1.0000
± 0.3419
± 1.0000
± 0.3521
I
± 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
T0
± 0.2721
± 0.0981
± 0.2767
± 0.1068
+ 0.3653
+ 0.1249
± 0.3689
± 0.1299
T|
+ 0.7279
+ 0.2623
± 0.7233
± 0.2792
± 0.6347
± 0.2170
± 0.6311
+ 0.2222
0
± 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
± 0J010
± 0.0356
tl
+107.4660
±38.7279
±123.4241
+47.6463
±80.3119
±27.4603
± 88.7883
±31.2619
Tr
± 14.6462
+ 5.2781
+ 14.5330
+ 5.6103
+ 18.0682
+ 6.1779
+ 24.4216
+ 8.5987
DDE
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
±_ 0.1479
± 0.3222
± 0.1463
T0
± 0.2211
± 0.0794
± 0.2262
± 0.1064
± 0.3466
±0.1516
± 0.3311
± 0.1504.
T|
± 0.7818
± 0.2808
± 0.7761
± 0:3651
± 0.6544
± 0.2863
± 0.6697
± 0.3041
0
± 0.1899
± 0.0682
± 0.1929
± 0.0907
+ 0.2348
± 0.1027
± 0.2204
± 0.1001
D
± 0.0287
± 0.0103
± 0.0314
± 0.0148
± 0.1033
± 0.0452
± 0.1018
+ 0.0462
tl
± 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
+30.4277;
±13.3109
± 32.6922
+14.8445
44
-------
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, Tq, and Tj. The estimates obtained with the 16 and 57 sample sets were
significantly different for Net, I, and Tq, and the estimates of Tq 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 Tq 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 Tj and Tq-
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 cm 3. 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 hot 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
-------
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
-------
Table 20. MEAN OF THE ESTIMATES FOR THE SOUTH MONTEREY BAY SYSTEM AND
ASSOCIATED DESCRIPTIVE STATISTICS.
Mean
S.D.
S.E.
95% C.L.
C.V.
%
C1
DDT
DDD
(ppb)
(ppb)
3.4752
2.6144
+
+
0.4281
0.3196
+
+
0.2141
0.1598
+ 0.6812
+- 0.5086
12.3
12.2
DDE
(ppb)
5.7870
+
0.6837
*
0.3419
"5" 1.0878
11.8
C2
DDT
DDD
(ppb)
(ppb)
15.6411
2.4491
+
+
0.4375
0.1504
+
+
0.2188
0.0752
+ 0.6961
+ 0.2393
2.8
6.1
DDE
(ppb)
.6.2605
+
0.1207
+
0.0604
+ 0.1921
1.9
Net
DDT
+ 1.2015
+
0.8764
t
0.4382
+ 1.3944
72.9
DDD
+ 0.1186
+
0.0327
+
0.0164
+ 0.0521
27.6
DDE
+ 0.1522
+
0.0298
+
0.0149
+ 0.0475
19.6
I
DDT
+ 1.2969
+
0.8587
+
0.4294
+ 1.3663
66.2
DDD
+ 0.2533
+
0.0278
+
0.0139
t 0.0442
11.0
DDE
+ 0.2816
+
0.0096
+
0.0048
+ 0.0152
3.4
O + D
DDT
- 0.0955
+
0.0096
+
0.0114
+ 0.0364
24.0
DDD
• 0.1347
+
0.0229
+
0.0042
* 0.0134
6.2
DDE
- 0.1294
+
0.0084
+
0.0157
0.0499
27.3
Tq&T,
DDT
DDD
+- 0.8009
t 0.2041
+
+
0.5504
0.0071
+
+
0.2752
0.0036
+ 0.8756
+ 0.0113
68.7
3.5
DDE
- 0.2190
+
0.0318
+
0.0159
0.0505
14.5
0
DDT
- 0.0592
+
0.0212
+
0.0106
+ 0.0338
35.8
DDD
- 0.1096
+
0.0146
+
0.0073
+ 0.0233
13.3
DDE
- 0.1029
+
0.0375
+
0.0187
t 0.0596
36.4
D .
DDT
- 0.0362
+
0.0091
+
0.0045
t 0.0145
25.1
DDD
- 0.0251
+
0.0090
+
0.0143
+ 0.0143
35.9
DDE
¦ 0.0265
+
0.0061
+
0.0031
^ 0.0097
23.0
tl
DDT
DDD
(years)
(years)
28.9680
44.0829
+
+
7.4078
16.0370
+
+
3.7039
8.0185
+11.7858
125.5148
25.6
36.4
DDE
(years)
39.2945
+
9.0835
+
4.5418
14.4519
23.1
tr
DDT
DDD
(years)
(years)
10.9868
7.4454
+
+
2.8952
0.4893
+
+
1.4476
0.2447
+- 4.6062
* 0.7785
26.4
6.6
DDE
(years)
8.0853
+
1.9717
+
0.9859
- 3.1371
24.4
47
-------
48
Table 21. 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.
Kilograms
Pounds
Pounds/Acre
Amount at Sample Time 1
DDT
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
511
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
DDE
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
DDD
18
40
0.001
year interval
DDE
51
112
0.002
TOTAL
532
1172
0.018
Expected amount Output to
DDT
35
77
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
DDT
21
46
0.0007
in next time interval.
DDD
2
5
0.0001
DDE
6
14
0.0002
TOTAL
29
65
0.0010
-------
©
.CIRCULATION OF DDT DERIVATIVES
FIGURE 8. Composite chart of the translocation of DDT compounds based upon the rates
of changs, K, at individual stations in the southern portion of Monterey Bay.
49
-------
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 can be obtained by measurement of the amount,
of 1^C02 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 D^q^. 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 ^^CC>2 content. There is no significant difference between the DCO2 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 D(]Q2
of DDT, DDD, and DDE. This Table also includes the results of assays in which the effect
of environmental variables on the Dq^ was determined.
The Q10 for Dcq2 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 D^^^. 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"' % 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
-------
1
1
2
2
3
3
4
4
5
5
1
1
2
2
3
3
4
4
5
5
1
1
2
2
3
3
4
4
5
5
1
1
2
2
3
3
4
4
5
5
OF A LABORATORY ASSAY OF ANNUAL RATE OF DECAY OF DDT
lC02. EXPRESSED AS A DECIMAL FRACTION OF THE INITIAL CONCEN-
OF DDT MAINTAINED AT 10°C. UNDER AEROBIC CONDITIONS.
dco2
Means
S.D.
Means
S.D.
Mean.
S.D.
.0046
.0045
.00455
t .000071
.0048
.0042
.00450
t .000424
!
.0059
.0056
.00575
t .000212
:0050
.0045
.00475
t .000354
.0046
-
.0053
.00495
t .000495
.00490
+ .000544
.0050
.0052
.00510
t .000141
.0058
.0048
.00530
t .000707
.0045
.0056
.00505
t .000778
.0056
.0057
.00565
t .000071
.0051
.0056
.00535
t .000354
.00529
t .000436
.0050
.0059
.00545
+• .000636
.0045
.0046
.00455
+ .000071
.0062
.0057
.00595
t .000354
.0058
.0052
;00550
t .000424
.0063
'
.0058
.00605
t .000354
.00550
t .000638
.0057
.0057
.00570
+ -0000
.0045
.0047
.00460,
t .000141
.0051
, .0051
;00510
t .0000
.0055
.0058
.00565
t .00Q212
.
.0063 .
.0053
,00580
t .000707
.00537
t .000542
.00527
+ .000570 ,
51
-------
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
CM.
o
Q
Mean
S.D.
Aerobic, 10°C
DDT 100 ppm
10 ppm
'I ppm
100 ppb
.0050
.0053
.0055
.0054
.00529
+ .00023
Aerobic, 20°C
DDT 100 ppm
10 ppm
1 ppm
100 ppb
.0100
.0111
.0167
.0154
.01320
Q10 2.50
+ -00335
Anaerobic, 10°C
DDT 100 ppm
10 ppm
1 ppm
100 ppb
.0012
.0013
.0015
.0018
.00145
+ .00027
Anaerobic, 10°C
5 x 10"1% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0013
.0016
.0016
.00150
+ .00017
5 x 10"2% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0017
.0018
.0020
,00183
+ .00015
5 x 10'3% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0024
.0024
.0027
.00250
+ .00017
5 x 10'4% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0030
.0036
.0036
.00340
t .00035
5x 10"5%NaNO3
DDT 10ppm
1 ppm
100 ppb
.0037
.0034
.0037
.00360
t .00017
5 x 10'6% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0036
.0025
.0032
.00310
+ .00056
5 x 10"7% NaN03
DDT 10 ppm
1 ppm
100 ppb
.0031
.0032
.0031
.00313
+ .00006
52
-------
Table 23. CONTINUED (SECOND OF THREE PAGES)
Conditions
Concentration
dC02
Mean
S.D.
Anaerobic, 10°C,
5 x 10"1% Na N03
5 x 10"1% Na Acetate
DDT 10ppm
1 ppm
100 ppb
.0011
.0008
.0008
.00090
t,00017
5 x 10"2% Na Acetate
DDT 10ppm
1 ppm
100 ppb
.0008
.0008
.0010
.00087
t .00012
. !
5 x 10"3% N a Acetate
. DDT 10 ppm
1 ppm
100 ppb
.0022
.0022
.0023
.00223
+ .00006
5 x 10"4% Na Acetate
DDT 10 ppm
1 ppm
100 ppb
.0022
.0025
.0024
.00237
+ .00015
5 x 10"^% Na Acetate
DDT 10 ppm
1 ppm
100 ppb
.0022 ¦
.0023
.0023
.00227
+ .00006
5 x 10"®% Na Acetate
DDT 10ppm
1 ppm
100 ppb
.0019
.0022
.0023
.00213
+ .00021
5 x 10"^% Na Acetate
DDT 10ppm
1 ppm
100 ppb
.0024
.0024
.0024
.00240
t .00000
Aerobic, 10°C
5 x 10"1% Na Acetate
DDT 10ppm
1 ppm
100 ppb
.0031
.0033
.0031
.00317
+ .00012
5 x 10"^% Na Acetate
DDT 10ppm
1,ppm
100 ppb
.0034
.0031
.0027
.00307
+ .00035
5 x 10"^% Na Acetate
DDT 10 ppm
1 ppm
100 ppb
.0025
.0023
.0023
.00237
t .00012
53
-------
54
Table 23. CONTINUED (THIRD OF THREE PAGES)
Conditions
Concentration
dC02
Mean
S.D.
5 x 10*4% Na Acetate
DDT lOppm
.0028
1 ppm
.0030
.00297
t .00015
100 ppb
.0031
5 x 10'^% Na Acetate
DDT 10ppm
.0027
. 1 ppm
.0030
.00287
t .00015
100 ppb
.0029
5 x 10'®% Na Acetate
DDT lOppm
.0025
1 ppm
.0027
.00270
t .00020
100 ppb
.0029
i-
5 x 10'^% Na Acetate
DDT lOppm
.0028
1 ppm
.0030
.00277
t .00025
100 ppb
.0025
Anaerobic, 10°G
5 x 10'^% Ethanol
DDT 10 ppm
.0007
1 ppm
.0005
.00043
+ .00031
100 ppb
.0001
5 x 10"2% Ethanol
DDT 10 ppm
.0027
1 ppm
.0028
.00273
t .00006
100 ppb
.0027
5 x 10'3% Ethanol
DDT 10ppm
.0034
1 ppm
.0031
.00307
+ .00035
100 ppb
.0027
5 x 10*4% Ethanol
DDT lOppm
.0029
1 ppm
.0030
.00297
f .00006
100 ppb
.0030
5 x 10"5% Ethanol
DDT 10 ppm
.0034
1 ppm
.0032
.00320
+ .00020
100 ppb
.0030
5 x 10'6% Ethanol
DDT 10ppm
.0022
1 ppm
.0023
.00230
+ .00010
100 ppb
.0024
5 x 10 ^% Ethanol
DDT 10 ppm
.0023
1 ppm
.0022
.00233
+ 00015
100 ppb
.0025
Aerobic, 10°C
ODD 100 ppm
.0016
,
10 ppm
1 ppm
.0015
. .0015
.00173
+ .00000;
100 ppb
.0023
Aerobic, 10°C
DDE 100 ppm
.0030
10 ppm
1 ppm
.0028
.0031
.00325
+ .00058
100 ppb
.0041
-------
Table 24. RATES OF DECAY TO WATER SOLUBLE COMPOUNDS AND C02 DETERMINED
BY LABORATORY ASSAYS.
Laboratory Assays
DDT
DDD
DDE
S.D.
S.D.
S.D.
CM
O
o
Q
,
.00529
+ .00023
.00173
+ .00036
.00325
+ .00058
DWS
.01539
+ .000817
.00309
t .00052
.00459
+ .00074 ¦
Laboratory Assays
Corrected by Q-jg
DC02
.00600
t .00026
.00196
+ .00041
.00369
i
t .00066
DWS
.01746
+ .00093
.00351
t .00059
.00521
t .00084
Estimations from
Field Data
D
.0362
.0251
; .0265
55
-------
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 CO2 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 Qjq for the decay process under aerobic conditions presents no surprise as to its
magnitude.
A comparison of the Dq^ f°r DDT, DDD, and DDE reveals a similar relationship to the
total decay rates, D, estimated for South Monterey Bay in that DdDT,C02 ) ®DDE,C02>
dddd,co2 iust 33 Dddt > DDDE > °DDD- See Table 24-
For purposes of analysis the process of decay can be divided into a series of steps as follows,
DDT
PLS^
LS
DWS^
WS
Dco2
co2
DDD
PLS>
LS
%s>
WS
^2
co2
DDE
dls>
LS
°ws
WS
'Dg>2
co2
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 after high speed
centrifugation of samples from the initial preparations followed by acidification to remove
14co2.
D\ys values presented in Table 24 are based on the sum of the -^C present in water solu-
ble form plus that present as ^C02- 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 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
-------
estimation of .field rates. If we take the difference between the values of D^vs obtained
from laboratory assays and D obtained from field estimations the rates of decay of the
parent compounds to lipid soluble breakdown products, Dls, 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
-------
SECTION VI
REFERENCES
Calif. IX-pt. 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., 0. 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. Y. 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. 1974.
Woodwell, G. M. Toxic substances £md ecological cycles. Sci. Amer. 216:24-31. 1967.
58
-------
APPENDIX
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,I2,2(A4,A2),I2,2(1X,I2),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
-------
c
c
c
0001
0002
0003
0004
0005
0006
0006
0007
0008
0009
0010
0011
0012
0013
0014
0015
0016
0017
0018
0019
0020
0021
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
c
c
c
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),COVl(7),COV2(7)
REAL *4ME AN ,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,IA,I,K,KD,ID
COMMON/BLK1/NAME,TOT1M,STD,STE,CL95,ALOC,YR,CST,CpATE .MONTH,LI,L
COMMON/B LK2 /MR
READ (5,45) TABLE
READ (5,46) MONTH
READ (5,47) IA,ID
CALCULATE INDEXES.
NUMBER OF STATIONS CONVERTED TO A REAL NUMBER
ID + 1
ID+ 2
2 * ID+ 2
2 * ID + 3
3 * ID + 2
AI
IP1
IP2
I2TP2
I2TP3
I3TP2
AI=IA
IP1=ID+1
IP2=ID+2
I2TP2=2*ID+2
I2TP3=2"'ID+3
I3TP2=3;*ID+2
CLEAR X ARRAY.
DO 1 1=1,10
DO 1 J=1,IA
DO 1 K=1 ,IP1
1 X(I,J,K)=0.0
WRITE (6,50)
READ IN DERIVATIVE NAMES AND CONCENTRATION LEVEL ON UP TO 3 CARDS.
READ (5,48) NAME
READ IN DATA.
60
-------
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
0047
0048
DO 2 1=1,2
C
DO 2 J = 1,IA
2 READ (5,49) CST(I,J),(ALOC(I,J,L),L=l,6),(CDATE(I J,L),L=1,3),(X(I
1,J.K),K=1,ID)
c
c
C COMPUTE TOTAL OF EACH STATION.
C
DO 3 1=1,2
C
DO 3 J=1,IA
C
DO 3 L=1,ID
3 X(IJ,IP1)=X(I,J,L)+X(I,J,IP1)
C
C
C WRITE HEADING OF FIRST TWO PAGES.
C
DO 5 1=1,2
L=I
WRITE (6,51)1
WRITE (6,53) (NAME(N),N=1,IP1)
WRITE (6,52) (NAME(N),N=IP2,I2TP2)
WRITE (6,54)
C
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
C
C L1=NUMBER OF SETS COMPUTED.
C
C WRITE FIRST TWO PAGES.
L1=IP1
CALL PRINT
WRITE (6,53) (NAME(N),N=1,IP1)
WRITE (6,52) (NAME(N),N=IP2,I2TP2)
WRITE (6,54)
CALL PRINT2
5 CONTINUE
C
C
C COMPUTE PERCENTS.
C
61
-------
DO 8 1=3,4
L1=ID
L=I-2
WRITE (6,51) L
WRITE (6,53) (NAME(N),N=1,ID)
WRITE (6,52) (NAME(N),N=I2TP3,13TP2)
WRITE (6,54)
DO 6 K=1,ID
DO 6 J=1,IA
6 X(I,J,K)=X(L,J,K)/X(L,J,IP1)'M00.
DO 7 K=l,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 CL95(I,K)=CL
CALL PRINT
WRITE (6,53) (NAME(N),N=1,ID)
WRITE (6,52) (NAME(N),N=I2TP3,I3TP2)
WRITE (6,54)
CALL PRINT2
8 CONTINUE
DO 10 J=1,IA
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
-------
DO 12 K=1,ID
TOT(5,K)=0.
DO 11 J = l',I A
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=O.Q
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=1,1 A
IF (X(l,J,K).EQ.O) X(1 J,K)=.004
IF (X(2J,K).EQ.O) X(2,J,K)=.004
V=(DLOG 10(X(2,J ,K))—DLOG10(X( 1 ,J ,K)))/(X( 5 J ,K))
V2(J,K)=10.**V—1.0
15 SUM 1(K)=SUM 1(K)+V2(J ,K)
SORT K VALUES
DO 17 K=l,ID-
DO 17 J=1,1 A
IF (V2(J,K).GT.O) 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
-------
0106
0107
0108
0109
0110
0111
0112
0113
0114
0115
0116
0117
0118
0119
0120
0121
0122
0123
0124
0125
0127
0128
0129
0130
DO 19 K=1,1D
DO 19 J=1,IA
V=X(8,J,K)-SUM1(K)/AI
IF (V.GT.O) GOTO 18
X(10,J,K)=V
GO TO 19
18 X(9,J,K)=V
19 CONTINUE
C
C
C
C COMPUTE SUM AND MEAN FOR K VALUES
C
C
DO 21 K=1,ID
C
DO 21 1=6,10
V=0.0
C
C
DO 20 J=1,1 A
20 V=V+X(I,J,K)
C
TOT(I,K)=V
21 M(I,K)=V/AI
C
C
C CALCUALTE STANDARD DEVIATION, STANDARD ERROR, AND 95% CONFIDENCE
C LIMITS OF K VALUES.
C
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)
64
-------
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
-------
0157
0158
0159
0160
0160
0161
0161
0162
0163
0164
0165
0166
0167
0168
0169
0170
0171
0172
0173
0174
0175
0176
0177
0178
0179
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))
30 CALL STDEV2 (STD(7,K),STE(7,K),CL95(7,K))
C
C
C CALCULATION OF STANDARD DEVIATION K-NET AND ITS DISTRIBUTION.
C
C
C
DO 35 K=1,ID
V=0.0
W=0.0
DO 34 J=1,IA
IF(X(9,J,K)> 32,32,31
31 V=V+(X(9,J,K)**2)
32 IF(X(10,J,K)) 33,34,34
33 W=W+(X( 10,J ,K) * * 2)
34 CONTINUE
C
c
V=V/(AI—1.0)
W=W/(AI—1.0)
STD(9,K)=SQRT((V/(V+W))**2*(STD(8,K)**2))
CALL.STDEV2(STD(9,K),STE(9,K),CL95(9,K))
STD(10,K)=SQRT((W/(V+W))**2*(STD(8,K)**2))
35 CALL STDEV2(STD(10,K),STE(10,K),CL95(10,K))
C
C
C
CALL PRINT3
C
CALCULATE 0 AND ITS STANDARD DEVIATION
C
DO 41 K=1;ID
M( 11 ,K)=(M{9 ,K)/M(6 ,K)) *M(7 ,K)
STD(11>K)=SQRT(STD(7,K)**2*((M(9,K)/M(6,K))**2))
CALL STDEV2(STD( 11 ,K),STE( 11 ,K),CL95( 11 ,K))
C
C
C
C
C CALCULATION OF D
66
-------
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
C
C
M(12,K)=M(7,K)—M(11,K)
C
C
C CALCULATION OF STANDARD DEVIATION OF D
C
STD(12,K)=SQRT(STD(7,K)**2*(1.—M(9,K)/M(6,K))**2)
CALL STDEV2 (STD( 12,K),STE( 12 ,K) ,CL9 5 (12 ,K))
C
C
C CALCULATE TL.
C
C
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))
C
C
C CALCULATE TR.
C
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))
C
C
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)1M(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(71K)
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)JV1(13,K),STD(131K),STE(13,K))CL95(13,K)
WRITE (6,66)
WRITE (6,65) NAME (K),M(14,K),STD(14,K),STE(14,K),CL95(141K)
WRITE (6,67)
C
67
-------
0218
0219
0220
0221
0222
0223
0224
0225
0226
0227
0228
0229
0230
0231
0232
0233
0234
0235
0236
0237
0238
0239
0240
0241
0242
0243
0244
0245
0246
0247
0248
0249
0250
0251
0252
DO 43 L=l,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)1M(6,K),M(9,K),M(10,K))M(11,K),M
1(12,K)
44 CONTINUE
C
CALL FACTOR
STOP
C
45 FORMAT (IX, 13F6.3/13F6.3/4F6.3)
46 FORMAT (1214)
47 FORMAT (215)
48 FORMAT (10A8)
49 FORMAT (1X,I2,2(2A4,A2),I2,2(1X,I2),7F7.2)
50 FORMAT('l')
51 F0RMAT('1,,'C72X,I1,/3X,'STATION',3X,'LATITUDE',3X,'LONGITUDE',
-5X,'DATE')
52 FORMAT(48X,8(3X A8))
5 3 FORMAT('+',47X,8(3X,A8))
54 FORMAT(/)
55 FORMATS 1',IX,'RATES OF CHANGE FOR '.AS^OX/S.D.'JX.'S.E.'^X,
-'95% LIMIT'//)
56 FORMAT(2X,'MEAN OF K',13X,'= NET',3X^8,'=',3X^11.4/)
57 FORMAT(2X,'MEAN OF + ( K - NET ) = T',5X,A8,'=',3X,4F11.4)
58 FORMAT(27X,T7)
59 FORMAT(2X,'MEAN OF - ( K - NET ) = T\5X,A8,'=\3X,4F11.4)
60 F0RMAT(27X,'0'/)
61 FORMAT(2X,'MEAN OF + K',11X,*= I',5XtA8,'=',3X,4F11.4//)
62 FORMAT(2X,'MEAN OF - K',11X,'= O + D\1X,A8,'=\3X,4F11.4//)
63 F0RMAT(26X,'0',5X,A8>',3X,4F11.4/)
64 FORMAT(26X,'D',5X,A8,'=',3X,4F 11 A!)
65 FORMAT(26X,'T\5X,A8,'=\3X,4F11.4)
66 FORMAT(27X,'L7)
67 FORMAT(27X,'R')
68 FORMATdSX.'MEANC'^X.'MEAN C'.^X/lMOX.'T'^X.'-'^X/T'^X,
-':',5X,,0',5X,'-',5X,'D',9X,'N719X,'2M1X,'1,27X,'I',11X>'OV)
69 FORMAT(/97X,F 11.4)
70 FORMAT(2X,A8,F10.4,' =',F10.4,' ( 1.0 +',F10.4,' +',F10.4,3(F12.4)
V)')
END
C
C
68
-------
0001
0002
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( 2 3)
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,LI,L
C
DO 1 J=1,IA
1 WRITE (6,3) CST(L,J),(ALOC(L,J,K),K=l,6),(CDATE(L,J,K),K=l,3);(X(I
1 J,K),K=1,L1)
C
C SKIP TO BOTTOM OF PAGE
N=(68-(IA+6))/2
C
DO 2 J=1,N
2 WRITE (6,4)
C
RETURN
C
3 FORMAT (5X,I2,5X,2A4,A2,2X,2A4,A2,2X,I2,2('-',I2),8F11.2)
4 FORMAT (/)
END
C
C
SUBROUTINE PRINT2
DIMENSION TABLE(30)^ONTH(12)^.LOC(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,TAiBLE,lA,I,K,KD,ID
COMMON /BLKl/NAME,TOT^,STD,STE,CL95.ALOC.YR,CST.CDATE^IONTH,LI,L
WRITE (6,1) (T0T(I,J),J=1,L1)
WRITE (6,2) (M(I J),J=1,L1)
WRITE (6,3) (STD(I,J)J=1,L1)
WRITE (6,4) (STE(rj),J=l,Ll)
WRITE (6,5) (CL95(I,J),J=1,L1)
RETURN
C
1 FORMAT (34X,'TOTALS',6X,7F10.4)
2 FORMAT (/34X,'MEAN',8X,7F 10.4)
3 FORMAT (/34X,'S.D.',8X,7F10.4)
4 FORMAT (/34X,'S.E.\8X,7F10.4)
5 FORMAT (/34X,'95% CL',6X,7F10.4)
END
C
-------
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
0035
0036
0037
0038
0039
0040
70
SUBROUTINE PRINT3
DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6),TOT(10,8),STD(23.R)
1, STE(23,8),CL95(23,8)
REAL *8X00,60,7)
REAL *8NAME(23)
REAL *4MEAN,M(17,8)
INTEGER CST(2,60),CDATE(2,60,3)
COMMON X,TABLE,1 A,I,K,KD,ID
COMMON/BLK1/NAME,TOT,M,STD,STEjCL95,ALOC,YR,CST,CDATE,MONTH,LI,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 1 J=l,lA
1 WRITE (6,7) CST( 1 ,J),X(2,J,K),X( 1,J,K),X(5 J,K),(X(IX J,K),IX=6,10
1).
WRITE (6,8)
WRITE (6,17) TOT(2,K),TOT(1,K),TOT(5,1)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 (6il3)NAME(K)
WRITE (6,17)CL95(2,K),CL95(1,K),CL95(5,1),(CL95(L,K),L=6,1Q)
WRITE (6,12)
WRITE (6,15) NAME(K)
2 CONTINUE
RETURN
3 FORMAT ('1',IX,'STATION')
4 FORMAT (12X/C',9X,'C,,1 IX,'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,,R7)
7 FORMAT (4X,I2,lX,2F10.2,2X,3F10.4,3Fli.4)
8 FORMAT (/)
-------
0041
0042
0043
0044
0045
0046
0047
0048
0049
0050
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
9 FORMAT ('+',94X,'MEANS')
10 FORMAT (¦+"-,94X,'S.b.")
11 FORMAT C+')94X)'S.E.')
12 FORMAT (,+',94X,,95% CONFIDENCE LIMITS')
13 FORMAT C+', 99X,A8)
14 FORMAT (V,i02X,A8)
15 FORMAT (V,116X,A8)
16 FORMAT ('+',94X,'TOTALS')
17 FORMAT(/9X,5F 10.4,3F11.4)
END
C
C
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.YR 1 ,YR2 ,DA1 ,DA2 .DAYS
INTEGER CST(2,60),CDATE(2,60,3)
COMMON /BLK1/ N AME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,LI,L
COMMON X,TABLE ,1 A,I ,K ,KD ,ID
DAYS=0
NT=0
M01=CDATE(1 J,l)
DA1=CDATE( 1J ,2)
YR1=CDATE( 1J ,3)
DA2=CDATE(2,L,2)
YR2=CDATE(2 ,L, 3)
M02=CDATE(2,L,1)
AMO=MO 1
C
DO 4 I=YR1,YR2
A=I
LEAP=0
IZ=A/4.
Z=IZ
Z=Z*4.
IF (I.EQ.YR1) GO TO 1
GOTO 2
1 DAY S=3 6 5-(MONTH(MO 1 )+D A1)
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
-------
0033 IF (I.FAP.FQ.l) C.O TO 5
0034 GO TO o
0035 5 IF (M02.LT.3) NT=NT-1
0036 6 YR=NT-365+M0NTH(M02)+DA2
0037 YR=YR/365.
0038 RETURN
0039 END
C
C
0001 SUBROUTINE TDIST (T)
0002 REAL *8X( 10,60,7)
0003 DIMENSION TABLE(30)
0004 COMMON X,TABLE,IA,I,K,KD,ID
0005 11=IA-1
0006 AI=I1
0007 IF (II) 1,1,2
0008 1 WRITE (6,11) I
0009 GO TO 10
0010 2 IF (I1.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.)*(AI-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.)*(AI-40.)
0019 T=TINT+2.021
0020 GO TO 10
0021 6 IF (I1.LT.121) GO TO 7
0022 GO TO 8
0023 7 TINT=((2.000-1.980)/40.)*(AI-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 (T,'I INT TABLE =', 13)
0031 END
C
C
72
-------
0001
0002
0003
0004
0005
0006
SURKOi n INK RTDF.V (S.IJM X. XH AH.STO.ST1? .CI ,$}•
REAL *8X( 10,60,7)
DIMENSION TABLE( 30)
COMMON X,TABLE,IA,I,K,KD,ID
DEV=0.
SUMX=0
0007
0008
DO 1 J=1,IA
1 SUMX=SUMX+X(I,J,K)
0009
0010
AI=IA
XBAR=SUMX/AI
0011
0012
0013
DO 2 J=1,IA
DEV=(XBAR-X(I,J,K))**2+DEV
2 CONTINUE
0014
0015
0016
0017
0018
0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
C
C
STD=SQRT(DEV/(AI-1.))
STE=STD/SQRT(AI)
CALL TDIST (T)
CL$=T*STE
END
SUBROUTINE STDEV2 (STD,STE,CL$)
REAL *8X( 10,60,7)
DIMENSION TABLE(30)
COMMON X,TABLE,IA,I,K,KD,ID
AI=IA
STE=STD/SQRT( AI)
CALL TDIST (T)
CL$=T*STE
RETURN
END
73
-------
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
ooro
0031
0032
0033
0034
C SUBROUTINE FOR PROGRAM FOR ESTIMATING SYSTEM RATES
C 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), COVl(7), COV2(7)
REAL »4MEAN>I(17,8)JV1R(7)
REAL *8X(10,60,7),V2(6Q,7);NAME(23),V1(7)
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,LI,L
COMMON/BLK2/MR
C
C
C CALCULATE CORRECTION FACTOR FOR STANDARD DEVIATION
C
AI=IA
C
DO 14 K=1,ID
C
IF (M(8,K)) 1,4,5
1 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,KM(AlfM(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 TO 8
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)-yj*(M(8,K)+((AI*M(9,K))/Vjj)-M(8tK))**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
C
C
74
-------
^35 DO 9 J=1,IA
_j36 9 W=W+(X(8J,K)-M(8,K))**2
C
C
0037 W=W/(AI—1.0)
0038 C=((W—V)AV)**2
C
C CALCULATE CORRECTED STD,6,7,AND 8
C STD( 15,K) IS CORRECTED STD(6,K)
C
0039 STD(15,K)=SQRT(C*STD(6,K)**2)
0040 CALL STDEV2 (STD(15,K))STE(15,K),CL95(15,K))
C
C STD(16,K)IS CORRECTED STE(7,K)
C
0041 STD(16,K)=SQRT(C*STD(7,K)**2)
0042 CALL STDEV2 (STD(16,K),STE(16,K)1CL95(16,K))
C
C STD(17,K)IS CORRECTED STD(8,K)
C
0043 STD(17,K)=SQRT(C*STD(8,K)**2)
0044 CALL STDEV2 (STD(17,K)iSTE(17,K),CL95(17,K))
C
C CALCULATE CORRECTED STD(9,K) AND STD(10,K)
C
0045 V=0.0
C
C
0046 DO 11 J=1,1 A
C
0047 IF (X(9,J,K)) 11,11,10
0048 10 V=V+X(9J,K)**2
0049 11 CONTINUE
C
C
C
0050 V=V/(AI—1.0)
0051. W=0.0
C
C
005 J DO 13 J=1,IA
C
0053 IF (X(10J,K)) 12,13,13
0054 12 W=W+(X(10J,K))**2
0055 13 CONTINUE
C
C
C 75
-------
56 W=W/(A1—1.0)
C
C STD(18,K) IS CORRECTED STD(9,K)
C
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))
C
c
C STD(19,K) IS CORRECTED STD(10fK)
C
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))
C
C CALCULATE CORRECTED STD(20,K) CORRECTED STD(11,K)
C
0061 STD(20,K)=SQRT(STD(16,K)-*2*(M(9,K)/M(6,K))**2)
C
C
0062 CALL STDEV2 (STD(201K),STE(20,K),CL95(20,K))
C 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))
C
C CALCULATE STD(22,K) CORRECTED STD(13.K)
C
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»
C
C CALCULATE STD(23,K) CORRECTED STD(14,K)
C
0067 STD(23,K)=SQRT(STD(16,K)**2*(1.0/M(7,K)**2)**2)
0068 CALL STDEV2 (STD(235K),STE(23IK)1CL95(23IK))
C
C
0069 14 CONTINUE
C
C
0070
C
DO 15
0071
WRITE
0072
WRITE
0073
WRITE
0074
WRITE
0075
WRITE
76
-------
'6
Ou/7
0078
0079
0080
0081
0082
0083
0084
0085
0086
0087
0088
0089
0090
0091
0092
0093
0094
^95
v>096
0097
0098
0099
0100
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
C
C
16 FORMAT ('l',40X,'CORRECTED STANDARD DEVIATIONS'//,2X,'RATES OF CHA
INGE FOR ',A8,30X,'S.D.',7X,'S.E.',4X,'95% LIMIT'//)
17 FORMAT (2X,'MEAN OF K',13X,'= NET',3X,A8,'=',3X^11.4/)
18 FORMAT (2X,'MEAN OF + ( K - NET ) = T'^X^S.^'^X^Fll^)
19 FORMAT (27X,iV)
20 FORMAT (2X,'MEAN OF - ( K - NET ) = T,,5XA8,,=',3XP4F11.4)
21 FORMAT (27X,'OV)
22 FORMAT (2X,'MEAN OF + K\llX,'= 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,'L7)
28 FORMAT (27X/R')
C
RETURN
END
77
-------
APPENDIX
Program for estimating system rates based on sample values paired to mean values.
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.
C PROGRAM FOR ESTIMATING SYSTEM RATES BASED ON
C SAMPLE VALUES PAIRED TO MEAN VALUES.
C
C
0002
0003
0004
0005
0006
0006
0007
0008
0009
0010
0011
0012
0001
DIMENSION TABLE(30)^lONTH(12)^ALOC(2,60,6),TOT(10,8),STD(23,8)l
1, STE(23,8),CL95(23,8),VAR1(7),VAR2(7),VAR3(7),SUM1(7),SUM 2(
27), SUM3(7), SUM4(7)j_COVl(7), COV2(7), IA(2), AI(2)
REAL MMEAN,M(17,8),MR(7)
REAL •8X(10,60,7),V2(60,7j,NAME(23),Vl(7);
INTEGER CST(2,60),CDATE(2,60,3)
COMMON X,TABLE,IA,IB,I,K,KD,ID
COMMON /BLKl/ NAME,TOTjVl.STD.STK.CL
COMMON /BLK2/MR
1 FORMAT (IX,13F6.3/13F6.3/4F6.3)
READ (5,1) TABLE
2 FORMAT (1214)
READ (5,2) MONTH
READ (5,3) IA(l)'lA(2),ID
3 FORMAT (315)
C
78
-------
79
C CALCULATE INDEXES.
C AI NUMBER Ol STATIONS CONVERTED TO A REAL NUMUiiK.
C AI3 AI(1) + AI(2)
C IA3 IA(1) + IA(2)
C IP1 ID + 1
C IP2 ID + 2
C I2TP2 2 * ID + 2
C I2TP3 2 * ID + 3
C I3TP2 3* ID + 2
C J2T IA(1) + IA(2)
0013 AI(1)=IA(1)
0014 AI(2)=IA(2)
0015 AI3=AI(1)+AI(2)
0016 IA3=IA(1)+IA(2)
0017 IP1=ID+1
0018 IP2=ID+2
0019 I2TP2=2*ID+2
0020 I2TP3=2*ID+3
0021 I3TP2=3*ID+2
0022 J2T=IA(1)+IA(2)
C
C CLEAR X ARRAY.
C
0023 DO 4 1=1,10
C
0024 DO 4 J=1,J2T
C
0025 DO 4 K=1,IP1
0026 4 X(I,J,K)=0.0
C
0027 WRITE (6,9)
C
C READ IN DERIVATIVE NAMES AND CONCENTRATION LEVEL ON UP TO 3 CARDS.
0028 READ (5,5) NAME
0029 5 FORMAT (10A8)
C
C READ IN DATA.
0030 6 FORMAT (1X,I2,2(2A4,A2),I2,2(1X,I2),7F7.2)
C
0031 DO 7 1=1,2
0032 IB=IA(I)
C
0033 DO 7 J=1,IB
0034 7 READ (5,6) CST(I,J),(ALOC(I J,L),L=1,6),(CDATE(I,J,L),L=1,3),(X(I,
TJ,K),K=1,ID)
C
C
C COMPUTE TOTAL OF EACH STATION.
-------
c
0035 DO 8 1=1,2
0036 IB=IA(I)
C
0037 DO 8 J=1,IB
C
0038 DO 8 L=1,ID
0039 8 X(I J,IP1)=X(I,J,L)+X(I,J,IP1)
C
C
C WRITE HEADING OF FIRST TWO PAGES.
C
0040 DO 15 1=1,2
0041 IB=IA(I)
0042 L=I
0043 9 FORMAT ('1')
0044 10 FORMAT ('17C72X,II,/3X,'STATION',3X,'LATITUDE',3X,'LONGITUDE',
1 5X/DATE')
0045 WRITE (6,10) I
0046 11 FORMAT (48X,8(3XA8))
0047 12 FORMAT ('+',47X,8(3X,A8))
0048 WRITE (6,12) (NAME(N),N=1,IP1)
0049 13 FORMAT (/)
0050 WRITE (6,11) (NAME(N),N=IP2,I2TP2)
0051 WRITE (6,13)
C
0052 DO 14 K=1,IP1
0053 CALL STDEV (TOTAL,MEAN,SD,SE,CL)
0054 TOT(I,K)=TOTAL
0055 M(I,K)=MEAN
0056 STD(I,K)=SD
0057 STE(I,K)=SE
0058 14 GL95(I,K)=CL
C
C L1=NUMBER OF SETS COMPUTED.
C
C 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,I2TP2)
0063 WRITE (6,13)
0064 CALL PRINT2
0065 15 CONTINUE
C
c
C COMPUTE PERCENTS.
80
-------
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
C
DO 181=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=I2TP3,13TP2)
WRITE (6,13)
C
DO 16 K=1,ID
C
DO 16 J=1,IB
16 X(1,J,K)=X(L,J,K)/X(L,J,IP1)*100.
C
C
DO 17 K=l,3
CALL STDEV (TOTAL,MEAN ,SD ,SE ,CL)
TOT(I,K)=TOTAL
M(I,K)=MEAN
,STD(I,K)=SD
STE(I,K)=SE
17 CL95(I,K)=CL
C
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
C
CALL NCOMP
C
C CALCULATE TOTAL AND MEAN OF N.
C
DO 20 K=1,ID
TOT(5,K)=0.
C
DO 19 J=1,IA3
19 TOT( 5 ,K)=TOT( 5 ,K)+X( 5 J ,K)
C
20 M(5,K)=TOT(5,K)/AI3
C
C
DO 22 K=1,ID
V=0.0
C
81
-------
0098
0099
0100
0101
0102
0103
0104
0105
0106
0107
0108
0109
0110
0111
0112
0113
0114
0115
0116
0117
0118
0119
0120
0121
0122
0123
DO 21 J=1,1 A 3
21 V=(M(5,K)-X(5.J,K))**2+V
C
STD( 5 ,K)=SQRT( V/(AI 3-1.0))
22 CALL STDEV2 (STD(5,K),STE(5,K),CL95(5,K))
C
C
C CALCULATE K VALUES.
C DATA IN TWO SETS ARRANGED CHRONOLOGICALLY
C CALCULATE K VALUES
C
DO 24 K=1,ID
SUM1(K)=0.0
IB=IA(2)
C
DO 23 J=1,IB
IF (X(2,J,K).EQ.O.) X(2,J,K)=.004
V=(DLOG 10(X(2 J ,K))—ALOG 10(M( 1 ,K)))/(X( 5 ,J ,K))
V2(J,K)=10.**V—1.0
23 SUM 1(K)=SUM 1(K)+V2(J,K)
C
IB=IA(1)
C
DO 24 J=1,IB
IF (X(i;j,K).EQ.0.) X(1,J,K)=.004
V=ALOG 10(M(2 ;K))-DLOG10(X( 1J ,K)))/X(5 ,J+IA(2),K) * .43429)
y2(j+IA(2),K)=10.**(V* 43429)—1.&
24 SUM1(K)=SUM1(K)+V2(J+IA(2),K)
c
c
C SORT VALUES
C
DO 26 K=1,ID
C
DO 26 J=1 ,J2T
IF (V2(J,K).GT.O.) GO TO 25
X(7,J,K)=V2(J,K)
GO TO 26
25 X(6,J ,K)=V2(J ,K)
26 X(8,J,K)=X(7J,K)+X(6J,K)
C
C CALCULATE K-NET
C
DO 28 K=1,ID
C
82
-------
0124
0125
0126
0127
0128
0129
0130
0131
0132
0133
0134
0l 35
0136
0137
0138
0139
0140
0141
0142
0144
0145
0146
0147
0148
0149
0150
0151
0152
0153
0154
0155
DO 28 J=1,J2T
V=X(8J,K)-SUM1(K)/AI3
IF (V.GT.O) GO TO 27
X(10J,K)=V
GO TO 28
27 X(9J,K)=V
28 CONTINUE
C
C COMPUTE SUM & MEAN FOR K VALUES
C
DO 30 K=1,ID
C
DO 30 1=6,10
V=0.0
C
DO 29 J=1,J2T
29 V=V+X(I,J,K)
C
TOT(I,K)=V
30 M(I,K)=V/AI3
C
DO 311=6,10
C
DO 31 K=l,7
STD(I,K)=0.0
STE(I,K)=0.0
31 CL95(I,K)=0.0
C
C CALCULATE STANDARD DEVIATION, STANDARD ERROR, AND 95% CONFIDENCE
C 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
1B=IA(2)
C
DO 33 J=1,IB
V2(J,K)=DLOG(X(2,J,K))-DLOG(X(l,J,K))
SUM2(K)=V2(J,K)+SUM2(k)
SUM3(K)=(DLOG(X(l J,k))-ALOG(M(l,k)))**2+SUM3(K)
33 SUM4(K)=(DLOG(X(2 J,K))-ALOG(M(2,k)))* •2+SUM4(K)
C
DO 34 K=1,ID
83
-------
0156
0157
0158
0159
0160
0166
0167
0168
0169
0170
0171
0172
0173
0174
0175
0176
0177
0178
0179
0180
0181
0182
0183
0184
0185
0186
0187
0188
0189
0190
0191
0192
0193
0194
0195
0196
84
VARl(K)=(.43429/M(l,K))**2*SUM3(K)/(AI3-1.0)+(-.43429/M(2,K))**2
1*SUM4(K)/(AI3-1.0)
34 VI (K)=SUM2(K)/AI3
C
DO 36 K=1,ID
VAR2(K)=((1.0/M(5,K))**2*|VARl(K))+(-Vl(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),GL95(8,K))
C
C CALCULATE THE DISTRIBUTION OF VARIANCE BETWEEN +K AND-K.
C
DO 41 K=1,ID
V=0.0
C
DO 38 J=1 ,J2T
IF (X(6,J,K))38,38,37
37 V=(X(6J,K)-M(8,K))* *2+V
38 CONTINUE
C
V=V/AI3-1.0
W=0.0
C
DO 40 J=1,J2T
IF (X(7,J,K)) 39,40,40
39 -W=(X(7,J,K)-M(8,K))* *2+W
40 CONTINUE
C
W=W/AI 3-1.0)
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))
C
C CALCULATION OF STANDARD DEVIATION K-NET AND ITS DISTRIBUTION.
C
DO 46 K=1,ID
V=0.0
W=0.0
C
,DO 45 J=1 J2T
IF(X(9,J ,K))43,43,42
42 V=V+(X(9,J,K))**2)
43 IF(X( 1 Q,J,K))44,45,45
44W=W+(X(10,J,K)"2)
45 CONTINUE
-------
0197
0198
0199
0200
0201
0202
0203
0203
0204
0205
0206
0207
0208
0209
0222
0223
0224
0225
0226
0227
0228
0229
0230
0231
0232
0233
0234
0235
0236
C
V=V/(AI3-1.0)
W=W/(AI3-1.0)
STD(9,K)=SQRT(((V/(V+W))**2*(STD(8,K)**2))
CALL STDEV2(STD(9,K),STE(9,K),CL95(9,K))
STD(10,K)=SQRT(((W/(V+W))**2*(STD(8,K)"2))
C
46 CALL STDEV2(STD(10,K),STE(10,K),CL95(10,K))
CALL PRINT3
C
C CALCULATE O AND ITS STANDARD DEVIATION
C
DO 52 K=1,ID
M( 11 ,K)=(M(9,K)/M(6,K)) *M(7 ,K)
STD(11,K)=SQRT(STD(7,K)**2*((M(9,K)/M(6,K))**2))
CALL STDEV2 (STD(11,K),STE(11,K),CL95(11,K))
C
C
C CALCULATION OF D
M( 12,K)=M(7 11 ,K)
C
C CALCULATION OF STANDARD DEVIATION OF D
C
STD(12,K)=SQRT(STD(7,K)**2*(1.-M(9,K)/M(6,K))**2)
CALL STDEV2 (STD(12,K),STE(12JK),CL95(12,K))
C
C CALCULATE TL.
C
M(13;K)=-1.'0*l(l,K)jVl(6,K),M(9,K)^l(10,K)AI(ll,K),
-M(12,K)
0264 70 FORMAT(2X,A8,F10.4,' =',F10.4,' ( 1.0 +',F10.4,' +',F10.4,3(F12.4)
.
0265 71 CONTINUE
0266 CALL FACTOR
0267 STOP
0268 END
C
C
0001 SUBROUTINE PRINT
0002 DIMENSION TABLE(30),MONTH(12),ALOC(2,60,6),TOT(10,8),STD(23,8)u
1, STE (23,8),CL95(23,8),IA(2),AI(2)
0003 REAL *4MEAN^1(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,I,K,KD,ID
0007 COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,L1 ,L
C
86
-------
0008 DO 1 J = 1,1B
0009 1 WRITfc (6.3)c:Si,(l-.J).(AUX:
-------
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 /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATF.
-------
0047
0048
0049
0050
0051
0052
0053
0054
0055
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
11 FORMAT (V,94X/95% CONFIDENCE LIMITS')
12 FORMAT <¦+', 99X.A8)
13 FORMAT C+\102X,A8)
14 FORMAT (V,116X,A8)
15 FORMAT ('+',94X)'TOTALS')
16 FORMAT (/9X,5F10.4,3F11.4)
17 FORMAT (4X,I2,lX,F10.2,12X,3F10.4,3Fll.4)
18 FORMAT(4X,I2,1X,10X,F10.2,2X,3F10.4,3F11.4)
END
C
C
SUBROUTINE TDIST (KA,T)
REAL *8X( 10,60,7)
DIMENSION TABLE(30), IA(2), AI(2)
COMMON X,TABLE,IA,IB,I,K,KD,ID
I1=KA-1
AK=I1
IF (II) 1,1,2
1 WRITE (6,11)1
GO TO 10
2 IF (I1.LT.31) GO TO 9
IF (I1.LT.41) GO TO 3
GO TO 4
3 TINT=((2.042-2.021)/10.)*(AK-30.)
T=TINT+2.042
GO TO 10
4 IF (Il.Lt.61) GO TO 5
GO TO 6
5 TINT=((2.021-2.000)/20.)*(AK-40.)
T=TINT+2.021
GO TO 10
6 IF (II .LT. 121) GO TO 7
GO TO 8
7 TINT=((2.000-1.980)/40.)*(AK-60!)
T=TINT+2.000
GO TO 10
8 T=l.960
GO TO 10
9 T=TABLE(I1)
10 RETURN
C
11 FORMAT (T,'I INT TABLE =',I3)
END
C
C
89
-------
0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
0011
0012
0013
0014
0015
0016
0017
0018
0019
0001
0002
0003
0004
0005
0006
0007
0008
0009
0010
0011
0001
0002
0003
0003
0004
0005
0006
0007
0008
0009
00
SUBROUTINE STDKV (SUMX.XRAR.STniSTF.CI.!^
REAL *8X(10,60,7)
DIMENSION TABLE(30), IA(2), AI(2)
COMMON X,TABLE,IA,IB,I,K,KD,ID
DEV=0.
SUMX=0.
C
DO 1 J=1,IB
1 SUMX=SUMX+X(I,J,K)
C
AI(I)=IA(I)
XBAR=SUMX/AI(I)
C
DO 2 J=1,IB
DE V=(XBAR-X(I ,J ,K)) * "2+DEV
2 CONTINUE
C
STD=SQRT(DEV/(AI(I)-1.))
STE=STD/SQRT(AI(I))
KA=IB
CALL TDIST (KA,T)
CL$=T*STE
END
C
C
SUBROUTINE STDEV2 (STD,STE,CL$)
REAL «8X( 10,60,7)
DIMENSION TABLE(30), IA(2), AI<2)
COMMON X,TABLE,IA,IB,I,K,KD,ID
AI3=IA(1)+IA(2)
STE=STD/SQRT (AI3)
KA=IA(1),+IA(2)
CALL TDIST (KA,T)
CL$=T*STE
RETURN
END
C
C
SUBROUTINE NCOMP
DIMENSION TABLE( 30),MONTH(12),ALOC(2,60,6),TOT(10,8),STD(2 3,8)
1, STE(23,8),CL95(23I8),IA(2), AI(2)
DIMENSION IYRVAL( 5),IT0TDA(5)
REAL *4M(17,8)
REAL ~8X(10,60,7),NAME(23)
INTEGER CST( 2,60) ,CDATE( 2,60,3)
INTEGER SUMDA(2)
COMMON X,TABLE,IA,IB,I)K,KD,ID
COMMON /BLKl/ NAME,TOT^,STD,STE,CL95 ALOC,YR,CST,CDATE^lONTH,Ll,L
IJ=0
-------
DO 13 1=1,2
K=0
SUMDA(I)=0
ITOTDA(I)=0
STORE INITIAL TIME
M01=GDATE(I,1,1)
IDA1=CDATE(I,1,2)
IYR1 =CDATE(1,1,3)
IYRVAL(1)=365
A=IYR1
IZ=A/4.
IF (IZ*4.EQ.IYR1 .ANDJW01.GT.2) IYRVAL(1)=366
INT l=MONTH(MO 1 )+IDAl
FIND TIME INTERVAL OF FIRST DATE TO END OF FIRST YEAR
INT2=IYRVAL(1)-INT1
IB=IA(I)
DO 4 ]=1,IB
M02=CDATE(I ,J, 1)
IDA2=CDATE(I J,2)
I YR2=CD ATE( IJ, 3)
COMPUTE YEAR VALUES-365 OR 366
IF (IYR1.EQ.IYR2) TO TO 3
K STORES NUMBER OF INTERVENING YEARS
K=IYR24YR1
DO 1 L=1,K
IYRVAL(L+1)=365
A-IYR1+L
lZ=A/4.
IF (IZ*4.EQ.IYR1+L) IYRVAL(L+1)=366
1 CONTINUE
COMPUTE INTERVAL OF LAST YEAR
LASTl=MONTH(M02)+IDA2
CHECK FOR LEAPYR OF LAST YEAR
IF (IYRVAL(K).EQ.366.AND.M02.GT.2) LAST=LAST+1
LAST2=IYRVAL(K)-LAST1
COMPUTE TOTAL DAYS OF DATA SET
INT=FIRST YEAR
K-K+l
K= NUMBER OF YEARS
91
-------
0040
0041
0042
0043
0044
0045
0046
0047
0048
0049
0050
0051
0052
0053
0054
0055
0056
0057
0058
0059
0060
0061
0062
0063
0064
0065
0066
0067
0068
0069
0070
0071
0072
DO 2 L=1,K
2 ITOTDA{I)=ITOTDA(])+IYRVAL(L)
C
C SUM ALL DAYS OF YEARS INVOLVED
ITOTDA(I)=ITOTDA(I)-INTl-LAST2
SUMDA(I)=SUMDA(I)+ITOTDA(I)
GO TO 4
3 INT2=M0NTH(M02)+IDA2
ITOTDA(I)=INT2-INTl
SUMDA(I)-SUMDA(I)+ITOTDA(I)
4 CONTINUE
C
C COMPUTE MEAN OF TIME
MEANT=SUMDA(I)/IA(I)
C SUBTRACT FIRST YEAR
IX=MEANT+INT 1
IF (K.EQ.0) GO TO 7
C
DO 5 L=1,K
IF (IX.LT.IYRVAL(L)) GO TO 6
IF (IX.EQ.IYRVAL(L)) TO TO 6
IX=IX-IYRVAL(L)
5 CONTINUE
C
C COMPUTE YEAR
6 IYR=L-1+IYR1
IF (IYRVAL(L).EQ.366.AND.IX.GT.59) IX=IX-1
GO TO 8
7 IF (IYRVAL(1).EQ.366.AND.IX.GT.59) IX=IX-1
IYR=CDATE(I,1,3)
C
8 DO 9 N=l,12
C LOCATE MONTH
IF (IX.LT.MONTH(N+l)) GO TO 10
IF
-------
0073
0074
0075
0076
0077
0078
0079
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
C
c
c
c
c
DO 11 K=1,ID
X(5,IJ ,K)=YR
11 CONTINUE
12 CONTINUE
13 CONTINUE
RETURN
END
SUBROUTINE LEAPYR (J,IMON,IDAY,IYR)
DIMENSION TABLE(30), MONTH(12), ALOC(2,60,6), TOT(10,8), STD(23,8)
1,STE(23,8), CL95(23,8), IA(2), AI(2)
REAL *4MEAN, M(17,8)
REAL *8X(10,60,7),NAME(23)
INTEGER YR1.YR2,DAI,DA2,DAYS
INTEGER CST(2,60),CDATE(2,60,3)
COMMON /BLK1/NAME,TOT,M,STD,STE,CL951ALOC,YR,CST,CDATE,MONTH,Ll,L
COMMON X,TABLE,IA,IB,I,K,KD,ID
DAYS=0
NT=0
IF (I.EQ.2) GO TO 1
M01=IM0N
DAl=IDAY
YR1=IYR
MO 2=CD ATE( 2, J, 1)
DA2=CDATE(2J,2)
YR2=CDATE(2,J,3)
GO TO 2
1 M02=IMON
DA2=IDAY
YR2=IYR
MO 1 =CD ATE( 1 ,J, 1)
DA 1=CDATE( 1J ,2)
YR1=CDATE(1 J,3)
2 AMO=MO 1
0026
0027
0028
0029
0030
0031
0032
0033
DO 6 IY=YR1,YR2
A=IY
LEAP=0
IZ=A/4.
Z=IZ
Z=Z*4
IF (IY.EQ.YR1) GO TO 3
GO TO 4
93
-------
0034
0035
0036
0037
0038
0039
0040
0041
0042
0043
0044
0045
0046
3 DAYS=365-
-------
0001
0002
0003
0002
0003
0004
0005
0006
0007
0008
0009
0010
0011
0042
013
0014
0015
0016
0017
0018
0019
0020
0021
0022
0023
0024
0025
0026
0027
0028
0029
0030
CF031
0032
0033
0034
C SUBROUTINE FOR PROGRAM FOR ESTIMATING SYSTEM RATES
C BASED ON SAMPLE VALUES PAIRED TO MEAN 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), COVl(7), COV2(7), IA(2), AI(2)
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,IB)I,K,KD,ID
COMMON /BLK1/ NAME,TOT,M,STD,STE,CL95,ALOC,YR,CST,CDATE,MONTH,LI,L
COMMON /BLK2/ MR
C
C
C CALCULATE CORRECTION FACTOR FOR STANDARD DEVIATION
C
IA3=IA(1)+IA(2)
AI3=IA3
C
DO 14 K=l, iD
C
IF (M(8,K)) 1,4,5
1 JX=(AI3*M(7,K)—AI3*M(10,K))/M(8,K)
VJ=JX
V=(((AI3*M(10,K))/VJ)**2)*VJ
IF ((M(8,K)+( (AI3*M(10,K))/VJ))*VJ—(AI3*M(7,K))) 3,3,2
2 V=V+(AI3*M(7,K)-VJ*(M(8,K)+( (AI3*M(10,K) )/VJ))-M(8,K))»*2
V=V+( ((AI3*M(6,K))/AI3—VJ—1.0))—M(8,k))**2*(Ai3—VJ—1.0)
GO TO 8
3 V=V+( ((AI3*M(6,K))/(AI3—VJ))—M(8,K))**2*(AI3—VJ)
GO TO 8
4 JX-AI3/2.0
VJ=JX
V=( (AI3*M(6,K)/VJ)**2)*VJ
V=V+( (AI3*M(7,K)/VJ)**2)*VJ
GO TO 8
5 JX=(AI3 *M(6,K)—AI3 *M(9,K))/M(8,K)
VJ=JX
V=(((AI3*M(9,K))A^J)**2)*Vjf
IF ((M(8,K)+((AI3*M(9,K))/VJ))*VJ—(AI3*M(6,K))) 6,7,7
6 V=V+(AI3*M(6,K)—VJ*(M(8,K)+((AI3*M(9,K))/VJ))—M(8,K))**2
V=V+(((Al3*M(7,kj)/(AI3—Vj—1.0))—M(8,k))**2*(AI3—VJ—1.0)
GO TO 8
7 V=V+( ((AI3*M(7>K))/(AI3-VJ))-M(8,K))^2*(AI3-VJ)
8 V=V/(AI3—1.0)
W=0.0
C
C
95
-------
0035 DO 9 J=1,IA3
>036 9 W=W+(X(8,J,K)—M(8,K))**2
C
c
0037 W=W/(AI3—1.0)
0038 C=( (W—V)AV)**2
C
C CALCULATE CORRECTED STD,6,7,AND 8
C STD(15,K) IS CORRECTED STD(6,K)
C
0039 STD(15,K)=SQRT(C*STD(6,K)"2)
0040 CALL STDEV2 (STD(15,K),STE(15,K),CL95(15,K))
C
C STD(16,K)IS CORRECTED STE(7,K)
C
0041 STD(16,K)=SQRT(C*STD(7,K)**2)
0042 CALL STDEV2 (STD(16,K),STE(16>K),CL95(16,K))
C
C STD(17,K) IS CORRECTED STD(8,K)
C
0043 STD(17,K)=SQRT(C*STD(8,K)**2)
0044 CALL STDEV2 (STD(17,K),STE(17,K),CL95(17,K))
C
C CALCULATE CORRECTED STD(9,K) AND STD(10,K)
C
0045 V=0.0
C
C
0046 DO 11 J=1,IA3
C
0047 IF (X(9,J,K)) 11,11,10
0048 10 V=V+X(9J,K)*;*2
0049 11 CONTINUE
C
C
C
0050 V=V/(At3—1.0)
0051 W=0.0
C
C
0052 DO 13 J=1,IA3
C
0053 IF (X(10,J,K)) 12,13,13
0054 12 W=W+(X(10,J,k))**2
0055 13 CONTINUE
C
C
C
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W=W/(AI3—1.0)
C
C STD(18,K) IS CORRECTED STD (9,K)
C
STD(18,K)=SQRT((V/(V+W))**2*C*(STD(8,K)**2))
CALL STDEV2 (STD(18,K),STE(18,K),CL95(18,K))
C
C
C STD(19,K) IS CORRECTED STD(10,K)
C
STD(19,K)=SQRT((W/(V+W))**2*C*(STD(8,K)**2))
CALL STDEV2 (STD(19,K),STE(19,K),CL95(19,K))
C
C CALCULATE CORRECTED STD(20,K) CORRECTED, STD(11,K)
C
STD(20,K)=SQRT(STD(16,K)"2*(M(9,K)/M(6,K))**2)
C
C
CALL STDEV2 (STD(20,K),STE(20,K),CL95(20,K))
C 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))
C
C CALCULATE STD(22,K) CORRECTED STD(13,K)
C
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))
C
C CALCULATE STD(23,K) CORRECTED STD(14,K)
C
STD(231K)=SQRT(STD(16,K)**2*(1.0/M(7,K)**2)**2)
CALL STDEV2 (STD(23,K),STE(23,K),CL95(23,K))
C
C
14 CONTINUE
C
C
DO 15 K=1,ID
C
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)
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)
97
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1079 WRITE (6,24) NAME(K)1M(11,K),STD(20>K),STE(20,K))CL95(20,K)
J080 WRITE (6,25) NAME(K),M(12,K))STD(21)K),S;TE(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)JW(14,K),STD(23,K),STE(23;,K),CL95(23,K)
0084 WRITE (6,28)
0085 15 CONTINUE
C
C
0086 16 FORMAT (' 1 \40X,'CORRECTED STANDARD DEVIATIONS'//,2X, 'RATES OF CHA
INGE FORf 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,T/)
0090 20 FORMAT (2X,'MEAN OF - ( K - NET ) = r,5XlA8,,=',3X,4F11.4)
0091 21 FORMAT (27X,'OV)
0092 22 FORMAT (2X,'MEAN OF + K',11X,'= r,5X,A8,'= ,3X,4F11.4//)
0093 23 FORMAT (2X,'MEAN OF - K',11X,'= 0+DMX,A8,l=',3Xt4F11.4//)
0094 24 FORMAT (26XI'0',5X,A8,'=,,3X,4F11.4/)
0Qg5 25 FORMAT (26X,'D',5X,A8,'=',3X,4F11.4/)
0096 26 FORMAT (26X)'T',5X,A8,'=,,3X,4F11.4)
0a97 27 FORMAT (27X,'L7)
0098 28 FORMAT (27X,'R')
C
0099 RETURN
0100 END
98
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