United States
Environmental Protection
Agency
Office of Research and
Development
Washington DC 20460
EPA/600/R-00/010
October 1999
Stormwater Treatment at
Critical Areas
Evaluation of Filtration Media
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EPA/600/R-00/010
October 1999
Stormwater Treatment At
Critical Areas
Evaluation of Filtration Media
Shirley Clark and Robert Pitt
Department of Civil and Environmental Engineering
The University of Alabama at Birmingham
Birmingham, Alabama
Cooperative Agreement No. CX 824933
Project Officer
Richard Field
Wet-Weather Flow Research Program
National Risk Management Research Laboratory
Edison, New Jersey 08837
National Risk Management Research Laboratory
Office Of Research And Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
Printed on Recycled Paper
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Notice
The information in this document had been funded wholly or in part by the United States Environmental
Protection Agency under cooperative agreement no. CX 824933 for the University of Alabama at
Birmingham. Although it has been subjected to the Agency's peer and administrative review and has
been approved for publication as an EPA document, it does not necessarily reflect the views of the
Agency and no official endorsement should be inferred. Also, the mention of trade names or commercial
products does not imply endorsement by the United States government.
ii
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Foreword
The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation's
land, air, and water resources. Under a mandate of national environmental laws, the Agency strives to
formulate and implement actions leading to a compatible balance between human activities and the ability
of natural systems to support and nurture life. To meet this mandate, EPA's research program is providing
data and technical support for solving environmental problems today and building a science knowledge
base necessary to manage our ecological resources wisely, understand how pollutants affect our health,
and prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency's center for investigation of
technological and management approaches for reducing risks from threats to human health and the
environment. The focus of the Laboratory's research program is on methods for the prevention and
control of pollution to air, land, water and subsurface resources; protection of water quality in public water
systems; remediation of contaminated sites and ground water; and prevention and control of indoor air
pollution. The goal of this research effort is to catalyze development and implementation of innovative,
cost-effective environmental technologies; develop scientific and engineering information needed by EPA
to support regulatory and policy decisions; and provide technical support and information transfer to
ensure effective implementation of environmental regulations and strategies.
This publication has been produced as part of the Laboratory's strategic long-term research plan.
It is published and made available by EPA's Office of Research and Development to assist the user
community and to link researchers with their clients.,
E. Timothy Oppelt, Director
National Risk Management Research Laboratory
111
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Abstract
This is one volume in the report series entitled "Stormwater Treatment at Critical Areas" and describes the
work conducted on filtration media for stormwater treatment between 1994 and 1996. Other volumes in
this report series describe the results of field investigations to determine sources of urban stormwater
runoff pollutants, field investigations of storm drain inlet devices, and development of a prototype
treatment device that could be installed at the storm drain inlet in critical source areas.
Filtration, especially 'slow' filtration, is of interest for stormwater runoff treatment because filters will work
on intermittent flows without significant loss of capability. This work was initially planned to be the
optimization of a sand filter to be installed in the filter chamber of the Multi-Chambered Treatment Train
(MCTT). However, the poor removals provided by newly constructed sand filters led to the investigation of
other media that had the potential to more 'permanently' retain pollutants.
Stormwater filters currently in operation typically use the following media - sand, compost, and peat. This
research tested the capabilities of the media currently in use, plus others with known filtering capability
(activated carbon, zeolite, a cotton milling waste, and a wood waste), in both controlled laboratory and
field conditions. Influent and effluent samples from each filter column were analyzed for toxicity, turbidity,
conductivity, pH, major anions and cations, and particle size distribution for each test.
This research demonstrated that physical clogging of the filters occurred well before the sorptive capacity
of most media is reached when stormwater runoff is filtered without adequate pre-treatment. If adequate
pre-settling is done, the solids remaining in the runoff are generally very small (colloidal). These filters are
capable of removing many of the colloidal sized particles; however, the percent removals (measured as
suspended solids removal) are smaller when there are fewer larger particles in the influent. Testing using
laboratory-scale columns showed that an activated carbon-sand filter is the best at removing the
stormwater pollutants. The range of cumulative suspended solids loadings is from 200 g/m2 (peat-sand) to
2,000 g/m2 (carbon-sand) before the hydraulic capacity is reduced to 1 m/day. Because these tests were
performed using small columns (4.76 cm diameter and 45.72 cm depth) and were not able to completely
dry between most of the tests, it is expected that the suspended solids loadings in full-scale filters will be
about five times greater than these values before the filter clogs.
In terms of chemical capacity, results of the testing showed that the activated carbon, peat moss, zeolite
and compost were the most efficient media at removing the toxicants from the runoff and retaining them
during subsequent flushings with clean distilled water. Sand, the most common filtering media currently in
use, effectively removed toxicants from the runoff; however, the effluent from subsequent distilled water
flushings through newly constructed sand filters indicated that the toxicants were displaced from their
"trapped" pores by the water. The flushing effluent was significantly more toxic than the flushing influent
clean water. Based on historical full-scale installations, aged sand, after being exposed to field conditions
for some time, apparently ripens due to deposition of organic and mineral material and can be much more
effective that when first installed. The compost, although an effective filter, added an undesirable color to
its effluent. The peat moss, also an effective filter, increased the turbidity of and added color to the runoff.
The activated carbon was found to be the most effective at removing the toxicants while not increasing
the turbidity and color. In all cases, the media had to be mixed with sand to maintain adequate flow rates.
Research is continuing regarding the ability of filters to treat stormwater runoff and it is anticipated that a
future volume in this series will detail the results of the ongoing work. This new phase of the filter project
has two purposes: 1) quantify the effects that pH, ionic strength and influent concentration will have on
the removal ability and capacity of the filter media; and 2) perform pilot-scale studies using several
selected media in order to determine the applicability of the bench-scale results to full-scale operations.
iv
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These two steps are required in order to develop design guidelines for stormwater filters that will be useful
for the engineering community and stormwater management planners.
This research was funded partly by the U.S. Environmental Protection Agency's Wet Weather Flow
Research Program (Richard Field, Leader and Project Officer) of the Water Supply and Water Resources
Division, National Risk Management Research Laboratory under Cooperative Agreement No. CR 824933,
and partly by the U.S. Army Corps of Engineers' Construction Engineering Research Laboratory (Richard
Scholze, Project Officer).
v
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Contents
Notice ii
Foreword ill
Abstract iv
Contents
Tables
Figures xlii
Acknowledgments xv
Chapter 1: Introduction 1
Characteristics of Urban Runoff 1
Nutrients 4
Organics and Pesticides 4
Pathogenic Microorganisms 4
Metals 6
Solids 6
Urban Snowmelt Water Quality 6
Pollutant Concentrations in Snowmelt Sheetfiows 7
Snowmelt Quality Summary 8
Filterable (Dissolved) Fraction of Stormwater Pollutants 11
Sources of Stormwater Pollutants 11
Stormwater Runoff Treatment Media 12
Future Research 15
Chapter 2: Review of Media Filtration for Stormwater Quality Control 16
Sand 16
Physical Characteristics 16
General Removal Capabilities 17
Ripening of the Sand Filter 18
Adsorbent Coatings 18
Limitations 19
Stormwater Runoff Treatment '. 19
Activated Carbon 22
Organic Removal Capability 22
Inorganic (Non-Metal) Removal Capability 24
Metal Removal Capability 25
Microorganism Removal Capability 25
Other Carbon-Based Filters 26
Limitations of Activated Carbon 26
Peat Moss , 27
Peat Composition 27
Hydraulic Characteristics 28
Organic Removal Capability .28
Inorganic (Non-Metal) Removal Capability 30
Metal Removal Capability 30
Limitations of Peat Filters 31
Stormwater Runoff Treatment.... 31
vii
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Compost 33
Zeolite .' 35
Physical Characteristics 35
Zeolite Synthesis 35
Zeolite Adsorption/Ion-Exchange Characteristics 36
Organic Removal Capability 37
Inorganic Removal Capability 37
Enretech 38
Forest Products Agrofiber 38
Gunderboom and EMCON Filter Fabrics 38
Limitations of the Literature Review 38
Chapters: Methodology 39
Overview of the Experimental Design 39
Experimental Procedure 40
Filtration Media and Test Apparatus 40
Collection of Stormwater Runoff 43
Laboratory Procedures 43
Initial Test Procedure for the Sand Column 44
Procedure for Determining the Effects of Sediment Accumulation on Filter Flow Rate 44
Procedure for Bench-Scale Testing (Effects of pH and Ionic Strength on Pollutant Removal) 45
Procedure for Long-Term Filtration Performance Testing 46
Chapter 4: Results and Discussion 48
Initial Test Procedure for the Sand Column 48
Effects of Sediment Accumulation on Flow Rates of Different Filters 49
Effects of pH and Ionic Strength on Pollutant Removal 52
Clogging Observations 53
Analysis Results 53
Long-Term Treatment Performance 62
Chapters: Conclusions: Design of Stormwater Filters 79
Selection of Filtration Media for Pollutant Removal Capabilities 79
Sand , 83
Activated carbon-sand 83
Peat-sand 83
Zeolite-sand 82
Compost-sand 82
Enretech-sand 82
Agrofiber-sand and Filter fabrics 83
Design of Filters for Specified Filtration Durations 83
Example Filter Designs 84
Example 1 85
Example 2 85
Example 3 85
References 87
Appendix A: Loadings on Media A-1
Carbon-Sand A-2
Compost-Sand A-3
Enretech-Sand A-4
Peat-Sand A-5
Sand A-6
Vlll
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Zeolite-Sand A-7
Appendix B: Bench-Scale Test-Results B-1
Toxicity . B-2
Turbidity B-9
Conductivity B-16
Color B-21
pH B-28
Chemical Oxygen Demand B-33
Hardness .....B-40
Suspended Solids B-47
Particle Size Distribution (6 to 8 j^m) B-54
Particle Size Distribution (20 to 22 jim) ....B-61
Particle Size Distribution (52 to 54 jam) B-68
Particle Size Distribution (4 to 128 ^m) ^.B-75
Zinc B-82
Copper B-89
Appendix C: Physical Parameters C-1
Toxicity C-2
Turbidity C-10
Conductivity C-14
Color , C-18
pH .' :........... C-26
Appendix D: Anions D-1
Anions (Carbonate, Bicarbonate, Fluoride, Chloride, Nitrite, Nitrate, Phosphate, Sulfate) D-2
Appendix E: Cations :...... E-1
Cations (Hardness, Lithium, Sodium, Ammonium, Potassium, Magnesium, Calcium): E-2
Appendix F: Solids and Particle Size Distribution F-1
Solids (Total, Dissolved, Suspended, Volatile Total, Volatile Dissolved, Volatile Suspended) F-2
Particle Size Distribution (1 to 2, 4 to 5, 11 to 12, 1 to 128 urn).. ...F-24
Appendix G: Metals G-1
Zinc G-2
Copper G-6
Appendix H: Organics and Pesticides H-1
Chemical Oxygen Demand H-2
Semi-Volatile Organics H-10
Pesticides H-29
IX
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Tables
1 Characteristics of stormwater runoff
2 Median stormwater pollutant concentrations for all sites by land use
3 Summary of NURP priority pollutant analyses
4 Toxic organic source area observations
5 Heavy metal source area concentrations
6 Comparison of snowmelt and rainfall runoff quality
7 Reported filterable (dissolved) fractions of stormwater toxicants
8 Urban runoff hazardous and toxic substances
9 Stormwater treatment device characteristics
10 Runoff treatment pollutant removal capabilities
11 Filtration media pollutant removal pathways
12 Physical/chemical properties of filter media
13 Pollutant removal efficiencies for sand filters
14 Peat-sand filter pollutant removal efficiencies
15 Compost filter pollutant removal efficiencies
16 Compost filter removal efficiencies - first flush
17 Laboratory analyses
18 Mass Balance Data
19 Stormwater runoff filtration in sand columns, measured as toxicity by Microtox™.
20 Particulate removal efficiencies
21 Performance classification for filter fabrics and media
22 Clogging results for initial media
23 Clogging test results for newly selected media
24 Treatment capacity as related to suspended solids loading
25 Influent characteristics for bench scale tests
26 Wilcoxon P values for toxicity ,
27 Wilcoxon P values for turbidity
28 Wilcoxon P values for conductivity
29 Wilcoxon P values for color
30 Wilcoxon P values for pH
31 Wilcoxon P values for hardness
32 Wilcoxon P values for chemical oxygen demand
33 Wilcoxon P values for PSD (4 to 128 jim)
34 Wilcoxon P values for PSD (6 to 8 jim)
35 Wilcoxon P values for PSD (20 to 22 |im)
36 Wilcoxon P values for PSD (52 to 54 jim)
37 Wilcoxon P values for suspended solids
38 Wilcoxon P values for zinc
39 Wilcoxon P values for copper
40 Wilcoxon P values for toxicity (unfiltered fraction)
41 Wilcoxon P values for toxicity (filtered fraction)
42 Wilcoxon P values for turbidity (unfiltered fraction)
43 Wilcoxon P values for turbidity (filtered fraction)
44 Wilcoxon P values for color (unfiltered fraction)
45 Wilcoxon P values for color (filtered fraction)
..2
,..3
...3
...5
...6
.10
.11
.12
.12
.13
.14
.14
.20
.32
.34
.34
.44
.45
.49
.50
.50
.51
.51
.52
.53
.55
.55
.55
.56
.56
.57
.57
.59
.59
.59
.60
.60
.61
.61
.63
.63
.64
.64
.64
.64
x
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47 Sign test P values for pH 65
48 Wilcoxon P values for carbonate 66
49 Wilcoxon P values for bicarbonate 66
50 Wilcoxon P values for fluoride 66
51 Wilcoxon P values for chloride 67
52 Wilcoxon P values for nitrate 67
53 Wilcoxon P values for sulfate 68
54 Wilcoxon P values for hardness 68
55 Wilcoxon P values for sodium 68
56 Wilcoxon P values for ammonium 69
57 Wilcoxon P values for potassium 69
58 Wilcoxon P values for magnesium 70
59 Wilcoxon P values for calcium 70
60 Wilcoxon P values for total solids ! 71
61 Wilcoxon P values for total dissolved solids 71
62 Wilcoxon P values for total suspended solids 71
63 Wilcoxon P values for volatile total solids.. ; 72
64 Wilcoxon P values for volatile dissolved solids 72
65 Wilcoxon P values for volatile suspended solids 72
66 Wilcoxon P values for PSD (1 to 2 pm) , 73
67 Wilcoxon P values for PSD (4 to 5 urn) 73
68 Wilcoxon P. values for PSD (11 to 12.5 (im) "74
69 Wilcoxon P values for PSD (1 to 128 urn) '", 74
70 Wilcoxon P values for zinc for presettled influent 74
71 Wilcoxon P values for copper for presettled influent 75
72 Wilcoxon P values for chemical oxygen demand (unfiltered fraction) 75
73 Wilcoxon P values for chemical oxygen demand (filtered fraction) 75
74 Wilcoxon P values for semi-volatile organics for presettled influent 76
75 Wilcoxon P values for pesticides for presettled influent 76
76 Average percent removal by media 78
77 Filtration capacity as a function of suspended solids loading 83
78 Filtration capacity of presettled water (<10 mg TSS/L influent) " 83
79 Filter flow rates for saturated and partially clogged filters and recovered filtration capacity after
thorough drying , 84
80 Filter categories based on capacity 84
81 Volumetric runoff coefficients by land use 85
82 Suspended solids concentration by land use 85
Appendix B: Bench-Scale Test Results B-1
Toxicity !!."""."!.""!! B-2
Turbidity ""!"!!.""""" B-9
Conductivity .'".'"!!!."""."!!" B-16
Color B-21
PH .B-28
Chemical Oxygen Demand 3.33
Hardness B-40
Suspended Solids .'.!"""."!." B-47
Particle Size Distribution (6 to 8 jam) !.".'"!."".'"." B-54
Particle Size Distribution (20 to 22 jj,m) , „].!.""!!!!!.'B-61
Particle Size Distribution (52 to 54 urn) .'.!..""s-68
Particle Size Distribution (4 to 128 (im) "".'"".""".' B-75
?inc !"Z"!""!!!"!"!""!""".""!;B-82
c°PPer • . B-89
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Copper B'89
Appendix C: Physical Parameters c'1
Toxicity c'2
Turbidity : c-10
Conductivity c'14
Color c"18
pH C-26
Appendix D: Anions D-1
Anions (Carbonate, Bicarbonate, Fluoride, Chloride, Nitrite, Nitrate, Phosphate, Sulfate) D-2
Appendix E: Cations • ^"1
Cations (Hardness, Lithium, Sodium, Ammonium, Potassium, Magnesium, Calcium) E-2
Appendix F: Solids and Particle Size Distribution F-1
Solids (Total, Dissolved, Suspended, Volatile Total, Volatile Dissolved, Volatile Suspended) F-2
Particle Size Distribution (1 to 2, 4 to 5, 11 to 12, and 1 to 128 ^m) F-24
Appendix G: Metals G~1
Zinc G'2
Copper G'6
Appendix H: Organics and Pesticides H'1
Chemical Oxygen Demand H-2
Semi-Volatile Organics H-10
Pesticides H'29
xii
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Figures
3-1 Column Construction 41
3-2 Columns on Carouse! 42
4-1 Flow rate vs. suspended solids loading on sand 52
4-2 Effluent suspended solids and chemical oxygen demand concentrations versus suspended
solids loading on media 58
Appendix A: Loadings on Media A-1
Carbon-Sand A-2
Compost-Sand „.. A-3
Enretech-Sand ; A-4
Peat-Sand A-5
Sand A-6
Zeolite-Sand A-7
Appendix B: Bench-Scale Test Results B-1
Toxicity B-6
Turbidity B-13
Conductivity B-17
Color B-25
PH B-29
Chemical Oxygen Demand B-37
Hardness B-44
Suspended Solids B-51
Particle Size Distribution (6 to 8 jam) B-58
Particle Size Distribution (20 to 22 |j.m) B-65
Particle Size Distribution (52 to 54 jam) B-72
Particle Size Distribution (4 to 128 jam) B-79
Zinc B-86
Copper B-93
Appendix C: Physical Parameters C-1
Toxicity C-4
Turbidity C-12
Conductivity C-16
Color C-20
PH C-28
Appendix D: Anions D-1
Carbonate D_6
Bicarbonate D-7
Fluoride O-8
Chloride !.!"!o-9
Nitrate ......D-IQ
Sulfate ; !""o-11
xixi
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Appendix E: Cations E-1
Hardness E-6
Sodium E-7
Ammonium E-8
Potassium E-9
Magnesium E-10
Calcium E-11
Appendix F: Solids and Particle Size Distribution F-1
Total Solids F-6
Dissolved Solids F-7
Suspended Solids F-8
Volatile Total Solids F-9
Volatile Dissolved Solids F-10
Volatile Suspended Solids F-11
Particle Size Distribution (1 to 2 ^m) F-26
Particle Size Distribution (4 to 5 ^m) F-27
Particle Size Distribution (11 to 12 ^m) F-28
Particle Size Distribution (1 to 128 ^m) F-29
Appendix G: Metals G-1
Zinc G-4
Copper G-8
Appendix H: Organics and Pesticides H-1
Chemical Oxygen Demand H-4
2,4-Dinitrophenol: PreSettled Influent H-24
2-Methyl-4,6-Dinitrophenol H-25
Di-n-butylphthalate H-26
Bis(2-ethylhexyl)phthalate H-27
Pentachlorophenol H-28
Dieldrin H-39
4,4'-DDT H-40
xiv
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Acknowledgments
This research was mostly funded by the Wet-Weather Flow Research Program (formally the Storm and
Combined Sewer Pollution Control Program) of the U.S. EPA, Edison, New Jersey. Richard Field, the
project officer, provided much guidance and assistance during the research. Chi-Yuan Fan, David
Fischer, Izabela Wojtenko, Michael Brown and Thomas O'Connor of this program also provided valuable
project assistance. Additional funding was also provided by the U.S. Army Corps of Engineers
Construction Engineering Research Laboratories in Champaign, Illinois. Rick Scholze's efforts are greatly
appreciated.
Many UAB graduate students and staff freely gave of their time to support this project, especially Brian
Robertson, Olga Mirov, Charles Robinson, Lyn Lewis, Jay Day, and Tim Awtrey. Four MSCE theses in
the Department of Civil and Environmental Engineering at the University of Alabama at Birmingham were
also prepared by graduate students working on this EPA sponsored project series:
• Shirley Clark's Evaluation of Filtration Media for the Treatment of Stormwater (1996),
• Brian Robertson's Evaluation of a Multi-Chambered Treatment Train for Treatment of Stormwater
Runoff from Critical Pollutant Source Areas (1995),
• Ali Ayyoubi's Physical Treatment of Urban Storm Water Runoff Toxicants (1993), and
• Patricia Barren's Characterization of Polynuclear Aromatic Hydrocarbons in Urban Runoff (1990).
Much of the material in this report was previously presented in these theses, which also contain
considerable additional supporting information.
The authors would also like to thank the following for donation of materials to the project: Polar Supply
Company, Inc. of Anchorage, Alaska for donating Gunderboom filter fabric material, Emcon North West of
Bothell, Washington for the EMCON fabric, Stormwater Management, Inc. of Portland, Oregon for
donating the compost media, RAM Services, Inc. of Birmingham, Alabama for the Enretech, and Forest
Products Lab of the U.S. Forest Service for the agrofiber.
xv
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Chapter 1
Introduction
Infiltration of stormwater runoff into soil has long been an accepted practice for the disposal of stormwater
and replenishment of groundwaters in many locations in the United States. With the advent of
urbanization, many of the natural infiltration areas have disappeared permanently, due to both covering
the land with pavement and buildings and to the regrading and compacting that accompanies
construction. Along with the decrease in area available for infiltration, the volume of runoff from urban
areas has increased, as has the runoff's pollutant loadings. Some of this urban runoff may not be suitable
for replenishing groundwater due to its pollutant loading from the surfaces over which it flows.
Investigation of treatment systems for this runoff is an on-going process; however, there is little
information available that compares the various treatment devices. Two recent works that compare the
performance of some of the treatment devices are Claytor and Schueler's Design of Stormwater Filtering
Systems (1996) and Herrera Environmental Consultants' work for the City of Bellevue, WA (1991 and
1995).
Because of the manner in which storm drainage systems are designed and constructed, the untreated
runoff from problem areas is combined at its inflow point to the storm sewer system with runoff already in
the system. This combined runoff typically is directly discharged into surface waters, or occasionally to
groundwaters. It is unlikely to be treated prior to discharge to either surface or ground receiving waters.
Even if the runoff were to be treated at the 'end of the pipe' prior to its discharge, the volume of runoff is
so large that treatment facilities would be very expensive to construct and maintain. In some locations,
stormwater runoff is combined with sanitary wastewater and the combined flow is directed toward the
municipal wastewater treatment plant. However, in most cities with these combined sewers, the volume of
water to be treated during and immediately following a rain event is too large to be completely treated.
Much of the combined sewage bypasses the treatment plant (combined sewer overflow 'CSO') and may
be only partially treated (e.g., coarse screening and disinfected) before discharge. Treating runoff from
critical source areas before it is combined with runoff from other areas is more cost effective.
To prevent harm either to the surface waters or to the groundwater, the stormwater runoff from problem
or critical source areas or stormwater hotspots needs to be treated. Stormwater hotspots are those places
where generation of significantly higher concentrations of hydrocarbons, toxic trace metals, or other
toxicants and pollutants may occur. Examples of these hotspots include the following: airport deicing
facilities, auto recyclers/junkyards, commercial garden nurseries, parking lots, vehicle fueling and
maintenance stations, bus or truck (fleet) storage areas, industrial rooftops, marinas, outdoor transfer
facilities, public works storage areas, and vehicle and equipment washing/steam cleaning facilities
(Bannerman, et al. 1993; Pitt, et al. 1995; Claytor and Schueler 1996). Rather than treating the large
volume of runoff at the end of the pipe, one potentially cost-effective approach is to treat the runoff from
the specific problem sources before it mixes with the runoff from the majority of 'non-problem' areas, such
as residential developments, institutional developments, and non-industrial rooftops (Pitt, et al. 1995;
Claytor and Schueler 1996). Single, small point-source treatment devices have been developed and are
currently being marketed. Most of these treatment devices, however, are designed to remove settleable
solids, not colloidal or soluble pollutants. Only recently have these in-line treatment devices begun to use
filtration as a planned treatment step to remove the colloidal and soluble pollutants.
Characteristics of Urban Runoff
Urban runoff is comprised of many different flow phases, such as dry-weather base flows, stormwater
runoff, nonstormwater and inappropriate entries, combined sewer overflows (CSOs), sanitary wastewater
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and snowmelt. The relative magnitudes of each phase's volume vary considerably, based on many
factors. Season (cold versus warm weather, or dry versus wet weather) and land use have been identified
as important factors affecting base flow and stormwater runoff quality.
Land development increases stormwater runoff volumes and pollutant concentrations. Impervious
surfaces, such as rooftops, driveways, sidewalks and roads, reduce infiltration of rainfall and runoff into
the ground, increase runoff quantity, and degrade runoff quality. The most important hydraulic factors
affecting urban runoff volume (and therefore the amount of water available for infiltration) is the quantity of
rain and the extent of impervious surfaces directly connected to a water body or a drainage system.
Directly connected impervious surfaces include paved streets, driveways, and parking areas draining to
curb-and-gutter drainage systems, and roofs draining directly to a storm or combined sewer. Generally,
the 5-day biochemical oxygen demand (BOD5) and nutrient concentrations in stormwater are lower than in
raw sanitary wastewater; they are closer in quality to treated sanitary wastewaters. However, urban
stormwater has relatively high concentrations of bacteria, as well as high concentrations of many metallic
and some organic toxicants.
Table 1 presents older stormwater runoff quality data while Tables 2 and 3 summarize the stormwater
data collected as part of the Nationwide Urban Runoff Program (NURP) from approximately 1979 to 1982.
The NURP data is the most comprehensive runoff quality data available on a nationwide basis. These two
data sets highlight the important effects that land use and source areas (parking areas, rooftops, streets,
landscaped areas, etc.) have on stormwater runoff quality.
Fable 1. Characteristics of stormwater runoff (Source: APWA 1969)
Location
East Bay Sanitation District, Oakland, CA
Minimum
Maximum
Average
Cincinnati, OH
Maximum seasonal means
Average
Los Angeles County Average 1 962-63
Washington, DC catch-basin (rain)
Minimum
Maximum
Average
Seattle, WA
Oxney, England
Moscow, U.S.S.R.
Leningrad, U.S.S.R.0
Stockholm, Sweden
Pretoria, South Africa5
Residential
Business
Detroit, Michigan
BOD5
(mg/L)
3
7,700
87
12
17
161
6
625
126
10'
100"
186-285
36
17-80
30
34
96-234
Total solids
(mg/L)
726
1,401
260
2,909
2,045'
1,000-3,500*
14,541
30-8,000
310-914
Suspended solids
(SS) (mg/L)
16
4,400
613
227
26
36,250
2,100
102-213'
Chloride
(mg/L)
300
10,260
5,100
199
11
160
42
COD
(mg/L) i
110
111
18-3,100
29
28
a Maximum b Mean c Single value reported for study (value not designated as mean or maximum)
BOD: biochemical oxygen demand COD: chemical oxygen demand
Because some municipalities and water management districts want to use this runoff as a recharge water
source for groundwater, there is a need for effective pretreatment of it prior to groundwater recharge
(National Academy of Sciences 1994; Pitt, etal. 1995). Reviews of the research being done on direct
infiltration of urban runoff has shown that contamination of groundwater has occurred by infiltration of
urban runoff containing the following problem substances:
• Nutrients
• Organics and Pesticides
• Pathogenic Microorganisms
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• Metals
• Solids (Suspended and Dissolved)
Table 2. Median stormwater pollutant concentrations for all sites by land use (Nationwide Urban Runoff
Program, NURP) (Source: EPA 1983)
Pollutant
BODS, mg/L
COD, mg/L
TSS, mg/L
TKN, ng/L
NO,+NO, (as N) ng/L
Total P, ng/L
Soluble P, |ig/L
Total Lead, |ig/L
Total Copper, ^g/L
Total Zinc, ng/L
Residential
Median
10
73
101
1900
736
383
143
144
33
135
COV
0.41
0.55
0.96
0.73
0.83 '
0.69
0.46
0.75
0.99
0.84
Mixed land use
Median
7.8
65
67
1288
558
163
56
114
27
154
COV
0.52
0.58
1.14
0.50
0.67
0.75
0.75
1.35
1.32
0.78
Commercial
Median
9.3
57
69
1179
572
201
80
104
29
226
COV
0.31
0.39
0.85
0.43
0.48
0.67
0.71
0.68
0.81
1.07
Open/nonurban
Median
-
40
70
965
543
121
26
30
--
195
COV
-
0.78
2.92
1.00
0.91
1.66
2.11
1.52
--
0.66
COV = coefficient of variation :
standard deviation
mean
TKN: Total Kjeldahl nitrogen
P: phosphorus
Table 3. Summary of NURP priority pollutant analyses' (Source: EPA 1983)
Pollutant
Pesticides
a-BHC
y - BHC (lindane)
Chlordane
a - Endosulfan
Metals and cyanide
Antimony
Arsenic
Beryllium
Cadmium
Chromium
Copper
Cyanides
Lead
Mercury
Nickel
Selenium
Zinc
PCBs and related compounds
Halogenated aliphatics
Methyiene chloride
Ethers
Monocyclic aromatics
Phenols and Cresols
Phenol
Pentachlorophenol
4-Nitrophenol
Phthalate esters
Bis(2-ethylhexyl)phthalate
Polycyclic aromatic hydrocarbons
Chrysene
Fluoranthene
Phenanthrene
Pyrene
Frequency of detection
20
15
17
19
13
52
12
48
58
91
23
94
10
43
11
94
Range of detected concentrations
(Mfl/L)
0.0027 to 0.1
0.007 to 0.1
0.01 to 10
0.008 to 0.2
2.6 to 23
1 to 51
1 to 49
0.1 to 14
1 to 190
1 to 100
2 to 300
6 to 460
0.6 to 1.2
1 to 182
2 to 77
10 to 2400
None detected in >1% of samples
11
5 to 15
None detected in any samples
None detected in >6% of samples
14
19
10
22
10
16
12
15
1 to 13
1 to 115
1 to 37
4 to 62
0.6 to 10
0.3 to 21
0.3 to 10
0.3 to 16
Based on 121 samples from 17 cities. This table contains only those compounds found in >10% of outfall samples.
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Nutrients
Nitrogen- and phosphorus-containing compounds are found in urban runoff primarily from highways.
Nitrates result both from vehicular exhaust on the road itself and adjacent soils from fertilization of
landscaped areas beside the roads (Hampson 1986; Schiffer 1989; German 1989). Nitrate (NO32") is very
soluble and does not sorb well to soil components during infiltration (Spalding and Kitchen 1988). Table 2
shows that the highest concentrations of nitrogen-containing compounds, measured both as total Kjeldahl
nitrogen (TKN), and nitrite plus nitrate (NO2 + NO3), found in urban runoff in the NURP study were from
residential areas. This most likely results from regular fertilization and watering of residential lawns.
Highway runoff also contains phosphorus from motor oils, fertilizers, bird droppings, and animal remains
(Hampson 1986; Schiffer 1989; German 1989). Phosphorus tends to sorb to soil components during
infiltration, thus preventing phosphorus from reaching the groundwater (Crites 1985). However, as the
sorption sites fill, i.e., the cation exchange capacity of the soil is exceeded, and phosphorus removal
decreases (White and Dornbush 1988).
Organics and Pesticides
Nationwide testing during NURP did not indicate any significant regional differences in the toxicants
detected, or in their concentrations (EPA 1983). However, land use (especially residential versus
industrial areas) has been found to be a significant factor in toxicant concentrations and yields.
Concentrations of many urban runoff toxicants have exceeded the EPA water quality criteria for human
health protection by large amounts.
Pesticides are used in urban areas for weed and insect control along roadsides, in parks, on golf courses,
and on private lawns. Pesticides (e.g., a-BHC, y-BHC, chlordane, and a-Endosulfan) are mostly found in
dry-weather flows from residential areas (Pitt and McLean 1986), and have been related in some
locations to the amount of impervious cover and to the distance the runoff must travel before infiltration
(Lager 1977; Pruitt, et a\. 1985; Butler 1987; German 1989; Domagalski and Dubrovsky 1992; Wilson, et
a/. 1990). Pesticides reach groundwater when their residence time in soils is less than the time required to
filter them or biologically or chemically convert them (Jury, et al. 1983).
The appearance of organics in groundwater, like elevated concentrations of nitrates (NO/"), has been
used as an indicator of groundwater contamination in heavily industrial areas (Lloyd, et al. 1988). Most
organics are either removed or reduced in concentration during percolation through the soil. Groundwater
contamination occurs most readily in areas with pervious soils, such as sand and gravel, and where the
distance to the aquifer is small (Troutman, era/. 1984). Although organics are also commonly found in
stormwater runoff from residential and commercial areas, runoff from industrial areas has been shown to
contain higher concentrations of certain organics, such as pentachlorophenol and bis(2-ethylhexyl)
phthalate, and some of the polycyclic aromatic hydrocarbons (PAHs) (chrysene, fluoranthene,
phenanthrene, and pyrene) (Pitt and McLean 1986).
The concentrations of many of these toxic pollutants exceeded the U.S. EPA water quality criteria for
human health protection by large amounts. As an example, typical standards for PAHs in surface waters
used as drinking water supplies are 0.0028 |ig/L (EPA 1986). As shown in Table 4, urban runoff
concentrations of chrysene (0.6 to 10 (ig/L), fluoranthene (0.3 to 21 jig/L), phenanthrene (0.3 to 10 jig/L),
and pyrene (0.3 to 16 ng/L) (four of the most common PAHs found in urban runoff) were reported to be
from 100 to as much as several thousand times greater than this criteria.
Pathogenic Microorganisms
Most bacterial characterization of urban runoff has focused on fecal coliforms, mainly because of their
historical use in water quality standards. However, many researchers have concluded that, for many
reasons, the fecal coliform test is not a reliable test for accurately assessing the pathogenicity of
recreational waters receiving urban runoff from storm sewers with no known source of contamination.
Pathogenic bacteria routinely have been found in urban runoff at many different locations (Pitt 1983).
-------
Table 4. Toxic organic source area observations (Source: Pitt, et al. 1995)
Toxicant
Benzo(a) anthracene
Benzo(b) fluoranthene
Benzo(k) fluoranthene
Benzo(a) pyrene
Fluoranthene
Naphthalene
Phenanthrene
Pyrene
Chlordane
Butyl benzyl phthalate
Bis(2-chloroethyl) ether
Bis (2-chloro-isopropyl) ether
1 ,3-Dichlorobenzene
Maximum
(H9/L)
60
226
221
300
128
296
69 .
102
2.2
128
204
217
120
Detection
Frequency (%)
12
17
17
17
23
13
10
19
13
12
14
14
23
Significant sources
Gasoline, wood preservative
Gasoline, motor oils
Gasoline, bitumen, oils
Asphalt, gasoline, oils
Oils, gasoline, wood preservative
Coal tar, gasoline, insecticides
Oils, gasoline, coal tar
Oils, gasoline, bitumen, coal tar, wood preservative
Insecticide
Plasticizer
Fumigant, solvents, insecticides, paints, lacquers,
varnishes
Pesticides
Pesticides
Historically, fecal coliform limits of less than 200 organisms/100 ml_ have been recommended because
the detection frequency for Salmonella has been found to increase sharply in waters receiving sanitary
sewer discharges when the fecal coliform number exceeds this standard. The occurrence of Salmonella
in urban runoff is generally low, with reported densities ranging between less than one to ten
organisms/100 ml_ when it is detected;, however, numerous urban runoff studies have not detected any
Salmonella. The occurrence of Salmonella in urban runoff at these concentrations generally is not ,
considered to be a health hazard because the required infective dose is greater than these
concentrations. Salmonella observations have not been found to correlate well with fecal coliform
observations, illustrating the poor quality of the fecal coliform test for assessing pathogenicity of the runoff
(Pitt 1983).
Urban runoff has also been found to contain other pathogens whose required infective dose is much
smaller than that of Salmonella or whose mode-of-entry'is not ingestion. These pathogens include, but
are not limited to, Pseudomonas aeruginosa, Staphyloccus aureous, Escheria coll, Shigella, or
enteroviruses. Shigella species causing bacillary dysentery are one of the primary human-enteric-
disease-producing bacteria present in water. Pseudomonas is reported to be the most abundant
pathogenic bacteria organism in urban runoff and streams, with several thousand P. aeruginosa
organisms per 100 mL being common (Olivieri, et al. 1977). Relatively small populations of P. aeruginosa
are reported to be capable of causing water-contact health problems ("swimmers ear" and skin
infections), and P. aeruginosa is resistant to antibiotics. The results of several epidemiologic studies on
the health effects of pathogens in urban runoff have been referenced in Field, et al. (1993). One recent
cohort study of beachgoers in Santa Monica found that swimmers near (0 - 45 m) a stormwater outfall
showed an increased risk of fever, chills, ear discharge, vomiting, gastrointestinal illness, and respiratory
disease (Haile, et al. 1996). Pathogenic E. co//can also be commonly found in urban runoff (Pitt 1983).
Viruses also are potentially harmful pathogens in urban runoff. Very small viral concentrations are
capable of producing infections or diseases, especially when compared to the large numbers of bacterial
organisms required for infection. Viruses are usually detected, but at low levels, in urban receiving waters
and stormwater (Pitt 1983).
Infiltration will increase bacterial and viral penetration into the soil profile. Like the organics, the greatest
chance for contamination occurs when the distance to the groundwater is small (Boggess 1975). Most,
but not all, pathogens are usually filtered out or inactivated during percolation through the soil (Gerba and
Haas 1988). However, should these pathogens reach the groundwater, they may persist from several
hours to several years, depending on the environmental conditions and on the pathogenic species
(Goldschmid 1974; Crites 1985; Ku and Simmons T986; Wellings 1988; Jansons, et al. 1989; Tim and
Mostaghim 1991).
-------
Metals
The heavy metals of most concern in urban .runoff are lead, zinc, copper, nickel, and chromium. Most of
these heavy metals have very low solubilities at the typical pH of receiving waters. They are either
removed by sediment adsorption or are organically complexed with other particulates (Hampson 1986)
and are easily removed during filtration. Metals in urban runoff originate both at industrial sites and on
highways, etc., as part of the exhaust and other residue left by vehicular use (Lloyd, et al. 1988). Metals
seem to be more prevalent in stormwater runoff from industrial areas, although they are also commonly
found in runoff from residential and commercial areas. High concentrations of many of the heavy metals
found in industrial area runoff were found during both dry and wet weather conditions (Pitt and McLean
1986). Table 5 lists the maximum concentration and the maximum mean concentration (highest average
concentration) of several heavy metals in urban runoff, as well as the land use of the area draining to the
sampling location (e.g., roof areas, parking areas, storage areas, street runoff, loading docks, vehicle
service areas, landscaped areas, urban creeks and detention ponds).
Table 5. Heavy metal source area concentrations (Source: Pitt, et al. 1995)
Toxicants
Cadmium
Maximum*
Maximum mean*
Chromium
Maximum*
Maximum mean'
Copper
Maximum*
Maximum mean*
Lead
Maximum*
Maximum mean*
Nickel
Maximum*
Maximum mean*
Zinc
Maximum"
Maximum mean*
Concentration (ng/L)
220
37
710
85
1830
290
330
105
170
87
13100
1730
Source area
Street runoff
Street runoff
Urban receiving water
Roof runoff
Urban receiving water
Storage area runoff
Storage area runoff
Storage area runoff
Parking area runoff
Landscaped area runoff
Roof runoff
Roof runoff
a Maximum concentration detected of all land uses
b Maximum mean is the highest of the mean values reported for each land use
Solids
Suspended solids are of concern in runoff because of their ability to clog infiltration areas (Crites 1985)
and treatment devices that use filtration. During percolation, the suspended and colloidal particles that
were not stopped at the surface travel downward until they are trapped by pores of sufficiently small
diameter. Fine to medium textured soils remove essentially all of the suspended solids by straining, while
coarse textured soils allow deeper penetration of these particles (Bouwer 1985; Treweek 1985). If the
ground water table is close to the surface and the soil does not provide adequate filtration, the suspended
particles will enter the aquifer and increase the turbidity and pollutant content of the groundwater.
Dissolved solids are in urban runoff due to the use of salt to de-ice roads in the winter and due to fertilizer
and pesticide salts from the use of those items on residential lawns, parks, golf courses, and roadsides
(Merkel, et al. 1988). Most salts are not removed during percolation through the soil or through a filter
media. In fact, the dissolved solids concentration in groundwater tends to increase due to the leaching of
salts out of the soils (Nightingale and Bianchi 1977). In general, once contamination with salts begins, the
rapid movement of salts occurs (moving as fast as the groundwater) and the concentration does not
decrease until the source is removed (Higgins 1984).
Urban Snowmelt Water Quality
For many years, emphasis was placed on the study and control of stormwater runoff pollution while other
-------
urban runoff sources, such as snowmelt, received little attention. However, a large percentage of the
annual runoff in northern climates comes from snowmelt, and in urban areas with seasonal snow cover,
snowmelt runoff may contribute significantly to the pollution of streams, lakes and rivers.
The limited studies that are available on snowmelt runoff have shown that the median concentrations of
pollutants in snowmelt are not strikingly different from the NURP average concentrations, except for
chloride, some solids, and bacteria concentrations. The few studies that have examined both cold
weather and warm weather runoff at the same urban outfall have demonstrated that snowmelt runoff
contains approximately the same concentration of pollutants as rain runoff, with the exception of higher
dissolved solids concentrations, as chlorides, in the snowmelt due to road salting. In addition,
phosphorous concentrations appear to be consistently lower in snowmelt than in urban rainfall runoff.
Results from several investigations that examined both warm and cold weather runoff are presented in
Table 6.
Bacteria data are not shown in Table 6, but they have been shown to be significantly lower in snowmelt
compared to warm weather rainfall runoff. Pitt and McLean (1986) found that fecal coliforms, fecal
streptococci, and Pseudomonas aeruginosa populations were significantly lower (by about ten fold) in
cold weather runoff compared to warm weather runoff: The Municipality of Anchorage has been studying
the bacteriological quality of its surface water resources over several years and also has found that winter
coliform measurements are almost exclusively lower than in warm weather runoff (Jokela 1990).
When it rains on a snowpack, heavy pollutant loads can be produced because both soluble and
particulate pollutants are flushed simultaneously from the snowpack and from deposited sediment on the
urban surfaces such as roads, parking lots, roofs, and saturated soil surfaces. The intensity of runoff from
a rain-on-snow event is usually much greater than during a summer thunderstorm because the ground is
saturated or frozen (minimal infiltration), and the rapidly melting snowpack also provides added runoff
volume (Oberts 1994). During monitoring in Toronto, Pitt and McLean (1986) found that rainfall on an
existing snowpack contributed over 80% of the total cold weather runoff volume.
Much of the high dissolved solids concentrations in snowmelt can be attributed to high chloride levels.
Year-round monitoring of pollutants has been conducted at the Monroe Street detention pond in Madison,
Wl, from 1986 to 1988 (House, etal. 1993). Chloride levels were found to decrease dramatically between
February and April. February runoff samples typically contained 1,000 to 3,000 mg/L chloride, but
decreased to less than 100 mg/L by the end of April. Snowmelt chloride concentrations during the next
winter rose again to over 1,000 mg/L.
Pollutant Concentrations in Snowmelt Sheetflows
Pitt and McLean (1986), during analysis of snowmelt sheetflows from residential and urban catchments in
Toronto, found that, in general, source areas exhibit similar water quality patterns during both rain and
snowmelt events. For example, the highest concentrations of lead and zinc in both snowmelt and rainfall
runoff were found in samples collected from paved areas and roads.
Fecal coliforms and suspended solids, however, showed significant differences between snowmelt and
rainfall runoff. Fecal coliform counts were significantly higher on sidewalks and on, or near, roads during
snowmelt periods compared to warm weather periods, even though the outfall fecal coliform counts
during the winter were much less than during warm weather. It is likely that dogs, and hence their feces,
stayed in areas that were generally free of snow. In warm weather, dogs would be less likely to be
restricted to these areas. Cold weather sheetflow median suspended solids concentrations in grass and
open areas (80 mg/L) were much less than the concentrations observed during warm weather runoff (250
mg/L). Total solids in snowmelt sheetflows in grass or bare open areas also were reduced dramatically
compared to warm weather runoff, probably because snowmelt has significantly less erosion energy than
rain. Grass and open areas generally are located relatively far from the drainage system and particles
from these areas are not easily transported long distances during periods of low energy. In contrast to the
grass and open areas, in road-sheetflow samples, total solids concentrations were greater during
-------
snowmelt periods, likely due to the large amount of road sanding debris and high chlorides near roads
that was relatively easy to transport in the gutter and drain systems.
Roadways generally contributed the most pollutants (yields and concentrations) to snowmelt runoff. Pitt
and McLean (1986) analyzed snow samples along a snowpack transect perpendicular to a road. These
data showed that the pollutant levels dropped dramatically at greater distances from the roadway. At
distances greater than about 3 to 5 meters from the edge of the'roadway, the snowpack pollutant
concentrations were relatively constant.
Snowmelt Quality Summary
The following conclusions were obtained after reviewing numerous studies that have investigated urban
snowmelt quality:
• Urban snowmelt runoff quality is similar in nature to stormwater runoff quality from the same source
area, except for dissolved solids and chlorides (much higher), and bacteria (much lower).
• The high dissolved solids concentrations in snowmelt result from the high chloride quantities used in
road salting.
• Atmospheric scavenging of air pollutants by snowflakes is the source of only a small fraction of the
snowmelt pollutants.
• Most of the contamination of snow occurs after it is on the ground. Snow becomes polluted while it
accumulates for long periods in snowpacks. Snowmelt runoff picks up few pollutants as it flows over
the various urban surfaces. However, rainfall on an existing snowpack causes most of the snowpack-
related discharges.
• Roads, parking lots and storage areas are important pollutant sources in all land uses during
snowmelt periods. In residential areas, yards and open areas are also major sources of nutrients.
-------
[This page intentionally left blank]
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Filterable (Dissolved) Fraction of Stormwater Pollutants
Table 7 summarizes the filterable (dissolved) fraction of toxicants found in stormwater runoff sheet flows
from many urban areas (Pitt, et al. 1995). Pollutants that occur mostly in a filterable form have a greater
potential of affecting the groundwater and are more difficult to control using conventional stormwater
control practices, sedimentation and sand filtration. Fortunately, most of the toxic organics and metals are
associated with the non-filterable fraction (suspended solids) of the runoff. However, probable exceptions
to this rule include zinc, fluoranthene, pyrene, and 1,3-dichlorobenzene. In general, dry weather flows in
storm drainage systems tend to have much higher concentrations of the toxicants in the filterable fraction.
Table 7. Reported filterable (dissolved) fractions of stormwater toxicants (Source: Pitt, ef al. 1995)
Constituent
Cadmium
Chromium
Copper
Iron
Lead
Nickel
Zinc
Benzo (a) anthracene
Fluoranthene
Naphthalene
Phenanthrene
Pyrene
Chlordane
Butyl benzyl phthalate
Bis (2-chloroethyl) ether
Bis (2-chlrorisopropyl) ether
1 ,3-dichlorobenzene
Filterable Fraction (%)
20 to 50
<10
<20
Generally < 20, but can be higher
<20
Generally < 20, but can be higher
>50
None found in filtered fraction
65-
25
None found in filtered fraction
95
None found in filtered fraction
Irregular
Irregular
None found in filtered fraction
75
Sources of Stormwater Pollutants
Harmful constituents in stormwater may originate in a variety of sources. High bacterial populations have
been found in sidewalk, road, and some bare ground sheetflow samples collected from locations where
dogs would most likely be "walked." Tables 4 and 5 summarize toxicant concentrations and likely sources
or locations having some of the highest concentrations detected (Pitt, et al. 1995). The detection
frequencies for the heavy metals are all close to 100 percent for all source areas, while the detection
frequencies for the organics shown ranged from about 10 to 25 percent. Vehicle service areas had the
greatest abundance of observed organics, with landscaped areas having many of the observed organics.
Residential source areas can contribute a significant variety of toxic metals and organics to the runoff, as
is shown in Table 8. However, because the contribution of any single residence is generally small and
typically does not have the variety of chemicals listed in Table 8, attempting to treat the runoff from
residential source areas on a residence-by-residence basis is not feasible.
One reason that many of the chemicals listed in Table 8 and in prior tables do not vary much between the
land uses is that a major contributor to baseline pollution in all urban runoff is atmospheric deposition of
airborne pollutants. Airborne pollutants land indiscriminately in a watershed and where they land is
determined by the wind's dispersion ability and the pollutant's nature at the time of discharge into the
atmosphere. Thus, the runoff loading from a watershed is a combination of the atmospheric deposition
baseline across the watershed (independent of land use) and the additional pollutant release from
individual locations in the watershed. It is these additional pollutant loadings that are related to land use
and are of concern.
Based upon a review of the data collected during the NURP program and by other stormwater
researchers, the control of small critical area contributions to urban runoff ('hotspots') may be the more
cost-effective approach for treatment/reduction of stormwater toxicants. The general features of the
critical source areas appear to be large paved areas, heavy vehicular traffic or areas with many vehicular
starts, and the outdoor use and/or storage of problem pollutants. Using these general guidelines, the
11
-------
problem point source areas identified for this work are industrial manufacturing facilities, service stations,
vehicle maintenance facilities, and some other commercial developments. Residential runoff is relatively
innocuous and is well below the national average concentration in runoff for most hydrocarbons, metals
and priority pollutants, although it is a major contributor of several conventional stormwater pollutants
including solids/sediment, total phosphorus, and bacteria. Residential runoff usually is not a problem in a
watershed because residential areas contribute smaller unit area volumes of runoff and because the
runoff concentration is relatively low.
Table 8. Urban runoff hazardous and toxic substances* (Sources: Galvin and Moore 1982; EPA 1983; Pitt and
McLean 1986)
Residential Areas
Bfs(2-Ethvlene)phthalate
Phenol
Butylbenzvl phthalate
Di-N-butyl phthalate
Benzene
BHC
Chlordane
DteWrfn
Endosuifan Sulfate
Endrin
Isophorone
Methoxychlor
Pentachlorophenol
Aluminum
Copper
Lead
Zinc
Cadmium
Other Heavy Metals
Industrial Areas
1 ,2-Dichloroethene
Methylene Chloride
Tetrachloroethylene
Butylbenzylphthalate
Di-N-butvl phthalate
Phenanthrene
Pyrene
Benzene
Chloroform
Ethylbenzene
n-Nitrosodimethylamine
Toluene
PCB-1254
PCB-1260
Pentachlorophenol
Phenol
Aluminum
Chromium
Lead
Other Heavy Metals
Substances found in >10% of stormwater analyzed
Stormwater Runoff Treatment Media
Most stormwater treatment devices currently in use or in development use sedimentation as their primary
pollutant removal mechanism since most of the pollutants in runoff are associated with the particulates.
Filtration may also be used as a second step because the contaminated particulates are strained out as
the water passes through the filter bed and either are trapped on the surface of the filter or among the
media's pores. Filtration is very effective, as it can achieve 90% removal of particles between 6 and 41
Urn. However, filtration/straining alone cannot remove soluble pollutants (Pitt, et al. 1995; Claytor and
Schueler 1996). Several comparisons have been done between filtration and other devices for stormwater
runoff treatment. The first comparison is to look at the feasibility of each type of treatment device. The
results are given in Table 9. The comparison of pollutant removal capabilities is given in Table 10.
Table 9. Stormwater treatment device characteristics (Source
Claytor and Schueler 1996)
Criterion
Soils
Drainage area
Head
Space
Cost/Acre"
Water Table
Cleanout
Life
Ponds
Most
10 Acres min.
0.9-1 .8m
2-3% Site
Low
No Restrictions
2-10 yrs.
20-50 yrs.
Wetlands
Most
1 0 Acre min.
0.3-1 .8m
3-5% Site
Moderate
No Restrictions
2-5 yrs.
20-50 yrs.
Infiltration
Soil-dependent
2-5 Acre max.
0.6-1 .2m
2-3% Site
High
1 .2 m below
1-2 yrs.
1 -5 yrs.
Filters
All
2-5 Acre max.
0.3-2.4 m
2-7% Site
Mod-Hiqh
0.6 m below
1-3 yrs.
5-20 yrs. (estimated)
No dollar figures given by Claytor and Schueler
12
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Table 10. Runoff treatment pollutant removal capabilities (Source: Claytorand Schueler1996)
Pollutant
Sediment
Phosphorus
Nitrogen
Soluble Nutrients
Bacteria
Hydrocarbons
Trace Metals
Ponds
Excellent
High
Fair
High
Low-High
High
Fair
Wetlands
Excellent
High
Fair
Fair
Unknown
High
Fair-Excellent
Infiltration
Excellent
Excellent
High
High
unknown
unknown
High
Filters'
Excellent
Fair-High
Fair
Low
Low-High
Excellent
Fair-Excellent
Low. 0-25% removal Fair. 26-50% removal High: 51-75% removal Excellent 76% -t- removal
a Includes both organic and sand filters. Sand filter removal efficiency at lower end of range for phosphorus and trace
metals. Organic filters have higher removal efficiencies for many trace metals and bacteria, although some organic filter media will
leach nutrients. See detailed descriptions of each media in literature review.
Filtration can be defined as an interaction between a suspension and a filtering material (Ives 1990).
Pollutants are removed from the solution when they become attached to the media or to previously
captured particles. In general, the three key properties of a filter are surface area, depth and profile. Filter
performance is measured by effluent water quality (traditionally, turbidity and suspended solids
concentration, as well as particle counts and dissolved organic carbon concentration [DOC]), water
production (unit filter run volume), and head-loss development (rate and time to back wash), all of which
change overtime (Clark, etal. 1992; Tobiason, etal. 1993).
Surface area loading is usually given as the percentage of the total impervious area draining to the filter,
compared to the filter surface area. The filters examined during this research would require about 1% of
the impervious drainage area. The surface area required for any filter depends upon the media type and
the rainfall patterns for the area. The depth of the media is also important with stormwater filter depths
usually ranging between eighteen inches and four feet. Shallow bed depths are typically used for both
hydraulic and cost reasons because less filtering time and less media are required in a shallow bed.
However, the tradeoff for shallow filter depth is usually effluent quality, i.e., the shallower the filter, the
less removal that is likely to occur. In general, filtering systems should be sized using the volume of runoff
to be filtered, and filtering media selected based upon the pollutants of interest.
The performance of filters that are also adsorbers or ion-exchangers is measured by the change in
concentration of the constituents of interest as a result of filtration. Filtration performance depends on the
source water quality (types and concentration of natural organic matter and suspended particles), any
required chemical additions and mixing processes, and physical characteristics of the media (type, size
distribution, depth, and hydraulic loading rate) (Tobiason, etal. 1993). Although not likely to be significant
for most stormwater filters, two fluid properties that can affect filtration are viscosity and density. Density
and viscosity are both temperature dependent, and density will also depend upon the concentration of
dissolved solids in the water (Clark 1990). In stormwater runoff treatment, viscosity variations in the runoff
between areas is insignificant because the water would be either as viscous as ice or as non-viscous as
steam before the viscosity change would affect the filter's performance. Density changes may have a
larger effect on filtration of runoff because it is also dependent upon the dissolved solids concentration.
This effect, however, is only likely to be noticeable for filters receiving snowmelt runoff. In general, the
biggest control on a filter's overall performance is the concentration of previously deposited particles
(Tobiason, et al. 1993).
Properties of the media that can affect filtration performance include straining ability, adsorption/ion-
exchange ability, available microbial action, and plant resistance and uptake. These last two properties
are usually only important in stormwater filters that have a steady water supply and a thriving, but well-
maintained, plant cover. For other filters, only the first two properties are of interest in filtration design.
The chemical properties of media that are good ion-exchange or adsorption agents include a high organic
content or clay, a high cation exchange capacity (CEC), and a neutral to alkaline pH. Pure sand has
minimal adsorption capacity; however, once the filter ages and a biofilm covers the sand grains, the sand
filter is capable of excellent adsorption when the pH conditions are in the correct range. This pH
dependence is also present in organic media.
13
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Microbial action is very important in many filtration processes. It used to be believed that stormwater
filters dried out between storms when the interevent dry period was several days and that this drying of
the media would prevent the formation of an effective microbial colony. Research has shown, however,
that the media (especially the organic media) do not dry out between storms, and a microbial colony is
established in areas of the filter where there is a sufficient organic carbon source. Two of the more
important microbial processes in filtration are nitrification and de'nitrification. Nitrification converts organic
nitrogen to ammonia and the ammonia to nitrite followed by nitrate. Denitrification converts the nitrate to
nitrogen gas, which is released to the atmosphere. Research on stormwater filters currently in use
indicates that significant nitrification is occurring in the filters, and the concentration of nitrate in the
effluent is greater than it was in the influent. Denitrification pockets have been located in some stormwater
filters; however, denitrification does not occur to a sufficient degree. Because of the concern over
nutrients (e.g., nitrates) entering surface waters, some new filters are being constructed to provide a
denitrification zone. The ability to denitrify to an appreciable extent requires that a filter section be
anaerobic. This is usually done by providing a saturated zone at the bottom of the filter, where several
inches of gravel remain submerged, even when the rest of the filter dries out. In order to keep the filter
working appropriately (most other beneficial microbial action requires an aerobic environment), the
submerged area should be separated from the rest of the filter by several inches of dry gravel (Claytor
and Schueler 1996).
The media described below are the media of interest for this research. These media have been selected
because of their prior use in either stormwater or wastewater treatment devices, or both. A comparison of
the pollutant removal pathways for different media is in Table 11. The only difference between sand filters
and other media is the ability of the organic media to act as an ion-exchange resin. Both sand and
organic filters currently in use have a pretreatment area that is a sedimentation chamber and that slows
the runoff velocity. Both media strain out particles to the size limit imposed by the pores of the media.
Sand can adsorb pollutants once the filter is aged, i.e., when a microbial biofilm has formed on the
surface. In order to determine the appropriate filter media, the properties of the individual media must be
compared, as they are in Table 12.
Table 11. Filtration media pollutant removal pathways (Source: Claytor and Schueler 1996)
Removal Pathway
Sedimentation
Straining
Adsorption
Microbial Action
Plant Uptake
Infiltration
Dissolved Solids Leaching?
Nitrification/ Denitrification
Sand Filters
In pretreatment ceil
In media
By organics on filter surface
On filter surface
None, unless cover crop
None, unless open system
Yes
Nitrif.: Yes Denitrif.: No
Organic Filters
In pretreatment cell
In media
Peat or compost media
On filter surface
None, unless cover crop
None, unless open system
Yes
Nitrif.: Yes Denitrif.: No
Table 12. Physical/chemical properties of filter media (Source: Clavtor and Schueler 1996)
Property
Hydraulic Conductivity (cm/hr)
Water Holding Capacity (cm/cm)
Bulk Density (g/cm)
pH
Organic Matter (%)
Cation-Exchange Capacity
Total P (%)
Total N (%)
Filtration Efficiency after 0.45 m (%)
Sand
3.3
0.14
2.65
N/A
<1
1-3
0.0
0.0
93
Compost
unknown
unknown
1-2
7.8
30-70
66
<0.1
<1.0
16
Peat
0.025-140
0.01-0.2
<0. 1-0.3
3.6-6.0
80-98
183-265
<0.1
<2.5
47
A review of available literature on the filtration media selected for this project (sand, activated carbon,
peat moss, compost, zeolite, Enretech, agrofiber, and filter fabrics) is given in Chapter 2. The literature
review focuses on the ability of these various media to remove specific compounds from either water or
14
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from a mixed liquid. For those media that have been used in stormwater filters, a review of their
effectiveness is also given.
Chapter 3 describes the overall design of the project as well as the procedures followed during each
phase of this research:
• Initial Evaluation for the Sand Column
• Effects of Sediment Accumulation on Filter Flow Rate
• Effects of pH and Ionic Strength on Pollutant Removal
• Long-Term Filtration Performance
Included in Chapter 3 are discussion of the laboratory procedures used to analyze the samples as well as
the statistical tools used to process the data.
Chapter 4 presents the results of the testing and includes the statistical summaries for each of the
parameters investigated during each phase of this project. Table 76 at the end of Chapter 4 summarizes
the statistically significant average removal percentages for each media.
Chapter 5 presents the conclusions of this research and includes a brief summary of each medium.
These summaries detail the effects of pH and ionic strength on a medium's removal ability as well as a
brief review of the medium's performance during long-term testing. At the end of this chapter are three
example filter designs. They are provided in order to give the user the opportunity to see how the
information in this report would be used in a practical application.
Future Research
The work presented here is the first part of an ongoing effort to investigate the ability of filtration media to
treat stormwater runoff. In order to develop effective design criteria for stormwater filters, additional work
is required to clarify several issues, including for example:
• Quantification of the effects of pH, ionic strength, and influent concentration on removal ability and
media capacity for a pollutant (chemical breakthrough testing);
• Quantification of the effect that filter construction, as it relates to contact time, has on removal ability
and media capacity;
• Quantification of scale-up factors that will allow a designer to take the results of bench-scale tests on
a filter media and use them in the design of a'full-scale filter installation.
Laboratory set-ups would be appropriate for the first two items above. For each media during each test,
filtration will continue until chemical breakthrough occurs for each pollutant. Once these tests are
complete, several media will be chosen to investigate contact time effects. Contact time will be controlled
either by adjusting the sand content of the mixed media section or by restricting the effluent port. Last,
pilot-scale filters will be built in 220 L (55 gallon) Nalgene drums. Presettled influent test water will be
obtained from detention ponds (as compared to using spiked tap water during some of the bench-scale
work) in the Birmingham area and laboratory analyses will be as given in Table 17 (Chapter 3).
15
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Chapter 2
Review of Media Filtration for Stormwater Quality Control
Sand
The use of sand filtration is common for drinking water and sanitary wastewater treatment/effluent
polishing. Water supply treatment plants have successfully used sand filtration for many years.
Wastewater treatment plants often use sand filtration to polish their effluent before release, especially as
the regulatory requirements for the discharge of suspended solids becomes more stringent. Sand filters
are also popular as stormwater runoff treatment, especially in urban areas where the filters must be
retrofitted and property values decree that the filters be located underground (Claytor and Schueler 1996).
Physical Characteristics
Slow sand filters are characterized by slow filtration rates, an extremely narrow range of sand particle
sizes, the lack of chemical pretreatment, relatively long filter runs between cleanings, and surface
scraping and sand removal instead of backwashing as a cleaning technique (Collins, etal. 1992).
Filtration rates are as much as fifty times slower than those of rapid sand filters; consequently, slow sand
filters require significantly more surface area in order to filter comparable volumes of water (Crittenden, ef •.
al. 1993). Slow sand filter media is characterized by certain parameters: size distribution, settling velocity,
porosity, grain integrity, shape, hardness (resistance to attrition), and the results of visual and microscopic
examinations (Ives 1990). Slow sand filters need to have a minimum vertical distance (or fall) of at least
0.6 m, but preferably 1.5 m, from inflow to outflow to drive the water by gravity through the entire filter
(Claytor and Schueler 1996).
Fine sand/silt filters remove particulates by direct straining on the surface of the filter media. The
combination of grain size and bed depth will determine the effectiveness of the filter. Naghavi and Malone
(1986) demonstrated that the combination of grain size (0.2 mm) and a shallow bed depth produced an
average fluorescence removal of approximately 97%, even with no chemical pretreatment. This
combination also had the highest initial filtration rate (226 m3 m'2 day'1) and a lower initial headless (7.3
cm). The effect of media size on filtering ability also was demonstrated by Tobiason, et al. (1993) in a 2.5
cm inner diameter (ID) acrylic column filled with 17 cm of 0.4 mm glass beads along with the test
suspensions that contained either one size or a mixture of 0.27, 1.3 and 10 urn diameter particles. The
use of smaller diameter media affected the rate of removal of larger particles and the rate of head-loss
development. Head-loss development was typically linear with time, and, for suspensions of mixed
particle sizes, it generally was the same as, or somewhat lower than, head loss for monodisperse
suspensions of the smaller-sized particle (Tobiason, etal. 1993). Head loss (or hydraulic resistance) is
determined by the filter's surface area, which depends on the size and number of grains, not the grains'
weight. In order to have the same head loss development pattern in a 'single-size' media filter, the new
filter would require a diameter equal to the d10 of the mixed-size media (Ives 1990). Head loss results from
increased fluid drag, pore constriction, and increased interstitial velocities caused by particle deposition.
Small particles cause more head loss because of their high surface area per unit volume (Tobiason, et al.
1993). Head loss is spread more evenly through the filter in larger particle diameter media. Therefore,
capturing a particle with larger diameter media results in less head loss than capturing it with smaller
media (Clark, etal. 1992).
Removal is different at the various depths of the filter, with the influent particle concentration being
reduced dramatically in the top section of the filter and smaller reductions occurring near the bottom of the
filter. This effect is most pronounced for filters with smaller sand sizes; therefore, removal efficiency in the
16
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larger media improves substantially compared to the smaller media at each successive depth of the filter.
Later in the filter run, large particles apparently are less effectively removed in the top section of the filter,
suggesting that small particles entered the filter and were captured by previously retained particles,
thereby forming a floe on the media surface. If the floes break off the surface, they may pass unhindered
through the filter media and be measured as larger particles. In addition, particles with surface chemistry
favorable for retention in the medium likely are captured in the top section of the filter while the particles
with unfavorable surface chemistry reach the lower section where they still are not removed from solution
(Clark, et at. 1992). Percent removal is a function of both sand depth and particle size; using coarse sand
and a deep bed is recommended by Farooq and AI-Yousef (1993) because this type bed will require less
cleaning than fine sand in a shallow bed filter.
Filtration velocity, to a lesser extent than media size, affects removal efficiency, bed depth use, and head
loss. Head loss is directly proportional to velocity in new filters, but for ripened filter beds, the direct
proportionality does not apply. Increased velocity pushes particles deeper into the filter bed prior to
capture, thus allowing more of the filter depth to be used in particle capture. This leads to reduced head
loss and, therefore, larger quantities of water can be treated before cleaning (Clark, et al. 1992). There is,
however, an upper limit on filtration velocity. At loading rates higher than 5 m/day of sanitary wastewater,
the sand filter clogs within a few days while for loadings less than 1 m/day, collected organic particles
decompose in the filter and free up pore space, and the run length on a volume-treated basis is
quadrupled (Fujii, et al. 1987).
For sand, as for other filter media, the shape of the curve of percent captured versus particle diameter
depends on the particle capture mechanism, the filter medium, the fluid being filtered, and the filtration
conditions (Shucosky 1987). Generally, dissolved oxygen concentrations and pH decrease in sand
filtration. Particulate chemical oxygen demand (COD), paniculate organic nitrogen, and particulate
phosphorus are removed during filtration, even before the filter is ripened. However, very little of the
soluble fraction of the above constituents is removed (Fujii, et al. 1987).
Using lateral viewing endoscopes, unexpected phenomena, such as tumbling grain motion and void
formation ('wormholes,' or pores larger than a sand particle's diameter), have been observed in traditional
sand filters, especially rapid filters or those using countercurrent filtration. These 'wormholes' start with
holes in the surface deposit and remain open despite the continuing flow of solids into them. Aggregates,
especially those of weakly-bound compounds, that enter the wormholes, even if they are larger than the
hole, may be deformed or disrupted by the hole, yet they do not completely stop flow through the hole.
This aggregate 'destruction' during filtration only occurs to an appreciable extent when substantial surface
deposits are present (Ives 1989). Preferential flow (macropore, fingering, orfunneled flow) also has been
observed in sand filters, as it has in many other filters and soils. During preferential flow, the fluid follows
the local wetting front in wormholes and bypasses the matrix pore space. Filtration efficiency for
preferential flow pathways is much smaller than it is for matrix pore flow because flow through preferential
pathways is more rapid and less time is available for straining and/or sorption (Steenhuis, et al. 1980).
General Removal Capabilities
Slow sand filters are extremely effective in removing suspended particles, and effluent turbidities are
consistently below 1.0 NTU. Bacteria, viruses and Giardia cysts are also removed with enhanced filtration
once a bacterial population is established on the filter. However, sand filters have only a limited ability to
remove organic material that are precursors to trihalomethane formation and the biodegradable fraction of
dissolved organic carbon (BDOC) (Collins, et al. 1992; Eighmy, et al. 1992; Farooq and AI-Yousef 1993).
Stratified sand filters have been shown to remove enteric viruses, along with total organic carbon (TOG)
from septic tank effluent at a loading rate of 0.061 m/day, even from sand filters that contained new sand,
i.e., had no bacterial biofilm ("schmutzdecke") and, therefore, no bacterial breakdown of pollutants (Gross
and Mitchell 1990). A sand filter with an effective grain size of 0.23 mm and a loading rate of 3.84 m/day
was shown to effectively remove biochemical oxygen demand (BOD) (86%), suspended solids (68%),
turbidity (88%), and total coliform bacteria (99%) from sanitary wastewater (Farooq and AI-Yousef 1993).
High algae removal can be accomplished using media with median sand size < 0.2 mm (Naghavi and
17
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Malone 1986). Sand filtration at a Superfund site showed suspended solids removal of about 50% for
waters that contained mostly colloidal-sized particles and 80% to 100% removal for waters whose solids
were larger. One unexpected result for the filtration was that solids breakthrough occurred much earlier
than expected, possibly because the filter was not in continuous operation (Dahab, et al. 1991). The
presence of wormholes was not investigated by Dahab, et al. (1991) although this is one potential
explanation for the early breakthrough.
Sand filtration, without modification of the sand by ripening or by adding a surface coating of an adsorber
such as manganese or ferric oxide, is not effective at removing dissolved constituents. Deethylatrazine
was consistently detected in the effluent of one sand filter (2 cm ID x 30 cm long filter) used to treat
natural groundwater spiked with 200 ng/L of atrazine (applied at 5 mL/min for 70 days; 23 m3 m"2 day"')
until the filter ripened, when it was no longer detected (Selim and Wang 1994). Sand filtration also does
not remove total suspended solids (TSS) from pulp and paper mill secondary effluent as effectively as it
does from municipal secondary effluent, likely because the nature and size of the solids are considerably
different (unimodal at 2 |im) from the nature and size of the organisms filtered from secondary wastewater
(bimodal at 4 and 85 (am). The pulp and paper mill effluent had mostly very small particles, a range where
the sand filter is not as effective (Biskner, et al. 1978).
Ripening of the Sand Filter
Ripening is the development of a bacterial biofilm, the 'schmutzdecke,' on the sand filter that improves the
removal ability of the filter. This increased efficiency occurs for all particle sizes initially, but eventually
only continues for small sizes with the removal efficiency decreasing and possibly becoming negative for
larger particles. Captured particles aid in the collection of subsequent particles by partially blocking and
restricting passage through the pores. Therefore, the rate of increase in particle removal efficiency
depends on the influent particle concentration. When more time elapses between collisions of particles on
the media surface and those in solution, the first collected particle may migrate to the bottom of the grain
and greatly reduce the opportunity for interaction with the next incoming particle. Thus, the removal
efficiency is greater and ripening is quicker when the influent concentration is greater (Clark, et al. 1992).
Submicron particles also improve the deposition of larger particles because they increase the apparent
surface roughness of the media and/or the large particle (Tobiason, et al. 1993). Ripening of the filter
creates rougher pore channels, which slows down the flow and provides more contact time between the
media and the pollutants in the water (Fujii, et al. 1987). In addition, larger particles may hinder the initial
deposition of the smaller particles because of unfavorable hydrodynamic interactions or differences in
destabilization (Tobiason, et al. 1993).
Sand filters have a more limited capacity for substrate growth and thus have a smaller microbial
population, as compared to organic media filters of the same size (Selim and Wang 1994). Even when
ripening is complete, head-loss development is approximately linear with time (or mass deposited)
(Tobiason, et al. 1993).
Adsorbent Coatings
Another technique for improving the removal efficiency of a sand filter is by adding an adsorbent coating,
usually an iron or manganese oxide, to the sand grains, thus providing adsorption sites for the ions in
solution. Potential sorption mechanisms include diffusion into the lattice of the minerals; adsorbing at sites
on the sand surface; adsorbing sites on hydrous iron and manganese oxides and hydroxides; and
complexing at sites on natural organic matter in the schmutzdecke. The iron oxide coating on sandy soil
has been found to bind metals of all sizes very strongly. Metal binding strength is relatively low in the
exchangeable fraction (the portion of the pollutant concentration that participates in ion-exchange rather
than in complexation or chemisorption) and increases in the non-exchangeable fraction because metals in
the non-exchangeable fraction likely are incorporated within the crystalline lattice or strongly sorbed to the
mineral surface. The non-exchangeable fraction, therefore, is 'permanently bound' to the sand under
normal operating conditions. The non-exchangeable fraction also contains the greatest concentration of
18
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sorbed metals, except zinc. The smallest sized media have the greatest mass concentration of metals.
Lead binds more strongly to the smaller particles while arsenic, copper, and zinc show similar affinities for
all size fractions. Metal sorption kinetics show the existence of both a fast reaction, where metals bind to
surface sites, and a slow reaction, where metals bind to interior sites. Reaction kinetics also affect the
availability of metals for sorption. Metals from the dissolution of the soluble compounds are available
more quickly for sorption while metals in precipitates or other covalently bonded compounds are not (Van
Benschoten, etal. 1994).
Manganese oxide coatings can remove manganese(ll) from solution with the rate of sorption being
positively correlated to the number of available surface adsorption sites. Chlorine in the manganese(ll)-
containing influent will oxidize the adsorbed manganese(ll) and, therefore, continually regenerate the
filter. Removal efficiency is a function of the surface MnOx(s) concentration, its oxidation state, and the
influent pH. Manganese(ll) sorption capacity is greater, and the reaction rate is faster when the influent
pH is raised (reducing H+ ion competition for sites). For a given pH, sorption capacity also is increased as
the surface MnOx(s) concentration is increased. Efficient manganese(ll) sorption was found even during
the winter when the sorption rates likely are significantly slower. Further research has shown that the
coatings do not affect the filter hydraulics either during a run or during cleaning, the clean-bed head loss
of the filter, or the effective size and density of the filter media (Knocke, et al. 1991).
Limitations
Slow sand filtration has the following limitations and concerns: (1) a limited acceptable range of influents
(usually less than two hundred milligrams per liter influent total suspended solids [TSS]); (2) a limited
ability to remove organic precursor materials because of a lack of sorption surfaces; and (3) extensive
filter downtimes and ripening periods (Collins, et al. 1992).
Cleaning and re-ripening a slow sand filter is difficult and time-consuming; however, several techniques
have been developed to "speed up" that process. Wet harrowing in West Hartford, CT, removed the
surface mat yet kept the biomass in the filter media down to the depth of harrowing (Eighmy, et al. 1992).
Nonwoven, synthetic fabrics have been placed on the sand surface. The fabric has a greater porosity and
specific area and is a more efficient filter for larger particles. The benefits of filter mats/fabrics placed on
top of the sand surface are longer run times and simpler cleaning that requires only the removal and
cleaning of the fabric. However, a filter cover does not improve the ability of a sand filter to treat raw
waters of varying quality, and no suitable cleaning method exists for the fabrics in large-scale installations
(Collins, et al. 1992).
Stormwater Runoff Treatment
Sand filtration for stormwater treatment began on a large scale in Austin, TX. The Austin sand filters are
used both for single sites and for drainage areas less than fifty acres. The filters are designed to hold and
treat the first one-half inch of runoff with very good pollutant removal ability.
According to the City of Austin design guidelines, the minimum sand depth should be eighteen inches.
These filters may have either gravel, a geotextile, or other fabric on top of the sand to prevent premature
clogging with large particles. For a filter built according to Austin's design guidelines, the assumed
pollutant removal efficiencies, which are based upon the preliminary results of the City's stormwater
monitoring program, are given in Table 13.
In Washington, D.C., sand filters are used both to improve water quality and to slow the runoff in order to
prevent large slug inputs to the combined sewer system (CSO). Water quality filters are designed to retain
and treat three-tenths to qne-half inch of runoff with the exact design based upon the amount of
impervious area in the watershed (Shaver 1994).
In Delaware, the sand filter is an acceptable method for achieving the 80% suspended solids reduction
requirement. These filters are intended for sites that have impervious areas that will drain directly to the
filter, such as fast-food restaurants and gas stations. In many areas, sand filters precede an infiltration
19
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device in order to prevent or postpone clogging of the infiltration device. Sand filters are also used on
sites where there is no space to retrofit other infiltration devices (Shaver 1994).
Table 13. Pollutant removal efficiencies for sand filters (Source: City of Austin 1988)
Pollutant
Fecal Cotiform Bacteria
Total Suspended Solids (TSS)
Total Nitrogen
Total Kheldajl Nitrogen
Nitrate - Nitrogen
Total Phosphorus
Biochemical Oxygen Demand (BOD)
Total Organic Carbon
Iron
Lead
Zinc
Removal Efficiency (%)
76
70
21
46
0
33
70
48
45
45
45
According to Delaware's guidelines, the sand filter can be expected to adequately remove particulates
(TSS removal efficiency 75 - 85 %) but not soluble compounds. Studies of a six-year old sand filter in
Maryland that was installed at the drain of a heavily-used parking lot showed that the filter is now
becoming clogged. Inspection of the sand below the filter surface has shown that oil, grease, and finer
sediments have migrated into the filter, but only to a depth of approximately two to three inches (Shaver
1994; Galli 1990).
The sand filter used in Delaware has a similar design to the Austin filters with an eighteen-inch sand
depth and a six-inch gravel underdrain. Each filter has a minimum of six to twelve inches of ponding
depth/storage head available on top of the filter. Monitoring of a Delaware sand filter which treats the
runoff from a 0.28 ha (0.7 acre) section of a parking lot near National Airport in Alexandria, VA, showed
that the filter had an average 72% removal of total phosphorus, >80% removal of total suspended solids
(influent concentration = 50 mg/L), and >90% removal of zinc (200-630 ng/L influent concentration). The
sand filter, which had an underdrain layer, continued to function during freezing weather. Anaerobic
conditions will develop in sand filters unless the bottom of the filter is exposed to air. Anaerobic conditions
enhance nitrate removal by denitrification but reduce total phosphorus removal because the iron
phosphates degrade and release phosphorus (Galli 1990).
Monitoring of a Delaware sand filter at the Alaska Marine Terminal in Seattle showed >80% removal of
total petroleum hydrocarbons (TPH) when influent concentrations were 1.2 mg/L. and >90% removal of
TPH when influent concentrations were 3.1 mg/L. Suspended solids and phosphorus removals were
similar to those noted at the National Airport in Alexandria, VA (Galli 1990).
Herrera Environmental Consultants (1991 and 1995) also have evaluated sand filters as a media for
stormwater treatment. Their results indicate that sand filters by themselves are the least effective at
removing both total phosphorus (0 to 28 percent removal) and soluble phosphorus (0 to 38 percent
removal). Iron sand and sand amended with other constituents, such as calcitic lime and hypnum peat,
were found to remove significantly more total phosphorus and soluble phosphorus than sand alone. The
sand/calcitic lime mixture removed between 29 and 79 percent of the total phosphorus and between 25
and 93 percent of the soluble reactive phosphorus. The sand/hypnum peat mixture removed between 31
and 94 percent of the total phosphorus and 36 to 99 percent of the soluble reactive phosphorus (Herrera
Environmental Consultants 1991). The addition of steel wool to the sand filter as an adsorbent showed
that it was also an effective sorbent media for total and soluble phosphorus removal. Phosphorus removal
occurs because the steel wool oxidizes in the presence of water and oxygen and the oxidized iron easily
reacts with the phosphate in solution (Herrera Environmental Consultants 1995).
Urbonas (1999) has broken the stormwater detention and filtration process down into the individual unit
processes that occur in a sand filter during suspended solids removal and has provided recommendations
20
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for using the information gathered during the unit process analysis to design new sand filter installations.
Hydraulic capacity, a function of the suspended solids loading, is the design variable. This approach of
Urbonas is novel in stormwater filter design because maintenance is addressed as a design variable in
the sizing calculations, i.e., the recurrence interval of maintenance is used in the calculation of the amount
of suspended solids removed per square foot of filter surface area.
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Activated Carbon
Activated carbon separation has long been used in the water treatment and chemical process industries
and in hazardous waste cleanup as an effective method for removing trace organics from a liquid.
Activated carbon is made first by charring materials such as almond, coconut and walnut hulls, other
woods or coal. The char particles are activated by exposing them to an oxidizing gas at high
temperatures. The activation process makes the particles porous which creates a large internal surface
area available for adsorption (Metcalf and Eddy 1991).
Organic Removal Capability
Activated carbon has been used for more than fifty years in drinking water treatment plants to remove
taste- and odor-causing compounds, along with most synthetic organic chemicals, pesticides, herbicides,
color, and trihalomethane precursors (Rael, etal. 1995). Disinfection by-products, including the
trihalomethane precursors, have also been removed from drinking water by granular activated carbon
(GAG) (Crittenden, etal. 1993; Abuzald and Nakhla 1994).
Slow GAG filters achieve excellent organic removals (> 90 percent), with the removal efficiency limited by
the depth of the filter. This dependence is due to 'slowness' of the transport kinetics and attachment
mechanisms inherent in activated carbon sorption. The problem with activated carbon is its exponential
head loss curve, i.e., increasing removal increases head loss development rates, and, therefore, the
filters must be cleaned more frequently (Collins, etal. 1992).
Anaerobic charcoal chip reactors, along with anaerobic sand packed reactors, can remove up to 80% of
the chemical oxygen demand (COD) at an organic loading rate of 7 kg COD/nf-d and 60% at 12 kg
COD/m3-d and were able to withstand a shock loading of over 22 kg COD/m3-d. However, efficiency
dropped when wastewaters contained a high concentration of SO/" and Na+. In general, the removal t
efficiency of COD is inversely related to loading rates, and no clogging was observed even after one year *
of operation (Chin 1989).
Granular activated carbon (GAC) is useful for treating wastewaters with inhibitory, yet adsorbable,
compounds that make conventional biological treatment difficult or impossible (Fox, etal. 1990). Activated
carbon can remove both dissolved and synthetic organic carbon (DOC and SOC, respectively)
compounds from solution. However, provided that adequate contact time exists in the treatment system,
equilibrium capacity of the carbon decreases with decreasing initial DOC or SOC concentration. The SOC
adsorption rate onto activated carbon decreases with decreasing initial SOC concentration due to
competition by natural organic matter. Equilibrium is achieved after three hours with an initial
concentration of 109 j.ig/L trichlorophenol, yet equilibrium takes twenty-four hours when the initial
concentration is 34 |ig/L trichlorophenol (Najm, etal. 1993). At steady state, activated carbon with a
growing microbial colony can remove approximately 40% of the initial DOC from solution by one or more
of three independent mechanisms: surface degradation, film degradation, and pore degradation (including
in micropores) (Koch, etal. 1991). In a test of two carbon types at a Superfund site (wood treatment
plant), both carbons had excellent total organic carbon (TOG) removal (minimum 80% removal after 64
bed volumes, influent 320 mg/L TOG). However, the same removal efficiency was not found for waters
with an exceptionally high influent TOG concentration (50% removal after 64 bed volumes, influent 900
mg/LTOC) (Dahab, etal. 1991) A growing microbial community also is not easily removed during
backwashing (Servais, etal. 1991).
Pore diffusion appears to control the intraparticle mass transfer rate for DOC with either or both the pore
and surface diffusion coefficients being linearly dependent on particle size and with the observed pore
diffusion coefficient decreasing over time. Possible reasons for this decrease include the following: (a)
the rapid initial diffusion is intraparticle, while the later, slower diffusion is micropore diffusion; (b) the
diffusion path length increases as the pores fill; or (c) the displacement of previous adsorbed DOC by
more strongly adsorbed DOC causes counter diffusion. Isotherm calculations for DOC sorption onto
22
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activated carbon showed that the percent adsorption after 15 days was nearly identical to that of 7 days.
Also, it was determined that for a desired effluent concentration of 1 mg/L DOC (eye, = 0.4), the optimum
empty bed contact time (EBCT) was between twenty and thirty minutes (Crittenden, et al. 1993).
Excellent removal of phenolic compounds from a groundwater spiked with 20 ng/L trichlorophenol (TCP)
has been shown for activated carbon. The maximum adsorption capacity is dependent on the influent
sorbate concentration, i.e., capacity and rate of adsorption decrease with decreasing influent
concentration (13 mg/L PAC dosage needed one hour contact to reach equilibrium [5 [.ig/L] while 4 mg/L
needed a 24 hour contact time). The adsorption efficiency for a floe-blanket reactor was found to be equal
to the adsorption efficiency for batch isotherm tests, indicating that a reactor or filter with sufficient contact
time can achieve the maximum removal efficiency for the solute of interest. The adsorption rate of TCP
onto activated carbon can be described by the homogeneous surface diffusion model (HSDM) in which an
adsorbate molecule first diffuses through the carbon particle's stagnant liquid film layer before
instantaneously adsorbing to the carbon's outer surface. The adsorbate then slowly diffuses along the
carbon pores' inner surfaces (Najm, et al. 1993).
However, the capacity of granular activated carbon (GAG) for phenolic compounds in deionized water is
decreased under anaerobic conditions. In the presence of oxygen, the TCP likely is converted to different,
unmonitored compounds in the effluent. This results in an erroneously high estimation of adsorptive
capacity (Adham, et al. 1991). Phenol and o-cresol undergo oxygen-induced polymerization reactions on
activated carbon that increase both the amount adsorbed and the strength of adsorption. The increases
are dependent on the dissolved oxygen (DO) concentration. Seventy percent of the adsorbed phenol was
recovered from Filtrasorb 400 activated carbon after adsorption under anoxic conditions while only 25%
was recovered after adsorption under aerobic conditions, demonstrating that the adsorption under aerobic
conditions led to stronger bonding between the phenol and the carbon. The molecular oxygen aids in the
formation of acidic surface oxides on the carbon, which enhances dimer and trimer formation on the
carbon surface. The polymerization also significantly increases the time required to reach equilibrium
because it is the rate-limiting step. Adsorption is then limited by intracrystalline diffusivity rather than
external mass transport resistance. For example, adsorption of phenol on Filtrasorb 400 activated carbon
took 48 hours to reach equilibrium under anoxic conditions while it took 14 days to reach equilibrium
under aerobic conditions. This increase in adsorption capacity in the presence of dissolved oxygen,
however, does not hold for aliphatic organic compounds (Abuzald and Nakhla 1994).
Chlorinated phenols are strongly adsorbed by activated carbon; however, biodegradation of these
compounds can also occur on the carbon. Anaerobic degradation of the highly chlorinated phenols, i.e.,
tetra- and pentachlorophenol, will produce various lower chlorinated phenols, i.e., tri-, di-, and
monochlorophenols. This biodegradation and adsorption of the chlorinated phenols will occur
simultaneously with pH significantly influencing the adsorption of compounds with acidic functional
groups. Batch equilibrium adsorption data for eight chlorinated phenols on Calgon Filtrasorb 400 activated
carbon in two concentration ranges at pH 7.0 and 30°C showed the adsorptive capacities increasing from
pentachlorophenol to the trichloroprienols and holding fairly constant from the trichlorophenols to the
monochlorophenols. The adsorptive capacity for the neutral molecules (monochlprophenols dominant) is
higher than that for the ionized forms (pentachlorophenols dominant). The chlorine's position on the
phenyl ring, however, has little influence on a chlorophenol's adsorption (Nelson and Yang 1995).
The good fit of the Langmuir isotherm to the adsorption data suggests that a fixed number of accessible
adsorption sites exists on the carbon for a given range of solute concentrations. A surface complexation
model has been proposed in which the carbon's functional groups can be divided into two types: acidic
(carboxyl, phenolic, quinonoid, and normal lactone) groups and basic (chromene and pyrone-like) groups.
The surface complexation model fits the adsorption data for 2,4,5-trichlorophenol, 2,4-dichiorophenol, and
4-chlorophenol for different pHs. Tests have shown only slight differences between isotherms for 2,4,5-
TCP between pH 4.15 and pH 5.22, but significant differences between the isotherms at higher pH (>
6.5). Solution pH less than the pKa (6.94 for TCP) does not significantly affect the adsorption capacity of
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the activated carbon, but when the pH is greater than the pKa, there is a linear decrease in adsorption
capacity with the increase in pH (Nelson and Yarig 1995).
Benzene in groundwater also can be adsorbed on activated carbon. However, this adsorption may be
retarded by one or more of the following reasons: fouling of the carbon by various components in
groundwater; differences in adsorption and mass transfer kinetics of the various components; adsorption
interference and competition by other compounds in groundwater, such as pesticides and herbicides; and
interference by chemicals that precipitate on the carbon. At a benzene concentration of 20 mg/L,
adsorption may be limited by film diffusion. However, at higher concentrations (50 mg/L), adsorption is not
limited by film diffusion because of the larger concentration gradient available, arid because pore diffusion
controls the rate of adsorption. Bacterial growth on the carbon surface may be either an advantage or a
disadvantage. This strictly depends on the microbial population available (Rael, et al. 1995).
It has been demonstrated at both a Superfund site and for an industrial wastewater that activated carbon
will remove more than one organic compound from a solution. The Superfund site water contained
various phenolic compounds (i.e., pentachlorophenol, 4-methyIphenol, and 2,4-dimethylphenol), pyrene,
fluoroanthene, and unidentified total organic carbon (TOG), and color-producing compounds that were
removed from solution by the carbon. However, competitive adsorption led to lesser adsorption efficiency
as compared to the efficiency for pure test compounds (Dahab, et al. 1991). Competitive adsorption also
reduced the capacity of carbon for the individual organics in the industrial wastewater, as compared to
their respective single compound isotherms. Capacity reduction can be correlated with the percent of the
total organic carbon (%TOC) in solution contributed by the target compound, i.e., the smaller the %TOC,
the larger the capacity reduction, because other compounds are available in sufficient concentration to
compete for many of the adsorption sites. Mass transport limitation also can significantly reduce a
compound's adsorption capacity, especially for large organic contaminants such as color agents (Ying, et
al. 1990).
Activated carbon also can remove pesticides from solution. Atrazine and two of its degradation products,
deethylatrazine and deisopropylatrazine, have been adsorbed from contaminated groundwater (200 jig/L
atrazine filtered at 5 mL/min for 70 days through a 2 cm ID x 30 cm long filter column) (Selim and Wang
1994). A sand filtration/carbon treatment system can reduce a diversity of organophosphate,
organochlorine, and pyrethroid pesticide residues down at least to their detection limit. The sand filtration
step removes the pesticides associated with particulate matter while the carbon adsorbs the
nonparticulate pesticides in the solution. Average removal efficiencies for the total treatment system were
79% for pyrethroids, 92% for organophosphates, and 96% for organochlorines (Moore, et al. 1985).
Activated carbon filters also can provide a good environment for microorganisms that may biodegrade
certain organic molecules. The biodegradation often will increase the apparent adsorptive capacity of the
carbon (Selim and Wang 1994).
Inorganic (Non-Metal) Removal Capability
Activated carbon fiber has been shown to remove iodine and iodide compounds from acetic acid in water,
methanol, and ethanol solutions. When compared to other conventional adsorbents (activated carbon,
silica gel, alumina, NaY zeolite, Ag ion-exchanged NaY zeolite, and Ag ion-exchanged Amberlyst XN
1010), the activated carbon fiber had the greatest adsorptive capacity for the iodine and iodide
compounds. Iodine removal was inversely related to iodine's solubility in the solution. The excellent
removal by the fiber can be explained by the unique structural characteristics of activated carbon fiber
which promote fast adsorption. Since the fiber contains only micropores with a pore diameter less than 2
nm while activated carbon has a broader pore size distribution, the adsorptive capacity is greater for the
fiber. This is because the major (stronger) adsorption sites are located only in the micropores with weaker
adsorption in the meso- and macropores. Iodine diffusion to the strong binding sites is the rate-limiting
step in activated carbon adsorption; this diffusion is eliminated in the fiber because the micropores are on
the surface (Yang, et al. 1993).
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Activated carbon also can reduce chlorite ions to chloride by having the oxychlorine-species react with the
radical sites, oxygen-containing functional groups, and metal ions on the activated carbon to form the
radical entities CIO2, Cl°, and CIO". These then form CI2O2, CI2O3, HOCI, etc. with chloride, chlorate ions,
and oxygen as final products. Increasing the initial chlorite concentration increases carbon's adsorption
capacity for other compounds because the chlorate-forming secondary reactions are favored which
increases the concentration of acidic surface functional groups, thus increasing the number and type of
sites available for adsorption by not only chlorite but also other compounds. One gram of granular
activated carbon removed 600 mg/L of chlorite from solution (Vel Leitner, etal. 1994).
The presence of phenol or p-nitrophenol in solution or preadsorbed on carbon, however, will decrease its
capacity to remove chlorite because many byproducts, such as chlorophenols, p-benzoquinone,
dimerization, and carboxylation products, are formed on the carbon surface once the chlorite contacts the
organics. These halogenation reactions occur in the granular activated carbon (GAG) bed both when the
chlorite is in solution with the organics and when the chlorite-free organic solution is passed over chlorite-
preoxidized activated carbon. Oxidation of activated carbon with chlorite apparently promotes the catalytic
properties of the carbon surface. Other disinfectants such as NH2CI, CI2, CIO2 also undergo halogenation
reactions with organics in the presence of activated carbon. These byproducts may be less desirable than
the organics originally in solution. Some of the byproducts formed from reactions of organics and
disinfectants on the activated carbon surface include aromatic acids (benzoic acid, salicylic acid,
hydroxynitrobenzoic acid, and nitrobenzoic acid), benzaldehyde, hydroxybenzaldehyde, 4-
phenoxyphenol, 4-phenoxymethoxybenzene, 2,2'-dihydroxybiphenyl, benzofuran, 2,3-benzofurandione,
chloronitrobenzenes, and nitrosophenol (Vel Leitner, et al. 1994).
Metal Removal Capability
Hexavalent chromium is effectively removed by a pH-dependent adsorption with the peak adsorption at
pH 6 (Sharma and Forster 1993). More than 80% of inorganic and organic mercury in a solution has been
removed by a commercial granular activated carbon, with even greater removals resulting when humic
acid or nitrilotriacetic acid (NTA) was added to the solution (initial solution, 10 ^g/L Hg(ll) and 5 mg/L of
humic acid or NTA). Activated carbon from peanut shells is seven times more effective than
commercially-available activated carbon at the removal and recovery of mercury from solution, possibly
because the peanut hull carbon has a higher moisture content that may increase its porosity and makes
available more sorption sites. Peanut hull carbon also has a lower ash/higher carbon content (70 mg
peanut hull carbon for adsorption of 20 jig/L in 100 mL solution versus 500 mg commercially available
activated carbon for the same adsorption). Peanut hull carbon has lower decolorizing capacity and a
moderate ion-exchange capability as compared to the commercially available carbon, implying that it will
not be as suitable for organic adsorption. Peanut hull carbon adsorption also is not as pH dependent as
commercially-available activated carbon. Rice-husk and coconut-shell activated carbon also has been
effective in the removal of heavy metals from aqueous solutions. The adsorption process follows both the
Freundlich and Langmuir isotherms with pore diffusion being only one of the rate-controlling steps
(Namasivayam and Periasamy 1993).
Microorganism Removal Capability
Historically, it has been believed that silver-impregnated activated carbon rendered bacteria inactive, i.e.,
made drinking water 'safer,' possibly because low pH, lower temperatures, higher mineral matter, and
phosphate concentrations could reduce bacterial action. Testing of a commercial silver-impregnated
carbon filter showed that the concentration of Salmonella typhiwas reduced more than 5 logs (99.999
percent) at a silver concentration of 50 |ig/L and 1 hour of exposure; however, the concentration of
Pseudomonas aeruginosa was reduced less than 50% and the concentration of poliovirus type 1 was not
reduced under the same conditions. Under most circumstances and with long-term use, the silver-
impregnated activated carbon filters have negligible ability to remove microorganisms from solution (Bell
1991). Silver has been fused into activated carbon and some ceramic filters in order to prevent biofilm
growth in some household water filtration units, e.g., Katadyn water filters.
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Other Carbon-Based Filters
Carbonaceous residues such as wheat straw have been used to remove nitrogen from reclaimed
wastewater In a nitrification/denitrification sequence. The wheat straw is then a source of carbon for the
microbial colonies that perform the nitrification and denitrification. The straw's capacity for nitrogen,
ammonia, and nitrate immobilization was found to be about 9 mg N/g (mg nitrogen per gram). Significant
reductions in BOD, organic carbon, chlorophyll, phosphorus, algae, and clay concentrations in the influent
were also found (Lowengart, et at. 1993). The wheat straw substrate has a poor nutrient content that
leads to the removal of nitrogen and phosphorus from the influent water by the microbial biomass (Diab,
et a/. 1993).
Ultrafiltration membrane pores (0.001 - 0.1 jam) are relatively large and can remove only those molecules
and particles that are larger than the pores. Inorganic ions readily pass through these membranes.
Activated carbon has been added to Ultrafiltration systems in order both to remove the organics that
cause early clogging of the filter and to sorb many compounds that would pass through the filter. The
activated carbon concentration should be less than 600 mg/L for the best operational efficiency.
Powdered activated carbon (PAC) is usually used in conjunction with Ultrafiltration membranes because
the smaller particle sizes of the PAC have considerably faster adsorption kinetics and reduce the required
contact time. As with all activated carbons, the carbon concentration required to achieve a particular •
effluent concentration is directly related to initial concentration of the contaminant in question (Adham, et
a/. 1991).
Limitations of Activated Carbon
Activated carbon cannot desorb high boiling solvents and will polymerize or oxidize some solvents to toxic
or insoluble compounds (Block! 1993). It has a very small net surface charge and is ineffective at
removing free or hydrated metal ions, unless they are complexed with easily-adsorbed organics prior to
filtration. However, once they are complexed with these insoluble organics, the complexed metals are
readily adsorbed onto the carbon, which result in the desired high removal rates (Anderson and Rubin
1981).
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Peat Moss
Peat is loosely defined as partially decomposed organic material, excluding coal, which is formed from
dead plant remains in water in the absence of air. The physical structure and chemical composition of
peat' is determined by the types of plants (mosses, sedges and other wetland plants) from which it is
formed. Peat is. physically and chemically complex and is highly organic with its main components being
humic and fulvic acids and cellulose.
Peatland development is controlled by several processes, including peat accumulation, Sphagnum
acidification, and climate. The general movement from rich to poor fen and then to bog is primarily a result
of peat accumulation. Peatland development can range from <1500 years to >2000 years and usually
occurs in areas with gentle topography and where the prevailing climate has short, warm, moist summers
and long, cold winters. Bogs and poor fens are Sphagnum-dominated while rich fens contain mostly
brown mosses (Kuhry, et al. 1993).
Peat accumulation causes the land surface to become separated from the mineral-rich ground water, i.e.,
the depth to the water table increases. Mesotrophic rich fens develop into oligotrophic poor fens that are
further acidified by Sphagnum. Continued peat accumulation results in the development of ombrotrophic
bogs, which depend exclusively on precipitation for nutrients and water. The rapid transition from rich fen
(pH > 6) to poor fen and bog (pH < 5) is most probably a result of chemical factors, i.e., the 5 - 6 pH
transition range is also where the bicarbonate alkalinity becomes zero. Once this bicarbonate buffer is
gone, the peatland is very sensitive to further oligotrophication and Sphagnum acidification. The removal
of regular contact with the deeper, mineral-rich ground water also reduces the opportunity for
neutralization of the acidification caused by Sphagnum (Kuhry, et al. 1993).
Peat Composition
Peat contains the products of inhibited plant and vegetable matter decomposition and may contain up to
15% bituminous substances, including a wide range of saponifiable (e.g., C18-C30 free fatty acids, fatty acid
triglycerides, and non-glyceride esters) and unsaponifiable liquids (e.g., long-chain hydrocarbons,
alcohols, and steroids). At ambient temperature, the peat bitumen is a solid-liquid system. The solid
phase consists of several different crystalline species of carboxylic acids and esters while the liquid phase
is highly viscous and consists of a mixture of paraffins, carboxylic acids, alcohols, and esters. The flow
behavior of the bitumen is similar to that of a yield pseudoplastic fluid. The behavior is extremely
temperature sensitive because of both the melting and crystallizing of the crystalline minerals and the
changing polar interactions in the non-crystalline component. At ambient temperature using polarized light
microscopy, the bitumen was found to contain many small crystallites (diameter, 5.4 |im). Using
successive organic extraction steps, the peat bitumen was found to contain wax (43.9%), resin (37.9%),
and asphaltene (6.7%) with the remaining 11.5% containing some visible peat fibers but probably
consisting mostly of polymerized peat fatty acids and hydroxy acids. Infrared spectroscopy indicated that
the polar species such as esters and acids are primarily in the wax and asphaltene fractions, while the
resins consist largely of non-polar constituents (Leahy and Birkinshaw 1992).
Carboxylic acids and esters in the wax fraction likely are the dominating Theological influence in the
bitumen. They affect the peat's physical behavior because they crystallize at a low temperature and
mechanically hinder flow, and because their secondary bonding increases the liquid's viscosity. The
crystallizing species appear to be the esters of the fatty acids rather than the more polar acids,
possessing molecular weights below 1200 (Leahy and Birkinshaw 1992).
While the wax consists primarily of medium and high molecular weight species, the liquid resin is almost
completely low molecular weight material, such as paraffinic liquids, and carbonyl and hydroxyl species.
No aromatic or unsaturated species appear to be in the resin. The paraffinic liquids are non-crystalline,
with flow characteristics, at ambient temperature, of a low-viscosity Newtonian fluid. As the crystallinity of
the resin increases, the flow becomes yield pseudoplastic (Leahy and Birkinshaw 1992).
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The asphaltene fraction appears to consist of similar-sized species to those in both the wax and the resin
but is believed to contain more polar constituents. The crystallizing species in the asphaltene are of
relatively high molecular weight; however, analysis of the asphaltene indicates that low molecular weight
species are present and dilute the crystallizing species. The first fraction of the asphaltene on an infrared
spectra is a paraffin, followed by mixtures of saturated acids and esters, with esters. Acids increase in
significance and concentration in the later fractions. The largest-sized fractions of the asphaltene appear
to contain several unsaturated compounds (Leahy and Birkinshaw 1992).
Hydraulic Characteristics
Peat moss (sphagnum moss) is a fibrous ("fibric") peat and is typically brown and/or yellow in color. It has
easily identifiable undecomposed fibrous organic materials, and its bulk density is generally less than 0.1
g/cc. Because of its highly porous structure, peat moss can have a high hydraulic conductivity, up to 140
cm/hr. (Galli 1990). Its chemical and physical structure (pore volume of 80-90% [Karamanev, et al. 1994])
encourages water retention, and it can contain up to approximately 90% water by weight (Leahy and
Birkinshaw 1992). Peat permeability varies greatly and is determined both by its degree of decomposition
and the plants from which it came. A 50% change in a peat's moisture content can change its
permeability up to five orders of magnitude (Mitchell and McDonald 1992). Generally, the more
decomposed the peat is, the lower its hydraulic conductivity. Peats lose mpst of their hydraulic
conductivity when compressed. Two different flow regimes exist in peat filters because of the peat's three-
level, fractal-like structure, i.e., the same shape of the structure is observed at three different
magnifications. At low velocities, the liquid flows through the peat moss particles; however, at high
velocities (above the critical velocity of approximately 0.1 cm/s), the liquid mainly flows between the solid
aggregates with only a small amount penetrating the particles forming the aggregates. The mass transfer
mechanisms appear to be due to the following: 1) diffusional transfer at the smallest level; 2) convective
or diffusional transfer (or both) at the second level, depending on the liquid velocity; and 3) convective
transfer at the largest level (Karamanev, et al. 1994).
Peat moss' coarse structure likely causes the observed decrease in hydraulic conductivity as the water
content is reduced. Peat also exhibits a hysteresis between the drying and wetting curves, likely because
as the material dries out it becomes more hydrophobic and, consequently, more difficult to rewet (da
Silva, et al. 1993), with severely dried peats (>= 35% moisture loss) being exceptionally difficult to rewet.
Possible reasons for this phenomenon include macropore collapse and high micropore suction-pressures.
Drying also shrinks humic molecules, binding the color-producing, lower-molecular-weight fractions
together. The peat initially will repel new water; however, continuous rewetting eventually will lead to
water penetrating all pore spaces, saturating the peat, and flushing out any accumulated color-producing
organic acids (Mitchell and McDonald 1992).
Natural peaty clays have a high organic content (>20%) and are compressible because of void volume in
the mix. However, amendment of the peat with sand can greatly reduce its compressibility, which also will
increase its bulk density and decrease its moisture content. When the sand to peat ratio is 1.76, the bulk
density of the mixture increases from 1,310 kg/m3 to 1,776 kg/m3, and the moisture content decreases
from >80% to 23% (Lo, et al. 1990).
Organic Removal Capability
Peats can extract substantial amounts of either free-phase or dissolved hydrocarbons from water
(between 50 and 90% of the starting wet volume and 63 and 97% of dissolved hydrocarbons from
saturated solutions). In general, the best peats for hydrocarbon adsorption are low in fiber and birefringent
organics and high in ash and guaiacyl lignin pyrolysis products. Because these parameters indicate the
degree of peat decomposition, adsorption appears to increase as decomposition increases, possibly for
the following reasons: (1) greater surface areas are associated with smaller particles; (2) chemical
changes resulting from decomposition; or (3) inherent chemical or physical differences in the source
plants. Sorption possibly results from the aromatic surfaces attracting the hydrocarbon while cross-linking
side chains "trap it" and hold it in place. Another potential explanation of hydrocarbon sorption to peat is
28
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that the intermolecular distances and area within the lignocellulosic polymer are suitable for absorption
between basal lignin units. Inter- and intra-molecular forces between the lignin and the hydrocarbon
control the competition between the two mechanisms (Cohen, etal. 1991).
Toluene is sorbed more slowly to peat than either benzene or m-xylene, yet toluene had much less
variation in its sorption to different peat types than benzene and m-xylene. With sufficient contact time,
toluene sorption capacity is similar to that of benzene and m-xylene. In free-phase experiments, the
absorbencies exhibited by the specific peat types did not depend on the type of hydrocarbon sorbed, with
the Maine sphagnum peat having somewhat less absorption per unit volume than other peats. This may
be a result of the visibly larger pore size in Sphagnum peat compared to other peats. Sphagnum has
more visible, preserved fibers, a higher water-holding capacity, and a relatively high porosity, which, along
with pore size, type, and shape, may be significant factors in hydrocarbon adsorbency (Cohen, et al.
1991).
Peat moss can, however, shrink or swell in the presence of some organic compounds, possibly because
sorption site availability increases in liquid sulfoxides, with the increase being dependent on humification
despite the general decrease in oxygen/carbon ratio with humification. Swelling and/or shrinkage of the
peat has been demonstrated by sorption of pure (>95%) methyl, tetramethylene, and propyl sulfoxides
and propyl sulfones on dewaxed, acid-form peats. Apparently, the cellulose particles adhere to one
another when dry. The addition of a liquid, even a nonswelling one, lubricates the particles so that initially
they compact slightly (Lyon 1995).
Alcohol sorption curves are similar, even with large differences in humification between the two peats
studied, implying that the alcohol sorption sites within peats are not changed significantly by humification.
Significant swelling was observed for peats immersed in propyl sulfoxide, demonstrating that the
approximate limit of swelling, as found by Lyon and Rhodes, by solvents with molar volumes < ca. 93 cm3
mol"1, can be exceeded when the liquid contains a strongly interacting functional group. The swelling limit
for most alcohols is probably influenced more by the peat's basic sites rather than the acidic sites, and,
therefore, different limits are possible for acidic and basic organic liquids (Lyon 1995).
The binding of polycyclic aromatic hydrocarbons (PAHs) to both solid soil humic materials and dissolved
humic substances appears to be controlled by both adsorption and partitioning with the filter media, with
the partitioning term being the most important for largely nonpolar sorbates. The sorption of phenols and
PAHs correlates well with their hydrophobicity. The sorption of nonpolar organics correlates well with the
oxygen content of the organic matter in the peat, with the exception of a few polymers that have a high
oxygen content. Nitro and hydroxyl groups on a sorbate molecule tend to strengthen the molecule's
sorption because of the charge transfer interactions that occur between the sorbate and the peat. The
correlation between a nonpolar organic's hydrophobicity and sorption capacity is not valid for aromatic
amines where sorption exceeds the estimated bonding by five to ten times. The number of aromatic rings
also appears to influence sorption capacity significantly. Fulvic acids are slightly more polar than humic
acids, and, thus, they are slightly more water soluble and have slightly different sorption capabilities
(Kopinke, etal. 1995).
Peat can also leach organic compounds, especially colored organic matter such as humic and fulvic
acids. The amount of leaching of colored compounds is dependent upon season (for an outdoor filter) and
soil moisture. One possible explanation for the correlation of peat moisture and color distribution and
intensity is the change in pH and water content during filtration. The peat showed a rapid initial rise in
color and pH/acidity, followed by a gradual decline. The length of drying between filtration events
indicates the size of the "store" of water-soluble, color-producing organic acids, especially in the top 3 cm
where aerobic decomposition and oxidation also is occurring. When the filter is initially wetted, this "store"
is released, and the effluent becomes colored as the decomposition products come into contact with
water and become 'color' (Mitchell and McDonald 1992).
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Inorganic (Non-Metal) Removal Capability
A peat-filter system has been developed for enhanced nitrogen removal or transformation in sanitary
wastewater. The filter uses a layer of sphagnum peat moss placed below the weeping tile bed where
nitrogen is assimilated into the fungal biomass, thus reducing the nitrogen content of the wastewater.
Sixty to 100 percent removals have been achieved for nitrate levels up to 125 mg N/L (Robertson and
Cherry 1995). Peat is an excellent substrate for microbial growth, with large colonies of nitrifying and
denitrifying bacteria typically present. It can assimilate nutrients and organic wastes because of its high
C:N:P ratio, which often approaches 100:10:1. Long-term phosphorus retention in peat is related to its
calcium, aluminum, iron, and ash content with the higher the content of each of the above constituents,
the higher the retention capability (Galli 1990). A peat filter system for treating septic tank effluent has
been able to treat wastewater at a hydraulic loading rate of 40 L/m2 of filter surface while maintaining a
high effluent quality: NO3-N (<5 mg/L), NH3-N (0-17 mg/L), organic-N (0 - 7 mg/L), BOD5 (5 - 20
mg/L), DO (3 -13.3 mg/L), TSS (5-15 mg/L), pH (5.3 - 6.5), and fecal coliforrns (reduced by 99.99+
%). The major drawback to the system was the tea color of the effluent (Daigle 1993).
Metal Removal Capability
Because of the lignins, cellulose, and humic and fulvic acids in peat, peat is highly colloidal, is polar, has
a high cation-exchange capacity, and has a high specific adsorption capacity for transition metals and
polar organics (Galli 1990). Sphagnum moss contains an anionic polysaccharide ('sphagnan') that
selectively binds calcium and other multivalent metal cations. As the dead moss slowly becomes peat,
soluble sphagnan is gradually released. However, sphagnan is unstable, and in the mildly acidic
conditions of peatland formation, it is slowly converted into humus or humic acid. Humic acid also binds
multivalent metal cations, and its selectivity for Ca2+ is even higher than that of sphagnan, thus ensuring
that peatlands are permanently decalcified (Painter 1991).
Peat moss has been used to treat metal-bearing industrial effluents since it will adsorb, complex, or
exchange various metal cations (Gosset, era/. 1986). Peat has an excellent natural capacity for ion
exchange with copper, zinc, lead, and mercury, especially at pH levels between 3.0 and 8.5. The peat
contains polar functional groups such as alcohols, aldehydes, ketones, acids, and phenolic residues
which chemically bind metal ions from a solution (Sharma and Forster 1993). However, the sorption
capacity of peat is finite and reversible and is controlled by the pH of the solution (Galli 1990).
Immobilization of a metal by peat depends on (i) the metal ion capture chemistry, (ii) solute transport rates
from the bulk solution to the adsorbent surface, and (iii) the transport rates and equilibria within the
adsorbent's interstices. For metal adsorption on peat, film diffusion appears to be the rate-controlling step;
although at small peat-to-metal ratios, internal mass transfer also greatly influences the sorption. A three-
step model can be used to describe the metal immobilization process by peat: (i) solute mass transfer
from the solution to the particle surface, (ii) ion-exchange reactions at fixed sites on the peat, and (iii)
internal diffusion of solute. In general, the ion-exchange reaction is very fast compared to the other two
steps and is not the kinetic rate-limiting step. At high peat concentrations, film and external mass transfers
are most important while at low peat concentrations, intraparticle diffusion controls the reaction rate
(Allen, et al. 1992).
In buffered solutions, the order of sorption.for four metal ions to peat is Ni2+ > Cu2t> Cd2t = Zn2+,
independent of peat origin. Above pH 3, copper binding is similar to nickel and is dependent upon the pH
of the solution; cadmium and zinc present a similar pH dependence but are less strongly bound than the
copper and nickel. Only the nickel cation, however, is bound strongly enough not to be desorbed when
.the pH is dropped to below 1.5 (Sharma and Forster 1993).
In unbuffered solutions, the pH drops between 0.2 and 0.6 pH units during filtration for all metal-peat
combinations tested (Gosset, era/. 1986) because of the release of humic and fulvic acids during
adsorption or ion exchange (Sharma and Foster 1993). Unsieved and non-acidified oligotrophic or
eutrophic peat samples seem to bind copper more rapidly and efficiently than sieved and acidified ones,
possibly because the structure of the peat is changed during acid pretreatment. The sorption curves for
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the metals are not linear, regardless of the peat-metal combination, indicating that the peat-metal complex
stoichiometry and thermodynamics are probably dependent both on the free metal concentration and on
pH, which varies in unbuffered .solutions. Although saturation limits of 200 mmol metal/kg dry weight peat
were observed in buffered solution, sorption saturation (even at 0.1 M metal in 50 g/L peat) was not
observed in unbuffered solutions. Maximum removal could be achieved when the metal concentration in
the buffered solution was in the 0.1 -1 mM range, provided that there is adequate contact time (Gosset,
et al. 1986). Sphagnum moss has been shown to remove iron (75% reduction) and manganese (25%)
from acid mine drainage in Pennsylvania ("Moss Tested to Remove Manganese from Mine Drainage,"
1984).
Sphagnum moss peat concentrations ranging from 4 to 40 g/L can effectively remove hexavalent
chromium from solution (10 to 1000 mg/L Cr(VI)), especially when the ion concentrations are low. At
equilibrium pH of 2.0, almost complete removal of Cr(VI) can be achieved when chromium concentrations
are less than 100 mg/L, while at equilibrium pH of 1.5, 64% Cr(VI) removal can be achieved when
chromium concentrations are less than 1000 mg/L. The sorption is pH dependent, with the optimum range
being 1.5-3, and is controlled by (i) chemical reduction, i.e., Cr(VI) to Cr(lll); and (ii) adsorption of the
mainly Cr(VI) species. The chromium is strongly bound, and little desorption occurs in low molarity caustic
solutions. In high molarity caustic solutions, the peat itself 'disintegrates' (Sharma and Forster 1993).
Limitations of Peat Filters
The release of color upon wetting is one problem with peat. Another potential problem is that peat may
leach some nutrients, depending on the soil and water chemistry and water level. Sphagnum peat
generally wiil release significantly more phosphorus and ammonium than Carex peat with the water
quality determining the extent of nutrient release, especially in waters with a high sulfate concentration.
Temperature also influences the amount of ammonium, potassium, and phosphate leached. Nutrient
leaching will increase two to three fold after the peat has been frozen (Koerlsman, et al. 1993).
Stormwater Runoff Treatment
Urban road runoff generally has large concentrations of heavy metals and particulate organic carbon, as
well as high alkalinity. Peat moss has been used as a growth medium for plants, such as red maple and
cranberry seedlings, to treat urban stormwater runoff containing lead and zinc, in general, metals in acidic
swampwater were more available to the plants than those in alkaline runoff and uptake of the metals
usually increased with decreasing pH and decreased with increasing soil organic matter content.
However, soluble organic acids can mobilize heavy metals into solution, even those in alkaline runoff
water (Vedagiri and Ehrenfeld 1991).
Peat-sand filters (PSF) have been proposed to treat urban runoff. The PSF is an aerobic, "man-made"
filtration system, unlike older sand or peat filtration systems that use naturally occurring soils as the filter.
The peat-sand mixture layer must be manufactured, as it does not occur in nature. A PSF can be
expected to remove most of the phosphorus, BOD, and pathogens, and with a good grass cover, other
nutrients (Galli 1990).
The Peat-Sand Filter System designed by the Metropolitan Washington Council of Governments
(Washington, D.C.) would have a good grass cover on top underlain by 12 to 18 inches of peat. The peat
layer is supported by a 4-inch mixture of sand and peat that is supported by a 20- to 24-inch layer of fine
to medium grain sand. Under the sand are gravel and the drainage pipe. The mixture layer is needed
because it will provide the necessary continuous contact between the peat and the sand layers and
ensure uniform water flow. Because the PSF is a biological filtration system, it will work best during the
growing season when the grass cover can provide the additional nutrient removal that will not occur in the
rest of the filter (Galli 1990). The expected pollutant removal efficiencies are given in Table 14.
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Table 14. Peat-sand filter pollutant removal efficiencies (Source: Galli 1990)
Pollutant
Suspended Solids
Total Phosphorus
Total Nitrogen
BOD
Trace Metals
Bacteria
Removal Efficiency (%)
90
70
50
90
80
90
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Compost
Composts made from yard waste, primarily leaves, have been found to have a very high capacity for
adsorbing heavy metals, oils, greases, nutrients, and organic toxins due to the humic content of the
compost. These humic compounds are stable, insoluble, and have a high molecular weight. They act like
polyelectrolytes and remove the toxicants from the runoff either by adsorption or ion-exchange. The exact
content of and aging process for the composts used by W&H Pacific/CSF Systems, Inc. are not public
knowledge with the result that the filter installation-and-maintenance company supplies the compost to
the stormwater treatment device owner.
The composted leaf filter was developed by W&H Pacific for Washington County (WA), the Unified Sewer
Agency, and the Metropolitan Service District of Washington County (W&H Pacific 1992a). The filter
consists of a bottom impermeable membrane with a drainage layer above it. Above the drainage layer is a
geotextile fabric upon which rests the compost material. The actual toxicant removal occurs in the
compost layer by filtration, adsorption, ion exchange, or biodegradation, or by a combination of these
processes.
The composted leaf filter is advertised as an improvement over other stormwater treatment devices, such
as detention ponds and grass swales, because the square footage required for the filter is much smaller
than for the other devices. A small presettling area (less than one minute detention time) is
recommended; otherwise, the larger particles and floatables will prematurely clog the filter and reduce its
treatment efficiency. Filter design was based on permeability tests performed by W&H Pacific and the
design flow was selected as 2.25 gallons per minute (0.30 m3/min), which gives a required compost bed
surface area of 200 ftVcfs (60,435 mVmVsec.). The results from the testing of a prototype Compost Storm
Water Filter System (CSF) are given in Table 15. This filter was located where the drainage area is 74
acres (3.9 acres highway, 70 acres mixed residential).
A three-year testing program on the CSF has shown that the filter is excellent at removing metals and
hydrocarbons from the runoff. Sediment accumulation, always a potential problem for any filtering system,
was, during the 1992-93 testing season, approximately 74 ft3 (2.1 m3) with an average thickness range of
0.25 to 1.27 ft (0.07 to 0.4 m). During the 1993-94 season, 111 ft3 (3.1 m3) of sediment with an average
thickness of 0.5 to 1.2 ft (0.14 to 0.4 m) collected in the system (CSF Systems 1994). Based upon the
sample results at the location of the compost filter, the first flush of a storm had the heaviest pollutant
loadings, and the filter had the highest removal efficiencies during this first flush. This indicates that the
CSF System is capable of treating a shock loading of pollutants while producing an acceptable effluent.
The average first flush removal rates for the three years of operation are given below in Table 16.
CSF Systems, Inc., the manufacturer and distributor of the compost filter, outlines the advantages and
disadvantages of this compost system. One advantage is that the filter has a very high buffering capacity
in the alkaline range. When the influent is between pH 6.7 and 8.3, the effluent is consistently between
pH 7.0 and 8.0. However, because the media acts as an ion-exchange resin, whenever a pollutant sorbs
to the media, an ion is 'leached off.' In the case of the compost, soluble phosphorus is one of the ions
that is leached off during ion exchange (influent, 0.09 -1.0 mg/L; effluent, 0.29 mg/L). Soluble
phosphorus likely is released from the captured solids through microbial action and since the compost
only has a weak anion exchange capacity, most of the soluble phosphorus is not removed from the water
once it is leached from the compost. Testing has also shown an increase in boron and nitrate in the
effluent of the compost filter (CSF Systems 1994).
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Table 15. Compost filter pollutant removal efficiencies (Source: CSF Systems 1994)
Pollutant
Turbidity
Total Solids
Suspended Solids
Total Volatile Suspended Solids
COD
Setlieable Solids
Total Phosphorus
Ammonia
Total Kjeldahl Nitrogen
Copper
Zinc
Lead
Aluminum
Iron
Petroleum Hydrocarbons
Oil and Grease
Influent/Effluent Concentration Range
0-90 mg/L Influent; 0-14 mq/L Effluent
0-4 mL/L Influent; 0.05-0.1 mL/L Effluent
, Removal Rate (%)
82
49
92
89
70
95
49
60
57
7
83
83
84
91
84
81
Table 16. Compost filter removal efficiencies - first flush (Source: W&H Pacific 1992b; CSF Systems 1994)
Pollutant
Turbidity
Total Solids
Total Suspended Solids
Settleable Solids
Total Volatile Suspended Solids
COD
Total Phosphorus
Ammonia
Total Kjeldahl Nitrogen
Copper
Zinc
Lead
Aluminum
Iron
Removal Rate (%)
86
63
94
98
97n
79
63
65
72
83
86
86
88
93
* Results are from the first year of operation only.
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Zeolite
Adsorbents must be sufficiently selective and have adequate capacity and stability to achieve the required
separation economically over a prolonged period of time. To get the required capacity, the adsorbent
must have a high specific surface area, i.e., be highly porous with fine pores (micropores). Furthermore,
most important adsorbents use physical adsorption (multilayer) rather than chemisorption in which the
capacity is limited to monolayer coverage (Ruthven 1988). Zeolites are preferred as adsorbents in the
chemical process industry because they are inorganic, non-flammable, and can withstand very high
temperatures (Vaughn 1988). Generally, they are porous aluminasilicates which may occur naturally but
also can be synthesized (Blocki 1993). They have been used in such diverse applications as natural gas
purification (chabazite), radioactive waste disposal (clinoptilolite), ammonia recovery from sewage
effluents (clinoptilolite), and various petroleum and petrochemical catalyst applications (erionite,
mordenite) (Vaughn 1988).
Physical Characteristics
Zeolites occur naturally in basaltic lava, in specific rocks subjected to moderate geologic temperature and
pressure, and in altered and reacted volcanic ash deposits (Vaughn 1988). Clinoptilolite is the most
abundant naturally occurring zeolite. The formula of one cell of clinoptilolite is (Ca,Na2,K2)3[AI6Si30O72]-24
H2O. It has a two-dimensional 8-ring and 10-ring channel structure with the largest cavity measuring 4.4 x
7.2 A. Zeolite surface chemistry is similar to that of smectite clays with the difference between the two
being that natural zeolites may be millimeter or greater sized particles and do not exhibit shrink-swell
behavior (Haggerty and Bowman 1994).
The primary building block of zeolite is a tetrahedron of four oxygen atoms surrounding a central silicon
atom (SiO4)4". Zeolite polyhedra are connected by shared oxygen atoms on the corners, and these
polyhedra connect to form the various specific zeolite crystal structures. Different combinations or
arrangements of the same polyhedra may give numerous distinctive zeolites. Other elements, such as Al,
Ga, Ge and Fe (Haggerty and Bowman 1994), may be substituted for the silicon, provided that they "fit"
into the center of the four tetrahedral oxygen atoms without too much strain on the oxygen bonds and that
the resultant structure is electrically neutral (Vaughn 1988). Union Carbide scientists in alumino-
phosphate chemistry recently have expanded zeolite compositions to include about 13 elements,
including Li, Be, B, Mg, Co, Mn, Zn, P, As, and Ti (Haggerty and Bowman 1994). These variations in the
chemistry in the basic structure change the pore sizes available for sorption and therefore alter the
selectivity that can be achieved by a zeolite (Blocki 1993).
Zeolites often are called molecular sieves because their crystalline framework has channels (pores) and
interconnecting voids of molecular size (3 to 10 A) (Vaughn 1988). Zeolite species are often specified by
letters after their name. Zeolite A has 8-member oxygen rings with a void size of 4.3 A in the Ca2+ form,
3.8 A in the Na* form and 3.0 A in the K* form. X and Y zeolite pores, both of which have 12-member
oxygen rings and whose frameworks are identical, are larger, having a free aperture of about 8.1 A. The
difference between the X and Y zeolite is the Si/AI ratio which controls the cation density and therefore
affects its adsorptive properties. The zeolite with the intermediate pore size has a 10-member oxygen ring
and has a pore size of about 6.0 A (Ruthven 1988). The ability to control access to the reactive sites by
selecting the zeolite with the pore size in the desired range, as well as the size and stereochemistry of the
site itself, makes molecular-level control of chemical reactions possible (Vaughn 1988).
Zeolite Synthesis
Zeolite synthesis is usually a batch process run at one of the following conditions: (1) 90-100°C, 1 atm.
pressure, pH > 10; (2) 140-180°C, 5-10 atm., pH > 10; or (3) 100-180°C, water + "amine" autogenous
pressure, pH > 10. The metal phosphates, a relatively new class of zeolites, are made under conditions
similar to (3) above, except that the pH is between 3 and 6 (Vaughn 1988). By varying the chemistry in
the basic structure, different pore sizes and different selectivities can be achieved (Blocki 1993).
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Once the crystal synthesis is complete, the zeolite is mixed with a binder, and then formed into beads,
pills, tablets, or extrudates. In most applications, the binder must be completely inert to avoid side
reactions. Fabrication of the zeolite pellet is difficult because one must avoid plugging the pores with the
binder and must avoid crushing the crystalline structure in high-pressure pilling processes. Most
applications require maximum activity or sorption capacity, and, therefore, the manufacturing process
tries to maximize zeolite content and minimize binder content (Vaughn 1988).
Zeolite Adsorption/Ion-Exchange Characteristics
Because micropore size is uniform in zeolites, these adsorbents have a rather sharp cut-off of sorption
with increasing molecular size. Although the framework primarily determines the pore size, the free
aperture, particularly in the smaller 8-ring sieves, may be modified by ion exchange, again tailoring the
zeolite to a specific effective pore size. Zeolite also is a polar molecule, and it has some unique affinities
that are promoted by the ability to fit a particular molecular shape into a pore. These features also
contribute to the ability of zeolite to be a highly selective adsorbent. Adsorption forces for zeolites can be
divided into van der Waals forces, induced dipole interactions, and other electrostatic forces (polarization,
dipole and quadrupble interactions). Van der Waals forces affect any sorbate-sorbent pair because they
depend on the surface (micropore) geometry and increase with the polarizability of the sorbate molecule.
Molecules which just 'fit' in the pore channel have maximum van der Waals interaction energy. By
contrast, electrostatic forces, except for polarization energy, require both a surface electric field, i.e., polar
or heterogeneous adsorbent, and a dipolar or quadrupolar sorbate molecule (Ruthven 1988).
When A!3* is substituted for Si4* in the zeolite framework, a net negative charge on the molecule results.
This is compensated for by a 'nonframework' cation (e.g., Na*), which is 'held' in the pores of the
structure. Because this cation is not a part of the crystalline lattice, it is relatively mobile and easily
exchangeable for other cations (Vaughn 1988). Ion-exchange and adsorption processes for zeolites often
are even more complicated than for organic ion-exchange resins because the zeolite has two distinct pore
structures: micropores in the crystals and macropores in the binder, both of which can participate in
sorption (Robinson, era/. 1994). Zeolites have internal and external surface areas of up to several
hundred meters squared per gram. They can have cation-exchange capacities (CECs) of up to several
equivalents per kilogram (Haggerty and Bowman 1994).
Because of the exchangeable cations, zeolites are polar adsorbents. Molecules such as water or
ammonia (high dipole), CO2, N2 (quadrupolar) or aromatic hydrocarbons (n layer interaction) therefore
adsorb more strongly than nonpolar compounds of similar molecular weight. This affinity generally
increases with increasing charge on the exchangeable cation and decreasing cation radius, but its effect
may be masked by water, which, because it is strongly bound to a zeolite, will reduce the zeolite's affinity
for other, less polar molecules. Aqueous sorption has considerable amounts of water present in the
intracrystalline fluid (Ruthven 1988).
Although most zeolites are strongly hydrophiiic (because the strongly polar water molecule interacts with
the cation), the zeolites with a high silica content (nonpolar surfaces) are actually hydrophobic because
water is adsorbed less strongly than most organics. The adsorption is limited to van der Waals forces,
and water is adsorbed less strongly than the more polarizable organics (Ruthven 1988). The hydrophiiic
zeolites may not separate volatile organic compounds (VOCs) well in a humid atmosphere, where
complete drying may not occur between sorption events (Blocki 1993).
Liquid and concentration-dependent surface diffusion both contribute to macropore diffusion (Robinson,
etal. 1994). Diffusivities (at 600 K) range from 10"6 - 10'r cmVs for benzene and p-xylene to 10'14 -10~15
cmVs for hexamethylbenzene and anthracene. Although diffusivity changes cannot be correlated directly
to molecular weight, molecular length, or critical molecular diameter sequence, the diffusivities generally
tend to decrease with increasing sorbate size. Diffusivity instead correlates well with the sorbate's
moment of inertia, suggesting that restrictions of the rotational freedom of the sorbate molecule affects
diffusivity. This pattern indicates that the diffusion of sterically hindered planar molecules within the pores
of a zeolite is controlled primarily by entropy effects, not because the pore size is too small. Therefore, a
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sharp cutoff of sorbate size exists and, for molecules larger than the cutoff and whose deformation is
sterically hindered, essentially no intracrystalline pore penetration and sorption exist (Ruthven and Kaul
1993b).
Organic Removal Capability
Hydrophobic zeolites generally are non-flammable, temperature-resistant (up to 1000°C), inert to many
polar and nonpolar solvents, and are efficient adsorbents for a wide concentration range (Block! 1993).
The saturation capacity is expected to be one molecule per pore, and the adsorption isotherms for many
higher weight aromatic hydrocarbons, such as benzene, toluene, xylene, mesitylene, tetramethylbenzene,
naphthalene, hexamethylbenzene, dimethylnaphthalene, and anthracene, approach this saturation
capacity. There is very little difference between either the isotherms or heats of sorption for different
aromatic sorbates with the same carbon number. Therefore, for sufficiently large molecules, steric
restrictions of the pores reduce the contact between neighboring molecules and, therefore, their potential
for interaction that would prevent sorption (Ruthven and Kaul 1993a).
The higher molecular weight aromatics are very strongly adsorbed, and intracrystalline diffusion is quite
slow and temperature dependent. The sorption capacity, however, is essentially independent of
temperature, reflecting the tendency of the larger molecules to average out the effect of adsorbent
heterogeneities (Ruthven and Kaul 1993a). Zeolites can also sorb unsaturated hydrocarbons with the
sorption 'strength' pattern as follows: aromatics > olefins > paraffins (Ruthven 1988). However, unlike
activated carbon with its variety of pore sizes, hydrophobic zeolite is slower at separating some relatively
common solvents such as xylene because the solvent molecules' diameters are less than the
hydrophobic zeolite's pore sizes (Blocki 1993).
Modifying the surface of a zeolite by initially performing ion-exchange with a cationic surfactant can
increase the sorption capacity for organics that do not sorb well to natural zeolite. Quarternary amine
(HDTMA)-modified zeolites can remove chlorinated aliphatic compounds and benzene derivatives from
aqueous solution by a partitioning-like mechanism without lowering the zeolite's naturally high-sorption
affinity for transition metal cations such as lead (Eyde 1993; Haggerty and Bowman 1994).
Inorganic Removal Capability
Because of its net negative charge, natural zeolite does not sorb anions well, if at all (Eyde 1993).
Surface modification, such as ion-exchange with cationic surfactants, has improved the ability of zeolite to
sorb anions and other compounds that natural zeolite did not sorb well. These sorbed cationic surfactants
alter the surface charge of the zeolite, thus allowing it to sorb anions and other compounds of interest.
Removal of inorganic oxyanions, such as chromate, selenate and sulfate from aqueous solutions
improved from nearly zero sorption when a clinoptilolite-dominated zeolite was modified by 140 mmol/kg
zeolite (15 meq/g) of hexadecyltrimethylammonium (HDTMA). Anion sorption was greatest when the
HDTMA satisfied the zeolite's total external cation-exchange capacity. Anion retention (4 mmol/kg for
CrO4 and >2 mmol/kg for SeO4 compared to 1 mmol/kg for both on natural, unmodified zeolite) resulted
from the formation of an HDTMA-anion precipitate on the zeolite surface (Eyde 1993; Haggerty and
Bowman 1994).
Some zeolites are unstable at low pH because the aluminum in the framework is hydrolyzed, and so one
approach to exchanging transition metals at low pH is to first form ammonia complexes by dissolving
them in dilute aqueous ammonium hydroxide and then carrying out the exchange at high pH (Vaughn
1988). The HDTMA-modified surface, however, is stable at low pH, higher ionic strength and with organic
solvents (Eyde 1993; Haggerty and Bowman 1994). For the US Bureau of Mines, zeolites are an
alternative to conventional precipitation removal techniques for metals such as lead (Eyde 1993).
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Enretech
ENRETECH I is a light-weight, non-toxic, 100% cellulose product (waste from cotton milling) that can be
used to clean up oil spills, especially in areas where it is difficult for people to transport themselves and
their supplies to the spill and clean it up. It can also be used in areas such as tank storage sites, fueling
locations, oil production fields, and oil field pipe treatment yards to collect slow leaks. ENRETECH I is
also effective at cleaning up fuel, oil, paint, or coolant spills on highways (RAM Services, Inc. 1995). The
ENRETECH I material has the consistency of blown-in fiberglass or mineral wool insulation.
Forest Products Agrofiber
The Forest Products Research Lab agrofiber product was developed as both an economic oil adsorbent
and as an economic ion-exchange medium for pollutant removal from water. Keriaf and jute fibers, along
with forest wastes such as barks and pine needles, have been found to efficiently remove copper from
water. Chemical treatment of the kenaf with reactive yellow-2 significantly increased the adsorption
capacity of the kenaf for copper (Forest Products Research Lab 1995).
Gunderboom and EMCON Filter Fabrics
The Gunderboom filter fabric is a woven textile that is marketed as a sorbent fabric for oil spill cleanups.
The EMCON filter fabric is a woven fabric that was sold for use in stormwater treatment devices. Emcon
North West in Bothell, WA developed it for use in existing storm sewer inlets. It is currently being
marketed as the 'Type I Catchbasin Filter" (Foss Environmental Services in Seattle, WA).
Limitations of the Literature Review
For most of the investigated media, very little information is available regarding their ability to remove
pollutants from a mixed-component influent and what information is available may not be applicable to
stormwater runoff treatment. This is because the work was performed using continuous filtration and/or
the influent concentration was many times greater than the pollutant concentrations typically found in
urban runoff. Complete information on design life and maintenance requirements is not available. This
project was designed to supplement the available information about these filters. In particular, the project
was designed in order to determine the life of a filter in the field and to investigate any potential
maintenance problems. Testing was done on a laboratory-scale using actual stormwater runoff to address
these issues. The following two chapters detail the results of the laboratory-scale tests. Future work will
examine selected filter media at a pilot-scale.
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Chapters
Methodology
Overview of the Experimental Design
The initial scope of this project was to determine the design variables for the sand filter that would polish
the effluent from the settling chamber of the Multi-Chamber Treatment Train (MCTT), a stormwater runoff
treatment device that has been designed by Dr. Robert Pitt at the University of Alabama at Birmingham
(DAB) to treat the runoff from small, problem source areas, such as service stations and maintenance
yards. The MCTT consists of three chambers, the sump (grit removal), the settling chamber, and the filter.
This device is designed to be installed at the storm sewer inlet from a problem source area with the
effluent from the device being directly discharged to the storm drain system. The appeal of this device to
owners of small, problem source areas is that the device is low maintenance (1-2 times per year
maximum) and low cost for construction and operation.
Based on the results from the Austin, TX, sand filters, the MCTT's initial design was to have a sand filter
as the effluent polisher. The purpose of this project was to determine the optimum depth and grain size
characteristics for this filter. A filtration column was constructed using the design guidelines from Austin
(18" [46 cm] of sand on top of a gravel underlayer) in 1000 mL graduated Kimax burets (acquired from
Fisher Scientific). The first tests evaluated the water retention in the column, steady state flow rate
through the media and the quantity of solids that can be loaded on the column before 'clogging.' Mass
balance analyses were then performed by filtering a sodium chloride solution (4 g/L) through the column
followed by filtering repeated slugs of 18 MQ resistivity water. These tests with NaCI determined the water
retention and exchange of the material with repeated flushings. Stormwater runoff was then filtered, and
grab samples were collected and analyzed for toxicity (Microtox™), turbidity, and conductivity. The results
of all these tests indicated that the filter was not performing as expected based on the Austin results.
Permanent retention of toxicants was not occurring in the column; instead, trapped toxicants were
displaced from (flushed out of) the pores during subsequent tests.
Because of these results, this project was expanded to evaluate several prospective stormwater filtration
media using the filter construction specifications from Austin. Since the physical straining in the sand filter
was not effective at permanently retaining the toxicants, other media were selected based on their ability
to remove pollutants of interest through chemical reactions, either adsorption or ion exchange. The
filtration media used in the continuation of this research included the following: activated carbon, peat
moss, zeolite, compost, Enretech (a cellulose waste), and a chemically-modified agrofiber. Sand was also
used as a standard for comparison. These materials had a wide range of expected performances and
included relatively expensive media known to provide excellent treatment (activated carbon) and waste
materials (composted leaves, Enretech, and the agrofiber) with uncertain removal characteristics.
Although their expected pollutant removal efficiencies were low (Agnew 1995), two filter fabrics were also
selected for testing. One of the fabrics (EMCON fabric from BAMCON) was available commercially for
stormwater treatment at the time of acquisition, and the other (Gunderboom) was being used in the MCTT
at the Transportation Parking Lot at DAB to distribute water equally across the surface area of the filter.
Past testing of the Gunderboom fabric found that water will not flow through the fabric until a two-to-three
inch (5 to 7.5 cm) head had built up on it. Therefore, the Gunderboom can be used on top of a
conventional filter to evenly distribute water across the filter surface and prevent bypassing of part of the
filter (Pitt and Clark 1996).
The purpose of the revised research was to determine which filtration media provided the "best" removal
for the pollutants of interest with the intention that this information be used by stormwater filter designers
to determine the filter media that best suits their needs. A secondary purpose was to determine and
39
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describe potential drawbacks to the use of each of the media. A new testing program was designed, and
the components of that program are listed below:'
• sediment loading on media before clogging
• effects of pH and ionic strength on adsorption of pollutants
• long-term tests to measure chemical breakthrough
The formula needed to determine the number of samples given a predefined sample error is provided by
Cameron and is as follows:
n = (Z,0 + Z,.p)V/d2
where n is the number of samples needed; Z is the area under the normal distribution at the locations (1-
a) and (1-p); a2 is the variance; and d is the number of units higher than the true mean that is acceptable.
Using an alpha 0.05, a power of 90%, a d that is equal to twice the mean, and a coefficient of variation of
1, the number of samples required during each long-term performance evaluation is at least five. It was
decided that six grab samples should be collected during the bench-scale tests because statistical
significance for most parameters can be determined using the Wilcoxon signed-rank method to less than
0.01, yet the required number of laboratory analyses can be held to a reasonable level. Additional
samples will be collected for the long-term performance tests if more runoff events occur during the
testing time.
Experimental Procedure
Filtration Media and Test Apparatus
Because these experiments involved testing of the filtration media as they are used in the field, the
columns were constructed according to the design guidelines provided by the City of Austin (1988) and
Gall! (1990), and were rinsed according to the rinsing directions supplied by CSF Systems, Inc. (1994).
The filtration columns used in these experiments were Kimax-brand, one-liter, graduated burets (from
Fisher Scientific) (inner diameter = 48 mm) or, for the filter fabrics, borosilicate glass (from Curtin
Matheson Scientific) (inner diameter = 45 mm) cut to approximately the same length as the burets. The
filtration media columns were constructed by first cutting a piece of fiberglass window screen, purchased
at a local hardware store, into a 10 cm x 10 cm square. This screen was placed in the bottom of the buret
and approximately five centimeters of epoxy-coated fish-tank gravel (from Wal-Mart) were poured on top
of it to the 1000 mL mark. The column was then rinsed with one hundred milliliters of tap water.
Fifteen centimeters of sand were then added on top of the gravel, as recommended Galli (1990). The
fifteen layer sand filter is added to the bottom of the column to ensure proper drainage in the lower
section of the column. It is desirable to maintain aerobic conditions in the bottom of the filter for aerobic
microbial activity. Otherwise, during field operations, a layer of water may collect in the bottom of the filter,
turning that area anaerobic and causing release of previously retained pollutants. The sand was then
rinsed at least twice, in one hundred milliliter increments, with tap water. After the sand layer had drained,
approximately thirty centimeters of the media of interest (mixture 50/50 by volume of the sorption media
and sand) were added to the column on top of the sand underlayer. After the medium of interest had
been added, the filters were rinsed several times with tap water in accordance with the directions supplied
by CSF Systems, Inc. for constructing the compost filter and then allowed to stand overnight before use
as per their specifications. Since a sand filter was compared to the other media, the sand filter was
constructed in a manner similar to the other filters. This includes a 15-cm sand bottom layer and a 30-cm
sand layer on top of that, for a total of 45 centimeters of sand.
40
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Influent
- 30.5 cm
(12 Inches)
15.3 cm
(6 inches)
;.,7cm:
Filtration Media Mixed
50/50 (v/v) with Sand
Sand
Gravel Support
Effluent
Figure 3.1 Column Construction
Filter fabric test columns were constructed by attaching a 15 cm x 15 cm piece of the fabric to the bottom
of the glass tubes with stainless steel hose clamps that were purchased locally. The fabric and column
were then set in a borosilicate glass funnel (from Fisher Scientific).
A carousel was constructed to hold all ten of the filtration columns needed for a single run. The carousel
was made from painted plywood. The need for homogeneity of the influent dictated the use of a flow
splitter. The flow splitter was designed to allow a single influent flow to be randomly split into a maximum
of ten equal effluent flows. Delrin plastic was used to construct the splitter with the machining on the flow
splitter done by MGM Machining in Helena, AL. Ten holes designed to accommodate ten one-half inch
I.D. pipe-to-tube adaptersior plugs were drilled into a six-inch cylinder of Delrin plastic at 45 degree
angles and 36 degrees center to center. The holes were drilled so that they would converge at a sharp
point in the center of the piece. The purpose of the sharp point was to remove a potential settling surface
for any larger particles that may settle out of the runoff. The exterior bottom section was angled at
approximately 45 degrees. A plexiglass support was constructed for the flow splitter so that the splitter
was high enough to allow the runoff to flow down the tubes at a 45-degree angle from the base of the
splitter. This 45-degree angle was assumed to be sufficient to prevent particle deposition on the insides of
the tubes, even during low flow conditions.
In order to address the concern about leaching from the construction materials, all construction materials
were leach-tested by soaking them in approximately 400 mL of 18 MQ water for about 65 hours. The
water was then tested for toxicity, turbidity, pH, conductivity, color, organics, pesticides, and heavy
metals. Results of these tests showed that the use of the Delrin Plastic, Plexiglas, Black Plastic Fittings,
and Reinforced PVC Tubing on the sections of the apparatus that came into contact with the stormwater
runoff would be acceptable. The fiberglass window screen was found to be toxic to the Microtox™
luminescent bacteria when the screen was left to soak overnight. However, occasional rinsing of the
screen did not add toxicity to the water.
The filtration media used in this project included the following: sand, activated carbon, peat moss, zeolite,
compost, ENRETECH I, Forest Product agrofiber, Gunderboom filter fabric, and EMCONtilter fabric.
Because of the variability in the hydraulic conductivities and contact times of the adsorbent media alone,
sand was mixed with all media (approximately half and half by volume), except the fabrics, before the
mixed media was added to the filtration columns. In order to get a better "distribution" or "mixing" of media
for the Enretech and Forest Products material, these materials were broken apart by hand (unclumped for
the Enretech and torn apart for the Forest Products material) into small pieces.
41
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The sand was purchased from Porter Warner Industries in Birmingham, AL, the supplier of sand for the
wastewater treatment plants operated by Jefferson County, AL. The type of sand selected was the type
that was closest in size distribution to that used in the Cahaba River Wastewater Treatment Plant in
Hoover, AL. The sand used in these tests had a uniformity coefficient of approximately 1.45, with d10 =
0.31 mm and d^ = 0.45 mm. The ratio of column diameter to median filter grain particle size for the sand
filter (the media used to determine filter height and column diameter) was greater than 100 which,
according to other researchers, should be sufficient to avoid significant wall effects and to get the
Reynolds number for flow through the filter to be greater than 20 (Clark, et al. 1992).
The activated carbon and zeolite were purchased from Aquatic Eco-Systems, Apopka, FL. The peat moss
was a sphagnum moss sold by K-Mart in their garden supply area. The compost was a municipal leaf
compost supplied by CSF Systems, Inc., in Portland, OR. According to CSF Systems, the compost was
generated from only certain types of leaves in order to achieve the maximum adsorption capacity and,
therefore, maximum pollutant removal from the stormwater of Portland, OR (John Knudsen, personal
communication 1994). However, visual inspection of the compost received from them revealed pieces of
glass, indicating that the selection process for the compost generated in mass quantities is not as
particular as it was for the prototype devices. Because this compost is different 'than that used in the
prototype, pollutant removal efficiencies likely are different than that described in the literature review.
When selecting the compost to be used in the filter, no large pieces of twigs or glass were chosen.
The ENRETECH I material, supplied by RAM Services, Inc., Birmingham, AL, is a cellulose waste fiber
from cotton milling with the consistency of blown-in fiberglass or mineral wool insulation. It was developed
for cleaning up oil spills. The Forest Product was an agrofiber made from kenaf that is sandwiched
between two fabric layers that have the texture of cobwebs. It was designed and is still being optimized
for use in removing pollutants from water, especially stormwater. The Gunderboom was a filter fabric
supplied by Amoco for use in oil spill cleanup. The EMCON fabric was supplied by Emcon North West
(Bothell, WA) and is now sold by Foss Environmental Services Company (Seattle, WA). These two filter
fabrics were selected from many that were tested for particle removal capability by particle size
distribution analysis of their effluents. The Gunderboom was also selected because it is currently being
used in the Multi-Chambered Treatment Train (MCTT) as described in the first volume of this research
series (Pitt, et al. 1999).
Figure 3-3. Columns on Carousel
42
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A peristaltic pump (from Cole Farmer Instruments) with Masterflex tubing was used to pump the sample
either from a 200 L Nalgene drum (for the unpretreated runoff tests and bench-scale tests) or from the
settling chamber of the MCTT (presettled runoff) to the splitting funnel where it was split into ten equal
portfons and dispensed to the ten columns on the carousel. Both grab samples and a composite sample
were collected of the effluent samples from filtering unpretreated runoff. Grab samples were collected in
clean 500 ml_ HOPE bottles that were pre-rinsed with distilled water. The composite samples were
collected in Nalgene-brand, eight-liter polypropylene jugs (from Curtin Matheson Scientific). Grab samples
from the bench-scale testing effluents were collected in clean 500 ml_ amber glass jars that were pre-
rinsed with distilled water. Effluent samples from filtering presettled runoff in the MCTT were collected in
clean, Nalgene-brand, eight-liter polypropylene jugs that were pre-rinsed with distilled water. After
collection, the composite samples were immediately split into unfiltered and filtered fractions by filtering a
portion of the well-mixed sample through 0.45 u.m nominal pore size gel membrane filters (Gelman
Metricel filters from Fisher Scientific). The sample portions, both filtered and unfiltered fractions, to be
used in metals analysis were immediately preserved with 6 M nitric acid to a sample pH of less than 2. All
other portions were then refrigerated at 4°C until analysis.
Collection of Stormwater Runoff
For all filtration tests, Stormwater runoff had to be collected. For the preliminary investigations on the sand
filter, the runoff used was a composite of runoff received from Stafford Township, NJ. The unpretreated
runoff was a composite of runoffs collected from Stafford Township, NJ, the UAB Remote Parking Lot, the
Ruby Avenue Public Works Garage in Milwaukee, WI, and a metal roof in Wilsonville, AL. Sheetflow
runoff was collected in the settling chamber of the MCTT at UAB Fleet Services Operation and Remote
Parking Lot at the corner of 8th Street South and 7lh Avenue South, Birmingham, AL. Runoff from this
location was used both for the bench-scale testing and for filtering the presettled runoff. The location on
the UAB campus was chosen for two reasons: (1) it was believed to be a critical source area (large
paved area with heavy traffic and where vehicle maintenance is performed), and (2) security for the
collection devices was acceptable because a ten-foot chain length fence with razor wire surrounded the
lot and security personnel patrolled the area when occupied.
For the testing with the presettled runoff, the filtering column apparatus was moved beside the MCTT and
settled runoff was pumped using the peristaltic pump with Masterflex tubing directly from the settling
chamber into the flow splitter. For the bench-scale tests, well-mixed runoff was siphoned into two types of
collection vessels. One type was the 8 L Nalgene HOPE jug; the other was a 10 L semi-rigid,
polyethylene cubitainer (from Fisher Scientific). Approximately 750 liters of runoff was removed from the
settling chamber, put into these containers and transported to the lab where it was split into five
homogeneous sections, one section for each of the bench-scale runs. When the filter column apparatus
was not in use and out in the field, the carousel was covered with a plastic tarpaulin to keep out bugs, bird
feces, and anything else that potentially could end up in one or more columns and contaminate the
influent to only one column.
Filter media columns were reconstructed after every series of tests, such as between the initial sediment
solids loading experiment and the testing on unpresettled runoff, between the unpresettled runoff testing
and the bench-scale testing, and between the bench-scale tests and the field testing with presettled
runoff. New columns were also constructed for each of the bench-scale tests.
Laboratory Procedures
The laboratory techniques used in this series of experiments were based upon either Standard Methods
for Water and Wastewater (APHA 1992) or on EPA-Approved Methods, and they are described in the
Quality Assurance Project Plan approved by U.S. EPA for this project (Farmer and Pitt 1995). Some
modifications of these methods were required in order to have more effective analyses of the Stormwater
pollutants. Quality assurance/quality control samples were collected and analyzed in accordance with the
laboratory's approved QAPP document. Table 17 lists the chemical analyses that were conducted for
each test series.
43
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Clogging
Unpretreated
runoff
Neutral pH. salt
Low pH. no salt
High pH, no salt
Low pH. salt
Htqh pH. salt
PreSettled'
Toxicity
X
X
X
X
X
X
X
Physical
Character1
X
X
X
X
X
X
X
Hardness
X
X
X
X
X
X
X
Solid & PSD
X
X
X
X
X
X
X
X
COD
X
X
X
X
X
X
X
Anion &
Cation
X
X
SVOCs &
Pesticides
X
X
Heavy
Metals
X
X
X
X
X
X
X
1. Turbidity, Conductivity, Color, pH.
2, Runoff: composite from NJ, Wl, AL (not allowed to settle before filtration).
3. Runoff: settling chamber of MCTT (allowed to presettle for minimum of three days).
PSD: Particle Size Distribution (4 to 128 \un for bench-scale tests; 1 to 128 urn for long-term performance testing)
SVOC: Semi Volatile Organic Compounds
Initial Test Procedure for the Sand Column
This phase of testing was designed to measure the water retention and characterize the pollutant removal
capability of a filter. These results were the determining factor for expanding this project to include
evaluation of other media. A sand column was constructed as described above, and water retention
testing was done on the new column. Water retention was measured by pouring a specific volume of
water through the column (300 mL) and allowing the column to drain overnight. The difference between
the influent and effluent volumes of water is the water retention in the column. Next, stormwater runoff
from one of the three Stafford Township, NJ, sites was slowly passed through the filter in 100 mL
increments. A 40-mL grab sample was collected of the effluent from each of these increments and
analyzed for toxicity, turbidity, and conductivity.
When the results of these tests did not agree with Austin results for their sand filters, the possibility of a
lack of permanent retention of pollutants in the filter was investigated by performing mass balance
analyses on the column. A calibration curve was created for a sodium chloride solution, where
concentration was plotted against conductivity. A solution containing a concentration of 4 g/L NaCI (from
Fisher Scientific) was made (800 mg NaCI in 200 mL 18 MQ. water) and filtered through a previously
wetted column and the conductivity of the effluent was measured. Then 200 ml. increments of 18 MQ
water were filtered through the column. The conductivity of the incremental effluents was then measured
with the incremental flushing of the filter continuing until the conductivity of the solution was below the
detection limit of the conductivity meter (10 u,S/cm).
Procedure for Determining the Effects of Sediment Accumulation on Filter Flow
Rate
The purpose of these tests was to determine the quantity of solids that could be loaded on the filtration
media before flow became 'negligible.' The first phase involved the filter fabrics, along with a sand, an
activated carbon, a peat moss, and a sand-peat-mix column, and used the cumulative volume occupied
by particles and their size distribution for both the influent and effluent to measure the fabrics' ability to
remove solids. This test used runoff composited from several storms at three locations in Stafford
Township, NJ.
The second phase was designed to determine cumulative suspended solids loading on the media. A
solution of tap water and a local, red clayey soil was used as the filter media influent. This clay-water
solution was pumped using the peristaltic pump with Masterflex tubing until the flow 'stopped.' The total
solids loading needed to cause clogging was determined from the known concentration and cumulative
flow into each column. Next, the depth of red clay penetration into the column was measured visually.
44
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Results from the other experiments, including the bench-scale and both the unpretreated and presettled
runoff tests, also were used to determine suspended solids' accumulation on the surface and penetration
into the media. Both the benctvscale tests and the tests that used unpretreated runoff had significantly
higher influent suspended solids concentrations than the presettled runoff, and physical clogging occurred
before chemical breakthrough. For all tests, suspended solids concentrations were measured both for the
influent and effluent with the solids accumulation on the media being equal to the difference between the
influent and effluent suspended solids concentrations multiplied by the volume of water that passed
through the media. When the media's filtration loading rate slowed to less than 5 meters per day (m3
runoff water/m2 filter surface area), maintenance was done on the surface of the filter. This maintenance
generally included breaking up any mats on the top of and in the top 2 centimeters of the media. In
general, disturbance of the top of the media temporarily improved filtration loading rates to more than 5
m/day (but still less than 10 m/day), but disturbance was required after each aliquot of water had been
added. When breaking up mats was no longer effective, the maintenance activity of removing the top 1 to
2 centimeters of filter media began. Removal of the top of the media column significantly improved flows
(to approximately 10 m/day) temporarily. Visible cakes of solids (approximately 5 mm thick) were also
removed from the top of the compost-sand column for the 'low pH, high ionic strength' run and from the
top of both the peat-sand and compost-sand columns of the 'high pH, high ionic strength' run when the
columns were rebuilt prior to the next run. In spite of the above described maintenance, the peat-sand
column clogged during the 'neutral pH, high ionic strength' and the 'high pH, high ionic strength' runs, and
the compost-sand clogged during the 'low pH, high ionic strength' and 'high pH, high ionic strength' runs.
These columns had to be pulled out of service prior to the completion of the run, with the exception of the
peat-sand column in the 'high pH, high ionic strength' run which clogged at the scheduled end of the test.
The 'unpretreated runoff tests used water that was a composite of runoff from six locations: UAB Remote
Transportation Parking Lot, UAB Lot 15 Student Parking Lot in front of the Engineering Building, Ruby
Avenue Public Works Garage, and three sites in Stafford Township, NJ. During filtration, the influent
water to the columns was stirred regularly to ensure that very few solids could settle out on the bottom.
Significant reductions in flow rate were observed after 5.5 m3 of runoff per m2 of filter area had been
filtered.
The 'presettled runoff tests used water that had been collected in the settling chamber of the MCTT at
least three days prior to the test date. The settling chamber of the MCTT is approximately 1.2 m deep and
contains Lamella plates to a height of 0.6 m from the bottom of the chamber. The purpose of the lamella
plates is to assist in settling so that after three days, very few particles larger than colloidal size remain in
the runoff near the top of the chamber. Because the suspended solids in the presettled water were
colloidal, retention of solids was not observed for any of the media even after the fifth storm event
although the significant decreases in flow rates indicated physical retention of solids.
Procedure for Bench-Scale Testing (Effects of pH and Ionic Strength on Pollutant
Removal)
The bench-scale tests were designed to determine the effects of pH and ionic strength on the ability of
the filter media to capture and retain pollutants because other researchers have shown that, for some of
the media of interest, pH and ionic strength can significantly influence the ability of an adsorbent both to
sorb and to permanently retain pollutants. A series of five experiments, using a full 22 factorial (with a
midpoint) experimental design, was used to quantify the effect of pH and ionic strength on the removal
efficiency and permanent retention ability of the various media of interest (activated carbon, peat, zeolite,
compost, ENRETECH, sand). An empty glass column was used as the "blank" or "control." The filter
fabrics were not tested as part of this phase since it was assumed that their removal efficiencies for
dissolved pollutants would be poor under ideal conditions. The filter fabrics were tested in the field only in
order to confirm this assumption. Approximately 600 liters of runoff was collected from the settling
chamber of the MCTT after the water had been stirred up to resuspend any solids and transported back
to the laboratory where it was split into five equal portions. The portions that were waiting to be used were
stored either in 8-L Nalgene jugs or 10-L polyethylene cubitainers.
45
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Immediately prior to each bench-scale run, one portion of the stored runoff was poured into the two-
hundred liter Nalgene drum, and the pH and ionic strength were adjusted as necessary. Either
concentrated sulfuric acid or sodium hydroxide pellets were used to adjust the pH of the runoff in the
desired direction. Dried seawater salt was used to adjust the ionic strength (Aquarium Seawater Salt,
from An Urban Jungle, Hoover, AL). The portions were adjusted according to the following scheme:
• low pH, low ionic strength
• low pH, high ionic strength
• high pH, low ionic strength
• high pH, high ionic strength
• neutral pH, high ionic strength
Prior to adjustment, the runoff had a natural pH of about 7 and a specific conductivity of several hundred
fiS/cm. The pH values were adjusted with sulfuric acid to about 5 (low pH), with sodium hydroxide to
about pH 9 (high pH), and no pH adjustment was done for the neutral pH sample. The low ionic strength
was unadjusted runoff (200-400 u,S/cm), while the medium and high ionic strength solutions were
prepared using the evaporated seawater salt. The high ionic strength portions had a conductivity of
approximately 10,000 jiS/cm. The 'midpoint' portion had a pH of approximately 7 and a conductivity of
about 8,000 u,S/cm. The filter fabrics were not tested in this phase.
After any adjustments were made to pH and ionic strength, an initial grab sample was made of the well-
mixed influent. Six grab samples of influent and effluent from all columns were also captured periodically
during each filter run. The first grab was collected after 1/6 of the portion had been filtered, the second
after 1/3 (2/6) of the portion had been filtered, etc. At the end of each bench-scale run and after the filters
had been allowed to drain (dry) for at least 24 hours, one liter of distilled water was passed through each
column to see if future washings would desorb (dislodge) any pollutants. In addition to the analyses listed
in Table 17, color adsorption over a continuous range from the ultraviolet to the visible light wavelengths
was measured. Additionally, flow rate and cumulative water volume passing through the filter were noted.
Procedure for Long-Term Filtration Performance Testing
Long-term performance information is crucial in designing filters for any application because it determines
the required maintenance schedule. One criterion for a good stormwater filter will be the lack of regular
maintenance. The long-term performance of these filters was measured in two separate sets of
experiments. The first set used composite runoff that had not been presettled. At that time, the media
being investigated included sand, activated carbon, peat moss, zeolite, Enretech, compost, and three
filter fabrics (ADS 4420, Gunderboom, and EMCON). An empty glass column was included as the "blank"
or "control." The activated carbon, peat moss, and zeolite columns contained the 50/50 mixture of
adsorbent and sand. The compost and the Enretech were not combined with sand since their
manufacturers indicated that they should be used as supplied. Five storm events of composited runoff
were treated by the media. During each storm event, two grab samples of effluent were collected (after
approximately 25% and 50% of the potential influent had been filtered). In addition to the grab samples, a
composite effluent was collected from each column. The grab samples were analyzed for toxicity,
turbidity, conductivity, pH, color, chemical oxygen demand, hardness, and particle size distribution (4 to
128 jim range). The composite samples were analyzed for the parameters shown in Table 17.
The in-situ tests were designed to evaluate the long-term removal efficiency for the filter media under
conditions similar to that which would be encountered by the filtration media in the MCTT, i.e., the
filtration influent was runoff that was allowed to presettle for at least three days. All columns were rebuilt
prior to the beginning of this series of tests. Because of its poor performance, one of the filter fabrics, the
ADS 4420, was deleted from the design prior to the start of this run, and an additional filter media, the
Forest Products Laboratory agrofiber, was added to. the list of media to be evaluated. Also, because of
the hydraulic problems of the Enretech (compression of media reduced flow significantly) and the
compost (flow through media significantly smaller than other media and smaller than desired for the
46
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planned application), these media (and the agrofiber, which was expected to act like the Enretech) were
mixed with sand in a 50/50 (v/v) mixture, prior to column construction.
Sheetflow samples from the UAB Remote Parking area were collected in the settling chamber of the
MCTT and allowed to settle for at least three days before filtration occurred. The columns were not
cleaned out and rebuilt between the storm events in order to examine pollutant removal and retention
under typical, long-term usage. Presettled runoff also was used because this series of tests was designed
to evaluate chemical breakthrough, and the bench-scale tests had shown that physical clogging occurred
well before chemical breakthrough when the runoff was not presettled, i.e., chemical adsorption capacity
was not completely exhausted before the filter columns clogged. Composite effluents from each filter for
each storm event were collected in 8 liter Nalgene HOPE jugs. The composites were then taken back to
the laboratory and split into filtered and unfiltered fractions. In addition to the analyses given in Table 17,
color adsorption over a continuous range from ultraviolet to visible wavelengths was measured.
47
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Chapter 4
Results and Discussion
Several sets of tests were performed on the filter media and the results of these tests are included in this
chapter. The experiments performed include the following:
• Water retention in column
• Mass balance experiments for pollutant flushing
• Sediment clogging
• Bench-scale tests to measure the effect of pH and ionic strength on effluent
• Long-term treatment performance (for both unsettled and presettlecl runoff)
Initial Test Procedure for the Sand Column
The first test performed on the sand column was a water retention test to determine the volume of water
that was retained in the pores of the filter matrix after gravity drainage. This was important in order to
evaluate potential carry-over from one filter test to another and, in field use, potential carry-over from one
storm event to another. It was determined that approximately 50 ml_ of water was retained in the column
for every 820 cm3 of sand (the volume of sand in a column with inner diameter of 2.4 cm and height of
45.7 cm).
Further tests using saline solutions were conducted to verify the flushing of the retained water held in the
column between tests. The results of the mass balance experiment with the 4 g/L NaCI solution are given
in Table 18. These tests showed that the salt water displaced any 'clean' water that was already held in
the sand column pore matrix after a single flush. Recovery of the influent salt was 92%. The 8% loss of
salt is likely due to one of two possibilities. First, some of the salt reacted with a potential coating on the
sand and is 'permanently retained' on the sand. It is unlikely, however, that a significant amount of salt
was sorbed onto the sand since this was a new column that contained sand that had not been pretreated
to add an adsorptive coating and that had not been allowed to age. The second and more probable
explanation is that the detection limit of the conductivity meter was such that accurate measurements of
the salt concentration of the standard solution could not be made when the meter read less than 10-30
|iS/cm. Readings in this range were assumed to contain less than 1 mg of salt.
Table 18. Mass balance data
Salt water influent
18 MO water flush
18 MO water flush
18 MO water flush
18 MO water flush
Influent Conductivity
(uS/cm)
6500
0
0
0
0
Effluent Conductivity
(uS/cm)
2900
2100
30
30
19
Mas;; salt in
(mg)
800
0
0
0
0
Mass salt out
(mg)
413
324
<1
<1
<1
The salt water Influent volume was 200 mL and the flush water volume was 250 mL
This initial trapping and subsequent displacement (flushing) was further documented with the filtration of
stormwater runoff from Stafford Township, NJ. During filtration of the runoff, the column removed those
materials that were causing the water to be toxic to the Microtox™ test luminescent bacteria (measured
as percent reduction in luminosity, which is linked to the test organism's respiration). Subsequent filtration
of five aliquots of 18 MQ. water, which is not toxic to the luminescent bacteria, had effluent toxicities less
than the stormwater influent but that were still toxic (in the low to moderately toxic range). This indicated
that the clean water was displacing the trapped toxicants from the pores and resuspending them in the
48
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effluent. The results of these tests are given in Table 19, where 125% denotes a specific reduction in
bacterial luminosity during the Microtox™ test after 25 minutes of organism exposure to the sample.
Three of the later runs of 18 MQ water through the column had a greater toxicity than the previous run,
indicating potential desorption of toxicant from the sand itself.
Table 19. Stormwater runoff filtration in sand columns, measured as toxicity by Microtox™
NJ runoff
1 8 MO water
1 8 MO water
1 8 MQ water
18 MQ water
1 8 MCI water
Influent (I25 % reduction)
99
0
0
0
0
0
Effluent (I25 % reduction)
22
32
27
37
5
28
Based on the Austin stormwater results (Austin, 1988), it had been expected that the sand column would
retain any particles that it trapped. However, as the data in Table 19 demonstrates, sand by itself did not
retain stormwater toxicants (which are mostly associated with very fine particles), but mostly exchanged
(flushed) older retained solutions and fine particulates for newer solutions passing through the column.
This lack of ability to retain stormwater toxicants prompted the investigation of other filtration media during
this research project. Combinations of filtration media, especially those with a known adsorbent capability
such as activated carbon, peat moss, composted leaves, and ion exchange resins, along with sand, were
then selected for future testing.
Water retention and hydraulic capacities of the newly chosen media were then tested. The results of
these tests showed that water flowed through the activated carbon and zeolite very quickly, which
indicated that providing adequate contact time would be a problem. Testing of the peat and compost
showed that these media had very slow flow rates and had the potential to compact, which would further
decrease their hydraulic conductivities. In order to address these problems, sand was added to the
adsorbent media (activated carbon, zeolite, compost, peat moss, Enretech, and agrofiber) in a 50/50
mixture by volume. This slowed the water in the 'fast' activated carbon and zeolite columns and slowed
the compression of the other media. Mixing peat and compost with sand allowed channels for water flow
and still provided good contact with the media, while preventing the loss of flow capacity due to
compression of the media. The newly constructed columns, containing the 50/50 mixture, had more
uniform hydraulic conductivities at the start of the tests. Modification of the filter fabrics (whiqh are not
considered media for the following discussions) was not performed before any of the testing.
Effects of Sediment Accumulation on Flow Rates of Different Filters
The first phase of this project involved comparing the particulate removal efficiencies of eight filter fabrics
and seven filtration media. This was done by comparing the influent and effluent particle size distributions
over the range of 4 to 128 jim for each fabric and media. A Coulter Multisizer He was used to measure the
particle size distributions, and all comparisons were made using the count data (number of particles in
each size range). The influent for each medium was a composite of stormwater runoff received from
Stafford Township, NJ. The results of the particle size distribution analysis over the range of 6 to 41 urn
(which contained 99% of the particles in the influent) are given in Table 20.
Based upon these test results, the filter fabrics and filtration media were divided into four performance
classes:
A: Greater than 75% removal for all size ranges
B: Greater than 75% removal of larger particles only (>20 p,m)
C: Moderate removal (10 to 50%) for all particle sizes
D: Very low removal for all particle sizes
49
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Table 20. Participate removal efficiencies
Particle size (f.lm):
Influent distribution (% by count)
6-7
'77
>7-10
18
>10-15
3.1
>15-20
1.0
>20-25
0.4
>25-30
0.2
>30-35
0.1
>35-40
0.04
Overall
Removal (%)
N/A
Fabric removal efficiencies (%) by size
HolchsM125
Holchst1120
HolchSt1135
EMCON
Exxon
ADS 4000
ADS 4420
Gunderboom
82
9
0
28
29
0
0
75
80
11
0
44
49
0
0
74
70
16
0
59
48
0
13
79
74
27
28
90
81
0
0
93
13
63
0
100
60
0
0
91
50
40
0
100
100
N/A
0
100
71
N/A
0
100
100
0
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0
N/A
100
78
9
0
37
36
0
3
70
Filtration media removal efficiencies (%) by size
Sand
Carbon
Compost Leaf
Peat
Soil*
93
93
0
31
95
92
94
53
69
92
88
98
29
79
94
94
80
0
73
100
N/A
100
25
93
100
N/A
N/A
N/A
N/A
N/A
N/A
100
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
93
93
16
47
94
1 Compost Leaf in these tests was a local composting leaf mixture (leaves still visible), not the medium sold by CSF Systems, Inc.
These results are not directly applicable to the mixture supplied by Stormwater Management, Inc. (formerly CSF Systems, Inc.).
* Soil is a local (Birmingham, AL area) soil collected near DAB. The soil column was constructed in a similar manner to the other
columns (not taken and used as a soil core).
N/A: Individual influent-effluent pairs were collected for each medium or fabric (approximate influent distribution, based on a single
sample, Is shown in the top row) and N/A indicates that, for that medium or fabric, no particles in the given size range were found in
the influent.
Table 21 classifies the fabrics and media according to the above categories. The table also provides a
descriptor of the flow rate through the medium, any comments related to the flow through the medium,
and an estimate of the clogging potential of each filter. The clogging potential was defined as the
maximum suspended solids load, in kilogram per square meter of filter area, that could be loaded on the
medium before excessive head loss occurred.
Once the additional filter media had been selected, new columns were constructed, and the water
retention characteristics and flow rate of each medium were determined. The flow rate tests provided a
ranking, from highest to lowest, of the media: sand > zeolite-sand » composted leaves > "carbon-sand >
compost-sand > peat-sand > Enretech-sand > Agrofiber-sand. The filter fabrics selected for further
testing, ADS 4420, Gunderboom, and EMCON, had significantly higher flow rates than any of the media.
Table 21. Performance classification for filter fabrics and media
Category A
High efficiency
(6 to 41 urn)
Category B
High efficiency
(>20nm)
Category C
Mod. Efficiency
(6 to 41 urn)
Category D
Poor efficiency
(6 to 41 urn)
Fabric/Media
Holchst1125
Gunderboom
Sand
Carbon
Soil
EMCON
Exxon
Peat
Holchst1120
Comp. Leaf
Holchst1135
ADS 4000
ADS 4420
Flow Rate
Fast
Slow
Fast
Very Fast
Slow
Fast
Very Slow
Slow
Fast
Very Fast
Fast
Fast
Fast
Clogging Potential
3 kg/m2
0.5 kg/m2
0.2 kg/m2
2 kg/m2
Comments
5+ cm of head needed for
flow
1 0+ cm of head needed for
flow
1 Comp. Leaf in this table refers to a local composting leaf mixture (leaves still visible), not the filter media sold by CSF Systems,
Inc. These results are not directly applied to the medium sold by Stormwater Management, Inc. (formerly CSF Systems, Inc.).
50
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Once the flow rate testing was complete, additional clogging tests were conducted. The solution used for
the clogging tests was a clay mixed in water (approximately 6 g/L). The red clay was selected because it
would be visible in the column even in areas where the concentration was low, thus allowing visual depth
of penetration measurements to be taken. The results of these tests are given in Table 22. Once the
clogging tests were completed, the selection of media was re-evaluated, and it was decided to substitute
the CSF compost (a pre-prepared media for which pollutant removal information was available) for the
local composting leaf mixture, as well as remove the soil from consideration as a viable filtration medium.
Table 22. Clogging results for initial media
Filtration media
Sand
Composted leaf*
Peat
Soil
Peat-sand
Maximum suspended solids
loading at clogging (g/m2)
4000
2100
200
630
1700
Avg. penetration depth at
clogging (cm)
3.8
5.1
0.6
0.3
2.5
Penetration into column (%
of media depth)
13
17
2
1
10
Composted leaf in this table refers to a local composting leaf mixture, not to the filter media sold by CSF Systems, Inc.
The clogging tests were then performed on the newly selected media and media-sand combinations. The
results of the new clogging tests are given in Table 23. Visual observation of the red clay penetration into
the filter media showed the development of channels that the clayey water flowed through, thus allowing it
to penetrate further into the filter medium, yet also allowing it to avoid interacting with the top few
centimeters of the media. Penetration is beneficial in that it allows for more of the filter depth to be used
for treatment; however, bypassing of the media could become a problem for shallow filters.
Graphs showing the effect of suspended solids' loading on flow rate for each medium which was used in
the bench-scale testing as well as the in-situ tests (carbon-sand, compost-sand, Enretech-sand, peat-
sand, sand, and zeolite-sand) are in Appendix A. This effect of suspended solids' loading on the flow rate
through sand is demonstrated in Figure 4-1. As seen in the figure, even a very small suspended solids
loading caused a dramatic and rapid reduction in the water flow rate through the column. However, this
rapid reduction in flow capacity does not hold true once the flow is decreased to about 20 m/day. At that
point, the curve becomes nearly flat, and filtration will continue for three-to-four times as long as the time
required to reduce the flow rate to about 20 m/day.
Table 23. Clogging test results for newly selected media
Filtration media
Sand
Peat-sand
Carbon-sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
EMCON
Gunderboom
Range of suspended solids
loading at clogging (g/m2)
1200-4000'"
200-1700'"
500->2000
1200->2000
350-800
400-1500
75-300
3800
3800
Avg. penetration depth at
clogging (cm)
3.8
2.5
3.8
5.0
2.5
2.5
2.5
0.1-0.2'°'
0.1-0.2""
Penetration depth as % of
filter depth
9
5
9
11
5
5
5
N/A
N/A
(a) Results from characterization of each initial media; tests not rerun.
(b) This is the height of the solids cake that formed on the top of the filter fabric, not a penetration depth into the fabric.
Table 24 gives filtration capacity as a function of suspended solids' loading. This information is important
because the maintenance requirements of the filters are based on the predicted life of the filter, which is
dependent upon both the influent suspended solids' concentration and the amount of solids that have
already accumulated on top of the filter. The wide range in filter loading capacity to reach a pre-selected
'undesirable' flow rate results from the variety of suspended solids' concentrations and particle size
distributions in the influents of the runs that were used to create Table 23.
51
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Table 24. Treatment capacity as related to suspended solids loading
Media
Sand
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Loading to 20 m/day (g/m2)
150-450
150-900
100-300
200-700
100-700
75-300
Loading to 1 0 m/day (g/m2)
400->2000
200-1100
150-1000
800-1500
200-750 -
125-350
Loading to <1 m/day (g/m2)
1200-4000
500->2000
200-1700
1200->2000
350-800
400-1500
* Forest-sand (Agrofiber-sand) was not tested for clogging; however, its behavior is expected to be similar to the behavior of
Enretech-sand, since both media are fibrous. This assumption of similarity in flow rates was found to be true in future testing (long-
term performance testing).
200
—o-~ PreSettled
—«—• Neutral pH, Salt
mm£a*m |_OW pH, NO Salt
» High pH, No Salt
O Low pH, Salt
• High pH, Salt
0 200 400 600 800 1000 1200 1400 1600
Suspended Solids Loading on Media (g/m2)
Figure 4-1. Flow rate vs. suspended solids loading on sand
Effects of pH and Ionic Strength on Pollutant Removal
The literature search indicated potential problems with filtration and sorption when the influent is not near
neutral pH or has a high ionic strength. In order to investigate these possible effects, a series of five
controlled laboratory experiments comprising a full-factorial experiment (including an intermediate
position) was conducted. The full factorial experiment consisted of testing combinations of low and high
Influent pH and ionic strengths for newly constructed columns (low pH and low ionic strength; low pH and
52
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high ionic strength; high pH and low ionic strength; high pH and high ionic strength).- By testing these
factors in the combinations, it could be determined if a factor or the combination of the factors affected the
removal capability, while performing a minimum number of tests. Testing of the midpoint was performed
(pH = 7; conductivity = 7500 u.S/cm) in order to mimic snowmelt runoff. The influent pH and conductivities
for the bench-scale tests are in Table 25.
Table 25. Influent characteristics for bench scale tests
Neutral pH, moderate salt
Low pH, no salt
High pH, no salt
Low pH, high salt
High pH, high salt
PH
6.88 - 7.05
4.80-5.18
9.46-10.00
4.50 - 5.41
9.50-10.96
Conductivity (U,S/cm2)
7800 - 8500
290-318
200-210
8900 - 9050
7500 - 7900
The test water was collected from the settling chamber of the MCTT. The pH of the influent was adjusted
using either reagent grade sulfuric acid (from Fisher Scientific) or reagent grade sodium hydroxide (from
Fisher Scientific). The salt content of the influent was adjusted using a sea water salt sold locally for use
in saltwater aquariums. The filter media used in these tests included carbon-sand, peat-sand, zeolite-
sand, compost-sand, Enretech-sand, and sand, as well as an empty glass column used as a 'blank' to
collect a sample of the influent reaching each filter.
During each run, six 500-mL grab samples were collected of the effluent from each column. These grab
samples were not split into filtered and unfiltered fractions. The samples were collected after about 3.5,
6.5, 9.5, 12.5, 16 and 21 L of sample had passed through each column. This corresponds to hydraulic
loadings on the columns of 1.9, 3.6, 5.2, 6.9, 8.8, 11.6m (m3 water/m2 filter area). At least one day after
the run was complete, each column was rinsed with one liter of distilled water. This effluent was collected
and analyzed to determine what, if any, toxicants were flushed out of the media in the presence of a
relatively aggressive water. Each sample was analyzed fortoxicity, turbidity, color, pH, chemical oxygen
demand (COD), UV-visible light adsorption, hardness, suspended solids, particle size distribution, and
heavy metals (cadmium, copper, lead, and zinc).
Clogging Observations
Near the end of each run, all the filters had significantly reduced flow rates. Several filters clogged
completely before the tests were completed. The peat-sand column clogged during the 'neutral pH,
moderate ionic strength' run after a hydraulic loading of approximately 7 m. The compost-sand column
clogged during both the 'high ionic strength runs.' This clogging occurred after a hydraulic loading of
approximately 7 m in the 'high pH' run and after 12m during the 'low pH' run. The effects of the
suspended solids loading on the flow rate in each medium during each run are incorporated into the
graphs in Appendix A.
Analysis Results
Tables containing the laboratory analysis results for the various parameters analyzed in the bench-scale
tests are in Appendix B, as are the graphical representations of the results. Statistical analysis of this data
was performed by two independent methods. A one-tailed Wilcoxon sign-rank analysis (procedure
described in Lehmann, 1975) was used to test the hypothesis that filtration would not significantly change
the influent concentration for the parameter of interest. P values less than 0.10 are considered significant
and lead to the conclusion that filtration significantly affected the concentration of a given parameter. The
Wilcoxon sign-rank analysis was selected because it is a nonparametric, paired-sample test, i.e., no
underlying distribution of the data is assumed. It has not been demonstrated that stormwater runoff or
filter effluent samples follow a specific statistical distribution such as the normal or log-normal distributions
and therefore, a nonparametric test was required. If a distribution had been assumed for the data, then
other tests of paired samples could have been used, and more statistically significant results likely would
have been found. The weakness of this test as it was run is that the P values do not indicate whether the
significant changes that occurred during filtration were a reduction or an increase in a parameter's
53
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concentration. The tables in each of the following subsections contain the P-values from the Wilcoxon
sign-rank analysis for each parameter. P values for significant reductions are given in italics to distinguish
them from significant increases in concentrations or inconsistent removals.
The second statistical test performed was a factorial analysis for the four bench-scale tests where both
pH and ionic strength were modified. This allowed the effects of influent pH, influent ionic strength and the
combination of the two factors to be evaluated in only four test runs. The midpoint (pH 7, ionic strength
7500 nS/cm) was also tested to mimic snowmelt runoff conditions. The detailed procedure for performing
the factorial analysis is given by Berthouex and Brown (1994) and for interpreting the results is given in
Box, Hunter and Hunter (1978). In general, pH, ionic strength, or the interaction of the two was
considered significant when the calculated effect for each influence was greater than three times the
group standard error. Factorial analysis was performed on two sets of results for each parameter: the
effluent concentrations, and the removal efficiency, measured as percent decrease, in a constituent due
to filtration. The tables of contrast for each of the analyses are also located in Appendix B.
Toxicity
The Wilcoxon sign-rank analysis P values for toxicity are given in Table 26. These results showed that
none of the media were capable of reducing the toxicity of the influent under all conditions of pH and ionic
strength although the compost was effective under all conditions except high pH and high ionic strength
and the only medium capable of significant removal of toxicity at the midpoint conditions (influent: pH 7,
ionic strength 7500 nS/cm).
One possible explanation for why no single medium was capable of reducing toxicity under all conditions
likely is directly related to the test organisms used in the Microtox™. The luminescent bacteria,
Photobacterium phosphoreum, are a marine bacteria and therefore require a salt water environment to
live. Previous research by Ayyoubi (1993) with the Microtox™ proved that there was a wide range of salt
concentrations at which these test bacteria performed at their optimum. However, there is an upper limit
after which the bacteria cannot survive, and the effluent samples from the high ionic strength tests likely
exceeded that upper limit. Like most organisms, these bacteria also have a narrow pH range at which
they live. For most of the runs where there was no significant reduction in toxicity during filtration, it is
likely that since the influent pH was outside of this range, the effluent pH was also outside the tolerable
range for P. phosphoreum because most of the media did not significantly move the pH toward neutral.
Table 26. Wilcoxon P values for toxicity*
Filtration
Media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. Salt
0.25
0.56
0.13
0.06
0.69
0.31
Low pH, no
salt
0.03
0.03
0.13
0.03
0.41
0.08
High pH,
no salt
0.02
0.02
0.28
0.02
0.42
0.69
Low pH,
salt
0.03
0.06
0.02
0.03
0.41
0.05
High pH,
salt
0.13
0.02
0.50
0.13
0.50
0.16
Probability that influent and effluent have the same concentration.
The factorial analysis showed that the effluent toxicities of the carbon-sand and zeolite-sand columns
were controlled by the interaction of pH and ionic strength, with the high pH, high ionic strength condition
having the most toxic effluent. The removal efficiency, however, was controlled by ionic strength for the
carbon-sand and by pH for the zeolite-sand. High influent salt concentrations caused an increase in the
toxicity of the carbon-sand effluent while a high influent pH caused an increase in toxicity of the zeolite-
sand effluent. The high influent ionic strength made the peat-sand effluent more toxic while the removal
efficiency for toxicity across this medium was controlled by the interaction of the pH and the salt. High
influent pH caused an increase in the toxicity of the Enretech-sand effluent. The effluent toxicity for the
sand medium was controlled both by the influent pH and ionic strength independently. However, the
removal efficiency was controlled by the interaction of the ionic strength and the pH.
54
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Turbidity
Table 27 gives the results of the Wilcoxon sign-rank analysis for turbidity. These results were as expected
for most of the media. The carbon-sand and the zeolite-sand columns were excellent removers of turbidity
both due to sorption of the contaminants and due to physical straining of unsorbed particulates. The peat-
sand contributed particles to the effluent because many of the particles that were washed from the peat
during filtration were too small to be strained out during filtration through the bottom sand layer. In
general, the sand column strained out the particles during filtration. The other media had mixed results,
indicating that they would not be good for use in areas that are likely to receive runoff with a variation of
pH conditions and salt concentrations.
Table 27. Wilcoxon P values for turbidity
Filtration
media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.02
0.44
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.06
0.16
0.11
0.16
0.54
High pH,
no salt
0.02
0.02
0.06
0.06
0.16
0.08
Low pH,
salt
0.02
0.11
0.02
0.16
0.03
0.02
High pH,
salt
0.02
0.34
0.02
0.12
0.02
0.02
The influent ionic strength and pH generally did not influence the effluent turbidity, except for the zeolite-
sand. The zeolite-sand effluent turbidity was controlled by the influent ionic strength, with the lower
effluent turbidities occurring when the influent ionic strength is high. The efficiency of filtration is controlled
by the interaction of the influent pH and ionic strength (high influent pH and salt concentrations caused
the smallest average percent removal across the media). For the carbon-sand and peat-sand media, the
influent ionic strength controlled the removal efficiency (high influent salt concentration conditions caused
greater turbidity removal in the carbon-sand and smaller addition of turbidity in the peat-sand). For the
Enretech-sand and the sand media, the influent pH and ionic strength independently controlled the
removal efficiencies (both high influent pH and high influent salt concentrations increased the removal
efficiency of these media).
Conductivity
The Wilcoxon sign-rank analysis P values are given in Table 28. Since conductivity is caused by charged
ions which are dissolved in solution, conductivity will only be removed by media that are capable of
removing dissolved ions, especially the monovalent sodium and chloride ions. Most of the media are ion-
exchange resins that are not good at removing sodium and chloride. In fact, they add sodium to the
solution when they remove other compounds because the compounds sorb at the locations on the media
where the sodium is held. Although several of the media show significant reductions in conductivity, the
size of the reductions is very small (less than 20 percent). Because ionic strength is one of the
parameters that were being controlled, the results of a factorial analysis would be meaningless and,
therefore, are not presented.
Table 28. Wilcoxon P values for conductivity
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. salt
0.31
0.02
0.02
0.02
0.02
0.06
Low pH,
no salt
0.22
0.50
0.50
0.03
0.22"
0.11
High pH,
no salt
0.06
0.02
0.08
0.05
0.36
0.54
Low pH,
salt
0.02
0.03
0.06
0.03
0.16
0.02
High pH, salt
0.38
0.02
0.02
0.50
0.16
0.45
Color
Table 29 gives the P values for the Wilcoxon sign-rank analysis for color. Based on the literature, carbon-
sand was expected to remove color because it can sorb the organic acids that cause color in the runoff,
and carbon-sand, in fact, was found to remove color under ail test conditions. Peat and compost leach
55
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these color-producing organic acids during filtration; therefore, they were not expected to remove color
from the influent. In fact, these two media significantly increased the effluent color. The other media only
removed color during favorable conditions for that medium.
Influent pH controls the final effluent color only for the peat-sand filter with a high influent pH producing
high effluent color. The final effluent color of the carbon-sand and zeolite-sand is influenced by the
influent salt concentration. High influent ionic strength produces'more color in the carbon-sand effluent
but less color in the zeolite-sand effluent. The removal efficiency in the peat-sand column was controlled
by the interaction of the influent pH and ionic strength (largest average removal occurred in low pH, high
salt conditions). The influent ionic strength controls the removal efficiency in the zeolite-sand column (high
influent salt concentrations caused greater removal of color). Influent pH controls the removal efficiency
(high influent pH caused less color addition to the effluent). The removal efficiency for color in the sand
column is controlled by the influent pH and salt concentration independently.
Table 29. Wilcoxon P values for color
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.02
0.31
0.16
0.02
0.66
0.58
Low pH,
no salt
0.02
0.06
0.09
0.02
0.34
0.08
High pH,
No salt
0.02
*
0.03
*
0.02
0.02
Low pH,
salt
0.02
0.03
0.02
0.02
0.02
0.02
High pH,
salt
0.02
0.02
0.02
0.02
0.02
0.02
No difference notable between influent and effluent color for these columns; therefore, no results for Wilcoxon sign-rank analysis.
pH
The Wilcoxon sign-rank P values are given in Table 30. For this parameter, italics refer to cases where
the pH was brought closer to 7. Only two of the media showed significant changes in the pH of the
effluent. The compost-sand always tried to move the pH toward neutral, even with both low and high pH
Influents. The peat-sand always tried to lower the pH between 1 to 1.5 units, even when the influent pH
was already in the pH 4 to 5 range. When the influent pH was greater than 7, the peat-sand lowered the
pH in the effluent (compared to the influent) by 1.5 to 3 units. The carbon-sand, the zeolite-sand, and the
sand all attempted to increase the pH when the influent pH is low. However, these media did not
consistently reduce the pH when the influent pH is high. Since pH is one of the parameters being
controlled, the results of a factorial analysis would be meaningless and, therefore, are not presented.
"ji, ' ,
Table 30. Wilcoxon P values for pH
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. Salt
0.02
0.31
0.02
0.66
0.08
0.02
Low pH,
no salt
0.02
0.02
0.02
0.02
0.34
0.09
High pH,
no salt
0.02
0.02
0.50
0.02
0.02
0.02
Low pH,
salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
salt
0.02
0.02
0.02
0.13
0.02
0.03
Hardness
Table 31 gives the Wilcoxon sign-rank P values for hardness. Hardness reductions were expected for
those media that could remove divalent cations either during sorption or ion-exchange (such as zeolite).
The carbon-sand is the only medium which consistently reduced the hardness in the influent. The other
media either were inconsistent at reducing the hardness, or they exchange divalent cations into solution.
Because the zeolite chosen for these experiments was designed as an ammonia remover, it was not
expected to be as effective at removing hardness as other zeolites that are designed to remove calcium
from water.
56
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The interaction of influent pH and ionic strength did not affect the effluent hardness for any media.
However, the hardness in the effluent from all of the media was influenced either by the influent pH, salt
concentration, or both pH and ionic strength acting independently. The influent pH controls the effluent
hardness for both the Enretech-sand and the peat-sand (higher hardness values occurred when the
influent pH was low). The influent ionic strength controls the effluent hardness for the zeolite-sand column
(higher hardness occurred when the influent salt concentration was high). The influent pH and ionic
strength, acting independently, influence the effluent hardness for the other media, the carbon-sand,
compost-sand, and sand (highest effluent hardness concentration occurred for each medium when the
influent pH was low and the influent salt concentration was high). The influent pH controls the removal
efficiency of both the carbon-sand and the peat-sand media (higher removal efficiencies occurred when
the influent pH was greater than 7). The influent ionic strength controls the removal efficiency for the
zeolite-sand and compost-sand media (smallest addition to the hardness occurred when the influent salt
concentration was low).
Table 31. Wilcoxon P values for hardness
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. salt
0.03
0.02
0.02
0.02
0.08
0.46
Low pH,
no salt
0.03
0.03
0.22
0.02
0.50
0.03
High pH,
no salt
0.02
0.02
0.22
0.03
0.64
0.05
Low pH,
salt
0.02
0.16
0.02
0.02
0.59
0.03
High pH,
salt
0.02
0.02
0.02
0.02
0.08
0.22
Chemical Oxygen Demand (COD)
The calculated P values for the Wilcoxon sign-rank analysis are given in Table 32. Chemical oxygen
demand was consistently removed by all of the media except cornpost-sand under all influent conditions.
The Enretech-sand and sand media also reduced COD influent concentrations for all conditions except
for high pH and no salt addition. As is demonstrated in Figure 4-2, the influent (control) chemical oxygen
demand appears to be related to the influent (control) suspended solids concentration. This indicates that
the media which can remove particulates from the solution and retain them in their pores are the ones
most likely to be able to remove chemical oxygen demand during filtration. This mimicry of the suspended
solids concentration is also seen in the COD of the filter effluents. Therefore, both the influent and effluent
COD are directly related to the influent and effluent suspended solids concentration.
Table 32. Wilcoxon P values for chemical oxygen demand
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. salt
0.02
0.06
0.02
0.13
0.03
0.02
Low pH,
no salt
0.02
0.02
0.02
0.06
0.02
0.02
High pH,
no salt
0.02
0.08
0.02
0.06
0.22
0.08
Low pH,
salt
0.02
0.02
0.02
0.22
0.02
0.02
High pH,
salt
0.02
0.62
0.03
0.22
0.02
0.02
The effluent COD concentration was controlled by the interaction of the influent pH and ionic strength for
five of the six media, including carbon-sand, peat-sand, zeolite-sand, compost-sand and sand. The
highest effluent COD concentrations occurred when the influent pH and salt concentrations were high for
the carbon-sand, peat-sand, zeolite- sand and compost-sand. A low influent pH and a high influent salt
concentration caused sand's highest effluent COD concentration. The Enretech-sand filter was the only
one whose effluent COD concentration was not controlled by the interaction of the influent pH and ionic
strength. The effluent COD for Enretech-sand is controlled only by the influent ionic strength (high influent
salt concentration caused high effluent COD). The removal efficiency of the peat-sand filter was controlled
by the influent pH (greatest percent removal occurred when the influent pH was less than neutral). The
interactions of the influent pH and ionic strength controlled the removal efficiencies of both the carbon-
sand and sand media. The greatest percent removal of COD occurred for carbon-sand when the influent
57
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pH was high and influent salt concentration was low, and the greatest percent removal for sand occurred
when both the influent pH and salt concentration were high.
CO
3
LU
DC
g
O
C3
X
Q.
O
Suspended Solids
1000
10
l l l l lr
2 4 6 8 10 12 14
Loading on Media (m)
Chemical Oxygen Demand
—•- Control (influent)
-I3~ Carbon-Sand
-A— Peat-Moss
V Zeolite-Sand
- ^ Compost-Sand
> Enretech-Sand
-O- Sand
1000
I
O
8
O
100-
Loading on Media (m)
Figure 4-2. Effluent suspended solids and chemical oxygen demand concentrations versus suspended solids
loading on media
Particle Size Distribution (4 to 128
Table 33 gives the calculated P values for the Wilcoxon sign-rank analysis. Except for the peat-sand
during high pH, high ionic strength influent conditions, all media were excellent at removing particles
across the size range of 4 to 128 urn. The factorial analysis for the cumulative particle size distributions
58
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for these media show that neither the pH nor the ionic strength controls either the removal efficiency or
the effluent quality. There also were no observed significant effects of the interaction of pH and ionic
strength on removal efficiency and effluent quality.
Table 33. Wilcoxon P values for PSD (4 to 128
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
Mod. Salt
0.02
0.06
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
no salt
0.02
0.08
0.02
0.02
0.02
0.02
Low pH,
salt
0.02
0.02
0.03
0.03
0.03
0.03
High pH,
salt
0.02
0.62
0.02
0.02
0.02
0.02
Particle Size Distribution (6 to 8 jam)
Table 34 gives the calculated P values for the Wilcoxon sign-rank analysis for the particle size distribution
in the 6 to 8 u,m range. All media were capable of removing the smaller-sized particles from the influent
with the exception of the compost-sand filter at the high influent pH, high influent ionic strength condition.
Table 34. Wilcoxon P values for PSD (6 to 8
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.02
0.06
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
Low pH,
salt
0.03
0.03
0.03
0.03
0.03
0.03
High pH,
salt
0.02
0.02
0.02
0.13
0.02
0.02
The influent pH controlled both the effluent quality and removal efficiency for the peat-sand filter (low
influent pH resulted in the best effluent quality and removal efficiency). The influent ionic strength also
independently influenced the peat-sand's effluent quality (high influent ionic strength resulted in the best
effluent quality). The influent ionic strength controlled both the effluent quality and removal efficiency for
the Enretech-sand filter (best effluent quality and removal efficiency occurred when the influent salt
concentration was high).
Particle Size Distribution (20 to 22 jam)
Table 35 gives the calculated P values for the Wilcoxon sign-rank analysis. Except for the compost-sand
during the high influent pH, high influent salt condition, all media were capable of removing the medium-
sized particles from the influent. The factorial analyses showed that influent pH, influent ionic strength, or
the interaction of pH and ionic strength did not control the effluent quality or removal efficiency for any of
the media except peat-sand. The interaction of influent pH and influent high ionic strength controlled the
removal efficiency of the peat-sand filter (worst average removal efficiency occurred when the influent pH
was high and the influent salt concentration was low).
Table 35. Wilcoxon P values for PSD (20 to 22 p.m)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.02
0.06
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
Low pH,
salt
0.03
0.03
0.03
0.03
0.03
0.03
High pH,
salt
0.02
0.02
0.02
0.13
0.02
0.02
Particle Size Distribution (52 to 54 \im)
The calculated P values from the Wilcoxon sign-rank analysis are given in Table 36. All media, with two
exceptions, were capable of removing the larger-sized particles from the influent. The exceptions were
59
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the compost-sand filter at the high influent pH, high influent ionic strength condition,.and the peat-sand at
a neutral pH, moderate ionic strength condition. The factorial analyses indicate that neither pH, ionic
strength, nor the interaction of pH and salt controlled either the effluent quality or the removal efficiency of
the media.
Table 36. Wilcoxon P values for PSD (52 to 54 urn)
filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. salt
0.06
0.25
0.06
0.08
0.06
0.06
Low pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
Low pH,
salt
0.03
0.22
0.03
0.03
0.09
0.03
High pH,
salt
0.02
0.02
0.03
0.12
0.02
0.02
Suspended Solids
Table 37 gives the calculated P values for the Wilcoxon sign-rank analysis for suspended solids. Except
for the compost-sand at the high influent pH, high influent ionic strength condition, all media were capable
of removing suspended solids from the influent. For all media, the quality of the effluent was controlled by
the interaction of the influent pH and ionic strength. The low influent pH and high influent salt
concentration had the highest average suspended solids concentration in the effluent. The removal
efficiency of none of the media was controlled by the influent pH or ionic strength acting independently.
For the carbon-sand and the zeolite-sand media, the interaction of the influent pH and ionic strength
controlled the removal efficiency. For these media, the poorest removal efficiency occurred when the
influent pH was low and the influent salt concentration was high.
Table 37. Wilcoxon P values for suspended solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. salt
0.02
0.06
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
Low pH,
salt
0.02
0.02
0.02
0.03
0.02
0.02
High pH,
salt
0.02
0.02
0.02
0.12
0.02
0.02
Zinc
The calculated P values for the Wilcoxon sign-rank analysis are given in Table 38 for zinc. Except for the
compost-sand during the high influent pH, high influent ionic strength condition, all media were capable of
significantly removing zinc from the influent during filtration. Effluent quality was controlled by the
interaction of the influent pH and ionic strength for four media: peat-sand, zeolite-sand, Enretech-sand,
and sand. For each of these media, the effluent quality was poorest when the influent pH was low and the
influent salt concentration was high. For the carbon-sand and peat-sand filters, the effluent quality and
removal efficiency were controlled by the influent pH (worst average effluent quality and removal
efficiency occurred when the influent pH was low).
Removal efficiency was controlled by the interaction of the influent pH and influent ionic strength for three
of the media: zeolite-sand, compost-sand, and sand. The smallest removal efficiency occurred for each
medium when the influent pH was low and the influent salt concentration was high. The Enretech-sand
filter's effluent quality was controlled by the influent pH and influent ionic strength acting independently.
For Enretech-sand, low influent pH, low influent salt concentrations, or both caused poorer average
removal efficiencies.
60
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Table 38. Wilcoxon P values for zinc
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.02'
0.06
0.02
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02
• 0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.02
0.02
0.02
0.02
Low pH,
salt
0.02
0.02
0.02
0.02
0.02
0.02
High pH,
salt
0.02
0.02
0.02
0.13
0.02
0.02
Copper
Table 39 gives the calculated P values for the Wilcoxon sign-rank analyses for copper. Most of the media
were able to remove copper from the solution during most tests. However, the carbon-sand, peat-sand,
and zeolite-sand were not able to significantly remove copper from the influent when the pH was neutral.
However, the solution had a moderate ionic strength (salt was added to the runoff), which may have
affected copper removal.
Table 39. Wilcoxon P values for copper
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Sand
Neutral pH,
mod. Salt
0.41
0.50
0.28
0.02
0.02
0.02
Low pH,
no salt
0.02
0.02
0.02 '
0.02
0.02
0.02
High pH,
no salt
0.02
0.02
0.08
0.02
0.22
0.02
Low pH,
salt
0.02
0.02
0.02
0.03
0.02
0.02
High pH,
salt
0.02
0.02
0.02
0.13
0.02
0.02
The factorial analyses showed that the final effluent quality was controlled by the interaction of the influent
pH and influent ionic strength for four of the media: peat-sand, zeolite-sand, Enretech-sand, and sand.
The poorest effluent quality was found when the influent pH and salt concentration were low for the peat-
sand, zeolite-sand, and Enretech-sand media. The sand's effluent quality was worst when the influent pH
was low and the influent salt concentration was high. For the compost-sand filter, effluent quality was
controlled by the influent pH and influent ionic strength acting independently. The removal efficiency for
five of the media, peat-sand, zeolite-sand, compost-sand, Enretech-sand, and sand were controlled by
the interaction of the influent pH and ionic strength. For all five media, the poorest removal efficiency
occurred when the influent pH was high and the influent salt concentration was low.
Other Observations
The expected significant clogging of the filter media with the suspended solids was found during the tests.
The UV-vis absorbance test evaluations showed some, but limited, decrease in sorption capacity during
the tests. The clogging was affected by changes in pH and ionic strength. The changes in pH and ionic
strength also affected the permanent retention of the pollutants in the columns after the tests. No
chemical breakthrough was noted for any of the tests during the test durations; the columns clogged and
ceased to allow filtration before their chemical removal capacity was exceeded.
Clogging of the peat-sand filter occurred during the neutral pH, high ionic strength run, but not during the
other runs (except at the end of the high pH, high ionic strength run), indicating that filtering influents with
high conductivities will reduce the life of the filter, while either a significantly acidic or alkaline influent will
tend to prolong the filter run. The clogging of the compost-sand filter during both the high ionic strength
tests (low and high pH) indicates that filtering influents with high conductivities will reduce the life of the
filter, and, unlike peat, a significantly acidic or alkaline runoff does not appear to prolong the life of the
filter.
61
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Long-Term Treatment Performance
Evaluation of long-term treatment performance was performed on two separate occasions by filtering
runoff that had not been allowed to presettle through the columns as the first run and presettled runoff
through the columns as the second run. The purpose of these tests was to determine chemical
breakthrough during filtration of a complex influent. The literature search had indicated that most of these
media were effective at removing pollutants under laboratory conditions with analytical grade chemicals
used to spike water or an organic solvent. Although these tests were informative about the chemicals that
each media could remove and the potential removal mechanisms, relatively few tests had been done
using a more 'complex' influent, i.e., where some compounds are present in more than one form and
where there is likely significant competition for the removal sites. This is the reason that the location
selected to study the runoff was a potential critical source area -- the intention was to use the 'dirtiest'
runoff water that could be obtained easily and from a location where the sampling equipment was secure.
However, this runoff was not as dirty as expected because only the fueling operations and vehicle
cleaning operations were outdoors. Fleet vehicle maintenance was performed in a garage where the oil
and other pollutants were collected and not allowed to run outside the building.
Analytical Results
The tables and graphs of the data collected during these two tests are given in the following appendices:
• Appendix C. Physical Parameters (Toxicity, Turbidity, Conductivity, Color, pH)
• Appendix D. Major Anions (Carbonate, Bicarbonate, Fluoride, Chloride, Nitrite, Nitrate, Phos-
phate, Sulfate)
• Appendix E. Major Cations (Lithium, Sodium, Ammonium, Potassium, Magnesium, Calcium,
Hardness)
• Appendix F. Solids, Particle Size Distributions
• Appendix G. Heavy Metals (Zinc, Copper)
• Appendix H. Organics, Pesticides (COD, Semi-Volatile Organics, Pesticides)
A Wilcoxon sign-rank analysis was used to test the hypothesis that treatment did not significantly change
the concentration of a given parameter. P values less than 0.10 were considered significant and led to the
conclusion that treatment did significantly change the concentration of a parameter during passage
through the column. However, this P value does not indicate whether or not a specific media removed the
parameter of interest or leached out more of that parameter. Therefore, P values that indicate statistically
significant removals are in italics in the tables. For those parameters where both the unfiltered and filtered
fractions of a sample were analyzed, Wilcoxon sign-rank P values have been calculated for both sample
fractions.
Toxicity
Table 40 gives the calculated P values for the Wilcoxon sign-rank analysis for the unfiltered fraction, and
Table 41 gives the P values for the filtered fraction. For the unpretreated influent, which had a greater
influent toxicity, the carbon-sand, zeolite-sand, and compost media had significant removals of toxicity
during treatment. However, for the presettled runoff, none of the media were capable of significantly
removing toxicity from the unfiltered fraction, and only carbon-sand, peat-sand, and zeolite-sand were
capable of removing it from the filtered fraction.
One potential explanation for the difference in removal in the unfiltered fraction between the normal runoff
and the presettled runoff is that the presettled runoff, unlike the normal runoff, only contained colloidal
particles. When the particles in the influent are colloidal, they are not likely to be removed during
treatment because the media do not have pores small enough to trap these particles, and any toxicity
associated with these particles is not removed. The filterable fraction of the toxicity (toxicity that was due
to the pollutants that were not removing by filtering through a 0.45 jim membrane filter) was removed
during both tests because these media are capable-of sorbing the dissolved pollutants to their surfaces.
62
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Table 40. Wilcoxon P values for toxicity (unfiltered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.06
0.13
0.06
N/A*
0.06
N/A
0.09
N/A
0.06
0.36
0.45
0.31
PreSettled influent
0.44
0.44
0.38
0.16
N/A
0.13
N/A
0.38
0.50
0.50
0.25
N/A
N/A: this test was not performed for this medium and water combination.
Table 41. Wilcoxon P values for toxicity (filtered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.03
0.03
N/A
0.06
N/A
0.44
N/A
0.16
0.06
0.03
0.22
PreSettled influent
0.06
0.06
0.06
0.45
N/A
0.16
N/A
0.31
0.50
0.56
0.56
N/A
Turbidity
The calculated P values for the Wilcoxon sign-rank analysis are given in Table 42 for the unfiltered
fraction and Table 43 for the filtered fraction. Except for the Gunderboom for the filtered fraction of the
normal runoff, no media were capable of significantly removing turbidity either from the unfiltered or
filtered fractions of either the presetted or normal runoff during treatment. For the unfiltered fraction, peat-
sand, zeolite-sand, and sand significantly added turbidity to the normal influent, and the peat-sand,
Enretech-sand, and Forest-sand significantly added turbidity to the presetted influent. When the influent
was not presettled, removal of turbidity was inconsistent. With three exceptions, when the influent was
presettled, turbidity removal was also inconsistent. Peat-sand, compost-sand, and Forest-sand media
consistently added turbidity to the effluent. The added turbidity from many of the media is likely due to the
flushing of colloidal particles which are too small to be trapped in the media pores and which, because of
their small size, are likely part of the filtered fraction, i.e., less than 0.45 (am.
Color
The calculated P values for the Wilcoxon sign-rank analysis for color for the unfiltered fraction are given in
Table 44, and the P values for the filtered fraction are given in Table 45. For the presettled influent, no
medium was capable of removing color from the unfiltered fraction of the influent, and only carbon-sand
significantly removed color from the filtered fraction. This is likely due to the ability of the carbon to
remove the organics that are causing color in the influent, and yet some of the very small pieces of
carbon are washed out during treatment, and this adds color to the unfiltered fraction of the effluent. For
the normal influent, the carbon-sand was the only media that was capable of significantly reducing the
influent color for both the unfiltered and filtered fractions. The peat-sand, compost-sand, compost, and
Enretech all added color to the unfiltered fractions of their effluents. Only for the Enretech was this added
color due to particulates that were able to be removed by filtering of the effluent through a 0.45 jam filter.
63
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Table 42. Wilcoxon P values for turbidity (unfiltered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.50
0.03
0.06
N/A
0.16
N/A
0.31
N/A
0.06
0.31
0.50
0.31
PreSettled influent
0.13
0.06
0.50
0.50
N/A
0.06
N/A
0.09
0.03
0.50
0.16
N/A
Table 43. Wilcoxon P values for turbidity (filtered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.41
0.50
0.45
N/A
0.31
N/A
0.41
N/A
0.16
0.09
0.56
0.16
PreSettled influent
0.50
0.08
0.44
0.06
N/A
0.16
N/A
0.06
0.22
0.31
0.41
N/A
Table 44. Wilcoxon P values for color (unfiltered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.03
0.31
N/A
0.03
N/A
0.03
N/A
0.31
0.31
0.03
0.03
PreSettled influent
0.13
0.03
0.06
0.03
N/A
0.19
N/A
0.19
0.13
0.31
0.50
N/A
Table 45. Wilcoxon P values for color (filtered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.03
0.50
N/A
0.06
N/A
0.16
N/A
0.19
0.50
0.45 •
0.26
PreSettled influent
0.03
0.13
0.31
0.03
N/A
0.31
N/A
0.31
0.69
0.50
0.31
N/A
64
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Conductivity
Table 46 gives the calculated P values for the Wilcoxon sign-rank analysis for conductivity. The only
media that were capable of significantly reducing conductivity were the filter fabrics for the normal influent.
The other media either were incapable of removing dissolved ions from solution, or they were ion-
exchange resins and leached off one ion when they adsorbed another with minimal influence on
conductivity.
Table 46. Wilcoxon P values for conductivity
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.31
0.31
N/A
0.03
N/A
0.03
N/A
0.16
0.08
0.03
0.03
PreSettled influent
0.06
0.03
0.13
0.03
N/A
0.38
N/A
0.13
0.31
0.16
0.31
N/A
pH
The calculated P values for the sign test analysis for pH are given in Table 47. The media were
considered to be removing pH problems when their effluents were closer to the neutral pH of 7 than their
influents. In the bench-scale tests, the peat-sand filter tended to lower the pH of the solution while the
compost-sand tended to move the pH of the solution toward neutral. In these tests, the results for all
media are mixed because the influent pH is near neutral. The exception was the peat-sand that
significantly lowered the pH in each test.
Table 47. Sign test P values for pH
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.19
0.03
0.13
N/A
0.03
N/A
0.50
N/A
0.50
0.50
0.31
0.03
PreSettled influent
0.03
0.03
0.50
0.03
N/A
0.03
N/A
0.03
0.03
0.19
0.19
N/A
Carbonate
The calculated P values for the Wilcoxon sign-rank test are given in Table 48. The carbon-sand and the
peat-sand media significantly removed carbonate from the influent during treatment. None of the other
media could consistently remove carbonate from its influents. The carbon-sand was expected to remove
the carbonate because it is a sorption medium, and the peat-sand was expected to remove carbonate
because the peat acts as a scavenger of carbonate. For the other sorption or ion-exchange media, the
influent carbonate concentration likely was not great enough to promote significant sorption or ion-
exchange.
65
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Table 48. WHcoxon P values for carbonate
Filtration media
Carbon-sand
Peat-sand
Zeoiite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.06
0.50
N/A
0.03
N/A
0.22
N/A
0.31
0.41
0.41
0.31
PreSettled influent
0.06
0.03
0.31
0.22
N/A
0.50
N/A
0.16
0.41
0.50
0.50
N/A
Bicarbonate
Table 49 contains the calculated P values for the Wilcoxon sign-rank analysis for bicarbonate. The
carbon-sand was the only medium that was capable of removing bicarbonate from the solution both when
the influent was not presettled and when it was settled for several days prior to treatment. The peat-sand
medium could only significantly remove the bicarbonate ion from the presettled runoff. The compost-sand
consistently leached bicarbonate into the effluent.
Table 49. Wilcoxon P values for bicarbonate
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.19
0.03
N/A
0.03
N/A
0.03
N/A
0.16
0.22
0.50
0.41
PreSettled influent
0.06
0.03
0.16
0.03
N/A
0.06
N/A
0.03
0.16
0.22
0.22
N/A
Fluoride
The calculated P values for the Wilcoxon sign-rank analysis for fluoride are given in Table 50. No media
could consistently remove fluoride from all influents. Peat-sand could only remove fluoride from the
normal influent.
Table 5Q. Wilcoxon P values for fluoride
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.31
0.03
0.41
N/A
0.03
N/A
0.41
N/A
0.50
0.03
0.19
0.31
PreSettled influent
0.22
0.31
0.16
0.50
N/A
0.19
N/A
0.50
0.50
0.56
0.09
N/A
66
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Chloride
Table 51 gives the calculated P values for the Wilcoxon sign-rank analysis for chloride. The carbon-sand
medium consistently leached chloride into its effluent. The peat-sand and zeolite-sand media were only
capable of removing chloride from presettled influent. The other media did not significantly and
consistently remove chloride from or add chloride to the solution during treatment.
Table 51. Wilcoxon P values for chloride
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.03
0.22
N/A
0.09
N/A
0.03
N/A
0.50
0.31
0.22
0.31
PreSettled influent
0.03
0.03
0.03
0.16
N/A
0.22
N/A
0.50
0.16
0.22
0.50
N/A
Nitrate
The calculated P values for the Wilcoxon sign-rank analysis are given in Table 52. Carbon-sand is the
only medium that consistently removed nitrate during treatment. The other media were inconsistent at
removing nitrate from solution. In many areas, nitrate is considered a problem pollutant that must be
controlled because excess nitrate in a drinking water source can lead to methemoglobinemia in infants.
Excess nitrate also may cause eutrophication in a nitrogen-limited water body. For those areas where
nitrate must be controlled, the carbon-sand is the only medium that will consistently remove it from
solution. In order to remove nitrate from the influent with the other media, a zone of denitrification must be
established at the bottom of the media or in a subsequent chamber.
Table 52. Wilcoxon P values for nitrate
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.06
0.13
0.06
N/A
0.03
N/A
0.19
N/A
0.50
0.44
0.22
0.06
PreSettled influent
0.06
0.56
0.56
0.50
N/A
0.13
N/A
0.19
0.56
0.03
0.13
N/A
Sulfate
Table 53 gives the calculated P values for the Wilcoxon sign-rank analysis for sulfate. No media
consistently removed sulfate from solution. For the carbon-sand medium, sulfate is one of the major ions
that is exchanged when other ions are removed from solution.
67
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Table 53. Wilcpxon P values for sulfate
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.03
0.06
N/A
0.09
N/A
0.03
N/A
0.50
0.31
0.41
0.41
PreSettled influent
0.03
0.06
0.41
0.50
N/A
0.21
N/A
0.31
0.16
0.50
0.41
N/A
Hardness
The calculated P values for the Wilcoxon sign-rank analysis for hardness are given in Table 54. Hardness
is a measure of the divalent cation concentration in the water, and it is primarily composed of calcium and
magnesium. Peat-sand is the only medium that effectively removed hardness from the influent because it
is lacking in calcium and scavenged calcium from solution. Compost increases the hardness of the
solution during treatment, indicating that it is leaching divalent cations into the water.
Table 54. Wilcpxon P values for hardness
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.27
0.03
0.41
N/A
0.03
N/A
0.22
N/A
0.31
0.45
0.22
0.41
PreSettled influent
0.45
0.03
0.31
0.03
N/A
0.22
N/A
0.22
0.44
0.31
0.13
N/A
Sodium
Table 55 contains the calculated P values for the Wilcoxon sign-rank analysis for sodium. Only the ADS
4420 fabric significantly removed sodium from the solution for the unpretreated influent. The other media
were inconsistent at removing sodium from the solution or, like the carbon-sancl for presettled runoff,
leached sodium into the water.
Table 55. Wilcpxon P values for sodium
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.22
0.03
0.09
N/A
0.03
N/A
0.03
N/A
0.56
0.16
0.41
0.03
PreSettled influent
0.03
0.50
0.03
0.31
N/A
0.06
N/A
0.03
0.41
0.50
0.50
N/A
68
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Ammonium
The calculated P values for the Wilcoxon sign-rank analysis for ammonium are given in Table 56. No
medium was capable of consistently removing ammonium from solution, including the zeolite that was
designed for ammonia removal. The Enretech was capable of removing ammonium from the normal
influent, yet the Enretech-sand medium was not capable of removing ammonium from the presettled
influent.
Table 56. Wilcoxon P values for ammonium
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.56
0.31
0.44
N/A
0.44
N/A
0.06
N/A
0.31
0.44
0.31
0.44
PreSettled influent
0.16
0.31
0.22
0.31
N/A
0.50
N/A
0.50
0.41
0.16
0.31
N/A
Potassium
The calculated P values for the Wilcoxon sign-rank analysis for potassium are given in Table 57. The
carbon-sand and zeolite-sand media were capable of significantly removing potassium from solution. The
peat-sand and compost-sand added potassium during treatment due to their ion-exchange capabilities.
None of the other media was consistent at either removing potassium from or leaching potassium into the
water during treatment.
Table 57. Wilcoxon P values for
potassium
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.06
0.03
0.03
N/A
0.03
N/A
0.16
N/A
0.41
0.16
0.31
0.31
PreSettled influent
0.03
0.03
0.03
0.03
N/A
0.06
N/A
0.03
0.31
0.13
0.31
N/A
Magnesium
Table 58 contains the calculated P values from the Wilcoxon sign-rank analysis for magnesium. Compost-
sand was the only medium that consistently leached magnesium into its effluent. No medium was capable
of significantly removing magnesium from the runoff during treatment.
69
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Table 58. Wilcoxon P values for magnesium
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.06
0.31
0.03
N/A
0.03
N/A
0.16
N/A
0.41
0.31
0.16
0.31
PreSettled influent
0.45
0.31
0.22
0.03
N/A
0.16
N/A
0.50
0.50
0.16
0.50
N/A
Calcium
The calculated P values for the Wilcoxon sign-rank analyses for calcium are given in Table 59. Peat is
calcium-poor, and, therefore, the peat-sand medium was expected to remove calcium from the influent
during treatment. It was the only medium capable of regularly removing calcium from solution. The
zeolite-sand significantly removed calcium from the influent when the runoff was presettled prior to
treatment, yet it leached calcium when the influent was not presettled.
Table 59. Wilcoxon P values for calcium
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Unpretreated influent
0.22
0.03
0.09
N/A
0.03
N/A
0.03
N/A
0.56
0.16
0.41
0.03
PreSettled influent
0.22
0.03
0.03
0.16
N/A
0.16
N/A
0.41
0.06
0.09
0.31
N/A
Solids
Table 60 gives the calculated P values for the Wilcoxon sign-rank analysis for total solids; Table 61 gives
the P values for dissolved solids; and Table 62 gives the P values for suspended solids. The peat-sand
was the only medium capable of removing total solids from the presettled influent when the influent
concentration of total solids was small. The sand, Gunderboom, and EMCON were capable of
significantly removing total solids from the normal influent, indicating that their best removal efficiencies
occur when the total solids in the influent are fairly high, i.e., the runoff has not been allowed to settle for
several days. Only peat-sand and the EMCON fabric were capable of significant removal of total
dissolved solids with the presettled influent. No other media or fabric was capable of any significant
removal of dissolved solids for any test. Only the four media, carbon-sand, zeolite-sand, sand, and
Gunderboom, were capable of removing suspended solids from the influent and then only when the
influent concentration was high, such as when the runoff was not presettled.
70
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Table 60. Wilcoxon P values for total solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Unpretreated influent
0.22
0.16
0.45
N/A
0.03
N/A
0.06
N/A
0.06
0.09
0.06
0.13
PreSettled influent •
0.50
0.06
0.63
0.06
N/A
0.50
N/A
0.50
0.45
0.22
0.41
N/A
Table 61. Wilcoxon P values for total dissolved solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Unpretreated influent
0.03
0.16
0.05
N/A
0.03
N/A
0.03
N/A
0.41
0.27
0.41
0.41
PreSettled influent
0.50
0.03
0.03
0.06
N/A
0.16
N/A
0.50
0.44
0.13
0.03
N/A
Table 62. Wilcoxon P values for total suspended solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Unpretreated influent
0.06
0.50
0.09
N/A
0.50
N/A
0.50
N/A
0.03
0.13
0.06
0.06
PreSettled influent
0.19
0.44
0.50
0.16
N/A
0.31
N/A
0.41
0.41
0.41
0.31
N/A
Volatile Solids
The calculated P values for the Wilcoxon sign-rank analysis for volatile total solids are given in Table 63;
for volatile dissolved solids, Table 64; and for volatile suspended solids, Table 65. When the runoff is
allowed to settle for several days prior to treatment, the Enretech-sand and sand media were capable of
removing volatile total solids from the influent. For the same influent, however, the compost-sand medium
added volatile total solids during treatment, likely because pieces of the compost were leaching from the
media. None of the media were capable of removing either volatile dissolved solids or volatile suspended
solids from presettled influent. For the normal runoff, where the influent concentration was greater,
carbon-sand, zeolite-sand, sand, Gunderboom, and ADS 4420 were capable of removing volatile total
solids. Again the compost-sand medium, as well as the peat-sand medium, leached organics from the
filter into the effluent. Carbon-sand was the only medium capable of removing both volatile dissolved
solids and volatile suspended solids from the normal runoff. The zeolite-sand could significantly remove
only volatile suspended solids from the normal runoff. The compost and the peat-sand media both
consistently added volatile dissolved and suspended solids to the runoff during treatment.
71
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Table 63. Wilcoxon P values for volatile total solids
Filtration media
Carbon-sand
Paat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.09
0.03
N/A
0.03
N/A
0.06
N/A
0.03
0.06
0.16
0.03
PreSettled influent
0.16
0.27
0.63
0.03
N/A
0.09
N/A
0.16
0.06
0.22
0.31
N/A
Table 64. Wilcoxon P values for volatile dissolved solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.06
0.31
N/A
0.03
N/A
0.03
N/A
0.31
0.31
0.45
0.16
PreSettled influent
0.38
0.31
0.45
0,06
N/A
0.50
N/A
0.22
0.37
0.44
0.25
N/A
Table 65. Wilcoxon P values for volatile suspended solids
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.27
0.09
N/A
0.09
N/A
0.55
N/A
0.13
0.55
0.16
0.45
PreSettled influent
0.45
0.22
0.45
0.45
N/A
0.22
• N/A
0.16
0.16
0.41
0.44
N/A
Particle Size Distribution (1 to 2 urn)
The calculated P values for the Wilcoxon sign-rank analysis for particle size distribution (1 to 2 u,m) are
given in Table 66. None of the media were capable of removing these small-sized particles from solution
during treatment. In fact, the peat-sand, zeolite-sand, compost-sand, Enretech-sand, Forest-sand, and
sand media had some of their finer particles washed out of the media and into the effluent. These filters
were not expected to effectively remove particles in this size range because this is their approximate pore
size.
72
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Table 66. Wilcoxon P values for PSD (1 to 2 u.m)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.16
0.03
0.06
N/A
0.31
N/A
0.03
N/A
0.22
0.41
0.16
0.08
PreSettled influent
0.16
0.03
0.03
0.03
N/A
0.03
N/A
0.06
0.03
0.31
0.16
N/A
Particle Size Distribution (4 to 5 u.m)
Table 67 gives the calculated P values for the Wilcoxon sign-rank analysis for the particle size distribution
between 4 and 5 jam. When the runoff is presettled, no medium is capable of significantly removing
particles in this size range. However, when the runoff was not presettled prior to filtration, the carbon-sand
and sand media were able to significantly remove 4 to 5 urn particles from their influents. The peat-sand
and the compost media washed particles of this size range out of the filter into their effluents. The zeolite-
sand, Enretech-sand, and the ADS 4420 also may add particles of this size range to the solution, but this
addition is not consistent when the runoff has been presettled.
Table 67. Wilcoxon P values for PSD (4 to 5 urn)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.09
0.03
0.09
N/A
0.16
N/A
0.06
N/A
0.06
0.16
0.22
0.03
PreSettled influent
0.16
0.06
0.31
0.09
N/A
0.31
N/A
0.31
0.31
0.41
0.22
N/A
Particle Size Distribution (11 to 12.5 u,m)
The calculated P values for the Wilcoxon sign-rank analysis for the particle size distribution in the 11 to
12.5 jam range are given in Table 68. For the presettled runoff, the carbon-sand, Gunderboom, and
EMCON produced statistically significant reductions of particles in this size range; however, the carbon-
sand was the only medium which was capable of producing a removal efficiency of greater than ten
percent. When the influent was not presettled, the carbon-sand, zeolite-sand, compost, and sand media
were capable of producing a significant removal of particles in this size range.
Particle Size Distribution (1 to 128 urn)
Table 69 gives the calculated P values for the Wilcoxon sign-rank analysis for particle size distribution
across the range of 1 to 128 urn. When the runoff was not presettled, carbon-sand, peat-sand, zeolite-
sand, and sand were all capable of significant removal of particles from this size range (measured as
cumulative volume occupied by particles per milliliter of solution). However, when the influent had settled
for several days, none of the media were capable of significantly removing particles during treatment.
73
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Table 68. Wilcoxon P values for PSD (11 to 12.5 urn)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.03
0.41
0.03
N/A
0.09
N/A
0.31
N/A
0.03
0.16
0.41
0.41
PreSettled influent
0.03
0.03
0.31
0.06
N/A
0,50
N/A
0.16
0.41
0.06
0.06
N/A
Table 69. Wilcoxon P values for PSD (1 to 128 u.m)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.09
0.03
0.09
N/A
0.16
N/A
0.06
N/A
0.06
0.16
0.22
0.03
PreSettled influent
0.16
0.06
0.31
0.09
N/A
0.31
N/A
0,31
0.31
0.41
0.22
N/A
Zinc
The calculated P values for the Wilcoxon sign-rank analysis for zinc, unfiltered and filtered fraction, are
given in Table 70. All of the media were capable of significantly removing zinc from both the unfiltered and
filtered fraction of the influent during treatment. Neither of the filter fabrics could remove the zinc during
treatment, which was expected since zinc tends to sorb to small particles in solution. Zinc sorption to
small particles enhances its ability to pass through the filters and the fabrics.
Table 70. Wilcoxon P values for zinc for presetted influent
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
Unfiltered fraction
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.41
0.50
Filtered fraction
0.06
0.03
0.03
0.03
0.03
0.03
0,03
0.31
0.50
Copper
The calculated P values for the Wilcoxon sign-rank analysis for copper, unfiltered and filtered fractions,
are given in Table 71. No media were capable of removing copper from the runoff, possibly because the
influent concentrations were low and the runoff did not have sufficient contact time with the media for
sorption to occur. The Forest-sand media added particulate copper to the runoff during treatment,
indicating that copper was leaching from the media.
74
-------
Table 71. Wilcoxon P values for copper for presettled influent
Filtration media
Carbon-sand
Peat-.sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
Unfiltered fraction
0.50
0.31
0.50
0.31
0.41
0.06
0.16
0.41
0.41
Filtered fraction
0.41
0.50
0.22
0.22
0.50
0.41
0.41
0.50
0.50
Chemical Oxygen Demand (COD)
Table 72 gives the calculated P values for the Wilcoxon sign-rank analysis for COD for the unfiltered
fraction, and Table 73 gives the P values for the filtered fraction. Only the carbon-sand medium was
capable of removing dissolved chemical oxygen demand from both the presettled and normal runoffs.
Carbon-sand, Gunderboom and EMCON significantly removed particulate COD from the presettled
runoff. No significant removals occurred during treatment of the normal influent.
Table 72. Wilcoxon P values for chemical oxygen demand (unfiltered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.13
0.06
0.50
N/A
0.09
N/A
0.06
N/A
0.50
0.50
0.50
0.16
PreSettled influent
0.03
0.50
0.22
0.03
N/A
0.31
N/A
0.31
0.25
0.03
0.09
N/A
Table 73. Wilcoxon P values for chemical oxygen demand (filtered fraction)
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Compost
Enretech-sand
Enretech
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
ADS 4420 fabric
Normal influent
0.06
0.03
0.31
N/A
0.03
N/A
0.06
N/A
0.06
0.16
0.31
0.09
PreSettled influent
0.03
0.31
0.31
0.03
N/A
0.31
N/A
0.22
0.19
0.22
0.19
N/A
Semi-Volatile Organics
The semi-volatile organics were only analyzed on the effluents from the media that received presettled
runoff. Because this runoff was presettled and the particulate loading was much smaller than the loading
likely would be in normal runoff, very few of the organics of interest were found in both the settled runoff
influent and effluent. A Wilcoxon sign-rank analysis was performed for the five organics which were
detected in at least ten percent of the samples: 2,4-dinitrophenol, 2-methyl-4,6-dinitrophenol, di-n-
butylphthalate, bis(2-ethylhexyl) phthalate, and pentachlorophenol. The calculated P values for the
Wilcoxon sign-rank analysis are given in Table 74. For the semi-volatiles only, the P value used for
significance was 0.15. This value was chosen because not all of the storms had detectable
75
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concentrations of a semi-volatile organic in the influent and a P of less than 0.15 meant that the media
had to measurably alter, in one direction only, the concentration of that organic for all storm events in
which that compound was detected in either the influent or effluent. The variability of the data causes the
conclusions reached to be tentative, and in need of further study, especially since phthalate
contamination from plastics is a known problem in environmental analysis. Based upon the literature,
carbon-sand would be expected to remove most of these organics from solution. However, it was only
capable of removing 2,4-dinitrophenol and bis(2-ethylhexyl) phthalate from solution consistently. Peat-
sand was capable of removing three of the five organics: 2,4-dinitrophenol, di-n-butyl phthalate, and bis(2-
ethylhexyl) phthalate. The zeolite-sand and the sand media could only remove two organics: bis(2-
ethylhexyl) phthalate and pentachlorophenol. The Enretech-sand also could only remove two organics:
2,4-dinitrophenol and pentachlorophenol. The Forest-sand medium could only remove the
pentachlorophenol. The EMCON fabric could not remove any of the detected semi-volatile organics while
the Gunderboom fabric could remove the 2,4-dinitrophenol and di-n-butyl phthalate. The influent
concentration of many of these compounds was very low. The sorption media may have been able to
remove more compounds or could have had higher removal efficiencies if the influent concentration of
these compounds had been higher, i.e., if the influent concentration was significantly above the threshold
concentration at which no detectable sorption will occur.
Table 74. Wilcoxon P values for semi-volatile organics for presettled influent
Filtration media
Carbon-sand
Paat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
2,4-Di-
nitrophenol
0.13
0.13
0.25
0.38
0.13
0.38
0.31
0.13
0.06
2-Methyl-4,6-
dinitrophenol
0.38
0.25
0.38
0.50
0.63
0.25
0.25
0.25
0.56
Di-n-butyl-
phthalate
0.63
0.13
0.38
0.38
0.38
0.38
0.25
0.13
0.19
Bis(2-ethyl-hexyl)
phthalate
0.13
0.13
0.13
0.25
0.38
0.25
0.13
0.44
0.31
Pentachloro-
phenol
0.44
0.19
0.06
0.31
0.06
0.06
0.06
0.19
0.56
Pesticides
Like the semi-volatile organics, not all of the pesticides analyzed were detected in every sample. The
pesticides detected in more than 20 percent of the samples were dieldrin and 4,4'-DDT. The calculated P
values for the Wilcoxon sign-rank analysis for these two compounds are given in Table 75. Only peat-
sand was capable of significantly removing dieldrin during treatment while none of the media were
capable of significantly removing 4,4'-DDT during treatment. The Forest-sand medium, containing the
kenaf-based agrofiber, leached lindane (gamma-BHC) into its effluent. Effluent concentrations of lindane
fqr this filter ranged from 0.03 to 0.6 mg/L for the three storm events in which it was detected. None of the
storm events had any detectable lindane in the influent runoff before treatment; therefore, the lindane
must have originated from the agrofiber.
Table 75. Wilcoxon P values for
jesticides for presettled influent
Filtration media
Carbon-sand
Peat-sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
Sand
Gunderboom fabric
EMCON fabric
Dieldrin
0.31
0.06
0.56
0.56
0.31
0.31
0.41
0.41
0.22
4,4'-DDT
0.31
0.16
0.13
0.63
0.31
0.06
0.38
0.50
0.16
76
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Other Observations
Pretreatment of the water by settling for a minimum of three days to significantly reduce the suspended
solids increased the water volume that could be treated before clogging. However, it generally decreased
the amount of sediment needed to clog the media columns. The settling pretreatment removed all of the
faster-sinking particles (generally the largest particles), leaving the smaller and less dense particles in the
solution. These particles appeared to have a greater detrimental effect on the flow rate through the media
than the larger and denser particles.
The activated carbon showed the greatest pollutant concentration reductions compared to the other
media. The removal capability seemed to slightly decrease with time; however, there was no indication
that chemical breakthrough had been achieved for this medium. The other media did not show as great
an adsorption ability as the activated carbon. The zeolite-sand, Enretech-sand, and Forest-sand filters
showed limited removal ability. The compost-sand and peat-sand media showed significant increases in
organics in their effluents due to the natural humics that are washed off the media during treatment.
Table 76 summarizes the results of the long-term tests by giving average percent removals during
treatment for those media that had significant concentration reductions of a given parameter. The results
are presented for each parameter for the presettled influent first and then the normal influent that was not
presettled. An entry of "*" means that the media made no significant reductions in that parameter during
treatment. Parameters that are not listed had no media that caused a significant removal during
treatment.
The Enretech-sand, Forest-sand, and the filter fabrics had the poorest removal efficiencies of all the
media. They were only capable of significantly removing between three and five parameters. The
compost-sand also was not effective at removing many constituents from the influent. The zeolite-sand
medium was only slightly better than the sand medium for the number of potential pollutants that it
removed. The two best media, based on the number of parameters they were capable of significantly
removing, were the carbon-sand and the peat-sand. Carbon-sand's advantage is that it does not have as
many undesirable side effects, such as adding suspended solids and color to its effluent.
77
-------
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78
-------
Chapter 5
Conclusions: Design of Stormwater Filters
The information obtained during this research can be used to develop guidelines for stormwater treatment
using filtration, especially when used in conjunction with reported information in the literature. The design
of a stormwater filter needs to be divided into two phases. The first phase is the selection of the filtration
media to achieve the desired pollutant goals. The second phase is the sizing of the filter to achieve the
desired run time before the media must be replaced.
The main objective of this research was to monitor a variety of filtration media to determine their pollutant
removal capabilities. However, it soon became apparent that the filters were more limited by clogging
caused by suspended solids in stormwater runoff. The clogging occurred long before reductions in their
pollutant removal capabilities could be identified. Therefore, measurements in filter run times, including
flow rates and clogging parameters, were added to the research activities. However, the small-scale filter
set-ups used for the pollutant removal measurements probably under-predicted the actual run times that
could be achieved under full-scale applications. Even with increased filter depth utilization and better
drying between storms that may be achieved with full-scale applications, pretreatment of the stormwater
so the suspended solids content is about 10 mg/L is probably necessary in order to take advantage of the
pollutant retention capabilities of most of the media. This level of pretreatment, however, may make
further stormwater runoff control unnecessary. Of course, it may be more cost-effective to consider
shortened filter run times, without pretreatment, or pretreatment of only a few minutes (thus, not using all
the pollutant retention capacities of the media).
Selection of Filtration Media for Pollutant Removal Capabilities
The selection of the filter media needs to be based on the desired pollutant removal performance and the
associated conditions, such as land use. If the selection criterion were suspended solids removal for
stormwater that was not pretreated (most common), then the filtration media would be ranked according
to the following (bench-scale testing results, which may differ, reported in parentheses):
• >50% reduction for suspended solids: Sand and carbon-sand (both long- term and bench-scale
testing indicated these high suspended solids reductions)
• 20-50%: Zeolite-sand and filter fabrics (long-term testing; bench scale removals: >90% zeolite-sand,
<10% filter fabrics)
• <10%: Peat-sand and Enretech-sand (long term testing; bench scale removals: 80-90% peat-sand,
>90% Enretech-sand)
As can be seen by the comparison of the long-term testing with the bench-scale results for the neutral pH,
moderate ionic strength condition, results will vary depending on the quality of the influent, i.e., particle
size distribution of influent. Influents with a greater concentration of larger particles are likely to have
better removal efficiencies than have been found in these tests. The results of the neutral pH bench-scale
tests indicate that the dissolved solids in runoff may improve the ability of the media to trap and retain
suspended solids. It also would be expected that the longer the filter is in service, i.e., run nearer to
breakthrough or clogging, the greater the percentage of the influent suspended solids that will be
removed from solution and retained by the media.
If the filter media were being selected based upon a wider range of pollutants for normal stormwater that
is not presetted, then the ranking, based on the number of pollutants that would be removed during
filtration, would be as follows (with additional comments pertaining to degradation by other pollutants in
parentheses):
• Carbon-sand (minimal to no degradation of effluent)
79
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• Peat-sand (degradation of effluent with higher turbidity, color, COD, small particles)
• Zeolite-sand and sand (minimal degradation of effluent)
• Enretech-sand (minimal degradation of effluent)
• Compost-sand (degradation of effluent with higher color, COD, solids)
• Forest-sand and filter fabrics (minimal degradation of effluent)
All of the filters perform better after they are aged because they have the potential to build up a biofilm
that will aid in permanent retention of pollutants. Aged filters also have fewer small particles that may be
available to be washed out of the media during filtration.
Potential problems with the media were outlined in Chapter 4 for each parameter measured. However,
when selecting a media, the designer must remember that most of these media are ion-exchange
materials. This means that when ions are removed from solution by a filter medium, then other ions are
released into solution. In most instances, these exchangeable ions are not a problem in receiving waters,
but the designer should know what is being added to the water. For this activated carbon, the
exchangeable ion is mostly sulfate; while for the compost, it is usually potassium. The zeolite appears to
exchange sodium and some divalent cations (increasing hardness) for the ions it sorbs.
Another potential problem caused by stormwaters entering receiving waters is eutrophication due to the
loading of inorganic nitrogen, phosphate, or both into the water. Only the activated carbon was capable of
effectively removing nitrate from the runoff. Phosphates, which are a greater problem in most areas of the
country, were not present in the runoff that was tested, and, therefore, no judgments can be made about
the ability of these media to remove phosphate from the water.
Presettling of the stormwater was conducted to reduce the solids loadings on the filters to increase the
run times before clogging (as described below) in order to take advantage of the chemical retention
capabilities of the filters. The settling reduced the stormwater suspended solids concentrations to about
10 mg/L, with about 90% of the particles being less than 10 ^m in size (by volume and therefore assumed
by mass). The unpretreated stormwater had a suspended solids concentration of approximately 30 mg/L,
With about 90% of the particles being less than 50 urn. The presettling also reduced the other stormwater
pollutants (for example, color and turbidity by about 50%, and COD by about 90%). This presettling was
similar to what would occur in a well-designed and operated wet detention pond or in the settling chamber
of the Multi-Chamber Treatment Train. This presettling had a significant effect on filter performance, as
noted, and the rankings would be as follows, using a wide range of stormwater pollutants. Since the
Suspended solids concentration is not likely to be further reduced by the filters, it by itself would no longer
be a suitable criterion for selecting a medium.
• Carbon-sand (minimal effluent degradation)
• Peat-sand (degradation of effluent color, turbidity, pH)
• Zeolite-sand, Enretech-sand, Forest-sand, sand (min. effluent degradation)
• Compost-sand (minimal removal, color degradation)
• Filter fabrics (minimal improvement or degradation)
Obviously, the stormwater control objectives and options will significantly affect the selection of the media.
This is most evident with the compost media. If suspended solids removal alone is the criterion, and if a
slight color increase is acceptable, then the compost filter is a good choice for an unpretreated
stormwater. However, if the filter is to be used after significant pretreatment, the compost filter then is not
a very good choice.
The stormwater control objectives may dictate a combination of filter media similar to that employed in
this research for the bench-scale and long-term filter tests. The peat-sand and the compost-sand media
provide excellent removal for some pollutants but they add some potentially undesirable constituents to
the water. However, a three-layer filter may be a consideration (sand as the bottom layer, activated
carbon-sand as the middle layer, and compost-sand or peat-sand as the top layer). By sandwiching the
activated carbon-sand layer between the compost or peat and the sand layer, some color removal from
the organic media leachate may be possible. Also, the dual layer may provide additional turbidity and
80
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solids removal. The cost of activated carbon may prevent it from being used as the selected medium;
however, by using a trilayer filter setup, the cost of a small activated carbon layer would be minimal.
Operational considerations also may dictate the choice of media. For installations with no pretreatment,
the addition of a filter fabric on the top layer may be desirable. This filter fabric will trap the large particles
and postpone clogging, and it will evenly distribute the runoff across the filter and prevent bypassing of
parts of the filter. The use of a filter fabric should noticeably increase the life of the filter because the filter
fabric can be removed easily and cleaned. Cleaning the top layer of the filter itself would be significantly
more work for the filter owner. A filter fabric top layer is recommended even if the water is presettled to
facilitate flow distribution across the media.
The following list is a summary of the likely significant reductions in concentration for the filters. This list
also includes the minimum expected effluent concentrations for suspended solids, color, and turbidity.
Sand
The sand filter will provide moderate to good removal for many pollutants that are associated with
particulates and has a greater removal efficiency when the stormwater is not presettled. When the influent
was presettled, significant removal occurred only for volatile total solids, zinc, and two of the organics,
bis(2-ethylhexyl) phthalate and pentachlorophenol. Influent pH and ionic strength, acting independently,
can affect both the final effluent quality and removal efficiency with the highest effluent zinc, suspended
solids, and COD concentrations occurring when the influent pH was low and the influent salt
concentration was high.
For the sand filter, the level of control available for any parameter is associated with the retention of
suspended solids and the associated particulate fractions of pollutants. The sand filter can flush out
previously captured pollutants until the filter is aged and a biofilm is grown that will more permanently
retain pollutants. When the water is presettled, little removal benefit occurs. The likely minimum effluent
concentrations are as follows: 10 mg/Lfor suspended solids, 50 HACH color units, and 10 NTU for
turbidity.
Peat-sand
The peat-sand filter provides moderate to excellent pollutant control for most pollutants in both normal
and presettled stormwater runoff. In general, the best average removal efficiency occurred for presettled
runoff. The disadvantage of the peat-sand filter is the increase in turbidity and color in the effluent and the
reduction in the pH of approximately one to two pH units. The influent pH and ionic strength will control
both the effluent quality and removal efficiency. Low influent pH causes a poorer effluent quality for
hardness, zinc, copper, and color. High influent pH leads to higher effluent COD concentrations. The
influent ionic strength controls the effluent turbidity and zinc.
Unlike the sand filter, the peat-sand is capable of removing pollutants immediately by either sorption or
ion-exchange. Presettling of the runoff prior to filtration appears to improve the removal ability of the filter.
The drawback with the use of the peat-sand filter is the addition of turbidity and color to the effluent. Color
and turbidity can be expected to be added to the filter every time that the filter goes dry, which will occur
regularly for most stormwater filters. The expected minimum effluent concentrations for the peat-sand
filter would be 5 mg/L for suspended solids, 85 HACH color units, and 10 to 25 NTU for turbidity.
Activated carbon-sand
The carbon-sand filter provides good to excellent control for many pollutants, especially if the stormwater
is not presettled. The carbon-sand filter does not have as good a removal efficiency when the effluent has
been allowed to settle for several days. The influent pH and ionic strength will affect the effluent quality
and removal efficiency for this filter. The interaction'of these two parameters controls the effluent COD
and toxicity, and the influent ionic strength controls the turbidity and the color. The influent pH appears to
have the greatest effect on metals removal, with the greater removal efficiency and best effluent quality
occurring when the pH is above neutral. The addition of salt to the influent positively influences the
81
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effluent turbidity but provides a negative influence on the effluent toxicity, color, and-chemical oxygen
demand.
The carbon-sand filter is also capable of removing pollutants immediately upon use through either
sorption or ion-exchange. The carbon tested in these experiments uses sulfate as its exchangeable ion. A
new carbon filter, however, will wash the carbon black dust out of the filter during the first couple of
washings, and there may be a slight increase in turbidity for the first two or three storms if the runoff is
presented prior to filtration. The expected minimum effluent concentrations are 5 mg/L for suspended
solids, 25 HACH color units, and 5 NTU for turbidity.
Zeolite-sand
The zeolite-sand filter provided moderate-to-good removal for several pollutants when the runoff was not
allowed to settle prior to filtration. However, removal efficiency was not as good and occurred for fewer
parameters when the runoff was presettled. Because the zeolite particles were very large (2 to 5 mm in
diameter), the possibility exists that channels were formed in the media, and the runoff flowing through
the channels did not have sufficient contact time with the media. The influent pH and ionic strength
controlled the effluent toxicity, turbidity, chemical oxygen demand, and zinc. When the influent salt
concentrations were high, the effluent turbidity and color were lower (compared to the effluent from the
low salt influent conditions), but more hardness was added to the effluent.
The zeolite-sand mixture was expected to provide better removal than was shown in these experiments.
However, if channels were present in the media and the underlying sand layer did not provide sufficient
retention of water in the mixed zeolite-sand layer, then adequate contact time may not have been
available for pollutant removal. The other problem with this zeolite is that it was designed for ammonia
removal, and the pore size may not have been large enough to encourage removal of a wider variety of
pollutants. The expected minimum effluent concentrations are 10 mg/L suspended solids, 75 HACH color
units, and 15 NTU for turbidity.
Compost-sand
The compost-sand filter provided moderate-to-excellent removal of many pollutants when the runoff was
not presettled. However, when the runoff was presettled, the compost-sand did little to improve water
quality and worsened the color, hardness, and chemical oxygen demand of the effluent. Like the other
sorption and ion-exchange media, heavy metals' removal was good in this media even for presettled
runoff. The influent pH and ionic strength interacted to control the effluent quality and removal efficiency
for hardness, chemical oxygen demand, zinc, and copper. For the metals, the poorest effluent quality
occurred when the pH was low and the salt concentration was high. The addition of salt to the influent
caused more hardness to be present in the effluent than when the runoff's salt concentration was not
adjusted.
The compost-sand mixture has the ability to remove pollutants immediately upon use. However, like the
peat-sand filter, when the filter goes dry between storms, color-producing organics are likely released
from the medium and retained in the pores, waiting to be washed out during the next filtration. Also, the
potential exists to wash solids from the media that are small enough to avoid being trapped during
passage through the underlying sand filter. The minimum expected effluent concentrations for the
compost-sand filter are 10 mg/L for suspended solids, 100 HACH color units, and 10 NTU for turbidity.
Enretech-sand
The Enretech-sand filter provided moderate control for several pollutants in untreated runoff, but it had
little pollutant removal ability when the runoff was allowed to settle for several days. Low influent pH
caused an increase in the effluent hardness while a high influent ionic strength caused the poorest
effluent chemical oxygen demand. The interaction of pH and ionic strength controlled the removal of the
heavy metals. The minimum expected effluent concentrations for the Enretech-sand filter are 10 mg/L for
suspended solids, 80 HACH color units, and 10 NTU for turbidity.
82
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Agrofiber-sand and Filter fabrics
The agrofiber-sand filter provided little removal with the exception of the heavy metals. The filter fabrics
were capable of removing suspended solids from the runoff and pollutants associated with those solids.
Of the filter fabrics tested, the Gunderboom provided the best overall removal capability. It would be an
excellent choice for use as the top layer for gross solids removal.
Design of Filters for Specified Filtration Durations
The filtration durations measured during these tests can be used to develop preliminary filter designs. It is
recommended that allowable suspended solids loadings be used as the primary controlling factor in this
design. For these designs, clogging is defined to occur when the water flow rate through the medium
becomes less than one meter per day. Filtration, obviously, will still occur when the flow rate becomes
less than one meter per day; however, except for small rains in arid areas, much of the runoff would have
to bypass the filter and would not be treated. Tables 77 and 78 summarize the observed filtration
capacities of the different media (detailed plots of suspended solids loading versus flow rate are given in
Appendix A).
The wide ranges in filter run times as a function of water loading are dependent mostly on the suspended
solids content of the water, especially for the tests where the water was presettled. For this reason, the
suspended solids loading capacities (Table 77) are recommended for use when selecting a filter.
Table 77. Filtration capacity as a function of suspended solids loading
Filtration media
Sand
Peat-sand
Carbon-sand
Zeolite-sand
Compost-sand
Entetech-sand
Capacity to 20 ml day
(gSS/m2)
150-400
100-300
150-900
200-700
100-700
75-300
Capacity to 1 0 ml day
(gSS/nf)
400->2000
150-1000
200-1100
800-1500
200-750
125-350
Capacity to <1 ml day
(gSS/m2)
1200-4000
200-1700
500->2000
1200->2000
350-800
400-1500
Table 78. Filtration capacity of presettled water (<10 mg TSS/L influent)
Filtration media
Sand
Peat-sand .
Carbon-sand
Zeolite-sand
Compost-sand
Enretech-sand
Capacity to 20 m/day (m)
6-20
3-17
5-25
7-25
3-20
3-11
Capacity to 1 0 m/day (m)
8->25
4-22
6->25
8->25
4-30
4-25
Capacity to <1 m/day (m)
13->40
7-30
15->40
14->40
6->30
15-30
The most restrictive materials (the Enretech and Forest Products media) are very fibrous and, even when
mixed with sand, still show some compaction. The most granular media (activated carbon and zeolite) are
relatively uniform in shape and size but are very large when compared to the sand grains. Sand was used
with the carbon and the zeolite to reduce the water's flow rate through the media to increase contact time
for better pollutant removal. The sand has the highest filtration rate because it has the most uniform
shape and size.
The test observations indicate that only about 2.5 cm of the filter columns (about 10% of the column
depth) was actually used for solids retention during these tests. It is assumed that a full-scale filter could
use about 5 times these depths for solids retention if careful, selective piping to deeper depths, while.
preventing short-circuiting of the entire filter, was provided. The Metropolitan Washington (D.C.) Council
of Governments recommends placing a turf grass layer on top of the media where the roots of the grass
would cause channel development through the top layer only (Galli, 1990). They recommend that the
roots of the grass cover do not extend below about one-half the filtration depth (up to approximately 12
cm).
Mechanical removal of the clogged layer to recover filter flow rates was not found to be very satisfactory
during this research, but it has been used successfully during full-scale operations. Great care must be
83
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taken when removing this layer since loosening the media may enable trapped pollutants (associated with
the suspended solids) to be easily flushed from the media.
The flow rates through filters that have been thoroughly dried between filter runs are significantly
increased when compared to the flow rates prior to drying. The small-scale tests run here restricted
complete drying during normal inter-event periods. Drying may pccur more frequently in full-scale filters.
Wetting and drying of filters (especially peat) has been known to produce solution channels through the
media that significantly increases the flow. If these solution channels extend too far through the filter,
however, the runoff may bypass part of the media and removal efficiency will be decreased. Table 79
shows the observed increases in filter flow rates for saturated (and partially clogged filters) and the
associated flow capacity recovery for filters that have been thoroughly dried and then re-wetted. This data
is approximate (not planned as part of the initial experimental design) and was collected from the
presettled influent columns after the filters had been allowed to dry out for several weeks. After the
columns had been allowed to dry, flow rates through the columns were determined using tap water.
The filter fabrics did not indicate any flow-rate improvements with wetting and drying. As expected, the
peat-sand filter had the greatest improvement in flow capacity (by about ten times). The other media
showed more modest improvements (but still about a two to three times increase in flow rate).
Table 79. Filter flow rates for saturated and partially clogged filters and recovered filtration capacity after
thorough drying
Fitter media
Sand
Peat-sand
Carbon-sand
Zeolite-sand
Compost-sand
Enretech-sand
Forest-sand
EMCON fabric
Gunderboom fabric
Saturated/partially
clogged (m/day)
13
4
17
17
13
8.4
8.4
850
200
Recovered flow rate after drying
(m/day)
40
42
33
39
32
24
17
850
200
Increase in flow
(multiple)
3.1 X
11X
1.9X
2.3 X
2.5 X
2.9 X
2.0 X
1.0 X
1.0X
The filter capacity ranges given in Table 77 were determined from several test conditions (both bench-
scale and long-term performance testing). When designing a filter based on suspended solids removal
and required flow rate, the media may be grouped into the approximate categories shown in Table 80. A
multiplier of five (from the data shown in Table 77) was used to account for the greater anticipated filter
flow capacity associated with full-scale operations. The values given in Table 80 are total suspended
solids loadings on the filter and do not distinguish between whether the runoff is presettled or not.
Table 80. Filter categories based on capacity
Capacity to <1 m/day (gSS/mz)
5,000
5,000
10,000
15,000
Capacity to 1 0 m/day (gSS/m2)
1,250
2,500
5,000
7,500
Filtration media in category
Enretech-sand; Forest-sand
Compost-sand; Peat-sand
Zeolite-sand; Carbon-sand
Sand
Example Filter Designs
Filters can be designed based on the predicted annual discharge of suspended solids to the filtration
device and the desired filter replacement interval. As an example, volumetric runoff coefficients (Rv) (as
shown on Table 81) can be used to approximate the fraction of the annual rainfall that would occur as
runoff for various land uses and surface conditions.
Table 82 summarizes likely suspended solids concentrations associated with different urban areas and
waters.
84
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Table 81. Volumetric runoff coefficients by land use (Pitt 1996)
Area
Low density residential land use
Medium density residential land use
High density residential land use
Commercial land use
Industrial land use
Paved areas
Sandy soils
Clayey soils
Volumetric Runoff Coefficient (Rv)
0.15
0.3
0.5
0.8
0.6
0.85
0.1
0.3
Table 82. Suspended solids concentration by land use (Pitt 1996)
Source Area
Roof runoff
Paved parking, storage, driveway, streets, and walk areas
Unpaved parking and storage areas
Landscaped areas
Construction site runoff
Combined sewer overflows
Detention pond water
Mixed stormwater
Effluent after high level of pretreatment of stormwater
Suspended Solids Concentration (mg/L)
10
50
250
500
10,000
100
20
150
5
Using the information in Tables 81 and 82 and the local annual rain depth, it is possible to estimate the
annual suspended solids loading from an area and to size a needed stormwater filter. The following three
examples illustrate these simple calculations (Pitt 1996).
Example 1
A 1.0 ha paved parking lot (Rv = 0.85), in an area receiving 1.0 m of rain per year:
(50 mg SS/L) (0.85) (1 m/yr) (1 ha) (10,000 mVha) (1,000 L/m3) (g/1,000 mg)
= 425,000 g SS/yr
Therefore, if a peat/sand filter is to be used having an expected suspended solids capacity of 5,000 g/m2
before clogging, then 85 m2 of this filter will be needed for each year of desired operation for this 1.0 ha
site. This is about 0.9% of the paved area per year of operation. If this water is pretreated so the effluent
has about 5 mg/L suspended solids, then only about 0.2% of the contributing paved area would be
needed for the filter. A sand filter would only be about 1/3 of this size but would provide little added
benefit if the runoff were pretreated.
Example 2
A 100 ha medium density residential area (Rv = 0.3), 1.0 m of rain per year:
(150 mg SS/L) (0.3) (1 m/yr) (100ha) (10,000 mVha) (1,000 L/m3) (g/1,000 mg)
= 45,000,000 g SS/yr
The unit area loading of suspended solids for this residential area (425 kg SS/ha-yr) is about the same as
in the previous example (450 kg SS/ha-yr), requiring about the same area dedicated for the filter. The
reduced amount of runoff is balanced by the higher suspended solids concentration.
Example 3
A 1.0 ha rooftop in an area (Rv = 0.85) having 1.0 m of rain per year:
(10 mg SS/L) (0.85) (1 m/yr) (1 ha) (10,000 mVha) (1,000 L/m3) (g/1,000 mg)
= 85,000 g SS/yr
The unit area loading of suspended solids from this area is 85 kg SS/ha-yr and would only require a filter
about 0.2% of the roofed drainage area per year of operation.
85
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It is recommended that the filter media be about 50 cm in depth and that a surface grass cover be used
(roots should not extend below the top half of the filter). This should enable a filtration life of about five
times the basic life observed during these tests. In addition, it is highly recommended that significant
pretreatment of the water be used to reduce the suspended solids concentrations to about 10 mg/L
before filtration for pollutant removal. This pretreatment can be accomplished using grass filters, wet
detention ponds, or other specialized treatment (such as the sedimentation chamber in the multi-
chambered treatment train described by Pitt, 1996). The selection of the specific filtration media should be
based on the desired pollutant reductions, and the selection should include amendments to plain sand if
immediate and permanent pollutant reductions are desired.
A more detailed design procedure for a sand filter for stormwater treatment is given by Urbonas (1999).
Similar to the approach shown above, it is based on hydraulic capacity of the filter media. It also
specifically addresses the maintenance needs of the filter media by inserting a maintenance frequency
variable into the TSS removal calculation. Future work by the UAB group also will be addressing
maintenance issues. This difference between the UAB group and Urbonas' work will be investigating the
impact that the non-sand media have on required maintenance cycles and life of the filter before media
replacement will be needed. In order to compare our results to the results of Urbonas and others, sand
will be used as a control filter.
86
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95
-------
-------
Appendix A:
Loadings on Media
A-1
-------
Carbon-Sand
Pre-Treated
Neutral pH, Salt
UwpHNoSalt
T-HghpH,NoSalt
<> LowpHSalt
•O" Hgh pH, Salt
'V",
T
T
200 400 600 800 1000 1200
Suspended Solids Loading on Media (gtaf)
1400 1600
A-2
-------
Compost-Sand
160
$
DC
140-
120-
100-
80-
200
-®~ Pre-Treated
-»- Neutral pH, Salt
-A- Low pH, No Salt
-V- High pH, No Salt
-<|> Low pH, Salt
™
-------
Enretech-Sand
160-
140-
120-
100-
80-
60H
40-
20-
Pre-Treated
-»- Neutra! pH, Salt
-A- Low pH, No Salt
-^- High pH, No Salt
-<^ LowpH, Salt
-O«' High pH, Salt
'-0-
-0-
1 1 1 1 1 1—
0 200 400 600 800 1000 1200
Suspended Solids Loading on Media (g/m2)
—I
1400 1600
A-4
-------
Peat-Sand
200 400
i 1 r
800 1000 1200 1400 1600
Suspended Solids Loading on Media (g^m
A-5
-------
Sand
Pre-Treated
-m- Neutral pH, Salt
-A- Low pH, No Salt
-T- Hgh pH, No Salt
- LowpH, Salt
--0- Hgh pH, Salt
200
1 ,— 1 -p-
400 600 800 1000 1200
Suspended Solids Loading on Media (g/nf)
1400
1600
A-6
-------
Zeolite-Sand
—@— Pre-Treated
-»- Neutral pH, Salt
-A-Low pH, No Salt
High pH, No Salt
LowpK Salt
Ugh pH, Salt
200 400
800 1000 1200 1400 1600
Suspended Solids Loading on Media (g/m)
A-7
-------
-------
Appendix B:
Bench-Scale Test Results
Toxicity
Turbidity
Conductivity
Color
pH
Chemical Oxygen Demand
Hardness
Suspended Solids
Particle Size Distribution (6 to 8 jam)
Particle Size Distribution (20 to 22 jam)
Particle Size Distribution (52 to 54 ^m)
Particle Size Distribution (4 to 128 jam)
Zinc
Copper
B-1
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Low pH, Low Salt
0 3 6 9 12 15
••' Loading on Media (m)
High pH, Low Salt
120
12 15
Loading on Media (m)
Neutral pH, High Salt
120-
80-
40 H
0 3 6 9 12 15
Loading on Media (m)
Low pH, High Salt
— Blank
~•— Carton-Sand
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-•— Sand
High pH, High Salt
120-
I 80-
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IO
c\i
Loading on Media (m)
1 I I
0 3 6 9 12 15
Loading on Media (m)
TOXICITY: Bench-Scale Testing
B-6
-------
CONTRAST TABLE
EFFLUENT QUALITY
TOXICITY
CARBON-SAND
Run#
1
2
3
4
Effect
PH
-1
1
-1
1
44
Salt
-1
-1
1
1
45
(pH)(Salt)
1
-1
-1
1
40
Result
1
6
7
91
26
#0bs.
6
6
6
6
S.E.
1
6
4
6
4
PEAT-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
-11
Salt
-1
-1
1
1
49
(pHXSalt)
1
-1
-1
1
-10
Result
3
2
62
42
27
#Obs.
6
6
6
6
S.E.
3
1
11
11
8
ZEOLITE-SAND
Run*
1
2
3
4
Effect
pH
-1
1
-1
1
83
Salt
-1
-1
1
1
8
(pHXSalt)
1
-1
-1
1
14
Result
6
75
0
97
44
#Obs.
6
6
6
6
S.E.
3
8
0
4
4
COMPOST-SAND
Run*
1
2
3
4
Effect
pH
-1
1
-1
1
4
Salt
-1
-1
1
1
1
(PH)(Salt)
1
-1
-1
1
3
Result
3
5
1
8
4
#Obs.
6
6
5
3
S.E.
3
2
1
3
3
ENRETECH-SAND
Run*
1
2
3
4
Effect
pH
-1
1
-1
1
75
Salt
-1
-1
1
1
13
(pHXSalt)
1
-1
-1
1
5
Result
9
80
18
97
51
#Obs.
6
6
6
6
S.E.
5
8
4
3
5
SAND
Run*
1
2
3
•4
Effect
pH
-1
1
-1
1
84
Salt
-1
-1
1
1
14
(pHXSalt)
1
-1
-1
1
1
Result
0
83
14
98
49
#Obs.
6
6
6
6
S.E.
0
5
3
2
3
B-7
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
TOXICITY
CARBON-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-30
Salt
-1
-1
1
1
-58
(pHXSalO
1
-1
-1
1
-23
Result
95
88
60
7
62
#Obs.
5
6
6
6
S.E.
5.20
12.17
21.94
5.84
14
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
143
Salt
-1
-1
1
1
-172
(DHXSalO
1
-1
-1
1
132
Result
86
97
-218
58
6
#Obs.
5
6
6
6
S.E.
14.00
0.82
82.44
11.18
44
ZEOLITE-SAND
Run *
1
2
3
4
Effect
DH
-1
1
-1
1
-72
Salt
-1
-1
1
1
22
foHMSalt)
1
-1
-1
1
-27
Result
51
6
100
2
40
#Obs.
5
6
5
6
S.E.
33.14
8.28
0.00
1.50
16
COMPOST-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
I
2
Salt
-1
-1
1 .
1
4
foHXSalt)
1
-1
-1
1
-7
Result
86
95
97
92
93
#Obs.
5
6
5
3
S.E.
14.00
2.33
1.96
2.65
8
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
42
Salt
-1
-1
1
1
51
CoHMSalO
1
-1
-1
1
-50
Result
-93
-1
8
1
-21
#Obs.
5
6
6
6
S.E.
111.69
8.81
27.51
0.83
50
'IB-1
SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-72
Salt
-1
-1
1
1
-28
(pHKSalt)
1
-1
-1
1
34
Result
100
-6
38
0
33
#Obs.
5
6
6
6
S.E.
0.00
5.95
19.90
0.00
11
B-8
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Low pH, Low Salt
High pH, Low Salt
80 •
40 -
I I I I
0 3 6 9 12 15
Loading on Media (m)
80-
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I I I I
0 3 6 9 12 15
Loading on Media (m)
Neutral pH, High Salt
80-
40 -
Loading on Media (m)
—•—'Blank
—«— Carbon-Sand
—'— Peat-Sand
—r— Zeolite-Sand
—o— Compost-Sand
—•— Enretech-Sand
—•— Sand
Low pH, High Salt
80-
40 -
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0 3 6 9 12 15
Loading on Media (m)
High pH, High Salt
80 •
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0 3 6 9 12 15
Loading on Media (m)
TURBIDITY: Bench-Scale Testing
B-13
-------
CONTRAST TABLE
EFFLUENT QUALITY
TURBIDITY
CARBON-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
0.03
Salt
-1
-1
1
1
-1.32
(oH)fSalt)
1
-1
-1
1
-1.93
Result
2.05
4.02
2.67
0.77
2.38
#Obs.
6
6
6
6
S.E.
0.40
1.34
0.94
0.09
0.85
PEAT-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
13
Salt
-1
-1
1
1
-13
(oHKSalO
1
-1
-1
1
-9
Result
16.90
38.83
12.55
16.92
21.30
#Obs.
6
6
6
6
S.E.
3.11
5.29
3.34
6.10
4.64
ZEOLITE-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-1
1
-1
Salt
-1
-1
1
1
-5
(nHKSalt)
1
-1
-1
1
-2
Result
6.67
8.38
4.27
1.26
5.14
#Obs.
6
6
6
6
S.E.
0.87
2.21
0.98
0.22
1.29
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
7
Salt
-1
-1
1
1
4
(oHKSalt)
1
-1
-1
1
1
Result
11.40
18.00
14.90
22.67
16.74
#0bs.
6
6
5
3
S.E.
2.07
3.21
3.64
3.38
3.11
ENRETECH-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-6
Salt
-1
-1
1
1
-4
(oHXSalt)
1
-1
-1
1
-4
Result
11.52
9.33
11.08
1.12
8.26
#Obs.
6
6
6
6
S.E.
1.63
2.02
4.72
0.06
2.69
SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-5
Salt
-1
-1
1
1
-5
(DH)CSalO
1
-1
-1
1
-1
Result
11.50
6.90
7.48
1.67
6.89
#0bs.
6
6
6
6
S.E.
2.86
2.04
2.78
0.29
2.25
B-14
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
TURBIDITY
CARBON-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
0
Salt
-1
-1
1
1
20
(oHXSalt)
1
-1
-1
1
9
Result
74
66
85
95
80
#Obs.
6
6
6
6
S.E.
6.12
9.89
2.17
1.78
6
, PEAT-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-93
Salt
-1
-1
1
1
177
(oHHSalt)
1
-1
-1
1
51
Result
-104
-248
22
-20
-87
#Obs.
6
6
6
6
S.E.
35.80
50.90
10.95
48.41
40
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-32
Salt
-1
-1
1
1
16
foHKSalt)
1
-1
-1
1
-40
Result
17
25
73
2
29
#Obs.
6
6
6
6
S.E.
14.07
20.16
3.61
1.50
12
COMPOST-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-45
Salt
-1
-1
1
1
-1
(DH)(Salt)
1
-1
-1
1
-24
Result
-41
-61
-17
-87
-51
#0bs.
6
6
5
3
S.E.
25.39
28.39
22.92
10.04
26
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
57
Salt
-1
-1
1
1
83
foHySalt)
1
-1
-1
1
-9
Result
-47
19
44
93
27
#Obs.
6
6
6
6
S.E.
23.88
15.90
14.11
1.88
16
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
53
Salt
-1
-1
1
1
71
(oHHSalt)
1
-1
-1
1
-23
Result
-36
40
58
88
38
#Obs.
5
6
6
6
S.E.
28.16
16.13
8.79
3.67
17
B-15
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B-19
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Low pH, Low Salt
High pH, Low Salt
300-
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Loading on Media (m)
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11000 -
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Loading on Media (m)
Low pH, High Salt
11000-
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Loading on Media (m)
300-
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Loading on Media (m)
Bank
Carbon-Sand
Peat-Sand
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Sand
High pH, High Salt
11030-
10000-
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0 3 6 9 12 15
Loading on Media (m)
CONDUCTIVITY: Bench-Scale Testing
B-20
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LowpH, Low Salt
High pH, Low Salt
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80-
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Loading on Media (m)
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120-
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CXX.OR: Bench-Scale Testing
B-25
-------
CONTRAST TABLE
EFFLUENT QUALITY
COLOR
CARBON-SAND
Run #
1
2
3
4
Effect
nH
-1
1
-1
1
2
Salt
-1
-1
1
1
6
foHMSalt)
1
-1
-1
1
-1
Result
24
27
31
32
29
#Obs.
6
6
6
6
S.E.
4
2
2
0
9
PEAT-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
18
Salt
-1
-1
1
1
-6
(oHHSalt)
1
-1
-1
1
6
Result
88
100
76
100
91
#Obs.
6
6
6
6
S.E.
4
0
7
0
4
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
3
Salt
-1
-1
1
1
-13
foHKSalt)
1
-1
-1
1
5
Result
69
67
51
59
61
#Obs.
6
6
6
6
S.E.
3
8
2
1
4
COMPOST-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-1
1
0
Salt
-1
-1
1
1
0
fomrsaio
i
-i
-i
i
0
Result
100
100
100
100
100
#Obs.
6
6
5
3
S.E.
1
0
0
0
0
ENRETECH-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
2
Salt
-1
-1
1
1
-5
fDH)(Salt)
1
-1
-1
1
5
Result
69
66
59
66
65
#Obs.
6
6
6
6
S.E.
6
2
12
1
7
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-7
Salt
-1
-1
1
1
-13
foHVSalO
1
-1
-1
1
4
Result
70
59
53
50
58
#Obs.
6
6
6
6
S.E.
6
7
8
1
6
B-26
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
COLOR
CARBON-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
4.67
Salt
-1
-1
1
1
-4.00
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•1
-1
-1
1
-1.83
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67
. 73
65
67
67.92
# Obs.
6
6
6
6
S.E.
5.19
2.39
2.31
9.97
5.86
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
1.83
Salt
-1
-1
1
r
15.67
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1
-1
-1
1
-16.50
Result
-18
0
14
-1
-1.33
#Obs.
6
6
6
6
S.E.
7.66
0.00
4.27
0.83
4.40
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
13.67
Salt
-1
-1
1
1
19.33
(oHXSalt)
1
-1
-1
1
-8.50
Result
8
30
3.6
41
28.42
#Obs.
6
6
6
6
S.E.
5.06
7.96
1.71
0.88
4.81
COMPOST-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
25.45
Salt
-1
-1
1
1
7.05
(oHHSalt)
1
-1
-1
1
-8.72
Result
-34
0
-18
-2
-13.56
#Obs.
6
6
5
3
S.E.
6.50
0.00
5.32
1.67
4.81
El
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
12.83
Salt
-1
-1
1
1
13.83
•4RETECH-SAND
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1
-1
-1
1
-14.50
Result
7
34
35
34
27.58
# Obs.
6
6
6
6
S.E.
9.48
2.20
10.48
0.88
7.16
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
21.08
Salt
-1
-1
1
1
21.08
(DH)CSalt)
1
-1
-1
1
-12.42
Result
7
41
41
50
34.63
#Obs.
6
6
6
6
S.E.
4.60
7.24
6.85
0.92
5.51
B-27
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B-32
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B-36
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LowpH, Low Salt
200-
150-
100-
50-
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0 3 6 9 12 15
Loading on Media (m)
High pH, Low Salt
•200-
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0 3 6 9 12 15
Loading on Media (m)
Neutral pH, High Salt
200-
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Loading on Media (m)
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200-
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Loading on Media (m)
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Peat-Sand
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High pH, High Salt
200-
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Loading on Media (m)
CHEMICAL OXYGEN DEMAND:
Bench-Scale Testing
B-37
-------
I) ill.
li ill
CONTRAST TABLE
EFFLUENT QUALITY
COD
CARBON-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-I
1
-5
Salt
-1
-1
1
1
9
(nHMSalt)
1
-1
-1
1
7
Result
12
0
14
15
10
#Obs.
6
6
6
6
S.E.
4
0
1
1
2
PEAT-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
11
Salt
-1
-1
1
1
19
foHHSalt)
1
-1
-1
1
24
Result
43
29
37
72
45
#Obs.
6
6
6
6
S.E.
2
2
2
6
3
ZEOLITE-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-1
1
-11
Salt
-1
-1
1
1
20
(oHHSalt)
1
-1
-1
1
12
Result
34
11
42
43
32
#Obs.
6
6
6
6
S.E.
3
3
2
5
3
COMPOST-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-1
1
31
Salt
-1
-1
1
1
70
foHHSalt)
1
-1
-1
1
39
Result
49
41
80
150
80
#Obs.
6
6
5
3
S.E.
8
8
7
27
11
ENRETECH-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
6
Salt
-1
-1
1
1
16
(oHXSalt)
1
-1
-1
1
-8
Result
20
34
43
41
34
#Obs.
6
6
6
6
S.E.
6
11
1
5
6
SAND
Run*
1
2
3
4
Effect
uH
-1
1
-1
1
0
Salt
-1
-1
1
1
-5
rnHVSalO
1
-1
-1
1
-9
Result
39
47
43
34
41
#Obs.
6
6
6
6
S.E.
2
3
3
1
2
B-38
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-------
CONTRAST TABLE
REMOVAL EFFICIENCY
COD
CARBON-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
5.75
Salt
-1
-1
1
1
-11.25
(pHKSam
1
-1
-1
'1
-10.25
Result
84
' 100
83
79
86.38
#Obs.
6
6
6
6
S.E.
5.39
0.00
2.62
2.55
3.26
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-36.75
Salt
--1
-1
1
1
-5.42
(oHHSalt)
1
-1
-1
1
-17.58
Result
40
20
52
-3
27.21
#Obs.
6
6
6
6
S.E.
2.22
10.59
7.19
11.57
8.70
ZEOLITE-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
5.42
Salt
-1
-1
1
1
-19.58
fpHKSalt)
1
-1
-1
1
-14.25
Result
52
71
46
38
51.71
#Obs.
6
6
6
6
S.E.
4.51
7.30
6.32
11.03
7.67
COMPOST-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-83.67
Salt
-1
-1
1
1
-81.83
(oHHSalt)
1
-1
-1
1
-35.67
Result
30
-18
-16
-135
-34.75
#Obs.
6
6
5
3
S.E.
12.39
32.33
11.79
64.66
28.25
ENRETECH-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-28.17
Salt
-1
-1
1
1
-1.83
(pHXSalt)
1
-1
-1
1
25.50
Result
72
18
45
42
44.25
#Obs.
6
6
6
6
S.E.
8.21
25.02
6.80
8.45
14.24
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-31.58
Salt
-1
-1
1
1
40.25
(DHXSalt)
1
-1
-1
1
37.92
Result
44
-26
46
53
29.21
#Obs.
6
6
6
6
S.E.
3.56
12.70
5.85
4.26
7.52
B-39
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B-42
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Low pH, Low Salt
200-
100-
»-«--
i nn j
;; o 36 9 12 15
Loading on Media (m)
High pH, Low Salt
400-
300-
200-
100-
0 3 6 9 12 15
Loading on Media (m)
Neutral pH, High Salt
300-
200-
100-
6
<*if=st=»«-^l
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0 3 6 9 12 15
Loading on Media (m)
Low pH, High Salt
300-
200-
100-
n i i \
0 3 6 9 12 15
Loading on Media (m)
-•— Bank
—•— Cartxn-Sand
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-T- Zeolite-Sand
—>— Compost-Sand
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-*- Sand
High pH, High Salt
400-
300-
200-
100-
0
l l l ;i
0369 12 15
Loading on Media (m)
HARDNESS: Bench-Scale Testing
B-44
-------
CONTRAST TABLE
EFFLUENT QUALITY
HARDNESS
CARBON-SAND
Run*
1
2
3
4
Effect
DH
-1 -
1
-1
1
-27
Salt
-1
-1
1
1
14
(DHHSalt)
1
-1
-1
1
0
Result
76
49
90
64
70
#0bs.
6
6
6
6
S.E.
3
2
4
1
3
PEAT-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-51
Salt
-1
-1
1
1
5
(pHXSalt)
1
-1
-1
1
-13
Result
73
35
91
27
56
#Obs.
6
6
6
6
S.E.
4
10
3
5
6
ZEOLITE-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-16
Salt
-1
-1
1
1
128
(oH)fSalt)
1
-1
-1
1
-1
Result
92
77
221
204
148
#Obs.
6
6
6
6
S.E.
2
8
23
14
14
COMPOST-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-51
Salt
-1
-1
1
1
97
(DH)fSalt)
1
-1
-1
1
21
Result
122
51
199
169
135
#Obs.
6
6
5
3
S.E.
8
4
19
31
14
ENRETECH-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-24
Salt
-1
-1
1
1
7
(oHHSalt)
1
-1
-1
1
-5
Result
87
68
99
70
81
#Obs.
6
6'
6
6
S.E.
5
1
3
4
3
SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-17
Salt
-1
-1
1
1
10
(oHXSalt)
1
-1
-1
1
1
Result
80
62
89
73
76
#Obs.
6
6
6
6
S.E.
2
2
2
3
2
B-45
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
HARDNESS
CARBON-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
11.17
Salt
-1
-1
1
1
-7.33
(oHHSalrt
1
-1
-1
1
-2.50
Result
13
27
9
17
16.50
#Obs.
6
6
6
6
S.E.
4.77
4.49
1.82
2.47
3.62
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
46.17
Salt
-1
-1
1
1
1.83
(oHHSalt)
1
-1
-1
I
13.33
Result
18
51
6
66
35.00
#Obs.
6
6
6
6
S.E.
5.85
12.37
4.21
6.25
7.81
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-23.33
Salt
-1
-1
1
1
-137.50
(oHKSalt)
1
-1
-1
1
-13.17
Result
-5
-15
-129
-166
-78.67
# Obs.
6
6
6
6
S.E.
6.66
13.53
28.42
16.21
18.01
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
-1
1
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1
29.83
Salt
-1
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1
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1
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-38
25
-114
-117
-61.00
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6
6
5
3
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7.25
5.85
18.33
37.77
14.95
E
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1
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5.50
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1
1
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1
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6.00
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0
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9
1.58
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6
6
6
6
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10.62
3.57
1.92
4.40
6.10
SAND
Run#
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-1
1
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1
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-1
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1
1
-2.08
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1
-1
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1
-1.75
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10
9
9
5
7.96
#Obs.
6
6
6
6
S.E.
5.10
3.91
2.87
4.77
4.25
B-46
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B-50
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HghpH, Low Salt
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Leading on Media (m)
Loading on Media (m)
Neutral pH Ugh Salt
280-
240-
200-
160-
120-
80-
40-
0
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0 2 4 6 8 10 12 14
Loading on Media (m)
Bank
Carbon-Sand
Peat-Sand
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Sand
Low pH, High Salt
High pH, High Salt
I I 1 1 I T
0 2 4 6 8 10 12 14
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rr-7
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2 4 6 8 10 12 14
Loading on Media (m)
SUSPENDED SOUDS: Bench-Scale Testing
B-51
-------
II' " II.
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CONTRAST TABLE
EFFLUENT QUALITY
SUSPENDED SOLIDS
CARBON-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-15.08
Salt
-1
-1
1
1
15.08
(oHKSalt)
1
-1
-1
1
-15.92
Result
0.33
1.17
31.33
0.33
8.29
#Obs.
6
6
6
6
S.E.
0.33
0.83
2.12
0.33
1.16
PEAT-SAND
Run#
1 ,
2
3
4
Effect
DH
-1
1
-1
1
-6
Salt
-1
-1
1
1
9
(oHMSalt)
1
-1
-1
1
-15
Result
2.00
11.17
26.33
4.67
11.04
#Obs.
6
6
6
6
S.E.
0.86
1.35
2.49
1.74
1.72
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-12
Salt
-1
-1
1
1
14
(oHKSalt)
1
-1
-1
1
-14
Result
0.33
1.83
28.67
2.33
8.29
#0bs.
6
6
6
6
S.E.
0.21
0.21
1.67
0.80
0.94
COMPOST-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-6
Salt
-1
-1
1
1
19
foHVSalt)
1
-1
-1
1
-10
Result
2.17
6.00
31.00
14.33
13.38
#Obs.
6
6
5
3
S.E.
0.79
1.71
3.49
2.91
2.24
ENRETECH-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-13
Salt
-1
-1
1
1
13
foHKSalt)
1
-1
-1
1
-14
Result
1.50
2.83
27.83
1.50
8.42
#Obs.
6
6
6
6
S.E.
0.43
0.54
1.45
0.96
0.93
SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-11
Salt
-1
-1
1
1
10
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1
-1
-1
1
-13
Result
0.50
2.50
23.50
0.33
6.71
#Obs.
6
6
6
6
S.E.
0.34
0.89
2.79
0.21
1.48
B-52
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-------
CONTRAST TABLE
REMOVAL EFFICIENCY
SUSPENDED SOLIDS
CARBON-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
18.58
Salt
-1
-1
1
1
-18.92
(oHKSalt)
1
-1
-1
1
20.92
Result
99
97
60
99
88.71
#Obs.
6
6
6
6
S.E.
0.67
2.29
9.40
1.00
4.88
PEAT-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
8.75
Salt
-1
-1
1
1
2.58
(DH)fSalt)
1
-1
-1
1
17.75
Result
82
73
67
93
78.63
#Obs.
6
6
6
6
S.E.
10.49
4.20
6.78
2.56
6.71
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
18.17
Salt
-1
-1
1
1
-15.50
foHVSalt)
1
-1
-1
1
16.17
Result
94
96
62
96
86.92
#Obs.
6
6
6
6
S.E.
5.40
3.28
8.21
1.73
5.25
COMPOST-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
14.92
Salt
-1
-1
1
1
-16.75
(pHXSalt)
1
-1
-1
1
2.08
Result
73
86
54
71
70.88
#Obs.
6
6
5
3
S.E. .
21.31
4.21
9.35
12.22
14.49
ENRETECH-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
21.17
Salt
-1
-1
1
1
-7.67
(oHVSalt)
1
-1
-1
1
11.33
Result
85
94
66
98
85.58
#Obs.
6
6
6
6
S.E.
10.44
1.58
'f 6.85
1.44
6.33
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
17-.33
Salt
-1
•-1
1
1
-6.00
(pmCSalt)
1
-1
-1
1
11.33
Result
88
94
71
100
88.33
#Obs.
6
6
6
6
S.E.
11.08
1.94
6.70
0.21
6.55
B-53
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oo" *J so" tn oo" oo"
r*i r- co CM Q
\O ON O OO ~\
r- oo CM o
o -^ »n" cT J5
m — oo in 2
o oo — ^ « .
co" co" "n" »n ^
— CM co -^ »n so
rt rt rt rt rt rt
o o o a o o
•o
CO
a.
\
O O O1
ON ON ON o o o
r-» CM oo »n co o
— « oo -^f oo t~- o
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co c-l to — ' — r-i
— • ON ON 00 g 5i
r>» cs oo r- °°~ Vl-
o
-------
o
IX)
a
X) X) XI X>
O O O O O O
0 VO ON < < <
QO CM * vi v>
1/1 ^. •> O O O
_ ^ c c- c
5 S 5 S? 1 K
(N CM OO C1- - -
v{ ^f ^ QQ en jo
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o-f CM" -cf" vo 2 ™
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-------
Low pH, Low Salt
'•£
"E
'Hit
': ; o
J""""
3
1
Q
•4f>
ID
14-
12-
10-
8-
6-
4-
2-
*-7^*-^^
Z V
u— u u ~u — ~-%t
n o /i c o m 10 i
Loading on Media (m)
_ Neutral pH, High Salt
0 2 4 6 8 10 12 14
Loading on Media (m)
Low pH, High Salt
16-
14-
12-
0 2 4 6 8 10 12 14
Loading on Media (m)
High pH, Low Salt
0 2 4 6 8 10 12 14
Loading on Media (m)
-*— Hank
—•— Carbon-Sand
—*— Peat-Sand
—» Zeolite-Sand
—a— Conpost-Sand
—*— Enretech-Sand
•o Sand
High pH, High Salt
2 4 6 8 10 12 14
Loading on Media (m)
PAFmCLE SIZE CHSTRIBUnON: Bench-Scale Testing
(6 to 8 nm)
B-58
-------
CONTRAST TABLE
FINAL EFFLUENT
PSD (6 to 8 urn)
CARBON-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-66112
Salt
-1
-1
1
1
-59273
(oHKSalt)
1
-1
-1
1
29436
Result
176629
81081
87920
51245
99219
#Obs.
6
6
6
6
S.E.
73971
14349
36719
14788
42558
PEAT-SAND
Run*
1
2
3
4
Effect
pH
-1
1
-1
1
742666
Salt
-1
-1
1
1
-386578
foHHSalt)
I
-1
-1
1
-280677
Result
178648
1201991
72747
534736
497031
# Obs.
6
6
6
6
S.E.
33977
193714
18994
144903
122513
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
22429
Salt
-1
-1
1
1
-61359
(DHKSalO
1
-1
-1
1
-60970
Result
61121
144519
60731
22191
72140
#Obs.
6
6
6
6
S.E.
12405
66073
11901
3692
34186
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
_j
1
-1
1
595744
Salt
-1
-1
1
1
-139980
foHMSalt)
1
_j
-1
1
-43792
Result
871625
1511161
775437
1327389
1121403
#Obs.
6
6
5
3
S.E.
490420
499532
90503
424943
446494
ENRETECH-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-32637
Salt
-1
-1
1
1
-90331
(oHXSalt)
1
-1
-1
1
-1178
Result
167898
136439
78744
44930
107003
#Obs.
6
6
6
6
S.E.
32578
41084
19365
9563
28354
SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-38406
Salt
-1
-1
1
1
-35361
(DtWSalt)
1
-1
-1
1
26314
Result
130833
66113
69158
57067
80793
#Obs.
6
6
6
6
S.E.
32774
16583
18833
6950
20929
B-59
-------
lil"1!}'1' "if1 "
CONTRAST TABLE
REMOVAL EFFICIENCY
PSD (6 to 8 um)
CARBON-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
2.20
Salt
-1
-1
1
1
1.80
(pHXSalO
1
-1
-1
1
-1.13
Result
95
98
98
99
97.23
#Obs.
6
6
5
6
S.E.
2.32
0.37
1.66
0.71
1.47
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-18.02
Salt
-1
-1
1
1
8.68
(pHXSalt)
1
-1
-1
1
4.82
Result
94
72
98
85
87.26
# Obs.
6
6
5
6
S.E.
0.99
4.10
0.66
6.89
4.24
ii, "1 ' i
ZEOLITE-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-0.40
Salt
-1
-1
1
1
1.90
(pH)(Salt)
1
-1
-1
1
1.10
Result
98
97
99
100
98.20
#Obs.
6
6
5
6
S.E.
0.26
1.52
0.20
0.22
0.82
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-16.71
Salt
-1
-1
1
1
1.38
(pHXSalt)
1
-1
-1
1
-6.21
Result
74
63
81
58
69.10
#Obs.
6
6
4
3
S.E.
14.51
12.29
4.37
16.48
12.14
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
1.32
Salt
-1
-1
1
1
2.85
(oHXSalt)
1
-1
-1
1
-0.52
Result
95
97
98
99
97.18
# Obs.
6
6
5
6
S.E.
0.83
1.02
0.37
0.37
0.73
SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
1.28
Salt
-1
-1
1
1
1.38
(oHXSalt)
1
-1
-1
1
-1.05
Result
96
99
99
99
98.03
#Obs.
6
6
5
6
S.E.
1.11
0.34
0.51
0.31
0.67
B-60
-------
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B-64
-------
Low pH, Low Salt
16
12-
8H
§
0 2 4 6 8 10 12 14
Loading on Media (m)
Neutral pH, High Salt
16-
12-
8-
5 4^
0 2 4 6 8 10 12 14
Loading on Media (m)
Low pH, High Salt
0 2 4 6 8 10 12 14
Loading on Media (m)
High pH, Low Salt
•16
12-
o _
4-
g 0
S
0 2 4 6 8 10 12 14
Loading on Media (m)
Blank
Carbon-Sand
Peat-Sand
Zeolite-Sand
Compost-Sand
Enretech-Sand
Sand
High pH, High Salt
I I I T
0 2 4 6 8 10 12 14
Loading on Media (m)
PARTICLE SIZE DISTRIBUTION: Bench-Scale Testing
(20 to 22 urn)
B-65
-------
CONTRAST TABLE
EFFLUENT QUALITY
PSD (20 to 22
CARBON-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-110725
Salt
-1
-1
1
1
-39958
(oHMSalt)
1
-1
-1
1
58683
Result
221144
51736
122503
70461
116461
#Obs.
6
6
6
6
S.E.
182751
14594
83600
15200
101033
• t '
PEAT-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
59724
Salt
-1
-1
1
1
-47689
foHHSalt)
1
-1
-1
1
-37146
Result
66711
163581
56168
78747
91302
#Obs.
6
6
6
6
S.E.
16752
16526
36082
7265
21843
ZEOLITE-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
68874
Salt
-1
-1
1
I
-26225
foHMSalrt
1
-1
-1
1
-59435
Result
30026
158334
63236
72674
81068
#0bs.
6
6
6
6
S.E.
8779
58089
13081
25849
32752
COMPOST-SAND
Run #
1
2
3
4
Effect
oH
-1
1
-1
1
-2576
Salt
-1
-1
1
1
-6124
foHXSalt)
1
-1
-1
1
-20477
Result
70319
88220
84671
61619
76207
#Obs.
6
6
5
3
S.E.
15426
36789
28096
5573
28221
ENRETECH-SAND
Run #
1
2
3
4
Effect
DH
-1
1
-1
1
12747
Salt
-1
-1
1
1
4934
foHX'Salt)
1
-1
-1
1
8047
Result
43811
48511
40698
61491
48628
#0bs.
6
6
6
6
S.E.
10547
6278
8500
19890
12435
SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
12873
Salt
-1
-1
1
1
1693
fomrsam
1
-1
-1
1
14514
Result
59720
58080
46900
74286
59746
#0bs.
6
6
6
6
S.E.
18641
7709
7328
11436
12159
B-66
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
PSD (20 to 22 um)
CARBON-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
6.33
Salt
-1
-1
1
1
1.00
(oHKSalt)
1
-1
-1
1
-1,17
Result
90
97
92
97
94.08
#Obs.
6
6
5
6
S.E.
8.38
0.76
6.51
1 11
5.25
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-2.00
Salt
-1
-1
1
1
2.00
(pHXSalt)
1
-1
-1
1
3.17
Result
97
92
96
97
95.58
#Obs.
6
6
5
6
S E
0.60
0.37
1.64
0.60
0.85
ZEOLITE-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-3.23
Salt
-1
-1
1
1
2.07
(DHXSalO
1
-1
-1
1
2.77
Result
99
93
98
97
96.53
#Obs.
6
6
5
6
S.E.
0.50
2.43
0.58
1.26
1.48
COMPOST-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-0.21
Salt
-1
-1
1
1
0.21
(pHXSalt)
1
-1
-1
1
1.13
Result
97
95
96
97
96.10
#Obs.
6
6
4
3
S.E.
0.80
2.17
2.59
0.33
1.68
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-0.83
Salt
-1
-1
1
1
0.67
(oHMSalty
1
-1
-1
1
-0.33
Result
98
98
99
98
98.08
#Obs.
6
6
5
6
S.E.
0.63
0.43
0.32
0.87
0.62
SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-0.27
Salt
-1
-1
1
1
0.77
(DH)CSalt)
1
-1
-1
1
-0.27
Result
97
97
98
98
97.55
#Obs.
6
6
5
6
S.E.
0.95
0.40
0.49
0.61
0.66
B-67
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B-71
-------
LowpH, Low Salt
High pH, Low Salt
0 2 4 6 8 10 12 14
Loading on Media (m)
Neutral pH, High Salt
3-
2~
5 1-
r*T*r-l
0 2 4 6 8 10 12 14
Loading on Media (m)
LowpH, High Salt
0 2 4 6 8 10 12 14
Loading on Media (m)
0 2 4 6 8 10 12 14
Loading on Media (m)
-*- Bank
—•— Carbon-Sand
—*— Peat-Sand
•-•*•- Zeolite-Sand
-~»~~ Compost-Sand
—•— Enretech-Sand
»•- Sand
High pH, High Salt
G 0 2 4 6 8 10 12 14
Loading on Media (m)
PAFmCLE SIZE DiSTRIBimON: Bench-Scale Testing
(52to54jLim)
B-72
-------
CONTRAST TABLE
EFFLUENT QUALITY
PSD (52 to 54 um)
CARBON-SAND
Run*
1
2
3
4
Effect
DH
-i
1
-1
1
-12974
Salt
-1
-1
1
1
24813
(DHHSalO
1
-1
-1
1
1709
Result
20672
5989
43776
32511
25737
#Obs.
6
6
6
6
S.E.
10379
5989
15974
12185
1 1696
PEAT-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-107128
Salt
-1
-1
1
1
97706
(oHXSalt)
1
-1
-1
1
-117108
Result
22827
32807
237641
13405
76670
#Obs.
6
6
6
6
S.E.
16698
17273
180640
7066
91184
ZEOLITE-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
36456
Salt
-1
-1
1
1
14021
(DH)CSalt)
1
-1
-1
1
13368
Result
15508
38595
16161
65984
34062
#Obs.
6
6
6
6
^
S.E.
10664
16060
7275
53961
28880
COMPOST-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
2509
Salt
-1
-1
1
1
8482
(oH)fSalt)
1
-1
-1
1
-8051
Result
0
10560
16534
10991
9521
#Obs.
6
6
5
3
S.E.
0
6688
6982
10991
6166
ENRETECH-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-50585
Salt
-1
-1
1
1
38770
foKKSalt)
1
-1
-1
1
-40106
Result
38453
27974
117329
26638
52599
#Obs.
6
6
6
6
S.E.
13429
10109
84792
26638
45227
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
184
Salt
-1
-1
1
1
184
(0H)(Salt)
1
-1
-1
1
-10320
Result
20998
31502
31502
21366
26342
#Obs.
6
6
6
6
S.E.
13285
16338
16338
10582
14338
B-73
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
PSD (52'to 54 um)
CARBON-SAND
Runt
1
2
3
4
Effect
oH
-1
1
-1
1
4
Salt
-1
-1
1
1
-8
(oHHSalO
1
-1
-1
1
0
Result
95
98
86
90
92
#Obs.
6
6
5
6
S.E.
3.18
1.67
9.18
5.92
5
PEAT-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
21
Salt
-1
-1
1
1
-19
foHHSalt)
1
-1
-1
1
22
Result
95
94
54
97
85
#Obs.
6
6
5
6
S.E.
3.76
3.04
35.63
3.12
16
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-19
Salt
-1
-1
1
1
-10
foHXSalt)
1
-1
-1
1
-9
Result
97
88
96
68
87
#Obs.
6
6
5
6
S.E.
2.01
7.03
2.40
31.20
17
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
0
Salt
-1
-1
1
1
-2
(oHHSalt)
1
-1
-1
1
2
Result
100
97
95
97
97
#Obs.
6
6
4
3
S.E.
0.00
1.86
3.82
2.67
2
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
17
Salt
-1
-1
1
1
-19
(oHKSalt)
1
-1
-1
1
17
Result
92
92
55
90
82
#Obs.
6
6
5
6
S.E.
2.34
4.42
38.99
10.17
18
SAND
Run*
1
2
3
4
Effsst
oH
-1
1
-1
1
2
Salt
-1
-1
1
1
-1
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i
-i
-i
i
8
Result
96
90
87
98
93
#Obs.
6
6
5
6
S.E.
2.32
6.82
6.85
1.45
5
B-74
-------
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Ugh pH, Ugh Salt
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Loadng on Meda (m)
PARTICLE SIZE DISTRIBLmON: Bench-Scale Testing
(4 to 128pm)
B-79
-------
CONTRAST TABLE
EFFLUENT QUALITY
PSD (4 to 128 um)
CARBON-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
I
-1087221
Salt
-1
-1
1
1
-418752
(oHKSalt)
1
-1
-1
1
364928
Result
2136887
684737
1353207
630913
1201436
#Obs.
6
6
6
6
S.E.
990150
153936
856869
114038
661687
PEAT-SAND
Run*
I
2
3
4
Effect
t>H
-1
1
-1
1
963552
Salt
-1
-1
1
1
-88115
(DH)CSalf)
1
-1
-1
1
-2093307
Result
1119931
4176790
3125123
1995368
2604303
#Obs.
6
6
6
6
S.E.
158856
561351
1861073
290648
985954
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
229571
Salt
-1
-1
1
1
-32021
(pHXSalt)
1
-1
-1
1
-154663
Result
692622
1076856
815265
890173
868729
#Obs.
6
6
6
6
S.E.
144763
218079
166385
515859
300961
COMPOST-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
1399275
Salt
-1
-1
1
1
-564871
foHXSalt)
1
-1
-1
1
-616155
Result
2558349
4573780
2609633
3392753
3283629
#Obs.
6
6
5
3
S.E.
1035450
1186863
323197
904887
1008874
El
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
123080
Salt
-1
-1
1
1
-261477
SHRETECH-SAND
foHXSalt)
1
-1
-1
1
308354
Result
1101313
916038
531481
962915
877937
#Obs.
6
6
6
6
S.E.
137622
130749
101137
333851
198570
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-247754
Salt
-1
-1
1
1
-126228
(DHXSalt)
1
-1
-1
1
-319015
Result
1 148457
1219718
1341244
774476
1120974
#Obs.
6
6
6
6
S.E.
290968
345148
599776
125111
380517
B-80
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
PSD (4 to 128 um)
CARBON-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
5.78
Salt
-1
-1
1
1
1.05
(oHKSalt)
1
-1
-1
1
-0.72
Result
91
97
93
98
94.61
#Obs.
6
6
5
6
S.E.
4.08
0.67
5.67
1.02
3.30
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-3.43
Salt
-1
-1
1
1
0.77
(oHNSalt)
1
-1
-1
1
7.90
Result
95
84
88
93
90.05
#Obs.
6
6
5
6
S.E.
0.61
1.73
6.64
2.36
3.24
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-0.98
Salt
-1
-1
1
1
1.15
(DPWSalt)
1
-1
-1
1
0.35
Result
97
96
98
97
96.91
#Obs.
6
6
5
6
S.E.
0.61
0.95
0.49
1.56
1.03
COMPOST-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
-4.17
Salt
-1
-1
1
1
0.33
(oFDfSalt)
1
-1
-1
1
0.17
Result
89
85
89
85
86.83
#Obs.
6
6
4
3
S.E.
4.84
4.46
3.19
4.51
4.23
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-0.70
Salt
-1
-1
1
1
1.20
(DH)fSalt)
1
-1
-1
1
-1.70
Result
96
97
98
96
96.60
#Obs.
6
6
5
6
S.E.
0.76
0.43
0.24
2.25
1.27
SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
1 55
Salt
-1
-1
1
1
062
(oHKSalt)
1
-1
-1
1
1.55
Result
95
95
94
98
95.64
#Obs.
6
6
5
6
S.E.
1.23
1.38
2.84
0.43
1.57
B-81
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Loading on Meda (m)
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Peat-Sand
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Loadng on Meda (m)
Low pH High SaJt
500-
400-
300-
200-
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\ I I I
0 3 6 9 12 15
Loadng on IVfeda (m)
high pH, High Salt
500
0 3 6 9 12 15
Loadng on Meda (m)
2NC: Bench-Scale Testing
B-86
-------
CONTRAST TABLE
EFFLUENT QUALITY
ZINC
CARBON-SAND
Run*
1
2
3
4
Effect
pH
-1
1
-1
1
-61.11
Salt
-1
-1
1
1
20.51
(oHHSalt)
1
-1
-1
1
-8.90
Result
62.84
10.62
92.24
22.24
46.98
#Obs.
6
6
6
6
S.E.
5.82
4.07
6.57
14.96
8.91
PEAT-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-86
Salt
-1
-1
1
1
30
(DHXSalO
1
-1
-1
1
-19
Result
68.65
1.94
117.83
12.96
50.35
#Obs.
6
6
6
6
S.E.
7.01
0.90
2.53
2.25
3.92
ZEOLITE-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-55
Salt
-1
-1
1
1
41
foHXSalt)
1
-1
-1
1
-73
Result
16.97
35.03
131.23
3.05
46.57
#Obs.
6
6
6
6
S.E.
4.61
4.71
6.67
1.46
4.74
COMPOST-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-i
i
-2
Salt
-1
-1
1
1
12
(oH)fSalt)
1
-1
-1
1
-10
Result
9.00
17.64
31.15
19.29
19.27
#Obs.
6
6
5
3
S.E.
2.04
1.49
10.29
6.32
5.64
ENRETECH-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-97
Salt
-1
-1
1
1
-1
(DH)fSalt)
1
-1
-1
1
-30
Result
103.02
35.86
132.07
5.26
69.05
#Obs.
6
6
6
6
S.E.
4.86
2.10
3.39
1.09
3.19
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-95
Salt
-1
-1
1
1
0
fomrsaio
1
-1
-1
1
-40
Result
97.93
43.24
138.83
3.21
70.80
#Obs.
6
6
6
6
S.E.
3.96
5.40
3.76
1.28
3.89
B-87
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
ZINC
CARBON-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
I
40.50
Salt
-1
-1
1
1
-1.50
(nHHSalt)
1
-1
-1
1
-2.50
Result
49
92
50
88
69.92
# Obs.
6
6
6
6
S.E.
3.71
2.65
5.44
8.56
5.56
PEAT-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
54.08
Salt
-1
-1
1
1
-7.75
(pHXSalt)
1
-1
-1
1
3.75
Result
48
98
37
94
69.29
# Obs.
6
6
6
6
S.E.
5.14
0.80
5.17
1.05
3.71
ZEOLITE-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
26.50
Salt
-1
-1
1
1
-15.00
(pHXSalt)
1
-1
-1
1
42.00
Result
87
72
30
99
71.92
#Obs.
6
6
6
6
S.E.
3.50
4.01
4.13
0.76
3.39
COMPOST-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
0.42
Salt
-1
-1
1
1
-2.25
(oHXSalt)
1
-1
-1
1
7.92
Result
93
86
83
91
88.29
#Obs.
6
6
5
3
S.E.
1.58
1.23
4.85
3.84
2.91
ENRETECH-SAND
Run#
1
2
3
4
Effect
pH
-1
1
-1
1
59.25
Salt
-1
-1
1
1
17.08
(pHXSalt)
1
-1
-1
1
9.92
Result
22
71
29
98
54.71
#Obs.
6
6
6
6
S.E.
3.84
2.01
6.28
0.48
3.82
SAND
Runt
1
2
3
4
Effect
pH
-1
1
-1
1
56.58
Salt
-1
-1
1
1
16.08
(pHHSalt)
1
-1
-1
1
16.42
Result
26
66
25
98
53.79
#Obs.
6
. 6
6
6
S.E.
2.79
2.68
6.14
0.71
3.65
B-88
-------
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B-92
-------
Low pH, Low Salt
HJghpH, Low Salt
80
°Eft 40-
• — I
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80-
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20-
Loading on Media (m)
I I I \
0 3 6 9 12 15
Loading on Media (m)
Neutral pH, High Salt
80-
60-
40-
20-
I I I F
0 3 6 9 12 15
Loading on Media (m)
-— Blank
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-^- Peat-Sand
•-»-- Zeolite-Sand
—*— Compost-Sand
—«— Enretech-Sand
-«- Sand
Low pH, High Salt
80-
60-
40-
20-
I \ I \
0 3 6 9 12 15
Loading on Media (m)
High pH, High Salt
60-
40-
20-
I I I \
0 3 6 9 12 15
Loading on Media (m)
COPPER: Bench-Scale Testing
B-93
-------
CONTRAST TABLE
EFFLUENT QUALITY
COPPER
CARBON-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
0.81
Salt
-1
-1
1
1
0.52
(pHXSalt)
1
-1
-1
1
0.00
Result
3.61
4.41
4.12
4.93
4.27
# Obs.
6
6
6
6
S.E.
0.18
0.86
0.55
2.29
1.26
PEAT-SAND
Run*
1
2
3
4
Effect
oH
-1
I
-1
1
2.78
Salt
-1
-1
1
1
-0.49
(oH)(Salt)
1
-1
-1
1
-4.07
Result
5.07
11.92
8.65
7.36
8.25
#Obs.
6
6
6
6
S.E.
0.78
1.07
0.77
1.64
1.12
ZEOLITE-SAND
Run#
1
2
3
4
Effect
oH
-1
1
-1
1
-0.32
Salt
-1
-1
1
1
-2.54
foHHSalt)
1
-1
-1
1
-6.75
Result
9.72
16.14
13.93
6.86
11.66
#Obs.
6
6
6
6
S.E.
1.83
0.99
0.78
1.30
1.29
COMPOST-SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
8.57
Salt
-1
-1
1
1
3.79
(oHXSalt)
1
-1
-1
1
-1.07
Result
2.72
12.35
7.57
15.07
9.43
# Obs.
6
6
5
3
S.E.
0.81
0.70
0.65
3.00
1.10
II1
ENRETECH-SAND
Runt
1
2
3
4
Effect
oH
-1
1
-1
1
0.38
Salt
-1
-1
1
1
-4.89
fotWSalt)
1
-1
-1
1
-6.31
Result
9.03
15.72
10.45
4.52
9.93
#Obs.
6
6
6
6
S.E.
1.17
2.79
0.95
2.00
1.87
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
-4.79
Salt
-1
-1
1
1
-2.43
foHKSalt)
1
-1
-1
1
-4.15
Result
10.92
10.27
12.64
3.70
9.38
#Obs.
6
6
6
6
S.E.
0.92
0.85
1.18
0.19
0.87
B-94
-------
CONTRAST TABLE
REMOVAL EFFICIENCY
COPPER
CARBON-SAND
Run#
1
2
3
4
Effect
DH
-1
1
-1
1
-4.83
Salt
-1
-1
1
1
3.33
(DH)fSalt)
1
-1
-1
1
4.00
Result
86
77
86
85
83.42
#Obs.
6
6
6
6
S.E.
0.75
4.65
3.06
7.62
4.73
PEAT-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-16.67
Salt
-1
-1
1
1
14.83
(pHXSalt)
1
-1
-1
1
25.50
Result
80
38
70
78
66.50
#Obs.
6
6
6
6
S.E.
3.50
6.29
5.10
6.08
5.35
ZEOLITE-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-9.25
Salt
-1
-1
1
1
27.92
(DHXSalt)
1
-1
-1
1
37.42
Result
62
16
53
81
52.79
#Obs.
6
6
6
6
S.E.
7.60
7.66
4.79
4.09
6.25
COMPOST-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-36.67
Salt
-1
-1
1
1
-1.67
(DHXSalt)
1
-1
-1
1
17.33
Result
90
36
71
52
62.17
#Obs.
6
6
5
3
S E
2.78
4.63
3.45
8.76
4.44
ENRETECH-SAND
Run*
1
2
3
4
Effect
DH
-1
1
-1
1
-11.50
Salt
-1
-1
1
1
34.00
(offi(Salt)
1
-1
-1
1
36.33
Result
66
18
63
88
58.58
#Obs.
6
6
6
6
S.E.
3.88
16.07
6.51
5 68
933
SAND
Run*
1
2
3
4
Effect
oH
-1
1
-1
1
11.75
Salt
-1
-1
1
1
20.08
(oHHSalt)
1
-1
-1
1
22.58
Result
58
47
56
90
62.63
#Obs.
6
6
6
6
SE.
3.64
3.53
7.72
0.70
4.63
B-95
-------
-------
Appendix C:
Physical Parameters
Toxicity
Turbidity
Conductivity
Color
pH
C-1
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C-3
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Carbon-Sand
Peat-Sand
Zeolite-Sand
.59
Influent
Effluent
Influent
Effluent
Ctornpost-Sand
Enretech-Sand
Influent Effluent
Forest-Sand
20-
10-
VWco>ccnP= 0.1563
30-
g 20^
""
W!lcoxonP»0.1250
Inftuent
Effluent
OH^—
Influent
Effluent Influent
Effluent
Sand
Gunderboom
EMCON
20-
10-
VWco)«onP= 0.5000
Effluent
Effluent
TOXIdTY: PreSettled Influent
Unfiltered Fraction
Effluent
H'" ' ' ilii • \
; C-4
jM\ ..... a .....
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
40-
WIIcoxonP = 0.0625
30-
20
™ 10-
40-
20-
» 10 J
0-0
WllcoxonP = 0.0325
40-
WllcoxonP = 0.0625
30-
20
10-
Influent Effluent
Compost-Sand
Influent Effluent
Enretech-Sand
V
Influent Effluent
Forest-Sand
40-
WilooxonP=0.3125
30-
^10-
Influent Effluent
Sand
Influent Effluent
Gunderboorn
Influent Effluent
EMCON
40-
^ inJ'—
Influent
30-
20-
!± 10-
WilcoxonP=a5625
Effluent Influent
SE#1 -•- SE#2
OH
Effluent Influent
SE#3 -T-SES4
Effluent
>- SE#5
TOXiaTY: PreSettled Influent
Rltered Fraction
C-5
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c
o
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Carbon-Sand
Peat-Sand
40
30-
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WllcoxonP= 0.0625
40
30-
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Influent
Effluent
0-U
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Sand
Enretech
40-
30-
20-
VW!coxonP=0.0625
0;
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i
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•••"•I •
40
30-
VWIooxonP = 0.0625
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40-
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Compost
so-
10-
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VWIcoxonP=0.0625
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ii. •.;
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Influent
Effluent Influent
EMCON
Gunderboom
' k;
Effluent
ADS 4420
,)!/ .•(; • l it ,;•„/,
Effluent Influent
SE#1 -m- SE#2
Effluent Influent,
SE#3 -T-'SE#4 i
Effluent
- SE#5
TX)XiaTY: UnJDretrealed Influent
Unfiltered
C-8
-------
Carbon-Sand
Influent Effluent
Sand
Influent
Bfluent
EMCON
Influent
Effluent
Peat-Sand
Zeolite-Sand
50-
40-
30-
i
i
20-
WlcoxcnP= 0.0313
Influent Effluent
Enretech
Influent Effluent
Compost
50-
40-
20-
10-
V\JlcoxmP= 0.0625
Influent
Effluent
Influent
Effluent
Gunderboom
ADS 4420
Influent
Effluent
Influent
Effluent
SE#1
SE#3
>- SE#5
TOXiaTY: Unprelr^ated Influent
Rltered Fraction
C-9
-------
u
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C-11
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r !
50-
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30-
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40-
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W!coxcnP=0.1250
[- „«_— . — -i
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40-
30-
20-
10-
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WilcoxonP = 0.0625
/
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Compost-Sand
WtaconP =0.5000
^J
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50-
40-
30-
20-
|
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0-
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50-
I
40-
30-
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Zeolite-Sand
WflcoxonP = 0.5000
^
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I
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WilooxonP =0.0625
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40-
30-
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V«lcoxDnP= 0.0938
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Sand Gunderboom
WllcoxcnP =0.5000
^^^^z^l
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40-
30-
20-
10-
WilcoxmP= 0.5000
•". '....' y
50 -
40-
30-
20-
10-
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EMCON
WilcoxonP=0.1563
^ _T _ ^— -J
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Influent Effluent Influent Effluent Influent Effluent
i'iln; , .:•' i ' • !!!!; ' ( . . •., if ' ;i>! .1 • ; j- , '; ,, i • • • • '; i! i., » ;•; ' . ,:,;!;;,! , " v '" .• j ii .»,j
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i, ,;!, ...,i'i! S,,,1 ,,|, ;,' , 'IS 1 ' : !h ,; ! , :i „ . • , '".iS'T !' i »; li'iSlii I1' ,h! '!!''i ! 'I1 i" niBi:1'''!:!!:1'1 111 ,, ,lh, i1 , , ,• i M'JI.
Unfiltered Fraction
,i,,ii , • ' , * • , • ' ''"i ,„ ' ji'ii i h ' ' ,1,1:,' , , ,, , • ,:••,, ,i,, , ' , , • , ' n " t" i"
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i
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Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Compost-Sand
Influent
Sand
Effluent Influent
Effluent
Enretech-Sand
Bfluent Influent
Gunderboom
Influent Effluent Influent
-*- SE#1 -»- SE#2
Influent Effluent
Forest-Sand
Effluent Influent
Effluent
EMCON
Effluent Influent
SE#3 -T - SE#4
Effluent
SE#5
TURBIDITY: PreSettled Influent
Filtered Fraction
C-13
-------
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100-
80-
RM1
<§. 40-
20-
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100-1
80-
60 -<
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20-
0-
Infli
100-
80-
i""!
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20-
o-
Infli
Carbon-Sand
VVllooxonP= 0.0625
j_ll ^=^__ -
jent Effli
Compost-Sand
WilcoxonP=0.0313
jent Effli
Sand
WilcoxonP = 0.3125
— — - 1
jent Effli
100-
80-
CO 40-
20-
o-
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100
> 80
60
.0
CO 40
20
0
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100-
80-
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i
20-
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Peat-Sand
WilcoxonP= 0.0313
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t
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Enretech-Sand
VyiooxonP= 0.3750
*— — ^=±=-=-
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Gunderboom
WllcoxonP = 0.1563
k :
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^
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Zedite-Sand
Influent
Effluent
100-
80-
60-
40-
20-
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Forest-Sand
\MlcoxonP= 0.1250
Effluent
EMCON
80-
60 -€
i
40-
20-
WlcoxmP= 0.3125
: . _i
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SE«3
Influent
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Effluent
SE#5
CXDNDUCT1VITY: PreSettled Influent
C-15
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1
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C-16
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Carbon-Sand
500 —
400-
300-
o
55 200-
1
100-
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500-
400-
300-
P
f H
100-
1
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500-
400-
300-
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100 -;
0-
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/
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^™" " —\.
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500-
(
400-
300-
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1
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I
0-
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500
Peat-Sand
'WilcoxonP= 0.3125
N=-r- "
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500-
400-
300-
o
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1 ""loo-
0-
lent Infli
Zeolite-Sand
WllcoxonP = 0.3125
h !
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Enretech Compost
WlcoxonP =0.0313
400- 400-
300- 300-
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500-
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SE#3
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CXDNDUCT1VITY: Unpretreated Influent
C-17
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C-19
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Kir. : is.1'! t..1, > '•'" w: i;. WA Jlf'ir 1 m If™':'1' • • •i':j" rt>i : U» ,>
Carbon-Sand
Peat-Sand
Zeolite-Sand
120-
80-
Wl!coxonP = 0.1250
120-
80-
40-
WilcoxcnP = 0.0625
Influert Effluert Influert Effluert
Compost-Sand EnretecrhSarid
Influent Effluent
.::: h,'i.. I-' ;
Forest-Sand
Influert
Effluent Influert
Effluent
Effluent"
Sand
Gunderboom
EMCON
120
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d*
I
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1
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U-_
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Influert
Effluert Irfluert
SE#1
Effluert Influert
SE#3 -Y--SEM
Effluert
SE#5
COLXDR: PreSettled Wluent
Unfiltered Fraction
C-20
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
120-
80-
40-
WlcoxonP = 0.1250
120-
80-
40-
WllcoxonP=0.3125
Influent
Effluent Influent
Effluent Influent
Effluent
Compost-Sand
Enretech-Sand
Forest-Sand
120-
80-
40-
Wi!coxonP=0.3125
120-
80-
40-
WlcoxonP=0.3125
Influent
Effluent Influent
Effluent Influent
Effluent
Sand
Gunderboom
EMCON
120
80-
Influent
40-
Effluent Influent
.SE#1 -•- SE#2
120
Bfluert
Influent Effluent
--0- SE#5
COLOR: Presetted Influent
filtered Fraction
C-21
-------
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C-23
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Carbon-Sand
Peat-Sand
Zeolite-Sand
120
80-
40-1
Influent
120-
80-
.40-
' WilooxonP = 0.3125
Effluent Influent
Effluent Influent
Effluent
Sand
Enretech
Compost
120-
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80-
40-4
Influent
Effluent
EMCON
Influent Effluent
Gunderboom
Influent
Effluent
ADS 4420
120-
VWlo»onP=0.0313
80-
40-.
Influent
Effluent
80-
40-
i
Inflt
W!looxonP= 0.3125
i^— — " '" — ~" ~' "~
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120-
80-
40-4
VWIcoxonP=0.0625
Influent
Effluent
SE#1
SE#3
SE#5
COLOR: Unpretreated Influent
Unfiltered Fraction
C-24
-------
Garbon-Sand
Peat-Sand
Zeolite-Sand
120-
80-
5
WlcoxcnP=0.0313
120
Influent
Effluent Influent
Effluent Influent
Effluent
Sand
Enretech
Compost
0
Influent
o
Bfluent Influent
Effluent Influent
Effluent
EMCON
Gunderboom
ADS 4420
120-
80-
40
WlcoxcnP=0.4532
80-
40
WlcoxcnP= 0.5000
.a
so~
40
WlooxcinP= 0.2657
t5^
Influent Effluent influent Effluent Influent Effluent
-*- SE#1 -*- SE#2 -±- SE#3 -T-SE#4 -^-SE#5
COLOR: Unprelreated Influent
Rltered Fraction
C-25
-------
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C-26
i: : : ::: :.: ::..:..
-------
Carbon-Sand
Sgi Test P= 0.0313
Influent
Effluent
Cornpost-Sand
Influent
Effluent
Sand
Peat-Smd
Influent
Effluent
Enrelech-Saxl
Influent
Effluent
Gunderboorn
Influent Effluent Influent
-«- SE#1 -m- SE#2
Zeolite-Sand
Influent
Effluent
Forest-Sand
Influent
Effluent
EMCON
Effluent Influent
SE#3 -r-SE#4
Effluent
pH: PreSettled Influent
C-27
-------
I i'"
" It]:
FfH
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II
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SAMPLED
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C-28
-------
Carbon-Sand
Peat-Sand
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Influent
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Effluent Influent
Effluent
Sand
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ADS 4420
— 8-
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WlcoxcnP=0.0313
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-9- SE#1 -»-SE#2
Effluent Influent
Effluent
pH: Unpretreated Influent
C-29
-------
,
i •;•
-------
Appendix D:
Anions
Carbonate
Bicarbonate
Fluoride
Chloride
Nitrite
Nitrate
Phosphate
Sulfate
D-1
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D-5
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
0.04-r
acs-
0.02-
Q01 -
aco
Influent
0.04-
0.03-
5 0.02-
0.01 -
aoo
\Mcoxm P=0.3125 1
Bfluent
Influent
Influent
Effluent
Compost-Sand
Enretech-Sand
Forest-Sand
aot-
aos-
aoa-
aoi-
aoo
\Mta»mP=Q2188
0.04
0.03-
5 0.02-
001-
aco
0.04
0.03-
5 0.02-
Q01 -
aoo
Influent Bfluent
Sand
Influent
Effluent
Influent
Effluent
Gunderboom
;•!:; K •:"• " .VI.
ao4-
ao3-
ao2-
aoi-
aoo
\Affla»cnP=a
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Effluent
Influent
Effluent
Influent
Effluent
Compost-Sand
Enretech-Sand
80-
70-
60 -i
cu -j
50-
40-
30 -1
20-
10-
VyicoxcnP= 0.0625
i (
1 l
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Forest-Sand
80-
70-
50-
40-
30 J
20-
10-
WlcoxonP=O.OG13
i <
>— _ —3
r — "
I I -'rrr^ ' "|
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Influent
Effluent
Influent
Effluent
Influent
Effluent
Sand
Gunderboom
EMCON
80-
70-
60-,
50-
40-
30J
20-
10-
Wlco>cnP= 0.1563
1
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p^rr-":r=~"J "
au —
80-
70-
SO-7
50-
j
30-
20-
10-
VUtcoxDnP= 0.2188
>— — — '
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i
Influent
Effluent
Influent
Effluent
Influent
Effluent
SE#1
SES2
SE#3
'-SE#4
BICARBONATE: Pre-Settled Influent
D-7
-------
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Carbon-Sand
Peat-Sand
Zeolite-Sand
0,5-
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05-
I
0.1-
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ttb
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0.0
Influent
Effluert
Influert
Effluert
Influert
Compost-Sand
Enretech-Sand
Effluert
Forest-Sand
0.5
0.4-
0.2-
Vy|coxmP=0.1875
0.0
0.0
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„;; ;; , , , ;;;•; • QO.-U-J
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Gunderboom
0.0
.>^ A
Influent
Effluert
EMCON
0.5-
04-
02-
0.1-
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0.0
*
0.5
^
0.4-
0.3-
0.2-
!
0.1-
0.0
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/
3
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0.4-
0.3-
0.2-
E
0.1-
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Bfluert
Influert
Sfluert
Influert
Effluert
SE#I '
SE«3
SE#5
FLUOFflDE: Resettled Influent
D-8
-------
Carbon-Sand
Influent
Hfluent
Compost-Sand
Influent Effluent
Sand
Influent
Effluent
Peat-Sand
4-
3-
2
1 -
Wllco>cnP =0.0313
Influent
Effluent
Enretech-Sand
Influent Effluent
Gunderboom
Influent
Effluent
Zeolite-Sand
\McoxcnP=0.0313
Influent
Effluent
Forest-Sand
4-
WIcoxmP=0.5000
^_--J
Influent
Effluent
EMCXDN
VyicoxcnP= 0.5000
-»
Influent
Effluent
SE#1
SE#3
'-SE#4
-- SE#5
CHLORIDE Fte-Settled Influent
D-9
-------
Cation-Sand Peat-Sand Zeolite-Sand
I
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)
21
1
1-
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Concentration (rrgl)
3 -1 IO CO J
L i .a i
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I
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> -* M CO ^
1 ^1 1
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r±r=^
1 — ' — — —
influent Effiuent Influent Effluent Influent Effluent
Oonpost-Sand Ehretech-Sand Forest-Sand
3 -
1-
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traticn(rrgl)
to co j
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|
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Sand Guncterboom EMCON
3-
21
1-
0-4
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Concentration (mp/L)
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L- 1 n. -» to co f
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:::: ;«; _«_ ^^ _»_ gg^ A^- SE#3 ' "'-T-'SE#4' "':-^--SE#5
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M7RATE Pre-Settled Influent
D-10
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Carbon-Sax!
Peat-Said
20-
15-
10-
?
5-1
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Effluent
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BTretech-Sand
03
20-
15-
10-
j
i
5-1
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5-1
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Sand
Influent Effluent
Gunderboom
20-
15-
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Effluent
Influent
Effluent
Zeolite-Sand
23-
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Influent
Effluent
Forest-Sand
20-
15-
10-
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5-1
n
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r *
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B/CON
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20-
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?
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Effluent
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D-11
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D-16
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Peat-Said
Zeolite-Sand
400-
300-
5 200-
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400-
300-
5 200-
100-
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400-
300-
200-
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Influent
Hfluent
Influent
Bfluent
Influent
Bfluent
Sand
Enretech
Compost
400-
300-
S 200-
VMIooxcnP=ai563
400-
300-
5 200-
Wi!ctM3nP=0.0313
Influent Bfluent
EMCON
Influent Bfluent
Gunderboom
Influent
Bfluent
AIDS 4420
400-
300-
2DO-
wnoaxmP=0.2188
400-
300-
5 200-
Wloa>ccnP=a4C63
Influent Bfluent Influent
-«- SE#1 -*- SE#2
Sfluent Influent
SE#3 --r-SEM
Bfluent
SE#5
BICARBONATE: Unpretreated Influent
D-17
-------
.,.' If i'l
Carbon-Sand
Peat-Sand
Zeolite-Sand
0.3-
02-
0.1-
010
VtacnP=03125
0.3-
0.2-
0.1 -
=0.4063
0.0
Influent
Effluent Influent
Effluent Influent
Sand
Enretech
Effluent
Compost
0.3-
0.2-
ai-
ao
WBcxj>OTP=0.5000
0.3-
0.2-
0.1-
VyicoxcnP=0.4063
0.0
Influent
Effluent
Influent Effluent
Gunderboom
Influent
Effluent
0.3-
ADS 4420
0.2-
0.1-
V\(looxaiP=Q0313
0.3-
ao
0.2-
0.1-
0.0
WlcoxmP=0.3125
T 'i ~"~~~
Influent Effluent Influent
SE#1 -*- SE#2
Effluent Influent
SE#3
Effluent
-O-- SE#5
FLUOFUDE Uhpretreated Influent
D-18
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Effluent
Influent
Bfluent
Sand
Enretech
ID
12-
8-
j
WlcoxcnP= 0.5000
I i
Influent Effluent
EMCON
Influent Effluent
Gunderboomi
16-
12-
S 8-
VyiooxcnP=0.2188
16-
12-
5 8-
WlooxcnP=0.3125
o
?.-
8-
1
1 -*
VUlcoxcnP =0.2188
V— — • '
Influent
Effluent
Compost
ID
12-
8-
|
4-<
WlcoxcnP= 0.0338
(
I
1
Influent
Effluent
ADS 4420
Influent
Effluent
Influent
SE#1
Effluent Influent
SE#3 --r-SEM
Effluent
SE#5
CHLORIDE Uhpretreated Influent
D-19
-------
Carbon-Sand
Peat-Said
20-
10-
5-
VMtcoxcnP=0.0625
20-
15-
S 10-
V\JlcoxoiP=0.12SO
Effluent
Influent
Effluent
Sand
Enretech
15-
10-
5-
OHh
VMIcracnP=0.5000
20-
15-
S 10-
C _
^
Vy|cx»cnP=0.1875
Influent Effluent
EWICCDN
Influent Effluent
Gunderboom
20-
15-
10-
5 ~~
V«looxcnP=0.2188
20-
15-
S 10-
Wloo>cnP=0.4375
Influent
Effluent
Influent
Effluent
Zedite-Sand
Influent
Effluent
(Compost
Influent
Effluent
20-
ADS 4420
15-
S 10-
5-
WlcoxcnP=0.06S5
Influent
Effluent
SE#1
SE#2
SE#3
MtRATE Unpretreated Influent
D-20
-------
Carbon-Sand
Peal-Sand
Zeolite-Sand
200
200-
150-
100-
50-
•WlcoxcnP=0.0313
200-
150-
100-
50-
V\JlooxcnP=0.0625
Influent
Effluent
Influent
Effluent
Influent
Effluent
Sand
Enretech
Compost
S 100-
Vy)coxcnP=0.5000
150-
S 100-
so-
WlcoxcnP =0.0313
Influent Effluent
EMCOM
230-
150-
50-
VMIcoxmP =0.0908
Influent Effluent
Gunderboorri
Influent
Effluent
ADS 4420
150-
100-
50-
i
WHcoxcnP=0.4063
l 1
200-
150-
100-
50-
WlcoxEnP=0.3125
200-
150-
100-
50-
VMIoo>cnP=0.4063
Influent
Effluent
Influent
Effluent
Influent
Effluent
SE#1
SE#2
SE#3
SULFATE: Unpretneated Influent
D-21
-------
...I
-------
Appendix E:
Cations
Hardness
Lithium
Sodium
Ammonium
Potassium
Magnesium
Calcium
E-1
-------
to.''!••>!•'
if i
c
o
3
C
•o
o
u
to
o
2
O
H
w —
n v.
o o o o o
c* o o oo r—
o o o o o
2 r- T <^ '
f*i •* c** r*
Q vo r- f . rr
g 0 0 - -
o o o o
m oo *o o» o
O C*J O — —
00000
t- O O »n O
r- o c*- oo c\
\O O — M O*
ro r4 — — O
c* ov — tn t-
O — \O VO O
ON CO CO C\ O
O O O O O
< < < < <
2 2 2 2 Z
O Q Q Q O
22222
Q D Q Q Q
22222
•o
e
w e E E E H
g in -.•*.* 9
1 « - - s a
(3
u
•a
u
«
>
t>
<
vd 0 VO — 0
o t— co oo r—
— o o o o
o- o o oo r-
00000
3 t- °° « *
•* o\ tj- m co
o r— o co \c
o o -* — —
o o o o o
in oo vo ON o
o es o — ~
o o o o o
•
c\ ov r- vo r-
o o >n cs oo
rf r- vo O CO
— 0 0 — 0
oi c% — m r-
O — vo vo O
O OO OO O\ ON
o o o o o
< < < < <
22222
Q Q Q Q Q
22222
Q Q Q Q Q
22222
S £ E E E
10 - ^. ^ °.
_.: r% vo o >n
00 „ « (S (S
•a
e
(3
°?
C3
U
cu
vO O OO OO to
•^- f, r*-, m m
00000
ON O O 00 r-
o o o o o
g r-, ^ ^ 0
2 >n «7 . —
r*-. — m vo
Q — O 00 fS
0 O 0 0
in co vo ON o
o w o — —
o o o o o
r- — <*i W oo
t^- oo m oo r-
vO ON O r- •*
C^ <-> M •* —
01 ON — — cs — < —
cv o o co r-*
o o o o o
^
7 ' '
r- vo vo t^- vo
r- r-- n
•0 °° — — l ON
vo r- vo r- f.
o o o o fn
ON O O OO f-
00000
ON es oo r- o
•* r- oo — o
O O O — • vo
0 O O O 0
»n oo vo ON o
0 CM 0 — —
o o o o o
. , , „
vo m r- ON vo
>n o 9
„: fo vo o >n
-a °° » — o* CM
c
(S
C/3
JS
w
u
u
c
UJ
E-2
-------
1
c
c
o
u
^—/
en
3 i
*—' CO
2 S
.2 °
S j
§, g
5i
£ CO
E 2
•P 7
o 11
E J
S g
~ i
i *
E m
E 2
o "-J
oo C
5
___ e:
t 2
1 °'
•^ T
J Q
W
S
<
z
0.
o
02
O
s
2
<;
00
ecrease
Q
£
Sffluent
c
«>
3
_C
(D
C3
2^
?
c
oj
3
E
w
c
4>
3
C
ecrease
Q
^
1
&
W
o>
3
C
V.
i
"c
OJ
s
U-l
c
u
c
c
O •*!• — • oo oo
CM — — — CM
CO O VO O vo
r~ oo p~ vo i~-
O O O O O
•* — CM r~. m
ON o o oo r^
in r~ r^ >n in
O C O O O
oo _ r^- vo ^
"? r~ ^ CM NO
— O •* CM ON
p^ r^ oo ro CM
O O O — CM
C3 O O O O
in oo vo ON o
SCO vo F~ *5f
M 0 — —
O O O O O
? 8 •" ^° S
CO 00 O CM CO
— O O — —
O — ' vo vo O
ON OO OO ON ON
o o o o o
z z z z z
Q Q D Q D
Z Z Z Z Z
Q Q Q Q Q
Z Z Z Z Z
1 c £ E E E
C/5 ^-j — • ^ vo O
en « fl VD O in
•a
Cu
0
o
a.
>O — 8
Tt VO ON CO VO
VO — vo ON CM
o o oo oo r^
— ' — C5 O 0
O •— * VO vo O
ON OO OO ON ON
o o o o o
< < < < <
z" z z z z
Q Q Q 0 D
z z z § z
Q Q Q a a
z z z z z
E E E E E
j^ — • "^ vo O
..X o-i vo O m
oo — — o) es
-o
c
a
00
^ °] r-, **t O\
VO — •« •<* CO rt
CM Tl- CO O CS
vo co vo vq w-j
o" o" o o o*
rt — c ^J -7
rj co vo m in
co -3- — i TJ- in
O cs — — —
o o" O O o
in co vo o\ o
-^j- m vo t^- "^
O CM O — • ~
o o o o o
\o o\ r*- r— in
co cs »n r-- m
co vo — m in
— * vo r- o o\
•3-" o o — " o
cs ON — »n p-
c> -^ vo vo o
ON CO CO ON ON
O O O O O
< < < < <
Z. Z. Z, Z. Z.
Q Q Q Q Q
Z. Z. Z. Z, Z.
Q Q Q Q Q
Z. Z. Z Z. Z.
.g c E S S £
^ m -: ^ *> P
[2 od ^ 2 S S
c
S
.0
c
O
-st op in CM ^t
r-. ON ^j- oo o
— • m co — o
vo t— t— m vo
o o o o o
•* — • CM r~ in
ON O O 00 <—
m r~ r- m m
o o o o o
ON _ CM ^j.
r- — t— CM —
vo -^- oo oo co
o — o o --
o o o o o
in oo vo ON o
•<* CO VO t~- *^-
O CM O — i —
o o o o o
^f m rr\ ^ ^
in in CM in O
-^ in oo in o
CM 0 O 0 — I
CM ON — in r^
o — vo vo o
ON 00 00 ON ON
o o o o o
< < < < <
Z Z Z Z Z
D Q Q Q Q
Z Z Z Z Z
Q Q Q Q D
Z Z Z Z Z
g E E E E
m — •* "° °.
o _j co vo o in
•C °° — — CM CM
£
2
O
u
w
E-3
-------
.no
O
to
s
Qu
D
o
td
C:.
t('r I
O
U
z;,,
o
U
8 o
g o
1 5
x S
•3 -£
o y
t- E
.j
Calcium
DL- 0.318 mi
S
3*
* £
a S
.2 o
8 It
S, J
a Q
2 S
ROUPNAME
SAMPLE G
:rcase j
V
D
*
c
u
a
fc
U3
e
u
3
C
O
Irt
13
0
U
Q
&
\ Effluent
1 Influent
% Decrease
~
s
rr
Ul
e
u
s
r"
c
01 *° *"* - ^
OO VO »n TT O
r-. — o — • —
0 «*» „ _ _.
n- -3- o r- cs
2 o-' r-. so 0 «n
w — • — M C4
(3
CJ
•o
H
G3
>
tJ
<
"
•* c\ oo *— ts
r- — . o — —
c* n~. •* oo tn
cs t^-i -a- «o r-
c» oo CN o\ r^
d d d d cs
« o» « r- «
ZJ r- r- in ^
. oo p r-^ o
2 *n oo NO r-
r- ^ cv ON m
>n M c*-. -7 -7
Cs C\ OO VO n c\ -*
o o o o —
— • oo oo \o *n
o o « o r-
•"3- VD C^ OO C\
— o o o o
£ H £ E E
^ „ TJ; vo q
• r-, \o o *n
00 ^- -. cs cs
•o
c
re
co
a
.u
a.
r- — o — —
— Tf r- oo «-,
Cv \O rf O> r-
»n — ; ^ : ^ "*
oC vi vd ^t vd
^ n
o o \o o r-
•**• \o c\ oo c?\
— o o o o
g E E E £
„ — •* so o
^ e^, \o 0 «n
00 — — rs cs
T)
C
a
W
o
"o
u
M
,
r- « o — —
J5 o en oo p~,
1J >n tn m a>
cs o >n os
^ ^- ON oo oo
£ cs - r- ^o
£ t- r- m •*
*; oo q r^ q
2 *n oo \d r-
c\ r- o\ *° ys
r- ^- oo _ oo
— Cs CS CS —
>n oo oo r- oo
cs o ~ ~ —
— oo oo vo »n
O O VO O 1—
Tf "O O\ CO C^
— 0 0 0 0
g E E £ £
^ — t vo 0
-J en \o o «n
•0 °° — — cs cs
«
CO
0
G.
E
o
U
1
t-. — o — —
2 o ** o TJ-
^, o r- cs ri
^ OS ro — P-
2 °° — — CS CS
c
n
CO
J=
u
u
£J
c
w
E-4
-------
ta
c
2
O
H >o
<| o\
S ON
<
Q
o
H
<
04
$
E
3
C
O
U
N '
cn
Z
O
H
<
U
g 0
"2 c3
£ »
£G a
S =3
o tfl
H £
1*
oo
c oo
is
U H
j
Q
J «i
W) G
^E- in
E S
.2 o
S II
M ^
a Q
S S
S
z
Cu
o
OS
O
S
CU
*s
S r- r- >n •*
*; oo o r— o
2 " " " "
CS fq — -^ Cjl
'
OO ^- ol ON cS
-^ O O CJ O
— « co oo vo »n
o o vo o r--
•^ VO ON CO ON
— • O O O O
g E E S S
m ™ . . .
« ro vo O
-------
Carbon-Sand
60-
50-
40-
23-
10-
WIooxcnP=0.4532
Effluert
Conpost-Sand
Irfluat
Effluert
Sand
Peat-Sand
ZeoliteSand
Influent
Effluert
Influent
Bfluent
Bir^fich-Sand
Influent Effluent
Gunderboom
Influent
Effluert
Influent Effluert
r.!1 1 ' : = . . '" ^
ForeslrSand
Influert
Effluert
EMCON
SES3
Influert Effluert
'-SE#4 -:0 -SE#5
. ,, i ,
":" .• , •']- /• -7 - •':
".:r":.'.-,(,. -;
R'e-Settled hitluent
E-6
I
-------
Carbon-Said
Influent
Effluent
Compost-Sand
Influent Effluent
Sand
Influent
Effluent
Peat-Said
Zeolite-Sand
Influent
Effluent
Enretech-Sand
Influent Effluent
Gunderixtom
Influent
Effluent
Influent
Effluent
Forest-Sand
Influent
Effluent
EMCON
Influent
Effluent
SE#1
- SE#3
SE#5
SODIM Pre-Settl9d Influent
E-7
-------
;! 1 Hi Bill!"!': •'•"* ''! llllll!!' ! I"'1 -'V! "1 "!<; 1 11 I 111 111 I I III 111 I 1 III II 1 1 1 111 III
;! : ' : iii ' II
u • ' I'l"! ' i 1 1
CartxrhSand PeafcSand 2
!' . ' II'1' ' '"' n~7 ' r\^ ' ' f\ -r
!„! :, ,. " ,- . U/ —
: ; ., 0.6-
, - ' 'Sij
fO.5-
_ 0.4-
g
j Q3-
« 0.2-
O 0.1-
.,.(
f\ ri
UO
Wloo>BnP=0.1563
'~:x=^^-
u,/ —
0.6-
fO.5-
_ a4-
S
'•§ °-3~
w 1
« 0.2^
v W .
WlcoxcnP=0.3125
jr^_^_- -j
0.6-
y- 0.5-
& 0.4-
S
1 0.3-
,f~t -
r § 0.2-
|
,. , i •:, • .I, i i, i i
1 v I '. '* , '.T'.V 1
ieolite-Sand
.i1'1 , : "!,!i ' ' ' ''• ' • !, ',;
Vyico)cnP= 0.2188
1 — .
r - - -
^"^ \I ^ ai -T ^=sss4 e 0.1 -T
r ^~tt Qpz— '
* • nn T
f~_
nn . T
Influent Effluent Influent Bfluert Influent
- — .
. — — M
I
'
Effluent
^''6arp^S3^ Bretech-Sand Forest-Sand
A*7 ,, rt~r ""»
U,/
. i Si!1 ' , ,i Jill .i
:,. , °&-
fas-
.^ 0.4-
g
1 0.3-
& 1
8 02-
VMIcoxcnP=Q3125 )
/
/
/
/ A
/ ..-•-•
^**2C- *
° aiiL/- — -^^-:J::^
A*—-
f\f\ _.,., ..
0.6-
f05-
^, 0.4-
> 5
I °-3~
"5 1
8 0.2-
u./
t^~ ——- :ss»_
> 0.6-
fO.5-
^ 0.4-
6
•* 0.3-
•g 1
8 0.2 -5
VWIooxcnP= 0.5000
k^
^•"s,
U-^.
; o ai-i ^":::^i <3 0.1 -T
A — — ~— — c
"___:^4 d Q1 JL— ^=^=3 ° a1 -5
p= — •
1
00-
1
1
0.0-
- • ^
-^
>
)
Effluent
EMCON
yyicoxDnP=0.3125
1-^
•^*-
•-— .
•
H*^— -JL
i i ;. .. . :' .'. , ,'T'i :,i:3 ii ','!,!,; i' , , „ ; ,, • • '••,, , • ,. ,-;. .• , ,i i , , • , . . j, • ,1 • •, -, .. liiiiii: /. ' |i
:'.•',;; ! Wuent,, Puert Influent , Effluert Influent
,,"'!' ' *' j! ' ',] • ;!;n ; „,'"'' • ::•' ,,» ||i
!' 1 ' !, ' '"lllll"! " ' I'' ' 'i: »„,.,, ' 'nj1 '':•": t
••!'..' *' . . .,'. ' ' iiV'i'l! •."!••' •>•.} ' ';'' •• •• >>•}; 'i;; •'.••., ',:£
;t> S i\\.-'-; IS: i;.;*: ^*-SE#1 -^'SE*2 -^- SE#3 ^r-SE#4
' " ' l' •« "'! '' " I,!' , '''.:, ' ' '"' ; „ . ' • '
i H' ' * ' 'i,',1' ,'''!' •' ' . ' ,.J
„!' ;' ..|,"»!i|, lhl , '" . : • 'I
.. i. ' ,': ill" :• " ' , ' i ii .! ,"" , "'
^^^^^^^^^M^
f, . „ f • , . < , •:: ; •;'•: •••.' [,•.
Effluent"
!, •:'• '•! . ' "-* ; !,:
'. '! • T ; ' f ": ''
•' • , ; ' ?" ii
:, .I ,f |,
- . . , n , i
11 lil J ' i ' " 1 i!'
•• ., '.' ' '"''' ; 'I
1 ' :
. .,
;;"' i. ,(I
'
I '
'1 I;1!
ilihi-
E-8
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
4-
5
WilcoxcnP=0.0313
2-
Influert
O —
4-
2-
WilcQxonP=0.0313
ri= i
n
0
4-
2-
Wlooxm P=aOS13
Bfluert Influent
Bfluent Influent
Bfluent
Conpost-Sand
Erretech-Sand
Forest-Sand
4-
2-
VMIcoxcnP=0.0625
4-
2-
W!coxDnP=0.0313
Influent Effluent
Qunderboom
Influent
Bfluent
B/ICON
4-
2-
0
WlcoxcnP=a3125
j -^- J
o
4-
S
2-
V\flcoxcnP=0.1325
4-
2-
WlooxonP=Q3125
Influent
Efluent Influent
Bfluert Influent
Bfluent
SE#1
SE#5
POTASS11M
E-9
-------
Hill! .. , i1! ' 1 . •
Iff*
i* f:
Peat-Send
or
, 111''
2-
1-<
1
1
WlooxcnP =0.4532
j
•-"
Influent
Effluent
Gonpost-Sand
Erretech-Said
o —
2-
^
1t
1
1
Vyico>inP=0.1563
Influent Effluent Influent Effluent
...... " ' ' .......... .......
.
Sand Gunderboom
•3
5
O —
'I,,, II' 1
:,. ,ii!ul.
2-
1-<
i
1
WtacnP=a5000
o
2-
1-1
1
1
Wloo>cnP=ai563
I -" '
Influent
Effluent Influent
Effluent
Zeolite-Sand
2-
Wlco>cnP=a2188
Influent
Effluent
Forest-Sand
2-
Wlcoxm P=0.5000
Influent
Effluent
BVCON
2-
1-t
1
1
VVIIcoxcnP=0.5000
,|
Influent
"i-lli ......... , '. ..... i'. I.
Effluent
- SE#1
f* , f' ,'v- '^•^•"'•.•.'•^ KMGfsESiUl
,: i';:,i':, " , , ,.'. • '; ii(; , • fr,;-. ii" ,.' > .;i ;, » - 1 fili.Y ". „• ("'''I i':;/" l.V":» #-j>. i'::;" '>, "': ' I-
FfeSettled Influent
E-10
-------
Cation-Sand
Peat-Sand
Influent
Bfluent
Corrpost-Sand
Influent
Bfluent
Sand
15
12-
W[coxmP=0.0625
9-
6
3-
Influert
Bfluent
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15
\McoxDnP=0.1563
V
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Influert Bfluert
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13
12-
I
9-
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. (
t
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Influent
Bfluent
Influent
Bfluent
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Influent
Bfluent
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12-
(
9-
6-|
3-
V\flcoxonP=0.4063
S
_<
1 - ' " 1
Influent Bfluent
EMCON
Influent
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SE#1
•-SEM
CALQUM: Resettled Influent
E-11
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r^- in r- io co
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-------
;
Carbon-Said
Peat-Sand
Zeolite-Sand
200-
150-
100-
50-
i
Wtoo>acnP=Q2657
200-
150-
g 100-
50-
WlcoxcnP=0.0313
200
g 100-
WlcoxcnP=0.4063
^ - — ~
t — _
-\
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.<
— 9
Influent
Effluent
Influent
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influent
Sand
Enretech
Effluent
Compost
200-
100-
V\Jkx»«onP=a3125
200-
150-
5 100-
— I
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50-
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200
150-
S 100-
50-
Influent Bfluent
EMCON
Influent Effluent
Gunderboom
Influent
Effluent
ADS 4420
150-
100-
50-
6
VVkx»cnP=Q2188
150-
g 100-
50-
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WicoxDnP=0.4532
200-
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50-
V\(lcoxDnP =0.4033
Influent
Effluent Influent
Effluent
Influent
SE#1
SE#3
Effluent
SE#5
HAROVESS: Unpretrealed Influent
E-16
-------
Carbon-Sand
Peat-Sand
80-
eo-
5 40-
20-
W(icoxcnP=0.0313
0-0=
Influent
Influert
Bfluent
Sand
Enretech
80-
60-
S 4°-
20-
WlooxcnP=0.5625
80-
60-
40-
20-
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Influent
I
Effluent
EMCON
g)
g" 40-
(
VUIooxcnP=0.4063
k—
(
Influent Effluent
Qtixterboom
80
60
Zeolite-Sand
80-
60-
S 40-
20-
VUIcoxmP=0.0938
I
Influert
Effluent
Corrpost
80-
60-
.6 4°-
20-
WlcoxmP=0.0313
Influent
Effluent
ADS 4420
5 40-
20-
Influent
Effluent
WHooxmP=0.1563
! — • —i
jert Bfli
60-
g" 40-
P 20-
> 0-*
jert Infli
VUIooxcnP= 0.0313
N- ' .
[ ~i
jert Bfli
SE#1
SE#2
•-SEM
SODIIM Unpretreated Influent
E-17
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Bfluent Influent
0.0
Effluent Influent
Bfluent
Sand
Ehretech
Compost
1.5.:
0.0
1(
0.0
Influent Bfluent
EMCON
Influent Bfluent
Gunderboom
0.0
Influent
Bfluent
ADS 4420
0.0
Hfluent Influent
SE#1 -"- SE#2
0.0
Bfluent Influent
Bfluent
SE#3
SE#5
AJVIVOMLM Unpretreated Influent
E-18
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
30-
20-
10-
WlcoxcnP=0.0625
30-
20-
10-
WlcoxmP=0.0313
Bfluert Influert
Effluent Influent
Effluent
Sand
Enretech
Compost
30-
20-
10-
W!ooxcnP=0.4063
30-
20-
10-
WlcoxonP=0.1563
o-5?
1 I
Influert Bfluert
EMCON
un i
Influert Bfluert
Gunderboomi
Influent Bfluert
ADS4420
30-
20-
10-
WlcoxmP=0.3125
30-
20-
10-
VWooxcnP=0.1563
Jfc
30-
20-
10-
VyicoxmP=0.3125
un i un^
Influent Effluent Influent
SE#1 -u- SE#2
I
Effluent
" I I
Influert Effluent
SE#3
POTASSIUM: Unpretreated Influent
E-19
-------
a k.
Carbon-Sax)
6-
4-
WtooxcnP=0.3125
Irfluert Efluert
;' ,r 'r.ii! , .,
-------
Carbon-Sand
Peat-Sand
Influent
Bfluent
Influent
Bfluent
Sand
Enretech
40-
30-
5 20-
VWcoxcnP=0.5625
40-
30-
5 20-
VWcoxonP=0.0313
10
Influent Effluent
EMCON
Influent Bfluent
Gunderboom
40-
30-
5 20-
10
WlcoxonP=0.4063
40
30-
20-
10-4
WlcoxmP=0.1563
Zeolite-Sand
40
5 20-
10
VyicoxcnP= 0.0938
H
Influent
Effluent
Compost
Influent Effluent
ADS 4420
40-
30-
5 20-
10-
WlcoxonP=0.0313
Influent
Effluent
SE#1
Influent
SE#2 '
Effluent
Influent
Effluent
SE#3
SE#5
CALQUM: Unpretreated Influent
E-21
-------
• • • IIIIIIIIB ^'iW'riili'J1!1!!!'! TIE!,!!1!!1!!, ''
'.""',* umr*i •iT^1|»r!
nl" !'
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!'' 'I'lF11!!!!;1'"!'!1.' iliV'I'ilitiiinii'ill1!!"'!1"!"!! I!!, 'liWiB"1 i -llll'^'iHIIBiflllbiBIIIIIIIIIIII' I'
""i,,"1!",1 , •,.,,i'hi . 'Ii;,'. S •"' H" .i|"":'!!i|illb .
11
-------
Appendix F:
Solids and Particle Size Distribution
Total Solids
Dissolved Solids
Suspended Solids
Volatile Total Solids
Volatile Dissolved Solids
Volatile Suspended Solids
Particle Size Distribution (1 to 2 (am)
Particle Size Distribution (4 to 5 urn)
Particle Size Distribution (11 to 12 ^m)
Particle Size Distribution (1 to 128 urn)
F-1
-------
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CM CM — CM —
CM m CM CM m
CO CM ro CM —
s E S S S
^ — "fr ya o
- 2 2 S S
C
rt
on
a.
VI
o r- — CM o
vn i r-i (*-, *!f
1
CM ^ ^ T if.
r-. f. o Jp ^'
° oo -rr 22 oo
CO ° CM O? °
O CO rj- — CO
CM CM oo o r- —
•* CO o» — ' —
'
— "^ — — —
0 00
CM CN O — ^£
CM CM V% Tf ^
OJ — _ — — .
CM CO CM CM CO
CO CM CO CM ^-
s £ S S £
__' CO 'O O VI
•a °° ^ M ri n
a
u
u
Ul
F-4
llllllK • i, .il: Jiii „ i!illilll :&i:>wiHL
-------
e
3
c
t—*
-a
_o
o
oo
s
^
s
s
I
I
1
g
IX
VI
e Suspended So
(mg/L)
_«
o
/ed Solids
)
"S ^-i
8 E
S •=•
—
^
'o
M
•o
00
/olatile Total
(mg/L)
01
Decrease |
«R
Effluent
1
C
i
#
„
§
c
m
1
c
% Decrease
w
„
§
£
z
SAMPLE GROUP
Sen — •• \o o
p-* vo — • VO
0 <* - 2 CM
CM 12 £5 •* m
r- 10 CM ON o
• "T en en V
01 *3- r- — « CM
en °° "* — °°
.,.,,
CM OO OO —« **
en — CM CM —
CM en CM 0) en
en CM en CM — •
1 e s E s e
co v, « •* vq o
3
tx
1
° <- CM g Q
en oo co „ "*
O\ C4 ^ O co
N 10 oo ,,. „,
t en CM o *n
rQ r- ON 2 NO
o oo ^ 2 oo
\o — • en oo — •
i vO ~^ — • CO
"'•f rt\ ®^ ®® ON
ci ^' °° ^ in
p^ m o oo — .
fn CM "i CN
°^ °^ oi ^ oo
0 oo „- 22 oo
ON f rj 0 en
ON TJ- r~- CM t-^
CM C^ ^^ CM ^^
CM en CM CM m
en CM en CM — •
.g c £ E S S
£ 2 2 S § S
1
1
o
o
rCJ fn 0\ r-- 0
S 2 ^o = „
M 10 CO „. „
S 3 i 5 °
-
2 en S ^o oo
S °° •* 2 oo
« e^ S ?! 0
5 S S £ 2
CN CO CN C-l CO
CO CS CO CN •—
c £ E £ E
10 -. ^ «? °.
•c °° 2 S ° cQ
\
O
I_>
w
F-5
-------
Si:
' ••''. ";;:„ :Carbon-Sand
120-
Peat-Sand
Zeolite-Sand
100-
80-
60-
23-
WtacnP=0.5000
-. :r-A
==^V
100-
<
n
S eo-
20-
V\tocnP= 0.6250
Influent
Effluent
Influent
Bfluent
Influent
Conposl-Sand
Enretech-Sand
Effluent
Forest-Sand
120
100-
60-
4°
20-
Wlco)cnP= 0.5000
120
100-
(
60-
1
L
20-
0
VUIooxcnP= 0.5000
Influent
Effluent
Influent
Effluent
Influent
Sand
Gunderboom
Effluent
EMCON
120-
100-
ion
8
1
20-
o
VWIcmoiP =0.2188
Effluent , , Influent,
-•- SE#2'
Effluent
Influent
SE#3
Effluent
TOTAL SOUDS: Pre-Settled Influent
. •','.'Wl""» rLllJl'i I
F-6
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
120
Influert
Bfluent
Influent
Bfluent
Compost-Sand
Enretech-Sand
Influent
Effluent
Influent
Effluent
Sand
Gunderboom
120
100-
80-
VUIcoxcnP= 0.4375
60-
40
20-
0
<>. - -..... .... X
-E^-~IZJ^-1C3
Influent
Effluent
Influent
Effluent
100-
80-
60 J
40 -j
20-
vyico)oip=ao3i3
»(
' — - — !
influent
Effluent
Forest-Sand
Influent
Effluent
EMCON
120
100-
80-
WllcoxonP= 0.0313
20-
0
Influent
Effluent
SE#3
DISSOLVED SOUDS: PreSettled Influent
F-7
-------
Cation-Sand
Peat-Sand
Zeolite-Sand
40-
30-
20-
10-
Wlco>cnP=0.1876
Influent
Bfluent
Influent
Bfluent
Influent
Compost-Sand
Enretech-Sand
Bfluent
40-
-> 30-
aa-
1°-
0.1563
40-
Fbrest-Sand
,!• . :::: :,
A
30-
S 20-
10~
WlcoxcnP= 0.3125
Influent
Bfluent
Influent
Bfluent Influent
Bfluent
Sand
Gunderboom
EMCON
Iri'uent
Bfluent Influent
SE4H -»-SE#2
Bfluent
Influent
Bfluent
SE#3
SE#5
: PreSettled Influent
F-8
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Bfluent Influent
Effluent Influent
Effluent
Compost-Sand
Enretech-Sancl
Forest-Sand
40-
l
20-
•1
0
WlcoxDnP=0.1563
. . -^ --^
Influent Effluent Influent
SE#1 -•- SE#2
Effluent Influent Effluent
SE#3 -^--SEW -4- SE#5
VOLATILE TOTAL SOUDS: PreSettled Influent
F-9
-------
Cartxn>Sand
Peat-Sand
Zeolite-Sand
Influent
Effluent Influent
Effluent
Compost-Sand
Enretech-Sand
Influent Effluent
Forest-Sand
60-
40-
20-:
WlcoxcnP=0.2188
Influent
Effluent Influent
Effluent Influent
Sand
Gunderboom
Effluent
EMCON
60-
40-
20-:
Wicoxcn P=0.3750
Irfluent
Effluent Influent
SE#1
Effluent Influent Effluent
-T-SE#4 -•«• SE#5
VOLATILE DISSOLVED SOLJDS: PreSettled Influent
F-10
-------
Carbon-Sand
Pfeat-Sand
Zeolite-Sand
30-
20-
10-
WlcoxcnP=0.2188
30-
20-
10-
VWooxcnP=0.4532
Influent
Effluent Influent
Effluent Influent
Effluent
Compost-Sand
Enretech-Sancl
Forest-Sand
Influent
Effluent Influent
Effluent Influent
Effluent
Sand
Gunderboom
EMCON
Influent
Effluent Influent
Effluent Influent
Effluent
SE#1
SE#3
VOLATILE SUSPENDED SOUDS: PreSettled Influent
F-11
-------
Carbon-Sand
Peal-Sand
Zeolite-Sand
Influent Effluent
Compost-Sand
Influent Effluent
Enretech-Sand
Influent Bfluent
Forest-Sand
Bfluent
Sand
Influent Bfluent
Gunderboom
Influent Bfluent
' "'. ' \ ifl' ' *
EMCON
15-
E
10-
WlcoxcnP=0.3125
E
<
10-
5-
j
i
VWcoxcnP= 0.2188
— (
^^^^^
r^ "
Influent
Effluent
Influent
SE#1
Bfluent Influent
SE#3 -T-SE#4
Bfluent
SE#5
!: PreSettled influent
.;!,i!iii1:.,|l»!l,i1i;|! FJhil11,, * lll^ .',• "fi" i!»
I -:,! * .«
IlliiaillllillillJ ir ,ii, illi ..... mull „ jilOMnilfi: ....... iiliUii,. i III; ...... I ill ......... liiiilim i
-------
a.
c
D
2
O
< Tt-
32
•< u.
5. U
'-J
S ^
o
H
Total Solids
(mg/L)
jROUPNAME
SAMPLE <
[ % Decrease
| Effluent
1 Influent
crease
D
Q
£
Effluent
(3
U
C
| % Decrease
u
E
c
0>
c
0)
Q
| Effluent
[ Influent
O — r* oo r~
c* r- n ^ f, o
CM -. ° g V,
2 — — o —
-- W 0 P> •*
« 2 ? s •"
rr c-l
tr> T~ *° *~~ °°
SS PS^
2 5 S 5 2
•o
c
ASSESS
A
1
rt
0
r-, r- ^ — oo
§ ?> ?. 1 S
K i s § 1
•sf V> ^ e*C O
-------
111
I
c
c
t-^
•£
2
Q.
!§
%
I
|l
ly
s 5
|2
ROUPNAME
SAMPLE G
% Decrease
c
>u
3
{=
W
c
=3
C
c
% Decrease
Effluent
C
w
3
C
J3
SS
Effluent
i
c
c
% Decrease
c
u
s
(5
"c
«J
3
e
c
•d- en fn id- o\
oo tn ^ — r-
r- -"a- 01 S3 -3-
>0 CN 01- £! 00
0\ 00 •* "t 00
en r-" 01" 5! •*
tr 0 01 S 0
o\ — , oo °i en
en t-~ 06" ~ vo"
\O — ' to U-l ol
r~ oo S; oo o
« "1 ?S -. °.
vo in __- o\ o Tt- o cs *n
r*» en ON r-J •— «
CM en — cM cs
^ iG m -* ^o
2 S •* o" •* S 2
>o — • .„ «-, rl
r- oo S =o o
m in g) — o
VO U-, CTi CM
« -. s r. s.
S 2 -*• 2 S
in n g "~- —
\o vo 2 "7 P-
~ vo o 2 t-
— • vo o en T(-
en — — — CM
*? — CM •* en
IJ 2 en CM i^-
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& 5 en TI- vo
2 t- 01 0 2
3 § S 5 S
2 5 K 5 §
E E E S E
— ' CM en •* »n
-^ — < oi en •* vl
I
|
CM vo en CN vo
u~. T — • c-) r-
00 cv ^f £ >n
«. S « " S
| S P i= §
M. ci o\ . -^
™ oo" ro* 2 t^-"
vo — .- 9 oo o
"I n CN -: o
vo »n • ON 01
=. -. R = -.
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PL. — ol en •*]• wS
C
i
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1
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VO O _ S O
w-( — en fs^
— en -^ ol oo
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,§ *— oi cri ^J" vi
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8
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F-14
-------
TD
U
O,
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££
<
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H
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^ o o o o
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£ « 2 « r-
fi o o **o r*-
22-22
^t r- o r- o
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vi «n c^i W m
•a
e
«? S S S S S
g — OJ r^ rf in
ji — ri r^ Tj1 m"
«
U
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u
„-, c*- o o __
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11-71
in o o r- r-
Tf r- o r- o
« 5 g 2 2
'
c\ o o c\ r-
m m w M n
S S <= E S
•— es cn
— ol f^ TJ- >n
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CO
s s s 1 §
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2 «*> 2 n d d c^
S £ S 6 E
— CM m Tf *n
— i c^ n Tf »n
o
u
e
pa
F-15
-------
" 1 "I i!1'
•' ';:!'"& wii1'1: r i-f ••: f~" t: 'i9iKfi, sowi. .'
,1
C/J
*^ 3
£"* P
_o £
o
V,
SJ
o
a
$£
C
UJ
C
c
i
Q
^
c
u
s
UJ
c
1
c
i
§
O
*
c
c:
w
e
e
c
2
o.
D
O^
O
i
en
5 § § § §
r-J m oo ^ o
»n ffi o r) j^.
ON OO O O\ CO
oo M r- oo co
r^- r-« r** *o o
oj b 5 o o
Tf r- o r- o
Tf Tf — CS CO
R S S S S
i i i i i
S S ^ 2 -*
« 1Q ON ^ o\
C\ O O Os t—
in in cs f» co
E £ E S S
— • CN co Tf in
— cs co Tf m
C/)
O
d.
o
0
CO g 0 0 2
^ O — cO OO
!2 m 2 f*i r-
00 ^ O m o
. - v? co cs
CS Ol -O OO Tf
Tf r-- o p- o
Tf Tf — " Ol CO
Q vo in oo Tf
'
in cs r- — • cs
*O Tf —• CN CO
O\, O O ON p1-
in vi cs
-------
CarborvSand
Peat-Sand
Zeolite-Sand
400-
300-
5 200-
100-
VUIcoxcnP=0.4532
Influent
Effluent
Influent
Effluent
Influent
Effluent
Sand
Enretech
Compost
400
B 200-
100
Wlco)cnP=0.0938
400-
300-
5 200-
f
100-O
V\JlooxmP=0.1250
• -o
Influent
Effluent
Influent
SE#1
Effluent Influent
SE#3 -T-SE#4
Effluent
TOTAL SOUDS: Unpretreated influent
F-17
-------
, ' *' |i'!! IP," "'L,'1:,,,
Carbon-Sand
Peat-Sand
Zeolite-Sand
400
Influent
Effluent
sand"
cnP= 0.0469
<:
t=_-^=r=~S
jent Efflt
; -I (;,;•;; . ;;;, •;• |i. "" i ;
" ' 1 Millf iSi1
Ehretech
Compost
400-
300-
za-
1CO-
VMIcoxcnP=0.4063
Influent
Effluent
Influent
Effluent
Influent
EMCON
Gunderboom
Effluent
ADS 4420
WkX33CnP=0.4063
400-
300-
200-
100-
V\JlooxcnP=0.2657
400-
300-
200-
100-
V\«looxDnP=0.4063
Influent Effluent Influent
„;:; ,!:;:,;; -•- SE#1 -»- SE#2
Effluent
Influent
II-
Effluent
SE#5
DISSOLVED SOUDS: Unpretrealed Influent
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Bfluent
Sand
Influent
Bfluent
EMCON
Influent
Bfluent
Enretech
Influent
Bfluent
Gunderboom
Influent Bfluent Influent
SE#1 -m- SE#2
Bfluent
Influent
Bfluent
Compost
Influent
Bfluent
ADS 4420
SE#3
Bfluent
- SE#5
SUSPENDED SOUDS: Unprelreated Influent
F-19
-------
Kill
lit1 [, .•I'l,.1
tit >
ill >!'
ir I I
ii1"'
t1
Carbon-Sand
Peat-Sand
Zeolite-Sand
160-
120-
80-
WlcrocnP=0.0313
Sand
Influent Effluent
i • i " •; ' i i
,ll,Enretech; ,.r
Influent
Bfluent
Compost
ifli '« I . • .: , , • V ;, •.
160
160
Influent
Efluent
Influent
Effluent
Influent
Effluent
EMCON
Gunderboom
ADS 4420
160-
120-
S 80-
40
VWcoxonP=0.0313
Influent P"yent , Influent
""","" .'. -«-SE#1 -U-'SE#2.
.................. .Effluent ............ Influent
SE#3 -T-SE#4 "'
Effluent
ydL/ffiLE TOTAL SOUDS: Unpretrealed influent
F-20
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent Effluent
Enretech
Influent Effluent
Corrpost
160-
120-
S 80-
40 J
WllcQxcnP=0.3125
Influent
Effluent
Influent
Effluent
Influent
Effluent
EMCON
Gunderboom
ADS 4420
160-
120-
80-
40-T
WlcoxmP =0.3125
160-
120-
80-
40 J
VUlcoxmP=0.1563
Influent
Effluent
Influent
Effluent
Influent
Effluent
SE#1
SE#3
SE#5
VCXAHLE DISSOLVED SCXJDS: Unprelreated Influent
F-21
-------
Rl-iilil!
Carbon-Sand
Influent
Effluent
Sand
Influent
Effluent
EMCON
50-
30-
20-
V«lcaxcnPs0.1563
Peat-Sand
50-
40-
30-
20-
10
McoxcnP=0.2657
Influent Effluent
Enretech
Effluent
Gunderboom
Influent Effluent Influent
-•- SE#1 -9- SE#2
Effluent
Zeolite-Sand
Influent Effluent
Compost
Influent
Effluent
ADS 4420
Influent
Effluent
SE#3
•- SE#4
>• SE#5
: Unpretreated Influent
F-22
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent Bfluent
Sand
Influent Bfluent
Ehretech
Influent Bfluent
Compost
Influent
Effluent
Influent
Bfluent Influent
Bfluent
EMCON
Gunderboom
ADS 4420
Influent Bfluent Influent
-*-- SE#1 -*- SE#2
Bfluent Influent
SE#3 -T-SE84
Bfluent
SE#5
PARnCLESIZEDISTFaBUTlON: Unpretreated Influent
(1 to 128 |jm)
F-23
-------
111! I '. ( I. ill! I"
!. i't • "'" '
J
B
'^'
b
3 g
tt S
Q
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2
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11.
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p*. VQ o o r-*
VO VQ Tf r? CM
TT 0 vo g ^
2 3 5 S S
m CN Tf 2 ™
r- ^o oo ^ c,
CN O O — VC
Ol en vo CN p—
CM — VO CM vo
e
S
i S S E S £
5 « " •*. *°. °-
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u
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<
vi p _ — 2
S = g S 3
o V-. in CM 01
O P- CO O- OO
» CM
^r oi •* oo CM
"'i OO OO VO —
PJ tn CN of en
% § I ° 2
01 — — ON -*
en oo
vo
tj vo so *n
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p-T so" irt •*£ -*t
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oo CM O en, ON
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°° ™
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in Tf co oo p-
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CM *n CM CM en
ON ON O — « vo
en vo o vo m
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g S £ £ £
"^ OQ" en vd O v
CO
-------
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CO
2
a s
g "E
c3 3
1. 2
•n E
7 "|
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ti
SAMPLE GROUP NAME
% Decrease
c
u
s
W
Influent
% Decrease
E
w
Influent
% Decrease
Effluent
Influent
% Decrease
1
w
1
ES
>s
r- S C! 22 **
CM in T 't "7
ON OO O — - CM
\O — •" \O OO »O
— ON OO ' —• ^f
CM Tl- OO CM CM
vo CM uo oo Tf
CO OO O OO r-
ON oo co" CM" — "
£ CM r- oo t--
£ CM •* 00 CM
- oo. oo^ vq. — ; ^
£$ in ON" CM" co
£2 — t— vi m
°°.. *•* r- ON m
CN „_- " — " «"
•^f — co -*• co
\o ^t- oo ^ cr\
*3- oo ON ,_, vo
wo »n oo 2 TT
VO -^ ON g£ •*
O O f- -T CM
*""• £J ""> oo 2
iS o wo S wo
S. 8 S St 3
s a s § s
o\
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c- M- °? 8 °?
r~~ in
ON CM ^* C— WO
vra X- CN WO VO
o" \o °°- ^ cn-
u-i vo -^f yo co
" 3 £ § £
OO «^ O CO O\
VO 0 t> O O
- (N (N CO -i
CO CO C- O •^~
r< \o o o r-
l," — • Tt 04 CM
-q-
o o r- rj
S ^ co r^ g
in co oo r- oo
O CM CO Tf CN
CM O CM — < VI
in \o — • ON o
r-
oC >n" -- °i •*.
t- m >n — n-
2 ~- f: S S
oo CM o co ON
\o o r- o o
- CM CM_ CO. -H
R S 5 § S
5 - *- r~ in m
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oo. oo_ oo_ vq —
Pi in" cC
-------
Ill 1111 ill II
III
1!1;;
Carbon-Sand
Peat-Sand
Zeolite-Sand
1.00-
3.
<° 0.75-
O
~rn 0.50-
0.25 -i
V\JlcoxcnP= 0.0313
•f ^-
i 0.00-
Influat Bfluent
Corrpost-Sand
1.00
« avs-
Q50-
aas-i
aoo
Influent Bfluent
EnretectvSand
1.00
Influent Bfluent
I
|
Forest-Sand
1.00-
Influert
i
Bfluent
Influent
Bfiuent ..... ..... Influent"
' '
Effluent
' '
S" I'll : I
'% '.:;!'«! -Sand
Gunderboom
EMCXDN
1.00
0.75-
aso-
Q.2S-,
aoo
1.00-
E
0.7B-
0.50-
0.25-;
0.00-
WlcoxcnP=0.3125
1.00-
5
0.75-
0.50-
0.25
0.00-
VW!coxcnP=0.1563
Influent
Bfluent Influent
SE#1 -»- SE82
Bfluent
Influent
Effluent
SE#3
SE#5
Pil-
PAICLE SIZE DISTRIBUTION: PreSettled Influent
F-26
I '!"U: ";'-!
i: if isr
11
lill. Hill
-------
Carbon-Sand
Influent
Bfluent
Compost-Sand
Influent
Bfluent
Sand
Peal-Sand
Zeolite-Sand
Influent
Bfluent
Influent
Effluent
Enretech-Sand
Forest-Sand
Influent
Effluent
Influent
Effluent
Gunderboom
EMCON
4-
WllooxonP=0.4063
4-
3 2H
o-?S
Influent Bfluent Influent
-9- SE#1 -•- SE#2
Effluent Influent
SE#3 -T-SE#4
Effluent
>- SE#5
PARTICLE SJZEDISTFaBlJTlON: PreSettled Influent
(4to5jjm)
F-27
-------
SI'-I in.1!
!* I' '/'-I, i, .,,
:»2'tM "H;
Carbon-Sand
Peat-Sand
Zeolite-Sand
1.00
...... .;•, . lofluent
Effluent
Influent Effluent,
Enretech-Sand
Influent Effluent
Forest-Sand
Effluent
Gunderboom
• *" , "t!ij':;^ : *<':•*••''? jigj:;,; "
0.75-
0.50-
(
0.25-
i
nm
WHooxDnP= 0.4063
^\
^^~!^
"i
«° 0.75 -
0
IT 0.50-
"3 '
-------
Carfcon-Sand
Peat-Sand
Zeolite-Sand
Influent
Bfluent
Influent
Bfluent
influent
Bfluent
Compost-Sand
Enretech-Sand
Forest-Sand
Influent Bfluent
Sand
Influent Bfluent Influent Bfluent
Gunderboom EMCON
15-
10-
5H
.1
V\JlcoxcnP=0.3185
10-
l
WlcoxcnP= 0.2188
j
_ -•<
^=—~^
I
Influent Effluent Influent
-«- SE#1 -f- SE#2
Bfluent Influent
SE#3 -T-SE#4
Bfluent
SE#5
PARTICLE SIZE aSTRIBUTlON: PreSettled Influent
(1 to 128pm)
F-29
-------
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-------
1
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Cumulative
(um'/mL)
£ _
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SAMPLE GROUP NAME
% Decrease
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1
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1
c
c
% Decrease
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% Decrease
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=s vo 5j en t~
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c^ £ ^' 2 S
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F-31
-------
I III
Carbon-Sand
Peat-Sand
Zeolite-Sand
1.5-
,. !;„, '' .. . «•
us; i • ••;, £
1.0-
'•::/: -: ' o
18 it'':*'-.
0.5 H
WlcoxmP=0.1563
3 ao'.
I, i"'iii "III.'S '"'; : III'SJ 1
Effluent
Influent
Effluent Influent
Effluent Influent
SE#1
SE#3
-SEM
Effluent
- SE#5
P/^TICLESIZEDISTFIIBUTION: Unpretreated Influent
F-32
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
Effluent Influent
? 23 0.5
Bfluent Influent
Effluent
Sand
Enretech
Compost
Influent
Bfluent Influent
Hfluent Influent
Effluent
EMCON
Gunderboom
ADS 4420
Influent
Effluent Influent
Effluent influent
Effluent
SE#1
PARTICLE SIZE DiSTRlBUnON: Unprelreated Influent
(4to5|Lim)
F-33
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
in in
Influent
Bfluent Influent
Effluent Influent
Sand
Enretech
Effluent
Compost
Influent
EMCON
Ml II
Effluent
Influent
I
Gunderboom
Effluent Influent
I
Effluent
ADS 4420
Influent Effluent
' '-'•<>- SE#5 '.
Nil,!,
'in , ji'iiiiii I'M1,'! ' •]• •,ja.j'iii;.•__•_«jf' • ,.-,1, .!i-;, .in.! > •;,• •..> -ii, ... > \ inii ii i
PABTICLE SIZE DISTRIlUnON: Unpretreated Influent
(11 to 12 jam)
F-34
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
Influent
I
Effluent
Sand
Influent Effluent
EMCON
Influent Effluent
Enretech
Influent Effluent
Compost
Influent Effluent
Gunderboom
Influent
Effluent
ADS 4420
Influent Effluent Influent
-9- SE#1 -*- SE#2
Effluent Influent
SE#3 -T-SEM
Effluent
- SE#5
PARTICLE SIZE DISTRIBUTION: Unpretreated Influent
(1to 128pm)
F-35
-------
illii-i , • I"* li'1'.k
if ill!-.
U
filii V I:!!!
i, J V*!!1. "'I!"1, ; ' "V
i m *•'
-------
Appendix G:
Metals
Zinc
Copper
G-1
-------
c
-a
O
to
z
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c-^ -^
-------
ll
'I'frM i ' "ill1'!:!'!1, Mill!,
sis'i 'i- ,'!M.; ! mi
CarbooSand
Peat-Sand
,:„-' „ '•filll'irlilliili:1 ii'; -I"! ,<
Zedite-Sand
Influent
Bfluert Influent
Effluent Influent
:H.P[?TlPos*"®and
Ehretech-Sand
Influent
Bfluert Influent
Sand
'
Gunderboom
Influent
Effluent Influent
SE#1
ZINC: PreSettled Influent
Unfiltered Fraction
Effluent
Forest-Sand
Effluent Influent
Effluent
EWCON
' '
Effluent Influent
Effluent
, i,'! ; 'ft I
I, '1 ii ,, |U
:,"":'Kill,
G-4
-------
Carbon-Sand
Influent
Effluent
Compost-Sand
Influent
Effluent
Sand
Influent
Effluent
Peat-Sand
Zeolite-Sand
VMIooxoiP= 0.0313
40-
30-«
20
10-
3
Influent
Effluent
Influent
Effluent
Enretech-Sand
Forest-Sand
Influent
Effluent
Influent
Effluent
Gunderboom
EMCON
Influent
Effluent
SE#1
SE#3
Effluent
SE#5
ZINC: PreSettled Influent
Filtered Fraction
G-5
-------
c
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00
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Peat-Sand
Zeolite-Sand
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10-
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10-
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Effluent Influert
Effluent Influent
II
^
Effluent
Cpnpost-Sand
EnretedvSand
15-
10 -
WlcoxmP= 0.4063
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'Hfluert
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infuert
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Sand
Gunderboom
EMCON
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'
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•
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COPPER PreSettled Influent
Unfiltered Fraction
I'l'mEi >! 1!
G-8
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-------
Carbon-Sand
Peat-Sand
Influent
Bfluert
Compost-Sand
Influert
Bfluert
Sand
Influent
Bfluert
Enretech-Sand
Influent
Bfluert
Gunderboom
Zeolite-Sand
10-
WlcoxonP=0.2188
Influert
Effluert
Forest-Sand
Influert
Bfluert
EMCON
Influert Bfluert Influert
-9- SE#1 -*- SE#2
Bfluert
Influert
Bfluert
SE#3
SE#5
COPPER PreSettled Influent
Filtered Fraction
G-9
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'V, !•: t.; stilt , ••. r i "if ail fr'r.< :.
-'I" " " 'lill • nil Jill
"!w "'.""111,', f II
• is."i.;,'
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-------
Appendix H:
Chemical Oxygen Demand
Semi-Volatile Organics
Pesticides
H-1
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-------
Carbon-Sand
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40-
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EMCON
Influent
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CHEIVICAL OXYGEN DEMAND PreSettled Influent
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H-5
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100-
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150-
100-
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Effluent
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150
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CHBVICAL OXYGEN DEMAND: Unpretreated Influent
Filtered Fraction
H-9
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y
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a
s
^
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frl
1
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Z "Z ™~" ~"
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z z z g z
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Z Z g Z Z
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£
55888
Q ° D Q Q
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i;:!"*! *
in i •! •
Carbon-Sand
Peat-Sand
1.5-
1.0-
0.5-
WtoxcnP=0.12SO
1.5-
1.0-
0.5-^
0.0
VUlcoxcnP=0.1250
1.5-
Zeolite-Sand
, , i , ,
!
1.0-
0.5-
0.0 -u
VMIcoxoiP=0.2500
Influent
1!; ,, i!*!! «;!!, i
Influent
Effluent' " " ' Influent
Effluent
", iir-i "• ,,n<
Compost-Sand
Enretech-Sand
1.5-
1.0-
05
0.0
WkoxonP=0.3750
1.5-
Eprest-Sand
1.0-
0.0-
VWIooxmP=0.12SO
1.5-
1.0-
0.0-
Influent
Bfluent
Sand
Influent Effluent
Gunderboom
WlcoxcnP=0.3750
Influent Effluent
EMCON
1.5-
1.0-
0.5-
O.OHh
WooxcnP=0.3125
1.5-
1.0-
P
en
0.0-
V\JlooxcnP= 0.1250
\
\
\
1.5-
WllcoxmP= 0.0625
1.0-
0.5-4^-
0.0
Inflyej* Effluent Influent
SE#1 -«- SE#2
Effluent Influent
"I ','
-T- SE#4
Effluent
2,4-aisnROPHENCX: PreSettled Influent
H-24
I l
-------
Carbon-Sand
Peal-Sand
Zeolite-Sand
0.0
VWooxonP= 0.3750
-?
/_. N,,
0.4-
0.3
. 0.2-
0.1 -
WilcOXDnP = 0.2500
Influent
Effluent
0.0-
I
influent
0.4-
.§ 0.2-
VWIooxonP= 0.3750
Effluent
0.0 -CjH—
Influent
-"—HI
Effluent
Compost-Sand
Enretech-Sand
Forest-Sand
0.4-
0.3-
0.2-
0.1 -
0.0
WllcoxDnP=0.5000
0.4-
0.3-
0.2-
0.1 -
Wi1coxonP=0.6250
0.4-
0.3-
0.2-
0.1 -
0.0-
WllcoxonP=0.2500
Influent Bfluent
Sand
Influent Effluent
Gunderboom
Influent Effluent
EMCON
0.4-
0.3-
0.2-
0.1 -
0.0
WilcoxonP= 0.2500
0.3-
0.2-
-9
WilcoxonP =0.2500
^H
Influent
Effluent
SE#1
0.0 -cp—
Influent
^#2
——9
Effluent Influent
SE#3 -T-SEM --*--SE#5
Effluent
2-METHYL-4,6-DINITROPHENOL: PreSettled Influent
H-25
-------
llll'l'I'HIIll' I l»l|"!"l ||',I,T I||M||I' " "i ' ill Hill II II III IIIIIIIIIIUIII 1 illl II II ' " LlllJi, . WillUM1 ,•„• ", '"1 "' 1 1 1 II II l| illl illl Illl Illl II 1
1,0-
0.8-
;:;,,., 7;; •;;:.. ,| M^
":; V ; " "',; ! " ;J --_^
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Compost-Sand
I'll! ii! |!"i l».'. 'i, Wlf", ' II! K 1 * ' , J.U
0.8-
S. 0.6-1
T ' ,'" ,'' 1 °'4~
,,::" ;. :: ' sr- ',. I ^J
i,|i'!il';, 1 i, IF , Ii- ' '! *>!
1.0-
•., .;.;•,. .• .. 0.8 ~
•§• 0.6 -I
,§ 0.2-
II '. . r ™t
W!coxcnP= 0.3750
>_.,
*'•-..
r \
jliiiiijil j,.. " . ., , !•
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Sand
WicoxcnP =0.2500
\
"•---^
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I ''. I | .,•!" , , ' IlliiJl!'! " SI , 1 ''•, ' , „,;!,;!„.•
1.0-
i
0.8-
§. 0.6 -t
S 0.4-
1 0.2-5
',, , • ,a°^
jent Infli
1.0-1
0.8-
* 0.6 -)
S
1 0.4-
1 02\
0.0-
jent Infli
1.0-
0.8-
§. 0.6-1
5
I 0.4-
o a2~
1
5 0.0-1
jent Infli
Peat-Sand
WicoxcnP =0.1250
1-
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^.--^..
* ' . ~*
rn i
jent Effli
Enretech-Sand
WicoxcnP =0.3750
L__
' . . (
r ^
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Gunderboom
WlcoxcnP=0.1250
\
h- r \._ (
r . "j(
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':,, ' , , '•'Illli, 11 !"
1.0-
0.8-
3- 0.6-1
1 -S
1 0.4-
1 0.2^
f
> 0.0 -t
jent Infli
1.0-j
0.8-
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S
1 0.4-
r 1 Q2j
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> 0.0-1
jent Infli
0.8-
S 0.6-1
S
1 0.4-
} 0.0 -i
jent Infli
'" ' , 'I, "ill: ', *:
Zedite-Sand
VWIcoxcnP= 0.3750
. 1
1— -"
>TT_ ,
II " • .
"
1
r
jent" Effluent
Forest-Sand
WlcoxonP= 0.3750
L_ __ -
""""•\
I
r
jent Effluent
EMCON
VyicoxonP=0.1875
«
\
y^^.
i
t
S
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ij - ' ' ' ' • -I1 •• "''• 'if 'i' v •] ..iiiiii1. jiiLf,,,
,.,,.,.,„ .. . l!r ,, . , , ..,*, ,.-r«-:SE#1 -•- SE#2 . -A- SE#3 -T-SEK '"O--SES5
' ' '
,
DJ-N-BUTYUWHAU^ B^Settled Influent
I ihl • •,: ' i, 1 ;,',", 'ii ,,;.'! '"' !•" " „ • •"'!•'; ',,",•'• .•• 5 / '"''' •'• fliii,!'il:"'":i . ,v ', '•,;•,!' , • • ,i' •' : : . 'f'1' •! h li,!1 ""»
H-26
-------
Carbon-Sand
5
4-
3-
I
2-
i
1 -
VyicoxmP= 0.1250
Influent
Effluent
Compost-Sand
o —
4-
"§> 3_
.i i
1 ^
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Vyicoxcn P =0.2500
k
^x
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r H
Influent Effluent
Sand
4-
3-
I
2-
i
1 -
0.1250
Influent
Effluent
Peat-Sand
4-
3-
\McoxonP=0.1250
-^4
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Effluent
Enretech-Sand
4-
3-
I
2-
1
WllcoxcnP= 0.3750
Influent Effluent
Gunderboom
0-y
Influent
Effluent
Zeolite-Sand
VyicoxcnP=0.1250
0-^)—
Influent
Effluent
Forest-Sand
3, 3-
s
Wlco>cnP= 0.2500
°-t—
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Effluent
EMCON
4-
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o^
Influent
Effluent
SE#1
SE#3
-SE#4
BIS(2-ETHYmEXYL)F1-rrHALArE: PreSettled Influent
H-27
-------
Carbon-Sand
Peat-Sand
Zeolite-Sand
nut 'i!>,, i n'< • "•' • • ni ii'i'i"
Si' ml l!Vv i ••
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1.5;
a
W!coxcnP=0.4375
Q.pry—
lofluert
1.5
1-0-
0.5-
0.0
WI
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