FINAL REPORT
SURVEY OF
MATHEMATICAL MODELS
AD HOC COMMITTEE ON MATHEMATICAL MODELING
RESEARCH PANEL
FEDERAL WORKING GROUP ON PEST MANAGEMENT
EPA-540/9-77-C21
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This report has been compiled by the Criteria and
Evaluation Division, Office of Pesticide Programs,
U.S. Environmental Protection Agency, in conjunc-
tion with other sources listed on the title page.
Contents do not necessarily reflect the views and
policies of the Environmental Protection Agency,
nor does mention of trade names or commercial pro-
ducts constitute endorsement or recortinendation for
use.
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FINAL REPORT
SURVEY OF PREDICTIVE mTHEMATICAL MODELS
Ad Hoc Conmittee on Mathematical Modeling
Research Panel
Federal Working Group on Pest Management
Dr. P. R. Datta, Chairman EPA
Dr. J. Mossiman NIH
Mr. L. S. Joel NBS
Dr. J. E. Fletcher - NIH
Dr. R. G. Nash USDA
Captain T. A. Miller DOD
Mr. Duncan MacDonald DOI
Dr.'William Schaff NQAA
Dr. R. J. Peterle Ohio State (ERDA)
Dr. S. D. Haseltine Ohio State (ERDA)
Dr. Arthur Emery CNR (DOD)
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CONTENTS
Pages
Overview i
Introduction 1
Background 2
Committee's Accomplishments in the "Action Program" 5
Results of "Test Runs" 8
Knowledge Gained in the Use of the DYNAMO Compiler in a
Simulation System 9
Structure and Extension of Parameters or Compartments
in the Modified Model' 11
Paucity or Lack of Data in Various Compartments of the
R&M Model " 16
DDT in the Atmosphere 16
DDT in Soil 17
DDT in Oceans 18
DDT in Rivers and Lakes 19
Sensitivity Analysis 20
Critical Analysis and Usefulness of the R&M Model or its
Modified Version 22
Related Miscellaneous Work Initiated and/or Accomplished ... 28
Aid to Policy and Decision-Making Process 29
Aid in Evaluation for the Registration and Regulation
of Pesticides 30
Recommendations 32
Figure and Appendices 34
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The work of the ad hoc Committee on the survey of mathematical model (s)
capable of predicting the fate and movement of pesticides or other toxic
pollutants in the environment has been terminated. In its surveillance
of the existing global models, the Committee finds that the Banders and
Meadows (R&M) model is the most detailed global model available, and that
other available models can be integrated into it. The R&M model has been
found to be suitable for refinement and adaptation as new data and knowledof-
beoome available.
The interagency committee members from NBS have implemented the
DYNAMO simulation language with the R&M model. Thousands of parametric
"test runs" using the primitive compiler, DYNAMO O, with various scenarios
and the available data or imaginary data in various compartments with or
without modification of the structure of the model by the addition or
deletion of parameters or compartments were conducted at NBS for purposes
of: (1) gaining familiarity with the interfacing of the R&M model computer
technology and the DYNAMO simulation language; (2) assessing the structure
and extension of the parameter compartments of the R&M model for purposes
of defining the refinements required; (3) determining the priority of
"data needs" in each compartment of the model via sensitivity analysis;
and, (4) analyzing the usefulness of the model concept in the decision-
making process of pesticide regulatory matters.
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After an examination of these results, it became apparent to the
ad hoc Committee members that the perplexities and complexities of
simulation DYNAMO language computer model(s) for application to DDT as a
model pesticide were overwhelming, primarily due to the paucity of data
on DDT in each compartment of the R&M model; although, in truth, there is
more voluminous data on DDT than any other pesticide.
Furthermore, the "test run" results revealed "data needs" in various
compartments, for example:
1. DDT in the abyssal layer of the ocean;
2. Sedimentation below the mixed layer of the ocean;
3. Benthic fish rate of uptake and elimination of DDT;
4. Photodegradation rate of DDT in the atmosphere;
5. Evaporation from the ocean surface and the oil layer of the ocean;
6. DDT in fresh water lakes and sediment;
7. Uptake and elimination of DDT by fresh water fish or other
aquatic organisms; and,
8. Rate and flow of DDT from an aquatic environment to terrestrial
environmental organisms, such as birds.
An in-depth literature survey of DDT data for each compartment of the
model was subsequently completed by Drs. Peterle and Haseltine of Ohio State
University (under a $14K contract frorn ERDA, See Appendix 2). The accuracy
and reliability of these data, however, were never verified due to a lack
of funds, nor was there ever an opportunity to incorporate these data into
the appropriate compartments of the model.
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After the "test runs" had been conpleted and analyzed, the ad hoc
Committee recommended, and was authorized to purchase (EPA Project #2050407} t
a second generation DYNAMO compiler system vastly superior to the DYNAMO 0,
called DYNAMO IL,, which is adaptable to operation on a UNIVAC 1108
computer.
This system was finally installed at NBS after a lengthy delay due to
legal complications in the procurement and contract procedures. The compiler
has recently (July, 1976) undergone acceptance testing at NBS. While it
appears that the DYNAMO simulation language, using the DYNAMO lip compiler, \\
adequate for the resolution of the fate and movement of a pesticide pollutant
in the environment, the complete integration and expected "test runs" have not-
been conducted due to a lack of funds or transfer of funds from EPA to NBS.
A request for funds was denied by EPA.
A systematic investigation regarding "sensitivity analysis" was also not
conducted due to a lack of funds. It is of the utmost importance that
sensitivity analysis be conducted before the use of any mathematical model to
predict the fate and movement of a pesticide (such as DDT) or other pollutant
in the environment.
Other related activities of the Committee included: (1) the obtaining
of several ocean core samples from the U.S. Geological Survey, and the
arranging for their preliminary analysis by the Buefort laboratory of NCAA.
However, a further systematic investigation was not initiated due to the
Committee's funding constraints; and, (2) the securing from the United Nations
Focal Point Information Center located in EPA information identifying the
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sources of data on the behavior of DDT in the environment in various countries
of the world. However, none of these data was ever obtained due to a lack
of funds and administrative authorization.
The consensus of the interagency committee members is that the predic-
. tive modeling of pesticide flow in the environment is extremely important:
(a) To gain knowledge about the effect of a pesticide in the ecosystem;
(b) To resolve controversy over the use of a pesticide;
(c) To avoid use of an ascientific method;
(d) To obtain scientifically informed judgments on the behavior of a
chemical or pesticide in the environment; and, finally,
(e) To provide a framework for integrating scientific information with
social value judgments in a manner which is scientifically, socially,
and ethically defensible.
For these reasons, a predictive mathematical model would be an invalu-
able tool in the policy and decision-making process and of inestimable worth
as an aid in evaluations for the registration and regulation of pesticides.
At present, the ad hoc Committee is disbanded until EPA or other
agencies e>cpress an intent to support the Committee's reccmrrendations.
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INTRODUCTICN
Pesticides are used as chemical agents for the management of pests
in agriculture and health. The uses of pesticides have considerable economic
benefits in the production of food and fibers and in control of insect-borne
diseases in public health. The presence of residual pesticides and/or
their degradation products in plants and animals, including man, and in
soil, air, water, fish, etc. of the biosphere constitutes environmental
pollution. The persistence and toxicitv of these pesticidal pollutants
could result in the contribution of adverse effect(s) on human health and
welfare.
Reliable methodologies for the quantitative measurement (ppm level or \es?,}
and for the identification of residual pesticides and/or their degradation
products are currently available for direct monitoring and for the establish-
ment of tolerances. However, the rates of movement of residual pesticides
and/or their degradation products and their degree of bioaccumulation, if any,
are difficult to measure directly.
Since it is desirable to understand the fate and movement of pesticides
and/or their degradation products in the ecosystem now and in the projected
future, the development of predictive mathematical models is of importance.
Such predictive mathematical models could be used as an analytical tool in
the formulation of "balance decisions" and scientifically informed judgments
on the use patterns of a specific pesticide.
Based on the published literature, there have been relatively few serious
attempts to develop true quantitative analytical methodologies as models useful
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for determining and/or predicting the residual fate of pesticides and/or
their degradation products or other pollutants in the environment or to survey
those which are available. Thus the raison d etre of this ad hoc Committee.
BACKGROUND
On March 21, 1973, the'Chairman of the Research Panel, FW3PM, asked
Dr. P. Datta of that Panel to organize and chair an interagency and interdisci
plinary ad hoc Ccnmittee to assess the "state of the art" of mathematical imrVl
capable of predicting the behavior of pesticides in the environment, and
to focus attention on the residual fate of DDT via models.
On July 18, 1973, Dr. Datta chaired the first meeting of this ad hoc
Committee which was made up of four Research Panel members as well as variox;-.
resource personnel from NIH, NBS, USDA, NCAA, DOD, and EPA. At this meeting
the Committee discussed, clarified, and resolved its mandate. The ad hoc
Committee's charges were perceived to be basically two-fold and it was
decided to pursue them simultaneously. These were:
l(a) To provide the Research Panel with a compendium of mathematical models
which depict or attempt to the behavior (i.e., degradation,
transport, modification, biomagnification, etc.) of pesticides in soil,.
air, and other environmental components;
(b) To indicate to the Panel those models most suitable and useful for
assessing and predicting pesticide residues in the environment and
the health impact(s) thereof;
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(c) To classify, organize, and evaluate all models related to the
behavior of DDT in the environment. DDT was chosen as the model
compound because substantial data on DDT is in the published
literature; and,
2. To suggest the critical need(s) for research relating to this problem
area.
The ad hoc Committee met for four monthly meetings and reviewed all
available mathematical models on DDT and other pesticides. These models
are of two types:
(1) Those which are primarily descriptive of a specific physical, chemical,
and/or biological process or a concatenation of such processes; and,
(2) Those models which are primarily predictive i.e., intended only to
forecast changes in state over time of an aggregate system, using
parameters which are generally composed of various processes in
ecosystem compartments.
Published models were analyzed for mathematical assumptions, functions,
and underlying theories of mathematics, and for fundamental assumptions which
determine the behavior of specific pollutants in the environment.
The Committee specifically looked into the explicit and implicit expla-
nations contained in each model on DDT as to: how the decisions were arrived
at; what assumptions were included; what information was included; how the
information or data was processed; whether the model under examination made
a "balance decision" on DDT behavior in the environment; and, relevancy of
hazards to wildlife, fish, flora, fauna, and humans.
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As a result of several meetings, the ad hoc Committee reached a consensus
about the following items:
(1) That the literature searches being conducted by individual Committee
members for, and of, available information sources needed to complete
the compendium of mathematical model(s) were proceeding satisfactorily
and, in due time, the cumulative reference materials would be transmitted
to the ad hoc Committee chairman for compilation, etc.; and,
(2) That the survey of the theoretical mathematical models must be supplementi.c
by actual computer runs of existing models, using DDT as a model compound,
in order to gain information on the computational behavior of the models
and to learn computational responses to assumptions of the models and
resolution of various assumptions embodied in the various values of
DDT parameters and, therefore, an Action Program for this specific
purpose must be recommended to the FWSPM.
Such an Action Program was deemed urgently needed in order to:
(a) Indicate to this Committee and to the Research Panel of the FWGPM which
model(s) is/are the most suitable and useful for evaluating and predict-
ing DDT or other pesticide residues in environmental media (i.e. soil,
water, and air) and the health hazards thereof; and,
(b) Identify the critical needs and priorities of research data relating to
the problem areas of environmental safety and health safety.
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COMMITTEE'S ACCQgLISHMENTS IN THE "ACTION PROGRAM"
In late 1974, pursuant to these circumstances and findings, the above
projects were sponsored as follows: NBS, FY 75, Project 12050156, Dr. Goldman
and Mr. Joel; EPA, FY 75, Project #2050407, Mr. Dan Cerelli of TSD/OPP; and
an information retrieval FY 75, support project of ERDA (under contract to
Dr. Peterle of Ohio State University).
The objectives of these interagency projects were: (1) to test existing
predictive mathematical models; (2) to secure a literature survey of the
published data on DDT by information retrieval; and, (3) to identify criticaJ'.
research needs in this field of modeling to facilitate future predicting of
the fate and movement of DDT or other pesticides in the ecosystem of the
biosphere.
The ad hoc Coitmittee members, being volunteers, could not dedicate their
full time to the appropriate research needed for the "Action Program."
Drs. J. Mossiman and J. E, Fletcher of the Computer Division of NIH completed
the survey of the concepts and underlying assumptions of published predictive
models; however, they were not available, due to time constraints, to "test run"
the existing predictive mathematical models.
During their preliminary survey, four existing global models for DDT were
identified. It was decided to confine the "test runs" to the Randers and
Meadows global model (Chapter 3 of Toward Global Equilibrium: Collected
Papers, Wright-Allen Press, 1973)_ because it was apparently the most nearly
complete and the report included the listing of the computer program for the
model in DYNAMO language.
Bearing this in mind, the Committee agreed to undertake the above FY 75
projects in the following terms:
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(a) Mr. L. S. Joel, under the guidance of Dr. A. J. Goldman and the direc-
tion of Dr. W. H. Kirchhoff (Deputy Director of the Office of Air and
Water Measurements, NBS), would "test run" the R&M model using a
"DYNAMO" compiler obtained (gratis) from UNIVAC until EPA transferred
$20K - $25K to allow purchase of a second-generation 11^, compiler and
to cover the costs of computer time sharing and electronic data processing;
(b) Dr. R. J. Peterle of Ohio State University with $14K of ERDA funds, in
close cooperation with Mr. Dan Cerelli of TSD/OPP/EPA, would gather all
the relevant data base information on DDT required for each compartment
or component of the R&M model from the published literature through the.i ir-
respective information-retrieval systems; and,
(c) The results of the "test runs" and the literature survey would be subnuiJ.'--
to the ad hoc Committee mc^rmittently for evaluation purposes and for
identifying critical research and data needs required for the modeling
activity.
The Committee directed NBS to pursue the following activities regarding
the evaluation of the R&M mathematical predictive model:
1. Evaluate the mathematical assumptions in depth underlying the model
parameters;
2. Evaluate the structure of the model;
3. Operate the model and make predictive runs employing various scenarios
future rate application, non-application, etc.;
4. Perform parameter sensitivity analysis of the model;
5. Investigate the possibility of refinement of the model (disaggregation,
seasonal cycles, fish type, river type, soil type, sediment type, etc.)
and model extension; and,
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6. Estimate the scope of applicability of the model and identify critical
data needs and directions for its refinement.
Accordingly, in January 1975, Mr. L. S. Joel of the Applied Mathematics
Division of NBS began to "test run" the model documented in J. Panders'
"DDT Movement in the Global Environment (which is Chapter 3 of Toward Global
Equilibrium: Collected Papers, edited by D. L. Meadows and D. H. Meadows,
Wright-Allen Press, 1973) with the following goals:
(a) To verify the portability of the model by operating it through a DYNAMO
compiler compatible with the NBS computer and its operating system;*
(b) To check that the systen dynamics model accurately represented the
differential equation(s) system which follows directly from the defin-
ing transfer relationship;
(c) To identify the most critical model assumptions and parameters in terms
of sensitivity of outputs; and,
(d) To identify the model assumptions most questionable because of the absence
of corroborating data (or the presence of alternative plausible hypothesr-s
also compatible with data); and,
(e) To identify critical directions and data needs for refining the model.
Also, in 1975, Drs. R. J. Peterle and S. D. Haseltine at Ohio State Univo _. Lty,
and Mr. Dan Cerelli of TSD/OPP/EPA, began to search all the literature on DDT
for each compartment of the model or components of the ecosystem. Drs. Haseltine
and Datta also searched all the EPA information files of the DDT hearings to
obtain data, and Dr. Haseltine indexed the literature references on DDT which
* The "test runs" were conducted using a rather primitive DYNAMO 0 compiler
obtained (gratis) from UNIVAC.
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belonged within the various parameters of the R&M model. The listing of
these references is included in Appendix #2. After a cursory inspection
of this listing, it was readily apparent that several of the published data
and ongoing research were not reflected in the list. A further search of
the literature for data on DDT was deemed warranted, but the necessary funds
were lacking. A follow-up search is still needed.
The data from the above annotated literature list were not submitted,
due to lack of funding by EPA, to academic institutions or other expert scienU;vts
in the various disciplines to evaluate and certify their reliability, accorar^
etc. The Committe believes that the examination of these data would be a
worthwhile task, since the evaluation of the model at NBS was substantially
constrained to mathematical and system theoretical criteria only.
RESULTS OF "TEST RUNS"
Briefly, relative to the above-stated goals for the "test runs," the
results showed:
(a) The model per se is operable on a variety of computers (i.e., is "portsMe"),
but difficulties with the DYNAND compiler system may be encountered in
transferring from one computer installation to another;
(b) Computationally, the DYNAMO model is equivalent to the appropriate system
of differential equations;
(c) & (d)_ As might be expected, the outputs (DDT residues) are highly sensitive to
some model parameters (transfer rates, etc.) and insensitive to others;
and,
(e) The model appears to be suitable for analysis of long-term global behavior
of DDT (and other pollutants), but would require considerable revision
to afford information about concentrations in a more finely grained ecosystem.
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Accurate data is needed for critical parameters in the global model
and a fortiori in any more detailed modifications.
These findings are discussed in detail later.
KNOWLEDGE GAINED IN THE USE OF THE DYNAMO COMPILER
IN A SIMUIATION SYSTEM
In evaluation of a model as a prototype for global tracing of pollutants,
the total programming system which produces the outputs is as important as
the actual model formulation, because such models might be constructed and
run at a variety of sites with differing physical and operational computer
systems. Thus, a narrative description of the implementation experience at NK
(on the UNIVAC 1108 computer) is pertinent to decisions about the utility
of the Banders and Meadows model.
DYNAMO was originally developed in about 1959-60 for the IBM computer
at MIT as a tool for implementing models according to J. W. Forrester's
"system dynamics." A succession of refinements ensued as the modeling
technique gained acceptance, primarily among industrial managers and some
scientists. It seems to be particularly popular with ecological scientists
with orientation toward "systems analysis." The DDT flew model of Banders anr':
Meadows was apparently realized through a "second generation" DYNAMO compiler
on an IBM computer, judging by the program listing in the published version of
their report.
The DYNAMO compiler furnished to NBS by the UNIVAC Corporation was a
translation by a Japanese contractor to UNIVAC, of the original DYNAMO system,
into a form suitable for operation on the 1108 computer. This system is
designated here as DYNAMO 0.
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The R&M model was transcribed for operation at NBS by making the modiri-
cations of the published version necessitated for conformity with the somewjyri
restrictive conventions of DYNAMO 0.
After some time lost in the incorporation of the DYNAMO 0 compiler
into the NBS computer executive system (exacerbated by occasional orient-
alisms in the text of the compilers' documentation), the NBS computer
replicated the model outputs in the Randers and Meadows paper and both
the model and the compiler were provisionally considered operational.
[The difficulty with the computer executive system is not unusual. In
spite of much research and prodigious efforts at standardization over a
period of almost 20 years, portability of complicated computer programs is
a well-known pervasive source of problems in the use of computers. This
is stated to mitigate, partly, the implied dissatisfaction with the DYNAMO 0
compiler.]
Subsequently, however, errors occurred in runs of the transcribed
model with no changes other than variation of the basic time increment of
the model (the magnitude of the smallest computational interval distinct
from the model time "unit" which is 1 year), in the course of the numerical
experiments comparing DYNAMO model outputs with those of Kunge-Kutta
integration of the difference equations. As the model was modified to include
representations of additional flux processes (which were judged to be signi-
ficant because of new baseline data, possible relevance to pesticides with
physical characteristics different from those of DDT, or both), an increasing
difficulty in running the modified versions and finally in compiling them was
encountered. As a result, after the preliminary "test runs," the ad hoc
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Committee recommended purchase of a second generation DYNAMO compiler system
called DYNMO !!, which is roughly equivalent to the version of DYNAMO usec*
by Panders and Meadows, but amenable to operation on a UNIVAC 1108 computer.
Purchase of this compiler was funded by EFA Project #2050407. This system
has just recently (July 1976) completed acceptance tests.
Implementation of DYNAMO lip could not be initiated for six months after
acquisition of the system was authorized as a result of contract negotiations
with the proprietary owner of the system (such delays in acquisition of soft
ware systems are so commonplace as to escape comment, usually). The technical
process of dovetailing DYNAMO IJL, with the computer executive system requires
two additional months.*
STRICTURE AND EXTENSION OF PARAMETERS OR COMPARTMENTS IN THE MODIFIED MODF.i,
The R&M model uses a set of "material budget" difference equations to
trace over time the flow and accumulation of DDT among/in 5 major ecological
"compartments" (soil, air, rivers, oceans, and fish), each considered as a
single homogeneous worldwide aggregate. The flow, which is triggered by
application of DDT and its mathematical analysis, stops short of considering
the uptake of DDT by life forms higher than fish.
Randers and Meadows described the environmental flow of DDT as follows-
"When DDT is sprayed onto a crop or in a horns, only part of it reaches the
target. The rest remains suspended in the atmosphere. Much of the DDT reach> r^
the target also eventually finds its way into the atmosphere by evaporation i ; AH
This DYNAMO IHL, compiler enabled proceeding with the most elaborate
version of the model, in a form which is undoubtedly overburdened
with little bits and pieces of phenomenological representations. The
availability of the up-to-date DYNAMO compiler will facilitate any
process of sensitivity testing and paring the system down to a form in
which it will be more nearly realistic while maintaining the conscision
of Randers and Meadows original version of the model.
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the soil. Once in the air, the pesticide can be carried long distances
before it finally falls back on soil or into the ocean. Some DDT is also
washed downstream in watersheds.
"Some of the DDT in the ocean will be taken up by plankton and other
organisms; as the plankton are eaten by fish, the DDT enters higher animals.
Ultimately, fish-eating birds and man can absorb DDT by eating the DDT-contai.o
ing fish this is the food chain effect. The concentrations of DDT usually
become higher as it progresses up the food chain, an effect commonly called
biological concentration. Some DDT also returns to the ocean through excre-
tion from fish, or simply when the fish dies. DDT residues survive this
long journey because of their great stability. DDT is removed from the
environment at each stage through degradation in soil, in water, and in
living organisms.
"Notice that we chose not to include in the model an explicit represen-
tation of higher levels of the food chain for example, fish-eating birds
and human beings. This exclusion does not invalidate the accounting of DDT
flows because the amounts of DDT that actually enter terrestrial organisms
are very small relative to the flows included in the model. (The excluded
small flows are important to ecosystem stability, however, because they are
relatively concentrated.)
"There is reasonable consensus that Figure 1 does in fact represent the
flow of DDT in the environment. Some disagreement may exist about the rela-
tive importance of DDT transportation in rivers, of the sedimentation of DDT
in oceans, of the uptake of DDT in plants, and of local or regional differences
in DDT concentration, but by and large the heated discussions on DDT do not
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question the structure outlined here. This disagreement occurs over
the precise numerical values involved in the processes illustrated in
Figure 1. For instance, how fast does DDT break down? How much of it
sediments? At what rates does it evaporate? By what factor does it con-
centrate in fish?"
Randers and Meadows also stated, "Experience with radioactive debris
injected into the troposphere by nuclear explosions has established that
mean half-life of residence in the atmosphere for small particles ranges
from a few days to about a month. Following Wbodwell, we assigned that
these data also apply to pesticide crystallites and pesticide absorbed to
dust particles. Vie thus concluded that once injected, DDT particles remain
in the lower atmosphere for a period the precipitation half-life, PHL
varying between a few days or a month. In that time they can easily move
around the globe.
"The amount of pesticide degraded in the air by sunlight and reactive
compounds is unknown (HEW publication "Pesticides and their Relationship").
However, given the short residence time (2 weeks) compared with the degrada-
tion half-life in soil (10 years), it seems safe to assume that the amount
of DDT degraded in the atmosphere is small; hence it was neglected."
One could reasonably say that the R&M model at its given level of detail
can possibly be strengthened, that is made more flexible and better approxi-
i
mative of our perception of the real world, by incorporating representations
jr
of additional sinks or reserviors of DDT, sources of feedback between compart-
ments and processes that mediate (primarily delay) flows between the compartments
of the system. At a somewhat more demanding level of detail, but without
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appreciabiy extending the objective of the irodel/ that of estimating the
global fate of DDT, the model can be expected to furnish more reliable time
predictions if it is disaggregated to represent the effects of spatial
and temporal concentrations resulting from variations in the physical
milieu, e.g., meteorological conditions, and by extending the boundaries to
include higher levels in the trophic chain, hence uptake and release at higher
levels of bioaccumulation.
Panders and Meadows' assumption of relatively small flows in higher trophic
levels was verified by the NBS model test runs in which a very crude replica-
tion of their "fish" equations was used as a representation of "higher carnivores",
with their "DDT in consumed fish" as the exclusive source of input to
this compartment and back-of-the-hand estimates of excretion and mortality
rates furnishing a release rate to the soil.
Phenomena relating to the oceans are of critical importance to the
determination of global persistence of DDT (and indeed of any readily dispersed
microbiotic substance without sufficient volatility for the atmosphere to
become its primary reservoir). For this reason further efforts and resources
should be committed to attempts to improve the state of knowledge of, e.g.,
sedimentation in continental shelves and on the pelagic bottom, surface
evaporation, degradation (metabolic and other), and all possible mechanisms
of transfer from benthic regions to the mixed layer. This should be
done irrespective of any decision to modify or refine the structure of
the current model.
If degradation processes in lakes differ drastically from those in
the oceans, and if lakes are non-negligible catchbasins for "wash off" in
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appreciably extending the objective of the model/ that of estimating the
global fate of DDT, the model can be expected to furnish more reliable time
predictions if it is disaggregated to represent the effects of spatial
and temporal concentrations resulting from variations in the physical
milieu, e.g., meteorological conditions, and by extending the boundaries to
include higher levels in the trophic chain, hence uptake and release at higher
levels of bioaccumulation.
Randers and Meadows' assumption of relatively small flows in higher trophic
levels was verified by the NBS model test runs in which a very crude replica-
tion of their "fish" equations was used as a representation of "higher carnivores",
with their "DDT in consumed fish" as the exclusive source of input to
this compartment and back-of-the-hand estimates of excretion and mortality
rates furnishing a release rate to the soil.
Phenomena relating to the oceans are of critical importance to the
determination of global persistence of DDT (and indeed of any readily dispersed
microbiotic substance without sufficient volatility for the atmosphere to
become its primary reservoir). For this reason further efforts and resources
should be ccranitted to attempts to improve the state of knowledge& of, e.g.,
sedimentation in continental shelves and on the pelagic bottom, surface
evaporation, degradation (metabolic and other), and all possible mechanisms
of transfer from benthic regions to the mixed layer. This should be
done irrespective of any decision to modify or refine the structure of
the current model.
If degradation processes in lakes differ drastically from those in
the oceans, and if lakes are norjhegligible catchbasins for "wash off" in
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land rrasses, global longevity will be affected. Lake and pond phenomena
should be studied more intensively, and in this case the model must be
appropriately extended.
The principal mechanisms absent from the original R&M model are:
(1) photodegradation of DDT in the atmosphere, (2) evaporation of DDT from
ocean surfaces, and, (3) sinking of DDT below the ocean's "mixed layer"
into the benthic deep. For example, with the parameter values chosen,
insertion of (1) and (2) led after 100 simulated years to a total of 30%
less DDT in the 5 stipulated compartments (of the original model), but
more than before in all but the ocean compartment. The sixth compartment
postulated by (3), with the chosen parameters, proved a potent and
quickly reached sink.
The needed modifications will entail substantive restructuring of the
original R&M model and even more stringent data. The possible payoff would
include the possibility of getting much closer to an assessment of perils, if
any, associated with the persistence of DDT, because clearly exposure is more
closely related to local concentration over time than to mean global presence.*
In addition, the disaggregated modified model for the study of spatial concen-
tration will permit one to apply the R&M type modified model to the investigation
of the flow of water-soluble pesticides, such as kepone, or highly persistent
toxic compounds such as PCS.
* During the study, a crude initial attempt in this direction was made,
splitting the R&M soil compartment into .two "continents." DDT was applied
on one of them and the other received its burden through flows from the first.
The experiment proved unrewarding because, totally lacking data, we had to
assume all transport rates.
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PAUCITY OR LACK OF DATA IN VKRIOUS CCM'AR'IMENTS
CSF THE R&M MODEL
DDT in the Atmosphere
Randers and Meadows assumptions were consistent with information availr-' i -
at the time they formulated their model. Current literature continues to
reflect great uncertainty concerning these natters. Woodwell and Craig (197"!v
estimate atmosphere residence time of DDT as high as 3.3 years. Bidlerran
and Olney (1973) determined atmosphere residence time over the Sargasso Sea
at 40-50 days or "20 times shorter than previously estimated for DDT from
rainfall. . .data." But note that their estimate is itself about 3-4 timei,
greater than the 2 weeks cited by Sanders and Meadows in 1968. Similarly,
doubt has been cast on earlier estimates that the rate of photolysis of DDT
is negligible in the atmosphere by Ivie and Casida (1971) who determined thai-
pesticide decay in the atmosphere can be substantially accelerated in the
presence of other compounds which potentiate photolysis. Because of these
considerations and the possibility of evaporation of DDT from the ocean's
surface which results in additional cycling of DDT into the atmosphere (discu<-.ed
further below under "DDT in Oceans"), photolytic decay of DDT was incorporate:.-'-
into the revised model. Model runs losing an "extreme" photodegradation rate
(half-life of 0.1 year) reduced the time of total disappearence of DDT from the
model ecosphere by 30%. The Ccramittse believes that acquisition of data (unavail-
able during the study because of funding constraints) from researchers cur-
rently engaged in measurements of photodegradaticn and effective buoyancy of
pesticides in the atmosphere is important.
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17-
DDT in Soil
Ihe R&M "best estimate" of the fraction of DDT applied by crop dusting
that reaches the soil directly is probably low, in that they assume that the DDT
which is not "on target" is all carried by convection into the atmosphere.
It seems more likely that a substantial fraction falls to earth near the spray.1-'!
target (Wbodwell, 1971; Cramer, 1972}. As R&M point out, in the absence of
definitive physical experiments, one can "experiment" with the model by
varying values of the model parameter AEF (See Appendix 1), which defines the
function of applied DDT which is deposited on soil directly. In any event
(confirming intuition), the short term effect of changing this fraction in
model runs is great only for "soil" levels of DDT, and the long-term effects ;\>r
negligible in all compartments.
Wbodwell, in 1971, stated that the chemical decomposition of DDT in soil.
was probably greater than had been assumed previously (R&M information about
degradation reflects research prior to 1968) . Members of the ad hoc Committee
have been told informally at several symposia that researchers believe that t)"k
chemical degradation of DDT (in air and water as well as soil) is related to
pH and temperature and is probably not negligible, as assumed by R&M, in compcn -
son to biological degradation.
As with the soil/air partition of applied DDT, independent variation
of the degradation rate in soil and the solution rate over the (fairly
substantial) ranges defined between the R&M "optimistic" and "pessimistic"
values, produced very small long-term effects in runs of the model. Increas-
ing the solution rate produced a fairly large rise in the level of DDT in
"rivers" over the short term, a fact which will be discussed under DDT in
Rivers and Lakes.
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Ihe Ccranittee feels that the DDT soil data needs further scrutiny and thai.
the analytical methods used before 1968 for measurement of DDT residues als/p
need to be reviewed.
DDT in Oceans
The oceans in the R&M model are a vast storehouse toward which virtually
all paths point and in which all DDT, except for some minor sinks ashore
(degradation in soil) and some inconsequential losses through "fish consumed"
quietly degrades over a period of about 100 years.
On balance this scheme is plausible, but its integument displays some
lesions into which the virus of skepticism may enter. Firstly, S&M assume
that DDT brought to the ocean surface will eventually dissolve if not
ingested. But Wbodwell suggests that some of the pesticide strongly sorbed
to larger particles of other matter may sink to the bottom over a period of
4 to 7 years. Assuming sedimentation, the disappearance of DDT into the abyss
could be fairly abrupt, and indeed, model runs with this effect included showed
DDT reduced to zero levels in the mixed (upper) layer of the ocean in about
2/3 the time for this to happen in the standard model. But this, too, is
open to question. DDT at great depths can be considered banished to the
figurative abyss only if no route of return to upper levels exists. There is
very little knowledge in this area. Recent research at the Woods Hole
Oceanographic Institute resulted in findings of negligible amounts of DDT
in two or three core samples (suspected, at that, of being contaminated in the
trip to the surface), and examples of benthic fish with low concentrations of
DDT, but high concentrations of DDE.
(Many ocean core samples were obtained from the U.S. Geological Survey for
analysis by the Buefort laboratory of NQAA. Some samples were analyzed along
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with a few benthic fish, turtles, etc. The Committee was unable to invite
the researcher to present his data at a Committee meeting due to a restrictJ c -
of funds.)
At the ocean surface, R&M exclude representation of evaporation on the
grounds that the concentration of DDT in the ocean is very small and, that
if significant evaporation occurs, "the DDT will simply cycle back again
through the atmosphere and settle back on land or water." This statement
provokes some criticism of the conceptual elaboration of the R&M thesis be-
cause it casually dismisses the application of a basic notion of the system
underlying Meadows1 cosmogony - that of feedback analysis.
Moreover, in adducing lew concentrations as a justification for the
omission, R&M disregard the fact that the level of DDT in the ocean in their
model is several orders of magnitude larger over time than the level in any
other compartment, so that with the model's "standard" formulation of exponential
rates of release depending on the absolute magnitude of the source, even small
rates would result in the transfer of large quantities to the atmosphere. Kvar"
oration from the ocean, if it occurs to any substantital extent, can certainly
affect the duration of the DDT life cycle appreciably, a fact which was borne
out by model runs in which evaporation of DDT from the ocean surface was
introduced (constrained by the fraction of DDT in the ocean considered to be
contained in the surface microlayer and hence subject to evaporation).
DDT in Rivers and Lakes
R&M treat rivers as conduits which transfer small amounts of DDT directly
fraa the soil caipartment to oceans (delayed by the low solution rate). Thus,
the identification of all fresh water bodies with rivers is exposited in the
text of their paper, but merely tacit in the model. In point of fact, it can r>e
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conjectured that large lakes (and possibly small ones, also) could be a cr.vi..Ical
distinguishable component of the system of flows of DDT in the biosphere,
their small fractions of the earth's water volume and surface area notwithstanding.
Lakes acting as drains in the vicinity of application sites (and to a
lesser extent elsewhere with respect to precipitated DDT) capture some
portion of the pesticide. Typically, concentrations found in lakes vary
(Wbodwell, 1970; Peterle, 1971; and Portmann, 1971) in an interval far higher
than concentrations in rivers or in the ocean. In lakes, sedimentation might
produce sinks for appreciable amounts and, conconitantly, lakes are feeding
troughs for lacustrine biota, thus allowing for inetabolic degradation of some
DDT (along with chemical degradation, if any, occurring in benthic aquatic
environments) and transmittal of some upward through the food chain. Uptake
of DDT by fresh water fish, of course, affords justification for reopening
the question of extension of the boundary of the basic model to include some
higher level food chain flows, in spite of the lack of strong effect exhibitr
by previously mentioned model runs representing ocean fish as DDT donors
to extra-aquatic predators, because total flows into and from a "carnivore"
compartment may not, after all, be negligible in their effect on global fate.
A summer intern at NBS conducted a search for data on freshwater lakes
and found that very little is known about the rates and routes of DDT trans-
port in and out of lakes. FurthenrDre, she showed justifications for includLv
a lake compartment in the modified R&M model. For details see Appendix 3.
SENSITIVITY ANALYSIS
The identification of critical parameters in the model by comparison of
outputs from model runs resulting from changes in the parameter values is an
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example of a process known as sensitivity analysis. In the current study,
for instance, the rate of sedimentation of DDT in the oceans could be judged
critical because changes in this (rate) parameter substantially affected
the total duration of DDT in the model biosphere. In general, with a compli-
cated system, the response of the system to changes in particular individual
parameters (inputs and/or specifications), or combinations of parameters
while all others remain fixed, is not easily predictable in advance. For a
mathematical model of a system, sensitivity analysis becomes an orderly plan
for operating the model with changes in the values of parameters in order
to learn something about the underlying subject system and to measure, by
comparison with real world data, the validity of the model. Because, in
principle, all possible combinations of changes may have to be examined, this
may become an impossibly expensive and time-consuming task, particularly
if "differential" (very small) as well as "discrete" (moderately large)
changes are of interest.* In consequence, increasing study has been devoted
in the literature of modeling and systems analysis to the development of
sophisticated strategies for obtaining relevant information from tractably
sized sets of parameter combinations. One of the motivations for seeking
more precise estimates of the rate constants in the DDT study is that the
range of tests involving parameters (representing phenomena that are not sub-
ject to actual physical change) can obviously be greatly reduced if these
parameters are known precisely.
The Committee believes that an adequate program of sensitivity analysis
must be an integral step in the development of a refined working model for any
predictive purpose.
Very crude sensitivity tests of the DDT model have required over 100
model runs.
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CRITICflL ANALYSIS AND USEFUINE5S OF THE RSM MDDEL
OR ITS MODIFIED VERSICN
Simple, highly aggregated models such as the Randers/Meadows model
cannot be expected to produce really accurate predictions of the global
persistence or distribution of DDT residues. This is so because the rate
constants that control the behavior of the model are not truly average
values, but composites from analyses of many phenomena that are still
imperfectly understood or "ex post facto" measurements of concentrations who,.- -
actual mean values depend on the very distributions such models are intended
to discover.
But it is also unlikely that any model,whatsoever, within the present
reach of the world coitmunity of science, can give substantially better predic
tions of these global quantities, regardless of wealth of detail or sophist.i-
cation of mathematical structure. By "substantially better," one means that
the great- inherent risk in using model outputs as a primary basis for drastic;
and binding policy decisions would not be perceptibly reduced by replacing
the model by one with greater detail in the next year or two.
Moreover, for establishing a perspective or framework for the
consideration of policy alternatives, for clarifying the relationships that
define the long-term disposition of DDT or any other of a large number of the
potentially undesirable substances that are released into the biosphere, and iY
identifying critical directions for continued research, models of the type
addressed in this report achieve a balance between convenience and reliability
which make them very useful.
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In other words, this model (R&M) is cast in a form which is easy to
comprehend, easy and inexpensive to modify/ and exhibits graphic outputs
that facilitate qualitative analysis, yet mirrors known data well enough to
be plausible. This does not mean that the model should not be improved,
i.e., that a moderately substantial outlay of resources would be either
redundant or foolish. Indeed, it could be stated that additional investi-
gation in several areas is important for tying up loose ends and for the
possibility of obtaining outputs at a level of confidence to soften the
caveat against precipitate use in policy matters. The recannendaticns set
forth herewith for additional disaggregated models for the study of spatial
concentrations, etc., will clarify the above statement.
Broad brush system representation, such as the DDT flow model by Randers
and Meadows which partitions the world into a small number of distinct struc-
turally differentiated homogeneous entities, and in which dynamic processes arc:
described by mean rates of change, are adequate and, one is tempted to say,
uniquely suitable for the study of pesticide flow and fate in the biosphere,
given the present state of knowledge of the physical properties of these
substances.
The output of the model affords an examination of the dynamic course of
the flows which will be of heightened iirportance if the cumulative effect of
identified feedbacks results in cyclic behavior. Moreover, systematic varia-
tion of parameter values or structural alteration of the system can be accom-
plished with far less effort than is needed to make a scratch pad calculation,.
once the basic outputs are conveniently specified and readily grasped in
graphic depictions of system behavior over time.
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Cbjections to "the" model center around the extravagantly vague
estimates of the values of key parameters, and can be dismissed more or
less out of hand because they are tantamount to the denial of -validity
to any model, or more broadly, any descriptive or predictive analysis of
any system whatsoever, unless it is supported by detailed accurate data.
The real problem is a philosphical one relating to our subjective precep-
tions of context and it arises from the uses to which models are put
rather than from their methods of formulation.
Numerical values embedded in informal conjectures retain their aura
of uncertainty. Unfortunately, for many people including those who should
know better, conjectures formalized into computer models accompanied by
printed outputs develop an existence on their own right independent of
the real world from which the models were "correctly" or "incorrectly" abstractO,
and the values of the ancillary parameters come to be accorded Mosaic status,
despite disclaimers. This is the reason why some thoughtful men will not
counterance any model not supported by parameter values below a predetermined
standard of reliability.
Is a model as broadly aggregated as R&M useful for investigating the
global persistence of a pesticide? Superficially, the prospects are
discouraging:
(1) Inasmuch as all the flow and decay rates are global mean values, a
set of estimates of these rates could be employed in an even simpler
formulation to yield projections of total "lurking" duration and the
fraction of the substance entering the food chain, in a few hours
calculation with a desk calculator, at a level of confidence not
substantially below that of the current model with all its paraphernalia
of integration of difference equations.
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(2) The outputs are useless because the rates themselves remain only vaguely
specified, after much painstaking and expensive research, to such an extent
that, for example, our conjectures about the phenomena of sedimentation
in lakes and the ocean, and volatilization from the ocean surface, and
transport and loss to the upper atmosphere, which in an orderly universe
would be mutually exclusive sets of behavior whose selection would depend
solely on mass and perhaps vapor pressure, are so complicated by ques-
tions of sorption, turbulences, differential solution rates, and whatnot,
that any, or none of these processes may, in fact, be significant and, to date,
we are not sure which. In general, the determination of reasonable charac-
teristic values or even acceptable estimates of parameter ranges from scanty
data is a very chancy undertaking.
However, these arguments are straw men, and can be countered as follows:
(1) The supercrude single number of scratch calculations may be adequate as
a benchmark for discussion purposes, but the R&M model, or some modifica
tion- of it, or another equivalently detailed, is necessary for obtaining
any insight into the dynamic behavior of the DDT flows with any one set of
system parameters and a fortiori for any investigation of the sensitivity
of the accumulations and decays to variations in these parameters. Althoix;-i
the construction of the model required orders of magnitude of effort
greater than scratch pad analysis, once it is available for use, varia-
tions in parameter values can be effected (with voluminous graphic as wel.l
as tabular outputs produced) virtually by a "stroke of the pen," while the
back-of-the-hand calculations would have to be repeated on the back of the
hand, i.e., manually, many times, each replication furnishing just one
numerical output.
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(2) As for the difficulty resulting from imprecision in rate estimates, the
validity of any model must suffer great damage if baseline date are inac-
curate. The more elaborate or detailed the model, the greater the risks.
There is a certain virtue in opting for mean-value formulations/ as long
as the analyst or user doesn't hypnotize himself into overconfidence in
the outputs. The point here is that if any formal analysis at all is
worth undertaking (and surely it is better than raw guesswork, once again
given requisite caution in interpreting outputs), realistic bounds should
be imposed on the degree of fine focus in the early stages of the invest'/i
gation, i.e., the initial model, but the extent of abstract simplification
should also be constrained to insure some specificity in the meaning of
the outputs.
One judges models of the R&M type to be substantially at the proper
level of detail for the investigation of the flow and fate of pesticides in
geographical or gecmorphological systems ranging in size from a U.S. state,
e.g., Michigan or Pennsylvania, to global. Global models can illuminate the
mean persistence of pesticides in the various compartments, but there then
remain serious questions concerning local concentrations, even if one tempor-
arily tables questions about toxicity or ecological effects.
Firstly, if one is interested in the differential intensity of use in difr, >-
ent parts of the world, i.e., the extent to which a nation that calls the tune
can cause another to help pay the piper, the inchoate "two-continent" modifica-
tion must be amplified full-scale with detailed mechanisms of transport, meteo::; /-
logical movements, ocean currents, etc., unless it>can be established that the
assumption of homogeneous diffusion over time on which
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the R&M model rests is true. Also, as in our previous suggestion of the pos-
sible importance of lakes, if various routes of transport are accompanied by
different degradation rates, then again, the paths must be explicitly modeled
in spite of ultimate homogeneous distribution.
Another facet of the relationship between concentration and persistence
that must be studied further before it can be neglected in estimating persis-
tence, is the possibility that some release rates are as much dependent on
degree of concentration, as on total levels, as in the model. An example of
this (not necessarily significant except for illustrative purposes) is that,
in general, evaporation is controlled by surface area, i.e., a given mass of
almost anything will evaporate more rapidly strewn or dispersed than it will
in a coherent lump.
Lastly, one has a major phenomenological question which is likely to
require study of local concentrations, where by "local" one means local in
time as well as in space. This is the estimation of probability of episodic
or chronic exposure of individual organisms or of a "species of interest" to
various levels of pesticide concentrations as a determinant of health or
ecological effects. It would obviously be desirable here to mount research
leading to parsimonious model forrmlation. Otherwise, one would be faced with
the necessity of a completely unwieldy, highly detailed, large-scale model,
or a host of small ones, involving stratification according to depth, altitude,
climatology, season, land use, human and zoological population densities, etc.
Ihe consensus of the Committee is that all of these considerations are
germane to a wide spectrum of substances beyond DDT, or even pesticides in
general, and that the relevant modeling methodologies are sufficiently fungible
that continued investigation would be rewarding.
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REIATED MISCELLANEOUS WORK INITIATED AND/OR ACCOMPLISHED
(A) Since this model was based on global .movement and fate of pesticide;-,
(DDT as model compound}, an attempt was made to obtain information on DDT
behavior in environmental media (soil, water, air), ecological systems (fj
fauna), and sediments in various countries through the United Nations PCX , !
Point Information Center located at EPA.
The responses to the inquiry were overwhelming. Scientists from
each country contacted replied and indicated they would extend full cocpc --.-
tion in obtaining the data needed for the development of predictive math>~<: ;.'!-.-
ical model (s) by the interagency Committee and an interest in this novel
undertaking. However, none of these data was ever obtained by the Commit ire
due to a lack of funds and administrative authorization.
(B) A visiting team of Russian scientists under a USA/USSR cooperative
program were very much interested in this U.S. Federal Government-wide
program to develop models to describe the fate of pesticides around the
globe. The details of the correspondence are in Appendix 4.
(C) The Committee approached the U.S. Geological Survey to obtain ocean
core samples for analysis of chlorinated hydrocarbons, particularly DDT
and its major metabolites. Several samples from the Atlantic and Pacific,
Oceans were obtained for curiosity analyses. The samples were sent to th;.
Buefort laboratory of NCAA (Department of the Interior) for analysis. A
few samples (ca 6 to 10J were analyzed; however, a further systematic
investigation could not be initiated due to funding constraints.
(D) The Vfoods Hole laboratory in Massachusetts, the Oceanographic
Institution of Lajola, California, and the Ocean Environmental Science
Department of Rhode Island University are a few examples of interested
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academicians and research scientists in the USA who wished to partici-
pate in the modeling activity by providing data from their "ongoing"
research and to evaluate input data to each compartment of the model.
However/ this was not possible due to lack of funds for contract
research to boost the "ongoing" projects and travel funds for participa-
tion in Committee deliberation activities.
AID TO POLICY AND DECISION-MAKING PROCESS
The decision on mankind's use of DDT or other pesticides should rest on
the answers to the following basic questions:
(1) What are the actual benefits in health, comfort/ and agricultural
productivity gained by a given level of DDT or other pesticide usage?
(2) What are the total costs in human health and in adverse effects on
natural ecological balances incurred as a result of a given level of
DDT or other pesticide usage?
(3) How are the benefits and costs (i.e./ risks) of a given pattern of DDT
or other pesticide usage distributed over space and time?
(4) How do possible alternative measures of insect control compare with DDT
or other suspect pesticide(s) in terms of costs and benefits distributed
over space and time?
Although all these questions are important to policy makers, the third
question is of global interest and the fourth question is of particular interest
to EPA's Substitute Chemical Program of the OPP. The questions concerning
the distribution of DDT's or any other pesticide's costs through
time as a function of different application rate is of interest because
analysis may reveal that policies which seem to be beneficial in view of
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their short-term effects may no longer seen so when the long-term consequence--
of the policy actions are realized and taken into account. The application
of system dynamics analysis to the tine aspect of the third question is relevant
in our effort to devise a "working" mathematical model of predictive quality.
It is hoped that further analysis of the results of test running the R&M
model and its preliminary modifications will identify the research priorities
and data requirements for the development of a model sufficiently detailed,
i.e., disaggregated, to produce significant answers to question (3).
AID IN EVALUATION FOR THE BEGISTPATICN AND
REGULATION OF PESTICIDES
Policy makers and scientists disagree on how scientific facts are to
be integrated with social value judgments. There is an endless debate about
the role of science and scientists in the body politic. Current methodologies
to integrate scientific facts and social value judgments in the formation of
responsible public policy are either of the adversary procedure or the person--
oriented approach. In the adversary method, scientists with differing judgments
are pitted against one another in front of a judge or jury or both. This
method is limited because of an ascientific commitment to victory rather than
truth. In the person-oriented approach, one searches for and uses scientists
with mysterious talents and reputations for wisdom in the exercise of judgments.
This approach is also limited by an ascientific focus on persons and their
motives rather than on the adequacy of methods. The major shortcoming of
these approaches is that they are primarily self-serving.
Recently, scientists have recognised the need for explicit methods or
system analysis methods for decision making in areas where science and public
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interest interface, for exanple, the regulation of pesticides in the
environment. Predictive mathematical model (s) is an explicit method and is
based on system analysis. The predictive model (si is readily subject to
scientific criticism because it meets the required standard of replication,
quantification, logic, and availability to public inspection as to the locus
and degree of perfection in method used and subsequent improvement by modi-
fication. Therefore, this mathematical modeling method is scientifically
defensible. This method also separates scientific judgments frcm social
value judgments.
The predictive mathematical model (s) can be utilized as a scientific
aid for the registration and regulation of pesticides, for example:
(1) When the issue with respect to a given pesticide reduces to whether
there is a significant exposure through environmental transport, or
whether the steady-state build-up of a toxic compound in a certain
compartment of the environment is at an unacceptable level over backgrou)-.
this type of predictive model could permit a much earlier_ decision than
would otherwise be possible;
(2) When one intends to substitute one pesticide for an alternative one and
the decision-maker wants to know what are the choices of pesticides from
which he can choose, a comparison of the steady-state build-up values
for each pesticide under consideration or its toxic degradation products ,! -
the various compartments of the model representing the various compartmeril <
of the ecosystem will quantify the degree of build-up above background
level of each compound. This information would be helpful in the Substitute
Chemicals Program of OPP/EPA;
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(3) If the development of forecasting mathematical model (s) for social
value judgments is carried out simultaneously, analytical method (s) for
integration of the results of the social value judgment model with the
results of the predictive mathematical model (s) for the distribution
of pesticides in the environment could be developed. This would
permit quantitative estimation of the risk/benefit relationship utilizec'
for the formation of public policy. The integrative phase would provide
on overt, rather than covert, process for combining facts and values,
and would integrate the scientific facts with social value judgments
analytically, instead of judgmentally, and thus would provide a socially
responsible public policy which would be scientifically, socially, and
ethically defensible.
RECOMMENDATIONS
The Committee members keenly appreciate the need for mathematical,
statistical, ecological, and biochemical expertise in the development of
workable predictive mathematical model (s) for pesticide flow in the eco-
system. The Committee is also acutely concerned that such endeavor be promoted
in interagency collaboration, with field studies and the leadership needed for
a national effort in this area.
The Committee therefore recommends that the EPA or some other agency with
authority establish a permanent group to:
(a) Conduct research of its own in this endeavor of mathematical modeling
of pesticide flow;
(b) Establish and administer a research grants program and interagency
collaborative studies to develop working model(s) and collect needed data;
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(c) Make an effort to integrate analytically, not judgmentally, the
scientific information and knowledge gained on the behavior of
pesticide (s) in the environment via modeling with social value
judgments; and,
(d) Mvise on the possible import of policy decisions regarding regulation
and registration of pesticides and their effects on the environment by
a scientifically, socially, and ethically defensible means, rather
than by the current widespread use of ascientific methodology (i.e., th<
adversary system and the person-oriented approach).
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FIGURE AND APPENDICES
Figure 1: The Flow of DDT in the Environment (R&M model).
Appendix 1:
(A) Survey of Concepts of Predictive Mathematical Model(s)
by Dr. J. E. Fletcher and Dr. J. Mossiman/ NIH
(B) Brief Description of Mathematical Equations
by Mr. L. S. Joel, NBS
Appendix 2:
Literature Survey of DDT for the R&M Model Compartments
by Dr. S. D. Haseltine and Dr. R. J. Peterle, Ohio State Unviversity
Appendix 3:
Search for Data on DDT Movement in and out of the Freshwater Lakes
Compartment of the Model
by a summer student at NBS
Appendix 4:
Write-Up on USA/USSR Cooperative Program of EPA
by Dr. P. R. Datta, EPA, and Mr. L. S. Joel, MBS
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APPENDICES
1A and IB
FIGURE 1
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APPENDIX 1 (A) !
"SURVEY OF CONCEPTS OF PREDICTIVE MATHEMATICAL MODEL(S)".
by Dr. J. E. Fletcher & Dr. F. Mossiman.
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MODELING CONCEPTS
There are basically two approaches to modeling using deterministic mathe-
matics. The first, called a distribution parameter model, attempts to
describe a given quantity relative to its location in space' and time.
That is, for example, the concentration of DDT might be given or computed
as a function of its coordinates relative to the earth, and as a function
Z A ^ Y mOSTHERE EARTH-S SURFACE
COORDINATION /
Typically such an approach involves a vector-partial differential equation
in time and space of the form.
at
= - -vy-
where f represents sources and sinks, is the flow velocity vector, D.
is the diffusivity of the substance, and
operator:
-- -? *
v =
is the vector differential
The solution of such an equation with the proper entital and boundary
conditions would provide a global map of the DDT concentrations.
However, such a model has net yet been constructed and if it were available,
its solution is not likely to be amendable to computation for the following
reasons:
1. The geometry of the model is highly irregular. That is,
the interfaces of land, air, sea, and rivers have no describ-
able nattem.
-------
2. The flow properties in lakes, rivers, and oceans, as well
as the atmosphere5 are not well defined.
3. The Scale of the model rules cut a numerical solution via
computer due to the large number of variables necessary for
problem descriptions.
Possibly such a model could be used on a local level where the scale
can be controlled.
An alternative to this model is a lumped parameter model where all
quantities lose their spatial identity, in this formulation, all similar
quantities are "lumped" into a single entity or compartment. For example,
air, water, soil, etc., are not distinguished according to location. The
interactions or exchanges among these compartments are called transfer or
exchange rates. An example of such a model is the following:
f(t)
INPUT
X 30
The system of differential equations can be written down as balance equation.*
dci = X 12C-i_ + X 21 C2 + f (t) (inflow minus outflow)
dt
dC2 = X 12C! - X 21 C2 - * 23 C2 + * 32 C3
dt
= X 23C2 - X 32 03 - X 30 C3
The compartments will have initial conditions
G! (o) = A!, c3 (o) = A3,
C? (0) = A-2,
and these initial conditions represent known conditions at the starting
time t = 0. If the exchange rates are specified, then the time course
of the compartments can be calculated from these equations. Note that
one obtains a "lumped average" as a function of time and there is no
-------
identification with geographical location in this model. We list the
following as features of this type of model:
1) Specific entities lose their identity.
2) Transfer rates are necessarily lumped averages.
3) Compartmental values represent lumped averages.
4) Local variations and predictions are lost in the
lumping process.
Advantages:
1) Model generates ordinary differential equations.
2) Solution possible by existing techniques.
3) Fewer parameters and relationships needed for simulation.
4) Easily modified, components added, deleted, etc.
Validating Model:
1) Parameters come from independent measurements or experimental
tests.
2) Results should predict past history or known results.
3) Parameter sensitivity tests to examine relative importance of
factors and assumptions.
4) Predict future trends after model is validated.
Survey of Existing Models:
1) Woodwell et_al., conceptual model of DDT
MIXED
LAYER OF
ocean
-------
EXTENTION QF WOODWELL MODEL
CREWS, W.B.
n. nnin
TERRESTRIAL
BIOTA
MARINE
BIOTA
0.10
m
0.014
BIQDKGH<"DA-
TIOH
0.1 BIODEGRADA1TON
-------
EXTENDED RANDERS & MEADOWS MODEL
APPLICATION
DEGRADATION
BY SUNLIGffl1?
EVAPORATION V
DfuHA-
|)ArjrJON
ABYSS
UFDJAKK
DEGRADATION
-------
APPENDIX 1 (B)
THE "BASIC MODEL" IS THE UNMODIFIED RANDERS AND MEADOWS MODEL
By Mr. L. S. Joel
-------
SOME REMARKS ON THE MATHEMATICAL DDT MODEL
The vehicle which carried our investigation of the utility of mathe-
matical models for the study of pesticide fate in the environment, was a
version of a computer model proposed in 1970-71 by Randers and Meadows,
based loosely on the techniques of J. W. Forrester's "System Dynamics"
and cast in the associated DYNAMO simulation language. That model is docume-^ <^d
in J. Randers' "DDT Movement in the Global Environment", chapter 3 of Toward
Global Equilibrium: Collected Papers (ed: D. L. Meadows and D. H. Meadow;
Wright Allen Press, 1973).
The model uses a set of linear material-budget equations involving
"levels" and transformation rates, to trace over time the flow and accumu-
lation of DDT in a system consisting of five major ecological compartments
("soil," "air," "river," "ocean," and "fish") each considered as a homogeneous
worldwide aggregate. Very large fresh water bodies are considered integral vith
the "ocean," while all other fresh water is subsumed under "rivers."
Life-forms higher than fish are excluded from the model, except to furnish
a "sink" for some portion of the systems DDT, .as noted below.
The driving force for the system is the rate-of application of DDT.
Because in reality, most application is assumed to occur as crop dusting of
cultivated land areas, the model splits application into "air" and "soil"
components to represent convective dispersion during the dusting process.
-------
Page 2
The Randers paper explicitly indentifies the following flows;
(1) from soil-to air by evaporation, to rivers by solutions,
percolation or wash off and out of the system by bacterial
and chemical degradation.
(2) from air-to soil and oceans by precipitation and out of
the system by photochemical degradation*.
(3) from rivers-to the ocean by runoff.
(4) from the ocean-to air by evaporation*, to fish by ingestion
through plankton, and out of the system through sedimentation,
i.e., settling into the abyssal depths*.
(5) from fish-into -;he ocean by excretion and mortality and
out of the system through destructive metafaolysis (labeled
"harmless excretion") and trophic predation by higher life
forms.
The model equations contain terms representing these phenomena ex-
cept that: (1) in the flow from soil to rivers, percolation and wash
off are not distinguished, nor are chemical and biological degradation from
soil. (2) Photodegradation in the atmosphere and evaporation and sedimenta-
tion from the ocean (marked by asterisks above), were excluded from the
originial model based on data available in 1969; the model was modified
at NBS to include them.
i
Sample model equations in the DYNAMO notation give the level of DDT
in rivers:
R.K. = R.J + (DT)(SR.JK - ROR.JK)
-------
Page 3
SR.KL = S.K/(1.S*SHL)
ROR.KL = R.K/(1.5*ROHL)
R = DDT in Rivers (Tons)
S = DDT in Soil (Tons)
ROR = Run off Rate (Tons/Year)
SR = Solution Rate in Soil (Tons/Year)
ROHL = Run off Half-life (Years)
SR = Solution Half -life (Years)
DT = Time step * (Years)
R = 0
RI = RI Initial value
RI « 0
K, J are time signatures for forward and current time periods
JK, KL are time signatures denoting intervals
Written using standard algebraic notation, this set of equations
becomes
^ Yl,k+l - Yl,k + h(>lYl,k + a2Y2,k>
which can be recognized as a iterate in the solution by Euler's method,
of differential equations of the form
(2) YjCt) = a^t) + a2y2(t); Y^O) = YQ
In the difference equation (1) we have replaced DT by h, R.K by Y, . .,
R.J by Y. , , ROR.JK = R.K/(1.5 ROHL) by a9Y0 etc., whereas in (2) the
A > K
-------
Page 4
Use of the term "Half-life" in the parameter designations for the trans-
formations throughout the model indicates that they are exponential function:
of time of the form Y = aY, i.e., Y = YQe~at. (The recurrent constant 1/1. F-
is an approximation of the value I/log 2 which occurs in the determination <...(
the constant a by solving YO/2 = Y0e~a h where n is the given half-life
for the exponential process.)
Thus the underlying set of differential equations is the linear system
Cusing matrix notation)
(3) ? = AY*+ f (tO ?(0) = YQ
where Y is the S component vector of DDT levels, A is a constant matrix and
f(t) is the forcing function, (the application rate of DDT).
The solution of this system for Y(0) = 0 is
(4) Y = ft eACt"s) f(s)ds
0
The system has desirable properties, ecologically speaking, if A is
a "stability matrix", that is, one for which the real parts of all charac-
teristic roots ("eigenvalues") are negative, as turns out to be true in
our case for any plausible range of the parameter-values. For an application
function which becomes zero the value of Y approaches zero. Thus the
underlying mathematical system and the model computational outputs confirm
our intuition by yielding ultimate decay to zero DDT levels after all
application has ceased. Again, the mathematical theory for the differen-
tial equations and for the solutions of the difference equation system
by Euler's method tells that for f(t) constant, that is a constant
-------
Page 5
application rate of DDT, the levels in all compartments rise to values at
which they remain constant, rather that increasing indefinitely. This
was bourne out of runs of the model. Finally, although a simple linear
system can be solved explicitly in closed form, Dynamo using Euler's
method (1) gives convenient stepwise values of the output functions and
(2) as we learned by comparing computations Dynamo solutions to the difference
equations were not appreciably less accurate nor more time consuming
than solution by stepwise Runge-Kutta integration, the most popular standard
method for numerical solution of differential equations.
-------
PLOT SYMBOLS § SCALES
* = APPLICATION'RATE (TONS/YEAR) SCALE: (0 - 500,000)
A = DDT IN ATMOSPHERE (TONS) SCALE: (0 - 50,000)
F = DDT IN FISH (TONS) SCALE: (0 - 500)
0 = DDT IN OCEANS (TONS) SCALE: (0 -2,500,000)
R = DDT IN RIVERS (TONS) SCALE: (0 - 500)
S = DDT IN SOIL (TONS) SCALE: (0 - 500,000)
TIME SIGNATURE: YEAR "0" REPRESENTS 1940
-------
RANGE OF VALUES USED TG TEST THE SENSITIVITY OF THE MODEL
The first group is from the basic model. The second group represents
added terms. "Optimistic" values are those for which disappearance of
DDT residues should be rapid. "Pessimistic" values are those which should
increase
ABF
BWEPY
COF
DFRA
DHLO
DHLS
EHLS
EXHL
HLF
MF
MML
OPCF
PHL
ROHL
SF
SHL
DHLA
EHLO
FOS
SHLA
SPF
persistence of residues.
Optimistic
AIRBORNE FRACTION (DIMENSIONLESS) .1
BODY WEIGHTS EATEN PER YEAR (I/YEAR) 5
CONSUMED FRACTION (DIMENSIONLESS) .5
DEGRADED FRACTION (DIMENSIONLESS) 1
DEGRADATION HALFLIFE IN OCEAN (YEARS) 3
DEGRADATION HALFLIFE IN SOIL (YEARS) 3
EVAPORATION HALFLIFE FROM SOIL (YEARS) .5
EXCRETION HALFLIFE FROM FISH (YEARS) .05
HALFLIFE OF FISH (YEARS) 1
MASS OF FISH (TONS) 6.108
MASS OF MIXED LAYER (TONS) 3.1016
OCEAN- PLANKTON CONCENTR. FACTOR
(DIMENSIONLESS) 1,000
PRECIPITATION HALFLIFE (YEARS) .01
RUN-OFF HALFLIFE (YEARS) .05
SOIL FRACTION (DIMENSIONLESS) .3-
SOLUTION HALFLIFE (YEARS) 200
DEGRADATION HALFLIFE IN AIR (YEARS) .05
EVAPORATION HALFLIFE FROM OCEAN (YEARS) .5
FRACTION SUBJECT TO EVAP. OCEAN .05
(DIMENSIONLESS)
SEDIMENTATION HALFLIFE TO ABYSS (YEARS) 1
FRACTION SUBJECT TO SEDIMENTATION .5
(DIMENSIONLESS)
Best
estimate pessimistic
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10 50
.5 .5
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15 30
10 30
2 10
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3 10
6.108 6.108
3.1016 3.1016
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APPLICATION
PRECIPITATION
IN OCEAN
SOLUTION
IN RIVERS
DOT
IN RIVERS
\
DOT IS REMOVED FROM THE
SYSTEM THROUGH DEGRADATION
IN SOIL, OCEAN AND FISH.
.
RUNOFF
INTO OCEAN\
k. »
DDT
IN PLANKTON
EXCRETION AND
DEATH
CONSUMED ON HIGHER
LEVELS IN FOOD CHAIN
FIGURE 1 1HE FLCW OF DDT IN THE ENVIRONMENT
(Banders & Meadows)
-------
APPENDIX -2
-------
REFERENCES
Abbott, D. C., R. Harrison, J. Tatton, and J. Thompson. 1965. Organo-
chlorine pesticides in the atmospheric environment. Nature 208:
1317-1318.
ppf DDT a and X BHC in London atmosphere rainwater; insufficient to
determine 8-BHC, pp1 TDE or pp' - DDE. Other samples of rain and
snow around London showed similar results, along with dieldrin. Two
samples from remove Scotland -> negligible contamination. 'Scrubbing
out' therefore occurs, -air 10-20 ppb.
Abbot, D. C., R. B. Harrison, J. Tatton, and J. Thompson. 1966.
Organochlorine pesticides in the atmosphere. Nature 211:259-261.
Rain may "scrub" pesticides from the air as it passes through.
How get into atmosphere
(1) Direct drift from spraying - inversely to distance from
spray site - local.
(2) Vaporize from soil - slow, long term process
(3) Industrial processes - pesticide manufacture or mothing
air 10-100X less pesticide than rainwater, but greater
volume may make important. Soil acts as gas chromatograph.
Treated soils will lose, while untreated soils gain.
BHC, DDT, DDE, TDE found and dieldrin - London; Dieldrin - Norfolk;
Aberystwytle - none.
Also breakdown products of organochlorine pesticides are indicated
by GLC.
Acree, P., M. Bowman, and M. Beroza. 1963. Codistillation of DDT with
water. J. Agr. Pd. Chem. 11:278-280.
(1) 25, 30, 35°C, 0. 36-81 ppb, for 24 hr.
(2) Related to DDT concentration in solution up to 100 ppb.
Ahr, W. 1973. Long-lived pollutants in sediments from the Laguna
Atacosa National Wildlife Refuge, Texas. Geol. Soc. Am. Bull. 84:
2511-2515.
(1) Cores 5 cm diameter and 153 cm long
a) Animals may mix DDT in cores in burrowing - so don't trust
dating
(2) Water sediemnt, plants, fish, birds showed Increased DDT levels
Albone, E. S., G. Eglinton, N. Evans, J. Banter, and M. Rhead. 1972.
Fate of DDT in Severn estuary sediments. Environ. Sci. Tech. 6:
914-919.
Field - 14°C - DDT
Estuarine sediments - 46 days, small amount of pp'DDD 48:1, 13:1
pp'DDT/pp"DDD, but all DDT in one spot.
Lab - (under HS) 30 ppm DDT -> 21 days 1/1.1, 1/3-3 DDT/DDD, when DDT
is dispersed. Some polar products.
Anaerobic sewage sludge (H2) -» 1/7-2, 1/17, 1/2, 1/5.4 with more
polar metabolites.
-------
DDT reduced bacterial counts in both anaerobic and aerobic mud
cultures, but most bacteria could decompose DDT to at least ODD.
Aloone, E. S., G. Eglinton, N. Evans and M. Rhead. 1972. Formation of
bis (p-chlorophenyl)-acetonitrile (pp'DDCM) from pp'DDT in anaerobic
sewage sludge. Nature 240:420-421.
400 ml sludge, 5% w/w solids, pH 8.2 at 37°C for 88 days with
7.45 ng 14C - pp2DDT and 20 g minced beef (4.7 uCi)
Liquid -» 0.4 uCi; solid extract -* 1.5 uCi, solid + 1.5 uCi.
Solid extract -» Zones AEG - 62:23:9% radioactivity
A = pp'DDT and pp'TDE
B = pp'DDCN 11.7%
C = ?
Alexander, M. 1965. Persistence and biological reactions of pesticides
. in soils. Soil Sci. Soc. Amer. Proc. 29:1-7-
DDT life in soil = 10 yr (at least)
A general statement on the difficulties of considering soil micro-
organisms omnipotent in biodegrading ability and in applying lab
results to natural conditions.
Concentrates on herbicides (phenols).
Alexander, M. 1973- Nonbiodegradable and ether recalcitrant molecules.
Biotechnol. Bioeng. 15:611-647.
General Review
Anderson, J. P., E. Lichtenstein and W. Whittingham. 1970. Effect of
Mucoi alterans on the persistence of DDT and dieldrin in culture
and soil. J. Econ. Entomol. 63:1595-99.
(1) 1 ppm DDT for 8 days with live mycelium -+42$ recovery by GLC
(fungal enzymes).
(2) l^c DDT at 50 yg/ml for 4 days -> 49.5% in fungus and medium,
47.5$ in aqueous phases, metabolized to soluble molecule
(3) This did not work in soil just in pure cultures.
Anderson, J. P. E. and E. T. Lichtenstein. 1972. Effects of various
soil fungi and insecticides on the capacity of Mucor altemans to
degrade DDT. Can. J. Microbiol. 18:553-560.
(1) Always to water soluble derivatives.
(2) Other fungi depressed or obliterated the response.
(3) Lindane, parathion and Dyfonate also decreased the response.
(4) Fungus does not use DDT as a carbon source (1970).
Antommaria, P., M. Corn, L. DeMaio. 1965- Airborne particulates in
Pittsburgh. Associated with pp'-DDT. Science 150:1476-1477-
June - Dec., 1964, 1.22 m3/min air flow for 14 consecutive days and
nights.
a) Only pp'DDT was quantified although DDD, DDE or pp'DDT was
also present.
b) Highest = 1.36 u/1000 mm3; range 0 -* 0.23 next highest value
-------
Bailey, G. W., R. R. Swank and H. P. Nicholson. 1974. Predicting
pesticide run-off from agricultural lard: A conceptual model.
J. Environ. Qual. 3:95-102.
Single rainfall, single application, single watershed model.
Barker, P. S., F. 0. Morrison, R. S. Wnitaker. 1965. Conversion of
DOT to DDD by Proteus vulgaris, a bacterium isolated from the in-
testinal flora of a mouse. Nature 205:621-2.
Pure pp'DDT in evaporated ethanol in tubes, media introduced and
inoculated with mice gut isolates. 5 days at 30°C.
Methanol and chloroform -* paper chromatography.
(1) P_. vulgaris only -* DDT. (P. vulgaris invades tissues after
death) 5.45 mg DDT
Time of Incubation DDD in mg
(day) 30°C 37°C
6 0.355
10 0.395
15 0.270 0.355
20 0.243 0.300
(3) This does not work with DDE cultures.
(4) £DD being further metabolized from quantity results (paper
chrom. (?)).
Bevenue, A., J. Ogata, and J. Hylin. 1972. Qrganochlorine pesticides
in rainwater, Oahu, Hawaii, 1971. SECT 8:238-241.
Rainwater - 1-14- pp trillion, mean 4 ppt.
Snow - 15 ppt.
Lakewater - 5 ppt.
Birrell, K. S. 1963. Thermal decomposition of DDT by some soil con-
stituents. New Zealand J. Sci. 6(2):l69-
(1) Couldn't obtain reference.
Bishara, R. H., G. Born and J. E. Christian. 1971. An observation on
the multiple development of DDT and some metabolites on aluminum
oxide thin-layer chromatograms. J. Chromatog. 57:444.
DDT, DDE, DDD, DDA, DDMJ were allowed through solvent systems then
hit for 2 min with UV light.
All metabolites showed additional spots of different Rf. This did
not happen when normal light was used.
It did not happen with Uv light when silica gel plates"were used.
Bowman, M. C., F. Acree, Jr. and M. Corbett. I960. Solubility of
Carbon-14 DDT in water. J. Agr. Food Chem. 8:406-8.
i
(1) 1.2 ppb or less at 25°C. |
(2) Does not take into account undissolved DDT particles on carrier. f
-------
Bowman, M. C., F. Acree, C. Lofgren, and M. Eeroza. 1964. Chlorinated
insecticides: Fate in aqueous suspensions containing mosquito
larvae. Science 146:1480-1481.
20 hours at 26.5°C with chlorinated hydrocarbon, then assayed for
residues.'
(1) More than 1/2 of DDT in system lost by codistillation with
H20. This was expected but other insecticides had low
recovery too.
Use electron-affinity gas chromatography on low cone, aqueous
solution.
Bradshaw, J. S., E. L. Loveridge, K. P. Rippee, J. L. Peterson, D. A.
White, J. R. Barton and D. K. Fuhriman. 1972. Seasonal variations
in residues of chlornated hydrocarbon pesticides in the water of
the Utah Lake drainage system - 1970 and 1971. Pest. Monlt. J. 6:
166-170.
DDE in water samples preceded by rain storms. DDT recorded once.
Up to 4 ppb.
Smaller younger fish contained less DDT, use Declining? 0.05-
0.96 ppm DDE in fish.
Bridges, W. R., B. Kallinan, and A. Andrews. 1963. Persistence of DDT
and its metabolites in a farm pond. Trans. Am. Fish Soc. 92:421-7-
0.02 ppm DDT in water
(1) After 3 wk, nothing water.
(2) 8 wk, mud had declined to control levels, but vegetation
still high.
(3) 1 yr after treatment, vegetation levels were control values
(new crop).
(4) Fish - 3-4 ppm after 1 month.
(5) 17 months later, 2-3 ppm DDD and DDE
(6) Crayfish levels generally 1/2 of fish.
Burdick, G. E., H. Dean, E. Karris, J. Skea, R. Karcher and C. Frisa.
1969. DDT: The effect of time and rate of feeding on the repor-
duction of Salmonid fishes, reared and held under control conditions.
(Rough draft, in press).
Gas Chromatography
Loss of fry-brown and brock trout - from females fed DDT and not -
time and dosage controlled
(a) Only one stage showed diff. mortality hatch -» feeding
therefore fry must intake DDT itself though yolk sac. - Brown
trout adults 3.39 mg/kg body wt (44 wk)
Brook trout - below environmental levels.
Burdick, G. E., E. Harris, H. Dean, T. J. walker, J. Skea, and D. Colhy.
1964. The accumulation of DDT in lake trout and the effect on
reporduction. Trans. Am. Fisheries Soc. 93: 127-136.
Lake George, New York
Fry dying at period of fat glyceride absorption. 1951-55, 7,3000 Ib
DDT on Lake for gypsy moth. 1955-57, 25,950 Ib and private use
extensive - some figures pp'DDE or pp'DDT.
-------
All fish and egg samples were dry weight - spectrophotometry, paper
chromatography but calculated as wet.
(1) COnc. of DDE was r.ot correlated ro mortality in fry.
(2) High range of DDT in fish oil, but prep, to water content.
(3) No relation of female content and egg content.
(4) 4.75 ppm is starting point for mortality, 2.95 by spectro-
photometry.
Surge, W. D. 1971. Anaerobic decomposition of DDT in soil: Accelera-
tion by volatile components of alfalfa (J. Agr. Fd. Chem.) 19:375-8.
DDT was stable in aerobic soil, even with alfalfa; main product in
anaerobic is DDD, but radioactivity disappears.
pp'DDT, DDD, DDE and DDA 1.0-2.0 mg. DDT was added to a 100 g
sample and that mixed with other soil; glucose and alfalfa were
added the same way. }
DDT converted to DDD in 46 days (anaerobic was enhanced by alfalfa
distillate), but not in aerobic, this disappeared in 166 days.
DDD and DDE are stable in both anerobic anaerobic and aerobic setups.
Above 2% oxygen the cultures did not transform DDT; at 2% probably
all oxygen was used before transformation began.
Butler, P. A. 1966. Fixation of DDT in estuaries. Trans. NA Wildl.
Conf. 31:184-189.
7-10 ppb will inhibit shell deposition in oysters.
Add anhydrous sodium sulfate to sample to preserve pesticide -
- 3-10X weight of sample homogenized. Oyster concentrate and flush
DDT at constant rate, fish concentrate and only lose when starve.
increased trophic level -* increased DDT.
Castro, T. P. and T. Yoshida. 1971. Degradation of organochlorine
insecticides in flloded soils in the Phillippines. J. Agr. Fd.
Chem. 19:1168-1170.
15 ppm - Laboratory reconstruction
DDT and DDD degraded faster in flooded than upland and in soils
with higher organic components. DDD accumulated in DDT treated
soil. "
Upland = 80$ water holding capacity.
Chacko, C. I., J. L. Lockwood, and M. Zabik. 1966. Chlorinated
hydrocarbon pesticides: Degradation by microbes. Science 154:
893-5.
Aerobic
Cultured for 6 days with 5 to 10 yg of pesticide/ml (gas chroma-
tography).
Nine actinomycetes and 8 fungi.
(1) 6 of 9 actinomycetes, but no fungi degraded DDT to DDD. MOST;
effective Nocardia erythropolis, S_. aureofaciens, S_.
viridochromogenes, and S_. clnnamoneus.
(2) Maximum degradation of 25/5 was achieved in 6 days.
(3) Degradation occurred only in the phase of active growth.,
Check, R. M. and M. T. Canario. 1972. Residues of chlorinated hydro-
carbon pesticides in the northern quahog (hard-shell clam), Mercen-
aria mercenaria - 1968 and 1969. Pest. Monit. J. 6:229-23.
-------
Narragansett Bay, R.I. 56 composite samples pp'DDD in 3 samples
0.026 ppm. No detectable DDE or DDT was found.
Northern bay increased more than southern in residues.
Cliath, M. M. and W. P. Spencer. 1972. Dissipation of pesticides from
soil by Volatilization of degradation products I. Lindane and DDT.
Environmental Science and Technology 6:910-914.
30°C vapor pressure pp'DDE (109 ng/2,) 8x vapor pressure pp'DDT
(13.6ng/i).
a) pp'DDT or pp'DDE (10 yg/g) to Gila silt loam, 30°C.
b) Saturation vapor density - 15-39 vg/£ soil.
c) Vapor density of pp'DDE reach 1.4 ngA in 65 days.
d) 66$ of atmospheric DDT after an agricultural area was pp'DDE
(no rates) (7 yr, not for 14 months).
Soil - 23.1 ppm DDT's
Air - 4.96 ppm DDT's
Cole, H., D. Barry and D. H. Prer. 1967. DDT levels in fish, streams,
stream sediments and soil before and after DDT aerial spray appli-
cation for fall cankerworm in northern Pennsylvania. SECT 2:127-
146.
0.5 lb DDT/acre
Small levels before treatment
Pretreat
("1) Trout 20-100X watershed soils and stream sediments.
(2) White suckers 6-15X the trout (lake)
(3) TDE were found in fish, but not soil.
Post-treat
(₯)TDE and pp'DDT increased for four months after treatment, then
decreased. Soils stayed same.
Cory, L., P. Pyeld, and W. Serat. 1970. Distribution patterns of DDT
residues in the Sierra Nevada mountains. Pest. Mbnit. J. 3-'204-211.
Frogs - pp'DDE was the most common residue.
Contamination throughout even above 12,000 ft.
Highest in central and south, lowest in north.
Highest on west slope, wind blown from aerial spraying irt
California.
Yosemite was high, but sprayed in 1953-1956.
Courtney, C. H. and J. K. Reed. 1972. Accumulation of DDT from food"
and from water by golden shiner minnows, Notemigonus crysoleucas.
Proc. 25th Annual Southeastern Assn. Game and Fish Commis. pp. 426-
431.
Not able to locate.
Cox, J. L. 1970. Accumulation of DDT residues in Triphoturus mixicanus.
Nature 227(5254):192-193.
(1) Not near hot spots of DDT. Gulf of California, mid water fish.
(2) 13-79 ppb wet wt.
(3) t in DDE with t body wt.
-------
of pesticide residues in wild animals. Ann. N. Y. Acad. Sci.
(1) Pesticides low solubility in water makes them cling to plants
and bottom sediments to be taken up by Invertibrates or fish or
both (from water too at least in fish)
(2) If fish or invertebrates become resistant to pesticides by
changing to non-toxic substance, good predators; If merely
store large quantities unchanged * bad for non-resistant
predators.- Also on land, although earthworms and slugs cannot
concentrate as some oysters and fish. Plants accumulate also.
(3) Build-up does not go on indefinitely (storage, metab., absorp-
tion and excretion). If equilibrium at low levels, no problem;
if high * toxicity and death. The equilibrium value may change
with °[ cone.] of pesticides in environment.
(4) Pood habits and metabolism -> residue levels (+ history of
exposures).
(5) Correlation - DDT and + repro. from
(a) the higher residues in declining than non-declining
(b) timing of declines and large-scale treatment
(c) decline in areas of pesticide use
(6) Physiological effects: (a) t liver enzymes; (b) t drug
metabolism -> I fent; (c) nervous system -* aberant behavior;
(d) egg shell thinning; (e) storage in fact - good or bad de-
pending on circumstance; (f) molt (g) disturbance.
Earnest, R. D. and ?. E. Benville. 1971. Correlation of DDT and lipid
levels for certain San Francisco Bay fish. Pest Mbnit. J_.,5-
235-241.
Copy not at OSU libraries.
Eichelberger, J. W. and J. J. Lichtenberg. 1971. Persistence of
pesticides in river water. Environ. Sci. Technol. 5:541-544.
Ems'
(1) Eight wk, 10
(2) Little Miami River water, GLC for 0 and 8 wk determinations.
(3) DDT, DDE and DDD did not degrade; DDE and DDT did not degrade
in distilled water either.
;, W. 1972. Degradation of [liJC]DDT on silica gel G chromatograms
under laboratory conditions. J. Chromatogr. 67:179-181.
(1) In dark
(2) Laboratory daylight
(3) Under a fluorescent lamp - shortwave UV > polar substances
even after only a 15 min period -> 4 compounds
(a) all others caused some polar formation
No quantitative data.
Framer, W. J., K. Igue, W. F. Spencer and J. P. Martin. 1972.
Volatility of Organochlorine insecticides from soil. I. Effect
of Concentration, Temperature, Airflow Rate and Vapor Pressure.
Proc. Soil Sci. Soc. Am. 36(3):443-47.
No water movement (net) during volatilization
(a) controlled by vapor pressure and cone.
(b) Maximum DDT loss was 5 kg/ha/yr, (2-2.2^/day) as soil cone.4-.
-------
8 ml/s air flow, 10% soil water, 100$ humidity, 30°C.
(c) Gila silt loam to ethylene glyccl traps
(d) 10, 50, 100 or 500 yg of C1^ pesticide.
Vapor pressure lindane > dieldrin > DDT
Pateyeva, 0. P. 1972. DDT residues in the soil and in roots of apple
trees folowing repeated spraying. Khim. Sel. Khoz. 10 (3): 195-
198. (Russian)
DDT - 15,000 a/ha, 7 g DDT/£ - 2-3 applications
(1) 0-5 cm had highest DDT
(2) 1 yr after = 52. 4-63. 2$ decrease in DDT
(3) 2-3 yr = 20-36$ decrease in DDT
(4) Apple seeds contained large quantities of DDT (4.6-60 mg/kg),
but not the fruit.
Frank, R. 1971. Unpub. Rep., Provinvial Pesticide Residue testing
laboratory, Ontario Dept. of Agr. and Pood, Guelph, Qnt., in
Hurtig H. (1972).
Pish, Ontario recreational areas
Location No. ppm Muscle % Fat ppm Fat
Trent River 329 .507 1.75 29.0
Holland Marsh 312 .682 2.77 24.6
Muskoka Lakes 519 7.91 3-60 221.4
Great Lakes 404 .750 4.25 17-6
Ottawa River 57 .118 3-22 3.66
Freed, V. H., R. Haque and D. Schmedding. 1971. Vaporization and
environmental contamination by DDT. Chemosphere (in press) Tech
Paper No. , Oregon Agr. Expt. Sta.
(a) Aerosol spray or dust suspension.
(b) Wind erosion of contaminated dust.
( c ) Vaporization
Soil diff . from glass use HL = £l. x Mr§; ]_ Q^ 2 are water and DDT
W2 ?2 Mjf"
68°? (20°C) =0.082 ppm of water f ef-ici-t
86°F (30°C) =0.133 ppm of water ^ lleld 10/' eniclent
0.1 Ib/acre/yr is real value
Soil Exp. - 25°C, 10 ppm DDT in sandy loam soil 1/2 moistened
1/2 dry
No loss in either sample after 10 days
Even when soil in thin layer and constant wind, no loss in 7 days
Thus losses in soil are different from vaporization from the
chemical or from inert surfaces.
French, A. L. and R. A. Hoopingamer. 1970. Dechlorination of DDT by
membranes isolated from Escherichia coll. J. EC on. Entomol . 63 :
756-759.
(1) Washed membranes after lysosomal treatment and osmotic shock
(incubated 4 hr with l
-------
(2) Gas and TLC for DDT analysis
(3) DDT -» DDD occurred and was enhanced by the additions of Kreb's
cycle cofactors (PAD but not NAD)
(4) PAD, inorganic phosphate and unboiled membranes -> 72.6$ DDT,
22.5$ TDE.
Pricke, G. 1972. Comparison of the soil contamination with organo-
chlorine insecticides in 1969 and 1972. (Part I: Large scale
vegetable gardening. Qesunde Pflanz. 24:177-179.
(1) 48$ of garding area free from DDT in 1969.
(2) DDT residue 0.01-0.1 ppm - 1969, Avg = 0.102 ppm.
(3) By 1972, that was down to 1/10 of 1969 levels, Avg = 0.015 ppm.
Gakstatter, J. H. and C. M. Weiss. 1967. The elimination of
dieldrin-Cl1^ and Lindane-C14 from fish following a single sub
lethal exposure in aquaria. Trans. Am. Fish. Soc. 96:301-307-
60-70 (bluegill, Lepomis macrochirus; goldfish, Carassius auratus )
in tank with 0.03 Ppm DDT C-i-4 for 5 to 19 hr.
Recovery tanks for 32 days. Only 50$ of DDT was eliminated. Trans
fer to control fish occurred even though water in control tank was
changed by circulation 2.5 tines/day
Initial cone, of DDT averaged 5-1 Ppm (whole body) after exposure.
George, J. L. and D. E. H. Frear. 1966. Pesticides in the Antarctic.
J. Appl. Ecol. 3 ( suppl. ): 155-167.
Levels in individual organisms.
Georgii, H. W. 1973. DDT in the biosphere. Hippokrates 44(1) : 98-100.
German.
20 yr to degrade DDT
Some 20,000 tens /annum by precipitation - nothing
Gram, C. S., A. R. Kauks, R. L. Richardson, W. M. Sachett and M. K.
Wong. 1972. DDT, DDE and polychlorinated biphenyls in biota from
the Gulf of Mexico. Pest. Monit J. 6:139-143.
Coastal areas were higher than open water samples. Fish, shrimp,
crabs, - all samples were contaminated.
Grib, N. V., V. Kovban and A. Burtsev. 1972. Zapadnogo Poles1 ya
insektitsidami (pri bcr'be s gnusom) na ikk gidrobiologicheskiy
rezhim. Gidrobiol. ,Zh. (kiev) 8(1): 98-101 (Russian) - Abstracts.
0.2 g/m3 DDT was given for 30 rain -» 0.1 mgA DDT in 20 hr..
8 km from point of introduction - 0.18 mgA - 3 hr benthic
0.125-0.175 rag/kg
Death of infusoria and arthropods and proliferation, of diatons
+ Ca, t Mg
-------
Grice, G. D., G. Howey, V. T. Bowen and R. H. Backus. 1970. The col-
lection and presentation of open ocean marine organisms for
pollutant analysis. SECT 7:125-132.
mg/kg lipid (means)
Sorgassum - 0.35 ppb; zooplankton 0.4 ppb; flying fish -2.3 ppb;
trigger fish - 0.1 ppb; dolphin - 49 ppb; mesopelagic fish (5,-
whole) - 12, Chauliodes danae; mesopelagic crustacean (17, whole)
5.7, Systellaspis debilis.
Grzenda, A. R., H. P. Nicholson, J.I. Teasley and J. H. Patric. 1964.
DDT residues in mountain stream water as influenced by treatment
practices.
-------
The avg DDT-R cone, in HgO was directly related to DDT cone, placed
in the bottom. Hydrcsoil (14 ppm CDT and DDD) in the first 5 days
decreasing over the year. Percentage breakdown of DDT to DDD was
inversely related to DDT cone. Algae absorb DDT-R so what is there
in ppm of tissue is a function of water cone, and algae biomass.
Invertebrates followed K20 cone., rapidly up than down.
There was a stepwise Increase in pesticide content of different
trophic levels whether the intervening trophic levels were there
or not. So in lentic environments the rule must be resorption and
absorption vs. release; solubility differences most - lipid and
water but fish -* water -> blood -» fat - 1 x 105 concentration,
pesticides are less hazardous in a eutrophic lake since the sedi-
ments act as a reservior and are more soluble to DDT-R in a eutrophic
lake.
Hartley, G. S. 1969- Evaporation of pesticides. Adv. in Chem Series
86:115-13^. *
1.2 Ib/acre vaporization in England (glass plate)
(a) pesticide vaporization is t for bulk ficw of water to surfac
as it evaporates pulls pesticide with it to + cone, and
volatilization at surface
Helrich, X., S. RAce and J. Reed. 1970. DDT residue disappearance
from field sprayed lettuce. SECT 5(1):30-33.
(1) Lettuce was not at low levels for 50 days.
(2) Rainfall did not affect disappearance rate.
Herzel, ?. 1972. Organochlorine insecticides in surface waters in
Germany - 1970 and 1971. Pest Mcnit. J. 6:179-187.
All in pptr. (ngA range
DDD and DDE found infrequently except for the Berlin Teltowkareal
(suspended solids0
Hicks, G. G. and T. -R. Comer. 1973- Location and consequences of
1,1,1,-triehlora-2,2-0is(p-chlorphenyl) ethane uptake by Bacillus
megaterium. Appl. Micro'Diol. 25:381-357.
No detriment when cultures started with up to 100 pg DDT/ml, but
grown cultures showed enhanced death with only 1 yg/ml DDT
(0.5 u/g dry wt.). Mortality was time and dose dependent. Cell
bound up to 1.7 pg DDT mg/ceil dry wt. in membranes. Some con-
version to DDE with faster cell release. REspiration not inhibited
Membrane appearance was altered.
Holden, A. V. 1962. A study of the absorption of l^C-labelled DDT from
water by fish. Ann Appl Biol. 50:467-477.
Removes rapidly from H20; stored in stomach, pylcric caeca,
intestine, spleen, muscle ana skin.
Lipid expression best, may determine tcxicity to fish, levels in
reproductive organs are dangerous. Don't use static water
-------
(1) [Cone.] at 300X, 80-902 of DDT removed in 10 hr.
(2) Blood-brain barrier held and no build-up there yet.
(3) Don't use static'water in experiments, for toxicity, because
[cone.] DDT 4- too fast.
Horn, W., R. Risebrough, A. Sontar and D. Young. 1974. Deposition of
DDE and polychlorinated biphenyls in dated sediments of the Santa
Barbara basin. Science 184(4l42):1197-1199.
PCB - 19^5, DDE - 1952
Both t to 1967.
Deposition rates 1967, DDE = l.Q x 1C4 g/m3/yr; PCB = 1.2 x 10~^
g/m3/yr.
Hurtig, H. 1972. Long distance transport of pesticides. CEPPIEPPQ
Bull. No. _4:5-25.
Residues in soil: volatilization, photo-decomposition, chemical
decomposition, adsorption, leaching, dilution, erosion (mechanical,
co-distillation, uptake by plants).
Not any data.
Ive, G. W. and J. Casida. 1970. Enhancement of photoalteration of
cyclodiene insecticide chemical residues by rotenone. Science 157:
1520-1622.
10 ppm to 100 ppm both compounds, sunlight for 1 hr.
No DDT result of DDD.
Ivie, G. W. and J. Casida. 1971. Sensitized photo-decomposition and
photosensitizer activity of pesticide chemicals exposed to sunlight
on silica gel chromatoplates. J. Agr. Food Chen. 19:405-409-
Sunlight for 1 hr
Very slight action. Aromatic amines sensitize DDT photo-decomposition
by formation of charge transfer complexes. Nothing quantitative.
2 pg in 2 ml methanol of pesticide - in open air.
Jannasch, H. W., K. Eimhjellen, C. 0. Wirsen and A. Fanranfarmaian.
1971. Microbial degradation of organic matter in the deep sea.
Science 171:672-675-
Limited microbial degradative ability - 10-100X less than open
water under same temperature.
5000 m depth
Jarvinen, A. W., M. J. Hoffman and T. W. thorslund. 1975- Significance
to fat head minnows (Pimephales promelas) of food and water exposure
to DDT. In press.
Higher DDT from, water than diet. Diet and water residue were additive
Cone. 1.2 times from diet and 100, 000 times from water. Residues
were 4X in water exposed fish as dietary. Higher mortality from both
exposures than from one or the other. Dietary DDT -t- PCO 0.025 survival
DDT in water - estimated maximum toxicant 0.9
DDT in diet and water (56.7 ug/g) 0.4 yg
-------
Embryo and larval levels are 2X when parents have DDT in both
water and food as when only to water.
60% of mean total micrograms in fish exposed at 0.5 yg/£ in water
and diet was eliminated in 56 days. Virtually all if only dietary
was used. None was eliminated with only water exposure.
Clams X 25,000 from DDT-treated water.
Jensen, S., R. Gothe and M. -0. Kindstedt. 1972. Bis(p-chlorophenyl)-
acetonitrile (DON), a new DDT derivative formed in anaerobic
digested sewage sludge and lake sediment. Nature 240:421-422.
1 £ activated sludge and 100 mg pp DDT with 5 uCi lijC-DDT with DDD
and DDE, 8 days at 20°C.
pp'DDT 1/2 life = 7 hr.
DDE disappeared in 48 hr.
DDCN was found in a natural lake sediment (Lake Malaren, Sweden,
0.6 ppm/dry wt.)
Sludge from a treatment plant in Uppsala also contained DDCN
(0.012 ppm/dry/wt.)
Johnson, 3. T., T. Goodman and H. Boidberg. 1967. Conversion of DDT
to DDD by pathogenic and saprophytic bacteria associated with plants.
Science 157:560.
(1) 23 of 28 microorganisms converted pp'DDT to pp'DDD, anaerobi-
cally 10 ug/ml DDT for 14 days.
(2) Range of conversion was from trace to 5 ug/ml.
(3) Most conversion occurred in last 7 days.
(4) Other metabolites were present.
(5) GLC analysis.
Johnson, B., C. R. Saunders and H. Sanders. 1971. Biological magnifi-
cation and degradation of DDT and aldrin by freshwater invertebrates.
J. Fish. Res. Bd. Can. 28:705-709-
Freshwater aquatic Crustacea and immature insects on continuous
now of 14C-labelled aldrin -and DDT to get magnification from water
and degradation in invertebrates less than 100 ng/liter
HpO - 3 days, no food.
Results - Rapid uptake without regard to surface/volume or taxonomy.
Some of 100,000 magnif. No plateaus of uptake observed. Conversion
to DDE, some shrimp also DDD, DTMC, and DBF, aldrin and dieldrin
* invertebrates (1) contribute to rapid accumulation when DDT's
present for only short time.
(2) when pesticides at constant rate, they magnify.
(3) also magnify degradation products.
Johnson, H. E. and R. C. Ball. 1972. Organic pesticide pollution in
an aquatic environment. Great Lakes Res. Synp.:1-10.
General overview.
Jones, 3. R. and J. Mogle." 1963- Population of plankton animals and residual
chlorinated hydrocarbons in soils of six Minnesota ponds treated for control
of mosquito larvae. Trans .Am. Fish. Soc. 92(3):211-215-
-------
On bentonite and verrniculite in smooth layer on lake bottom (1 To/
acre)
Counts of cladocerous, copepcds, ostracods, rotifers, and volvox
were not effected 15 days after. Soils -> 1.5 -> 25.5 ppm DDT.
There is a slight depression in micro-organisms (407 days) that
recovers by 15 days.
Juengst, F. W. and M. Alexander. 1973. DDT: An anomalously resistant
molecule. Naval Research26(12): 1-9.
v/
Brackish water; salt marsh; subtidal zone - 1 mile; subtidal zone -
2 miles; brackish water; subtidal zone - 2 ft water - fine sand;
subtidal zone - coarse gravel.
Test - if bacteria in samples can convert water - insoluble
DDT to water soluble compound > 1/4 to 2/3 of bacteria can trans-
form 5-10$ of ! 'C-DDT. No sol. in single experiments lab
Some bacteria decompose very rapidly, so why is DDT persistent
(a) binded to lipids, (b) microbes capable of decomposition are
prevented access competitively
Kallroan, B. J. and A. K. Andrews. 1963. Reductive dechlorination of
- DDT to DDD bt teast. Science 1^1:1050.
was formed from C-DDT, but no ^C-DDE when 1 g yeast was
incubated aerobically at 25 C for 50-200 hr.
(1) Paper chromotcgraphy
(2-) * DDT -* DDD by.reductive dechlorination
[DDT reductive ) DDD ^ does not go through DDE
I dechlorination
Idehydrcchlorination
DDE]
Kanitz, S., C. Costello and P. Orlando. 1971. Effects of radiation on
the decomposition of organochlorine pesticide residues in foods.
Gig Med Prev 12(1):51-57. Italian."
y - radiation on op'DDT, pp'DDT and op'DDE in n-hexane and water.
Hexane - breakdown depends on cone. 96-173 pg/ml
solutions required 1 Mrad for 5Q% degradation. The same results
were obtained with 0.5 Mrad if 16-22 pg/ml solutions were used.
Oxygen is necessary for this effect; 10-16 pg/ml in aqueous ->
85-90$ breakdown at 160 krad; 10-16 pg/ml in organic -* 85-90/5
breakdown at 2.9 Mrads
Kapoor, I. P., R. Met calf, R. Nystrom and G. Sangha. 1970. Comparative
metabolism of methoxychlor, methiochlor and DDT in mouse, insects,
and in a model ecosystem. J. Agr. Fd. Chem. 18:1145-1152.
Mouse - 1.02$ eliminated in 24 hr.
Model ecosystem cone. DDT 90, OOOX
DDT, DDE and DDD were stored.
Kawahara, T. 1972. Chlorinated hydrocarbon pesticide residues in the
rice straw, paddy soil and Italian rye grass soil. Hull. Chem.
Insp. Sta. 12:101-102. (Japanese)
-------
Rice straw - 0.132 ppm pp'DDE, 0.464 pprn op'DDT, 0.66 ppm pp'DDT.
Paddy soil - 0.030 ppm pp'DDE, 0.13 ppm pp'DDD, 0.105 ppm op'DDT,
0.40 ppm pp'DDT.
Kearney, P.C., R. G. Nash and A. R. Iseuee. 1969. "Persistence of
pesticide residues in soils" in Chemical Fallout (Charles C. Thomas,
Pub., Springfield, 111.) p. 54-6T
Persistence is a relative term. 75 to 100 bioactivity of control
or 75-100$ loss of pesticide.
Chi. Hydr. = 18 months and up for normal agricultural levels.
DDT = 4 years, when large quantities are applied, they last 2-3
times longer.
Disappearance
*(1)1st order - the rate of loss is 1 to the amount in the soil.
(2) Biological metabolism - delay before removed to food chain.
(3) Levels with repeated application amounting to loss.
(4) Mercury and arsenic levels are very complex depending on soil
type, moisture, what compound is left. So their values are
more complex.
(5) If the pesticide is biodegradable, then it follows a signifi-
cant curve.
Ko, W. H. and J. L. Lockwood. 1968. Conversion of DDT to DDD in soil
and the effects of these compounds on soil microorganisms. Can.
J. Microbiol. 14:1069-73.
Submerged soil with alfalfa residue
t conversion with t alfalfa.
2 of 10, and 4 of 10 bacteria were inhibited by 10 ppm DDT or DDD
in nutrient media.
DDD was more inhibitory than DDT on microorganisms.
This did not happen in soil.
Fungi were not affected even in nutrient media.
Kramer, R. E. and R. W. Plapp. 1972. DDT residues in fish fromthe
Brazos River basin in central Texas. Environ. Entom. 1:406-409.
Streams
Agricultural > range land > recreational gar1 (Lepesosteus spp.) had
highest levels (muscle)
None over 1 ppm.
Knur, R. J., A. Davis and E. Taschenberg. 1972. DDT residues in a
vineyard soil after 24 years of exposure. SECT 8:329-333-
4-16 Ib active DDT/acre/yr for 25 years; 164.85 Ib/DDT/acre in
24 years; 54 Ib/acre in 9 years
6 and 12 yr data - DDT in top 3", 1/2 life = 6 yr, 1/3 H-e = 12 yr,
DDE only present.
Spring '71 - treated and control soil samples [average of 4 repli-
cate plots].
[0-3" cores, 3-6" cores, center rows and drip place.]
6, -12, -24 yr % DDE t. 6 yr = 12%, 24 yr = 27*, 24 yr loss of DDT =
22% recovered
Check plots near fields contained low levels of DDT (3) (1.4 Ib/ acre)
and no DDE; in 24 yr the DDT had t and moved down to 3-6" and DDE
was contained in plots.
-------
Kuwatuka, S. 1972. Pesticides In the soil. Kagaku Kogyo. 23(11):81-88.
(Japanese)
75% of DDT remains for more than 6 months under aerobic condition.
Anaerobic conditions or 1% alfalfa addition + 1% DDT in 12 weeks.
General review.
Leland, H. V., W. Bruce and N. Shrimp. 1973- Chlorinated hydrocarbon
insecticides in sediments of southern Lake Michigan. Environ. Sci.
Tech. 7:833-838.
t organic carbon -* t DDT residue levels in ppb and general dis-
tributed and available to benthic organisms.
Lichtenstein, E. P. and K. R. Schulz. 1959- Persistence of some
chlorinated hydrocarbon insecticides as influenced by soil types,
rate of application and temperature. Econ. Ent. 52:124-131.
10 or 100 Ib/acre - samples at 6, 12, 18, 24, 30, 36, 42 months
Miami siH loam (organic - 3.8$) 22% of DDT recovered 42 months
Muck soil (organic = 40.0$) 33$ recovered 42 months.
More original application -» longer 1/2 life
Lichenstein, E. P. and K. R. Schulz. 1961. Effect of soil cultivation,
soil surface and water ont he persistence of insecticidal residues
in soils. J. Econ. Entomol. 54:517.
Persistence of DDT was not effected by the amount of water evaporated
from soils on glass surfaces, or by surface enlargement.
Field 4 lb/5" acre DDT with daily discing gave - 25$ reduction in
3 months (24$ ncndisked, 44$ disked)
Lichtenberger, J. J., J. W. Eichelberger, R. C. Dressman and j. E.
Longbottom. 1970. Pesticides in surface waters of the United
States - a 5 year summary, 1964-1968. Pest Monit. J. 4:71-86.
(1) Not applicable to model; stored values better
Lindquist, R. A., H. A. Jones and A. H. Maddeu. 1946. DDT residual
type sprays as affected by light. J_. Econ. Entomol. 39:55-59.
Nothing substantial, (1) wet more degradative than dry soil
Liu, H. J., P. Silk and I. Unger. 1972. The photodecomposition of an
analogue of DDT. Can. J. Chein. 50(1):55-60.
1,1,l-trichloro-2,2bis(5'chloro-1'methoxyphenylethane (MPA)
light > 300 ran.
Solid -> MPE and HCL, MPO, MFD and MPC
02
Liquid -» MPE and HCL, MPD, MPC and MPO
NO
Liquid -* HCL, MPD, MPC, and MFE; MPD and MPC were larger than MPE
02 .
Lloyd-Jones, C. 1971. Evaporation of DDT. Nature 229:65-66.
Vapor pressure = 1.5 x 10"? mmHg 20 C
Gas diff. coeff. =0.05 cm2s-l
-------
Still air layer thickness = 2 mm
. . evap. rate at 20 C = 3 x 10-3 ^ cm"2^1
Experimentally labeled Cl4} on carbon rings -> 0.5 ug cm2, several
experiments with measuring label
Over time -> a loss of evaporation rate of 2 In/acre/yr in summer;
0.3 Ib/acre/yr in winter or over half of the DDT applied.
Macek, K. J. and S. Kom. 1970. Significance of the food chain in DDT
accumulation by fish. J. Fish. Res. Bd., Can. 27:1496-1498.
Food vs. water in DDT accumulation in fish
3+0.3 pptr. pp'DDT-labeled for 120 days in H20
3 + 0.15 ppm ^c-pp'DDT
1% mortality in both groups - 120 days in H20 -» 25.6 ppb, 120 days
in feed ^ 1.92 ppm.
Uptake in both cases linear for 60 days, then leveled off a little.
Fish in H20 gained 3.55$ of DDT available, fish in feed gained
35.5$ of DDT available
At H20 rate, 12 yr to obtain wild levels, in food - 1 yr, so food I
levels were more important.
\
Macek, K. J. , C. Rodgers, D. Stalling and S. Kom. 1970. The uptake, j
distribution and elimination of dietary 14C-DDT and -^C-dieldrin
in rainbow trout. Trans. Am. Fish. Soc. 99(1) : 689-695-
DDT Dieldrin
0.2 mg/kg/wk - 1.0 mg/kg/wk equilibrium in 140 days
20-24$ 9-11$ portion accumulated
shape of accumulation
160 days 40 days time to eliminate 50$ ,
* lipogenesis tlipogenesis j
(a) presence of dieldrin enhanced DDT uptake, (b) presence of DDT i
I dieldrin uptake, (c) dieldrin inhibits DDT elimination, (d) DDT j
does not effect dieldrin elimination
Meeks, R. L. 1968. The accumulation of Cl ring-labeled DDT in a
freshwater marsh. JWM. 32:376-398.
DDT granules 1st to bottom, then DDT released and plankton and
larger organisms removed. 1-3 days -* max. producer levels (+ 1-3
days) -> invertebrate max. through food web for levels separated.
Snakes more than 1 yr later = max.
Loss of total DDT throughout year from codistillaticn with f^O.
Soil got some and collections.
Some organism [cone.] DDT 200-5COX, avg. = 50.
Fat good indicator in vert, tissues, not others.
Variation in accumulation at all levels is high.
Mendel, J. and M. Walton. 1966. Conversion of pp'DDT to pp'DDD by
intestinal flora of the rat. Science 151:1527-
pp'DDT given rats intraperitioneally and by stomach tube varied as
to pp'DDD in liver and feces. Stomach tube animals did, but not
IP treated.
-------
(1) Coliform bacteria from faces could reductiveiy dechlorinate
pp'DDT to pp'DDD
(2) .'. site of pp'DDT conversion is not liver but G.I. tract.
Menzel, D. J., J. Anderson and A. Randhe. 1970. Marine phytoplankton
vary in their response to chlorinated hydrocarbons. Science 167:
1724-1726.
Varying response, some insensitive, some lethal at 0.1 to 1.0 ppm
DDT, intermediates exhibited 4- photosynthesis.
Metcalf, R. L., I. P. Kapoor and A. Hirwe. 1971. Biodegradable analogues
od DDT. Bull. Wld. Health Org. 44:363-374.
All synthetic analogue data
Review
Miller, L. L., R. Narange and G. Nordnlcm. 1973- Sensitized photolyses
of DDT and decyl bromide. J. Qrg. Chem. 33(2):340-346.
Aromatic amines can break down alkyl halides. DDT broken down at
254 nm, especially in presence of oxygenated methanol.
Sulfides inhibit this process, but direct photolysis is not
effected in ethanol.
At 310 mn photolysis is ingibited by oxygen but not at 254 nm. So
not in sublight spectrum.
Mikus, R. P., D. Blair and J. Casida. 1965. Conversion of DDT to ODD
by'bovine rumen fluid, lake water, and reduced porphyrins. J. Agr.
M. Chem. 13:481-483.
Incubated with (6 samples) 14C-DDT -0.01 ppm, 7 days, room temp, in
stoppered flask, lake water Clear Lake, California
(1) 80$ of label was in ODD position on paper chromatography.
(2) No good unity of conversion %', varied with 02 content and
plankton count in water samples.
(3) Boiled and distilled water under vacuum showed no conversion.
(4) Rumen fluid converted 65% of C14-DDT to C14- ODD in 24 hr
(0.04 ppm to samples 2 hr post feeding and strained)
(5) No hemoglobin conversion unless under anaerobic conditions
when porphyrins reduced.
Mosier, A. R., W. Guenzi and L. Miller. 1969. Photochemical decompo-
sition of DDT by a free-radical mechanism. Science 164:1083-1085.
Solid and in hexane solution, 2537 A (UV light), thin layers on
inside of quartz tubing; 48 hr -> 80% conversion to ODD, DDE, and
DDC = 0
No evaporation
Mosser, J. L., N. Fisher, C. Warster. 1971. PC3s and DDT alter species
composition in mixed cultures of algae. Submitted to Science
Thalasiiosira pseudonana - sensitive diatom, Dunaliella tertiolecta -
resistant green alga.
Each culture 104 cells/ml at zero time, mixed - 1:1 ratio
-------
(a) 25 ppb PCB and 100 ppb DDT Inhibited T. pseudodonana, no
effect on algae
(b) Even at lower cone., T. p_. did not compete with D. t_. in mixed
cultures.
(c) Final cell counts were the same in all cultures; only species
composition changed.
Murphy, P. G. 1971. The effect of size on the uptake of DDT from water by fish.
Bull. Environ. Contam. Toxicol. 6:20-23 /
Mosquito fish (Gambusia affinis)
41 ppt pp'DDT-Ci^ 19.5-21.0 C for 48 hr
Residues from field indicate that equilibria with the environment
was reached by 150 mg in wt.
Small fish were more efficient than larger at DDT uptake (cut-off
point = 200 mg) (mean cone, of small fish 4X that of large fish)
70 mg -* 36 ppb; 200 mg -> 34 ppb, 300 mg ^ 28 ppb; 400 mg -*- 18 ppb;
1000 mg -* 10 ppb.
The fish (23) removed 21$ of the DDT in the water in 48 hr.
Nash, R. G. and E. Woolson. 1967, Persistence of chlorinated hydro-
carbon insecticides in soils. Science 157=924-926.
0-448 kg insect./acre throughout profile
C.H. Yr. % Remaining Yr. C.H.
Tech. Aldrin 14 40 10 14 BHC
Chlordane 14 40 45 14 Toxaphene
Cendrin 14 41 28 15 Par. aldrin
Heptachlor 14 16 31 15 Tech. dielrtr'n
Dilan 14 23 39 17 Tech. DDT'
Iscdrin 14 15
Leaching, volatilization, photodecopposition, mechanical removal,
biological decomposition were at a minimum. This may be an upper
limit of persistence.
Nash, R. G., W. Harris and C. Lewis. 1973. Soil pH and metallic
amendment effects on DDT conversion to DDE. J_. Environ. Qual. 2:
390-394.
t pH -* t DDT to DDE
(a) pE > 9) the conversion is enhanced by MgO
(b) Temperature little effect.
(c) Moisture does not affect pH effect.
Total residues were not effected by pH.
Newsom, L. D. 1967. Consequences of insecticide use on non-target
organisms. Annu. Rev. Entomol. 12:257-
General review [soil, air, plant, animals (not complete)]
to this time
Odum, W. E., G. Woodwell and C. Wurster. 1969. DDT residues absorbed
from organic detritus by fiddler crans. Science 164:576-577.
DDT absorbed most readily to 250-1000 micron diameter particles.
Fiddler crabs, Uca pugnax, fed 10 ppm DDT detritus of this sjfee for
-------
11 days showed altered behavior and DDT in muscle of claw increased
3-fold.
(a) Size determined from screening field samples from a con-
taminated stream. Gas chromatography
(b) Control claws - 0.235 ppm DDT, DDT - 0.885 ppm
(c) Behavior alteration included ^coordination causing loss of
footing and lack of fear by day 5- Cause of disappearance
from contaminated area.
Onsagu, J., H. Rusk and L. Butler. 1970. Residues of aldrin, dieldrin,
chlordane, and DDT in soil and sugar-beets. J. Econ. Entomol. 63:1143-1146.
Residues in sugarbeets proportional to soil (of soil) residues at
the tine of planting. DDT (5.5*).
Patil, K. C., F. Matsuraura and G. Eousch. 1971. DDT metabolized by
microorganisms from Lake Michigan. Nature 230:325-6.
Isolated cultures (anaerobic) from Lake Michigan (24 sites on
Wisconsin shore) water, silt, 6-12" below bottom.
Approx. 300 microorganisms found; majority converted DDT to TDK
No. No. No.
No. Forming ~ Forming Forming
Average Cultures TDK DDNS DDE
Water 68 54 34 15
Top silt 59 47 37 30
Bottom silt 35 27 17 13
Both TDE and DDNS are acricidal.
Patil, K. C., F. Matsumura and G. M. Boush. 1972. Metabolic transfor-
mation of DDT dieldrin aldrin and endrin by marine microorganisms.
Environ. Sci. Techno!. 6:629-632.
(1) 30 days with 14C-DDT; seawater, bottom sediments from ocean
and estuaries, surface films, algae and marine plankton.
(2) 35 of 100 microbes degraded DDT to TEE."
(3) No water samples degraded DDT by chemical or photochemical
means, even polluted water
(4) Surface films, sediments and plankton degraded DDT to TDE,
DDNS and DDOH « (algae)
(5) Sea sediments were very low in degradation.
Peterle, T. J. 1969. DDT in Antarctic snow. Nature 224(52919):620.
From snow melt - 0.04 x 109 g/g from sample 6, 29.2 and 70.8£ op'DDT
pp'DDT respectively.
There could be as much as 2.4 x 10° kg of DDT accumulated in the
Antarctic snow.
Pfaender, F. K. and M. Alexander. 1972. Extensive microbial degra-
dation of DDT in vitro and DDT metabolism by natural communities.
J. Agr. Fd. Chem. 20:842-846.
-------
Hydrogenomonus sp_. converts DDT to ODD and DBMS, DBF under anaerobic
conditions
Arthrobacter -> same; ring cleavage there
(T) Natural samples -» degradation, but slow by few organisms
past DBF.
Pfaender, F. K. and M. Alexander. 1973- Effect of nutrient additions
on the apparent cometabolism of DDT. J. Agr Food Chem. 21:397-399.
90% breakdown in polluted water to DDE, ODD, and DBF. Glucose
enhanced ODD formation but slowed DBF biosynthesis. Diphenylmethane
reduced ODD and DBF.
The number of microorganisms aboe to produce DDD and DBF t with
glucose and diphenylmethane. 7 wk 0.005% DDT
Pierce, R. H., Jr., C. E. Olney and G. T. Felbeck, Jr. 1971. Pesticide
adsorption in soils and sediments. Env. Let. 1:157-
Reprint not available.
Plirmier, J. R., U. KLingebiel and B. Hummer. 1970. The collection and
preservation of open ocean marine organisms for pollutant analysis.
Science 167=67-69.
DDT - In methanol with bubbling nitrogen (photooxidation of DDT
and DDE with 02)
Intermediates formed by free radicals of hydrogen from
methanol -> benzole acids, aromatic hetones, and chlorinated
phenols.
DDE - Undergoes photocyclization to dichlorofluorene derivatives.
Poirrier, M. A., B. Bordelon and J. Laseter. 1972. Adsorption and
concentration of dissolved Carbon 14-DDT by coloring colloids in
surface waters. Environ. Scl. Tech. 6:1033-1035.
Colored (Natural - humic or brown) colloids concentrate 0.168 ppb
in natural surface water to 15,90OX in 1 hr.
Colloids - 5-10 mm, 68$ iron, fulvic acid - 68-78$, hymatcmelanic
acid - 16-28%, humic acid [this colloid can be precipitated to
sediments by many aquatic changes] - 3-3-9.5$.
-^C-teehnique.
Rautapaa, J. 1972. DDT, lindane, and endrin in some agricultural soils
in Finland. J. Sci. Agr Soc_. Finland 44:199-206.
21 sugarbeet fields; DDT residues average 0.73 ppm, 5% DDE of op'DDT
+ pp'DDT
21$ of DDT applied in total was still present (Range = 2-65$).
Relnbold, K. A., I. Kapoor, W. Childers, W. N. Bruce and R. L. Mstcalf
1971. Comparative uptake and biodegradability of DDT and methxocychlor
by aquatic organisms. 111. Mat. Hist. Surv. Bull. 30:^05-417.
Couldn't get reference.
-------
Reinert, R. 1970. Pesticide concentrations in Great Lakes fish. Pest .
Monit. J. 3:233-240.
DDT and dieldrin in all fish. Lake Michigan contains 2-7x other
Great Lakes.
t size -» i DDE within species on whole fish basis. On oil basis,
the size diff. disappears.
Lab - pptr. f^O * ppro fish.
Risebrough, R. W. , R. J. Huggett, J. J. Griffin and E. D. Goldberg.
1968. Pesticides: transatlantic movements in the northeast trades.
Science 159:1233-1235-
Air transport (1) codistillation with H20 detection in air and
rainwater 3 (3) atmospheric dust from Texas -» Ohio, (4) mineral talc,
DDT carrier occurs in rain in much higher degree than expected, in
airborne particulate matter over the sea.
(1) Total cone, of C. H.'s in air more in winter, overall pesti-
cides did not change.
(2) No correlation with pesticides and plants or minerals.
(3) 4l ppb in dust - wind currents and dispersal in agricultural
areas.
(4) No PCS from Calif, but prcbablu in vapor and transported
same way.
Robinson, J. A., A. Richardson, A. Crabtree, J. Conlson and G. Potts.
1967. Organochlorine residues in marine organisms. Mature 214:
1307-13H.
Many organisms and trophic levels.
Saito, M. and M. Kitayama. 1973. EEC and DDT residues in arable soil
Hokkaidoritsu Eisei Kenkyushoho 23 : 116 . (Japanese )
(1 yr after DDT ban)
Paddy Fields Arable Land
0.051-0.232 ppm 0.135-01845 ppm pp'DDT
0.009-0.045 ppm 0.018-0.59 ppm pp'DDE
This shows a decrease in paddy fields, 1969 - 0.036 pp'DDT
arable, 1969- 1.272 ppm pp'DDT
Shtannikoa, Ye. 1972. Decontamination of water contaminated with DDT
and BHC. GigSanit. 37(9):97-99. (Russian)
2 mg DDT - Coagulate with sodium carbonate -* 75-99* removal
All artificial
Spencer, W. F. and M. M. Cliath. 1972. Volatility of DDT and related
compounds . J . Agr. Food Chem. 20 : 645-9
op'DDT's (7-5) are more volatile than pp'DDT (1)
At 30 C - atm contains 62% op 'DDT, 16% op 'DDE, 14$ cp'DDE and
8% pp'DDT.
Technical DDT up to 20 mg/g ^ equal op and pp DDT in soil and atm,
but at higher cone, op 'DDT in the atmosphere increases more than
-------
pp'DDT.
Dieldrin did not effect volatilisation.
Air drying 4- volatilization.
pp'DDE has a higher volatilization rate.
pp'DDT vapor pressure were 1.52 x 10"? mm - 20 C [
sand 7.26 x 10-7 mm - 30 C
33.2 x 10-7 m _ i}Q C
Stadnyk, L., R. S. Campbell and B. T. Johnson. 1971. Pesticide effect
on growth and l^c assimilation in a freshwater alga. Bull. Envir.
Cont. and Toxicol. 6(l):l-8.
Evaluate in terms of changes in growth and metabolism rather than
death - cell biomass, cell number and carbon-14 assimilation.
Cultured in an equivalent to a entrophic lake - Duiron, carbaryl,
2-4D, DDT, dieldrin, tixaphene, and diazinon were investigated.
Results - diuron (herbicide) - 4- bian?ass~:severe for 8 days and
* carbon assimilation
carbaryl - exact opposite effect.
2-4D - less severe duiron effect DDT 925-51), toxaphehe
and dieldrin (22-32) all + cell numbers at all
concentrations and cell biomass (toxaphene only
3-4? .
DDT - Day 2 - 75$ + C-14 assimilation
toxaphene - Day 2 450$ + C-14 assimilation
^ algae ->-.l energy throughout ecosystem
Stenersen, J. H. V. 1965. DDT metabolism in resistant and susceptible
stable files and in bacteria. Nature 207:660-661.
in Serratla marcesceus Anaerobic and aerobic
resistant Alcaligenes faecalis cultures with
fly feces + one other 25 and 37 C
E. coll 24 or 72 hr (H2S04
B. brevis added)
A. aerogenes
(1) Anaerobically, S_. marcesceus , S. coli and other -* 90$ TDE (ODD)
and 5% DDE; ncthin in aerobic.
(2) There was no difference in rate of absorption, detox, or
excretion of DDT in susceptible and resistant flies.
Stenersen, J. and J. Kualuag. 1972. Residues of DDT and its degradation
products in cod liver from two Norwegian fjords. SECT 8:120-121.
(Gadus morrhus L. ) cod that are stationary inf jords
No Fruit Growing Fruit Growing
Sample Size 19 5
DDT 0.5 ppm 5.05 ppm
DDE 0.27 2.67
ODD .. 0.42 1.85
1.28 ppm 9-57 ppm
At lew levels DDT in liver is dependent on liver wt. '
-------
Swoboda, A. R., G. Thomas, F. Cady, R. Eaird and W. Khlsel. 1971. ;
Distribution of DDT and toxaphene in Houston Black Clay on three
watersheds. Environ. Sci. Technol. 5:141-5. !
10 yr - less than 16% of the DDT recovered in the top 5 ft of soil. jj
60-70$ of that recovered was in the top 12". Leaching and erosion f
of top soil from abnks caused downward movement. |
Tabor, E. 1965. "Pesticides in Urban Atmospheres," Paper No. 65-30 at [
58th Ann. Meeting of Air Pollution Control Assoc., Toronto, Canada, I
June 20-24.
Mean DDT in air, agricultural 5 ug/1000 mm3
Range up to 23 ug/1000 mm3 DDT
Tarrant, K. R. and J. O'G. Tatton. 1968. Organochlorine pesticides in
rainwater in the British Isles. Nature 219:725-727-
Up to 400 ppb in rainwater; high in London because of carbon
particles.
12 months in 7 areas in England -> rainwater in amber colored glass
to prevent photodegradaticn.
Samples analyzed after 3 months. TLC on silica gel with hexane,
then GLC.
(1) Vary throughout yr. but pp'DDT, pp'DDE, pp'TDE always there,
in ppb quantities, no matter what is the use in specific
areas. So world-wide distribution is supported.
Tatton, J. O'G. and J. H. A. Ruzicka. 1967. Organochlorine pesticides
In Antarctica. Nature 215:346-348.
McMurdo Sound DDT may be due to human activities, not weather, wind,
water (ocean currents, etc.)
More remote birds and their prey were sampled and analyzed for
several insecticides.
(1) All remote penguins contain at least Traces of BHC isomer,
dieldrin, pp'DDT and pp'DDE in their liver, blubber and fat.
(a) heptachloroxide and pp'DDE were also present.
(2) Kill their major prey had lower levels of all compounds.
Trofimova, M. G. and A. Mitrofanov. 1972. Effect of granulated DDT,
used for mosquito control, on aquatic organisms, (preliminary
report) Med. Parazitol Parazit Bolez. 4l(5):620-622. (Russian)
Surface and bottom water; aquatic plants, sediments (reservior)
5 kg 10% granulated DDT/ha - aerial
1-30 days - surface water and aquatic plants - no DDT
10, 20, 30 days - benthic water - 0.001, 0.003, and 0.007 mgA
1, 10, 20, 30 days - benthic silt - 0.5, 0.8, 1.1, 0.9 mg/kg
Benthic pop. of Chironomidae deid after application, but surface
organisms lived. TLC
Vrochinskiy, K. K., I. V. Grib and A. V. Grib. 1970. Organochlorine
insecticide residue levels in aquatic plants. Gidrobiol. Zh. (Kiev)
6(6):107-109. (Russian)
-------
DDT
Lemna minor L.
Spirodela polyrhiza 2-3.8 mg/kg for }
Nymphaea abba L. 11.5 mg/kg other species [
Acorus calamus L. [
Potamogeton pectinatus L. [
i
Water = 1 mg/kg, so they concentrate f
Benthic =1.4 rag/kg DDT, DDE and ODD from plant rot.
Warner, K. and 0. C. Penderson. 1962. Effects of DDT spraying for
forest insects on Maine trout streams. JWM. 26:86-93.
+ populations, especially young of year class., but didn't persist
into 1959-
Caddis fly larvae were affected.
Waybrant, R. C. 1973- Factors controlling the distribution and per-
sistence of lindane and DDE in lentic environments. Purdue
University Ph.D. thesis. Hamelink, J. L. - Major Professor.
200 pptr. in the epilimnion or 50 pptr. of the whole lake in a
thermally stratified ultra-olitotrophic flooded limestone quarry.
(a) Persistence controlled by absorption on suspended particles.
DDE with 15X the absorption disappeared 15X faster. In 3
months, 85$ of DDE was in the sediments, 12% of lindane'was
still in water.
e.g., Stand 1
Year DDT
1958 .409 +0.80 kg/hectare
I960 1.496 + .360 kg/hectare
1961 ' 1.622 kg/hectare
Woodwell, G. A., C. Wurster and P. Isaacson. 1967. DDT residues in an
East Coast estuary: A case of biological concentration of per-
sistent insecticide. Science 156:821-824.
Larger animals in higher trophic levels had most residues.
0.04 ppm in plankton -> 75 Ppm herring gull.
DDT -* DDE -» ODD as move up trophic levels.
4- repro. in shrimp, amphipds, blue crab, toad, woodcock.
Variability in the amounts among a species leads to continuous
cropping of higher individuals and no spectacular kill.
Woodwell, G. M., P. Craig and H. Johnson. 1971. DDT in the biosphere:
Where does it go? Science 174:1101-1107.
Physical properties - (1) lipid soluble and . . attract to biological
material, (2) persistence, (3) high vapor pressure.
Avg. DDT/acre = 1.50 in U.S. agricultural soils - other stat. of
DDT use, etc.
DDT reserviors - land surface, trophosphere, mixed layer of ocean,
the abyss.
Major effects as in British Isle captors comes from local contami-
nation, not world-wide spread, and will respond to change.
-------
atmosphere
land " ocean
abyss
'Wurster, C. 1969- DDT reduces photosynthesis by marine phytoplankton.
Science. 159:1474-1475.
1-2 ug of pure DDT (pp')/culture. 20-24 hr -> add ^C-bicarbonate,
and let run for 4-5 hr. Radioactivity measured and taken as an
index to photosynthetic rate. Cell cone, about equal at start.
Dark uptake was subtracted from all values.
t Effect at \ cell cone, for low soluble DDT in H20 is greatly
attracted to biological material.
Typical dose response curve in photosynthesis rate. But sensitive
even to very low levels.
Repres. natural levels for DDT in phytop. are not known.
Greatest effect at low cell concentrations, so selective effect
and shifting pyramid base of food chain is possible.
Young, R. H. F. 1972. Effects on groundwater. J. WPCF 44(6):1208-1210.
Just a few references; the best is Swoboda.
Young, 0. S.3 J. J. Chodan and A. R. Wolcott. 1970. Adsorption of DDT
by soils, soil fractions and biological materials. J_. Agric. Pd.
Chem. 18:1129-1133.
pp'DDT - incubated in soil with aqueous medium to determine adsorp-
tion isotherms, to see if DDT adsorption is directly related to
organic content. It was not. It does depend on
(1) structural and water repellent effects of lipid deposits on
sorptive surfaces,
(2) differences in mineral structures and the way organics bond
with them,
(3) nature and proportion of non-humic and humic portions of
organics in soil.
Yule, W. N. 1973. Intensive studies of DDT residues in forest soil.
SECT 9:57-64.
6,000 tons/10 million acres in 16 yr - all forested.
(1) All in top 6" - 0.63 ppm was top mean sample for transect
10.79 oz/zcre left in 1968 from application
Disappearance curves, 1/2 life of 10 yr without vertical runoff
1968-71 - pp'DDT + while pp'DDE t
Zabik, M. J. 1969. The contribution of urban and agricultural pesti-
cide use to the contamination of the Red Cedar River. Mich. Inst.
of Water Research, Prlj. No. A-012, Michigan. I
i
DDT saturated all year j
t on sediments and downriver \
Bottom -» water is rapid > more downstream. j
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APPENDICES
3 and 4
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APPENDIX - 3
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APPENDIX - 3
Lake Compartment
Foreword
Meadows and Panders-^ constructed a model of DDT transport in the global
environment in 1971. We extended Meadows and Randers' model and evaluated
the accuracy and scope of their model. This report examines a facet of the
extension of Meadows and Banders' DDT model.
Introduction
In Meadows and Randers' model of DDT transport in the environment, they
neglected to include lakes as a DDT pathway or sink. We feel that this is
a shortcoming in the model. The impact of DDT in lakes on man is probably
greater than the impact of DDT in oceans because of the proximity of lakes
to man, and the available drinking supply in lakes.
Although lakes comprise only .1 to .2% of the earth's surface area and
contain .015$ of the total water volume on Earth, lakes could be reserviors
of DDT. Even a minute fraction of the total DDT production which reaches the
lakes has the potential to produce harmful effects on the lake ecosystems.
High concentrations of DDT (DDT concentrations of lake fish have been as
high as 13 ppm: Reinert 1965-1968) can reduce food webs and eliminate
carnivores (Woodwell 1971). The destruction of food webs can intensify pol-
lution problems, particularly in lakes that receive mineral nutrients in
sewage or in water draining from heavily fertilized farm lands. The plants,
which are no longer consumed by animals, sink to the bottom to devay, pro-
ducing noxious gases and further deteriorating the environment (Woodwell
1967: Scientific American Vol. 216, No. 3, P. 24) It is Important in a
global model of DDT transports to include lakes in order to comprehend the
total impact of DDT on the global environment;. Thus we feel it is justifiable
to incorporate a lake compartment in our DDT mathematical model.
iMeadows and Randers' Sample Study of DDT movement is the first entry in
the bibliography.
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DDT in Lakes and Lake Biota
Several studies have been made cf DDT concentrations in lakes and lake
fish.
The following are some of the results:
.29 -13.28 ppm DDT residues in Lake Michigan fish
.02 - 8.61 ppm DDT residues in Great Lakes fish
(1965-1968 Reinert: Pesticides Monitoring Journal, Vol. 3, No. 4S
p. 233)
1 -11.17 ppm DDT residues in Lake Superior lake trout (1969)
Not Detectable - 15.7 ppm DDT residues in Lake Michigan lake trout
(1965, 1966) (Great Lakes Fishery Laboratory: Progress Report for
Annual Meeting, June 1970).
.16 -11.79 ppm DDT and metabolites in Great Lakes fish
(1967-1968 Henderson, Inglis, Johnson: Pesticides Monitoring
Journal, Vol. 3, No. 3, p. 145)
.74 -8.61 ppm DDT and metabolites in Great Lakes fish
(1969 Henderson, Inglis, Johnson: Pesticides Monitoring Journal,
Vol. 5, No. 1, p. 1)
9.3 ppb p,pl DDT1 in Southern Lake Michigan surficial sediments
I p,p2 DDT are DDT metabolites
(1969-1970 Leland, Bruce, Shimp: Environmental Science and Technology,
Vol. 7, No. 9, p. 833)
.1 -4.1 ppb DDT-type compounds in the Utah Lake drainage system
79 ppb DDT in catfish in Utah Lake
123-956 ppb DDT in carp in Utah Lake (1970-71 Bradshaw, Loveridge, Rippee.,
Peterson, White, Barton, Puhriman: Pesticides Monitoring
Journal, Vol. 3, No. 3, p. 166)
.01 ppm DDT residues in lake biota (1971 Woodwell: Science Vol. 174,
December 10, 1971, p. 1101)
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100 ppb DDT2 in Lake Michigan sediments (1971 Schact)
These figures may not be of significance until compared with other DDT
concentrations. For example, the concentration of DDT in the oceans has
been estimated at .005 ppb (Meadows, Banders 1970) and at .00015 to .0056 ppb
(Portmann 1974) compared with the value of .1 to 4.1 ppb DDT in the Utah Lake
(1970-1971). The concentration of DDT in ocean fish has been estimated at ..1
to 1 ppm (Meadows, Randers 1970) and at .0006 to .004 ppm (Portmann 1974)
compared with the values of .123 - .956 ppm DDT in carp in Utah Lake (1970-
197D and .74 to 8.61 ppm DDT in Great Lakes fish (1969). Thus, the observer
lake concentrations are of the same magnitude or even higher magnitude than
the observed ocean concentrations. Even though DDT is present in larger
quantities in the oceans, DDT may have a greater impact on the lakes. There-
fore, the DDT rates and routes in and out of the lake compartment should be
explored furter.
Chosen Parameters
There was a lack of information and research on exact rates and routes
of DDT transport in and out of lakes. For this reason, we could only use
very crude estimates of average rates in our DDT mathematical model. These
chosen values are very likely not accurate, since there are no data to sup-
port precisely correct rates. But other values can be almost effortlessly
inserted without altering the structure of our global model. Assuming expo-
nential decay, rates are represented in terms of half lifes.
The mass of lake fish consumed by man was estimated to be almost one-
half of the total mass of fish (15,000,000) with birds consuming another
two-tenths. The values for the lake fish - the body weights eaten per year.
Degraded fraction, excretion half life and fish half life - were taken to be
the same as in seafish. Therefore, Meadows and Panders' values for ocean
fish were employed. The volume of lakes in 125,000,000,000,000 cubic meters
2 tDDT includes all of the DDT residues
-------
(Encyclopedia Britanlca). The lake fraction was chosen to be .05 and
the lake basin fraction was chosen to be .05 in order to magnify the effect
of DDT on lakes. The precipitation half life and evaporation half.life
were chosen to be the same as the values used in the ocean compartment of
our model. The ocean and soil fractions of the earth were changed in order-
to make room for a lake compartment. The lake plankton concentration factor
was estimated from data of DDT concentrations in marsh biota (Perterle 196?)
to be approximately 1000.
Soil to lake transfer includes leaching into the underground water
table and direct run-off into lakes occurring in the lake basin portion
of the earth. Leaching was found to be a contributing factor to DDT con-
centration in depths of soil below one foot (Swoboda, Thomas, Cady, Baird,
Khisel: Environmental Science and Technology, Vol. 5, No. 2). We did not
incorporate a lake to soil transfer rate though it is possible for the DDT
to leach from the lake sediments back into the soil. This is probably not a
significant process, since DDT residues in the sediments of Southern Lake
Michigan were found to be concentrated in the upper 2 centimeters (Leland,
Bruce, Shimp 1973). Lake to river transfer includes leaching from the sedi-
ments into the ground water to the rivers, as well as DDT that's transported
by water currents from lakes that feed rivers. River to lake transfer
included DDT that leach into the ground water to the lakes, and DDT from
rivers that enters directly into lakes. Of course, these rates are very
small fractions of the total DDT production, but they do represent actual
transfers in and out of the lake compartment. Very crude estimates (river
to lake half life- 1000 yeats, lake to river half life - 2000 years) were
chosen, with a relatively short half life (5 years) selected for the soil
to lake transfer in order to clearly observe the impact of a lake compart-
ment in the DDT model.
The sedimentation half life was estimated to be on the order of 5 years,
resolving reports of little downward transport of DDT (Sberhardt, Meeks, and
-------
Pertle 1971) and sedimentation as fast as one month in ponds (Bridges,
1963 Trans. American Fisheries Soceity, Vol. 92). Water in lakes that
contain only a trace of DDT can continuously transport it from bottom sedi-
ments to organisms (Wbodwell 1967). If the benthic organisms in lakes
can obtain much DDT from bottom sediemnts, this could contribute to the
extistence of high DDT concentrations in fish in lakes for many years since
such benthic organisms are an important food source for aquatic predators,
(Leland, Bruce, Shimp 1973). Taking into account turbulence and resuspensJon
of DDT residues in lake sediments, and fish feeding on the lake bottoms,
a substantial fraction (.8) of the sedimented DDT residues is estimated to
re-enter the lake fish.
Results
The DDT model with the lake compartment was written in Dynamo language,
and run and compiled in" a Dynamo Iljr system using a Univac 1108 computer.
The total amount of DDt applied to the biosphere in our model system was
1,000,000 tons. The DDT in lakes reached a peak of approximately 325 tons
and DDT in lake fish reached a peak of about 14 tons. Although the appli-
cation rate reaches zero in about 55 years, the DDT in lakes and lake fish
does not approach zero until more than 100 years after the first application.
Concentration of DDT in lakes reaches a peak of 2.56 ppb fifty years
after the first application. Concentration of DDT in lake fish reaches a
peak of 944 ppm fifty years after the first application. The ocean, air
and soil concentrations all reach their peaks thirty or thirty-five years
after the first application.
The concentration in ocean fish reaches its peak at 634 ppb, almost
three orders of magnitudes lower than the concentration in lake fish. The
concentration in oceans reaches its peak at .077 ppb, about one or two orders
of magnitudes lower than the concentration in lakes. At the end of a
century after the first application of DDT, the concentration in lake fish
is 778 ppm, the highest concentration of any part o the biosphere at that
-------
period of time. Concentration in seafish is only 58.45 ppb after a century
After a hundred years, concentration in lakes is 2.11 ppb compared with .007
ppb of DDT in the oceans.
Analysis and Conclusions
We have successfully incorporated a lake compartment into our DDT
global model. The parameters used were certainly not precise, but they
served a purpose. The purpose was to show the potential impact DDT could
have on lakes and lake biota. Although our analysis and estimation of
parameters was not as detailed or exhaustive as Meadows and Randers' analysts,
our results are exaggerated conclusions, they are nevertheless meaningful
conclusions. Actual calculations of lake concentrations and lake fish con-
centrations have been reported up to three orders of magnitude higher than
concentrations in oceans and seafish, which is comparable to our outcomes.
The DDT in lakes in our model has been shown to persist longer in greater
concentrations than in any other compartments of the models. This agrees
with the assumption that recycling of DDT sediments in lake food webs is of
significance. Our model can be of great use in portraying DDT flows into
and out of lakes, so that we can determine the total biological effects that
can occur.
DDT may not only affect the lake biota, but also humans. In the United
States, lake waters provide 98$ of the surface waters available for drinking
purposes and provide 7,400,000 tons of fish for human consumption. The
inhabitants of the United States have already absorbed seme of the DDT cir-
culating in the world (11 ppm DDT residues in fat tissues, Woodwell 1971;
6.6 - 12 ppm DDT residues in fat tissues; Metcalf 1973: Journal of Agricul-
ture and Pood Chemistry, Vol. 21, No. 4). Although DDT is not known to
present a health hazard in the current concentrations, there may be disastrous
results if DDT is present in higher concentrations in humans, or is mixed with
°ther toxic chemicals int he body.
-------
Of course, the peaks of DDT production and usage have passed, and all
this speculation and modelling of DDT transports may be irrelevant now.
But DDT is still being used in other parts of the world such as India
(India's inhabitants have absorbed 12.8 to 31 ppm of DDT-Woodwell 1967).
With DDT's well-documented extensive half life in nautre, we could still
be feeling the adverse effects of DDT for years to come. Peaks of DDT
concentrations can re-occur in local areas because of turbulence in
surface waters causing resuspension and release of previously unavailable
DDT to the biota. DDT sediments may also be oxidized (Woodwell 1971) and
re-enter the food chain. Benthic organisms in lakes may also consume the
DDT sediments and this will cause the recycling of DDT into the food web.
So high concentrations of DDT could exist in lake fish for years to come.
Once again, we would like to stress that these parameters are very
crudely estimated, and in some cases, magnified in order to emphasize the
importance of introducing a lake compartment into a DDT global model. In
spite of this magnification, our results were similar to actual observations.
This indicates that further study of DDT in aquatic environments is needed.
And once again, let us let of stress that even though very little DDT reaches
lakes, judging from the residues in lakes and lake biota, it has had
quite an impact on lake ecosystems. Of course, this may all be irrelevant
since DDT usage has declined. But this model can serve as an example for
transport models of other toxic chemicals that man introduces to the en-
vironment, and can hopefully predict the flows and Impacts of other toxic
chemicals in the global environment.
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BIBLIOGRAPHY
1. Randers, Jorgen; Meadows, Dennis L.
System Dynamics Group, MIT
1971 System Simulation to Test Environmental Policy: A Sample
DDT Movement in the Environment
2. Acree, Fred; Beroza, Morton; Bowman, Malcolm
Entomology Research Division, U.S.D.A.
July-August 1963 Codistillation of DDT with Water
Journal of Agriculture and Food Chemistry Vol. 11, No. 4, pp. 2Vf- /'!:0
3. Bandy, LeRoy W.; Peterle, Tony J.
Ohio State University
June 1969 Transfer to Chlorine-36 DDT in a Meadow
Symposium^ on Radioecology, pp. 232-239
4. Bidleman, T. F.; Olney, C. E.
Department of Food and Resource Chemistry, U. of Rhode Island
October 1973 Chlorinated Hydrocarbons in the Sargasso Sea
Atmosphere and Surface Water
Science, Vol. 183 pp. 516-518
5. Bowman, Malcolm; Acree, Fred; Corbett, M. K.
Entomology Research Division, Agri. Research Service, U.S.D.A.
September-October 1960 Solubility of Carbon-14 DDT in Water
Journal of Agriculture and Food Chemistry, Vol. 8, No. 5, pp 406-'' ;
6. Branson, R. L.; Pratt, P. F.; Roades, J. D.; Oster, J.D.
Department of Soil Science Agriculture, U. of California; U. S.
Salinity Laboratory
1975 Water Quality in Irrigated Watersheds
Journal of Environmental Quality, Vol. 4, No. 1, pp. 33-40
7. Chopra, N. M.; Osborne, Neil B.
Department of Chemistry, NC Agricultural and Technical State University
i
June 1971 Systematic Studies on the Breakdown of p,p -DDT in Tobac;. *
Smokes II, Isolation,and Identification of Degradation Products fa o-
the Pyrolysis of p,p -DDT in a Nitrogen Atmosphere.
Analytical Chemistry Vol. 43, No. 7, pp. 849-453
8. Cramer, J.
School of Chemical Engineering, U. of Pennsylvania
1973 Model of the Circulation of DDT on Earth
Atmospheric Environment, Vol. 7, pp. 241-256
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-2-
9. Crews, W. Brian
U. of California, Davis
After 1971 Static and Dynamic Transport Models of Lead and DDT
pp. 535-548
10. Eberhardt, L.L.; Meek, R.L. Peterle, T. J.
Ecosystems Dept., Winous Point Shooting Club; Ohio State U.
March 1970 DDT in a Freshwater Marsh--A Simulation Study
AEG Research and Development Report , 63 pages
11. Eberhardt, L.L.; Meeks, R. L.; Petele, T.J.
Pacific N. W. Laboratory, Winous Point Shooting Club; Ohio State 1)
March 5, 1971 Food Chain Model for DDT Kinetics in a Freshwater Marsh
Nature, Vol. 340, No. 5288, pp. 60-62
12. Eichelberger, T.W.; Lichtenberg, J. J.
June 1971; Persistence of Pesticides in River Water
Environmental Science and Technology 5(6); 541-544
13. Fisher, Nicholas
Woods Hole Ocean Institute.
August 8, 1975 Chlorinated Hydrocarbon Pollutants and Photosym.hi
of Marine Phytoplankton: A Reassessment
Science, Vol. 189, pp. 463-464
14. Frere, M.H.
Soil Scientist, U.S.D.A.-A.R.S.
1975 Integrating Chemical Factors with Water and Sediment Transport
from a Watershed
Journal of Environmental Quality, Vol. 4, No. 1, pp. 12-17
15. Friess, Seymour L.
Environmental Biological Sciences Dept., Naval Medical Center
Some Observations on the Role of Statistics in Analyzing Environme^ia1
Health Problems Caused by Chemical Pollutants, 16 pages
16. G. W. University Medical Center - Sponsor
March 1, 1976 A Literature Study of Benchmark Pesticides
17. Harrison, H. L.; Loucks, O.L.; Mitchell, J. W.; Parkhurst, D.F.; Tracy,
C.R.; Wats, D.G.; Yannacone, V.J., Jr.
University of Wisconsin
October 1970 System Studies of DDT Transport
Science, Vol. 170, pp. 503-508.
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-3-
18. Hartung, Rolf; Klinger, Gwendolyn W.
Dept. of Industrial Health, U. of Michigan
May 1970 Concentration of DDT by Sedimented Polluting Oils
Environmental Science and Technology, Vol. 4 No. 5, pp. 407-410
19. Hurtig, H.
Canada Dept. of Agriculture
1972 Long-Distance Transport of Pesticides
CEPP/EPPO Bulletin, No. 4., pp. 5-25
20. Lloyd-Jones, C.P.
Long Ashton Research Station, University of Bristol
January 1, 1971 Evaporation of DDT
.Nature, Vol. 229, pp 65-66
21. Ivie, Glen Wayne; Casida, John E.
Division of Entomology, U. of California
1971 Sensitized Photodecomposition and Photosensitizer Activity of
Pesticide Chemicals Exposed to Sunlight on Silica Gel Chromato -
plates
Journal of Agriculture and Food Chemistry, Vol. 19, No. 3, pp. 405-40^
22. MacKay, Donald; Leinonen, Paul J.
December 1975 Rate of Evaporation of Low-Solubility Contaminants
Environmental Science and Technology, Vol. 9, pp. 1178-1180
23. Mayer, R.; Letey, J.; Farmer, W. J.
Dept. of Soil Science and Agri. Engineering, U. of California, Riverside
1974 Models for Predicting Volatilization of Soil-Incorporated Pesticides
Soil Science Society of America's Proceedings, Vol. 38, pp. 563-568 i
!
25. Meeks, Robert L.
Ohio Co-op Wildlife Research Unit
April 1968 The Accumulation of Cl Ring-labelled DDT in a Freshwater
Marsh
The Journal of Wildlife Management, Vol. 32, No. 2, pp. 376-398
26. Nash, R.G.
A.R.S., U.S.D.A.
1973 DDT Persistence in Soil
Agricultural Environmental Quality Inst.-A.P.C.
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-4-
27. Nash, Ralph; Woolson, Edwin
Agricultural Research Service, U.S.D.A.
August 1967 Persistence of Chlorinated Hydrocarbon Insecticides in
Soils
Science, Vol. 157, pp. 924-926
28. Nicholson, H.P.,
Chief, Agro-Environmental Systems Branch, EPA
1975 The Need for Water Quality Models on Agricultural Watersheds
Journal of Environmental Quality, Vol. 4, No. 1, pp. 21-23
29. Nisbet, Ian C.T.
Massachusetts Audubon Society
December 1974 Banning DDT: An Ill-Planned Biogeochemical Experiment
Technology Review, pp. 10-11
30. Onstad, C.A.; Moldenjauer, W.C.
Agricultural Engineering, USDA, Soil Scientist USDA, U. of Minnesota
1975 Watershed Soil Detachment and Translocation Factors
Journal of Environmental Quality, Vol. 4, No. 1, pp 29-33
31. Parker, Patrick; Duce, Robert; Fain, C.S., Marine Science Institute
U. of Rohode Island; Texas A § M University.
January 11-12, 1974 Pollutant Transfer to the Marine Environment, 6!>
pages NSF/IDOE Pollutant Transfer Workshop
32. Peterle, Tony J.
Faculty of Zoology, Program in Environmental Biology, College of BioJ.
Sciences, Ohio State University.
November 9, 1969 DDT in Antarctic Snow
Nature, Vol. 224, p. 620
33. Peterle, Tony J.
Ohio State University
1967 Translocation and Bioaccumulation of Cl-36 DDT in Freshwater Marsh
Proceedings of the 7th Congress of Biologists, pp. 297-308
34. Poirrier, Michael A.; Bordelon, Billy Ray; Laseter, John L.
Dept. of Biol. Sciences, Louisiana State University
November 1972 Adsorption and Concentration of Dissolved Carbon-14
DDT by Coloring Colloids in Surface Waters
Environmental Science and Technology, Vol. 6, No. 12, pp. 1033-1035
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-5-
35. Portmann, J. E.
Ministry of Agriculture, Fisheries and Food, Fisheries Laboratory,
Burnhamon-Crouch, Essex
1975 The Bioaccumulation and Effects of Organochlorine Pesticides
Proceedings, R. Soc. London, B. 189, 291-304
36. Stewart, D. K.R.; Chisholm, D.
Research Station, Canada Dept. of Agriculture
Oct. 1971 Long-Term Persistence of BHC, DDT and Chlordane in a
Sandy Loam Soil
Canadian Journal Soil Science, Vol. 51, pp. 379-385
37. Tatton, J. O.G.; Ruzicko, J.H.A.
Laboratory of the Government Chemist, London
July 22, 1967 Organochlorine Pesticides in Antarctica
Nature, Vol. 215, pp. 346-348
38. Sponsors - U. S. EPA, NBS, Dept. of Commerce, NSF, Energy Research
and Develop. Admin.
May 11-13, 1976 Symposium on Nonbiological Transport and Transformation
of Pollutants on Land and Water. Processes and CritJraJ
Required for Predictive Description
39. Winteringhan, F.P.W.
Joint Div. of Inter. Atomic Energy Agency and Food and Agri. Org. of U K
1971 Some Global Aspects of Pesticide Residue Problems
Israel Journal of Entomology, Vol. VI.
40. Woodwell, George; Wurster, Charles F.; Isaacson, Peter
Biology Dept., Brookhaven National Laboratory
Dept. of Biological Sciences, State University of New York
May 1967 DDT Residues in an East Coast Estuary
Science, Vol. 156, pp. 821-823
41. Woodwell, George M.
March 1967 Toxic Substances and Ecological Cycles
Scientific American, Vol. 216, No. 3, pp. 24-31
42. Woodwell, George M.; Craig, Paul P.; Johnson, Horton H.
Brookhaven National Laboratory
December 10, 1971 DDT in the Biosphere: Where Does It Go?
Science, Vol. 174, pp. 1101-1107
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APPENDIX -
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APPENDIX - 4
September 10, 1975
Academician Yuri Antonlevich Israel
Chief, Main Administration of Hydrometeorological
Service of the USSR
Moscow, pereulok Pavlika Morczova, 12
USSR
Dear Academician Izrael:
As you can see from the enclosed we have a U.S. Government-wide
program to develop models to describe the fate of pesticides on the
globe. The first trial run is being done on DDT and as you might guess
the model would like to be fed more data than we have. The problem does
seem to fit nicely under the category of "Comprehensive Analysis of the
Environment." I am therefore writing to ask if you would be interested
in helping with the data requests listed on the sheet entitled Specific
Data Needs.
I think that these modelling efforts could turn out to be very
instructive and useful in performing comprehensive environmental assess-
ments, and that such an area is an excellent one for US/USSR cooperation.
Should such a joint effort look attractive to yoy, I suggest that the
appropriate Soviet specialist establish direct - contact with:
Dr. Padma R. Datta
Chairman, Interagency Ad_ Hoc
Committee on Mathematical Modeling
U.S. Environmental Protection Agency
Room 809, Crystal Mall Building #2
1921 Jefferson Davis Highway (WH-568)
Arlington, Virginia 20460
I look forward with great anticipation to seeing you again on
October 19.
Sincerely yours,
Roger S. Cortesi
Acting Dirfector, Criteria Development
and Special Studies Division
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Specific Data Needs
1. Photodegradation of DDT in air (a) over the ocean surface particu-
larly from Arctic Ocean and (b) land mass in Siberia or agricultural
land mass.
2. Concentration of DDT or its major metabolites DDE and TDE in aquatic
organisms and terrestrial organisms particularly birds, shrews, and
similar insect-eating mammals.
3. Concentration of DDT and degradation products in Benthic organisms
or suspended particles in Benthic regions of oceans.
4. The data of Nos. 2 and 3 are needed to determine the actual "sink"
of DDT and its metabolites.
5. The rate of dispersion from soil to air and rate of redeposition
to the soil.
6. Agricultural "runoff" to freshwater lakes, estuarine and marine
estuarine (Caspian Sea).
7. The bioconcentration or bioaccumulation if fish (edible and non-
edible) and plankton different species.
8. The biochemical effects of DDT in low concentration (pp, ppt) in
photosynthesis organisms (phytoplankton).
9. The rate of degradation (kinetics) of DDT on the ocean surface and
the concentration of tis degradation product(s).
10. The "terminal" residue levels of DDT, degradation products and
metabolites (DDE and TDE) in food and fiber.
11. The concentration of DDT and its metabolites in ice core samples
before 19^0 and up to the present.
12. The rate of movement of DDT and its metabolites from ocean air,
ppt in soil.
13. The rate of accumulation and dissipation from various ecosystems
(tundra, taiga, estuarines, etc.).
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14. The available data for the rate of uses or total production of
DDT in Russia and other countries.
15. Solutions to mathematical differential or difference equations
for diffusion and absorption/adsorption processes In the environment.
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A Compendium of Matters of Interest
to the Ad Hoc Committee on Mathematical Models
-------
The current thrust of our activity is the treatment of the dispo-
sition of DDT in the biosphere as a paradigm for the study of pesticides.
The vehicle for our investigation is a version of a computer model proposed
in 1970-1971 by D. Meadows and J. Banders, based loosely on the techniques
of J. W. Forerester's "Systems Dynamics" and cast in the associated DYNAMO
simulation language. The model is documented in J. Banders' "DDT Movement
in the Global Environment," Chapter 3 of Toward Global Equilibrium: Collect;
Papers (ed. by D. L. Meadows and D. H. Meadows, Wright-Allen Press, 1973).
The model uses a set of linear difference equations to trace over the
flow and accumulation of DDT in a system consisting of five major ecological
compartments ("soil," "air," "rovers," "ocean," and "fish") each considered
as a homogeneous worldwide aggregate. Very large fresh water bodies are
considered integral with the "ocean1,"' while all other fresh water is sub-
sumed under -"rivers."
Life-forms higher than fish are excluded from the model, except to
furnish a "sink" for some portion of the systems DDT, as noted below.
The driving force for the system is the rate of application of DDT
Because in reality, most application is assumed to occur as crop dusting
of cultivated alnd areas, the model splits application into "air" and "soil"
components to represent convective dispersion during the dusting process.
The model explicitly identifies the following flows:
(1) from soil-to air by evaporation, to rivers by solution
percolation and washing (not separately distinguished) and
out of the system by bacterial and chemical (not distin-
guished) degradation.
(2) from air-to soil and oceans by precipitation and out of
the system by photochemical degradation.
(3) from rivers-to the ocean by runoff.
(4) from the ocean-to air by evaporation, to fish by ingestion
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through plankton, and out of the system through
sedimentation, i.e., settling into the abyssal
depths.
from fish-lnto the ocean by excretion and mor-
bidity and out of the system through destructive
metabolysis (labelled "harmless excretion") and
by trophic predation by higher life forms.
The decay and growth used in the model are all "average" exponential
rates, i.e., linear functions of the levels of various quantities at a
given time. The level of precision can ve inferred from the fact that the
basic units are tons/year.
Most of the assumptions in the model were made by Randers and Meadows
on the basis of a fairly exhaustive literature search at the time of the cor-
struction of the basic model, and are they subject to drastic revision.
The terms describing photochemical action, evaporation from the ocean, and
sedimentation were added by us later and the associated parameter values are
even more crudely approximative than the others.
There are obviously many directions in which refinements could be
attempted, but some questions which we consider critical at present involve
actual rates of photodegradation of DDT (if they are indeed not negligi-
ble) over land and over water, the fate of particulates in the upper atmo-
sphere, the absorption, ingestion by plankton (DDT is lipophilic), whether
there really is substantial sedimentation and whether DDT reaching benthic
levels below the "well mixed layer" in the ocean can readily be transported
back out of the abyss, or if such DDT is essentially removed from the poten-
tially damaging pool in the biosphere, and of course, the broad questions
of transfer rates through the interface between this limited system and one
including birds and mammals, and whether or noth there is any validity at
all in considering systems as highly aggregated as the one we have at hand.
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We append into an internal memo from two mathematician members of
the ad hoc committee on Mathematical Models, outlining the substantive
questions resulting from an introductory rather rapid consideration of the
technical problems to be addressed in constructing a broad scale pesticide
model. It's purpose was and is to stimulate dialogue.
Finally, there is a short list, in no particular order, of
published studies on ecological models and modeling.
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1. INTRODUCTION
We now have the DYNAMO simulation-language compiler up and running on the
NBS computer. We have set up the model, and checked its outputs on our
machine against those reported for the same cases in the Panders-Meadows
(R&M) paper. Furthermore, we have developed a corresponding differential-
equation version, and are proceeding to derive its closed-form solution
in various parametric regimes; this should permit more efficient analysis
than does simulation.
What else can and should we be doing with this model? Our present ideas
can be grouped under the following 5 headings:
(a) Update Data. The R-M model was developed in 1970-1971. One should
by now have better data on the "preferred" values of the various parameters.,
and/or on their reasonable upper and lower limits, as well as production
and/or application data for 1970-1974.
(b) Update Structure. New data insights may be available to guide
changes in the structure of the model. Have additional propagation paths
been observed? Have some "inter-sector" transfer rates, previously thought
negligible, been found appreciable (or vice versa)? Linear kinetics are
assumed thoughout the present model; are there physical considerations
(e.g., encapsulation of remaining DDT, by reaction products, away from
other reactants) which suggest modifying this, and how?
(c) Further Sensitivity and "Predictive" Runs. Once the model is updated
as Indicated by (a) and (b) above, additional runs to ascertain sensitivity
to various uncertainties may be in order. Are there particular patterns
of combinations of parameter-levels which the Ccimittee would like us to
run, or shall we make these selections? Various scenarios as to future rates
of application should be run' which would the committee recommend? For
both sensitivity and "predictive" runs, what outputs would the committee like
emphasized, say for grouping to facilitate comparison of different cases?
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(d) Model Refinement. It is mainly disaggregation that we have in mind
here. In the time domain, this might represent annual differences (due to
malaria epidemics, crop-pest plagues, meteorological abnormalities, etc.)3.
or seasonal cycles. Other plausible areas for disaggregation include spatial,
soil-type, river-type, etc. Suggestions? From a mathematical viewpoint,
the crux is that a combination of exponential decays with different half-lives
is not equivalent to any one exponential decay with some intermediate half-life ,
(e) Model Extension. This has three possible aspects. First, to extend the
model up the chain-of-life from the "fish" level at which it presently termi-
nates. Second, to pass from "concentration" outputs to mortality/morbidity/
disreproduction rates in the affected species. Third, to evaluate the resul-
tant "impacts" in part, in economic coin, but also trying to deal with the-
"Cost to Man" if some species is lost from viewing and from Earth's ecologies
pool. These three aspects are progressively more difficult, and we trust ..-
is clear that our role in any of them (NBS is not a life-science or economic-
science institution) would rely principally on Initiatives by inputs from the
other agencies represented on the Committee. Yet the desire that our joint
efforts be policy-relevant does seem' to demand some efforts in these directJu ,
Indeed, since the "third aspect" above refers to cost impacts of DDT usage,
one should also have available models to estimate and evaluate benefit Impactr
(on public health and agriculture) of such usage but this seems to me
beyond our Committee's charter.
Specific questions relative to (a) - (e) above, and keyed to successive
sections of the R-M paper, are given in (2)-(10) below. Some of them may
be answered in documents available to us, but not yet digested. The questions
pertain to improving the model's inputs and structure; they say nothing
about direct or indirect validation of its (intermediate or final) outputs.
The latter seem so aggregate as to defy checking, obviously a situation of
grave concern for any modeling or model-evaluating effort. Suggestions?
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2. APPLICATION OF DDT
(a) Do we have any better data now, on world or U.S. production of DDT
during 1940-1970? How about 1971-7^? What about the future,, with its
pressures of population on food supply? Do we have better data on the
amount used, year by year, for malaria control? Is there information,
on yearly outbreaks of malaria or particular large programs of malaria
control, which could be used to refine the model's implicit "20$ per year"
to a time series?
(b) The model irrplicityly assumes that each year's application amount of
DDT is equal to that year's production level. Is this reasonable, or are
there inventory/reserve-stock considerations? For example, if pest infesta-
tions or malaria outbreaks have a known cyclical pattern, one might stock
DDT to await the "danger year".
(c) The model assumes in effect that each year's application of DDT occurs
uniformly over the year. This seems dubious, in view of the seasonal cycle
of agriculture, pest life-cycles, and perhaps (?) malaria. Please advise.
The model's time-scale (presently 0.02 yr.) is more than fine enough to
permit representing seasonal effects. This might require spatial disaggre--
gation, say of the Northern and Southern Hemispheres, or perhaps of tempera-
ture zones.
(d) Re the fraction (AEF) of applied DDT that remains airborne: any reason
to change past or current values? Are technological improvements to reduce
this, in mode of delivery or delivered form, likely? Would changes of the
latter type, i.e. in particle size or accessibility to reactions, affect
other model parameters?
3. DDT IN SOIL
(a) What if any are the significant seasonal effects? For example, is the
fall-down to change the assumption that the amount of DDT removed by harvesting
is negligible?
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(b) Any better estimates on degradation rates? Any reason to expect
significantly nonlinear decay?
(c) Does erosion or wash-off lead anywhere except rivers? Significant
take-up by birds, animals, insects, worm-?
(d) Is it plausible that the substantial amount of DDT on walls (which
the model includes in variable S) has the same degradation rate as that
really in soil? That wall-DDT has the same rates of loss by evaporation ancj
by movement to rivers as does soil-DDT? Similarly re plant-DDT?
(e) Can we make a coarse desaggregation into 2-3 classes of soils? Kow is
application divided among them?
4. REMOVAL THROUGH RIVERS
(a) Any better data bearing on solution half-life in soil prior to suspensr'or
in rivers? Is it reasonable to model this as a linear process?
(b) Similarly for run-off rate (river-to-ocean movement). Any evidence
counter to the assumption of negligible degradation while in rivers? What
about deposits cf soil on land, from rivers?
(c) What are the significant seasonal effects?
(d) Is it worthwhile to try using some crude classification of rivers,
perhaps by flow speed?
5. EVAPORATION FROM SOIL
(a) Has there been confirmation of the R-M paper's tentative conclusion
that this must be a significant mechanism for removal of DDT from soil?
If not, what other explanation of its disappearance rate has emerged?
(b) Better data on rate? Reason to introduce nonlinearities? Seasonal
effects? Some useful spatial or soil-type disaggregation?
6. PRECIPITATION FROM ATMOSPHERE
(a) Are the particle sizes right for using data on a "radioactive debris"?
Anything new on precipitation half-life? Why treat this as a linear process?
(b) Any reason to doubt the assumption of negligible degradation while in
the atmosphere? Might volumes and precipitation half-Iifes over land differ
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systematically from those over seas?
(c) Significant seasonal factors? One would expect them for rain,
though not for gravity-induced precipitation.
7. DDT IN OCEANS
(a) Any further evidence on the assumption that almost all ocean DDT
dissolves rather than settles?
(b) Any further evidence on the assunption that evaporation from the ocean
is negligible? Sensitivity to this would be easy to test.
(c) Might there be significant differences between oceans in degradation
rates say due to differences in temperature or salinity? If these match
differences in distributions of plankton and/or fish, then this is a
plausible area for disaggregation.
(d) Any better information on the "mass of the mixed layer"? Apparently
it was not varied in the R-M runs. Is a separation into upper and lower
layers worthwhile?
8. DDT IN PLANKTON
(a) Is the concept of an ocean-plankton concentration factor acceptable?
Any new evidence about its value?
9. UPTAKE IN PISH
(a) Any new evidence on the assumption that uptake direct from water is
negligible relative to that from food? That representation as a 2-level
food chain (fish eat plankton) is adequate?
(b) Any new data on total fish mass and feeding rate? Seasonal effects?
Does DDT harm plankton or fish, tending to reduce their populations?
(c) Is there some useful disaggregation by fish type to be made, because
of either non-uniformities at this point in the model cr differences in
uptake by higher life forms?
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10. ELIMINATION FRCM FISH
(a) Any new information en excretion half-lives? Is a disaggregation on
this basis worthwhile? (The R-M paper mentions some evidence for two
superimposed processes.)
(b) Anything new on fraction of excreted DDT which is degraded form?
(c) Any new data or trends re level of fish removed from ocean (by birds
or man)? Is stock-fish supply negligible? Future shift to more fish in
world diet?
(d) New data or disaggregation re half-life of fish? Is exponential
decay a reasonable way to model deaths of fish?
M.H. Frere, C. A. Omstad and H. N. Eoltan, ACTMD, An Agricultural Chemical
Transport Model," ARS-H-3, June 1975, U.S.D.A.
R. Mayer, J. Letey and W. J. Farmer, "Models for Predicting Volatilization
of Soil-Incorporated Pesticides," Soil Sci. Soc. Amer. Proc., Vol. 38,
1974, pp 563-568.
J. E. Flinn and R. S. Reimers, "Development of Predictions of Future
Pollution Problems," EPA-600/5-74-005, March 197^.
J. Gillett et al., "A Conceptual Model for the Movement of Pesticides
Through the Environment," EPA-66Q/3-74-024, December 197^.
R. M. May "Stability and Complexity in Model Ecosystems," Princeton U.
Press, 1973.
Woodwell Gralg & Johnson, "DDT in the Biosphere: Where Does It Go?"
Science 12/10/71, pp 11-1107.
S. A. Levin, Editor, "Ecosystem Analysis & Predication," Proceedings of a
Conference, Alta, Utah, July 1-5, 197^, S.I.A.M.
J.I. Teasley and L. H. Keith, Proceedings of 169th National Meeting of the
American Chemical Society, Philadelphia Pennsylvania, April 6-11, 1975
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(Symposium on Fate of Pollutants in the Air and Water Environments;
Symposium on Mathematical Modelling of Biochemical Processes in Aquatl c
Ecosystems).
The Journal of Environmental Modelling, Copenhagen, Denmark.
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Summary of the M Hoc Committee's Activities As Report
to the FWGPM by Committee Chairman Dr. P. R. Batta
of EPA on 5/21/75
This interagency, interdisciplinary ad hoc Committee on Mathematical Models
of Pesticide Behavior in the Environment was charged (1) with evaluating all-
available mathematical model(s) capable of predicting the fate and movement <.
pesticide(s) in the environment and (2) with devising a working mathematical!
model or models.
The committee selected DDT as a model compound due to the voluminous data In
the literature and the opportunity to determine the fate and movement of resi-
dual DDT in the continental United States since the banning of its use here-
in 1972.
The Action Program (Devember 1973) was submitted by this ad hoc committee and
finally approved by the FWGPM and other federal agencies. The program consisted
of an evaluation of the intrinsic and extrinsic merits of the various pre-
dictive mathematical model (s) by computer simulation test runs using the DYJM "":
simulation language compiler. EPA (OPP/TSD) has now accepted the lead in
menting this interagency effort. The ad hoc committee's activities are as
follows:
a. IBS of the Department of Commence, in cooperation with NTH
computer division of DHEV, is currently evaluating the various
predictive mathematical model(s). Most of the published mathe-
matical model(s) based on system dynamics are of the DYNAMO
model type. To date, 45 different computer simulation DYNAMO
model test runs have been conducted to evaluate the mathematical
properties of the linear, non-linear functions of the system
parameters in each compartment and sensitivity analysis using
differential and/or difference equations at various steady-
state equilibriums. The results indicate that there is a
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paucity of data on several model compartments of critical
importance, for example, data en the ocean water surface,
ocean mixed layer and ocean abyssal layer. Due to this
paucity of data, coupled with low mean residence time of
DDT in the atmosphere (30-40 days) and the extremely low
concentration of DDT in the ocean (ppt), the assumption
that oceans act as a "sink" for DDT as postulated by the
published model(s) cannot be ascertained as the true fate of
DDT in the environment at this time. The committee, therefore,
requested: (1) Lament Geographical Laboratory of Columbia
University to supply a few ocean bottom core samples (both pre-
and post 1942) for analysis of DDT by a member of the com-
mittee of NOAA. (2) Ten principle investigators of the NSF
International Decade of Ocean Exploration of Pollutant Trans-
fer Program to supply existing data en DDT or to obtain samples
for analysis of DDT in the ocean's water surface, mixed layer,
and abyssal layer. (3) The International Activities Office of
EPA's Administrator to help this committee in obtaining data
on DDT or samples for analysis of DDT. in the water surface,
mixed layer and abyssal layer of the world's oceans. (4) Army's
AIDZEC project and CRREL project to obtain a few ice core samples
from Greenland, Antarctica, and the North Pole (both pre and post
1942) for analysis of DDT by NCAA's Bauefort Laboratory.
b. To update the data on DDT, a literature search will be conducted
by a graduate student working half-time in Dr. Peterle's Ecology
Department at Ohio State University under the supervision of this
Committee through TSD/OPP/EPA who will supply the graduate student
with an on-line computer system (desk model). This literature
search program will be supported financially along with Dr. Peterle's
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work on behavior of DDT in fresh water marshes and terrestrial
organisms by ERDA/Environmental Safety Division.
c. The evaluation and validation of the updated data before input
into the model(s) will be conducted by committee members
versed in specific disciplinary areas of the model parameters.
d. After completion of the simulation test runs with updated data.
using the DYNAMO simulation language compiler, the committee
may consider changes in the DYNAMO model(s) structure, refine-
ment (disaggregation), extension (propagation pathways), and
predictive runs having various scenarios.
e. The committee intends to identify the type of data needs,
knowledge gaps, research priorities, etc., during the model
evaluation efforts and sensitivity analysis (absolute and/or
relative sensitivity) in each compartment of the DYNAMO Model(s)
so as to improve the model's input and structure and validation
of its output (final, intermediate, etc.). The committee wMl
also evaluate cost to man, resultant impact in socio-econcmics
and health effects, etc.
f. The committee is also considering the purchase of an 1108 DYNAMO
compiler from Pugh Roberts Associates providing the justification
is substantial.
The committee has requested figures of the world product of DDT slrx
from World Health Organization. Dr. whittemore, operations Division/
OPP/EPA, made available to the members of the committee the latest report en
production of DDT by FAO. It appears that the estimated world production of
DDT in 1975 will be about 100,000 metric tons.
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ft
f
I
BIBLIOGRAPHY . \.
!,;
1. Randers, Jorgen and Meadows, Dennis L.
System Dynamics Group
MIT
1971 System Simulation to Test Environmental Policy: A Sample
Study of DDT Movement in the Environment
2. Acree, Fred; Eeroza, Morton; Bowman, Malcolm
Entomology Research Division U.S.D.A.
July-August 1963 Codistillation of DDT with Water
Agri. and Food Chemistry Vol. 11, No. 4, pp. 278-280
3. Bandy, LeRoy W.; Peterle, Tony J.
Ohio State University
June 1969 Transfer of Chlorine-36-DDT in a Meadow
Symposium on Radioecology, pp. 232-239
4. Bidleman, T. P.; Olney, C.E.
Dept. of Food and Resource Chemistry, U. of Rhode Island
October 1973 Chlorinated Hydrocarbons in the Sargasso Sea Atmosphere
and Science,, Vol. 183 pp. 516-518
5. Bowman, Malcolm; Acree, Fred and Corbett, M.K.
Entomology Research Division, Agri. Research Service, U.S.D.A.
September- October 1969 Solubility of Carbon-l4 DDT in Water
Agricultural and Food Chemistry, Vol. 8 No. 5, pp 406-408
6. Branson, R.L., Pratt, P. P.; Rhoades, J. D., Oster, J.D.
Dept. of Soil Science Agriculture, U. of California; U.S Salinity
Laboratory
1975 Water Quality in Irrigated Watersheds
Journal of Environmental Quality, Vol. 4 No. 1, pp 33-40
7. Chopra, N. M. and Osborne, Neil B.
Dept. of Chemistry, NC Agricultural and Technical State University
June 1971 Systematic Studies on the Breakdown of p, p1 - DDT in Tobacco
Smokes II. Isolation and Identification of Degradation Products from
the Pyrolysis of p, p1 - DDT in a Nitrogen Atmosphere. Analytical
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8. Cramer, J.
School of Chemical Engineering, Y. of Pennsylvania
1973 Model of the Circulation of DDT on Earth
Atmospheric Environment, Vol. 7, pp. 241-256
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9- Crews, W. Brian
U. of California, Davis
After 1971 Static and Dynamic Transport Models of Lead and DDT
PP. 535-5^8.
10. Eberhardt, R. L. ; Meeks; Peterle, T. J.
Ecosystems Dept., Winous Point Shooting Club, Ohio State U.
March 1970 DDT in a Freshwater MarshA Slinulation Study
AEG Research and Development Report, 63 pages
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Pacific N.W. Laboratory, Winous Point Shooting Club; Ohio State U.
March 5, 1971 Food Chain Model for DDT Kinetics in a Freshwater
Marsh Nature, Vol. 340, No. 5288, pp. 60-62
12. Eichelberger, T. W.; Lichtenberg, J. J.
June 1971 Persistence of Pesticides in River Water
Environmental Science and Technology 5(6): 541-544
13. Fisher, Nicholas
Woods Hole Ocean. Institute
August 8, 1975 Chlorinated Hydrocarbon Pollutants and Photosynthesis
of Marine Phytoplankton: A Reassessment
Science, Vol. 189, pp. 463-464
14. Frere, M. H.
Soil Scientist, U.S.D.A. - A.R.S.
1975 Integrating Chemical Factors with Water and Sediment Transport
from a Watershed
Journal of Environmental Quality, Vol. 4, No. 1, pp. 12-17
15. Friess, Symour L.
Environmental Biological Sciences Dept., Naval Medical Center
Some Observations on the Role of Statistics in Analyzing Environmental
Health Problems Caused by Chemical Pollutants, 16 pages
16. G. W. University Medical Center - Sponser
March 1, 1976 A Literature Study of Benchmark Pesticides
17. Harrison, H. L.; Loucks, 0. L.; Mitchell, J. W.; Parkhurst, D. P.;
Tracy, C. R., Watts, D. G.; Yannacone, V. J., Jr.
University of Wisconsin
October 1970 Systems Studies of DDT Transport
Science. Vol. 170, pp. 503-508
18. Hartung, Rolf and KLinger, Gwendolyn W.
Dept. of Industrial Health, U. of Michigan
May 1970 Concentration of DDT by Sedimented Polluting Oils
Environmental Science and Technology, Vol. 4 No. 5, pp. 407-410
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19. Hurtig, H.
Canada Dept. of Agriculture
1972 Long-Distance Transport of Pesticides
OEFP/EPPO Bulletin. No. 4, pp. 5-25
20. Lloyd-Jones, C.P.
Long Ashton Research Station, University of Bristol
January 1, 1971 Evaporation of DDT
Nature, Vol. 229, PP 65-66
21. Ivic, Glen Wayne and Casida, John E.
Division of Entomology, U. of California
1971 Sensitized Photodecomposition and Photosensitizer Activity of
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December 1975 Pate of Evapoartion of Low-Solubility Contaminants
Environmental Science and Tech. Vol. 9, pp. 1178-1180
23. Mackay, Donald; Wolkoff, A. W.
Department of Chemistry Engineering and Applied Chemistry
1973 Evaporation Rates of Low-Solubility Contaminants from Water Bodies
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Environ. Science and Technology, Vol 7, pp. 6ll-6l4
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Dept. of Soil Science and Agri. Engineering, U. of California,
Riverside
1974 Models for Predicting Volatilization of Soil-Incorporated Pesticides
Soil Science Society of America's Proceedings. Vol. 563-568
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Ohio Co-op Wildlife Research Unit
April 1968 The Accumulation of 36C1 Ring-labelled DDT in a Freshwater
Marsh
The Journal of Wildlife Management, Vol. 32, No. 2, pp. 376-398
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Agricultural Research Service, U.S.D.A.
August 1967 Persistence of Chlorinated Hydrocarbon Insecticides in So.i 1 r
Science, Vol. 157, pp. 924-926
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28. Nicholson, H.P.,
Chief, Agro-Enviormental Systems Branch EPA
1975 The Needs for Water Quality Models en Agricultural Watersheds
Journal of Environmental Quality, Vol. 4, No. 1, pp. 21-23
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Massachusetts Audubon Society
December 1974 Banning DDT: An Ill-Planned Biogeochemical Experiment
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Agricultural Engineering, USDA, Soil Scientist USDA, U. of Minnesota
1975 Watershed Soil Detachment and Trans. Factors
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Faculty of Zoology, Program in Environmental Biology, College of Bid.
Sciences, Ohio State U.
Nov. 8, 1969 DDT in Antarctic Snow
Nature, Vol. 224, p. 620
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Ohio State U.
1967 Translocation and Bioaccumulation of Cl-36 DDT in Freshwater Marsh
pp. 297-308 Proceedings of the 7th Congress of Biologists
34. Poirrier, Michael A.; Bordelon, Billy Ray; Laseter, John L.
Dept. of Biol. Sciences, Louisiana State U.
Nov. 1972 Adsorption and Concentration of Dissolved Carbon-l4 DDT by
Coloring Collaids in Surface Waters
Environmental Science and Technology, Vol. 6, No. 12, pp. 1033-1035
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Ministry of Agriculture, Fisheries and Food, Fisheries Laboratory, Eurnbyn
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Oct. 1971 Long-Term Persistence of BKC, DDT and Chlordane in a Sandy Loa;.
Soil
Canadian Journal Soil Science 51: 379-383
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37. Tatton, J. O'G.; Ruzicko, J. H. A.
Laboratory of the Government Chemist, London
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Nature, Vol. 215, PP 346-348
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May 11-13 3 1976 Symposium on Nonbiological transport and transformat.ic r-
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data required for predictive description
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Joint Div. of Inter. Atomic Energy Agency and Food and Agri. Org. of U.N,
1971 Some Global Aspects of Pesticide Residue Problems
Israel Journal of Entomology, Vol. VI
40. Woodwell, George, Wurster, Charles P. Isaacson, Peter
Biology Dept., Brookhaven National Laboratory
Dept. of Biological Sciences, State University of New York
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Science, Vol. 156 pp 821-823
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March 1967 Toxic Substances and Ecological Cycles
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42. Woodwell, George M., Craig, Paul P., Johnson, Horton H.
Brookhaven National Laboratory
December 10, 1971 DDT in the Biosphere: Where does it go?
Science, Vol. 174, pp. 1101-1107
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