Stormwater Treatment at Critical Areas The Multi-Chambered Treatment Train (MCTT)


vvEPA
        United States
        Environmental Protection
        Agency
            Office of Research and
            Development
            Washington, DC 20460
EPA/600/R-99/017
March 1999
Stormwater Treatment at
Critical Areas:
The Multi-Chambered
Treatment Train
(MCTT)

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                                                    EPA/600/R-99/017
                                                       February 1999
Storm water Treatment At Critical Areas:
    The Multi-Chambered Treatment Train
                         (MCTT)
                              By

               Robert Pitt, Brian Robertson, Patricia Barron,
                    Ali Ayyoubi, and Shirley Clark
             Department of Civil and Environmental Engineering
                The University of Alabama at Birmingham
                    Birmingham, Alabama 35294
                 Cooperative Agreement No. CR 819573
                         Project Officer

                          Richard Field
                Wet-Weather Flow Management Program
               Water Supply and Water Resources Division
              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 U.S. Environmental Protection Agency
under Cooperative Agreement No. CR 819573 for the University of Alabama at Birmingham. It has been subjected
to the Agency's peer and administrative review and has been approved for publication as an EPA document.
Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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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 the first volume for this report series and describes the work conducted during the early years of this project
through recent full-scale tests. Other volumes in this report series describe the results of field investigations of storm
drain inlet devices and the use of filter media for stormwater treatment.

The first project phase investigated typical toxicant concentrations in stormwater, the origins of these toxicants, and
storm and land-use factors that influenced these toxicant concentrations. Nine percent of the 87 stormwater source
area samples analyzed were considered extremely toxic (using the Microtox™ toxicity screening procedure).
Thirty-two percent of the samples exhibited moderate toxicity, while fifty-nine percent of the samples had no
evidence of toxicity. Only a small fraction of the organic toxicants analyzed were frequently detected, with 1,3-
dichlorobenzene and fluoranthene the most commonly detected organics investigated (present in 23 percent of the
samples). Vehicle service and parking area runoff samples had many of the highest observed concentrations of
organic toxicants. All metallic toxicants analyzed were commonly found in all samples analyzed.

The second project phase investigated the control of stormwater toxicants using a variety of conventional bench-
scale treatment processes. Toxicity changes were monitored using the Azur Environmental Microtox™ bioassay
screening test. The most beneficial treatment tests included settling for at least 24 h (up to 90 percent reductions),
screening and filtering through at least 40 fj.m screens (up to 70 percent reductions), and aeration and/or
photo-degradation for at least 24 h (up to 80 percent reductions). Because many samples exhibited uneven toxicity
reductions for the different treatment tests, a treatment train approach was selected for testing during the third
project phase.

The third project phase included testing of a prototype treatment device (the multi-chambered treatment train, or
MCTT). However, the information provided in this report can also be used to develop other stormwater treatment
devices. This device, through pilot and initial full-scale testing, has been shown to remove more than 90% of many
of the stormwater toxicants, in both particulate and filtered forms. The MCTT is most suitable for use at relatively
small and isolated paved critical source areas, from about 0.1 to 1 ha (0.25 to 2.5 acre) in area. These areas would
include vehicle service facilities (gas stations, car washes, oil change stores, etc.), convenience store parking areas
and areas used for equipment storage, along with salvage yards. The MCTT is an underground device that has three
main chambers: an initial grit chamber for trapping of the largest sediment and release of most volatile materials; a
main settling chamber (providing initial aeration and sorbent pillows) for the trapping of fine sediment and
associated toxicants and floating hydrocarbons; and a sand and peat mixed media "filter" (sorption-ion exchange)
unit for the reduction of filterable toxicants. A typical MCTT requires between 0.5 and 1.5 percent of the paved
drainage area, which is about 1/3 of the area required for a well-designed wet detention pond.

A pilot-scale MCTT was constructed in Birmingham, AL, and tested over a six month monitoring period. Two
additional full-scale MCTT units have recently been constructed and are currently being monitored as part of
Wisconsin's 319 grant from the U.S. EPA. During monitoring of 13 storms at a parking facility, the pilot-scale
MCTT was found to have the following overall median reduction rates: 96% for total toxicity, 98% for filtered
toxicity, 83% for SS, 60% for COD, 40% for turbidity, 100% for lead, 91% for zinc, 100% for n-Nitro-di-n-
proplamine, 100% for pyrene, and 99% for bis (2-ethyl hexyl) phthalate. The color was increased by about 50% due
to staining from the peat and the pH decreased by about one-half pH unit, also from the peat media. Ammonia
nitrogen was increased by several times, and nitrate nitrogen had low reductions (about 14%). The MCTT therefore
operated as intended: it had very effective reduction rates for both filtered and particulate stormwater toxicants and
SS. Increased filterable toxicant reductions were obtained in the peat/sand mixed media sorption-ion exchange
chamber, at the expense of increased color, lowered pH, and depressed COD and nitrate reduction rates. The
preliminary full-scale test results substantiate the excellent reductions found during the pilot-scale tests, while
showing better control of COD, filterable heavy metals, and nutrients, and less detrimental effects on pH and color.
IV

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                                              Contents
Notice	,	  ii
Foreword	iii
Abstract	iv
Contents	  v
Tables	viii
Figures	  x
Acknowledgments	,	xiii

Chapter 1 - Introduction and Conclusions	  1
  Conclusions	  1
  Organization of report	,	 3

Chapter 2 - Sources of Urban Stormwater Pollutants  	 4
  Sources and characteristics of urban runoff pollutants  	 5
  Chemical quality of rocks and soils	,	 6
  Street dust and dirt pollutant sources	 8
    Characteristics  	 8
    Street dirt accumulation	 9
    Washoff of street dirt	 12
  Observed particle size distributions in stormwater	 21
  Atmospheric sources  of urban runoff pollutants  	 21
  Source area sheetflow and particulate quality 	 26
    Source area particulate quality	 26
    Warm weather sheetflow quality	 2?
  Other pollutant contributions to the storm drainage system	 39
  Phase 1 project activities - Sources of stormwater toxicants	 39
    Phase 1 - analyses and sampling	 39
    Phase 1 - potential  sources	 42
    Phase 1 - results	 42

Chapter 3 - Laboratory-Scale Toxicant Reduction Tests	 49
  Phase 2 - analysis and sampling	 49
  Phase 2 - experimental error  	 49
  Phase 2 - treatability tests	 50
  Phase 2 - results	 50

Chapter 4 - The Development of the MCTT		 60
  Oil and water separators	 62
    Factors relevant to oil/water  separator performance 	 62
       Oil droplet size and critical rise rate	 62
       Design flow rate	 64
       Effective horizontal separation area	 64

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       Other considerations	 64
     Gravity separation 	 64
       Conventional American Petroleum Institute (API) oil/water separator	 65
       Separation vaults 	 67
     Coalescing plate interceptor oil/water separators	 68
     Impingement coalescers and filtration devices	 69
     Maintenance of oil/water separators	 70
     Performance of oil/water separators for treating stormwater	 71
   The multi-chambered treatment train (MCTT) 	  72
     Phase 3 - field demonstrations of the multi-chambered treatment train	  72
     Development of the MCTT  	  73
       Catchbasin/grit chamber	  74
       Main settling chamber	  74
         Upflow velocity	  74
         Toxicity reductions associated with particle settling	  77
       Filter/ion exchange chamber  	  79
         Sand	  79
         Peat moss 	  79
         Combined sand and peat moss filters	  80
         Preliminary filtration tests with stormwater	  80
     Site specific design requirements of the MCTT main settling chamber	  81
       Toxicity reduction through settling 	  81
       Storage/treatment trade-offs in MCTT design	  82
     Additional considerations in MCTT design and construction	 90

Chapter 5 - Pilot-Scale and Preliminary Full-Scale Test Results of the MCTT	  91
     Pilot-scale MCTT design	  91
       Leaching of materials used for the construction of treatability test equipment	  91
     Pilot-scale MCTT operation	  92
     Pilot-scale MCTT sampling and analytical techniques  	  96
     Results of the pilot-scale MCTT evaluation tests	  98
     Preliminary full-scale MCTT test results	  113

Chapter 6 - General Design Procedures  for the MCTT	  122
  Design procedure	  122
     Pollutant removal goal	  122
  Catchbasin inlet chamber design 	  124
  Main settling chamber design  	  127
     Drainage of main settling chamber  	  128
  Final filtrations-sorption-ion exchange chamber	  129
     Selection of filtration media for pollutant reduction capabilities	  129
     Design of filters for specified filtration durations  	  130
  Example design of full-scale MCTT  	  133
     Determine the pollutant removal goal	  133
     Main settling and filtration chamber designs	  133
       Rainfall for Detroit and expected performance of MCTT	  134
       Site surveys 	  134
       MCTT sizing options	   135
     Catchbasin/grit chamber design	   137
     Maintenance activities	   137
     Preliminary material specifications:	   138
                                                   VI

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References 	  159

Appendix A - Plotted MCTT Performance Data	  A-l

Appendix B - Tabular MCTT Performance Data	  B-l

Appendix C - Source Area Pollutant Observations  	  C-l
Appendix D - Receiving Water Impacts  	  D-1
  Toxicological effects of stormwater	  D-2
  Ecological effects of stormwater	  D-2
  Fates of stormwater pollutants in surface waters	  D-5
  Human health effects of stormwater 	  D-6
  Groundwater impacts from stormwater infiltration	  D-6
    Constituents of concern 	  D-7
       Nutrients	  D-7
       Pesticides  	  D-7
       Other organics 	  D-7
       Pathogenic microorganisms	  D-8
       Heavy metals and other inorganic compounds	  D-8
       Salts 	  D-9
    Recommendations to protect groundwater during stormwater infiltration  	  D-9

Appendix E - Laboratory Procedures Used For MCTT Pilot-Scale Evaluations	  E-l
                                                   VII

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                                                Tables
                                                                                                    Page

 2.1      Uses and sources for organic compounds found in stormwater	       6
 2,2      Common elements in the lithosphere  	,	       7
 2.3      Common elements in soils	       7
 2,4      Street dirt loadings and deposition rates	      11
 2.5      Suspended solids washoff coefficients	      21
 2,6      Summary of reported rain quality ,.,	,	,,.,,,      23
 2.7      Atmosphere dustfall quality	      24
 2.8      Bulk precipitation quality	,	;      25
 2.9      Urban bulk precipitation deposition rates	      25
 2,10     Summary of observed street dirt chemical quality	       28
 2.11     Summary of observed particulate quality for other source areas	,	      29
 2.12     Sheetflow quality summary for other source areas	      30
 2.13     Sheetflow quality summary for undeveloped landscaped and freeway pavement areas	      36
 2,14    Source area bacteria sheetflow quality summary	     37
 2.15    Source area filterable pollutant concentration summary	,	      38
 2,16    Numbers of samples collected from each source area type	,,.....,	      39
 2.17    List of toxic pollutants analyzed in samples	      40
 2.18    Fraction of samples rated as toxic	,	      41
 2.19    Stormwater toxicants  detected in at least 10% of the source area sheetflow samples	     44
 2,20    Relative toxicity of samples using Microtox™  	,	     45
 3.1      Phase 2 treatability sample descriptions	,	      50
 3,2      Two-sided probabilities comparing different treatment tests	,	,	      51
4,1      Example oil droplet size distribution  	,	,,....	      64
4.2      Short-circuiting factor	,.,.,	      67
4.3      Characteristics of coalescing plate interceptor separators	      69
4.4      Reported filtration media performance for stormwater control	      79
4.5      Median toxicity reduction for different holding times	      82
4.6      Excel* spreadsheet model used to develop MCTT design curves	      83
4.7      Risk assessment and design evaluation of an MCTT for Birmingham, AL, conditions	      84
5.1      Potential sample contamination from sampler material	      92
5.2      Potential sample contamination from materials that may be used in treatability test apparatus	      95
 5.3      Pilot-scale MCTT construction material leach test	      96
5.4      Compounds analyzed during MCTT tests	      97
 5.5      Analytes and volumes collected	      98
 5.6      MCTT catchbasin chamber performance summary	      99
 5.7      MCTT settling chamber performance summary	     101
 5.8      MCTT sand-peat chamber performance summary	     103
 5.9      Overall MCTT performance summary	     105
 5.10    Median percent reductions by chamber	     107
 5.11    Significant (1-sided p value <0.05) concentration changes for MCTT	     108
 5,12    Preliminary performance information for full-scale MCTT tests, compared to Birmingham pilot-
        scale MCTT results  	     114
                                                   Vlil

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6.1     Full MCTT pollutant removals compared to design toxicity reductions	     123
6.2     Approximate suspended solids accumulations in catcbbasin sump 	     127
6.3     MCTT main settling chamber required sizes	      127
6.4     Filtration capacity as a function of suspended solids loadings	     130
6.5     Filtration capacity as a function of pretreated water loading	     130
6.6     Filter media categories and filtration capacities	      131
6.7     Typical volumetric runoff coefficients for different land use areas	,	      131
6.8     Likely suspended solids concentrations for different source areas	     132
6.9     Example pollutant removals for example design alternatives	      133
                                                     IX

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                                                Figures

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2.1     Deposition and accumulation of street dirt 	        10
2.2     Particle size distribution of HDS test	        16
2.3     Particle size distribution for LCR test	        16
2.4     Washoff plots for HCR test	        17
2.5     Washoff plots for LCR test	        17
2.6     Washoff plots for HDR test	        18
2.7     Washoff plots for LDR test	        18
2.8     Washoff plots for HCS test	        19
2.9     Washoff plots for LCS test	        19
2.10    Washoff plots for HDS test	       20
2.11    Washoff plots for LCS test	       20
2.12    Tenth percentile particle sizes for stormwater inlet flows	       22
2.13    Fiftieth percentile particle sizes for stormwater inlet flows	       22
2.14    Ninetieth percentile particle sizes for stormwater inlet flows	       22
3.1      Toxicity reduction on control samples - industrial loading and parking areas	       52
3.2     Toxicity reduction on control samples - automobile service facilities	       52
3.3      Toxicity reduction on control samples - automobile salvage yards	       52
3.4     Toxicity reduction from settling treatment - industrial loading and parking areas	       53
3.5      Toxicity reduction from settling treatment - automobile service facilities	       53
3.6      Toxicity reduction from settling treatment - automobile salvage yards	       53
3.7      Toxicity reduction from aeration treatment - industrial loading and parking areas	       54
3.8      Toxicity reduction from aeration treatment - automobile service facilities	       54
3.9      Toxicity reduction from aeration treatment - automobile salvage yards	       54
3.10    Toxicity reduction from sieve treatment - industrial loading and parking areas	       55
3.11    Toxicity reduction from sieve treatment - automobile service facilities	       55
3.12    Toxicity reduction from sieve treatment - automobile salvage yards	       55
3.13    Toxicity reduction from photo-degradation treatment - industrial loading and parking areas	       56
3.14    Toxicity reduction from photo-degradation treatment - automobile service facilities	       56
3.15    Toxicity reduction from photo-degradation treatment - automobile salvage yards	       56
3.16    Toxicity reduction from aeration and photo-degradation treatment - industrial loading and parking
        areas	       57
3.17    Toxicity reduction from aeration and photo-degradation treatment - automobile service facilities ..       57
3.18    Toxicity reduction from aeration and photo-degradation treatment - automobile salvage yards	       57
3.19    Toxicity reduction from floatation treatment (top layer samples) - industrial loading and parking
        areas	       58
3.20    Toxicity reduction from floatation treatment (top layer samples) - automobile service facilities ....       58
3.21    Toxicity reduction from floatation treatment (top layer samples) - automobile salvage yards	       58
3.22    Toxicity reduction from floatation treatment (middle layer samples) - industrial loading and
        parking  areas	       59
3.23    Toxicity reduction from floatation treatment (middle layer samples) - automobile service facilities       59

3.24    Toxicity reduction from floatation treatment (middle layer samples) - automobile salvage yards ...       59

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4.1     MCTT cross section	       61
4.2     Performance of API oil/water separators	       63
4.3     API oil/water separator	       65
4.4     Downflow parallel plate separator	       69
4.5     Monthly changes in sediment in 17 oil/water separators	       71
4.6     Critical Velocity and Settling Tank Dimensions	       75
4.7     Effects of hydraulic loading on toxicity reduction	       78
4.8     Effects of storage volume and treatment time on annual toxicity reduction, 2.1m settling depth ...       90
5.1     Pilot-scale MCTT under construction	       93
5.2     Pilot-scale MCTT in place at the UAB parking facility	       93
5.3     Automatic samplers installed on the pilot-scale MCTT	       94
5.4     Pilot-scale MCTT during a storm event	       94
5.5     MCTT performance for suspended solids	      109
5.6     MCTT performance for relative toxicity, by Microtox™, - unfiltered sample	      110
5.7     MCTT performance for zinc - unfiltered sample	      Ill
5.8     MCTT performance for bis(2-ethylhexyl)phthalate - unfiltered sample	      112
5.9     Ruby Garage, Milwaukee, drainage area	      115
5.10    Ruby Garage, Milwaukee, MCTT installation	      115
5.11    Ruby Garage, Milwaukee, MCTT installation	      116
5.12    Ruby Garage, Milwaukee, MCTT installation	      116
5.13    Ruby Garage, Milwaukee, MCTT catchbasin inlet and piping	      117
5.14    Ruby Garage, Milwaukee, MCTT main settling chamber inclined tube settlers and sorbent pillows      117
5.15    Minocqua, WI, MCTT, drainage  area	      118
5.16    Minocqua, WI, MCTT, installation of box culverts	      118
5.17    Minocqua, WI, MCTT, installation of box culverts	      119
5.18    Minocqua, WI, MCTT, placement of tube settlers	       119
5.19    Minocqua, WI, MCTT, filter fabric being prepared for  installation	      120
5.20    Minocqua, WI, MCTT, grit chamber	      120
5.21    Minocqua, WI, MCTT, interior of final filtration chamber	      121
5.22    Minocqua, WI, MCTT, site after  installation	      121
6.1     Conventional catchbasin with inverted sump	       125
6.2     Suspended solids capture vs. flowrate	       126
6.3     Amount of rainfall treated before  sumps are 60% full	      126
6.4     MCTT design curves for Atlanta,  GA	      139
6.5     MCTT design curves for Austin, TX	      140
6.6     MCTT design curves for Birmingham, AL	      141
6.7     MCTT design curves for Bozeman, MT	      142
6.8     MCTT design curves for Buffalo, NY	      143
6.9     MCTT design curves for Dallas, TX	      144
6.10    MCTT design curves for Detroit,  MI	      145
6.11    MCTT design curves for Little Rock, AR	      146
6.12    MCTT design curves for Los Angeles, CA	      147
6.13    MCTT design curves for Madison, WI	      148
6.14    MCTT design curves for Miami, FL	      149
6.15    MCTT design curves for Milwaukee, WI	      150
                                                   XI

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6.16    MCTT design curves for Minneapolis, MN	     151
6.17    MCTT design curves for Newark, NJ	     152
6.18    MCTT design curves for New Orleans, LA	     153
6.19    MCTT design curves for Phoenix, AZ	     154
6.20    MCTT design curves for Portland, ME	;	     155
6.21    MCTT design curves for Rapid City, SD	     156
6.22    MCTT design curves for Reno, NV	      157
6.23    MCTT design curves for Seattle, WA	-..      158
6.24    MCTT design curves for St. Louis, MO	      159
                                                 xn

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Acknowledgments

This research was mostly funded by the Wet-Weather Flow Management and Pollution Control 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. Michael Brown of this program also
provided valuable project assistance. Additional funding was also provided by the U.S. Army-Construction
Engineering Research Laboratory in Champaign, Illinois. Rick Scholtz's efforts are greatly appreciated.

Special thanks are also extended to the cities of Minocqua and Milwaukee, the state of Wisconsin, and Region V of
the EPA for funding, constructing, and monitoring of the full-scale MCTT installations. Roger Bannerman and Tom
Blake of the Wisconsin Department of Natural Resources, along with Steve Corsi of the USGS in Madison, were
especially instrumental in carrying out these full-scale tests. COM, Detroit, and the City of Milwaukee also
supported the design of the full-scale MCTT test units presented in this report.

Many UAB graduate students and staff freely gave of their time to support this project, especially Olga Mirov,
Michael Richards, Lyn Lewis, Jay Day, Janice Lanthrop, Joe Farmer, Tim Awtrey, Niki Beckom, Melissa Lilburn,
and Holly Ray. 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:

• 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 Poly nuclear 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 author would also like to thank the following for donation of materials to the project: Jaeger Products, Inc. of
Houston, Texas for donating column packing spheres, Polar Supply Company, Inc. of Anchorage, Alaska for
donating filter fabric material, and Sherman Industries of Birmingham, Alabama for donating filtering media.

Some of the data presented in this report was obtained during an earlier EPA sponsored project that was conducted
under a subcontract to Foster Wheeler-Environsponse, Inc. of Edison, New Jersey. Grateful assistance was given by
the New York City Department of Environmental Protection, under the direction of Angelika Forndran, and their
contractors who provided the combined sewer overflow samples. Nelle Alexander of R.W. Beck of Seattle,
Washington and Roger Bannerman of the Wisconsin Department of Natural Resources also provided valuable help
by delivering additional samples from their areas for special analyses.

Special laboratory toxicity analyses were appreciatively provided by Allen Burton of Wright State University;
Teresa Norberg-King of the EPA's Environmental Research Laboratory in Duluth, Minnesota; and Gary Schimmel
of the EPA's Marine Effects Division of the Environmental Research Laboratory in Narragansett, Rhode Island.
Finally, grateful assistance was provided by the staffs of the of the Birmingham Water Works Board's water quality
laboratory and Jefferson County's Barton Laboratory.
Xlll

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Chapter 1
Introduction and Conclusions
Past studies have identified urban runoff as a major contributor to the degradation of many urban streams and rivers
(Field and Turkeltaub 1981; Pitt and Bozeman 1982; Pitt and Bissonnette 1984, and Pitt 1994, which includes an
extensive literature review). Previous studies also found organic and metallic toxicants in urban storm induced
discharges (EPA 1983a; Hoffman, et al. 1984; Fram, et al. 1987) which can contribute to receiving water
degradation. Appendix D contains a summary of basic receiving water problems associated with urban stormwater,
stressing recent research that supplements the above referenced studies and reviews.

The Nationwide Urban Runoff Program (NURP) monitored stormwater toxicant discharges from 28 cities and
concluded that urban areas were responsible for substantial discharges of toxicants (EPA 1983a). The NURP data
were collected mostly from residential areas and did not consider snowmelt. Furthermore, only a few commercial
and light industrial areas were represented. NURP did not identify any significant regional differences in toxicants
found, or in their concentrations. However, other information indicates that industrial stormwater, snowmelt runoff,
and dry weather discharges (including illegal discharges into storm drainage) can all contribute significant amounts
of toxicants to receiving waters (Pitt and McLean 1986).

The objective of this research was to further characterize stormwater toxicants, confirm the source areas of concern,
and investigate the effectiveness of treatment processes to control the toxicants. A parallel EPA sponsored research
project resulted in a user's guide for the investigation of inappropriate discharges into storm drainage systems (Pitt,
et al. 1993) and a comprehensive review of groundwater impacts from stormwater infiltration (Pitt, et al. 1994 and
1996). Clearly, an effective urban runoff control program must consider all seasonal flow phases and sources of
critical pollutants. If warm weather stormwater runoff was the only source considered, storm drainage control
programs in many areas would be disappointingly deficient. A complete control program must consider dry weather
flows, plus snow melt in northern areas, in addition to stormwater runoff. The results of the research reported here is
only one component of this complete control program approach.

Conclusions
Previous studies have indicated that urban stormwater runoff contains a variety of conventional and potentially toxic
pollutants that can degrade receiving waters and impair beneficial uses. Receiving water impacts are due to many
variables, including: the magnitude of the dry and wet weather discharges; the transport and fate mechanisms of the
toxicants; and effects from other discharges and receiving water conditions. These factors, and the unknown and site
specific relationships between them, make the prediction of receiving water effects difficult, if not impossible,
especially if one only relies on water column quality measurements. In situ biological community structure studies
can give an indication of the receiving water effects, especially if pre-development or control conditions are known
for comparison purposes. However it will generally be difficult to relate any identified impacts to any specific
pollutant, but an in-stream biological community structure and habitat study will indicate whether the receiving
water is being adversely effected.

Phase 1 of this research detected only a small fraction of the organic toxicants analyzed (as is typical for stormwater
evaluations), but detected heavy metals in the majority of the samples analyzed. The study also confirmed that many
toxicants are associated with particulate matter in the runoff. Industrial/commercial areas are likely to be the most
significant pollutant source areas, with the highest toxicant concentrations and most frequent occurrences found at
vehicle service and parking/storage areas. The duration of the antecedent dry period before a storm and the intensity
of the storm event were found to be significant factors influencing the concentrations of most of the toxicants
detected. These critical areas were sampled for the phase 2 treatability tests.

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The treatability study (phase 2) found that settling, screening, and aeration and/or photo-degradation treatments
showed the greatest potential for toxicant reductions, as measured by the reduction in toxicity of the samples, using
the Microtox™ toxicity screening test. Studies to measure the actual toxicant reductions in full-scale applications are
needed to confirm the real benefit of the potential treatment processes. The results from the second study phase, in
conjunction with results from the first project phase, will enable the modification of treatment devices and system
designs (for new installations and for retrofitting existing installations) to optimize toxicant reductions from critical
stormwater runoff source areas. The third project phase examined the toxicant reduction benefits of large-scale
applications of the most suitable treatment unit processes investigated.

The third phase of this research examined the use of a multi-chambered treatment tank (MCTT) to collect and treat
runoff from critical stormwater source areas, including gas stations, oil change facilities, transmission repair shops,
and other auto repair facilities. The collected runoff is first treated in a catchbasin chamber where larger particles are
removed by settling. The water then flows into a main settling chamber containing oil sorbent material where it
undergoes a much longer treatment period (24 to 72 h) to remove finer particles and associated pollutants. The final
chamber contains a mixed media filter material comprising equal amounts of sand and peat. This final chamber acts
as a polishing "filter" to remove some of the filterable toxicants from the runoffby other processes, such as ion
exchange and sorption.

The pilot- and full-scale test results show that the MCTT is providing substantial reductions in stormwater toxicants
(both in particulate and filtered phases) and suspended solids. Increases in color and a slight decrease in pH also
occurred during the final treatment step when using peat as part of the filtering/ion-exchange media.

The main settling chamber provided substantial reductions in total and dissolved toxicity, lead, zinc, certain organic
toxicants, SS, COD, turbidity, and color. The sand-peat chamber also provided additional filterable toxicant
reductions. However, the catchbasin/grit chamber did not provide any significant improvements in water quality,
although it is an important element in reducing maintenance problems by trapping bulk material.

Zinc and toxicity are examples where the use of the final chamber was needed to provide high levels of control.
Otherwise, it may be tempting to simplify the MCTT by removing the last chamber. Another option would be to
remove the main settling chamber and only use the pre-treating capabilities of the catchbasin as a grit chamber
before the peat "filtration" chamber (similar to many stormwater filter designs). This option is not recommended
because of the short life that the filter would have before it would clog (Clark and Pitt 1997). In addition, the bench-
scale tests showed that a treatment train was needed to provide some redundancy because of frequent variability in
sample treatability storm to storm, even for a single sampling site.

It is important not to confuse the MCTT with an oil/water separator or a grit chamber. Oil/water separators are
mainly industrial wastewater treatment devices that work well for removing high concentrations of relatively large
droplets of oil from wastewater. Stormwaters rarely have such levels of hydrocarbon contamination. If an area did
produce stormwater having these hydrocarbon contamination conditions, then oil/water separators should be used,
but further treatment may also be needed to remove other pollutants. Unfortunately, the available literature does not
contain many examples of successful applications of oil/water separators for stormwater control. Common problems
include lack of maintenance and under-sized separators for the flows encountered. Scouring of previously captured
material is also common.

Several proprietary stormwater treatment devices have recently been marketed throughout North America. These
devices can also be located underground. Unfortunately, comprehensive testing with actual stormwater is not
available for most of these devices. The designs and demonstrations are mostly based on reduction of relatively
large particles that rarely occur in stormwater. As indicated in this report, the suspended solids in stormwater is
mostly in the range of 1 to 100 um, with only a small fraction of the mass (usually <10%) associated with particles
greater than 100 um. These devices are designed to capture particle sizes that have typically been found on streets,
not in the runoff water (Pitt 1987). These devices are excellent grit chambers (and can probably capture floating oils)
and can be used to prevent sand-sized particles from accumulating in sewerage. Very little scour of the captured grit
material is also likely with these devices. However, they are not likely to provide important reductions of most
stormwater pollutants, especially the toxicants. The MCTT was designed to remove pollutants of a specific class of

-------
concern in stormwater: participates as small as a few jam and associated participate bound toxicants, plus filterable
toxicants. If a site is grossly contaminated with oils or grit, then a proprietary oil/water separator or grit chamber is
needed, but further treatment will also likely be necessary.

The MCTT is capable of reducing a broad range of stormwater pollutants that cause substantial receiving-water
problems (Pitt 1995). The MCTT has a high potential for cost-effective use as an integrated component in watershed
management programs designed to protect and enhance receiving waters.

Organization of Report

This report includes discussions pertaining to the major issues that must be addressed when developing a stormwater
management plan. These issues include a knowledge of the receiving water problems caused by stormwater
(Appendix D), a knowledge of the problem pollutants and where they originate in the watershed (Chapter 2), and a
knowledge of the control of these critical pollutants (Chapters 3, 4, 5 and 6). This EPA sponsored cooperative
agreement with UAB included three research phases reported in this report covering these basic elements. The first
phase included investigating sources of critical stormwater pollutants, the second phase included conducting bench-
scale treatability tests to identify the effectiveness of many unit processes, while the third project phase included
testing of a pilot-scale treatment device containing many of the most promising unit processes. These project phases
are all presented in this report, along with preliminary information from full-scale testing conducted by the state of
Wisconsin. The project research information is also substantially supported by information from the literature,
especially on effects of stormwater (Appendix D) and sources of pollutants (Chapter 2).

Chapter 1 contains a brief discussion of the conclusions from the research, while Chapter 2 includes much literature
information, plus the results of source area characterization studies conducted during this research project. Chapter 3
presents the results of the bench-scale treatability tests. Chapter 4 begins with a discussion of oil/water separators for
stormwater control, and then discusses the development of the MCTT. Chapter 5 presents the results of the pilot-
scale tests of the MCTT conducted in Birmingham and the preliminary test results from the full-scale tests being
conducted in Wisconsin. Chapter 6 includes the general design procedure for the MCTT, including an example
design for a Detroit site. Appendices A, B, and C include detailed observations obtained during this research.
Appendix D reviews receiving effects from stormwater, while Appendix E is an excerpt from the project Quality
Assurance Project Plan (QAPP) describing the laboratory analytical methods used during this project.

This is one of three project reports prepared for this cooperative agreement. The other two volumes describe tests of
stormwater inlets and stormwater filtering media for their ability to reduce concentrations of stormwater pollutants.
Previous reporting efforts of this cooperative agreement included an earlier report (and a book published by Ann
Arbor Press) on groundwater effects of stormwater infiltration, a soon-to-be published book (CRC/Lewis) on
conducting receiving water studies, and numerous technical conference presentations and published articles, many
through the Engineering Foundation/ASCE series of stormwater conferences.

-------
Chapter 2
Sources of Urban Stormwater Pollutants
Urban runoff is comprised of many separate source area flow components that are combined within the drainage
area and at the outfall before entering the receiving water. It may be adequate to consider the combined outfall
conditions alone when evaluating the long term, areawide effects of many separate outfall discharges to a receiving
water. However, if better predictions of outfall characteristics (or the effects of source area controls) are needed,
then the separate source area components must be characterized. The discharge at the outfall is made up of a mixture
of contributions from different source areas. The "mix" depends on the characteristics of the drainage area and the
specific rain event. The effectiveness of source area controls is therefore highly site and storm specific.

Various urban source areas all contribute different quantities of runoff and pollutants, depending on their specific
characteristics. Impervious source areas may contribute most of the runoff during small rain events. Examples of
these source areas include paved parking lots, streets, driveways, roofs, and sidewalks. Pervious source areas
become important contributors for larger rain events. These pervious source areas include gardens, lawns, bare
ground, unpaved parking areas and driveways, and undeveloped areas. The relative importance of the individual
sources is a function of their areas, their pollutant washoff potentials, and the rain characteristics.

The washoff of debris and soil during a rain is dependent on the energy of the rain and the properties of the material.
Pollutants are also removed from source areas by winds, litter pickup, or other cleanup activities. The runoff and
pollutants from the source areas flow directly into the drainage system, onto impervious areas that are directly
connected to the drainage system, or onto pervious areas that will attenuate some of the flows and pollutants, before
they discharge to the drainage system .

Sources of pollutants on paved areas include on-site particulate storage that cannot be removed by usual processes
e.g., rain, wind, street cleaning, etc. Atmospheric deposition, deposition from activities on these paved surfaces (auto
traffic, material storage, etc.) and the erosion of material from upland areas that directly discharge flows onto these
areas, are the major sources of pollutants to the paved areas. Pervious areas contribute pollutants mainly through
erosion processes where the rain energy dislodges soil from between plants. The runoff from these source areas
enter the storm drainage system where sedimentation in catchbasins or in the sewerage may affect their ultimate
discharge to the outfall. In-stream physical, biological, and chemical processes affect the pollutants after they are
discharged to the ultimate receiving water.

It is important to know when the different source areas become "active" (when runoff initiates from the area,
carrying pollutants to the drainage system). If pervious source areas are not contributing runoff or pollutants, then
the prediction of urban runoff quality is much simplified. The mechanisms of washoff, and delivery yields of runoff
and pollutants from paved areas, is much better known than from pervious urban areas (Novotny and Chesters
1981). In many cases, pervious areas are not active except during rain events greater than at least five or ten mm.
For smaller rain depths, almost all of the runoff and pollutants originate from impervious surfaces (Pitt 1987).
However, in many urban areas, pervious areas may contribute the majority of the runoff, and some pollutants, when
rain depths are greater than about 20 mm. The actual importance of the different source areas is highly dependent on
the specific land use and rainfall patterns. Obviously, in areas having relatively low density development, especially
where moderate and large sized rains occur frequently (such as in the Southeast), pervious areas typically dominate
outfall discharges. In contrast, in areas having significant paved areas, especially where most rains are relatively
small (such as in the arid west), the impervious areas would dominate outfall discharges. The effectiveness of
different source controls would therefore be quite different for different land uses and climatic patterns.

-------
If the number of events exceeding a water quality objective are important, then the small rain events are of most
concern. Stormwater runoff typically exceeds some water quality standards for practically every rain event
(especially for bacteria and some heavy metals). In the upper Midwest, the median rain depth is about 6 mm, while
in the Southeast, the median rain depth is about twice this depth. For these small rain depths and for most urban land
uses, directly connected paved areas usually contribute most of the runoff and pollutants. However, if annual mass
discharges are more important, e.g. for long-term effects, then the moderate rains are more important. Rains from
about 10 to 50 mm produce most of the annual runoff volume in many areas of the U.S. Runoff from both
impervious and pervious areas can be very important for these rains. The largest rains (greater than 100 mm) are
relatively rare and do not contribute significant amounts of runoff pollutants during normal years, but are very
important for drainage design. The specific source areas that are most important (and controllable) for these different
conditions vary widely.

The remaining portions of this chapter describe sources of urban runoff flows and pollutants as reported from many
past studies as found in the literature. This chapter also reports on the specific source area sampling activities
conducted as part of this EPA funded research.

Sources and Characteristics of Urban Runoff Pollutants
It has been known for many years that the vast majority of stormwater toxicants and much of the conventional
pollutants are associated with automobile use and maintenance activities and that these pollutants are strongly
associated with the particulates suspended in the stormwater (the non-filterable components, or suspended solids). It
has been difficult to reduce or modify automobile use to reduce the use of these compounds, with the notable
exception of the phasing out of leaded gasoline. Current activities, concentrated in the San Francisco area, are trying
to encourage brake pad manufactures to reduce the use of copper. The effectiveness of most stormwater control
practices is therefore dependent on their ability to remove these particles from the water, or possibly from
intermediate accumulating locations (such as streets or other surfaces) and not through source reduction. The
removal of these particles from stormwater is dependent on various characteristics of these particles, especially their
size and settling rates. Some source area controls (most notably street cleaning) affect the particles before they are
washed-off and transported by the runoff, while others remove the particles from the flowing water. This discussion
therefore summarizes the accumulation and washoff of these particulates and the particle size distribution of the
suspended solids in stormwater runoff to better understand the effectiveness of source area control practices.

Table 2.1 shows that most of the organic compounds found in stormwater are associated with various human-related
activities, especially automobile and pesticide use, or are associated with plastics (Verschueren 1983). Heavy metals
found in stormwater also mostly originate from automobile use activities, including gasoline combustion, brake
lining, fluids (brake fluid, transmission oil, anti-freeze, grease, etc.), undercoatings, and tire wear (Durum 1974,
Koeppe 1977, Rubin 1976, Shaheen 1975, Solomon andNatusch 1977, and Wilbur and Hunter 1980). Auto repair,
pavement wear, and deicing compound use also contribute heavy metals to stormwater (Field, et al. 1973, and
Shaheen 1975). Shaheen (1975) found that eroding area soils are the major source of the particulates in stormwater.
The eroding area soil particles, and the particles associated with road surface wear, become contaminated with
exhaust emissions and runoff containing the polluting compounds. Most of these compounds become tightly bound
to these particles and are then transported through the urban area and drainage system (or removed) with the
particulates. Stormwater concentrations of zinc, fluoranthene, 1,3-dichlorobenzene, and pyrene are unique in that
substantial fractions of these compounds remain in the water and are less associated with the particulates.

All areas are affected by atmospheric deposition, while other sources of pollutants are specific to the activities
conducted on the areas. As examples, the ground surfaces of unpaved equipment or material storage areas can
become contaminated by spills and debris, while undeveloped land remaining relatively unspoiled by activities can
still contribute runoff solids, organics, and nutrients, if eroded. Atmospheric deposition, deposition from activities
on paved surfaces, and the erosion of material from upland unconnected areas are the major sources of pollutants in
urban areas.

-------
Table 2.1. Uses and Sources for Organic Compounds found in Stormwater (Source: Verschueren 1983)

COMPOUND EXAMPLE USE/SOURCE
Phenol gasoline, exhaust
N-Nitroso-cfi-n-propylamine contaminant of herbicide Treflan
Hexachloroethane plasticizer in cellulose esters, minor use in rubber and insecticide
Nitrobenzene solvent, rubber, lubricants
2,4-Dimethylphenol asphalt, fuel, plastics, pesticides
Hexachlorobutadiene rubber and polymer solvent, transformer and hydraulic oil
4-Chloro-3-methylphenol germicide; preservative for glues, gums, inks, textile, and leather
Pentachlorophenol insecticide, algaecide, herbicide, & fungicide mfg., wood preservative
Fluoranthene gasoline, motor and lubricating oil, wood preservative
Pyrene gasoline, asphalt, wood preservative, motor oil
Di-n-octylphthalate general use of plastics

There have been many studies in the past that have examined different sources of urban runoff pollutants. These
references have been reviewed as part of this study and the results are summarized in this section. These significant
pollutants have been shown to have a potential for creating various receiving water impact problems, as described in
Appendix D of this report. Most of these potential problem pollutants typically have significant concentration
increases in the urban feeder creeks and sediments, as compared to areas not affected by urban runoff.

The important sources of these pollutants are related to various uses and processes. Automobile related potential
sources usually affect road dust and dirt quality more importantly than other paniculate components of the runoff
system. The road dust and dirt quality is affected by vehicle fluid drips and spills (gasoline, oils, etc.) and vehicle
exhaust, along with various vehicle wear, local soil erosion, and pavement wear products. Urban landscaping
practices potentially affecting urban runoff include vegetation litter, fertilizer and pesticide. Miscellaneous sources
of urban runoff pollutants include firework debris, wildlife and domestic pet wastes and possibly industrial and
sanitary wastewaters. Wet and dry atmospheric contributions both affect runoff quality. Pesticide use in an urban
area can contribute significant quantities of various toxic materials to urban runoff. Many manufacturing and
industrial activities, including the combustion of fuels, also affects urban runoff quality.

Natural weathering and erosion products of rocks contribute the majority of the hardness and iron in urban runoff
pollutants. Road dust and associated automobile use activities (gasoline exhaust products) historically contributed
most of the lead in urban runoff. However, the decrease of lead in gasoline has resulted in current stormwater lead
concentrations being about 1/10 of the levels found in stormwater in the early 1970s (Bannerman, et al. 1993). In
certain situations, paint chipping can also be a major source of lead in urban areas. Road dust contaminated by tire
wear products, and zinc plated metal erosion material, contribute most of the zinc to urban runoff. Urban
landscaping activities can be a major source of cadmium (Phillips and Russo 1978). Electroplating and ore
processing activities can also contribute chromium and cadmium.

Many pollutant sources are specific to a particular area and on-going activities. For example, iron oxides are
associated with welding operations and strontium, used in the production of flares and fireworks, would probably be
found on the streets in greater quantities around holidays, or at the scenes of traffic accidents, The relative
contribution of each of these potential urban runoff sources, is, therefore, highly variable, depending upon specific
site conditions and seasons.

Specific information is presented in the following subsections concerning the qualities of various rocks and soils,
urban and rural dustfall, and precipitation. This information is presented to assist in the interpretation of the source
area runoff samples collected as part of this project.

Chemical Quality of Rocks and Soils
The abundance of common elements in the lithosphere (the earth's crust) is shown in Table 2.2 (Lindsay 1979).
Almost half of the lithosphere is oxygen and about 25 percent is silica. Approximately 8 percent is aluminum and 5
percent is iron. Elements comprising between 2 percent and 4 percent of the lithosphere include calcium, sodium,
potassium and magnesium. Because of the great abundance of these materials in the lithosphere, urban runoff
transports only a relatively small portion of these elements to receiving waters, compared to natural processes. Iron

-------
 and aluminum can both cause detrimental effects in receiving waters, if in their dissolved forms. A reduction of the
 pH substantially increases the abundance of dissolved metals. Table 2.3, also from Lindsay (1979), shows the
 rankings for common elements in soils. These rankings are quite similar to the values shown previously for the
 lithosphere. Natural soils can contribute pollutants to urban runoff through local erosion. Again, iron and aluminum
 are very high on this list and receiving water concentrations of these metals are not expected to be significantly
 affected by urban activities alone.

 Table 2.2 Common Elements in the Lithosphere
 (Source: Lindsay 1979)
Abundance Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Element
O
Si
Al
Fe
Ca
Na
K
Mg
P
C
Mn
F
S
Cl
Ba
Rb
Zr
Cr
Sr
V
Ni
Concentration
in Lithosphere
(mg/kg)
465,000
276,000
81,000
51,000
36,000
28,000
26,000
21,000
1,200
950
900
625
600
500
430
280
220
200
150
150
100
Table 2.3 Common Elements in Soils (Source: Lindsay 1979)
Abundance
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Element
O
Si
Al
Fe
C
Ca
K
Na
Mg
Ti
N
S
Mn
P
Ba
Zr
F
Sr
Cl
Cr
V
Typical
Minimum
(mg/kg)

230,000
10,000
7,000

7,000
400
750
600
1,000
200
30
20
200
100
60
10
50
20
1
20
Typical
Maximum
(mg/kg)

350,000
300,000
550,000

500,000
30,000
7,500
6,000
10,000
4,000
10,000
3,000
5,000
3,000
2,000
4,000
1,000
900
1,000
500
Typical
Average
(mg/kg)
490,000
320,000
71 ,000
38,000
20,000
13,700
8,300
6,300
5,000
4,000
1,400
700
600
600
430
300
200
200
100
100
100

-------
The values shown on these tables are expected to vary substantially, depending upon the specific mineral types.
Arsenic is mainly concentrated in iron and manganese oxides, shales, clays, sedimentary rocks and phosphorites.
Mercury is concentrated mostly in sulfide ores, shales and clays. Lead is fairly uniformly distributed, but can be
concentrated in clayey sediments and sulfide deposits. Cadmium can also be concentrated in shales, clays and
phosphorites (Durum 1974).
Street Dust and Dirt Pollutant Sources

Characteristics
Most of the street surface dust and dirt material (by weight) are local soil erosion products, while some materials are
contributed by motor vehicle emissions and wear (Shaheen 1975). Minor contributions are made by erosion of street
surfaces in good condition. The specific makeup of street surface contaminants is a function of many conditions and
varies widely (Pitt 1979).

Automobile tire wear is a major source of zinc in urban runoff and is mostly deposited on street surfaces and nearby
adjacent areas. About half of the airborne particulates lost due to tire wear settle out on the street and the majority of
the remaining particulates settle within about 6 meters of the roadway. Exhaust particulates, fluid losses, drips, spills
and mechanical wear products can all contribute lead to street dirt. Many heavy metals are important pollutants
associated with automobile activity. Most of these automobile pollutants affect parking lots and street surfaces.
However, some of the automobile related materials also affect areas adjacent to the streets after being transported by
wind after being resuspended from the road surface by traffic-induced turbulence.

Automobile exhaust particulates contribute many important heavy metals to street surface particulates and to urban
runoff and receiving waters. The most notable of these heavy metals has been lead. However, since the late 1980s,
the concentrations of lead in stormwater has decreased substantially (by about ten times) compared to early 1970
observations. This decrease, of course, is associated with significantly decreased consumption of leaded gasoline.
Solomon and Natusch (1977) studied automobile exhaust particulates in conjunction with a comprehensive study of
lead in the Champaign-Urbana, Illinois area. They found that the exhaust particulates existed in two distinct
morphological forms. The smallest particulates were almost perfectly spherical, having diameters in the range of 0.1
to 0.5 um. These small particles consisted almost entirely of PbBrCl at the time of emission. Because they are small,
they are expected to remain airborne for considerable distances and can be captured in the lungs when inhaled. They
concluded that the small particles are formed by condensation of PbBrCl vapor onto small nucleating centers, which
are probably introduced into the engine with the filtered engine air.

Solomon and Natusch (1977) also found that the second major form of automobile exhaust particulates were rather
large, being roughly 10 to 20 um in diameter. These had typically irregular shapes, with somewhat smooth surfaces.
They found that the elemental compositions of these irregular particles were quite variable, being predominantly
iron, calcium, lead, chlorine and bromine. They found that individual particles did contain aluminum, zinc, sulfur,
phosphorus and some carbon, chromium, potassium, sodium, nickel and thallium. Many of these elements (bromine,
carbon, chlorine, chromium, potassium, sodium, nickel, phosphorus, lead, sulfur, and thallium) are most likely
condensed, or adsorbed, onto the surfaces of these larger particles during passage through the exhaust system. They
believed that these large particles originate in the engine or exhaust system because of their very high iron content.
They found that 50 to 70 percent of the emitted lead was associated with these large particles, which would be
deposited within a few meters of the emission point onto the roadway, because of their aerodynamic properties.

Solomon and Natusch (1977) also examined urban particulates near roadways and homes in urban areas. They found
that lead concentrations in soils were higher near roads and houses. This indicated the capability of road dust and
peeling house paint to contaminate nearby soils. The lead content of the soils ranged from 130 to about 1,200 mg/kg.
Koeppe (1977), during another element of the Champaign-Urbana lead study, found that lead was tightly bound to
various soil components. However, the lead did not remain in one location, but it was transported both downward in
the soil profile and to adjacent areas through both natural and man-assisted processes.

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Street Dirt Accumulation
The washoff of street dirt and the effectiveness of street cleaning as a stormwater control practice are highly
dependent on the available street dirt loading. Street dirt loadings are the result of deposition and removal rates, plus
"permanent storage." The permanent storage component is a function of street texture and condition and is the
quantity of street dust and dirt that cannot be removed naturally or by street cleaning equipment. It is literally
trapped in the texture, or cracks, of the street. The street dirt loading at any time is this initial permanent loading plus
the accumulation amount corresponding to the exposure period, minus the re-suspended material removal by wind
and traffic-induced turbulence. Removal of street dirt can occur naturally by winds and rain, or by human activity
(by the turbulence of traffic or by street cleaning equipment). Very little removal occurs by any process when the
street dirt loadings are small, but wind removal may be very large with larger loadings, especially for smooth streets
(Pitt 1979).

Figure 2.1 shows very different street dirt loadings for two San Jose, CA, residential study areas (Pitt 1979). The
accumulation and deposition rates (and therefore the amounts lost to air) are quite similar, but the initial loading
values (the permanent storage values) are very different. The loading differences we7re almost solely caused by the
different street textures. Table 2.4 summarizes many accumulation rate measurements obtained from throughout
North America. In the earliest studies (APWA 1969; Sartor and Boyd 1972; and Shaheen 1975) it was assumed that
the initial street dirt loading values after a major rain or street cleaning were zero. Calculated accumulation rates for
rough streets were therefore very large. Later tests measured the initial loading values close to the end of major rains
and street cleaning and found that they could be very high, depending on the street texture. When these starting
loadings were considered, the calculated accumulation rates were therefore much lower. The early, uncorrected,
Sartor and Boyd accumulation rates that ignored the initial loading values were almost ten times the correct values
shown on this table. Unfortunately, most urban stormwater models used these very high early accumulation rates as
default values.

The most important factors affecting the initial loading and maximum loading values shown on Table 2.4 were
found to be street texture and street condition. When data from many locations are studied, it is apparent that smooth
streets have substantially less loadings at any accumulation period compared to rough streets for the same land use.
Very long accumulation periods relative to the rain frequency resultant in high street dirt loadings. During these
conditions, the wind losses of street dirt (as fugitive dust) may approximate the deposition rate, resulting in
relatively constant street dirt loadings. At Bellevue, WA, typical interevent rain periods average about 3 days.
Relatively constant street dirt loadings were observed in Bellevue because the frequent rains kept the loadings low
and very close to the initial storage value, with little observed increase in dirt accumulation overtime (Pitt 1985). In
Castro Valley, CA, the rain interevent periods were much longer (ranging from about 20 to 100 days) and steady
loadings were only observed after about 30 days when the loadings became very high and fugitive dust losses
caused by the winds and traffic turbulence moderated the loadings (Pitt and Shawley 1982).

An example of the type of research conducted to obtain the values shown in Table 2.4 was conducted by Pitt and
McLean (1986) in Toronto. They measured street dirt accumulation rates and the effects of street cleaning as part of
a comprehensive stormwater research project. An industrial street with heavy traffic and a residential street with
light traffic were monitored about twice a week for three months. At the beginning of this period, intensive street
cleaning (one pass per day for each of three consecutive days) was conducted to obtain reasonably clean streets.
Street dirt loadings were then monitored every few days to measure the accumulation rates of street dirt. Street dirt
sampling procedures developed by Pitt (1979) were used: powerful industrial vacuums (two units, each having 2
HP, combined with a "Y" connector, and using a 6 in. wide solid aluminum head) were used to clean many separate
subsample strips across the roads which were then combined for physical and chemical analyses.

In Toronto, the street dirt particulate loadings were quite high before the initial intensive street cleaning period and
were reduced to their lowest observed levels immediately after the last street cleaning. After street cleaning, the
loadings on the industrial street increased much faster than for the residential street. Right after intensive cleaning,
the street dirt particle sizes were also similar for the two land uses. However, the loadings of larger particles on the
industrial street increased at a much faster rate than on the residential street, indicating more erosion or tracking
materials being deposited onto the industrial street. The residential street dirt measurements did not indicate that any
material was lost to the atmosphere as fugitive dust, likely due to the low street dirt accumulation rate and the short

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 2600
                                                  30
               DAYS SINCE LAST CLEANED
Figure 2.1 Deposition and accumulation of street dirt (Pitt 1979).
                          10

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Table 2.4  Street Dirt Loadings and Deposition Rates
                                                    Mreet Dirt Loadings (grams/curb-meter) and Deposition Rates (grams/curb-meter-day)

Smooth and Intermediate Textured Streets
Reno/Sparks, NV - good condition
Reno/Sparks, NV - good with smooth gutters (windy)
San Jose, CA - good condition
U S nationwide - residential streets, good condition
U S nationwide - commercial streets, good condition
Reno/Sparks, NV - moderate to poor condition
Reno/Sparks NV - new residential area (construction)
Reno/Sparks, NV - poor condition, with lipped gutters
San Jose CA - fair to poor condition
Castro Valley, CA - moderate condition
Ottawa Ontario - moderate condition
Toronto Ontario - moderate condition, residential
Toronto Ontario - moderate condition, industrial
Bcllevue WA - dry period, moderate condition
Bellevue, WA - heavy traffic
Bellevue WA - other residential sites

average:
range:


Rough and Very Rough Textured Streets
San Jose, CA - oil and screens overlay
Ottawa, Ontario - very rough
Reno/Sparks, NV
Reno/Sparks, NV - windy
San Jose, CA - poor condition
Ottawa, Ontario - rough
U S nationwide - industrial streets (poor condition)

average:
range:
Initial Loading
Value

80
• 250
35
110
85
200
710
370
80
85
40
40
60
140
60
70

150
35-710



510
TuT
630"
540
220~
200
190

370
190-630
Daily
Deposition
Rate

1
7
4
6
4
2
17
15
4
10
20
3V
40
6
1
3

9
1 -40



6
20
10
34
6
20
10

' Is
6-34
Maximum
Observed
Loading

85
400
>140
140
140
200
910
630
230
290
na
100
351
>230
110
140

>270
85-910



>7IO
na
860
> 1,400
430
na
370

>750
370 -> 1,400
Days to Observed
Maximum
Loading

5
30
>50
5
5
5
15
35
70
70
na
>IO
>10
20
30
30

>25
5-70



>50
na
35
>40
30
na
10

>30
10->50
Reference

Pill and Sutherland 1982
Pitt and Sutherland 1982
Pill 1979
Sartor and Boyd 1972 (corrected)
Sartor and Boyd 1972 (corrected)
Ml and Sutherland 1982
'ill and Sutherland 1982
Pitt and Sutherland 1982
Pill 1979
Put and Shawley 1982
Pill 1983
3itt and McLean 1986
'ill and McLean 1986
Pitt 1984
'ill 1984
Pill 1984






Pill 1979
Pill 1983
Pitt and Sutherland 1982
Pitt and Sutherland 1982
Pitt 1979
Pitt 1983
Sartor and Boyd 1972 (corrected)


1

-------
periods of time between rains. The street dirt loadings never had the opportunity to reach the high loading values
needed before they could be blown from the streets by winds or by traffic-induced turbulence. The industrial street,
in contrast, had a much greater street dirt accumulation rate and was able to reach the critical loading values needed
for fugitive losses in the relatively short periods between the rains.

Washoff of Street Dirt
The Yalin equation relates the sediment carrying capacity to runoff flow rate (Yalin 1963). Yalin stated that
sediment motion begins when the lift force of flow exceeds a critical lift force. Once a particle is lifted, the drag
force of the flow moves it downstream until the weight of the particle forces it back down. The Yalin equation is
used to predict particle transport, for specific particle sizes, on a weight per unit flow width basis. It is used for fully
turbulent channel flow conditions, typical of shallow overland flow in urban areas. The receding limb (tail) of a
hydrograph may have laminar flow conditions, and the suspended sediment carried in the previously turbulent flows
would settle out. The predicted constant Yalin sediment load would therefore only occur during periods of rain, and,
the sediment load would decrease, due to sedimentation, after the rain stops. The critical particle bedload tractive
force, the tractive force at which the particle begins to move, can be obtained from the Shield's diagram. However,
Shen (1981) warned that the Shield's diagram alone cannot be used to predict "self-cleaning" velocities, as it gives
only a lower limit below which deposition will occur. It defines the boundary between bed movement and stationary
bed conditions. The Shield's diagram does not consider the particulate supply rate in relationship to the particulate
transport rate. Reduced particulate transport occurs if the sediment supply rate is less than the transport rate. The
Yalin equation by itself is therefore not sensitive to particulate supply; it only predicts the carrying capacity of
flowing waters.

Besides the particulate supply rate, the Yalin equation is also very sensitive to local flow parameters (specifically
gutter flow depth). Therefore, a hydraulic model that can accurately predict sheetflow across impervious surfaces
and gutter flow is needed. Sutherland and McCuen (1978) statistically analyzed a modified form of the Yalin
equation, in conjunction with a hydraulic model for different gutter flow conditions. Except for the largest particle
sizes, the effect of rain intensity on particle washoff was found to be negligible.

The Yalin equation is based on classical sediment transport equations, and requires some assumptions concerning
the micro-scale aspects of gutter flows and street dirt distributions. The Yalin equation, as typically used in urban
stormwater evaluations, assumes that all particles lie within the gutter, and no significant washoff occurs by
sheetflows traveling across the street towards the gutter. The early measurements of across-the-street dirt
distributions made by Sartor and Boyd (1972) indicated that about 90 percent of the street dirt was within about 30
cm of the curb face (typically within the gutter area). These measurements, however, were made in areas of no
parking (near fire hydrants because of the need for water for the sampling procedures that were used), and the traffic
turbulence was capable of blowing most of the street dirt against the curb barrier (or over the curb onto adjacent
sidewalks or landscaped areas) (Shaheen 1975). In later tests, Pitt (1979) and Pitt and Sutherland (1982) examined
street dirt distributions across-the-street in many additional situations. They found distributions similar to Sartor and
Boyd's observations only on smooth streets, with moderate to heavy traffic, and with no on-street parking. In many
cases, most of the street dirt was actually in the driving lanes, trapped by the texture of rough streets. If extensive
on-street parking was common, much of the street dirt was found on the outside edge of the parking lanes, where
much of the resuspended (in air) street dirt blew against the parked cars and settled to the pavement.

Another process that may result in washoff less than predicted by Yalin is bed armoring (Sutherland, et al, 1982). As
the smaller particulates are removed, the surface is covered by predominantly larger particulates which are not
effectively washed-off by rain. Eventually, these larger particulates hinder the washoff of the trapped, under-lying,
smaller particulates. Debris on the street, especially leaves, can also effectively armor the particulates, reducing the
washoff of particulates to very low levels (Singer and Blackard 1978).

Observations of particulate washoff during controlled tests using actual streets and natural street dirt and debris are
affected by street dirt distributions and armoring. The earliest controlled street dirt washoff experiments were
conducted by Sartor and Boyd (1972) during the summer of 1970 in Bakersfield, CA. Their data was used in many
stormwater models (including SWMM, Huber and Heaney 1981; STORM, COE 1975; and HSPF, Donigian and
Crawford 1976) to estimate the percentage of the available particulates on the streets that would wash off during
12

-------
rains of different magnitudes. Sartor and Boyd used a rain simulator having many nozzles and a drop height of 1-1/2
to 2 meters in street test areas of about 5 by 10 meters. Tests were conducted on concrete, new asphalt, and old
asphalt, using simulated rain intensities of about 5 and 20 mm/hr. They collected and analyzed runoff samples every
15 minutes for about two hours for each test. Sartor and Boyd fitted their data to an exponential curve, assuming that
the rate of particle removal of a given size is proportional to the street dirt loading and the constant rain intensity:

dN/dt = krN

where: dN/dt = the change in street dirt loading per unit time
k = proportionality constant
r = rain intensity (in/hr)
N = street dirt loading (Ib/curb-mile)

This equation, upon integration, becomes:

N = N0e-krt

where: N = residual street dirt load (after the rain)
N0 = initial street dirt load
t = rain duration

Street dirt washoff is therefore equal to N0 minus N. The variable combination rt, or rain intensity (in/h) times rain
duration (h), is equal to total rain depth (R), in inches. This equation then further reduces to:

N = N0e'KR

Therefore, this equation is only sensitive to the total depth of the rain that has fallen since the beginning of the rain,
and not rain intensity. Because of decreasing particulate supplies, the exponential washoff curve also predicts
decreasing concentrations of particulates with time since the start of a constant rain (Alley 1980 and 1981).

The proportionality constant, k, was found by Sartor and Boyd to be slightly dependent on street texture and
condition, but was independent of rain intensity and particle size. The value of this constant is usually taken as
0.18/mm, assuming that 90 percent of the particulates will be washed from a paved surface in 1 h during a 13 mrn/h
rain. However, Alley (1981) fitted this model to watershed outfall runoff data and found that the constant varied for
different storms and pollutants for a single study area. Novotny (as part of Bannerman, et al. 1983) also examined
"before" and "after" rain event street particulate loading data from the Milwaukee Nationwide Urban Runoff
Program (NURP) project and found almost a three-fold difference between the constant value of k for fine (<45 um)
and medium sized particles (100 to 250 um). The calculated values were 0.026/mm for the fine particles and
0.01/mm for the medium sized particles, both much less than the "accepted" value of 0.18/mm. Jewell, et al. (1980)
also found large variations in outfall "fitted" constant values for different rains compared to the typical default
value. Either the assumption of the high removal of particulates during the 13 mm/hr storm was incorrect or/and the
equation cannot be fitted to outfall data (most likely, as this would require that all the particulates are originating
from homogeneous paved surfaces during all storm conditions).

This washoff equation has been used in many stormwater models, along with an expression for an availability factor.
An availability factor is needed, as N0 is only the portion of the total street load available for washoff. This
availability factor (the fraction of the total street dirt loading available for washoff) is generally used as 1.0 for all
rain intensities greater than about 18 mm/hr and reduces to about 0.10 for rains of 1 mm/hr.

The Bellevue, WA, urban runoff project (Pitt 1985) included about 50 pairs of street dirt loading observations close
to the beginnings and ends of rains. These "before" and "after" loading values were compared to determine
significant differences in loadings that may have been caused by the rains. The observations were affected by rains
falling directly on the streets, along with flows and particulates originating from non-street areas. The net loading
differences were therefore affected by street dirt washoff (by direct rains on the street surfaces and by gutter flows
13

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augmented by "upstream" area runoff) and by erosion products that originated from non-street areas that may have
settled out in the gutters. When all the data were considered together, the net loading difference was about 10 to 13
g/curb-m removed. This amounted to a street dirt load reduction of about 15 percent, which was much less than
predicted using either of the two previously described washoff models. Very large reductions in street dirt loadings
during rains were observed in Bellevue for the smallest particles, but the largest particles actually increased in
loadings (due to deposited erosion materials originating from off-street areas). The particles were not source limited,
but armor shielding may have been important. Most of the particulates in the runoff were in the fine particle sizes
(<63 |um). Very few particles greater than 1000 um were found in the washoff water. Care must be taken to not
confuse street dirt particle size distributions with stormwater runoff particle size distributions. The stormwater
particle size distributions are much more biased towards the smaller sizes, as described later.

Suspended solids washoff predictions for Bellevue conditions were made using the Sutherland and McCuen
modification of the Yalin equation, and the Sartor and Boyd equation. Three particle size groups (<63,250-500, and
2000-6350 um), and three rains, having depths of 5, 10, and 20 mm and 3-h durations, were considered. The gutter
lengths for the Bellevue test areas averaged about 80 m, with gutter slopes of about 4.5 percent. Typical total initial
street dirt loadings for the three particle sizes were: 9 g/curb-m for <63 um, 18 g/curb-m for 250-500 um, and 9
g/curb-m for 2000-6350 um. The actual Bellevue net loading removals during the storms were about 45 percent for
the smallest particle size group, 17 percent for the middle particle size group, and -6 percent (6 percent loading
increase) for the largest particle size group. The predicted removals were 90 to 100 percent using the Sutherland and
McCuen method, 61 to 98 percent using the Sartor and Boyd equation, and 8 to 37 percent using the availability
factor with the Sartor and Boyd equation. The ranges given reflect the different rain volumes and intensities only.
There were no large predicted differences in removal percentages as a function of particle size. The availability
factor with the Sartor and Boyd equation resulted in the closest predicted values, but the great differences in washoff
as a function of particle size was not predicted.

The Bellevue street dirt washoff observations included effects of additional runoff water and particulates originating
from non-street areas. The additional flows should have produced more gutter paniculate washoff, but upland
erosion materials may also have settled in the gutters (as noted for the large particles). However, across-the-street
particulate loading measurements indicated that much of the street dirt was in the street lanes, not in the gutters,
before and after rains. This particulate distribution reduces the importance of these extra flows and particulates from
upland areas. The increased loadings of the largest particles after rains were obviously caused by upland erosion, but
the magnitude of the settled amounts was quite small compared to the total street dirt loadings.

In order to clarify street dirt washoff, Pitt (1987) conducted numerous controlled washoff tests on city streets in
Toronto. These tests were arranged as an overlapping series of 23 factorial tests, and were analyzed using standard
factorial test procedures described by Box, et al. (1978). The experimental factors examined included: rain intensity,
street texture, and street dirt loading. The differences between available and total street dirt loads were also related
to the experimental factors. The samples were analyzed for total solids (total residue), dissolved solids (filterable
residue: <0.45 um), and SS (particulate residue: >0.45 um). Runoff samples were also filtered through 0.45 um
filters and the filters were microscopically analyzed (using low power polarized light microscopes to differentiate
between inorganic and organic debris) to determine particulate size distributions from about 1 to 500 um. The runoff
flow quantities were also carefully monitored to determine the magnitude of initial and total rain water losses on
impervious surfaces.

The total solids concentrations varied from about 25 to 3000 mg/L, with an obvious decrease in concentrations with
increasing rain depths during these constant rain intensity tests. No concentrations greater than 500 mg/L occurred
after about 2 mm of rain, while all concentrations after about 10 mm of rain were less than 100 mg/L. Total solids
concentrations were independent of the test conditions. A wide range in runoff concentrations was also observed for
SS, with concentrations ranging from about 1 to 3000 mg/L. Again, a decreasing trend of concentrations was seen
with increasing rain depths, but the data scatter was larger because of the experimental factors. The dissolved solids
(<0.45 um) concentrations ranged from about 20 to 900 mg/L, comprising a surprisingly large percentage of the
total solids loadings. For small rain depths, dissolved solids comprised up to 90 percent of the total solids. After 10
mm of rain depth, the filterable residue concentrations were all less than about 50 mg/L.
14

-------
Manual particle size analyses were also conducted on the suspended solids washoff samples, using a microscope
with a calibrated recticle. Figures 2.2 and 2.3 are examples of particle size distributions for two tests. These plots
show the percentage of the particles that were less than various sizes, by measured particle volume (assumed to be
similar to weight). The plots also indicate median particle sizes of about 10 to 50 (am, depending on when the
sample was obtained during the washoff tests. All of the distributions showed surprisingly similar trends of particle
sizes with elapsed rain depth. The median size for the sample obtained at about 1 mm of rain was much greater than
for the samples taken after more rain. The median particle sizes of material remaining on the streets after the
washoff tests were also much larger than for most of the runoff samples, but were quite close to the initial samples'
median particle sizes. The washoff water at the very beginning of the test rains therefore contained many more
larger particles than during later portions of the rains. Also, a substantial amount of larger particles remained on the
streets after the test rains. Most street runoff waters during test rains in the 5 to 15 mm depth category had median
suspended solids particle sizes of about 10 to 50 urn. However, dissolved solids (less than 0.45 urn) made up most
of the total solids washoff for elapsed rain depths greater than about 5 mm.

These particle size distributions indicate that the smaller particles were much more important than indicated during
previous tests. As an example, the Sartor and Boyd (1972) washoff tests (rain intensities of 50 mm/h for 2 h
durations) found median particle sizes of about 150 um which were typically three to five times larger than were
found during these tests. They also did not find any significant particle size distribution differences for different rain
depths (or rain duration), in contrast to the Toronto tests which were conducted at more likely rain intensities (3 to
12 mm/h for 2 h).

The particulate washoff values obtained during these Toronto tests were expressed in units of grams per square
meter and grams per curb-meter, concentrations (mg/L), and the percent of the total initial loading washed off during
the test. Plots of accumulative washoff are shown on Figures 2.4 through 2.11. These plots show the asymptotic
washoff values observed in the tests, along with the measured total street dirt loadings. The maximum asymptotic
values are the "available" street dirt loadings (N0). The measured total loadings are seen to be several times larger
than these "available" loading values. As an example, the asymptotic available total solids value for the HDS (high
intensity rain, dirty street, smooth street) test (Figure 2.10) was about 3g/m2 while the total load on the street for this
test was about 14g/m2, or about five times the available load. The differences between available and total loadings
for the other tests were even greater, with the total loads typically about ten times greater than the available loads.
The total loading and available loading values for dissolved solids were quite close, indicating almost complete
washoff of the very small particles. However, the differences between the two loading values for SS were much
greater. Shielding, therefore, may not have been very important during these tests, as almost all of the smallest
particles were removed, even in the presence of heavy loadings of large particles.

The actual data are shown on these figures, along with the fitted Sartor and Boyd exponential washoff equations. In
many cases, the fitted washoff equations greatly over-predicted suspended solids washoff during the very small rains
(usually less than 1 to 3 mm in depth). In all cases, the fitted washoff equations described suspended solids washoff
very well for rains greater than about 10 mm in depth.

Table 2.5 presents the equation parameters for each of the eight washoff tests for suspended solids. Pitt (1987)
concluded that particulate washoff should be divided into two main categories, one for high intensity rains with dirty
streets, possibly divided into categories by street texture, and the other for all other conditions. Factorial tests also
found that the availability factor (the ratio of the available loading, N0, to the total loading) varied depending on the
rain intensity and the street roughness, as indicated below:

• Low rain intensity and rough streets: 0.045
• High rain intensity and rough streets, or low rain intensity and smooth streets: 0.075
• High rain intensity and smooth streets: 0.20

Obviously, washoff was more efficient for the higher rain energy and smoother pavement tests. The worst case was
for a low rain intensity and rough street, where only about 4.5% of the street dirt would be washed from the
pavement. In contrast, the high rain intensities on the smooth streets were more than four times more efficient in
removing the street dirt.
15

-------
                                    20       30       40     '  SO
                                          Particle size (nlcrons)
60
         70
Figure 2.2  Particle size distribution of HDS test (high rain intensity, dirty, and smooth street) (Pitt 1987).
                                          Part I da size (Microns!
Figure 2.J  Particle size distribution for LCR test (light rain intensity, clean, and rough street) (Pitt 1987).
                                                  16

-------
                                                                0,3
                                                                0.2
                                                                         0.65 g/a2
                                                       20
0  ' 5
                                                                           10 ' 15
                                                                                   28
                                           Rain (M)
Figure 2.4 Washoff plots for HCR test (high rain intensity, clean, and rough street) (Pitt 1987).
                                              2   3
                                            Rain (••)
                                                                       1234
 Figure 2.5 Washoff plots for LCR test (light rain intensity, clean, and rough street) (Pitt 1987).
                                             17

-------
                 10  15  20
                                                                           18  15 ' 20
                                          Rain CM)
Figure 2.6  Washoff plots for HDR test (high rain intensity, dirty, and rough street) (Pitt 1987).
                                          Rain (u)





Figura 2.7 Washoff plots for LDR test (light rain intensity, dirty, and rough street) (Pitt 1987).
                                            18

-------
                                     2.0y
                                 I  l.«
0.8


0.7


0.6
                                    0.3-V
                                              1.8 g/B2
                                                                 1.0


                                                                 0.8
                                                                 0.3
                                                                0.2
                                                              M

                                                              " 0.1S
                                                              ^ 0.08'
                   10   IS   20
            10
                                           Rain  (•*)
                15
                                     0.87 g/m2
                                                        20
                                                                     0  'S
                                                                             10
                                                                                 15
Figure 2.8  Washoff plots for HCS test (high rain intensity, clean, and smooth street) (Pitt 1987).
           01234
                                            Roln [ul
 Figure 2.9 Washoff plots for LCS test (light rain intensity, clean, and smooth street) (Pitt 1987).
                                              19

-------
                10   IS  20
                                                                1.3-r
                                                             -£  0.5
                                                                0.3-
                                                             a 0.2-
                                               10  15   20
                                           Rain («)
Figure 2.10  Washoff plots for HDS test (high rain intensity, dirty, and smooth street) (Pitt 1987).
    2.0
                                                                  0   1  1  3  4  5  &
                                          Rain (uil
 Figure 2.11 Washoff plots for LCS replicate test (light rain intensity, clean, and smooth street)
                                         (Pitt 1987).
                                             20

-------
Table 2.5 Suspended Solids Washoff Coefficients (Pitt 1987)1
Test
condition
code
HCR
LCR
HDR
LDR
HCS
LCS
HDS
L(D)CS
Rain
intensity
category
high
low
high
low
high
low
high
low
Street dirt
loading
category
clean
clean
dirty
dirty
clean
clean
dirty
(actually clean)
Street
texture
category
rough
rough
rough
rough
smooth
smooth
smooth
smooth
Calculated k
0.832
0.344
0.077
0.619
1.007
0.302
0.167
0.335
Standard
error for k
0.064
0.038
0.008
0.052
0.321
0.024
0.015
0.031
Ratio of available
load to total initial
load
0.11
0.061
0.032
0.028
0.26
0.047
0.13
0.11
'Note:
N = N0eKR

where: N = residual street dirt load, after the rain (Ib/curb-mile)
No = initial street dirt load
R = rain depth (inches)
k = proportionality constant (1/hr)
Observed Particle Size Distributions in Stormwater
The particle size distributions of stormwater greatly affect the ability of most controls in reducing pollutant
discharges. This research has included particle size analyses of 121 stormwater samples from three states that were
not affected by stormwater controls (southern New Jersey as part of the inlet tests; Birmingham, Alabama as part of
the MCTT pilot-scale tests; and in Milwaukee and Minocqua, Wisconsin, as part of the MCTT mil-scale tests).
These samples represented stormwater entering the stormwater controls being tested. Particle sizes were measured
using a Coulter Multi-Sizer He and verified with microscopic, sieve, and settling column tests. Figures 2.12 through
2.14 are grouped box and whisker plots showing the particle sizes (in um) corresponding to the 10th, 50th (median)
and 90* percentiles of the cumulative distributions. If 90 percent control of SS was desired, then the particles larger
than the 90th percentile would have to be removed, for example. The median particle sizes ranged from 0.6 to 38 um
and averaged 14 um. The 90* percentile sizes ranged from 0.5 to 11 um and averaged 3 um. These particle sizes are
all substantially smaller than have been typically assumed for stormwater. In all cases, the New Jersey samples had
the smallest particle sizes, followed by Wisconsin, and then Birmingham, AL, which had the largest particles. The
New Jersey samples were obtained from gutter flows in a residential semi-xeroscaped neighborhood, the Wisconsin
samples were obtained from several source areas, including parking areas and gutter flows mostly from residential,
but from some commercial areas, and the Birmingham samples were collected from a long-term parking area.

Atmospheric Sources of Urban Runoff Pollutants
Atmospheric processes affecting urban runoff pollutants include dry dustfall and precipitation quality. These have
been monitored in many urban and rural areas. In many instances, however, the samples were combined as a bulk
precipitation sample before processing. Automatic precipitation sampling equipment can distinguish between dry
periods of fallout and precipitation. These devices cover and uncover appropriate collection jars exposed to the
atmosphere. Much of this information has been collected as part of the Nationwide Urban Runoff Program (NURP)
and the Atmospheric Deposition Program, both sponsored by the U.S. Environmental Protection Agency (EPA
1983a).

One must be very careful in interpreting this information, however, because of the ability of many polluted dust and
dirt particles to be resuspended and then redeposited within the urban area. In many cases, the measured atmospheric
deposition measurements include material that was previously residing and measured in other urban runoff pollutant
source areas. Also, only small amounts of the atmospheric deposition material would directly contribute to runoff.
Rain is subjected to infiltration and the dry fall particulates are likely mostly incorporated with surface soils and
21

-------
            100
            80
            60
            40
            20 -
                      NJ       Wl
                            AREA
                                      AL
 Figure 2.12  Tenth percentlle particle sizes for stormwater inlet flows.
            40
            30
           20
            10
                                      I
                      NJ      Wl      AL
                            AREA
Figure 2.13 Fiftieth percentile particle sizes for stormwater inlet flows.
            15
            10  -
                              1
                      NJ
                              Wl
                            AREA
                                      AL
Figure 2.14  Ninetieth percentile particle sizes for stormwater inlet flows.
                                  22

-------
only small fractions are then eroded during rains. Therefore, mass balances and determinations of urban runoff
deposition and accumulation from different source areas can be highly misleading, unless transfer of material
between source areas and the effective yield of this material to the receiving water is considered. Depending on the
land use, relatively little of the dustfall in urban areas likely contributes to stormwater discharges.

Dustfall and precipitation affect all of the major urban runoff source areas in an urban area. Dustfall, however, is
typically not a major pollutant source but fugitive dust is mostly a mechanism for pollutant transport, as previously
mentioned. Most of the dustfall monitored in an urban area is resuspended particulate matter from street surfaces or
wind erosion products from vacant areas (Pitt 1979). Point source pollutant emissions can also significantly
contribute to dustfall pollution, especially in industrial areas. Transported dust from regional agricultural activities
can also significantly affect urban stormwater.

Wind transported materials are commonly called "dustfall." Dustfall includes sedimentation, coagulation with
subsequent sedimentation and impaction. Dustfall is normally measured by collecting dry samples, excluding
rainfall and snowfall. If rainout and washout are included, one has a measure of total atmospheric fallout. This total
atmospheric fallout is sometimes called "bulk precipitation." Rainout removes contaminants from the atmosphere by
condensation processes in clouds, while washout is the removal of contaminants by the falling rain. Therefore,
precipitation can include natural contamination associated with condensation nuclei in addition to collecting
atmospheric pollutants as the rain or snow falls. In some areas, the contaminant contribution by dry deposition is
small, compared to the contribution by precipitation (Malmquist 1978). However, in heavily urbanized areas,
dustfall can contribute more of an annual load than the wet precipitation, especially when dustfall includes
resuspended materials.

Table 2.6 summarizes rain quality reported by several researchers. As expected, the non-urban area rain quality can
be substantially better than urban rain quality. Many of the important heavy metals, however, have not been detected
in rain in many areas of the country. The most important heavy metals found in rain have been lead and zinc, both
being present in rain in concentrations from about 20 up to several hundred ug/L. It is expected that more recent
lead rainfall concentrations would be substantially less, reflecting the decreased use of leaded gasoline since these
measurements were taken. Iron is also present in relatively high concentrations in rain (about 30 to 40 ug/L).
Table 2.6. Summary of Reported Rain Quality

Suspended solids, mg/L
Volatile suspended solids, mg/L
Inorganic nitrogen, mg/L as N
Ammonia, mg/L as N
Nitrates, mg/L as N
Total phosphates, mg/L as P
Ortho phosphate, mg/L as P
Scandium, ug/L
Titanium, ng/L
Vanadium, ^g/L
Chromium, (ig/L
Manganese, ng/L
Iron, (ig/L
Cobalt, ug/L
Nickel, ug/L
Copper, ug/L
Zinc, ug/L
Lead, ug/L
1 Rubin 1976
2 Wilbur and Hunter 1980
3 Manning, era/. 1976
Rural-
Northwest
(Quilayute,
WA)'

<0.002
nd
nd
<2
2.6
32
0.04
nd
3.1
20

Rural-
Northeast
(Lake George,
NY)1

nd
nd
nd
nd
3.4
35
nd
nd
8.2
30

Urban- Urban- Other
Northwest Midwest Urban3
(Lodi, NJ)2 (Cincinnati, OH)3

13
3.8
0.69
0.7
0.3
<0.1
0.24

3
6
44
45

Continental
Avg. (32
locations)1

nd
nd
nd
nd
12

nd
43
21
107

-------
The concentrations of various urban runoff pollutants associated with dry dustfall are summarized in Table 2.7.
Urban, rural and oceanic dry dustfall samples contained more than 5,000 mg iron/kg total solids. Zinc and lead were
present in high concentrations. These constituents can have concentrations of up to several thousand mg of pollutant
per kg of dry dustfall. Spring, etal. (1978) monitored dry dustfall near a major freeway in Los Angeles. Based on a
series of samples collected over several months, they found that lead concentrations on and near the freeway can be
about 3,000 mg/kg, but as low as about 500 mg/kg 150 m (500 feet) away. In contrast, the chromium concentrations
of the dustfall did not vary substantially between the two locations and approached oceanic dustfall chromium
concentrations.

Table 2.7. Atmosphere Dustfall Quality
Constituent, (mg
constituent/kg total solids)
PH
Phosphate-Phosphorous
Nitrate-Nitrogen, ng/L
Scandium, \\gl\-
Titanium, |ig/L
Vanadium, |jg/L
Chromium, jig/L
Manganese, jig/L
Iron, ng/L
Cobalt, ng/L
Nickel, ng/L
Copper, ng/L
Zinc, ng/L
Lead, ug/L
Urban1 Rural/ Oceanic1 Near freeway 500' from
suburban1 (LA)2 freeway (LA)2

5
380
480
190
6700
24000
48
950
1900
6700

3
810
140
270
1400
5400
27
1400
2700
1400

4.3
1200
5800
4
2700
18
38 34
1800
21000
8

4500
230
2800
4.7
1600
9000

550
Summarized by Rubin 1976
2 Spring 1978

Much of the monitored atmospheric dustfall and precipitation would not reach the urban runoff receiving waters.
The percentage of dry atmospheric deposition retained in a rural watershed was extensively monitored and modeled
in Oakridge, TN (Barkdoll, et al. 1977). They found that about 98 percent of the lead in dry atmospheric deposits
was retained in the watershed, along with about 95 percent of the cadmium, 85 percent of the copper, 60 percent of
the chromium and magnesium and 75 percent of the zinc and mercury. Therefore, if the dry deposition rates were
added directly to the yields from other urban runoff pollutant sources, the resultant urban runoff loads would be very
much overestimated.

Tables 2.8 and 2.9 report bulk precipitation (dry dustfall plus rainfall) quality and deposition rates as reported by
several researchers. For the Knoxviile, KY, area (Betson 1978), chemical oxygen demand (COD) was found to be
the largest component in the bulk precipitation monitored, followed by filterable residue and nonfilterable residue.
Table 2.9 also presents the total watershed bulk precipitation, as the percentage of the total stream flow output for
the three Knoxviile watersheds studies. This shows that almost all of the pollutants presented in the urban runoff
streamflow outputs could easily be accounted for by bulk precipitation deposition alone. Betson concluded that bulk
precipitation is an important component for some of the constituents in urban runoff, but the transport and
resuspension of particulates from other areas in the watershed are overriding factors.

Rubin (1976) stated that resuspended urban particulates are returned to the earth's surface and waters in four main
ways: gravitational settling, impaction, precipitation and washout. Gravitational settling, as dry deposition, returns
most of the particles. This not only involves the settling of relatively large fly ash and soil particles, but also the
settling of smaller particles that collide and coagulate. Rubin stated that particles that are less than 0.1 um in
diameter move randomly in the air and collide often with other particles. These small particles can grow rapidly by
this coagulation process. These small particles would soon be totally depleted in the air if they were not constantly
replenished. Particles in the 0.1 to 1.0 um range are also removed primarily by coagulation. These larger particles
grow more slowly than the smaller particles because they move less rapidly in the air, are somewhat less numerous
and, therefore, collide less often with other particles. Particles with diameters larger than 1 um have appreciable
24

-------
Table 2.8. Bulk Precipitation Quality
Constituent (all units mg/L
except pH)


Calcium
Magnesium
Sodium
Chlorine
Sulfate
PH
Organic Nitrogen
Ammonia Nitrogen
Nitrite plus Nitrate-N
Total phosphate
Potassium
Total iron
Manganese
Lead
Mercury
Nonfilterable residue
Chemical Oxygen
Demand
Zinc
Copper
1 Betson 1978
2 Malmquist 1978
Urban
(average of
Knoxville
St. Louis &
Germany'
3.4
0.6
1.2
2.5
8.0
5.0
2.5
0.4
0.5
1.1
1.8
0.8
0.03
0.03
0.01
16
65





Rural
(Tennessee)1


0.4
0.1
0.3
0.2
8.4
4.9
1.2
0.4
0.4
0.8
0.6
0.7
0.05
0.01
0.0002







Urban
(Gutebura,
Sweden)









2
1
0.03



0.05


10

0.08
0.02


Table 2.9. Urban Bulk Precipitation Deposition Rates (Source: Betson 1978)a
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Constituent
Chemical oxygen demand
Filterable residue
Nonfilterable residue
Alkalinity
Sulfate
Chloride
Calcium
Potassium
Organic nitrogen
Sodium
Silica
Magnesium
Total Phosphate
Nitrite and Nitrate-N
Soluble phosphate
Ammonia Nitrogen
Total Iron
Fluoride
Lead
Manganese
Arsenic
Mercury
Average Bulk
Deposition Rate
(kg/ha/yr)
530
310
170
150
96
47
38
21
17
15
11
9
9
5.7
5.3
3.2
1.9
1.8
1.1
0.54
0.07
0.008
Average Bulk
Prec. as a % of
Total Streamflow
Output
490
60
120
120
470
360
170
310
490
270
130
180
130
360
170
1,100
47
300
650
270
720
250
' Average for 3 Knoxville, KY, watersheds.
                                                   25

-------
settling velocities. Those particles about 10 um in diameter can settle rapidly, although they can be kept airborne for
extended periods of time and for long distances by atmospheric turbulence.

The second important particulate removal process from the atmosphere is impaction. Impaction of particles near the
earth's surface can occur on vegetation, rocks and building surfaces. The third form of particulate removal from the
atmosphere is precipitation, in the form of rain and snow. This is caused by the rainout process where the
particulates are removed in the cloud-forming process. The fourth important removal process is washout of the
particulates below the clouds during the precipitation event. Therefore, it is easy to see that re-entrained particles
(especially from street surfaces, other paved surfaces, rooftops and from soil erosion) in urban areas can be readily
redeposited through these various processes, either close to the points of origin or at some distance away.

Pitt (1979) monitored airborne concentrations of particulates near typical urban roads. He found that on a number
basis, the downwind roadside particulate concentrations were about 10 percent greater than upwind conditions.
About 80 percent of the concentration increases, by number, were associated with particles in the 0.5 to 1.0 urn size
range. However, about 90 percent of the particle concentration increases by weight were associated with particles
greater than 10 um. He found that the rate of particulate resuspension from street surfaces increases when the streets
are dirty (cleaned infrequently) and varied widely for different street and traffic conditions. The resuspension rates
were calculated based upon observed long-term accumulation conditions on street surfaces for many different study
area conditions, and varied from about 0.30 to 3.6 kg per curb-km (1 to 12 Ib per curb-mile) of street per day.

Murphy (1975) described a Chicago study where airborne particulate material within the city was microscopically
examined, along with street surface particulates. The particulates from both of these areas were found to be similar
(mostly limestone and quartz) indicating that the airborne particulates were most likely resuspended street surface
particulates, or were from the same source. PEDCo (1977) found that the re-entrained portion of the traffic-related
particulate emissions (by weight) is an order of magnitude greater than the direct emissions accounted for by vehicle
exhaust and tire wear. They also found that particulate resuspensions from a street are directly proportional to the
traffic volume and that the suspended particulate concentrations near the streets are associated with relatively large
particle sizes. The medium particle size found, by weight, was about 15 um, with about 22 percent of the
particulates occurring at sizes greater than 30 um. These relatively large particle sizes resulted in substantial
particulate fallout near the road. They found that about 15 percent of the resuspended particulates fall out at 10m,
25 percent at 20 m, and 35 percent at 30 m from the street (by weight). In a similar study Cowherd, et al. (1977)
reported a wind erosion threshold value of about 5.8 m/s (13 mph). At this wind speed, or greater, significant dust
and dirt losses from the road surface could result, even in the absence of traffic-induced turbulence. Rolfe and
Reinbold (1977) also found that most of the particulate lead from automobile emissions settled out within 100 m of
roads. However, the automobile lead does widely disperse over a large area. They found, through multi-elemental
analyses, that the settled outdoor dust collected at or near the curb was contaminated by automobile activity and
originated from the streets.

Source Area Sheetflow and Particulate Quality
This chapter section summarizes the source area sheetflow and particulate quality data obtained from several studies
conducted in California, Washington, Nevada, Wisconsin, Illinois, Ontario, Colorado, New Hampshire, and New
York since 1979. Most of the data obtained was for street dirt chemical quality, but a relatively large amount of
parking and roof runoff quality data has also been obtained. Only a few of these studies evaluated a broad range of
source areas or land uses.

Source Area Particulate Quality
Particulate potency factors (usually expressed as mg pollutant/kg dry particulate residue) for many samples are
summarized on Tables 2.10 and 2.11. These data can help recognize critical source areas, but care must be taken if
they are used for predicting runoff quality because of likely differential effects due to washoff and erosion from the
different source areas. These data show the variations in chemical quality between particles from different land uses
and source areas. Typically, the potency factors increase as the use of an area becomes more intensive, but the
variations are slight for different locations throughout the country. Increasing concentrations of heavy metals with
decreasing particle sizes was also evident, for those studies that included particle size information. Only the quality
26

-------
of the smallest particle sizes are shown on these tables because they best represent the particles that are removed
during rains.

Warm Weather Sheet/low Quality
Sheetflow data, collected during actual rain, are probably more representative of runoff conditions that the
previously presented dry particulate quality data because they are not further modified by washoff mechanisms.
These data, in conjunction with source area flow quantity information, can be used to predict outfall conditions and
the magnitude of the relative sources of critical pollutants. Tables 2.12 through 2.15 summarize warm weather
sheetflow observations, separated by source area type and land use, from many locations. The major source area
categories are listed below:

• roofs
• paved parking areas
• paved storage areas
• unpaved parking and storage areas
• paved driveways
• unpaved driveways
• dirt walks
• paved sidewalks
• streets
• landscaped areas
• undeveloped areas
• freeway paved lanes and shoulders

Toronto warm weather sheetflow water quality data were plotted against the rain volume that had occurred before
the samples were collected to identify any possible trends of concentrations with rain volume (Pitt and McLean
1986). The street runoff data obtained during the special washoff tests reported earlier were also compared with the
street sheetflow data obtained during the actual rain events (Pitt 1987). These data observations showed definite
trends of solids concentrations verses rain volume for most of the source area categories. Sheetflows from all
pervious areas combined had the highest total solids concentrations from any source category, for all rain events.
Other paved areas (besides streets) had total solids concentrations similar to runoff from smooth industrial streets.
The concentrations of total solids in roof runoff were almost constant for all rain events, being slightly lower for
small rains than for large rains. No other pollutant, besides SS, had observed trends of concentrations with rain
depths for the samples collected in Toronto. Lead and zinc concentrations were highest in sheetflows from paved
parking areas and streets, with some high zinc concentrations also found in roof drainage samples. High bacteria
populations were found in sidewalk, road, and some bare ground sheetflow samples (collected from locations where
dogs would most likely be "walked").

Some of the Toronto sheetflow contributions were not sufficient to explain the concentrations of some constituents
observed in runoff at the outfall. High concentrations of dissolved chromium, dissolved copper, and dissolved zinc
in a Toronto industrial outfall during both wet and dry weather could not be explained by wet weather sheetflow
observations (Pitt and McLean 1986). As an example, very few detectable chromium observations were obtained in
any of the more than 100 surface sheetflow samples analyzed. Similarly, most of the fecal coliform populations
observed in sheetflows were significantly lower than those observed at the outfall, especially during snowmelt. It is
expected that some industrial wastes, possibly originating from metal plating operations, were the cause of these
high concentrations of dissolved metals at the outfall and that some sanitary sewage was entering the storm drainage
system.

Table 2.15 summarizes the very little filterable pollutant concentration data available, before this EPA project, for
different source areas. Most of the available data is for residential roofs and commercial parking lots.
27

-------
 Table 2.10  Summary of Observed Street Dirt Chemical Quality (means)
             (mg constituent/kg solids)

p
TKN
COD
Cu
Pb
Zn
Cd
Cr
Residential
620 (4)
540 (6)
1100 (5)
710 (1)
810 (3)
1030 (4)
3000 (6)
290 (5)
2630 (3)
3000 (2)
100,000 (4)
150,000 (6)
180,000 (5)
280,000 (1)
180,000 (3)
170,000 (2)
162 (4)
110 (6)
420 (2)
1010 (4)
1800 (6)
530 (5)
1200 (1)
1650 (3)
3500 (2)
460 (4)
260 (5)
325 (3)
680 (2)
<3 (5)
4 (2)
42 (4)
31 (5)
170 (2)
Commercial
400 (6)
1500 (5)
910 (1)
1100 (6)
340 (5)
4300 (2)
110,000 (6)
250,000 (5)
340,000 (1)
210,000 (2)
130 (6)
220 (2)
3500 (6)
2600 (5)
2400 (1)
7500 (2)
750 (5)
1200 (2)
5 (5)
5 (2)
65 (5)
180 (2)
Industrial
670 (4)
560 (4)
65,000 (4)
360 (4)
900 (4)
500 (4)

70 (4)
References; location; particle size described;

(1)  Bannerman, ef a/. 1983 (Milwaukee, Wl) <31 urn
(2)  Pitt 1979  (San Jose, CA) <45 urn
(3)  Pitt 1985  (Bellevue, WA) <63 ^m
(4)  Pitt and McLean 1986 (Toronto, Ontario) <125 urn
(5)  Pitt and Sutherland 1982  (Reno/Sparks, NV) <63 urn
(6)  Terstrip, era/. 1982 (Champaign/Urbana, IL) >63 urn
                                                     28

-------
 Table 2.11 Summary of Observed Particulate Quality for Other Source Areas (means for <125 urn
          particles) (mg constituent/kg solids)
                                           TKN
COD
                                                                 Cu
                  Pb
                                                                                Zn
Cr
Residential/Commercial Land Uses
Roofs
Paved parking
Unpaved driveways
Paved driveways
Dirt footpath
Paved sidewalk
Garden soil
Road shoulder
Industrial Land Uses
Paved parking
Unpaved parking/storage
Paved footpath
Bare ground
1500
600
400
550
360
1100
1300
870

770
620
890
700
5700
790
850
2750
760
3620
1950
720

1060
700
1900
1700
240,000
78,000
50,000
250,000
25,000
146,000
70,000
35,000

130,000
110,000
120,000
70,000
130
145
45
170
15
44
30
35

1110
1120
280
91
980
630
160
900
38
1200
50
230

650
2050
460
135
1900
420
170
800
50
430
120
120

930
1120
1300
270
77
47
20
70
25
32
35
25

98
62
63
38
Source: Pitt and McLean 1986 (Toronto, Ontario)
                                                 29

-------
            Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference)
UJ
O
Pollutant and Land Use
Total Solids (ma/L)
Residential:
Commercial:
Industrial:
Suspended Solids (ma/U
Residential:
Commercial:
Industrial:
Dissolved Solids (ma/U
Residential:
Commercial:
Roofs

58(5)
64(1)
18(4)
95(1)
190(4)
113(5)

22(1)
13(5)

4(5)

42(10
5(5)

Paved Parking Paved Unpaved
Storage Parking/Storage

1790(5) 73(5)
340 (2)
240 (1)
102(7)
490(5) 270(5) 1250(5)

1660(5) 41(5)
270 (2)
65(1)
41 (7)
306 (5) 202 (5) 730 (5)

130(5) 32(5)
70(2)
175(1)
61(7)
Paved Unpaved Dirt Paved Streets
Driveways Driveways Walks Sidewalks

510 (5) 1240(5) 49(5) 325(5)
235 (4)
325 (4)
506(5) 5620(5) 580 (5) 1800(5)

440 <5) 810(5) 20(5) 242(5)
242 (5)
373(5) 4670(5) 434(5) 1300(5)

70 (5> 430(5) 29(5) 83(5)
83(4)
83(5)
                Industrial:
109(5)
                                                     184(5)
68(5)
520(5)
133(5)
                                                                      950(5)
                                                                                                                                    146(5)    500 (

-------
Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference) (Continued)
Pollutant and Land Use
BODg (mq/L)
Residential:
Commercial:
COD (mq/L)
Residential:
Commercial:
Industrial:
Total Phosphorus (mq/L)
Residential:
Commercial:
Roofs
3(4)
7(4)

46(5)
27(1)
20(4)
130(4)
55 (5)

0.03 (5)
0.05(1)
0.1 (4)
0.03 (4)
0.07 (4)
Paved Parking Paved Unpaved
Storage Parking/Storage
22(4)
11(1)
4(8)

173(5) 22(5)
190(2)
180(4)
53(1)
57(8)
180(5) 82(5) 247(5)


0.16(1)
0.15(7)
0.73 (5)
0.9 (2)
0.5 (4)
Paved Unpaved Dirt Paved Streets
Driveways Driveways Walks Sidewalks
13(4)


178 (5) 62(5) 174(5)
170(4)
174(5)
138(5) 418(5) 98(5) 322(5)

°-36 (5) 0.20 (5) 0.80 (5) 0.62 (5)
0.31 (4)
0.62 (5)
    Industrial:
                            <0,06 (5)
2.3 (5)
0.7 (5)
1.0(5)
0.9 (5)
3.0 (5)
                                                                                                                           0.82(5)      1.6(5)

-------
            Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference) (Continued)
UJ
to
Pollutant and Land Use
Total Phosohate (ma/U
Residential:
Commercial:
Industrial:
TKN (ma/U
Residential:
Commercial:
Industrial:
Ammonia (ma/U
Residential:
Commercial:
Roofs

<0.04 (5)
0.08 (4)
0.02 (4)
<0.02 (5)

1.1 (5)
0.71 (4)
4.4 (4)
1.7(5)

0.1 (5)
0.9(1)
0.5 (4)
1.1 (4)
Paved Parking Paved Unpaved
Storage Parking/Storage


0.03 (5) <0.02 (5)
0.3 (2)
0.5 (4)
0.04 (7)
0.22 (8)
0.6(5) 0.06(5) 0.13(5)


3.8 (5)
4.1 (2)
1.5(4)
1.0(1)
0.8 (8)
2.9 (5) 3.5 (5) 2.7 (5)

0.1 (5) 0.3 (5)
1.4(2)
0.35 (4)
0.38(1)
Paved Unpaved Dirt Paved Streets
Driveways Driveways Walks Sidewalks

<0-2<5) 0.66(5) 0.64(5) 0.07(5)
0.12 (4)
0.07 (5)
<0.02(5) 0.10(5) 0.03(5) 0.15(5)

3'1(5) 1-3(5) 1.1(5) 2.4(5)
2.4 (4)
2.4 (5)
5'7(5> 7'5<5> 4.7(5) 5.7(5)

<0'1(5) 0.5(5) 0.3(5) <0.1(5)
0.42 (4)
<0.1 (5)
                Industrial:
0.4 (5)
                                                       0.3 (5)
0.3 (5)

-------
            Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference) (Continued)
L.J
Ul
Pollutant and Land Use
Phenols (mq/L)
Residential:
Industrial:
Aluminum (uq/D
Residential:
Industrial:
Cadmium (ua/L)
Residential:
Commercial:
Industrial:
Chromium (ua/L)
Residential:
Commercial:
Industrial:
Roofs

2.4 (5)
1.2(5)

0.4 (5)
<0.2 (5)

<4(5)
0.6(1)

<4(5)

<60 (5)
<5(4)
<5(4)
<60 (5)
Paved Parking Paved Unpaved
Storage Parking/Storage

12.2(5) 30.0(5)
9.4 (5) 2.6 (5) 8.7 (5)

3.2 (5) 0.38 (5)
3.5 (5) 3.1 (5) 9.2 (5)

2 (5) <5 (5)
5.1 (7)
0.6 (8)
<4 (5) <4 (5) <4 (5)

20(5) <10(5)
71 (4)
19(7)
12(8)
<60 (5) <60 (5) <60 (5)
Paved Unpaved Dirt Paved Streets
Driveways Driveways Walks Sidewalks

9.7(5) <0.4(5) 8.6(5) 6.2(5)
7.0(5) 7.4(5) 8.7(5) 24(7)

5.3(5) <0.03(5) 0.5(5) 1.5(5)
3.4(5) 41(5) 1.2(5) 14(5)

5 (5) <1 (5) <4 (5) <5 (5)
<5(5)
<4 (5) <4 (5) <4 (5) <4 (5)

<6°(5) <10(5) <60(5) <60(5)
49(4)
<60 (5)
<60(5) 70(5) <60(5) <60 (5)

-------
Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference) (Continued)
Pollutant and Land Use Roofs
Copper (ua/U
Residential: 10(5)
<5(4)
Commercial: 110(4)
Industrial: <2° <5)
Lead (|jg/L)
Residential: <4° (5)
30(3)
48(1)
17(4)
Commercial: 19 W
30(1)
Paved Parking Paved Unpaved
Storage Parking/Storage

100(5) 20(5)
40(2)
46(4)
110(7)
480(5) 260(5) 120(5)

250 (5) 760 (5)
200 (2)
350 (3)
1090 (4)
146(1)
255 (7)
54(8)
Paved Unpaved Dirt Paved Streets
Driveways Driveways Walks Sidewalks

210(5) 20(5) 20(5) 40(5)
30(4)
40(5)
40(5) 140(5) 30(5) 220(5)

1400 (5) 30(5) 80(5) 180(5)
670 (4)
180(5)
    Industrial:
                             <40 (5)
230 (5)
280 (5)
210(5)
260 (5)
                                                          340 (5)
                                                                                                                          <40 (5)       560 (5)

-------
Table 2.12 Sheetflow Quality Summary for Other Source Areas (mean concentration and reference) (Continued)
Pollutant and Land Use
Roofs
Paved Parking Paved Unpaved Paved Unpaved Dirt Paved Streets
Storage Parking/Storage Driveways Driveways Walks Sidewalks
Zinc (uq/L)



Residential:
Commercial:
Industrial:
320 (5)
670(1)
180(4)
310(1)
80(4)
70(5)
References:
(1) Bannerman, etal. 1983 (Milwaukee, Wl)
(2) Denver Regional Council of Governments
(3) Pitt 1983 (Ottawa)
(4) Pitt and Bozeman 1 982 (San Jose)
520 (5) 390 (5)
300 (5)
230 (4)
133(1)
490 (7)
640(7) 310(5)
(NURP)
1983 (NURP)
1000 (5) 40(5) 60(5) 180(5)
140 (4)
180(5)
410(5) 310(5) 690(5) 60 (5) 910 (5)

(5)  Pitt and McLean 1986 (Toronto)
(7)  STORE! Site #590866-2954309 (Shop-Save-Durham, NH) (NURP)
(8)  STORET Site #596296-2954843 (Huntington-Long Island, NY) (NURP)

-------
 Table 2.13 Sheetflow Quality Summary for Undeveloped Landscaped and Freeway Pavement Areas
           (Mean Observed Concentrations and reference)


        Pollutants              Landscaped Areas         Undeveloped Areas       Freeway Paved Lane and
                                                                               Shoulder Areas
Total Solids, mg/L
Suspended Solids, mg/L
Dissolved Solids, mg/L
BOD5, mg/L
COD, mg/L
Total Phosphorus, mg/L
Total Phosphate, mg/L
TKN, mg/L
Ammonia, mg/L
Phenols, ng/L
Aluminum, jig/L
Cadmium, (ig/L
Chromium, ng/L
Copper, ng/L
Lead, ng/L
Zinc, ng/L
388 (5)
100 (5)
288 (5)
3 (4)
70 (4)
26 (5)
0.42 (4)
0.56 (5)
0.32 (4)
0.14(5)
1.32(4)
3.6 (5)
1.2 (4)
0.4 (5)
0.8 (5)
1.5 (5)
<3 (5)
10 (4)
<20 (5)
30 (3)
35 (4)
<30 (5)
10(4)
588 (5)
400 (2)
390 (5)
193 (5)
	
72 (2)
54 (5)
0.40 (2)
0.68 (5)
0.10 (2)
0.26 (5)
2.9 (2)
1.8 (5)
0.1 (2)
<0.1 (5)
	
. 11 (5)
<4 (5)
<60 (5)
40 (2)
31 (4)
<20 (5)
100 (2)
30 (3)
<40 (5)
100 (2)
100 (5)
340 (6)
180 (6)
160 (6)
10 (6)
130 (6)
	
0.38 (6)
2.5 (6)
	
	
	
60 (6)
70 (6)
120 (6)
2000 (6)
460 (6)
References:
(2)  Denver Regional Council of Governments 1983 (NURP)
(3)  Pitt 1983 (Ottawa)
(4)  Pitt and Bozeman  1982  (San Jose)
(5)  Pitt and McLean 1986 (Toronto)
(6)  Shelly and Gaboury 1986 (Milwaukee)
                                                  36

-------
Table 2.14 Source Area Bacteria Sheetflow Quality Summary (means)
Unpaved
Pollutant and Paved Paved Parking/ Paved Unpaved Dirt
Land Use Roofs Parking Storage Storage Driveways Driveways Walks

(ft/1 00 mL)
Residential: 85(3) 250,000(5) 100(5) 600(5)
<2(4)
1400 (5)
Commercial 9(4) 2900(3)
350 (4)
210(1)
480 (7)
23,000 (8)
Industrial- 1600 (5) 8660(8) 9200(5) 18,000(5) 66,000(5) 300,000(5)
Fecal Strep
W/IOOmL)
Residential: 170(3) 190,000(5) <100(5) 1900(5) 1800(5)
920 (4)
2200 (5)
Commercial: 17(3) 11,900(3)
>2400 (4)
770(1)
1120(7)
62,000 (8)
Industrial:
690(5) 7300(5) 2070(5) 8100(5) 36,000(5) 21,000(5)
Pseudo. Aerua
(#/100mU
Residential: 30,000 1900(5) 100(5) 600(5) 600(5)
(5)
Industrial' 50(5) 5800(5) 5850(5) 14,000(5) 14,300(5) 100(5)
Freeway
Paved Land- Un- Paved Lane
Sidewalks Streets scaped developed and
Shoulders
11,000(5) 920(4) 3300(5) 5400(3) 1500(9)
6,900 (5) 49 (4)
55,000(5) 100,000(5)
>2400(4) 43,000(5) 16,500(3) 2200(9)
7300 (5) 920 (4)
3600 (5) 45,000 (5)
570(5) 2100(5)
3600 (5) 6200 (5)
References:
(1) Bannerman, at al. 1983 (Milwaukee, Wl) (NURP)
(3) Pitt 1983 (Ottawa)
(4) Pitt and Bozeman 1982 (San Jose)
(5) Pitt and McLean 1986 (Toronto)
(7) STORET Site #590866-2954309 (Shop-Save-Durham, NH) (NURP)
(8) STORET Site #596296-2954843 (Huntington-Long Island, NY) (NURP)
(9) Korbringer, etal. 1981 and Gupta, et al. 1979

-------
 Table 2.15 Source Area Filterable Pollutant Concentration Summary (means)

Roof Runoff
Solids (mg/L)
Phosphorus (mg/L)
Lead (ng/L)
Paved Parking
Solids (mg/L)
Phosphorus (mg/L)
TKN (mg/L)
Lead (ng/L)
Arsenic ((ig/L)
Cadmium (ng/L)
Chromium (ng/L)
Paved Storage
Solids (mg/L)
Residential
Total Filterable % Filt.
64 42 66(1)
58 45 77 (5)
0.054 0.013 24(1)
48 4 8(1)








Commercial
Total Filterable % Filt.



240 175 73(1)
102 61 60(7)
1790 138 8(5)
0.16 0.03 19(1)
0.9 0.3 33 (2)
0.77 0.48 62 (8)
146 5 3(1)
54 8.8 16(8)
0.38 0.095 25 (8)
0.62 0.11 18(8)
11.8 2.8 24(8)
73 32 44 (5)
Industrial
Total Filterable %Filt.
113 110 97(5)


490 138 28 (5)






270 64 24 (5)
References:

(1)  Bannerman, et al. 1983 (Milwaukee)  (NURP)
(2)  Denver Regional Council of Governments 1983 (NURP)
(5)  Pitt and McLean 1986 (Toronto)
(7)  STORET Site #590866-2954309 (Shop-Save-Durham, NH) (NURP)
(8)  STORET Site #596296-2954843 (Huntington-Long Island, NY) (NURP)
                                                   38

-------
Other Pollutant Contributions to the Storm Drainage System
The detection of pentachJophenols in the relatively few samples previously analyzed indicated important leaching
from treated wood. Frequent detections of polycyclic aromatic hydrocarbons (PAHs) during the U.S. Environmental
Protection Agency's Nationwide Urban Runoff Program (EPA 1983a) may possibly indicate leaching from creosote
treated wood, in addition to fossil fuel combustion sources. High concentrations of copper, and some chromium and
arsenic observations also indicate the potential of leaching from "CCA" (copper, chromium, and arsenic) treated
wood. The significance of these leachate products in the receiving waters is currently unknown, but alternatives to
these preservatives should be considered. Many cities use aluminum and concrete utility poles instead of treated
wood poles. This is especially important considering that utility poles are usually located very close to the drainage
system ensuring an efficient delivery of leachate products. Many homes currently use wood stains containing
pentachlorophenol and other wood preservatives. Similarly, the construction of retaining walls, wood decks and
playground equipment with treated wood is common. Some preservatives (especially creosote) cause direct skin
irritation, besides contributing to potential problems in receiving waters. Many of these wood products are at least
located some distance from the storm drainage system, allowing some improvement to surface water quality by
infiltration through pervious surfaces.

Phase 1 Project Activities - Sources of Stormwater Toxicants
The first project phase of this research project included the collection and analysis of 87 urban stormwater runoff
samples from a variety of source areas under different rain conditions (Table 2.16). All of the samples were
analyzed in filtered (0.45 ^m filter) and non-filtered forms to enable partitioning of the toxicants into "particulate"
(non-filterable) and "dissolved" (filterable) forms.

Table 2.16. Numbers of Samples Collected from each Source Area Type
Local Source
Areas3
Roofs
Parking Areas
Storage Areas
Streets
Loading Docks
Vehicle Service Area
Landscaped Areas
Urban Creeks
Detention Ponds
Residential
5
2
na
1
na
na
2

Commercial/
Institutional
3
11
2
1
na
5
2

Industrial
4
3
6
4
3
na
2

Mixed

19
12
a All collected in Birmingham, AL.

Phase 1 - Analyses and Sampling
The samples listed in Table 2.16 were all obtained from the Birmingham, AL, area. Samples were obtained from
shallow flows originating from homogeneous source areas by using several manual grab sampling procedures. For
deep flows, samples were collected directly into the sample bottles. For shallow flows, a peristaltic hand operated
vacuum pump created a small vacuum in the sample bottle which then gently drew the sample directly into the
container through a Teflon™ tube. About one liter of sample was needed, split into two containers: one 500 mL
glass bottle with Teflon™ lined lid was used for the organic and toxicity analyses, and another 500 mL polyethylene
bottle was used for the metal and other analyses.

An important aspect of the first phase of this research was to evaluate the effects of different land uses and source
areas, plus the effects of rain characteristics, on sample toxicant concentrations. Therefore, careful records were
obtained of the amount of rain and the rain intensity that occurred before the samples were obtained. Antecedent dry
period data were also obtained to compare with the chemical data in a series of statistical tests.
39

-------
 All samples were handled, preserved, and analyzed according to accepted protocols (EPA 1982 and 1983b). The
 organic pollutants were analyzed using two gas chromatographs, one with a mass selective detector (GC/MSD) and
 another with an electron capture detector (GC/ECD). The pesticides were analyzed according to EPA method 505,
 while the base neutral compounds were analyzed according to EPA method 625 (but only using 100 mL samples).
 The pesticides were analyzed on a Perkin Elmer Sigma 300 GC/ECD using a J&W DB-1 capillary column (30m by
 0.32 mm ID with a 1 ^m film thickness). The base neutrals were analyzed on a Hewlett Packard 5890 GC with a
 5970 MSD using a Supelco DB-5 capillary column (30m by 0.25 mm ID with a 0.2 urn film thickness). Table 2.17
 lists the organic toxicants that were analyzed.
 Table 2.17. List of Toxic Pollutants Analyzed in Samples
Pesticides
DL = 0.3 ug/L
BHC (Benzene
hexachloride)

Heptachlor

Aldrin

Endosulfan

Heptachlor epoxide

DOE (Dichlorodiphenyl
dichloroethylene)
ODD (Dichlorodiphenyl
dichloroethane)

DDT (Dichlorodiphenyl
trichloroelhane)
Endrin
Chtordane
Phthalate Esters
DL = 0.5pg/L
Bis(2-ethylhexyl) Phthalate

Butyl benzyl phthalate

Di-n-butyl phthalate

Diethyl phthalate

Dimethyl phthalate

Di-n-octyl phthalate









Poly nuclear Aromatic Hydrocarbons Metals
DL =
Acenaphthene

Acenapthylene

Anthracene

Benzo (a) anthracene

Benzo (a) pyrene

Benzo (b) fluoranthene

Benzo (ghi) perylene
Benzo (k) fluoranthene

Chrysene

Dibenzo (a,h) anthracene


0.5 pg/L DL = 1 ug/L
Fluoranthene Aluminum

Fluorene Cadmium

Indeno (1 ,2,3-cd) Chromium
pyrene
Copper
Naphthalene
Lead
Phenanthrene
Nickel
Pyrene
Zinc







D.L. = Detection Limit
Metallic toxicants, also listed in Table 2.17, were analyzed using a graphite furnace equipped atomic absorption
spectrophotometer (GFAA). EPA methods 202.2 (Al), 213.2 (Cd), 218.2 (Cr), 220.2 (Cu), 239.2 (Pb), 249.2 (Ni),
and 289.2 (Zn) were followed in these analyses. A Perkin Elmer 3030B atomic absorption spectrophotometer was
used after nitric acid digestion of the samples. Previous research (Pitt and McLean 1986; EPA 1983a) indicated that
low detection limits were necessary in order to measure the filtered sample concentrations of the metals, which
would not be achieved by use of a standard flame atomic absorption spectrophotometer. Low detection limits would
enable partitioning of the metals between the solid and liquid phases to be investigated, an important factor in
assessing the fates of the metals in receiving waters and in treatment processes.

The Microtox™ 100% sample toxicity screening test, from Azur Environmental (previously Microbics, Inc.), was
selected for this research after comparisons with other laboratory bioassay tests. During the  first research phase,
twenty source area stormwater samples and combined sewer samples (obtained during a cooperative study being
conducted in New York City) were split and sent to four laboratories for analyses using 14 different bioassay tests.
Conventional bioassay tests were conducted using freshwater organisms at the EPA's Duluth, MM, laboratory and
using marine organisms at the EPA's Narraganssett Bay, RI, laboratory. In addition, other bioassay tests, using
bacteria, were also conducted at the Environmental Health Sciences Laboratory at Wright State University, Dayton,
Ohio. The tests represented a range of organisms that included fish, invertebrates, plants, and microorganisms.
                                                   40

-------
The conventional bioassay tests conducted simultaneously with the Microtox™ screening test for the 20 stormwater
sheetflow and combined sewer overflow (CSO) samples were all short-term tests. However, some of the tests were
indicative of chronic toxicity (life cycle tests and the marine organism sexual reproduction tests, for example),
whereas the others would be classically considered as indicative of acute toxicity (Microtox™ and the fathead
minnow tests, for example). The following list shows the major tests that were conducted by each participating
laboratory:

• University of Alabama at Birmingham, Environmental Engineering Laboratory
Microtox™ bacterial luminescence tests ( 10-, 20-, and 35-minute exposures) using the marine
Photobacterium phosphoreum.

• Wright State University, Biological Sciences Department
Macrofaunal toxicity tests:
Daphnia magna (water flea) survival; Lemma minor (duckweed) growth; and Selenastrum
capricornutum (green alga) growth.
Microbial activity tests (bacterial respiration):
Indigenous microbial electron transport activity;
Indigenous microbial inhibition of p-galactosidase activity;
Alkaline phosphatase for indigenous microbial activity;
Inhibition of P-galactosidase for indigenous microbial activity; and
Bacterial surrogate assay using Onitrophenol-p-D-galactopyranside activity and Escherichia coli.

• EPA Environmental Research Laboratory, Duluth, Minnesota
Ceriodaphnia dubia (water flea) 48-h survival; and
Pimephales promelas (fathead minnow) 96-h survival.

• EPA Environmental Research Laboratory, Narragansett Bay, Rhode Island
Champia parvula (marine red alga) sexual reproduction (formation of cystocarps after 5 to 7 d
exposure); and
Arbacuapunctulata (sea urchin) fertilization by sperm cells.

Table 2.18 summarizes the results of the toxicity tests. The C. dubia. P. promelas, and C. Parvula tests experienced
problems with the control samples, and those results are therefore uncertain. The A. pustulata tests on the
stormwater samples also had a potential problem with the control samples. The CSO test results (excluding the
fathead minnow tests) indicated that from 50% to 100% of the samples were toxic, with most tests identifying the
same few samples as the most toxic. The toxicity tests for the stormwater samples indicated that 0% to 40% of the
samples were toxic. The Microtox™ screening procedure gave similar rankings for the samples as the other toxicity
tests.

Table 2.18. Fraction of Samples Rated as Toxic

Sample series Combined sewer Stormwater, %
overflows, %
Microtox™ marine bacteria 100 20
C. Dubia 60 Oa
P. promelas 0' Oa
C. parvula 100 Oa
A. punctulata 100 Oa
D. magna 63 40
L minor 50^ 0__

" Results uncertain, see text
41

-------
Laboratory toxicity tests can result in important information on the effects of stormwater in receiving waters, but
actual in-stream taxonomic studies should also be conducted. A recently published proceedings of a conference on
stormwater impacts on receiving streams (Herricks 1995) contains many examples of actual receiving water impacts
and toxicity test protocols for stormwater.

All of the Birmingham samples represented separate stormwater. However, as part of the Microtox™ evaluation,
several CSO samples from New York City were also tested to compare the different toxicity tests. These samples
were collected from six CSO discharge locations having the following land uses:

• 290 acres, 90% residential and 10% institutional;
• 50 acres, 100% commercial;
• 620 acres, 20% institutional, 6% commercial, 5% warehousing, 5% heavy industrial, and 64% residential;
• 225 acres, 13% institutional, 4% commercial, 2% heavy industrial, and 81% residential:
• 400 acres, 1% institutional and 99% residential; and
• 250 acres, 88% commercial. 6% warehousing, and 6% residential.

Therefore, there was a chance that some of the CSO samples may have had some industrial process waters.
However, none of the Birmingham sheetflow samples could have contained any process waters because of how and
where they were collected.

The Microtox™ screening procedure gave similar toxicity rankings for the twenty samples as the conventional
bioassay tests. It is also a rapid procedure (requiring about one hour) and only requires small (<1 mL) sample
volumes. The Microtox™ toxicity test uses marine bioluminescence bacteria and monitors the light output for
different sample concentrations. About one million bacteria organisms are used per sample, resulting in highly
repeatable results. The more toxic samples produce greater stress on the bacteria test organisms that results in a
greater light attenuation compared to the control sample. It should be emphasized that the Microtox™ procedure was
not used during this research to determine the absolute toxicities of the samples, or to predict the toxic effects of
stormwater runoff on receiving waters, but to compare the relative toxicities of different samples that may indicate
efficient source area treatment locations, and to examine changes in toxicity during different treatment procedures.

Phase 1 - Potential Sources
A drainage system captures runoff and pollutants from many source areas, all with individual characteristics
influencing the quantity of runoff and pollutant load. Impervious source areas may contribute most of the runoff
during small storm events (e.g., paved parking lots, streets, driveways, roofs, sidewalks, etc.). Pervious source areas
can have higher material washoff potentials and become important contributors for larger storm events when their
infiltration rate capacity is exceeded (e.g., gardens, bare ground, unpaved parking areas, construction sites,
undeveloped areas, etc.). Many other factors also affect the pollutant contributions from source areas, including:
surface roughness, vegetative cover, gradient, and hydraulic connections to a drainage system; rainfall intensity,
duration, and antecedent dry period; and pollutant availability due to direct contamination from local activities,
cleaning frequency/efficiency, and natural and regional sources of pollutants. The relative importance of the
different source areas is therefore a function of the area characteristics, pollutant washoff potential, and the rainfall
characteristics (Pitt 1987).

Important sources of toxicants are often related to the land use (e.g., high traffic capacity roads, industrial processes,
and storage area) that are unique to specific land uses activities. Automobile related sources affect the quality and
quantity of road dust particles through gasoline and oil drips/spills; deposition of exhaust products; and wear of tire,
brake, and pavement materials (Shaheen 1975). Urban landscaping practices potentially produce vegetation cuttings
and fertilizer and pesticide washoff. Miscellaneous sources include holiday firework debris, wildlife and domestic
pet wastes, and possible sanitary wastewater infiltration. In addition, resuspension and deposition of
pollutants/particles via the atmosphere can increase or decrease the contribution potential of a source area (Pitt and
Bozeman 1982; Bannerman, etal. 1993).

Phase 1 - Results
Table 2.19 summarizes the source area sample data for the most frequently detected organic toxicants and for all of
the metallic toxicants analyzed. The organic toxicants analyzed, but not reported, were generally detected in 5, or
42

-------
less, of the non-filtered samples and in none of the filtered samples. Table 2.19 shows the mean, maximum, and
minimum concentrations for the detected toxicants. It is important to note that these values are only based on the
observed concentrations only. They do not consider the non-detectable conditions. Mean values based on total
sample numbers for each source area category would therefore result in much lower concentrations. The frequency
of detection is therefore an important consideration when evaluating organic toxicants. High detection frequencies
for the organics may indicate greater potential problems than infrequent high concentrations.

Table 2.19 also summarizes the measured pH and SS concentrations. Most pH values were in the range of 7.0 to 8.5
with a low of 4.4 and a high of 11.6 for a roof and concrete plant storage area runoff sample, respectively. This
range of pH can have dramatic effects on the speciation of the metals analyzed. The SS concentrations were
generally less than 100 mg/L, with impervious area runoff (e.g., roofs and parking areas) having much lower SS
concentrations and turbidities compared to samples obtained from pervious areas (e.g., landscaped areas).

Thirteen organic compounds, out of more than thirty-five targeted compounds analyzed, were detected in more than
10 percent of all samples, as shown in Table 2.19. The greatest detection frequencies were for 1,3-dichlorobenzene
and fluoranthene, which were each detected in 23 percent of the samples. The organics most frequently found in
these source area samples (i.e., polycyclic aromatic hydrocarbons (PAH), especially fluoranthene and pyrene) were
similar to the organics most frequently detected at outfalls in prior studies (EPA 1983a).

Roof runoff, parking area and vehicle service area samples had the greatest detection frequencies for the organic
toxicants. Vehicle service areas and urban creeks had several of the observed maximum organic compound
concentrations. Most of the organics were associated with the non-filtered sample portions, indicating an association
with the particulate sample fractions. The compound 1,3-dichlorobenzene was an exception, having a significant
dissolved fraction.

In contrast to the organics, the heavy metals analyzed were detected in almost all samples, including the filtered
sample portions. The non-filtered samples generally had much higher concentrations, with the exception of zinc
which was mostly associated with the dissolved sample portion (i.e., not associated with the SS). Roof runoff
generally had the highest concentrations of zinc, probably from galvanized roof drainage components, as previously
reported by Bannerman, et al. (1983). Parking and storage areas had the highest nickel concentrations, while vehicle
service areas and street runoff had the highest concentrations of cadmium and lead. Urban creek samples had the
highest copper concentrations, which were probably due to illicit industrial connections or other non-stormwater
discharges.

Table 2.20 shows the relative toxicities of the collected stormwaters. A wide range of toxicities were found. About
9% of the non-filtered samples were considered highly toxic using the Microtox™ toxicity screening procedure.
About 32% of the samples were moderately toxic and about 59% were considered non-toxic. The greatest
percentage of samples considered the most toxic were from industrial storage and parking areas. Landscaped areas
also had a high incidence of highly toxic samples (presumably due to landscaping chemicals), and roof runoff had
some highly toxic samples (presumably due to high zinc concentrations). The phase 2 treatability study activities
indicated that filtering the samples through a range of fine sieves and finally a 0.45um filter consistently reduced
sample toxicities. The chemical analyses also generally found much higher toxicant concentrations in the non-
filtered sample portions, compared to the filtered sample portions.

Replicate samples were collected from several source areas at three land uses during four different storm events to
statistically examine toxicity and pollutant concentration differences due to storm and site conditions. These data
indicated that variations in Microtox™ toxicities and organic toxicant concentrations may be partially explained by
rain characteristics. As an example, high concentrations of many of the PAHs were associated with long antecedent
dry periods and large rains (Barren 1990).
43

-------
Table 2.19. Stormwater toxicants detected In at least 10% of the source area sheetflow samples (ng/L, unless otherwise noted).
Parking Storage Street Loading
Roof areas areas areas runoff docks
N.F.a F.b N.F. F. N.F. F. N.F. F. N.F. F.
Total samples 12 12 16 16 8 8 6633
Base neutrals (detection limit = 0.5 ng/L)
1,3-Dichlorobenzene detection frequency = 20% N.F. and 13% F.
No. detected0 32 32111100
Mean" 52 20 34 13 16 14 5.4 3.3
Max. 88 23 103 26
Min.6 14 17 3.0 2.0
Fluoranthene detection frequency = 20% N.F. and 12% F.
No. detected 32 3210 1100
Mean 23 9.3 37 2.7 4.5 0.6 0.5
Max. 45 14 110 5.4
Min. 7.6 4.8 3.0 2.0
Pyrene detection frequency = 17% N,F, and 7% F.
No. detected 10 3210 1100
Mean 28 40 9.8 8 1.0 0.7
Max. 120 20
Min. 3.0 2.0
Benzo(b)fluoranthene detection frequency = 15% N.F. and 0% F.
No. detected 40 3000 1000
Mean 76 53 14
Max. 260 160
Min. 6.4 3.0
Benzo(k)fluoranthene detection frequency = 11% N.F. and 0% F.
No. detected 00 30001000
Mean 20 15
Max. 1
Min. 3.0
Benzo(a)pyrene detection frequency = 15% N.F. and 0% F.
No. detected 40 30001000
Mean 99 40 19
Max. 300 120
Min. 34 3.0
Vehicle
service
areas
N.F. F.
5


3
48
72
6.0

3
39
53
0.4

3
44
51
0.7

2
98
110
90

2
59
103
15

2
90
120
60
5


2
26
47
4.9

2
3.6
6.8
0.4

2
4.1
7.4
0.7

0




0




0



Landscaped
areas
N.F. F.
6


3
29
54
4.5

3
13
38
0.7

2
5.3
8.2
2.3

1
30



1
61



1
54


6


2
5.6
7.5
3.8

2
1.0
1.3
0.7

0




0




0




0



Urban
creeks
N.F. F.
19 19


2 0
93
120
65

1 0
130



1 0
100



2 0
36
64
8.0

2 0
55
78
31

2 0
73
130
19
Detention
ponds
N.F. F.
12


1
27



2
10
14
6.6

2
31
57
6.0

0




0




0



12


1
21



1
6.6



1
5.8



0




0




0

-------
Table 2.19. Continued).
Parking Storage Street Loading
Roof areas areas areas runoff docks
N.F.a F.b N.F. F. N.F. F. N.F. F. N.F. F.
Total samples 12 12 16 16 8 8 6633
Bis(2-chloroethyl) ether detection frequency = 12% N.F. and 2% F.
No. detected 31 2000 1000
Mean 42 17 20 15
Max. 87 2 39
Min. 20 2.0
Bis(chloroisopropyl) ether detection frequency = 13% N.F. and 0% F.
No. detected 30 3000 0000
Mean 99 130
Max. 150 400
Min. 68 3.0
Naphthalene detection frequency = 11% N.F. and 6% F.
No. detected 20 1100 0000
Mean 17 72 6.6
Max. 21
Min. 13
Benzo(a)anthracene detection frequency = 10% N.F. and 0% F.
No. detected 10 3000 0000
Mean 1 6 24
Max. 73
Min. 3.0
Butylbenzyl phthalate detection frequency = 10% N.F. and 4% F.
No. detected 10 2100 0000
Mean 100 12 3.3
Max. 21
Min. 3.3
Pesticides (detection limit = 0.3 ng/L)
Chlordane detection frequency = 11% N.F. and 0% F.
No detected 20 20 301000
Mean 1.6 1.0 1.7 0.8
Vehicle
service Landscaped
areas areas
N.F. F. N.F. F.
556 6

1110
45 23 56



2010
120 85
160
74

2110
70 82 49
100
37

2010
35 54
39
31

2210
26 9.8 130
48 16
3.8 3


1 000
0.8
Urban Detention
creeks ponds
N.F. F. N.F. F.
19 19 12 12

1010
200 15



200 0
59
78
40

1122
300 6.7 43 12
68 17
18 6.6

1000
61



1010
59 13




0000

Max.            2.2              1.2           2.9
Min.            0.9              0.8           1.0

-------
Table 2.19. Continued).
Parking Storage
Roof areas areas areas
N.F.a F.b N.F. F. N.F. F.
Total samples 12 12 16 16 8
Metals (detection limit = 1 ng/L)
Lead detection frequency = 100% N.F. and 54% F.
No. detected 121 16 8 8
Mean 41 1.1 46 2.1 105
Max. 170 130 5.2 330
Min. 1.3 1.0 1.2 3.6
Zinc detection frequency = 99% N.F. and 98% F.
No. detected 12 12 16 16 8
Mean 250 220 110 86 1730
Max. 1580 1550 650 560 13100
Min. 11 9 12 6 12
Copper detection frequency = 98% N.F. and 78% F.
No. detected 1 1 7 15 13 8
Mean 110 2.9 116 11 290
Max. 900 8.7 770 61 1830
Min. 1.5 1.1 10 1.1 10
Aluminum detection frequency = 97% N.F. and 92% F.
No. detected 12 12 15 15 7
Mean 6850 230 3210 430 2320
Max 71300 1550 6480 2890 6990
Min. 25 6.4 130 5.0 180
Cadmium detection frequency = 95% N.F. and 69% F.
No. detected 1 1 7 15 9 8
Mean 3.4 0.4 6.3 0.6 5.9
Max. 30 0,7 70 1.8 17
Min. 0.2 0.1 0.1 0.1 0.9
Chromium detection frequency = 91% N.F. and 55% F.
No. detected? 2 15 8 8
Mean 85 1.8 56 2.3 75
Max. 510 2.3 310 5.0 340
Min. 5.0 1,4 2.4 1.1 3.7
8


7
2.6
5.7
1.6

7
22
100
3.0

6
250
1520
1.0

6
180
740
10

7
2.1
10
0.3

5
11
32
1.1
Street
runoff
N.F. F.
6


6
43
150
1.5

6
58
130
4.0

6
280
1250
10

6
3080
10040
70

6
37
220
0.4

5
9.9
30
2.8
6


4
2.0
3.9
1.1

6
31
76
4.0

5
3.8
11
1.0

6
880
4380
18

5
0.3
0.6
0.1

4
1,8
2.7
1.3
Loading
docks
N.F, F,
3


3
55
80
25

2
55
79
31

3
22
30
15

3
780
930
590

3
1.4
2.4
0.7

3
17
40
2.4
3


1
2.3



2
33
62
4.0

2
8.7
15
2.6

1
18



3
0.4
0.6
0.3

0



Vehicle
service
areas
N.F. F.
5


5
63
110
27

5
105
230
30

5
135
580
1.5

5
700
1370
93

5
9.2
30
1.7

5
74
320
2.4
5


2
2.4
3.4
1.4

5
73
230
11

4
8.4
24
1.1

4
170
410
0.3

3
0.3
0.5
0.2

1
2.5


Landscaped
areas
N.F. F.
6


6
24
70
1.4

6
230
1160
18

6
81
300
1.9

5
2310
4610
180

4
0.5
1
0.1

6
79
250
2.2
6


1
1.7



6
140
670
18

6
4.2
8.8
O.i

5
1210
1880
120

2
0.6
1
0.1

5
2.0
4.1
1.4
Urban
creeks
N.F. F.
19


19
20
100
1.4

19
10
32
<1

19
50
440
<1

19
620
19


15
1.4
1.6
<1

19
10
23
<1

17
1.4
1.7
<1

19
190
3250 500
<5

19
8.3
30
<0.1

19
62
710
<0.1
<5

15
0.2
0.3
<0.1

15
1.6
4.3
<0.1
Detention
ponds
N.F. F,
12


12
19
55
1

12
13
25
<1

12
43
210
0.2

12
700
1570
<5

12
2
11
0.1

11
37
230
<0.1
12


8
1.0
1.0
<1

12
14
25
<1

8
20
35
<1

12
210
360
<5

9
0.5
0.7
0.4

8
2.0
3.0
<0.1

-------
Table 2.19. Continued).
Roof areas
N.F.a F.b
Total samples 12 12
Nickel detection frequency =
No. detected 10 0
Mean 16
Max. 70
Min 2.6
Other constituents (always
pH
Mean 6.9
Max. 8.4
Min 4.4
Suspended solids
Mean 14
Max. 92
Min. 0.5
Parking Storage
areas areas
N.F. F. N.F. F.
16 16 8 8
90% N.F.
14
45
130
4.2
detected,

7.3
8.7
5.6

110
750
9.0
and 37% F.
4 8 1
5.1 55 87
13 170
1.6 1.9
Vehicle
Street Loading service
runoff docks areas
N.F. F. N.F. F. N.F. F.
6

5
17
70
1.2
analyzed only for non-filtered

8.5
12
6.5

100
450
5.0

7.6
B.4
6.9

49
110
7.0
6 3

0 3
6.7
8.1
4.2
samples)

7.8
8.3
7.1

40
47
34
355

1 5 1
1.3 42 31
70
7.9


7.2
8.1
5.3

24
38
17
Landscaped
areas
N.F. F.
6 6

4 1
53 2.1
130
21


6.7
7.2
6.2

33
81
8.0
Urban
creeks
N.F. F.
19 19

18 16
29 2.3
74 3.6
<1 <1


7.7
8.6
6.9

26
140
5.0
Detention
ponds
N.F. F.
12

11
24
70
1.5


8.0
9.0
7.0

17
60
3.0
12

8
3.0
6.0
<1









aN.F/. concentration associated with a nonfiltered sample.
b F.: concentration after the sample was filtered through a 0.45 urn membrane filter.
c Number detected refers to the number of samples in which the toxicant was detected.
d Mean values based only on the number of samples with a definite concentration of toxicant reported (not on the total number of samples analyzed).
0 The minimum values shown are the lowest concentration detected, they are not necessarily the detection limit.

-------
Table 2.20. Relative Toxicity of Samples Using Microtox™ (Non-filtered)
Local Source
Areas
Roofs
Parking Areas
Storage Areas
Streets
Loading Docks
Vehicle Service Areas
Landscaped Areas
Urban Creeks
Detention Ponds
All Areas
Highly
Toxic
(%)
8
19
25
0
0
0
17
0
8
9%
Moderately
Toxic
(%)
58
31
50
67
67
40
17
11
8
32%
Not
Toxic
(%)
33
50
25
33
33
60
66
89
84
59%
Number
of
Samples
12
16
8
6
3
5
6
19
12
87
                 Microbics suggested toxicity definitions for 35 minute exposures:
                         Highly Toxic - light decrease >60%
                         Moderately Toxic - light decrease <60% & >20%
                         Not Toxic - light decrease <20%
                                                  48

-------
Chapter 3

Laboratory-Scale Toxicant Reduction Tests

The phase 2 activities of this project examined methods to reduce stormwater toxicity from critical source areas
using a variety of conventional bench-scale treatment processes. The data from phase 1 identified the critical source
areas which generally had the highest toxicant concentrations for study during this research phase. The critical
source areas targeted for this additional study were storage/parking and vehicle service areas.

Phase 2 - Analysis and Sampling
The objective of this second research phase was to quantify improvements in stormwater toxicity using different
stages of several bench-scale treatment methods. These data were used to indicate the relative effectiveness of
different treatment efforts and processes. To meet this objective and the resource restraints of cost and time, the
Azur Environmental (previously Microbics, Inc.) Microtox™ screening toxicity test was chosen to indicate the
relative changes in toxicity.

The efficiency of many pollution control devices is affected by the particle sizes and settling velocity distributions of
the pollutants in the wastewater. Therefore, settling column tests were conducted to determine the pollutant settling
velocities. Standard gravimetric solids analyses (EPA 1983b) were conducted on the settling column samples to
calculate the settling velocities and specific gravities of the particulates. Nephelometric turbidity analyses were also
conducted (EPA 1983b) for all subsamples during the treatability tests.

Samples were collected in the same manner from the critical source areas selected for testing as described in phase
1, but a larger volume of sample (10 to 20 liters) was collected from each location.

Phase 2 - Experimental Error
The second phase included intensive analyses of samples from twelve sampling locations in the Birmingham, AL,
area. Table 3.1 lists the sampling dates, source area categories, and relative toxicity category prior to treatment.
These sampled storms represent practically all of the rains that occurred during the field portion of the second
project phase (July-November, 1990). Independent replicates (obtained during separate analysis runs) were used to
determine the measurement errors associated with the Microtox™ procedure. The total number of Microtox™
analyses that were conducted for all of the treatability tests for each sample is also noted, as are the means, standard
deviations, and coefficients of variation of the replicate toxicity values.

The initial toxicity values (before treatability tests) were plotted on normal-probability paper to indicate their
probability distribution characteristics. Almost all of the samples had initial toxicity values that were shown to be
normally distributed. Therefore, the coefficient of variation (COV = standard deviation/mean) values shown on
Table 3.1 can be used as an indication of the confidence intervals of the Microtox™ measurements. The COVs
ranged from 2.3 to 9.8 percent, with an average value of 5.1 percent. Therefore, the 95 percent confidence interval
(two times the COV values include 95.4 percent of the data, if normally distributed) for the Microtox™ procedure
ranged between 5 and 20 percent of the mean values. These confidence intervals are quite narrow for a bioassay test
and indicate the good repeatability of the Microtox™ procedure. In all cases, statistical tests were performed on the
test results to indicate the significance of the different treatability tests.

Table 3.1 also shows that samples B and D were initially extremely toxic, while the remainder of the samples were
moderately toxic. All samples were reduced to "non-toxic" levels after various degrees of treatment.
49

-------
Table 3.1. Phase 2 Treatability Sample Descriptions
Sample Date Initial Number of Standard
Source Toxicity" Analyses Deviation6
(%)
Automobile Service Area Samples
B 7/10/90 78 28 7.6
C 7/21/90 34 42 2.9
E 8/19/90 43 74 1.3
H 10/17/90 50 88 1.5
Industrial Loadinq & Parking Area Samples
D 8/2/90 67 74 2.1
F 9/12/90 31 88 1.5
G 10/3/90 53 88 3.0
I 10/24/90 55 89 1.9
J 11/5/90 49 89 1.1
K 11/9/90 28 89 2.2
Automobile Salvage Yard Samples
L 11/28/90 26 89 1.4
M 12/3/90 54 89 1.8
Coefficient of
Variation"
(%)
9.8
8.5
3.0
3.0
3.1
4.9
5.7
3.4
2.3
8.1
5.5
3.4
" Toxicity measured as percent light reduction after 35 minute exposure.
b Applies to replicate samples only.

Phase 2 - Treatability Tests
The selected source area runoff samples all had elevated toxicant concentrations, compared to the other urban source
areas initially examined, allowing a wide range of laboratory partitioning and treatability analyses to be conducted.
The treatability tests conducted were:

• Settling column (37 mm x 0.8 m Teflon™ column).
• Floatation (series of eight glass narrow neck 100 mL volumetric flasks).
• Screening and filtering (series of eleven stainless steel sieves, from 20 to 106 um, and a 0.45 urn
membrane filter).
• Photo-degradation (2 liter glass beaker with a 60 watt broad-band incandescent light placed 25
cm above the water, stirred with a magnetic stirrer with water temperature and evaporation rate
also monitored).
• Aeration (the same beaker arrangement as above, without the light, but with filtered compressed
air keeping the test solution supersaturated and well mixed).
• Photo-degradation and aeration combined (the same beaker arrangement as above, with
compressed air, light, and stirrer).
• Undisturbed control sample (a sealed and covered glass jar at room temperature).

Because of the difficulty of obtaining large sample volumes from many of the source areas that were to be
examined, these bench-scale tests were all designed to use small sample volumes (about one liter per test). Each test
(except for filtration, which was an "instantaneous" test) was conducted over a duration of 3 d. Subsamples (40 mL
each) were obtained for toxicity analyses at 0, 1, 2, 3, 6, 12, 24,48, and 72 h. In addition, settling column samples
were also obtained several times within the first hour, at: 1,3,5, 10, 15,25, and 40 minutes.

Phase 2 - Results
The Microtox™ procedure allowed toxicity screening tests to be conducted on each sample partition during the
treatment tests. This procedure enabled more than 900 toxicity tests to be made. Turbidity tests were also conducted
on all samples.

Figures 3.1 to 3.24 (placed at end of chapter) are graphical data plots of the toxicity reductions observed during each
treatment procedure examined, including the control measurements. These figures are grouped in threes for each
treatment type. One group contains the treatment responses for the automobile service facility areas (samples B, C,
E, and H), another group is for the industrial loading and parking areas (samples D, F, G, I, J, and K), and the last
group is for the automobile salvage yards (samples L and M). These plots indicate the reduction in toxicity as the
50

-------
level of treatment increased. As an example, Figures 3.1 through 3.3 show three separate plots for the undisturbed
samples undergoing very little change, except for samples F (which increased in toxicity with time) and C (which
decreased in toxicity with time). In contrast, Figures 3.4 through 3.6 show the dramatic improvements available with
plain physical settling. All samples, except for B, showed dramatic reductions in toxicity with increasing settling
times. Even though the data are separated into these three groups, very few consistent differences are noted in the
way the different sample types responded to various treatments. As expected, there are greater apparent differences
between the treatment methods than between the sample groupings.

Table 3.2 summarizes results from the non-parametric Wilcoxon signed ranks test (using SYSTAT: The System for
Statistics, Version 5, SYSTAT, Inc., Evanston, 111.) for different treatment combinations. This statistical test
indicates the two-sided probabilities that the sample groups are the same. A probability of 0.05, or less, is used to
indicate significant differences in the data sets (indicated by bold italics in the table). As an example, Table 3.2
indicates that there were significant differences (probabilities of 0.02) for all of the treatment tests done on sample D
(an extremely toxic sample), compared to the undisturbed control sample.
Table 3.2. Two-sided Probabilities Comparing Different Treatment Tests

Auto. Service Area Industrial Loading & Parking Area
Auto. Salvage
Undisturbed versus:
settling
aeration
photodegradation
aeration &
photodegradation.
flotation - top layer
flotation - mid. layer
B C E H
n/a 0.25 0.02 0.41
n/a 0.31 0.25 0.07
n/a 0.12 0.06 0.16
n/a 0.35 0.24 0.06
n/a n/a 0.74 0.02
n/a n/a 0.31 0.87
D F G I J K
0.02 0.12 0.09 0.07 0.01 0.01
0.02 0.05 0.06 0.04 0.01 0.01
0.02 0.04 0.03 0.07 0.01 0.01
0.02 0.05 0.03 0.09 0.01 0.01
0.02 0.05 0.13 0.01 0.03 0.21
0.02 0.78 0.02 0.26 0.16 0.17
L M
0.02 0.02
0.02 0.03
0.02 0.16
0.02 0.09
0.01 0.09
0.59 0.89
The aeration test provided the most samples that had significant probabilities of being different from the control
condition. Settling, photo-degradation, and aeration and photo-degradation combined, were similar in providing the
next greatest number of samples that had significant probabilities of being different from the control condition. The
floatation test had six samples that had significant differences in toxicity between the top floating layer and the
control sample. However, the more important contrast between the middle sample layers (below the top floating
layer) and the control sample, which would indicate a reduction in toxicity of post-treated water, had only two
samples that were significantly different from the control sample.

The absolute magnitudes of toxicity reductions must also be considered. As an example, it may be significant, but
unimportant, if a treatment test provided many (and therefore consistent) samples having statistically significant
differences compared to the control sample, if the actual toxicity reductions were very small.

As shown on Figures 3.1 to 3.24, important reductions in toxicities were found during many of the treatment tests.
The highest toxicant reductions were obtained by settling for at least 24 h (providing at least 50 percent reductions
for all but 2 samples), screening through at least a 40 um screen (20-70 percent reductions), and aeration and/or
photo-degradation for at least 24 h (up to 80 percent reductions). Increased settling, aeration or photo-degradation
times, and screening through finer meshes, all reduced sample toxicities further. The floatation tests produced
floating sample layers that generally increased in toxicity with time and lower sample layers that generally
decreased in toxicity with time, as expected; however, the benefits were quite small (less than 30 percent
reductions). As shown on Table 3.2, only about 40% of the floatation test toxicity changes were statistically
different from the variations found in the control samples.

These tests indicate the wide ranging behavior of these related samples for the different treatment tests. Some
samples responded poorly to some tests, while other samples responded well to all of the treatment tests. Any
practical application of these treatment unit processes would therefore require a treatment train approach, subjecting
critical source area runoff to a combination of processes in order to obtain relatively consistent overall toxicant
reduction benefits. The next three chapters describe a treatment train that was evaluated to reduce critical source
area stormwater toxicity.
51