TVA
EPA
i ennessee
Valley
Authority
U.S. Environmental
Protection Agency
Office of Research
and Development
L/ivision i tnergy Kesearcn
Division of Environmental Planning
Chattanooga. TN 37401
Industrial Environmental Research
Laboratory
Research Triangle Park NC 2771 1
KK;
EP-79
EPA-600
February 1979
Characterization of
Coal Pile Drainage
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 m 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-600/7-79-051
February 1979
Characterization of Coal
Pile Drainage
by
Doye B. Cox, Tien-Yung J. Chu,
and Richard J. Ruane
Tennessee Valley Authority
1320 Commerce Union Bank Building
Chattanooga, Tennessee 37401
Interagency Agreement No. EPA-IAG-D5-E-721
Program Element No. INE624A
EPA Project Officer Michael C Osborn.:
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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ABSTRACT
The five objectives of this research are (1) to develop an adequate
chemical characterization of coal pile drainage; (2) to develop a simple
laboratory methodology for predicting the chemical quality of coal pile
drainage; (3) to develop an estimation of rainfall return flow that could
be easily applied at other TVA locations; (4) to examine a practical
method for treatment of the waste; and (5) to achieve the first two
objectives using coal from at least twr sources.
Sampling programs were established at two TVA coal-fired steam
plants. Coal samples were collected from these plants for development
and application of a shaker-type elution test for coal analysis. Rain
gages were established at both plants, and runoff from one plant was
measured. Drainage was collected and subjected to a number of bench-
scale treatment studies using fly ash. Results indicate that:
1. Coal pile drainage is a highly acidic waste stream with pH's
ranging from 2.2 to 3.1. Total suspended solids concentrations
are generally low during base flow periods but increase drama-
tically during storm runoff to levels as high as 2300 mg/L.
Sulfate concentrations were also quite high with ranges from
1800 to 9600 mg/L. Concentrations of iron and manganese were
both very high, ranging from 23 to 1800 mg/L, and from 1.8
to 45 mg/L, respectively. Other substances with concentra-
tions of note include aluminum, zinc, mercury, arsenic, and
selenium.
2. About 73 percent of the total rainfall results as direct run-
off. There was no determination of evaporation or percolation
losses.
3. Characteristics of elutes from shaker-type laboratory studies,
with the exception of pH, do not reflect values from field
drainages of the same stored coal.
4. Treatment with alkaline fly ash slurries using ash sluicing
ratios commonly encountered can effectively raise the final
solution pH and remove a variety of metals from solution.
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CONTENTS
Page
Abstract jj
Figures fy
Tables V
Acknowledgments vl
1. Introduction 1
2. Conclusions and Recommendations 3
Hydrology 3
Chemical and physical characteristics 3
Laboratory studies 3
3. Background 5
4. Methodology 7
Plant J 7
Plant E 10
Laboratory studies 13
Data analysis 15
5. Results 16
Hydrology 16
Physical and chemical characteristics 16
Acidity and pH 19
Solids 22
Metals and trace substances 22
Discrete storm analyses 25
Data interrelationships 27
Laboratory studies 35
Acid-base balance 35
Coal analysis 35
Shaker tests 40
Neutralization studies 47
The pH of coal pile drainage and ash
sluice water mixture 48
Removal of metal ions by
precipitation in ash ponds 48
Effect of volumetric ratio of
coal pile drainage to ash
sluice water 48
Effect of ash character and
concentration 54
Effect of retention time .... 57
Solids settling 57
Field evaluation 57
References 63
Appendices
A. Procedures for coal analysis ..... 67
B. Hydrological data 73
C. Physicochemical data 80
D. Regression models for coal pile drainage 83
E. Quality Control data for TVA Water Quality Laboratory 86
ill
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FIGURES
Number Page
1 Coal pile and drainage collection system, plant J . . . 8
2 Sample collection system, plant J 9
3 Coal pile and associated drainage system, plant E . . . 11
4 Sample collection system, plant E 12
5 Regression of rainfall versus runoff 17
6 Physiochemical data for plants J and E 18
7 Results of discrete storm analysis 26
8 Results of time to equilibrium analyses 41
9 Coal pH 42
10 Results of varying coal to elute ratio and coal size . 43
11 Results of varying elute pH and hardness 45
12 Titration curves for alkaline fly ash slurry with
coal pile drainage 49
13 Titration curves for neutral fly ash slurry with coal
pile drainage 50
14 Residual iron concentration and volumetric ratio of coal
pile drainage to ash sluice water vs. pH 52
15 Concentrations of dissolved metals vs. pH 53
16 Equivalent concentrations of dissolved metal
concentrations 55
17 Residual iron concentration and ash concentration
vs. pH 56
18 pH vs. retention time 58
19 Residual iron concentration and initial volumetric
ratios of coal pile drainage to ash sluice water
vs. pH 59
20 Settling curve of coal pile drainage - fly ash
mixture 60
21 pH vs. total iron concentrations in an ash pond
effluent 62
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TABLES
Number Page
1 Comparison of Data from Plant J vs. Plant E 20
2 Rainfall Analysis 21
3 Inorganic Elements in Coal 23
4 Correlation Matrix - Plant E 28
5 Correlation Matrix - Plant J 30
6 Correlation Matrix - Both Plants (Plant E and Plant J) . 32
7 Correlations with r Values >0.71 34
8 Models Using IDS as Independent Variable 36
9 Acid-Base Balance 37
10 Coal Analysis - Plants J and E 38
11 Coal Analysis - Plant J 39
12 Results of Shaker Tests - Plants J and E 46
13 Chemical Composition of Coal Pile Drainage Used for
Treatment Study 48
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ACKNOWLEDGMENTS
This study was initiated by TVA as part of the project entitled
"Characterization of Effluents from Coal-Fired Utility Boilers," and
is supported under Federal Interagency Agreement Numbers EPA-IAG-D7-D-721
and TV-41967A between TVA and EPA for energy related environmental
research. Thanks are extended to EPA project officers, Julian W. Jones,
Michael C. Osborne, and Dr. Ron A. Venezia, and TVA project director
Dr. Hollis B. Flora II. Appreciation is also extended to Roger P. Betson,
Ralph D. Gillespie, Jerry E. Liner, Kenneth L. Ogle, Frank G. Parker,
Randall L. Snipes, and J. Michael Wyatt for their aid in the project.
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SECTION 1
INTRODUCTION
Twelve Tennessee Valley Authority (TVA) steam electric power plants
use coal combustion as an energy source. Because the waste streams from
these facilities are variable and diverse, TVA has been involved in
characterizing the wastewater effluents from coal-fired power plants
since 1968. More recently TVA, in conjunction with the Environmental
Protection Agency (EPA), initiated a comprehensive study entitled
"Characterization of Effluents from Coal-Fired Utility Boilers." This
comprehensive study includes projects to characterize chemical cleaning
wastes, limestone and slaked-lime sulfur dioxide scrubber wastewater,
cooling tower blowdown, chlorinated once-through cooling water, ash pond
effluents, ash pond leachate, and coal pile drainage. Additional studies
include ash pond mass balance studies and investigations of effluents
from once-through chlorinated cooling waters. This report deals with
the chemical/physical and hydrological characterization of runoff from
precipitation on coal storage piles. This runoff is contaminated with
the oxidation products of metallic (mostly iron) sulfides associated
with the coal. These oxidation products lower the pH of the runoff.
As a result of this depressed pH, the solubilities of many trace metals
associated with the coal are increased and they are leached from the
pile. Other oxidation products include iron, in ferrous and ferric form,
and sulfates.
Legal constraints restricting the discharge of these wastes are
promulgated by EPA in the form of NPDES permits. At present these
permits regulate only pH and suspended solids concentrations in the run-
off. The purpose of this characterization is to (1) determine the phy-
sical and chemical makeup of the waste, (2) compare the characterized
waste with existing regulations, and (3) examine or suggest possible
treatment technologies that will not only meet existing regulations,
but also achieve the purpose of existing regulations, i.e., the
protection of the aquatic environment.
If the untreated waste were to reach a receiving stream, it could
adversely affect the aquatic community in a number of ways. Most notably,
it could (1) depress the pH of smaller receiving streams (the effects of
low pH on aquatic life are well documented,1'2'* and will not be dis-
cussed here); (2) result in the precipitation of metallic hydroxides in
larger or highly buffered receiving streams (these particulates frequently
result in flocculent coatings that cover the stream bottom and effectively
destroy the benthic habitat); or (3) increase significantly the concen-
trations of trace metals in the receiving water (this usually results in
increased concentrations in edible species because of absorption or food
chain uptake). More dramatically, it could prove acutely or chronically
toxic and deplete sensitive species.
The project was developed with a number of objectives in mind:
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1. To develop an adequate chemical characterization of coal
pile runoff. This characterization would be limited to inor-
ganic constituents due to the high cost of analysis for trace
organics and problems with preservation of the samples.
2. To develop a simple laboratory methodology for predicting the
chemical quality of coal pile drainage. The method should be
easy to apply and require only readily available equipment and
expertise.
3. To develop an estimation of rainfall return flow that could
be easily applied at other TVA locations for use in design
of coal treatment, storage, and transport facilities.
4. To examine a practical method for treatment of the waste,
realizing that (1) the waste is probably high in dissolved
metals and will produce considerable amounts of sludge,
(2) the waste will be a high-volume waste that will occur
intermittently, and (3) the use of existing facilities would
be especially desirable.
5. To achieve the first two objectives using coal from at least
two sources. These two coals should differ chemically so that
the results would be applicable over a broader range of
conditions.
-2-
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SECTION 2
CONCLUSIONS AND RECOMMENDATIONS
HYDROLOGY
Results of the rainfall-runoff regression analysis indicate that
about 73 percent of the total rainfall results as direct runoff. No
investigations were performed to determine losses through evaporation or
percolation into the soil. The effects of this leachate on ground
water could be quite drastic if a significant portion of the losses
enter the aquifer. Studies to determine these effects should be under-
taken at a coal storage facility. In selecting sites for these future
studies, care should be taken to avoid facilities such as ash ponds
or other materials or waste storage facilities that could also affect
ground water quality. Other studies that would be of value are exami-
nations of the effects of various soil types, ground slopes, rainfall
regimes, and other climatological factors on rainfall return flows.
CHEMICAL AND PHYSICAL CHARACTERISTICS
Analysis of bulk precipitation samples indicate that atmospheric
loadings are not significant when compared to the total load of pollutants
in coal pile drainage. In general, coal from eastern sources has a
highly acidic waste stream with pH's ranging from 2.2 to 3.1. Total
suspended solids concentrations are generally low during base flow
periods but increase dramatically during storm runoff to levels as high
as 2300 mg/L. Sulfate concentrations were also quite high with ranges
from 1800 to 9600 mg/L. Concentrations of iron and manganese were both
very high, ranging from 23 to 1800 mg/L and from 1.8 to 45 mg/L, respec-
tively. Other substances with concentrations of note include aluminum,
zinc, mercury, arsenic, and selenium.
Total dissolved solids concentrations can be used to model the con-
centrations of several other variables. Since most of the dissolved
solids appear to be sulfate salts and high sulfate concentrations are
an indication of enhanced pyrite oxidation, it appears that many metals
may be mobilized as a part of the pyrite oxidation process. There was
no significant relationship between pH, suspended solids, or total flow
and other variables.
LABORATORY STUDIES
Total and pyritic sulfur analysis and the acid-base balance appear
to be poor indicators of the magnitude of acid production. The acid-base
balance in both cases indicated excess acidity but also indicated a larger
excess at plant E, which conflicts with field data.
Shaker-type elution tests do not accurately reflect field concentra-
tions of most constituents. It is not clear at this time whether this
type data can be used to predict field concentrations of iron, sulfate,
or nickel, where trends for laboratory and field data are the same.
-3-
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Certainly pH, total dissolved solids, and manganese cannot be predicted
since trends differ. Future studies involving other types of laboratory
type leaching studies would be desirable. These studies should involve
methods similar to those employed by Caruccio.4
Treatment of coal pile drainage by diverting it into an alkaline
fly ash pond appears to be quite feasible for pH control and removal of
iron and several other trace metals. Similar studies should be conducted
using dry fly ash for the treatment of coal pile drainage to demonstrate
a treatment technology where dry fly asn handling is employed.
-4-
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SECTION 3
BACKGROUND
To ensure uninterrupted generation of electricity, an outdoor coal
reserve is maintained at each power plant. This coal supply is available
for use if normal deliveries are delinquent, temporarily discontinued, or
inadequate to meet peak electricity demands. A 90-day coal supply is
customarily maintained to provide a sufficient safety factor. Factors
that preclude a larger coal stockpile include (1) cost of land required
for storage, (2) workmen and equipment needed to maintain the coal storage
area, (3) cost of the larger inventory, and (4) oxidative degradation
that occurs when coal is stored for long periods of time. Although the
physical volume of coal storage required varies with the plant consump-
tion rate, coal piles are typically 8 to 12 m (8.7 to 13.1 yd) high and
spread over an area 10 to 40 ha (25 to 100 acres). Normally 600 to
1800 m3 (780 to 2340 yd3) of coal storage is required for every megawatt
of rated capacity.
Coal pile drainage results from percolation of rainfall through
stored coal. The water quality of the drainage is affected by the leaching
of oxidation products of metallic sulfides associated with the coal.
The sulfide-bearing minerals that predominate in coal are pyrite and
marcasite, both iron sulfide ores. Marcasite is unstable and degrades
into pyrite. The oxidation of pyrite results in the production of ferrous
iron and acidity,8
2 FeS2(s) + 702 + 2 H20 -» 2 Fe*2 + 4H+ + 4 S04"2. (1)
This ferrous iron then undergoes oxidation to the ferric state in
a rate-limiting step:
4 Fe*2 + 02 + 4H* •» 4 Fe"1"3 + 2H+ + 2 OH*. (2)
Ferric iron then hydrolyzes to form insoluble ferric hydroxide, thus
producing more acidity:
Fe+3 + 3 H20 + Fe (OH)3 (s) + SH* (3)
or oxidizes pyrite directly, thus producing more ferrous iron and acidity:
FeS2(s) + 14 Fe"*"3 + 8 H20 -» 15 Fe+2 + 2 S04"2 + 16 H* (4)
The stoichiometry of this reaction reveals that for every mole of
ferrous iron oxidized in equation (2), there is a net increase of two
moles of hydrogen ion. This net increase in acidity provides hydrogen
ions for further oxidation of ferrous iron and subsequent acid production.
As the pH decreases below 5, certain acidophilic, chemoautotrophic
bacteria become active. These bacteria (Thiobacillus ferrooxidans,
Ferrobacillus ferrooxidans, Metallogenium, and similar species) are
active at pH 2.0 to 4.5 and use C02 as their carbon source.6 They are
-5-
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the main contributor to the oxidation of ferrous iron to the ferric
state, the rate-limiting step in the oxidation sequence. Their presence
indicates rapid pyrite oxidation and is usually accompanied by waters
low in pH and high in iron, manganese, and total dissolved solids.
Factors that possibly affect production of acidity in coal piles
and the subsequent leaching of trace metals are (1) concentration and
form of pyritic sulfur in the coal, (2) size of the coal pile, (3) method
of coal preparation and cleaning before storage, (4) climate, including
rainfall and temperature, (5) concentration of CaCOg and other neutral-
izing substances in the coal, (6) concentration and form of trace metals
in the coal, and (7) the residence time of the water in the coal pile.
-6-
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SECTION 4
METHODOLOGY
PLANT J
In 1972 a system was installed to collect coal pile drainage and
transfer it to an ash pond (Figure 1). Collection was accomplished by a
series of maintained channels around the coal pile that drain into a
storage basin. These channels are simple, earthen ditches which, over
time, have become lined with coal fines. Because the contribution of
these materials to the total load would be small, no attempt was made to
determine the effect of leachate from drainage ditch lining material on
the overall coal pile drainage characteristics. A manually operated
pump, an associated piping system, and a secondary maintained channel
transferred the drainage from the storage basin to the ash pond. The
storage basin was designed to contain the runoff from a moderately small
storm of perhaps one-half to one inch in a 24-h period. Because of this
limited capacity, the pump was activated manually at the start of almost
all rainfall events and actual detention time in the basin proper was small.
The sampling system (Figure 2) was designed so that pressure in the
line from the pump to the ash pond forced a sample into collection barrels.
The sample line was composed of tygon tubing with plastic fittings.
The sample barrels were plastic garbage cans with an approximate volume
of 150 liters each. The flow rate of coal-pile drainage from the storage
basin to the ash pond was about 2900 liters per min (770 gal/min). Flow
through the sample line was adjusted to about 0.1 liters per minute
(0.025 gal/min). This arrangement supplied a sample that was a composite
of the total volume pumped to the ash pond. Because of the acid nature
of the waste and the desire to collect pH and acidity data, the sample
was not preserved by acidification until the date of collection. The
maximum time lapse between the actual runoff collection and sample analy-
sis and/or preservation in the laboratory was seven days. However, since
rainfall occurred randomly throughout any given week, the mean time lapse
between collection and analysis and/or laboratory preservation was 3.5
days. The samples were manually stirred and then collected from a line
draining both barrels. Bulk precipitation samples were collected during
two rainfall periods. A plastic sample container was placed onsite and
allowed to remain until the completion of the first rain after placement.
This period was generally only a few days. Precipitation in this con-
tainer represented, in effect, atmospheric input to the pile. Chemical
analyses were performed at the TVA Water Quality Laboratory with methods
prescribed by the American Public Health Association,7 and EPA.8 Quality
Control Data for the TVA Water Quality Laboratory is presented in
Appendix E.
In summary, the samples collected at plant J represented a weekly
composite of a number of individual storms that may have occurred during
any given week. During a week when no rainfall occurred, no samples
were collected. Each of these weekly composites obviously consist of
at least one storm but may actually have been composites of several
storms. For statistical purposes, the former was assumed.
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DRAINAGE AREA * 53.3 ACRES (21.6 ho)
TO ASH
PONO
i
oo
COLLECTION
SUMP
Figure 1. Coal pile and drainage collection system, plant J.
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TO ASH POND
SAMPLE
LINE
SAMPLE
BARRELS
COLLECTION
SUMP
Figure 2. Sample collection system, plant J.
-9-
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A rain gage was placed next to the coal pile so that a relationship
between rainfall and runoff could be developed. This information will
be used to design future storage basins and to estimate losses through
evaporation and percolation. The amount of rainfall was compiled daily,
tabulated, and compared with hours of pumping time. Pumping rate was
determined by placing a temporary weir in the drainage channel down-
stream from the pump; this installation was subject to only minimal inflow
from the immediate vicinity. In cases of intermittent rain on several
consecutive days, which resulted in almost continuous operation of the
pump, the determination of individual -ainfall events and the associated
concurrent runoff was impossible. Instead, during consecutive days of
rainfall, total rainfall, and associated runoff over the entire period
were considered as single events.
Coal samples were also collected at plant J. Two methods were used.
An initial sample was obtained by grab sampling at eight locations on the
coal pile. These samples were composited to one 18-kg sample, which was
subsequently used to develop the shaker tests. Other samples were obtained
as monthly composites by plant personnel. These samples were extracted
from the coal bunkers daily and composited. All samples were crushed and
sieved to three size fractions (-40 mesh, +40/-18 mesh, and +18 mesh).
These samples were stored in plastic bags until use.
PLANT E
At the beginning of this project there was no systematic collection of
drainage from the coal storage pile. A system for transferring drainage to
the ash pond was recently completed. However, during the sampling period
the drainage moved in three separate directions (Figure 3)—drainages A and
B united at some distance downstream and flowed into a holding pond where
there was significant dilution of the coal drainage; drainage C quickly
spread out onto a mud flat. Because of the diversity of these discharges
and the expense of installing and maintaining even temporary flow gages,
drainage volume at plant E was not measured.
A modified automatic water sampler (ISCO model 780) was placed at one
drain, and a small sample pool was constructed (Figure 4). The water
sampler was equipped with a stage activation device so that the sampler
initiated sampling with the rise of the storm waters. Samples were col-
lected hourly and composited, thus representing a simple composite of
each storm event.
In summary, where weekly composites at plant J may have consisted of
runoff from one or many more than one storm, samples at plant E consisted
of a composite of only one storm runoff event. Statistical comparison of
samples grouped in this manner is valid since degrees of freedom were
limited, not by plant J, but by plant E.
Discrete samples were collected of a single storm event on February 24,
1977. Total rainfall for this event was 5.3 cm (2.0 in). These samples,
collected at 20-min intervals were analyzed for pH, acidity, dissolved
solids, suspended solids, sulfate, iron, and manganese. Rainfall was
measured onsite so that runoff could be estimated. Loadings of pollutants
-10-
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B
Figure 3. Coal pile and associated drainage system, plant E.
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I
>-•
K>
SAMPLER
STAGE
ACTIVATOR
LINE s,
H ,-STAFF GAGE
CONDUCTIVITY,
CELL
WEIR
Figure A. Sample collection system, plant E.
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can be projected by applying this estimate to composites of individual
storm events. Application of this simple method of composite and average
flow to calculate loadings of pollutants was demonstrated to be adequate.9
Three bulk precipitation samples were collected at this site in the
manner previously outlined.
LABORATORY STUDIES
There was a need to develop a laboratory procedure that could be
used to predict the chemical quality of drainage from coal storage piles
without resorting to expensive field sampling. Such a procedure should
be easy to apply and should require readily available equipment and only
a working knowledge of chemical and engineering principles.
These constraints eliminated the possibility of long-term leaching
studies which would be necessary if the biochemical processes that occur
in the field were to be duplicated in the laboratory. This being the
case, it was necessary to identify only those processes most important
in determining runoff quality and replicate them in the laboratory. These
processes were determined to be:
1. Oxidation of pyrite and subsequent acid production,
2. Chemical leaching of neutralizing substances in the coal, and
3. Weathering of the coal and subsequent leaching of trace metals.
The concepts and stoichiometry of pyritic oxidation have been pre-
viously discussed. Secondary concepts that must be applied with acid pro-
duction are neutralization potential and the acid-base balance (see
appendix A).
Neutralization potential is a measure of the neutralizing bases
present in a rock or, in this case, coal. Neutralization potential is
determined by treating the sample with a known excess of hydrochloric
acid, heating it to ensure complete reaction, and then titrating the
unconsumed acid with a standard base.10 By use of this procedure, the
neutralizing power in terms of CaCOs equivalent per unit of coal can be
calculated.
Acid production can be estimated in the laboratory by use of hydrogen
perioxide as an oxidant. The procedure involves boiling the sample in
reagent grade hydrogen perioxide to oxidize pyritic materials. The
resulting solution is then titrated with standard base. The acid poten-
tial can be calculated in terms of Ca(X>3 equivalent per unit of coal.
These quantities can then be summed to produce an acid-base balance
that will reflect either excess acidity or neutralizing potential. It
should be recognized that this quantity represents at best a semiquanti-
tative estimate of the acid-base relationship.
-13-
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An extensive literature review revealed that very few studies have
investigated coal pile drainage and fewer still have proposed methods
for predicting the quantity and quality of this drainage. These studies
generally were long-term leaching studies primarily concerned with strip
mine overburden. Leaching of coal was a relatively minor part of these
experimental designs. There were, however, laboratory tests designed
for application to strip mine overburdens. It was determined that an
elution-type leaching procedure would best approximate weathering of
coal, and development of this procedure was undertaken.
The three size fractions produced from the 18-kg sample of coal
collected at plant J were subjected to a series of analyses, including
(1) proximate analysis, (2) ultimate analysis, and (3) forms of sulfur
analysis.
Subsamples were ashed and the ash analyzed for the following parameters:
Si02 S03
A1203 Na20
Fe203 K20
CaO Mn
TiO Pb
MgO Cu
The remainder of the samples were used to evaluate conditions that
might affect results of the leaching procedure. The variables included
shaking time to equilibrium, coal pH, coal to elute ratio, size of coal,
elute pH, and elute hardness. The procedures for these investigations
are included in appendix A.
Once the effects of varying these parameters were known, a set of
standard conditions was chosen. Monthly samples of coal collected by
plant personnel at the two plants were shaken using these standard
conditions. Results obtained from the two plants were compared with
each other and field data.
A series of neutralization studies was undertaken to address the
fourth objective of this project, i.e., development or demonstration
of a method for treatment of coal pile drainage.
Bench-scale treatment tests were performed to examine the ability
of fly ash slurry to treat coal pile drainage. The variables involved
in these bench-scale studies involved examination of the effects of (1) the
volumetric ratios of coal pile drainage to ash sluice water, (2) the con-
centration of ash in the sluice water, (3) filtration of the ash before
mixing, (4) variations in ash characteristics, and (5) retention time of
the ash-sluice coal pile drainage system on the final pH and the removal
of iron and other trace metals from the mixture.
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Solids settling tests were also performed using the iron hydroxide
floes (that were produced when the coal pile drainage was neutralized with
ash sluice water) and iron hydroxide floes mixed with fly ashes.
DATA ANALYSIS
Data analysis was accomplished by a number of statistical techniques
applied by use of a software computer program (SAS, Statistical Analysis
System) available from the SAS Institute, Inc., P.O. Box 10066, Raleigh,
North Carolina 27605.1X
A detailed description of statistical techniques is well beyond the
scope of this presentation. Textbooks particularly helpful in the statis-
tical evaluation of data include works by Draper and Smith (1966),12 Lipson
and Sheth (1973),l3 and Tukey (1977).14
-15-
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SECTION 5
RESULTS
HYDROLOGY
Most of the rain that falls on a coal pile either drains as surface
runoff, percolates into the soil to become ground water, or is lost
through evaporation. Some small amoun^ of moisture flux also is asso-
ciated with coal pile dynamics. Evaporation will occur primarily on
the surface of the coal pile because of rapid drainage of rainwaters
through interstices that are large relative to soils. Therefore,
conventional estimates of evapotranspiration used in most hydrological
models would probably be inapplicable. Because of these problems and
the expense of installing large flumes for long-term measurement of
flows, detailed hydrological models were not calibrated for use as a part
of this study. Instead, a simple relationship between rainfall and runoff
was developed. Because rainfall, temperature, wind velocity, and humidity
are similar throughout much of the Tennessee Valley, such a rainfall-runoff
relationship can be used to estimate detention basin design and to calcu-
late acid loads to the ash pond for TVA facilities or for other locations
having similar conditions.
A regression analysis of storm period rainfall vs. runoff was
performed for data collected over a seven-month period at plant J
(see appendix B). Runoff was calculated by multiplying hours of
pumping time by an average pumping rate. The average pumping rate
was determined by placing a temporary weir downstream from the pipe
discharge. This flow rate for 31 storms that occurred between
March 11, 1977, and June 27, 1977, was determined to be 2900 liters
per min (771 gal/min) with a standard deviation of 790 (appendix B).
Rainfall was measured continuously onsite. A plot of the regression
line and the 95 percent confidence intervals of the mean are presented
in Figure 5. The regression, equation (5) can be used to predict the
runoff (in centimeters of depth) over the coal pile area for a given
amount of storm rainfall (in centimeters).
Runoff (cm) = 0.726 rainfall (cm) (5)
Runoff can be converted to total runoff by multiplying by the
drainage area and an appropriate volumetric term. Losses attributable
to evaporation and infiltration, as indicated by equation (5), are about
27 percent. Application of this relationship is, of course, limited to
similar climates and to coal piles of similar size. Additional factors
that could affect the relationship include significant amounts of snowfall
and different soil permeabilities.
PHYSICAL AND CHEMICAL CHARACTERISTICS
Figure 6 depicts means, ranges, and standard deviations of the
physicochemical properties of coal pile drainage from plant J and
plant E. A listing of the raw data appears in appendix C.
-16-
-------
12.7 r
RUNOFF =0.726 RAINFALL
5.1
7.6
RAINFALL (cm)
102
12.7
95% CONFIDENCE LIMITS
FOR THE MEAN
152
Figure 5. Regression of rainfall versus runoff.
-------
Figure 6. Physicochemical data for plants J and E.
IOOOO:
lOOOOOp
1000 =
u
10000-
100;=
€ K>
0 le
Mn
a
f-
L " _
Zn
m
ff i
i
'C
g F
100-
t
\
CO
i !
001 =
OOOI1-
-fcf-
I'OOO)
(J) (E)
o -o-
Hg 1 I]
jl-J
100 c
10000 =
fe 1000 n
F C
100-
10
o.sou
10 =
S04
AOO
CONO
I
PM
SSOL
_L i
JI-2Z3)
8 o.ifc
r—
F
r~
0.011
0.001
-18-
Ba
Ti Sb
(J) (E) I
-ry^v n
RFI
A
-0--0-
ll
I
L d
B«
5
I
i
i
1
PLANT
E J
O O -MEAN
•RANGE
II-
| Q - STANDARD DEVIATION
( ! -MIMMUM STANDARD DEVIATION
-------
Table 1 shows the results of an analysis of t distributions for
comparing the means of data from plants J and E. The assumptions of
equal and unequal variances are presented. Either hypothesis will
suffice in all instances with the exceptions of chlorides, cadmium,
and titanium. In the case of chlorides, there are insufficient
analyses at plant J. Cadmium and titanium are always below the
detection limit at one plant or another. These circumstances render
the t test inappropriate.
Results of bulk precipitation analyses appear in Table 2. The
rainfall pH is quite low at both plants; however, acidity is also low.
These results reflect analyses of samples containing both dryfall
(particulate) and rainfall. Since no chemical data is readily
available on particulate fallout and the metal content in bulk
precipitation samples small, it can be assumed that the contribution
of this type sample is small in comparison to the total metal content
in coal pile drainage. However, metals in which atmospheric loadings
could be significant are copper, lead, mercury, and possibly zinc and
nickel.
Acidity and pH
Both systems investigated exhibited highly acidic drainages.
Acidity was determined as ''c^_
-------
TABLE 1. COMPARISON OF DATA FROM PLANT .1 VS PLANT E
Parameter
pH
Acidity
Conductivity
Chlorides
Sulfate
IDS
TSS
Fe
Mn
Si02
Cu
Zn
Cr
Al
Ni
Ca
Mg
Pb
Hg
Ba
As
Cd
Se
Ti
Be
Sb
t
3.26
3.22
1.80
-3.61
2.79
3.76
0.962
5.15
10.7
6.91
9.32
4.81
0.133
8.97
9.04
-0.408
5.62
0.00
-4.79
0.831
5.26
-2.17
2.32
0.00
8.14
3.69
Variances
Degrees of
freedom
27.4
29.9
19.9
11.6
25.5
29.8
23.4
25.5
27.2
20.5
28.1
27.6
23.2
22.7
20.7
15.2
21.6
30.0
10.9
20.1
20.0
11.0
23.0
11.0
27.0
24.0
unequal
Means significantly
different at
95% confidence
Yes
Yes
No
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
No
Yes
No
No
No
Yes
Yes
Variances equal
t
3.06
2.80
1.88
-1.45
2.53
3.25
0.768
4.06
8.59
5.15
7.54
3.87
0.134
6.61
6.83
0.472
4.58
0.00
-6.36
0.843
3.53
-2.91
1.70
0.00
6.78
2.83
Degrees of
freedom
31.0
30.0
27.0
12.0
27.0
30.0
30.0
31.0
31.0
29.0
31.0
31.0
28.0
30.0
31.0
31.0
29.0
31.0
30.0
28.0
27.0
.31.0
28.0
31.0
28.0
27.0
Means significantly
different at
95% confidence
Yes
Yes
No
No
Yes
Yes
No
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
No
Yes
No
Yes
Yes
No
No
Yes
Yes
-------
TABLE 2. RAINFALL ANALYSIS
Rainfall, cm
pH, standard units
Conductivity, ymhos/cm
Acidity, mg/L as CaC03
Dissolved solids, mg/L
Suspended solids, mg/L
Elements, mg/L
Iron
Manganese
Chloride
Sulfate
Copper
Silica
Zinc
Chromium
Aluminum
Nickel
Magnesium
Calcium
Lead
Beryllium
Antimony
Barium
Arsenic
Cadmium
Selenium
Titanium
Mercury
J
5.16
4.5
51
-
20
1
0.14
0.01
2
19
0.07
1.8
0.07
<0.005
<0.2
<0.05
1.9
-
0.01
<0.01
<0.1
<0.1
<0.005
<0.001
<0.001
<1.0
-
J
2.29
4.5
180
6
40
8
0.21
<0.01
3
16
0.07
0.30
0.14
<0.005
0.3
<0.05
0.2
1.0
0.03
<0.01
<0.1
<0.1
<0.002
0.002
<0.001
<1.0
0.0006
J
3.73
4.5
116
6
30
5
0.18
0.01
3
]8
0.07
1.1
0.11
<0.005
0.3
<0.05
1.1
1.0
0.02
<0.01
<0.1
<0.1
<0.005
0.002
<0.001
<1.0
0.0006
Plant
E
8.28
3.5
360
25
20
2
1.1
0.02
2
3
0.03
0.10
<0.01
<0.005
0.5
0.05
0.5
1.0
0.015
<0.01
<0.1
<0.1
<0.002
<0.001
<0.001
<10
0.0002
E F.
4.24 5.33
4.4 4.1
33 31
6 7
30 <10
16 43
0.56 <0.05
0.02 0.01
<0.1
8 10
0.05
73
0.20
- -
_
0.09
0.1
1.0
_
<0.01
<0.1
-
- -
- -
-
-
0.0060
E
5.95
4.0
141
13
20
20
0.57
0.02
0.11
7
0.04
37
0.11
<0.005
0.5
0.07
0.3
1.0
0.015
<0.01
<0.1
<0.1
<0.002
•0.001
<0.001
<10
0.003
-------
Solids
Concentrations of total suspended solids are of primary interest in
characterization of coal pile* drainage. Elevated concentrations occur
during rainfall periods when high runoff rates suspend coal fines and
transport them from the pile. This is generally not a problem during
base-flow conditions, but occurs during runoff events at levels up to
2300 mg/L.
Concentrations of suspended solids at plant J ranged from 8 to 2300
mg/L, with a mean of 470 mg/L; these samples were collected after they
had passed through the collection sump. At plant E, where direct runoff
was collected as a simple composite sample for each storm event, the mean
and range of suspended solids concentrations were not significantly dif-
ferent from plant J. This similarity indicates that residence time in
the collection sump was not sufficient for appreciable settling to occur.
Values for suspended solids much higher than this were presented by
Matsugu.17 The Environmental Protection Agency has promulgated regula-
tions limiting total suspended solids concentrations from materials
storage to 50 mg/L.
Concentrations of total dissolved solids were significantly higher
at plant J than at plant E. Inspection of the data reveals that most of
the total dissolved solids are sulfate salts. Hence, higher concentra-
tions of total dissolved solids are a consequence of enhanced pyritic
oxidation by equations (1) and (4) and suggest that pyritic oxidation
is occurring at plant J.
Metals and Trace Substances
Little information is available on trace element concentrations in
coal pile drainages. Trace elements of environmental concern in coal
that have been identified by EPA18 are presented in Table 3. These
constituents, except for yttrium, potassium, and sodium were analyzed
in drainages from both plants. Several other elements were analyzed
in both drainages.
Iron and manganese are often discussed simultaneously because of
their similar behavior in water. Both are increasingly soluble with
decreasing pH, exist in both the reduced and oxidized states, and form
coatings on particles that may limit solubilities of other metals.19
Typically, iron and manganese concentrations in pyritic systems are
quite high. Iron minerals are the substrate necessary for acid
production, equations (1) through (4). As such, lower concentrations
would be expected only where pyritic oxidation is repressed or where
pH is not depressed sufficiently to allow for iron solubility. Values
for iron reported by Nichols15 ranged from 0.17 to 93,000 mg/L, with a
mean of 19,500 mg/L. This range seems to be exceptionally wide,
probably because of the diversity of coal samples. A somewhat
narrower range of 10 to 5300 mg/L and a lower mean of 1150 mg/L were
reported by Anderson and Youngstrom.16
-22-
-------
TABLE 3. INORGANIC ELEMENTS IN COAL
CJ
I
Major
Element
Silicon
Iron
Aluminum
Calcium
Potassium
Magnesium
Titanium
Sodium
Range
(Wt. %)
0.6-6.1
0.3-4.3
0.4-3.1
0.1-2.7
0.1-0.4
0.1-0.3
0.0-0.3
0.0-0.2
Element
Beryllium
Nickel
Copper
Zinc
Arsenic
Trace
Range
(Mg/g)
0-31
0.4-104
2-185
0-6000
0.5-106
Element
Selenium
Yttrium
Cadmium
Mercury
Lead
Range
(ug/g)
0.4-8
0.1-59
0.1-65
0.01-1.6
4-218
Source: Environmental Protection Agency. 1976. Fuel cleaning program:
Report, SPA-600/7-76-024, Washington, DC.
coal. EPA Program Conference
-------
Iron concentrations at both plants are lower in range and mean than
concentrations encountered by these investigators. Iron concentrations
at plant E ranged from 23 to 590 mg/L, with a mean of 350 mg/L. Concen-
trations of iron at plant J were significantly higher, with a range of
240 to 1800 mg/L and a mean of 940 mg/L. These concentrations, as do
elevated sulfate concentrations, suggest enhanced pyritic oxidation.
Silicon (as Si02) appears in drainages from plant J at a mean level
of 174 mg/L and at plant E at a mean level of 33 mg/L. The difference is
significant at the five percent level.
Aluminum, a fourth major element in coal, is included as a toxic
substance by the National Academy of Sciences*0 in their development
of proposed water quality criteria, but eliminated by EPA21 in their
development of finalized criteria. Thus, the significance of aluminum
as a toxic substance is questionable. The mean concentrations of
aluminum in drainages from the two plants were 43 and 260 mg/L for
plants E and J, respectively. The difference in the means is
statistically significant.
Titanium concentrations were below the detection limits for all
samples at both plants.
Calcium and magnesium concentrations in the drainages reflect the
presence of neutralizing substances in the coal. Concentrations of
calcium were similar in both drainages as reflected by the means, 300
mg/L for plant J, and 320 mg/L for plant E. Magnesium concentrations
were significantly higher at plant J than at plant E with means of 245
mg/L and 65 mg/L, respectively. This lower mean suggests that there are
less neutralizing substances leached from the coal at plant E.
Acidity and pH of the drainage reflect acid production, solubility
of the acids produced, and neutralization of the acids from alkaline
materials. Since there are more alkaline materials in solutions from
plant J than for solutions of equal pH and acidity at plant E, there
would have to be more acid produced at plant J to neutralize these
materials and still maintain the same pH and acidity. This conclusion
substantiates the evidence of enhanced oxidation of pyrite at plant J.
This hypothesis is reinforced when sulfate concentrations are
compared. Sulfate is the best indicator of pyrite oxidation since
(1) for every mole of pyrite oxidized, two moles of sulfate are
produced, and (2) sulfate is a relatively conservative substance
when compared to pH and acidity which can be easily affected by the
presence of neutralizing substances or iron which can be readily
precipitated. Concentrations at plant J are significantly higher
than those at plant E. The respective means are 5000 mg/L and 3050 mg/L.
Concentrations of copper at plant J are lower than those reported
by Nichols,15 or Anderson and Youngstrom.16 Concentrations for plant
E are lower still and do not appear to be significant from the standpoint
of water quality.
-24-
-------
Levels of zinc are high with respec'. to ambient quality. The mean
concentrations of 6.46 mg/L at plant J and 2.42 mg/L at plant E are
similar to the means of 5.9 mg/L reported by Nichols15 and 3.67 mg/L
reported by Anderson and Youngstrom.16 The criteria established by
EPA21 for public water supply is 5 mg/L.
Cadmium concentrations are quite low in drainages from both plants.
At plant J no values exceeded detection limits; at plant E no values
exceeded established water quality criteria.21
Concentrations of nickel are above levels generally found in surface
water,20 and, as with other metals, significantly higher at plant J.
Chromium concentrations are well below established criteria at both
plants with both means at 0.006 mg/L.21
Toxicity of beryllium, like that of several other metals, is inversely
related to hardness of the solute. Coal pile drainage is quite hard (the
mean calcium and magnesium concentrations for plant J were 300 and 245 mg/L,
respectively). Levels of beryllium are well below established criteria for
waters of this hardness.21
Mercury concentrations were almost an order of magnitude higher at
plant E than at plant J. Mean levels at these plants were 3.0 x 10 3
mg/L and 3.7 x 10 4 mgA» respectively, while the water quality criteria
for mercury is 5.0 x 10 s mg/L for freshwater aquatic life and wildlife.21
Arsenic levels in drainage from plant J ranged from 0.005 to 0.36 mg/L,
with a mean of 0.15 mg/L. These values generally exceeded established
criteria (0.050 mg/L), whereas those concentrations found at plant E
generally did not.21
The behavior of concentrations of selenium and arsenic were similar
in that levels at plant J generally exceeded criteria, whereas levels at
plant E did not. This finding is significant since selenium and arsenic
exhibit antagonistic toxicities,22 that is, each acts as a detoxifying
agent for the other.
Lead values never exceeded the detection limit (0.01 mg/L) at either
plant.
Concentrations of barium were similar at plant J and plant E, with
no values exceeding established water quality criteria.21 Mean
concentrations of barium were 0.17 and 0.14 mg/L, respectively.
Discrete Storm Analyses
Results of the storm event survey at plant E appear in Figure 7.
The "first flush" phenomenon is apparent in values for all constituents
with the exception of suspended solids. Of the remaining parameters,
all except pH and iron reached a minimum concentration at 2 h, after
start of the storm. Iron concentrations also stabilized after about 2 h,
20 min. Total suspended solids concentrations reflect the storm
-25-
-------
I
ho
30
2.8
2.6
2.4-
22-
2.0
nH
x .v - — P"
\ / v^ Acidity
\ ' v
\ ' »
— \
\
\
\
\ /
\
"'• H
, —
> ^'
_ V.--'
.... 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ... I ....
50 100 150 200 250
TIME
(MIN)
raw
1250
3°
looo y
s
760 i
>-
500 5
^
250
0
8000
6000
>- 4000
i-
O 2000
Cond
TDS
8000
6000
4000 ~
2000
50
100
150
TIME
(MIN)
200
250
400
300
& 200
100
Manganese
Iron
I .
I ,
i i i i i i i
6.0
6000
4.0
1
c
2.0
50
100
150
TIME
(MIN)
200 250
4000
2000-
3000
100
150 200
TIME
(MIN)
250
-2000
CO
- 1000
Figure 7. Results of discrete storm analysis.
-------
hydrograph in small watersheds, but tend to be more abrupt.23 The peak
total suspended solids concentration should occur at about the same time
as the peak hydrograph. If this is the case, the lowest concentrations
of most constituents occur at the hydrograph peak, a sharp contrast to
many other nonpoint source studies where most pollutants are associated
with the suspended fraction. It is evident that the iron and manganese
are transported in the dissolved fraction.
DATA INTERRELATIONSHIPS
A first step in determining the relationship of individual consti-
tuents to each other is correlation analysis. It should be noted, however,
that correlation does not necessarily reflect mechanistic relationships.
A high correlation between two values merely suggests that the values
vary in a related manner. Any inferences drawn from correlation analysis
should conform to chemical, physical, and intuitive logic. Results of
correlation analysis for plant J, plant E, and both plants combined,
appear in Tables 4, 5, and 6. Table 7 contains the number of correlations
in which ? exceeds 0.71. When this occurs, more than 50 percent of the
variation in the dependent variable can be attributed to variation in
the independent variable. This is, admittedly, an arbitrary mode of
selecting significance. However, for large samples (i.e., >20) signifi-
cance of correlation at the 95 percent level is achieved at ij values
>0.444 or when only 19.7 percent of the dependent variable variation
is explained. In essence, the parameters could be significantly
correlated, but the correlation would be of little practical significance.
There were insufficient chloride analyses at plant J for correlation
analysis. Titanium, lead, and cadmium (at plant J) did not exceed detection
limits so correlation analysis is inappropriate in these instances.
It is interesting to note that no constituent varied in relation to
pH or total suspended solids. The narrow range of pH values encountered,
and the fact that pH is a logarithmic quantity probably accounts for the
lack of correlation. The failure of total suspended solids values to
correlate with values for other constituents when compared with the
number of significant correlations with total dissolved solids suggests
that most elements occur in the dissolved form. This is chemically
and intuitively sound since at low pH most metals will be highly soluble
(the solution was highly colored and at most times appeared to have a very
low turbidity even though turbidity was not measured; solids appeared to
be mostly composed of coal fines that settled very rapidly).
Another instance where a significant correlation would be expected
but was not found was in analysis of the effects of rainfall on runoff
quality. Five rainfall variables were examined at plant J including
rainfall during the sampling period (RF1); rainfall the week prior to
the sampling period (RF2); time, in days, since the previous storm
event, counted from the first storm of the sampling period (TSLS);
a measure to include both rainfall and antecedent rainfall (RF3);
-27-
-------
TABLE 4. CORRELATION MATRIX—PLANT E
K>
00
PH
Acid.
Cond.
Cl
804
D.Sol
S.Sol
Fe
Mn
S102
Cu
Zn
Cr
Al
NI
Ca
MR
Pb
Hg
Ba
As
Cd
Se
Tl
Be
Sb
RF1
RF4
PH
1.00
-.375
-.251
-.592
-.303
-.332
-.305
.010
-.248
-.273
.194
-.113
.581
-.013
-.120
-.562
-.395
0.00
.157
-.286
.645
.087
-.065
0.00
-.197
-.167
-.225
.086
Acid.
1.00
.039
.398
.605
.510
-.028
.628
.436
.136
.187
.435
-.078
.725
.740
.819
.433
0.00
-.010
.237
-.153
-.156
-.221
0.00
-.109
.678
.141
-.302
Cond.
1.00
.717
.651
.807
-.319
.415
.766
-.070
.360
.757
.177
-.399
.368
.285
.846
-0.00
-.141
.866
-.432
0.00
-.304
0.00
.171
.377
.240
-.084
Cl
1.00
.738
.840
-.096
.399
.562
.481
-.053
.512
-.021
-.065
.309
.630
.856
0.00
-.134
.842
-.403
-.254
-.362
0.00
.281
.647
,2.r>5
.015
804
1.00
.843
-.475
.722
.760
.273
.391
.666
-.025
.091
.629
.541
.733
0.00
.176
.791
-.329
-.289
-.415
0.00
.126
.897
.474
-.383
D.Sol
1.00
-.341
.655
.810
.040
.351
.743
.150
.101
.507
.676
.939
-0.00
.038
.755
-.443
-.024
-.640
0.00
.165
.714
.155
-.071
S.Sol
1.00
-.340
-.405
-.020
-.609
-.283
-.143
.211
-.322
.151
-.228
0.00
-.527
-.364
.323
-.255
.307
0.00
-.198
-.355
-.393
.335
Fe
1.00
.715
.122
.570
.552
.227
.380
.717
.535
.603
-0.00
.158
.508
.003
.113
-.333
0.00
.099
.644
-.145
-.013
Mn
1.00
-.220
.668
.651
-.049
-.043
.628
.390
.763
0.00
-.140
.746
-.504
.186
-.300
0.00
.146
.466
.226
-.224
Si02
1.00
-.378
-.184
-.014
.038
.006
.186
.122
0.00
.163
.296
.213
-.406
.189
0.00
.160
.485
.131
.151
Cu
1.00
.445
.230
.143
.513
.0'6
.359
0.00
.209
.210
-.376
.420
-.171
0.00
-.076
.09S
.054
-.044
7,n
1.00
.441
.341
.750
.549
.784
0.00
-.081
.514
-.136
-.136
-.278
0.00
-.16U
.629
.221
-.320
Cr
1.00
.365
.218
.053
.279
0.00
-.022
-.164
.707
-.050
-.218
0.00
-.22^
-.038
-.423
.455
Al
1.00
.485
.692
.148
0.00
.054
-.370
.249
-.053
-.129
o.oo
-.472
.211
-.299
.148
-------
TABLE 4 (continued>
i
N>
VO
Ni
Ca
Mr
Pb
Hg
Ba
As
Cd
Se
Ti
Be
Sb
RF1
RF4
Ni
l.on
.S32
.S33
0.00
-.141
.367
-.047
-.036
.065
0.00
-.105
.666
.209
-.418
Ca
1.00
.680
0.00
.035
.194
-.244
-.058
-.432
0.00
-.055
.498
-.154
.054
M«
1.00
0.00
-.112
.738
-.456
.018
-.464
0.00
.137
.527
.030
.138
Ph
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
H_R
].00
-.211
-.157
.200
-.518
0.00
.142
.047
-.053
-.018
J5a
1.00
-.301
-.221
-.151
0.00
.364
.669
.458
-.253
As
1.00
-.514
.275
0.00
-.310
.105
-.379
.284
Cd
1.00
-.187
0.00
.120
-.571
-.510
.331
_S_e__
1.00
0.00
-.188
-.348
.200
-.261
Ti Re Sb RF1 RM
1.00
0.00 1.00
0.00 .03R 1.00
0.00 -.078 .526 1.00
0.00 .037 -.529 -.781 1.00
-------
o
pH
Acid. Cond. Cl
oil 1.00
Acid. -.229 1.00
Cond. -.053 .698 1.00
Cl -1.00 -1.00 0.00
804 -.029 .839 .781
D.Sol -.114 .828 .895
S.Sol .250 -.462 -.097
Fe -.178 .784 .775
Mn -.089 .717 .794
Si02 -.023 .616 .754
Cu -.116 .539 .581
Zn -.145 .664 .761
Cr -.342 -.279 -.502
Al -.119 .701 .653
Ni -.071 .832 .831
Ca .157 .624 .409
Mg .113 .839 .700
Pb 0.00 -0.00 -0.00
Hg .258 -.204 -.023
Ba -.037 .643 .613
As .211 -.287 -.106
Cd 0.00 0.00 0.00
Se .086 -.203 -.415
Tl 0.00 0.00 0.00
Be -.130 .688 .803
Sb -.050 .295 .138
RF1 .114 .069 -.134
RF2 .138 -.483 -.309
RP3 -.108 .413 .102
RF4 -.175 -.290 -.510
TSLS -.073 .128 .043
1.00
-1.00
-1.00
-1.00
-].00
-i.on
-i.oo
-i.
-i.
i.
-i.
-i.
-i.
00
00
00
00
00
00
0.00
0.00
0.00
0.00
0.00
0.00
00
0.00
0.00
0.00
00
0.00
0.00
1.00
-1.00
-1
-1
JARLF. 5. J^Rmj^TIpJ^mTRJX--PLAIIT .1
SiOo
D.Sol S.Sol Fe
Mn
Cu
Zn
1.00
.878 1.00
-.088 -.091 1.00
.867 .840 -.220 1.00
.767 .834 -.008 .677 1.00
.687 .738 .073 .503 .754 1.00
-.352 -.372 -.141 -.323 -.526 -.308 -.363 -.301
.352 .240 -.018 .083 .498 .234 .341 .055
Cr
Al
Nl
Ca
.764
.621
-.398
.633
.892
.633
.857
•0.00
-.178
.532
.188
0.00
-.317
0.00
.623
.400
.013
-.372
.281
.583
.750
-.351
.755
.934
.549
.762
-0.00
-.093
.679
-.092
0.00
-.274
0.00
.755
.314
-.085
-.394
.257
.133
-.499
-.042
-.026
-.046
.144
-.350
-0.00
-.022
-.226
.638
0.00
.118
0.00
-.390
.306
.240
.325
-.117
.599
.602
-.502
.690
.809
.474
.714
0.00
-.107
.488
-.142
0.00
-.304
0.00
.814
-.071
-.066
-.537
.391
.642
.526
-.526
.764
.870
.515
.709
0.00
0.00
.384
.011
0.00
-.001
0.00
.621
.306
-.053
-.615
.475
.698
.453
-.522
.640
.757
.240
.634
-0.00
-.186
.363
.176
0.00
-.141
0.00
.482
.514
-.216
-.338
.119
1.00
.457
-.551
.522
.766
.396
.566
0.00
-.133
.183
.218
0.00
-.085
0.00
.478
.390
-.051
-.285
.244
1.00
-.584
.470
.760
.519
.578
-0.00
-.162
.558
-.298
0.00
-.063
0.00
.501
.337
.189
-.048
.113
1.00
-.296
-.565
-.188
.565
0.00
-.049
-.134
.106
0.00
-.205
0.00
-.631
.136
.069
.422
-.306
1.00
.770
.352
.459
-0.00
-.028 -.139 -.186
.574 .648 .303
-.04
0.00
.434
.413 -.447
-.292 .135
1.00
.610 1.00
.800 .386
0.00 -0.00
-.102
0.00
-.109
0.00 0.00
.431
.294
-.017
0.00
0.138
0.00
.176
.368
.205
.721
.381
.021 -.098
-.517 -.394 -.141
.259 .1*8
-.408 -.289
.345 .212
-------
TABLE 5 (continued)
Mg
Pb
Hg
Ba
As
Cd
Se
Tl
Be
Sb
RF1
RF2
RF3
RF4
TSLS
Mg
1.00
-0.00
-.087
.516
-.282
0.00
.001
0.00
.705
.202
-.078
-.312
.182
-.334
.281
Pb
1.00
0.00
0.00
0.00
2.36
0.00
0.00
0.00
-n.no
0.00
0.00
0.00
0.00
0.00
HP,
1.00
-.242
.047
0.00
-.036
0.00
-.002
-.282
-.035
-.072
.057
-.090
.021
Ba
1.00
-.304
0.00
.128
0.00
.369
.322
-,22f>
-.109
-.056
.202
.215
As
1.00
0.00
-.341
0.00
-.391
.293
.342
.003
.192
-.271
.048
Cd
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.00
0.00
Se
1.00
o.no
-.269
.434
-.021
.200
-.030
-.120
.455
Ti
1.00
0.00
0.00
0.00
0.00
0.00
0.00
n.oo
Be
1.00
-.284
-.451
-.516
.187
-.166
.?!]
Sb
1.00
.236
.230
-.091
.014
.100
RF1
1.00
.057
.528
-.327
-.?27
RF2
1.00
-.818
.131
-.40?
RF3 RF4
1.00
-.346 1.00
.262 -.2^'
TSLS
i.on
-------
TABLE 6. CORRELATION MATRIX - BOTH PLANTS
(PLANT E AND PLANT J)
I
w
— "' """-
PH
Acid.
Cond.
Cl
S04
D.Sol
S.Sol
Fe
Mn
S102
Cu
Zn
Cr
Al
Ni
Ca
Mg
Pb
Hg
Ba
As
Cd
Se
Tl
Be
Sb
RF1
RF2
RF3
RF4
TSLS
pH
1.00
.038
.042
-.626
.122
.130
.220
.179
.354
.290
.351
.177
.005
.290
.337
-.167
.334
0.00
-.271
-.027
.408
-.189
.197
0.00
.309
.164
-.309
,138
-.108
-.068
-.073
Acid.
1.00
.524
.394
.841
.827
-.305
.814
.714
.666
.630
.724
-.178
.731
.796
.486
.845
-0.00
-.375
.531
.041
-.257
-.031
0.00
.700
.493
.032
-.483
.413
-.169
.128
Cond.
1.00
.752
.726
.810
-.042
.642
.603
.662
.526
.697
-.132
.584
.603
.282
.656
-0.00
-.305
.696
.241
-.152
-.200
0.00
.610
.442
-.008
-.309
.102
-.264
.043
Cl
1.00
.746
.833
-.124
.292
-.064
-.040
-.315
.380
-.078
-.305
-.249
.655
.824
o.on
.101
.842
-.286
-.135
-.330
0.00
.281
.647
.369
0.00
0.00
-.238
-1.00
S04
1.00
.898
-.074
.868
.745
.719
.729
.708
-.232
.672
.814
.409
.866
-0.00
-.310
.610
.374
-.291
-.112
0.00
.686
.599
.069
-.372
.281
-.212
.352
D.Sol
1.00
-.021
.866
.816
.786
.694
.816
-.160
.788
.874
.381
.846
-0.00
-.389
.633
.248
-.242
-.074
0.00
.789
.535
-.079
-.394
.257
-.203
.240
S.Sol
1.00
-.099
.101
.148
.164
.028
-.046
.095
.076
.093
-.165
-0.00
-.171
-.188
.586
-.110
.159
0.00
-.107
.317
.131
.325
-.117
-.110
-.018
Fe
1.00
.792
.687
.760
.733
-.259
.797
.865
.">51
.831
0.00
-.444
.441
.236
-.255
-.056
0.00
.861
.270
-.128
-.537
.391
-.172
.083
Mn
1.00
.864
.883
.717
-.199
.899
.943
.136
.831
0.00
-.642
.343
.479
-.366
.250
0.00
.861
.553
-.109
-.615
.475
-.149
.498
Si02
1.00
.837
.661
-.215
.R23
.873
.095
.794
-0.00
-.539
.329
.512
-.365
.123
0.00
.767
.674
-.194
-.338
.119
-.110
.234
Cu
1.00
.681 1
-.188 -
.807
.904
.073
.772
0.00 -0
-.606 -
.227
.550
-.312 -
.193
0.00 0
.803
.579
-.119
-.285 -
.244
-.087 -
.341
Zn
.00
.248
.693
.829
.?94
.751
.00
.464
.47«
.130
.290
.101
.00
.693
.538
.070
.048
.113
.145
.055
Cr
1.00
-.069
-.248
-.063
-.284
0.00
-.095
-.139
.161
-.040
-.154
0.00
-.251
.091
-.134
.422
-.306
.337
-.292
Al
1.00
.904
.177
.728
-0.00
-.577
.364
.424
-.383
.174
0.00
.770
.537
-.099
-.517
.434
-.164
.135
Ni
1.00
.188
.379
0.00
-0.606
.433
.385
-.360
.170
0.00
.883
.584
-.142
-.394
.259
-.138
.345
Ca
1.00
.218
-0.00
.046
.242
-.011
-.001
-.155
0.00
.019
.255
.039
-.141
.198
-.177
.212
-------
TABLE 6 (continued)
i
OJ
to
I
Mg
Ph
Hg
Ba
As
Cd
Se
Ti
Re
Sb
RF1
RF2
RF3
RF4
TSLS
MR Pb
1.00
-0.00 1.00
-.508 0.00
.450 0.00
.255 0.00
-.293 0.00
.222 0.00
0.00 0.00
.834 -0.00
.459 -0.00
-.097 0.00
-.312 0.00
.182 0.00
-.146 0.00
.281 0.00
HR
1.00
-.230
-.408
.432
-.284
0.00
-.574
.422
.107
-.072
.058
-.132
.021
Ba
1.00
-.132
-.194
.109
0.00
.324
.361
.028
-.109
-.056
.163
.215
As
1.00
-.244
-.085
0.00
.261
.462
.101
.003
.192
-.111
.048
Cd
1.00
-.136
0.00
-.310
-.344
-.184
0.00
0.00
-.073
0.00
Se
1.00
0.00
.163
.543
-.079
.200
-.030
-.067
.455
Tl
0.00
n.oo
0.00
0.00
0.00
0.00
0.00
0.00
Be
1.00
.198
-.334
-.516
.187
.042
.211
Sb
1.00
.202
.230
-.091
.089
.190
RF1
1.00
.057
.528
-.287
-.227
RF2
1.00
-.818
.181
-.402
RF3 RF; TSI
1.00
-.346 1.00
.262 -.205 l.C
-------
TABLE 7. CORRELATIONS WITH r VALUES >0.71
Parameter
pH
Acidity
Conductivity
Cl
S04
TDS
TSS
Fe
Mn
Si02
Cu
Zn
Cr
Al
Ni
Ca
Mg
Pb
Hg
Ba
As
Cd
Sc
Ti
Be
RF1
RF2
TSLS
RF3
RF4
Plant J
0
6
8
-
8
11
0
7
8
4
2
2
0
4
12
0
7
-
0
0
0
_
0
-
5
0
0
0
0
0
Plant E
0
3
6
5
6
7
0
3
6
0
0
4
1
1
3
1
7
-
0
6
1
0
0
-
0
0
-
-
-
0
Both plants
0
8
3
-
11
12
0
10
12
8
8
7
1
10
11
0
12
-
0
1
0
-
0
-
8
0
_
-
_
0
-34-
-------
and the square of the rainfall during the sampling period (RF4). At
plant E only RF1 and RF4 were examined. There were no significant
correlations of these rainfall parameters with any water quality
parameters.
After the correlation tables were examined, a common variable was
chosen for regression analysis. Constraints on the common variable
should include ease of analysis, availability of equipment, availability
of expertise, and correlation with a large number of important constituents.
The total dissolved solids variable fits these criteria well.
Table 8 contains a series of regression equations and regression
statistics for total dissolved solids vs. other water quality constituents.
These constituents were selected because of their importance as potential
pollutants and their high correlation with total dissolved solids concen-
trations. These models were developed by using data from both plants and
are significant at the 95 percent level. Models for acidity, iron, and
manganese would be quite valuable in design of treatment facilities. Plots
of the regression lines appear in appendix D.
LABORATORY STUDIES
Acid-Base Balance
Table 9 contains total potential acidity and neutralization potential
data for the seven monthly coal samples collected at plants J and E. In
addition to laboratory determinations, total potential acidity can be
calculated from pyritic and organic sulfur contents as demonstrated by
Grube, et al.24 The excess acidity is determined by subtracting neutra-
lization potential from total potential acidity. Excess acidity was
calculated using both methods. These results are also presented in
Table 9. These findings are not consistent with field data, which
suggest that more pyritic material is being oxidized at plant J.
Neutralization potential values also disagree with the field data;
i.e., higher (Ca + Mg) values for plant E. The nonconformity of the
acid-base balance is due to the high values for total potential acidity
encountered in coal samples from plant E. A probable cause of error
in the determination may result from chloride interference, which is
noted in the procedure. The possibility of error was introduced in the
washing procedure to remove carbonates and sulfates. One step involved
washing with a solution of hydrochloric acid. The chlorides introduced
in this step took 14 days and more than 6 liters per 2.0 g sample to
remove. This prolonged wash procedure may have been a source of error.
Coal Analysis
Results of the analysis of coal samples collected at plants J and E
appear in Tables 10 and 11. Samples J50A and J50B represent the composite
sample used in development of the shaker tests. Sample A represents the
-35-
-------
TABLE 8. MODELS USING IDS AS INDEPENDENT VARIABLE
Degrees of
Model Freedom
Aciditv
Aciditv = 0.422 TDS + 60
(mr/1 as CaC03, me/1) 29
Conductivity
Conductivity * 0.258 TDS + 2400 27
Chlorides
Cl = 0.084 TDS - 130 (meVD 12
Sulfate
S04 = 0.515 TDS + 990 (me/1) 27
Iron
*-e = 0.106 TDS + 26 (me/1) 30
Manpanese
Mn - 3.01 x 10~3 TDS + 0.049 (mp/1) 30
Zinc
Zn = 7.67 x 10~4 TDS + 0.09 (me/1) 30
Nickel
Ni = 3.18 x 10~4 TDS - 0.34 (mg/1) 30
Si02
SiO, = 2.07 x 10~2 TDS - 6.13 (mg/1) 29
r2 F Value
0.683 62.6
0.656 51.6
0.694 27.23
0.807 112.8
0.751 90.3
0.666 59.9
0.666 59.9
0.764 96.9
0.618 47.0
Aluminum
Al - 2.8 x 10~2 TDS + 3.16 (me/1) 29 0.620 47.4
Macnesium
Me = 3.10 x 10"2 TDS - 31.9 (meVl) 28 0.716 70.7
Bervllium ,
Be = 3.80 x 10 TDS + 5.7 x 10~3 (mg/1) 27 0.623 44.7
-36-
-------
TABLE 9. ACID-BASK BALANCE
Laboratory
Sample potential acidity
No. (ton/CaC03/1000 ton)
J776
J876
J1076
E1076
E1176
E1276
E177
E277
1 _
15.5
14.0
14.5
43.5
43.5
34.5
35.5
31.0
Calculated
potential acidity
(ton/CaC03/1000 ton)
45.5
47.5
49.5
102.5
103.5
112.0
108.0
101.5
Laboratory Laboratory
neutralization potential excess acidity*
(ton CaC03/100Q ton) (ton CaC03/1000 ton)
<0.3
<0.3
<0.3
7.6
0.8
7.6
7.3
1.1
15.2
13.7
14.2
35.9
42.7
26.9
28.2
29.9
Calculated
excess acidity**
(ton/CaC03/100 ton)
45.2
47.2
49.2
94.9
102.7
104.4
100.7
100.4
*Laboratory potential acidity minus laboratory neutralization potential.
**Calculated potential acidity minus laboratory neutralization potential.
-------
TABLE 10. COAL ANALYSTS—PLANTS .1 AND E
Approximate analysis
% total moisture
Dry basis
% volatile matter
% ash
% fixed carbon
% total sulfur
Btu/lb
^ As received
<» Dry
A&MF
Forms of S (dry)
% sulfate
% pyritic
% organic
% total
J50A
2.0
37.1
13.5
49.4
1.9
12,885
13,117
15,159
0.04
0.82
1.02
1.88
J50B
2.0
37.4
13.3
49.3
1.7
12,879
13,160
15,173
0.04
0.69
0.96
1.69
Plant J
J776
3.0
33.0
16.6
50.4
2.11
12,048
14,446
0.46
0.69
0.96
2.11
J876
2.8
33.4
15.6
51.0
2.04
12,183
14,441
0.32
0.76
0.96
2.04
J1076
2.8
33.2
15.6
51.2
2.12
12,252
14,523
0.33
0.81
0.98
2.12
E1076
3.2
Plant F,
Ell 76 " Ef276
3.2
3.1
E177
3.4
E277
4.0
36.8
15.1
48.1
4.09
12,293
14,477
0.27
2.13
1.69
4.09
37.3
14.8
47.9
4.15
12,414
14,566
0.28
2.21
1.66
4.15
36.7
16.6
46.7
4.51
12,082
14,489
0.22
2.54
1.75
4.51
37.1
15.7
47.2
4.27
12,210
14,490
0.24
2.39
1.64
4.27
37.6
14.6
47.8
4.10
12,351
14,460
0.32
2.06
1.72
4.10
Particle size
As received -18/+40 -18/4-40 -18/+40 -18/+40
-18/+40 -18/+40 -18/+40 -18/+40 -18/+40
-------
TABLE 11. COAL ANALYSIS - PLANT J
Sample Number
Analysis of Ash (%)
Si02
A1203
Fe2°3
CaO
MgO
S03
Na20
K20
Ti02
Analysis of Ash (mg/1)
Mn
Pb
Cu
J50A
51.6
27.9
11.7
1.8
1.1
1.4
0.3
2.5
1.2
120
92
213
J50B
52.4
28.2
10.6
1.6
1.0
1.7
0.3
2.5
1.2
110
101
269
-39-
-------
raw sample as received. Sample B represents the sample after processing.
A comparison of values reveals that most variations are within limits of
analytical error. However, values for copper suggest that some contamina-
tion may have occurred during processing of the sample.
Values for coal samples from plant J are similar to those presented
for plant E with the exception of sulfur analysis. The coals from plant
E are consistently higher in total pyritic and organic sulfur contents.
Sulfate sulfur contents are not significantly different.
Shaker Tests
Development of standard conditions for the shaker tests involved
analysis of the time to equilibrium, coal pH, and the effects of
varying coal to elute ratio, size fraction of coal, elute pH, and
elute hardness on test results. The coals were shaken in a Lab-Line
Model 3597 Environmental Shaker at 250 rpm and 25°C.
Results of the time to equilibrium analyses are presented in Figure
8. Calcium concentrations appeared to equilibrate after about 72 hours,
but the concentrations in later samples tended to increase. Conductivity
data varied from 3000 to 3950 (Jmhos/cm with no discernable trend. Sulfate
concentrations continued to increase over the 10-day study period. Values
for pH did not change appreciably over the length of the study period.
Dissolved iron values decreased from a mean of 24.3 mg/L for the first
day to a mean of 13.8 mg/L over the last eight days of the experiment.
In summary, two constituents continued to increase, two exhibited no
trend, and one reached equilibrium after about 48 hours. An optimum
point of minimal shaking time with maximum concentrations was not
obvious. As a result, five days was chosen as an arbitrary point
where those constituents that would equilibrate had done so, and
those that would increase had reached a reasonably high concentration
with respect to the first day's concentration.
Coal pH was determined via a modification of the method for soil
pH. Generally soil pH involves mixing a 1:1 solution of soil and
water for 30 minutes, letting the solution stand to remove the clay
particles and then measuring the pH. The coal-water suspensions were
filtered instead of settled. The pH of the suspension after 30 minutes
was 3.2 (Figure 9). After the 100-minute period, the coal pH had
increased to 3.4 and appeared to be stabilized.
Figure 10 contains the results of varying size fraction of coal
and coal to elute ratio. In these experiments, coals of -18 to +40
mesh and -40 mesh were mixed in ratios of 0.04 to 1, 0.1 to 1, 0.2
to 1, and 0.3 to 1, with deionized water. In all instances, the
smaller coal size provided higher concentrations. However, the
smaller mesh coal did not mix well and tended to adhere to the sides
-40-
-------
*(-
ol—1_ 1 1 1 1 I . I
I 2 3 « 9 24 48 72 98 120
•8 192 Z» 240
168 I9Z 216 240
400
MO
I 500
* tS°
r too
190
100
90
i i i t i
2 9 4 S 244ST2MOOI44l68IK2tt240
30
-
24 48 72 98 120
THE 11')
M«2»240
200
MO
160
MO
120
! 00
6O
40
SO
0
i i L- J
I 2
: J^ 1
3 24
48 72 W
TIME (hf)
l_ L.
120 144
I9B B« 24O
Figure 8. Results of time to equilibrium analyses
-------
i
*»
6.0
-$ 4.0
°c
T3
"35
x 2.0
20
40 60
TIME
(min)
80
100
Figure 9. Coal pH.
-------
CO
I
40 W)
Weight (gram)
«o
80
Figure 10,
Ehrtt Volume-Z50 ml
ACoalSize - 40
c CoolStfe -ISA 40
Results of varying coal to elute
ratio and coal size.
i _ i._ a -
10 20
so
40 50
(gram)
60
ro
60
-------
of the bottle above the swirl line of the solution. Thus, the amount of
coal in suspension was not always known. Because of this, the -18/+40
mesh coal was chosen for procedure use. Concentrations of all constitu-
ents increased with increasing coal to elute ratios. The pH values
decreased with increasing coal to elute ratios. These variations were
linear for iron, sulfate, and pH, but nonlinear for conductivity and total
dissolved solids.
At higher coal to elute ratios (0.2 to 1 and 0.3 to 1), the coal
did not remain well mixed and tended to settle to the bottom. As in the
case of the -40 mesh coal, the amount -
-------
3.0
300r
x
a.
20
1.0
e 200
100
1500
J. 1000
500
100 200 300 400 5OO
100 200 300 400
CoCo, Addsd
50O
4000
3OOO
o
c
O*
V)
2000
1000
100 200 300 400 500
100 200 3OO 400
Co Co, Added
5OO
3.0
3 20
to
sooor
E 2000
o
c
en
a
1000
1.0 2.0 3-0 4.0 5-0 &0 7.0
0 2.0 3.0 4.0 50 6.0 70
pH initial
o
c
300
200
100
1.0 2.0 3-0 4.0 5.0 6.0 7.0
4000
?
— 3000
I
2OOO
in
1.0 20
3.0 4.0 5.0
pH initial
6.0 70
Figure 11. Results of varying elute pH and hardness.
-45-
-------
TABI.F. 12. RESULTS OF SHAKER TFSTS--PLANTS I AND
X
pH a
Ranee
X
_
Fe o
Ranee
X
_
HD o
Range
H
JIN
<* x
TDS o
Range
H
X
S0fi a
Range
H
X
HI o
Range
S
J776
2.64
0.01
2.62-2.66
6
250
39. 5C1
no- 310
6
1.7
0.17
1.5-2.0
6
1533
57.74
1500-1600
3
1100
O.OT
1100-1100
3
0.70
0.09
0.62-0.87
6
n.A.s
.I87b
2. 75
0.02
2.73-2.7'
6
183
19.66
160-210
6
1.32
0.12
1.7-1.5
6
1067
57.76
1000-1100
3
813
23.09
300-840
3
0.67
0.13
0.55-0.83
6
1 .!
J1076
2.73
0.12
j.;n-P.75
6
170
33.98
140-^20
6
1.17
0.08
1.3-1.5
6
1033
57.74
1000-1100
3
813
23.09
800-840
3
0.69
0.14
1.55-0. S3
6
PLANT E
Total
2.70
0.05
2.6^-2.77
18
201
46. V>
141-310
la
1.46
0.21
1.2-2.0
18
1211
247.2
1000-1600
9
909
144.3
800-1100
9
0.69
0.11
0.55-0.37
13
E1076
7.12
O.'.t,
6.47-7.90
6
0.23
0.18
<.05-.46
6
1.11
0.19
0.83-1.2
6
1067
57.74
1000-1100
3
700
45.83
650-740
3
0.33
0.16
0.17-0.50
6
E1176
6.46
0.26
6.10-6.82
6
0.30
0.22
<.05-.53
6
1.22
0.36
0.87-1.6
6
1200
100
1100-1300
3
790
26.46
770-820
3
0.41
0.20
0.20-0.65
6
El 286
f .83
0.1')
6. 70-6.94
6
O.?l
0.08
0.17- J. 30
6
1.01
0.26
0.73-1.7
6
1033
57.74
1000-1100
3
723
15.28
710-740
3
0.27
0.11
0.17-0.44
6
E177
fi.4n
0.20
6.23-6.66
6
0.17
0.1<>
'.01-. 55
6
1.23
0.29
0.95-1.5
6
1033
57.74
1000-1100
3
717
25.17
690-740
3
0.29
0.08
0.22-0.42
6
F.2J7
5.94
0. Ji
5.11-ii.3.-i
6
0.44
0.24
0.25-0.92
6
1.95
0.29
1.6-2.3
6
1300
100
1200-1400
3
850
266.3
570-1100
3
0.46
0.12
0.37-0.69
6
Total
6.57
0.49
5.51-7.01
10
0.27
0.20
'.05-. 92
30
1.28
0.44
0.78-2.3
30
1127
128.0
1000-1400
15 .
756
113.4
570-1100
15
0.35
1.15
0.17-0.6
30
-------
-.uggests that relative differences may be predictable for a few constitu-
ents but that field concentrations cannot, at least at this time, be
predicted from shaker-type elution tests.
Neutralization Studies
The low pH of coal pile drainage increases the solubility of iron,
manganese, and other trace metals, thus resulting in high concentrations
of the metals, especially iron. Coal pile drainage can be treated to
remove metals by (1) lime or limestone neutralization,25 or sulfide
precipitation followed by sedimentation,26 or (2) by sedimentation and
filtration followed by ion exchange or reverse osmosis.27 These
processes have been used to treat acid mine drainage, which is some-
what similar to coal pile runoff. However, all methods are costly,
and some are either impractical or unreliable. TVA has investigated
an economical method of treating coal pile drainage in alkaline ash
disposal ponds. The coal pile runoff can be collected in a storage
basin and then routed through an ash pond before it is discharged
into receiving streams. Reducing the concentration of iron in the
coal pile drainage to 1.0 mg/L by treatment in the ash pond is
desirable.
Fly ash has been used successfully as a treatment aid in sewage and
industrial wastewaters. Reports indicate thai fly ash can be used to
remove heavy metals from aqueous solutions,28'29 phosphates,30'31'32
organics such as phenolic compounds,33'34 TNT,35 alkyl benzene sulfonate
(ABS),36 refractory organics in secondary treated sewage effluents,37 and
color in paper mill effluents.38'39 Fly ash consists primarily of metal
oxides such as Si02, A^Oa, FeaOs, CaO, and MgO), and other oxides such
as SOs- Metal oxides in contact with water will produce an alkaline
solution; conversely, sulfides will be oxidized in aerobic waters to
sulfate and sulfuric acid, yielding an acidic solution. The final pH of
the solution depends on the ratio of alkaline metal to sulfate concentra-
tion in the ash pond effluent.40 Metallic cations will precipitate as
hydroxides at high pH. Also, metal ions may adsorb on fly ash because of
the high content of silica and alumina in fly ash.28 Bench-scale treat-
ment tests were performed to examine the ability of fly ash slurry to
remove iron from coal pile drainage. The characteristics of coal pile
drainage used for these studies are shown in Table 13.
-47-
-------
TABLE 13. CHEMICAL COMPOSITION OF COAL PILE
DRAINAGE USED FOR TREATMENT STUDY
Constituent
Acidity, as CaC03
Total dissolved solids
Total suspended solids
Iron
Manganese
Zinc
Nickel
Copper
Arsenic
Selenium
Chromium
Mercury
Concentration
Total
9,100
6
3,000
46
12
4.4
1.6
0.28
<0.001
<0.005
<0.002
(mg/L)
Dissolved
19,000
3,000
44
12
4.4
1.3
0.28
<0.001
<0 . 005
<0.0002
The pH of Coal Pile Drainage and Ash Sluice Water Mixture—Aliquots
(100 ml) of two types of fly ash slurry, neutral and alkaline, with pH
ranges typical of ash concentrations for sluicing, were titrated with
coal pile drainage. Figures 12 and 13 show the resulting titration curves.
At TVA's 12 coal-fired power plants, the annual volumetric ratio of total
flow of coal pile drainage to total flow of ash pond effluent averages
0.001 to 0.012. However, coal pile runoff occurs only intermittently,
whereas the flow of ash pond effluent is continuous. Thus, the instan-
taneous volumetric ratio of coal pile drainage to ash sluice water could
be greater than 0.012 (1.2 ml coal pile drainage in Figures 12 and 13).
These higher ratios would cause a significant drop in pH in the neutral
ash solutions at the high ratios, as shown in Figure 12. The pH values
of the mixture of coal pile drainage and ash sluice water also depend on
the ash concentration in the slurry.
Removal of Metal Ions hy Precipitation in Ash Ponds—Effect of volu-
metric ratio of coal pile drainage to ash sluice water—In these tests,
equal amounts of alkaline fly ash from plant E were vigorously mixed with
deionized water for two hours. The ash concentration, 20 g/L, was a
typical ratio of ash to water for sluicing. After mixing, one set of
these ash solutions was filtered through 0.45-|J filters to remove the
ash; the second set remained unfiltered. Various amounts of coal pile
drainage were added to each duplicate filtered and unfiltered solution.
-48-
-------
i
*»
NO
13
12
II
10
I9
c!
l/t
U.
O
i i i i r~T~T
i""T~i i rn — i — r
— 5.03! of FLY ASM Ifl SLURRY
2.50S Of FLY ASM IN SLURRY
1.29S of FLY ASM I'l SLURRY
1.09-, of RY ASH ID SLURRY
N
\
\
\
\
\
\
68 10 12 14 16 IB
COAL PILE ORA!NAr,[ (ml) ADDED PER 110 nl OF ASH SLURRY
20 22 24
Figure 12. Titration curves for alkaline fly ash slurry with coal pile drainage.
-------
o
i
2.50- of riv ASM in SLURRY
!.?•»" of FLY ASH PI SLURRY
l.nr of FLY ASH IN SLURRY
I
0.5 1.0 1.5
COAL PILE DRAINAGE (ml) ADDED PER 100 ml OF ASH SLURRY
2.0
2.5
Figure 13. Titration curves for neutral fly ash slurry with coal pile drainage.
-------
These solutions were mixed at 100 rpro for 3 minutes and at 30 rpm for
30 minutes. The floe in the solutions was then allowed to settle, and
the supernatants were filtered and analyzed.
Figure 14 shows the residual iron concentrations in the supernatant
vs. the pH of the mixtures. Filtering the ash before the addition of
coal pile drainage had no effect on the pH of the solution (11.9).
However, the filtered solutions experienced a larger change in pH with
addition of the coal pile drainage than did the unfiltered solutions
(Figure 13). These differences were caused by the reaction of acid
radicals from the coal pile drainage with alkaline metal oxides
remaining on the fly ash. The iron concentration in the coal pile
drainage was 3000 mg/L (Table 13). Therefore, the initial iron con-
centrations, with dilution ratios of 0.005:1 to 0.07:1, ranged from
15 to 196 mg/L. The additional iron removed by adsorption on fly
ash (i.e., the differences of iron concentrations remaining in the
solutions between filtered and unfiltered beakers, but having an
equal amount of coal pile drainage added) was not detectable. These
results indicate that the removal of iron resulting from combining
the coal pile drainage with alkaline ash solutions is caused by
precipitation.
As shown in Figure 14, the supernatant iron concentrations drop
sharply at a pH of about 6, which indicates that by comparison with
the solubilities of ferric iron in water41 much of the iron dissolved
in the coal pile drainage was in the form of ferrous iron.
In addition to iron, other trace metals present in relatively
high concentrations in this particular sample of coal pile drainage
were also studied. The results indicated that concentrations of
copper, manganese, nickel, and zinc in the solution decreased when
the pH was increased by mixing the acid coal pile drainage with
the alkaline ash sluice water. Metals were removed primarily by
precipitation as metal hydroxides. Figure 15 shows the relation
of metal concentrations in the supernatants to pH. In general,
these curves coincide with their theoretical optimal pH values for
minimum solubilities. However, soluble metal concentrations were
lower than their theoretical curves at pH values that were not
optimum. This variance was due to the low metal concentrations in
the solutions of coal pile drainage diluted by the ash sluice water.
To investigate the actual metal removal by precipitation and adsorp-
tion in an alkaline ash pond, the reduction of metal concentrations
by dilution should be excluded. Therefore, the actual concentrations
of dissolved metals in the solutions after treatment were calculated
with the effects of dilution factored out. This calculation was
done by multiplying the measured concentrations of dissolved metals
by the dilution ratios used. The resultant concentrations of metals
are equal to those that would remain in the treated and undiluted
coal pile drainage and are referred to as "equivalent" concentrations.
-51-
-------
100
10
o
i
I —
0.1 —
0.01
fO ASH FILTERED HE FORE
[» COAL PILE SRAI-iArc ADDED
/_ ASH UNfr'.TERED BEFORE
) A COAL PILE DHAINAGE ADDED
O.I
0.01
£
13
C
0.001
5 6 7 8 9 10 II
pH (STANDARD UNITS)
Figure 14. Residual iron concentration and volumetric ratio of
coal pile drainage to ash sluice water vs. pH.
-52-
-------
IO
(0
.g
O
§
O
Ql
0.01
n-Cu
O-Mn
A-Ni
O-Zn
0.001
1
1
Figure 15.
9 12
pH (SU)
Concentrations of dissolved metals vs. pH.
-53-
-------
Figure 16 shows the relation of the remaining equivalent concen-
trations of dissolved metals in the treated coal pile drainage to pH.
For instance, a pH of 6.3 or more is required to remove iron to the
level of 1 mg/L as shown in Figure 14; however, if the equivalent
concentration is required, a pH of 7 or more would be necessary
according to Figure 16. The significance of Figure 16 is that it
proves that trace metals such as copper, iron, manganese, nickel,
and zinc in the coal pile drainage can be effectively removed in
alkaline ash solutions at the optimal pH values. It is logical to
assume that other trace metals which exist in significant concentra-
tions in the coal pile drainage, such =»s beryllium, cadmium, and
chromium, will also be removed at the optimum pH values. Of primary
importance is obtaining the optimal pH values, perhaps by selecting
an alkaline ash pond or by controlling ash concentrations during
sluicing, volumetric ratio of coal pile drainage to ash sluice water,
or retention time of the ash pond. Some trace metals, such as
arsenic and selenium are not functions of pH. Their degrees of
removal by coprecipitation and adsorption in the ash pond treatment
system need further investigation.
Effect of ash character and ash concentration—As described
previously, iron is removed by precipitation at an alkaline pH
level. The character and concentration of ash during sluicing
will significantly affect the change in pH caused by adding coal
pile drainage to ash sluice water. As shown in Figure 12, the
neutral fly ash would not be sufficient to treat the coal pile
drainage because of the low alkalinity. Therefore, to remove
iron, only alkaline fly ash is adequate for neutralization of the
high acidity in coal pile drainage at high-volume ratios. The
factors that govern the formation of alkaline fly ash at coal-
fired power plants were discussed by Chu, et al.40 Figure 17 shows
the supernatant iron concentrations vs. the pH of the solutions that
were affected by the different ash concentrations used for sluicing:
6, 12, 20, and 36 g/L. The ratio of coal pile drainage to ash
sluice was 0.015. The experimental procedures were the same as
described earlier.
Before the coal pile drainage was added, the pH was the same
for ash-filtered and ash-unfiltered solutions having the same initial
ash concentration. For solutions having ash concentrations of 6, 12,
20, and 36 g/L, the pH values were 11.5, 11.7, 11.9, and 11.95,
respectively. After equal volumes of coal pile drainage were added,
the pH values decreased; this decrease was proportional to the decrease
in fly ash concentration. As discussed earlier, the pH values were
higher for unfiltered ash solutions than for filtered solutions,
and the relationship between residual iron concentration and pH in
Figure 17 follows the same curve as shown in Figure 14.
-54-
-------
100
&.
o> ^
* 8
8 I
5
cr
UJ
D-Cu
X-Fe
O-Mn
A-Ni
O-Zn
Figure 16. Equivalent concentrations of dissolved metal concentrations.
55
-------
10
O.I
0.01
O ASH FILTERED BEFORE
• COAL PILE DRAINAGE ADDED
A ASH Ui'rILTERED 3EFORE
A COAL PILE DRAINAGE ADDED
100
10
0
I
6789
pH (STANDARD UNITS)
10 II 12
Figure 17. Residual iron concentration and ash concentration vs. pH.
-56-
-------
Effect of retention time—In several tests, the pH of the mixture
of coal pile drainage and ash sluice water was observed to change with
retention time. Therefore, tests were conducted to evaluate the effect
of retention time, including cumulative mixing to simulate ash pond systems.
Alkaline fly ash was vigorously mixed for 2 hours, with river water
in four tanks holding identical ash concentrations of 25 g/L. Coal pile
drainage was added to the fly ash solutions at volumetric ratios of 0.035:1,
0.06:1, 0.08:1, and 0.105:1 to give pH values of 9.5, 7.6, 6.36, and 4.35,
respectively. Then the solution in each tank was mixed at 100 rpm for 3
minutes, followed by 10 rpm for six days. During the slow mixing, almost
all the ash settled to the bottom of the tanks. Grab samples were taken
at varying time intervals. Figure 18 shows that the pH values of the
solutions change with retention time because the alkaline metal oxides
dissolve continuously from the ash and the C02 from the air goes into
the solution. About 28 hours was required to change the initially acidic
solution, pH 4.35, to pH 7, the pH required to reduce the iron concentra-
tion to below 0.05 mg/L. This change in pH may not occur if the fly ash
does not contain sufficient alkalinity.
As part of this study, samples were also analyzed for iron. Results,
shown in Figure 19, indicate a similar relationship between residual iron
concentration and pH.
Solids settling—In addition to fly ash, solids can be produced by
iron precipitation as ferrous and ferric hydroxides. The fly ashes are
spherical particles, whereas iron hydroxides are flocculent materials.
Bench-scale settling tests were conducted to investigate the settling
characteristics of (1) iron hydroxides, and (2) iron hydroxides mixed
with fly ashes. In these tests, alkaline fly ash was mixed with river
water in two beakers, with an ash concentration of 25 g/L for each.
After being mixed, the solution in one beaker was filtered to remove all
the fly ash. Coal pile drainage was added to both beakers at a volu-
metric ratio of 0.08:1 to give a pH value of 7. After the jar test pro-
cedures, both solutions were transferred into two cylinders for settling
tests. The resulting settling curves, shown in Figure 20, indicate a
good settling characteristic for the iron hydroxide floe and the sludge
of iron hydroxides plus fly ash. The initial settling velocity for iron
hydroxide floe is calculated as 3 cm/min, and the settling velocity for
iron hydroxide floe combined with fly ash is calculated as 8.6 cm/min.
The area required for thickening per unit flow rate of_wastewater is 0.56
cm2'cm~3*min"1 for iron hydroxide floe and 0.42 cm2-cm 3-min 1 for iron
hydroxide floe plus fly ash.
Field evaluation—To verify these experimental results, data col-
lected from field tests at plant J were evaluated. This plant uses
pulverized coal from eastern Kentucky and eastern Tennessee, and the fly
ashes produced have a neutral character. As mentioned, all the coal
-57-
-------
O VOLUMETRIC RATIO OF COAL PILE DRAINAGE TO ASM SLUICE WATER = 0.105
& VOLUMETRIC RATIO OF COAL PILE DRAINAGE TO ASH SLUICE WATER = 0.08
D VOLUMETRIC RATIO OF COAL PILE DRAINAGE TO ASH SLUICE WATER = O.Of
< VOLUMETRIC RATIO OF COAL PILE DRAINAGE TO ASH SLUICF WATER = 0.035
II -
vo
s
a
cc
1
<
-------
100
10
E
O
UJ
o
o
eg
O.I
0.01
I I
O 45 mln AFTFR COAL PILE
A DRAINACF.
11 h AFTER COAL PILE
DRAINAGE ADDED
50 h AFTER COAL PILE
DRAINAGE A.ODEH
0.105
0.08
0.06
0.035
J_
O.I
0.01
CD
-------
I
o*
o
I
INTERFACE HEIGHT VS. TIME
(SAMPLE VOLUME = TOO LITERS)
IROH HYDROXIDE FLOCS
IRON HYDROXIDE FLOCS PLUS FLY ASH
.1.1.1.1.1
20
40
60
TIME (min)
80
100
120
Figure 20. Settling curve of coal pile drainage - fly ash mixture.
-------
pile drainage at plant J is collected in a storage basin and then pumped
into the ash pond. Further modifications are being made, including addi-
tional diversion dikes and similar runoff control structures, to increase
the efficiency of runoff collection and transfer to the ash pond. The
pH of this ash pond varies seasonally, possibly as a result of the low
buffer capacity of water used for sluicing or the discharge of coal pile
drainage into the ash pond. Based on the quarterly data of ash pond
effluent collected in three years, Figure 21 indicates that most of the
iron from the coal pile drainage and ash materials is removed in the
complex ash pond system at the high pH level. It has been verified that
the iron concentration in the solutions of coal pile drainage and ash
sluice water mixture will be less than 1 mg/L if the pH is about 6.3 or
more.
-61-
-------
QUARTERLY SAMPLES
1,2,3,4 DURING 1973
Al,2,3,4 DURING 1974
Dl,2,3,4 DURING 1975
Figure 21. pH vs. total iron concentrations in an ash pond effluent.
-62-
-------
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1. European Inland Fisheries Advisory Commission. "Water Quality
Criteria for European Freshwater Fish—Extreme pH Values and Inland
Fisheries." Prepared by EIFAC Working Party on Water Quality
Criteria for European Freshwater Fish. Water Research, 3:5C3, 1969.
2. Mount, D. I. "Chronic Effect of Low pH on Fathead Minnow Survival,
Growth, and Reproduction." Water Research, 7:987, 1973.
3. Bell, H. L. "Effect of Low pH on the Survival and Emergence of
Aquatic Insects." Water Research, 5:513, 1971.
4. Caruccio, F. T., G. Geidel, and J. M. Sewell. "The Character of
Drainage as a Function of the Occurrence of Framboidal Pyrite and
Ground Water Quality in Eastern Kentucky." Proceedings of 6th
Symposium on Coal Mine Drainage Research, NCA/BCR Coal Conference
and Expo III, Louisville, Kentucky, 1976. 291 pp.
5. Federal Water Quality Administration. Oxygenation of Ferrous Iron.
U.S. Government Printing Office, Washington, DC, 1970. 201 pp.
6. Silver-man, M. P. "Mechanism of Bacterial Pyrite Oxidation."
J. Bacteriology, 94:4, 1967.
7. American Public Health Association, American Water Works Association,
and Water Pollution Control Federation. Standard Methods for the
Examination of Water and Wastewater, 14th Edition, Washington, DC,
1976. 1193 pp.
8. U.S. Environmental Protection Agency. Manual of Methods for Chemical
Analysis of Water and Wastes. EPA-625/6-74-003, Washington, DC, 1974.
298 pp.
9. Grizzard, T. J., C. W. Randall, and R. C. Hoen. "Data Collection for
Water Quality Modeling in the Occoquan Watershed of Virginia."
Proceedings of Conference on Environmental Modeling and Simulation,
EPA-600/9-76-016, U.S. Environmental Protection Agency, Cincinnati,
Ohio, 1976. 847 pp.
10. Smith, Richard M., Walter E. Grube, Jr., Thomas Arkle, Jr., and
Andrew Sobek. Mine Spoil Potentials for Soil and Water Quality.
EPA-670/2-74-070, U.S. Environmental Protection Agency, Cincinnati,
Ohio, October 1974. 302 pp.
11. Barr, Anthony J., James H. Goodnight, John P. Sail, and Jane T.
Helwig. A User's Guide to SAS 76. SAS Institute, Inc., Raleigh,
North Carolina, 1976. 329 pp.
12. Draper, Norman, and Harry Smith. Applied Regression Analysis.
John Wiley and Sons, Inc., New York, 1966. 407 pp.
-63-
-------
13. Lipson, Charles, and Narendra J. Sheth. Statistical Design and
Analysis of Engineering Experiments. McGraw-Hill Book Company,
New York, 1973. 518 pp.
14. Tukey, John W. Exploratory Data Analysis. Addison-Wesley Publishing
Company, Reading, Massachusetts, 1977. 688 pp.
15. Nichols, C. R. Development Document for Effluent Limitations
Guidelines and New Source Performance Standards for the Steam
Electric Power Generating Point Source Category. EPA-440/l-74-029-a,
U.S. Environmental Protection Agency, Washington, DC, 1974. 770 pp.
16. Anderson, W. C., and M. P. Youngstrom, "Coal Pile Leachate Quantity
and Quality Characteristics." Proceedings of Sixth Symposium on
Coal Drainage Research, NCA/BCR Coal Conference and Expo III,
Louisville, Kentucky, 1976. 291 pp.
17. Matsugu, R. S. Ontario Hydro Research Division Report, Toronto,
Ontario, 1976. 32 pp.
18. U.S. Environmental Protection Agency. EPA Program Conference Report.
Fuel Cleaning Program: Coal. EPA-600/7-76-024, Washington, DC, 1976.
132 pp.
19. Jenne, E. A. "Controls on Manganese, Iron, Cobalt, Nickel, Copper,
and Zinc Concentrations in Soils and Water: The Significant Role
of Hydrous Iron and Manganese Oxides." Trace Inorganics in Water.
American Chemical Society, Washington, DC, 1968. 396 pp.
20. National Academy of Sciences. Water Quality Criteria 1972. U.S.
Government Printing Office, Washington, DC, 1973. 594 pp.
21. U.S. Environmental Protection Agency. Quality Criteria for Water.
EPA-440/9-76-023, Washington, DC, 1976. 501 pp.
22. National Academy of Sciences. Medical and Biological Effects of
Environmental Pollutants—Arsenic. National Academy of Sciences,
Washington, DC, 1977. 332 pp.
23. Minear, Roger A., and Bruce A. Tschantz. "The Effect of Coal Surface
Mining on the Water Quality of Mountain Drainage Basin Streams."
Journal Water Pollution Control Federation, 48:2550, November 1976.
24. Grube, W. E., Jr., R. M. Smith, R. N. Singh, and A. A. Sobek.
"Characterization of Coal Overburden Materials and Mionesoils in
Advance of Surface Mining." Proceedings of the Research and Applied
Technology Symposium on Mined-Land Reclamation, Bituminous Coal
Research, Inc., Monroeville, Pennsylvania, 1973. 150 pp.
25. McDonald, D. G., H. Yocum, and A. E. Grandt. "Studies of Lime-
Limestone Neutralization of Acid Mine Drainage." Proceedings of
Fifth Symposium on Coal Mine Drainage Research, NCA/BCR Coal
Conference and Expo I, Louisville, Kentucky, 1974. p. 229
-64-
-------
26. Ross, L. W. Removal of Heavy Metals from Mine Drainage by Precipi-
tation. EPA-670/2-73-080, U.S. Environmental Protection Agency,
Washington, DC, 1973. 64 pp.
27- Rosehart, R. G. "Mine Water Purification by Reverse Osmosis."
Canadian Journal of Chemical Engineering, 51(6):788, 1973.
28. Gangoli, N., D. C. Markey, and G. Thedos. "Removal of Heavy Metal
Ions from Aqueous Solutions with Fly Ash." Proceedings of the Second
National Conference on Complete Water Reuse, Chicago, Illinois, 1975.
1255 pp.
29. Chu, T.-Y. J., G. R. Steiner, and C. L. McEntyre. "Removal of Complex
Copper-Ammonia Ions From Aqueous Wastes with Fly Ash." Proceedings
of the 32nd Annual Purdue Industrial Waste Conference, Purdue, Indiana,
1977.
30. Gangoli, N., and G. Thedos. Journal Water Pollution Control Federation,
45(5):842, 1973.
31. Tenney, M. W., and T. G. Cole. Journal Water Pollution Control Federation,
40(8):R281, 1968.
32. Tenney, M. W., and W. F. Echelberger. "Fly Ash Utilization in the
Treatment of Polluted Waters." Proceedings of the Second Ash
Utilization Symposium, U.S. Bureau of Mines Information Circular
8488, Pittsburgh, Pennsylvania, 1970. 351 pp.
33. Lorenz, K. Gesundh. Ing., 75:189, 1954.
34. Rieche, A., and J. Strankmueller. Wasserwirtsch. Wassertech.,
8:64, 1968.
35. Bolin, V., and M. Kustka. Science Papers, Institute of Chemical
Technology, 2:247. Faculty of Technology of Fuel and Water,
Prague, 1958.
36. Mancy, K. H., W. E. Gates, J. D. Gye, and P. K. Deb. "Adsorption
Kinetics of ABS on Fly Ash." Proceedings of the 19th Annual Purdue
Industrial Waste Conference, Purdue, Indiana, 1965. 803 pp.
37. Deb, P. K., A. J. Rubin, A. W. Launder, and K. M. Mancy. "Removal
of COD from Wastewater by Fly Ash." Proceedings of the 21st Annual
Purdue Industrial Waste Conference, Purdue, Indiana, 1967. 1122 pp.
38. Rhoad, F. H. Pulp Pap, 32(9):62, 1969.
39. Nasr, M. S., R. G. Gillies, N. N. Bakshi, and D. G. McDonald.
"Color Removal of Pulp Mill Effluents with Fly Ash." Proceedings
of the Second National Conference on Complete Water Reuse, Purdue,
Indiana, 1975. 1311 pp.
-65-
-------
40. Chu, T.-Y. J., R. J. Ruane, and G. R. Steiner. "Characteristics
of Wastewater Discharges From Coal-Fired Power Plants." Proceedings
of the 31st Annual Purdue Industrial Waste Conference, Purdue,
Indiana, 1976. 1164 pp.
41. Stumm, W. "Chemistry of Natural Waters in Relation to Water Quality."
Symposium on Environmental Measurements. U.S. Public Health Service
Publication, 99-WP-15:299, 1964.
-66-
-------
APPENDIX A
PROCEDURES FOR COAL ANALYSIS
-67-
-------
APPENDIX A
PROCEDURES FOR COAL ANALYSIS
MEASUREMENT OF NEUTRALIZATION POTENTIAL*
1. Weight 2.00 % 0.01 g of sample, ground to pass a 60-mesh (F250 mm)
sieve, into a 250 ml Erlenmeyer flask.
2. Carefully pipet 20.00 ml of 0.1 N HC1 (the normality of which is
known exactly) into the flask.
3. Heat nearly to boiling until reaction (acid + carbonates) is complete
(5 minutes usually is sufficient).
4. Add H_0 to a total volume of 150 ml; boil 1 minute; cool.
5. Titrate, using 0.1 N NaOH (concentration exactly known), to pH 7.0
using pH meter.
A. If the pH of the suspension is greater than 7.0 prior to
beginning the back titration with NaOH, it can be assumed
that there is a CaCO- equivalent of over 50 tons per thousand
tons of material.
B. If an exact value of this neutralizing capacity is desired, rerun
the sample using a greater amount of acid initiallly, or using
above procedure but substituting 1.0 N HC1 and 1.0 N NaOH.
6. Calculate neutralization potential using Equation c(2), below.
A. ml acid consumed by sample = ml of acid added to sample, minus
ml base required to neutralize sample x
ml of acid (only) in a flask
ml of base required to neutralize it
B. Parts CaCO- equivalent/million parts of soil = ml acid consumed
by sample x N of acid x
100 10,000 50 grams of CaCOj
grams of sample used 1,000 ^ cram of H*
*Grube, W. E., Jr., R. M. Smith, R. N. Singh, and A. A. Sobek, "Characteriza-
tion of Coal Overburden Materials and Minnesoils in Advance of Surface
Mining," Proceedings of the Research and Applied Technology Symposium on
Mined-Land Reclamation, Bituminous Coal Research, Inc., Monroeville,
Pennsylvania (1973).
-68-
-------
C. For a 2.0 g sample:
(1) Tons CaC03 equivalent/1,000 tons = ml acid consumed by
sample x ^§§1 x N of acid.
(2) Tons CaCO, equivalent/thousand tons of soil = ml x 25 0 x
N of acid?
D. Maximum CaCO- requirement for neutralization of acid developed
from total sulfur = %S x 31.25 (assuming all sulfur occurs as
pyrite or marcasite).
MEASUREMENT OF POTENTIAL ACIDITY WITH PEROXIDE*
Note: If sample contains no carbonates and no sulfates, and the pH
is less than 5.5 in a 1:1 soil-water suspension, then step 1 can be
eliminated.
1. Place 3 g of sample (F60 mesh) into a funnel fitted with filter paper
(11.0 cm, Whatman No. 41). Leach sample with 300 ml of 2:3 HC1 (HC1:
Water) in funnel-full increments, followed by distilled and deionized
water (in funnel-full increments) until effluent is free from chloride
as detected by 10% silver nitrate. Air dry filter paper and sample
overnight, or place in 50@C forced-air oven until dry.
2. Carefully scrape dried sample from paper surface and mix.
3. Weigh out accurately 2.00 g of sample into a 300 ml tall form beaker.
Add 24 ml of reagent grade 30% ILO. and heat beaker on hotplate until
solution is approximately 40@C. Remove beaker from hotplate and allow
reaction to go to completion, or for 30 minutes, whichever comes first.
Three blanks for each batch of samples should be handled in the same
manner. Caution: Initial reaction may be quite turbulent when samples
contain 0.1% sulfur or greater.
4. Add an additional 12 ml of reagent grade H_02 (30%) to beaker and allow
to react for 30 minutes, then place beaker on hotplate at approximately
90 to 95@C for 30 minutes to destroy any unreacted H-O left in beaker.
5. Wash down the sides of the beaker with distilled H_0 and make the
volume of solution to approximately 100 ml.
6. Place beaker on the hotplate or over a Bunsen burner and heat the
solution to boiling to drive off any dissolved CO., then cool the
solution to room temperature.
*Grube, W. E., Jr., R. M. Smith, R. N. Singh, and A. A. Sobek, "Chacteriza-
tion of Coal Overburden Materials and Minnesoils in Advance of Surface
Mining," Proceedings of the Research and Applied Technology Symposium on
Mined-Land Reclamation, Bituminous Coal Research, Inc., Monroeville,
Pennsylvania (1973).
-69-
-------
7. Titrate the solution, with 0.01 N NaOH that is free of C0_ and
protected from the atmosphere, to pH 7.0 using a glass electrode
pH meter. Note: The NaOH must be standardized precisely with
KHCfiH,0, to obtain its exact normality with will be used in the
calculation.
8. Calculations:
A. (ml of NaOH) x (normality of NaOH) x (50) = meq (H*)/100 g
B. meq H /100 g x 0.01 = tons K /thousand tons of material
C. One ton of H requires 50 tons of CaCCL equivalent to
neutralize it.
PROCEDURES USED IN DEVELOPMENT OF COAL PILE DRAINAGE SHAKER TESTS
1. Evaluate time to equilibrium.
A. Label 30 acid-washed and deionized water-rinsed bottles.
B. Weigh out 50 g of -18/+40 coal into 20 of the bottles.
C. Place 250 ml deionized water in all 30 bottles.
D. Place bottles in environmental shaker, set oscillation at 250 rpm
and temperature at 25@C.
E. Record time, date, and pH, Ca , Al , acidity, alkalinity, and
SO, of deionized water.
F. Remove three bottles simultaneously at 24-h intervals.
G. Filter samples using 0.45 m filters.
H. Run pH, Ca-H-, dissolved Fe, SOT, conductivity of each sample.
2. Evaluate coal pH.
A. Label 15 acid-washed and deionized water-rinsed bottles.
B. Place 50 g of -18/+40 coal and 50 ml of deionized water in
10 of these bottles.
C. Put 50 ml of deionized water in remaining 5 bottles.
D. Place bottles in environmental shaker, set oscillation at
250 rpm and temperature at 25@C.
E. Record time, date, and pH of deionized water.
F. Remove bottles in sequence at 20-min intervals.
-70-
-------
G. Filter samples using 0.45 m filters.
H. Run pH of samples immediately after filtering.
3. Evaluate effect of coal-to-elute ratio.
A. Label 10 acid-washed and deionized water-rinsed bottles.
B. Weigh out replicate 10, 25, 50, and 75 g samples of -18/+40
coal and place in bottles.
C. Place 250 ml of deionized water in remaining bottles and label
blank.
D. Place bottles in environmental shaker, set oscillation at
250 rpm and temperature at 25@C.
E. Record time, date, and characteristics of deionized water.
F. Filter samples using 0.45 m filters.
G. Run pH, IDS, dissolved Fe, SOT, conductivity of samples.
4. Evaluate size of coal fraction employed.
A. Label 10 acid-washed and deionized water-rinsed bottles.
B. Weigh out replicate 10, 25, 50, and 75 g samples of F40 mesh
coal and place in bottles.
C. Place 250 ml of deionized water in remaining bottles and label
blank.
D. Place bottles in environmental shaker, set oscillation at
250 rpm and temperature at 25@C.
E. Record time, date, and characteristics of deionized water.
F. Filter samples using 0.45 m filters.
G. Run pH, TDS, dissolved Fe, SOT, conductivity of samples.
5. Evaluate elute pH.
A. Label 21 acid-washed and deionized water-rinsed bottles.
B. Weigh out samples of coal in a quantity determined by step C
and place in 18 of the bottles.
C. Make up liter aliquots of water having pH values of 2, 3, 4,
5, 6, and 7, respectively, by diluting standard HC1 with
deionized water.
D. Add 250 ml of each aliquot to three samples. Add 250 ml
deionized water to remaining 2 bottles.
-71-
-------
E. Place in shaker, set controls.
F. Record time, date, and characteristics of deionized water.
G. Filter samples using 0.45 m filters.
H. Run pH, dissolved Fe, IDS, SOT, conductivity of samples and
aliquots.
6. Evaluate elute hardness.
A. Label 12 acid-washed and deionized water-rinsed bottles.
B. Weigh out samples of coal in a quantity determined in step C
and place in 10 of these bottles.
C. Make up liter aliquots of water containing 0.02, 0.05, 0.1,
0.2, and 0.5 g/1 of CaC03, respectively, by dissolving CaCOg
in deionized water.
D. Add 250 ml of each aliquot to three coal samples. Add 250 ml
deionized water to remaining bottles.
E. Place in shaker, set controls.
F. Record time, date, and characteristics of deionized water.
G. Filter samples using 0.45 m filters.
H. Run pH, IDS, dissolved Fe, SOT, conductivity of samples
and aliquots.
COAL SHAKER TEST
1. Weigh out six 25 g replicate samples of each -18/+40 coal sample*
into 500 ml shaker bottles.
2. Place 250 ml deionized water in each bottle.
3. Place bottles in environmental shaker, set oscillation at 250 rpm
and temperature at 25@C.
4. Remove bottles after 5 days, and filter samples using 0.45 m filters.
5. Analyze samples for pH, conductivity, IDS, iron, manganese, sulfate,
and nickel.
*Coal sample should be as representative of incoming coal as possible.
These were monthly composites of daily samples. Coal should be riffled
to about 50 g sample before weighing to assure representativeness of
the sample.
-72-
-------
APPENDIX B
HYDROLOGICAL DATA
-73-
-------
TABLE B-l. INSTANTANEOUS FLOW MEASUREMENTS
Flow
Date Method (gal/min)
03-03-76 California pipe 572
06-16-76 Pigmy meter 582
10-15-76 Pigmy meter 375
10-27-76 Pigmy meter 1,108
11-01-76 Pigmy meter 564
11-03-76 Pigmy meter 980
-74-
-------
TABLE B-2. RAINFALL-RUNOFF DATA - PLANT J
Test period
(1977)
03/30-04/03
04/12-04/15
04/22-04/25
05/01-05/03
05/07-05/08
05/11-05/19
05/28-06/01
06/02-06/05
06/11-06/21
06/25-06/30
07/02-07/06
07/08-07/17
07/22-07/22
07/26-08/08
08/15-08/18
08/26-08/28
08/31-09/06
09/20-09/27
09/29-10/10
10/12-10/15
10/17-10/25
10/30-11/11
Rainfall
(in)
2.65
0.12
0.95
1.03
0.53
5.05
3.35
2.24
2.03
1.87
1.6
0.85
0.1
0.55
0.45
0.30
1.05
2.95
1.1
0.05
3.77
0.9
Pumping time
(h)
71.5
13.0
6.5
14.0
5.5
114.5
96.75
38.0
41.5
25.75
56.75
22.0
15.75
13.25
12.75
6.5
11.75
78.0
14.25
1.0
72.75
17.75
-75-
-------
TABLE B-3. WEIR READINGS FOR DETERMINATION OF PUMPING RATE
Date
03-11-77
03-12-77
03-13-77
03-14-77
03-20-77
03-28-77
03-30-77
03-31-77
04-03-77
04-06-77
04-08-77
04-16-77
04-19-77
04-23-77
04-24-77
04-25-77
04-26-77
05-01-77
05-03-77
05-21-77
05-23-77
05-24-77
06-14-77
06-20-77
06-20-77
06-21-77
06-21-77
06-21-77
06-23-77
06-24-77
06-27-77
X
s
H
0.34
0.33
0.35
0.38
0.38
0.375
0.395
0.37
0.31
0.33
0.33
0.32
0.35
0.32
0.34
0.31
0.34
0.36
0.36
0.32
0.32
0.31
0.30
0.29
0.21
0.17
0.22
0.15
0.28
0.20
0.29
0.315
0.085
Flow
(cfs)
1.94
1.85
2.02
2.28
2.28
2.225
2.37
2.19
1.69
1.85
1.85
1.77
2.02
1.77
1.94
1.69
1.94
2.11
2.11
1.77
1.77
1.69
1.61
1.53
0.948
0.692
1.02
0.575
1.45
0.881
1.53
1.72
0.47
Flow
(gal/min)
870.67
830.28
906.58
1,023.26
1,023.26
998.58
1,063.66
982.87
758.47
830.28
830.28
794.38
906.58
794.38
870.67
758.47
870.67
946.97
946.97
794.00
794.00
758.00
723.40
686.00
425.00
311.00
458.00
258.00
651.00
395.00
687.00
771.00
208.2
-76-
-------
TABLE B-4. CONVERSION OF RAW RAINFALL-RUNOFF DATA
Input (Rainfall) = Output (Runoff) + Losses
(Drainage area)(Rainfall) = (Pumping rate)(Pumping time) + Losses
(53.3 acres)(R inches) = (46,320 gal/h)(T hours) + Losses
Convert to Common Units:
(53.3 acres)(R inches) = (1.705 acre-in/h) (T hours) + Losses
R (inches) = 3.19 x 10~2 T inches + Losses
Regression can be run by inputting inches of rainfall and hours of
pumping time,_or by inputting centimeters of rainfall and changing
the 3.19 x 10*2 conversion factor to 8.1 x 10*2.
-77-
-------
TABLE B-5. REGRESSION OF RAINFALL VS RUNOFF
Number of Observations in Data Set = 22
(General Linear Models Procedure)
Dependent variable - runoff
Source DF Sum of squares Mean square F value PR J F
Model 1 300.9
21 19.3
Uncorrected Total 22 320.2
300.9
0.919
327.53 0.0001
R-square
C.V.
Standard
deviation
Runoff mean
0.940
34.07
0.9585
2.8133
Parameter
Estimate
t for HO:
Parameter = 0
PR J t
Standard error
of estimate
Rainfall
0.726
18.10
0.0001
0.040
Continued
-78-
-------
TABLE B-5 (Continued)
Number of Observations in Data Set = 22
(General Linear Models Procedure)
Observation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Dependent variable - runoff
Observed Predicted Lower 95% Cl
value value Residual for mean
5.79
1.05
0.527
1.134
0.446
9.27
7.84
3.08
3.36
2.09
4.60
1.78
1.28
1.07
2.21
0.527
0.952
6.32
1.15
0.081
5.89
1.44
4.88
0.221
1.75
1.90
0.977
9.31
6.17
4.13
3.74
3.45
2.95
1.57
0.184
1.01
0.829
0.553
1.94
5.44
2.03
0.0921
6.95
1.66
0.907
0.832
-1.22
-0.764
-0.531
-0.0336
1.66
-1.05
-0.380
-1.36
1.65
0.215
1.09
0.059
1.39
-0.026
-0.984
0.881
-0.873
-0.011
-1.06
-0.221
4.32
0.196
1.55
1.68
0.865
8.24
5.47
3.65
3.31
3.05
2.61
1.39
0.163
0.897
0.734
0.489
1.71
4.81
1.79
0.082
6.15
1.47
Upper 95% Cl
for mean
5.45
0.247
1.95
2.12
1.07
10.4
6.88
4.60
4.17
3.84
3.29
1.75
0.205
1.13
0.925
0.616
2.16
6.06
2.26
0.103
7.75
1.85
-79-
-------
APPENDIX C
PHYSICOCHEMICAL DATA
-80-
-------
TABLE C-l. WATER ftUALITV DA1A--HAHT J
1
00
r
Date
3- 9-76
l«- 7-76
U-13-76
U-29-76
5- 5-76
5-H*-76
5-26-76
6- 9-76
6-17-76
6-22-76
7- 1-76
7- 7-76
7-29-76
8-27-76
9- 1-76
o- 8-76
9.29-76
10- 6-76
10-13-76
10-20-76
10-27-76
Date
3- 9-76
U-7-76
U-13-76
i*-29-76
5- 5-76
5-1U-76
5-26-76
6- 9-76
6-17-76
6-22-76
7- 1-76
7- 7-76
7-29-76
8-27-76
9- 1-76
9- 8-76
9-29-76
10- 6-76
10-13-76
10-20-76
10-27-76
Jfl
(30)
2.9
2.6
2.8
2.5
3.0
2.9
3.0
3.0
2.8
2.9
2.3
3.0
2.9
3.1
2.6
2.5
3.0
3-0
2.3
3.1
2.9
Al
(mgA>)
190
66
350
300
270
2UO
70
2l*0
370
310
350
96
1*1*0
380
250
1*30
260
220
180
270
180
Acidity
{C«CO,)
(«*/£)
1700
1100
5300
2200
2l»00
11*00
300
5500
3700
6100
1700
5900
7100
5900
3600
3900
31*0
3100
3800
3900^,
HI
(ng/L)
1.7
0.7
3.5
2-3
2.2
2.1.
1.2
2.5
3.9
2.7
3.9
l.U
i*.o
U.3
fi.5
2.2
2.3
1.8
1.6
2.1*
l.U
Conductivity Cl
(|iBho*/on ) (mg/L)
2UOO
21*00
5200
U600
.
_
UOOO
5300
U200
5600
.
5UOO
5900
5500
3700
U700
1*1*00
U3oo
J^ 3300
Ca
(ag/L)
190
1*00
31
220
31*0
230
320
330
320
370
260
280
1*90
1*30
300
300
350
320
360
2l*0
Mg
(mg/L)
6k
320
270
220
260
.
160
31*0
210
350
95
380
1*80
1*1*0
17
320
27
150
29 C
290
0
20
_
_
_
„
„
_
„
_
„
_
_
_
_
_
_
_
_
-
Pb
(ng/L)
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
1* D. Sol.
(ng/L) (Bg/L)
2600 3200
1800 2500
1*500 91*00
3100 6800
7500
2700 3100
I*50C 590C
7200 UOOO
1*600 7l»00
71*00 1300C
1800 3500
7800 1200C
7600 16000
9600 11*000
3700 760C
630C
81*00
3800 U700
8000 7700
Ul*00 5800
Ha =B
(mg/L) (cg/L)
< 0.0002
<0.0002
.!
0.0007 <0.1
S. Sol
550
uo
150
ll*0
120
8
2300
210
11*00
uuo
280
1*6
61
170
75
U80
1900
39
71*
63
As
0.010
<• 0.01*5
0.150
o.uo
0.070
o.oUo
0.360
0.170
0.310
0.006
0.080
0.180
0.005
0.20C
o.oeu
0.260
0.310
0.180
0.260
0.200
Fe
(ag/L)
510
300
1800
1100
790
8i*o
2UO
580
760
620
1700
U70
1800
11*00
1600
790
1000
750
780
1UOO
580
c
-------
tABLBC-2. HATER QUALITY DATA--FLAHT E
tat.
11- 3-76
11-27-76
12- 2-76
12-16-76
12-22-76
12-28-76
3- 2-77
3- 7-77
3-ll»-77
l|- 6-77
l*-26-77
6-21-77
1 Date
"l* 11- 3-76
11-27-76
12- 2-76
12-16-76
12-22-76
12-28-76
3- 2-77
3- 7-77
3-1M7
l»- 6-77
l)-26-77
6-21-77
(80)
3.1
2.6
2.6
2.6
2.5
2.6
2.5
2.6
2.5
2.1*
2.3
2.1*
Al
(ngA)
56
38
50
60
22
3b
39
26
38
20
92
Acidity
(C«C03)
(MA)
1600
1300
2100
1300
860
1000
920
700
1200
2500
1*800
1500
HI
(M/L)
0.1*0
0.28
0.1)6
0.31
0.21*
0.26
0.15
0.20
O.UO
0.1)6
0.1*9
o.i»o
Conductivity
(u»ho*/c»)
3000
3000
1*500
31*00
3000
3100
3300
2700
2600
61*00
2200
6000
C«
(M/L) I
210
230
31*0
3-»o
250
2X>
320
110
11*0
1*00
7*0
520
M
[oK/L]
U6
38
81
89
1*5
50
51
31
22
130
78
120
Cl
(»fl'l
19
1£O
1*1.
260
170
170
190
120
15
660
31*0
1*70
1
)
Pb
(ng/L)
<0.01
<0.01
<0.01
<0.01
-------
APPENDIX D
REGRESSION MODELS FOR COAL PILE DRAINAGE
-83-
-------
0.08
Be = 3flO x IO"6TOS «5.7 x 10" 3
0.06
o>
~ 0.04
0.02
500
400 -
300 -
o»
At A
0.00 m I i I
. Mg=3,IO» ID"2 TOS-31.9
200 -
00
2500 5000 7500 10000 12500 15000 17500 0 2500 5000 7500 10000 12500 15000 17500
c
Mn = 3.01 x I(T IDS • 0.049
r1-: 0.666
i I i i i i I i i i i I i i i i I i. i i i
10 -
-Ni=3.l8 x ID'4 IDS -0.34
il 11 i i I i i i i i i i i i I i i i i I i i t i I i i i i
0 2500 5000 7500 10000 12500 15000 17500
IDS
2500 5000 7500 10000 12500 15000 17500
TDS
-------
800
4 r2 = 0.694
lA i i I i i i i I i i i i I i i i i I i i i i I i i i i
2000
1500
9
J 1000
500
-Fe = OI06 TDS»26
i i i ill i i i i I i i i i E i i i i I i i i i I i i i
8000
0 250O 5000 7500 10000 12500 15000 17500 0 2500 5000 7500 10000 12500 15000 17500
*a 6000
> 4000
h-
u
o
g 2000
10000
. CONDUCTIVITY = 0,258 TDS » 2400
A* A
A A
I I I I I I I I I I i i i i I i i i i I i i i i I i i i i I
^=0.656
i ' ' ' I
r2=0.807
I I 1 I I I I i I I i i i i I i i i i. I i i i i J i .1 i i I i.i i i
0 2500 5000 7500 10000 12500 15000 17500
TDS
0 2500 5000 7500 10000 12500 15000 17500
TDS
-------
20
-4
. Zn= 7.67 X 10 IDS » 0.09
15
3 10
c
N
I i i i i I i i i i I i i i j I i i i i I i iiiliiii
400
300
•5 200
P^
V)
100
-2
SiOg= 2.07 XIO TOS-6.13
i i I i i i i 1 i i i i I i i i i
= 0.618
i
00
500
400
~ 300
200
100
2500 5000 7500 10000 12500 15000 17500 0
8000
25OO 5000 7500 10000 12500 15000 17500
-Al = 23x10 IDS'3.16
r2=0.620
i I i i i i I i t i i I i i i i I i i i i I i
6000
VI
4000
t
2000
AODITY = 0.422 IDS«60
i i i
A ****
I i i i i I i i i i I i i i i I i i i i I i i i i I i l i
2500 5000 7500 10000 12500 15000 17500
TOS
2500 5000 7500 10000 12500 15000 17500
TDS
-------
APPENDIX E
QUALITY CONTROL DATA FOR TVA
WATER QUALITY LABORATORY
-87-
-------
TABLE E-l
SHORT TERM SINGLE OPERATOR DATA
BASED ON SEVERAL REPLICATES
ANALYZED AT LEAST THREE DIFFERENT CONCENTRATION LEVELS
Equation for
Parameter Standard Deviation (So=Mx+b)
Cu 0.00945x+4.50
Zn 0.00652x+2.93
Cr 0.0454x+2.71
Ni 0.0133X+8.82
Pb 0.00843x+2.47
Hg 0.0163X+0.079
As* -0.0211x-H.68
As** 0.0429X+0.357
Cd 0.0106x+0.395
Se 0.0571X+0.100
Be 0.00184x+3.92
Sb*** 0.002x+70
Concentration
Range & Units
10-536Mg/l
ll-519|Jg/l
20-llOng/l
226-1150Hg/l
15-l49Mg/lHgA
1.13-5.71ng/l
10-48.5Mg/l
2-lOjJg/l
0.9-21.7Mg/l
5-20yg/l
47-515MS/1
5,000-15,OOOMg/1
Range
of Bias
0 to 14%
-2 to 10%
-3 to 0%
•HO to +14%
-26 to +3%
•*-5 to +38
-3 to 0%
-20 to -3.6%
-10 to +14%
-1 to +1%
-6 to +3%
-4% to -3%
*From 3/76 to 10/12/76 arsenic was analyzed by the silver diethyl
dithiocarbamate method.
**From 10/12/76 to present arsenic was analyzed by the gaseous hydride
method.
***Data from EPA manual.
-88-
-------
TABLE E-2
LONG TERM QUALITY CONTROL CHART DATA
BASED ON OBSERVATIONS FROM MARCH 1976 TO JUNE 1977
% Relative Standard Deviation
Mean Mean Average
Parameter Observations # Concentration (pg/1) %RSD %Bias
Cu 120 280 0.96 0,93
Zn 140 310 0.98 0.75
Cr 180 51 3.98 0.39
Ni 120 570 2.26 1.22
Pb 200 53 5.22 2.36
Hg 110 1.9 3.28 2.01
As* 55 25 4.77 1.21
As** 60 7.4 5.38 1.98
Cd 169 7.9 2.63 0.75
Se 100 9.0 4.95 2.75
Be 69 250 0.93 0.65
Sb 16 1,900 0.81 1.52
*Frotn 3/76 to 10/12/76 arsenic was analyzed by the silver diethyl
dithiocarbamate method.
**From 10/12/76 to present arsenic was analyzed by the gaseous hydride
method.
-89-
-------
TABLE E-3
COMPARISON OF SHORT TERM SINGLE OPERATOR DATA WITH THAT PREDICTED
FROM LONG TERM QUALITY CONTROL CHART DATA
Standard Deviation
Mean Value (Mg/1) (Mg/D (Hg/D
Parameter from Control Charts So Predicted**** So Found*****
Cu 280 7.14 2.69
Zn 310 4.95 3.04
Cr 51 5.02 2.03
Ni 570 16.4 12.9
Pb 53 2.92 2.77
Hg 1.9 0.110 0.118
As* 25 1.15 2.98
As** 7.4 0.674 0.398
Cd 7.9 ' 0.479 0.208
Se 9.0 0.414 0.446
Be 250 4.39 2.33
Sb 1,900 73.4*** 15.4
*From 3/76 to 10/12/76 arsenic was analyzed by the silver diethyl
dithiocarbamate method.
**From 10/12/76 to present arsenic was analyzed by the gaseous
hydride method.
***Data from EPA manual.
****So predicted is found by using mean value from control charts to
solve equation for standard deviation for short term single operator
data in Table I.
*****So found is product of long term RSD and mean value from control
charts.
-90-
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/7-79-051
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Characterization of Coal Pile Drainage
6. REPORT DATE
February 1979
6. PERFORMING ORGANIZATION CODE
7.AUTHOR(S)
r. •* w I r-iwni^i ^^
Doye B. Cox, Tien-Yung J. Chu, and
Richard J. Ruane
B. PERFORMING ORGANIZATION REPORT NO.
9 PERFORMING ORGANIZATION NAME AND ADDRESS
Tennessee Valley Authority
1320 Commerce Union Bank Building
Chattanooga, Tennessee 37401
10. PROGRAM ELEMENT NO.
INE624A
11. CONTRACT/GRANT NO.
EPA-IAG-D5-E-721
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 COVERED
Final; 5/75 - 1/79
14. SPONSORING AGENCY CODE
EPA/600/13
IB. SUPPLEMENTARY NOTES yjERL-RTP project officer is Michael C. Osborne, MD-61, 919/
541-2898.
16. ABSTRACT
repOrt gives results of sampling programs at two TVA coal-fired
steam plants. Coal samples were collected from the plants for development and
application of a shaker-type elution test for coal analysis. Rain gages were installed
at both plants, and runoff was measured from one plant. Drainage was collected and
subjected to a number of bench-scale treatment studies using fly ash. Results indi-
cate that coal pile drainage is highly acidic with pH's of 2. 2 to 3. 1. Total suspended
solids concentrations, generally low during base flow periods, increase dramati-
cally during storm runoff to levels as high as 2300 mg/liter. Sulfate concentrations
were also quite high: 1800 to 9600 mg/liter. Concentrations of Fe and Mn were both
very high: 23 to 1800 and 1. 8 to 45 mg/liter, respectively. Other substances with
concentrations of note include Al, Zn, Hg, As, and Se. Characteristics of elutes
from shaker-type laboratory studies, except for pH, do not reflect values from field
drainage of the same stored coal. Treatment with alkaline fly ash slurries , using
ash sluicing ratios commonly encountered, can effectively raise the final solution
pH and remove a variety of metals from solution. It was also observed that about
73% of the total rainfall is direct runoff.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Pollution
Coal Storage
Coal
Drainage
Runoff
Sampling
Analyzing
Fly Ash
Sulfates
Iron
Manganese
Pollution Control
Stationary Sources
Coal Piles
13B
081
08G
08H
146
21B
07B
21. NO. OF PAGES
97
18. DISTRIBUTION STATEMENT
Unlimited
IB. SECURITY CLASS (TUs Report)
Unclassified
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (8-73)
91
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