v>EPA
United States
Environmental Protection
Agency
Industrial Environmental Research EPA-600/7-79-140
Laboratory June 1979
Research Triangle Park NC 27711
Criteria for Assessment
of Environmental
Pollutants from CoaJ
Cleaning Processes
Interagency
Energy/Environment
R&D Program Report
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the INTERAGENCY ENERGY-ENVIRONMENT
RESEARCH AND DEVELOPMENT series. Reports in this series result from the
effort funded under the 17-agency Federal Energy/Environment Research and
Development Program. These studies relate to EPA's mission to protect the public
health and welfare from adverse effects of pollutants associated with energy sys-
tems. The goal of the Program is to assure the rapid development of domestic
energy supplies in an environmentally-compatible manner by providing the nec-
essary environmental data and control technology Investigations include analy-
ses of the transport of energy-related pollutants and their health and ecological
effects; assessments of, and development of, control technologies for energy
systems; and integrated assessments of a wide range of energy-related environ-
mental issues.
EPA REVIEW NOTICE
This report has been reviewed by the participating Federal Agencies, and approved
for publication. Approval does not signify that the contents necessarily reflect
the views and policies of the Government, nor does mention of trade names or
commercial products constitute endorsement or recommendation for use.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/7-79-140
June 1979
Criteria for Assessment
of Environmental Pollutants
from Coal Cleaning Processes
by
R. A. Ewing, B. W. Cornaby, P. Van Voris,
J. C. Zuck, G. E. Raines, and S. Min
Battelle-Columbus
505 King Avenue
Columbus, Ohio 43201
Contract No. 68-02-2163
Task No. 242
Program Element No. EHE623A
EPA Project Officer: James D. Kilgroe
Industrial Environmental Research Laboratory
Office of Energy, Minerals, and Industry
Research Triangle Park, NC 27711
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Research and Development
Washington, DC 20460
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FOREWORD
Many elements and chemical compounds are known to be toxic to man and
other biological species. But, our knowledge concerning the levels and
conditions under which these substances are toxic is extremely limited.
Further, little is known concerning the emission of these pollutants from
industrial processes and the mechanism by which they are transported,
transformed, dispersed, or accumulated in our environment.
Portions of the Federal Clean Air Act, the Resource Conservation and Recovery
Act, and the Federal Water Pollution Control Act require the U.S. Environmental
Protection Agency (EPA) to identify and regulate hazardous or toxic substances
which result from man's industrial activities. Industrial pollutants are often
identified only after harmful health or ecological effects are noted. Remedial
actions are costly, the damage to human and other biological populations is
often irreversible, and the persistence of some environmental contaminants
may endanger future populations.
EPA's Office of Research and Development is responsible for health and
ecological research, studies concerning the transportation and fate of pollutants,
and the development of technologies for controlling industrial pollutants.
As a part of this Office of R&D, the Industrial Environmental Research Laboratory,
which is responsible for development of pollution control technology, conducts
large environmental assessment program. The primary objectives of this program
a
are:
The development of information on the quantities of toxic
pollutants emitted from various industrial processes—
information needed to prioritize health and ecological
research efforts.
• The identification of industrial pollutant emissions
which pose a clearly evident health or ecological risk
and which should be regulated.
• The evaluation and development of technologies for
controlling pollution from these toxic substances.
The coal cleaning environmental assessment program has as its specific
objectives the evaluation of pollution and pollution control problems which
are unique to coal preparation, storage, and transportation. The coal
preparation industry is a mature yet changing industry and in recent years
significant achievements have been made in pollution abatement. The environ-
mental assessment work will document existing environmental regulations and
the adequacy of commercial pollution control techniques. Hopefully, any
potential long range environmental problems which may exist will be identified,
Specifically, this report provides preliminary criteria for the assessment of
environmental pollutants associated with coal cleaning processes.
11
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ABSTRACT
The objective of this research was to develop criteria for the assess-
ment of environmental pollutants associated with coal cleaning processes.
The primary problem is concerned with emissions of pollutants to all three
media—air, water, and land—and assessment of their effects on man and the
environment.
The pollutants associated with coal cleaning are primarily inorganic
compounds associated with the ash fraction. Lists of potential pollutants
from coal cleaning and utilization containing hundreds of entries have been
proposed. A group of 51 elements and 23 substances or groups of substances
was selected judgmentally from larger lists for investigation.
The fundamental criterion for ranking the importance of any pollutant
is the relationship between its expected environmental concentration and the
maximum concentration which presents no hazard to man or biota on a long-term
basis. Environmental concentrations depend upon emission rates and the
effects of physical transport and dispersion. Ultimately, these data will
come from field measurements but in the interim must be estimated. Method-
ology for these estimations are reviewed; the requisite methodology is well
developed and little further development appears necessary.
Ecological transport and distribution is much less well developed, and
the investigation has revealed that there are large gaps in the data for
many elements and many species. Illustrative data are presented for eight
of the most important trace elements.
Twenty formulae for deriving estimated permissible concentrations
(EPC's) were identified and considered in this study. No one formula was
found to fulfill all needs; recommendations were developed for suggested
improvements. A major deficiency in all formulae is the inability to utilize
the variety of pertinent toxicological data available. Improved methods
are badly needed for interconversion of toxicological data to more useable
iii
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forms. Equations have been developed for conversion of toxicological data
for four non-oral routes of administration to an LD^Q basis.
This preliminary investigation has shown that the problem of an adequate
health and toxicological effects data base equals or exceeds the methodology
problem. One of the most critical information needs to support the derivation
of EPC's are dose-response data on the health and ecological effects of
individual pollutants and their mixtures. Data are sparse on the pollutants
of concern to coal cleaning, and much more research needs to be done in this
area.
This report was submitted in partial fulfillment of Subtask 242 of
Contract No. 68-02-2163 by Battelle's Columbus Laboratories under the sponsor-
ship of the U .S .Environmental Protection Agency. The report covers the period
from November 8, 1976, to October 30, 1978, and work was completed as of
December 30, 1978.
iv
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TABLE OF CONTENTS
Foreword ±±
Abstract ill
List of Tables ix
List of Figures xi
Acknowledgements xii
1.0 Executive Summary/Overview ...... 1
1.1 Introduction 1
1.2 Potential Environmental Pollutants/Regulations 2
1.3 Estimating Environmental Concentrations 5
1.4 Developing Environmental Goals 7
1.5 Decision Criteria for Prioritization 13
1.6 Recommendations for Future Work 13
2.0 Introduction 15
2.1 Basis for Environmental Assessment 16
2.2 Approach to Environmental Assessment 16
3.0 Potential Environmental Pollutants
and Applicable Regulations 18
3.1 Universe of Pollutants 18
3.1.1 Pollutants of Concern 18
3.1.2 Pollutants in Coals 25
3.2 Federal and State Standards and Criteria 28
3.2.1 Air Pollution Regulations 31
3.2.1.1 Federal . . . 31
3.2.1.1.1 Ambient Air Quality Standards ... 31
3.2.1.1.2 New Source Performance Standards . . 33
3.2.1.1.3 Hazardous Pollutant Emission
Standards 35
3.2.1.1.4 Prevention of Significant
Deterioration of Air Quality ... 35
3.2.1.1.5 Visibility Protection for
Federal Class I Areas 36
3.2.1.1.6 Nonattainment Areas 35
3.2.1.2 State 38
v
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TABLE OF CONTENTS (Continued)
Page
3.2.2 Water Pollution Regulations 30
3.2.2.1 Federal 39
3.2.2.1.1 Effluent Guidelines Limitations ... 39
3.2.2.1.2 Toxic Pollutants 40
3.2.2.1.3 Water Quality Criteria 43
3.2.2.2 State 43
3.2.3 Solid Waste Regulations , ^,
3.2.3.1 Federal
3.2.3.2 State
46
3.3 References ........................ ^
4.0 Estimation of Environmental Concentrations ........... rn
4.1 Modeling of Pollutant Emissions ...... <....... 50
4.1.1 Fractionation Factors ......... , ..... r,
4.1.2 Estimation of Emission Concentrations ....... /-
4.2 Modeling of Physical Transport and Distribution
4.2.1 Air Dispersion of Pollutants ............ ,-n
4.2.2 Water Dispersion of Pollutants ........... /-Q
4.2.3 Dispersion Through Porous Media .......... 63
4.2.4 Goundwater Dispersion of Pollutants ........
4.3 Ecological Transport and Distribution
4.3.1 Ecological Overview
4.3.2 Pollutant Transfer
4.3.2.1 Pollutant Uptake in Plants ........ 72
4.3.2.2 Pollutant Uptake/Retention
in Animals ............... 73
4.3.2.3 Ecological Accumulation and
Magnification .............. -,,
4.3.3 Designated Priority 1 Pollutants .......... 77
4.3.3.1 Arsenic .................. 70
4.3.3.2 Beryllium .............. '.'.'. 80
vi
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TABLE OF CONTENTS (Continued)
Page
4.3.3.3 Cadmium 83
4.3.3.4 Iron 91
4.3.3.5 Lead 91
4.3.3.6 Manganese 96
4.3.3.7 Mercury 97
4.3.3.8 Selenium 103
4.3.3.9 Other Pollutants 107
4.3.4 Discussion 107
4.4 References 110
5.0 Development of Environmental Goals 122
5.1 Introduction 123
5.1.1 Basic Problem 123
5.1.2 Working Definitions 124
5.1.3 Scope 125
5.2 Research Approach 126
5.3 Review of Formulae 126
5.3.1 Basic Formula 127
5.3.2 Overview of State-of-the-Art Formulae 127
5.4 Identification of Major Strengths
and Weaknesses of Formulae 132
5.4.1 Media Viewpoint 132
5.4.2 Dose/Response Viewpoint 133
5.4.2.1 Strengths 133
5.4.2.2 Limitations 134
5.4.3 Adjustment Factors 134
5.4.3.1 Strengths 135
5.4.3.2 Limitations 135
5.4.4 Selection of Limitations for Analysis 137
5.5 Research to Reduce Limitations in Formulae 139
5.5.1 Identification of Other Formulae 139
vii
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TABLE OF CONTENTS (Continued)
Page
5.5.1.1 Maximum Permissible
Concentrations for Radioisotopes . . . 140
5.5.1.2 CUMEX (Cumulative Exposure) Index ....
5.5.2 Correlation of Oral LD and Other Routes
of Administration
5.5.3 Use of Chronic Effects Data ...........
5.5.4 Extrapolation of Response of One
Animal Species to Another ........... -j.51
5.5.4.1 Method I 153
5.5.4.2 Method II ' [ 156
5.5.4.3 Comparison of Methods I and II
5.5.5 Toward a Biological Basis for
Safety Factors
5.5.5.1 Ranges of Sensitivity in Selected
Aquatic Plants and Animals
5.5.5.2 Ranges of Sensitivity to Toxicants
of Selected Terrestrial Animals .
5,5.5.3 Selected Findings Related
to Safety Factors
5.6 Application of Improved Formulae ............
5.7 References ....................... 165
6.0 Decision Criteria for Prioritizing Pollutants,
Sources, and Problems ...................
6.1 References ....................... 173
7.0 Recommendations for Future Work ............... 174
7.1 Potential Environmental Pollutants ........... 174
7.2 Estimation of Environmental Concentrations ....... 174
7.3 Development of Environmental Goals ........... 175
Appendix A. Sample Computer Printout for Emission
Concentration Model ................ 177
Appendix B. Additional Formulae for Developing Estimated
Permissible Concentrations (EPC's) ......... 183
viii
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LIST OF TABLES
Paee
TABLE 3-1. Proposed Priority 1 Pollutants for
Coal Cleaning Processes
TABLE 3-2. Mean Analytical Values for Elemental Concentration
in Coal Samples from Various Regions 26
TABLE 3-3. Geometric Mean Concentrations of
Eight Elements in Coal 28
TABLE 3-4. Concentrations of Trace Metals in
Coal and Coal Dust 29
TABLE 3-5. National Ambient Air Quality Standards 32
TABLE 3-6. Allowable Pollutant Increases above
Baseline Concentrations 37
TABLE 3-7. Effluent Limitations Guidelines for
Coal Preparation Plants 41
TABLE 3-8. List of 65 Pollutants Being Considered
for Effluent Limitations 42
TABLE 4-1. Values for Arsenic Uptake 81
TABLE 4-2. Values for Beryllium Uptake 84
TABLE 4-3. Values for Cadmium Uptake 86
TABLE 4-4. Values for Iron Uptake 92
TABLE 4-5. Values for Lead Uptake 94
TABLE 4-6. Values for Manganese Uptake 98
TABLE 4-7. Values for Mercury Uptake 100
TABLE 4-8. Values for Selenium Uptake 105
TABLE 5-1. EPC/MATE Formulae for the Air Medium 128
TABLE 5-2. EPC/MATE Formulae for the Water Medium 129
ix
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LIST OF TABLES (Continued)
Page
TABLE 5-3. EPC/MATE Formulae for the Land Medium 130
TABLE 5-4. Summary of Rankings of Limitations of Formulae
Used in Development of Environmental Goals .... 133
TABLE 5-5. Equations Relating Toxicological Effects from Non-Oral
Administration Routes to the Oral Route
TABLE 5-6. Summary of Biological Effects of
Various Elements on Mice and Rats
During Life-Time (Chronic) Experiments 148
TABLE 5-7. Summary of Biological Effects of Six Elements
on Multigenerations of Mice and Rats 150
TABLE 5-8. Tissue Concentrations of Tour Elements
in Organs of Controls and Exposed
Mice and Rats 152
TABLE 5-9. LC^Q Concentrations of Various Metals for
Three Species of Freshwater Plankton 161
TABLE 5-10. Sensitivity of Early Juvenile Fish
to Various Metals 162
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LIST OF FIGURES
Page
FIGURE 3-1. Illustration of Relationship of Elements
Selected for Priority 1 Pollutant List
to Those Omitted 23
FIGURE 4-1. Fractionation Factor Versus Ionic Potential 52
FIGURE 4-2. Calculation of Fractionation Factors, Arsenic,
Herrin (No. 6), Illinois (Float-Sink Set 1) 55
FIGURE 4-3. Generalized Flow Quantities in Coal
Cleaning Process 57
FIGURE 4-4. General Area for Which Generic Ecosystem is
Defined for Purposes of Estimating Distribution
of Potential Coal Cleaning Pollutants 68
FIGURE 4-5. Compartmental Model of Generic Ecosystem and
Dominant Pathways of Pollutant Transport 69
FIGURE 4-6. Matrix Configuration of Important Rate Transfer
Coefficients Within the Generic Ecosystem 70
FIGURE 4-7. Mercury Interconversions in the Environment 75
FIGURE 5-1. Interrelationships of Five Principal
Phases of Environmental Assessment 125
FIGURE 5-2. Subcutaneous LD ' s for Hydrogen Cyanide 155
LjU
FIGURE 5-3. Oral LD 's for Arsenic Trioxide 157
XI
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ACKNOWLEDGEMENTS
This study was conducted as a task on Battelle's Columbus Laboratories'
program, "Environmental Assessment of Coal Cleaning Processes", supported
by the Industrial Environmental Research Laboratory, U.S. Environmental
Protection Agency, Research Triangle Park (IERL/RTP), North Carolina,
under Contract No. 68-02-2163.
In addition to the authors, significant contributions were made by
Steven E. Pomeroy, M. Claire Matthews, Ralph I. Mitchell, and Frederick
K. Goodman. The contributions of the Program Manager, G. Ray Smithson, Jr.;
the Deputy Program Manager, Alexis W. Lemmon, Jr.; and the Task Leader,
Gerald L. Robinson, are gratefully acknowledged.
The advice, counsel, and comments of the EPA Project Officer, Mr. James
D. Kilgroe, and others at the IERL/RTP facility were invaluable in performance
of this work.
xii
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1.0 EXECUTIVE SUMMARY
1.1 Introduction
The fundamental criterion for assessing environmental pollutants
associated with coal cleaning is the relationship of the permissible
environmental concentrations to those which actually can or do occur.
Elucidating this relationship involves determining a number of factors, some
of which are complex:
(1) The pollutants most needing control need to be identified,
either because of the quantities emitted or their toxicities,
or both. Also, almost by definition, substances designated as
pollutants by EPA are candidates for control. Identification
of the pollutants most needing control is a basic objective of
this study. The pollutants likely to be associated with coal
cleaning are discussed in Section 3.1. Also important are the
ever-changing Federal and state environmental regulations
governing the emission of pollutants; the current status of
those regulations likely to affect coal cleaning processes
are discussed in Section 3.2.
(2) Data on the quantities and concentrations of those pollutants
emitted to the environment are needed. These data come from
other subtasks analyzing the process steps (coal cleaning,
handling, transportation, storage, and combustion). The
approach to this problem is discussed in Section 4.1.
(3) Estimates of environmental concentrations of pollutants in
all three media—air, water, and land—are needed. This
estimation initially involves physical transport and dispersion;
the approaches to modeling physical distribution are discussed in
Section 4.2. Ecological transport and distribution is much
less well-studied; there are large gaps in the data for many
elements and many species. Qualitatively, the pathways and
mechanisms for accumulation and dispersal have been identified;
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the problems arise in attempting to quantify these mechanisms.
The approach to these problems and several illustrative
examples are described in Section 4.3.
(4) One of the most critical information needs is data on the
toxicities of the individual pollutants, from which estimated
permissible concentrations (EPC's) can be derived. Also
needed are improved methods for converting toxicological data
to the threshold levels represented by EPC's, and biologically
supported safety factors for incorporation into the formulae.
The complexities of deriving EPC's on the basis of available
toxicological data are discussed in Section 5.
(5) Decision criteria are needed to determine the relative priori-
ties to be assigned to controlling specific pollutants.
Compiling and analyzing the data mentioned above will lead to
these criteria. Approaches to this somewhat subjective exercise
are discussed in Section 6.
(6) The environmental assessments to be performed as another task
on this program will require quantitative emission and
distribution data for specific process configurations, coal types,
geographic locations, etc. In developing and illustrating
assessment criteria and methodologies, this study utilizes
approximations of emissions and dilutions such as might be
associated with a hypothetical coal cleaning plant.
1.2 Potential Environmental Pollutants/Regulations
The pollutants directly associated with coal cleaning are primarily
inorganic compounds associated with the ash fraction. Water will be the
major receptor of these pollutants; operations causing major emission of
air pollutants are infrequent in coal cleaning. The largest air emissions
will arise as particulates from thermal dryers and as fugitive dust from coal
storage and refuse piles and coal handling. The reverse situation is true
in the ultimate combustion of coal; air emissions, particularly SC^ and
suspended particulates, are of much more concern than water effluents.
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Lists of potential pollutants from coal cleaning and utilization
containing hundreds of entries have been compiled. To arrive at a more
manageable number, a "Priority 1" list was selected to include those elements
and substances already identified as pollutants of concern, and whose
presence in finite concentrations in coal cleaning processes is known or
highly suspected. This list contains 49 elements and 23 substances or groups
of substances, the latter including such well-known items as SO , total
suspended particulates (air), and total suspended solids (water).
An abbreviated pollutant "short list" of eight elements and four
compound groups was also employed to limit the scope of some of the explora-
tory studies undertaken.
Abundance is a factor in evaluating the significance of a pollutant.
Almost every naturally occurring element occurs in coal, but the abundances
vary widely, both regionally and from seam to seam. Averages and ranges
representative of U. S. coals determined by the Illinois Geological Survey
are being used in pollutant evaluations.
Health and ecological considerations are important criteria for
assessing environmental pollutants. Also important are Federal and state
regulations governing emissions. Recent significant changes in Federal
regulations have occurred, and more are mandated by laws passed but not yet
fully implemented. Some of these will directly affect allowable emissions
from coal cleaning processes. Others will affect the processes indirectly,
through new and more restrictive regulations governing emissions from
coal utilization.
The Clean Air Act Amendments of 1977 may have the most effect on
both coal cleaning and utilization. Earlier regulations had established
New Source Performance Standards (NSPS) for particulate emissions from
coal cleaning plants. The 1977 Amendments require establishing percentage
reduction standards for S0« emissions from the combustion of coal in large
electric utility steam generating units; 85 percent has been proposed. This
cannot now be achieved by coal cleaning alone. The effects of these probable
regulations on the utilization of coal cleaning is uncertain. More restrictive
regulations on existing boilers, which are also possible, may increase the
demand for cleaned coal. Existing boilers are likely to represent a larger
market for clean coal than new boilers for years to come.
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Other sections of the Clean Air Act Amendments of 1977 which may
significantly influence both the role of cleaned coal and the operation of
coal cleaning plants are those to prevent significant deterioration of air
quality (PSD) and the emission control measures which will be required in
nonattainment areas not now achieving primary or secondary ambient air
quality standards. States are to continue to make "reasonable further
progress" in achieving annual incremental reductions of pollutants not
meeting standards; these requirements will tend to favor cleaner fuels.
In 1977, effluent guidelines were promulgated for existing coal
cleaning plants and proposed for new sources. Regulated pollutants are
total suspended solids (TSS), iron, and manganese. Discharge limits for TSS
are sufficiently low (35 ppm for a 30-day average) so that any plant in
compliance should have no siltation problem downstream. The proposed perfor-
mance standards for new sources are structured to strongly favor the recycle
of wastewater. No discharge of pollutants is permitted for sources which do
not recycle wastewater.
The Clean Water Act of 1977 introduced a new requirement for the
control of toxic pollutants which are to be limited by the application of
the best available technology economically achievable (BATEA). Pursuant to
this act, the EPA Administrator published a list of 65 toxic pollutants for
which effluent standards are required. Regulations previously existed for
six of the listed pollutants, but regulations have not yet been promulgated
for any of the other listed pollutants. EPA has further identified specific
compounds, within the chemical classes in the published list, to be considered
for effluent standards. The thirteen elements in the published list, and
their compounds, should receive emphasis in the environmental assessment of
coal cleaning processes because of their observed existence in coal. However,
none of the classes of organic chemicals in the list appears to have signifi-
cance as a pollutant from coal cleaning processes because they have not been
observed to exist in coal and have not been used as agents in coal cleaning
operations.
Existing regulations for solid waste disposal, basically only guidelines,
do not establish new standards but set forth requirements and recommended
procedures to ensure that the design, construction, and operation provide
for environmentally acceptable land disposal site operations. Additionally,
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their thrust is toward sanitary and municipal wastes, and mining or coal
cleaning wastes are essentially ignored.
The management of solid and hazardous wastes entered a new era on
October 21, 1976, upon the passage of the comprehensive Resource Conservation
and Recovery Act (RCRA) of 1976. Although the Act has not yet been implemented,
it is already clear that the management of solid and hazardous wastes will be
revolutionized by the specific regulations now in the process of being drafted
by EPA. Whether coal cleaning refuse (and combustion ash) will be classified
as hazardous wastes is presently uncertain.
1.3 Estimating Environmental Concentrations
Estimates of environmental concentrations of pollutants are needed
during the interim period before field measurements of emissions and environ-
mental concentrations can be conducted at actual operating plants. These
estimates of environmental concentrations must be based upon pollutant emission
rates, which are themselves estimates.
Estimates of emission concentrations are based on process configura-
tions, coal type and composition, percentage recovery, and fractionation
factors, among other parameters. All of these parameters except the fraction-
ation factor are controlled or reasonably well-known. Fractionation factors
are characteristic of a given coal but vary among coals. In this study, the
fractionation factors used were based on the coal washability tests conducted
on numerous coals by the Illinois Geological Survey. Illustrative emission
calculations use a simple mass-flow model of a coal cleaning plant and fraction-
ation factors appropriate for the assumed coal; simulation experiments were
made both with and without assumed pollution controls.
Only limited efforts were directed to physical transport and
dispersion models. The state of the art in this area is quite advanced and
the principal problem will be in selecting the model or combination of models
to use. Air dispersion and dilution models are well known and readily available.
Only simple models of dispersion and dilution in surface water courses may be
needed, since most streams receiving coal cleaning plant effluents are so small
they can possibly be treated as fully mixed. The areas of greatest uncertainty
are leaching and runoff of precipitation through coal storage and coal refuse
piles and percolation through the bottoms of tailings ponds. Available
5
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simplified approaches to estimating pollutant adsorption and leaching in porous
media are expected to be applicable to this general problem.
Ecological transport and distribution previously has been much less
well-studied than physical transport and distribution. For this reason, a
substantial effort was expended in this study investigating the ecological
aspect of the problem. A principal finding of the study is that little is
known and much more needs to be learned before predictions can be made with
confidence on the ecological transport and fate of potentially hazardous
pollutants that might be released by a coal cleaning facility.
The potential sources of coal cleaning pollutants vary from facility
to facility but in general include leachate and runoff from coal storage and
refuse disposal piles; process wastewater or blowdown from closed water circuits;
and dust and gases emitted from coal piles, refuse piles, and thermal dryers.
The more apparent environmental effects from these contaminants can be seen in
direct contact toxicity resulting from changes in pH in the surrounding media;
increasing levels of sulfate sulfur, sulfur dioxide, nitrate nitrogen, and
nitrogen oxides; or resultant chemical changes in the abiotic components. These
types of effects are usually long term and easily identified. The fate of
those trace elements (e.g., arsenic, cadmium, and mercury) whose release is
into both terrestrial and aquatic ecosystems is not quite so apparent.
The present preliminary study has focused on the short list of poten-
tially hazardous trace contaminants mentioned previously. These include elemental,
inorganic and organic forms of arsenic, beryllium, cadmium, iron, lead, manganese,
mercury, and selenium. It is well known and documented that these contaminants
are absorbed, retained, released, and cycled among the biotic (i.e., producers,
herbivores, omnivores, carnivores, and decomposers) and the abiotic (i.e., soil,
groundwater, surface water, and sediment) compartments.
The toxicity of these contaminants to living systems under certain
conditions has been established by other researchers. So, the ultimate goal
of transport and fate studies is to determine whether or not toxic concentrations
could be reached through normal environmental exposure pathways. That is, even
if the source release rates for a specific pollutant from a coal cleaning
facility were below the current U.S. Government regulations, would concentration
of the contaminant ecologically magnify to a point at or beyond the toxic
threshold values?
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When magnified by an organism, concentration of a contaminant is
greater than that of its source or donor compartments. The term describing
this is eco-magnification, which is non-source-specific. It includes all
potential exposure pathways (ingestion, inhalation, adsorption, and immersion)
within the ecosystem. Eco-magnification is frequently misunderstood as a
simplistic biological phenomenon when, in fact, it is quite complex. Eco-
magnif ication is all inclusive, whereas the classic term bio-magnification
only considers food ingestion as the mode of exposure. Thus, the ability of
an organism to accumulate or magnify contaminants depends on a number of
ecological, chemical, and physiological factors, such as:
• Chemical form of contaminant
• Concentration of contaminant in soil, water, or air
• Interaction with other trace elements
• Soil characteristics and properties
• Genetic makeup of target organism.
The ultimate goal of the study of ecological transport and fate was
to identify likely distribution factors and supply much needed input data for
simulation models describing the transport and fate of these pollutants. Computer
simulation of transport and fate would enable scientists to compare the computer-
predicted long-term body burdens with reported toxic concentrations for individual
pollutants. Unfortunately, the need to use computer simulations and then compare
the results to reported toxic effects values is ahead of the data base. The
data required to accurately calculate the rate transfer coefficients are not
available in the literature. Investigators, in general, fail to consider or
report: (1) the measurement of major parameters affecting transport and fate,
(2) partitioning data into specific exposure sources (i.e., food source, inhalation,
direct absorption), (3) chemical form of the pollutant, and/or (4) time duration
of the experiment. Therefore, computer modeling to predict ecological transport
and fate of pollutants is still beyond the state of the art.
1.4 Developing Environmental Goals
Documenting and evaluating biological effects ideally should precede
setting of standards and development of control technology for coal cleaning
facilities. The burden of proof of a need for establishing environmental goals
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rests with health and ecological effects data; i.e., if no problem exists,
there is no need for a solution. Data need to be sound, complete, and rigorous,
and they must be interpreted correctly to support environmental goals and
recommendations for further development of control devices for coal cleaning
facilities. Materials highly toxic to many life stages of many important
species during the entire year will require a different level of effort for
their control than those mildly toxic to only one unimportant species at a
particular time of the year. Unfortunately, the differentiation is not always
easy to make. Effects data are not only relatively sparse compared to those
needed for adequate assessments but also are typically laboratory results
rather than real results from practice. Thus, the following material was
developed as another step in providing the necessary feedback for setting
standards and for developing control strategies, i.e., which substances need
how much control in order to protect health and the environment.
Most biological effects data are obtained in the laboratory and need
to be extrapolated to "real world" situations. Extrapolation is the process
of inferring or extending a known toxicological response into an unknown area.
This extension of knowledge assumes a continuity, similarity, or other parall-
elism between the two situations. Often biological effects need to be extra-
polated from (1) laboratory to field - many differences make this difficult;
(2) one species to another - no two species are alike; (3) one medium to another -
drinking is not the same as breathing; and (4) one life stage to another -
ranges of sensitivity may differ by orders of magnitude. In the present state
of the art, biological effects data are collected from a few life stages of a
few species for a few routes of entry in a few controlled conditions. On the
other hand, the real world situation around a coal cleaning facility contains
thousands of species in many stages of growth, all of which may be continuously
exposed to various types of doses. Clearly, extrapolation must be done with
caution.
Despite the technical difficulties involved in estimating permissible
concentrations of toxicants in emission streams, rational approaches are
available for dealing with the problem. There are many potentially applicable
formulae, some of them developed by or for the U.S. EPA. The formulae have
two basic parts: a dose/response part and an adjustments part. The dose/
response generally consists of one of the typical laboratory effects measurements:
-------
LD , LC ~, and TL -96 hr.* Each effects measurement is adjusted by several
factors, the argument being that the adjusted dose/response data better conform
to the "real world" situation. Adjustments include the following: media
conversion (e.g., airborne to waterborne toxicants), safety factors (e.g., 0.01),
various types of exposure (e.g., work day to full week), and elimination rate
(biological half-life). All the formulae provide estimates of permissible
concentrations for single chemicals. All three media (air, water, and land)
are considered for both human and nonhuman populations. The multimedia
environmental goals (MEG) chart is the principal tool for displaying these
quantitative values and represents a major ongoing work supported by the U.S.
EPA. The predicted permissible pollutant concentrations are compared against
observed environmental concentrations to identify those pollutants whose
concentrations exceed the estimated acceptable level.
Twenty formulae were identified and considered in this study. The
formulae were reviewed for their major strengths and limitations from three
viewpoints: media, dose/response data, and adjustment factors. This evaluation
provided a good basis from which to improve the state of the art.
Ten major strengths of the formulae were identified. Some of the
most powerful were embodied in the formulae used to estimate permissible
concentrations for airborne pollutants. These formulae use a variety of the
most rigorous dose/response data, which include a variety of measurements, e.g.,
threshold limit values (TLV's) and other large data sets. The ability to
incorporate simple adjustment factors is seen as a strength; generally, the
prediction is assumed to improve as more adjustment factors are incorporated.
Particularly useful adjustment factors are those for exposure time, elimination
rates, and safety factors.
Seventeen major limitations of the formulae were identified. From
the media viewpoint, the formulae for land- or food-borne pollutants exhibit
* LD : Lethal dose 50, i.e., the dose of a pollutant required to kill
50 percent of a particular animal species by methods other than
inhalation.
LD : Lethal dose low, i.e., the lowest dose of a substance introduced
in one or more portions by any route other than inhalation over
any period of time and reported to have caused death in a
particular animal species.
TL : Median threshold limit value, i.e., the concentration in water of
a pollutant required to kill 50 percent of a particular aquatic
species.
-------
the most limitations; the crop uptake model is too simplistic among other
deficiencies. Many available toxicological response data, e.g., LD 's,
lj(j
have not been used in the available formulae. Responses are limited to a
few species of animals; few or no responses are provided for plants and
microorganisms. The bulk of the effects data are based on acute or short-
term exposure when chronic or long-term exposure effects data are needed. The
effects data are for single chemicals when responses to mixtures of chemicals
are needed. So, from the dose/response viewpoint, there are many deficiencies.
From the adjustment factor viewpoint, there is a great need for validation of
the reasonableness of the factors. Safety factors need a biological basis.
And for every limitation in the effects data, there should be compensatory
adjustment. For example, when chronic effects data are not available (the
usual case), an adjustment factor can be used with the more readily available
acute effects data to estimate chronic effects.
The scope of work permitted research to reduce or remove 5 of the
17 major limitations. The relevance and availability of pertinent data were
ranked for each limitation. Five limitations were regarded as the most fruitful
research candidates. Their mitigation required research to identify alternative
state-of-the-art formulae; correlate nonoral with oral LD ' s; use chronic
effects data; extrapolate data from one species to another; and develop a
biological basis for safety factors. The following material summarizes some
of the major points achieved in the research.
Other formulae merit incorporation into the present system. Some
formulae handle exposure and biological half-lifes more rigorously than any
one of the twenty formulae. Typical state-of-the-art formulae are those for
(1) maximum permissible concentration for radioisotopes, and (2) CUMEX (cumulative
exposure) index. Inclusion of the former would provide a more rigorous estima-
tion of waterborne radionuclides and related pollutants. The latter would
provide estimates for permissible air and water pollutant exposures separately
and simultaneously.
Multiple exposures are the reality, and more formulae capable of handling
such exposures need to be developed for future estimations of potential
dangers to living organisms,
A major deficiency common to all of these formulae is the inability
to utilize the variety of available pertinent toxicological data. For example,
one of the best formulae in use requires that dose/response data be in the form
10
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of oral LD for rats. However, there are many nonoral toxicological response
data which could be used, if a conversion method were available. To overcome
this limitation, specially designed equations have been developed to permit
quantitative conversion of toxicological data for nonoral routes of administra-
tion to the oral route. Conversions were developed for intraveneous, intraperi-
toneal, and subcutaneous LD ' s and inhalation LC _ to the oral LD™. For
example, the relationship for intraveneous LD to oral LD „ is:
J>n(oral LD5()) = -0.5714 + 1.587 Łn(intraveneous LD5Q)
This research expands the access to other readily available toxi-
cological effects data and is immediately applicable. However, this research
needs to be extended to better utilize the wealth of toxicological data for
other routes of administration, e.g., LD TD LC etc., and for other
LJ(J LjO LjO
species (e.g., mice, hamsters, and dogs).
Limitations inherent to biological effects data for short-term (acute)
exposure can be removed only by use of effects data for long-term (chronic)
exposure. Chronic exposure (low levels of chemicals for long periods of time)
can depress reproductive capacity, increase the number of malignant tumors,
and generally shorten the life span of males, females, or both. Chronic effects
for life-term (1000+ days) and multi-generation (three-generation) studies for
rodents are discussed herein. Generally, concentrations lower than those
used in acute exposure (high levels of chemicals for short periods of time)
cause effects that could not have been known on the basis of acute tests only.
Concentrations of 5 ppm for some elements in drinking water seem to show
increasingly harmful effects the longer the study and the greater the number
of generations studied. At present, there seems to be no quantitative way to
predict chronic effects based on effects data only from acute experiments.
When chronic effects data are available, they should be used in the dose/
response part of the formulae if the effects are greater than those indicated
by acute exposure data.
Animal toxicity data can be extrapolated from one species to another
in two ways. In Method 1, the equation deals with only one toxicant at a time,
but this single equation can be used to predict the responses of animals of
many sizes (including man) to that particular toxicant. In Method 2, the
11
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equation deals with responses to many different toxicants, but it can only be
used to extrapolate from the response of one particular species to the response
of another species (say, from rat to human). Both methods are described in
detail, using the basic relationship of Y = aW where Y = the response, W =
body weight (or area), and a and b are constants relative to the particular
Y. Examples of both approaches indicate that often the basic data are not
readily available. Of the many other limitations with these approaches, not
the least is the credibility of even attempting extrapolation of response
from one species to another.
The range of sensitivity for certain organisms to given toxicants
provides a biological basis for safety factors. Toxic levels and effects of
a substance vary greatly. For example, toxicity ratios for young of a species
versus adults can vary from 0.002 to 16 - a variation of nearly four orders
of magnitude. Green algae species differ in their response to cadmium by a
factor of 100. Frog embryos and larvae are more sensitive than adults to
mercury by factors of 100 and 1000, respectively. Bird embryos and fetal and
newborn mammals are more susceptible to metals than their adult counterparts.
Baby mammals appear to be four or five times more sensitive than adults to some
chemicals. Thus, in aquatic situations, safety factors of 100 to 1000 seem
reasonable if available effects data are from least sensitive (most resistant)
species. If effects data are from tests on more sensitive species in an
ecosystem, such high safety factors are not needed to protect the less
sensitive species. In terrestrial situations, smaller safety factors seem
biologically reasonable. For example, 10 to 100 would be reasonable safety
factors when the available dose/response data are for resistant species.
All of these improvements still fall short of the needed advancements
in this important research to protect human health and the environment from
adverse effects. True, the formulae provide quantitative values, and increas-
ingly higher quality effects data and adjustment factors are being used in
such formulae. The state-of-the-art predictions are not absolute; they are
relative. Furthermore, the relative relationships of one prediction to
another may not be correct. Caution is warranted. Validation and future
monitoring are needed to confirm the reliability of the predictions. Another
major step forward involves the issue of mixtures as compared to single chemical
species. The approach of predicting permissible concentrations for single
chemical species will need to be replaced by approaches addressing synergistic/
12
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antagonistic effects associated with actual emission streams. Then, the
feedback to standards setting and control technology development will be
more sound biologically.
1.5 Decision Criteria for Prioritization
Since all pollutants from coal cleaning processes are not equal in
toxicities nor in quantities, there are differing degrees of hazard, and
corresponding differences in the relative importance necessary to be placed
upon identifying and controlling them.
All of the parameters making -up the total hazard of a pollutant are
embodied in the estimated permissible concentration (EPC). However, as noted
in the previous section, for many pollutants of known importance, EPC's cannot
yet be established.
EPA contractors are developing multimedia environmental goals (MEG)
and minimum acute toxicity effluent (MATE) values for an increasing list of
pollutants; when this work is complete,, a rigorous prioritization of pollutants
should be possible—at least into groups of similar hazard. However, because
these lists are incomplete, their usefulness is limited.
For the near term, it appears that less rigorous and more pragmatic
prioritization criteria may be required to fill the gap. Since the relative
importance of controlling a pollutant can be generally assessed from its acute
toxicity and its abundance in coal cleaning processes, criteria are available
for their categorization. Also, substances with established criteria or those
designated as pollutants should be prioritized. The "Priority 1" pollutants
mentioned above were selected using criteria of this type.
A further modifying parameter, for which data are not yet available
to implement, is the availability or lack of availability of adequate control
technology for pollutants identified as inherently high-risk.
1.6 Recommendations for Future Work
While substantial progress in developing environmental assessment
criteria for coal cleaning processes has been made during the past two years,
additional work is required. Recommended tasks include:
13
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• Pragmatically group the Priority 1 pollutants into 3 to
5 severity classes using available data on pollutants from
coal cleaning processes (i.e., abundances in raw coal,
toxicities, and quantities released). This approach will
allow environmental assessments to proceed until data to
support more rigorous rankings are available.
• Select, exercise, and validate models recommended
to assess physical transport and dilution.
• Determine the relative importance of each ecological
exposure pathway; determine the rate transfer coefficients
for each dominant pathway; and develop and validate
simulation models for ecological transport and fate.
• Continue development of the methodology for establishing
realistic environmental goals from the multiplicity of
toxicological and epidemiological data which are available;
further develop interconversion factors between different
routes of administration and between different species;
and continue the rationalization of safety factors.
Research needs and recommendations for future work are described in
detail in Section 7.
-------
2.0 INTRODUCTION
Coal cleaning is one of several energy technologies whose environmental
implications are being investigated by the Energy Assessment and Control
Division of the Industrial Environmental Research Laboratory of the U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
A primary objective of these environmental assessment programs is to identify
potential environmental problems which are likely to be associated with the
large-scale commercial application of the technology and to identify suitable
mitigative and control measures. Such an approach, when effectively implemented,
can eliminate the necessity of subsequent cumbersome and expensive retrofits
for pollution control.
The cleaning of coal by removal of noncoal materials is an old art;
in its early days it was sometimes no more sophisticated than picking shale
and rock from a belt carrying the lump coal. Over the years it has become a
much more complex and sophisticated operation, impelled by various economic,
technical, and political factors.
Two of the most significant factors have been the sharp increases
in the price of coal over the past few years and the increasingly restrictive
regulations on emissions of sulfur dioxide. Additionally, the impending
substitution of increasing amounts of coal for gaseous and liquid fossil fuels
will demand enormous new tonnages of coal. These demands cannot be wholly
satisfied by using only the best coals; it will be necessary to rely increasingly
upon lower grade coals.
Thus, coal cleaning, which is already an important link in the utili-
zation of coal, especially of the lower grades, will become increasingly
important. Cleaning upgrades coal by removing both ash and S02-forming
constituents. This reduces pollution from the combustion of coal, at the
potential expense of environmental pollution caused by the cleaning operation.
Accordingly, both economic and environmental benefits and costs associated
with the cleaning process need to be identified and assessed for decision-
15
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making purposes. The benefits and costs can be markedly influenced by the
quantities and characteristics of the pollutants emitted, as well as by the
type and extent of control technologies needed for control of these pollutants
Both benefits and costs increase as broader and more rigorous controls are
introduced. In order to make critical benefit/cost judgments, criteria are
needed for rating the relative importance which should be placed on identifying
and controlling specific pollutants.
The problems are several. Almost every naturally occurring element
is found in coal at some detectable concentration. However, the coal industry
heretofore has been so result-oriented and so marginally profitable that it
was never possible to generate the- needed research data base on pollutant emissio
from coal cleaning processes. On the other side of the equation, a similar
data gap exists with respect to environmental effects, so that it is not yet
known which pollutants should be most controlled or how much control is
required. The present investigation is designed to help answer some of these
questions.
2.1 Basis for Environmental Assessment
The fundamental criterion for evaluating the importance of any
pollutant is the relationship between its expected environmental concentration
and the maximum concentration which presents no hazard to man or biota on a
continuous long-term basis. This threshold concentration is designated as the
estimated permissible concentration (EPC).
While simply stated, this concept represents a rather complex utili-
zation of a number of subcriteria dealing with specific phases of the overall
problem:
• Selecting those environmental pollutants of
most concern
• Selecting methods for estimating environmental
concentrations of pollutants resulting from
coal cleaning
• Selecting methods for evaluating the EPC's for
man and biota.
16
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2.2 Approach to Environmental Assessment
The pollutants selected for consideration include those which have
already been identified as pollutants of concern and whose presence in coal
cleaning processes is known or highly suspected. Such a list is large, and
further selection is needed to derive a list with a manageable number of
candidates. Substances already identified and designated by EPA as pollutants
are almost automatic candidates for consideration.
The criteria for selecting methods for estimating environmental
concentrations of pollutants are relatively straightforward. Numerous models
have been developed for estimating air and water concentrations resulting
from emissions from point sources and for transport and diffusion through
the physical environment. Thus, the problem is to select the most suitable
model or combination of models.
The basic criterion for an EPC of a potentially hazardous pollutant
is that this concentration shall not adversely affect man or biota upon
continuous long-term exposure. These are, thus, threshold concentrations,
even lower than the TLV's (threshold limit values) suitable for workroom
atmospheres. Unfortunately, very few dose/response data at threshold concen-
trations are available for the pollutants of concern in coal cleaning
processes. Available data are, characteristically, for acute or chronic
exposures, and hardly ever for man. Conversion of such data to EPC's poses
some major problems, which have not yet been totally overcome. More work in
this area is badly needed.
17
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3.0 POTENTIAL ENVIRONMENTAL POLLUTANTS
AND APPLICABLE REGULATIONS
The extent of the universe of potential pollutants for this study de
on the boundaries adopted for coal cleaning processes. The definiti
boundaries has evolved during the conduct of this studv Tm'n'nii .
j • j-ii-LLiaiiy , the uni-
verse was taken to include pollutants generated during the combustio f
in coal-fired power plants and the burning of coal refuse piles n H
interpretation, the myriad organics formed by the combustion of ™ai •
UL coai in oxygen-
deficient regimes (coking-type reactions) were included as representative
gob-pile burning. These numbered in the hundreds; over 800 compounds have been
identified from the coking of coal. Many different pollutants have be
tified as being associated with raw coal or with some segment of the
industry. A number of lists from various sources, containing hundreds of
ments and compounds, have been compiled and were presented in Battelle'
cleaning technology overview draft report.
As a result of discussions with the U.S. EPA Project Officer the
of this subtask was subsequently redefined to include (1) only those act' ' •
directly related to coal cleaning, handling, transportation, and storage and
(2) a Priority 1 list of potential pollutants, discussed later, which contains
74 of the principal pollutants of concern.
3.1 Universe of Pollutants
3.1.1 Pollutants of Concern
The original lists of potential pollutants, reproduced in the technolo
overview draft report were based on a survey of other experiment 1 •
tigations. These studies had been performed by different investigate
different objectives and different approaches, so that there ar« ™ • j.r
*• e Tna~]or differ-
ences in the manner and format in which the results are
in some
18
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cases, the approach was tnineralogical, i.e., individual minerals and mineral
classes were identified. In others, where wet chemical analyses were performed,
pollutants were variously reported as oxides, in some other analytical conven-
tion, or, often, on an elemental basis. Trace element analysis results, by
either emission spectrography or spark source mass spectrography (SSMS), report
only the element, giving no indication of the chemical form(s) present.
Thus, one of the first tasks involved the reorganization and rational-
ization of the overlapping lists, particularly the organic compounds. However,
even after the rationalization of the list of organic compounds, many hundreds
remained, only a fraction of which could be represented by "type" compounds
representative of the numerous subgroups. Reexamination of the basic problem
led to the conclusion that the boundaries could and should be narrowed, to
eliminate pollutants that result from coking-type reactions. Most of these
compounds will be present in only minute quantities, some not at all, in
oxidizing combustion gases, such as are encountered in thermal coal dryers or
in coal-fired power plants.
Gob-pile burning is not an intrinsic operation in coal cleaning; rather,
it is symptomatic of mismanagement of refuse piles. The simple solution, which
eliminates a need to consider the related complex organic compounds, is preven-
tion of such burning.
The pollutants directly associated with the cleaning of coal are primarily
inorganic compounds associated with the ash fraction. Water will be the
principal receptor of these pollutants. Operations causing major emissions of
air pollutants are infrequent in the cleaning of coal. The largest air
emissions will include fugitive dust from coal handling and transfers, and
particulates and combustion products from thermal dryers.
As the investigation progressed, it became clear that it would be advan-
tageous to develop a relatively small list of pollutants of most interest for
the first-phase effort. The original goal was a list of 50 or less; as the
list was created, it seemed advisable to slightly exceed this number, and the
final list contains 74 entries.
For the first phase, a logical criterion for selection was to define
Priority 1 pollutants as those that already have been identified as pollutants
of concern and whose presence in finite concentrations in coal cleaning
processes is known or suspected. The chemical substances on this list were
19
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drawn from a number of sources, including:
(2 3)
• EPA criteria pollutants for air '
* Pollutants identified by effluent guidelines for
(4 5)
coal mining and coal preparation '
• Substances included in EPA "Quality Criteria for Water"(
• Toxic and hazardous pollutants listed by EPA which may
(7 8^
be associated with coal cleaning. '
In addition to these specific pollutants, a number of more general non-
chemical pollutants and aggregated pollutant parameters were included in the
list. The proposed list, shown in Table 3-1, includes 51 elements and 23
chemical substances or aggregated pollutant parameters. The selection of
elements was based on a number of factors, including their recognition by EPA
as pollutants to be regulated, their elemental group, their abundance in coal,
and the availability of information on toxicity, abundance, fractionation
factors, etc.
The elements selected and their relationship to the rest of those in the
periodic table are shown in Figure 3-1; the omitted elements are shaded. The
following elemental groups, or portions thereof, were omitted for the reasons
shown:
• Hydrogen Not applicable
• Group IIIB, except lanthanum Low abundance;
which will represent the group low toxicity
• Group VIIIA, fixed gases Not applicable
• Group VIII, all precious metals Low abundance;
low toxicity
• All lanthanides, except lanthanum Low abundance;
low toxicity
• All actinides, except uranium and Not applicable
thorium
• All other radioactive elements, i.e., Not applicable;
technetium, radium low abundance
• All elements above atomic number 57, Low abundance;
except mercury, thallium, lead, little information
uranium, and thorium
While the selection rules may be somewhat arbitrary, the elements selected
are judged to include those of greatest priority. Other elements and substances
not listed should not be considered as nonhazardous but as falling in a lower
20
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TABLE 3-1. PROPOSED PRIORITY 1 POLLUTANTS FOR COAL CLEANING PROCESSES
Elements
Aluminum
An t imony
Arsenic
Barium
Beryllium
Boron
Bromine
Cadmium
Calcium
Carbon
Cerium
Cesium
Chlorine
Chromium
Cobalt
Copper
Fluorine
Gallium
Germanium
Indium
Iodine
Iron
Lanthanum
Lead
Lithium
(a)
Specific Pollutant Limitations
ABCDEFGH
X X
X XXX
X X X
X XX
X X
X
X X X X
X
XTJ-
/i \ A
(hi
X(M X X X
x(
(b)
X^ / V V
A A
X
X
X X
X XX
fa)
Specific Pollutant Limitations
Elements ABCDEFGH
Magnesium
Manganese XXX
Mercury X X X X X
Molybdenum X
Nickel X XX
Niobium
Nitrogen
Oxygen
Phosphorus X
Potassium
Rubidium
Selenium X XX
Silicon
Silver X
Sodium
Strontium
Sulfur
Tellurium X
Thallium X
Thorium
Tin
Titanium X
Uranium X
Vanadium X
Zinc X XXX
-------
TABLE 3-1. (Continued)
Elements
Specific Pollutant Limitations
ABCDEFGH
(a)
Elements
Specific Pollutant Limitations
ABCDEEGH
(a)
Zirconium
Groupings
X
Alkalinity
Ammonia
Cyanide
Chlorides
Nitrates
Sulfides
Sulfates
SO
NOX
X
X
X X
X X
X X
X
X
X
X
X
X X
X
Total Suspended
Solids (TSS)
Total Dissolved
Solids (TDS)
Chemical Oxygen
Demand (COD)
Total Suspended
Partic. (TSP) X
Carbon Dioxide
Carbon Monoxide X
X
X
Organic Nitrogen
Compounds
Polycyclic Organic
Materials (POM's)
Carbon Chloroform
Extract (CCE)
(a) Column headings are defined as follows:
A. National Primary and Secondary Ambient Air Quality
Standards^2)
B. OSHA Standards for Workroom Air Contaminants'
C. National Emission Standards for Hazardous Air
Pollutants(7)
D. New Stationary Source Performance Standards
(Coal Preparation Plants)^) , .
E. Interim Drinking Water Regulations (EPA) ,..,,
F. EPA Toxic Pollutant Effluent Standards (Proposed)
G. EPA Toxic Pollutant List<8)(See Table 3-8)
H. EPA Water Quality Criteria (Proposed - not
regulations)("'
(b) Metal as fume or dust.
(9)
Hydrocarbons
Photochemical
Oxidants
Oil and Grease
Phenols
Organic Sulfur
Compounds
X
X
-------
GROUP
IA
VIIIA
9m
mmsmm
Selected Elements
Omitted Elements
FIGURE 3-1. ILLUSTRATION OF RELATIONSHIP OF ELEMENTS SELECTED FOR PRIORITY
1 POLLUTANT LIST TO THOSE OMITTED
-------
priority class. Also, some of the 51 elements now included may be dropped
later on the basis of insignificant abundance or lack of sufficient
mation for analysis and evaluation.
The remaining 23 entries on the proposed Priority 1 list co
number of substances (e.g., sulfur dioxide) defined statutorily as a criteria
air pollutant, as well as aggregated pollutant parameters (e.g., total
pended solids), also defined as a pollutant in effluent guidelines ^
many pollutants of the latter type may be found in variable and undefin bl
mixtures, there may be insufficient information to Denrvft- i-ho-» «.
fciuu.i. cneir treatment in a
rigorous fashion.
Table 3-1 also indicates where existing and proposed standards and criteria
are judged to have application to coal cleaning processes, based in
Cleland and Kingsbury's recent draft report of key Federal regulation ^12^
Column H indicates water quality criteria recently issued by EPA^
will achieve the status of regulations when they are ultimately adopted by the
states as part of their implementation plans. Column G in Table 3-1
elements included in the recent "Toxic Pollutant List" published by EPA ^
Although the Priority 1 list satisfies the requirement of a manageable
list containing the important pollutants expected from coal pi0o«-»
<-j.eaning processes,
there appeared to be a need for an even more abbreviated list suitabl
preliminary testing of some of the concepts and approaches to environment
assessment. To meet this need, an abbreviated "short list" has been
which includes the following chemical pollutants:
Arsenic Manganese
Beryllium Selenium
Cadmium Sulfate sulfur
Iron Sulfur dioxide
Mercury Nitrate nitrogen
Lead Nitrogen oxides
This list, which includes both air and water pollutants, is suitable for the
evaluation of chemical and physical transport models, as well as estimated
emissions and permissible concentrations.
When the data base on Priority 1 pollutants is complete, it is reco
that a Priority 2 list of pollutants be selected for further consideration
Such pollutants, by definition, would be of lesser importance and conce
24
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the basis of today's knowledge of estimated environmental concentrations and
estimated permissible concentrations. Such a list may include part or all
of the pollutants initially identified as being in the universe of potential
pollutants.
Compilation and analysis of data on the Priority 2 pollutants probably
will result in the upgrading of a few to the lower end of the Priority 1
group, with the rest assigned to the category of less important pollutants.
3.1.2 Pollutants in Coals
The importance of a pollutant- is a function not only of its toxicity but
also of its abundance. Thus, the quantities of the pollutants cited above in
coal are an important parameter. Unfortunately, there is no simple measure of
abundance; the composition of coals varies greatly, not only from region to
region, but also from seam to seam and within a seam. Thus, analysis and
comparison demand recourse to averages and ranges about those averages. Probably
the most complete and definitive investigation of the analyses of coals
has been the work of Ruch, Gluskoter, et al., at the Illinois State Geological
Survey. ' ' This group has analyzed, in considerable detail, hundreds of
U.S. coal samples, not only from the Illinois Basin, but elsewhere. Summaries
of their analyses of 165 coal samples from three regions are presented in Table
3-2. It is apparent that the concentrations of some pollutants range tremen-
dously, from sample to sample. The inclusion of a few exceptionally high values
will severely bias an arithmetic mean. Thus, although both arithmetic and
geometric means were reported, geometric means are regarded as better measures
of the central value and are shown here. Also, as pointed out by Gluskoter,
et al., the geometric mean more closely approximates the value that would
be expected in an unknown sample.
The geometric mean concentrations listed in Table 3-3 for the eight
elements on the Priority 1 "short list" are illustrative. Even though there
are fairly large variations, the order of magnitude is consistent, suggesting
that these averages are suitable for generic, non-site-specific environmental
assessments.
25
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TABLE 3-2. MEAN ANALYTICAL VALUES FOR ELEMENTAL CONCENTRATION IN
COAL SAMPLES FROM VARIOUS REGIONS^)
Illinois Basin^
Geometric
Element Mean, ppm
Aluminum 12
Antimony
Arsenic
Barium
Beryllium
Boron
Bromine
Cadmium
Calcium 5
Cerium
Cesium
Chlorine
Chromium
Cobalt
Copper
Dysprosium
Europium
Fluorine
Gallium
Germanium
Hafnium
Indium
Iodine
,000
0.81
7.4
75
1.6
98
10
0.6
,100
12
1.2
800
16
6.0
13
1.0
0.25
63
3.0
4.8
0.49
0.13
1.2
Iron 19,000
Lanthanum
Lead
Lutetium
Magnesium
Manganese
Mercury
Molybdenum
Nickel
Phosphorus
Potassium
Rubidium
Samarium
Scandium
Selenium
Silicon 23,
Silver
6.4
15
0.08
500
40
0.16
6.2
19.
45
17
1.1
2.5
2.0
000
0.03
Range, ppra
Minimum Maximum
4,300 30,000
0.1
1.0
5.0
0.5
12
0.6
0.1
100 27
4.4
0.5
100 5
4.0
2.0
5.0
0.5
0.1
29
0.8
1.0
0.13
0.01
0.24
4,500 41
2.7
0.8
0.02
100 1
6.0
0.03
0.3
7.6
10
2.0
0.4
1.2
0.4
8.9
120
750
4.0
230
52
65
,000
46
3.6
,400
60
34
44
3.3
0.9
140
10
43
1.5
0.43
14
,000
20
220
0.44
,700
210
1.6
29
68
340
46
3.8
7.7
7.7
5,800 47,000
0.02
0.08
Appalachian Coals
Geometric
Mean, ppm
16,000
1.1
15
170
1.1
28
8.9
0.19
3,400
23
1.6
1,000
18
7.6
16
2.0
0.47
84
5.2
0.87
1.1
0.22
1.4
13,000
14
4.7
0.18
500
12
0.17
1.8
14
81
21.80
19
2.4
4.5
3.4
26,000
0.02
Range , ppm
Minimum Maximum
11,000 31,000
0.25
1.8
72
0.23
5.0
0.71
0.10
900 26
11
0.4
100 8
16
1.5
5.1
0.7
0.16
50
2.9
0.1
0.6
0.13
0.33
500 26
6.1
1.0
0.04
200 1
2.4
0.05
0.10
6.3
7.7
100
420
2.6
120
26
0.6
,000
42
6.2
,000
90
33
30
3.5
0.9
150
11
6
2.2
0.37
4.9
,000
23
18
40
,500
61
0.47
22
28
15 1,500
9.0
0.9
1.6
1.1
63
4.3
9.3
8.1
10,000 63,000
0.01
0.06
Western Coals (c)
Geometric
Mean , ppm
8,800
0.45
1.5
450
0.35
48
2.1
0.15
15,000
9.1
0.16
200
8.1
1.5
8.5
0.57
0.16
57
2.1
0.5
0.7
0.07
0.46
4,900
4.5
2.6
0.05
1,200
28
0.07
0.59
4.4
82
300
2.4
0.56
1.5
1.3
13,000
0.02
Range, ppm
Minimum Maximum
3,100 22,000
0.18
0.34
160 1
0.10
16
0.5
0.10
440 38
2.8
0.02
100 l
2.4
0.6
3.1
0 22
0.07
19
0.8
0.10
0.26
0.01
0.20
3,000 12
1.8
0.7
0.01
300 3
1.4
0.02
0.10
1.5
10
100 3
0.3
0.22
0.50
0.40
3,800 47
0.01
3.5
9.8
,600
1.4
140
25
0.60
,000
30
3.8
,300
20
7
23
1.4
0.80
140
6.5
3.0
1.3
0.25
1.0
,000
13
9.0
0.43
,900
220
0.63
30
18
510
,200
29
1.4
4.5
2.7
,000
0.07
26
-------
TABLE 3-2. (Continued)
Illinois Basin(a)
Element
Sodium
Strontium
Sulfur
Tantalum
Terbium
Thallium
Thorium
Tin
Titanium
Tungsten
Uranium
Vanadium
Ytterbium
Zinc
Zirconium
Geometric
Mean , pptn
300
30
34,000
0.14
0.18
0.59
1.9
0.94
600
0.63
1.3
2.9
0.53
87
41
Range, ppm
Minimum Maximum
2
10
5,600 64
0.07
0.04
0.12
0.71
0.2
200 1
0.04
0.31
11
0.27
10 5
12
,000
130
,000
0.3
0.65
1.3
5.1
51
,500
4.2
4.6
90
1.5
,300
130
Appalachian Coals
Geometric
Mean, ppm
300
100
19,000
0.26
0.28
_
4.0
0.97
900
0.62
1.3
35
0.73
19
41
Western Coals (c)
Range, ppm Geometric
Range, ppm
Minimum Maximum Mean, pp Minimum
100
28
5,500
0
0
-
1
0
500
0
0
14
0
2
8
50
.12
.06
.8
.2
1
.22
.40
.18
.0
.0
800
550
,000
1.1
0.63
_
9.0
8.0
,600
1.2
2.9
73
1.4
120
88
600
220
7,000
0.12
0.17
_
1.8
0.43
500
0.58
0.99
12
0.34
5.0
26
100
93
3,400
0.
0.
_
0.
0.
200
0.
0.
4.
0.
0.
12
Maximum
19
04
06
62
10
1
13
30
8
13
30
600
500
,000
0.33
0.58
—
5.7
15
,300
3.3
2.5
43
0.78
17
170
(a) 114 Samples
(b) 23 Samples
(c) 28 Samples.
27
-------
TABLE 3-3. GEOMETRIC MEAN CONCENTRATIONS OF EIGHT ELEMENTS IN COAL(14^
Concentration, ppm
Arsenic
Beryllium
Cadmium
Iron
Lead
Manganese
Mercury
Selenium
Illinois
Basin
7.4
1.6
0.6
19,000
15
40
0.16
2.0
Appalachian
15
1.1
0.19
13,000
4.7
12
0.17
3.4
Western
1.5
0.35
0.15
4900
26
28
0.07
1.3
Another factor needing consideration, however, is the fact that coal dust
appears to be significantly enriched in inorganic constituents compared to
coal, as suggested by Blackwood and Wachter. They compared the analysis
(by spark source mass spectrometry) of a "typical" coal with that of particu-
late matter from personal samplers carried by coal miners, considered to repre-
sent the dust in the interior of a mine. It is assumed that the samples were
from comparable coals, although this is not explicitly stated in the original
report. As shown by Table 3-4, the concentrations of almost all elements
were greater in the respirable dust fractions than in coal, in some instances
by large factors.
3.2 Federal and State Standards and Criteria
One aspect of this study was a summarization of Federal and state regula-
tions governing pollution resulting from activities associated with coal
cleaning, transportation, storage, and handling. This scope, as defined, was
considered to include the combustion of coal as a fuel, but not the conversion
of coal to coke or other liquid or gaseous fuels. Also, the investigation
focused on pollution, per se, and hence excluded other regulations which may
impinge upon coal cleaning processes, such as those governing health and
safety standards for the work place environment or the quality of community
drinking water supplies. Some of these other regulations are discussed in
several recent reports. '
Pollution regulations with direct influence on coal cleaning activities
were discussed in an earlier preliminary report on the development of environ-
28
-------
TABLE 3-4. CONCENTRATIONS OF TRACE METALS IN
COAL AND COAL
Concentration, pptn
Element
Aluminum
Arsenic
Barium
Bismuth
Bromine
Boron
Cadmium
Calcium
Cerium
Chlorine
Chromium
Cobalt
Copper
Fluorine
Gallium
Germanium
Iodine
Iron
Lanthanum
Lead
Magnesium
Manganese
Molybdenum
Neodymium
Nickel
Niobium
Phosphorus
Potassium
Praseodymium
Rubidium
Samarium
Scandium
Selenium
Silicon
Silver
Coal
Major
0.30
69
0.20
0.30
42
0.19
4,000
13
130
4.5
2.3
25
5.7
8.7
0.33
0.20
1,600
5.8
3.9
4,500
30
3.0
8.3
2.7
20
380
410
4.7
3.0
1.7
1.3
0.32
Major
0.22
Coal Dust
283,000
26.4
453
7.50
11.3
3.30
3.80
13,200
45.3
230
170
11.3
868
1.90
68.0
18.9
3.80
79,200
22.6
26.4
792
45.3
15.1
45.3
755
7.60
306
16,600
11.1
7.60
3.80
30.2
7.60
294,000
7.60
Concentration, ppm
Element Coal Coal Dust
Sodium 5,000 755
Strontium 100 291
Sulfur 6,100 3,130
Tellurium 0.25 3.80
Titanium 620 15,800
Uranium 1.9 2.26
Vanadium 12 166
Yttrium 7.7 7.60
Zinc 10 415
Zirconium 76 60.4
29
-------
mental assessment criteria, which was subsequently updated. However,
pollution regulations frequently change, and both of the above summaries are
already out of date. By the same token, pending and foreseeable developments
further regulating pollution will probably make portions of the following
discussion obsolete within the next six months to a year.
The following Federal Acts constitute the primary regulatory authority
governing pollution from activities associated with coal cleaning processes.
Air Pollution
Clean Air Act of 1970 (P.L. 91-604)
Energy Supply and Environmental
Coordination Act of 1974 (P.L. 93-319)
Clean Air Act Amendments
of 1977 (P.L. 95-95)
Water Pollution
Federal Water Pollution Control
Act Amendments of 1972 (P.L. 92-500)
Clean Water Act of 1977 (P.L. 95-217)
Solid Waste
Solid Waste Disposal Act
of 1965 (P.L. 89-272)
Resource Recovery Act of 1970 (P.L. 91-512)
Resource Conservation and
Recovery Act of 1976 (P.L. 94-580)
All of the above Acts are administered and enforced by the U.S. Environ-
mental Protection Agency and are embodied in Title 40 of the Code of Federal
Regulations.
The applicability of the provisions of these Acts to coal cleaning will
be discussed in the following sections. The discussion will not include
other Federal Acts which at this time are only potentially applicable.
For instance, the Toxic Substances Control Act (P.L. 94-469), enacted in
1976, instructs the EPA Administrator to use other Federal laws to protect
against the risks of toxic substances, unless it is in the public interest
to use TSCA. While the possibility exists of adopting this alternative to
control coal cleaning pollutants classified as toxic substances, it is
regarded as slight.
30
-------
The discussion will also contain some general mention of state
pollution regulations. State regulations are generally written or amended
to incorporate, as a minimum, the provisions of the Federal laws. In some
instances, state regulations are more stringent than are the Federal regula-
tions. The states are usually required to submit implementation plans for
EPA approval outlining how Federal standards will be met and specifying a
reasonable time frame for implementing those standards. This state certifi-
cation procedure is essentially complete for air pollution, well underway
for water pollution, and just beginning for solid wastes.
3.2.1 Air Pollution Regulations
3.2.1.1 Federal. The development and implementation of air pollution
controls has been approached in two different ways by the U.S. Environmental
Protection Agency, in accordance with the provisions of the Clean Air Act.
Emission standards regulate the quantities of pollutants emitted from sources;
ambient air quality standards regulate the concentrations of pollutants in the
atmosphere.
3.2.1.1.1 Ambient Air Quality Standards. The U.S. EPA, under Section 109
of the Clean Mr Act, has established national primary and secondary ambient
air quality standards (NAAQS), which regulate pollutant levels in order to
protect, respectively, human health and public welfare (property and plant
and animal life). ^
Implementation is the responsibility of the individual states, under a
State Implementation Plan (SIP) which must be approved by EPA. Also, the
permissible levels for certain named pollutants (criteria pollutants) are
established by EPA and must not be exceeded in the SIP. Some of these
"criteria pollutants" arise mainly from motor vehicles. Those of interest to
coal cleaning processes (total suspended particulates, sulfur oxides, and
nitrogen oxides) arise from stationary sources and are generated mainly from
coal combustion. Current national ambient air quality standards for the
criteria pollutants are summarized in Table 3-5.
(3)
A national ambient air quality standard for lead has just been promulgated.
31
-------
TABLE 3-5. NATIONAL AMBIENT AIR QUALITY STANDARDS
Averaging Period
Permissible
Concentration,
yg/m3 (ppm)
Primary Secondary
Particulates
Sulfur dioxide
Carbon monoxide
Hydrocarbons
Photochemical
oxidants
Annual Geometric mean
Max. 24-hr concentration, not to be
exceeded more than once per year
Annual arithmetic mean
Max. 24-hr concentration, not to be
exceeded more than once per year
Max. 3-hr concentration, not to be
exceeded more than once per year
Max. 8-hr concentration, not to be
exceeded more than once per year
Max. 1-hr concentration, not to be
exceeded more than once per year
Max. 3-hr (6-9 a.m.) concentration,
not to be exceeded more than once
per year
Annual arithmetic mean
Max. 4-hr concentration
Max. 1-hr concentration, not to be
exceeded more than once per year
75
260
80
(0.03)
365
(0.14)
10
(9)
40
(35)
160
(0.24)
Nitrogen dioxide Annual arithmetic mean
160
(0.08)
100
(0.05)
60
150
60
(0.02)
260
(0.1)
1300
(0.5)
10
(9)
40
(35)
160
(0.24)
160
(0.08)
100
(0.05)
32
-------
This is designed to regulate emissions from the nonferrous metals industry
and the combustion of leaded gasoline and will have no effect upon coal
cleaning processes.
3.2.1.1.2 New Source Performance Standards. In accordance with Section
III of the Clean Air Act, EPA is required to compile a list of categories of
emission sources that may contribute significantly to air pollution and to
establish Federal standards of performance for new and modified stationary
sources in such categories. Unlike the ambient air quality standards, these
standards of performance are not based on the effects of pollutants on public
health and welfare, but on "the degree of emission limitation achievable through
the application of the best system of emission reduction which (taking into
account the cost of achieving such reduction) the Administrator determines
has been adequately demonstrated."* Agency terminology for this is Best
Available Control Technology (BACT).
Regulations have now been promulgated for over 25 types of sources. The
foremost category on the list is fossil-fuel-fired stationary sources; many
provisions of the Clean Air Act Amendments of 1977 are aimed specifically at
such sources, and the restrictions applied are much more rigorous than in the
past. Where the original New Source Performance Standard (NSPS) for large
(>250 million Btu/hr heat input), coal-fired boilers permitted the emission of
1.2 Ib SO-/million Btu, the 1977 Amendments specify, in addition, that the
revised NSPS "...shall reflect the degree of emission limitation and the per-
centage reduction achievable through application of the best technological
system of continuous emission reduction...", i.e., a percentage reduction
will be required rather than maintenance of emissions below an upper limit.
The criteria are tempered by the usual energy, cost, and environmental impact
considerations. Also, credit may be taken for any cleaning of the fuel or
reduction in the pollution characteristics of the fuel after extraction and
before combustion.
The 1977 Amendments require the promulgation of regulations not later
than one year after the date of enactment, i.e., by August 7, 1978. However,
framing of the regulations is behind schedule. Proposed regulations
* It should be noted that the setting of NAAQS provides the justification
for setting emission standards for these pollutants.
33
-------
were published for comment on September 19, 1978. The proposed standards
for solid fuels would continue to limit maximum SC^ emissions to 1.2 lb/
million Btu, and, additionally, uncontrolled S02 emissions would be required
to be reduced by 85 percent (on a daily basis). For three days per month
a 75 percent reduction requirement would apply, providing some allowance for
system variance.
A key provision in the proposed S0» standards is that exemptions would not
be allowed for malfunctions. Suggested compliance alternatives include installa-
tion of spare FGD modules, derating of steam generators, or temporary shutdown
and satisfaction of electric demand from other sources.
The proposed particulate emission standard would be reduced from the
present 0.1 Ib/million Btu to 0.03 Ib/million Btu, and uncontrolled particulate
matter emissions would have to be reduced by 99 percent. These proposed
emission standards are based on emission levels achievable with electrostatic
precipitators (ESP) and baghouses.
Proposed NO emission standards for bituminous coals are decreased to
X
0.6 Ib/million Btu from the present 0.7 lb limit, with the additional require-
ment of a 65 percent reduction from uncontrolled emissions, although the percent
reduction would not be controlling.
Since the proposed NSPS apply only to electric utility steam generating
units larger than 250 million Btu/hr heat input, no boilers employed in coal
cleaning activities will be affected by these new standards. On the other
hand, many, if not most, of the utility users of coal use boilers of this size
or larger. Thus, depending somewhat on the S02 regulations finally promulgated,
the revisions to the NSPS for fossil fuel boilers are likely to have a signifi-
cant, but indirect, impact upon coal cleaning. The role of coal cleaning in
the utilization of coal undoubtedly will be influenced materially, although
in what way is as yet unclear. The percentage reductions required are unlikely
to be achievable by coal cleaning alone, so that some supplemental form of S02
removal probably will be required. On the other hand, the converse may also
be true, especially on high-sulfur coals, so that coal cleaning may be tech-
nically desirable (and possibly also economically advantageous) to supplement
flue gas desulfurization. Additionally, coal cleaning offers a non-capital-
intensive option for significantly reducing S02^emissions from the generally
smaller industrial boilers, for which emission regulations have not yet been
proposed. _,
-------
New source performance standards which are directly applicable to coal
cleaning processes are those for new and modified coal preparation plants and
handling facilities. Processes covered include thermal dryers, pneumatic
coal cleaning equipment (air tables), coal processing and conveying equipment
(including breakers and crushers), coal storage systems (except for open
storage piles) and coal transfer and loading systems (including barge loading
C4>
facilities). [Although the regulations in 40 CFR Part 60.250^ ' do not
specify their application other than to coal preparation plants, the explanatory
discussion in the promulgation announcement (41 Federal Register 2232, January
15, 1976) also included other sources which handle large amounts of coal,
such as power plants, coke ovens, etc.]
Limitations set by these NSPS, applicable to all coal preparation or
handling facilities processing more than 200 tons/day, include:
• Emissions from thermal dryers may not exceed 0.070 g/dscm
(0.031 gr/dscf) and 20 percent opacity.
• Emissions from pneumatic coal cleaning equipment may not
exceed 0.040 g/dscm (0.018 gr/dscf) and 10 percent opacity.
• Emissions from any coal processing and conveying equipment,
coal storage system, or coal transfer and loading system
processing coal (nonbituminous as well as bituminous coal)
may not exceed 20 percent opacity.
3.2.1.1.3 Hazardous Pollutant Emission Standards. The atmospheric
emission of several hazardous pollutants is already regulated under Section
112 of the Clean Air Act. Two of these pollutants (beryllium and mercury) are
found in coal, but not at levels such that their emission would be expected
to violate standards. The establishment of regulations governing arsenic
emissions is now under consideration. Other hazardous pollutants under
consideration include polycyclic organic matter (POM) and lead, with uncertain
decision dates. Except for POM's, emissions of the other hazardous pollutants
mentioned above in concentrations likely to be affected by the standards are
expected only from sources other than fossil fuel combustion.
35
-------
3.2.1.1.4 Prevention of Significant Deterioration of Air Quality. A new
Part C (Sections 160-169) was incorporated into the Clean Air Act Amendments
of 1977 for the prevention of significant deterioration (PSD) of the present
ambient air quality. Three land use classes are established, which are
interpreted by EPA to have the following characteristics:
• Class I - little or no development
• Class II - scattered development
• Class III - concentrated or large-scale development.
Classification in Class I is mandatory for National parks exceeding 6,000 acres
in size and similar state parks and wilderness areas. The verbiage is complex
and involved, but the significant "fact with respect to coal cleaning processes
is that any new source in an area subject to the provisions of this section
is to employ the Best Available Control Technology for each pollutant subject
to regulation. Consideration of the cost of achieving such emission reduction
is not invoked as a factor. Thus, the best available control technology
required for prevention of significant deterioration must be better than NSPS.
It is obvious that these are site-specific problems, and that a uniform
national standard will not be utilized. Each proposed new source will be
considered by the affected state on a case-by-case basis, under the state
implementation plan. The Act provides for maximum allowable increases in S07
and particulates for each class of area, with the provision that the NAAQS
shall not be exceeded. Allowable pollutant increases are shown in Table 3-6
along with national primary and secondary ambient air quality standards.
3.2.1.1.5 Visibility Protection for Federal Class I Areas. Section 169
of Part C of the 1977 Amendments specifically addresses the national goal set
by the Congress of preventing any future impairment of visibility and remedying
any existing impairment from man-made air pollution in mandatory Class I Federal
areas. By August 7, 1979, the Administrator shall promulgate regulations to
assure reasonable progress toward meeting the national goal. The requirements
include existing sources, and may require use of the best available retrofit
technology.
3.2.1.1.6 Nonattainment Areas, The new Part D (Sections 171-178) was
also incorporated into the Clean Air Act Amendments of 1977, to address alle-
36
-------
TABLE 3-6. ALLOWABLE POLLUTANT INCREASES ABOVE
BASELINE CONCENTRATIONS
Concentration, yg/m'
Class Area
II
III
NAAQS
Primary
Secondary
Partlculate Matter
Annual geometric mean 5 19 37
24-hr maximum 10 37 75
75
260
60
150
Sulfur Dioxide
Annual arithmetic mean 2 20 40
24-hr maximum 5 91 182
3-hr maximum 25 512 700
80
365
60
260
1,300
37
-------
viation of air pollution problems in areas where one or more air pollutants
exceed any national ambient air standard. Theoretically, no new emission
source could be constructed in a nonattainment area. Since this was judged
to be an impractical answer, the compromise solution was to require the
"lowest achievable emission rate" (LAER). This is an even more restrictive
standard than the BACT specified for prevention of significant deterioration.
It includes either the most stringent emission limitation for such category
of source in any state implementation plan, or the most stringent emission
limitation actually achieved in practice, whichever is more stringent. In
no event shall it be less restrictive than the NSPS for that category of
source. Like prevention of significant deterioration, this is to be imple-
mented by the individual states through the state implementation plans on a
case-by-case basis. A key provision is that the states are to continue
"reasonable further progress" in achieving annual incremental reductions of
the applicable air pollutant, including such reduction in emissions from
existing sources in the area as may be obtained through the adoption, at a
minimum, of reasonably available control technology (RACT).
The above is part of the so-called "offset" approach, wherein existing
emissions are reduced to permit addition of a new source, with the additional
constraint that an overall decrease should be shown.
In general, designation as a nonattainment area means that an applicable
SIP must be revised to provide for the attainment of the NAAQS as expeditiously
as possible. The revised SIP must require permits for the construction and
operation of major (>250 T/yr emission of any pollution) new and modified
stationary sources, and must contain a prohibition against major new source
construction where emissions would contribute to increases in pollutants for
which a NAAQS was being exceeded.
The U.S. EPA has published a list of the NAAQS attainment status of all
(21)
areas within each state. This list is revised from time to time.
3.2.1.2 State. Although the U.S. EPA promulgates national ambient air
quality standards (NAAQS), states have the privilege of establishing more
stringent standards. Thirty-three states and the District of Columbia have
ambient air quality standards for one or more pollutants that are more strin-
gent than the NAAQS. Ten of the 19 states with coal preparation plants have
38
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ambient air quality standards (AAQS) that are more stringent than the Federal
standards.
Since the concentrations of nitrogen oxides and pollutants other than
sulfur oxides and particulates (for which AAQS exist) are only marginally
related to the quality of coal prepared or burned, emphasis has been placed
on the standards for sulfur dioxide and particulate matter (total suspended
particulates). Those states with more stringent AAQS are Alaska, Arizona,
California, Connecticut, Colorado, Delaware, Florida, Georgia, Hawaii, Indiana,
Kentucky, Louisiana, Maine, Maryland, Minnesota, Mississippi, Missouri,
Montana, Nevada, New Hampshire, New Mexico, New York, North Carolina, North
Dakota, Ohio, Oregon, South Dakota, Tennessee, Vermont, Washington, West
Virginia, Wisconsin, and Wyoming,
States are required to develop state implementation plans which, on
approval by the U.S. EPA, specify how the NAAQS or their own state standards,
if more stringent, will be achieved within three years of the promulgation of
the SIP's. The SIP's cover limitations on existing sources and, where appli-
cable, on new sources. These plans employ different regulatory means for
controlling pollutants from fuel-burning equipment. SIP's exist for sulfur
dioxide, total suspended particulates, and nitrogen dioxide.
In terms of new source performance standards, all new sources in regulated
industry categories must conform to emission limits set by the U.S. EPA, but
states are required to develop new source review procedures to ensure that all
new sources constructed do not violate NAAQS even if it involves facility
resiting or a total denial of a permit to construct a facility.
3.2.2 Water Pollution Regulations
3.2.2.1 Federal. There are no national ambient water quality standards
analogous to those for air; water pollution is regulated nationally on the
basis of emissions, termed effluents in the case of water.
3.2.2.1.1 Effluent Guideline Limitations. The enabling Act providing
the authority to establish effluent limitations is the Federal Water Pollution
Control Act (FWPCA) Amendments of 1972 (P.L. 92-500). Basic effluent limita-
tions for existing sources have not been promulgated for numerous industries;
39
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others have been challenged by the affected industries and are still in abey-
ance pending further development. The FWPCA was further amended by the Clean
Water Act of 1977 (P.L. 95-217). Effluent guidelines presently are based on
the best practicable control technology currently available (BPCTCA), which
was to have been achieved by July 1, 1977. By July 1, 1983, effluent limi-
tations were to have required the application of the best available technology
economically achievable (BATEA). The Clean Water Act of 1977 extended this
date a year to July 1, 1984.
Effluent guidelines are also being promulgated for new sources. These
new source performance standards are intended to be the most stringent
standards applied.
Federal control of water pollution sources associated with coal prep-
aration and handling is achieved through the issuance of NPDES (National
Pollutant Discharge Elimination System) permits to each discharger. These
permits limit specific pollutants in the effluents. Effluents from
coal cleaning are regulated as a part of the coal mining point source
category (40 CFR, Part 434), which defines a "coal preparation plant" as a
facility where coal is crushed, screened, sized, cleaned, dried or other-
wise prepared and loaded for transit to a consuming facility. The term
"associated areas" means the plant yards, immediate access roads, slurry
ponds, drainage ponds, coal refuse piles, and coal storage piles and
facilities. Regulations have been divided into two groups, one for acidic,
and one for alkaline wastes. Final regulations for BATEA effluent limita-
tions have not yet been promulgated.
Regulations for existing plants and proposed new source performance
(22)
standards are summarized in Table 3-7.
3.2.2.1.2 Toxic Pollutants. The Clean Water Act of 1977 introduced a
new requirement for the control of toxic pollutants, which must be limited
by the application of BATEA. Pursuant to this act, the EPA Administrator
published a list of 65 toxic pollutants, shown in Table 3-8, for which
effluent standards are required. This list of 65 toxic substances and
families of substances was identified in the consent decree between EPA
and the National Resources Defense Council (NRDC). Regulations previously
existed for six of the listed pollutants, but regulations have not yet been
40
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TABLE 3-7. EFFLUENT LIMITATIONS GUIDELINES FOR COAL
PREPARATION PLANTS(5>22)
Acidic Wastes Alkaline Wastes
Effluent
Characteristic
Daily 30-Day Daily
Maximum Average Maximum
30-Day
Average
Existing Sources
TSS, mg/1
Iron, total, mg/1
Manganese, total,
pH, daily range
TSS, mg/1
Iron, total, mg/1
Manganese, total,
pH, daily range
70.0
7.0
mg/1 4.0
6.0-9.0
New Source Performance
70.0
3.5
mg/1 4.0
6.0-9.0
35.0 70.0
3.5 7.0
2.0
6.0-9.0
Standards (c'd)
35.0 70.0
3.0 3.5
2.0
6.0-9.0
35.0
3.5
-
35.0
3.0
-
(a) Excess water effluent from a facility designed to contain or treat the
volume of water from the 10-year 24-hour precipitation event not subject
to limitations.
(b) pH may be slightly exceeded to achieve manganese limitation, up to 9.5
(c) Proposed NSPS.
(d) No discharge of pollutants from facilities which do not recycle waste
water for use in processing.
41
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TABLE 3-8. LIST OF 65 POLLUTANTS BEING CONSIDERED
FOR EFFLUENT LIMITATIONS
1. Acenaphthene 36.
2. Acrolein 37.
3. Acrylonitrile 38.
4. Aldrin/Dieldrin* 39.
5. Antimony and compounds 40.
6. Arsenic and compounds 41.
7. Asbestos 42.
8. Benzene 43.
9. Benzidene* . 44.
10. Beryllium and compounds 45.
11. Cadmium and compounds 46.
12. Carbon tetrachloride 47.
13. Chlordane 48.
14. Chlorinated benzenes 49.
15. Chlorinated ethanes 50.
16. Chloroalkyl ethers 51.
17. Chlorinated naphthalene 52.
18. Chlorinated phenols 53.
19. Chloroform 54.
20. 2-chlorophenol 55.
21. Chromium and compounds 56.
22. Copper and compounds 57.
23, Cyanides 58.
24. DDT and metabolites* 59.
25. Dichlorobenzenes 60.
26. Dichlorobenzidine 61.
27. Dichloroethylenes 62.
28. 2,4-dichlorophenol 63.
29. Dichloropropane and dichloropropene 64.
30. 2,4-dimethylphenol 65.
31. Dinitrotoluene
32. Diphenylhydrazine
33. Endosulfan and metabolites
34. Endrin* and metabolites
35. Ethylbenzene
Fluoranthene
Haloethers
Halomethanes
Heptachlor and metabolites
Hexachlorobutadiene
Hexachlorocyclohexane
Hexachlorocyclopentadiene
Isophorone
Lead and compounds
Mercury and compounds
Naphthalene
Nickel and compounds
Nitrobenzene
Nitrophenols
Nitrosamines
Pentachloropheno1
Phenol
Phthalate esters
Polychlorinated biphenyls (PCB's)*
Polynuclear aromatic hydrocarbons
Selenium and compounds
Silver and compounds
2,3,7,8-Tetrachlorodibenzo-p-dioxin
Tetrachloroethylene
Thallium and compounds
Toluene
Toxaphene*
Trichloroethylene
Vinyl chloride
Zinc and compounds
* Pollutants for which regulations have been promulgated.
42
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promulgated for any of the other listed pollutants. EPA has further identified
specific compounds, within the chemical classes in the published list, to be
considered for effluent standards. The thirteen elements in the published
list, and their compounds, should receive emphasis in the environmental
assessment of coal cleaning processes because of observed existence in coal.
However, none of the classes of organic chemicals in the list appears to have
significance as a pollutant from coal cleaning processes because they have
not been observed to exist in coal and have not been used as agents in coal
cleaning operations.
3.2.2.1.3 Water Quality Criteria. While ambient air quality standards
are set at the Federal level, water quality standards are primarily a state
responsibility. The only existing Federal water quality standards are those
for drinking water, applicable to public (community) water supplies. Maximum
contaminant levels in public water supplies have been set for the following
contaminants that are associated with coal and coal activities: arsenic,
barium, cadmium, chromium, fluoride, lead, mercury, nitrate, selenium, and
silver.
Federal water quality criteria (guidelines) have recently been revised
and expanded, and published by the U.S. EPA. ' While these criteria do not
have direct regulatory application, the states are expected to adopt these in
implementing state water quality regulations. The criteria are two-fold. In
one instance, the goal is water quality that will provide for the protection
and propagation of fish and other aquatic life and for recreation in and on
the water. Criteria are also presented for domestic water supply use. These
suggested limits were used in this study in developing estimated permissible
concentrations (EPC's) for the pollutants listed.
3.2.2.2 State. The situation on control of water pollution by the
states is analogous to that for air pollution. Emission standards (effluent
guidelines) are established on a national level by EPA, but their implementa-
tion is regarded as a state responsibility. The Federal Water Pollution
Control Act Amendments of 1972 (P.L. 92-500) provides for the reduction of
duplicate laws by delegating permit issuance authority to the states. Dele-
gation of authority takes place when a state demonstrates that it has legal
43
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authority and resources to operate the program as envisioned by that Federal
law. The States of Colorado, Indiana, Kansas, Maryland, Missouri, Montana,
North Dakota, Ohio, Virginia, Washington, and Wyoming are delegated NPDES-
issuing states. The effluent limitations vary among the delegated and non-
delegated states.
Water pollution control enforcement is based on effluent standards
rather than stream quality, and plant discharges must be within certain
limits prescribed for each industry. The objective of such control systems
is to achieve or maintain ambient water quality standards which are primarily
a state responsibility. If these are not achieved by compliance with effluent
standards, more stringent limits may be applied.
3.2.3 Solid Waste Regulations
3.2.3.1 Federal. Prior to October 21, 1976, protection of the environ-
ment from pollution arising from the land disposal of solid wastes was provided
by the Solid Waste Disposal Act of 1965 (P.L. 89-272), as amended by the
Resource Recovery Act of 1970 (P.L. 91-512), Federal guidelines for the Land
(23)
Disposal of Solid Wastes are given in Title 40 CFR, Part 241. '
Pursuant to Section 211 of the Solid Waste Disposal Act as Amended in
1970, the guidelines are mandatory for Federal agencies and are recommended
to state, interstate, regional, and local governmental agencies for use in
their solid waste disposal activities. However, these are only guidelines,
and do not establish new standards, but set forth requirements and recommended
procedures to ensure that the design, construction, and operation provide for
environmentally acceptable land disposal site operations. The thrust of Part
241 is towards sanitary and municipal wastes. Mining wastes are essentially
ignored.
The management of solid and hazardous wastes entered a new era on
October 21, 1976, with passage of the comprehensive Resource Conservation and
Recovery Act (RCRA) of 1976 (P.L. 94-580). Although this Act is not yet imple-
mented, it is already clear that the management of solid and hazardous wastes
will be revolutionized by the specific regulations that are currently being
drafted by the U.S. EPA.
44
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The introductory section of the Act describes the Federal role as one
of providing financial and technical assistance and leadership in the develop-
ment, demonstration, and application of new and improved methods of waste
management. In practice, it appears that guidelines and regulations will be
developed by the U.S. EPA, for adoption and promulgation by the states, poss-
ibly in a fashion similar to the SIP's used for air pollution control. The
individual states would enforce their adopted regulations.
Some of the general provisions of the Act are:
• The U.S. EPA was to issue guidelines by October 21,
1977, for defining sanitary landfills as the only
acceptable land disposal alternative which can be
implemented; open dumps are to be prohibited.
• By October 21, 1977, the U.S. EPA was to develop and publish
suggested guidelines for solid waste management.
• By April 21, 1978, the U.S. EPA was to promulgate criteria
for identifying hazardous waste; standards for generators
and transporters; and standards for treatment, storage,
and disposal of hazardous wastes.
• Permit programs are to be managed by the states under
minimum guidelines provided by the U.S. EPA.
• Each regulation promulgated shall be reviewed and, where
necessary, revised at least every three years.
The development of specific regulations is appreciably behind schedule,
and discussion of possible requirements is, accordingly, unavoidably specula-
tive. However, it is evident that very great attention will be given to those
wastes classified as hazardous. The criteria for their identification and
classification have not yet been proposed; the boundaries finally selected will
have a major impact upon waste management. It is presently uncertain whether
coal refuse (and combustion ash) will be classified as non-hazardous wastes,
which would avoid the most restrictive provisions of the Act. In the absence
of developed regulations, it is not possible at this time to delineate either
the details of its application or its impact upon coal cleaning.
The Geological Survey of the U.S. Department of the Interior has estab-
lished regulations for the disposal of wastes from coal preparation plants
located on the surface of land associated with mining. Preparation is
defined as any crushing, sizing, cleaning, drying, mixing, or other processing
45
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of coal to prepare it for market. The operator is required to:
"dispose of all waste resulting from the mining and preparation
of coal in a manner designed to minimize, control, or prevent
air and water pollution and the hazards of ignition and combustion."
Additionally, more specific requirements are given for waste pile construction,
covering, and revegetation, and for settling ponds.
3.2.3.2 State. A few states have solid waste disposal regulations
directly applicable to coal preparation or consumption. The various states
have general regulations covering solid waste management, solid waste disposal,
and solid waste disposal areas (landfills, sanitary landfills, etc.). Solid
wastes are not to be disposed of in a place or in a manner that will endanger
human health and plant or animal life or contribute to air pollution. Disposal
areas are to be located to ensure the least possibility of contaminating
surface or ground waters. The provisions of the Resource Conservation and
Recovery Act of 1976 will allow definitive guidelines to be established by
each state for the storage and disposal of solid wastes, including those
generated from coal preparation and consumption.
46
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3.3 References
(1) Min, S., Tolle, D.A., Holoman, V.L., Grotta, H., and Minshall, C.W.,
"Technology Overview of Coal Cleaning Processes and Environmental
Controls", Draft Report to U.S. Environmental Protection Agency,
Battelle's Columbus Laboratories (January, 1977).
(2) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 50, "National
Primary and Secondary Ambient- Air Quality Standards", pp 3-33.
(3) U.S. Environmental Protection Agency, "National Ambient Air Quality
Standard for Lead", Final Rules and Proposed Rulemaking, 43 FR 46246-
46277 (October 5, 1978).
(4) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 60, Subpart Y,
"Standards of Performance for Coal Preparation Plants", pp 57-58.
(5) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 434, "Coal
Mining Point Source Category", pp 685-689.
(6) U.S. Environmental Protection Agency, "Quality Criteria for Water",
EPA 440/9-76-023, U.S. Environmental Protection Agency, Washington,
D.C., 501 pp (1976).
(7) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 61, "National
Emissions Standards for Hazardous Pollutants", pp 143-220.
(8) U.S. Environmental Protection Agency, "Publication of Toxic Pollutant
List", 43 FR 4108-4109, January 31, 1978.
(9) U.S. Department of Labor, Occupational Safety and Health Administration,
Code of Federal Regulations 29, Labor, Revised as of July 1, 1977,
Office of the Federal Register, National Archives and Records Service,
General Services Administration, Washington, D.C. (1977), Part 1910,
Subpart 2, "Toxic and Hazardous Substances", pp 612-712.
47
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(10) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 141, "National
Interim Drinking Water Regulations", pp 169-182.
(11) U.S. Environmental Protection Agency, "Proposed Toxic Pollutant
Effluent Standards", 38 FR 35388-35395 (December 27, 1973).
(12) Cleland, J. G. and Kingsbury, G. L., "Summary of Key Federal
Regulations and Criteria for Multimedia Environmental Control",
Draft Report to U.S. Environmental Protection Agency, Research
Triangle Institute (June, 1977), 132 pp + Appendix.
(13) Ruch, R. R., Gluskoter, H. J., and Shimp, N. F., "Occurrence and Distri-
bution of Potentially Volatile Trace Elements in Coal: A Final
Report", Environmental Geology Notes No. 72, Illinois State Geological
Survey, Urbana, Illinois (August, 1974), pp 41-50.
(14) Gluskoter, H. J., Ruch, R. R., Miller, W. G., Cahill, R. A., Dreher, G. B.,
and Kuhn, J. K., "Trace Elements in Coal", EPA-600/7-77-064, Industrial
Environmental Research Laboratory, U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina (1977), 163 pp.
(15) Blackwood, T. R. and Wachter, R. A., "Source Assessment: Coal Storage
Piles", Draft Report to U.S. Environmental Protection Agency, Monsanto
Research Corporation (July, 1977), 96 pp.
(16) Brown, R., Jacobs, M. Y., and Taylor, H. E., "A Survey of the Most Recent
Applications of Spark Source Mass Spectrometry", American Laboratory,
4_, 29-40 (November 1972).
(17) Energy and Environmental Analysis, Inc., "Laws and Regulations
Affecting Coal with Summaries of Federal, State, and Local Laws and
Regulations Pertaining to Air and Water Pollution Control, Reclamation,
Diligence, and Health and Safety", DOI/OMPRA/CL-76-01, Report to U.S.
Department of the Interior, Office of Mineral Policy and Research
Analysis (June, 1976), 200+ pp.
(18) Ewing, R. A., Tolle, D. A., Min, S., Raines, G. E., and Holoman, V. L. ,
"Development of Environmental Assessment Criteria", Draft Preliminary
Report to U.S. Environmental Protection Agency, Battelle's Columbus
Laboratories (April 8, 1977), 46 pp.
(19) Battelle's Columbus Laboratories, "Environmental Assessment of Coal
Cleaning Processes", Draft Annual Report to U.S. Environmental Protection
Agency, Vol. II (October, 1977).
(20) U.S. Environmental Protection Agency, "Electric Utility Steam Generating
Units, Proposed Standards of Performance", 43 FR 42154-42184 (September
19, 1978).
48
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(21) U.S. Environmental Protection Agency, "National Ambient Air Quality
Standards, States Attainment Status", 43 FR 8962-9059 (March 3, 1978).
(22) U.S. Environmental Protection Agency, "Coal Mining Point Source
Category", 41 FR 21380, April 26, 1977.
(23) U.S. Environmental Protection Agency, Code of Federal Regulations 40,
Protection of Environment, Revised as of July 1, 1977, Office of the
Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 241, "Guidelines
for the Land Disposal of Solid Wastes", pp 529-538.
(24) U.S. Department of the Interior, Geological Survey, Code of Federal
Regulations, 30 Mineral Resources, Revised as of July 1, 1977, Office
of the Federal Register, National Archives and Records Service, General
Services Administration, Washington, D.C. (1977), Part 211, "Coal-
Mining Operating Regulations", pp 563-623.
49
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4.0 ESTIMATION OF ENVIRONMENTAL CONCENTRATIONS
Eventually, emissions and environmental concentrations at coal cleaning
plants will be measured rather than estimated. For the present, however,
it is necessary to estimate these concentrations using appropriate models.
The approaches to estimating emissions are described in Section 4.1,
followed by discussions of physical transport and dispersion (Section 4.2)
and ecological transport and distribution (Section 4.3).
4.1 Modeling of Pollutant Emissions
By virtue of its origin, coal has been found to contain nearly every
naturally-occurring element. The concentrations of these elements in coal
vary widely. Many of these elements, e.g., arsenic, beryllium, cadmium,
lead, and mercury are recognized as toxic substances.
The various lists of potential pollutants described earlier (Section
3.1.1) identify those pollutants that may be of concern in coal cleaning,
provided that they are present and emitted above some yet undefined rate
of release and/or concentration. The ranges of pollutant concentrations
characteristic of coals (Section 3.1.2) provide some information on their
presence but none on their possible emissions. The first item needed to
estimate emissions is information on the process steps embodied in the
cleaning flowsheet (these are a "given"). Many alternatives and combinations
of alternatives are possible in crushing, sizing, and washing coal, and in
separating coal from refuse. The actual combination of process elements
will influence the degree of pollutant emissions but not the kind. Thus,
for purposes of developing assessment criteria and methodology, reasonable
approximations of a generic process flowsheet will suffice and are used in
this report.
50
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4.1.1 Fractionation Factors
The second item needed for estimating emissions is information on
"fractionation factors", i.e., the distribution of substances in raw coal
to another fraction or phase as the coal passes each process step. Examples
are coal:refuse, in cleaning; and coal:ash and coal:atmosphere in combus-
tion.
One way of classifying noncombustible components in coal is to
characterize the mineral matter as either "inherent" or "extrinsic, extra-
neous, or adventitious". Inherent mineral matter is usually defined as
that portion of mineral matter originally combined with the coal. ' It
cannot be detected petrographically or separated by physical methods.
These constituents would be considered as having a high "organic affinity".
Extrinsic or adventitious mineral matter is readily detected petrographi-
cally and more or less readily separated from coal. It may have originated
during coal formation (syngenetic) or after the coal had formed (epigenetic).
Extrinsic constituents would have a low "organic affinity". The degree of
organic affinity is useful in predicting the distribution of elements
between coal and refuse in coal cleaning. The theoretical aspects of this
(2)
have been examined by Zubovic and coworkers at the U.S. Geological Survey.
Zubovic postulated that trace metals in coal are present in the organic
phase as chelated metal organic complexes. Metal ions with a high ratio
of ionic charge to ion radius would be the preferred species undergoing
complex formation and would have higher organic affinity. Experimental data
supported the existence of such complex formations.
There may be some correlation between the fractionation factor and the
ionic potential of the element. Figure 4-1 plots fractionation factors
of trace elements, estimated from float-sink experiments, against ionic
potential (the ratio of ionic charge to ion radius for each element).
Although the data are somewhat scattered, there is a correlation between
the two parameters; i.e., the fractionation factors tend to increase as
the ionic potential increases. The fractionation factors can be approxi-
mated as a function of the ionic strength, and they generally fall in the
range between the two straight lines drawn in Figure 4-1. In Battelle's
51
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5 6 7 8 9 10
Ionic Potential = |charge/radius|
14
15
FIGURE 4-1. FRACTIONATION FACTOR VERSUS IONIC POTENTIAL
-------
preliminary draft report on development of environmental assessment
(3)
criteria , fractionation factor ranges were estimated for a number
of elements using this approach. This approach may be useful for
estimating the upper and lower limits of the fractionation factors
for trace elements for which no experimental data are available.
However, it suffers from the fundamental fact that coals are not alike,
and an element may not be consistently associated with either the organic
or the inorganic fraction, from one coal to another.
More useful than fractionation factors are empirical data based
on laboratory experiments. Float-sink, or washability data, have been
(4)
compiled for many coals. Gluskoter, et al., have examined this
aspect of coals intensively, concentrating on Illinois Basin coals, but
also including numerous other Eastern coals.
In one series of extensive washability tests of four Illinois Basin
coals, three Appalachian coals, and one Arizona coal, they found, not
surprisingly, that the Illinois coals were much more similar to each
other with regard to organic affinities than they were to coals from
other areas. It was possible to make several generalizations for these
coals:
• Ge, Be, B, and Sb tended to have the highest organic
affinities
• Zn, Cd, Mn, As, Mo, and Fe tended to have the lowest
organic affirmities
• A number of metals including Co, Ni, Cu, Cr, and Se,
were intermediate in value, suggesting a partial
contribution from sulfide minerals in the coal,
along with the presence of organometallic compounds
that contain these elements, or the presence of chelated
species and/or adsorbed cations.
The grouping of these elements is generally consistent with the
ordering based on ionic potential (Figure 4-1). Gluskoter, et al.,
observed that as Appalachian and Arizona coals were included, the number
of generalizations possible decreased.
They classified the elements into four groups:
Organic Intermediate-inorganic
Intermediate-organic Inorganic.
53
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The "organic affinity" indices separating the groups varied from coal
to coal; similarly, some elements occasionally shifted from one group
to the next. It is clear that no hard and fast grouping is possible
for all elements in all coals, and the rankings are perhaps better
expressed as tendencies. For the purposes of investigating environmental
assessment criteria, "average" behaviors of the elements generally have
been utilized.
If it is desirable to base the calculations on a specific coal,
for which washability data are available, fractionation factors
calculated for that coal can be used. A simple computer program
has been developed and tested which permits estimation of fraction-
ation factors for elements as a function of specific gravity separation
points and/or yield. Illustrative are the computer plots for arsenic
in Herrin No. 6 Illinois coal (Figure 4-2), based on the data of
(4)
Gluskoter, et al.
Calculating the fractionation factors for a particular constituent
of a particular coal requires data on the ppm of that constituent by
specific gravity fraction and the total weight of material in each specific
gravity fraction. The first step in the calculation is to compute cumula-
tive ppm of the constituent from lightest specific gravity fraction to
heaviest and cumulative weight in these fractions. Dividing the cumulative
weight values by the total weight gives yield. Cumulative ppm versus yield
is shown in Figure 4-2 (b).
Now the fractionation factor is simply that portion of the total
amount of the constituent in each specific gravity fraction, shown plotted
against yield in Figure 4-2 (c). Finally, the fractionation factors are
plotted against the midpoints of the specific gravity fractions in Figure
4-2 (d).
"Fractionation factors" are also available from Klein, et al.,
and others, for the partitioning of elements upon combustion in a
boiler. These can be used to estimate losses to the atmosphere from
the thermal drying of cleaned coal. For partitioning of elements between
coal and the atmosphere during transport, handling, and storage,
"fractionation factors" would correspond to emission factors, such as
those estimated by EPA and others. Analogous "emission factors"
54
-------
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storage piles, ash ponds, etc.
4.1.2. Estimation of Emission Concentrations
Values of emission concentrations are required as input to dispersion
models to permit the calculation of ground level concentrations (GLC)
for air pollutants and surface water concentrations (SWC) for water
pollutants. A simplified preliminary material balance model has been
developed covering the direct process steps from raw coal to combusted
ash, illustrated by Figure 4-3. The incidental losses to air and
water arising from transportation, handling, and storage are not
included in this preliminary model, but can readily be included when
data become available. The model, which is normalized to a combustion
output of 10 Btu, can provide estimates of absolute emissions and
average concentrations of any number of trace constituents in (1)
recirculated water, (2) thermal dryer atmospheric discharge, (3)
stack discharge from combustion, and (4) ash flow based on composite
flows, given an analysis for the starting raw coal.
The model has been derived, programmed, and run with example
cases, using a composite fuel analysis of 68 percent coal from the
Helvetia mine and 32 percent coal from the mine simulating feed to the
Homer City coal cleaning plant.* The results of a recent run of this
model, using an assumed 80 percent coal recovery, and fractionation
factors based on the float-sink data of Gluskoter, et al., for 3/8-in.
x 28 mesh Pittsburg No. 8 coal, are shown in Appendix A.
Only a few elements are shown in the illustrative example in
Appendix A. These can be expanded to include all elements for which
fractionation factors are available or can be estimated. In this example,
* This MCCS (Multistream coal cleaning system) facility, to be in
operation in 1978, is located near the Homer City Generating Station
Power Complex, Homer City, Pennsylvania. The coal cleaning facility
is owned by Pennsylvania Electric Company (a subsidiary of General
Public Utilities Corporation) and New York State Electric and Gas
Corporation.
56
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Thermal dryer
discharge
970 »cf ^
(includes 0.6 Ib
combustion pro-
* . i
ducts and
particulates)
Raw coal ^
93.9 Ib.
Thermal dryer
air flow """"
970 scf
X.
^|
166.2 Ib Flue go
Water 835 Ib
4
/
/
/
i
Physical { _
Cleaning 74.3 Ib
(thermal Cleaned Combustion
dryers Coal
use 0.8 Ib
T
•
185
Ib
166.2 Ib "^ — Wct refuse
recirculated
water
\
1
t"-^
Ash from ^sn
thermal
dryers 9-4 lb
0.2 Ib
I06 Btu
Air 9.9 x tO scf
(10% excess)
19.0 Ib
Dry refuse
FIGURE 4-3. GENERALIZED FLOW QUANTITIES IN COAL CLEANING PROCESS
57
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application of some control technology was assumed. The use of a
Venturi scrubber was assumed for the thermal dryer exhaust (efficiencies
( 8)
based on Abel, et al. ) and use of an electrostatic precipitator on
the boiler ultimately burning the coal was assumed. Other control
technology alternatives can be substituted.
4.2 Modeling of Physical Transport and Distribution
Pollutants emitted in the course of coal cleaning, handling, trans-
portation, storage, and combustion can both accumulate and disperse, in
both a physical and biological sense, depending upon the characteristics
of the pollutant and the compartment. Biological transport and fate
are discussed in Section 4.3. In this section, modeling of the preceding
physical transport and dispersion are discussed. The general need for
modeling is to make estimates of the concentrations of trace pollutants
in environmental media as a result of operation of a coal cleaning
plant. No regulations or design criteria are available yet for most of
these, although regulations will be proposed and promulgated by EPA
within the next year or two for a number of toxic pollutants (see
Section 4.2.2), which may affect coal cleaning plants.
In succeeding paragraphs, modeling approaches are discussed relative
to surface water, groundwater, air, and porous media. Generally, the air
pollution model should account for deposition, both wet and dry,
providing one input to surface water and soils. Surface water run-off
will pick up material in the upper soil layer. The coal pile will be
leached by precipitation, which will also generally be carried into
surface water. Leaching and leakage through sedimentation pond bottoms
will generally contribute to groundwater pollution, although the movement
of some pollutants through the subsoil and into the groundwater requires
years because of adsorption of materials on soils. The refuse area,
usually some kind of a fill, will be leached by the downflow of water
from precipitation and surface flow, contributing to both stream
pollution and groundwater pollution. The rationale that should be
incorporated in the modeling approach is to build a capability of
evaluating individual coal cleaning complexes, either existing or
58
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under design. This approach is recommended because the many different
characteristics, e.g., meteorology, topography, stream geometry, soil, and
groundwater characteristics required to characterize a given complex,
vary widely from one plant to another, making generalizations risky
at this time.
On the other hand, the objective of the present investigation is to
develop criteria and associated methodologies for their application rather
than to estimate site-specific environmental impacts for a given complex.
The solution would seem to be to include the necessary provisions in the
models for the multiplicity of detailed parameters that will ultimately
be required, but to use nominal values, or ranges, or possibly even
"worst-case" estimates, for a hypothetical site in the developmental
phase.
Validation is an important aspect of model development, and should be
planned for, utilizing one of the coal cleaning sites chosen for field
data acquisition. Field data will permit validation and calibration of
the models and suggest their application for future sites. However, it
is not possible within the time frame of the present program to wait
until field data are available to initiate model development. For that
matter, it is not desirable to wait because modeling will define data
that need to be gathered and will give preliminary evaluations, using
data that are available in the literature from other areas.
A review of models for air, water, and groundwater quality
assessment, which are applicable to coal cleaning, has been compiled by
(9)
Ambrose, et al.
4.2.1 Air Dispersion of Pollutants
The concentration of key pollutants in the thermal dryer atmospheric
discharge and in the flue gases from combustion of the cleaned coal will
provide input for calculations of atmospheric dispersion. The basic
purpose of the dispersion calculation is to provide an estimate of the
dilution factor which, when, divided into the stack emission concentrations,
will yield ground level concentrations.
59
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Two basic models are required, depending on whether the pollutant is
associated with large (> 100 ym) or small (< 100 ym) particles. Large
particles tend to deposit on surfaces near the stack so that their
concentration in the air diminishes as distance from the stack increases.
The concentration of smaller particles is reduced only by dispersion.
Simplified dispersion models, typified by that presented by
Turner, are available that consider stack height and diameter, stack
gas temperature and exit velocity, and ambient air temperature and wind
speed. Calculations are performed for different weather categories.
Multiple sources can be considered to include the effects of more than
one stack if distance between stacks is large enough to merit this
refinement.
The large particle deposition model requires only the deposition
factor, wind speed, and effective stack height. Deposition factors are
available in the literature for various wind speeds of interest.
A fugitive dust emission model, based on the EPA Multiple Point
Source Model (PTMTP), has been used by Battelle to help in selecting
environmental sampling sites and to project mass atmospheric concentrations.
It is a Gaussian plume, multiple-source model, with a generation function
for fugitive emissions dependent on wind speed squared. Deposition is
accounted for (but not plume depletion), and the model has been calibrated
by Battelle based on field data. The operation of this model has been
described. The model may require modification to account for wet
deposition which has been shown to account for far more than half of
the deposition of Cd, Hg, Pb, and other trace elements in eastern
Tennessee (from power p]
are also available^ '.
(12)
Tennessee (from power plant plumes) . Experimental deposition velocities
4.2.2 Water Dispersion of Pollutants
Two types of effects may need consideration when modeling pollutant
discharges to water: (1) dispersion and sedimentation of particulate solids,
and (2) dispersion and dilution of soluble pollutants.
For estimating surface water concentrations, data on the concentration
of pollutants and the flow of waste discharges are required. Emission
60
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sources to be considered inlcude the waste water discharge from coal
cleaning, and runoff and percolation from coal and refuse storage piles,
as well as from ash ponds at coal cleaning plants and from coal storage
piles at user plants.
Sedimentation in settling basins can be modeled by the use of deposi-
tion coefficients. Since sedimentation removes only a portion of the
pollutant from a water column, a residual concentration remains which is
then further diluted by dispersion and additional sedimentation in streams,
etc. Simplified dispersion models using point sources of pollutants can
be used. These models provide a correlation of dispersion coefficient
with flow velocity and stream configuration so that reasonable approxima-
tions for surface water concentrations associated either with a specific
facility or with a generalized case can be calculated for average flows,
low flows, and high flows. Sedimentation is incorporated by using deposi-
tion factors that relate sedimentation rate to pollutant concentration in
the water body. Output consists of sedimentation rate and concentration
in water as a function of position (normally distance downstream) for each
case. Pseudo-steady state models are believed to be adequate. With these
models, when conditions such as release rates or flow of the stream change,
concentrations make a step change from one steady state to another.
Sediment accumulates on the stream bottom linearly with time until such
a change in conditions occurs.
Fully mixed (with stream cross section and depth) models are more
appropriate for small narrow streams, which are likely to be around a coal
cleaning plant. In such a case, the stream concentration, C., for
pollutant A is given by
RA
exp (-k.t) (1)
where R. is the release rate of pollutant A (gm/day), Q is the stream
A o
discharge rate (m /day), k. is the sedimentation coefficient for pollutant
-1
A (day ), and t is the travel time (days) to the downstream position of
interest.
/xwddx
t is defined by
61
-------
where x is the distance downstream, w is the stream width, and d is the
stream depth (note that w and d can be variable). For a stream with a
uniform cross section, t is simply x/V where V is stream velocity (m/day).
k. is equal to k, ./d where k, . is a bottom deposition coefficient (m/day)
and d is the depth.
The flux of pollutant A to the bottom at any given location is given
^ WV
In the case of a shoreline release to a large stream, it may be
advantageous to use a two-dimensional model, using dispersion in the cross
stream direction as the mixing mode. In such a case, C.(t,y) is given by
A
R.w
CA(t,y) exp
Q /TrDt
(2)
C.(t,y) is dependent on both downstream travel time (or position) and cross-
stream position, y. D is the dispersion ocefficient, which is characterized
by stream geometry and flow rate. Sedimentation at a given location is
calculated by \\ct.(tiy)-
These solutions to the transport equation have been known for years,
and they are reasonably applicable for continuously flowing freshwater
streams.
The need for a sedimentation model is not certain. The U.S. EPA has
promulgated effluent guidelines for existing coal preparation plants and
(13)
associated areas and also has proposed new source performance stan-
(14)
dards , both of which establish upper limits of total suspended solids
(TSS) of 70 mg/1 (maximum for any one day) and 35 mg/1 (average of daily
values for 30 consecutive days). For new sources, these values apply
to facilities that recycle waste water for use in processing (nearly all
new facilities should fall into this category). A "no-discharge-of-
process-waste-water" limitation is proposed for new facilities that do
not recycle waste water.
The definition of "coal preparation plant associated areas" is broad,
including plant yards, immediate access roads, slurry ponds, drainage
ponds, coal refuse piles, and coal storage piles and facilities . Thus,
in order to be in compliance, effluent from all areas of a coal preparation
plant, including coal and refuse piles, will have to be controlled so that
62
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the total aqueous TSS discharge does not exceed a 30-day average of 35
mg/1. At this concentration, sedimentation probably can be neglected.
4.2.3 Dispersion Through Porous Media
Although emission of pollutants to the atmosphere and to surface waters
is regulated by the U.S. EPA, heretofore the invisible and difficult-to-
measure escape of aqueous pollutants downward through the soil has essen-
tially avoided regulation. This situation is beginning to change, and
this pollutant transport path should be considered in regard to environ-
mental criteria for coal cleaning-plants. As indicated in the introduction
to this section, this pollutant release pathway can come into play beneath
storage piles of raw and cleaned coal or refuse, as well as under refuse
ponds.
Simplified approaches to modeling adsorption and leaching of pollutants
in porous media are available. Simplified one-dimensional models are
described by Raines along with comparisons with sophisticated results
such as computerized finite difference models with Langmuir adsorption-
desorption. In many cases, the simplified models are quite adequate. It
is recommended that initial emphasis be directed toward correlation of data
and estimation with these models.
One simplified solution for adsorption is given by
C.(T,Z) - i C
1-erf
-T*
Z-T
Av ' ' 2 ACIN)
A ^ AUW; 2 /N^
where CA(T,Z) is the concentration of pollutant A in the liquid at any
A.
relative position z in the porous medium and at any normalized time, T.
T is given by t/0, where t is real time and 6 is the residence time for
the bulk fluid. CA(-TN\ is the concentration in the liquid at the point
where it enters the porous medium. T* is the ratio T/Cl+lL.) where KL, is
a linear equilibrium constant for the adsorption/desorption process. N
is the dispersion parameter, D/(VL), where D is the dispersion coefficient,
V is the average liquid velocity, and L is the characteristic length of
the porous medium. The notation erf denotes the error function which is
tabulated in standard references. This solution assumes local equilibrium,
63
-------
i.e., the concentration of adsorbed pollutant A is always in equilibrium with
the liquid concentration immediately adjacent to it.
The concentration of pollutant A leaving the porous body after adsorption
is given by
CA(T,1) -±
-AM,-/ 2 -A(IN)
The analogous solution for desorption is
1-erf
(4)
CA(T'1)=2CAO
1 + erf
Z-T*
(5)
where C,
-._ is the concentration in .the fluid phase during the adsorption step.
The concentration of pollutant A leaving the porous body after desorption
is given by
1-T*
2 CAO
1 + erf
Plotting of either C._ /C.,_.TX or C._,,/CA_ on a probability scale
AEa A(IN) AEd AO
(6)
versus (T*-!)/ /r*" yields a straight line with the 0.5 value occurring at
T* = 1. This model says that a given exit concentration that would be
achieved at a value T with no adsorption or desorption will not occur until
(1 + K_)T with adsorption or desorption present.
The simplified concept for leaching of coal piles or refuse areas would
employ Equation (6) where C is equal to the concentration in water in
Ł\\J
equilibrium with the trace element concentration in the coal or refuse.
4.2.4 Groundwater Dispersion of Pollutants
Groundwater modeling for accurate estimation of flows and resulting
trace contamination is sophisticated and complicated. A sophisticated
approach is not deemed within the scope of this program at the present
time. The recommended approach consists of specifying a groundwater flow
rate and then using Equation (3) to estimate the concentration of pollutant
A in the groundwater at various locations and times of interest.
Experimental data for various trace elements and various soils are
available from which approximate IC, values can be determined. The data
given in Reference (16) are plots from experimental adsorption in soil
64
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columns; a graph of C /CA(TN') for the different element-soil combinations
versus the number of pore volumes of liquid passed through the column were
given. The number of pore volumes is identical to the parameter, T, in the
simplified model. Thus, K^ is estimated by subtracting one from the value
of T at which an experimental value of 0.5 for C4T, /CA/T,,X is obtained.
AEa A(IN)
Estimates for As, Be, Cd, Cr, Cu, Hg, Ni, Pb, Se, V, and Zn in 10 soils
are available. The soils include variations of sands, loams, and clays.
Results range from Kg= 0 (no adsorption) to no detectable trace element in
the effluent for the duration of the experiment, which, in these particular
experiments, corresponds to a 1C, greater than about 30.
(16)
Hg was the most mobile of the trace elements tested, showing at
least some pass-through for all soils tested. Cd was highly mobile (Kp, ^ 0)
in two soils: Wagram, a loamy sand from North Carolina, and Ava, a silty
clay loam from Illinois. Numerical values for results are not given in
the Korte paper, and it probably will be desirable to try to obtain the
numerical data from the authors.
4.3 Ecological Transport and Distribution
In order to assess the ecological effects of the release of pollutants
from coal cleaning processes, an elucidation of their ecological transport
and fate is necessary. The pollutant's chemical form, concentration, and
mode of entry into the ecological system (i.e., atmosphere, food source,
or water) depends on the coal type, environmental conditions, and type of
coal cleaning technology employed at a facility. The ultimate concern
when dealing with ecological fate is the rate at which the toxicant or
pollutant moves within the ecosystem and whether or not the pollutant
ecomagnifies within its various components.
Requirements for implementing a quantitative study focused on deter-
mining the ecological transfer of a toxicant are extremely rigorous. Recent
investigations have shown that the variability in a pollutant's chemistry,
specific target ecosystem, source release rate, abiotic dispersion factors
and the environmental factors (i.e. soil type, etc.) affect the ability to
accurately quantify ecological transport of pollutants. This quantifi-
cation requires knowledge of general soil or sediment parameters, dominant
65
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vegetative species composition, and other important parameters to accurately
calculate potential rates of movement and specific target organisms' body
burdens. Such information cannot be extracted from the literature. Most
researchers have avoided or ignored these confounding parameters altogether,
thus adding to the general misunderstandings of pollutant transport rate
and ultimate fate reported in the literature. It is not that reported
values are incorrect or inadequate, but that dominant influencing parameters
are not being adequately characterized. As a result, these investigators
cannot adequately estimate movement of the pollutant in the environment
with respect to time.
Investigation of the entire list of Priority 1 pollutants (see
Table 3-1) was beyond the scope of this subtask, which focused on the
abbreviated "short list" extracted from that group. Since sulfur and
nitrogen are part of the biological cycle, they were eliminated, and the
following eight elements were investigated.
• Arsenic
• Beryllium
• Cadmium
• Iron
• Lead
• Manganese
• Mercury
• Selenium.
The specific objectives of this aspect of the study were to:
• Identify the typical components of the generic ecosystem that
are most likely to receive process wastes from a coal cleaning
facility
• Determine the dominant pathways that are likely to control
pollutant transport through a generic food web
• Determine which of the designated pollutants are most likely
to cause long-term environmental risk
• Estimate from reported literature values the concentration
factors for each pollutant. These values for concentration
factors will be expressed as the percent uptake-retention
66
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and are calculated based on reported concentrations In both
the donor and recipient compartments.
4.3.1 Ecological Overview
In this portion of the study, the potential or final distribution of
pollutants within a generic ecosystem has been investigated. The hypothet-
ical temperate ecosystem chosen can be found in northern Appalachian and
midwestern regions (Figure 4-4). The ecosystem is composed of both terres-
trial and aquatic components, with biotic functional groups being specified
for each compartment (i.e., producers, herbivores, omniovores, carnivores,
and decomposers). Literature values pertaining to the abiotic components
(soil, sediment, surface water, and groundwater) and functional groups
likely to be found in the zone demarcated in Figure 4-4 were used in
determining ultimate projected distribution.
This generic ecosystem has been partitioned into functional compartments
which represent the dominant sinks, biotic groups, and pathways of a typical
ecosystem. Figure 4-5 is a fifteen-compartment model of the hypothetical
system under consideration. This diagram allows one to conceptualize more
easily the number of sources that may influence a specific compartment's
concentration and their complex interactions. Here a semantic difficulty
needs clarification. If an organism magnifies a pollutant, its concentra-
tion on a per gram basis is greater than any of its source compartments.
The term "magnify" is non-source specific and includes both food sources
and abiotic exposure. For this discussion, this has been designated as
ecomagnification or eco-accumulation. The classical terminology, in contrast,
has been "biomagnification", based on the assumption that higher concen-
trations in the recipient organism result from food source ingestion only.
This assumption disregards the abiotic exposure via inhalation, adsorption,
or immersion. Therefore, in this presentation, ecomagnification is used
and is based on all potential exposure modes within the ecosystem.
An alternate method of expressing the interactions of biotic and abiotic
components in an ecosystem is shown in Figure 4-6. This matrix form of
interactive notation lends itself to rigorous linear mathematical analysis
and leads to defining the transient or time-based behavior of an individual
67
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ON
00
FIGURE 4-4. GENERAL AREA FOR WHICH GENERIC ECOSYSTEM IS DEFINED FOR PURPOSES OF
ESTIMATING DISTRIBUTION OF POTENTIAL COAL CLEANING POLLUTANTS
-------
VO
-» " ^ -V*'
, '•*,- *16
SURFACE (STREAM.
POND. OR LAKE)
WATER X3
TERRESTRIAL
AQUATIC
(having components F.^ and F1_2) = airborne atmospheric
forcing function, and F2 = aquatic input forcing
function.] Man is shown, but no data are reported.
FIGURE 4-5. COMPARTMENTAL MODEL OF GENERIC ECOSYSTEM AND DOMINANT
PATHWAYS OF POLLUTANT TRANSPORT
-------
Biological Transport
Abiotic
Components
_*"s^
Aquatic
Components
>
Terrestrial
Components
Physical i
Transport \
Biological
Transport'
Abiotic
Components
Aquatic /
Components
Terrestrial
Components
Soil X,
Groundwater X2
Surface Water X3
Sediments X4
Producers X6
Herbivores X,
V
Omnivores X7
Carnivores X8
Decomposers X9
Producers X10
Herbivores X, ,
Omnivores X12
Carnivores X,3
Decomposers X,4
MANX15
x,
»
pi
*
•
(a)
(a)
(a)
•
Xz
*
Ipfs
MMf
W
Xa
(b)
BAN!
•
•
*
•
•
(c)
-------
component or of the entire system. This can be done by expressing the
solution to each compartment's interactions as a differential equation with
respect to time. For example, the rate of change of a pollutant concentra-
tion Xg in compartment 8, the aquatic carnivore, is given by:
~dT = a3-8X3 + V8X6 + S7-8X7 ~ &9-8X9 " a!2-8X12
~ a!3-8X13 ~ a!5-18X15
where Xg is the pollutant concentration in compartment 8, a. _8 represents the
rate transfer coefficients for compartment i to compartment 8, and X. is the
pollutant concentration in compartment i, where i = 3, 6, 7, 9, 12, 13, or 15.
Therefore, compartmental values of pollutant concentration transient
behavior could be predicted if and only if these transfer coefficients
could be defined. The current state-of-the-art of research pertaining to
the designated Priority 1 pollutants and their movement does not yet lend
itself to accurate analysis of this nature.
4.3.2 Pollutant Transfer
During coal cleaning, some contaminants are released and dispersed in
the aquatic and terrestrial environments by means of atmospheric and aqueous
inputs from refuse and coal storage areas, emissions from thermal dryers,
waste water discharge, etc. However, long-term ecological behavior of trace
elements in the biosphere including pathways, rates of dispersion, resi-
dence times in various components of the ecosystem, and chemical transfor-
mations, is largely unknown. Of the Priority 1 pollutants, cadmium, lead,
and mercury represent the most heavily studied. Despite this, information
relative to their rate of ecological transport is scarce. Cycling of
heavy metals — their accumulation and transfer from water to man through
the food chain — often can be brief and potentially dangerous. In addition,
harmful effects on members of ecosystems usually have an indirect impact
on man. For example, Truhart notes:
(1) Food resources are directly affected by immense fish
kills caused by industrial discharge containing toxic
71
-------
materials into rivers or lakes, or by the havoc wrought
to agricultural crops by air pollution.
(2) Agricultural productivity is indirectly affected by
assaults on organisms that have a beneficial function
in the biosphere, such as bees as vehicles for pollen,
or earthworms and other organisms that ensure aeration
of the soil medium.
(3) Production of primary source materials, such as textile-
producing plants and forest cultures, is affected by
industrial discharge.
(4) Toxification of certain constituents of the food chain
results in effects such as the toxification of fish
and the passage of various residues into milk. The
presence of trace amounts of toxic organic contaminants
in drinking water produced from contaminated river water
can pose problems of the same magnitude.
(5) The disturbance of biological balance or ecological
stability can result in disastrous consequences on the
regenerative capacities of the ecosystem and, as a
result, the quality of life as a whole.
Iron, manganese, and selenium are essential elements for biological
activities; however, excessive concentrations have been found to be toxic.
Thus, there is a very delicate balance between the utilization of metals
for important catalytic processes which occur in cells of organisms and
the eco-accumulation of metals to a level that may be toxic to the cell.
The accumulation of heavy metals by organisms is governed by many physio-
logical and environmental factors, many of which are still unknown. Their
toxicity and tolerance is equally complex.
4.3.2.1 Pollutant Uptake in Plants. Terrestrial autotrophs absorb
pollutants via their roots from soil solution and direct adsorption of
atmospheric particles deposited on leaf tissues. Aquatic plants, in
addition to root uptake, absorb pollutants directly from the surrounding
water. The availability and movement of elements and pollutants from soils
and water to plants are not completely understood. Both direct ion
72
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absorption and uptake of organic complexes are involved. Various conditions
and factors influence the uptake of trace elements by plants. These
include:
(1) Chemical form of the pollutant
(2) Concentration of the pollutant in soil or water
(3) Interactions with other trace elements
(4) Genetic constitution of the plant species
(5) Solubility of the pollutant compound
(6) Climatic conditions
(7) Soil characteristics (e.g., pH, texture, till, composition,
and structure)
(8) Cation exchange capabilities of the soil.
The most important condition to consider in determining plant uptake
is the availability of the trace element to the plant. Some soils may
contain high concentrations of pollutants, but transport into plant
tissues may be low due to the pollutants' unavailability. Soils high in
organic matter or clay particles have an affinity for or the ability to
retain large quantities of heavy metals. This decreases the availability
of the heavy metals for plant uptake. In contrast, sandy soils have a
lower capacity to retain heavy metals. This translates into a greater
available concentration for plant uptake. On the other hand, leachability
of heavy metals in sandy soils is greater, therefore reducing the amount
available for plant uptake. These and other factors listed above, to a
greater or lesser extent, influence the availability of trace elements and
other pollutants for plant uptake.
4.3.2.2 Pollutant Uptake/Retention in Animals. Pollutants are
absorbed by animals in one or more of the following ways: inhalation
through the lungs, ingestion through the gastrointestinal tract, direct
absorption through the skin or gills, fetal transfer through the placenta,
and ovarian transfer into the egg. The percent uptake/retention in
animals depends on several factors. These include:
(1) Chemical form of the pollutant
(2) Genetic constitution of the animal species
(3) Concentration of the pollutant consumed or inhaled
73
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(4) Interactions with other trace elements, such as competitive
antagonism among elements with similar properties and
synergistic interactions
(5) Element content in the gastrointestinal tract, such as
in chelated or complexed formations, and in adsorption
on surfaces of insoluble compounds
(6) Feeding behavior of the animal.
Biological transformation can alter the pollutant either by synthesis
or degradation into a form that is more or less available or toxic than
the original form. A noteworthy example of biotransformation is shown in
Figure 4-7 for mercury. In this case, both physical and biological forces
change the form of mercury. In addition, it has been shown that inorganic
mercury can be methylated in bottom sediments contained in fresh water
aquaria to form both mono- and dimethylmercury. It is believed that this
conversion involves anaerobic microbes. Thus, the relatively nontoxic
inorganic and arylmercurials can be biologically converted to the extremely
(18)
toxic methylmercury. The pollutant, in various forms, is released into
the environment from the animal by excretion (urine, feces, or volatili-
zation from the body surface) and by decomposition after the animal's death.
Three mechanisms that are important in the metabolism of a pollutant in an
animal's body are transport, tissue retention, and excretion. These
mechanisms are responsible for the length of time a pollutant remains in
the body. Various pollutants also are retained in specific tissues in the
body; this is evidenced by mercury and cadmium in the liver and kidney and
by lead in bones.
4.3.2.3 Ecological Accumulation and Magnification. Those trace
elements whose concentrations are higher in herbivorous animals than in
plants, higher in omnivorous animals than in herbivores, and highest of all
in top carnivores are said to be ecologically magnified or "accumulated in
food chains". However, these terms, frequently misunderstood, present a
misleading impression of simplicity of these mechanisms. The phenomenon of
eco-accumulation, in fact, is quite complex. The ability of plants to
concentrate metal ions is minimized by a number of factors; ion inactiva-
tion, soil fixation, accumulation at the soil surface above the root zone,
74
-------
Bocleriol oxidollon
Plankton
Plant!
Inorganic
reactions
Mercuric ion.
cheloted cations and onions,
simple complex**,
o«id**, sulphides
Hg(ll)
Bacterial reduction
El*m*ntol mercury
ot vapouj. liquid
or dissolute
Hg (0)
Bacterial oxidotion
Plant*
Inorganic reactions
DispropN>rtionotion and
electro" exchange
Fungi
Plants
Inorganic reactions
Sunlight
Bacteria
"Sunlight
.Bacterial reduction
Fungi
.Plants
Inorganic
Bacterial synthesis
Chtlolion
Bacteria,
conversion by
organic oxidonts
Organo • mercury
compound*
R, R' = alkyl, aryl,
mercopto,
protein, etc.
X * monovolent onion
eg. halide, acetate.
etc
Bacterial synthesis
Chelation
Organic oxidanti
Mercurous ion,
ckelaled cations and onions,
simple complexes
FIGURE 4-7. MERCURY INTERCONVERSIONS IN THE ENVIRONMENT
(18)
Reprinted with permission from
Jonasson, I.R., and Boyle, R.W.,
"Geochemistry of Mercury", Proc.
Soc. Can. Symp., Mercury in Man's
Environment, Ottawa, February 15-16,
1971, p. 5-21.
75
-------
(19)
exclusion at the root zone, and immobility in the root. The term
accumulation refers to the greater trace metal concentration in the plant
(recipient) than in the growth medium (donor).
Terrestrial animals ingest trace contaminants primarily through their
food, or as a result of certain feeding habits, and by inhalation. Aquatic
organisms, such as fish and crustaceans, absorb trace contaminants both
from food and directly from the water in which they are immersed. Aquatic
organisms must process large volumes of water to obtain oxygen so that water
becomes their main route of exposure to toxic materials. Thus, for aquatic
organisms, with the uptake/retention of a pollutant being primarily from
ambient water, there is greater likelihood for eco-accumulation than in
terrestrial organisms, where exposure to pollutants originates primarily
with food sources. However, ecomagnification for terrestrial organisms
does occur (e.g., for mercury and DDT).
According to the equilibrium theory , organisms exposed to constant
levels of toxicants display a rapid initial increase in the concentrations,
which then level off to reach a quasi-equilibrium value. At this concentra-
tion, the rate of toxicant intake is balanced by the rates of excretion
and metabolic breakdown. The lower the rate of excretion, the longer it
takes to reach equilibrium and the higher the ultimate tissue concentra-
tions. In general, larger animals have more difficulty excreting toxicants
due to a lower metabolic rate and a smaller surface-to-volume ratio.
Since predators are usually larger than their prey, a greater concentration
can be expected in the predator. The equilibrium theory has been
questioned since most animals in their natural environment are usually not
exposed to a constant level of pollutant. This is due to the fact that
environmental pollutants are not homogeneously distributed in the environ-
ment. However, pollutants tend to accumulate in biologically productive
areas; thus predators, which usually concentrate their activities in such
areas, can be exposed to high levels of pollutants.
In the past, there has been much controversy and confusion involving
the term magnification. References to biomagnification through a food web
seem to leave the impression that the toxicant is transferred solely
through food sources. Thus, the focal point of the confusion is the
exposure source. It is virtually impossible to delineate between the two
76
-------
routes of exposure in the real environment. Huckabee agrees with the
general feeling that methyl mercury is biomagnified in terrestrial
(22)
ecosystems; however, he argues with Goldwater's^ ' and Peakall and
(23)
Lovett's contention that mercury biomagnifies in the aquatic ecosystem.
Here we avoid the argument by defining the term as ecomagnification, which
includes all sources of exposure. It then becomes clear that ecological
magnification of toxic materials is a phenomenon controlled by numerous
ecological variables, in addition to physiological and physico-chemical
factors.
4.3.3 Designated Priority 1 Pollutants
The review of the literature has been limited to those references
dealing with movement of Priority 1 pollutants for which percent uptake/
retention (on a concentration basis) could be calculated. Information
extracted from these references is listed in Tables 4-1 through 4-8 for
each of the eight elements investigated. The tables are arranged according
to the individual pollutant, and within each table entries are classified
according to the functional component (i.e., abiotic component, terrestrial
producers, terrestrial herbivores, etc.). Functional components lacking
representative samples were omitted. Listed for each entry are the sample
type, source form, percent uptake/retention, additional remarks, and
reference. The sample types are listed by common name, but the scientific
name is listed when given in the reference.
As stated previously, the chemical form of the pollutant in question
is of paramount importance when dealing with ecological transport and fate
problems. In the following narrative sections and tables dealing with the
ecological distribution of Priority 1 pollutants, it may seem as if the
reference is to the elemental form of that pollutant; however, it should
be recognized that an unspecified form of that pollutant is being referred
to. For example, mercury-contaminated fly ash used in plant uptake
experiments or discussion of the toxic effects of beryllium do not neces-
sarily refer to the elemental form of these metals, but rather to an
unspecified chemical form of the pollutant in question.
77
-------
Calculation of values for percent uptake on the basis of concentration
required specific pieces of information. Plant uptake values were calcu-
lated by dividing the concentration of pollutant in the plant by the con-
centration of pollutant in the soil and nutrient solution. For example,
5 ppm cadmium is present in the soil and 2.5 ppm cadmium is present in an
oak tree grown in the contaminated soil; therefore, the percent uptake on
a concentration basis is 50 percent. Animal uptake values were calculated
in a similar manner by dividing the concentration of pollutant in the
recipient by the concentration of pollutant in the food source, water, or
gas to which the animal was exposed. The percent uptake values are
recorded as single values, range values, or a mean value + the standard
deviation. Similar values recorded as concentration factors are most
common in the literature; however, for purposes of these tables, the values
have been recorded as percent uptake/retention. The percent uptake/
retention is equal to the concentration factor times 100.
In addition, such information as type of experiment, mode of adminis-
tration or application, time period, soil characteristics and/or tissue
concentration sampled have been presented as remarks when available or
pertinent. Identifying the type of experiment, either field, laboratory,
or microcosm, can be extremely important when interpreting the percent
(24)
uptake values. In a microcosm study by Huckabee and Blaylock , a radio-
isotope was applied to a model ecosystem. At the termination of the exper-
iment a materials balance was performed to identify target organisms and
sinks. Studies of this type identifying total distribution of a pollutant
within an ecosystem are highly desirable but are extremely scarce.
Microcosm studies should be interpreted from an overall systems view.
f 7 S 9fi 97 )
Laboratory experiments * ' , on the other hand, are usually based on
response of an individual organism to a pollutant. That is, a laboratory
animal is given a contaminated food and after a period of time is analyzed
to determine the pollutant concentration. This type of study examines an
individual's metabolism of the pollutant while the microcosm study examines
the system's metabolism of the pollutant. In field experiments, percent
uptake values are determined from resident pollutant concentrations present
(28 29)
in the environment and biota ' or by spiking the ecosystem with known
concentrations of pollutants and determining concentrations in each
78
-------
compartment. ' ' Information presented as representing standing pool
values was of little use for calculating percent uptake on a concentration
basis in this study. Standing pools of toxicants are represented as the
total amount in any of the ecological compartments (i.e., biomass x con-
centration) .
It should be emphasized that since the conditions and methods are quite
different for each experiment type, differences in calculated percent uptake
values can be expected. The tables are not intended to represent accurate
uptake values, but rather are to be used for identifying concentration
and/or expected magnification within the functional components of a generic
ecosystem of Priority 1 pollutants.
A.3.3.1 Arsenic. Arsenic appears in Group V of the Periodic Table of
Elements which also includes nitrogen, phosphorus, antimony, and bismuth.
Although it is strictly a nonmetal or metalloid, the element in one free
form is commonly referred to as "arsenic metal". It usually occurs in small
quantities in association with other metals and in crystalline rocks,
schists, and coals. Therefore, it is considered as a potential pollutant
in association with the coal cleaning process. The most prevalent chemical
forms are the oxides, arsenates, sulfides, and complexes with other metals.
Research work over the past century has clearly demonstrated that
arsenic is toxic when received either as an inhalant or through food source
(33)
contamination. Most reports have dealt solely with acute exposures
from industries that manufacture products containing high levels of arsenic
(certain war gases or pesticides) rather than chronic (low level) exposures
that one might anticipate from a coal cleaning facility. This makes
references related to arsenic movement within ecosystems usually unavailable
because research has concentrated on the chemical form of input, its
transition chemistry, toxicity, and the analytical methods.
The toxicity of the most common inorganic arsenic form, a + 3 valence,
(34)
varies widely, as reported by Schroeder and Balassa. Bacteria have
been toxified with as low as 290 ppm and as high as >10,000 ppm, whereas
rats and mice have been found to have LD concentrations ranging from 5.8
ppm to 21.0 ppm. The phenomenon of decreasing toxicity as one moves closer
79
-------
to the more rudimentary or fundamental single cellular organisms is not
uncommon in environmental toxicology. Thus, prediction of effective con-
centrations (EC) or permissible release rates is difficult and usually
inaccurate.
Bio-accumulation of arsenical pesticides has been noted by Woolson.
/Og\
Luh, et al., also report bio-magnification to be evident in aquatic food
webs. However, the same argument is posed for arsenic as for all other
Priority 1 pollutants; that is, it has not been clearly demonstrated
whether the increasing concentrations of toxicants as one moves through the
food web result from abiotic exposure or from actual biological ingestion.
Table 4-1 presents the best available data as it relates to antici-
pated distribution of arsenic in a typical generic ecosystem as so defined.
4.3.3.2 Beryllium. There is a strong contrast between the toxic effects
of beryllium released as a result of industrial activities and the lack of
harmful effects of beryllium in natural materials. Beryllium is widespread
in the rocks of the earth's crust and in soils derived from them. The con-
centration of beryllium in soils in the United States ranges from less than
1 up to 7 ppm, with a mean value of approximately 1 ppm. Areas rich in
beryllium are small and usually located away from areas important in food
production. Very little beryllium is released to groundwater during
weathering because of prompt capture by clay particles. The concentrations
(37)
in surface waters of the eastern U.S. range from 0.1 to 0.9 ppb. But
beryllium has been found in coal ash, originating primarily from the organic
matter of the coal, in concentrations as high as 100 ppm.
(27 38}
The toxic effects of beryllium have been documented ' ; however,
very little information exists on its uptake by plants and animals. The
major potential toxic hazard to humans is via the inhalation of beryllium-
containing fumes and dusts that might emanate during processing
(39)
operations. Inhaled beryllium concentrates in the skeletal system and
lungs depending on the compound. However, the highest beryllium con-
centrations are usually associated with the liver, spleen, and bone
marrow.
An inhibiting effect of beryllium on the growth of bush beans was
evident from the dry weight of the plants grown in beryllium solutions of
80
-------
TABLE 4-1. VALUES FOR ARSENIC UPTAKE
oo
Sample
Soil
Water
Water
Water
Water
Sediment
Sediment
Grass (mixture)
Ferns
Fine needles
Agricultural crops
Agricultural crops
Agricultural crops
Source Form
74
Pentavalent As in soil
74
As in water
Arsenic** in water
Arsenic**
AsSO, in solution
AsSO. in solution
Arsenic**
Arsenate in solution
Arsenate in water
Arsenate in soil
Arsenic pesticides in soil
Arsenic pesticides in soil
Arsenic pesticides in soil
Percent Uptake/Retention*
Abiotic Components
66.2-97.1
14.5-16.4
5.0
1.2
10.0
87.0
96.0
Terrestrial Producers
2.14
12.31
8.79
16. 0-0. 10
0.83
1.25
Remarks
Microcosm
Microcosm (sediment)
Field (New Zealand)
Field (Newfoundland)
Field experiment (30 days)
Field experiment (30 days)
Field (Newfoundland)
Field (natural background
study)
Field (natural background
study)
Field (natural background
study)
Field
Field
Field
Reference
42
43
44
45
46
46
45
34
34
34
47
48
49
*0n a concentration basis.
**Chemical form not specified.
-------
TABLE 4-1. (Continued)
Sample
Benthic algae
Algae
Algae
00
ho
Mollusks
Snails and daphnla
Daphnids
Fish
Crustacean and fish
Source Form
Potassium arsenate
Sodium arsenate
14C-Cacodylic acid
Arsenic** in water
Potassium arsenate
Sodium arsenate in water
14C-Cacodylic acid
Arsenic** in water
14
C-Cacodylic acid in water
Potassium arsenate
Sodium arsenate in water
Percent Uptake/Retention*
Aquatic Producers
200
450
3400
Aquatic Herbivores
650
44-86
40-50
Aquatic Omnivores
3.1-5.7
400-700
Remarks Reference
Field 36
Microcosm 50
Microcosm (model ecosystem) 35
Field 36
Microcosm 50
Microcosm (model ecosystem) 35
Microcosm 50
Field 36
* On a concentration basis.
** Chemical form not specified.
-------
various concentrations. ' Beryllium might also be injurious to higher
plants if high levels were dispersed onto soil or into ground and irrigation
waters where plant roots might come in contact with beryllium concentrations
exceeding 1 ppm. Studies by Slonim indicated that the amount of beryllium
concentrated within the bodies of guppies (Lebestes reticulatus) varied
directly with the concentration of beryllium in the surrounding medium and
(27)
to a lesser extent with the exposure period. In general, Slonim's results
indicate that toxicity and lethality may depend on the amount of beryllium
concentrated within the fish but would more likely be due to the effect of
beryllium on a particular target organ or cellular or subcellular component.
According to the data presented in Table 4-2, beryllium accumulates
to a considerable degree in various vegetable crops and in the aquatic
omnivore, Lebestes reticulatus. Beryllium concentrations were noted to be
highest in the root zone of vegetable crops and in the gastro-intestinal
tracts, kidneys, and ovaries of aquatic omnivores. There can be no con-
clusion drawn on the ecological magnification of beryllium in either aquatic
or terrestrial ecosystems; however, the existing data imply that beryllium
concentrations in plants and animals can be greater than those in the
medium.
4.3.3.3 Cadmium. Cadmium may be considered as one of the rarer elements
found naturally in the earth's crust; however, it is fairly accessible mainly
as an industrial by-product. Cadmium, which is always found in association
with zinc, is released as a result of zinc smelting operations and electro-
lytic refining. Many of the forms of cadmium released as a result of these
processes are soluble and biologically active; therefore, they pose a
(52)
serious, potential source for organism contamination. Zinc is an
essential element for biological processes while cadmium is not. Concern
about environmental contamination from cadmium stems from the metal's known
tendency to replace zinc in certain enzymes, thereby altering their
(28)
stereostructure, impairing their catalytic activity, and causing disease.
Cadmium is present in various quantities in soil, water, air, and food. In
non-polluted areas, the concentration of cadmium is reported to be <1 ppm in
soil and <1 ppb in water.
83
-------
TABLE 4-2. VALUES FOR BERYLLIUM UPTAKE
Sample
Source Form
Percent Uptake/Retention*
Remarks
Reference
oo
Alfalfa
Barley
Pea
Lettuce
Bush bean
Bed- in nutrient solution
Bed- in nutrient solution
BeCl. in nutrient solution
Bed- in nutrient solution
Be in solution**
Terrestrial Producers "
1.93 x 102 + 0.72 x 102
3.50 x 102 +0.91 x 102
1.29 x 10 +0.57 x 104
5.48 x 102 +1.57 x 102
7.0 + 102 + 3.80 x 102
4.08 x 104, + 1.01 x 104
6.46 x 10Z + 1.29 x 102
15.4 x 102 + 1.34 x 102
1.77 x 102 + 0.35 x 102
Leaf and stem concentrations 53
Foliage concentration 53
Root concentration
Leaf and stem concentrations 53
Foliage concentration • 53
Root concentration 51
Stem concentration
Leaf concentration
Fruit concentration
Terrestrial Omnivores
Lab rat
Guppy
(Lebistes reticulatus)
BeCl2 in solution
BeSO, in water
< 0.2
Aquatic Omnivores
1.216 x 102 + 0.95 x 102
Laboratory, administered
by stomach tube
Laboratory
26
27
* On a concentration basis.
** Chemical form not specified.
-------
There have been numerous studies documenting the toxicity of cadmium
to plants and animals. However, there is little information in the liter-
ature related to the behavior of cadmium in ecosystems and to its transport
through food webs. Cadmium is relatively immobile in both terrestrial and
aquatic environments. According to the data presented in Table 4-3, the
greatest proportion (98.9 percent) of the cadmium remains in the soil and
litter, and of the cadmium introduced into the aquatic environment, 92
percent remains in the sediment. In ecosystems subject to various inputs
of cadmium, those animals whose food base is in the soil and litter or
detritus are most susceptible to contamination. The terrestrial decomposers,
earthworms and woodlice, substantiate this susceptibility by displaying
2 3
uptake values ranging from 1.9 x 10 percent to 1.74 x 10 percent. In
addition, the crayfish whose food base is in the detritus also shows signs
of ecological magnification of cadmium. However, this phenomenon is due
solely to direct uptake from the water environment. Ecological magnifi-
(52)
cation of cadmium in a grassland arthropod food chain does not occur.
Field crickets accumulated 60 percent of the cadmium concentration found in
the contaminated vegetation and the predatious wolf spider accumulated
only 70 percent of the cadmium found in the crickets. Ecological magnifi-
(54)
cation of cadmium is evidenced in the aquatic environment. Martin
states that cadmium concentrations in zooplankton are more than 6000 times
that in water. In addition, concentrations in algae are 100 to 1000 times
that in water. 5'
As shown in Table 4-3, producers, in most cases, do not ecomagnify
cadmium. Pollutant uptake by plants, as mentioned in a previous section,
depends on many factors. In a radiotracer study of cadmium behavior in
aquatic and terrestrial ecosystems, two chemical forms of cadmium were
tested. The water soluble CdCl was found to have a greater avail-
ability for uptake than the water insoluble CdO. Uptake of trace elements
in soil by plants is highly dependent on the equilibrium of the chemical
activity of cations in the soil solution. It is important to measure the
free ion in solution to estimate availability. Cadmium uptake from soil
by plants was found to be greater in acid soils and lower in organic soils
than in mineral soils; however, organic acids from decaying leaf litter
85
-------
TABLE 4-3. VALUES FOR CADMIUM UPTAKE
cx>
Sample
Soil
Source Form
109
CdCl2 in solution
ino
CdCl_ in solution
115
CdCl, in solution
CdCl2 in solution
1 OQ
1 *CdCl2 in solution
Percent Uptake/Retention*
Abiotic Components
98.9 + 1.2
95.7 + 3.7
85.5
88.4 + 2.7
91.2
Remarks
Field, spray application to
clipped plot
Field, spray application to
undipped, vegetated plot
Microcosm, applied as
simulated rainfall, 27 days
Microcosm, applied as
simulated rainfall, 70 days
Field, applied as simulated
rainfall, 6 months
Reference
56
24
57
31
Sediment
Water
Moss
Higher plants
Grass
Grasses, forbes, and
goldenrod
115
CdCl0 in solution
115
CdCl« in solution
115
115
CdCl. in solution
CdCl, in solution
Cd from automobile
emissions in soil **
109
CdCl- in solution
92.47 + 1.82
6.07 + 0.26
Terrestrial Producers
9.2 + 1.4
0.20 + 0.14
127.0 +33.0
19.8 + 5.8
0.71 + 0.75
3.25 + 1.82
Microcosm, transport from a 24
terrestrial microcosm, 27 days
Microcosm, transport from a 24
terrestrial microcosm, 27 days
Microcosm, 27 days 24
Microcosm, 27 days 24
Field, soil pH 5.9 28
Field, soil pH 7.1
Field, applied as simulated 31
rainfall, clipped plots
Field, applied as simulated
rainfall, undipped plots
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-3. (Continued)
Sample
Old field vegetation
Vegetable crop
Soybean
oo Oat shoots
Wheat
Oak tree
Sweet clover
Rabbit
Sheep
Cow
Goat
Grasshopper
Source Form
CdCl2 In solution
Cd in soil**
11sCd in soil**
1 Cd in solution**
Cd in soil**
Cd in soil**
Cd in litter-soil**
Cd in fly ash**
Cd in iron dust**
CdCl2 in feed
CdCl2 in feed
109CdCl2 in feed
Cd in vegetation**
Percent Uptake /Retention*
2.0 + 0.9
6.9 + 1.9
141.26 + 24.0
15.78
1.93
34.8-41.3
39.2-66.2
167.9 + 159.3
34.9 + 0.5
25.4
Terrestrial Herbivores
*> 30.0
5.3
18.0
-v 2.0
^ 130
Remarks
Field, spray application to
clipped plots, 1 month
Field, spray application to
undipped plots, 1 month
Field
Field, root uptake from soil
Field, foliage application
and uptake
Field, 46 ppm applied in soil
Field, 1.3 ppm applied in soil
Field
Field
Field
Laboratory, inhalation
Field
Reference
56
58
59
32
60
61
62
63
64
65
66
67
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-3. (Continued)
Sample
Lab rat
Lab rat
Lab mouse
Lab mouse
Lab mouse
Lab mouse
Lab mouse
Chipping sparrow
Field cricket
Cog
Wolfe spider
Predatory arthropod
Source Form
109
*CdCl2 in solution
115CdN03 in solution
CdCl- in gaseous form
109Cd**
109
CdCl- in solution
109
CdCl2 in solution
115CdCl2 in solution
Wild bird seed soaked in
109Cd solution**
Vegetation grown in
109cd solution**
CdCl2 in gaseous form
Crickets fed on
109cd-grown vegetation**
Cd in prey**
Percent Uptake/Retention*
Terrestrial Omnivores
0.5-8
1-2
10-20
0.5-3.0
4.5-12
1.0-2.3
1.6
7.3
2.7
8
60.9
Terrestrial Carnivores
•v 40
71.4
124.0 + 93.5
Remarks
Orally administered, 4 hours
Administered by stomach tube,
24 hours
Inhalation
Stomach injection, 11 hours
Stomach injection, 164 hours
Orally administered, VL5 days
Orally administered, 24 hours
Orally administered, 48 hours
Ingestion, 20 days
Ingestion, 30 days
Inhalation
Ingestion, 30 days
Field, ingestion
Reference
68
69
70
71
72
25
73
74
52
75
52
76
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-3. (Continued)
Sample Source Form
Earthworm Cd in soil**
Earthworm Cd In soil**
Earthworm Cd in soil**
Woodlouse Cd in litter-soil**
Arthropod litter Cd in litter**
oo consumer
vo
Watercress 115CdCl2 in water
Snail 115CdCl2 in water
(Goniobasis clavaefor
clavaeformis)
109
Crayfish CdCl, in water
(Orconectes propinquus)
Fish 115CdCl2 in water
(Gambusia af finis)
Percent Uptake/Retention* Remarks
Terrestrial Decomposers
3 3
1.74 x 10 + 0.42 x 10 Microcosm
1.03 x 103 + 0.03 x 103
1.63 x 103
4.96 x 102 + 1.90 x 102
36.8 + 18.4
Aquatic Producers
< 2.06 Microcosm, 27 days
Aquatic Omnivores
< 2.25 Microcosm, 27 days
1.84 x 105 Field
Aquatic Carnivores
< 2.25 Microcosm, 27 days
Reference
30
77
78
54
76
24
24
79
24
*0n a concentration basis.
**Chemical form not specified.
-------
increases solubility and subsequent transport of heavy metals ^80\ Data
presented by Miller, et al. show a cadmium uptake by corn plants higher
than values reported in most literature. This may have been due to the low
ion exchange capacity of the sandy loam soil used in the experiment. A
change in soil pH from 5.9 to 7.1 decreased the percent cadmium uptake from
( 2.8)
127 percent to 20 percent. In the absence of iron chelates there was
no difference between cadmium uptake from pH 4 and pH 6 soil solutions,
while in the presence of Fe DTPA, plants grown in lower pH soil had a
significantly greater uptake. Also, the addition of zinc to cadmium con-
/OON
taminated soils decreased the availability of cadmium for plant uptake.
Cadmium is predominantly released from industrial activities as an
atmospheric aerosol, with the airborne particulates containing cadmium
being deposited on the surface of soils and plants by rain, snow, or as
particulate fallout. In grain crops, cadmium absorption via the foliage
from airborne particulates is not as serious as absorption via the root
(59)
systems from contaminated soils. However, it is important to remember
that those crops consumed by either man or animals are continuously exposed
directly to atmospheric contamination. Cadmium is absorbed and retained to
a considerable degree in the body of animals following inhalation. The
absorption is primarily directly from the lungs. Animal experiments have
shown that absorption is between 10 and 40 percent of the inhaled cadmium.
A considerable difference might well exist for different cadmium
compounds.
There are no clear indications from the data presented in the litera-
ture of any differences in the cadmium uptake of herbivorous and carnivorous
animals. Body concentrations of cadmium are greatest in the liver and
kidneys. Cadmium retention from gastrointestinal absorption is
(83)
greater for acute doses than for chronic doses. Dietary factors have
been shown to influence uptake and retention of cadmium in animals.
Laboratory rats on a low calcium diet accumulate 50 percent more cadmium
f 85)
than rats on a high calcium diet . Mice on a low protein diet had
(72)
higher levels of cadmium than mice on a high protein diet. Cadmium
will be found in blood, internal organs, and excreta after absorption
following exposure via air, oral intake, or injection.
With increasing amounts of cadmium entering the biosphere, it is
important to examine the uptake and elimination of this element in organisms
90
-------
and to relate elemental cycling processes to food web dynamics. An under-
standing of these mechanisms would allow predictions of the concentrations
of cadmium in the various ecological compartments.
4.3.3.4 Iron. Iron ranks second to aluminum in abundance in the earth's
crust. Depending on the season, river water concentrations of iron may range
( 86)
up to several parts per million. Iron exists in the environment in close
association with sulfur. It is sufficiently stable to exist in the free
state and its compounds may be in either of two oxidation states, both of
which can form readily under natural conditions.
Iron is an essential element-; it is vital for both plants and animals.
In higher animals the blood pigment, hemoglobin, contains an iron complex.
Iron may also be present in some enzymes. The iron bacteria (general
Leptothrix, Gallionella, and Spirophyllum) accumulate ferric hydroxide in a
sheath as a part of their cell structure. Phytoplankton exhibit a capacity
to concentrate iron up to 100,000 times the concentration in water.^
There are other species that have the ability to ecomagnify iron, but a
true understanding of this system remains obscure.
Referring to Table 4-4, terrestrial plants and animals show very low
percent uptake values; however, macrophytes and whitefish ecomagnify iron
in the aquatic environment. Their most significant route for uptake seems
to be by absorption from the water environment rather than transfer through
food sources.
4.3.3.5 Lead. Large quantities of lead are used each year in the United
States. The largest consumer is the electric-storage battery industry (39
percent), followed by the petroleum industry which uses 20 percent of the
total for gasoline additives. The amount of lead released into the atmosphere
over the United States is measured in hundreds of tons per day, of which 98
percent can be attributed to the combustion of gasoline. Since lead from
automobile exhaust is an important source of lead contamination, many
(88 89 90 91)
studies involve roadside ecosystems. ' ' ' In addition, lead
smelters have been investigated as a major contributor to environmental
lead contamination. ' The concentration of lead in the atmosphere
is highly variable depending on vehicular density and climate. Much of
91
-------
TABLE 4-4. VALUES FOR IRON UPTAKE
Sample
vo
ho
Sweet Clover
Cotton rat
Assassin bug
(Triatomid)
Macrophyte
Whitefish
Source Form
Percent Uptake/Retention* Remarks
Fe in fly ash **
59.
,**
Fe tagged lettuce
59
Fe in hemoglobin
injected in chicken**
Fe in water**
Fe in water
**
Terrestrial Producers
0.51
Terrestrial Herbivores
1.5
Terrestrial Carnivores
-v2.0-3.0
Aquatic Producers
3.6 x 105~ (wet weight)
2.3 x 105
Aquatic Carnivores
1.4 x 104 (wet weight)
1.5 x 10^ (x^et weight)
Field
Laboratory, absorbed in
tissue after 15 hours
Laboratory, 87 days
(blood sucking and/or
insectivorous)
Field
Field, muscle concentration
Field, bone concentration
Reference
62
92
93
29
29
* On a concentration basis.
** Chemical form not specified.
-------
the lead in the air is removed by aggregation and precipitation. The usual
(94)
range of lead in soils is from 2 to 200 ppm. A majority of the lead
in the aquatic ecosystem is insoluble and apparently ends up in the sedi-
ments.
Soil lead is largely unavailable for uptake by plants; only 0.003-
0.005 percent of the total lead in soil is available for such uptake.
Lead can be accumulated in plants from air and soil, but it rarely
ecomagnifies. In an exception to the rule, however, fungi in a laboratory
experiment concentrated lead at 34 times the concentration in the culture
(95)
medium. A majority of the lead deposited on vegetation from the atmo-
sphere can be removed by washing ' . Translocation of lead from the roots
(97)
is highly variable depending on soil characteristics and plant species
Most of the lead seems to accumulate in the root system, with significantly
(98)
lower levels in the stems and leaves. The edible portion of exposed
vegetable plants contains only slightly more lead than control plants, but
(99)
the non-edible portion contains 2 to 3 times as much lead . The for-
mation of organic chelates may make lead more mobile in the soil but less
>le pi
.(98)
available to plants. The level of available phosphorus in the soil
also affects lead uptake in a variety of plants
Lead is a non-essential, cumulative element, which is stored mainly
in the bones and kidneys. A low intestinal absorption (less than 5
percent) was noted in cattle six days after ingestion of lead-203 spiked
grain feed. In a study involving levels of lead in roadside animals,
inhalation of lead sorbed on particles was demonstrated to be another
important avenue of intake/ ' Even though high concentrations of lead
are retained in the soil (97 percent), soil decomposers, such as the
earthworm and arthropod litter consumers, do not ecomagnify lead (Table 4-5)
However, lead is ecomagnified from the herbivore to carnivore-trophic level
in arthropod food webs. ' In the vicinity of lead mining and milling
operations in Missouri, there was no magnification of lead found in the
grazing food chains involving aquatic vegetation heavily laden with
lead. Leland and McNurney , in a study on distribution and
bioaccumulation of lead in a river ecosystem, found higher lead concentra-
tions in detrital feeders and herbivores than carnivores. Aquatic
93
-------
TABLE 4-5. VALUES FOR LEAD UPTAKE
vo
Sample
Soil
Lichens
Fungi
Vegetable crop
Corn
Soybean
Lettuce
Lettuce
Oats
Oats
Source Form
Pb in aqueous slurry**
Pb in soil**
Pb in culture median**
Pb in soil**
PbCl2 in soil
PbCl2 in soil
Pb (N03)2 in soil
PbCl2 in soil
Pb(N03)2 in soil
PbCl2 in soil
Percent Uptake/Retention*
Abiotic Components
•\. 97.0
Terrestrial Producers
4.0
125.0
3.4 x 103
31.49 + 52.32
45.0
15.1
10.9
14.1
4.0
11.4
5.7
Remarks
Microcosm
Laboratory, soil
concentration - 27,500 ppm
Laboratory, soil
concentration - 20 ppm
Laboratory
Field
Shoots
Roots
Tops
Reference
105
106
95
58
107
107
96
108
96
108
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-5. (Continued)
Sample
Source Form
Percent Uptake/Retention*
Remarks
Reference
Cattle
Predatory arthropod
Earthworm
Earthworm
Woodlouse
203,
'Pb in feed**
Pb In prey**
Pb In soil**
Pb in soil**
Pb in litter-soil**
Arthropod litter consumer Pb in litter**
consumer
Bulrush
(Scirpus americanus)
Spike rush
(Eleochaus smallii)
Pitchforks
(Bidens cernera)
Mayfly
Stonefly
Pb in solution**
Pb in solution**
Pb in solution**
Pb(N03)2 in solution
Pb(N03)2 in solution
Terrestrial Omnivores
< 5.0
Terrestrial Carnivores
116.0 + 29.0
Terrestrial Decomposers
17.4
95.0 + 25.0
60.0 + 14.8
7.0 + 2.0
Aquatic Producers
3.6 x 103
5.9 x 104
2.3 x 104
2.2 x 105
9.3 x 103
4.2 x 104
Aquatic Herbivores
11.82 x 105 +2.57 x 105
Aquatic Omnivores
4.29 x 104 + 1.39 x 104
6 days
Field, ingestion
Stem, laboratory
rhizome
Stem, laboratory
rhizome
Stem, laboratory
rhizome
Laboratory
Laboratory
101
76
56
77
54
76
109
109
109
110
110
* On a concentration basis.
** Chemical form not specified.
-------
organisms display ecomagnification of lead in solution; however, the
occurrence of this phenomenon is most likely due to direct uptake of lead
in solution and not to transfer in the food web.
4.3.3.6 Manganese. Manganese, the twelfth most abundant element, con-
stitutes about 0.10 percent of the earth's crust. Manganese is next to
iron in the periodic series, similar to it in its chemical behavior, and often
closely associated with it in its natural occurrence. Total manganese in
the soil ranges from <1 ppra to 7000 ppm with a geometric mean of 340 ppm .
Manganese in soils reflects the influence of rock sources as soil parent
materials and the nature of unconsolidated deposits on which soils are
formed, as well as manganese losses through soil weathering. The manganese
ppm t<
(114)
content of groundwater ranges from <0.01 ppm to 0.87 ppm and natural
waters generally contain 0.2 ppm or less.
Manganese deficiencies and toxicities are well documented for a wide
range of plants ; however, data dealing with percent uptake and ecologi-
cal transport are scarce. Manganese in the ecosystem has well established
lines of movement from rocks to soils to plants to animals, from soils to
water, to organisms and back to water and soils. It has been shown that
marine organisms can concentrate manganese in their bodies to many times
the concentration in water. In addition, there are less apparent move-
ments of manganese under natural conditions among the components of the
ecosystem. The existence of both passive (nonmetabolic) and metabolically
dependent pathways of manganese uptake have been recognized. In the
presence of excess manganese, uptake continues with a consequent build-up
in various vegetative parts of the plant. Most plants can tolerate internal
manganese concentrations up to 200 ppm without showing adverse effects.
The availability of manganese to plants from soils can be evaluated by
determining the amount of secondary manganese released from various soil
extractants. The secondary forms, in general, are amorphic and represent
the bulk of the active manganese fraction in soil.
Many factors will affect the availability of manganese in soil and
subsequent uptake by plants; these include concentrations of other cations
and total salts, pH, cation exchange capacity, drainage, organic matter
content, temperature, compaction, and microbial activity.
96
-------
Plants apparently absorb manganese primarily in the divalent state.
Lowering the soil pH or reducing soil aeration by flooding or compaction
favor the reduction of manganese to this form and thereby increases its
solubility and availability to plants. The addition of organic matter to
soils generally reduces the availability of manganese for plant uptake.
A reduction in the population of manganese-oxidizing organisms may increase
manganese solubility.
Of the trace elements found in the environment, manganese is among
the least toxic to mammals and birds. Manganese is an essential
mineral for nearly all organisms. Most animals can tolerate concentrations
of manganese ranging from 500 to 4,920 ppm without evidence of ill effects.
Large fluctuations in dietary intake do not result in appreciable changes
in the tissue concentrations. Manganese was absorbed in experimental
animals following the inhalation of automobile exhaust, as indicated by
increased tissue concentrations. Higher concentrations of manganese
are usually associated with the pigmented portions of the body, pituitary
gland, pancreas, liver, kidney, and bones.
The data presented in Table 4-6 seem to indicate that manganese is
ecologically magnified in macrophytes and fish in the aquatic environment.
This magnification is due to a direct uptake from the water rather than to
transport within the food web.
4.3.3.7 Mercury. Mercury is a relatively rare element and there are
comparatively few places in the world where it occurs naturally in more than
trace amounts. Essentially, the range of mercury in waters in the U.S. is
from 0.5 ppb to 10 ppb with the great majority of waters having concentrations
of less than 1 ppb. The natural background levels of total mercury in
surface and groundwaters is well below 0.5 ppb. The largest use of mercury
is in the production of electrical apparatus and in the electrolytic prepara-
tion of chlorine and caustic soda. Organic-mercury fungicides have had
enormous economic importance since the 1940's in the prevention of seed
borne diseases of cereals and flax. Besides the direct use of mercury by
man, other activities such as the burning of fossil fuels and land altera-
tions causing erosion increase the cycling of mercury in the environment.
97
-------
TABLE 4-6. VALUES FOR MANGANESE UPTAKE
Sample
Source Form
Percent Uptake/Retention* Remarks
Reference
oo
Sweet clover
Lab rat
Macrophytes
Whitefish
Mn in fly ash**
Terrestrial Producers
13.80
Terrestrial Omnivores
54
Mn orally administered** 4.0
Mn in water**.
Mn in water **
Aquatic Producers
1.5 x 10^- (wet weight)
1.4 x 102-
Aquatic Carnivores
3
1.0 x 10 (wet weight)
1.0 x 105 (wet weight)
Field 62
Initially absorbed 120
Field 29
Field, muscle concentration 29
Field, bone concentration
* On a concentration basis.
** Chemical form not specified.
-------
The toxic effects of mercury on aquatic and terrestrial organisms,
including man, have been recognized for centuries. In recent years, high
mercury concentrations in the food supply of man, causing neurological
disorders, e.g., the Minamata disease in Japan, have been discovered. This
awareness of the potentially harmful effects has led to a need for an
understanding of mercury's behavior in the environment, in both aquatic and
terrestrial subsystems. This need has been partially fulfilled, primarily
by studies dealing with mercury in the aquatic system. However, the
dynamics of the movement of different forms of mercury in aquatic or
terrestrial food webs and the relative contributions of the direct uptake
component and the trophic component to mercury body burdens in organisms
are largely unknown.
Most of the mercury reaching surface waters is deposited in the
sediments and subsequently remobilized slowly by microbial and chemical
(121 122)
processes ' y (see Figure 4-7). The concentration of mercury
increases from the shallow, near-shore, coarse sediments to the central,
deep-water-basin sediments of fine silty clays. This is because smaller
particles have a greater surface-area-to-volume ratio and a greater
(123)
adsorption affinity for mercury. The biological cycle of mercury from
sediments to waters by benthic organisms and by rooted aquatic plants has
(122) (124)
been investigated. ' According to Wood , the interconversions of
mercury compounds are manifested by a dynamic system of reversible reac-
tions, leading to a steady state concentration of methyl mercury in
sediments. These interconversions can be catabolized by microorganisms.
Although mercury is released into the environment in several organo-mercury
compounds or inorganic forms, conversion to the methyl form frequently
occurs as a result of bacterial action.
Ecological magnification of mercury was noted in soil fungi
(Aspergillus niger and Penicillum notatum), in aquatic plants (Elodes densa
and Myriophyllum spicatum L._), and in organisms (Gambusia affinis and
Carassius auratus) (see Table 4-7). Hardcastle and Mavichakana^
monstrated fungal uptake of mercury as an important aspect of food chain
contamination. Mercury uptake by the fungi varied according to the specific
mercury compound present and the mercury concentration in the nutrient
cultures. A greater uptake of mercury in the fungi was shown for inorganics
99
-------
TABLE 4-7. VALUES FOR MERCURY UPTAKE
Sample
Source Form
Percent Uptake/Retention*
Remarks
Moss
Grass
o Forbes
Soil fungi
(Aspergillus niger and
Penicillium notaturn)
Forbes, grasses, and
goldenrod
Sweet clover
Rooted plant
(Elodea densa)
Water milfoil
(Myriophyllum specatum
specatum L.)
203
Kg-tagged fly ash
**
203Hg-tagged fly ash**
203Hg-tagged fly ash**
203HgCl2 and CH3203HgCl
in nutrient culture
Terrestrial Producers
0.075
0.11
0.09
1.09 x 104 + 0.49 x 104
203
Hg(1103)2 in simulated rain 0.64 ± 0.50
2.73 + 2.08
Hg in fly astf*
CH 203HgCl and 2°3HgCl2
solution
Organic and inorganic Hg
in solution
8.64
Aquatic Producers
5.19 x 106 + 3.35 x 106
2.21 x 104 + 1.76 x 104
Reference
Soil-litter
Sediment
Sediment
203
Hg- tagged fly ash **
203
HG-tagged fly ash**
Abiotic Components
46.3
99.6
97.0
Microcosm, 139 days
Microcosm, 139 days
24
24
127
Microcosm, 139 days 24
Microcosm, 139 days 24
Microcosm, 139 days 24
Laboratory 126
Field application, 165 days 31
on clipped plots
Field application, 165 days
on undipped plots
Field 62
Laboratory 127
Laboratory, 8 days 122
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-7. (Continued)
Sample
Source Form
Percent Uptake/Retention*
Remarks
Reference
Goldfish
(Carassius auratus)
Snail
Fish
(Gambusia affinis)
Fish
(Gambusia affinis)
HgCl2 in solution
203.
203,
Hg-tagged fly ash
**
Aquatic Omnivores
1.14 x 10* + 1.03 x 104
Hg-tagged fly ash** 0.13
Aquatic Carnivores
0.02
Hg° and HgCl2 in solution 2.1 x 104
Laboratory, 81 hours
Microcosm, 139 days
Microcosm, 139 days
Laboratory, 24 hours
128
24
24
129
* On a concentration basis.
** Chemical form not specified.
-------
than organics; however, organics display greater toxicity. The percent
uptake of mercury is greater at lower environmental concentrations;
therefore, some organisms can accumulate significant amounts even on
f-\ OQ \
exposure to very low trace concentrations. Mosses do not assimilate
minerals and water from soil but rather derive most of their constituents,
including heavy metals, from the atmosphere . Mercury ions dissolved
in run-off water will accumulate in Dicranum scoparium (a mat-forming moss)
if the water contacts any part of the plant. Mercury bound in the soil
was not available for uptake by the moss, but soil mercury was evidently
mobile and leachable by groundwater. Mercury accumulation in vegetable
crops is notably in the root portions. The mercury concentration in leaf
lettuce, spinach, broccoli, cauliflower, peas, oats, radishes, and carrots
was higher in the root portions than the above-ground portion. The
remaining terrestrial producers, for the most part, exhibit low percent
uptake values.
Mercury uptake directly from the water medium is evidenced by percent
uptake values of 5.2 x 10 for rooted aquatic plants, 2.21 x 10 for water-
4 4
milfoil, 1.14 x 10 for goldfish, and 2.1 x 10 for fish. Of the mercury
in Swedish pike, 50 percent was shown to come directly from the water
(132)
rather than from the food chain. Mercury was found to concentrate
(128)
initially in the external mucous secreted by fish. Additional factors
influencing mercury uptake in fish include water hardness, temperature, pH,
volume and associated heavy metal ions. Mercury levels in predacious
fish (smallmouth bass, rock bass, green sunfish, and yellow bullhead) were
shown to be two to three times greater than mercury levels in non-predacious
(123)
fish (white suckers, carp, common shiners, and chubs). The predators
appear to accumulate higher concentrations of mercury from their diet
because of their position in the food chain; however, predators have higher
rates of respiration so greater mercury accumulation may occur due to
higher gill irrigation during respiration.
Fish accumulate mercury in aquatic environments, while fish-eating
birds may play a major role in transmitting mercury into the terrestrial
food chain. Mercury levels in two fish eaters, great blue heron and common
tern, far exceeded mercury levels in other species. Very high mercury
concentrations, up to 17.4 ppm in the liver, were found in fish-eating
102
-------
birds' . Osprey feed almost entirely on fish (^ 99 percent of diet), and
mercury concentrations in their body tissues appear to be three to five
times those of the fish on which they prey. ' In addition, increased
levels of mercury concentrations in animals of the terrestrial food chain
have been recognized with seed-eating species ingesting methyl mercury-
/QO\
contaminated seed.
Mercury concentrations appearing in the body accumulate to the greatest
degree in the liver and kidney/13 ' Mercury retention from inhalation
ranges from 10 to 100 percent, depending on the chemical form, aerosol
particle diameter, and density. ' Daily consumption of fish containing
5 to 6 ppm mercury may be lethal to humans.
In summary, there is evidence of ecological magnification of mercury
through the food web in both the aquatic and terrestrial food chain.
However, to speak of aquatic food web accumulation without quantification
of mercury uptake directly from the water may not be realistic. Aquatic
organisms accumulate mercury directly from the water medium and because of
their position in the food web, such as is the case with osprey and other
fish eating species. There is a need for detailed study on this subject.
4.3.3.8 Selenium. Selenium is erratically dispersed in geologic materials
but is usually associated with sulfur and sulfur compounds in sandstone, lime-
stone, and other sedimentary rocks. Average concentrations of selenium in
the earth's crust range from 0.03 to 0.8 ppm. The selenium content of
black shales and coal is 10 to 20 times the concentration in the earth's
crust. The selenium concentration in soils varies with the selenium con-
tent of the parent material. Selenium concentration in river water in the
United States is normally less than 0.5 ppb .
Interest in selenium in the environment and in human diets has
increased in recent years. Selenium has been shown to be an essential
element when present in trace concentrations but to be a toxicant when
present in greater quantities. The occurrence of selenium at toxic
concentrations in a number of species results from the movement of selenium
from highly seleniferous soils through plants to animals. At the other
end of the physiological scale, selenium is necessary for the prevention
of various degenerative processes, including white muscle disease in
103
-------
ruminants. Another reason for increasing interest in selenium stems from
high selenium concentrations discovered in coal fly ash. It is possible
that coal mining and combustion constitute the major movement of selenium
in North America . However, the selenium in fly ash has been found to
be present as elemental selenium, a form which is ordinarily only slightly
available to plants or to animals from ingested food.
Selenium is relatively mobile in the terrestrial environment in
comparison with the other contaminants of this study. Two references
cited in Table 4-8 report 68 and 76 percent of applied selenium retention
in the soil. However, as much as 99 percent of the selenium introduced
into the aquatic environment accumulates in the sediments. The secondary
sources of selenium are biological sinks in which selenium has accumulated.
The presence of above-average amounts of selenium in soils does not always
affect the uptake of selenium by all plants or, consequently, its presence
in the diet of animals. However, selenium accumulator plants (plants that
concentrate high levels of selenium) can contain selenium concentrations
that are toxic to animals. Plants are usually more tolerant to excessive
levels of selenium than are animals. The availability of selenium to
plants from soil is determined by various factors; these include the
chemical form of selenium in the soil, content of organics and clay in the
soil, soil pH, and interactions with other compounds such as phosphates and
sulfates in the soil. In general, plants may contain from 0 to 10 ppm
selenium; however, concentrations in accumulator plants may range from 50
to 100 ppm. According to Gissel-Nielson and Bisbjerg , elemental
selenium is generally not available for plant uptake. In addition,
selenate forms are much more soluble in soils and more available to plants
than selenite forms, and the danger of producing,plants containing toxic
levels of selenium is much greater with selenates than with selenites.
Thus, there is not necessarily a direct relation between the total selenium
concentration in the soil and .its concentration in plants.
Animals retain 25 to 70 percent of the dietary selenium consumed
Factors influencing retention include body stores of selenium as well as
the chemical form of selenium present in the diet. In reference to
selenium requirements and toxicity, it appears desirable to maintain the
104
-------
TABLE 4-8. VALUES FOR SELENIUM UPTAKE
Sample
Soil
Soil
Water
Sediment
M
g Pasture herbage
Ryegrass
Sweet clover
Clover
Barley
Mustard
Plants
Source Form
Sodium selenate solution
75SeO,
Ł
75Se02
75Se02
Sodium selenite solution
Se in soil**
Se in fly ash**
Se° .
Selenites
Selenates
Se°
Selenites
Selenates
Se°
Selenites
Selenates
75SeO,
f.
Percent Uptake/Retention*
Abiotic Components
68.0
75.6
-v 0.7
99.0
Terrestrial Producers
•v 1.0
< 2.0
13.96
0.005
1.0
46.7 + 20.3
0.02
1.0
22.3 + 9.0
0.07
1.1
44.3 + 18.8
8.0
Remarks
Field, top 9 Inches
Microcosm, applied as
simulated rainfall, 56 days
Microcosm, 56 days
Microcosm, 56 days
Field
Field
Field
Laboratory
Laboratory
Laboratory
Microcosm, applied as
simulated rainfall, 56 days
Reference
139
24
24
24
139
140
62
138
138
138
24
* On a concentration basis.
** Chemical form not specified.
-------
TABLE 4-8. (Continued)
Sample
Sheep
Sheep
o Swine
Lab rat
Lab rat
Snail
(Goniobasis
clavaefonnis)
Fish
(Gambusia affinls)
Source Form Percent Uptake/Retention*
Terrestrial Herbivores
75Se** 35.0
Se-selenious acid ^49.0
Terrestrial Omnivores
75Se** 85.0
Selenite-75 > 50.0
Wheat containing selenium ^ 40.0
Aquatic Omnivores
75Se02 < 0.1
Aquatic Carnivores
75Se02 < 0.1
Remarks
Wet absorption
Laboratory, introduced into
rumen, 72 hours
Net absorption
Laboratory, in carcass
Laboratory, 6 weeks
Microcosm, 56 days
Microcosm, 56 days
Reference
141
142
141
143
144
24
24
* On a concentration basis.
** Chemical form not specified.
-------
selenium concentration in human and animal diets in the range of 0.05 or
0.1 to 3 or 4 ppm.(137)
Referring to the data in Table 4-8, selenium does not appear to magnify
in any of the ecological components. The greatest absorption of selenium
was shown by swine, with a net absorption of 85 percent. The maximum
uptake in plants was 47 percent by clover. The interactions of
selenium in soils, plants, and animals are exceedingly complex and difficult
to predict; thus, future research dealing with the transport of selenium
from soils to plants to animals is needed.
4.3.3.9 Other Pollutants. As noted in the introduction of this section,
nitrogen and sulfur were not considered relevant to the objective of this
portion of the study. More specifically, sulfate sulfur, sulfur dioxide,
nitrate nitrogen, and nitrogen oxides were not included. Both elemental
sulfur and nitrogen are considered to be commonly occurring and biologi-
cally essential macro-nutrients to all living organisms. Neither element
is known to accumulate in any of the biological compartments in concentra-
tions that are toxic or in excess of that which is normally found in the
environment. Therefore, the concern involving these compounds is not their
potential accumulation or magnification through a food web, but either the
problem of direct contact toxicity or the problem of resultant chemical
changes effected by these pollutants on the abiotic components. The Copper
Basin at Copperhill, Tennessee, is a prime example of the problems of both
direct contact toxicity and long-term abiotic chemical changes resulting
from extremely high sulfur dioxide emissions on a terrestrial ecosystem.
4.3.4 Pis cus s ion
The objective of this preliminary study of ecological transport and
distribution was to review and. identify the current state-of-the art on the
likelihood of environmental transport within a generic ecosystem of certain
specific pollutants that might be generated by a coal cleaning facility.
In each section, the specific discussions (1) relate to the individual
pollutants under consideration and the parameters controlling the transport
and the ultimate ecological fate of each pollutant and (2) deal with the
107
-------
problems encountered and the limitations to be imposed on extrapolation
from the data reported.
All of the pollutants considered in this study have been found to be
toxic to living systems above certain concentrations . . However, the
concern here was whether or not those levels of reported toxicity are
likely to be reached through normal environmental exposure. That is, even
if the source release rate for a specific pollutant from a coal cleaning
facility were below the U.S. Government regulation levels, would the
pollutant ecomagnify to the point where the concentrations reached the
toxicity threshold?
The best method currently in. use to predict pollutant concentrations
through a food web is that of computer simulation. In order to accomplish
this goal of modeling total body burdens or specific organ concentrations
of a pollutant, one must be able to use data that reflect all possible
exposure routes and that identify the major parameters influencing transport
via those routes. Figure 4-5 reflects the individual exposure routes
that need characterization and measurement. These types of data, if avail-
able, would allow for calculation of the rate transfer coefficients and
would allow development of a system simulation model.
A significant finding related to this portion of the study was that
data enabling the calculation of rate transfer coefficients were not
available. Investigators in general either fail to consider or fail to
report:
(1) Chemical form of pollutant used in the experiment or
found in the environment
(2) Measurement of major parameters affecting transport in
their experiments
(3) Data partitioned into specific exposure sources (i.e.,
food source, inhalation, and adsorption)
(4) Experiment time duration.
Therefore, an accurate comparison between the percent uptake or dis-
tribution as reported here and the currently reported toxicity levels is
beyond the state-of-the-art.
108
-------
The data reported here represent a synthesis of information from many
literature sources. These data reflect the best estimation of what the
final fate of each pollutant might be in a generic ecosystem. They do not,
however, take into account such important factors as (1) pollutant chemical
form, (2) species composition of each functional group, (3) age structure
within species and its influence on uptake, (4) seasonal variation (i.e.,
rainfall, growth rates, and soil water freezing), (5) successional stage
variation, and (6) topography, to mention a few.
The information presented here was organized to permit the identifi-
cation of selected Priority 1 pollutant magnification among the functional
components of a generic Northern Appalachian-Midwest ecosystem (Figure 4-3).
As emphasized in the sections above, a number of factors, both abiotic and
biotic, directly affect the uptake of pollutants by plants and animals.
The pollutant's biological and physical distribution and behavior will vary
from region to region within the generic ecosystem. This variation is due
to the differences of these factors. A statement pertaining to the general
behavior of a pollutant, as has been made here, can be misleading if one is
not aware of the large possible variations. Therefore, limitations on the
usage of the data presented should be imposed. The information should be
used as a general identification of ecomagnification and not as an accurate
quantification of pollutant transfer. However, future research incorpo-
rating the necessary data, previously mentioned, for calculation of transfer
coefficients would produce a more accurate quantification.
109
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(122) Dolar, S.G., Keeney, D.R. and Chesters, G., "Mercury Accumulation
by Myriophyllum spicatum L.", Environmental Letters, !_, (3), 191-198
(1971).
(123) Bainbridge, K.L., D'ltri, P.M. and Bahr, T.G., "Mercury Dynamics in
a Warmwater Stream Receiving Municipal Wastewater", Proceedings of
the 29th Industrial Waste Conference, Part II, Lafayette, Indiana,
Purdue University (1974), 115 pp.
(124) Wood, J.M., "Biological Cycles for Toxic Elements in the Environment",
Science, 183 (4129), 1049-1052 (1974).
(125) Femreite, N., Holsworth, W.N., Keith, J.A., Pearce, P.A. and Guichy,
I.M., "Mercury in Fish and Fish-Eating Birds Near Sites of Industrial
Contamination in Canada", The Canadian Field Naturalist, 85_ (3), 211-
220 (1971).
(126) Hardcastle, J.E. and Mavichakana, Nara, "Uptake of Mercuric Chloride
and Methylmercury Chloride from Liquid Media by Aspergillus niger
and Penicillum notatum", Bulletin of Environ. Contamination and
Toxicology, 11 (5), 456-460 (1974).
(127) Mortimer, D.C. and Kudo, Akira, "Interaction Between Aquatic Plants
and Bed Sediments in Mercury Uptake from Flowing Water", J. Environ.
Qual., 4_ (4), 491-495 (1975).
(128) McKone, C.E., Young, R.G., Bache, C.A., and Lisk, D.J., "Rapid Uptake
of Mercuric Ion by Goldfish", Environ. Sci. and Technology, _5_ (H)»
1138-1139 (1971).
(129) Schindler, J.E. and Alberts, J.J., "Behavior of Mercury, Chronium
and Cadmium in Aquatic Systems", Environmental Research Laboratory,
U.S. Environmental Protection Agency, Athens, Georgia, EPA-600/3-77-
023 (1977), 62 pp.
(130) Huckabee, J.W., "Mosses: Sensitive Indicators of Airborne Mercury
Pollution", Atmospheric Environment, ]_, 748-754 (1973).
(131) Huckabee, J.W. and Janzen, S.A., "Mercury in Moss: Derived from the
Atmosphere or From the Substrate?", Chemosphere (1), 55-60 (1975).
(132) Jemelov, A. and Lann, H., "Mercury Accumulation in Food Chains",
Oikos, _22_ (3), 403-406 (1971).
120
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(133) Dustman, E.H., Stickel, L.F. and Elder, J.B., "Mercury in Wild
Animals", Lake St. Clair (1970).
(134) Birke, G., Johnels, A.G., Plantin, L., Sjostrand, B. and Westermark,
T., "Mercury Poisoning Through Eating Fish?", Lakarhdninger, j>4, 3628
(1967), Swedish with English summary.
(135) National Research Council, "Selenium", Geochemistry and the Environ-
ment. Volume I, A Report of the Workshop at the Asiloman Conference
Grounds, Pacific Grove, California, National Academy of Science,
Washington, D.C. (1974).
(136) Gardiner, M.R. and Gorman, R.C., "Further Observations on Plant
Selenium Levels in Western Australia", Expt. Agr. Animal Husbandry,
3, 284-289 (1963).
(137) Allaway, W.H., "Soil and Plant Aspects of the Cycling of Chromium,
Molybdenum, and Selenium", Proceedings of the International
Conference on Heavy Metals in the Environment Symposium, Toronto,
Canada, Electric Power Research Institute (1976), 371 pp.
(138) Gissel-Nielson, G. and Bisbjerg, "The Uptake of Applied Selenium by
Agricultural Plants 2. The Utilization of Various Selenium Com-
pounds", Plant and Soil, J32, 382-396 (1970).
(139) Davies, E.B. and Watkinson, J.H., "Uptake of Native and Applied
Selenium by Pasture Species", N.Z. J. Agric. Res., 9_, 317-327 (1966).
(140) Williams, C. and Thornton, I., "The Use of Soil Extractants to
Estimate Plant-Available Molybdenum and Selenium in Potentially
Toxic Soils", Plant and Soil, J14_, 149-159 (1973).
(141) Wright, Paul L., "The Absorption and Tissue Distribution of Selenium
in Depleted Animals", Symposium: Selenium in Biomedicine, 0. H.
Muth, Editor, The AVI Publishing Company, Inc., Westport, Connecticut
(1967), pp 313-328.
(142) Butler, G.W. and Peterson, P.J., "Aspects of the Faecal Excretion
of Selenium by Sheep", N.Z. J. Agric. Res., 4_, 484-491 (1961).
(143) Hopkins, L.L., Pope, A.L. and Bauman, C.A., "Distribution of Microgram
Quantities of Selenium in the Tissues of Rats and Effects of Previous
Selenium Intake", J. Nutrition, 88_ (1), 61-65 (1966).
(144) Anderson, H.D. and Maxon, A.L., "The Excretion of Selenium by Rats
on a Seleniferous Wheat Ration", The Journal of Nutrition, 22_ (2),
103-108 (1944).
(145) Luckey, T.D., Venugopal, B. and Hutcheson, D., Heavy Metal Toxicity,
Safety and Hormology, Academic Press, New York (1975), 120 pp.
121
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5.0 DEVELOPMENT OF ENVIRONMENTAL GOALS
Traditionally, adverse health and ecological (H/E) impacts have been
identified after a technology becomes operational. Then, suitable mitigations
are sought and applied. However, "retrofitted" controls are often costly and
may be only partially effective in protecting humans and other living organisms.
Comprehensive assessment of potential health and ecological effects associated
with coal cleaning facilities probably would confirm anticipated problems and
aid in identifying previously unknown problems. In short, a systematic identi-
fication of actual H/E problems could lead to better retrofits and aid in the
design of new coal cleaning facilities.
The U.S. EPA and others recognize the need for comprehensive and
careful interpretation of predicted and observed health/ecological effects
associated with coal cleaning technology. However, few methodologies are
available for systematically synthesizing and applying pertinent data on
biological and ecological effects. As part of EPA's Environmental Assessment
Programs, quantitative target values (environmental goals) are being developed
for many chemicals, nonchemicals (e.g., heat, noise), and nonpollutant factors
(e.g., land use). These environmental goals are based on toxicological and
other health/ecological effects data.
This section of the report presents material associated with the
development of environmental goals. First, the basic problem and working
definitions are provided for environmental goals and associated activities.
The scope and research plan are discussed. Then, a review of formulae used
by the U.S. EPA's Environmental Assessment Programs shows the basic dose/
responses and adjustment factors used in estimating permissible concentrations
in air, water, and land. The strengths and limitations of 20 formulae are
discussed. The limitations are categorized and a few factors are selected for
in-depth analysis. The bulk of the report deals with research to restrict these
limitations. Removal of the limitations means improved reliability of formulae
for developing environmental goals. Finally, the basic points of the research
are summarized and future directions are specified.
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5.1 Introduction
Many species of organisms exist near coal cleaning facilities. Many
of the individuals will be exposed to pollutants from the facilities' emission
streams. If pollutants are discharged to the atmosphere, toxic materials may
be deposited on plants and breathed by animals. Water-borne chemicals can
affect aquatic plants, animals, and microorganisms. Soluble pollutants can be
leached from land-filled materials and harm soil organisms, be assimilated
by crop species, and enter food chains. Previous sections deal with such
transfers. Here, the problem is to determine if the material can harm living
organisms, including man, once it is transferred to the organisms.
The burden of proof rests with the health and ecological effects data.
Since the application of control technology will be based on health/ecological
effects data, the expenditure of millions of dollars to design and implement
engineering control systems can best be justified on the basis of carcinogenic/
toxicological effects data that are as sound, as complete, and as rigorous as
possible. If, for example, no harm is predicted for any of the sensitive
organisms in fhe ecosystem surrounding the coal cleaning facility, then
judicious monitoring alone may suffice. If harm of varying types and degress
is predicted, then studies of control technology at the point of origin would
be the next step. Chemicals toxic to many species which are emitted in large
quantities, of course, would need greater control than chemicals which are
toxic to only a few species and emitted in lesser quantities.
5.1.1 Basic Problem
The basic need is to obtain high-quality health/ecological effects
data and to extrapolate this data correctly. Extrapolation is the activity
of inferring or extending known data into an unknown area. Conjectural know-
ledge of the unknown area is developed based on assumed continuity, corres-
pondence, or other parallelism between it and what is known. Extrapolations
of biological effects from (1) the laboratory (where most experiments are
conducted) to the field (where most problems lie), (2) one species to another,
and (3) one chemical to another are as much an art as a science. However,
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Incentives are increasing for systematically removing the "art" from such
extrapolations, and this report presents several improvements in the state-of-
the-art procedures for biological extrapolation.
5.1.2 Working Definitions
Environmental objectives are low concentration levels of pollutant(s)
below which humans, other organisms, and ecological systems would not be
harmed if the pollutant(s) were released into the air, water, and/or land.
These environmental objectives should (1) be based on sound extrapolations
which, in turn, are well-based on epidemiological, toxicological, and ecological
effects data, (2) be developed in a relatively process-independent manner, and
(3) provide control engineers with a quantitative goal against which to compare
emission inventories, identify problems, and improve the best available
control technology.
There are several types of environmental goals. One, called estimated
permissible concentrations (EPC), denotes the maximum allowable long-term
concentration of a substance in the ambient media away from a coal cleaning
or other facility. A second environmental goal is the minimum acute toxicity
effluent (MATE), which is the maximum concentration of a substance at the
point of emission for which short-term exposure will not adversely affect a
particular species of organism exposed for short periods of time, i.e.,
acute toxicity does not exist.
The Multimedia Environmental Goals (MEG) chart is the principal tool
for displaying environmental goals. The chart, developed at the U.S. EPA's
Industrial Environmental Research Laboratory (IERL), has been refined by
Research Triangle Institute (RTI) , with some assistance from Battelle's
Columbus Laboratories. The chart consists of two interrelated tables, (1) a
control engineering part including columns for best technology and MATE's, and
(2) a health/ecological part including columns for standards/criteria and
EPC's both for human health and for ecological systems. The chart has rows
for the three media—air, water, and land. The MEG chart is considered an
indispensable part of the environmental assessment programs at IERL. Any
work on environmental goals needs to be applicable eventually to the MEG
chart activities.
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5.1.3 Scope
The development of environmental goals is associated primarily with
the "effects" portion of the basic phases of environmental assessment. Briefly,
the basic phases are as follows:
• Source - The coal cleaning facility and its emission streams.
• Transport - The physical, biological, and ecological transfer
of toxic substances from the source to receptor
organisms.
• Effects - The positive and negative responses of organisms
exposed t'o the transported materials.
• Evaluation - The comparison of environmental objectives to
chemical concentrations measured in emission
inventories.
• Control - The selection, application, and development of
needed control devices and practices.
The interrelationships of these phases are depicted in Figure 5-1. The
previous section deals with transport. This section concentrates on the use
of dose/response and biological effects data. Properly used, dose/response
data will allow the evaluation to be sound and straightforward. Thus, the
correct control procedures and devices could be applied to reduce the health/
ecological hazard.
Control
Technology
tion
Eva
Source of
Pollutants
Transport/
Transformation
Biological
Effects
FIGURE 5-1.
INTERRELATIONSHIPS OF FIVE PRINCIPAL
PHASES OF ENVIRONMENTAL ASSESSMENT
125
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5.2 Research Approach
The research approach for this aspect of the study consists of four
interrelated steps as follows:
• Clarify scope
• Identify and review formulae
• Evaluate strengths and limitations of formulae
• Restrict limitations.
About two-thirds of the effort was devoted to the removal/reduction of limi-
tations and was regarded as the most critical step.
The research was coordinated closely with other work on development
of environmental goals. Scientists at Research Triangle Institute (RTI), North
Carolina, are performing the majority of this type of work for IERL. Also,
under the U.S. EPA's contract for environmental assessment of fluidized-bed
combustion technology, environmental objectives were developed at Battelle's
Columbus Laboratories for selected nonchemical and nonpollutant factors; the
present coal cleaning work benefited from both projects. Finally, there was
dialogue among authors of the other sections of this and other coal cleaning
reports. The coordination helped to develop as useful a product as possible.
Over twenty candidate formulae for estimating permissible concen-
trations were obtained through a search of the literature and evaluated.
Formulae identification was assisted by access to RTI's work. The liter-
ature necessary for the systematic removal of certain limitations was scattered,
and the data, when found, had to be adapted. Sometimes the data could not be
adapted to the coal cleaning problem. For example, the necessary concepts for
optimum use of chronic-effects data could not be developed within the scope
of the program and this limited certain activities. And, of course, extrapo-
lation of animal toxicity data to humans looms as one of today's major
intellectual challenges.
5.3 Review of Formulae
The first major step in'the research was to identify and review
formulae for estimating environmental goals. These formulae and their
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rationales, which are scattered in various reports, ranged in complexity
from simple use of raw dose/response data to well-thought-out formulae used
in radiological protection. Many notes were assembled about these formulae,
their purposes, and rationales; the exercise served to delineate the general
state of the art.
As many of the state-of-the-art formulae were being utilized by RTI
in their development of environmental objectives for single chemicals, the
present research was parallel to part of the RTI work. To facilitate the
consistency of the two programs, the identification code used by RTI was adopted
by BCL. Additional formulae not used in current MEG chart efforts were also
identified; two of these formulae are discussed later as possible approaches
for the reduction of limitations of the current procedure.
5.3.1 Basic Formula
The basic form for the equation for calculating environmental goals
(EPC's and MATE's) may be simply stated as:
EPC or MATE = dose/response x adjustment factor(s),
where dose/response is expressed as an oral LD , TLV (threshold limit value),
lowest concentration, or some similar form relating the dose of a particular
compound or substance to the response of a particular receptor population. A
variety of factors is used to adjust the dose/response data to yield an EPC
or MATE. Adjustment factors include exposure time, elimination rates, bio-
accumulation, method of exposure, and safety factors. Adjustment factors can
be used to correct deficiencies in the dose/response data or to compensate for
circumstances peculiar to the unknown s-ituation, such as accumulation of the
chemical in tissues that jeopardizes the organism's health.
5.3.2 Overview of State-of-the-Art Formulae
A review of the available formulae for developing EPC's and MATE's
for air, water, and land is given in Tables 5-1 to 5-3. All the formulae follow
127
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TABLE 5-1. EPC/MATE FORMULAE FOR THE AIR MEDIUM^
Basic Equation
EPC or
MATEU; Unit Conversion
(ug/m3) Dose/Response Factor
EPCAH1 " TLV (m8/m3) * 1()3
EPC 2 - Oral LD5Q (mg/kg) x 10
EPC - - Oral LD5Q (mg/kg) x 10
H EPC.,, - Lowest Reported Dose
g ** (Pg/m3) 1
MATE^ " TLV (mg/m3) x 103
MATEAH2 " ^SO (m8/k8) * 10
"^AHS " LC50' LCLO' or x 1C)3
TCIO (mg/m3)
Adjustment Factors
Exposure Time Safety Correlation Pollutant
Correction Factor Factor Loss Rate
x 40/168 x 0.01
x 40/168 x 4.5 x 10~*
x 5 x 10~ x-^j —
x 0.1
x 100 x 4.5 x 10~4
x 0.1(C)
Final
Inhalation Form of
Factor Equation
- [TLV (mg/m3) x 103] * 420
- LD5Q (mg/kg) x 0.107
*b7T43 ' LD50 (m*/kB) x °-°81
• Lowest Reported Dose
(ug/m3) x 0.1
- TLV (mg/m3) x 103
- LD5Q (mg/kg) x 45
-LC50,-LCLO, ^(mg/m3)
x 100
(a) Codes are those used in Reference 1.
EPC » estimated permissible concentration.
MATE » minimum acute toxicity effluent.
A - air; H - health; E - ecology.
1-3 • the number of a particular formula.
(b) The value 45 was developed from adjustment factors and the Monsanto/Handy and
Schindler model.(2)
(c) Safety factor derived by authors of this report.
-------
TABLE 5-2. EPC/MATE FORMULAE FOR THE WATER MEDIUM
(1)
N3
VO
Basic Equation
EPC or Adjustment Factors
MATEW Unit Conversion Air-Water TLV to LD.Q Safety Pollutant
(lig/1) Dose/Response Factor Conversion Factor Conversion Factor Factor Loss Rate
3 30 m3 air/day
Smi AH ^v&'m ) * 2 1 water/day
31 -40 693
Ell'....- • TLV VRg/m ) XlO X J«*.J XJX1UX OQ
EPCygj^ • Lowest TL (mg/1) x 10
EPCWE2 " Lowest concentration
to cause tainting
(wg/D
""CUM • Lowest TL (ug/l) x 10
wcj m
EPC_, • Maximum allowable.
concentration
(Pg/kg)
MATEWH1 " MATEAH1 (yg/m J * 2 1 water/day
MATEy^ - Lowest LC5() (mg/1) x 103
Final
Drinking Concentration Equation
Factor Factor (ug/l)
x Q 029 " TL™ (tug/™ ) * •L-J-°
x 0.05 - TL^ (mg/1) X 50
• Lowest concentration
causing tainting
* *"""$? ' TI, low (pg/l) x 103
raccor x Application
Factor
._ Concentration m (Maximum allowable
7 Factor*0' Concentration) +
(Concentration
Factor) (pg/kg)
- MATE.U (uR/m3) x 15
An
x 0.1 - 100 x Lowest LC
(a) Codes are those used in Reference 1.
EPC • estimated permissible concentration.
MATE • minimum acute toxicity effluent.
W • water; H - health; E • ecology; A - air.
1-4 - the number of a particular formula.
(b) Application factor varies according to recognized criteria.
(c) Concentration factor varies for each element. For example, it may be 10,000 for mercury.
-------
TABLE 5-3. EPC/MATE FORMULAE FOR THE LAND MEDIUM
(1)
U)
o
Basic Equation
EPC or
MATE(a)
(yg/g) Dose/Response
EPC = EPC (yg/m3)
Ln/ AH
EPC = EPCL (yg/Ł)
LtE* Wli
Adjustment Factor
Air-Land Water-Land
Conversion Factor Conversion Factor
2 Ł
X 1000 g
30 m3/day
^ g food/person-day
2 Ł
x 1000 g
2 Ł
X 1000 g
2 Ł
X 1000 g
Final
Crop Uptake Equation
Factor (yg/g)
u.uuz x t,rL vyg/x.;
WH
30 x EPC |
Axl 1 f •
yg food _ g food/person-day Ix yg °
A zg soil zg soil
= 0.002 x EPC^ (yg/Ł)
— U. UUZ X MAJ.E^ ^.Up/ x^
WH
Wlj
(a) Codes are those used in Reference 1.
EPC = estimated permissible concentration.
MATE = minimum acute toxicity effluent.
L = land; H = health; W = water; A = air; E = ecology.
1-2 = the number of a particular formula.
-------
the basic equation described in Section 5.3.1. Differences among them include
the type of dose/response data used and the kind and number of adjustment factors
employed. More data about each formula are available in RTI's MEG report
as well as the original source material whose citations are in the MEG report.
(2)
For example, Handy and Schindler developed some of the formulae. Types of
dose/response data used are TLV, oral LDcr. for rats, LDT^, TL , and lowest
jU Lu m
concentration to cause tainting. A single type of dose/response information
is insufficient; a multiplicity is desirable because
(1) Dose/response data are associated with particular
receptor species (e.g., TLV's are primarily for
human exposure; LD^ 's are for small mammal popu-
lations. )
(2) Lack of data (TLV's may be lacking for the receptor
population) requires the use of proxy data.
Generally, the expression best suited to the receptor population and to the
needs of the user is employed.
Numerous adjustment factors have been used in the EPC and MATE for-
mulae. These factors modify the dose/response data to fit particular circum-
stances or needs, often compensating for deficiencies in dose/response information.
The factors may be classed into six broad categories—(1) exposure time, (2)
exposure pathway, (3) elimination, (A) concentration, (5) safety, and (6)
conversion. The exposure time factor is the fraction of the day or week that
the receptor population is continuously exposed to the pollution. Exposure is
3
expressed as a concentration, i.e., yg/m or ppm. Elimination accounts for
the loss of the pollutant from the body through means such as fecal and urinary
excretion and is expressed as biological half-life. The concentration factor
provides a means to consider accumulation where an organism takes up and
concentrates a pollutant, resulting in a body burden greater than might be
expected if the chemical were not accumulated. Safety factors are generally
included when definitive information concerning safe, tolerable levels of the
pollutant are not available and a conservative arbitrary estimate must be made.
Finally, conversion factors of three kinds are used. First, a units factor,
131
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generally to convert mg to ug, is used in most formulae. Second, when only
oral LD _ data are available, an equation is used to convert an oral LD
value to a TLV concentration. Third, when dose/response data are not available
for the medium of interest, a media conversion factor is applied to convert
the EPC from the known medium to the unknown one. It is assumed that the more
adjustment factors used, the more accurate the EPC will be. No known formulae
use all the adjustment factors described. Some of the more complete formulae
include EPCAI1, in Table 5-1, EPCTTUO in Table 5-2, and EPCTU in Table 5-3.
AnJ WHZ LH
These formulae consider more variables which influence the safe body burden
of a pollutant than other formulae and are likely, therefore, to be more
accurate.
5.4 Identification of Major Strengths
and Weaknesses of Formulae
The strengths and weaknesses of the 20 formulae described in Section
5.3 were evaluated from three viewpoints: media, dose/response data, and
adjustment factors. Evaluations were based on common sense and broad professional
knowledge of biological systems. Many insights resulted in identifying those
limitations most deserving of initial consideration.
In the ensuing discussion, strengths and limitations are discussed
from several viewpoints. The evaluation is not meant to be exhaustive, rather
it is to provide a reasonable assessment. Finally, all the limitations are
listed in one place and they are ranked according to four criteria: relevance,
data, time, and expertise. The result of this ranking is the identification of
five limitations which are subjected to in-depth analysis in Section 5.5.
5.4.1 Media Viewpoint
From the media point of view, the formulae for breathing (air) are
the best. Land formulae are the least defendable or reasonable, with those for
water being intermediate. Air formulae have the most quantitative dose/response
data of the three media; there are more oral LD 's and LC,. 's used here than
132
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for water and land formulae. Also, the air formulae tend to have more
believable adjustment factors. For example, the exposure-time correction
is supported by good reasoning. For ecologically oriented EPC's and MATE's,
water formulae probably are the best. This makes sense since fish and other
aquatic life forms can be assayed directly and extrapolation from one life
form to another is minimal.
Land EPC's and MATE's start with modified dose/response data from
air and water predictions. In fact, the EPC's for land are based on EPC's
from the other media. Thus, if adjustment factors to basic effects data are
not sound for the other media, this distortion would be further reflected in
the land EPC's and MATE's. Clearly, the land predictions will require more
serious research to make them as rigorous as those for air, for example.
5.4.2 Dose/Response Data
There are also major strengths and weaknesses of dose/response
data. Such data are the foundation of all the extrapolation formulae and
this subject deserves considerable discussion.
5.4.2.1 Strengths. The formulae use a variety of toxicological
measurements rather than only one type of measurement. The TLV (threshold
limit value) for air concentration is appropriate to humans in workroom
environments and thus does not require species-to-species extrapolation when
used for human EPC's and MATE's. Use of the oral LD_n for rats, the largest
known data base for mammals, provided another major data source. The largest
data base for toxic effects on aquatic organisms is the LC^g and this measure-
ment was used in the formulae. Use of LD and LC response data rather
than other measurements is a strength because of the ready availability of
these two measurements in the published literature.
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'5.4.2.2 Limitations. On the other hand, the dose/response data
included several weaknesses. There are many types of LD,.,. measurements, and
the non-oral ones were either not used or used without interconverting the
(2)
non-oral administration route to an oral equivalent . The LD-- is only one
of several readily available types of toxicological measurements. For
example, the LD (lethal dose low or the lowest dose known to kill an indi-
LiO
vidual of a given species) and the TDT (toxic dose low, i.e., the lowest
LiO
dose known to be toxic to an organism) are available for many substances when
no LD_» is known. Thus, only a small part of readily available dose/response
data is being utilized in the formulae. Likewise, for responses to toxicants
by aquatic organisms, there are other types of measurements whose application
would strengthen the data base for many of the chemicals; they include such
measurements as the LD and LCT (lethal concentration low, i.e., the lowest
LiO LiO
concentration known to kill an individual of a given species).
There are other limitations. Little attention was given to responses
of nonhumans and nonmammals. While humans and similar species may be of
paramount importance, protection of other life forms (plants, micro-organisms)
is also recognized as being important by the U.S. EPA. Other dose/response
data are available but were used sparingly. The toxicological-effects data are
for short-term (hours, days or weeks) responses. Long-term (months or years)
responses can also be anticipated if a coal cleaning facility continuously
emits materials into one of the receiving media. Finally, the dose/response
data are for single chemicals, not mixtures of chemicals. Long-term effects
and mixtures causing synergisms or antagonisms are more like the "real world"
than short-term effects and single chemicals. For example, effects on ecosystem
function and mutagenesis are two possible long-term effects that acute bioassays
may not indicate. The lack of the above kind of data in formulae is a serious
limitation to the accuracy and biological meaningfulness of the EPC's and MATE's.
5.4.3 Adjustment Factors
Adjustment factors also have their strengths and limitations. Unfor-
tunately, these strengths and weaknesses can best be evaluated relative to the
degree to which the predictions provide actual or real protection. As this
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ideal reference point is not easily attained, again evaluations were based on
common sense and professional opinion (derived from a general knowledge of bio-
logical systems) instead of experimental data.
5.4.3.1 Strengths. No one adjustment factor seems to extrapolate
laboratory-observed dose/response data to the "real world" coal cleaning
problem. Rather, a series of adjustment factors have been developed as explained
in 5.3.2, each of which can be manipulated individually.
The formulae contain a variety of simple adjustment factors. Indeed,
the simplicity of these factors is a strength in that each is usually easy to
understand individually. Another strength is the adjustment of one exposure
time to another. This is particularly valuable in the air formulae where the
TLV (a measurement based on 8 hours of exposure per day for 5 working days per
week) was adjusted to 24 hours for the full 7 days or 168 hours of the week.
The safety factors, albeit arbitrary, can be viewed as a strength because they
are designed to provide a conservative estimate of an EPC or MATE. Development
of the research depends on a correlation between the TLV and the LD _. This
(21
correlation represents a first step to better utilization of all available
dose/response data. For example, if no TLV is known but the LD..Q is known,
the TLV can be predicted on the basis of the known relationships of TLV's
and LD,. 's for other substances. Also, formulae with pollution uptake and
loss rate are superior to those without biological half-life data.
5.4.3.2 Limitations. Adjustment factors have major limitations, the
greatest of which is the lack of validation about how well they really work.
Another major limitation is the lack of certain types of adjustment factors.
On the other hand, the ideal EPC's, MATE's, or their equivalent will probably
not be forthcoming because of the tremendous expenses in time, money, personnel,
and risk to get the ideal information. Rather than despair, the best approach
is to identify limitations and attempt to improve the formulae systematically.
135
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Safety factors need a biological basis. Review of background
material on safety factors showed that they were often developed arbitrarily.
This means that they were created without a biological rationale. For
example, safety factors of one hundredth or one tenth of the TLV, LD , or
LC ., have been proposed. Although there is nothing incorrect in establishing
an EPC or MATE based on a certain percent of the dose/response data, the
safety factor would be more defensible if there were a biological basis for it.
The adjustment factors for crop uptake may be limited in their applicability.
Some chemicals are not taken up by plants; others are concentrated. More work
on an adjustment factor for the food chain transfer is needed.
Omitted factors include extrapolation of data from one species to
another. Extrapolation of animal toxicity data to humans for the purpose of
creating environmental objectives is an especially controversial area, and is,
in fact, very risky. The ecosystem surrounding a coal cleaning facility
contains many thousands of species of animals, plants, and micro-organisms.
Since laboratory test species are limited to a few tens of species, any
formulae for developing environmental objectives would be more powerful if it
could allow extrapolation to various species.
Chronic effects, as explained in Section 5.4.2., are a limitation in
the dose/response portion of the equation. The lack of an adjustment for
chronic effects in the adjustment portion of the equation is also a major limi-
tation.
Other limitations of omission include the lack of
• Adjustment for complex mixtures and consequential synergistic/
antagonistic effects
• Adjustment factors for multiple pathways of exposure (the
formulae handles breathing, drinking, and eating as if
they were independent).
Thus, there are many limitations both of commission and omission.
136
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5.4.4 Selection of
Limitations for Analysis
The evaluation of the strengths and weaknesses of the formulae dis-
closed 16 major limitations deserving investigation. Time constraints allowed
the amelioration of only a few limitations. Clearly, a simple method was
needed for recognizing which limitations should be studied first, since research
to restrict all limitations was not possible at this time.
The identified limitations listed in Table 5-4 were evaluated according
to the following 4 (in some cases 5) criteria:
• Relevance Is the research relevant to the scope of the
coal cleaning program?
• Data Is there sufficient tmblished information
available to warrant literature synthesis?
• Time Is there time within the constraints of the
program to start and finish a block of work?
• Expertise Do Battelle scientists have the expertise to
solve the problem?
• Special For some limitations, the need for research was
so great that an additional special category was
added.
Although more criteria could have been developed, these five provide a reason-
able balance.
The degree of relevance, amount of data, amount of time, and avail-
ability of qualified experts were evaluated for each limitation with the use
of a 0 to 3 code where 3 means the most relevant, high availability of data,
etc. For example, if the limitation was of great relevance it was rated a
3, if of no relevance, the limitation was rated a 0. Intermediate importance
was rated 1 or 2. Rankings were based on informed judgement and completed by
the senior author in consultation with other authors.
The screening process showed that six of the limitations considered
received scores of 10 or greater (10 was an arbitrary cut-off point). The higher
the score the less the difficulty in reducing the limitation, and therefore
the higher the priority for present research. Topics related to these six
137
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TABLE 5-4. EVALUATION OF POSSIBLE LIMITATIONS IN FORMULAE USED FOR DEVELOPMENT OF ENVIRONMENTAL GOALS
oo
Evaluation Criteria
Potential Limitations
MEDIA FORMULAE
Air
Water
Land
DOSE/RESPONSE DATA
LD,-^ not interconverted
LD , etc., not used
Aquatic measurements other than LC _
Plant /microorganism responses
Chronic data need
Synergisms /antagonisms
ADJUSTMENT FACTORS
Need for validation
Extrapolation from Species 1 and Species 2
Better crop uptake model
Better safety factors
Chronic adjustment
Synergisms /antagonisms
Multiple pathways
Relevance
3
3
2
3
3
3
3
3
3
3
3
3
3
3
3
3
Data
2
2
1
3
2
2
2
1
2
1
2
2
3
1
2
2
Time Expertise Special
3
1
1
3
2
2
1
2
1
1
2
1
2
2
1
1
3
3
3
3
2
2
3
3 3
3
3
3
3 3
3
3
3
2
Total
11*
9
7
12*
9
9
9
12*
9
8
10*
12*
11*
9
9
8
* High priority selections for further research.
1 = little; 2 = intermediate; 3 = most (the higher the score, the less the difficulty of reducing the
limitation).
-------
limitations are air formulae that use more available data, LD 's not inter-
converted, chronic data, better safety factor, better crop uptake model, and
extrapolation from species 1 to species 2.
Five of these limitations are discussed in Section 5.5. The sixth,
better crop uptake model, is discussed, in part, in Section 4.0 on ecological/
biological transfer.
5.5 Research to Reduce Limitations in Formulae
Not all limitations identified in Section 5.4 were considered to be
of equal importance. Five limitations were judged to be the highest priority
ones to attempt to restrict at this time. The following narrative, tables,
figures, and conclusions pertain to these five limitations. They are as
follows, in order of their presentation:
(1) Identification of other formulae - some formulae
handle multiple pathways (breathing, drinking, and eating)
better than reviewed formulae.
(2) Correlation of oral LD and non-oral LD routes of
administration - the correlation values will increase
the accuracy of predictions for certain chemicals.
(3) Use of chromic effects - more research is needed, but a
good foundation was laid.
(4) Extrapolation of one animal species response to another
species - two logical approaches are presented and
examples are provided.
(5) Development of a biological basis for safety factors -
the findings have broad implications for formulae for
permissible concentrations for air and water.
5.5.1 Identification of
Other Formulae
Formulae other than those in Tables 5-1 to 5-3 are available.
scope of work permitted identification of more than the 20 formulae reviewed
139
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in Section 5.3. When one of the 20 formulae cannot be used to predict an
EPC or MATE, then it is possible to use another formula.
Two sample formulae are presented. The two formulae are (1) maximum
permissible concentration for radioisotopes, and (2) CUMEX (Cumulative Exposure)
Index. No attempt is made to evaluate the two formulae. Rather, a brief
explanation is presented here and details are provided in Appendix B. Both are
examples of reasonable alternatives to formulae being used in the U.S. EPA
MEG activities.
5.5.1.1 Maximum Permissible Concentrations for Radioiostopes. The
International Commission on Radiological Protection has established maximum
permissible concentrations of radioactive materials or radionuclides to which
man may be occupationally exposed via inhalation or ingestion. Formulae have
been derived for (1) body burden in comparison with radium, (2) body burden
based on a permissible RBE (relative biological effectiveness)* dose rate to
the critical body organ, (3) concentrations in air and water (based on an
exponential model) taken into critical organs other than the gastrointestinal
(GI) tract, and (A) concentrations in air and water based on RBE dose delivered
to various segments of the GI tract. The formulae described here are those
described for (3) above.
Maximum permissible concentrations are generally based on the RBE ;
dose, burden of the radionuclide in the critical body organ or segment thereof,
and the biological half-life of the radionuclide. Depending on the formula
utilized in calculating maximum permissible concentrations, the following
factors are needed:
• Effective energy - the total energy absorbed in the body organ
per disintegration of the radionuclide
* Relative biological effectiveness is the ratio of the dose of X-rays
or gamma rays, in rads, to the dose of the given radiation, in rads, which
has an equal biological effect.
140
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• Standard-man data
• Biological and physical data - average daily ingestion, mass
of reference organ, biological half-life, radiological half-
life, distribution fractions, concentration in critical organs,
etc.
Ideally, the maximum permissible body burden and the maximum per-
missible concentration of radioactive materials should be based on human studies
under working conditions over an extended period of time. However, human data
are scarce; therefore, data from animal studies must be extrapolated to man.
When animal data are not available» estimates are made from comparison with
elements having similar chemical behavior. Because of the many assumptions
and approximations made in applying much of the data, detailed refinements in
the calculations are deemed to be generally unwarranted. See Appendix B for
the equations.
5.5.1.2 CUMEX (Cumulative Exposure) Index. The CUMEX (cumulative
exposure) index is a site-specific hazard assessment based on the interrela-
tionships between one or more of the media and biota. The index relates the
concentration of the pollutant in the ambient medium to a preselected receptor
such as an organ concentration by considering all pathways from the point of
(A)
measurement to the end point
To apply the CUMEX index, data from the following are necessary:
• Environmental transport models (air, water, land) which estimate
pollutant dispersion through air and water, deposition on soil
and plant surfaces, uptake by plant, concentrations in air and
water, and intake by animals and human exposure through inhal-
ation and ingestion.
• Physiological models which estimate pollutant uptake and subse-
quent distribution among organs.
• Knowledge of the biological effects of the particular environ-
mental pollutants of concern.
141
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Presently, sufficient data are not usually available for utilizing the CUMEX
Index. This index is also limited to single pollutants although multiple
pollutants and multiple environmental pathways have been considered. This
latter capability makes CUMEX worth considering as a tool to handle multiple
pathways. See Appendix B for the equations.
5.5.2 Correlation of Oral LDcn and
Other Routes of Administration
In establishing permissible cpncentrations of pollutants for contin-
uous exposure, EPA/IERL in cooperation with Research Triangle Institute
( 2)
developed a relationship based upon correlating TLV standards with LD values.
This work was an extension of the original study in which Monsanto Research
Corporation correlated toxicological information for 30 selected agricultural
chemicals . A regression fit was established for 241 chemicals in the expanded
study. The best fit was on the equation for the type where
log (TLV) = log a + b log (LD5Q)
and the value of the constants was found to be
a = (0.0125 < 0.0291 < 0.0678) = 95%
b = (0.849 < 0.983 < 1.117) = 95%.
By using the lower confidence limit for a safety factor and correcting for
fractional work exposure, the following maximum permissible pollutant concen-
tration (x ) was derived*:
m
x > 1.07 x 10~4(LD,_) .
m — _>U
The bulk of the toxicity data were oral LD 's for rats; however, if
these data were not available, oral LD n values for other animals were used (e.g.,
mouse, guinea pig, dog, cat). If LD5Q data were not reported, oral LD-^
rats was used.
Toxicity data for a wide variety of materials via oral administration
are not available; however, they are available for other routes (intraveneous ,
subcutaneous, intraperitoneal, inhalation, etc.). Basically, it can be
* Maximum permissible concentration (x ) and estimated permissible concentration
(EPC) are synonomous here.
142
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assumed that, regardless of the administration route, it should take the same
quantity of toxicant in the blood stream to produce a lethal effect, and that
each administration route has its own transport efficiency. This will of
course, depend upon solubility and chemical reaction within the body for some
materials.
The purpose of this study was to try to correlate other routes of
administration with the oral route. The procedure followed was to tabulate
all rat toxicity data in the Toxic Substances List which had information
on other routes of administration as well as oral LD . With this information,
it was then possible to correlate data using a linear regression analysis.
The toxicity data was transformed logarithmically, resulting in the following
general equation:
In (oral LD ) = a + b In (dose/response data for other route of
administration).
For the intravenous route, 181 values were used to obtain the
following:
In
-------
data were presented in parts per million which then had to be converted to
milligrams per cubic meter. The linear regression equation was found to be:
In (oral LD5Q) = -4.64 + 1.389 In (ihl LCLQ) .
This relationship was used to confirm the reasonableness of the following
procedure for converting ihl LC^ to oral LE) .
Using a standard 200 g rat with an average breathing volume of 74 cc/
min it should be possible to calculate an approximate LC^ from LD,_n data.
Generally, the exposure period for such information is 4 hours, making a total
3
inspiration volume of 74 cc/min x 240 min = 17.76 liters or 0.0178 m .
Recognizing that the weight inhaled is equal to the weight ingested, the
relationship can be further developed. For a rat for a 4-hour period,
LC5Q x V = LD5Q x W ,
3
where LC,.- is in mg/m
V is volume inhaled = 0.0178 m
LD5Q is in mg/kg
W is weight = 0.2 kg
Therefore,
LC50 = V X LD50 = 0.0178 x LD50
LC5() = 11.24 xLD5Q .
If we assume an LE> of 100 mg/kg, then the calculated LC,-0 = 11.24 x
100 = 1,124 mg/m . The calculated LC using the above linear regression
equation is 777 mg/m . That this value is of the right magnitude, lower than
the approximate LC,.-., indicates a reasonable correlation.
Using the above correlations with oral LD values, it should then
be possible to approximate an estimated permissible concentration (x ) from
m
rat toxicity data using these other routes of administration.
144
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The above correlations permit non-oral LD 's and LC 's for rats
to be converted to an oral LD5~ for rats. The oral LD „ measurement, in turn,
is the dose/response data in some of the equations in Section 5.3. Use of the
correlations will improve the quality of dose/response data when no oral LD _
is available; hence, the quality of the EPC or MATE will also be improved.
Table 5-5 summarizes the equation for performing the conversions.
5.5.3 Use of Chronic Effects Data
Dose/response data in the formulae (Section 5.3) are usually for
short-term or acute effects. This' means that the receptor organisms are exposed
to a high dosage of the chemical for a short period of time (hours, days, or
weeks). Yet, long-term or chronic exposure (months or years) and effects are
more like the real world situation around a coal cleaning facility. In the
chronic case, exposure occurs over a long period of time and responses may also
occur over long periods of time. For example, the death rate may be altered
or the number of malignant tumors in the population may increase. Chronic
effects are usually more difficult to quantify than the relatively straight-
forward LD,-0 (lethal dose to 50 percent of the population) and other acute
measurements. Thus, chronic effects data are more difficult to compare among
themselves than are acute effects data. On the other hand, any progress in
the use of chronic effects data is seen as a positive step.
Available published literature was reviewed on the effects of various
elements on rodents in (1) life-term, (2) mult igenerat ion, and (3) field/
laboratory comparison studies. Attention was given to the 10 priority elements,
but other elements also were reviewed. In the experiments, rats and mice lived
in environments relatively free of trace contaminants. Dosages of about 5 ppm
of specified toxicants were generally given in the drinking water. Standard
weighings and autopsies of control and experimental animals showed certain
trends.
Most of the data come from the laboratory of H. A. Schroeder
Information on virus transfer, ethylnitrosourea, and pesticides effects on
( 18—
multigenerations is also available , but since these materials are not
usually associated with emissions from coal cleaning facilities, the articles
were used only as auxilliary background information.
145
-------
TABLE 5-5. EQUATIONS RELATING TOXICOLOGICAL EFFECTS FROM NON-ORAL
ADMINISTRATION ROUTES TO THE ORAL ROUTE
Conversions
ivn LDso — > orl LD50
ipr LD5Q — > orl LDsg
scu LD5Q — > orl LDsg
ihl LC50 — > orl LD50
ivn = intravenous
ipr = intraperitoneal
scu = subcutaneous
orl = oral
Sample
Size Equations
181 ln(orl LD50) = -0.5714 + 1.587 ln(ivn LD50)
311 ln(orl LD50) = -0.1818 + 1.299 ln(ipr LD50)
171 ln(orl LD50) = 0.126 + 1.053 In (scu LD50)
101 ln(orl LD50) = -4.64 + 1.389 ln(ihl LCLo)
also: (orl LD50) = 0.08897 x (ihl LC50)
ihl = inhalation
LD50 = lethal dose fifty
LCso = lethal concentration fifty
LCT = lethal concentration low
146
-------
Table 5-6 presents the biological effects associated with an exposure
for life-term conditions. Responses of rats and mice did not differ a great
deal when data were available for both species. Thus, the following general-
izations are believed appropriate to both species. Some elements are virtually
innocuous to laboratory rodents; aluminum, barium, beryllium, and tungstem were
especially so. Some elements or forms of elements were very toxic to rodents;
e.g., selenate, and chromium (VI) were the most harmful. The other 19 were
intermediate, with typical responses as follows: increased longevity (chromium
III), suppressed weight (indium, scandium, etc.), shortened life span in one
or both of the sexes (arsenic, cadmium, etc.), increased number of tumors
(palladium, yttrium, etc.). In general, many of the 5-ppm dosages had some
adverse effect on the rodents. However, a critical question is whether repro-
ductive capacity was affected.
Chronic effects from the multigeneration or reproductive capacity
point of view are shown in Table 5-7. A subset of the elements in Table 5-6
was administered in drinking water to rodents of reproductive age (F = first
filial generation) through their progeny (F0 = second filial generation) to the
(12)
third filial generation (F_) ' . The responses varied. Mice exposed to
arsenic survived well, while those exposed to lead died out by the F_ generation.
Rats and mice exposed to cadmium, nickel, selenium, and titanium were inter-
mediate in response compared to the controls. In general, most of the chemicals
disrupted reproductive capacity, which would not be evident from acute effects
data.
When effects from the life-term and multigeneration studies of the
same element and similar dosages are compared, an important generalization
emerges. The life-term effects did not indicate the magnitude of the toxicant
effect on reproductive status revealed by the multigeneration effects studies.
For example, the multigeneration studies showed that cadmium's effects increased
in the F_ generation compared to the F generation. And this trend was also
true of effects from nickel, selenium, and titanium. Thus, a relatively minor
effect (loss of body weight) in F may not indicate the entire picture of a
chronic effect. Effects data from the perspective of many generations are
superior to life-term data which, in turn, are superior to data from only one
or two weeks of exposure.
147
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TABLE 5-6. SUMMARY OF BIOLOGICAL EFFECTS OF VARIOUS ELEMENTS ON MICE AND RATS
DURING LIFE-TERM (CHRONIC) EXPERIMENTS
Life-Term Effects on Rate
Element
Aluminum
Antimony
Symbol
Al
Sb
Dosage
(PP«)
5
5
Sample
Site
334
603
Cot
•vents
Virtually Innocuous
Life span and
longevity les-
Reference
US)
(11)
Dosage
(PP«)
5
Life-Term Effects on Mice
Sample
Site
540
Comments Reference
Suppressed growth and longevity (10)
(Antlmonlte)
Arsenic
(Arsenite)
sened; nonfastlng serum
glucose levels lower than
fasting; serum cholesterol
in soft tissues; not tumori-
genic
643
some accu
tissues
ulatlon in aoft
Shortened life span of oldest
10Z males and females; ac-
cumulated in organs; not
carcinogenic
(9)
OO
Barium
Beryllium
Cadmium
Chromium (III)
Chromium (VI)
Ba 5
Be
Cd
Cr
334
461
461
Slight growth enhancement;
virtually Innocuous
Cr — —
Fluorine F
(Sodium Fluoride)
Gallium
Germanium
(Germans te)
Indium
Lead
Ca — —
Ge — —
Pb
603
Slight growth depression;
virtually Innocuous
Arterlolar sclerosis in kid-
neys; cirrhosis of liver;
did not accumulate in kid-
neys; reduced life span
Increased longevity in last
10Z; females resisted epi-
demics of pneumonia; did not
accumulate
(16)
(16)
(8)
(8)
Increased glycosuria; accumu-
lated in aoft tissues; coats
of males were poor; not tum-
origenlc
(11)
697 Increased male mortality; Ion- (7)
gevity decreased in oldest
10Z of both sexes; fewer tu-
mors in male than controls
697 No toxicity observed (7)
S 9S8 Weight suppressed at 8 of 16 (13)
Intervals; tumors in 281
compared to 27Z in controls;
all tumors malignant
10 540 Females grew larger than (10)
males at older ages; not
tumorigenlc
5 958 Weight suppressed at 14 of 16 (13)
intervals; survival of older
females less than controls;
tumors In 26Z relative to
16Z In control
5 643 Shortened life span of oldest (9)
10Z of males; accumulated in
spleen with age; not car-
cinogenic
5 958 Height suppressed at 8 of 16 (13)
intervals
5 697 Increased mortality in males; (7)
longevity less in oldest 10Z
of both saxes
-------
TABLE 5-6. (Continued)
Element
Life-Term Effects on Rats
Life-Term Effect* on Mice
Dosage Sample
Symbol (pp.) Size
Comments
Reference
Dosage
(ppm)
Sample
Size
Comments
Reference
VO
•IcUl
Niobium
(Nlobate)
Palladium.
Rhodium.
Scandium
Selenium
(Selenate,
Selenlte)
Tcllunlum
(Tallurlte)
Tin
Titanium
Tungsten
Hi
Mb
104
603
Rh —
Sc
Se
Te
2, 3
313
313
So — —
li — —
334
Slight Increase in growth;
virtually Innocuous; did noc
accumulate In tissues
Increased glycosuria; not
tumorlgenlc
Selenlte was extremely toxic;
selenate did not affect
growth but was tunorlgenlc
and carcinogenic In older
animals
Concentrated In kidneys; tel-
lurlte did not affect growth.
survival and longevity
Slight growth enhancement;
alight shortening of longev-
ity; virtually innocuous
(15)
(11)
697
540
958
958
958
(14)
(14)
643
(16)
Increased mortality In males
Suppressed growth and longevi-
ty in females; increase in
hepatic fatty aoid degenera-
tion; not tumorigenic; sone
accumulation in soft tissue*
WeIght suppressed at 7 of 16
Intervals; survival of Bales
more In 291 relative to 16X
In control; ..ore malignant
tumors; appeared to be
alight carcinogenic activity
Weight suppressed at 6 of 16
Intervals; tumors in 292 rel-
ative to 162 In controls;
more malignant tumors; ap-
peared to be slight carcino-
genic activity
Weight suppressed at 10 of 16
intervals; tumors in 27Z
compared to 16Z control
No toxicity observed;
accumulated in spleen with
age; not carcinogenic
Longevity decreased in oldest
10% of both sexes; accumu-
lated in organs
(7)
(10)
(13)
(13)
(13)
(9)
(7)
Vanadium
(Vaoadyl)
Yttrium
Zirconium
(as metal)
V 5 603 Serum choleatrol abnormal; (11)
not tumorlgenic
Y — —
Zr 5 603 Increaaed glycosuria; not (11)
tumorlgenic
5 643 No toxiclty observed; accumu-
lated in organs; not car-
clnogenlc
5 958 Growth suppressed at 12 of 16
Intervals; tumors in 33Z
compared to 27Z on controls;
all tumors malignant
5 540 Showed alight toxicity; not
tumorigenlc
(9)
(13)
(10)
-------
TABLE 5-7. SUMMARY OF BIOLOGICAL EFFECTS OF SIX ELEMENTS
ON MULTIGENERATIONS OF MICE AND RATS(12)
Dosage
Element Symbol (ppm) Species
Major Responses by F3 Generation
Arsenic
Cadmium
Lead
Nickel
Selenium
(Selanate)
Titanium
CONTROL
As 3 Mice Survived well through F3; no runts; 8 young
deaths; 1 failure to breed; only abnormality was
a reduction in litter size
Cd 10 Mice Toxic to breeding mice by F2 generation; 5 litters
had congenital abnormally of the tail; 13%
runts; 2 still-born; 3 or 5 pairs failed to
breed in F2 generation
Pb 25 Mice Died out by F2 generation
25 Rats More tolerant to Pb than mice; birth in first
litters delayed; 35 deaths in F2; 3 pairs failed
to breed; 1 dead litter; 173 rats in Fj and 22
in F3
Ni 5 Rats Litter size decreased with each generation; few
males in F3; 121 rats in Fj and 81 in F3
Se 3 Mice Strain began to die out by F3 generation; 24%
runts; 7 pairs failed to breed
Ti 5 Rats 103 rats in F! and 16 in F3
— Mice, Deaths and runts rare; bred normally for four
Rats generations; 209 mice in Fj and 230 in F3 for
total of 687; 114 rats in Fj and 113 in F3 for
total of 348
Fj - first filial generation; Fa « second filial generation; F3 = third filial generation.
150
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In addition to life-term and multigeneration studies, a third avenue,
field/laboratory comparisons, was explored. The tissue concentrations of
rodents exposed to arsenic, cadmium, lead, and vanadium showed that these
elements tended to concentrate at higher levels in target organs than did
(7 91
these elements in the same organs of control animalsv ' . The implication
for field monitoring is that rodents could be trapped in the area around a
coal cleaning facility. Their organs could be removed and analyzed chemically,
allowing a comparison of the concentrations in healthy (control) and sick (or
exposed) animals, as in Table 5-8. Then assessment could be made about the
relative health of small mammals as indicator organisms of the overall health
of the ecosystem. Also, the observed elemental concentrations in the small
mammals can be related to concentrations for elements in the pathways discussed
in Section 4.0.
The implication of the above research is that data on acute responses
alone are insufficient. Acute effects data need to be supplemented by chronic
data and/or an adjustment made in the formulae. A series of comparisons of
acute and chronic effects data were attempted in order to establish a quanti-
tative relationship between the two types of effects. Unfortunately, no
commonality was obvious. This means that, until more research is performed,
no adjustment can be advanced.
5.5.4 Extrapolation of Response of
One Animal Species to Another
Methods of extrapolating from animals to humans depend heavily upon
the expirical relationship Y = aW which describes many biochemical parameters
(21-23)
(Y) of an organism as a function of the organism's body weight (W) . For
example, Y can be defined as metabolic rate, oxygen consumption, or a parti-
cular toxic response. For any specific definition of Y, a and b are constants,
so the same equation fits data for mammals whose body weight, W, ranges over
several orders of magnitude (i.e., all the way from mice to elephants).
Kleiber^ ' showed that the relationship Y = 70 W , where W = weight in kg,
described total metabolism, Y, in kcal/day for mammals ranging in size from
a rat to a steer. Also, this type of equation fits such data more accurately
(25)
when W represents body weight rather than body surface area , although
when Y is a toxic response body area may be useful.
151
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TABLE 5-8. TISSUE CONCENTRATIONS OF FOUR ELEMENTS IN ORGANS OF CONTROLS
AND EXPOSED MICE AND RATS
-------
The basic procedure for using the equation Y = aW as a means for
extrapolation obviously requires, first, that the equation be explicitly
known. That is, W and Y must be clearly defined and quantitatively measurable,
and the units in which they are expressed must be specified. Also, the
values for a and b must be known (a must be a positive number, whereas b can be
either a positive or negative exponent). Once the equation is known, an
organism's unknown toxic response (Y) can be predicted from the equation
simply by using the organism's known body weight, W, as input to the equation
and calculating the predicted Y as output.
The problem which complicates this approach is the fact that the
constants a and b usually are not known. Consequently, a and b must be obtained
by statistical estimation using a group of (W,Y) data points which have been
previously collected. Fortunately, the statistical estimation is quite
straightforward because Y = aW converts to a linear function when logarithms
are taken of both sides of the equation. That is, log Y = log a + b log W.
Therefore a and b can be obtained by performing a linear regression on log Y
data as a function of log W data. Also, the Y,W data should appear to fall
approximately on a straight line when plotted on log-log graph paper. Indeed,
part of this approach was used in correlating routes of administration
(Section 5.5.2).
Two methods for applying basic extrapolation procedures depend on
what unknown responses are to be predicted and what kind of data are already
available. In Method I the equation deals with only one toxicant at a time,
but this single equation can be used to predict the responses of animals of
many different species (including man) to that particular toxicant. In Method
II, the equation deals with responses to many different toxicants, but it can
be used only to extrapolate from the response of one particular species to the
response of another species (say, from rat to human). Both of these methods
•
are described in more detail below.
5.5.4.1 Method I. First, one toxicant must be selected for study,
and some consistent way of quantifying various species responses to that
toxicant must be chosen. For instance, suppose the toxicant is HgCl_ and the
153
-------
form of toxic response to be measured is the LD . Then data must be collected
from laboratory experiments which determine the LD^'s for a variety of mammals
in response to HgCl_. There will be at least one LD,.,. (Y ) corresponding to
each species (i) tested. (No exact way exists for determining the minimum
number of species which must be tested, but it should include species ranging
over several orders of magnitude in size; for instance, mouse, rabbit, dog,
and pig.) Then each LDcn (Y.) must be paired with the body weight (W ) of the
corresponding animal, and when the resulting set of (W , Y ) points are plotted
on log-log graph paper they should fall approximately on a straight line.
The equation of this line is then determined by linear regression as explained
earlier. This will yield the values a and b in the equation Y = aW .
Y = LD5Q, mg/Kg
in response to
HgCl2 (log scale)
steer
Y = aW
W = weight of animal, g
(log scale)
To interpolate or extrapolate the unknown LD for an untested animal, it then
becomes a matter of substituting the weight, W, of that animal into the equation
Y = aW and calculating the predicted Y value. This calculation procedure
enables the prediction of the LD .. not only for a human but also for other
animals important in a particular ecosystem, such as beaver or deer.
Several illustrative examples of the method of applying Method I
may be cited. Figure 5-2 compares the LD response of three species
LO
154
-------
iaooo
1000
0>
\
o»
3
o
ICX)
10
E I i i i MIII I i i i mil I i y\11i±
— x
- x
X
Cot
Guinea Pig
I I II Mill I I I I Mill I I I
100
1000
10,000
Weight, g
FIGURE 5-2. SUBCUTANEOUS LDLQ'S FOR HYDROGEN CYANIDE
Mil
IOQOOO
155
-------
to hydrogen cyanide, administered subcutaneously. The LD values (yg/kg)
J_iU
are plotted as a function of the mammals' weights on log-log graph paper. If
these weight-response data fit the basic model, Y = aW , the plotted points
should appear to fall approximately on a straight line; in this case a rough
linear relationship is indicated. The dashed freehand line was drawn to show
how the true regression line might look if least squares regression were
actually performed on this small set of data.
Figure 5-3 shows another sample application of Method I. Oral LD 's
in response to arsenic trioxide are plotted as a function of the body weights
of three different mammals, including man. In this example, the indicated
regression line has a negative slope; this relationship can occur when the
exponent, "b", in the equation Y = aW has a negative value. In both Figures
5-2 and 5-3, the hand-drawn dashed lines were included to indicate the approx-
imate positions of actual regression lines which would be used for extrapolation
and prediction.
5.5.4.2 Method II. This method uses an equation derived from Y = aW
and which can be considered a slight variation of it. Two species of animals
must be selected for consideration, the first being one on which laboratory
tests can be conducted easily, e.g., a rat, and the second being the one for
which extrapolated results are desired (usually, a human). A specific way of
quantifying the toxic response must be chosen for each species. For instance,
suppose the rat's response and the human's response are to be quantified as the
ID,., and the LD , respectively. Suppose further that both responses are to be
expressed in term of dose (concentration) per unit weight of body tissue, for
instance, mg/kg. Then the rat's response (X = LD,-,,) to a given toxicant and
the human's response (Y = LD ) to the same toxicant will be mathematically
(26)
related to each other .by a fixed constant, (T . That is, Y = CX. (The body
weights of the two animals are indirectly incorporated into this equation
through C.)
In order to determine what value C has, data points must be collected
whereby the responses of the two species to a variety of toxicants are known.
156
-------
IOO
TTTT
—^^ Mouse
i i iiiiiii i 11mm rrm
TTTT
10
o*
o
in
O
0.1
Rat
Human
10
IOO
raoo 10,000
Weight, g
100,000
FIGURE 5-3. ORAL LD5Q'S FOR ARSENIC TRIOXIDE
-------
There will then be at least one data point (X , Y ) available for each toxicant
tested, and the range of responses should cover several orders of magnitude.
(The responses of a rat (X.) can easily be obtained from laboratory experiments,
although empirical data about the human's response (Y ) may need to be obtained
from clinical or industrial exposure observations.) The set of (X , Y.) data
can then be fitted to a straight line using standard regression techniques and
the equation Y = CX can then be determined.
Y = LDLQ, mg/kg
for human (log
scale)
Y = CX
tellurium
sodium fluoride
nickel sulfate
ircuric chloride
lydrogen cyanide
X = LD5Q for rat (mg/kg)
(log scale)
Finally, this equation can be used to predict the unknown human response to
a new toxicant by experimentally determining a rat's response to that toxicant,
substituting that X value into the equation and calculating the estimated Y
value.
Freireich, et al./26^ used this method to derive the equation
Y = (1/7)X describing the relationship between the responses of rats and humans
to a variety of cancer drugs.
So far, it has not been possible to provide a good demonstration of
either extrapolation method due to the lack of readily available, adequately
large sets of parallel data. For many substances, the toxic concentration
values reported were given using different modes of entry for different
test species, and it would not make sense to fit the same equation to data
consisting of (for example) oral LD^'s for rats and subcutaneous LD 's for
158
-------
dogs. The LD is not a very precisely defined measurement; it may be over-
LiO
estimated by one or more orders of magnitude. LD 's and LC_'s are more
accurate measurements, but these values comprise a fairly small percentage of
the total set of data. In the future, more substantial sets of data will
be needed on which to base applications of the models.
5.5.4.3 Comparison of Methods I and II. Each of the methods (I and II)
has its own unique advantages and disadvantages. In both methods, it is safer
to use the obtained regression line for interpolation than for extrapolation.
That is, one will obtain more accurate predictions from the portion of the
line falling within the range of the input data points, rather than from the
portions of the line extending well beyond this range in either direction.
Method I is more appropriate to use in a situation where only one
toxicant is being considered at a time, and the researcher wants to study
the effects of that toxicant upon many different species of animals within
some ecosystem. Only one equation is needed to estimate all these effects.
However, the disadvantages of this method are that a separate equation must
be derived for each toxicant, and to fit just one equation requires that the
responses of a number of individuals or species of various sizes be known.
Anderson and Weber used an equation of the form LD,.,. = aW
(Method I) to predict toxic responses of guppies of varying body weights to
(22)
heavy metal compounds and dieldrin. Krasovskii studied the quantitative
relationships among the toxic responses of mammals to several hundred chemical
compounds and found that the general equation Y = aW could be used to char-
acterize these relationships for 80 to 85 percent of the compounds.
Method II is appropriate to use if man or another species is the
only organism whose responses are to be predicted. Only one equation is
needed to predict the human responses to a variety of toxicants; and to provide
the input necessary to this equation, all that is required is a simple experi-
ment with a laboratory animal. However, the disadvantage of this method is
that in order to derive this equation in the first place, prior data on human
responses for at least several toxicants is required. Accurate information
of this type may not be easy to acquire because direct experimentation
involving toxicants in humans is not possible.
159
-------
5.5.5 Toward a Biological
Basis for Safety Factors
Safety factors are often used in formulae that estimate permissible
concentrations. The review of formulae showed that safety factors of 10 to
100 were typical. However, the biological rationale for such safety factors
usually was not given. The typical approach for developing safety factors
has been arbitrariness; thus, there is a need for improved rationales for
safety factors. Available data about the ranges of toxicological responses
for selected organisms are reviewed in this part of the report. This research
is to provide data on which realistic safety factors can be derived empirically.
The scope of the present research permitted identification, assembly,
and study of about 15 articles. Pertinent information is presented in two
sections, followed by a compilation of selected findings related to safety
factors from the two sections. Throughout, responses are presented by type
of organisms, e.g., algae, fish, birds. One should recognize, however,
that the available data are sketchy. On the other hand, merely getting
a qualitative idea of variability of response (and thus the possible threshold
of the most sensitive species) to toxicants represents a step forward.
Toxicity levels of compounds in air, water, and soil vary widely.
Some substances seem to have no toxic effect at all while others are toxic
at concentrations in the parts per billion (ppb) range. Toxic levels and
effects of a substance may vary considerably (a) between species, (b) sometimes
between subspecies or races, and (c) during different life stages of an
organism. For example, toxicity ratios of neonates to adults can vary from
(28}
0.002- to 16-fold, a variation of almost four orders of magnitude.
Many differences in toxicity can be explained by the quantitative
differences in detoxification processes in young versus adult animals.
Increased membrane permeability in the young has been suggested as a possible
mechanism for age-related differences. Differences in hepatic and clearance
ratios that have been shown to occur (possibly involved in age-dependent
toxicity effects) may contribute to toxicity variation at both ends of the
life span(28).
160
-------
Variation among species' responses to toxicants is due to many factors
(29 30)
such as differences in body size and physiological responses. ' As an
example, carnivores tend to be more sensitive to toxic materials than herbivores:
this is probably due to differences in physiology (e.g., rates of excretion).
5.5.5.1 Ranges of Sensitivity in Selected Aquatic Plants and Animals.
The sensitivity of green algae to cadmium may vary by a factor of 100 between
species. Growth is inhibited in Chlamymonas reinhardi at concentrations of
0.1 ppm while Euglena gracilis can withstand concentrations up to 10 ppm for
seven days with no effects. Some ostracods (zooplankton) have cadmium sensi-
(29)
tivity similar to Chlamymonas.
Zooplankton also exhibit interspecific reactions to toxicants. The
(3D
responses of three species of zooplankton to various metals is presented
below in Table 5-9. Cyclops is the most resistant, followed by Eudiaptomus,
while Daphia is considerably more sensitive than the other species. The widest
range of response is for copper; the ratio of the least sensitive to the most
sensitive is 500.
TABLE 5-9. l,C,n CONCENTRATIONS OF VARIOUS METALS FOR
(3D
THREE SPECIES OF FRESHWATER PLANKTONv '
48-Hour LC5Q, mg/1
Metal
Chromium
Lead
Mercury
Cadmium
Copper
Cyclops
abyssorum
10.0
5.5
2.2
3.8
2.5
Eudiaptomus
padanus
10.1
4.0
0.85
0.55
0.50
Daphia
hyalina
0.022
0.60
0.0055
0.055
0.005
Ratio, Least to
Most Sensitive
455
9
400
76
500
Frog and toad larvae are sensitive to several metals. Boreal toads
(Bufo boreas) will not metamorphose in water whose iron concentration is greater
than 30 mg/1. These amphibians are more resistant to acidity than most fish,
161
-------
but are similar to other anuran larvae and salmonids (fish) in resistance to
(32)
copper and zinc . Leopard frog (Rana pipiens) embryos are much more
sensitive to mercury than either larvae or adults by a factor of 100 to 1000,
respectively. Sensitivity also varies in the different stages of embryonic
development. Ten ppb is lethal to cleavage and blastula stages while the tail
bud stage can survive 100 ppb (0.1 ppm) concentration with 90 percent survival.
(33)
Adults exhibit no mortality in concentrations of 5.0 ppm mercury and less
Thus, sensitivity varies by 2 and 3 orders of magnitude.
Salamanders (Ambystoma spp.) and closely related species of different
sizes exhibit differential toxicity to beryllium; 96-hour survival in soft
water with 10 mg/1 beryllium is only 20 perdent, while those in hard water
(341
exhibit no mortality. '
Immature fish forms 'are generally more sensitive than adults; however,
this varies with species and toxicants by a factor of at least two. The LD__
for rainbow trout embryos continuously treated with methyl mercury is approx-
imately 5 ppb, the values for channel catfish and largemouth bass are about
.
25 ppb, and for goldfish, the LD_0 is 500 ppb. ' The lethal values of
mercurial compounds are 580-1300 ppb and 2000-9200 ppb for adult catfish and
(33)
trout, respectively. Fish with large eggs and/or long development time
appear to be more susceptible to mercury and perhaps other metals. Fish
embryos, larvae, and early juveniles (ELEJ) are more sensitive to cadmium
than are adults. ELEJ sensitivity to mercury, lead, and zinc often varies
/oc\
with species. Relative interspecific sensitivity of some fish species
to various metals is presented in Table 5-10.
TABLE 5-10. SENSITIVITY OF EARLY JUVENILE FISH
TO VARIOUS METALS (36)
Sensitivity Range
Metal Most < > Least
Cadmium Brooktrout > Flagfish > Bluegill > Fathead Minnow
Copper Brooktrout > Fathead Minnow > Bluegill
Chromium Brooktrout > Fathead Minnow
Lead Flagfish > Brooktrout
Mercury Fathead Minnow > Flagfish > Brooktrout
162
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5.5.5.2 Ranges of Sensitivity to Toxicants of Selected Terrestrial
Animals. Embryos of birds tend to be more susceptible to metals than adult
forms. Chicks are very sensitive to selenium poisoning. In fact, areas with
high levels of naturally occurring selenium are first detected by low hatch-
ability of chicken eggs; the eggs exhibit no sign of poisoning and may be
fertile, but they do not hatch because of malformed or deformed embryos.
The TL,-n of selenium and other metals for chick embryos is as follows: selenium
and arsenic together - 0.01 ppm; arsenic alone - 0.05 ppm; methyl mercury alone -
(35)
0.1 ppm; mercury and lead together - 1.0 ppm. Adult mallards are generally
more resistant to toxicants than are bobwhites and pheasants, except for terpene
polychlorinated and some mercury compounds. Pheasants are about three times as
resistant to Ceresan M in feed as mallards (LC,-n of 146 and 50 for pheasant
(38)
and mallard, respectively).
Fetal and newborn mammals tend to be more susceptible to some metals
(e.g., selenium, mercury, arsenic, iron) than adults, and females are more
(39-41)
sensitive to selenium than males. Selenium in the diet in excess of
5 ppm may cause chronic toxicity; 10 ppm fed to sows results in pigs that are
small, weak, or dead at birth. Malformed or deformed young may occur in pigs,
(37)
sheep, cattle, and rats on a seliniferous diet. Selenium is an essential
micronutrient, but if it occurs in excess it may interfere with reproduction,
even at subtoxic levels. The range of adult to newborn toxicity ratios for
many pharmaceutical compounds was about 0.1 to 50 and averaged around 4.5 for
(39)
a subset of 62 nonpharmaceutical chemicals on the list of 400. Perhaps
a rule of thumb, then, is that baby mammals are four or five times as suscep-
tible as their adult counterparts.
5.5.5.3 Selected Findings Related to Safety Factors. The following
selected findings bring together in one place the more quantitative relation-
ships discussed in the previous two sections on safety factors.
(1) Differences in toxicity of a substance to different species
or ages is due in part to physiological and metabolic differ-
ences and body size.
163
-------
(2) Herbivores are generally more resistant than carnivores.
(3) The green algae Chlamymonas reinhardi is 100 times more
sensitive to cadmium than the algae Euglena gracilis.
(4) The zooplankton Cyclops abyssorum is 455 times, 9 times, 400
times, 76 times, and 500 times more resistant to chromium,
lead, mercury, cadmium, and copper, respectively, than
Daphia hyalina. Eudiaptomus padanus is intermediate in
sensitivity.
(5) Boreal toads will not metamorphose in iron concentrations
greater than 30 mg/1.
(6) Leopard frog embryos are 100 times and 1000 times more
sensitive to mercury than larvae and adults, respectively.
The cleavage and blastula stages are the most sensitive
stages in embryonic development.
(7) Beryllium is not differentially toxic to salamanders of
various ages, but is at least 5 times as toxic in soft
water as in hard water.
(8) Rainbow trout and channel catfish larvae, respectively,
are 116 to 260 times and 80 to 360 times more sensi-
tive to mercury than the adults. Fish species with
large eggs and/or long development times are the more
sensitive species.
(9) Bird embryos are more sensitive than adults and are espe-
cially sensitive to selenium.
(10) Mammalian fetuses are more sensitive than adults. New born
are about 4.5 times as sensitive to arsanilic acid, 1.5
times as sensitive to ferrous sulfate and lead arsenate,
and 0.6 to 0.9 times as sensitive to some mercury compounds
as adults.
(11) Few studies exist that compare sensitivity to metals in
developing young and adult homeotherms.
164
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5.6 Application of Improved Formulae
Application of the findings is the next most important step. Some
of the advances in the state of the art can be implemented immediately, while
others still require more "fitting" of the solution to the problem. For
example, the interconversion of various types of LD_'s can be utilized any
time there is no oral but there are non-oral LD_n measurements. The additional
formulae certainly can be used in future refinements of estimating environmental
goals in air and water.
Extrapolation of dose/response data from one species to another is not
as straightforward as one would like. On the other hand, some generalizations
can be applied. Generally, the larger the weight and surface area of an
organism, the greater the relative dosage needed to adversely affect that
species. Using this and other concepts, predictions of how another species
would respond in general can be made.
More conceptual work is needed on understanding chronic effects before
these data or adjustments to formulae using acute effects can be attempted.
Safety factors, which are a function of the test species, now have a
much stronger data base. A safety factor of 1000 is appropriate for aquatic
populations when the available dose/response data are from one of the less
sensitive species in the ecosystem. Thus, the insensitive as well as the
sensitive species can receive protection. If, on the other hand, available
dose/response data are for sensitive aquatic species, then a much smaller
safety factor would be needed for protecting all less sensitive species in
the ecosystem. For terrestrial situations, safety factor recommendations
are more difficult to establish. However, a safety factor of at least 10
is justified biologically.
165
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5.7 References
(1) Cleland, J. G., and Kingsbury, G. L., "Multimedia Environmental Goals
for Environmental Assessment", U.S. EPA 600/7-77-136a, J^ 148 + Appendices.
(2) Handy, R., and Schindler, A., "Estimation of Permissible Concentrations
of Pollutants for Continuous Exposure", Research Triangle Institute
Report, Contract 68-02-1325, Task 34 (September, 1975).
(3) Internal Commission on Radiological Protection, "Recommendations of the
International Commission on Radiological Protection. Report of Committee
II on Permissible Dose for Internal Radiation", ICRP Publication 2,
Pergamon Press, New York, 233 (1959).
(4) Walsh, P. J., Killough, G. G., Parzuck, D. C., Rohwer, P. S., Rupp, E. M.,
Whitfield, B. L., Booth, R. S., and Raridon, R. J., "CUMEX - Accumulative
Hazard Index for Assessing Limiting Exposures to Environmental Pollutants",
ORNL-5263. Oak Ridge National Laboratory, Oak Ridge, Tennessee, 63 (1977).
(5) Blackwood, T. R., "A Method for Estimating TLV Values for Compounds
Where None Exist", Letter Report from Monsanto Research Corporation,
Dayton, Ohio, to Chemical Process Section of EPA (April 15, 1975).
(6) The Toxic Substance List, 1976 Edition, U.S. Department of Health,
Education, and Welfare, Public Health Service, Center for Disease Control,
National Institute for Occupational Safety and Health (June, 1976).
(7) Schroeder, H. A., Balassa, J. J., and Vinton, W. H., Jr., "Chromium,
Lead, Cadmium, Nickel, and Titanium in Mice: Effect on Mortality, •
Tumors, and Tissue Levels", J. Nutrition, 83, 239-250 (1964).
(8) Schroeder, H. A., Balassa, J. J., and Vinton, W. H., Jr., "Chromium,
Cadmium, and Lead in Rats: Effects on Life Span, Tumors, and Tissue
Levels", J. Nutrition, 86, 51-66 (1965).
(9) Schroeder, H. A., and Balassa, J. J. , "Arsenic, Germanium, Tin, and
Vanadium in Mice: Effects on Growth, Survival, and Tissue Levels",
J. Nutrition, 92^ 245-252 (1967).
(10) Schoreder, H. A., Mitchener, M., Balassa, J. J., Kanisawa, M., and
Nason, A. P., "Zirconium, Niobium, Antimony, and Fluorine in Mice:
Effects on Growth, Survival, and Tissue Levels", J. Nutrition, 95,
95-101 (1968).
(11) Schroeder, H. A., Mitchener, M., and Nason, A. P., "Zirconium, Niobium,
Antimony, Vanadium, and Lead in Rats: Life-Term Studies", J. Nutrition,
100, 59-68 (1970).
(12) Schroeder, H. A., and Mitchener, M., "Toxic Effects of Trace Elements
on the Reproduction of Mice and Rats", Arch. Environ. Health, 23,
102-106 (1971a).
166
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(13) Schroeder, H. A., and Mitchener, M., "Scandium, Chromium (VI), Gallium,
Yttrium, Rhodium, Palladium, Indium in Mice: Effects on Growth and
Life Span", J. Nutrition, 101, 1431-1438 (1971).
(14) Schroeder, H. A., and Mitchener, M., "Selenium and Tellurium in Rats:
Effect on Growth, Survival, and Tumors", J. Nutrition, 101, 1531-1540
(1971).
(15) Schroeder, H. A., Mitchener, M., and Nason, A. P., "Life-Term Effects
of Nickel on Rats: Survival, Tumors, Interactions with Trace Elements
and Tissue Levels", J. Nutrition, 104, 239-243 (1974).
(16) Schroeder, H. A., Mitchener, M., "Life-Term Studies in Rats: Effects
of Aluminum, Barium, Beryllium, and Tungsten", J. Nutrition, 105,
421-427 (1975).
(17) Schroeder, H. A., Mitchener, M., "Life-Term Effects of Mercury, Methyl
Mercury, and Nine Other Trace Metals on Mice", J. Nutrition, 105,
452-458 (1975).
(18) Johnson, A. B., Groff, D. E., McConahey, P. J., and Dixon, F. J. ,
"Transmission of Marine Leukemia Virus (Scripps) from Parent to Progeny
Mice as Determined by p30 Antigenemia", Gander Res., 36, 1228-1232 (1976).
(19) Tomatis, L., Ponomarkov, V., and Turusov, V., "Effects of Ethylnitrosourea
Administration During Pregnancy on Three Subsequent Generations of
BDVI Rats", Int. J. Cancer, J.9_, 240-248 (1977).
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in the Tissues of Mice Fed Aldrin and DDT for Seven Generations", Arch.
Toxicol., ^i, 173-182 (1975).
(21) Adolph, E. P., "Quantitative Relations in the Physiological Constitutions
of Mammals", Science, 109, 579-585 (1949).
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Man", Environmental Health Perspectives, 13, 51-58 (1976).
(23) Zeuthen, E., "Oxygen Uptake as Related to Body Size in Organisms", The
Quarterly Review of Biology, 2j3 (1), 1-12 (1953).
(24) Kleiber, M., The Fire of Life: An Introduction to Animal Energetics,
(1961), John Wiley & Sons, New York, 200-212.
(25) Kleiber, M., "Body Size and Metabolic Rate", Physiological Reviews,
27_ (4), 511-541 (1947).
(26) Freireich, E. J., Gehan, E. A., Rail, D. P., Schmidt, L. H., and Skipper,
H. E., "Quantitative Comparison of Toxicity of Anticancer Agents in
Mouse, Rat, Hamster, Dog, Monkey, and Man", Cancer Chemotherapy Reports,
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167
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(27) Anderson, P. D., and Weber, L. J., "Toxic Response as a Quantitative
Function of Body Size", Toxicology and Applied Pharmacology, 33,
471-475 (1975).
(28) Casarett, L. J., and Boull, J., "Toxicology-The Basic Science of Poisons",
MacMillan Publishing Company, Inc., New York, 768 (1975).
(29) Buehler, K., and Kirshfield, H. I., "Cadmium in an Aquatic Ecosystem:
Effects on Planktonic Organisms", in T. Novakov (Ed.) Trace Contaminants
in the Environment, Proceedings of 2nd Annual NSF-RANN Trace Contaminant
Conference, Lawrence Livermore Laboratory, University of California,
Berkeley, California, 283-294 (1974).
(30) Stickel, W. H., "Some Effects of Pollutants in Terrestrial Ecosystems",
in A. D. Mclntyre and C. F. Mills (Eds.), Ecological Toxicology Research,
Plenum Press, New York, 25-74 (1975).
(31) Baudouin, M. F., and Scoppa, P., "Acute Toxicity of Various Metals to
Freshwater Zooplankton", Bull. Environ. Contain, and Toxicol., 12 (6),
745-751 (1974).
(32) Porter, K. R., and Hakanson, D. E., "Toxicity of Mine Drainage to
Embryonic and Larval Boreal Toads (Bufonidae: Bufo boreas)", Copeia 2,
327-331 (1976).
(33) Birge,'W. J., and Just, J. J., "Sensitivity of Vertebrate Embryos to
Heavy Metals as a Criterion of Water Quality-Phase I", U.S. Department
of the Interior, University of Kentucky Water Resources Research Institute,
Lexington, Kentucky, Res. Rpt. No. 71, 33 pp. (1974).
(34) Slonim, A. R., and Ray, E. E., "Acute Toxicity of Beryllium Sulfate to
Salamander Larvae (Ambystoma spp)", Bull. Environ. Contam. Toxicol.,
13 (3), 307-312 (1975).
(35) Birge, W. J., Westerman, A. G., and Roberts, 0. W., "Lethal and Terato-
genic Effects of Metallic Pollutants on Vertebrate Embryos", in T.
Novakov (Ed.) Trace Contaminants in the Environment, Proceedings of 2nd
Annual NSF-RANN Trace Contaminants Conference, University of California,
Lawrence Livermore Laboratory, Berkeley, California, 366 (1974).
(36) McKim, J. M., "Evaluation of Tests with Early Life Stages of Fish for
Predicting Long-Term Toxicity", J. Fish. Res. Bd., Canada, 3^, 1148-1154
(1977).
(37) National Research Council, "Selenium", National Academy of Sciences,
Washington, D.C., 203 (1976).
168
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(38) Heath, R. G., Spann, J. W., Hill, E. F., and Kreitzer, J. F., "Compar-
ative Dietary Toxicities of Pesticides to Birds", U.S. Department of
the Interior, Fish and Wildlife Service, Special Scientific Report -
Wildlife No. 152, Washington, B.C., 57 pp. (1972).
(39) Goldenthal, E. I., "A Compilation of LDSO Values in Newborn and Adult
Animals", Toxicol. Appl. Pharmacol., JL8_, 185-207 (1971).
(40) Friberg, L., and Vostal, J., "Mercury in the Environment - An Epidemic-
logical and Toxicological Appraisal", CRC Press, Cleveland, Ohio, 215
(1972).
(41) Versar, Inc., "Preliminary Investigation of Effects on the Environment
of Boron, Indium, Nickel, Selenium, Tin, Vanadium, and Their Compounds",
Volume IV - Selenium, Office'of Toxic Substances, Washington, D.C.,
EPA-560/2-75-0050 (1975).
169
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6.0 DECISION CRITERIA FOR PRIORITIZING
POLLUTANTS, SOURCES, AND PROBLEMS
There are major differences in the hazards posed to man and the
environment from different pollutants released as a result of coal cleaning
processes. One of the objectives of this study is to establish criteria for
rating the relative importance which should be placed upon identifying and
controlling specific pollutants from coal cleaning processes.
The position has never been taken during the investigation that
pollutants from coal cleaning processes could be prioritized into an ordinal
array, from the worst to the least. Rather, it has been considered that this
is an unattainable ideal and that a more realistic goal is to categorize them
into groups of varying degrees of hazard.
As noted in the Introduction, the fundamental criterion for ranking
the importance of any pollutant is the relationship between its expected environ-
mental concentration and the maximum concentration which presents no hazard
to man or biota on a continuous long-term basis. The estimated environmental
concentrations (EEC) of pollutants can be projected on the basis of coal
feedstock, process configuration, control devices applied, environmental
dilution and dispersion, etc. In the case of actual coal cleaning processes,
the EEC of pollutants can be measured by Level 1, Level 2, or Level 3 analyses.
The other half of the relationship, the estimated permissible concen-
tration (EPC), is quite another matter. As discussed in Section 5.0, the
toxicological and epidemiological data needed to characterize the relative
health and ecological risks of the pollutants to be expected from coal cleaning
processes are woefully inadequate. The information base is in far better shape
for many of the chemical compounds encountered in the chemical and similar
industries, but almost none of these are of any concern to coal cleaning.
Actually, the exact chemical form of many coal cleaning pollutants is unknown
more often than not. There appears very little likelihood that the EPC data
base for coal cleaning pollutants will improve dramatically in the near future.
170
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Thus, in spite of its undeniable theoretical soundness, the EEC/EPC
relationships probably will be unable to provide substantial prioritization
guidance over the near term.
Looking toward the longer term, one of the U.S. EPA's contractors,
the Research Triangle Institute, is developing the concept of multimedia
environmental goals (MEG's), of which health-related and ecology-related
estimated permissible concentrations for air, water, and land are key parameters.
Current status of this ongoing effort has been described by Cleland and
Kingsbury. Because of the data insufficiencies mentioned above, the MEG
tabulations for pollutants from coal cleaning processes are incomplete, which
limits the present application of MEG's.
Another approach to the estimation of acceptable concentrations
utilizes Minimum Acute Toxicity Effluents (MATE's). These are considered to
represent the very approximate maximum concentrations of pollutants in air,
water, or land effluents without adverse effects for short-term exposure.
As developed by researchers at Research Triangle Institute^ ', six MATE concen-
trations may be described for a single compound; two MATE's based on health
and ecology for each medium. While there are also large gaps in the toxicological
data needed to estimate MATE's, the types of data from which MATE's can be
derived, e.g., TLV's, LD 's, LD 's, LC 's, TD 's, etc., do not require the
jU LiU _}U 1-ivJ
extrapolations which are necessary to convert them to EPC's (see Section 5.0)
and are thus more amenable to empirical treatment.
Source Analysis Models (SAM's) have been developed by Acurex, another
of the U.S. EPA's contractors, to assist in comparing elements of an environ-
mental assessment. The simplest SAM, designated SAM/IA, is designed for rapid
screening of effluent streams and assumes no effluent transport or transfor-
(2)
mation. As described by Schalit and Wolfe , rapid screening of the degree
of hazard and the rate of discharge of toxic pollutants may occur at any level
of depth of chemical and physical analysis and may even be used to provide
guidance for Level 2 analysis. In SAM/IA, effluent concentrations are compared
to the appropriate MATE's; the comparison may also evaluate the difference
between an uncontrolled process and one with pollution controls.
SAM/IA also estimates a "degree of hazard" (H) which is the ratio of
a specific pollutant concentration in an effluent stream to its corresponding
171
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health-based MATE; the total stream degree of hazard can be calculated by
summing the individual H's.
Similarly, Toxic Unit Discharge Rates (TUDR's) can be estimated by
multiplying the degree of hazard (H) by the stream flow rate; these too can
be summed for the total stream. At present the narrowness of the data base
on MATE's also limits the application of SAM/IA to coal cleaning processes.
For the near term, a pragmatic approach to prioritization is possible,
based on the assumption that the relative importance of a pollutant can be
based generally on its toxicity and its abundance and that those substances
for which criteria have been established or which have been designated as
pollutants are important. The preliminary "Priority 1" list of pollutants
(see Section 3.1) had its origin in these considerations. The relative
importance for investigation probably has increased for the 13 inorganic
elements and their compounds because of their inclusion in the list of 65
toxic pollutants being considered for effluent limitations, as listed in
Table 3-8.
An important modifying parameter influencing the prioritization of a
pollutant is the availability, or lack of availability, of adequate pollution
controls. A high-risk pollutant, for which state-of-the-art controls are
inadequate, should have top priority for the development of adequate controls.
More information on adequacy of control, by pollutant, is needed to apply
these adjustments to relative rankings.
Preliminary working prioritization lists can be derived by comparing
the emission concentrations (uncontrolled and controlled) in each stream (air
or water) with the concentrations established by air or water quality criteria
or by regulation. These concentration levels may be health- or ecology-based,
or both; or they may reflect available technology, e.g., "best available
control technology" (BACT). Such lists will provide a working basis for
prioritization of R&D efforts while the more precise and sophisticated MATE's
and MEG's are being perfected.
172
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6.1 References
(1) Cleland, J.G., and Kingsbury, G.L., "Multimedia Environmental Goals for
Environmental Assessment - Vol. 1", EPA-600/7-77-136a, November, 1977.
(2) Schalit, L.M. and Wolfe, K.J., "SAM/IA: A Rapid Screening Method for
Environmental Assessment of Fossil Energy Process Effluents", EPA-600/7-
78-015, February, 1978.
173
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7.0 RECOMMENDATIONS FOR FUTURE WORK
While this research effort has developed a sound understanding of
the types and forms of the environmental assessment criteria needed in support
of the coal cleaning environmental assessment program, the perceived problems
existing at its commencement have not all been answered, and major new problems
have been uncovered along the way.
Thus, the basic recommendation for future work is to continue to bring
to completion the tasks already begun. Several more specific recommendations
can also be made. The order is not chronological, although the output of
one subtask can be the input to another. Also, some of the more complex
and fundamental problems will require long-term research for their full
elucidation.
7.1 Potential Environmental Pollutants
The Priority 1 list of pollutants should be reassessed when better
estimates of emissions and EPC's are available, in order to winnow out marginally
important pollutants and focus attention and efforts on the truly important
ones. Concomitantly, a number of potential pollutants omitted from that list
should be reassessed to reconfirm the correctness of the omission.
7.2 Estimation of Environmental Concentrations
The physical transport and dispersion models which are to be recom-
mended should be selected and exercised on simulated coal cleaning and util-
ization systems to demonstrate their appropriateness and applicability. As
soon as possible, these models should also be validated in the field using
actual data and modified as suggested by field experience.
With respect to ecological transport and fate, the recommendations for
future research fall into three major categories. First, there is an immediate
need to conduct research designed to determine the relative importance of each
exposure pathway for a series of populations within each compartment. A series
174
-------
of closely controlled experiments could be designed to estimate these values.
This would enable concentrated effort to be focused on the second major
category, which is the determination of the rate transfer coefficients for
each dominant pathway and the controlling parameters for each. The third
category of recommended research is simulation model development and field
test validation of the forecasts obtained from such models. An orderly timing
of these research recommendations could produce an accurate short-term index
of anticipated impact from released trace contaminants from a coal cleaning
facility.
7.3 Development' of Environmental Goals
Several recommendations can be suggested in this complex area, which
has possibly the most uncertain base for environmental assessment. More work
needs to be conducted on methodology which will permit making better use of the
variety of toxicological and epidemiclogical data which are available. For
example, data are available on animals other than laboratory rodents and fish,
on vegetation, and on microorganisms. Epidemiological data exist that should
be taken advantage of. Also, a wider range of toxicological measurements needs
to be utilized; this includes TDTn, LD _, and others. One specific task would
JLU LiU
be to interconvert the various toxicological measurements from the less fre-
quently used ones to a more standard measurement, i.e., LD,....
Adjustment factors in the formulae for estimating permissible concen-
trations need to be improved simultaneously with the use and development of
more and better effects data. A literature review of synergistic/antagonistic
effects would help to close one of the larger data gaps. Such a review would
be indispensible in interpreting the results of bioassays using complex
mixtures. Other adjustment factors need to be included too. For example, more
work is warranted on the relationship of chronic versus acute effects and
how to adjust acute effects data when an approximation of chronic effects is
needed. Special attention should be directed to chronic effects involving
irreversible alteration of genetic material.
175
-------
Present formulae deal with only one pathway at a time. Formulae
that handle exposure from multiple pathways should be further identified and/or
developed.
The development and refinement of environmental goals should continue.
They should be developed for electromagnetic radiation, water usage, and
complex mixtures in effluents. The environmental goals for single chemical
species should undergo continuous refinement, particularly the systematic
reduction and removal of deficiencies in the prediction formulae. All findings
need to be incorporated into the MEG concept.
176
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APPENDIX A
SAMPLE COMPUTER PRINTOUT FOR EMISSION
CONCENTRATION MODEL
177
-------
APPENDIX A
SAMPLE COMPUTER PRINTOUT_FQR EMISSION
CONCENTRATION MODEL^
INPUT DATA FOR THIS KUN ARE PRINTED BELOW
ANALYSIS GIVEN IMMEDIATELY BELOW REFERS TO CLEANED COAL PRODUCT
CARBON= .75800 H2 = .05070 02= .03300 bULFUR= .01660 N2= .01340
ASH = 0.12700 BTU = 13526.0/LB
ANALYSIS RIVEN BELOW REFERS TO TRACE CONSTITUENTS IN RAW COAL
NAME FRACTION NAME FRACTION NAME FRACTION NAME FRACTION
PYR S . 1820E-0l(b)okG S .4500E-02 SUL S .5000E-03 N .1160E-H1
AS .2400E-04 CD .1000E-06 PB .1450E-04 HG .3900E-06
FE .2180E-01 MN .4500E-04 BE .2600E-05 SE .3000F-05
AL .2B60E-01 ZN .6200E-04 NI .1710E-04
MASS FRACTIONATION FACTORS TO CLEANED COAL AND REFUSE RESPECTIVELY FOR
THE COAL WASHING STAGES AKE GIVEN BELOW
0.8000 0.2000
TRACE FRACTIONATION FACTORS FOR COAL CLEANING TO CLEANED COAL ARE GIVEN
BELOW. FRACTION TO REFUSE IS ONE MINUS FRACTION TO COAL.
NAME FRACTION NAME FRACTION NAME FRACTION NAME FRACTION
PYR S .5000 ORG S .8700 SUL S .5000 N .8700
AS .5300 CD .5300 PB .6700 HG .5300
FE .5300 MN .5300 BE .6700 SE .5300
AL .4700 ZN .6000 NI .6000
ASH,BTU, AND SULFUR CONTENTS RESPECTIVELY OF RAW COAL ARE GIVEN BELOW
0.2367 11689.0 0.0232
PROCESS WATER REQUIREMENT IS GIVEN BELOW IN TONS PER TON OF HAW COAL
1 .770
AIR FLOW FOR THERMAL DRYER IS GIVEN BELOW IN MSCF PER TON 0^ CLEAN COAL
FROM DRYER
26.00
FRACTION OF CLEANED COAL PRODUCT PROCESSED BY THERMAL DRYER IS GIVEN
BELOW
1.000
EXCESS AIR FOR COMBUSTION IS GIVEN BELOW AS 1 PLUS FRACTION FOR EXCESS
AIR
1.100
(a) See Section 4.1.2, "Estimation of Emission Concentrations", for brief
discussion of model.
(b) E-01 means 10"1, etc.
178
-------
TRACE FKACTIONATION FACTORS FOR COMBUSTION) PROCESS TO SLAG ASH ARE RIVEN
BELOW.FOR EACH CONSTITUENT. FRACTION TO AIR IS (i - FRACTION TO ASH) X
(1 - PRECIPITATOR REMOVAL EFFICIENCY)
NAME
PYR S
AS
FE
AL
FRACTION
.0000
. 1090
.31 10
.2930
NAME
ORG S
CD
MN
ZN
FRACTION
.0000
.6710E-01
.2630
.4030E-01
NAME
SUL S
PB
• -BE
NI
FRACTION
.0000
.4070E-01
.0000
.1590
NAME
N
HG
SE
FRACTION
.0000
.7000E-02
. 1040E-02
REMOVAL EFFICIENCIES FOR ELECTROSTATIC PRECIPITATOR AND THERMAL DRYER
SCRUBBER RESPECTIVELY ARE GIVEN BELOW FOR EACH TRACE ELEMENT
PYR S
OKG S
SUL S
N
AS
CD
PB
HG
FE
MN
BE
SE
AL
ZN
NI
0.0000
0.0000
0.0000
0.0000
0.9814
0.9699
0.9636
0.1163
0.9943
0.9931
0.9000
0.8571
0.9957
0.9809
1 .000
0.5000
0,5000
0.5000
0.5000
0.9800
0.9600
0.9600
0.5000
0.9900
0.9800
0.7500
0.7500
0.9900
0.9800
0.9900
EMISSION FACTORS FOR NOX, PARTICLES, HYDROCARBONS, AND CO ARE GIVEN
BELOW. ALL BUT PARTICLES ARE LBS PER TON. PARTICLES EMISSION FACTOR IS
LB/TON/% ASH.
13.00 16.00 0.3000 1.000
NUMBER PRINTED BELOW INDICATES ENERGY SOURCE FOR THERMAL DRYERl 0 = RAW
COALJ 1 = CLEAN COAL
0
179
-------
CALCULATED RESULTS FOH THIS HUM ARE PRINTED BELOW
TRACE ELEMENT ANALYSIS FOR CLEANED COAL IS GIVEN BELOW
NAME
PYR S
AS
FE
AL
FRACTION
. 1 138E-H1
. 1590E-04
. 1444E-01
. 1680E-01
NAME
ORG S
CD
MN
ZN
FRACTION
.4H94E-02
.6625E-07
.2981 E-04
.4650E-04
NAME
SUL S
PB
BE
NI
FRACTION
.3125E-03
. 1214E-04
.2177E-05
. 1283E-04
NAME
N
HG
SE
FRACTION
. 1261E-01
.2584E-M6
. 1988E-05
REQUIRED QUANTITIES OF CLEANED COAL AND RAW COAL FOR. 1 MILLION BTUS OF
ENERGY INPUT TO COMBUSTION ARE GIVEN BELOW
73.93LB 93.27 LB
TOTAL AMOUNT OF WASTE WATER STREAM INCLUDING REFUSE AND THE AMOUNT OF
REFUSE COMPONENT THAT HAS BEEN ADDED TO THE WATER ARE GIVEN RELOW.
183.7LB 18.65 LB .
TRACE ELEMENT ANALYSIS OF TOTAL WASTE WATER STREAM IS GIVEN BELOW
PYR S
AS
FE
AL
•4619E-02
.5726E-05
.5201E-02
.7694E-02
ORG S
CD
MN
ZN
.2970E-03
.2386E-07
. 1074E-04
. 1259E-04
SUL S
PB
BE
NI
. 1269E-03
.2429E-05
.4355E-0*
.3472E-05
N
HG
SE
.7655F-93
•9305E-07
.7157E-PI-S
TRACE ELEMENT ANALYSIS OF THERMAL DRYER ATMOSPHERIC DISCHARGE IS GIVEN
BELOW IN MICROGRAMS PER CUBIC METER
PYR S .1300E+06 ORG S .3215E+05 SUL S 3572. N .8288E+05
AS 6.112 CD .5332E-01 PB 7.951 HG 2.767
FE 2146. MN 9.479 BE 9.288 SE 10.71
AL 2889. ZN 17.01 NI 2.055
CALCULATED AMOUNT OF COMBUSTION AIR IN MSCF/MILLION BTUS IS GIVEN BELOW
1 1 .06
TOTAL MSCF OF FLUE GAS AND LBS OF ASH RESPECTIVELY FROM THE COMBUSTION
PROCESS ARE GIVEN BELOW
11.44 9.389
180
-------
TKACE ELEMENT ANALYSIS IN MICROGRAMS PER CUBIC METER FOR FLUE GAS AND
WEIGHT FRACTIONS FOK ASH STREAMS RESPECTIVELY ARE RIVEN BELOW. ASH
INCLUDES FLY ASH FROM PHECIPITATOR.
PYR S 0.1180E+07 0.0000
ORG S 0.5077E+06 0.0000
SUL S 0.3242E+05 0.0000
N 0.1309E+07 0.0000
AS 27.34 0.1231E-03
CD 0.1930 0.5070E-H6
PB 43.99 0.9228E-04
HG 23.52 0.2492E-06
FE 5885. 0.1133
MN 15.73 0.2336E-03
BE 22.59 0.1543E-04
SE 29.44 0.1342E-04
AL 5300. 0.1319
ZN 88.43 0.3594E-03
NI 0.0000 0.1010E-03
SULFUR COMPOSITION OF FLUE GAS IN LBS S02/MILLION BTUS AND MICROGRAMS
PER CUBIC METER RESPECTIVELY ARE GIVEN BELOW
2.455 0.1722E+07
NOX, PARTICLE* HYDROCARBON, AND CO MICROGRAMS PER CUBIC METER FOR FLUE
GAS ARE GIVEN BELOW
0.9337E+06 0.1054E+06 0.1556E+05 0.51R7E+05
SULFUR COMPOSITION OF THERMAL DRYER EMISSION IN LBS S02/MILLION BTUS
CLEANED COAL AND MICROGRAMS PER CUBIC METER ARE GIVEN BELOW
0.3970E-01 0.3315E+06
MICROGRAMS PER CUBIC METER OF NOX, PARTICLES, HYDROCARBONS, AND CO IN
THE THERMAL DRYER EMISSION ARE GIVEN BELOW
0.1286E+0A 0.2706E+05 2143. 7145.
ABOVE CONCENTRATIONS 'FOR PARTICLES ASSIIME 99% COLLECTION EFFICIENCY
OX
BYE
181
(reverse blank - 182)
-------
APPENDIX B
ADDITIONAL FORMULAE FOR DEVELOPING
ESTIMATED PERMISSIBLE CONCENTRATIONS (EPC's)
183
-------
APPENDIX B
ADDITIONAL FORMULAE FOR DEVELOPING
ESTIMATED PERMISSIBLE CONCENTRATIONS (EPC's)
There are additional approaches to predicting possible health/
ecological problems associated with coal cleaning activities. Two represen-
tative formulae are provided. Formulations and brief rationales are presented.
Formulae for International Commissions
on Radiological Protection^)*
These formulae were developed for estimating maximum permissible
concentrations of radioactive materials to which man could be exposed via
inhalation or ingestion. Other general comments are available in the text
(Section 5.5.1.1).
Maximum-permissible-concentration formulae for air- and water-borne
harmful materials, particularly radionuclides, are:
(1) For air: 1Q-7
(MPC)a= Tf -0.693t/T *Ci/cm
a
where (MFC) = maximum permissible concentration in air
a
qf» = burden of the radionuclide in the
critical body organ (yC.)
(where q = total radionuclide in the body
and f_ = the fraction in a particular
organ;
T = effective half-life (days)
f = fraction of inhaled radionuclide reaching
the organ of reference
t = period of exposure (days)
Other values are constants.
* Reference (3), Section 5.0.
184
-------
(2) For water: ^ ^ 1Q-4qf
(MFC) = AQWT ^C /cmJ
W Tf (l-e"°'693t/T) i
w
where (MFC) = maximum permissible concentration in water
w
qf_ = burden of the radionuclide in the critical
body organ (viC^)
T » effective half-life (days)
f = fraction of that taken into the body by
ingestion that is retained in the critical
organ
t = period of exposure (days)
Other values are constants.
The rationale for the formulae follows:
(1) Radioactive material is taken into the critical body organ at
a rate of P yC./day, where P = intake,
(2) Biological elimination from critical organs follows a simple
exponential law.
(3) Allowable concentrations are to be calculated for occupational
and continuous exposure. Occupational exposure occurs at the
rate of 40 hours per week and 50 weeks per year for a continuous
work period of 50 years. Continuous exposure occurs at the
rate of 168 hours per week. For continuous occupational exposure,
the MPC values should be divided by 2 x 365/(5 x 50) = 2.92 except
for submersion (external to the body) where they should be
divided by 3 x 365/(5 x 50) = 4.38. These values are further
explained on page 16 of the reference.
(4) MPC values based on a critical organ are set by requirements
that the dose rate after 50 years of occupational exposures
shall not exceed:
(a) 3 rems for the gonads or the total body during any
period of 13 consecutive weeks.
(b) Average RBE dose to the skeleton due to a body burden
226
of 0.1 yC of Ra when the effective RBE dose delivered
185
-------
to the bone from Internal or external radiation
during any 13-week period was averaged over the entire
skeleton.
(c) 4 reins in any 13-week period or 15 rems in one year for
any single organ except the gonads, bone, skin, and
thyroid: 8 rems in a 13-week period or 30 rems in one
year for skin and thyroid.
(5) During a 50-year exposure period, equilibrium is reached for
the majority of radionuclides because effective half-life is
short compared to this work period.
7 3
(6) The average breathing rate is 10 cm of air per 8-hour work
7 3
day (one-half of the air breathed in 24 hours - 2 x 10 cm ).
(7) The average rate of water consumption is 1100 cm per 8-hour
3
work day (one-half of the water consumed in 24 hours - 2200 cm )
(8) Chemical toxicity is not generally considered in estimating the
body burden or MFC values.
90 239
(9) For bone-seeking radionuclides such as Sr , Pu , etc., which
emit significant amounts of particulate radiation, the estimate
9 9 ft
is based, on a comparison with Ra and daughter products.
(10) For non-bone-seeking radionuclides, the MPC and body burden
values are set to limit the weekly RBE (relative biological
effectiveness) dose received by the various organs of the body.
Formulae for CUMEX , ..
(Cumulative Exposure) Index
CUMEX is a site-specific hazard assessment based on relationships
among media and biota. The index relates the concentration of the pollutant
in the medium to its concentration in a biological target. Other comments
on this formula are available in Section 5.5.1.2.
* Reference (4), Section 5.0.
186
-------
The basic CUMEX formulae are:
(a) For air:
A
(VAf
v A a
f A_M_f
AFFw
f ATTVt.f
AWWw
kf,
where C*
= CUMEX index for airborne effluent with
air as the sampling medium
= acceptable organ burden limit
V. = breathing rate of reference individual
(cm /day)
f = fraction of inhaled pollutant deposited
.
in reference organ
= transfer coefficient from air to food
M_ = mass consumption rate of food (g/day)
r
ATT
AW
fraction of ingested pollutant reaching
reference organ
transfer coefficient from air to water
volume consumption rate of drinking water
(ml/day)
partition coefficient for pollutant between
air and blood (ug/ml per pg/cm^)
fraction of pollutant in blood that is
deposited in the reference organ
cumulative retention to time, T, of
pollutant in reference organ (days).
(b) For water:
where
C*
W J?
+ VTTf ) R
* W w
= CUMEX index for a liquid effluent with
water as the sampling medium
= accepted organ burden limit
= transfer coefficient from water to food
= mass consumption rate of food (g/day)
187
-------
f = fraction of ingested pollutant reaching
the reference organ
V = volume consumption rate of drinking
^ water (ml/day)
R = cumulative retention to time, T, of
pollutant in reference organ (days).
When both effluent (air and water) types are present,
cl ciT
3
where C = concentration of the pollutant in air (yg/cm )
A.
C = average concentration of the pollutant in
drinking water (pg/ml)
C* = CUMEX index for airborne effluent with air
A
as the sampling medium
C* = CUMEX index for a liquid effluent with water
as the sampling medium.
The rationale for CUMEX follows:
(1) CUMEX indices can be determined practically if one knows in
detail source emission characteristics, environmental transport
process, and biological effects.
(2) Exposure, dose, or concentration limit depends upon the knowledge
of biological effects.
(3) If relationships among environmental compartments are understood,
measurements in a particular sampling medium (air, water, food)
along with transport models can suffice to assess human intake.
(4) Any estimation of total pollutant intake by humans and resulting
health effects must include contributions from all possible
routes of exposure.
(5) For the third equation, measurements in at least two sampling
media, along with transport models, will be necessary to assess
total human intake if there is more than one effluent type.
188
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
. REPORT NO.
EPA-600/7-79-140
2.
3. RECIPIENT'S ACCESSION-NO.
TITLE AND SUBTITLE Criteria for Assessment of Environ-
mental Pollutants from Coal Cleaning Processes
. REPORT DATE
June 1979
. PERFORMING ORGANIZATION CODE
. AUTHOR(S)
R. A. Ewing, B. W. Cornaby, P. Van Voris,
J. C. Zuck, G. E. Raines, and S. Min
;. PERFORMING ORGANIZATION REPORT NO.
. PERFORMING ORGANIZATION NAME AND ADDRESS
Battelle-Columbus
505 King Avenue
Columbus, Ohio 43201
10. PROGRAM ELEMENT NO.
EHE623A
11. CONTRACT/GRANT NO.
68-02-2163, Task 242
12. SPONSORING AGENCY NAME AND ADDRESS
EPA, Office of Research and Development
Industrial Environmental Research Laboratory
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD C<
Task Final; 9/76 - 4/79
COVERED
14. SPONSORING AGENCY CODE
EPA/600/13
15. SUPPLEMENTARY NOTES jERL-RTP project officer is James D. Kilgroe, Mail Drop 61,
919/541-2851.
16. ABSTRACT The pep0rt describes the development of criteria for assessing environ-
mental pollutants associated with coal cleaning processes. The primary problem
concerns emissions of pollutants to all three media--air, water, and land—and
assessing their effects on humans and the environment. Pollutants associated with
coal cleaning are primarily inorganic compounds associated with the ash fraction.
Lists of potential pollutants from coal cleaning and utilization, containing hundreds
of entries, have been proposed. Selected for investigation were 51 elements and 23
substances or groups of substances. The major criterion for ranking the importance
of any pollutant is the relationship between its expected environmental concentration
and the maximum concentration which presents no long-term hazard to humans or
biota. Environmental concentrations depend on emission rates and the effects of
physical transport and dispersion. Although these data will ultimately come from
field measurements, for now they must be estimated. Methodology for these esti-
mates are reviewed; the methodology is well developed and little further develop-
ment appears necessary. Ecological transport and distribution is much less well
developed: investigation shows large data gaps for many elements and species. Illus-
trative data are presented for eight of the more important trace elements.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
. COS AT I Field/Group
Pollution
Coal Preparation
Assessments
Criteria
Toxicology
Pollution Control
Stationary Sources
13B
081
14B
06T
18. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
201
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
189
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