Performance and Operation of Partial Infiltration Permeable Pavement

Systems in the Ontario Climate

by

Jennifer Anne Pauline Drake

A Thesis

presented to

The University of Guelph

In partial fulfilment of requirements

for the degree of

Doctorate of Philosophy

in

Engineering

Guelph, Ontario, Canada

© Jennifer Drake, June, 2013

ABSTRACT

PERFORMANCE AND OPERATION OF PARTIAL-INFILTRATION PERMEABLE

PAVEMENT SYSTEMS IN THE ONTARIO CLIMATE

Jennifer A. P. Drake Advisor:

University of Guelph, 2013 Dr. Andrea Bradford

Partial-infiltration permeable pavement (PP) systems provide environmental

benefits by increasing infiltration, attenuating storm flows and improving stormwater

quality. This thesis focuses on the performance and operation of partial-infiltration PP

systems over low permeability soil in Ontario. Three PP, AquaPave®, Eco-Optiloc® and

Hydromedia® Pervious Concrete were monitored over two years and their performance

was evaluated relative to an impermeable Asphalt control. Field data was collected from

the Kortright PP pilot parking lot in Vaughan, Ontario. Through the use of restrictor

valves on underdrains the PP systems were shown to provide substantial hydrologic

benefits by eliminating stormwater outflow for rain events less than 7mm, reducing peak

flows by 91% and reducing total stormwater volume by 43%. Stormwater quality was

analyzed for winter and non-winter seasons. The PP were shown to greatly reduce the

concentration and total loading of suspended solids, nutrients, hydrocarbons and most

heavy metals. Some water quality data, such as pH, K, or Sr levels, indicate that the quality

of PP effluent will change as the system ages. Study of PP sample boxes at the University of

Guelph highlighted the role that construction materials have on effluent quality and

showed that pollutants introduced by the pavement and aggregate are almost entirely in a

dissolved form and decline very rapidly after a season of exposure to rainfall. Benefits to

water quality were sustained during winter months. The partial-infiltration PP systems

were shown to provide buffering of Na and Cl concentrations. Small and large-scale

maintenance practices for PP systems were investigated. Small-sized equipment testing

found that vacuum cleaning and pressure-washing have good potential to improve

infiltration capacity. Testing of full-sized streetsweeping trucks demonstrated that

permeability can be partially restored on PICP by suction-based sweeping. Vacuum-

sweeping was beneficial on a PC pavement which had experienced large permeability

losses. Results of this study indicate that partial-infiltration PP systems can be effective

measures for maintaining or restoring infiltration functions on parking lots and other low

volume traffic areas, even in areas with low permeability soils.

iv

ACKNOWLEGDMENTS I would first like to thank Dr. Andrea Bradford for offering me the opportunity to perform this

research. I would also like to thank Dr. Jiri Marsalek and Dr. Doug Joy for providing many

helpful suggestions and guidance throughout the preparation of this thesis.

This research would not have been possible without the investment of the Sustainable

Technologies Evaluation Program (STEP) at the Toronto and Region Conservation Authority

(TRCA) and without the hard work and collaboration of Mr. Tim Van Seters, his staff: Christy

Graham, Paul Greck, Matt Derro and Amanda Wilson, as well as Mr. Glenn MacMillian. It has

been a pleasure to work with everyone at TRCA and I hope that TRCA will continue to create

research opportunities for graduate students in the future. I have also been supported by fantastic

staff at the School of Engineering and would like to personally thank Barry, Joanne, Lucy, Ryan

and Ken. Thank you to many friends (Ashraf, Chris, Mark, Peter, Andy, Hailey and Vicki) who

have volunteered their time and support.

Financial support for this project was generously provided by the following organizations; Great

Lakes Sustainability Fund, Toronto and Region Remedial Action Plan, Ontario Ministry of the

Environment Best in Science Program, Ontario Ministry of Transportation, City of Toronto,

Region of Peel, York Region, Metrus Development Inc., Interlocking Concrete Paving Institute

and AECON. In kind-donations of services and materials were generously provided by the

following organizations: Urban Ecosystems Limited (Engineering consulting services), Brown’s

Concrete (Aquapave®), Unilock (Eco-Optiloc®), Lafarge (Hydromedia® Pervious Concrete),

Hanson (sampling vault), Ontario Ministry of the Environment (laboratory services), Armtec

(pipes), Condrain (construction services), Dufferin Aggregates (aggregate base), and Layfield

Plastics (liner).

Use and operation of the Elgin Whirlwind vacuum truck was provided by Joe Johnson

Equipment, Innisfil, Ontario. Use and operation of the Tymco DST-6 truck was provided by The

Equipment Specialists Inc., Hamilton, Ontario. Access to parking lots was provided by GO

Transit, Earth Rangers, MTO, The Town of Richmond Hill, St. Andrew’s Parish, TRCA,

Exhibition Place and Seneca College. Additional technical services were provided by the

Sustainable Technologies Evaluation Program (STEP) through TRCA, the Toronto and Region

Conservation Authority.

Finally, thank you (for so many reasons) to my husband and inspiration, Dr. Bennett Banting.

v

TABLE OF CONTENTS ABSTRACT ................................................................................................................................... iv

ACKNOWLEGDMENTS ............................................................................................................. iv

LIST OF TABLES ......................................................................................................................... ix

LIST OF FIGURES ........................................................................................................................ x

1 INTRODUCTION .................................................................................................................. 1

1.1 REFERENCES ................................................................................................................. 4

2 REVIEW OF ENVIRONMENTAL PERFORMANCE OF PERMEABLE PAVEMENT

SYSTEMS: STATE OF THE KNOWLEDGE............................................................................... 5

2.1 ABSTRACT ..................................................................................................................... 5

2.2 INTRODUCTION ............................................................................................................ 5

2.3 BACKGROUND .............................................................................................................. 6

2.4 HYDROLOGIC PERFORMANCE ................................................................................. 8

2.5 IMPACTS TO WATER QUALITY .............................................................................. 12

2.6 LONGEVITY & FUNCTIONALITY ........................................................................... 16

Clogging and Permeability Losses.......................................................................... 16 2.6.1

Effects of Frost ........................................................................................................ 19 2.6.2

Long-term Pollutant Removal................................................................................. 20 2.6.3

2.7 MAINTENANCE NEEDS ............................................................................................. 21

2.8 EMERGING RESEARCH AND RESEARCH NEEDS ............................................... 24

Costing and Performance Studies beyond Site-Scale ............................................. 24 2.8.1

2.9 Effects on Urban Heat Island ......................................................................................... 25

2.10 CONCLUSIONS ........................................................................................................ 26

2.11 REFERENCES ........................................................................................................... 27

3 HYDROLOGIC PERFORMANCE OF THREE PARTIAL-INFILTRATION

PERMEABLE PAVEMENTS IN A COLD CLIMATE OVER LOW PERMEABILITY SOIL 34

3.1 ABSTRACT ................................................................................................................... 34

3.2 INTRODUCTION .......................................................................................................... 34

3.3 METHODOLOGY ......................................................................................................... 36

Site Design .............................................................................................................. 36 3.3.1

Monitoring and Data Collection ............................................................................. 39 3.3.2

Data Analysis .......................................................................................................... 40 3.3.3

3.4 RESULTS AND DISCUSSION .................................................................................... 41

Tests of Homogeneity ............................................................................................. 41 3.4.1

Precipitation Data.................................................................................................... 42 3.4.2

vi

Infiltration into the PP ............................................................................................. 42 3.4.3

Outflow Volume ..................................................................................................... 43 3.4.4

Outflow Rates and Detention .................................................................................. 46 3.4.5

3.5 CONCLUSIONS ............................................................................................................ 50

3.6 REFERENCES ............................................................................................................... 50

4 PRELIMINARY ANALYSIS OF STORMWATER QUALITY DATA ............................ 53

4.1 INTRODUCTION .......................................................................................................... 53

4.2 METHODOLOGY ......................................................................................................... 53

4.3 Result of PRELIMINARY Analysis .............................................................................. 54

Seasonal Trends ...................................................................................................... 54 4.3.1

Inter-Annual Trends ................................................................................................ 56 4.3.2

Microbiology........................................................................................................... 56 4.3.3

4.4 CONCLUSIONS ............................................................................................................ 56

4.5 REFERENCES ............................................................................................................... 57

5 STORMWATER QUALITY OF SPRING-SUMMER-FALL EFFLUENT FROM THREE

PARTIAL-INFILTRATION PERMEABLE PAVEMENT SYSTEMS AND CONVENTIONAL

ASPHALT PAVEMENT .............................................................................................................. 58

5.1 INTRODUCTION .......................................................................................................... 58

5.2 METHODOLOGY ......................................................................................................... 60

Site Design .............................................................................................................. 60 5.2.1

Monitoring and Data Collection ............................................................................. 62 5.2.2

Sample Boxes.......................................................................................................... 63 5.2.3

Data Analysis .......................................................................................................... 65 5.2.4

5.3 RESULTS AND DISCUSSION .................................................................................... 66

General Quality and Petroleum-Based Hydrocarbons ............................................ 66 5.3.1

Nutrients .................................................................................................................. 68 5.3.2

Metals ...................................................................................................................... 73 5.3.3

Sample boxes .......................................................................................................... 76 5.3.4

5.4 CONCLUSIONS ............................................................................................................ 79

5.5 REFERENCES ............................................................................................................... 80

6 STORMWATER QUALITY OF WINTER EFFLUENT FROM THREE PARTIAL-

INFILTRATION PERMEABLE PAVEMENT SYSTEMS AND CONVENTIONAL ASPHALT

PAVEMENT ................................................................................................................................. 82

6.1 INTRODUCTION .......................................................................................................... 82

6.2 METHODOLOGY ......................................................................................................... 83

vii

Site Design .............................................................................................................. 83 6.2.1

Monitoring and Data Collection ............................................................................. 85 6.2.2

Data Analysis .......................................................................................................... 87 6.2.3

6.3 RESULTS AND DISCUSSION .................................................................................... 88

General Quality and Road Salt ............................................................................... 88 6.3.1

Nutrients .................................................................................................................. 94 6.3.2

Metals ...................................................................................................................... 97 6.3.3

6.4 CONCLUSIONS .......................................................................................................... 100

6.5 REFERENCES ............................................................................................................. 100

7 ASSESSING THE POTENTIAL FOR RESTORATION OF SURFACE PERMEABILITY

FOR PERMEABLE PAVEMENTS THROUGH MAINTENANCE ........................................ 103

7.1 ABSTRACT ................................................................................................................. 103

7.2 INTRODUCTION ........................................................................................................ 103

7.3 METHODOLOGY ....................................................................................................... 105

Small-Sized Equipment Testing ........................................................................... 105 7.3.1

Full-Sized Equipment Testing .............................................................................. 107 7.3.2

7.4 RESULTS..................................................................................................................... 109

Small-Scale Equipment Testing ............................................................................ 109 7.4.1

Full-Sized Equipment Testing as Rehabilitation .................................................. 112 7.4.2

7.5 Full-Sized Equipment Testing as Preventative Maintenance ....................................... 115

7.6 DISCUSSION .............................................................................................................. 116

Clogging ................................................................................................................ 116 7.6.1

Maintenance Techniques ...................................................................................... 116 7.6.2

Maintenance Needs of Modular and Poured PP ................................................... 119 7.6.3

7.7 CONCLUSIONS .......................................................................................................... 121

7.8 REFERENCES ............................................................................................................. 121

8 CONCLUSIONS AND RECOMMENDATIONS ............................................................. 123

8.1 CONCLUSIONS .......................................................................................................... 123

Objectives 1 and 2 ................................................................................................. 123 8.1.1

Objective 3 ............................................................................................................ 124 8.1.2

Objective 4 ............................................................................................................ 125 8.1.3

Objective 5 ............................................................................................................ 125 8.1.4

8.2 RECOMMENDATIONS ............................................................................................. 126

APPENDIX A: STORMWATER QUALITY ............................................................................ 128

APPENDIX B: DESCRIPTIVE STATISTICS .......................................................................... 130

viii

APPENDIX C: GRAPHICAL SUMMARIES (AP, EO, PC AND ASH) .................................. 135

APPENDIX D: GRAPHICAL SUMMARIES (AP AND APL) ................................................ 140

Appendix E: TIME SERIES ....................................................................................................... 145

APPENDIX F: SUMMARY TABLES ....................................................................................... 151

APPENDIX G: SPRING-SUMMER-FALL STORMWATER QUALITY RESULTS ............ 154

APPENDIX H: WINTER STORMWATER QUALITY RESULTS ......................................... 158

APPENDIX I: TEMPERATURE DATA AND ANALYSIS ..................................................... 162

ix

LIST OF TABLES Table 2-1: Effects of permeable pavement on runoff or exfiltration hydrograph characteristics 11 Table 2-2: Removal efficiency of common metals and suspended solids .................................... 14 Table 2-3: Infiltration performance of aged PPs ........................................................................... 18 Table 2-4: Observed effects of cleaning practice ......................................................................... 22 Table 2-5: Other maintenance investigations ............................................................................... 23

Table 3-1: Precipitation statistics .................................................................................................. 42 Table 3-2: Surface infiltration statistics ........................................................................................ 43 Table 3-3: Hourly peak flow statistics .......................................................................................... 46 Table 3-4: Hydrograph characteristics .......................................................................................... 49 Table 3-5: Attenuation characteristics .......................................................................................... 49

Table 5-1: Stormwater quality parameters .................................................................................... 63 Table 5-2: General quality concentration results .......................................................................... 66

Table 5-3: General quality mass loading results ........................................................................... 67 Table 5-4: Nutrient concentration results ..................................................................................... 69 Table 5-5: Nutrient mass loading results ...................................................................................... 69 Table 5-6: Heavy metal concentration results .............................................................................. 74

Table 5-7: Heavy metal mass loading results ............................................................................... 75 Table 5-8: Observed metals and nutrients .................................................................................... 78 Table 6-1: Stormwater quality parameters .................................................................................... 86

Table 6-2: General quality concentration results .......................................................................... 89 Table 6-3: General quality mass loading results ........................................................................... 89

Table 6-4: Nutrient concentration results ..................................................................................... 94 Table 6-5: Nutrient mass loading results ...................................................................................... 95 Table 6-6: Heavy metal concentration results .............................................................................. 98

Table 6-7: Heavy metal mass loading results ............................................................................... 99

Table 7-1: Parking lot details ...................................................................................................... 106 Table 7-2: Vacuum specifications .............................................................................................. 107 Table 7-3: Pre-treatment infiltration statistics ............................................................................ 109

Table 7-4: Infiltration test results ................................................................................................ 111 Table 7-5: Vacuum sediment samples ........................................................................................ 112

Table 7-6: Passing infiltration tests............................................................................................. 113 Table 7-7: Post maintenance statistics for infiltration tests (I >50mm/h) ................................... 113 Table 7-8: Pre- and post-maintenance infiltration statistics ....................................................... 115

x

LIST OF FIGURES Figure 1-1: The Kortright Permeable Pavement Parking Lot ......................................................... 2 Figure 2-1: Example of a typical permeable pavement cross-section (Image used with permission

of the Interlocking Concrete Pavement Institute) ........................................................................... 7 Figure 3-1: Site schematic ............................................................................................................ 37 Figure 3-2: Vertical cross-sections of PICP (a), PC (b) and Concrete Curbs (c) ......................... 38

Figure 3-3: Monthly stormwater volume and volume reduction, VR (VR not calculated for June

2011 due to data losses associated with power outage) ................................................................ 44 Figure 3-4: Individual event volume reduction, VR ..................................................................... 45 Figure 3-5: Linear regression permeable pavement outflow vs. ASH runoff volumes: observed

and predicted volumes for closed-valve tests ............................................................................... 45

Figure 3-6: Example of a two-stage response in EO and the impact on hydrograph parameters . 47 Figure 3-7: Example of PP flows and water levels above the underdrain .................................... 47

Figure 3-8: Flows during spring thaw, February 28 – April 6, 2011 ............................................ 48 Figure 4-1: Strontium probability plot .......................................................................................... 55

Figure 4-2: Seasonality in stormwater quality (note: 2012/2013 results >20 000 μg/L verified by

repeated analysis at MOE lab) ...................................................................................................... 55

Figure 4-3: Potassium time series ................................................................................................. 56 Figure 5-1: Site schematic ............................................................................................................ 60

Figure 5-2: Profile of Permeable Interlocking Concrete Paver .................................................... 61 Figure 5-3: Profile of Pervious Concrete ...................................................................................... 61 Figure 5-4: Material Boxes: EO (top-left), PC (top-right), AP (bottom-left), 19 mm aggregate

(bottom-right) ................................................................................................................................ 64 Figure 5-5: pH time series............................................................................................................. 68

Figure 5-6: Probability plots ......................................................................................................... 71

Figure 5-7: Nitrogen total pollutant mass ..................................................................................... 72

Figure 5-8: Total phosphorus (TP) boxplots and probability plot ................................................ 72 Figure 5-9: Potassium (K) and Strontium (Sr) concentration time series ..................................... 76

Figure 5-10: Total solids (TS), total suspended solids (TSS) and pH measured at the University

of Guelph ...................................................................................................................................... 77 Figure 5-11: Magnesium (Mg) and Potassium (K) concentrations .............................................. 79

Figure 6-1: Site schematic ............................................................................................................ 84 Figure 6-2: Profile of Permeable Interlocking Concrete Pavers ................................................... 84

Figure 6-3: Profile of Pervious Concrete ...................................................................................... 85 Figure 6-4: pH time series............................................................................................................. 90 Figure 6-5: Total suspended solids (TSS): probability plot (left), time series (right) .................. 91 Figure 6-6: Road salt time series: Chloride (Cl), Sodium (Na)............................................... 92

Figure 6-7: Time series: Chloride (Cl), Sodium (Na) ................................................................... 93 Figure 6-8: Nitrogen probability plots .......................................................................................... 96 Figure 6-9: Nitrogen total pollutant mass ..................................................................................... 97

Figure 7-1: Two examples of PPs which have lost their capacity to infiltrate water ................. 104 Figure 7-2: New PP installed 2009 (left) and old PP installed 2004 (right) ............................... 104 Figure 7-3: Surface infiltration measurements: double-ring infiltrometer (left), single-ring

infiltration (right) ........................................................................................................................ 106 Figure 7-4: Commercial streetsweepers: Tymco-DST 6 sweeper (left), Elgin Whirlwind sweeper

(right) .......................................................................................................................................... 108

xi

Figure 7-5: Examples of voids contributing to high pre-treatment surface infiltration rates: PICP

(left), PC (right) .......................................................................................................................... 112 Figure 7-6: Infiltration boxplots.................................................................................................. 114 Figure 7-7: Gradation of hopper grab samples ........................................................................... 114

Figure 7-8: Infiltration boxplots.................................................................................................. 115 Figure 7-9: Examples of inconsistent removal of joint material................................................. 118 Figure C--1: General quality graphical summaries (a) ............................................................... 135 Figure C-2: General quality graphical summaries (b) ................................................................ 136 Figure C-3: Nutrients graphical summaries ................................................................................ 137

Figure C-4: Metals graphical summaries (a) .............................................................................. 138 Figure C-5: Metals graphical summaries (b) .............................................................................. 139

1

1 INTRODUCTION

The use and management of water resources has implications at local, watershed, national and

international levels to environmental, social, cultural and economic aspects of society. The

design of stormwater collection, conveyance and treatment systems has implications on both

local and regional water quality, and availability. Historically, engineered stormwater systems

were designed primarily to protect communities from water ponding and flooding, however, the

uses of stormwater systems have since been expanded to address a much wider array of design

objectives. Today new stormwater management systems are expected to simultaneously provide

flood protection, improve water quality, enhance uses of rainwater in subpotable water supply,

limit downstream erosion or ecological degradation and replicate pre-development hydrology

without neglecting economic constraints or the cultural and social expectations of local

communities.

The benefits of maintaining a naturalized water balance within urban areas, where stormwater

not only flows to downstream surface water systems but is also allowed to infiltrate into

groundwater systems or to evapotranspire, are recognized and accepted by engineers, managers,

policy makers and stakeholders. In Ontario, provincial guidelines emphasize integrated

management (Ministry of the Environment (MOE), 2003) and prevention practices (MOE, 2002)

along with source, conveyance and end-of-pipe controls (MOE, 2003). Emphasis on maintaining

pre-development conditions and flow paths has meant that traditional engineered stormwater

systems, which rely almost exclusively on conveying stormwater to a surface water receptor, no

longer provide satisfactory design solutions. Although provincial design guidelines for low

impact development (LID) techniques do not yet exist, regional guidelines have been developed

(Credit Valley Conservation Authority (CVC) and Toronto Region Conservation Authority

(TRCA), 2010) and initiatives such as the Sustainable Technologies Evaluation Program (STEP)

have started to evaluate LID practices under southern Ontario climatic and geologic conditions.

Permeable pavement is one technology which can increase the volume of urban stormwater

which can infiltrate to subsurface and groundwater systems. Partial-infiltration PP systems that

are underdrained and connected to surface water drainage systems these pavements can reduce

peak storm flows, prevent thermal enrichment, and remove many common stormwater

pollutants.

In Ontario the use of permeable pavement for stormwater infiltration is hindered by a lack of

research in cold climates and on fine textured soils. Long-term performance of permeable

pavement is perceived to be uncertain in cold climates (Roseen et al., 2009). There have been

only a limited number of studies (Bean et al., 2007a; Bean et al., 2007b; Collins et al., 2008;

Collins et al., 2010; Rowe et al., 2010) which simultaneously evaluate permeable poured and

interlocking paver products under similar cold climate conditions. Lastly, the effective lifespan

of permeable pavements subjected to winter plowing, salting and sanding continues to be

unknown and practical maintenance procedures are widely untested. If permeable pavement is to

2

be more widely adopted in Ontario as an LID practice, research is needed to validate that

pavements can satisfy long-term performance objectives. This dissertation addresses these gaps

in the existing published research producing new and original results to determine the suitability

of permeable pavements for climatic and geologic conditions common to Ontario. Specifically,

TRCA’s pilot permeable pavement parking lot (Figure 1-1) at the Kortright Centre for

Conservation was monitored for two years to test and evaluate the performance of several

permeable pavements in typical Ontario conditions. The study evaluated the performance of

partial-infiltration PP systems over low permeability soils. The objectives of the research were

to:

1. Identify key factors affecting design (material type, traffic, maintenance practice, organic

inputs) and assess impacts on long term functional, hydrologic and water quality

performance;

2. Compare the performance of various porous pavements (interlocking permeable concrete

pavers and porous concrete) and traditional impervious asphalt in terms of functional,

hydraulic and water quality performance;

3. Assess opportunities to use permeable pavement in areas of native soils with low

permeability and determine the required type and degree of underdrainage;

4. Evaluate seasonal hydraulic and water quality performance over two years and identify

critical cold climate issues such as winter maintenance and material durability;

5. Evaluate and compare effectiveness of alternative cleaning practices; and

6. Recommend design (and operation and maintenance) modifications to enhance overall

performance.

Figure 1-1: The Kortright Permeable Pavement Parking Lot

3

The thesis consists of eight chapters, five of which are stand-alone manuscripts.

Chapter 1 (Introduction): Introduces the thesis topic, outlines objectives and presents the thesis

structure.

Chapter 2 (Literature review): Presents a review of relevant permeable pavement research. This

chapter is a stand-alone manuscript and has been reprinted from Water Quality Research Journal

of Canada, in press, with permission from the copyright holders, IWA Publishing.

Jennifer Drake, Andrea Bradford & Jiri Marsalek 2013 Review of Environmental Performance

of Permeable Pavement Systems: State of the Knowledge. Water Quality Research

Journal of Canada 48 (in press).

Chapter 3 (Hydrologic Performance): Presents hydrologic performance results of the Kortright

permeable parking lot. This chapter is a stand-alone manuscript and is under second review with

the ASCE Journal of Hydrologic Engineering and has been reprinted with permission from

ASCE.

Jennifer Drake, Andrea Bradford & Tim Van Seters 2013 Hydrologic Performance of Three

Partial-Infiltration Permeable Pavements in a Cold Climate and Over Low Permeability

Soil. Journal of Hydrologic Engineering (in review).

Chapter 4 (Organization of Water Quality Data): Outlines the organization and presentation of

water quality data from the Kortright permeable parking lot.

Chapter 5 (Spring-Summer-Fall Water Quality Performance): Presents water quality

performance of the Kortright permeable parking lot during spring, summer and fall seasons. This

chapter is a stand-alone manuscript.

Chapter 6 (Winter Water Quality Performance): Presents water quality performance of the

Kortright permeable parking lot during the winter season. This chapter is a stand-alone

manuscript.

Chapter 7 (Maintenance of Permeable Pavements): Evaluates the effectiveness of several

maintenance practices for rejuvenating the surface permeability of permeable pavements. This

chapter is a stand-alone manuscript. Preliminary study finding were presented in a manuscript

published in the CHI Monography 21. Final results are also presented in a journal manuscript

under second review with Water, Science and Technology.

Chapter 8 (Conclusions and Recommendations): Presents conclusions of thesis research and

discusses future research directions and recommendations.

Appendixes: Figures and Tables for Water Quality Results

4

1.1 REFERENCES

Bean, E., Hunt, W., & Bidelspach, D. (2007a). Evaluation of four permeable pavement sites in

Eastern North Carolina for runoff reduction and water quality impacts. J. Irrig. Drain. Eng. , 133

(6), 583-592.

Bean, E., Hunt, W., & Bidelspach, D. (2007b). Field survey of permeable pavement surface

infiltration rates. J.Irrig. Drain. Eng. , 133 (3), 249-255.

Collins, K., Hunt, W., & Hathaway, J. (2008). Hydrologic comparison of four types of

permeable pavement and standard asphalt in Eastern North Carolina. J. Hydrol. Eng. , 13 (12),

1146-1157.

Collins, K., Hunt, W., & Hathaway, J. (2010). Side-by-side comparison of nitrogen species

removal for four types of permeable pavement and standard asphalt in Eastern North Carolina. J

of Hydro. Eng., 15 (6), 512-521.

CVC and TRCA. (2010). Low Impact Development Stormwater Management Manual. Toronto:

Credit Valley Conservation and Toronto and Region Conservation.

Ministry of the Environment. (2003). Stormwater Management Planning and Design Manual.

Government of Ontario. Toronto: Queen's Printer for Ontario.

Ministry of the Environment. (2002). Stormwater Pollution Prevention Handbook- 4224e.

Toronto: Queen's Printer of Ontario.

Roseen, R., Ballestero, T., Houle, J., Avellaneda, P., Briggs, J., Fowler, G., & Wildey, R. (2009).

Seasonal performance variations for storm-water management systems in cold climate

conditions. J. Environ. Eng., 135 (3), 128-137.

Rowe, A., Borst, M., O'Connor, T., & Stander, E. (2010). Permeable pavement demonstration at

the Edison Environmental Center. Low Impact Development 2010: Redefining Water in the City

(pp. 139-151). San Francisco: ASCE.

5

2 REVIEW OF ENVIRONMENTAL PERFORMANCE OF PERMEABLE

PAVEMENT SYSTEMS: STATE OF THE KNOWLEDGE

2.1 ABSTRACT

Permeable pavement (PP) systems provide opportunities to mitigate the impacts of urbanization

on receiving water systems by providing at source treatment and management of stormwater.

However, they do not receive mainstream use throughout much of Canada and the USA because

of a lack of local guidance documents, demonstration projects and performance data. Studies

have repeatedly shown that PPs attenuate stormwater flows by reducing volume and frequency

of stormwater flows, reducing and delaying peak flow rates, and increasing flow durations. PP

systems have been shown to improve stormwater quality by reducing stormwater temperature,

pollutant concentrations and pollutant loadings of suspended solids, heavy metals, polycyclic

aromatic hydrocarbons, and some nutrients. This review is intended as a comprehensive

summary of the current state of knowledge of the environmental performance of PP systems.

Published research is synthesized to examine the hydrologic performance, impacts to water

quality, longevity and functionality and maintenance needs of PP systems. Where appropriate,

the limitations of current knowledge are discussed and emerging and future research needs are

presented. The intent of this review is to provide stakeholders in stormwater management with

the critical information that is needed to foster acceptance of PPs as a viable alternative to

traditional systems.

Keywords: hydrology; low impact development; maintenance; permeable pavements;

stormwater management; water quality

2.2 INTRODUCTION

The protection of natural water balances and flow paths is a critical design objective for

integrated urban stormwater management. This objective aims to mitigate or prevent disruptions

to natural processes that have been shown to: contribute to unhealthy stream systems (Walsh et

al., 2005); increase risks to public safety and property (Marsalek and Chocat, 2002); or degrade

surface and subsurface drinking water sources (Marsalek and Chocat, 2002). The range and

complexity of economic, environmental, social and cultural impacts associated with urban

stormwater necessitate the use of new types of planning techniques and engineered systems. Low

Impact Development (LID) is an increasingly accepted approach for addressing the challenges of

stormwater design and management. LID is a design philosophy, encompassing planning

methods and stormwater management technologies, to minimize the negative impacts most

commonly associated with urban stormwater including degradation of groundwater and surface

water quality, loss of recharge, erosion, flooding and loss of aquatic diversity (Coffman, 2000;

Dietz, 2007; CVC and TRCA, 2010). To emulate pre-development conditions, LID systems treat

locally and manage, at source, as much stormwater as possible.

6

Permeable pavement (PP) is a key LID technology, increasing the volume of locally managed

stormwater through subsurface storage and, where possible and environmentally safe,

groundwater recharge. Water quality benefits of PP systems include thermal mitigation and

reduced pollutant concentrations and overall loading for receiving systems. PPs have been

applied in parking lots, low-density traffic lanes and pedestrian pathways as part of numerous

experimental and demonstration programs since the 1980’s in the United States (e.g. Field et al.,

1982a and 1982b), Canada (e.g. Kresin et al., 1997; James and Verspagen, 1997; James and

Thompson, 1997), Europe (e.g. Pratt et al., 1989; Pratt et al., 1995; Colandini et al., 1995;

Baladès et al., 1995) and Japan (e.g. Watanabe, 1995; Fujita, 1997). Given the potential benefits

associated with this technology, coupled with the large body of literature documenting the

successful use of PP, it is perhaps surprising that PPs have not been more broadly applied across

Canada and USA. One reason for this is a limited understanding of the long-term environmental

impacts of stormwater infiltration, particularly on groundwater resources and in cold climate

conditions. Developers, designers, engineers, and planners are reluctant to implement

technologies which are perceived to be untested with respect to longevity, sustainable

performance and maintenance costs. Regionally, technical resources which provide design

guidance and outline benefits and limitations of PPs are often lacking. On-going advances have

meant that even extensive reviews such as Ferguson’s 2005 book, Porous Pavement, require

updating.

This review provides a synthesis of the current state of knowledge with respect to PP systems. It

describes the types of PPs currently available, the typical components of PP systems, and

clarifies the appropriate use of PP as an LID technology. Approaches to studying and evaluating

PPs are highly variable and this review aims to provide critical interpretations of existing studies

to advance the current understanding of hydrologic performance, impacts to water quality,

longevity and functionality and maintenance needs. Finally, the paper identifies emerging

research and needs.

2.3 BACKGROUND

A permeable (also called porous or pervious) pavement is a paving material which allows water

to infiltrate and be conveyed through its material matrix, open joints or voids (Figure 2-1). While

some researchers (Beecham and Myers, 2007) have drawn a distinction, the terms permeable,

porous and pervious are frequently used interchangeably. PP systems are composed of a

permeable paving surface as well as layers of coarse aggregate materials that function as an

aggregate reservoir, providing storage capacity during precipitation events. Depending on site

conditions, pavements can be designed with different boundary components for full, partial or no

exfiltration (i.e. infiltration to native soils). When exfiltration is not desired, underdrains

composed of perforated pipes are positioned at or near the base of the aggregate reservoir to

collect and convey infiltrating water to a storm sewer system, with or without further treatment.

Some PP parking lots have been designed with vault storage, allowing further control of outflow

7

and interception of spills. Stormwater which has infiltrated through a PP system and been

collected in an underdrain is referred to as exfiltrate (Bean et al., 2007a; Sansalone and Teng,

2004) or outflow. Elevating underdrains so that they are located above the base of the aggregate

reservoir increases the degree of partial exfiltration as water levels must rise to the elevation of

the underdrain invert before stormwater can drain through these pipes. Other components

commonly included in the design of PP systems are geotextiles, and small aggregate filter or

choker courses. PPs have also been applied as overlays (referred to as a permeable friction

course or an open-graded friction course) on highways. In this application infiltration to native

soils is not a design objective but rather the porous properties of the PP are used to reduce spray

and traffic noise (Barrett et al., 2006; Schaefer et al., 2010).

Figure 2-1: Example of a typical permeable pavement cross-section (Image used with

permission of the Interlocking Concrete Pavement Institute)

Ferguson (2005) identified nine types of PPs based on surface paving material: porous aggregate,

porous turf, plastic geocells, open-jointed paving blocks or permeable interlocking concrete

pavers, open-celled paving grids, porous concrete (or pervious concrete), porous asphalt, soft

paving materials and decks. In addition to these categories a tenth type, epoxy-bonded porous

materials, has been developed (e.g. Flexi®-Pave and FilterPave®).

Each type of PP has different functional, environmental, aesthetic and cost requirements. Most

research has focused on the more commercially applied materials: permeable interlocking

concrete pavers, pervious concrete, and porous asphalt, and these types are the focus of this

review. Permeable interlocking concrete pavers (PICP) consist of modular units separated by

joints filled with open-graded aggregate. Pervious concrete (PC) and Porous Asphalt (PA) are

permeable variations of concrete or asphalt where the binding agent coats the aggregate particles

without filling the voids between the particles (Kevern et al., 2010). These pavement types are

capable of supporting vehicular traffic, require limited maintenance, and are aesthetically

pleasing and affordable, making them suitable alternatives for parking lot, pedestrian and low-

8

density traffic roadways. Designed correctly, PPs can be successfully applied for a broad range

of traffic loadings; for example PICPs were used in airport fire training grounds in the UK

(Knapton and Cook, 2003) and in container handling areas in Brazil (Knapton and Cook, 2000).

In addition to traffic loads, the design of a PP system depends on the climate, native soils,

hydrology and land use of the site and adjacent lands. Infiltration to native soils may not be

possible or suitable at all sites such as those with low permeability native soils, soil

contamination, or existing or future land uses that may lead to poor stormwater quality (i.e. hot

spots) and risks to groundwater quality (CVC and TRCA, 2010). In northern climates de-icing

salts applied during the winter may present environmental concerns for down-gradient systems;

chloride in particular is expected to pass through the pavement structure largely unattenuated

(CVC and TRCA, 2010). Sand and gravel used for winter road maintenance can cause clogging

of PP systems and its use is not recommended (CVC and TRCA, 2010). PPs are also not feasible

in areas where clogging material is likely to be directed onto the pavement, for example, sites

adjacent to beaches (Ferguson, 2005).

2.4 HYDROLOGIC PERFORMANCE

The potential hydrological benefits of PP systems were initially reported by Thelen et al. (1972)

to the U.S. Environmental Protection Agency and since that time, hydrological performance has

been a prominent theme in much of the literature. This review focuses on the results from

monitoring and testing of full-scale parking lots, designed to accommodate monitoring

equipment and subjected to traffic and natural precipitation.

Research objectives typically focus on quantifying the water balance and measuring the timing

and rate of flows. Hydrologic results are dependent on local climatic and geological conditions,

confounding efforts to compare performance between studies. Differences in system design,

particularly boundary components (i.e. type of underdrainage), as well as the condition and age

of a pavement, are also critical to performance comparisons. To fully characterize the hydrologic

behaviour, a PP system must be monitored under a range of conditions (e.g. storm events of

varying magnitude, intensity and duration, and different antecedent and seasonally-variable

conditions). Within an installation, spatial heterogeneity is a common phenomenon due to

differential inputs, traffic loadings, drainage patterns and installation and maintenance conditions

across the pavement surface. Hydrologic performance of a PP system, with respect to outflow

volume, rate, timing and frequency, is typically measured and reported relative to an impervious

pavement ‘control’.

Many of the early monitoring studies (1980-2000) from the USA, UK, and Canada were for

PICP installations that used aggregate and block designs which are no longer commercially

available. Field et al. (1982a and 1982b), Pratt et al. (1989), and James and Thompson (1997)

found that even these early designs yielded promising runoff volume reductions. Some early

designs were constructed with impermeable membranes which prevented exfiltration to native

9

soils (Pratt et al., 1989; James and Thompson, 1997). Total volume reductions from systems

designed for no exfiltration are notably lower than those from systems designed for exfiltration;

however, Pratt et al. (1989) found that even lined systems produced no discharge for small

rainfall events (<5 mm). More recent studies have also found that PP systems do not produce

outflow for small events preceded by dry antecedent conditions (Bean et al., 2007a; Drake et al.,

2012).

Monitoring studies have progressively become more sophisticated, expanding the hydraulic

parameters monitored beyond volume and peak flow reductions to include analysis of flow

timing and duration (e.g. Fassman and Blackbourn, 2010a; Roseen et al., 2009). Statistical

analyses have become tools for performance evaluations of PP systems and researchers now

regularly report results in terms of statistically significant differences relative to ‘control’ plots

(Collins et al., 2010; Fassman and Blackbourn, 2010a; Roseen et al., 2009). Booth and Leavitt

(1999) were among the first to initiate side-by-side testing of different types of PPs, and Brattebo

and Booth (2003) provided an analysis of long-term performance, marking a departure from

earlier studies which had limited results from a small number of isolated rainfall events. Collins

et al. (2008) provide more side-by-side testing and were the first to evaluate performance

differences between poured and modular PP systems.

Table 2-1 summarizes the hydrologic performance for a range of PP systems. The description of

the systems provided in the cited studies allowed the results to be placed in context (e.g. with

respect to the system design, events monitored etc.). Poured and modular PP are expected to

have similar hydrologic behaviour since outflow is ultimately governed by boundary conditions

and precipitation inputs. Hydrologic performance evaluations have been almost exclusively

limited to newly-constructed PP installations and studies longer than 2.5 years are rare.

Differences in hydraulic behaviour between types of PPs are likely to become more apparent as

pavement ages and experiences surface permeability losses.

Reported volume and peak flow reductions are variable. Surface runoff and exfiltrate volumes

from PPs are generally smaller than those from asphalt pavements, but negative volume

reductions (i.e. increases in outflow) are possible when stormwater previously stored within the

PP system is released during an event (Drake et al., 2012; Abbott and Comino-Mateos, 2003).

Many studies (Collins et al., 2008; Kwiatkowski et al., 2007; TRCA, 2008) have reported no

direct runoff from PP during the entire monitoring period. It is difficult to document performance

for larger, infrequent events unless they happen to occur during a study. In the majority of

studies, the volume of exfiltrated stormwater is at least 30% smaller than precipitation inputs or

runoff from impermeable control pavements. As the number of hydrologic studies increases

evidence is emerging that, for small-to-moderately sized rainfall events, underdrained PPs

provide a minimum degree of volume reduction regardless of location or drainage design. High

volume reductions, above 30%, are frequently reported for PPs draining to sandy soils (Abbott

and Comino-Mateos, 2003; Bean et al., 2007a; Collins et al., 2008; Pratt et al., 1995; Rushton,

10

2001). Peak flow reductions, of 70% or more relative to an impermeable control, are commonly

reported but delays in timing of peak flows are less consistent between studies and highly

variable within individual studies.

Few studies have investigated the hydrologic performance of PP systems allowing exfiltration in

locations with low permeability soils. Dreelin et al. (2006) discussed the hydrologic performance

of an installation of porous turf over soils with high clay content. However, the reported

percolation rates of the soils (4.8 to 16.7 cm/hr) indicate that these soils actually had high

permeability. Another study of PICP on low permeability soils by Fassman and Blackbourn

(2010a) in New Zealand observed greater than expected volume reductions. The authors

proposed that evaporation and heterogeneous features within the native soils (i.e. fractures) were

the most likely explanations for the observed hydrologic losses. This highlights the issue that

standard methods of estimating soil properties which rely on small soil samples can significantly

underestimate the bulk hydraulic conductivity.

A number of other relevant findings emerged from the cited studies. Brattebo and Booth (2003)

found that during precipitation events, parked vehicles can create saturated conditions resulting

in overland flows, by concentrating rainfall onto small sections of pavement. Tyner et al. (2009)

found that constructing additional features such as infiltration trenches or boreholes, or ripping

the surface at the soil layer can increased the capacity to infiltrate water to low permeability

soils. Starke et al. (2010) and (2011) showed a 16% increase in evaporation rates from PPs

relative to impermeable pavements and evaporation rates were found to be dependent on sub-

base materials, vegetation and stone colouring.

Lab-scale research can complement field studies by allowing for the hydraulic properties of PP

to be evaluated under controlled conditions. It is important to use appropriate boundary

conditions in lab-scale studies; draining pavement specimens to open-air collection systems is

not realistic and may not accurately simulate performance of PP systems. Hou et al. (2008) is one

study which included a low hydraulic conductivity native soil layer as a boundary condition for

PP specimens. The Beijing-based researchers observed that exfiltrate water continued to flow out

of the soil layer for up to 10 days after a simulated rain event.

11

Table 2-1: Effects of permeable pavement on runoff or exfiltration hydrograph characteristics

Paper Type Boundary

Condition

Study

Length

Max

rainfall Volume Flows Timing

Abbott &

Comino-

Mateos (2003)

PICP impermeable liner

with underdrains 14 months 20.6 mm

UEV averaged 67% of SRV,

ranged between 30 – 120%

PF lag averaged 2 h, ranged

between 5 min and 9 h

Barrett (2008) PA

(overlay)

conventional

asphalt 2.5 yr 117 mm

Increased runoff due to loss of

spray and resuspension of

rainfall

Minimal lag between peak

rainfall and runoff

Bean et al.

(2007a)

CGP sandy soil 26 months 369 mm SRV was 44% of RV on

average

22% of all events produced

runoff

PC sandy soil 17 months 97 mm SRV was 31% of RV on

average

37% of all events produced

runoff > 1mm

CGP

sandy soils &

loam sand soil

with underdrains

10 months 88 mm No runoff observed

Collins et al.

(2008)

PICP

PC

CGP

sandy loam to

sandy clay loam

with underdrains

12 months 183 mm

SRV was <1% of RV, EV

reductions averaged 37-66%, no

exfiltration was observed for

rainfall events < 6 mm

PF reductions averaged 67%

(PC), 60-74% (PICP), 77%

(CGP)

PF lag averaged 28-50 min,

ranged between 0-312 min

Drake et al.

(2012)

PICP

PC

silty clay with

underdrains 22 months 51.6 mm

No direct runoff observed,

UEV was 57% of SRV PF reductions averaged 92%

hydrograph lag ranged

between 45 min and 57.5 h

Dreelin et al.

(2006) PGC

well-drained

clayey soils with

underdrain

4 months 18.5 direct runoff reduced by 93%

Fassman &

Blackbourn

(2010a)

PICP

silty clay/clayey

silt with

underdrains

11 months 152 mm UEV averaged 72% of SRV PF reduction averaged 89% median PF lag was 1 h

Kwiatkowski

et al. (2007) PC silty sand ~2.5 yr -

100% infiltration achieved for

rain events <5cm

Pratt et al.

(1989) PICP

impermeable liner

with underdrain 1 month - UEV was 61-75% of RV PF was 30% of rainfall intensity PF lag was 5- 10 min

Pratt et al.

(1995) PICP

impermeable liner

with underdrains ~2 yr 22.6 mm UEV averaged 24-47% of RV

Roseen et al.

(2012) PA

type ‘C’ soils with

raised underdrain 18 months 12.7 mm

No direct runoff observed

PP infiltrated 25% of RV PF reduction averaged 80%

Hydrograph lag averaged

21 h

Rushton

(2001) PP sandy soil ~2 yr - UEV was 35% of SRV

reduction was more pronounced

for small rain events

TRCA (2008) PICP impermeable liner

with underdrains 2.5 yr 72 mm

no runoff observed during the

summer except for 1 large rain

event (72mm)

SIR of mature pavements (3-17

yrs) ranged between 3-122 cm/h

PC=pervious concrete, PP=permeable pavement, PA=porous asphalt, CGP=concrete grid pavers, PGC=Plastic GeoCells, SRV = surface runoff volume, UEV=underdrain exfiltrate

volume, RV=rainfall volume, SIR= surface infiltration rate, PF=peak flow, PEF=peak exfiltrate flow

12

Both lab and field testing are important for poured products where mix design and placement

have a strong influence on hydraulic performance. Sansalone et al. (2008) developed methods to

assess pore characteristics including pore size, total and effective porosity, and tortuosity for PC.

Outdoor lab-scale studies are also useful for investigating processes such as evapotranspiration,

where exposure to natural environmental conditions may be important, but measurement

equipment, such as lysimeters, cannot be easily integrated into full-scale PP installations (Starke

et al. 2010).

A key limitation of the existing research is that the most extensive monitoring studies (Table 2-1)

have only looked at performance over 2.5 years which is a fraction of a pavement system’s

effective life; long-term (i.e. life-cycle) performance remains largely untested. There has been

limited use of poured permeable products such as PC, PA and epoxy-based materials in many

cold-climate regions and further demonstration and testing of these systems is merited.

2.5 IMPACTS TO WATER QUALITY

PP systems reduce the total pollutant mass delivered to receiving systems by reducing runoff and

outflow volumes and removing pollutants from stormwater (Bean et al., 2007a). Pollutants are

introduced into stormwater through a range of anthropogenic activities and environmental

processes. During periods of dry weather suspended materials deposited on pavements by

vehicular traffic as well as by atmospheric deposition. Vehicle wear leaves behind traces of

heavy metals. Hydrocarbons and PAHs are also deposited by wearing tires and oil and gas leaks.

Nutrients and bacteria may be introduced by leaf litter, animal waste or tracked in from nearby

areas. And lastly, winter road salting introduces chloride and other dissolved pollutants.

Suspended materials within stormwater are captured by mechanical filtration through the PP

surface and base layers. As water migrates through the porous media additional treatment is

possible through sorption and biologically mediated processes (Mothersill et al., 2000), including

nutrient transformations and degradation of organic compounds. Pollutants which are captured

by the PP accumulate over time within the pavement and base layers and eventually require

removal. Among the pollutants of interest are suspended solids, chloride, metals, nutrients,

hydrocarbons, and bacteria. Temperature and pH are also frequently measured because they

affect the solubility and toxicity of other parameters such as heavy metals. The majority of

published research focuses on impacts to surface water quality; however, since many PP systems

include partial or full exfiltration, PP treated stormwater can potentially impact groundwater

quality (Pitt et al., 1996).

Investigative work focused on water quality often aims to quantify the event mean concentration

(EMC) for specific pollutants (e.g. TSS, TN, TP, Cu, Zn) and to quantify reductions in terms of

pollutant concentration and mass (or load) relative to impervious pavements (Legret et al., 1996;

Rushton, 2001). Equally as significant as event-based concentrations are the total pollutant load

of contaminants produced from a pavement. Even if concentrations are not reduced by

13

infiltration through PP (e.g. chloride is not retained within PP systems) the reduction in total

volume of stormwater travelling to downstream surface water leads to a net reduction of total

pollutant loads. While some research reports pollutant loads (Pagotto et al., 2000; Rushton, 2001;

Sansalone and Teng, 2004; Collins et al., 2010) the majority of published work does not include

this information. Removal mechanisms are different for dissolved and particulate forms of

pollutants, so it is important to characterize the proportions of pollutants in each of these forms

within influent and effluent samples.

Starting in the 1980’s the potential benefits of PPs on stormwater quality were identified and

measured by researchers. Pratt et al. (1989) reported that exfiltrated stormwater from PICPs had

lower concentrations of suspended solids and total Pb compared to stormwater discharging from

traditional highway drainage catch basins. Based on observations, Baladès et al. (1995)

conservatively proposed that PPs may be capable of capturing 50-60% of certain pollutants,

specifically suspended solids, Pb, Zn and Cd. Legret et al. (1996) also reported concentration

reductions of a similar magnitude for suspended solids and metals from stormwater filtered

through a PA roadway. More recent studies (Rushton, 2001; Brattebo and Booth, 2003; Bean et

al., 2007a; TRCA, 2008; Roseen et al., 2009; Fassman and Blackbourn, 2010b) have repeatedly

found that the concentration of suspended solids and heavy metals (e.g. Pb, Zn, Cu, Cd and Fe)

are reduced by at least 50% when stormwater filters through PP (Table 2-2). In many of these

studies, stormwater was sampled for a small number of precipitation events (i.e. less than 5

events) and as independent stand-alone studies, they suffer from limited confidence in the

reported results. As a collective body of evidence it is clear that the most commonly used

pavements, PA, PICP and PC, remove suspended solids and studied heavy metals.

Exfiltrate from PP systems has been consistently documented to have a pH ranging between 8

and 9.5 (Pratt et al., 1995; Sansalone and Teng, 2004; Kwiatkowski et al., 2007; TRCA, 2008),

whereas rainfall and asphalt runoff tend to be acidic. For the protection of aquatic life, common

water quality guidelines recommend that pH should be maintained between 6.5 – 8.5 (MOE,

1994) and less than 9 for extreme conditions (US EPA, 1986), because PP exfiltrate sometimes

fails to meet these guidelines there may be impacts on aquatic life. As many metals are less

soluble at elevated pH levels PP systems may enhance precipitation and filtration of heavy

metals, or their transformation into less bioavailable species.

14

Table 2-2: Removal efficiency of common metals and suspended solids

Study Pavement Sampled

events

Average Removal (%) Average Residual Concentration

By

concentration

or mass

TSS Zn Cu Pb Cd TSS

(mg/L)

Zn

(μg/L)

Cu

(μg/L)

Pb

(μg/L)

Cd

(μg/L)

Barrett et al.

(2006) PA (overlay) 5 Concentration 94 76 75 93 7.6

40.4*

30.9** 6.8 0.9

Barrett (2008)

PA (overlay) 5 asphalt, 25

exfiltrate Concentration 93 79 52 88 8.80

34.7*

27.4**

12.9*

9.8**

1.5*

<1.0**

PA (overlay) 6 Concentration 87 83 61 87 23.17 23.3*

13.0**

12.4*

8.4**

1.4*

<1.0**

Fassman &

Blackbourn

(2010b)

PICP 8-17

Concentration* 56 93 57

10-80 8-60*

0-20**

3-8*

1-3**

Concentration** 93 52

Mass* 70 96 70

Mass** 95 69

Legret &

Colandini

(1999)

PA 11 Mass 59 73 84 77 8.3 45.6 8.3 0.25

Legret et al.

(1996) PA 22-38 Concentration 64 72 79 67 12 46 15 5.4 0.49

Pagotto et al.

(2000) PA 25

Concentration** 61 15 32 60

13 180 24 13 0.5 Concentration*** 74 70 83 73

Concentration* 81 66 35 78 69

Mass* 77 59 21 74 62

Roseen et al.

(2009) PA

unspecified,

24 months Concentration 96 79 2.22 100

Rushton

(2001)

porous paving

+ swale 12-30 Mass 91 75 81 85 3.76 18.6 3.35 1.25

Sansalone &

Teng (2004) PC 3

Mass*** 91 85 86 89 86

71.2*

29.2**

16.8*

12.3**

20.3*

17.6**

0.8*

0.7**

Mass** 91 88 76 86

Concentration*** 72 55 54 63 55

Concentration** 92 62 25 54

(*) Total, (**) Dissolved, (***) Particulate

When stormwater is allowed to infiltrate, hydrocarbons are retained at the pavement surface or

within the permeable media where they can volatize or degrade (Pitt et al., 1996). Research has

indicated that PPs provide suitable conditions for bio-degradation of hydrocarbons and the

addition of microbial mixtures does not necessarily improve removal rates (Pratt et al., 1989;

Newman et al., 2002). Researchers have not explicitly studied microbial populations or biofilms

within PP systems in terms of growth rates, survival or diversity. Studies have reported removal

rates for solvent extractable hydrocarbons (oil and grease), PAH, or petroleum hydrocarbons and

have consistently found that levels are below detection limits (James and Shahin, 1998; Pratt et

al., 1989; Rushton, 2001; Boving et al., 2008; TRCA, 2008; Tota-Maharaj and Scholz, 2010)

indicating that hydrocarbons are not a significant pollutant in PP effluent.

15

High nutrient levels in stormwater contribute to excessive eutrophication which has a negative

effect on surface water systems. In recent years there has been increased focus on nutrients

within the published literature (Pagotto et al., 2000; Bean et al., 2007a; Roseen et al., 2009;

Collins et al., 2010; Tota-Maharaj and Scholz, 2010). To date, Collins et al. (2010) is the only

study which intensively evaluates the transformation and fate of N through PP. This study

concluded that PP systems provide suitable conditions for nitrification H O

- based on the

observation that PP exfiltrate had consistently lower TKN and H concentrations and

consistently higher O - concentrations than asphalt runoff. Collins et al. (2010) also observed

that TN concentrations can occasionally be higher in PP effluent than in asphalt runoff and

atmospheric deposition. Further work to confirm this finding and determine the source of excess

nitrogen (materials used in the PP system, organic debris delivered at the surface) is needed.

Several studies have noted reductions in TP concentrations (Bean et al., 2007a; TRCA, 2008;

Roseen et al., 2009; Tota-Maharaj and Scholz, 2010). As a filtering system, particulate-bound P

within stormwater may be captured by the PP system; however, long-term observations are

needed to determine if P is remobilized over time.

Design components within PP systems including geotextiles, phosphorus absorbing material or

anaerobic zones may improve removal of nutrients and other contaminants but these techniques

have not yet been thoroughly tested or studied. Tota-Maharaj and Scholz (2010) performed lab

simulations that demonstrated a geotextile can have significant effect on the removal of certain

nutrients such as NH4+ and ortho-phosphate. Collins et al. (2010) observed that a concrete grid

paver system, which included a sand layer, had lower NO2,3-N and TN concentrations than PPs

without sand layers. Fach and Geiger (2005) reported that crushed brick substrate as well as

limestone gravel provided higher sorption of metals than crushed basalt.

Pollutants that are introduced into stormwater through the weathering of pavement and

aggregates have yet to be thoroughly evaluated. Materials within a pavement structure are known

to react chemically or dissolve over time when exposed to stormwater, increasing the pH,

conductivity, alkalinity, hardness and concentration of total dissolved solids of exfiltrate

(Sansalone and Teng, 2004). In particular, higher concentrations of calcium and magnesium have

been observed in PP exfiltrate (Sansalone and Teng, 2004). Aggregate type undoubtly has an

effect on the water quality and chemistry of exfiltrated water but Fach and Geiger’s research is

one of the few available examples where the influence of aggregate on water quality has been

directly investigated. Over the course of a three year study Fassman and Blackbourn (2010b)

observed that joint and bedding sand migrated into the drainage pipes. They concluded that the

majority of all pollutants in water samples originated from sand material and not from inputs

from the surface.

With the exception of salts, the potential for groundwater contamination as a result of infiltration

through a PP system is low (Pitt et al., 1996). Salts, originating from road salting practices in

16

cold climates, are generally poorly attenuated and migrate easily through the pavement and

aggregate and, ultimately, to groundwater and surface water receiving systems. In underlying

soils, cation replacement (Na+ for Ca

2+ and Mg

2+) can lead to the leaching or mobilization of

several heavy metals and changes in physical soil structure (Marsalek, 2003). Elevated levels of

metals have been observed within exfiltrate in winter and early spring months, but were

attributed to increased loading rates at the PP surface (Boving et al., 2008; TRCA, 2008). Since

PP systems alter the timing, rate and volume of stormwater flows there may be opportunities to

dilute seasonally high pollutant concentration but these processes have not been sufficiently

assessed or critically evaluated.

A large body of research exists on the impacts of PPs on stormwater quality but conclusive

performance statistics are limited. The quality of statistical analysis within the published

literature remains variable and authors use a wide range of methods for interpreting results.

Standardized reporting methods would be beneficial in making the water quality benefits of PPs

more widely understood and accepted. The body of literature tends to emphasize percent

removals rather than residual pollutant concentrations and there has been limited analysis of the

variability of removal rates. There remain several research areas which require further

investigation including: the source, fate and transportation of nutrients, the effect of material

selection and drainage design on water quality, and the implications of stormwater infiltration on

groundwater quality. PP research on water quality has been lab-based or at a site scale. The

impact of catchment-scale installations of PPs and other LID practices on stormwater quality

have not been investigated, in part due to the rarity of implementation at that scale.

2.6 LONGEVITY & FUNCTIONALITY

The functional lifespan of a PP system is determined by the pavement’s ability to meet

hydrologic, water quality and other objectives. There are multiple mechanisms through which a

PP system can potentially fail. Firstly, if the pavement loses its permeability it will fail to meet

necessary hydrologic and water quality objectives. Structural failures, such as excessive heaving,

rutting, cracking and ravelling, can also prevent a pavement from meeting its functional

objectives, including aesthetic and safety standards. Finally, as a pavement ages, dynamic

pollutant removal mechanisms such as sorption, may ultimately be exhausted. If the capacity for

pollutant removal is significantly diminished, a PP system may fail as a result of its inability to

maintain the design stormwater quality objectives.

Clogging and Permeability Losses 2.6.1

PPs function as a passive filter and, as such, the filtration of particles and fines decreases the

pavement’s capability to infiltrate water over time. This process has been documented by

numerous authors, but all stress that the effects of clogging on permeability should be reversible

through the application of regular maintenance (Colandini et al., 1995; Baladès et al., 1995;

Yong et al., 2008; Pezzaniti et al., 2009). The presence or impact of biofilms has not been

addressed even though biofilm clogging could also reduce a PP system’s permeability

17

(Mothersill et al., 2000). Lab-based trials examining the clogging process of PPs and aggregates

(Illgen et al., 2007; Brown et al., 2009; Pezzaniti et al., 2009; Haselbach, 2010; Tan et al., 2003)

have confirmed that with repeated exposure to fines, clogging occurs and surface infiltration

rates decrease. These studies cannot provide realistic time estimates of the clogging process

because lab simulations do not replicate the natural conditions as experienced by full-sized PP

systems including the cycling of dry and wet conditions, biofilm growth, surface crusting,

chemical (e.g. oil and chloride) inputs, vehicular loadings, variable rainfall, application of

traction agents, and atmospheric deposition of sediments.

A reduction in surface permeability has a two-fold effect on the functionality of a PP system. If

stormwater cannot infiltrate at a rate which exceeds precipitation rates, ponding and surface

runoff will occur. Once a PP begins to behave as an impermeable surface the environmental

benefits of the system, including reductions in peak flows and volumes and removal of

stormwater pollutants, are lost. In order to prevent this outcome it is important to conduct surface

maintenance and remove clogging material before the hydrologic and water quality functions of

the system are significantly inhibited. Current knowledge does not allow for accurate prediction

or modeling of surface clogging. Table 2-3 illustrates the mixed experiences from experimental

and demonstration projects; in some cases PPs are shown to perform well even after multiple

years of use, whereas in other cases permeability reductions are observed after only one or two

years. In cold climates, pavements that are sanded as a result of winter maintenance have been

observed to experience drastic permeability reductions, potentially over the course of a single

winter (van Duin et al., 2008).

Observational studies have linked several conditions with rapid permeability reductions. Traffic

loads are a major contributing factor in clogging and pavements subjected to higher traffic rates

are more susceptible to permeability losses (James and Gerrits, 2003; Brattebo and Booth, 2003;

Boving et al., 2008). In some instances, the use of geotextiles may inhibit infiltration. Noted in

both field (Boving et al., 2008) and laboratory (Yong et al., 2008; Brown et al., 2009) studies,

under certain conditions, geotextiles can act as a filter that results in accumulation of fine

materials which form an impermeable barrier beneath the surface. There may also be conditions

that help sustain permeability, such as plant growth and leaf litter (James and Gerrits, 2003).

18

Table 2-3: Infiltration performance of aged PPs

Study Pavement Age

(years)

Measured

Surface

Infiltration

Details

Pratt et al.

(1995) PICP 9 >100 cm/hr Infiltration rates exceeded 100 cm/hr

Baladès et al.

(1995) PICP unreported

Infiltration rates dropped by 35-50% over

the course of two years

Kresin et al.

(1997) PICP 1-3 <1.5 cm/hr No significant infiltration

James and

Gerrits (2003) PICP 8 <1.5 cm/hr No significant infiltration

Brattebo and

Booth (2003) PICP, Porous Turf 6

No surface infiltration measurements were

performed.

PICP infiltrated all precipitation during the

study (max rain fall intensity = 7.4 mm/hr).

Abbott and

Comino-Mates

(2003)

PICP 2 1.3 cm/hr No significant infiltration

Bean et al.

(2007b)

CGP unreported 4.9 cm/hr

Median infiltration rate

PICP (visibly clean) unreported 2000 cm/hr

PICP (visibly clogged) unreported 8.0 cm/hr

PC (visibly clean) unreported 4000 cm/hr

PC (visibly clogged) unreported 16 cm/hr

Hou (2008) Unspecified 4 >560 cm/hr

TRCA (2008) PICP

2 122 cm/hr

10 9.6 cm/hr

17 3.4 cm/hr

4-13 Reported parking lots with ‘good’

infiltration based on qualitative observations

4-8 Reported 2 parking lots with ‘poor’

infiltration based on qualitative observations

Beecham et al.

(2009) PICP 7-12 18.6 cm/hr

The median infiltration rate was 18.6 cm/hr.

Infiltration rates ranged between 7-108

cm/hr

Henderson and

Tighe (2011) PC 2

Infiltration rates on 5 sites ranged between 0

and 1800 cm/h

Roseen et al.

(2012) PA 3 >111 cm/hr

An overall decline in infiltration rates was

observed throughout the study

Drake and

Bradford (2012)

PICP 7 <5 cm/hr

PC 4 <5 cm/hr

Clogging of PPs will remain a serious and legitimate issue limiting the mainstream use of PP as a

LID technology, as long as the process is poorly understood and cannot be effectively predicted.

Further investigation is needed to identify pavement designs which optimize pollutant retention

19

and clogging resistance. Tools for designers such as models which can accurately predict gradual

loss of permeability are needed. Some hydraulic modeling of PPs has been performed by Hohaia

et al. (2011) and Schlüter and Jefferies (2002) but these were short-term simulations and

therefore did not incorporate long-term surface clogging processes. Tan et al. (2003)

demonstrated that under lab conditions, where the gradation of the clogging material is known,

empirical equations can be used to model permeability reductions of aggregate base layers.

Analytical tools like these, used in combination with field observations, will assist engineers and

managers in planning and timing maintenance and safeguarding pavement from failures due to

clogging, while simultaneously eliminating the cost of unwarranted maintenance.

Effects of Frost 2.6.2

PPs have repeatedly been shown to function in cold climates in North America and Europe

(TRCA, 2008; Roseen et al., 2009; Tyner et al., 2009; Houle et al., 2010; Gomez-Ullate et al.,

2010). Roseen et al. (2009) observed only minimal changes in hydrologic performance between

summer and winter seasons for a PA parking lot. Observations throughout a winter season by

Tyner et al. (2009) noted that, even though air temperatures within sample plots of PC dropped

below freezing on several occasions, water was not present within the storage volume when

these temperatures occurred because the PP systems drain readily. It has been argued that PP

systems are more resistant to freezing and, thus, are also more resistant to frost heave than

impervious pavements (Bäckström, 2000). Stormwater exfiltration causes higher moisture levels

in underlying soils which increases the latent heat of the ground and postpones freezing within

the pavement (Kevern et al., 2009; Bäckström, 2000). Simultaneously, thawing processes are

expedited by melt water infiltrating from the surface (Kevern et al., 2009; Bäckström, 2000). In

combination, these two processes lead to shorter periods of frost and shallow frost penetration

reducing the overall risk of frost damage.

A two year study of a PA parking lot in Durham, NH (latitude of 43.11 N) by Houle et al. (2010)

at the University of New Hampshire found that the PP performed extremely well in a northern

climate. Neither the presence of frost nor freeze-thaw cycling affected the hydraulic integrity of

the system. Many sections of pavement sustained surface infiltration measurements above 635

cm/hr through the winter and all permeability losses observed during the study were caused by

mechanisms unassociated with frost, such as binder-drain down, over-compaction and the influx

of clogging materials. In a laboratory study using PA specimens, Bäckström and Bergström

(2000) simulated the worst-case scenario of rapid freeze-thaw cycling occurring concurrently

with precipitation. These simulations were designed to ensure that water froze within the PA

instead of draining. Under this extreme scenario, the PA lost 90% of its original permeability but

infiltration rates remained within 6 – 30 cm/hr which would be sufficient to infiltrate snowmelt

delivered gradually to a PP system.

Freeze-thaw cycling is the principal cause of pavement breakdown in cold climates (Roseen et

al., 2012). Poured PPs have experienced mixed success throughout cold climates. Many early PA

20

and PC installations experienced degradation such as cracking, rutting and ravelling but as mix

designs and construction practices improved poured PPs have become longer lasting (Roseen et

al., 2012). Winter durability of PC has been tested and evaluated by several researchers (Cutler,

et al. 2010; Guthrie et al., 2010; Kevern et al., 2010). Specimen testing has shown that damage to

PC as a result of freeze-thaw cycling occurs more rapidly when PC surfaces are clogged (Guthrie

et al., 2010). Exposure to deicers has been documented to cause scaling in PC. Cutler et al.

(2010) demonstrated that surface degradation is affected by deicer type (order of severity: CaCl2

> NaCl > CMA) and mix design. Specimen testing performed by Kevern et al. (2010) found that

acceptable freeze-thaw performance can be achieved by using aggregates such as granite or

highly durable gravel in PC mixes.

Long-term Pollutant Removal 2.6.3

Very few studies have evaluated the potential for declining pollutant removal with time. Brattebo

and Booth (2003) noted both positive and negative changes in water quality after six years of

use; concentrations of Zn in exfiltrated water increased while concentrations of Cu and Pb

decreased. While Zn is more soluble than Cu or Pb, to understand changes over time it is

necessary to understand the speciation of the metals which are removed and the likelihood of

remobilization (Murakami et al., 2008). In samples of road dust analysed by Murakami et al.

(2008), Cu was in the form of organic complexes and carbonates whereas Mn, Zn and Cd were

likely to exist in the form of free ions. Lab simulations suggested that the free metal ions of Mn,

Zn, and Cd were more likely to desorb from sediments (Murakami et al., 2008) supporting the

findings of Brattebo and Booth (2003). The relative mobility of Cd and Zn is given by their

common presence in stormwater in the metal species which may be readily mobilized by changes

in the ambient water chemistry (Marsalek et al. 2006). The capacity for pollutant removal over

time and the possibility of remobilization has important implications for the potential

contamination of groundwater systems.

Many researchers have noted that the majority of pollutants are captured near the pavement

surface and within the first few centimetres of porous media (Barraud et al., 1999; Legret et al.,

1999; James and Gerrits, 2003; Boving et al., 2008). Consequently, in terms of water quality

objectives, PPs are far more likely to fail as a result of surface clogging than due to storage

exhaustion. Pollutant concentrations in underlying soils measured by Legret and Colandini

(1999) noted no significant contamination below a PICP parking lot after 8 years of use. Soil

samples collected, by removing pavers and aggregate materials, below 7 parking lots by TRCA

(2008), also displayed minimal contamination. Lab-based simulations have estimated that even

after 50 years of stormwater infiltration the concentration of heavy metals in underlying soils

will remain below regulation thresholds (Legret et al., 1999). This evidence suggests that

infiltrated stormwater from PP systems is unlikely to significantly impact soil quality. The issues

of chloride impacts on the mobility of chemicals stored in PP structures, or the effects of toxic

spills, have not been fully addressed so far.

21

2.7 MAINTENANCE NEEDS

Maintenance is an essential practice for all infrastructure; it improves the day-to-day

functionality of the system and, ultimately, extends the operational life of individual

components. PPs operate as a dual system, providing pavement for transportation needs and

drainage/infiltration, storage and treatment for stormwater management; consequently,

maintenance practices must address both of these functional objectives. Sediment and debris

buildup within a PP system are inescapable outcomes of urban runoff and thus operational

activities such as monitoring, maintenance and rehabilitation are best management practices for

PP systems.

In regions where PP systems are niche products, with limited use, it is still commonplace for

property owners to operate the pavement solely as transportation infrastructure and to neglect the

maintenance which sustains the hydraulic functionality of the pavement. Improper maintenance

leads to a higher incidence of pre-mature failure because clogging materials are not removed in a

timely and regular manner and become embedded within the pavement. Loss of hydraulic

functionality, induced by a lack of maintenance, propagates the perception that PP systems have

a short effective life and do not provide reliable infiltration. Since operators are often unaware of

the maintenance requirements of their PPs, performance failures, arising from excessive surface

clogging, may be interpreted as inadequacies inherent to permeable product instead of

associating the failure with improper care.

The studies which have attempted to test maintenance techniques and evaluate their effect on

surface permeability (Baladès et al., 1995; Kresin et al., 1997; James and Gerrits, 2003; Van

Duin et al., 2008; Chopra et al., 2010a, 2010b; Henderson and Tighe, 2011) have mainly relied

on hand-held equipment. Typically, these studies have reported results from tests from one or

two parking lots and, therefore, results cannot be supported by statistical analysis or shown to be

repeatable. Tables 2-4 and 2-5 summarize the key findings of the studies that have evaluated

maintenance techniques. Many studies confirm that removing fines and sediments which collect

on or near the surface of a PP provides partial or full restoration of surface infiltration rates

(Kresin et al., 1997; James and Gerrits, 2003). Nevertheless there is insufficient knowledge with

respect to the overall effectiveness of commercially practical removal techniques for various

systems and conditions.

Baladès et al. (1995) were among the earliest researchers to test practical cleaning treatments on

PICPs. They noted that as clogging becomes more pervasive, more intensive cleaning treatments

are required and recommended suction for preventative maintenance and pressure washing for

rehabilitative maintenance. Henderson and Tighe (2011) tested surface treatments of multiple PC

parking lots in 2009 and recommended the practice of washing surfaces with a large diameter

hose to renew permeability. Henderson and Tighe (2011) also observed that other surface

treatments, such as sweeping with a push broom, vacuum sweeping with a shop-vac and power

22

washing, did not provide significant improvements to pavement permeability. Similarly, Chopra

et al. (2010a) found pressure washing to better rejuvenate PC cores than vacuum sweeping in lab

experiments. Chopra et al. (2010b) also conducted field tests with an Elgin Whirlwind MV truck

on five types of PPs (FlexiPave, PC, PA, and two types of PICPs) which had been artificially

clogged. High groundwater levels complicated the study and influenced results but observations

still showed that vacuum sweeping could restore some permeability. The research highlighted

that clogging processes and the effectiveness of subsequent rejuvenation practices is affected by

the type of PP (Chopra et al., 2010b).

Table 2-4: Observed effects of cleaning practice

Study Pavement Age

(years) Maintenance

Post Treatment

Infiltration

(cm/hr)

Level of Rehabilitation

Kresin et al.

(1997) PICP 1-3

Manual removal of

material in top 5

mm

0.77 (Site 1) Negligible change

4.0 (Site 2) An increase of 168%

James and

Gerrits

(2003)

PICP 8

Manual removal of

material in top 25

mm

Post treatment infiltration

rates for the 1st plot (Eco-

Stone 3") only improved in

areas of low traffic

Removal of material in top

25 mm provided partial

rehabilitation

Henderson

and Tighe

(2011)

PC 2

Large hose 70 - 1300

Over 90% of the treated area

displayed improvement.

Significant results were

observed.

Hand held

sweeping

Between 20% and 80% of

the treated area displayed

improvement. Results were

not significant.

Hand held

sweeping and

power washing

Between 50% and 90% of

the treated area displayed

improvement. Results were

not significant.

Chopra et

al. (2010a) PC

6-18 Hand held vacuum

sweeping 25.4

6-18 Pressure washing 145

6-18

Hand held vacuum

sweeping and

pressure washing

170

23

Table 2-5: Other maintenance investigations

Study Pavement Age (years) Maintenance Level of Rehabilitation

Baladès et

al. (1995) PICP

10 Wetting and sweeping Negative effect

Unreported Sweeping and vacuum sweeping Severely clogged surfaces showed no improvement. Moderately

clogged surfaces were rehabilitated after two passes

Unreported Vacuum sweeping Partial or full rehabilitation was achieved after two passes

Unreported Pressure washing Partial or full rehabilitation was achieved

Van Duin et

al. (2008)

PA <1

Schwarze A8000 Regenerative-air

truck (single dry pass) Maintenance decreased measured infiltration rates

Schwarze A8000 regenerative-air

truck (three wet passes) Pavement appeared to be irreversibly clogged

PICP <1

Schwarze A8000 Regenerative-air

truck (single dry pass)

Measured infiltration rates improved in some areas. Increases in

infiltration related to depth of joint material removed.

Schwarze A8000 regenerative-air

truck (three wet passes)

Measured infiltration rates improved in some areas. Increases in

infiltration related to depth of joint material removed.

Chopra et

al. (2010b)

PC Specimen

simulations

Loading of sand followed by Elgin

Whirlwind vacuum truck Full rehabilitation was achieved after two passes

Loading of limestone followed by

Elgin Whirlwind vacuum truck Partial rehabilitation was achieved

Flexipave Specimen

simulations

Loading of sand followed by Elgin

Whirlwind vacuum truck No significant effect

Loading of limestone followed by

Elgin Whirlwind vacuum truck No significant effect

PICP Specimen

simulations

Loading of sand followed by

vacuum Full rehabilitation was achieved after two passes

Loading of limestone followed by

vacuum truck

Vacuum sweeping restored infiltration rates at one location and

failed at a second location

PA Specimen

simulations

Loading of sand followed by

vacuum truck

The first pass of the vacuum sweeper improved infiltration rates

but repeated passes decreased infiltration

Loading of limestone followed by

vacuum truck No significant effect

Drake et al.,

(2012)

PICP 2 Elgin Whirlwind vacuum truck Single pass of the vacuum sweeper partially restored infiltration

rates

PC 2 Elgin Whirlwind vacuum truck No significant effect

24

Understanding and evaluating the effects of maintenance remains one of the most important and

pressing topics for PP research. Current work assessing maintenance tends to overemphasize the overall

effectiveness of specific maintenance practices and underemphasize uncertainties created by localized

conditions during data collection and experimental procedures. None of the published studies provide

any estimates of the overall effective-life of the studied PP systems, most likely because the reported

results are inconclusive. Based on review of the available literature several trends have been identified:

The effectiveness of cleaning treatments decreases with repeated exposure to clogging materials.

Clogging causes irreversible decreases in permeability. Based on existing publications, cleaning

practices are likely to provide partial restoration, but not full restoration of surface infiltration rates.

Within an individual PP system the effectiveness of maintenance is highly variable and inconsistent.

Large-scale effective maintenance practices have been successfully demonstrated under limited

circumstances.

The effectiveness of cleaning practices on surface permeability is dependent on PP type.

It is the authors’ conclusion that the current research does not provide sufficient evidence to conclude

that maintenance, as executed in the published studies, will provide a significant and lasting level of

restoration. Published works have almost exclusively reported results from isolated experiments and

long-term investigations are needed to help clarify the effects of regularly organized maintenance on the

overall effective-life of a PP system. Without reliable and repeatable evidence of the effects that

maintenance has on long-term functionality, comparisons to conventional pavements regarding

operational costs and effective lifespans remain highly questionable.

2.8 EMERGING RESEARCH AND RESEARCH NEEDS

Costing and Performance Studies beyond Site-Scale 2.8.1

Life cycle analyses and costing information is required to foster acceptance of PP systems as viable

mainstream alternatives to traditional impervious pavements and traditional drainage systems. As a dual

system, providing infrastructure for transportation and stormwater management, cost comparisons must

account for the drainage infrastructure that is replaced or reduced as a result of the infiltration and

storage provided by a PP system. Implementation of PP, along with other LID technologies, is impeded

by a lack of reliable and accurate cost data (Roy et al., 2008). Additionally, without verifiable effective-

life estimates and proven maintenance practices, the operational costs and true life-cycle cost of this

technology remain unclear. The cost-effectiveness of PPs and LID practices, as a whole, are scale-

dependent with the largest potential benefits resulting from distributed implementation of a combination

of LIDs and, thus, costing and life cycle analysis is needed at both the lot-level and the community-

level.

Decentralizing stormwater management through the application of PP systems, as well as other LIDs,

will only produce desired environmental outcomes if oversight and watershed-scale management exist.

Studies are needed at this large scale to demonstrate the capacity of PP systems to achieve and sustain

25

environmental benefits within the context of large urban catchments. PP systems installed in a piecemeal

fashion without due consideration of the implications to the larger watershed are unlikely to maximize

overall net environmental benefits (Roy et al., 2008). Note that an analogous argument can be made

about LID; so far, LID benefits have not been demonstrated in the receiving waters at the catchment

level (Roy et al. 2008). Assessment tools are needed to provide decision support for developers and

policy makers. There are only a few publications which demonstrate costing and decision-making tools

for LIDs (Montalto et al., 2007; Stovin and Swan, 2007). The authors of this review are not aware of any

life-cycle, cost assessments or selection tools which offer comparisons between alternative PP products.

Montalto et al. (2007) developed an assessment tool to evaluate the cost-effectiveness of various LID

systems, including PPs, as a means of reducing combined-sewer overflows using hydrological and cost

accounting methods. Although the Montalto et al. (2007) example applies only to combined sewer

systems, tools like this allow different design and management scenarios to be evaluated quickly

ensuring that environmental benefits are maximized and costs are minimized.

2.9 EFFECTS ON URBAN HEAT ISLAND

Urban centres often experience warmer conditions than their rural surrounding as a result of human

activities; this phenomenon is known as an Urban Heat Island. Studies monitoring pavement

temperatures have observed minor to moderate differences between permeable and impermeable

pavements offering evidence that PP systems may mitigate heat island effects. Asaeda and Ca (2000)

studied the surface and internal temperatures of several pavement materials during summer conditions

and demonstrated that a PICP, which has a higher reflectivity than asphalt can still have very similar

diurnal temperatures if the pavers have high thermal conductivity. In Asaeda and Ca’s study, a pervious

ceramic pavement produced cooler conditions than PICPs or asphalt. It was proposed that the smaller

pore size of the ceramic pavement retained more water near the surface increasing evaporation rates

during the day and keeping the pavement cool (Asaeda and Ca, 2000).

It is widely assumed that PP systems provide improved growing conditions for urban trees, compared to

impervious pavement, by supplying air and moisture to the root system. However, there is limited

evidence which has documented measureable increases in tree growth, health or longevity. Volder et al.

(2009) monitored growth rates of mature trees surrounded by asphalt, concrete and PC but did not

observe any significant differences in growth. Research results have not observed significant differences

in soil moisture underlying permeable or impermeable pavements (Morgenroth and Buchan, 2009;

Volder et al., 2009). Research has shown that plant growth is more affected by pavement design than

pavement type. Tree specimens monitored by Morgenroth (2011) had increased root growth beneath PP

systems designed with an uncompacted subbase and a gravel base, whereas PP systems without these

design features had growth rates that were comparable to impervious pavements. In a separate study of

seedling growth parameters, Morgenroth and Visser (2011) also concluded that PPs improve tree growth

only when the pavement design includes an uncompacted aggregate base.

26

2.10 CONCLUSIONS

Even though the study of PPs, as LID system components and infiltration practices, has been ongoing

since the 1980’s, PP products have not received widespread use throughout many parts of Canada and

USA. Their lack of mainstream use throughout Canada and USA reveals that developers, designers,

engineers and planners have not been given sufficient tools and knowledge to foster acceptance of this

technology. Stormwater engineering designs need to cope with uncertain risks and thus long-term PP

performance data should generate confidence that these systems can provide the same degree of safety

and reliability as traditional end-of-pipe stormwater management measures. Comprehensive summaries,

like this review, which outline the current state of knowledge are one instrument for promoting

understanding and acceptance of PPs. Industry can better communicate realistic product cost

comparisons, effective-life information and maintenance costs. Government agencies can develop

incentive programs to ensure that costs and benefits are fairly distributed between developers and

residents. And, lastly, design tools, long-term performance modelling and decision-making tools will

support designers and planners considering the use of PPs.

As public interest in PP systems grows there is an increased need to critically evaluate the performance,

practicality and, in some instances, the limitations of this technology. Throughout this review gaps in the

current research as well as future research needs have been identified and can be summarized as follows:

1. Further performance demonstration with partial-infiltration to low permeability soils is needed. The

impact of boundary conditions on infiltration and water quality has not been thoroughly investigated

and is a critical component in maximizing environmental benefits.

2. Analyses of impacts on water quality must become more sophisticated and extend beyond EMCs to

include total load reduction, censored data (i.e. concentrations below detection levels) and frequency

analysis.

3. The processes connected with permeability reductions remain poorly understood and prohibit the

development of accurate effective-life estimates. The effects of vegetation on PP functionality and

performance, and control of weeds invading PP, also require further study.

4. More critical assessments and testing of maintenance practices are required. Commerically-avaliable

equipment needs to be rigorously tested and repeatable results should be demonstrated. Different PP

types will likely require different maintenance practices and this has yet to be thoroughly examined.

5. Catchment and watershed-scale studies are needed to quantify the cumulative effects of multiple

installations on urban hydrology and water quality. Cost-analysis for the small and large-scale

adoption of PP systems is needed.

6. There is a continuing need for long-term studies to determine the performance and functionality of

PPs over time.

PPs have been successfully implemented in cold climates and areas with low permeability soils. The PP

systems discussed in this review have been shown to significantly mitigate many of the negative effects

of urban development. PPs alleviate stresses on receiving surface water by substantially reducing runoff

volumes, delaying flows and limiting peak flow rates. For small hydrologic events, PPs effectively

27

capture and infiltrate all precipitation, substantially limiting the overall frequency of urban runoff flows.

PP systems have proven to improve urban water quality by capturing suspended sediments and heavy

metals, and reducing waste heat input into receiving waters. PPs capture and treat hydrocarbons and

under certain conditions promote favourable nutrient transformations. So far, large potential benefits to

surface water quality have been shown while, with the exception of chlorides in cold climates, risks to

receiving groundwater systems and soils appear to be limited.

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34

3 HYDROLOGIC PERFORMANCE OF THREE PARTIAL-INFILTRATION

PERMEABLE PAVEMENTS IN A COLD CLIMATE OVER LOW

PERMEABILITY SOIL

3.1 ABSTRACT

The hydrologic performance of three partial-infiltration permeable pavement (PP) systems was

evaluated at the Kortright Centre for Conservation in Vaughan, Ontario, over 22 months. The native

soils at Kortright are composed of clayey silt and silty clay till, with clay content ranging from 7 to 30%.

Flow restrictors on the underdrains were adjusted to the smallest orifice possible to assess the potential

for stormwater outflow volume reductions. The hydraulic behaviour of the PP systems was compared

with runoff from an asphalt parking lot control. Peak outflow rates from PP were 91% smaller than peak

flowrates of asphalt runoff on average, and attenuation of stormwater was observed during all seasons.

Stormwater was found to infiltrate at the surface of the PP systems throughout two winters. Increases in

outflow were observed during periods of seasonal thawing due to the delayed release of infiltrating

stormwater. But overall, the PP systems (with restricted flows from the underdrains) reduced stormwater

outflow volume by 43% and completely captured (i.e., infiltrated and evaporated) most rainfall events

that were less than 7mm in depth. The study confirmed that PP systems improve stormwater outflow

regime characteristics and demonstrated the capability for partial infiltration systems to achieve outflow

volume reductions where native soils have low permeability. These volume reductions are important for

achieving water quality benefits as well as improving hydrologic performance.

Keywords: permeable pavements, hydrology, infiltration, winter, low permeable soil

3.2 INTRODUCTION

Permeable pavements (PP) are dual-purpose systems that provide paved surfaces for pedestrian and

vehicular traffic as well as infiltration and storage capabilities for local stormwater management. PP

systems consist of a permeable hard pavement surface, aggregate bases, and in some cases geotextiles.

They help to mimic pre-development flow conditions by delaying stormwater flows and reducing runoff

volumes and peak flow rates (Ferguson 2005; CVC and TRCA 2010). In areas where full infiltration to

native soils is not possible, many environmental benefits can still be achieved by PP systems with

underdrains (Collins et al. 2008; Pratt et al. 1995). PP may be designed for full, partial or no infiltration

to native soils. In a partial-infiltration system, underdrains collect and convey infiltrating stormwater out

of the system whenever the infiltration capacity of the native soil is exceeded.

The hydrologic performance of PPs exposed to natural weather conditions and traffic loadings have been

investigated (Field et al., 1982; Pratt et al. 1989; James and Gerrits 2003; Brown et al. 2009; Gomez-

Ullate et al. 2010). A conventional asphalt pavement is often used as a control to examine performance

differences between permeable and impermeable pavements. Side-by-side testing allows for

performance comparisons between different PP products exposed to conditions and loadings as similar

as possible in a real setting (Bean et al. 2007; James and Thompson 1997; Booth and Leavitt 1999;

35

Brattebo and Booth 2003). Drake et al. (in press) provides a current review of the state of the knowledge

in PP research and highlights gaps in the existing research. There has been little side-by-side testing of

poured and interlocking permeable products. However, in a 14 month study of 56 events, Collins et al.

(2008) monitored the hydraulic behaviour of four underdrained PP products and an impervious asphalt

pavement in North Carolina. Two of the tested PP did not significantly reduce outflow volume but all PP

significantly reduced and delayed peak flows. High volume reductions from two of the monitored PPs

were attributed to an elevated underdrain which increased exfiltration to the native soil, as well as sand

in one of the cells, which retains water more effectively than crushed stone aggregate. These results

suggest that there are opportunities to enhance stormwater volume reduction provided by PP systems

through the design and operation of underdrain and outlet controls.

In cold climates, such as Canada, side-by-side studies of PP systems are needed to test winter

performance of different products. In individual studies PP systems have been repeatedly shown to

function well throughout winter months. Houle et al. (2010) and Roseen et al. (2009) demonstrated that

porous asphalt and pervious concrete parking lots in New Hampshire were capable of infiltrating

stormwater throughout a winter season and the presence of frost did not hinder hydrologic performance,

since even frozen coarse pavement and aggregate bases retained significant permeability. A two-year

study of a parking lot built with permeable interlocking concrete pavers (PICP) in Ontario by the TRCA

(2008) demonstrated that the system was capable of infiltrating stormwater to underdrains during winter

rain events. While these studies have provided promising results, other cold-climate research has

identified that PP deteriorate more rapidly when exposed to winter salting and sanding (Brown et al.

2010, Henderson 2012). Additional research is needed to improve designs and operational practices for

PP systems in cold climates and to confirm the hydrologic behaviour of these systems at sites with a

variety of conditions.

The hydrologic benefits of partial-infiltration PP systems, in which some stormwater infiltrates to native

soils and some stormwater is collected by underdrains and conveyed to a receiving surface water system,

are not thoroughly understood. PP systems have not been widely installed over low permeability soils,

because of structural concerns regarding soil stability and strength and because of the belief that without

substantial infiltration into native soils the environmental benefits of PP systems would be negligible.

However, structural concerns can be overcome with diligent analysis and proper design of base layers

and the hydrologic benefits of PP systems over low permeability soils warrant investigation.

Researchers Dreelin et al. (2010) and Fassman and Blackbourn (2010) attempted to demonstrate and

evaluate the hydrologic performance of partial-infiltration PP systems over low permeable soils.

However, both studies experienced higher than anticipated permeability due to heterogeneous soils.

Dreelin et al. (2006) monitored a grassed PP over clay-rich, but well-draining, soils in Georgia for nine

rainfall events over four months. The PP was shown to reduce runoff by 93% during the study. Fassman

and Blackbourn (2010) monitored outflow from a PICP installation over silty clay and clayey silt soils in

New Zealand for 81 precipitation events. Median runoff coefficients (i.e., runoff volume/rainfall

volume) for the asphalt and PP were 0.85 and 0.49, respectively. Volume losses within the PP were

attributed to evaporation, leakage to a perforated road drain and exfiltration to the subgrade soil. .

36

Verifying and quantifying the hydrologic benefits of partial-infiltration systems is critical to justify the

use of PP rather than traditional stormwater management systems. The objective of this study is to

address the current gaps in understanding hydrologic performance of PP in cold climates and over low

permeability soils. The study seeks to confirm performance with respect to peak flow reductions and

further assess potential volume reductions. This research evaluates the hydrologic performance of three

different PP systems over consecutive seasons in terms of total outflow volume, peak flow and detention

times.

3.3 METHODOLOGY

Site Design 3.3.1

The PP parking lot is located at the Kortright Centre for Conservation in Vaughan, Ontario. Constructed

over the fall of 2009 and the spring of 2010, the facility consists of four pavement cells which are

each 230-233 m2 in size with a capacity for 8-10 parked vehicles (Figure 3-1). Two cells were

constructed with permeable interlocking concrete pavements (PICP), AquaPave® (AP) and Eco-

Optiloc® (EO); one cell was constructed with Hydromedia® Pervious Concrete (PC) supplied by

Lafarge; and one cell was constructed with traditional asphalt (ASH). The pavement cells are separated

by a raised concrete curb that extends below surface to native soils preventing the cross-flow of

stormwater. Aggregate reservoirs (Figure 3-2) were constructed with layers of 19 mm and 50 mm

diameter clear stone following Ontario Provincial Standards and providing a combined depth of at least

40 cm. The EO pavement has joints that are 13 – 14 cm wide and uses 1 – 9 mm diameter high-

performance bedding (HPB, also known as ASTM No. 9 aggregate) as joint and bedding material,

whereas the AP pavement has joints that are 3 – 4 mm wide and uses HPB as bedding and Engineered

Joint Stabilizer (diameter ~ 2 – 3 mm, fitness modulus = 2.47) as joint material. The AP pavement also

includes an Inbitex® geotextile placed between the bedding and aggregate layers. The Inbitex geotextile

had an apparent opening size of 0.145 mm and a mean flow rate of 4800 L/min/m2. Vegetated berms

approximately 5 to 6 m wide with mature trees line the north and south sides of the parking lot and

approximately half of the berm area slopes towards the pavement.

The parking lot was plowed and salted during winter months by park staff. Snow was plowed

longitudinally from the ASH to the PC cell and vice versa. Snow was generally piled at the four

corners of the parking lot on the vegetated berms and adjacent to the asphalt and PC pavements.

37

Figure 3-1: Site schematic

(a)

38

(b)

(c)

Figure 3-2: Vertical cross-sections of PICP (a), PC (b) and Concrete Curbs (c)

39

Each PP cell was drained by a 100 mm diameter Big O perforated tubing placed at the base of stone-

filled trench (19 mm diameter clear stone) at the interface between the aggregate reservoir and the native

soil. The ASH cell was drained via a catchbasin and piped to a downstream sampling vault. Infiltrated

stormwater collected from each PP cell was conveyed separately in sealed pipes (at a 1% slope) to the

sampling vault. Concrete pipe collars at cell boundaries prevented water movement along granular

trenches surrounding the pipes. A Mirafi Filter Weave® 500 geotextile was placed below the aggregate

base to prevent soils from migrating up into the aggregate layer. The Mirafi geotextile had an apparent

opening size of 0.30 mm and a mean flow rate of 1426 L/min/m2. Inside the monitoring vault, underdrains

for each cell were fitted with gate valves as flow restrictors to control the rate of drawdown after storm

events and prolong the period over which infiltration can occur. PP flow restrictors were set, manually,

to the smallest orifice possible, approximately 1 mm wide, in order to maximize the detention of

stormwater within the PP systems and evaluate a drainage design capable of achieving volume

reductions even with low permeability native soils. Shallow wells that extended down to the base of the

aggregate were installed along one edge of each PP cell (shown in Figure 3-1 as W1, W2 and W3) and

adjacent to the central drainage pipes (shown in Figure 3-1 as W4 and W5). The respective depths for

W1-W5 were 32.5 cm, 43 cm, 40.8 cm, 65 cm and 95 cm. The base of the well was uncapped and buried

slightly into the native soils. The wells were surrounded with bentonite at the surface and screened over

their entire length. Geotechnical investigations were completed by Terraprobe Limited in the summer of

2008, prior to construction. Four shallow boreholes were drilled to depths ranging between 2.4 m and

3.1 m, and samples were collected from the boreholes using a split-barrel sampler advanced by a 63.5 kg

hammer dropping approximately 760 mm (Terraprobe, 2008). The borehole samples found silty clay

with frequent gravel inclusions and clayey silt till below the pre-existing parking lot pavement and fill

(Terraprobe, 2008). Glacial till soils, which are typical in this area, are often interspersed with cobbles

and boulders in addition to gravel inclusions (Terraprobe, 2008). Clay content in the samples ranged

between 7 and 30% (Terraprobe, 2008). The hydraulic conductivity of silty clay till materials typically

ranges between 10-4

and 10-6

cm/s (Das, 2007). Field saturated hydraulic conductivity, measured on-site

using a Guelph permeameter, ranged from 2.0 x 10-3

cm/s to 5.87 x 10-6

cm/s. The boreholes did not

encounter ground water; no subsurface water entered the excavation during construction and nearby

well records indicates that the seasonally high water table lies several meters below the pavement

surface.

Monitoring and Data Collection 3.3.2

Testing of the collection infrastructure and monitoring equipment was conducted between June and

August 2010. Monitoring of the pavements was conducted over 22 months between September 2010 and

June 2012. Rain data were collected at 5 minute intervals with a resolution of 0.2 mm and an accuracy

of ±2-3% from Campbell Scientific TB4 gauges placed in nearby fields. During the winter, precipitation

data were collected by a heated rain gauge located at the Albion Hills Conservation Area approximately

22 km north-west of the study site. Stormwater outflow from the collection pipes was monitored with

Geneq V2A-tipping counters. Measurements were recorded once a minute and had a resolution of 3 L.

Tipping counters were checked prior and after installation to confirm that they were functioning

40

properly and tipped when filled with 3 L of water. A gate valve was used and set such that the flow rate

of runoff from the ASH pavement would not exceed the maximum measurement threshold of the flow

gauge (60 L/min) before the catchbasin became inundated with water. For high intensity rainfall, when

the catchbasin flooded, a vertical bypass pipe installed inside the vault allowed water to flow through an

overflow pipe that was at the same elevation as the catchbasin grate. Flows were measured with a

Dynasonics Series TFXL flow meter which was tested upon installation. Power outages lasting more

than 24 hours at the site led to a loss of flow data for three summer storms (July 20-23, 2010; June 8-9,

2011; August 4-5, 2011).

Wells W1-W3 were equipped with Diver DI 240 water level loggers while wells W4 and W5 were

equipped with Onset Hobo U20 water level loggers. Water level data were collected at 5 minute

intervals with an accuracy of ±0.5 cm. Throughout the study, observations were recorded by the

Conservation staff regarding the presence of ponding. The installation of a surveillance camera in the

spring of 2011 also provided some daytime video of the parking lot.

For eight events during the study period, the flow restrictors on the PP underdrains (i.e., gate valves)

were closed. These closed-valve tests were performed in November 2011 and April/May 2012. They

were intended to explore the effect of extending detention of stormwater within the PP systems on

outflow volume, giving time for the stormwater to infiltrate and, potentially, evaporate. The detention

time depended on weather conditions and ranged from 32 hours to 15 days. At the end of a closed-valve

test the gate valves were opened fully and stormwater was allowed to drain freely from the PPs. The

total volume of outflow from the underdrains was recorded. Once the PPs were drained, the gate valves

were closed again in preparation for the next test. Due to the presence of glacial till soils it was unknown

if high infiltration would occur in localized areas with coarse material. Drawdown of water levels within

the monitoring wells provided additional evidence that the infiltration rates of the native soils were truly

representative of low permeability conditions. The drawdown rates observed in W5 ranged between 6.5

x 10-5

cm/s and 1.2 x 10-4

cm/s which, although not directly comparable, are within the right order of

magnitude for hydraulic conductivity for silty clay soils. Variation in drawdown rates is due to

differences in antecedent conditions, precipitation inputs and evapotranspiration rates between events.

In the spring each year, the surface infiltration capacity of the PPs was measured following the methods

described in ASTM C1701. Eighteen measurements were collected from each pavement and

measurements were always repeated at the same location within the pavement.

Data Analysis 3.3.3

Analysis methods were based on the recommendations for Low Impact Development (LID) monitoring

presented in the EPA Urban Stormwater BMP Performance Monitoring Manual (2009). For each

precipitation or melt event, hydrologic characteristics for outflow and runoff (volume (VT), unit volume

(Vunit), peak flow (QP), time to hydrograph centroid (tC)) were calculated and used to estimate total

volume and peak flow reductions, lag times and lag coefficients (Equations 1-5). For this study, a runoff

event is defined as the period from the start of surface runoff to the end of surface or underdrain

stormwater flow. To ensure that analysis of hydrologic data was consistent with previous local studies

41

(i.e., TRCA, 2008) underdrain flow less than 3 L/hr (i.e., less than one tip per hour) was used as the

condition to identify the end of individual hydrologic events. The response time of the PPs is often

several days; therefore, ‘events’ can include multiple discrete precipitation and asphalt runoff events.

Most outflow events lasted 24 hours or longer. Although flow data were collected at one-minute

intervals, analysis was performed using one-hour intervals. The larger time step allows for more

meaningful presentation of the results since differences in flow rates and timing are not evident at high

temporal resolutions.

Total Unit Volume, L/m2:

(Equation 1)

Percent volume reduction, % (VR):

(Equation 2)

Percent peak flow reduction, % (QR):

(Equation 3)

Lag time, hr (tl):

(Equation 4)

Lag coefficient (kl):

(Equation 5)

Statistical analysis was performed using the EPA’s ProUCL .1 statistical software as well as the open-

source statistical computing language and environment R. Non-parametric analysis was performed when

data did not conform to a normal or lognormal distribution. All analysis was performed for 95%

confidence.

3.4 RESULTS AND DISCUSSION

Tests of Homogeneity 3.4.1

A meaningful evaluation of different PP products is dependent on having comparable inflows. All three

pavements were exposed to the same precipitation inputs, are nearly identical in size and drain to the

same soil types. Therefore it would be expected that for a given event the underdrains would collect the

same volume of stormwater and that the total volume of water collected in the underdrains would be

split evenly. Tests to evaluate the hydraulic separation of the PP cells were performed early in the study

and repairs were performed as necessary. At the completion of the study 34% of the total observed storm

flows originated from the PC drain, 42% from the EO drain and 24% from the AP drain. It is possible

that some of the stormwater which infiltrated in the AP pavement found its way into the EO underdrain.

However, a variety of other factors could contribute to the observed variability in hydrologic responses,

including differences in flow through the control valves due to partial or temporary clogging of the

orifice (which was set at approximately 1 mm), differences in the products or as-built cell designs,

and/or variability associated with underlying soils.

42

Precipitation Data 3.4.2

In total, over 1483 mm of precipitation was recorded over 164 rain and snow events for which 127

discrete outflow events were identified. Descriptive statistics for the precipitation data are presented in

Table 3-1. Normal annual precipitation for this region is 792.7 mm, equivalent to 1431.6 mm for a 22-

month period analogous to that of the study (Environment Canada, 2012). The most intense rainfall from

which outflow was successfully measured was a 10 mm 30 min (21.8 mm/hr) summer storm. The largest

rainfall intensity recorded during the study was 7.6 mm in 5 minutes (9.12 cm/hr).

Snow accumulation during Winter 2011/2012 was uncharacteristically low. Significant accumulation

did not occur until the end of December and only 40.8 mm of snow was recorded for the entire season

(Environment Canada, 2012). As a result, approximately 90% of the 2011/2012 winter precipitation was

rainfall. Thirty year precipitation normals for this area from the nearest Atmospheric Environment

Service station show precipitation depths of 213 mm from December to March. Actual precipitation

during these four winter months measured at the same AES station in 2011/12 was 30% lower, at 150.8

mm. Air temperatures were also warmer, with average temperatures from December to March of

roughly 1.4 °C, well above the 30 year normal of -4 °C.

Table 3-1: Precipitation statistics

Statistic Depth

(mm)

Intensity

(mm/hr)

Duration

(hr)

Antecedent

Rainfall (days)

Max 51.6 21.8 123.3 15.8

Mean 10.7 1.4 18.0 2.9

Median 7.0 0.7 10.0 1.9

STD 11.1 2.3 22.3 3.0

CV 1.04 1.64 1.27 1.03

Infiltration into the PP 3.4.3

Direct runoff was not observed from any of the PP cells during this study. Surface infiltration capacity

was different for each pavement and declined over the course of the study. Table 3-2 summarizes

general statistics for surface infiltration measurements. After two years of use, measured median surface

infiltration rates for AP, EO and PC pavements were 20 cm/hr, 94 cm/hr and 1072 cm/hr, respectively

and remained well above the maximum recorded rainfall intensity. Based on staff observations, AP has

been more susceptible to temporary ponding than EO or PC. Ponding of slushy melt water was

infrequently noted during both winters on AP. The narrow joints of this pavement may be more

susceptible to icing. The sporadic winter maintenance at Kortright may have contributed to the ponding

and it might not have been observed had regular plowing and salting occurred. During the summer

temporary ponding for less than an hour has also been observed over the AP pavement during a few

intense storms. These events may have been affected by run-on caused by surcharging of the adjacent

catchbasin in the ASH cell, which occurred occasionally during very intense rain events. Ponded

stormwater ultimately infiltrated into the pavement for all of these incidents.

43

Table 3-2: Surface infiltration statistics

Year Statistic AP EO PC

# of measurements 18 18 18

2010

Range 38-419 140 – 945 460-5700

Median 155 504 2120

Mean 151 520 2330

STD 93 267 1330

CV 0.62 0.51 0.57

2011

Range 35-341 40-711 123-5364

Median 118 230 1340

Mean 136 294 1790

STD 85 221 1460

CV 0.63 0.75 0.82

2012

Range <5 – 164 6-382 21-4580

Median 20 94 1070

Mean 34 140 1360

STD 41 117 1150

CV 1.2 0.84 0.85

Outflow Volume 3.4.4

The partial-infiltration PP systems reduced the volume of stormwater directed to receiving surface water

systems by permitting infiltration and some evaporation. The total volume of stormwater, observed over

the study, from the PP underdrains was 43% smaller than the total volume of runoff from the ASH

pavement. This translated into 132 kL of stormwater infiltrating to the native soils or evaporating.

Previous studies of PP systems have reported volume reduction ranging from 25 – 75% (Drake et al., in

press). Lined PP systems which do not allow for any exfiltration to native soils have been observed to

have underdrain outflows which are still 20 to 50% smaller than rainfall volumes (Pratt et al. 1995). The

reduction of stormwater volume is thus a result of moisture retention and evaporation from the PP. The

volume reductions observed in this study were comparable to a lined system indicating that the total

exfiltration into the low permeability soils was small. The presence of native soils however did not

inhibit substantial reductions in total stormwater outflow volume.

Strong agreement was observed between monthly stormwater volumes produced by the PICPs and the

PC (Figure 3-3). During the spring, storm flows from the PC underdrain tended to be larger than those

from the PICP underdrains. Melting snow piles located along the edge of the PC were likely a

contributing factor and may have resulted in additional stormwater input for the PC cell. The boundary

conditions, including the gate valve and underlying soils, exert much more influence over the PP system

hydrology than the internal components of the PPs and consequently all three products provide similar

benefits in terms of volume reduction.

The PPs were observed to reduce the frequency of storm flows. During warm months, small

precipitation events with less than 7 mm of rainfall did not initiate outflow from the PP underdrains.

Similar hydrologic behaviour has also been reported by Collins et al. (2008) who noted that PP

44

underdrains did not generate discharge from rain events that were less than 6 mm. The infiltrated

stormwater was completely captured through wetting of the aggregate, infiltration to native soils and

evaporation. During the winter, mid-day runoff of melt water was regularly produced from ASH

pavement while the PP underdrains remained unresponsive. In total, 32 storms (43% of spring-summer-

fall events) and 31 thaws (60% of winter events) were completely captured by the PPs, representing 16

kL of stormwater. Reducing the frequency of small storm flows has important implications to the water

quality of receiving systems. Eliminating runoff and underdrain outflow prevents the migration of highly

concentrated pollutants within a small volume of stormwater.

A reduction in stormwater volume provided by the PPs was observed for most hydrologic events and

paired t-tests of log-transformed data showed that PICP and PC event volumes were significantly

smaller than ASH event volumes (PICP: p < 0.001, PC: p < 0.001). The percent volume reduction (VR)

for individual events (Figure 3-4) varied substantially depending on storm characteristics, antecedent

conditions and season. Despite a warm 2011/2012 winter, similar seasonal patterns were evident during

both the 2010/2011 and 2011/2012 winters. Negative VR occurred during periods of sustained thawing

and were typically preceded by events with very high VR. This pattern suggests that during the winter,

melted stormwater infiltrates more slowly through the PP system and maybe released days or weeks

later. Outflow volume results are included in Table 3-4.

Figure 3-3: Monthly stormwater volume and volume reduction, VR (VR not calculated for June

2011 due to data losses associated with power outage)

-120-100-80-60-40-20020406080100120

0

10000

20000

30000

40000

50000

Sep

-10

Oct

-10

No

v-1

0

Dec

-10

Jan

-11

Feb

-11

Mar

-11

Ap

r-1

1

May

-11

Jun

-11

Jul-

11

Au

g-1

1

Sep

-11

Oct

-11

No

v-1

1

Dec

-11

Jan

-12

Feb

-12

Mar

-12

Ap

r-1

2

May

-12

Jun

-12

VR

(%

)

Sto

rm

wate

r V

olu

me (

L)

ASH PC PICP PICP VR PC VR

45

Figure 3-4: Individual event volume reduction, VR

Detaining the stormwater during the closed-valve tests resulted in larger VR. Individual event VR

ranged between 72% and 100% and averaged 83%. Regression analysis found a statistically significant

linear relationship (p < 0.001) between ASH runoff and PP outflow for warm season data. This

relationship (shown in Figure 3-5) was expected as runoff and PP outflow are both determined by

rainfall depth (Collins et al., 2008). Using the linear relationship observed, PP outflow from the closed-

valve tests could be compared with predicted volumes and evaluated for statistical significance. Only

two of the tests produced outflow that was not statistically different from predicted outflow volumes.

These were small storms below the range where the relationship between precipitation and outflow was

expected to be valid. The six other tests produced smaller outflow volumes, and therefore larger VR,

which were below the lower 95% confidence boundary of the linear PP outflow vs. ASH runoff

regression line. These results demonstrate that additional volume reductions can be achieved by

temporarily detaining stormwater with the PP.

Figure 3-5: Linear regression permeable pavement outflow vs. ASH runoff volumes: observed and

predicted volumes for closed-valve tests

-200

-150

-100

-50

0

50

100

10/8/10 18/11/10 26/2/11 6/6/11 14/9/11 23/12/11 1/4/12 10/7/12

VR

(%

)

PICP

PC

R² = 0.7982

0

2000

4000

6000

8000

10000

12000

14000

16000

0 5000 10000 15000 20000 25000

PP

Ou

tflo

w (

L)

ASH Runoff (L)

Observed

Valve open to 1 mm

Predicted outflow

46

Outflow Rates and Detention 3.4.5

The PPs provided attenuation during all seasons and individual precipitation events. Table 3-3

summarizes general statistics for hourly peak flow rates (QP) and peak flow reductions (QR). Sign tests

found that the PP peak flow rates were significantly less than ASH peak flows. Peak flow reductions

(QR) were very high and consistent throughout the study, averaging 91%. This result was slightly higher

than results reported by Roseen et al. (2008) who found that a porous asphalt parking lot had an annual

peak flow coefficient of 0.18 (or QR = 82%). Variations in flow rates between the three PP systems

were minor relative to the difference between runoff from asphalt and PP. The largest instantaneous

outflow recorded from a PP outlet was 24 L/min and occurred during a 20 mm rain event which was

composed of a series of short and intense periods of rainfall (10 mm of rain fell within 195 minutes, an

intensity of 3 mm/hr, followed six and a half hours later by an additional 5 mm within 115 minutes, an

intensity of 2.6 mm/hr). The maximum instantaneous peak flow occurred during the second period of

intense rainfall when the PP had already infiltrated 10 mm into the aggregate reservoir. Nevertheless, the

PP provided significant QR and the overall QR for the event was still 88%.

Table 3-3: Hourly peak flow statistics

Parameter Statistic ASH AP EO PC

QP (L/hr)

Max 3810 426 393 276

Median 965 103 102 102

Mean 1592 96 123 102

STD 675 752.2 86.8 65.5

CV 0.58 0.75 0.71 0.64

QR (%)

Min

68 51 50

Median 93 89 92

Mean 91 86 88

STD 7.6 11.4 10.7

CV 0.08 0.13 0.12

Flow responses, as illustrated in Figure 3-6 with clearly visible primary and tail flow behaviour, were

most frequently observed from the EO underdrain with 70% of events exhibiting this pattern. A third of

all events from the PC outflow also had two-stage responses. Tail flows were not observed from the AP

outflow. Overall, tail flows represented only 5% and 3% of all outflow from EO and PC, respectively.

Tail flows have been previously observed in PP systems over low permeability soils (TRCA, 2008).

Although tail flows do not significantly influence VR or QR estimates they can greatly skew the

centroid of outflow hydrographs, increasing estimated tl and kl for an event. As an illustration the EO tail

flows lasted for 11 hours shifting the hydrograph centroid by 2 hours (Figure 3-6).

As shown in Figure 3-7, the shape of outflow hydrographs closely mirrors the water level patterns

within the aggregate. The beginning and end of the primary flow response coincide with rapid increases

and decreases in water levels. Elevated water levels, which indicate saturated conditions within the

lower aggregate, were not observed during the tail response suggesting that these flows represent

draining of residual moisture from the unsaturated aggregate and pavement. Table 3-4 outlines overall

and seasonal outflow duration statistics. Hydrograph shape and characteristics of partial-infiltration PP

47

systems have important implications to receiving water systems. Tail flows, originating from numerous

installations, may provide an important source of baseflow between rainfall events within a developed

watershed. This hydrologic feature could contribute to sustaining in-stream conditions, such as

temperature, wetted-width, depth and longitudinal connectivity that are needed to maintain the

ecological functions of the receiving water system during periods of low-flow.

Figure 3-6: Example of a two-stage response in EO and the impact on hydrograph parameters

Figure 3-7: Example of PP flows and water levels above the underdrain

0

0.02

0.04

0.06

0.08

24/6/12 25/6/12 26/6/12 27/6/12

Hou

rly

Flo

w (

L/s

)

EO

Tail Flows

Primary Flows

-100

-80

-60

-40

-20

0

20

40

60

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

25/7/11 26/7/11 27/7/11 28/7/11

Wate

r L

evel

(cm

)

Hou

rly F

Low

(L

/s)

AP OutflowEO OutflowPC OutflowW5 Water Level

48

Saturated conditions within the aggregate, based on well water levels, were frequently observed in W4

and W5 but not in W1-W3, which were installed to shallower depths near the edge of the cells (Figure 3-

1). The highest recorded water level at W5 was 53 cm, which occurred on May 15th

, 2011 during a 38

hr, 46 mm rain event. Elevated water levels within W1-W3 were only observed during March 2011; the

depth in the EO edge well, which is 43 cm deep, briefly reached 29 cm. The water level data have

shown that the available storage within the PP systems is significantly larger than the hydrologic

requirements of any precipitation events recorded during this study.

Flow responses were attenuated by the PP relative to the asphalt runoff. Lag times (tl), presented in

Table 3-5 for the asphalt and PPs ranged between 0.75 hr and 89 hr (3.7 days) and lag coefficients (kl)

for PPs ranged between 1.0 and 46. The highest kl values resulted from summer storms with short

durations and high intensities. There was essentially no detention of stormwater on the asphalt

pavement. As visible in Figure 3-5, the timing of outflow from the three PPs was often very well

matched, but small differences in detention time were observed over the study and, generally, increased

in the order of AP < EO < PC. Permeable products with smaller void areas have been shown to increase

attenuation (Anderson et al. 1999) but, in fact, the opposite pattern was observed at the site. The coarse

aggregate layers with smaller aggregate size offered no observable benefit to flow detention. Seasonal

differences in attenuation were apparent; however, the PPs continued to provide significant detention of

stormwater throughout the winter, with median lag ratios for AP, EO and PC of 1.6, 2.2 and 2.1,

respectively. The PPs were found to attenuate flows during spring thaws as illustrated by the March

2011 flows in Figure 3-8.

Figure 3-8: Flows during spring thaw, February 28 – April 6, 2011

0

0.05

0.1

0.15

0.2

0.25

0.3

26/2/11 3/3/11 8/3/11 13/3/11 18/3/11 23/3/11 28/3/11 2/4/11 7/4/11

Aver

ag

e H

ou

rly

Flo

w (

L/s

)

Average PP

ASH

49

Table 3-4: Hydrograph characteristics

Parameter Statistic

Overall Spring to Fall Winter

ASH AP EO PC ASH AP EO PC ASH AP EO PC

# of events 127 56 64 63 75 41 43 42 52 15 21 21

Volume (L)

Max 16 038 13 503 22 416 31 542 10 968 13 503 8 667 8 511 16 038 8 607 22 416 31 542

Mean 2 058 1 935 2 430 2 616 2 536 2 024 2 170 2 331 1 369 1 690 2 961 3 184

Median 1 221 1 333 1 662 1 830 1 831 1 221 1 674 2 019 257 1 260 1 383 1 248

STD 2 520 2 283 3 023 4 081 2 378 2 372 1 665 1 660 2 580 2 076 4 768 1 248

CV 1.2 1.2 1.2 1.6 0.9 0.9 0.8 0.7 1.9 1.9 1.6 2.1

Duration (hr)

Range 1 – 249 6 – 284 21 – 593 10 – 591 1 – 74 6 – 57 27 -143 13 – 144 1 – 249 11 – 284 21 – 593 10 – 591

Mean 16 33 82 75 14 26 65 55 19 51 123 124

Median 8 28 65 54 9 24 59 50 6 33 79 99

STD 26 37 77 81 13 12 25 36 37 67 131 131

CV 1.6 1.1 0.9 1.1 1.0 0.5 0.4 0.6 1.9 1.3 1.1 1.1

Table 3-5: Attenuation characteristics

Timing Statistic

Overall Spring-Fall Winter

AP EO PC AP EO PC AP EP PC

# of events 57 63 64 42 45 46 15 18 18

tl (hr)

Range 0.75-46 6.0-89 5.1-82 0.75-33 6.0-57 5.1-58 0.9-46 5.9-89 12-82

Mean 13 17 20 11 14 16 17 24 31

Median 11 14 17 9.7 12 15 17 18 23

STD 8.4 13 15 6.4 8.9 8.8 12 19 20

CV 0.7 0.8 0.7 0.6 0.6 0.5 0.7 0.8 0.7

kl

Range 1.0-29 1.1-31 1.1-46 1.1-29 1.1-31 1.2-46 1.0-3.8 1.1-11 1.1-27

Mean 3.9 5.1 6.0 4.6 5.8 6.5 1.9 3.1 4.6

Median 2.4 2.9 3.3 2.6 3.5 3.6 1.6 2.2 2.1

STD 4.5 5.5 7.2 5.0 6.1 7.6 0.8 2.6 6.1

CV 1.2 1.1 1.2 1.1 1.1 1.2 0.4 0.8 1.3

50

3.5 CONCLUSIONS

The hydraulic behaviour of the PPs at Kortright has shown that significant improvements to the

stormwater outflow regime are possible through the use of partial-infiltration PP systems over low

permeability soils. Outflow from the PP systems occurred less frequently, in smaller volumes, at slower

rates, and for longer durations than the runoff from the asphalt control. The implications to receiving

surface water systems are numerous: less frequent and smaller sized events reduce the volume of water

that can contribute to flooding and erosion. Increasing the duration of outflow events mitigates the

‘flashy’ behaviour of impervious pavements and tail responses mimic natural processes that can

contribute to baseflow. The 43% reduction in outflow volume throughout this study demonstrates that

significant losses are possible from partial-infiltration PP systems, even over low permeability soils. The

closed-valve tests produced promising evidence that the environmental benefits of PP systems are

enhanced by extending the detention of infiltrated stormwater. Overall, the poured and interlocking

pavements offered the same hydrologic benefits and behaved similarly.

Differences in hydrologic performance were evident between the winter and spring-to-fall seasons.

Volume reductions and detention time displayed greater seasonal dependency than the peak flow

reductions. Outflow from the permeable pavement was muted regardless of precipitation characteristics

or season, and peak flows were reduced by at least 50% throughout the study. During winter months

snow melt was detained within aggregate layers but the majority of the PP system remained unsaturated

at all times. Negative volume reductions occurred during sustained periods of warming due to the

delayed release of melted snow from the PP systems and possibly greater storage of snow adjacent to the

PP cells. Even though volume reductions should not be anticipated during periods of seasonal thawing,

flows will continue to be attenuated. The study has shown that AquaPave, Eco-Optiloc and Hydromedia

Pervious Concrete pavements function well under typical Ontario conditions and minimize the negative

hydrologic characteristics of parking lot runoff.

3.6 REFERENCES

Anderson, C., Foster, I., and Pratt, C. (1999). The role of urban surfaces (permeable pavements) in

regulating drainage and evaporation: development of a laboratory simulation experiment. Hydrol.

Process., 13: 597-609.

Bean, E., Hunt, W., and Bidelspach, D. (2007). Evaluation of four permeable pavement sites in eastern

North Carolina for runoff reduction and water quality impacts. J. Irrig. Drain. Eng., 133(6), 583-592.

Booth, D., and Leavitt, J. (1999). Field evaluation of permeable pavement systems for improved

stormwater management. J. Am. Plann. Assoc., 65(3), 314-325.

Brattebo, B., and Booth, D. (2003). Long-term stormwater quantity and quality performance of

permeable pavement systems. Water Res., 37(18), 4369-4376.

51

Collins, K., Hunt, W., and Hathaway, J. (2008). Hydrologic comparison of four types of permeable

pavement and standard asphalt in eastern North Carolina. J. Hydrol. Eng., 13(12), 1146-1157.

CVC and TRCA. (2010). Low Impact Development Stormwater Management Manual. Toronto: Credit

Valley Conservation and Toronto and Region Conservation.

Das, B. (2007). Principles of Foundation Engineering. Thomson: Toronto, 22.

Drake, J., Bradford, A., and Marsalek, J. (2013). Review of environmental performance of permeable

pavement systems: state of the knowledge. Water Qual. Res. J. Can., in press

Dreelin, E., Fowler, L., and Carroll, R. (2006). A test of porous pavement effectiveness on clay soils

during natural storm events. Water Res., 40(4), 799-805.

Environment Canada. (2012). National Climate Data and Information Archive. Updated: 29 May, 2012.

www.climate.weatheroffic.gc.ca. Accessed: 19 September, 2012.

Fassman, E., and Blackbourn, S. (2010). Urban runoff mitigation by a permeable pavement system over

impermeable soils. J. Hydrol. Eng., 15(6), 475-485.

Ferguson, B. (2005). Porous Pavements. Boca Raton: CRC Press.

Field, R., Masters, H., and Singer, M. (1982). Porous pavement: research; development; and

demonstration. Transp. Eng. J. of ASCE, 108, 244.

Gomez-Ullate, E., Bayon, J., Coupe, S., and Castro-Fresno, D. (2010). Perfomance of pervious

pavement parking bays storing rainwater in the north of Spain. Water Sci. Technol., 62(3), 615-621.

Henderson, V. (2012) Evaluation of the Performance of Pervious Concrete Pavement in the Canadian

Climate. PhD Thesis, Univ. of Waterloo, Waterloo, ON.

Houle, K., Roseen, R., Ballestero, T., Briggs, J., and Houle, J. (2010). Examination of pervious concrete

and porous asphalt pavements performance for stormwater management in northern climates. Low

Impact Development 2010: Redefining Water in the City (pp. 1281-1298). San Fransisco: ASCE.

James, W., and Thompson, M. (1997). Contaminants from four new pervious and impervious pavements

in a parking-lot. In W. James (Ed.), Advancements in Modeling the Management of Stormwater Impacts

(Vol. 5, pp. 207-222). Guelph: Computational Hydraulics International.

James, W., and Gerrits, C. (2003). Maintenance of infiltration in modular interlocking concrete pavers

with external drainage cells. In W. James (Ed.), Practical Modeling of Urban Stormwater Systems (Vol.

11, pp. 417-35). Guelph: Computational Hydraulics International.

Pratt, C., Mantle, J., and Schofield, P. (1989). Urban stormwater reduction and quality improvement

through the use of permeable pavements. Water Sci. Technol., 21(8), 769-778.

52

Pratt, C., Mantle, J., and Schofield, P. (1995). UK research into the performance of permeable pavement,

reservoir structures in controlling stormwater discharge quantity and quality. Water Sci. Technol., 32(1),

63-69.

Roseen, R., Ballestero, T., Houle, J., Avellaneda, P., Briggs, J., and Wildey, R. (2009). Seasonal

performance variations for storm-water management systems in cold climate conditions. J. Environ.

Eng., 135(3), 128-137.

TRCA. (2008). Performance Evaluation of Permeable Pavement and a Bioretention Swale. Sustainable

Technologies Evaluation Program. Toronto: Toronto and Region Conservation.

53

4 PRELIMINARY ANALYSIS OF STORMWATER QUALITY DATA

4.1 INTRODUCTION

The purpose of this chapter is to provide information regarding the preliminary analysis of stormwater

quality data. Results were initially analyzed by pavement type using data from the complete monitoring

period. This analysis confirmed that the winter and non-winter stormwater quality are very different and

therefore interpretation of results when lumped as a single dataset provided an incomplete understanding

as to the full extent of stormwater treatment provided by the permeable pavements. The stormwater

quality data was subsequently separated by season and analyzed separately for winter and non-winter

conditions. Stormwater quality was evaluated for general quality, metals, nutrients, polycyclic aromatic

hydrocarbons (PAH), microbiology and temperature. Analysis also identified pollutants for which

differences in concentration could not be determined based on pavement type.

4.2 METHODOLOGY

Water quality sampling was conducted over 24 months between June 2010 and June 2012. A complete

list of the pollutants and water quality parameters which were analyzed, minimum detection limits, the

number samples submitted and relevant water quality guidelines such as the Canadian Environmental

Quality Guideline (CWQG), Ontario Provincial Water Quality Objectives (PWQO) and the Canadian

Water Quality Guidelines (CWQG) is presented in Appendix A. Some nitrogen species which are

discussed in subsequent chapters are estimated indirectly:

Organically-bound nitrogen (org-N) is estimated by subtracting ammonia (

+ ) from

total Kjeldahl nitrogen (TKN);

Nitrate ( -) is estimated by subtracting nitrite (

-) from a combined

-+

- result

provided by the OMOE lab;

Total nitrogen (TN) is estimated by adding TKN and -+

-.

When possible, samples were analyzed from all four pavements for the same event however, on some

occasions; stormwater was collected from only one or some of the four pavements. The ASH pavement

in particular, frequently produced runoff while the PPs remained unresponsive. Analysis methods were

based on the recommendations for Low Impact Development (LID) monitoring presented in the EPA

Urban Stormwater BMP Performance Monitoring Manual (2009). Additional guidance books which

were also used include:

Burton and Pitt (2001). Stormwater Effects Handbook: A toolbox for watershed managers,

scientists, and engineers

Manly (2009). Statistics for Environmental Science and Management

Quian (2010). Environmental and Ecological Statistics with R

54

Initially the water quality data from each pavement was analyzed as a single data set encompassing all

seasons. The products of this analysis including descriptive statistics, graphical summaries, summary

tables etc. are provided in Appendixes A - G. Descriptive statistics include, mean ( ), geometric mean

(GM), median ( ), range (max/min), standard deviation ( ), skewness ( ) and coefficient of variation

( ). Graphical summaries include boxplots and probability plots. Time series illustrate pollutant EMC

in a time series plot. And, the summary tables identify parameters with more than 50% non-detection,

the percentage of samples that exceeded recommended guideline levels, statistical significance tests (t-

test or sign-test) and overall removal metrics (efficiency ratio - ER and median removal efficiency - RE).

ER is defined as the ratio of average outlet EMC to inlet EMC (Burton and Pitt, 2001). RE is defined as

the ratio of outlet EMC to inlet EMC for individual events (Roseen et al., 2009). Removal metrics are

not recommended as stand-alone assessment of performance (Burton and Pitt, 2009) and thus were

interpreted in context of all of the statistical analyses. ER was reported as it is the most commonly used

methods (Burton and Pitt, 2001). RE was also calculated as it generates more detailed performance

information than ER. Since the PP systems do not receive inflow from a single inlet the metrics were

modified and reported as the ratios of PP effluent EMC to ASH runoff EMC. Presentation of the

temperature data is provided in Appendix I.

4.3 RESULT OF PRELIMINARY ANALYSIS

Seasonal Trends 4.3.1

It was determined that the quality data contained two distinct seasonal populations. During the winter

different pollutants are introduced as a result of road salting and sanding which greatly alter the

characteristics of both ASH runoff and PP effluent. Parameters which were known to be influenced by

road salting could not be characterized by normal or lognormal distributions when data from all seasons

was analyzed together. When a pollutant was introduced into the runoff or effluent as a direct result of

salting two distinct distributions were visible within the pollutant’s probability plot and each distribution

could be paired with the presence or absence of road salting activities. Strontium, plotted in Figure 4-1,

exhibits two population distributions in PP effluents which are identified by a change in slope near the

85th

percentile. The change in slope is less apparent for ASH runoff but, nevertheless, is visible around

the 80th

percentile. The events above the 80th

and 85th

percentile all came from winter samples collected

between December and March when road salt was being applied on the pavement. The increase in

concentration is thus a direct result of the material introduced by winter maintenance.

55

Figure 4-1: Strontium probability plot

Similar observations suggesting two populations for some stormwater parameters were also visible in

time series plots. Using Strontium as an example, Figure 4-2 illustrates the large changes in event mean

concentrations (EMC) that were observed for some events during winter months.

Figure 4-2: Seasonality in stormwater quality (note: 2012/2013 results >20 000 μg/L verified by

repeated analysis at MOE lab)

Additionally, parameters influenced by road salting often produced ER and median RE results which

indicated opposing performance; one metric suggested concentrations were reduced while the other

metric suggested concentrations were increased (i.e. one metric was positive while the other was

negative). These parameters followed the seasonal-pattern of EMCPP < EMCASH during the winter

followed by the reverse, EMCPP > EMCASH during other seasons. Extremely high winter concentrations

in runoff skewed the EMCASH average causing ER to be positive even though for three of four seasons,

the runoff had lower concentrations than the PP effluent.

0.000.100.200.300.400.500.600.700.800.901.00

10 100 1000 10000 100000

% U

nd

er

Strontium (μg/L)

ASH

AP

EO

PC

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

22/1/10 10/8/10 26/2/11 14/9/11 1/4/12 18/10/12

Stro

nti

um

(μ

g/L)

Date

ASH

AP

EO

PC

Change in slope

Change in slope

Winter EMC

56

Inter-Annual Trends 4.3.2

Several inter-annual patterns were noted in the stormwater quality data which were not associated with

seasonality. Magnesium, potassium and strontium EMC as well as pH levels in PP effluent exhibited a

moving average throughout the entire monitoring period. The potassium time series, presented as an

example in Figure 4-3 (plotted on a log-scale), shows that effluent concentrations steadily declined

throughout the study. When pollutant concentrations were subjected to long-term changes the calculated

ER and median RE were found to be unreliable tools for quantifying performance.

Figure 4-3: Potassium time series

Some pollutants which exhibited inter-annual declines in concentration were suspected to have

originated from the PP systems as a result of weathering and mobilization of the aggregate materials. To

further investigate the sources of these pollutants an additional experiment was undertaken at the

University of Guelph (Chapter 5).

Microbiology 4.3.3

The hypothesis tests revealed that no significant differences were found in the microbiology parameters.

These parameters had high variability and ranged from non-detectable amounts to upwards of the

thousands. The number of paired samples was not sufficient to estimate difference in sample mean ±

error for a 95% confidence interval. For example, based on the observed variance of the fecal

streptococcus data, even if an error of 50% were assumed, over 100 paired-events would be needed to

compare means at a 95% confidence. Consequently, microbiology is not discussed in subsequent

chapters as there is insufficient data to perform meaningful analysis.

4.4 CONCLUSIONS

Stormwater quality data was initially analyzed as a single time series. Ultimately, winter stormwater

data was separated and analyzed independently. The results of this work are compiled into two stand-

along manuscripts (Chapters 5 & 6). The purpose of this chapter was to acknowledge that this initial

0.1

1

10

100

1000

22/1/10 21/6/10 18/11/10 17/4/11 14/9/11 11/2/12 10/7/12 7/12/12

Po

tass

ium

(m

g/L

)

ASH

AP

EO

PC

57

phase of analysis was performed and to present the evidence which supported the decision to analyze

data collected during the winter separately from data collected during spring, summer, and fall.

4.5 REFERENCES

Burton, A., & Pitt, R. (2001). Stormwater Effects Hanbook: A Toolbox for Watershed Managers,

Scientists, and Engineers. Boca Raton: Lewis Publishers. Retrieved from Robert Pitt's Group

Publications.

Canadian Council of Ministers of the Environment. (2007). Canadian Environmental Quality

Guidelines. Canadian Council of Ministers of the Environment.

Federal-Provincial-Territorial Committee on Drinking Water. (2012). Guidelines for Canadian Drinking

Water Quality. Health Canada.

Geosyntec Consultants and Wright Water Engineers,Inc. (2009). Urban Stormwater BMP Performance

Monitoring.

Manly, B. (2009). Statistics for Environmental Science and Management. Boca Raton: CRC Press.

Ministry of Environment and Energy (MOE). (1994). Water Management Policies Guidelines

Provincial Water Quality Objectives. Toronto: Queen's Printer for Ontario.

Quian, S. (2010). Environmental and Ecological Statistics with R. Boca Raton: CRC Press.

58

5 STORMWATER QUALITY OF SPRING-SUMMER-FALL EFFLUENT

FROM THREE PARTIAL-INFILTRATION PERMEABLE PAVEMENT

SYSTEMS AND CONVENTIONAL ASPHALT PAVEMENT

5.1 INTRODUCTION

Permeable pavements (PP) allow for the treatment and management of stormwater near to its source. PP

systems reduce the total pollutant mass delivered to receiving systems by capturing pollutants within the

pavement system and removing them from stormwater (Bean et al., 2007). In partial-infiltration systems,

a significant proportion of stormwater will infiltrate into native soils while some excess stormwater is

discharged to a receiving surface water system by way of underdrains. Outflow from an underdrained PP

system is not considered runoff and is referred to as exfiltrated stormwater or effluent (Bean et al., 2007,

Roseen et al., 2012). Particulates within stormwater are captured by mechanical filtration through the PP

surface and base layers. As water migrates through the PP additional treatment is possible through

adsorption, transformation, biological degradation and volatization.

In 1989 UK researchers Pratt et al. observed that exfiltrate from permeable interlocking concrete paver

(PICP) systems had lower concentrations of suspended solids and total Pb than runoff from highway

drainage gullies. Since Pratt’s study many more researchers (Rushton, 2001; Brattebo and Booth, 2003;

Bean et al., 2007; TRCA, 2008; Roseen et al., 2009; Fassman and Blackbourn, 2010) have observed that

PP effluent has lower suspended solids and heavy metal (e.g. Pb, Zn, Cu, Cd and Fe) concentrations than

runoff from traditional asphalt pavements. Long term studies, such as Brattebo and Booth (2003), have

noted that PP systems can continue to improve stormwater quality even after several years of use.

Effluent quality, however, does change with time which can result in both positive and negative changes

in performance. Brattebo and Booth (2003) observed that, when comparing stormwater quality data of a

PP parking lot when it was new and after six years of use, Zn concentrations increased while Cu and Pb

decreased as the pavement aged. The capacity for pollutant removal over time and the possibility of

remobilization have important implications for sustained benefits of PP systems as well as the potential

contamination of groundwater systems.

PP exfiltrate has been consistently shown to have a pH ranging between 8 and 9.5 (Pratt et al., 1995;

Sansalone and Teng, 2004; Kwiatkowski et al., 2007; TRCA, 2008) whereas rainfall and asphalt runoff

tend to be more acidic. For the protection of aquatic life, common water quality guidelines recommend

that pH should be maintained between 6.5 – 8.5 (MOE, 1994) so PP effluent sometimes fails to meet this

guideline. PP effluent has also been shown to contain low levels of petroleum-based hydrocarbons. A

two-year study by Roseen et al. (2009) found almost no detectable amounts of total petroleum-

hydrocarbon diesel range in PP effluent. Similarly, a three-year study by TRCA (2008) found polycyclic

aromatic hydrocarbons were frequently below minimum detection limits and oil and grease (solvent

extractable) concentrations were reduced by infiltrating stormwater though a PP system.

59

Nutrient concentrations in PP effluent have been addressed in several studies (Bean et al., 2007; Roseen

et al., 2009; Collins et al., 2010; Tota-Maharaj and Scholz, 2010). Collins et al. (2010) intensively

examined the transformation and fate of nitrogen through a full-sized PP system. This study found that

PP exfiltrate had consistently lower TKN and concentrations and higher

- concentrations than

asphalt runoff indicating that nitrification (

-) occurred as stormwater infiltrated through the

system. Collins et al. (2010) also observed that TN concentrations were occasionally higher in PP

effluent than in asphalt runoff and atmospheric deposition. As a filtering system, PP can capture

particulate-bound P leading to reductions in TP concentrations. Although several studies (Bean et al.,

2007; TRCA, 2008; Roseen et al., 2009; Tota-Maharaj and Scholz, 2010) have noted that PP effluent

has reduced TP levels, the long-term retention of nutrients has not yet been demonstrated.

Studies have shown that PP systems can reduce pollutant loads in direct runoff but effluent pollutant

loading from underdrained systems has received only limited attention. Legret and Colandini (1999)

reported pollutant loads for suspended sediments and heavy metals from forty monitored rain events

collected over four years. The researchers found that, relative to a reference catchment, runoff from a

porous asphalt pavement reduced the loading of suspended sediments, Pd, Cd and Zn by 59%, 84%,

77% and 73% respectively to downstream systems. Rushton (2001) evaluated the annual loads from

runoff from two PP-to-swale systems. Relative to a traditional asphalt pavement, the PP and swale

reduced nitrogen, TSS, and heavy metal (Fe, Pb, Mn and Zn) loads. The PP system was particularly

effective at capturing solids and metals as removal rates for these pollutants ranged between 75% and

94%. Phosphorus removal was inconsistent as one pavement performed well while the second pavement

increased ortho-phosphate and had a negligible effect on TP.

Two studies, Sansalone and Teng (2004) and Fassman and Blackbourn (2010), have reported exfiltrate

pollutant loads but both studies focused exclusively on solids and heavy metals. Sansalone and Teng

(2004) published pollutant loads in PP exfiltrate from three storms. The experimental set-up allowed for

direct sampling of influent and effluent stormwater draining through the PP system. Sansalone and Teng

(2004) reported both dissolved and particulate loadings of heavy metals. High pollutant removals

ranging between 68% and 99% were observed for Ca, Cd, Cu, Fe, Mg, Mg, Ni, Pb and Zn. Their

findings suggested that the PP system was somewhat more effective at capturing dissolved fractions of

Zn, Ni and Mn and particulate fractions of Pd, Mg and Ca. Fassman and Blackbourn (2010) observed

70% reduction in total suspended solids and Cu loads and a 96% reduction in total Zn loads from

sampled storms.

To fully understand the environmental impact of partial-infiltration PP systems more information is

needed regarding stormwater quality of effluent. In cold climates, like Ontario, a distinction between the

winter season and other times of the year is needed to interpret water quality performance data. The

objective of this study is to compare overall stormwater quality of PP effluent from three partial-

infiltration PP systems and asphalt runoff throughout spring-summer-fall seasons. The stormwater

quality of permeable interlocking concrete pavement (PICP) and pervious concrete effluent will be

examined and trade-offs between the two systems will be discussed. Stormwater quality is evaluated for

60

general quality, petroleum-based hydrocarbons, nutrients and metals. The results of this study

demonstrate the environmental benefits of partial-infiltration PP systems in the context of stormwater

quality.

5.2 METHODOLOGY

Site Design 5.2.1

The PP parking lot is located at the Kortright Centre for Conservation in Vaughan, Ontario. Constructed

over the fall of 2009 and the spring of 2010 the facility consists of four pavement cells which are 230-

233 m2 in size and have a capacity for 8-10 parked vehicles in each cell (Figure 5-1). Two cells are

constructed with PICP; AquaPave® (AP) and Eco-Optiloc® (EO), one cell is constructed with

Hydromedia® Pervious Concrete (PC) supplied by Lafarge and one cell is constructed with traditional

asphalt (ASH). The pavement cells are separated by a raised concrete curb which extends below the

surface to the native soils preventing the cross-flow of stormwater. Aggregate reservoirs below the PP

(Figure 5-2 and 5-3) are constructed with two layers of 19 mm and 60 mm diameter clear stone

providing a combined depth of at least 40 cm. The EO pavement has joints which are 13 to 14 cm wide

and uses high performance bedding (HPB) as joint and bedding material (diameter ~ 1 – 9 mm) while

the AP pavement has joints which are 3 to 4 cm wide and uses HPB as bedding and Engineered Joint

Stabilizer (diameter ~ 2 - 3 mm) as joint material. The AP pavement also includes an Inbitex®

geotextile placed between the bedding and aggregate layers. Vegetated berms approximately 5 to 6 m

wide with mature trees line the north and south sides of the parking lot and approximately half of the

berm area slopes towards the pavement.

Figure 5-1: Site schematic

61

Figure 5-2: Profile of Permeable Interlocking Concrete Paver

Figure 5-3: Profile of Pervious Concrete

Each PP cell is drained by a 100 mm diameter Big O perforated tubing placed at the base of an

aggregate trench at the interface between the aggregate reservoir and the native soil. The ASH cell is

drained via a catchbasin. Infiltrated stormwater collected from each PP cell is conveyed separately in

62

sealed pipes to a downstream sampling vault. Concrete pipe collars at cell boundaries prevent water

movement along granular trenches surrounding these pipes. A Mirafi Filter Weave® 500 geotextile is

placed below the aggregate base to prevent soils from migrating up into the aggregate layer. Underdrains

for each cell are fitted with flow restrictors to control the rate of drawdown after storm events and prolong

the period over which infiltration can occur.

Monitoring and Data Collection 5.2.2

Water quality sampling was conducted over 24 months between June 2010 and June 2012. Sampling

was suspended for two months in 2010 (July and August) and again in May 2011 while testing of the

collection system was performed. This paper reports the findings from data collected during the spring,

summer and fall months of the study. Flow-proportioned samples were collected by automated ISCO

samplers and submitted to the Ontario Ministry of the Environment (OMOE) Laboratory in Etobicoke

for analysis. Raw water quality data was presented in the 2012 report Evaluation of Permeable

Pavements in Cold Climates – Kortright Centre, Vaughan which can be obtained through the Toronto

and Region Conservation Authority’s Sustainable Technologies Evaluation Program (STEP). The water

quality parameters, which are the focus of this article, minimum detection limits (MDL) and relevant

water quality guidelines are listed in Table 5-1. When possible, samples were analyzed from all four

pavements for the same event however, on some occasions; stormwater was collected from only one or

some of the four pavements. The ASH pavement in particular, frequently produced runoff while the PPs

remained unresponsive.

63

Table 5-1: Stormwater quality parameters

Pollutant Units MDL Guideline

Max Level Source

General Quality

Alkalinity mg/L 2.5

Conductivity uS/cm 5

pH - 5 8.5 PWQO

DS mg/L 50 500 CWQG

TSS mg/L 2.5 variable CEQG

Cl mg/L 1 120 (long-term),

640 (short-term) CEQG

Na mg/L 0.04 200 CWQG

Metals

Al μg/L 1 75 PWQO-Interim

B μg/L 10 200 PWQO

Cd μg/L 0.5 0.5 PWQO-Interim

Cu μg/L 5 5 PWQO-Interim

Fe μg/L 30 300 PWQO

Pb μg/L 0.5 5 PWQO-Interim

Mn μg/L 0.01 50 CWQG

K μg/L 0.06

Sr μg/L 1

Zn μg/L 20 20 PWQO-Interim

Nutrients

mg/L 0.01 0.02 PWQO

mg/L 0.02 3.2 CWQG

mg/L 0.005 45 CWQG

org-N mg/L 0.09

TN mg/L 0.11

mg/L 0.0025

TP mg/L 0.01 0.03 PWQO-Interim

Petroleum based hydrocarbons

Solvent Extractable mg/L 1

PAHs ng/L - variable PWQO

Provincial water quality objective (PWQO)

Canadian water quality guideline (CWQG)

Canadian environmental quality guideline (CEQG)

Sample Boxes 5.2.3

After the Kortright parking lot had been monitored for a complete year, preliminary data indicated that

effluent quality was changing over time. The data suggested that stormwater was influenced by inter-

annual changes which were independent of seasonal temporal patterns. Some pollutants observed within

PP effluent were suspected to have originated from the PP systems as a result of weathering and

mobilization of the aggregate materials. To further investigate the sources of these pollutants an

additional experiment was undertaken. Drained boxes were constructed and filled with the individual

64

aggregate layers that made-up the Kortright parking lot. In total nine boxes (Shown in Figure 5-4) were

deployed outside at the University of Guelph Arkell property:

A plastic lined empty box

Two AP boxes replicating the AP surface, bedding layers and geotextile

Two EO boxes replicating the EO surface and bedding layer

Two filled with cast in place PC poured with the same batch of PC used in the construction of the

Kortright parking lot.

A box filled with 19 mm aggregate

A box filled with 60 mm aggregate

Figure 5-4: Material Boxes: EO (top-left), PC (top-right), AP (bottom-left), 19 mm aggregate

(bottom-right)

The box depth of each material box matched the constructed material depth at Kortright. At the time of

the study, a sample of the AP jointing material could not be acquired and therefore, the influence of this

material on stormwater quality was not assessed. Samples of exfiltrated water were collected for seven

events between July and October 2011 and submitted for analysis of metal and nutrient concentrations at

65

ALS Laboratories in Waterloo, ON. Total solids (TS) and total suspended solids (TSS) concentrations as

well as pH were measured at the University of Guelph.

Data Analysis 5.2.4

Analysis methods were based on the recommendations for Low Impact Development (LID) monitoring

presented in the EPA Urban Stormwater BMP Performance Monitoring Manual (2009). Descriptive

statistics including range, mean ( ), median ( ), standard deviation ( ), skew ( ) and coefficient of

variation ( ) were calculated for all parameters. All statistical analysis was performed for a 95%

confidence level. Data for each parameter were evaluated using the EPA’s statistical software ProUCL

4.1 for normal and lognormal distributions using goodness-of-fit statistics. Some of the water quality

data was censored by MDL. For a given parameter, if less than 10% of a data set was censored, results

were assumed to be

. When censored data represented 10 to 50% of the total data set, censored

results were estimated using regression-on-order statistics (ROS) with ProUCL 4.1. When more than

50% of a data set was censored, statistics were not calculated for the data.

Boxplots and probability plots for EMC data, grouped by pavement type, were created to examine

differences in stormwater quality. Graphical representation of the data provides additional information

of the general characteristic of the results and enables more comprehensive and statistically-valid

analysis (Geosyntec Consultants and Wright Water Engineers, 2009). Graphical summaries were created

using Microsoft Excel and statistical analysis was performed using the open-source statistical computing

language and environment R. Concentration data were compared with published results in the

International Stormwater Best Management Practices (BMP) Database Pollutant Category Summary

Statistical Addendum which has summarized stormwater quality data from many PP installations.

The percentage of results exceeding recommended water quality guidelines including Provincial Water

Quality Objectives (PWQO), Canadian Water Quality Guidelines (CWQG) and Canadian

Environmental Quality Guidelines (CEQG) were calculated for each parameter. Statistically significant

differences in water quality, by pavement type, were evaluated using paired t-tests for normal and

lograngnormally-transformed data and sign tests for all other data. After reviewing all statistics,

efficiency ratios (Equation 1) and median removal efficiencies (Equation 2) were calculated for

pollutants which demonstrated significant differences between pavement effluents.

Efficiency Ratio (ER):

(Equation 1)

Removal Efficiency (RE):

(Equation 2)

For each pavement, pollutant loads were calculated for individual events (Equation 3) and then summed

for the entire study (Equation 4). Pollutant loading reductions were evaluated using a ratio of PP loads to

ASH loads (Equation 5) as a performance metric. Reporting of loading was limited to parameters with at

least one gram of estimated pollutant mass.

66

Pollutant Load normalized by area (L):

(Equation 3)

Total Pollutant Mass (M): ∑ (Equation 4)

Summation of Pollutant Loads (SOL): ∑

∑

(Equation 5)

where A = pavement area, V = event volume and EMC = event mean concentration for events i =1,2,…,

n.

5.3 RESULTS AND DISCUSSION

General Quality and Petroleum-Based Hydrocarbons 5.3.1

The PPs altered the overall quality of infiltrating stormwater by filtering particulate materials and

introducing new dissolved solids. Descriptive statistics, performance efficiencies and statistical

significance tests for general quality concentration data are presented in Table 5-2 and mass loading data

are presented in Table 5-3.

Table 5-2: General quality concentration results

Pollutant Pavement Range ER RE p

Alkalinity

(mg/L)

ASH 22 – 138 47 35 30 1.7 0.6 - - - -

AP 73 – 135 99 97 16 0.7 0.2 -1.1 -1.9 1.5E-6* (<)

EO 80 – 151 108 103 20 0.6 0.2 -1.3 -2.1 9.7E-6* (<)

PC 109 – 202 156 154 26 -0.05 0.2 -2.3 -3.6 7.8E-7* (<)

Conductivity

(uS/cm)

ASH 57 – 336 128 92 86 1.4 0.7 - - - -

AP 253 – 581 385 350 106 0.8 0.3 -2.0 -3.1 7.7E-7* (<)

EO 247 – 668 410 393 110 0.9 0.3 -2.2 -3.3 3.0E-8* (<)

PC 316 – 1 510 667 656 257 1.5 0.4 -4.2 -6.2 3.0E-8* (<)

pH

ASH 6.8 – 7.9 7.6 7.7 0.25 -1.8 0.03 - - - -

AP 8.1 – 8.7 8.3 8.3 0.15 0.8 0.02 -0.09 -0.08 2.3E-16 (<)

EO 8.1 – 8.6 8.3 8.3 0.15 0.8 0.02 -0.09 -0.08 6.0E-8* (<)

PC 8.5 – 10 9.1 9.1 0.5 0.12 0.06 -0.19 -0.21 6.0E-8* (<)

DS

(mg/L)

ASH <MDL – 228 76 55 62 1.2 0.8 - - - -

AP 164 – 378 250 227 69 0.8 0.3 -2.3 -3.1 3.0E-8* (<)

EO 161 – 434 266 255 71 0.9 0.3 -2.5 -3.7 7.6E-10 (<)

PC 205 – 1 090 459 427 210 1.5 0.5 -5.0 -6.8 2.4E-11 (<)

TSS (mg/L)

ASH 13 – 236 54 44 42 3.1 0.8 - - - -

AP 1.3 – 31 11 9.2 8.8 0.9 0.8 0.80 0.83 1.2E-14 (>)

EO 1.3 – 23 7.2 5.7 5.6 1.4 0.8 0.87 0.87 5.2E-15 (>)

PC 1.3 – 36 11 6.5 9.3 1.6 0.9 0.80 0.81 <2.2E-16 (>)

Cl (mg/L)

ASH <MDL – 14.7 3.4 1.9 3.5 1.7 1.0 - - - -

AP 1.7 – 32 6.7 5.8 6.4 2.8 1.0 -1.0 -1.8 7.7E-4* (<)

EO <MDL – 54 9.8 5.2 12 2.6 1.2 -1.9 -2.6 3.3E-3* (<)

PC 1 – 25 8.1 5.8 6.5 1.1 0.8 -1.4 -2.1 7.3E-3* (<)

Na (mg/L)

ASH 0.3 – 10 2.1 1.1 2.7 2.1 1.3 - - - -

AP 10 – 102 28 22 20 2.3 0.7 -12 -15 3.0E-8* (<)

EO 7.8 – 113 33 27 25 1.5 0.8 -15 -17 3.0E-8* (<)

PC 16 – 89 41 33 21 1.3 0.5 -18 -36 3.0E-8* (<)

*sign test performed

(<) = EMC mean/median ASH < EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH = mean/median PP

67

Table 5-3: General quality mass loading results

Pollutant Pavement Range M SOL

DS

(kg/ha)

ASH 1.5 – 39 9.2 7.6 8.5 2.4 0.9 255 -

AP 6.5 – 79 28 25 17 1.4 0.6 555 -1.2

EO 7.8 – 88 29 26 19 1.5 0.7 578 -1.3

PC 15 – 119 48 45 30 0.82 0.6 967 -2.8

TSS (kg/ha)

ASH 5.8 – 100 26 17 25 2.2 1.0 192 -

AP 0.049 – 11 1.6 0.63 2.6 3.1 1.6 32 0.83

EO 0.042 – 7.0 1.0 0.51 1.6 3.3 1.5 20 0.89

PC 0.062 – 4.1 1.1 0.60 1.2 1.7 1.1 21 0.89

Cl (kg/ha)

ASH 0.056 – 4.1 0.62 0.31 0.94 2.9 1.5 13 -

AP 0.082 – 3.6 0.68 0.47 0.82 2.9 1.2 14 -0.04

EO 0.055 – 4.3 0.83 0.41 1.0 2.4 1.3 17 -0.27

PC 0.079 – 4.6 0.89 0.51 1.2 2.4 1.3 18 -0.37

Na (kg/ha)

ASH 1.7 – 43 12 9.4 11 1.7 0.9 10 -

AP 0.56 – 16 3.2 2.0 3.5 2.7 1.1 64 -5.5

EO 0.40 – 18 3.6 2.5 4.0 2.5 1.1 71 -6.3

PC 1.2 – 17 4.4 3.4 3.9 2.3 0.87 88 -8.0

The different PPs performed similarly and, relative to ASH, significantly (p < 0.05) reduced the

concentration and load of TSS within stormwater by 80% or greater. Median residual TSS

concentrations ranged between 6.5 mg/L and 9.2 mg/L which was less than median residuals (13.2

mg/L) reported by the International Stormwater BMP Database. Vehicles are likely the dominate

mechanism for introducing pollutants to the pavements; however the Kortight parking lot has low rates

of daily traffic. The low TSS residuals are a reflection of the low rate of pollution. Median ASH TSS (25

mg/L) concentrations were well below typical urban runoff concentrations, 58 mg/L (Pitt, 2004) and

therefore it is not surprising that the PP effluent had small amounts of TSS. The BMP Database is still

an evolving tool and its reported results are limited by the number and quality of installations used to

compile the database. The degree of stormwater treatment provided by a PP system is controlled by the

surrounding landuse, pavement and drainage design, traffic loading and climatic conditions. The

Kortright results illustrate that PP effluent in low-traffic applications will have better stormwater quality

due to less pollution exposure. Existing summaries of quality performance, such as the BMP Database

may not yet completely characterize the range and variability of PP performance. The development of

PP effluent pollutant concentration statistics based on site characteristics would be a valuable tool for

planners and designers and allow for more accurate description of PP performance as stormwater

treatment systems.

Runoff was significantly (p < 0.05) more acidic than PP effluent which had higher alkalinity,

conductivity and pH. All of the PPs had pH levels which occasionally exceeded recommended levels

(pH =8.5). The PC, in particular, had very high pH levels throughout the first year of the study (Figure

5-4). However, by the second year, levels appeared to stabilize and were increasingly comparable with

the PICP effluent (Figure 5-5).

68

Figure 5-5: pH time series

PP effluent contained higher levels of Cl and Na than runoff throughout the non-winter seasons of this

study. The 3.7 mg/L increase in median CL EMC was small and even the 26 mg/L increase in median

Na EMC was not large enough to result in an increase in total pollutant loading. Additionally, Cl and Na

concentrations were always well below recommended levels in non-winter seasons. Winter road salting

elevated spring and early-summer Cl and Na concentrations in PP effluent as the pollutants migrate

through the PP system slowly. During the study Cl followed a regular annual pattern with the highest

EMC occurring mid-winter and steadily declined over the year until the next winter (refer to Appendix

E).

The PPs essentially eliminated oil and grease (solvent extractable) from stormwater as less than 7% of

all analyzed samples had detectable concentrations while 84% of runoff samples contained measureable

amounts of these pollutants. Similarly, PAHs were rarely detected in effluent samples but were

frequently observed in runoff. Fluoranthrene, phenanthrene and pyrene were the most commonly

observed PAHs in runoff. Biodegradation has been identified as the most likely ultimate fate process for

these pollutants although dissolved portions may also undergo rapid photolysis (Burton and Pitt, 2001).

Additional removal mechanisms, specifically volatilization and adsorption, may also be important

removal processes (Burton and Pitt, 2001).

Nutrients 5.3.2

Infiltrating stormwater through the PP systems provided opportunities to trap or filter-out particulate-

forms of nutrients and time for some nutrient species to be transformed. Descriptive statistics,

performance efficiencies and statistical significance tests for nutrient concentration data are presented in

Table 5-4 and mass loading data are presented in Table 5-5.

6.5

7

7.5

8

8.5

9

9.5

10

10.5

16/6/10 16/12/10 16/6/11 16/12/11 16/6/12

pH

PWQOASHAPEO

69

Table 5-4: Nutrient concentration results

Pollutant Pavement Range ER RE p

(mg/L)

ASH <MDL – 1.2 0.27 0.24 0.25 2.0 0.9 - - - -

AP <MDL - 0.098 0.031 0.024 0.023 1.8 0.8 0.88 0.81 1.0E-5* (>)

EO <MDL – 0.11 0.031 0.025 0.026 1.5 0.83 0.88 0.87 2.0E-5* (>)

PC <MDL – 0.135 0.034 0.025 0.029 2.1 0.85 0.87 0.86 1.1E-4* (>)

- (mg/L)

ASH <MDL – 0.28 0.067 0.034 0.072 1.8 1.1 - - - -

AP <MDL – 0.034 0.0091 0.0070 0.0071 1.9 0.78 0.86 0.80 8.6E-8 (>)

EO <MDL - 0.039 0.0092 0.0070 0.010 2.1 1.05 0.86 0.82 6.8E-8 (>)

PC <MDL – 0.19 0.032 0.014 0.044 2.6 1.38 0.52 0.62 1.6E-3 (>)

- (mg/L)

ASH <MDL – 1.1 0.38 0.33 0.27 1.4 0.71 - - - -

AP 0.36 – 2.1 0.92 0.92 0.53 1.0 0.57 -1.43 -1.40 1.1E-5 (<)

EO 0.3 – 2.0 0.82 0.60 0.51 1.0 0.62 -1.17 -0.96 1.1E-4* (<)

PC 0.18 – 1.7 0.58 0.37 0.44 1.3 0.78 -0.54 -0.13 0.26* -

org-N (mg/L)

ASH <MDL – 3.5 1.0 0.74 0.80 1.8 0.80 - - - -

AP 0.042 - 0.282 0.16 0.16 0.08 0.04 0.49 0.84 0.80 9.5E-7* (>)

EO <MDL – 0.7 0.16 0.14 0.13 2.8 0.82 0.84 0.83 2.0E-5* (>)

PC <MDL – 0.73 0.30 0.25 0.17 1.0 0.59 0.70 0.70 3.3E-8 (>)

TN (mg/L)

ASH 0.76 – 4.6 1.7 1.3 0.96 1.7 0.56 - - - -

AP 0.46 - 2.4 1.1 1.1 0.59 0.8 0.53 0.35 0.35 0.0025 (>)

EO 0.38 - 2.4 1.0 1.0 0.57 0.9 0.56 0.40 0.45 0.00047 (>)

PC 0.35 – 2.3 0.95 0.80 0.58 1.1 0.6 0.45 0.43 3.8E-5 (>)

(mg/L)

ASH <MDL – 1.49 0.11 0.029 0.28 4.8 2.70 - - - -

AP <MDL – 0.0714 0.019 0.015 0.017 2.2 0.92 0.82 0.26 0.023 (=)

EO <MDL – 0.078 0.019 0.015 0.018 2.2 0.95 0.82 0.35 0.019 (>)

PC <MDL – 0.29 0.10 0.088 0.054 1.7 0.54 0.05 -1.75 2.4E-4 (<)

TP (mg/L)

ASH 0.068 – 2.1 0.25 0.17 0.39 4.6 1.54 - - - -

AP <MDL - 0.106 0.03 0.026 0.020 2.5 0.67 0.88 0.81 1.1E-11 (>)

EO <MDL – 0.116 0.035 0.025 0.029 1.7 0.80 0.86 0.82 1.8E-8 (>)

PC 0.049 – 0.3 0.13 0.12 0.063 1.0 0.47 0.47 0.09 0.027 (>)

*sign test performed

(<) = EMC mean/median ASH < EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH= mean/median PP

Table 5-5: Nutrient mass loading results

Pollutant Pavement Range M SOL

(g/ha)

ASH 1.44 – 91 34 25 29 0.8 0.8 610 -

AP 0.56 – 13 2.8 1.8 2.9 2.8 1.0 53 0.91

EO 0.20 – 13 2.8 1.87 2.9 2.3 1.0 54 0.91

PC 0.25 – 18 3.5 2.4 3.9 2.9 1.1 66 0.89

70

- (g/ha)

ASH 2.0 – 30 9.5 6.2 8.7 1.3 0.9 171 -

AP 0.075 – 5.6 1.1 0.57 1.4 2.5 1.3 20 0.8

EO 0.067 – 5.5 1.1 0.44 1.6 2.2 1.5 21 0.88

PC 0.45 – 11.5 2.1 1.1 2.7 2.8 1.3 40 0.76

- (g/ha)

ASH <MDL – 165 59 55 39 1.0 0.7 1059 -

AP 19 – 352 94 69 79 2.2 0.8 1778 -0.68

EO 15 – 339 81 65 75 2.4 0.9 1547 -0.46

PC 11 – 174 52 41 46 1.6 0.9 994 0.06

Org-N

(g/ha)

ASH <MDL – 314 130 138 82 0.5 0.6 2345 -

AP 2.5- 48 19 11 15 0.7 0.8 355 0.85

EO 1.3 – 59 18 15 14 1.4 0.8 333 0.86

PC 6.7 – 118 31 22 29 1.9 0.9 589 0.75

TN (g/ha)

ASH 91 – 525 231 185 119 0.9 0.5 4169 -

AP 22 – 402 116 88 93 1.8 0.8 2207 0.47

EO 17 – 406 103 82 91 2.3 0.9 1955 0.53

PC 19 – 264 89 62 72 1.3 0.8 1689 0.59

(g/ha)

ASH 0.68 – 358 29 5.2 81 4.1 2.8 550 -

AP 0.047 – 12 2.2 1.4 2.6 3.0 1.2 41 0.93

EO 0.14 – 13 2.3 1.3 3.0 2.8 1.3 44 0.92

PC 1.2 – 33 10 7.8 8.2 1.3 0.8 199 0.64

TP (g/ha)

ASH 5.0 – 505 54 21 112 4.0 2.1 1034 -

AP 0.57 – 18 3.5 2.3 3.9 2.8 1.1 66 0.94

EO 0.17 – 20 4.9 2.9 5.6 1.7 1.1 94 0.91

PC 3.5 – 40 14 10 10 1.3 0.77 258 0.75

Relative to runoff, the PPs significantly (p < 0.05) reduced the concentration and loading of H H ,

O2- and Org-N but increased the concentration and loading of O

-. Overall this created at least a 47%

reduction in the concentration of TN and 75% reduction in TN loading. Median TN residuals ranged

between 0.80 mg/L and 1.1 mg/L and were similar between the different PPs.

Effluent from each PP also contained similar H H residual concentrations but the PICP and PC

pavements had significantly (p < 0.05) different O2-, O

- and Org-N residuals (Figure 5-6). Nitrogen is

transformed through biologically-mediated processes within the PP system. In aerobic conditions, NH3

can be nitrified into O2- and then into O

-. The low H

H and O2- residuals coupled with

higher concentrations of O - observed in PP effluent indicate that nitrification is occurring within the

PP. Denitrification of O - into nitrogen gas requires anoxic conditions which are unlikely to exist in the

PP system as they are designed to be free-draining.

71

Figure 5-6: Probability plots

The low permeability of the native soils in combination with the gate valve at the parking lot outlet

temporarily detains stormwater at the base of the PP system after a rainfall event. Water level

measurements (Chapter 3) showed that small sections of the aggregate base were temporarily saturated

after moderate and large rainfalls (i.e. > 7 mm). The temporary saturation zone could generate

favourable condition for further denitrification. Increasing the detention time of stormwater within the

PP system by raising the elevation of underdrains or through the use of outlet control such as adjustable

elbows or valve may provide enhanced stormwater treatment for nitrogen. Designing outlets of

underdrained PP systems to be accessible and adjustable allows for the management of infiltrating

stormwater which meets seasonal objectives. Nutrient management is most critical during growing

seasons and therefore the ability to create temporary anoxic conditions during summer months would be

a useful modification to PP designs. Comparing the individual nitrogen species, which make up TN,

shown in Figure 5-7, revealed that Org-N and O - account for the majority of nitrogen load in the PP

effluent. The observed reduction of TN in PP effluent, relative to runoff, is likely mostly due to the

filtration of particulate Org-N, such as leaf litter or other organics attached to suspended solids. In the

long-term it is not clear if this nitrogen will remain trapped within the PP or if it will remobilize when

organic material decomposes and nitrogen is mineralized.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.001 0.01 0.1 1

Per

cen

t U

nd

er

NO2- (mg/L)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.1 1 10

NO3- (mg/L)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.01 0.1 1 10

Org-N (mg/L)

ASH

AP

EO

PC

72

Figure 5-7: Nitrogen total pollutant mass

The PICP and PC pavements had different effects on phosphorus concentrations and loadings. The PPs

remove phosphorus through a number of mechanisms. Filtration removes particulate-phosphorus and

geochemical sorption removes dissolved phosphorus through a combination of adsorption and

precipitation. Some phosphorus may also be taken up by plant activity connected with the PP system.

Relative to runoff, both types of PP reduced TP in effluent but performance metrics and graphical

summaries (Figure 5-8) indicated that the PICP (ERPICP = 0.86, REPICP = 0.81) had a larger effect than

the PC (ERPC = 0.47, REPC = 0.09). The higher TP residuals in PC effluent, relative to PICP effluent, is

associated with elevated concentration of PO -

in PC effluent. However, regardless of the differences in

residual concentrations, the PPs captured the majority of phosphorus within infiltrating stormwater and

reduced TP loading by over 75%.

Figure 5-8: Total phosphorus (TP) boxplots and probability plot

The PPs reduced the occurrence of nutrient levels which exceeded guidelines (Table 5-1). Almost all of

the sampled ASH runoff (25 of 26 samples) exceeded the PWQO for H H while a third of PP

0

500

1000

1500

2000

2500

3000

3500

4000

4500

ASH AP EO PC

Load

ing (

g/h

a)

Org-N

NO3-N

NO2-N

NH3+NH4

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.01 0.1 1 10

Per

cen

t U

nd

er

TP (mg/L)

ASH

AP

EO

PC

0.001

0.01

0.1

1

10

AP EO PC ASH

TP

(m

g/L

)

PWQO-

Interim

73

effluent samples did not exceed this guideline. Reducing the concentration of H H in stormwater

is an important environmental benefit because H can be toxic to many aquatic organisms. All runoff

and PC effluent exceeded the Interim-PWQO for TP but more than half of the sampled PICP effluents

were below this guideline. Lowering the concentration of TP in stormwater below the PWQO will

prevent excessive plant growth in downstream creeks and streams which degrades the health of these

surface water systems.

Reducing overall nutrient loading to surface water systems is essential in mitigating eutrophication.

Point sources of nutrients are becoming less significant contributors as wasterwater treatment facilities

are improved. Consequently, non-point sources such as stormwater are becoming increasingly important

contributors of nutrients. A local example is the Lake Simcoe watershed where stormwater from

urbanized areas is estimated to contribute a third of the total annual phosphorus loading to the Lake

(Lake Simcoe Region Conservation Authority, 2007). Phosphorus loading is an issue of the availability

of nutrients not just concentration. PP systems reduce overall nutrient availability by infiltrating

stormwater and decreasing the total volume of stormwater directed to surface water systems (Chapter 3).

Optimizing the drainage design of PPs to maximize volume reduction will thus have dual benefits to

both stormwater quantity and quality.

Metals 5.3.3

The PPs removed several heavy metals from infiltrating stormwater. Descriptive statistics, performance

efficiencies and statistical significance tests for heavy metal concentration data are presented in Table 5-

6 and mass loading data are presented in Table 5-7. Relative to runoff from the ASH pavement, the PP

systems significantly (p < 0.05) reduced the concentration and loading of Cu, Fe, Mn and Zn in

stormwater. Al levels were reduced in PICP effluent but elevated in PC effluent. Median Cu and Zn

residual concentrations were comparable to median levels reported by the International Stormwater

BMP Database but median Pb residuals were higher than those reported by the database. Although

stormwater was tested for Pb throughout the study during the first year of monitoring the minimum

detectable level (MDL) of laboratory analysis was 11 μg/L. The laboratory modified analysis to reduced

Pb MDL to 0.5 μg/L in mid-winter 2011 however this limited the stormwater sample sizes to less than

15 events which was insufficient to fully characterize Pb concentrations. Stormwater samples were also

tested for Cd, Cr, and Ni but concentrations were below detectable levels in more than 50% of collected

samples.

74

Table 5-6: Heavy metal concentration results

Pollutant Pavement Range ER RE p

Al (μg/L)

ASH 107 – 2 240 404 277 426 3.2 1.1 - - - -

AP 65 -821 261 198 191 1.5 0.7 0.35 0.35 1.1E-11 (>)

EO 44 – 922 215 164 192 2.4 0.9 0.47 0.24 1.8E-8 (>)

PC 189 – 1 060 564 525 256 0.6 0.5 -0.40 -0.51 0.027 (>)

B (μg/L)

ASH 10 – 29 20 23 8.0 -0.30 0.4 - - - -

AP 19 – 103 53 52 27 0.6 0.5 -1.6 -1.9 7.7E-7* (<)

EO 26 - 128 65 65 32 0.6 0.5 -2.3 -2.6 7.7E-7* (<)

PC 20 – 74 42 41 16 0.6 0.4 -1.1 -1.8 0.007* (<)

Cu (μg/L)

ASH 4.8 – 50 16 14 9.3 1.9 0.6 - - - -

AP 1.2 – 15 6.3 6.3 3.3 0.6 0.5 0.62 0.62 3.0E-8* (>)

EO 1.9 – 15 5.8 5.6 2.9 1.6 0.5 0.65 0.61 1.7E-8 (>)

PC 1.4 – 24 9.4 6.9 5.6 1.5 0.6 0.43 0.50 4.6E-4* (>)

Fe (μg/L)

ASH 140 – 2 360 653 481 535 1.5 0.8 - - - -

AP 40 – 642 221 165 156 1.4 0.7 0.66 0.60 2.0E-6 (>)

EO 30 – 600 174 135 135 2.1 0.8 0.73 0.74 6.8E-7 (>)

PC 120 – 737 381 379 164 0.7 0.4 0.42 0.32 0.0054 (>)

Pb (μg/L)

ASH 1 – 9.8 3.2 2.1 2.9 1.6 0.9 - - - -

AP 0.9 – 18 5.2 4 4.6 2.0 0.9 - - - -

EO 0.8 – 15 3.7 2.1 3.8 2.1 1.0 - - - -

PC 1.8 – 11 5.7 5.1 2.9 0.4 0.5 - - - -

Mn (μg/L)

ASH 19 – 439 103 534 101 2.0 1.0 - - - -

AP 2.7 – 57 16 15 11 2.2 0.7 0.85 0.87 2.6E-11 (>)

EO 3.8 – 43 12 10 8.4 2.4 0.7 0.88 0.82 5.4E-11 (>)

PC 7.5 – 72 26 21 16 1.3 0.6 0.75 0.71 1.06E-8 (>)

K (μg/L)

ASH 0.4 – 8.3 1.8 1.1 1.9 2.4 1.1 - - - -

AP 20 – 54 30 28 8.1 1.7 0.3 -16 -27 3.7E-16 (<)

EO 11 – 44 21 20 6.8 1.8 0.3 -11 -19 < 2.2E-16 (<)

PC 45 – 311 133 127 61 0.9 0.5 -75 -109 < 2.2E-16 (<)

Sr (μg/L)

ASH 42 – 506 147 83 138 1.7 0.9 - - - -

AP 1 400 – 5 310 3645 3675 986 -0.5 0.3 -24 -40 3.0E-8* (<)

EO 1 850 – 5 830 4 022 4 175 983 -0.3 0.2 -26 -49 3.0E-8* (<)

PC 550 – 2 510 1 210 1 115 581 0.7 0.5 -7 -9.3 3.0E-8* (<)

Zn (μg/L)

ASH 14 – 308 85 43 91 1.4 1.1 - - - -

AP 5.2 - 46 19 16 11.3 1.0 0.6 0.78 0.80 9.7E-6* (>)

EO 5.1 - 33 14 12 7.6 1.2 0.6 0.85 0.82 7.7E-7* (>)

PC 2.2 - 28 13 13 7.5 0.4 0.6 0.50 0.62 3.0E-8* (>)

*sign test performed

(<) = EMC mean/median ASH < EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH = mean/median PP

75

Table 5-7: Heavy metal mass loading results

Pollutant Pavement Range M SOL

Al

(g/ha)

ASH 5.3 – 248 65 42 60 1.7 0.9 1362 -

AP 2.8 – 172 37 22 45 2.2 1.2 736 0.46

EO 1.5 – 169 34 23 46 2.3 1.4 984 0.50

PC 13 – 230 70 53 62 1.6 0.9 1410 -0.04

B (g/ha)

ASH 0.91 – 4.8 2.4 2.0 1.5 1.5 0.6 12 -

AP 1.4 – 20 7.6 6.1 5.8 1.3 0.8 84 -6.1

EO 0.92 – 25 9.4 6.8 7.0 1.4 0.7 103 -7.7

PC 1.6 – 17 6.0 4.8 4.9 1.6 0.8 60 -4.0

Cu (g/ha)

ASH 0.47 – 13 3.2 2.5 2.9 2.2 0.9 67 -

AP 0.046 – 4.3 0.91 0.63 0.95 2.6 1.1 18 0.73

EO 0.083 – 5.2 0.86 0.57 1.1 3.4 1.3 17 0.74

PC 0.29 – 6.8 1.2 0.66 1.5 3.1 1.3 23 0.65

Fe (g/ha)

ASH 17 – 609 122 75 146 2.5 1.2 2 564 -

AP 2.4 – 98 29 19 29 1.4 1.0 570 0.78

EO 1.5 – 100 25 17 28 1.7 1.1 504 0.80

PC 8.6 – 137 46 43 36 1.0 0.8 924 0.64

Pb (g/ha)

ASH 0.13 – 3.6 0.65 0.30 1.0 3.2 1.5 7 -

AP 0.067 – 3.7 0.95 0.38 1.2 1.8 1.3 10 -

EO 0.021 – 3.0 0.76 0.35 1.0 1.7 1.3 8 -

PC 0.14 – 3.1 0.90 0.42 1.0 1.7 1.1 9 -

Mn (g/ha)

ASH 2.6 – 167 23 11 38 3.2 1.6 492 -

AP 0.19 – 14 2.5 1.3 3.4 2.6 1.3 50 0.90

EO 0.14 – 12 2.2 1.8 3.4 2.2 1.6 41 0.92

PC 0.37 – 14 3.3 2.3 3.7 2.2 1.1 66 0.87

K (kg/ha)

ASH 0.034 – 2.2 0.48 0.19 0.68 1.7 1.4 10 -

AP 0.75 – 11 3.6 3.3 2.3 1.3 0.6 72 -6.1

EO 0.39 – 8.0 2.6 2.6 1.9 1.0 0.7 53 -4.2

PC 2.8 – 38 16 14 11 0.8 0.7 313 -30

Sr (kg/ha)

ASH 0.0040 – 0.18 0.029 0.017 0.039 3.3 1.3 0.61 -

AP 0.069 – 0.83 0.42 0.48 0.23 0.0 0.5 8.4 -13

EO 0.085 – 1.0 0.5 0.47 0.30 0.3 0.6 9.9 -15

PC 0.026 – 0.36 0.12 0.10 0.087 1.4 0.7 2.4 -2.9

Zn (g/ha)

ASH 1.5 – 93 19 8.8 26 2.0 1.4 400

AP 0.28 – 12 2.3 1.2 2.9 2.7 1.3 45 0.89

EO 0.17 – 9.6 1.7 0.93 2.2 2.7 1.3 34 0.91

PC 0.10 – 7.2 1.4 0.78 1.7 2.5 1.2 28 0.93

The PP systems reduced the incidence of Zn concentrations which exceeded the PWQO (Table 5-1). The

majority of runoff samples, 83%, were above the PWQO while less than 20% of PP samples exceeded

this guideline. The PICP also reduced the incidence of Al, Cu and Fe concentrations which were above

the water quality guidelines. Overall, the PICP tended to capture more heavy metals, both in terms of

concentration and loading, than the PC but further investigation is needed to identify the removal

mechanism of metals. Additional monitoring is needed to evaluate the long-term retention of captured

heavy metals.

The PPs appeared to introduce new materials, such as B, K and Sr, into stormwater as it infiltrated

through the aggregates. PP effluent also had detectable levels of Ar, Mg, Mo and U which were not

present in runoff. K and Sr are not pollutants of concern and do not have associated drinking or

76

environmental water quality guidelines. There is a PWQO for B (Table 5-1) but concentrations in PP

effluent were well below this guideline. High K concentrations were particularly associated with PC

effluent while Sr concentrations were associated with PICP effluent. Shown in Figure 5-9, the

concentration of these pollutants in effluent decreased exponentially over the course of the study. These

results are not necessarily representative for other PP installations since they may be dependent on the

source of construction materials (i.e. quarry).

Figure 5-9: Potassium (K) and Strontium (Sr) concentration time series

Sample boxes 5.3.4

The concentration of TS and TSS as well as pH measured in water samples at the University of Guelph

are presented in Figure 5-10. Since the boxes were not subjected to traffic and only treated rainfall

which fell directly onto the box the water was fairly clean. Detectable traces of suspended material

(TSS) were only observed in water samples collected shortly after the boxes were deployed outdoors.

Following this the concentration of total solids (TS) in collected samples was comprised of almost

entirely dissolved solids (DS). During construction, all of the aggregates were noted to have small

amounts of dust clinging to the stones. This dust was the likely source of suspended material observed in

the collected samples. Stormwater collected later in the season was visibly less turbid and often did not

contain detectable concentrations of TSS. Effluent collected from the PC boxes demonstrated an

exponential decline in TS concentrations. From this result it was deduced that dissolved solids were also

exponentially declining. Smaller but consistent declines in dissolved solids were also indirectly observed

in AP, EO and aggregate effluent. Initially, the pH of PC effluent was much higher than the pH of the

other sample boxes however, by the fall levels had dropped significantly. The behaviour of the PC

boxes was very similar to the behaviour of PC pavement at Kortright. High pH levels in PC effluent are

a characteristic of newly exposed concrete but do not persist after the concrete is exposed to a few rain

events.

0

50

100

150

200

250

300

350

22/1/10 6/6/11 18/10/12

K (

mg

/L)

0

1000

2000

3000

4000

5000

6000

7000

22/1/10 6/6/11 18/10/12

Sr

(μg

/L)

AP

EO

PC

ASH

77

Analyzing effluent from the sample boxes allowed for investigation of the impact that the materials used

in the PP had on stormwater quality without the confounding influence of pollution from traffic. The

study budget limited the number of samples that could be analyzed from the empty box. Water samples

from the empty box were used as a reference to assess if the pavement materials were introducing new

metals or nutrients into the stormwater. Stormwater samples were tested for nutrients but findings were

generally inconclusive because the stormwater collected from the empty box was contaminated with

unexpected nutrient inputs including blown-in grass clippings and bird droppings. Table 5-8 summarizes

the pollutants which were found regularly in sampled effluent.

Figure 5-10: Total solids (TS), total suspended solids (TSS) and pH measured at the University of

Guelph

0.1

1

10

100

1000

10000

17/5/11 6/7/11 25/8/11 14/10/11

TS

(m

g/L

)

Empty box AP1 AP2 EO1 EO2 PC1 PC2 19 mm 60 mm

0.1

1

10

100

1000

10000

17/5/11 6/7/11 25/8/11 14/10/11

TS

S (

mg

/L)

6

7

8

9

10

11

12

17/5/11 6/7/11 25/8/11 14/10/11

pH

78

Table 5-8: Observed metals and nutrients

Pollutant AP EO PC 19 mm 60 mm

Al

Ar

Ba

Ca

Cr

Cu

Fe

Pb

Mg

Mn

Mo

Ni

P

K

Si

Na

St

Ti

V

Zn

O

TP

The different pavement and aggregate materials had varying effects on stormwater quality. Some metals

were only found in effluent from PICP and aggregate boxes (e.g. Ca) while others were only associated

with the PC (e.g. Cr). For many metals each material introduced a distinctive degree of pollution. Figure

5-11 plots the concentrations of Mg and K for each box to illustrate the influence that the material had

on stormwater quality. The 19 mm and 60 mm aggregate were shown to be a larger source of Mg than

the PICP pavers and PC effluent did not contain detectable amounts of Mg. PC and PICP pavements

were shown to be a source of K but to varying degrees. For most metals, concentrations consistently

declined as the boxes were exposed to more rain. This temporal pattern, which was also observed at

Kortright (Figure 5-9), suggests that the PP systems experience a period of stabilization immediately

after construction. In the short term, effluent quality appears to improve as mobile pollutants associated

with the pavement materials and aggregates are flushed from the system. Stabilization of PP effluent has

not been identified or discussed by other researchers but it may be an important process which

influences stormwater quality results. Since most monitoring studies, including this one, are initiated

immediately after construction while stabilization is occurring pollutant removal estimates will be

affected. The experiences at Kortright and with the pavement box experiment suggested that the largest

improvement to stormwater occur in the first few months post-construction but stabilization of some

pollutant concentrations may continue over the first two years of exposure to stormwater.

79

Figure 5-11: Magnesium (Mg) and Potassium (K) concentrations

5.4 CONCLUSIONS

Analysis of PP effluent at Kortright has shown that significant improvements to spring-summer-fall

stormwater quality are possible through the use of partial-infiltration PP systems. Stormwater treatment

is possible even without exfiltration to native soils because improvements to water quality are achieved

by the infiltration process through the permeable surface and aggregate layers. Partial-infiltration

systems reduce the loading of stormwater pollutants to downstream surface water systems by reducing

the volume of stormwater. Designed with the appropriate drainage system PP can be integrated on sites

with low permeability soils, such as Kortright, to provide at source treatment of stormwater.

Effluent from the Kortright PP systems contained 80% less TSS than ASH runoff. PP effluent contained

fewer heavy metal pollutants than ASH runoff as the PP systems captured 65% to 93% of Cu, Fe, Mn

and Zn loadings. Simultaneously, the PPs appeared to introduce new dissolved materials to the

stormwater as a result of infiltrating through the system. The PP systems were shown to reduce

concentration and loading of nitrogen and phosphorus in stormwater providing promising evidence that

0.1

1

10

100

16/7/11 5/8/11 25/8/11 14/9/11 4/10/11 24/10/11 13/11/11

Mg

(m

g/L

)

Empty box AP1 AP2 EO1 EO2 PC1 PC2 19 mm 60 mm

1

10

100

1000

10000

16/7/11 5/8/11 25/8/11 14/9/11 4/10/11 24/10/11 13/11/11

K (

mg

/L)

Empty box AP1 AP2 EO1 EO2 PC1 PC2 19 mm 60 mm

80

PPs may help limit the availability of nutrients in receiving surface water systems. As a low-traffic

parking lot pollutant residuals in PP effluent were sometime lower than those reported by the BMP

Database. Site specific characteristics such as traffic loading influence the performance of PPs as

stormwater treatment systems by controlling the rate and type of pollution entering the parking lot.

Further research is stormwater treatment performance statistics based on site characteristics such as land

use, traffic loading, pavement and drainage design and climate.

This study characterized the water quality of effluent of newly installed PP installations, more

monitoring is needed to assess the long-term behaviour of these systems. Some water quality data, such

as pH, K, or Sr levels, indicate that the quality of PP effluent will decline as the system ages. Study of

PP sample boxes at the University of Guelph highlighted the role that construction materials have on

effluent quality. Pollutants introduced by the pavement and aggregate are almost entirely in a dissolved

form and decline very rapidly after a season of exposure to rainfall. Pollutant concentrations associated

with construction materials, such as St and K in this study, were demonstrated to decline by 50% or

more over two years. The long-term removal processes of PP systems continue to be poorly understood

and the risk of remobilization of pollutants captured by the PP systems has yet to be evaluated. PICP and

PC effluent had different chemistry and quality but relative to runoff all three products, AquaPave, Eco-

Optiloc and Hydromedia Pervious Concrete provided the same overall improvements stormwater

quality.

5.5 REFERENCES

Bean, E., Hunt, W., & Bidelspach, D. (2007). Evaluation of four permeable pavement sites in Eastern

North Carolina for runoff reduction and water quality impacts. J. Irrig. Drain. Eng., 133(6), 583-592.

Brattebo, B., & Booth, D. (2003). Long-term stormwater quantity and quality performance of permeable

pavement systems. Water Res., 37(18), 4369-4376.

Burton, A., & Pitt, R. (2001). Stormwater Effects Hanbook: A Toolbox for Watershed Managers,

Scientists, and Engineers. Boca Raton: Lewis Publishers. Retrieved from Robert Pitt's Group

Publications.

Canadian Council of Ministers of the Environment. (2007). Canadian Environmental Quality

Guidelines. Canadian Council of Ministers of the Environment.

Collins, K., Hunt, W., & Hathaway, J. (2010). Side-by-side comparison of nitrogen species removal for

four types of permeable pavement and standard asphalt in Eastern North Carolina. J. Hydrol. Eng.,

15(6), 512-521.

Drake, J., Bradford, A., & Van Seters, T. (2012). Evaluation of Permeable Pavements in Cold Climates

– Kortright Centre, Vaughan. Toronto: Toronto and Region Conservation Authority.

Fassman, E., & Blackbourn, S. (2010b). Permeable pavement performance over 3 years of monitoring.

Low Impact Development 2010: Redefining Water in the City (pp. 152-165). San Fransisco: ASCE.

81

Geosyntec Consultants and Wright Water Engineers,Inc. (2009). Urban Stormwater BMP Performance

Monitoring Manual.

Geosyntec Consultants, Inc. and Wright Water Engineers,Inc. (2012). International Stormwater Best

Management Practices (BMP) Database Pollutant Category Summary Statistical Addendum: TS,

Bacteria, Nutrients, and Metals.

Health Canada. (2012). Guidelines for Canadian Drinking Water Quality. Healthy Environments and

Consumer Safety Branch, Water, Air and Climate Change Bureau. Ottawa, Ontario: Health Canada.

Kwiatkowski, M., Welker, A., Traver, R., Vanacore, M., & Ladd, T. (2007). Evaluation of an infiltration

best management practice utilizing pervious concrete. J. Am. Water Resour. Assoc., 43(5), 1208-1222.

Lake Simcoe Region Conservation Authority. (2007). Lake Simcoe Basin Stormwater Management and

Retrofit Opportunities. Lake Simcoe Region Conservation Authority: Newmarket.

Legret, M., & Colandini, V. (1999). Effects of a porous pavement with reservoir structure on runoff

water: water quality and fate of heavy metals. Water Sci. Technol., 39(2), 111-117.

Ministry of Environment and Energy (MOE). (1994). Water Management Policies Guidelines

Provincial Water Quality Objectives. Toronto: Queen's Printer for Ontario.

Pitt, R. (2004). The National Stormwater Quality Database (NSQD, version 1.1)

http://rpitt.eng.ua.edu/Research/ms4/Paper/Mainms4paper.html.

Pratt, C., Mantle, J., & Schofield, P. (1989). Urban stormwater reduction and quality improvement

through the use of permeable pavements. Water Sci. Technol., 21(8), 769-778.

Pratt, C., Mantle, J., & Schofield, P. (1995). UK research into the performance of permeable pavement,

reservoir structures in controlling stormwater discharge quantity and quality. Water Sci. Technol., 32(1),

63-69.

Rushton, B. (2001). Low-impact parking lot design reduces runoff and pollutant loads. J. Water Resour.

Plann. Manage,, 172(3), 172-179.

Sansalone, J., & Teng, Z. (2004). In situ partial exfiltration of rainfall runoff. I: Quality and quantity

attenuation. J. Environ. Eng., 130(9), 990-1007.

Toronto and Region Conservation Authority (TRCA). (2008). Performance Evaluation of Permeable

Pavement and a Bioretention Swale. Sustainable Technologies Evaluation Program. Toronto: TRCA.

Tota-Maharaj, K., & Scholz, M. (2010). Efficiency of permeable pavement systems for the removal of

urban runoff pollutants under varying environmental conditions. Environ. Prog. Sustainable Energy,

29(3), 358-369.

82

6 STORMWATER QUALITY OF WINTER EFFLUENT FROM THREE

PARTIAL-INFILTRATION PERMEABLE PAVEMENT SYSTEMS AND

CONVENTIONAL ASPHALT PAVEMENT

6.1 INTRODUCTION

Permeable pavement (PP) systems may be used for source control of urban stormwater. Partial-

infiltration PP systems allow for stormwater infiltration to native soils but drain excess water by way of

underdrains. Outflows from underdrains have improved water quality because the PP acts as a passive

filter removing suspended pollutants. Additional treatment is also possible through adsorption,

transformation, biological degradation and volatization. In cold climates winter stormwater is affected

by maintenance practices including road salting and sanding. The performance of PP as a stormwater

treatment system during the winter is different than performance during other times of the year.

PPs have repeatedly been shown to function in cold climates in North America and Europe (TRCA,

2008; Roseen et al., 2009; Tyner et al., 2009; Houle et al., 2010; Gomez-Ullate et al., 2010, Roseen et

al., 2012). Roseen et al. (2009) observed only minimal changes in hydrologic performance between

summer and winter seasons for a PA parking lot. Observations throughout a winter season by Tyner et

al. (2009) noted that, even though air temperatures within sample plots of PC dropped below freezing on

several occasions, water was not present within the storage volume when these temperatures occurred

because the PP systems drain readily. A two year study of a PA parking lot in Durham, NH by Houle et

al. (2010) at the University of New Hampshire found that the PP performed extremely well in a northern

climate. Neither the presence of frost nor freeze-thaw cycling affected the hydraulic integrity of the

system. It has been argued that PP systems are more resistant to freezing and, thus, are also more

resistant to frost heave than impervious pavements (Bäckström, 2000). Stormwater exfiltration causes

higher moisture levels in underlying soils which increases the latent heat of the ground and postpones

freezing within the pavement (Kevern et al., 2009; Bäckström, 2000). Simultaneously, thawing

processes are expedited by melt water infiltrating from the surface (Kevern et al., 2009; Bäckström,

2000). In combination, these two processes lead to shorter periods of frost and shallow frost penetration

reducing the overall risk of frost damage.

Permeable pavements have not been widely adopted in cold climates such as Ontario because of

concerns regarding durability and effective life of PPs subjected to freeze-thaw cycling and, as a result,

the quality of winter stormwater effluent from PP systems has received limited attention. PP systems

have been shown to provide substantial improvements to stormwater quality even when water is only

infiltrated through the pavement and aggregate base (Chapter 5) and thus underdrained PP systems

should be expected to improve stormwater quality regardless of the season. A few winter studies,

Roseen et al. (2009, 2012) and TRCA (2008) have produced promising results. Roseen et al. (2009)

found that TSS, total petroleum hydrocarbon-diesel and Zn efficiency ratios (a measure of overall

treatment performance) from a PP lot in New Hampshire did not vary between summer and winter

seasons.

83

Salts, originating from road salting practices in cold climates, are generally poorly attenuated and

migrate easily through the pavement and aggregate and, ultimately, to groundwater and surface water

receiving systems. In underlying soils, cation replacement (Na+ for Ca

2+ and Mg

2+) can lead to the

leaching or mobilization of several heavy metals and changes in physical soil structure (Marsalek,

2003). Elevated levels of metals have been observed within exfiltrate in winter and early spring months,

but were attributed to increased loading rates at the PP surface (Boving et al., 2008; TRCA, 2008). Since

PP systems alter the timing, rate and volume of stormwater flows there may be opportunities to dilute

seasonally high pollutant concentration but these processes have not been sufficiently assessed or

critically evaluated. The most significant environmental benefit of PPs may be their ability to limit the

application of road salts. Houle (2008) observed a 75% average reduction in annual salt use on porous

asphalt pavement compared with impermeable asphalt. On impermeable pavements melt water

frequently re-freezes as ice, requiring salt to maintain safe conditions for traffic and pedestrians. On PPs

melt water does not remain at the pavement surface but rather infiltrates into the PP system and therefore

the pavement surface requires less frequent salting.

To fully understand the environmental impact of partial-infiltration PP systems more information is

needed regarding stormwater quality of effluent. In cold climates, like Ontario, a distinction between the

winter season and other times of the year is needed to interpret water quality performance data. The

objective of this study is to compare overall stormwater quality of PP effluent from three partial-

infiltration PP systems and asphalt runoff throughout winter months. This paper will focus on how

winter stormwater quality differs from spring, summer and fall stormwater. The stormwater quality of

permeable interlocking concrete pavement (PICP) and pervious concrete effluent will be examined and

trade-offs between the two systems will be discussed. Stormwater quality is evaluated for general

quality, petroleum-based hydrocarbons, nutrients and metals. The results of this study demonstrate the

environmental benefits of partial-infiltration PP systems in the context of stormwater quality.

6.2 METHODOLOGY

Site Design 6.2.1

The PP parking lot is located at the Kortright Centre for Conservation in Vaughan, Ontario. Constructed

over the fall of 2009 and the spring of 2010 the facility consists of four pavement cells which are 230-

233 m2 in size and have a capacity for 8-10 parked vehicles in each cell (Figure 6-1). Two cells are

constructed with PICP; AquaPave® (AP) and Eco-Optiloc® (EO), one cell is constructed with

Hydromedia® Pervious Concrete (PC) supplied by Lafarge and one cell is constructed with traditional

asphalt (ASH). The pavement cells are separated by a raised concrete curb that extends below the

surface to the native soils preventing lateral flow of stormwater between cells. Aggregate reservoirs

below the PP (Figure 6-2 and 6-3) are constructed with two layers of 19 and 60 mm diameter clear stone

providing a combined depth of at least 40 cm. The EO pavement has joints which are 13 to 14 mm wide

and uses high performance bedding (HPB) as joint and bedding material (diameter ~ 1 – 9 mm) while

the AP pavement has joints which are 3 to 4 cm wide and uses HPB as bedding and Engineered Joint

84

Stabilizer (diameter ~ 2 - 3 mm) as joint material. The AP pavement also includes an Inbitex®

geotextile placed between the bedding and aggregate layers. Vegetated berms approximately 5 to 6 m

wide with mature trees line the north and south sides of the parking lot and approximately half of the

berm area slopes towards the pavement.

Figure 6-1: Site schematic

Figure 6-2: Profile of Permeable Interlocking Concrete Pavers

85

Figure 6-3: Profile of Pervious Concrete

Each PP cell is drained by a 100 mm diameter Big O perforated tubing placed at the base of an

aggregate trench at the interface between the aggregate reservoir and the native soil. The ASH cell is

drained via a catchbasin. Infiltrated stormwater collected from each PP cell is conveyed separately in

sealed pipes to a downstream sampling vault. Concrete pipe collars at cell boundaries prevent water

movement along granular trenches surrounding these pipes. A Mirafi Filter Weave® 500 geotextile is

placed below the aggregate base to prevent soils from migrating up into the aggregate layer. Underdrains

for each cell are fitted with flow restrictors to control the rate of drawdown after storm events and prolong

the period over which infiltration can occur. In order to explore the pollutants which could potentially

migrate to a groundwater system an additional perforated pipe was installed below the AP pavement

(referred to as AP Low or APL) and recompacted native soils (Figure 6-2).

The parking lot was plowed during the winter by park staff and salted using Windsor Safe-T-Salt®. A

solution of dissolved road salt and de-ionized water was submitted for analysis to evaluate the pollutants

that are introduced as a result of winter road salting. Road salt applied on the parking lot introduced

numerous pollutants beyond sodium and chloride. Analysis of a dissolved solution of road salt contained

measureable concentrations of metals (Al, Ar, Ba, B, Ca, Pb, Mg, Mn, Ni, K, Sr and Zn), nutrients

(nitrogen and phosphorus) and PAHs (naphthalene).

Monitoring and Data Collection 6.2.2

Water quality sampling was conducted over 24 months between June 2010 and June 2012. This paper

presents the findings from data collected during the winter months of the study. Flow-proportioned

86

samples were collected by automated ISCO samplers and submitted to the Ontario Ministry of the

Environment (OMOE) Laboratory in Etobicoke for analysis. Raw water quality data was presented in

the 2012 report Evaluation of Permeable Pavements in Cold Climates – Kortright Centre, Vaughan

which can be obtained through the Toronto and Region Conservation Authority’s Sustainable

Technologies Evaluation Program (STEP). The water quality parameters, which are the focus of this

article, minimum detection limits (MDL) and relevant water quality guidelines are listed in Table 6-1.

Table 6-1: Stormwater quality parameters

Pollutant Units MDL Guideline

Max Level Source

General Quality

Alkalinity mg/L 2.5

Conductivity uS/cm 5

pH - 5 8.5 PWQO

DS mg/L 50 500 CWQG

TSS mg/L 2.5 variable CEQG

Cl mg/L 1 120 (short-term),

640 (long-term) CEQG

Na mg/L 0.04 200 CWQG

Metals

Al μg/L 1 75 PWQO-Interim

B μg/L 10 200 PWQO

Cd μg/L 0.5 0.5 PWQO-Interim

Cu μg/L 5 5 PWQO-Interim

Fe μg/L 30 300 PWQO

Pb μg/L 0.5 5 PWQO-Interim

Mn μg/L 0.01 50 CWQG

K μg/L 0.06

Sr μg/L 1

Zn μg/L 20 20 PWQO-Interim

Nutrients

mg/L 0.01 0.02 PWQO

mg/L 0.02 3.2 CWQG

mg/L 0.005 45 CWQG

org-N mg/L 0.09

TN mg/L 0.11

mg/L 0.0025

TP mg/L 0.01 0.03 PWQO-Interim

Petroleum based hydrocarbons

Solvent extractable mg/L 1

PAHs ng/L - variable PWQO

Provincial water quality objective (PWQO)

Canadian water quality guideline (CWQG)

Canadian environmental quality guideline (CEQG)

87

When possible, samples were analyzed from all four pavements for the same event however, on some

occasions; stormwater was collected from only one or some of the four pavements. The ASH pavement

in particular, frequently produced runoff while the PPs remained unresponsive. Analysis of Na, K, Mg

was unintentionally omitted from several samples during February and March 2011. As a result the data

set for these pollutants is limited to 13 stormwater samples from the PP systems.

Data Analysis 6.2.3

Analysis methods were based on the recommendations for Low Impact Development (LID) monitoring

presented in the EPA Urban Stormwater BMP Performance Monitoring Manual (2009). Descriptive

statistics including range, mean ( ), median ( ), standard deviation ( ), skew ( ) and coefficient of

variation ( ) were calculated for all parameters. All statistical analysis was performed for a 95%

confidence level. Data for each parameter were evaluated using the EPA’s statistical software ProUCL

4.1 for normal and lognormal distributions using goodness-of-fit statistics. Some of the water quality

data was censored by MDL. For a given parameter, if less than 10% of a data set was censored, results

were assumed to be

. When censored data represented 10 to 50% of the total data set, censored

results were estimated using regression-on-order statistics (ROS) with ProUCL 4.1. When more than

50% of a data set was censored statistics were not calculated for the data.

Boxplots and probability plots for EMC data, grouped by pavement type, were created to examine

differences in stormwater quality. Graphical representation of the data provides additional information

of the general characteristic of the results and enables more comprehensive and statistically-valid

analysis (Geosyntec Consultants and Wright Water Engineers, 2009). Graphical summaries were created

using Microsoft Excel and statistical analysis was performed using the open-source statistical computing

language and environment R. Concentration data were compared with published results in the

International Stormwater Best Management Practices (BMP) Database Pollutant Category Summary

Statistical Addendum which has summarized stormwater quality data from many permeable pavement

installations.

The percentage of results exceeding recommended water quality guidelines including Provincial Water

Quality Objectives (PWQO), Canadian Water Quality Guidelines (CWQG) and Canadian

Environmental Quality Guidelines (CEQG) were calculated for each parameter. Statistically significant

differences in water quality, by pavement type, were evaluated using paired t-tests for normal and

lognormally-transformed data and sign tests for all other data. After reviewing all statistics, efficiency

ratios (Equation 1) and median removal efficiencies (Equation 2) were calculated for pollutants which

demonstrated significant differences between pavement effluents.

Efficiency Ratio:

(Equation 1)

Removal Efficiency:

(Equation 2)

88

For each pavement, pollutant loads were calculated for individual events (Equation 3) and then summed

for the entire study (Equation 4). Pollutant loading reductions were evaluated using a ratio of PP loads to

ASH loads (Equation 5) as a performance metric. Reporting of loading was limited to parameters with at

least one gram of estimated pollutant mass.

Pollutant Load normalized by area (L):

(Equation 3)

Total Pollutant Mass (M): ∑ (Equation 4)

Summation of Pollutant Loads (SOL): ∑

∑

(Equation 5)

where A = pavement area, Vi = event volume and EMC = event mean concentration for events i =1,2,…,

n.

6.3 RESULTS AND DISCUSSION

General Quality and Road Salt 6.3.1

The PPs altered the overall quality of infiltrating stormwater by filtering particulate materials and

introducing new dissolved solids. Descriptive statistics, performance efficiencies and statistical

significance tests for general quality concentration data are presented in Table 6-2 and mass loading data

are presented in Table 6-3.

The different PPs performed similarly and, relative to ASH, significantly (p < 0.05) reduced the

presence of TSS in stormwater. The PICPs and PC pavements reduced the concentration and loading of

TSS by over 90% and 75%, respectively. Median residual TSS concentrations ranged between 8.7 and

10 mg/L which was less than median residuals (13.2 mg/L) reported by the International Stormwater

BMP Database but higher than winter TSS residuals reported by Roseen et al. (2012). Runoff was

significantly (p < 0.05) more acidic than PP effluent which had higher alkalinity and pH. All of the PPs

had pH levels which occasionally exceeded recommended levels (pH =8.5). The PC, in particular, had

very high pH levels throughout the first year of the study (Figure 6-4). However, by the second year,

levels appeared to stabilize and were increasingly comparable with the PICP effluent (Figure 6-4).

89

Table 6-2: General quality concentration results

Pollutant Pavement Range ER RE p

Alkalinity

(mg/L)

ASH 17 – 95 523 51 18 0.4 0.3 - - - -

AP 49 – 164 88 78 33 1.0 0.4 -0.68 -0.71 4.1E-5 (<)

EO 58 – 150 101 100 29 0.26 0.3 -0.92 -1.1 9.1E-7 (<)

PC 93 – 421 186 156 95 1.3 0.5 -2.5 -2.8 7.2E-8 (<)

Conductivity

(uS/cm)

ASH 141 – 96 200 11 922 1 475 20 824 2.5 1.8 - - - -

AP 203 – 5 460 1 728 1 095 1 638 1.1 1.0 0.86 0.03 1* -

EO 291 – 4 500 1943 1 780 1317 0.44 0.7 0.84 -1.06 0.48* -

PC 334 – 4 360 1730 1 330 1130 0.7 0.7 0.85 -0.94 0.24* -

pH

ASH 7.4 – 8.1 7.8 7.8 0.20 -0.3 0.03 - - - -

AP 7.8 – 9.7 8.3 8.2 0.47 1.8 0.06 -0.07 -0.05 7.6E-6* (<)

EO 7.8 – 9.4 8.2 8.2 0.38 1.9 0.05 -0.06 -0.05 3.8E-6* (<)

PC 8.1 – 12 9.3 8.6 1.2 0.8 0.1 -0.2 -0.14 3.8E-6* (<)

DS

(mg/L)

ASH 92 – 68 500 7 525 776 14 042 2.9 1.9 - - - -

AP 132 – 3 450 1 016 622 988 1.3 0.8 0.87 -0.03 1* -

EO 189 – 3 190 1173 1 030 854 0.89 0.7 0.84 -1.3 0.48* -

PC 217 – 2 260 958 815 589 0.7 0.6 0.87 -0.89 0.24* -

TSS (mg/L)

ASH 12 – 313 112 93 79 1.1 0.7 - - - -

AP 2.8 – 33.6 13 9.0 9.5 0.8 0.7 0.88 0.90 7.5E-6 (>)

EO 2.5 – 45 12 8.7 11 1.75 0.9 0.89 0.92 3.2E-7 (>)

PC 1.3 – 101 28 10 30 1.2 1.1 0.75 0.89 2.4E-4 (>)

Cl (mg/L)

ASH 11 – 43 100 5 177 348 10 780 2.7 2.1 - - - -

AP 13 – 1 700 475 217 545 1.2 1.2 0.91 0.19 0.76 -

EO 11 – 1 460 543 456 452 0.58 0.8 0.90 -1.3 0.48* -

PC 9.8 – 1 150 359 200 344 1.1 1.0 0.93 -0.81 0.87 -

Na (mg/L)

ASH 10 – 27 900 3 956 352 6 618 2.3 1.7 - - - -

AP 18 – 972 314 176 338 0.8 1.1 0.92 0.56 0.39* -

EO 20 - 668 318 291 249 0.026 0.8 0.92 0.45 0.39* -

PC 20 - 780 276 194 250 0.7 0.9 0.93 0.19 1* -

*sign test performed

(<) = EMC mean/median ASH< EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH = mean/median PP

Table 6-3: General quality mass loading results

90

Pollutant Pavement Range M SOL

DS

(kg/ha)

ASH 2.1 -3 428 348 38 749 3.1 2.2 9 051 -

AP 2.1 – 426 119 35 154 1.4 1.3 1 306 0.86

EO 7.1 – 454 111 34 141 1.5 1.3 1 338 0.85

PC 9.8 – 441 115 44 145 1.7 1.3 910 0.90

TSS (kg/ha)

ASH 0.23 – 40 6.3 2.4 9.4 2.4 1.5 163 -

AP 0.095 – 4.1 1.1 0.63 1.1 2.2 1.1 12 0.93

EO 0.11 – 4.2 0.84 0.43 1.1 2.7 1.3 10 0.94

PC 0.21 – 20 3.5 0.55 6.2 2.3 1.8 38 0.77

Cl (kg/ha)

ASH 0.80 – 2 472 240 20 546 3.2 2.3 6 002 -

AP 0.37 – 225 61 8.9 83 1.2 1.4 670 0.89

EO 0.46 – 210 55 11 72 1.2 1.3 658 0.89

PC 0.63 – 224 49 17 75 1.9 1.5 368 0.94

Na (kg/ha)

ASH 0.60 – 1 485 150 17 331 3.3 2.2 3 589 -

AP 0.27 – 135 35 6.4 48 1.4 1.4 348 0.90

EO 0.78 – 105 31 16 38 1.1 1.2 310 0.91

PC 1.1 – 152 35 10 54 1.7 1.5 216 0.94

Figure 6-4: pH time series

The PPs eliminated oil and grease that are solvent extractable from stormwater while all runoff samples

contained measureable amounts of this pollutant. Similarly, PAHs were rarely detected in effluent

samples but were frequently observed in runoff. Biodegradation has been identified as the most likely

ultimate fate process for most PAHs (Burton and Pitt, 2001). It is probable that microbial activity is

subdued during the winter so the high removal of hydrocarbons is an unexpected benefit. Alternative

mechanisms such as volitization and sorption may be important processes which remove hydrocarbons

from infiltrating winter stormwater.

Analysis (i.e. descriptive statistics, graphical summaries and hypothesis tests provided in the Appendixes

B, D, F respectively) of AP and APL samples produced inconclusive results. Shown in Figure 6-5, APL

samples consistently contained higher concentrations of TSS than AP samples. This statistically

6.5

7.5

8.5

9.5

10.5

11.5

12.5

16/6/10 16/12/10 16/6/11 16/12/11 16/6/12

pH

PWQO

ASH

AP

EO

91

significant (p < 0.05) result is unexpected because the native soil should act as a fine filter removing

smaller suspended materials as stormwater infiltrates through the media. The high TSS concentrations

indicate that disturbed soils were draining into the APL collection pipe and subsequently, influencing the

concentration of pollutants found in APL effluent. Visual inspections of the APL ISCO sample noted

highly turbid water in some collection bottles. Lab analysis of metal and nutrient concentrations did not

distinguish between dissolved and particulate forms which could have allowed for the origin of

pollutants to be inferred.

Figure 6-5: Total suspended solids (TSS): probability plot (left), time series (right)

During the winter months ASH runoff tended to have DS concentrations and a conductivity which were

equal to or, on many occasions, much higher than levels in PP effluent. This was contrary to water

quality patterns during the spring, summer and fall in which PP effluent had higher DS concentrations

and conductivity than ASH runoff. The use of road salt during the winter introduced dissolved ions in

the form of Na+ and Cl

- as the salt mixed with snow and ice on the pavement surfaces. Throughout the

winter the ASH surface would regularly produce small (i.e. < 2 L/m2) amounts of runoff in the form of

mid-day melted ice and snow while PP outlets remained dry. These hydrologic events were not

associated with warm weather and runoff was confined to the mid-day hours when the sunlight

presumably heated the black asphalt allowing for small amounts of melting. The PP outlets remained dry

possibly because, the grey and more reflective concrete pavements did not permit surface water to melt

or/and because the volume of stormwater infiltrating through the PP systems was not large enough to

reach the outlets. During non-winter seasons the PP systems were found to be capable of infiltrating rain

events which were less than 7 mm in depth (Chapter 3) and so it is not surprising that these very small

melt flows did not reach the PP underdrains.

Water quality parameters associated with road salts were extremely high in runoff from small melt

events because the salt was dissolved into a very small volume of stormwater. Winter maximum DS, Cl,

Na and conductivity levels in ASH runoff and PP effluent differed by over an order of magnitude. By

eliminating the release of concentrated melted water, the PP systems controlled and mitigated the

concentration of Na and Cl during winter months. For both monitored winters in this study similar

0%

20%

40%

60%

80%

100%

1 10 100 1000

Per

cen

t U

nd

er

TSS (mg/L)

AP

APL

1

10

100

1000

10000

16/6/10 16/12/10 16/6/11 16/12/11 16/6/12

TS

S (

mg

/L)

PWQO

AP

APL

92

seasonal patterns (Figure 6-6) were observed in runoff and effluent quality; Na and Cl levels peaked in

the coldest months and receded in late February and March. The early winter was associated with Na

and Cl concentrations that were higher in runoff than in effluent while the late winter was associated the

reverse trend. Overall, this pattern suggests that the slower process of infiltrating stormwater through the

PP systems provides some temporary detention of road salt allowing dissolved ions to be diluted by a

larger volume of stormwater. The delayed release of Na and Cl is potentially beneficial for downstream

systems because there will be further opportunity to dilute pollutants with additional melt water during

the late winter when thawing of accumulated snow is more likely throughout the watershed.

Mass data for Na and Cl in runoff and effluent samples revealed that the PP systems drastically reduced

the loading of these pollutants in winter stormwater. Total pollutant loads were reduced by over 89%

during the winter months. Unfortunately, it was not possible in this study to estimate the total amount of

Na and Cl that migrated into native soils and, potentially, into groundwater systems. PP cannot retain

dissolved road salts and, therefore, these pollutants will ultimately migrate out of the pavement system.

Figure 6-6: Road salt time series: Chloride (Cl), Sodium (Na)

1

10

100

1000

10000

100000

1/11/10 1/5/11 1/11/11 1/5/12

Cl

(mg

/L)

CEQG short

CEQG long

ASH

AP

EO

PC

1

10

100

1000

10000

100000

1/11/10 1/5/11 1/11/11 1/5/12

Na

(m

g/L

)

CWQG

ASH

AP

EO

PC

93

Environmental concerns regarding infiltration of salt-laden stormwater are two-fold; salt will migrate

and potentially contaminate groundwater sources, and cation-exchange within soils may mobilize heavy

metals. The APL observations confirmed that Cl and Na passed through the native soil. There was no

evidence of metal mobilization in this study but long-term observations are still needed to evaluate if

mobilization occurs as the system ages. Cl and Na concentrations in AP and APL effluent were similar

(Figure 6-7) but APL tended to have slightly higher levels. APL effluent also had slightly higher Ca and

Mg concentrations (Appendix C) these ions could have been mobilized by cation replacement within the

soil. The importance of these small increases in concentrations is uncertain since unexpected fines were

flushing into the APL pipe.

Figure 6-7: Time series: Chloride (Cl), Sodium (Na)

Outflow volume reductions in March, were generally small (<20%) because cool, wet weather combined

with melting snow limited the opportunity for stormwater to evaporate or infiltrate into native soils

(Chapter 3). Thus during March, the majority of stormwater infiltrates into the PP and exits by way of

the underdrains. Although some infiltration into soils undoubtedly occurs, the low volume reduction

suggests that the mass of road salt migrating into the subsurface systems would be much smaller than the

mass of road salts migrating to the underdrain outflow. Interpreted together the low pollutant

concentrations, lack of pollutant loading in outflow and small volume reduction indicated that there was

1

10

100

1000

10000

16/6/10 16/12/10 16/6/11 16/12/11 16/6/12

Cl

(mg/L

)

CEQG short

CEQG long

AP

APL

1

10

100

1000

10000

16/6/10 16/12/10 16/6/11 16/12/11 16/6/12

Na

(m

g/L

)

CWQG

AP

APL

94

less road salt mixed into the PP stormwater and thus, the PPs may have required less winter salting than

the ASH pavement. This finding was further supported by the fact that park staff independently reported

that on some instances only the ASH pavement required salting during 2011/2012 winter. The

application rate of road salt on each pavement surface was not rigorously monitored during this study

but future research is planned to investigate the winter maintenance needs of PP systems.

Nutrients 6.3.2

Infiltrating stormwater through the PP systems provided opportunities to trap or filter-out particulate-

forms of nutrients and time for some nutrient species to be transformed. Descriptive statistics,

performance efficiencies and statistical significance tests for nutrient concentration data are presented in

Table 6-4 and mass loading data are presented in Table 6-5.

Table 6-4: Nutrient concentration results

Pollutant Pavement Range ER RE p

(mg/L)

ASH 0.059 – 3.9 0.51 0.31 0.68 3.9 1.3 - - - -

AP 0.015 – 0.20 0.065 0.038 0.056 1.5 0.9 0.87 0.86 6.0E-5 (>)

EO 0.01 – 0.16 0.042 0.025 0.038 2.1 0.9 0.92 0.85 2.8E-6 (>)

PC <MDL – 0.17 0.056 0.043 0.047 1.1 0.8 0.89 0.80 1.3E-4 (>)

- (mg/L)

ASH 0.02 – 0.27 0.07 0.06 0.06 1.9 0.8 - - - -

AP 0.003 – 0.068 0.022 0.018 0.018 1.3 0.8 0.70 0.72 6.0E-4 (>)

EO <MDL – 0.065 0.015 0.0095 0.015 2.3 1.0 0.79 0.81 4.4E-6 (>)

PC <MDL – 0.053 0.024 0.018 0.017 0.5 0.7 0.68 0.57 5.1E-4 (>)

- (mg/L)

ASH 0.12 – 2.6 0.89 0.71 0.61 1.3 0.7 - - - -

AP 0.34 – 1.6 0.81 0.76 0.34 0.9 0.4 0.09 -0.23 0.18 -

EO 0.34 – 1.9 0.72 0.65 0.40 2.2 0.6 0.19 -0.23 0.73 -

PC 0.22 – 1.63 0.55 0.42 0.38 1.9 0.7 0.38 0.24 0.13 -

org-N (mg/L)

ASH <MDL – 4.5 1.3 1.2 1.0 1.2 0.8 - - - -

AP <MDL – 0.45 0.17 0.16 0.11 1.1 0.6 0.87 0.89 1.2E-6 (>)

EO <MDL – 0.36 0.15 0.13 0.10 1.1 0.6 0.89 0.91 5.0E-8 (>)

PC <MDL – 0.8 0.33 0.177 0.25 0.5 0.8 0.75 0.76 1.2E-3* (>)

TN (mg/L)

ASH 0.75 – 8.6 2.7 2.4 1.7 1.6 0.6 - - - -

AP 0.5 – 1.9 1.06 0.98 0.40 0.9 0.4 0.61 0.52 8.6E-5 (>)

EO 0.42 – 2.19 0.92 0.83 0.45 1.6 0.5 0.66 0.64 4.7E-6 (>)

PC 0.41 – 1.87 0.96 0.86 0.47 0.9 0.5 0.65 0.69 3.7E-5 (>)

(mg/L)

ASH 0.0065 – 0.14 0.037 0.032 0.026 2.1 0.7 - - - -

AP 0.0058 – 0.09 0.028 0.023 0.021 1.6 0.8 0.25 0.37 0.24 -

EO 0.0034 – 0.12 0.020 0.012 0.025 3.7 1.3 0.47 0.57 3.8E-3 (>)

PC 0.011 – 0.219 0.058 0.043 0.051 2.0 0.9 -0.56 -0.43 0.1 -

TP (mg/L)

ASH 0.04 – 0.63 0.20 0.19 0.11 1.6 0.6 - - - -

AP 0.012 – 0.12 0.042 0.030 0.030 1.3 0.7 0.79 0.84 1.6E-5 (>)

EO <MDL – 0.185 0.040 0.027 0.043 2.7 1.1 0.80 0.85 4.7E-6 (>)

PC 0.043 – 0.66 0.15 0.12 0.15 2.5 1.0 0.26 0.51 0.24 -

*sign test performed

(<) = EMC mean/median ASH < EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH = mean/median PP

95

Table 6-5: Nutrient mass loading results

Pollutant Pavement Range M SOL

(g/ha)

ASH 0.29 – 156 29 16 34 2.3 1.2 746 -

AP 0.74 – 27 5.4 3.3 7.5 3.0 1.4 59 0.92

EO 0.46 – 14 3.1 2.1 3.7 2.4 1.2 37 0.95

PC 0.20 – 32 5.7 2.6 9.3 2.8 1.6 60 0.92

- (g/ha)

ASH 0.038 – 24 4.1 2.3 5.1 2.6 1.3 106 -

AP 0.14 – 9.8 2.0 1.1 2.8 2.7 1.4 22 0.79

EO 0.14 – 5.8 1.2 0.7 1.6 2.7 1.3 15 0.86

PC 0.20 – 9.0 2.7 0.9 3.0 1.3 1.1 27 0.75

- (g/ha)

ASH 0.59 – 238 54 34 61 1.6 1.1 1401 -

AP 5.2 – 189 65 50 54 1.4 0.8 711 0.49

EO 11 – 135 49 44 36 1.3 0.7 592 0.58

PC 14 – 146 45 29 42 1.9 0.9 387 0.72

Org-N

(g/ha)

ASH <MDL – 334 79 31 105 1.5 1.3 2043 -

AP 3.0 – 52 15 16 14 2.1 0.9 169 0.92

EO 1.9 – 37 11 7.7 9.4 2.3 0.9 126 0.94

PC 4.1 – 139 37 16 44 1.6 1.2 377 0.82

TN (g/ha)

ASH 1.7 – 653 161 78 182 1.4 1.1 4176 -

AP 12 – 278 87 69 76 1.7 0.9 961 0.77

EO 14 – 191 64 54 49 1.7 0.8 770 0.82

PC 19 – 326 90 47 90 2.1 1.0 850 0.80

(g/ha)

ASH 0.012 – 7.5 2.3 1.5 2.3 1.0 1.0 59 -

AP 0.39 – 6.6 1.9 1.8 1.8 2.1 0.9 21 0.65

EO 0.28 – 2.7 1.1 1.0 0.81 0.7 0.7 13 0.77

PC 1.2 – 28 5.7 3.3 7.7 3.1 1.4 57 0.03

TP (g/ha)

ASH 0.10 – 68 13 6.1 17 1.8 1.3 350 -

AP 0.51 – 11 2.6 1.7 3.0 2.7 1.1 29 0.92

EO 0.54 – 6.1 2.0 1.6 1.6 1.8 0.8 24 0.93

PC 2.3 – 71 17 6.2 22 1.8 1.3 175 0.50

Effluent from each PP had significantly (p < 0.05) lower residual concentrations of H H , O2

-

and Org-N than runoff from the ASH pavement. All runoff samples and most effluent samples exceeded

recommended guidelines for H H (Table 6-1). Throughout the spring, summer and fall the PP

systems provided removal of H H so that effluent residual concentrations were more likely to

meet the PWQO than runoff. This was not observed during the winter as H H effluent

concentrations were distinctly higher than concentrations present in the spring, summer and fall.

Throughout most of the year PP effluent contained higher levels of O - (Chapter 5) than runoff but

during the winter no significant differences were observed (p > 0.05). Probability plots, shown in Figure

6-8, illustrated that the three PPs produced similar O -, O2

- and Org-N concentrations during the

winter. TN removal was highest during the winter both in terms of reductions in concentration and mass

loading. Spring-summer-fall ER and RE ranged between 0.35 and 0.45 (Chapter 5) while winter ER and

RE ranged between 0.52 and 0.69. Similarly, spring-summer-fall SOL ranged between 0.47 and 0.59

(Chapter 5) while winter SOL ranged between 0.77 and 0.82. The improvement in nitrogen removal

96

during the winter was the result of higher TN concentrations within runoff (medianwinter TN = 2.4 mg/L

vs. medianspring-summer-fall TN = 1.3 mg/L) as well as a small decrease in TN concentration within effluent

(medianwinter TN = 0.89 mg/L vs. medianspring-summer-fall TN = 1.1 mg/L).

Figure 6-8: Nitrogen probability plots

The winter increase in TN concentrations in runoff was initially surprising since this nutrient often

originates from vegetation, which is dormant in winter, and from seasonally dependent land use

activities such as the use of fertilizers. However, the Windsor Safe-T-Salt which was used on the

Kortright parking lot contained detectable levels of nitrogen and subsequently, served as a pollutant

source throughout the winter.

Comparing the individual nitrogen species, which make up TN, shown in Figure 6-9, revealed that

loading of all nitrogen species was smaller in PP effluent than in ASH runoff. Nitrogen is transformed

through biologically-mediated processes within the PP system. In aerobic conditions, NH3 can be

nitrified into O2- and then into O

-. Denitrification of O

- into nitrogen gas requires anoxic conditions

which are unlikely to exist in the PP system as they are designed to be free-draining. During the spring,

summer and fall high O - indicated that nitrification occurs within the PP systems but conditions were

not suitable to sustain denitrification of O - into N2 gas. The distinctively lower O

- winter residuals

observed suggest that different transformational and removal processes are present during this season.

Water level measurements within the permeable pavement showed that during periods of thaw sections

of the PP base became temporarily saturation. Throughout the 2011 spring thaw a sustained shallow

saturation zones were present within the PP base for approximately two weeks and shown to extend

laterally to the edge of the pavement (Drake et al., 2012). It is thought that these temporary saturated

conditions may have facilitated additional denitrification of O -. Further investigation is needed to

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.001 0.1

Per

cen

t U

nd

er

NO2- (mg/L)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.1 1 10NO3

- (mg/L)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.01 0.1 1 10Org-N

ASH

AP

EO

PC

97

verify if this is a typical behaviour of PP systems in cold climates and to identify the mechanism and

conditions responsible for the observed nitrogen removal.

Figure 6-9: Nitrogen total pollutant mass

Larger PO -

and TP concentrations were observed in the sampled winter stormwater than in the sampled

spring-summer-fall stormwater. Once again this may have been the result of the application of Windsor

Safe-T-Salt on the pavement surfaces. All runoff and PC effluent samples exceeded the Interim-PWQO

for TP. The PICP and PC pavements had different effects on phosphorus concentrations and loadings.

Relative to runoff, both products reduced TP in effluent but performance metrics indicated that the PICP

(ERPICP = 0.79, REPICP = 0.84) had a larger effect than the PC (ERPC = 0.26, REPC = 0.51). The higher

TP residuals in PC effluent, relative to PICP effluent, is likely due to elevated concentration of PO -

in

PC effluent. However, regardless of the differences in residual concentrations, all three PPs reduced TP

loading by over 50%.

Metals 6.3.3

The PPs removed several heavy metals from infiltrating stormwater. Descriptive statistics, performance

efficiencies and statistical significance tests for heavy metal concentration data are presented in Table 6-

6 and mass loading data are presented in Table 6-7. Winter runoff contained large concentrations of

several heavy metals. The increase in pollution is a result of the application of the Windsor Safe-T-Salt

which contained traces of metals as well as pollutants deposited onto the pavement by traffic. Relative to

runoff, the PP systems significantly (p < 0.05) reduced the concentration and loading of Al (PICP only),

Cu, Fe, Mn and Zn in stormwater. Median Cu concentrations were comparable to median levels reported

by the International Stormwater BMP Database but median Pb residuals were higher than those reported

by the database. Dilution of winter samples by MOE laboratories negatively affected some heavy metal

data and caused reported concentrations to be below MDL. In particular, Cu data for the ASH runoff

was affected by this practice and as a result the overall impact of PPs may be somewhat underestimated

because some winter events were lost. In addition to the metals presented in Tables 6-6 and 6-7

0

500

1000

1500

2000

2500

3000

3500

4000

4500

ASH AP EO PC

Load

ing (

g/h

a)

Org-N

NO3-N

NO2-N

NH3+NH4

98

stormwater samples were also tested for Cd, Cr, and Ni but concentrations were below detectable levels

in more than 50% of collected samples.

Table 6-6: Heavy metal concentration results

Pollutant Pavement Range ER RE p

Al (μg/L)

ASH 144 – 1 410 609 485 354 0.8 0.6 - - - -

AP 44 – 1 100 320 205 307 1.9 0.96 0.47 0.59 3.2E-3 (>)

EO 45 – 1 460 281 123 362 2.5 1.3 0.54 0.75 4.0E-4 (>)

PC 48 – 1 260 521 486 401 0.4 0.77 0.14 0.08 0.30 -

B (μg/L)

ASH 10 – 60 24 12 21 1.3 0.9 - - - -

AP 5 - 42 19 18 11 0.8 0.56 0.21 0.07 1.4E-4* (<)

EO 14 – 54 29 27 13 0.75 0.5 -0.22 -0.50 7.3E-5* (<)

PC 12 – 82 36 28 24 0.6 0.67 -0.48 -0.08 0.81* -

Cu (μg/L)

ASH 6.4 – 160 30 17 38 2.8 1.3 - - - -

AP 1.1 – 17.7 5.4 3.3 4.5 1.6 0.83 0.82 0.79 3.2E-3* (>)

EO 2.4 - 11 5.5 4.8 2.8 0.84 0.5 0.82 0.73 3.2E-3* (>)

PC 1.8 – 57 15 8.8 15 1.4 1.04 0.51 0.58 0.019* (>)

Fe (μg/L)

ASH 260 – 3 850 1 089 846 823 1.8 0.8 - - - -

AP 70 – 950 300 145 286 1.4 0.95 0.72 0.79 1.4E-4 (>)

EO 30 – 1 200 253 110 304 2.1 1.2 0.77 0.73 1.1E-5 (>)

PC 30 – 970 387 310 315 0.6 0.81 0.64 0.58 8.5E-4 (>)

Pb (μg/L)

ASH 0.9 – 10.6 5.4 5.5 2.6 0.14 0.5 - - - -

AP 1.3 – 13.5 5.8 3.9 4.1 0.6 0.71 -0.08 0.40 0.97 -

EO 0.6 – 13.6 3.1 1.75 3.4 2.2 1.1 0.43 0.76 0.012 (>)

PC 0.6 – 12 4.2 1.8 3.7 0.9 0.89 0.22 0.58 0.18 -

Mn (μg/L)

ASH 20 – 485 182 136 140 0.99 0.8 - - - -

AP 4.3 – 51 21 14 16 0.9 0.74 0.88 0.89 1.1E-5 (>)

EO 2.6 – 84 18 12 20 2.5 1.1 0.90 0.91 2.2E-6 (>)

PC 2.7 – 61 21 16 18 1.2 0.83 0.88 0.85 1.3E-6 (>)

K (μg/L)

ASH 0.63 – 60 8.2 2.8 12 3.3 1.5 - - - -

AP 9.5 – 66 32 21 20 0.7 0.62 -2.9 -19 3.2E-3* (<)

EO 11.4 – 53.2 26 26 14 0.59 0.5 -2.2 -12 5.9E-3* (<)

PC 41 – 255 102 65 74 1.3 0.7 -12 -53 9.8E-4* (<)

Sr (μg/L)

ASH 78 – 2 840 649 274 714 1.5 1.1 - - - -

AP 1 420 – 33 400 314 176 338 0.8 1.08 -13 -19 7.6E-6* (<)

EO 3 720 – 40 400 12518 6 280 11 951 1.4 1.0 -18 -31 3.8E-6* (<)

PC 738 – 18 600 276 194 250 0.7 0.9 -6 -12 3.8E-6* (<)

Zn (μg/L)

ASH 18 - 789 108 69 134 4.2 1.2 - - - -

AP 11.5 – 49.7 27 24 13 0.5 0.46 0.75 0.84 7.3E-4 (>)

EO 0.4 - 56 16 14 12 2.3 0.7 0.80 0.85 7.2E-5* (>)

PC 18 – 789 12 10 6.5 0.72 0.5 0.26 0.51 2.0E-7 (>)

*sign test performed

(<) = EMC mean/median ASH < EMC mean/median PP

(>) = EMC mean/median ASH > EMC mean/median PP

(=) = mean/median ASH= mean/median PP

Differences in performance between PC and PICP pavements were less obvious during the winter than

during other seasons. The PPs reduced the incidence of Al, Cu and Fe concentrations which were above

water quality guidelines. The PP systems provided similar removal of Mn but provided different

removal performance for Al, Cu and Fe. The AP effluent contained significantly (p < 0.05) higher Zn

concentrations than EO and PC effluent. This distinction was not present during the spring, summer and

fall seasons of the study. Consequently, the AP effluent was also more likely to exceed PWQO (Table 7-

99

1). With the exception of one event, all runoff samples and most (12 of 18) AP samples were above the

PWQO for Zn. In contrast, 80% of EO and PC samples (4 of 19 samples) meet this objective.

Table 6-7: Heavy metal mass loading results

Pollutant Pavement Range M SOL

Al

(g/ha)

ASH 2.0 – 173 34 15 47 2.2 1.4 852 -

AP 4.3 – 70 17 11 19 2.4 1.1 191 0.78

EO 2.2 – 78 15 8.1 21 2.9 1.4 179 0.79

PC 5.7 – 147 47 19 52 1.4 1.1 499 0.41

B (g/ha)

ASH 0.13 – 6.2 2.0 0.88 2.5 1.8 1.3 10 -

AP 0.077 – 3.0 1.1 0.83 0.93 1.3 0.9 9 0.12

EO 0.92 – 3.8 1.8 1.5 0.98 1.7 0.6 14 -0.42

PC 0.59 – 11 2.8 1.4 3.3 2.3 1.2 20 -0.98

Cu (g/ha)

ASH 0.054 – 4.7 1.2 0.72 1.4 1.7 1.1 22 -

AP 0.034 – 2.6 0.45 0.21 0.72 3.0 1.6 5 0.78

EO 0.091 – 1.6 0.40 0.28 0.40 2.8 1.0 5 0.78

PC 0.086 – 11 1.9 0.66 3.3 2.6 1.8 20 0.11

Fe (g/ha)

ASH 2.9 – 326 54 37 75 2.7 1.4 1 414 -

AP 4.1 – 102 20 11 28 2.9 1.4 218 0.85

EO 1.8 – 90 15 6.6 25 3.0 1.6 184 0.87

PC 4.3 – 116 35 13 42 1.5 1.2 376 0.73

Pb (g/ha)

ASH 0.023 – 1.7 0.48 0.33 0.49 1.4 1.0 8 -

AP 0.044 – 1.3 0.37 0.26 0.41 1.8 1.1 4 0.54

EO 0.024 – 0.45 0.18 0.12 0.15 1.0 0.9 2 0.78

PC 0.047 – 1.7 0.42 0.16 0.59 1.8 1.4 4 0.56

Mn (g/ha)

ASH 0.43 – 37 9.1 3.1 11 1.4 1.2 235 -

AP 0.15 – 6.1 1.5 1.1 1.7 2.6 1.1 16 0.93

EO 0.14 – 4.1 0.94 0.68 1.1 2.6 1.1 11 0.95

PC 0.34 – 6.4 1.8 0.87 1.9 1.7 1.1 19 0.92

K (kg/ha)

ASH 0.0065 – 2.3 0.38 0.088 0.66 2.0 1.7 9 -

AP 0.15 – 8.6 3.0 1.5 2.9 1.0 1.0 30 -2.4

EO 0.37 – 7.7 2.7 1.3 2.7 1.0 1.0 26 -2.0

PC 2.0 – 35 11.7 4.7 12 1.2 1.1 86 -8.8

Sr (kg/ha)

ASH 0.0015 – 0.15 0.028 0.010 0.042 2.3 1.5 1 -

AP 0.022 – 4.2 1.1 0.33 1.4 1.4 1.3 12 -16

EO 0.13 – 4.6 1.4 0.34 1.7 1.1 1.2 16 -22

PC 0.052 – 2.7 0.56 0.17 0.83 2.2 1.5 3 -3.8

Zn (g/ha)

ASH 0.33 – 24 4.7 2.7 5.6 2.2 1.2 118 -

AP 0.42 – 7.2 2.0 1.7 1.9 2.3 1.0 22 0.81

EO 0.045 – 2.8 0.94 0.77 0.81 1.2 0.9 11 0.90

PC 0.26 – 4.2 1.1 0.65 1.1 2.2 1.0 11 0.91

Ni and Zn have been identified as pollutants which have a high potential to act as groundwater

contaminants while Cr and Pb have been identified as pollutants which have a moderate potential to act

as groundwater contaminants (Pitt et al., 1999). In this study, no significant differences (p < 0.05) were

observed between Zn concentrations between the AP and APL effluent. The risk of groundwater

contamination from Ni and Cr within infiltrating stormwater appeared to be low as concentrations were

regularly below detection limits (MDLcopper = 0.5 μg/L and MDLchromium = 5 μg/L) in both AP and APL

100

effluent. Finally, Pb concentrations in APL effluent were statistically smaller (p < 0.05) than AP

effluent.

6.4 CONCLUSIONS

In cold climates such as Ontario, winter stormwater quality is distinct from spring, summer and fall

stormwater. During the winter pavements are exposed to snow, freezing temperatures and maintenance

practices, such as road salting and sanding, which introduce different pollutants to stormwater. Analysis

of PP effluent at Kortright has shown that significant improvements to winter stormwater quality are

possible through the use of partial-infiltration PP systems. In this study, TSS concentrations were 90%

lower in PP effluent than ASH runoff. Environmental benefits are possible even without exfiltration to

native soils because improvements to water quality are achieved by infiltrating stormwater through the

permeable surface and aggregate base. The PP systems were shown to further improve stormwater

quality by buffering the concentration of Na and Cl in effluent. Throughout the monitored winters the

PPs reduced the loading of Na and Cl to downstream surface water systems by over 89%. There is

emerging evidence, both from the experiences of park staff at Kortright and from other research projects

(i.e. Houle, 2008), that PP systems may require less frequent salting and ultimately, reduce to amount of

road salting required throughout the winter but further investigation is needed to verify and measure the

winter maintenance needs of these pavements. In partial-infiltration PP systems quantity of Na and Cl

which may migrate into subsurface and groundwater systems requires further study.

Relative to runoff, residual TN and TP concentrations were generally 50% lower in PP effluent. Nutrient

levels within runoff increased during the winter, possible as a result of road salting practices. The PP

systems, however, continued to capture and remove nutrients from stormwater. Nitrogen data indicated

that suitable conditions for denitrification may be present within the PP system during the winter.

Some limitations with lab analysis of metals were encountered but results support findings from other

studies and the PP systems were shown to reduce the concentration metals in stormwater throughout the

winter. Long term studies are needed to evaluate the risk of remobilization of pollutants captured by the

PP systems. Differences in water quality performance were evident between the PICP and PC pavements

but all three products, AquaPave, Eco-Optiloc and Hydromedia Pervious Concrete provided a high level

of stormwater treatment.

6.5 REFERENCES

Bäckström, M. (2000). Ground temperature in porous pavement during freezing and thawing. J. Transp.

Eng., 126(5), 375-381.

Bean, E., Hunt, W., & Bidelspach, D. (2007b). Field survey of permeable pavement surface infiltration

rates. J. Irrig. Drain. Eng., 133(3), 249-255.

Boving, T., Stolt, M., Augenstern, J., & Brosnan, B. (2008). Potential for localized groundwater

contamination in a porous pavement parking lot setting in Rhode Island. Environ. Geol., 55(3), 571-582.

101

Canadian Council of Ministers of the Environment. (2007). Canadian Environmental Quality

Guidelines. Canadian Council of Ministers of the Environment.

Drake, J., Bradford, A., & Van Seters, T. (2012). Evaluation of Permeable Pavements in Cold Climates

– Kortright Centre, Vaughan. Toronto: Toronto and Region Conservation Authority.

Geosyntec Consultants and Wright Water Engineers,Inc. (2009). Urban Stormwater BMP Performance

Monitoring Manual.

Geosyntec Consultants, Inc. and Wright Water Engineers,Inc. (2012). International Stormwater Best

Management Practices (BMP) Database Pollutant Category Summary Statistical Addendum: TS,

Bacteria, Nutrients, and Metals.

Gomez-Ullate, E., Bayon, J., Coupe, S., & Castro-Fresno, D. (2010). Perfomance of pervious pavement

parking bays storing rainwater in the north of Spain. Water Sci. Technol., 62(3), 615-621.

Health Canada. (2012). Guidelines for Canadian Drinking Water Quality. Healthy Environments and

Consumer Safety Branch, Water, Air and Climate Change Bureau. Ottawa, Ontario: Health Canada.

Houle, K., Roseen, R., Ballestero, T., Briggs, J., & Houle, J. (2010). Examination of pervious concrete

and porous asphalt pavements performance for stormwater management in northern climates. Low

Impact Development 2010: Redefining Water in the City (pp. 1281-1298). San Fransisco: ASCE.

Houle, K. (2008). Winter performance assessment of permeable pavements: A comparative study of

porous asphalt, pervious concrete and conventional asphalt in a northern climate. M. Sc. Thesis.

University of New Hampshire: United States of America.

Kevern, J., Schaefer, V., & Wang, K. (2009). Temperature behavior of pervious concrete systems.

Transp. Res. Rec., 2098, 94-101.

Marsalek, J. (2003). Road salts in urban stormwater: an emerging issue in stormwater management in

cold climates. Water Sci. Technol., 48(9), 61-70.

Ministry of Environment and Energy (MOE). (1994). Water Management Policies Guidelines

Provincial Water Quality Objectives. Toronto: Queen's Printer for Ontario.

Roseen, R., Ballestero, T., Houle, J., Avellaneda, P., Briggs, J., & Wildey, R. (2009). Seasonal

performance variations for storm-water management systems in cold climate conditions. J. Environ.

Eng., 135(3), 128-137.

Roseen, R., Ballestero, T., Houle, J., Briggs, J., & Houle, K. (2012). Water quality and hydrologic

performance of a porous asphalt pavement as a storm-water treatment stategy in a cold climate. J.

Environ. Eng., 138(1), 81-89.

102

Toronto and Region Conservation Authority (TRCA). (2008). Performance Evaluation of Permeable

Pavement and a Bioretention Swale. Sustainable Technologies Evaluation Program. Toronto: TRCA.

Tyner, J., Wright, W., & Dobbs, P. (2009). Increasing exfiltration from pervious concrete and

temperature monitoring. J. Environ. Manage., 90(8), 2535-2541.

103

7 ASSESSING THE POTENTIAL FOR RESTORATION OF SURFACE

PERMEABILITY FOR PERMEABLE PAVEMENTS THROUGH

MAINTENANCE

7.1 ABSTRACT

Permeable pavements (PPs) have been used as stormwater management systems throughout Canada and

the United States for over 20 years. After years of exposure to sediment and debris build-up, surface

clogging reduces the infiltration of stormwater and inhibits the hydraulic and environmental functions of

the pavement. Removal of surface material has been shown to restore infiltration but the majority of

studies have been limited to small-scale testing. This paper presents the results small and full-size

equipment testing aimed at restoring surface permeability, including the first testing of regenerative-air

and vacuum-sweeping streetsweepers in Ontario. A regenerative-air truck was tested on two well-used

parking lots with well used permeable interlocking concrete pavers and pervious concrete, while a

vacuum-sweeping truck was demonstrated on a third parking lot with permeable interlocking concrete

pavers. Finally, the vacuum-sweeping truck was tested over a mildly-to-moderately clogged parking lot

which had been in use for only 2 years. Both streetsweepers provided partial rejuvenation of the PP

surface permeability. Post-treatment surface infiltration rates on all three parking lots displayed large

spatial variability, highlighting that localized conditions throughout the pavement have a confounding

influence over the overall effectiveness of maintenance. The impact of maintenance may be improved by

establishing regular cleaning intervals and developing instructional guidelines for pavement owners and

equipment operators.

7.2 INTRODUCTION

Permeable pavement systems are a beneficial stormwater management practice which improve

stormwater quality and mitigate the hydrologic effects of urbanization. Despite over 20 years of research

and demonstration, PP systems do not receive widespread use throughout many parts of Canada and the

United States. A commonly cited concern is the assumption that pavements will clog rapidly resulting in

a loss of infiltration and stormwater management capacity within a relatively short time period. PPs

remove particulate pollutants, such as suspended sediments and associated heavy metals and nutrients,

from stormwater through the processes of filtration and sedimentation. These removal mechanisms

capture and trap particulates inside the voids of the pavement and aggregate layers. Over time,

accumulation of materials within the PP system can decrease surface permeability and limit the ability of

stormwater to infiltrate (Figures 7-1 and 7-2).

104

Figure 7-1: Two examples of PPs which have lost their capacity to infiltrate water

Figure 7-2: New PP installed 2009 (left) and old PP installed 2004 (right)

Removal of fines at and near the pavement surface has been shown to provide partial or full

rehabilitation of surface permeability (Kresin et al., 1997; James and Gerrits, 2003). In recent years,

researchers have tested a variety of maintenance techniques on PPs but consensus on the best

maintenance practices and their overall effectiveness has not been achieved. While industrial

organizations such as the Interlocking Concrete Pavement Institute (ICPI) recommend vacuum-

sweeping some researchers (e.g. Henderson and Tighe, 2011; Chopra et al., 2010a) have recommended

pressure-washing. Testing of vacuum-sweeping equipment has only been performed on a few occasions.

Field tests performed by Chopra et al. (2010b) with an Elgin Whirlwind MV truck on five artificially

clogged PPs showed that vacuum-sweeping restores some surface permeability. Van Duin et al., (2008)

tested a Schwarze Model A800 vacuum-sweeper on UNI Eco-Stone PICP and porous asphalt after one

winter of normal traffic usage and road sanding practices. The truck was unable to restore the surface

permeability of the porous asphalt. Vacuum-sweeping was more successful on the Eco-Stone but results

were inconsistent and varied greatly between different locations.

Understanding and evaluating the effects of maintenance remains a critical topic for PP research.

Standardized maintenance practices have not yet been developed, which has likely contributed to the

105

fact that PPs throughout Canada and the United States are not maintained to protect their hydrologic

functionality. Improper maintenance leads to a higher frequency of pre-mature failure because clogging

materials are not removed before they become embedded within the pavement. Loss of surface

permeability, caused by a lack of maintenance, generates the perception that PP systems have a short

effective life and do not provide reliable infiltration. Since operators are often unaware of the

maintenance requirements of their PPs, performance failures, which result from excessive surface

clogging, are often interpreted as inherent inadequacies of permeable products instead of associating the

failure with improper implementation and use. Ultimately, improper maintenance and any subsequent

failures create reluctance towards the adoption of PP systems as a stormwater management technique

and even skepticism towards low impact development (LID) practices as a whole.

In order to promote the use of PP systems as viable stormwater management systems it is necessary to

demonstrate and evaluate the effectiveness of realistic maintenance equipment and methods. In this

paper the results and experiences of small and full-scale equipment testing, including the first testing of

regenerative-air and vacuum-sweeping trucks on PPs in Ontario, are presented.

7.3 METHODOLOGY

Eight PP parking lots, Sites 1 – 8 described in Table 7-1, were visited in the summer between 2010 and

2012 and surface infiltration measurements were performed before and after maintenance

Small-Sized Equipment Testing 7.3.1

Parking lots selected for small-sized equipment testing (Sites 1 – 7) were at least 3 years old and had

been exposed to several winter seasons without receiving any specialized maintenance to protect or

rejuvenate pavement permeability. Most of the parking lots receive annual mechanical sweeping of the

lot edges to remove debris. Surface permeability was measured using double-ring infiltration tests

(Figure 7-3) as described by Bean et al., 2007 which is a modified procedure of the ASTM D3385 test.

The two rings are sealed to the pavement with plumbers putty and filled with water. Water levels are

recorded at regular intervals as the water drains into the pavement and the falling-head is used to

calculate a vertical infiltration rate. Tests were limited to 40 minutes to ensure that at least 5 infiltration

tests could be performed in a single day. Double-ring infiltration tests do not simulate natural conditions

and calculated infiltration rates will be larger than rates during natural precipitation events because of

the large head of water.

106

Figure 7-3: Surface infiltration measurements: double-ring infiltrometer (left), single-ring

infiltration (right)

Table 7-1: Parking lot details

Site Location Visited Built Type* Uses Drainage Reservoir details

1 Earth Rangers

Foundation, Vaughan 2011 2004 PICP

Drop off and

parking unknown

Granular A base, high

performance bedding

2

MTO Guelph Line

Commuter parking lot,

Milton

2011 2007 PC Parking unknown unconfirmed

3

East Gwillimbury GO

Station, East

Gwillimbury

2010 2004 PICP

Commuter

Drop off and

Pick up

Yes

Granular A, Granular

B, geotextile at the

base

4 Exhibition Place’s

BMO Field, Toronto 2011 2007 PA Parking Yes unconfirmed

5 Sunset Beach,

Richmond Hill 2010 1998 PICP

Drop off

round about

& handicap

parking

No

sand bedding,

compacted Granular

A, well compacted

Granular B

6 Seneca College King’s

Campus, King City 2010 2004 PICP Parking No

Granular A base and

high performance

bedding

7 St. Andrew’s Church,

Niagara-on-the-Lake 2010 - PICP Parking unknown unconfirmed

8

Kortright Pilot

Permeable Parking Lot,

Vaughan

2012 2009/

2010

PICP

PC Parking Yes

high performance

bedding, 19 mm Clear

stone, 60 mm Clear

stone

*Pavement Type: Permeable Interlocking Concrete Pavement (PICP), Pervious Concrete (PC), Porous Asphalt (PA)

107

At each site infiltration measurements were conducted over two days. On the first day five test locations

were selected, mapped and an infiltration test was performed to determine the pre-treatment

performance. One location was cleaned with a Simoniz 1700 PSI electric pressure washer and left to dry

for at least 24 hours. On the second visit three more cleaning treatments were performed on different

spots: sweeping with a push broom as well as vacuuming with a Wet/Dry Mastervac 054-0005-2 and a

Wet/Dry Mastervac 054-0012-4 (see Table 7-2 for vacuum specifications). The remaining location acted

as a control and did not receive any cleaning treatment. The exposed depth in the pavement joints was

recorded and the joints were filled with new aggregate. Infiltration tests were repeated on the five points

to assess the impact of maintenance on surface permeability.

Table 7-2: Vacuum specifications

Cleaning Device Peak power

(hp)

Air flow

(m3/min)

Hose diameter

(cm) Filter

Wet/Dry Mastervac

054-0012-4 6 7.93 6.4 89% 0.5 μm

Wet/Dry Mastervac

054-00-5-02 3 5.95 3.2 89% 0.5 μm

Sediment and debris collected in the vacuums was collected. Debris and large vegetative material was

removed and samples were oven-dried and sieved. Fine material on vacuum filters was removed using a

series of two water traps connected to a suction pump. The collected soil-water mix was dried in an

oven and the remaining fines are weighed. Sediment samples were separated by size as gravel (>4.75

mm), sand (4.75 mm - 0.075 mm) or fines (<0.075 mm) following the Unified Soil Classification

System.

Full-Sized Equipment Testing 7.3.2

The effectiveness of suction-based streetsweepers as a rehabilitative and preventative maintenance

technique for the restoration and retention of surface permeability was explored. Streetsweepers were

tested as rehabilitation techniques on three parking lots (Sites 1 – 3 in Table 7-1) with severely degraded

permeability were revisited in 2011. A streetsweeping truck was tested as preventative maintenance in

2012 at a fourth lot (Site 8 in Table 7-1) which had experienced only mild-to-moderate permeability

losses. This site is a demonstration parking lot and is comprised of three different PP products:

AquaPave® (AP), Eco-Optiloc® (EO) and Hydromedia® Pervious Concrete (PC). At all four locations,

surface permeability was evaluated using single ring infiltration tests (Figure 7-3). By 2011, the ASTM

C1701 Standard Test Method for Surface Infiltration Rate for Pervious Concrete had become more

widely used than the double ring method. The test is comprised of two phases: a pre-wetting action

followed by the infiltration test. Surface infiltration is estimated by measuring the time required to

infiltrate a known volume of water through the pavement surface while water levels are kept at a

constant, shallow head. Once again this test does not simulate natural conditions but serves as a

benchmark to assess overall infiltration capacity or permeability. Surface infiltration rates were

measured before and after treatment with the sweeper truck. Modelling clay was used in place of

108

plumbers’ putty as the sealant material because the clay performed better under Ontario summer

conditions (>25° C). Time limits of thirty and ninety minutes were assigned for the pre-wetting phase

and infiltration test. If water did not completely infiltrate within this time limit the test was recorded as a

failed test. Infiltration rates for failed tests are estimated to be ≤50 mm/h. ICPI recommends cleaning

PPs when surface infiltration rates fall below 250 mm/h and thus the failure criteria of 50 mm/h used in

this study is well below currently accepted hydrologic performance standards.

Sites 1 and 3 were maintained using a regenerative-air Tymco-DST 6 truck (Figure 7-4) operating at low

speeds (1 to 3 km/h) and maximum power (2000 rpm). Sites 2 and 8 were maintained using an Elgin

Whirlwind vacuum truck (Figure 7-4) operating at low speeds ( to 3 km/h) and maximum power (2500

rpm). Regenerative-air trucks have an air recycling system which creates a dustless affect during

operation. A wide pickup head has a blower and a vacuum nozzle on opposite sides of the truck. This

creates a pressurized system which captures dust and debris along the pavement surface. Vacuum-

sweeping trucks operate as true vacuums using suction from a vacuum nozzle along one side of the truck

to remove debris. During the experiments, truck operators were encouraged to operate their vehicles to

maximize the effectiveness of the maintenance. This resulted in differences in approach at each site.

Operators at Site 2 elected to pre-wet the pavement surface while operators at Site 1, 3 and 8 ran the

truck over dry pavement. Tests at Site 1 were also affected by a large rain event 24 h before the

maintenance experiment. During the tests the pavement was dry but sediments within the joints were

still moist. It is unclear if the rain event impacted the effectiveness of the maintenance and further

testing is required to determine if moist conditions help or hinder the removal of fines lodged inside

PICP joints. Following the maintenance at PICP parking lots, new high performance bedding was swept

into joints to replace the material that had been removed.

Figure 7-4: Commercial streetsweepers: Tymco-DST 6 sweeper (left), Elgin Whirlwind sweeper

(right)

Grab samples were collected from truck hoppers at Sites 1, 2 and 3. Samples were oven dried and sieved

in order to analyze the gradation of materials collected by the trucks.

109

7.4 RESULTS

Small-Scale Equipment Testing 7.4.1

7.4.1.1 Pre-Treatment

Summary statistics of the pre-treatment infiltration rate are presented in Table 7-3. Prior to any cleaning

treatments, each parking lot exhibited a great deal of natural variation in surface permeability. The high

variability, indicated by a coefficient of variation (CV) greater than one in Table 7-3, is not unexpected

as there are several confounding variables; pavement age, traffic patterns, reservoir and underdrain

design, maintenance practices and vegetative inputs, which are different at each parking lot. Pre-

treatment infiltration measurements were confirmed as log-normally distributed (skewness (Cs > 0.5)

and Shapiro-Wilks test (p-value = 0.11)) which was also expected as measurements are bounded by the

minimum condition of no (i.e. zero) infiltration.

Table 7-3: Pre-treatment infiltration statistics

Statistics Pre-treatment

Range (mm/hr) 4 – 320

(mm/hr) 56

(mm/hr) 66

(mm/hr) 36

Cs 2.3

CV 1.2

PP systems are typically designed to allow water on the surface to quickly infiltrate, however with the

exception of Site 4, all of the visited parking lots exhibited uniformly low pre-treatment infiltration rates

(Table 7-4). Measured infiltration was frequently in the range of saturated hydraulic conductivity of silty

clay (36 mm/hr – 0.36 mm/hr) (Das, 2007). Such a low rate of infiltration indicated that voids had

become clogged with fine material and flow into the pavement was severely inhibited. The low surface

permeability observed at these sites was most likely caused by a lack of preventative maintenance over

several years. It is important to note, however, that even though infiltration rates were inhibited, the

parking lots retained some permeability prior to any maintenance and thus the pavements were still

providing some reduction of surface runoff. In many northern climates, such as Ontario, where rainfall

intensity is often less than 10 mm/hr the unmaintained PICP should be able to capture the rainfall from

frequent low-intensity precipitation events.

7.4.1.2 Post-Treatment

Improvements to hydrologic performance were different at each parking lot. Table 7-4 presents the

measured pre- and post-treatment infiltration rates, the calculated percent change and test observations.

Sites 2, 4 and 5 had minor or no improvements to infiltration rates while Sites 1, 3, 6 and 7 responded

very positively to vacuum and pressure washing treatments. Poured and modular PP systems responded

differently to the control tests. On the second day of testing PICP (Sites 1, 3, 5-7) tended to have higher

110

infiltration rates while poured PPs (Sites 2 and 4) exhibited reduced infiltration rates. It is postulated that

the initial infiltration test disturbs fine surface sediments with has differing implications on surface

infiltration depending on the pavement type. Fines in PICP are concentrated within the joints between

pavers the infiltration test fines are susceptible to being dislodged and redistributed onto the

impermeable paver resulting in observed increases in permeability during the following infiltration test.

Fines in poured PPs are evenly distributed over the entire surface. The infiltration tests dislodge this

material but re-deposits in as a homogenous film on the pavement surface resulting in observed

decreases in permeability during the following infiltration test. Consequently, there will be a bias in the

data towards larger or smaller infiltration rates on the second day of testing depending on the pavement

type. Changes were only deemed to be improvements in hydrologic performance (shown bolded and

shaded grey in Table 7-4) if the change in infiltration rate before and after a treatment was larger than

that in the control test.

Table 7-5 shows the mass of material collected by the vacuums and the distribution of gravel, sand and

fines from visited parking lots. At many sites the sediment collected by the low suction vacuum was

more than twice the total mass collected by the high suction vacuum. The low suction vacuum had a

small vacuum hose which could be used to break apart embedded and crusted fines which had

accumulated inside paver joints, whereas the high suction vacuum, with a larger hose, was limited to

suction applied at the pavement surface. Sediment samples from the low suction vacuum tended to

contain a larger percentage of gravel and fines compared to the high suction vacuum samples. The

higher percentage of gravel reflects that the ability of the low suction vacuum to remove material

beyond the surface crust where the majority of sand and fines are located. The higher percentage of fines

suggests that these particles are not only located at the surface but distributed throughout the crust and in

the clogged joint. If the fines were at the surface only then larger amounts of fines should have been

present in high suction vacuum samples. Fines are introduced into the permeable pavement through a

number of mechanisms the dominate process is vehicular traffic. Road sanding/salting is a standard

winter practice in Ontario which increases sediment loading to a permeable pavement during winter

months.

111

Table 7-4: Infiltration test results

Site Treatment Infiltration Rate (mm/hr) Absolute

Change (mm/hr)

%

Change

Depth

Exposed (cm) Pre-treatment Post-treatment

1

Control 541 389 335 620 NA

Hand Sweeping 40 43 4 9 <0.5

Low Suction Vacuum 112 1 616 151 1 348 1.5

High Suction Vacuum 29 1 937 191 6 625 3

Pressure Wash 58 1 760 170 2 956 3

2

Control 36 14 -22 -60 NA

Hand Sweeping - - - - NA

Low Suction Vacuum 36 54 18 50 NA

High Suction Vacuum - - - - NA

Pressure Wash 11 220 209 1 933 NA

3

Control 32 58 25 78 NA

Hand Sweeping 22 11 -11 -50 0.2

Low Suction Vacuum 22 2 538 252 11 650 1.0

High Suction Vacuum 25 965 940 3 729 0.5

Pressure Wash 36 2 959 292 8 120 2.5

4

Control 162 54 -108 -67 NA

Hand Sweeping 101 97 -4 -3.6 NA

Low Suction Vacuum 58 155 97 169 NA

High Suction Vacuum 94 94 0 0 NA

Pressure Wash 65 155 90 139 NA

5

Control 7 14 7 100 NA

Hand Sweeping 14 14 0 0 0.4

Low Suction Vacuum 4 14 11 300 0.8

High Suction Vacuum 7 29 22 300 0.4

Pressure Wash 7 > 2 5003 - 2.2

6

Control 11 29 18 167 NA

Hand Sweeping 7 47 40 550 0.1

Low Suction Vacuum 7 65 58 800 0.5

High Suction Vacuum 7 40 32 450 0.3

Pressure Wash 7 -4 - 3.0

7

Control 320 4755 155 48 NA

Hand Sweeping 101 65 -36 -36 0.1

Low Suction Vacuum 137 2 1135 1 976 1 445 3.5

High Suction Vacuum 104 1 004 900 862 1.0

Pressure Wash 173 2 462 2 290 1 325 4.5

1 Crusted sand was dislodged by the pre-treatment test

3 a seal between the rings and pavement was not achieved

4 infiltration rate into the pavement was too

fast to measure accurately 5 worms surfaced during the test

112

Table 7-5: Vacuum sediment samples

Site Vacuum

Suction

Collected

Sediment

Mass (g)

Particle-Size Classification (%)

Gravel Sand Fines (Silt &

Clay)

1 Low 974.14 20.9 72.4 6.7

High 1 228.68 15.7 83.3 1.0

3 Low 376.2 15.5 74.6 9.9

High 152.94 12.6 70.3 17.1

4 Low 54.08 5.8 72.3 21.9

High 70.48 24.4 68.4 7.2

5 Low 558.11 13.3 75.5 11.2

High 144.47 29.7 68.4 1.9

6 Low 316.21 16.6 73.7 9.7

High 77.12 10.1 84.9 5.0

7 Low 717.02 35.3 63.7 1.0

High 99.11 28.3 68.5 3.2

Full-Sized Equipment Testing as Rehabilitation 7.4.2

7.4.2.1 Infiltration

Pre-treatment infiltration measurements revealed that surface permeability had decreased to

unacceptably low levels at all three parking lots. At the two PICP lots, ponded water was observed in

low lying areas after small and moderate rainfall events. Less than 15% of the pre-treatment

measurements had surface infiltration rates >50 mm/h. Passing tests were anomalies and high infiltration

rates could be attributed to the presence of an isolated opening inside the infiltration ring (Figure 7-5).

Figure 7-5: Examples of voids contributing to high pre-treatment surface infiltration rates: PICP

(left), PC (right)

113

Table 7-6 summarizes the number of infiltration measurements >50 mm/h and >250 mm/h before and

after maintenance. At all three locations after maintenance, at least 45% of measurements showed

surface infiltration rates >50 mm/h.

Table 7-6: Passing infiltration tests

Site Total

tests

Pre-Maintenance

(I >50 mm/hr)

Post-Maintenance

(I >50 mm/hr)

Post-Maintenance

(I >250 mm/hr)

1 20 3 13 10

2 35 4 16 9

3 42 6 26 12

Statistics for passing tests (I >50 mm/hr) following maintenance are presented in Table 7-7. Boxplots of

pre- and post-maintenance infiltration rates are presented in Figure 7-6. Overall, following maintenance,

infiltration rates were shown to be higher than pre-treatment rates but the magnitude of improvement

was highly variable. Prior to maintenance, mean infiltration rates were less than 50 mm/h at all three

sites. Following maintenance, the lower 95% confidence interval (CI) of the mean measured infiltration

rate was greater than 50 mm/h at each site, indicating that the maintenance significantly improved

infiltration performance. Maximum recorded infiltration rates at sites 1, 2 and 3 were 2 220 mm/h, 3 625

mm/h and 1 366 mm/h, respectively. Results from Site 2 are notably different compared to the results

from Sites 1 and 3. In particular, Site 2 displayed much larger mean and median infiltration rates.

Regardless, infiltration measurements from Sites 1 to 3 displayed nearly identical variability; CV ranged

between 0.9 and 1.1 and a Cs of 1.4 to 1.5 was observed.

Table 7-7: Post maintenance statistics for infiltration tests (I >50mm/h)

Site Range

(mm/hr)

Mean

(mm/hr)

Median

(mm/hr)

σ

(mm/hr) Cs CV

95% CI* for

mean (mm/hr)

1 <50 – 3 625 515 205 586 1.4 1.1 89-719

2 <50 – 1 366 1 047 529 1 106 1.4 1.1 537-1 602

3 <50 – 2 220 430 307 404 1.5 0.9 242-648

*CI limits estimated using bootstrapping method

114

Figure 7-6: Infiltration boxplots

7.4.2.2 Collected Surface Material

The gradation of surface material collected from the truck hoppers is presented in Figure 7-7. The

regenerative-air and vacuum trucks have different collection systems which would have influenced the

gradation results. The regenerative-air truck had a secondary collection compartment where the majority

of fine material is captured. Results presented in this paper only include coarse material collecting in the

main hopper of the regenerative-air truck. Collected material from the vacuum truck hopper was less

accessible and grab samples could not be collected until a large amount of material had accumulated

inside the hopper. The material collected inside the truck hoppers was very coarse and contained only

small amounts of fine material. Specifically, a very small percentage of material, less than 5%, passed

through the #200 sieve.

Figure 7-7: Gradation of hopper grab samples

10

100

1000

10000

1 (Pre) 1 (Post) 2 (Pre) 2 (Post) 3 (Pre) 3 (Post)

Infi

ltra

tion

(m

m/h

r)

Site

0

10

20

30

40

50

60

70

80

90

0.010.1110

Sed

imen

ts P

ass

ing

(%

)

Size (mm)

GO

ER

MTO

115

7.5 FULL-SIZED EQUIPMENT TESTING AS PREVENTATIVE MAINTENANCE

The use of the Elgin Whirlwind Vacuum truck at Site 8 was considered preventative maintenance

because the PP at this location had only been in use for two years and all three PP products retained

substantial surface permeability prior to any vacuum treatment. Pre-treatment measurements showed

that EO and PC pavements had infiltration rates that exceeded the 250 mm/hr guideline while areas of

the AP pavement remained below this guideline. The AP also had four measurements that failed the

infiltration test (i.e. water was unable to infiltrate within 90 minutes). Statistics for pre- and post-

maintenance infiltration measurements are presented in Table 7-8 and boxplots are shown in Figure 7-8.

Table 7-8: Pre- and post-maintenance infiltration statistics

Pavement Range

(mm/hr)

(mm/hr)

(mm/hr)

(mm/hr) Cs CV

95% CI* for change

in infiltration

(mm/hr)

AP (pre) <50 – 641 158 73 199 1.9 1.26 85 - 182

AP (post) 116 – 660 291 258 156 1.2 0.54

EO (pre) 170 – 2 660 1 020 789 811 1.5 0.80 637 – 2 450

EO (post) 467 – 7 900 2 470 1 870 2 100 1.7 0.86

PC (pre) 7 640 – 13 900 18 200 13 900 9 580 0.5 0.53 -4 570 – 1 420

PC (post) 3 300 – 38 200 17 200 11 200 11 400 0.8 0.66

*CI limits estimated using bootstrapping

Figure 7-8: Infiltration boxplots

10

100

1000

10000

100000

AP (Pre) AP (Post) EO (Pre) EO (Post) PC (Pre) PC (Post)

Infi

ltra

tion

(m

m/h

r)

Pavement

Mean

116

7.6 DISCUSSION

Clogging 7.6.1

By total mass, sediment samples collected during the small-sized vacuums and streetsweeper hoppers

contained higher percentages of sand (2 – 0.075 mm) than fines (< 0.075 mm). Previously, clogging has

been attributed exclusively to fines less than <0.075 mm (James and Gerrits, 2003) but presence of sand

which is smaller than bedding material is, undoubtedly, a contributing factor. Clogging simulations by

Brown et al. (2009) which used synthetic stormwater mixed with fines less than 0.25 mm found that

bedding and coarse aggregate layers did not contribute significantly to the capturing of suspended

materials (i.e. the fines passed through the aggregate layers). This finding suggests that clogging

processes in full-sized PP installations must involve larger sized particles. In PP installations inputs from

traffic, as well as the breakdown of pavement and bedding material, introduce sand particles which

create smaller voids capable of capturing fines. In full-sized installations fines will also behave

differently once exposed and mixed with chemical pollutants such as petroleum-based hydrocarbons.

The combination of coarse sand, fine silts and clays and chemicals create a new material with very

different physiochemical properties that can influence hydraulic behaviour.

Site 7 was the only visited parking lot which had significant vegetative inputs. This location was

surrounded by very large overhanging trees and most of the pavement joints had been colonized by

plants. The PICP was used by church parishioners and received only minimal maintenance as well as

low traffic loads. As a result, plant material such as leaves had accumulated on the surface and plants

were thriving throughout the pavement. All five pre-maintenance infiltration measurements were greater

than 50 mm/hr and it was the only location during the small-sized equipment tests to have a pre-

maintenance measurement exceeding 250 mm/hr. Vegetative inputs like leaf litter have previously been

suggested to prevent surface clogging because material is decomposted (James and Gerrits, 2003).

Anecdotally, evidence of biological activity within the pavement system was observed when earth

worms surfaced during infiltration tests escaping the saturated conditions.

A very different relationship was observed at Site 8, where vegetation seemed to be indicative of low

permeability. Plants had established in PICP along the edges and grew in joints which were filled with

fines. These two experiences highlight the uncertainties which remain regarding the influence of

biological activity and plant colonization on surface permeability. The aeration benefits which have been

previously cited may only occur when plant material is allowed to accumulate on the pavement,

something which would likely be considered aesthetically unacceptable for most applications.

Maintenance Techniques 7.6.2

7.6.2.1 Pressure -Washing

Pressure washing was the most consistently effective method for increasing surface permeability in the

small-sized equipment tests. However, the practical application of this technique may be challenging at

117

larger scales. Pressure washing only dislodges crusted fines that are trapped near the pavement surface,

but this material must be collected and removed from the pavement if lasting improvements are to be

achieved. For small installations, such as walkways or private driveways, washing may be orientated so

that the clogging material is dislodged and washed off of the pavement onto adjacent land. But, for large

installations, pressure washing will likely need to be paired with a secondary technique.

7.6.2.2 Vacuum - Sweeping

Standard shop-vacs can be used to maintain small installations of permeable pavement (e.g. a driveway

or walkway). During the small-sized equipment tests, when vacuuming was effective, the low suction

vacuum removed more material and produced higher post-treatment infiltration rates than the high

suction vacuum. The results highlight that surface suction alone is not necessarily the best treatment

option. The hose of the high suction vacuum is 6.4 cm in diameter whereas the hose for the low suction

vacuum is 3.2 cm in diameter. Similarly, the high suction vacuum hose attachments were also twice as

big as those for the low suction vacuum. The difference in size proved to be important during testing

because only the hose attachments for the low suction vacuum were small enough to fit inside the joint

openings. This meant that the low suction vacuum was able to manually dislodge and break apart

compacted sediment allowing more material to be removed. Greater joint depths were exposed by the

low suction vacuum because the small attachments broke through the surface crust exposing clean

gravel beneath (Table 7-4).

During the full-sized equipment tests, a similar phenomenon was observed at PICP parking lots. When

fines formed a sealed and compacted crust extending over the entire area of a joint the material would

often remain undisturbed even after multiple passes with a streetsweeper. As with the high suction

vacuum, equipment on the Tymco and Elgin sweepers could only roll over the pavement surface and

could not mechanically dislodge or break apart fines. At sites with severe permeability losses (i.e. Sites 1

– 3) this resulted in highly inconsistent removal of joint material and after maintenance it was common

to observe joints that had retained fines next to joints which had been vacuumed empty (Figure 7-9). It

appears that a secondary, pre-treatment technique may be needed to help loosen crusted material. This

may mean fitting sweeper trucks so that the pavement is blasted with pressurized water or air followed

by suction from the vacuum nozzle. Alternatively, multiple techniques may be necessary, such as

pressure washing or manually loosening crusted fines followed by vacuum-sweeping.

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Figure 7-9: Examples of inconsistent removal of joint material

7.6.2.3 Improving the Effectiveness of Maintenance

Maintenance was less effective in areas of high traffic loading and in low lying areas which experienced

regular surface ponding. The maintenance needs of PP systems may be reduced by avoiding designs

with low lying areas and limiting the slope of pavements. In PP parking lots property managers should

anticipate that high traffic areas, such as entrances, exits and thorough-lanes will experience more rapid

clogging and may require more frequent inspection and preventative maintenance than low traffic areas.

The effectiveness of maintenance can likely be improved by implementing clear guidelines for

equipment operators. Some practices which may generate more uniform results include:

1. Implementing a minimum number of two passes over the pavement with streetsweepers;

2. Specifying the appropriate weather conditions for maintenance (i.e. dry conditions);

3. Developing specialized maintenance equipment which can remove embedded fines;

4. Creating and implementing inspection procedures (e.g. visual inspection, monitoring wells,

surface infiltration tests);

5. Performing infiltration tests between rounds of maintenance; and

6. Performing maintenance on regular intervals such as annually or bi-annually.

Additional testing is required to evaluate and compare the suitability of regenerative-air and vacuum

trucks for preventative maintenance and rehabilitation for PP systems. Since different equipment was

used at different locations it is not possible to make direct comparisons between the two technologies.

The two parking lots maintained with the regenerative-air truck (Sites 1 and 3) had very similar post-

maintenance infiltration rates. Coarse materials collected in the truck hopper, sieves #4 through #40, also

had nearly identical gradations even though the parking lots consisted of different types of PPs.

However, without side-by-side testing it is unclear if these results are a coincidence or a reflection of the

performance of the regenerative-air truck.

119

Maintenance Needs of Modular and Poured PP 7.6.3

The pre-maintenance measurements indicated that many PPs in Southern Ontario, the geographical

focus of this study, are not meeting hydrologic performance standards (I >250 mm/h). The small pre-

maintenance infiltration rates of the parking lots demonstrated that without specialized maintenance PPs

become clogged even if they are not subjected to winter sanding. Traditional maintenance practices such

as annual mechanical sweeping do not appear to have any benefit on sustaining surface permeability. As

all sites were less than ten years old it is clear that maintenance programs should be implemented while

the pavement is still young.

Unlike traditional pavements the entire surface of a PP should be cleaned. Because infiltration is

distributed fines and debris accumulate across the entire surface area and not just along gutters, curbs

and low points. On a vacuum truck the suction head is approximately a foot in diameter and so the

pavement must be cleaned in small strips. For small parking lots like Site 8 (AP, EO and PC pavements

are approximately 230 m2) the PP can be cleaned in a few hours. Although the vacuum sweepers were

shown to rejuvenate surface permeability the effectiveness of maintenance may be improved through the

development of specialized equipment designed to address the unique maintenance needs of PP systems.

7.6.3.1 PICP

At many PICP sites the small pre-maintenance infiltration rates were surprising because, at first glance,

joints often appeared to be open in many areas and evidence of ponding occurred in only small sections

of pavement. With closer inspection however, it was observed that compacted material was present

beneath a shallow layer of loose coarse aggregate. This highlights the limitation of visual inspections

when assessing surface permeability. In the past, isolated maintenance has been recommended for

pavement sections experiencing ponding. The experiences of this study suggest that the presence of

ponded water should be interpreted as a symptom of widespread and pervasive clogging throughout the

PICP lot. Consequently, once ponding after small-to-moderate rainfall is observed on a PP surface it

may be too late to implement preventative maintenance and operators will have to organize more

intensive, and possibly, more expensive practices to rehabilitate the pavement.

The streetsweepers were noticeably more effective, both in terms of consistency and magnitude of the

infiltration improvements, on the EO pavement which had experienced only mild-to-moderate

permeability losses. The streetsweepers often could not remove clogging material that extended several

centimeters down into joints and as a result parking lots with severely degraded permeability (Sites 1, 3,

and AP at Site 8) experienced smaller infiltration gains. The streetsweepers were also unable to remove

vegetation that had established itself within joints. Based on the findings of this study it is recommended

that suction-based streetsweeping be required annually or bi-annually for PICP. The experiences at Site

8 suggest that permeability losses may occur more rapidly on PICPs with small joint areas, such as the

AP pavement and therefore more frequent preventative maintenance may be required to maintain

acceptable levels of permeability.

120

The operation of streetsweepers must be carefully observed during maintenance. Vacuum-sweepers like

the Elgin Whirlwind have the ability to suck up bedding material below pavers and, in some cases, even

remove entire pavers. Any damage can be avoided by adjusting the vehicle speed and suction strength.

The cost and time associated with maintenance is anticipated to be higher for PICP than poured

pavements. Joint material removed by streetsweepers must be replaced following maintenance. In this

study new joint material was purchased and replaced manually with push brooms but for future

maintenance mechanical brooms included on streetsweepers could be used to redistribute new joint

material efficiently eliminating physical labour. It is also possible that materials collected by the

streetsweepers could be recycled and returned as joint material after fines and sand are separated through

sieving. The cost and volume of replacement material depends on the specific PICP product. At Site 8

replacement material costs for the EO pavement were less than $50 as the pavement required 1.5 tonnes

of high performance bedding which was purchased at $30.53/tonne. Replacement material costs for the

AP pavement was $300 as the pavement required 15 bags (0.34 tonnes) of engineered joint stabilizer

sand which was purchased at $18.50/bag.

7.6.3.2 Poured PP

Poured pavements did not respond as positively to vacuum cleaning as PICP pavements but the

significance of this result is uncertain due to several confounding factors. Site 2 and 4 are among the

earliest installations of PC and PA in Ontario. Issues associated with the placement of the concrete at

Site 2 have led to excessive ravelling throughout the parking lot. The loose aggregate has been further

broken down by traffic loadings and the cement paste has been ground into a fine material.

Consequently, ravelling may have expedited clogging processes at this site. Site 4 was used to store turf

when a soccer field was replaced in 2010. The construction activities damaged the pavement and

introduced large amounts of soil onto the pavement. In both cases the pavements were clogged by

materials which would not be typical of urban stormwater. Experiences at Site 4 demonstrate the

importance of education if PP systems are going to be implemented as alternatives to traditional

stormwater system.

The performance of PC at Site 8 demonstrated that during the early life of poured PP there is no benefit

from frequent sweeping. Infiltration is concentrated into small joints between pavers on PICPs while

poured PP distributes infiltration across the entire pavement surface. Subsequently, clogging material is

concentrated into joints in PICP while this material disperses evenly into poured PPs. Additionally, the

pavement surface of poured PPs often have larger total percentage of open spaces, and thus larger

infiltration capacity, than PICPs. While poured PPs may require less frequent maintenance it remains to

be seen if, once clogged, these pavement can be effectively rehabilitated. Permeability at Site 2, which

had severely degraded surface conditions, exhibited increased permeability following maintenance with

the regenerative-air truck. The improvements were not consistent throughout the parking lot and it is

possible that if fines migrate too far into the pavement matrix they may become impossible to extract,

permanently affecting surface permeability.

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7.7 CONCLUSIONS

The purpose of these tests was to explore the suitability and effectiveness of different techniques

including large-scale sweeper trucks for restoring and rejuvenating the surface permeability of PPs. The

testing of regenerative-air and vacuum-sweeping trucks on PP parking lots presented in this paper is the

first of its kind in Ontario. Pre-treatment infiltration measurements revealed that all of the visited

parking lots had experienced permeability losses and infiltration was inhibited by sand and fines which

had accumulated within the pavement. Small-sized equipment testing found that vacuum cleaning and

pressure-washing have good potential to improve infiltration capacity. Testing of full-sized

streetsweeping trucks demonstrated that permeability can be partially restored on PICP by suction-based

sweeping. Vacuum-sweeping was beneficial on a PC pavement which had experienced large

permeability losses. Standardized maintenance practices need to be developed to improve the overall

effectiveness of vacuum-sweeping. If PPs are to be more widely implemented it is crucial that

preventative maintenance practices are implemented to ensure that these systems maintain their

permeability and remain hydraulically functional for their designed life.

7.8 REFERENCES

ASTM. (2003). ASTM D 3385 - 03 Standard Test Method for Infiltration Rate of Soils in Field Using

Double-Ring Infiltrometer. West Conshohocken: American Society for Testing and Materials

International.

ASTM. (2009). ASTM C 1701 Standard Test Method for Infiltration Rate of In Place Pervious Concrete.

West Conshohocken: American Society for Testing and Materials International.

Bean, E., Hunt, W., & Bidelspach, D. (2007b). Field survey of permeable pavement surface infiltration

rates. J. Irrig. Drain. Eng., 133(3), 249-255.

Brown, C., Chu, A., van Duin, B., & Valeo, C. (2009). Characteristics of Sediment Removal in Two

Types of Permeable Pavement. Water Qual. Res. J. Can., 44(1), 59-70.

Chopra, M., Kakuturu, S., Ballock, C., Spence, J., & Wanielista, M. (2010a). Effect of rejuvenation

methods on the infiltration rates of pervious concrete pavements. J. Hydrol. Eng., 15(6), 426-433.

Chopra, M., Stuart, E., & Wanielista, M. (2010b). Pervious pavement systems in Florida - research

results. Low Impact Development 2010: Redefining Water in the City (pp. 193-206). San Fransisco:

ASCE.

Henderson, V., & Tighe, S. (2011). Evaluation of pervious concrete pavement permeability renewal

maintenance methods at field sites in Canada. Can. J. Civ. Eng., 38(12), 1404-1413.

122

James, W., & Gerrits, C. (2003). Maintenance of infiltration in modular interlocking concrete pavers

with external drainage cells. In W. James (Ed.), Practical Modeling of Urban Stormwater Systems (Vol.

11, pp. 417-35). Guelph: Computational Hydraulics International.

Kresin, C., James, W., & Elrick, D. (1997). Observations of infiltration through clogged porous concrete

block pavers. In W. James (Ed.), Advances in Modeling the Management of Stormwater Impacts (Vol. 5,

pp. 191-205). Guelph: Computation Hydraulics International.

van Duin, B., Brown, C., Chu, A., Marsalek, J., & Valeo, C. (2008). Characterization of long-term solids

removal and glogging processes in two types of permeable pavement under cold climate conditions. 11th

International Conference on Urban Drainage, (pp. 1-10). Edinburgh.

123

8 CONCLUSIONS AND RECOMMENDATIONS

8.1 CONCLUSIONS

The purpose of this research was to evaluate the performance and operation of partial-infiltration

permeable pavements under Ontario climatic conditions. In the following sections conclusions,

organized by research objective, are provided. In summary the research objectives were to:

1. Identify key factors affecting design (material type, traffic, maintenance practice, organic inputs)

and assess impacts on long term functional, hydrologic and water quality performance;

2. Compare the performance of various porous pavements (interlocking permeable concrete pavers

and porous concrete) and traditional impervious asphalt in terms of functional, hydraulic and

water quality effectiveness;

3. Assess opportunities to use permeable pavement in areas of native soils with low permeability

and determine required type and degree of underdrainage;

4. Evaluate seasonal hydraulic and water quality performance over two years and identify critical

cold climate issues such as winter maintenance, material durability and salt pervasiveness;

5. Evaluate and compare effectiveness of alternative cleaning practices; and

6. Recommend design (and operation and maintenance) modifications to enhance overall

performance.

Objectives 1 and 2 8.1.1

Design factors and their impact on performance were discussed in Chapters 3, 5, 6 and 7. In Chapter 3

the hydrologic performance of Kortright permeable parking lot was evaluated relative to an impervious

asphalt pavement, in Chapters 5 and 6 seasonal performances of the permeable and impermeable

pavements were assessed and in Chapter 7 the long-term hydraulic functionality of several Ontario PP

parking lots were explored. Based on this study the following conclusions address the 1st and 2

nd

research objective:

Influence of material type on performance

1. The PICP and PC pavements behaved similarly in terms of hydrologic functionality and at

Kortright both systems provided similar hydrologic benefits. Even though each product had

different surface permeability outflow hydrographs were not significantly different in terms of

outflow volume, peak flow rate, flow duration or timing. Hydrologic differences which were

observed were generally attributed to construction variables and not the result of the permeable

products.

2. Overall the PICP and PC behaved similarly in terms of water quality functionality but

differences in performances were observed for some pollutants. PPs filtered stormwater

removing a high amount of suspended solids, nutrients and many metals. The PPs drastically

reduced the incidence of detectable levels of hydrocarbons in stormwater. The effluent from all

124

three pavements had increased pH and, during non-winter season, higher conductivity and

dissolved solids. The pH of PC effluent exponentially decreased over the first and second year of

the study. There were notable differences in nutrient concentration and loading in PP effluent

from each pavement likely caused by differences in transformation and removal processes within

the each PP. Differences in effluent quality were also observed in some metals such as Ba, Ca,

Cr, Sr, K etc. which were associated with specific aggregate or pavement materials.

3. The AP, EO and PC pavements at Kortright experienced different rates of surface clogging over

time and had different maintenance needs. The rate of surface clogging was linked to the size of

surface openings. At Kortright the PICPs required maintenance after two years of use whereas

the PC still sustained very high surface permeability.

Influence of other factors on performance

4. Traffic patterns and loading rates have a significant impact on long term surface permeability.

Areas subjected to higher traffic loadings experienced more rapid and substantial rates of

clogging. This was observed at Kortright as well as the mature PP parking lots that were a part of

the study. Operators of PP systems should anticipate that traffic lanes will lose infiltration

capacity more rapidly than low traffic areas. Maintenance of severely degraded pavements was

less successful and highly variable. Therefore it remains unclear if infiltration capacity of high

traffic areas can be fully restored by maintenance.

5. Low lying areas which receive run-on from nearby pavements were also observed to experience

more substantial clogging. Most design guidelines and manuals for PPs already recommend that

large slopes and low spots should be avoided and the findings of this study support this practice.

Based on the observations and experiences of this study the use of PPs to treat and infiltrate run-

on water from adjacent impermeable surfaces may increase the rate of clogging.

6. At Kortright areas where vegetation established within the PP did not have higher surface

permeability. Biological processes within PP systems are not well understood and more

information is needed to determine the influence of vegetation on infiltration and stormwater

quality.

Objective 3 8.1.2

Opportunities to use PP in areas of native soils with low permeability were assessed through the

monitoring of the Kortright permeable parking lot and presented in Chapter 3. The benefits to

stormwater quality provided by the PP systems were presented in Chapters 5 and 6. Based on this study

the following conclusions address the 3rd

research objective:

1. The partial infiltration PP systems were found to provide substantial volume and peak flow

reductions for stormwater outflow. Overall the volume of stormwater released from the PPs was

43% smaller than runoff produced by the asphalt pavement. Peak flows were reduced, on

average, by 91% during the study. The hydrologic performance of the PPs at Kortright

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demonstrated that partial infiltration PP systems can provide stormwater quantity control over

low permeability soils.

2. The outlets of the PPs at Kortright were controlled by a gate valve. Restricting the outlet valves

increases the detention time of infiltration stormwater and thus provides more opportunities for

infiltration to the native soils, evapotranspiration and stormwater treatment. The closed-valve

tests, which simulated a raised outlet, demonstrated that the environmental benefits of PP

systems are enhanced by extending the detention of infiltrated stormwater.

3. The permeable pavements improved stormwater quality by reducing the concentration of

hydrocarbons, suspended solids, nutrients and most metals verifying that the presence of low-

permeability soils not a prohibitive site condition in achieving benefits for stormwater quality.

Objective 4 8.1.3

Seasonal hydraulic and water quality performance of the Kortright parking lot was evaluated in Chapters

3, 5 and 6. The AP, EO and PC pavements were shown to function hydraulically throughout two winters

in Chapter 3. The stormwater quality of PP effluent collected in the spring, summer and fall was

analyzed in Chapter 5 and winter stormwater quality was analyzed in Chapter 6. Based on this study the

following conclusions address the 4th

research objective:

1. Overall the PPs provided the same type of benefits to stormwater quality throughout the year but

the degree of treatment was different between winter and non-winter seasons. The permeable

pavements reduced the concentration and loading of suspended solids, hydrocarbons, nutrients

and many heavy metals throughout all seasons. The permeable pavements increased the pH of

stormwater and occasionally exceeded provincial water quality objectives for pH.

2. The PP pavements exhibited a stabilization of stormwater quality throughout the study. The

presence of this process was further confirmed by the pavement box experiment conducted at the

University of Guelph. The concentration of parameters associated with materials used to

construct the PP systems such as pH, K, and Sr rapidly declined during the first few months after

construction.

3. The winter monitoring produced many important findings. The PP systems buffered the

concentration of Na and Cl in stormwater effluent and reduced the loading of Na and Cl to

downstream surface water systems by over 89%. Nutrient levels within runoff increased during

the winter, possible as a result of road salting practices whereas winter nutrient residuals in PP

effluent remained unchanged or even slightly decreased. Nitrogen data indicated that conditions

may exist within the PP systems to allow for denitrification of O - to during the winter.

Objective 5 8.1.4

Several maintenance practices were tested and evaluated in Chapter 7. Based on this study the following

conclusions address the 5th

research objective:

126

1. During this study there were no noted problems associated with pavement durability or with

freeze-thaw cycling. The PC pavement weathered the two winters well and did not experience

significant cracking or ravelling. The Kortright parking lot receives low traffic loadings and only

minimal road salting during the winter, additionally, the 2011 winter was exceptionally warm

and dry (i.e. limited freeze-thaw) both of these variables would have limited structural

degradation of the PC.

2. Small-sized equipment testing found that vacuum cleaning and pressure-washing have good

potential to improve infiltration capacity. These maintenance practices could be used to maintain

small PP installations such as walk-ways and drive-ways.

3. The Kortright PICPs benefited from vacuum-sweeping after two years of exposure and usage.

Testing of full-sized streetsweeping trucks demonstrated that permeability can be partially

restored on PICP by suction-based sweeping.

4. Vacuum-sweeping was beneficial on a PC pavement which had experienced large permeability

losses however vacuum-sweeping at Kortright had no effect of the PC surface permeability. At

the time of the performed maintenance the Kortright PC still sustained high surface infiltration

and therefore it is not surprising that no changes in surface permeability were observed.

8.2 RECOMMENDATIONS

Results of this study indicate that partial-infiltration PP systems can be effective measures for

maintaining or restoring infiltration functions on parking lots and other low volume traffic areas, even in

areas with low permeability soils. The following recommendations are based on study findings and

observations.

Restricting outflow rates from partial-infiltration PPs through the use of outlet control features,

such as the gate valves applied in this study, is recommended to increase stormwater volume

reductions through infiltration.

The release of pollutant associated with pavement and aggregate materials was observed,

particularly for PC. The concentration of these pollutants was observed to decline as the

pavement aged. The level of pH in stormwater effluent was particularly high in PC effluent

during the first few months following construction. There may be opportunities to optimize PC

mix design to improve water treatment benefits.

Vacuum cleaning of PICPs was found to only partially restore surface permeability after 2 years

of operation. Further tests of different techniques for loosening or dislodging compacted material

in permeable pavement joints or pores prior to cleaning are needed to improve the effectiveness

of regenerative air and vacuum sweeping trucks.

Based on maintenance practices evaluated in this study, annual vacuum cleaning of permeable

interlocking concrete pavements is recommended to increase the operational life of these

pavements. The PC pavement maintained high surface permeability over the study period. Even

though the vacuum streetsweeping did not produce a measureable increase in surface

permeability regular maintenance is still recommended as a preventative practice.

127

Further research on the long-term (i.e. > two years) performance of PP systems is needed to

assess how the hydrologic, water quality and functional characteristics of the pavements may

change over time when subjected to Ontario climatic conditions.

In this study, the 2011/2012 winter was unseasonably warm with low amounts of snowfall.

Additional monitoring of winter performance and behaviour is recommended.

In 2011/2012 park staff found that the PPs did not require salting as frequently as the asphalt

pavement. Further research is needed to evaluate how and whether permeable pavements can

maintain safe conditions with lower salt use than conventional pavements.

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APPENDIX A: STORMWATER QUALITY

Table A-1: General chemistry, solids and floatables

Parameter Units Guideline

MDL Sample size

Quality Source ASH AP EO PC APL

Alkalinity mg/L 2.5 64 43 45 45 39

Chloride mg/L 120 (long-term), 640 (short-term) CEQG 1 63 43 45 45 39

Conductivity uS/cm 5 64 43 45 45 39

Solvent extractable mg/L 1 64 43 45 45 39

Hardness mg/L 0.1 55 38 39 38 34

pH - 8.5 PWQO 5 64 43 45 45 39

Solids, dissolved mg/L 500 CWQG 50 64 43 45 45 39

Solids, suspended mg/L variable CEQG 2.5 64 43 45 45 39

Solids, total mg/L 50 64 43 45 45 39

Sodium mg/L 200 CWQG 0.04 55 38 39 38 34

Table A-2: Nutrients

Parameter Units Guideline

MDL Sample size

Quality Source ASH AP EO PC APL

Ammonia + ammonium

nitrogen mg/L 0.02 PWQO 0.01 43 45 45 64 39

Nitrite + nitrate nitrogen mg/L 3.2 CWQG 0.025 43 45 45 64 39

Nitrite nitrogen mg/L 45 CWQG 0.005 43 45 45 64 39

Total kjeldahl nitrogen mg/L 0.1 43 45 45 64 39

Phosphate phosphorus mg/L 0.0025 43 45 45 64 39

Total phosphorus mg/L 0.03 PWQO-Interim 0.01 43 45 45 64 39

Table A-3: Microbiology

Parameter Units Guideline

MDL Sample size

Quality Source ASH AP EO PC APL

Escherichia coli c/100mL 100/100mL PWQO 4 40 30 30 29 23

Fecal streptococcus c/100mL 4 40 30 30 29 23

Pseudomonas aeruginosa c/100mL 4 40 30 30 29 23

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Table A-4: Metals

Parameter Units Guideline

MDL Sample size

Quality Source ASH AP EO PC APL

Aluminum μg/L 75 PWQO-Interim 1 63 43 45 45 39

Antimony μg/L 20 PWQO-Interim 0.5 39 29 29 29 27

Arsenic μg/L 5 PWQO-Interim 1 39 29 29 29 27

Barium μg/L 0.5 64 43 45 45 39

Beryllium μg/L 11 PWQO 0.5 64 43 45 45 39

Boron μg/L 200 PWQO 10 39 29 29 29 27

Cadmium μg/L 0.5 PWQO-Interim 0.5 64 43 45 45 39

Calcium mg/L 0.01 55 38 39 38 34

Chromium μg/L 8.9 PWQO 5 64 43 45 45 39

Cobalt μg/L 0.9 PWQO 1 39 29 29 29 39

Copper μg/L 5 PWQO-Interim 5 64 43 45 45 39

Iron μg/L 300 PWQO 30 64 43 45 45 39

Lead μg/L 5 PWQO-Interim 0.5 42 30 31 30 29

Magnesium μg/L 0.5 55 38 39 38 34

Manganese mg/L 50 CWQG 0.01 64 43 45 45 39

Molybdenum μg/L 40 PWQO-Interim 0.5 64 43 45 45 39

Nickel μg/L 25 PWQO 0.5 64 43 45 45 39

Potassium mg/L 0.06 54 38 39 38 34

Selenium μg/L 100 PWQO 5 39 29 29 29 27

Silver μg/L 0.1 PWQO 0.5 39 29 29 29 27

Strontium μg/L 1 64 43 45 45 39

Thallium μg/L 0.3 PWQO-Interim 0.5 39 29 29 29 27

Titanium μg/L 5 64 43 45 45 39

Uranium μg/L 5 PWQO-Interim 0.5 39 29 29 29 27

Vanadium μg/L 6 PWQO-Interim 0.5 55 42 44 45 39

Zinc μg/L 20 PWQO-Interim 2 64 43 45 45 39

Table A-5: Poly-aromatic hydrocarbons

Parameter Units Guideline

MDL Sample size

Quality Source ASH AP EO PC APL

1-methylnaphthalene ng/L 10 54 35 37 37 33

2-methylnaphthalene ng/L 10 54 35 37 37 33

7, 12-dimethylbenz(a)anthracene ng/L 10 64 43 45 45 35

Acenaphthene ng/L 5 800 CEQG 10 54 35 37 37 33

Acenaphthylene ng/L 10 54 35 37 37 33

Anthracene ng/L 0.8 PWQO-Interim 10 57 38 40 40 35

Benzo(a)anthracene ng/L 18 CEQG 20 57 38 40 40 35

Benzo(a)pyrene ng/L 15 CWQG 3 57 38 40 40 35

Benzo(b)fluoranthene ng/L 10 57 38 40 40 35

Benzo(k)fluoranthene ng/L 0.2 PWQO-Interim 10 57 38 40 40 35

BenzoIpyrene ng/L 20 57 38 40 40 35

Benzo(g,h,i)perylene ng/L 0.02 PWQO-Interim 10 57 38 40 40 35

Chrysene ng/L 0.1 PWQO-Interim 10 57 38 40 40 35

Dibenzo(a,h)anthracene ng/L 2 PWQO-Interim 20 57 38 40 40 35

Fluoranthene ng/L 0.8 PWQO-Interim 10 64 43 45 45 35

Fluorene ng/L 200 PWQO-Interim 10 54 35 37 37 33

Indeno(1,2,3-c,d)pyrene ng/L 20 57 38 40 40 35

Naphthalene ng/L 7 000 PWQO-Interim 10 54 35 37 37 33

Perylene ng/L 0.07 PWQO-Interim 10 57 38 40 40 35

Phenanthrene ng/L 30 PWQO-Interim 10 57 38 40 40 35

Pyrene ng/L 25 CEQG 10 57 38 40 40 35

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APPENDIX B: DESCRIPTIVE STATISTICS

Table B-1: ASH descriptive statistics

Pollutant Units Range GM General Chemistry

Alkalinity mg/L 17 – 138 50 45 43 24 1.3 0.5

Chloride mg/L <MDL – 43 100 2 878 44 24 8 393 3.8 2.9

Conductivity uS/cm 57 - 96200 6 762 91 295 16 604 3.5 2.5

Solvent extractable mg/L <MDL - 36 4 2.1 2 5.6 4.4 1.5

Hardness mg/L 27 - 790 148 66 66 170 2.0 1.2

pH - 6.8 – 8.1 7.7 7.7 7.7 0.2 -1.3 0.0

Solids, dissolved mg/L <MDL – 68 500 5 345 192 254 12 233 3.5 2.3

Solids, suspended mg/L 12 – 313 86 62 62 71 1.6 0.8

Solids, total mg/L 53 – 68 600 4 357 254 254 11 120 3.9 2.6

Sodium mg/L 0.3 – 27 900 1 943 24 10 5 007 3.6 2.6

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL– 3.9 0.42 0.24 0.288 0.55 4.4 1.3

Nitrite + nitrate nitrogen mg/L <MDL – 3.12 0.76 0.55 0.493 0.67 1.8 0.9

Nitrite nitrogen mg/L <MDL – 0.275 0.069 0.051 0.046 0.064 1.8 0.9

Nitrate nitrogen mg/L <MDL – 3.1 0.68 - 0.46 0.63 1.9 0.9

Total kjeldahl nitrogen mg/L 0.43 – 5.75 1.67 1.2 1.24 1.2 1.7 0.7

Organic nitrogen mg/L <MDL – 4.85 1.3 - 1.0 1.1 1.5 0.8

Total nitrogen mg/L 0.75 – 8.6 2.4 1.9 2.0 1.6 1.6 0.6

Phosphate phosphorus mg/L <MDL – 2.26 0.11 0.032 0.0345 0.35 5.1 3.0

Total phosphorus mg/L 0.04 – 2.98 0.29 0.17 0.178 0.45 4.8 1.6

Metals

Aluminum μg/L 107 – 2240 520 401 389 401 1.8 0.8

Antimony μg/L <MDL – 1.5 0.8 0.78 0.75 0.2 1.2 0.3

Barium μg/L 7.1 – 520 63 29 24 103 2.7 1.6

Calcium mg/L 10 – 289 53 33 23 62 2.0 1.2

Copper μg/L <MDL – 160 23 17 17 28 3.9 1.2

Iron μg/L 140 – 3 850 904 675 678 739 1.9 0.8

Lead μg/L <MDL – 11 4.6 3.6 4.2 2.9 0.4 0.6

Magnesium μg/L 0.5 – 16 3.4 2.2 2.0 3.9 2.1 1.1

Manganese mg/L 19 - 485 148 103 93 130 1.3 0.9

Nickel μg/L <MDL – 16 5.1 4.1 3.3 4.0 1.7 0.8

Potassium mg/L 0.4 - 60 4.9 2.0 1.4 9.1 4.5 1.9

Strontium μg/L 42 – 2 840 429 215 155 596 2.3 1.4

Titanium μg/L <MDL - 25 9.04 7.1 6.75 6.2 1.1 0.7

Vanadium μg/L 1.4 – 67 6.04 4.2 3.95 9.7 5.4 1.6

Zinc μg/L 14 - 789 98.11 64 58.6 117 3.7 1.2

Microbiology

Fecal streptococcus c/100mL <MDL -7 000 877.58 100 205 1 523 2.8 1.7

Pseudomonas aeruginosa c/100mL <MDL – 8 500 581.60 100 22 1 701 3.8 2.9

131

Table B-2: AP descriptive statistics

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 49 – 164 96 92 93 24 0.7 0.3

Chloride mg/L 2 – 1 700 195 23 10 419 2.5 2.1

Conductivity uS/cm 203 – 5 460 928 579 410 1244 2.5 1.3

Hardness mg/L 43 – 560 132 104 91 124 2.4 0.9

pH - 7.8 – 9.7 8.3 8.3 8.3 0.3 2.1 0.0

Solids, dissolved mg/L 132 – 3 450 561 363 266 739 2.6 1.3

Solids, suspended mg/L <MDL – 34 12 8.4 9 8.9 0.9 0.8

Solids, total mg/L 166 – 3 460 573 377 276 740 2.6 1.3

Sodium mg/L 10 – 972 122 41 27 238 2.5 2.0

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.2 0.04 0.033 0.027 0.042 2.5 1.0

Nitrite + nitrate nitrogen mg/L 0.36 – 2.1 0.90 0.78 0.81 0.46 1.0 0.5

Nitrite nitrogen mg/L <MDL – 0.068 0.015 0.10 0.011 0.014 2.1 1.0

Nitrate nitrogen mg/L 0.34 – 2.1 0.9 0.77 0.8 0.5 1.0 0.5

Total kjeldahl nitrogen mg/L <MDL – 0.65 0.21 0.18 0.18 0.12 1.8 0.6

Organic nitrogen mg/L <MDL – 0.45 0.16 - 0.16 0.09 0.8 0.5

Total nitrogen mg/L 0.46 – 2.38 1.1 0.98 1.0 0.5 0.8 0.5

Phosphate phosphorus mg/L <MDL – 0.091 0.02 0.017 0.017 0.019 1.8 0.8

Total phosphorus mg/L <MDL – 0.12 0.04 0.29 0.027 0.025 1.7 0.7

Metals

Aluminum μg/L 44 – 1 100 284 247 201 247 1.9 0.9

Antimony μg/L <MDL – 1.3 0.80 0.2 0.80 0.2 0.3 0.3

Arsenic μg/L <MDL – 6.6 2.04 1.5 1.6 1.5 1.7 0.7

Barium μg/L 25 – 555 86 110 51 110 3.2 1.3

Boron μg/L 11 – 103 39 27 28 27 1.1 0.7

Calcium mg/L 13 – 148 36 33 25 33 2.4 0.9

Copper μg/L <MDL – 17.7 5.9 3.8 5.4 3.8 1.0 0.6

Iron μg/L 40 – 950 250 221 150 221 1.8 0.9

Lead μg/L 0.9 – 18 5.5 4.3 3.8 4.3 1.2 0.8

Magnesium μg/L 2.9 – 46 11 10 7.3 10 2.4 1.0

Manganese mg/L 2.7 – 57 18 13 14 13 1.5 0.8

Molybdenum μg/L <MDL – 19 5.27 3.9 4.88 3.9 1.4 0.7

Nickel μg/L <MDL – 6.8 1.9 1.7 1.3 1.7 1.6 0.9

Potassium mg/L 9.5 - 66 31 13 27 13 1.2 0.4

Strontium μg/L 1 400 – 33 400 5 807 6 885 3 750 6 885 3.0 1.2

Uranium μg/L 0.25 – 2.3 1.21 0.6 1 0.6 0.6 0.5

Vanadium μg/L 0.25 – 12.6 3.02 2.6 2.4 2.6 1.7 0.9

Zinc μg/L 5.2 – 50 21.88 12.5 19.1 12.5 0.8 0.6

Microbiology

Fecal streptococcus c/100mL 24 – 110 000 5 557 594 540 20 018 5.2 3.6

Pseudomonas aeruginosa c/100mL 2 – 51 000 4 137 248 410 9 920 4.0 2.4

132

Table B-3: EO descriptive statistics

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 58 - 151 105 102 102 24 0.2 0.2

Chloride mg/L 0.5 – 1 460 235 28 14 393 1.8 1.7

Conductivity uS/cm 247 – 4 500 1 057 680 454 1 141 1.7 1.1

Hardness mg/L 53 – 720 172 135 110 153 2.3 0.9

pH - 7.8 – 9.4 8.3 8.3 8.3 0.3 1.7 0.0

Solids, dissolved mg/L 161 – 3 190 649 428 295 743 2.0 1.1

Solids, suspended mg/L <MDL – 45 9.4 6.7 5.8 9 2.2 0.9

Solids, total mg/L 161 – 3 190 659 448 302 745 2.0 1.1

Sodium mg/L 8 – 668 128 47 36 196 1.8 1.5

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.157 0.04 0.026 0.025 0.031 2.1 0.9

Nitrite + nitrate nitrogen mg/L 0.31 – 2.01 0.79 0.68 0.66 0.46 1.3 0.6

Nitrite nitrogen mg/L <MDL – 0.065 0.012 0.008 0.008 0.012 2.4 1.0

Nitrate nitrogen mg/L 0.30 – 2.0 0.78 0.67 0.65 0.46 1.3 0.6

Total kjeldahl nitrogen mg/L <MDL – 0.7 0.19 0.16 0.16 0.13 1.9 0.7

Organic nitrogen mg/L 0.008 – 0.70 0.16 0.12 0.13 0.12 2.4 0.7

Total nitrogen mg/L 0.38 – 2.4 1.0 0.87 0.9 0.5 1.0 0.5

Phosphate phosphorus mg/L <MDL – 0.12 0.02 0.013 0.015 0.021 3.1 1.1

Total phosphorus mg/L <MDL – 0.185 0.04 0.028 0.026 0.035 2.4 0.9

Metals

Aluminum μg/L 44 – 1 460 243 163 159 275. 2.8 1.1

Antimony μg/L <MDL – 1.3 0.8 0.8 0.8 0.2 0.4 0.3

Arsenic μg/L <MDL – 3.5 1.5 1.3 1.3 0.7 1.0 0.5

Barium μg/L 37 - 483 96 70 55 109 2.8 1.1

Boron μg/L 14 - 128 47 39 35 30 1.2 0.6

Calcium mg/L 15 - 203 48 38 32 42 2.3 0.9

Copper μg/L 1.9 – 15 5.7 5.1 5.5 2.8 1.3 0.5

Iron μg/L 30 – 1 200 207 141 129 223 2.7 1.1

Lead μg/L 0.6 – 15 3.4 2.2 2 3.5 2.0 1.0

Magnesium μg/L 3.6 – 52 13 9.8 8.3 12 2.3 0.9

Manganese mg/L 2.63 – 84 15 11 10 15 3.2 1.0

Molybdenum μg/L <MDL – 19 5.6 4.4 5.3 3.7 1.2 0.7

Potassium mg/L 11 – 53 23 21 20 10 1.4 0.4

Strontium μg/L 1 850 – 40 400 7 609 5 460 4 370 8 775 2.7 1.2

Uranium μg/L 0.5 – 2 1.1 1.0 1 0.4 0.6 0.4

Vanadium μg/L <MDL – 9.7 2.7 1.9 2.2 2.1 1.4 0.8

Zinc μg/L <MDL – 56 15 12 12.7 9.5 2.1 0.6

Microbiology

Fecal streptococcus c/100mL <MDL – 42 000 3 069 251 245 8 210 4.1 2.7

Pseudomonas aeruginosa c/100mL <MDL – 150 000 7 601 - 38 27 333 5.2 3.6

133

Table B-4: PC descriptive statistics

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 93 – 421 169 159 155 65 2.2 0.4

Chloride mg/L 1 – 1 150 156 14 15 281 2.2 1.8

Conductivity uS/cm 316 – 4 360 1 116 868 715 918 1.8 0.8

Hardness mg/L 23 – 260 67 55 51 55 2.6 0.8

pH - 8.1 – 11.8 9.2 9.1 9.1 0.8 1.0 0.1

Solids, dissolved mg/L 205 – 2 260 670 546 463 479 1.6 0.7

Solids, suspended mg/L 1.3 - 101 18 9.8 6.9 22 2.1 1.3

Solids, total mg/L 208 – 2360 688 560 469 490 1.6 0.7

Sodium mg/L 16 – 780 115 57 37 177 2.4 1.5

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.165 0.04 0.031 0.028 0.04 1.66 0.9

Nitrite + nitrate nitrogen mg/L 0.196 – 1.71 0.60 0.49 0.45 0.42 1.42 0.7

Nitrite nitrogen mg/L <MDL – 0.185 0.029 0.018 0.015 0.03 3.12 1.2

Nitrate nitrogen mg/L 0.183 -1.7 0.57 0.46 0.39 0.41 1.43 0.7

Total kjeldahl nitrogen mg/L <MDL – 0.9 0.36 0.29 0.26 0.23 0.78 0.7

Organic nitrogen mg/L 0.004 – 0.80 0.31 0.24 0.24 0.21 0.8 0.7

Total nitrogen mg/L 0.35 – 2.32 0.96 0.83 0.81 0.5 1.0 0.6

Phosphate phosphorus mg/L 0.0113 – 0.288 0.08 0.064 0.072 0.06 1.35 0.7

Total phosphorus mg/L 0.043 – 0.655 0.14 0.12 0.12 0.04 1.66 0.9

Metals

Aluminum μg/L 48 – 1 260 546 436 510 321 0.4 0.6

Antimony μg/L <MDL – 1.5 0.82 0.75 0.8 0.3 0.4 0.4

Arsenic μg/L 1.1 – 24.4 5.8 3.7 3.4 6.5 1.9 1.1

Barium μg/L 14.1 - 158 36 30 27 30 3.0 0.8

Boron μg/L 12 - 82 38 33 40 21 0.4 0.5

Calcium mg/L 6.1 - 55 16 14 13 12 2.3 0.7

Copper μg/L <MDL – 57 12 8.2 6.9 11 2.1 0.9

Iron μg/L 30 – 970 383 303 370 237 0.7 0.6

Lead μg/L 0.6 – 12.4 4.9 3.6 4.5 3.4 0.5 0.7

Magnesium μg/L 1.9 – 31 6.6 5.1 4.7 6.6 3.0 1.0

Manganese mg/L 2.7 – 72 24 19 19 17 1.2 0.7

Molybdenum μg/L <MDL – 49 8.7 6.4 6.6 8.3 3.1 1.0

Nickel μg/L <MDL – 8.4 2.7 2.18 2.4 1.8 1.3 0.7

Potassium mg/L 40.5 – 311 123 107 110 66 0.8 0.5

Strontium μg/L 550 – 18 600 2 608 1 613 1 430 3 706 3.2 1.4

Uranium μg/L <MDL – 1.6 0.79 0.70 0.6 0.4 0.7 0.5

Vanadium μg/L <MDL – 22.6 6.8 4.2 5 5.6 0.8 0.8

Zinc μg/L 2.17 – 27.5 12 10 12 7.0 0.5 0.6

Microbiology

Fecal streptococcus c/100mL <MDL – 2 300 337 111 200 518 2.8 1.5

134

Table B-5: APL descriptive statistics

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 60 – 366 130 119 116 60 2.5 0.46

Chloride mg/L 2.1 – 1 690 232 35 15 422 2.3 1.8

Conductivity uS/cm 276 – 5 440 1 150 739 516 1 270 2.1 1.1

Hardness mg/L 48 – 690 173 136 114 163 2.1 0.9

pH - 7.7 – 9.6 8.1 8.1 8.1 0.33 2.3 0.04

Solids, dissolved mg/L 179 – 3 660 718 467 335 819 2.4 1.1

Solids, suspended mg/L 1.25 – 148 26 18 19 27 2.4 1.1

Solids, total mg/L 199 – 3 690 744 498 414 822 2.4 1.1

Sodium mg/L 13 – 930 140 55 44 232 2.5 1.7

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.108 0.032 0.024 0.023 0.027 1.6 0.8

Nitrite + nitrate nitrogen mg/L <MDL – 2.24 0.83 0.67 0.64 0.54 1.1 0.7

Nitrite nitrogen mg/L <MDL – 0.128 0.014 0.008 0.009 0.02 4.4 1.5

Nitrate nitrogen mg/L <MDL – 2.1 0.78 - 0.6 0.5 1.1 0.6

Total kjeldahl nitrogen mg/L <MDL - 0.74 0.27 0.22 0.23 0.16 1.4 0.6

Organic nitrogen mg/L 0.004 – 0.726 0.23 0.18 0.208 0.15 1.6 0.7

Total nitrogen mg/L 0.47 – 2.5 1.1 0.99 1.0 0.5 0.9 0.5

Phosphate phosphorus mg/L <MDL – 0.12 0.024 0.013 0.013 0.029 2.3 1.2

Total phosphorus mg/L 0.019 – 0.208 0.06 0.047 0.044 0.047 2.1 0.8

Metals

Aluminum μg/L 73 – 1 980 360 262 245 349 3.0 1.0

Antimony μg/L <MDL – 2.5 0.83 0.72 0.7 0.48 1.8 0.6

Arsenic μg/L <MDL – 3.6 1.2 - 1.1 0.74 1.4 0.6

Barium μg/L 23 – 514 84 58 46 107 2.9 1.3

Boron μg/L <MDL – 109 42 34 35 27 1.0 0.6

Calcium mg/L 12.8 – 190 50 39 32 45 2.1 0.9

Copper μg/L <MDL – 16 7 5.8 7 3.8 0.5 0.5

Iron μg/L 73 – 2 030 359 263 240 348 3.2 1.0

Lead μg/L <MDL – 13 3.3 2.6 2.4 2.4 2.5 1.0

Magnesium μg/L 3.8 – 53 12 9.0 7.5 12 2.3 1.0

Manganese mg/L 3.4 – 132 28 20 19 25 2.4 0.9

Molybdenum μg/L <MDL – 9.4 4.3 3.4 4.2 2.5 0.1 0.6

Nickel μg/L <MDL – 17 4.7 3.8 3.1 4.0 2.3 0.9

Potassium mg/L 10.4 – 187 31 24 23 30 4.8 1.0

Strontium μg/L 842 – 36 800 5 971 3 902 3 220 7 912 2.8 1.3

Uranium μg/L 0.6 – 10.3 2.2 1.6 1.3 2.4 2.4 1.1

Vanadium μg/L 0.6 – 9.2 2.5 1.9 1.9 2.0 1.5 0.8

Zinc μg/L 4.5 - 79 23 19 16 17 1.7 0.7

Microbiology

Fecal streptococcus c/100mL <MDL – 12 000 868 76 120 2 559 4.3 2.9

135

APPENDIX C: GRAPHICAL SUMMARIES (AP, EO, PC AND ASH)1

Units of concentration for each pollutant or parameter are the same as shown in tables presented in

Appendix 9.1.2.

Figure C--1: General quality graphical summaries (a)

1 Legend for probability plots

0.1

1

10

100

1000

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100000

AP EO PC ASH

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AP EO PC ASH6

8

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AP EO PC ASH

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0.1 10 1000 100000

Chloride

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80%

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10 1000 100000

Conductivity

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20%

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6 8 10 12

pH

136

Figure C-2: General quality graphical summaries (b)

10

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AP EO PC ASH

1

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AP EO PC ASH

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1 10 100 1000

Solids, suspended

0%

20%

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100%

0.1 10 1000 100000

Sodium

137

Figure C-3: Nutrients graphical summaries

0.001

0.01

0.1

1

10

AP EO PC ASH

0.01

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AP EO PC ASH

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0.001 0.1 10

Ammonia + Ammunium

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0.1 1 10

Nitrite & Nitrate

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0.001 0.01 0.1 1

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0.01

0.1

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AP EO PC ASH

0.001

0.01

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AP EO PC ASH

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0.01

0.1

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AP EO PC ASH

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0.1 1 10

TKN

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0.001 0.1 10

Phosphate

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0.01 0.1 1 10

Total Phosphorus

138

Figure C-4: Metals graphical summaries (a)

1

10

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AP EO PC ASH

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0.4

0.8

1.2

1.6

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Barium

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Copper

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Iron

139

Figure C-5: Metals graphical summaries (b)

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AP EO PC ASH

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Lead

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Zinc

140

APPENDIX D: GRAPHICAL SUMMARIES (AP AND APL)2

Units of concentration for each pollutant or parameter are the same as shown in tables presented in

Appendix 9.1.2.

Figure D-1: General quality graphical summaries (a)

2Legend for probability plots

1

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APL AP

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7.5 8.5 9.5

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141

Figure D-2: General quality graphical summaries (b)

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Sodium

142

Figure D-3: Nutrient graphical summaries

0.001

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0.001 0.01 0.1 1

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0.01 0.1 1

Total Phosphorus

143

Figure D-4: Metal graphical summaries (a)

10

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APL AP

0.1

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Copper

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Iron

144

Figure D-5: Metal graphical summaries (b)

0.1

1

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APL AP

1

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APL AP

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Magnesium

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1 10 100

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1000 10000 100000

Strontium

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100%

1 10 100

Zinc

145

APPENDIX E: TIME SERIES

Figure E-1: General quality time series (a)

10

100

1000

22/01/10 10/08/10 26/02/11 14/09/11 01/04/12 18/10/12

Alk

alin

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(mg/

L)

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)

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(m

g/L)

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pH

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Dis

solv

ed

So

lids

(mg/

L)

146

Figure E-2: General quality time series (b)

1

10

100

1000

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Susp

en

de

d S

olid

s (m

g/L)

0.1

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1000

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Sod

ium

(m

g/L)

0.1

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10

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ctab

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0.001

0.01

0.1

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10

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NH

3 +

NH

4 (

mg/

L)

0

0.5

1

1.5

2

2.5

3

3.5

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NO

2 +

NO

3 (

mg/

L)

147

Figure E-3: Nutrients time series

0.001

0.01

0.1

1

22/01/10 10/08/10 26/02/11 14/09/11 01/04/12 18/10/12

NO

3 (

mg/

L)

0.01

0.1

1

10

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TKN

(m

g/L)

0.001

0.01

0.1

1

10

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Ph

osp

hat

e (

mg/

L)

0.001

0.01

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10

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Tota

l Ph

osp

ho

rus

(mg/

L)

148

Figure E-3: Metals time series (a)

10

100

1000

10000

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Alu

min

um

(μ

g/L)

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0.2

0.4

0.6

0.8

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tim

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y(u

g/L)

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Ars

en

ic (μ

g/L)

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10

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ium

(μ

g/L)

0

20

40

60

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100

120

140

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Bo

ron

(μ

g/L)

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Cal

ciu

m (

mg/

L)

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pp

er

(μg/

L)

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1000

10000

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Iro

n (μ

g/L)

149

Figure E-4: Metals time series (b)

0.1

1

10

100

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Lead

(μ

g/L)

0.1

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ne

siu

m (m

g/L)

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(μ

g/L)

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lyb

de

nu

m (μ

g/L)

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kel (μ

g/L)

0.1

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tass

ium

(m

g/L)

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10000

100000

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Stro

nti

um

(μ

g/L)

0.1

1

10

100

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Tita

niu

m (μ

g/L)

150

Figure E-5: Metals time series (c)

Figure E-6: Microbiology time series

0.1

1

10

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Ura

niu

m (μ

g/L)

0.1

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10

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Van

adiu

m (μ

g/L)

0.1

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10

100

1000

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Zin

c (μ

g/L)

1

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E-co

li (c

c/1

00

mL)

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1000000

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l str

ep

toco

ccu

s (c

c/1

00

mL)

1

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Pse

ud

om

on

as a

eru

gin

osa

(c

c/1

00

mL)

151

APPENDIX F: SUMMARY TABLES

Table F-1: Parameters with over 50% non-detects

Pollutant Pavement

Solvent Extractable AP, EO, PC, APL

Arsenic ASH

Beryllium ASH, AP, EO, PC, APL

Boron ASH

Cadmium ASH, AP, EO, PC, APL

Chromium ASH, AP, EO, PC, APL

Cobalt ASH, AP, EO, PC, APL

Molybdenum ASH

Nickel ASH, AP, EO, APL

Selenium ASH, AP, EO, PC, APL

Silver ASH, AP, EO, PC, APL

Thallium ASH, AP, EO, PC, APL

Titanium AP, EO, PC, APL

Uranium ASH

E-coli ASH, AP, EO, PC, APL

Pseudomonas aeruginosa PC

Table F-2: Percentage of samples exceeding guidelines

Pollutant % > Guideline

ASH AP EO PC

Chloride 35 28 33 33

pH 0 14 18 78

Dissolved Solids 33 23 33 47

Sodium 29 13 23 16

Total Phosphorus 100 35 49 100

Aluminum 98 93 78 98

Arsenic 1 7 0 3

Beryllium 0 0 0 2

Cadmium 14 19 16 9

Chromium 0 0 0 11

Cobalt 28 14 10 48

Copper 80 51 56 78

Iron 80 28 18 58

Lead 43 37 19 47

Manganese 73 5 4 11

Molybdenum 2 0 0 2

Thallium* 5 7 7 7

Vanadium 18 10 7 49

Zinc 89 47 20 20

E-coli 3 5 0 2

Pseudomonas aeruginosa 25 24 17 7

Benzo(a)pyrene* 4 0 0 3

Benzo(g,h,i)perylene* 9 0 0 3

Dibenzo(a.h)anthracene* 2 0 0 3

Fluoranthene* 64 2 0 7

Naphthalene* 35 0 0 3

Perylene* 0 0 0 3

Phenanthrene 39 3 0 5

Pyrene 28 3 5 8

*Guideline is less than MDL, % above MDL reported

152

Table F-3: p –values from hypothesis tests

Pollutant ASH-AP ASH-EO ASH-PC AP-EO AP-PC EO-PC

p p p p p p

Alkalinity 1.54E-11 (<) 4.72E-13 (<) <2.2E-16 (<) 4.67E-06 (<) 1.01E-15 (<) 2.72E-11 (<)

Conductivity 2.15E-04* (<) 4.48E-06* (<) 8.18E-07* (<) 1.69E-03* (<) 1.27E-05* (<) 9.57E-04* (<)

Hardness 2.88E-02* (=) 5.97E-04* (<) 7.36E-01* (=) 6.46E-06* (<) 1.05E-09* (>) 7.27E-12* (>)

pH 4.55E-13* (<) 1.14E-13* (<) 1.14E-13* (<) 5.00E-01* NO 4.55E-13* (<) 1.14E-13* (<)

Solids; dissolved 1.66E-03* (<) 1.05E-03* (<) 2.68E-04* (<) 1.47E-04* (<) 1.27E-05* (<) 9.57E-04* (<)

Solids; suspended 2.68E-15 (>) <2.2E-16 (>) 3.25E-16 (>) 3.45E-02 (>) 1.88E-01 (=) 8.49E-03 (<)

Solids; total 5.75E-03* (<) 3.03E-04* (<) 4.48E-06* (<) 6.61E-05* (<) 1.27E-05* (<) 9.57E-0*4 (<)

Aluminum 4.28E-04 (>) 7.66E-06 (>) 3.47E-05 (=) 3.60E-01 (>) 2.44E-06 (<) 1.51E-09 (<)

Antimony 7.19E-01 (=) 6.21E-01 (=) 7.89E-01 (=) 6.35E-01 NO 6.35E-01 (=) 8.04E-02 (=)

Arsenic - - - - - - 1.01E-04 (>) 1.55E-04* (<) 1.52E-06* (<)

Barium 3.92E-10* (<) 1.08E-10* (<) 1.58E-02* (<) 3.49E-01* NO 4.55E-13* (>) 1.14E-13* (>)

Boron - - - -

- 3.78E-09 (<) 5.24E-01* (=) 4.68E-03* (>)

Calcium 2.43E-01* (=) 1.88E-01* (=) 1.97E-03* (>) 6.46E-06* (<) 1.46E-11* (>) 7.28E-12* (>)

Chloride 8.30E-03* (<) 3.96E-03* (<) 1.58E-02* (<) 7.55E-01* NO 5.33E-01* (=) 8.78E-01* (=)

Copper 2.72E-12 (>) 4.04E-12 (>) 2.52E-06* (>) 7.64E-01 NO 7.45E-05* (<) 1.08E-04* (<)

Iron 2.98E-09 (>) 3.74E-11 (>) 3.03E-04 (>) 9.39E-06 (>) 9.11E-05 (<) 2.44E-06 (<)

Lead 3.43E-01 (=) 4.81E-02 (>) 9.41E-01 (=) 1.23E-08 (>) 3.20E-01 (=) 9.25E-04 (<)

Magnesium 9.71E-09* (<) 2.77E-10* (<) 9.71E-07* (<) 1.56E-04* (<) 6.46E-06* (>) 5.12E-09* (>)

Manganese 2.02E-14 (>) 3.10E-15 (>) 1.40E-13 (>) 8.71E-04 (>) 4.15E-03 (<) 4.93E-05 (<)

Molybdenum - - - - - - 6.63E-03 (<) 1.09E-04 (>) 9.77E-04 (.)

Potassium 5.38E-10* (<) 5.38E-10* (<) 2.91E-11* (<) 7.98E-15 (>) <2.2e-16 (<) <2.2e-16 (<)

Sodium 1.56E-04* (<) 3.76E-04* (<) 3.48E-05* (<) 2.43E-01* NO 1.56E-04* (<) 2.35E-02* (<)

Strontium 4.57E-13* (<) 1.14E-13* (<) 1.14E-13* (<) 3.92E-07* (<) 1.91E-11* (>) 1.14E-13* (>)

Uranium - - - - - - 2.39E-03 (>) 7.75E-07* (>) 2.82E-06* (>)

Vanadium 3.35E-04 (>) 2.66E-05 (>) 6.36E-01* (=) 6.58E-03 (>) 3.02E-07* (<) 2.82E-09* (<)

Zinc 3.05E-08 (>) 5.18E-15* (>) 1.08E-10 (>) 5.13E-08* (>) 2.78E-09 (>) 2.80E-01* (=)

Ammonia + Ammonium 3.32E-12 (>) 4.02E-12 (>) 8.96E-11 (>) 9.94E-03 (>) 4.89E-01 (=) 9.33E-03 (>)

Nitrate + Nitrite 7.85E-05 (<) 6.86E-03* (<) 1.00E+00* (=) 2.44E-06* (>) 3.92E-10* (>) 1.14E-13* (>)

Nitrite 1.64E-10 (>) 5.72E-11 (>) 8.20E-06 (>) 1.37E-02 (>) 4.97E-05 (<) 5.84E-08 (<)

TKN <2.2E-16 (>) <2.2E-16 (>) 2.33E-13 (>) 5.76E-02 NO 1.08E-06 (<) 6.16E-09 (<)

Phosphate 6.36E-03 (>) 3.32E-04 (>) 9.23E-05 (<) 2.88E-02 (>) 6.22E-09 (>) 5.45E-12 (<)

Total Phosphorus 4.30E-14 (>) 1.00E-13 (>) 1.06E-03 (>) 2.97E-01 NO 4.20E-14 (<) 5.30E-13 (<)

Fecal streptococcus 1.03E-01 (=) 5.71E-01 (=) 8.44E-03 (>) 1.17E-02 (>) 1.20E-05 (>) 2.70E-03 (>)

Pseudomonas aeruginosa 2.16E-02* (<) 8.39E-01* (=) - - 1.69E-01* NO - - - -

*sign test performed

(<) = EMC mean/median pavement 1 < EMC mean/median pavement 2

(>) = EMC mean/median pavement 1 > EMC mean/median pavement 2

(=) = mean/median pavement 1 = mean/median pavement 2

Table F-4: Average efficiency ratio

153

Pollutant Average ER Median RE

AP EO PC AP EO PC

Alkalinity -0.91 -1.09 -2.36 -1.46 -1.40 -3.26

Chloride 0.93 0.92 0.95 -1.54 -2.11 -1.40

Conductivity 0.86 0.84 0.83 -2.21 -2.69 -4.07

Hardness - -0.17 - - -1.21 -

pH -0.08 -0.07 -0.19 -0.07 -0.07 -0.19

Dissolved solids 0.90 0.88 0.87 -1.32 -1.85 -3.18

Suspended solids 0.87 0.89 0.79 0.86 0.87 0.82

Solids; total 0.87 0.85 0.84 -1.14 -1.30 -2.08

Sodium 0.94 0.93 0.94 -9.45 -10.32 -15.50

Aluminum 0.45 0.53 - 0.38 0.58 -0.10

Barium -0.37 -0.53 0.42 -2.06 -2.25 -0.44

Calcium - - 0.70 - - 0.37

Copper 0.74 0.75 0.49 0.68 0.66 0.50

Iron 0.72 0.77 0.58 0.71 0.81 0.39

Lead - 0.27 - - 0.57 -

Magnesium -2.06 -2.71 -0.92 -4.15 -4.35 -1.55

Manganese 0.88 0.90 0.84 0.87 0.88 0.76

Potassium -5.38 -3.72 -24.44 -21.85 -14.69 -84.19

Strontium -12.52 -16.72 -5.07 -26.86 -35.30 -9.64

Vanadium 0.50 0.56 -0.12 0.40 0.41 0.13

Zinc 0.78 0.85 0.87 0.71 0.79 0.85

Ammonia + Ammonium 0.90 0.92 0.90 0.86 0.87 0.81

Nitrate + Nitrite -0.19 -0.05 - -1.04 -0.37 -

Nitrite 0.79 0.83 0.59 0.77 0.82 0.59

Nitrate -0.28 -0.14 0.17 -1.12 -0.48 -0.05

TKN 0.88 0.88 0.79 0.84 0.87 0.77

Organic-Nitrogen 0.87 0.88 0.76 0.47 0.59 0.58

Total Nitrogen 0.55 0.59 0.61 0.85 0.88 0.74

Phosphate 0.80 0.83 0.26 0.37 0.44 -0.99

Total Phosphorus 0.88 0.87 0.51 0.82 0.84 0.25

Table F-5: Total pollutant mass (M) and summation of pollutant loads (SOL)

154

Pollutant Unit M SOL

ASH AP EO PC AP EO PC

Alkalinity, total fixed kg/ha 285 306 329 588 -0.07 -0.16 -1.06

Chloride kg/ha 6 015 683 674 554 0.89 0.89 0.91

Hardness kg/ha 540 425 499 198 0.21 0.08 0.63

Sodium kg/ha 3 599 412 381 408 0.89 0.89 0.89

Dissolved solids kg/ha 9 306 1 862 1 916 2 227 0.80 0.79 0.76

Suspended solids kg/ha 356 44 31 59 0.88 0.91 0.83

Total Solids kg/ha 9 769 1 905 1 946 2 286 0.80 0.80 0.77

Solvent extractable kg/ha 19 0.044 0.141 0.093 1.00 0.99 1.00

Aluminum g/ha 2 214 927 863 1 928 0.58 0.61 0.13

Barium g/ha 198 301 319 117 -0.52 -0.61 0.41

Boron g/ha 22 93 117 82 -3.28 -4.39 -2.79

Calcium g/ha 193 571 113 446 136 847 47 669 0.41 0.29 0.75

Copper g/ha 89 23 22 44 0.74 0.75 0.51

Iron g/ha 3 979 788 688 1 311 0.80 0.83 0.67

Magnesium g/ha 13 513 34 177 38 315 19 297 -1.53 -1.84 -0.43

Manganese g/ha 728 67 52 85 0.91 0.93 0.88

Potassium kg/ha 19 102 79 418 -4.38 -3.19 -21.10

Strontium g/ha 1 324 20 262 26 102 8 516 -14.31 -18.72 -5.43

Zinc g/ha 519 67 46 41 0.87 0.91 0.92

Ammonia + Ammonium g/ha 1 983 123 100 141 0.94 0.95 0.93

Nitrate + Nitrite g/ha 3 609 3 013 2 624 1 847 0.17 0.27 0.49

Nitrite g/ha 314 51 43 84 0.84 0.86 0.73

Nitrate g/ha 3 265 2 962 2 581 1 760 0.09 0.21 0.46

Organic-nitrogen g/ha 7 735 627 560 1 118 0.92 0.93 0.86

Total Nitrogen g/ha 13 298 3 763 3 284 3 097 0.72 0.75 0.77

TKN g/ha 9 718 750 660 1 258 0.92 0.93 0.87

Phosphate g/ha 1 484 76 73 339 0.95 0.95 0.77

Total Phosphorus g/ha 2 627 118 143 498 0.96 0.95 0.81

APPENDIX G: SPRING-SUMMER-FALL STORMWATER QUALITY RESULTS

Table G-1: ASH spring-summer-fall descriptive statistics

155

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 22 – 138 47 40 35 30 1.7 0.6

Chloride mg/L <MDL – 14.7 3.4 2.0 1.9 3.5 1.7 1.0

Conductivity uS/cm 57 – 336 128 107 92 86 1.4 0.7

Solvent extractable mg/L <MDL – 36 4.1 1.9 1.6 8.0 3.4 2.0

Hardness mg/L 27 - 181 71 60 50 49 1.4 0.7

pH - 6.8 – 7.9 7.6 7.6 7.7 0.25 -1.8 0.03

Solids, dissolved mg/L <MDL – 228 76 57 55 62 1.2 0.8

Solids, suspended mg/L 13 – 236 54 44 44 42 3.1 0.8

Solids, total mg/L 53 – 274 143 127 124 69 0.6 0.5

Sodium mg/L 0.3 – 10 2.1 1.2 1.1 2.7 2.1 1.3

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 1.2 0.30 0.17 0.23 0.31 1.9 1.0

Nitrite + nitrate nitrogen mg/L <MDL – 3.1 0.51 0.35 0.36 0.59 3.4 1.2

Nitrite nitrogen mg/L <MDL – 0.28 0.064 0.044 0.034 0.069 1.9 1.1

Nitrate nitrogen mg/L <MDL – 3.1 0.4 - 0.3 0.6 3.7 1.3

Total kjeldahl nitrogen mg/L 0.5 – 5.1 1.6 1.1 1.1 1.3 1.7 0.8

Organic nitrogen mg/L <MDL – 4.9 1.3 - 0.8 1.2 1.7 0.9

Total nitrogen mg/L 0.76 – 5.3 2.1 1.5 1.4 1.3 1.2 0.6

Phosphate phosphorus mg/L <MDL – 2.3 0.21 0.034 0.04 0.50 3.3 2.4

Total phosphorus mg/L 0.068 – 3.0 0.39 0.17 0.17 0.39 4.6 1.5

Metals

Aluminum μg/L 107 – 2 240 404 295 277 426 3.2 1.1

Antimony μg/L <MDL – 1.4 0.86 0.83 0.8 0.25 1.2 0.3

Arsenic μg/L - - - - - - -

Barium μg/L 7.1 – 42 18 16 14 11 1.1 0.6

Boron μg/L 10 - 29 20 18 23 8.0 -0.3 0.4

Calcium mg/L 10 - 66 25 21 18 18 1.5 0.7

Copper μg/L 4.8 - 50 16 14 14 9.3 1.9 0.6

Iron μg/L 140 – 2 360 653 483 481 535 1.5 0.8

Lead μg/L <MDL – 9.8 3.2 2.4 2.1 2.9 1.6 0.9

Magnesium μg/L 0.55 – 4.6 1.9 1.6 1.7 1.1 0.9 0.6

Manganese mg/L 19 - 439 103 72 54 101 2.0 1.0

Nickel μg/L 2 - 11 4.4 3.8 3.2 2.8 1.4 0.6

Potassium mg/L 0.4 – 8.3 1.8 1.2 1.1 1.9 2.4 1.1

Strontium μg/L 42 - 506 147 108 83 138 1.7 0.9

Uranium μg/L - - - - - - -

Titanium μg/L 0.8 - 15 5.6 4.5 4.9 3.6 1.5 0.6

Vanadium μg/L 1.8 - 11 4.9 4.4 4.5 2.5 0.8 0.5

Zinc μg/L 14 -308 85 52 43 91 1.4 1.1

Microbiology

Fecal streptococcus c/100mL 12 – 7 000 1 460 552 673 1 870 2.0 1.3

Table G-2: AP spring-summer-fall descriptive statistics

Pollutant Units Range GM

156

General Chemistry

Alkalinity mg/L 73 – 135 99 98 97 16 0.7 0.2

Chloride mg/L 1.7 – 32 6.7 5.0 5.8 6.4 2.8 1.0

Conductivity uS/cm 253 – 581 385 372 350 106 0.8 0.3

Hardness mg/L 43 – 168 92 87 89 31 0.9 0.3

pH - 8.1 – 8.7 8.3 8.3 8.3 0.15 0.8 0.02

Solids, dissolved mg/L 164 – 378 250 242 227 69 0.8 0.3

Solids, suspended mg/L 1.3 – 31 11 7.4 9.2 8.8 0.9 0.8

Solids, total mg/L 169 – 403 261 252 231 72 0.8 0.3

Sodium mg/L 10 - 102 28 23 22 20 2.3 0.7

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL - 0.098 0.031 0.025 0.025 0.023 1.8 0.8

Nitrite + nitrate nitrogen mg/L 0.36 – 2.1 0.94 0.80 0.94 0.52 0.9 0.6

Nitrite nitrogen mg/L <MDL – 0.034 0.01 0.0068 0.0075 0.007 1.6 0.8

Nitrate nitrogen mg/L 0.36 – 2.1 0.93 0.79 0.93 0.52 0.90 0.6

Total kjeldahl nitrogen mg/L <MDL - 0.35 0.19 0.17 0.19 0.083 0.2 0.4

Organic nitrogen mg/L 0.042 - 0.282 0.16 0.13 0.16 0.08 -0.02 0.5

Total nitrogen mg/L 0.46 - 2.4 1.2 0.97 1.1 0.58 0.8 0.5

Phosphate phosphorus mg/L <MDL – 0.0714 0.019 0.014 0.015 0.017 2.0 0.9

Total phosphorus mg/L <MDL - 0.106 0.031 0.026 0.026 0.020 2.2 0.7

Metals

Aluminum μg/L 65 -821 261 207 198 191 1.5 0.7

Antimony μg/L 0.6 - 1.3 1.0 1.0 1.1 0.2 -0.6 0.2

Arsenic μg/L 0.4 – 3.2 1.7 1.5 1.6 0.82 0.4 0.5

Barium μg/L 37 - 74 53 51 51 11 0.3 0.2

Boron μg/L 19 – 103 53 46 52 27 0.6 0.5

Calcium mg/L 13 – 46 25 24 24 8.5 1.0 0.3

Copper μg/L 1.2 – 15 6.3 5.3 6.3 3.3 0.6 0.5

Iron μg/L 40 – 642 221 177 165 156 1.4 0.7

Lead μg/L 0.9 – 18 5.2 3.9 4 4.6 2.0 0.9

Magnesium μg/L 2.9 – 13 7.3 6.8 7.3 2.5 0.6 0.4

Manganese mg/L 2.7 – 57 16 13 15 11 2.2 0.7

Molybdenum μg/L 1 – 19 6.5 5.5 5.7 4.0 1.6 0.6

Nickel μg/L 0.21 – 4.6 1.3 0.96 0.82 1.0 1.5 0.8

Potassium mg/L 20 – 54 30 29 28 8.1 1.7 0.3

Strontium μg/L 1 400 – 5 310 3 645 3 491 3 675 986 -0.5 0.3

Uranium μg/L 0.8 – 2.1 1.2 1.2 1.1 0.39 1.5 0.3

Vanadium μg/L 0.7 – 9.7 3.2 2.6 2.7 1.9 1.5 0.6

Zinc μg/L 5.2 - 46 19 16 16 11.3 1.0 0.6

Microbiology

Fecal streptococcus c/100mL 200 – 110 000 8 290 1 654 890 24 250 4.3 2.9

Pseudomonas aeruginosa c/100mL 2 – 51 000 6 102 577 1 300 11 745 3.3 1.9

Table G-3: EO spring-summer-fall descriptive statistics

Pollutant Units Range GM

157

General Chemistry

Alkalinity mg/L 80 – 151 108 106 103 20 0.6 0.2

Chloride mg/L <mdl – 54 9.8 5.5 5.2 12 2.6 1.2

Conductivity uS/cm 247 – 668 410 397 393 110 0.9 0.3

Hardness mg/L 53 -175 107 102 110 32 0.1 0.3

pH - 8.1 – 8.6 8.3 8.3 8.3 0.15 0.8 0.02

Solids, dissolved mg/L 161 – 434 266 258 255 71 0.9 0.3

Solids, suspended mg/L 1.3 – 23 7.2 5.3 5.7 5.6 1.4 0.8

Solids, total mg/L 161 – 445 274 265 257 72 0.9 0.3

Sodium mg/L 7.8 - 113 33 25 27 25 1.5 0.8

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.11 0.031 0.022 0.024 0.025 1.6 0.8

Nitrite + nitrate nitrogen mg/L 0.31 – 2.01 0.84 0.70 0.73 0.50 0.9 0.6

Nitrite nitrogen mg/L <MDL - 0.039 0.010 0.0060 0.007 0.010 1.9 1.0

Nitrate nitrogen mg/L 0.3 – 2.0 0.83 0.69 0.72 0.50 1.0 0.6

Total kjeldahl nitrogen mg/L 0.04 – 0.7 0.20 0.16 0.16 0.14 2.2 0.7

Organic nitrogen mg/L <MDL – 0.7 0.17 0.12 0.14 0.13 2.7 0.8

Total nitrogen mg/L 0.38 - 2.4 1.0 0.88 1.0 0.56 0.8 0.5

Phosphate phosphorus mg/L <MDL – 0.078 0.020 0.013 0.016 0.018 2.0 0.9

Total phosphorus mg/L <MDL – 0.116 0.037 0.028 0.026 0.028 1.6 0.8

Metals

Aluminum μg/L 44 – 922 215 161 164 192 2.4 0.9

Antimony μg/L 0.7 – 1.3 1.0 0.95 1.0 0.15 0.4 0.2

Arsenic μg/L 0.5 – 2.2 1.3 1.2 1.3 0.48 0.07 0.4

Barium μg/L 37 – 69 52 51 52 9.7 0.05 0.2

Boron μg/L 26 - 128 65 58 65 32 0.6 0.5

Calcium mg/L 15 – 52 30 29 30 9.4 0.3 0.3

Copper μg/L 1.9 – 15 5.8 5.2 5.6 2.9 1.6 0.5

Iron μg/L 30 – 600 174 138 135 135 2.1 0.8

Lead μg/L 0.8 – 15 3.7 2.6 2.1 3.8 2.1 1.0

Magnesium μg/L 3.6 – 11 7.7 7.4 7.7 2.1 -0.2 0.3

Manganese mg/L 3.8 – 43 12 11 10 8.4 2.4 0.7

Molybdenum μg/L 1.2 – 19 7.2 6.3 7.2 3.6 1.4 0.5

Potassium mg/L 11 – 44 21 20 20 6.8 1.8 0.3

Strontium μg/L 1 850 – 5 830 4 022 3 892 4 175 983 -0.3 0.2

Uranium μg/L 0.7 – 2 1.1 1.1 1.0 0.30 2.3 0.3

Vanadium μg/L 0.6 – 7.3 2.9 2.5 2.5 1.6 0.9 0.6

Zinc μg/L 5.1 - 33 14 12 12 7.6 1.2 0.6

Microbiology

Fecal streptococcus c/100mL 20 – 42 000 4 526 678 590 9 806 3.3 2.2

Pseudomonas aeruginosa c/100mL 1 – 150 000 11 338 384 850 33 108 4.3 2.9

Table G-4: PC spring-summer-fall descriptive statistics

158

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 109 – 202 156 154 154 26 -0.05 0.2

Chloride mg/L 1 – 25 8.1 5.8 5.8 6.5 1.1 0.8

Conductivity uS/cm 316 – 1 510 667 626 656 257 1.5 0.4

Hardness mg/L 23 – 145 49 45 45 24 2.7 0.5

pH - 8.5 – 10 9.1 9.1 9.1 0.5 0.12 0.06

Solids, dissolved mg/L 205 – 1 090 459 421 427 210 1.5 0.5

Solids, suspended mg/L 1.3 – 36 11 7.9 6.5 9.3 1.6 0.9

Solids, total mg/L 208 – 1 120 470 432 432 214 1.5 0.5

Sodium mg/L 16 – 89 41 36 33 21 1.3 0.5

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.135 0.034 0.025 0.026 0.029 2.1 0.8

Nitrite + nitrate nitrogen mg/L 0.20 – 1.7 0.62 0.48 0.43 0.46 1.2 0.8

Nitrite nitrogen mg/L <MDL – 0.19 0.032 0.018 0.014 0.043 2.7 1.3

Nitrate nitrogen mg/L 0.18 – 1.7 0.58 0.45 0.37 0.44 1.3 0.8

Total kjeldahl nitrogen mg/L 0.11 – 0.73 0.34 0.29 0.26 0.19 0.92 0.6

Organic nitrogen mg/L <MDL – 0.73 0.30 0.26 0.25 0.17 1.0 0.6

Total nitrogen mg/L 0.35 – 2.3 0.95 0.80 0.80 0.58 1.1 0.6

Phosphate phosphorus mg/L <MDL – 0.29 0.10 0.087 0.090 0.057 1.5 0.6

Total phosphorus mg/L 0.049 – 0.3 0.13 0.12 0.12 0.062 0.97 0.5

Metals

Aluminum μg/L 189 – 1 060 564 509 525 256 0.6 0.5

Antimony μg/L 0.7 – 1.5 1 1.1 1 0.24 0.2 0.2

Arsenic μg/L 1.7 – 7.2 3.8 3.5 3.8 1.6 0.8 0.4

Barium μg/L 14 – 46 26 25 24 9.1 0.6 0.3

Boron μg/L 20 – 74 42 39 41 16 0.6 0.4

Calcium mg/L 6.1 – 40 13 11 12 6.9 2.7 0.6

Copper μg/L 1.4 – 24 9.4 8.1 6.9 5.6 1.5 0.6

Iron μg/L 120 – 737 381 347 379 164 0.7 0.4

Lead μg/L 1.8 – 11 5.7 5.0 5.1 2.9 0.4 0.5

Magnesium μg/L 1.9 – 11 4.2 3.9 3.9 1.8 2.0 0.4

Manganese mg/L 7.5 – 72 26 22 21 16 1.3 0.6

Molybdenum μg/L 1.7 – 49 11 7.9 7.2 10 2.5 0.9

Nickel μg/L 0.5 – 5.0 2.0 1.7 1.8 1.1 0.8 0.6

Potassium mg/L 45 – 311 133 120 127 61 0.9 0.5

Strontium μg/L 550 – 2 510 1 210 1082 1 115 581 0.7 0.5

Uranium μg/L 0.5 – 1.6 0.85 0.79 0.7 0.36 0.9 0.4

Vanadium μg/L 1 – 22.6 7.3 5.2 6.5 5.7 1.1 0.8

Zinc μg/L 2.2 - 28 13 10 13 7.5 0.4 0.6

Microbiology

Fecal streptococcus c/100mL 23 – 2 300 489 270 280 585 2.3 1.2

APPENDIX H: WINTER STORMWATER QUALITY RESULTS

Table H-1: ASH winter descriptive statistics

159

Pollutant Units Range GM

General Chemistry

Alkalinity mg/L 17 – 95 523 50 51 18 0.4 0.3

Chloride mg/L 11 – 43 100 5 177 603 348 10 780 2.7 2.1

Conductivity uS/cm 141 – 96 200 11 922 2 420 1475 20 824 2.5 1.8

Solvent extractable mg/L 0.3 – 9.1 3.29 2.44 3.0 2.4 0.8 0.7

Hardness mg/L 29 – 790 226 147 110 212 1.0 0.9

pH - 7.4 – 8.1 7.8 7.8 7.8 0.20 -0.3 0.03

Solids, dissolved mg/L 92 – 68 500 7 525 1 462 776 14 042 2.9 1.9

Solids, suspended mg/L 12 – 313 112 88 93 79 1.1 0.7

Solids, total mg/L 153 – 68 600 7 635 1 751 842 14 046 2.9 1.8

Sodium mg/L 10 – 27 900 3 956 669 352 6 618 2.3 1.7

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 3.9 0.50 0.32 0.30 0.68 3.9 1.3

Nitrite + nitrate nitrogen mg/L 0.14 – 2.9 0.95 0.77 0.76 0.66 1.3 0.7

Nitrite nitrogen mg/L 0.02 – 0.27 0.074 0.058 0.055 0.060 2.0 0.8

Nitrate nitrogen mg/L 0.12 – 2.6 0.87 0.71 0.71 0.61 1.3 0.7

Total kjeldahl nitrogen mg/L 0.43 – 5.8 1.75 1.47 1.52 1.12 1.8 0.6

Organic nitrogen mg/L <MDL – 4.5 1.3 - 1.3 1.0 1.3 0.7

Total nitrogen mg/L 0.75 – 8.6 2.7 2.3 2.4 1.7 1.7 0.6

Phosphate phosphorus mg/L 0.0065 – 0.14 0.038 0.030 0.034 0.026 2.0 0.7

Total phosphorus mg/L 0.04 – 0.63 0.20 0.17 0.19 0.11 1.5 0.6

Metals

Aluminum μg/L 144 – 1 410 609 522 485 354 0.8 0.6

Antimony μg/L 0.5 – 1.5 0.78 0.75 0.70 0.23 1.4 0.3

Barium μg/L 7.1 - 520 97 49 29 128 1.8 1.3

Boron μg/L 10 – 60 24 18 12 21 1.3 0.9

Calcium mg/L 11 – 289 82 53 39 77 1.1 0.9

Copper μg/L 6.4 – 160 30 20 17 38 2.8 1.3

Iron μg/L 260 – 3 850 1 089 891 846 823 1.8 0.8

Lead μg/L 0.9 – 10.6 5.4 4.8 5.5 2.6 0.14 0.5

Magnesium μg/L 0.57 – 17 5.0 3.1 2.4 5.0 1.1 1.0

Manganese mg/L 20 – 485 182 137 136 140 0.99 0.8

Nickel μg/L 2 – 16.2 5.6 4.5 3.3 4.8 1.5 0.9

Potassium mg/L 0.63 – 60 8.2 3.7 2.8 12 3.3 1.5

Strontium μg/L 78 – 2 840 649 383 274 714 1.5 1.1

Vanadium μg/L 1.4 – 67 7.2 4.0 3.9 14 3.9 1.9

Zinc μg/L 18 - 789 108 77 69 134 4.2 1.2

Microbiology

Fecal streptococcus c/100mL 2 – 740 168 49 93 209 1.9 1.2

Pseudomonas aeruginosa c/100mL 1 - 120 18 5.0 3.5 34 2.5 1.8

Table H-2: AP winter descriptive statistics

Pollutant Units Range GM

General Chemistry

160

Alkalinity mg/L 49 – 164 88 83 78 33 1.0 0.4

Chloride mg/L 13 – 1 700 475 206 217 545 1.2 1.2

Conductivity uS/cm 203 – 5 460 1 728 1 097 1 095 1 638 1.1 1.0

Hardness mg/L 45 – 560 213 148 110 185 0.9 0.9

pH - 7.8 – 9.7 8.3 8.3 8.2 0.47 1.8 0.06

Solids, dissolved mg/L 132 – 3 450 1 016 652 622 988 1.3 0.8

Solids, suspended mg/L 2.8 – 33.6 13 10 9.0 9.5 0.8 0.7

Solids, total mg/L 166 – 3 460 1 029 672 633 988 1.3 1.0

Sodium mg/L 18 – 972 314 132 176 338 0.8 1.1

Nutrients

Ammonia + ammonium nitrogen mg/L 0.015 – 0.2 0.065 0.048 0.038 0.06 1.5 0.06

Nitrite + nitrate nitrogen mg/L 0.36 – 1.6 0.83 0.77 0.77 0.34 0.8 0.8

Nitrite nitrogen mg/L <MDL – 0.068 0.022 0.016 0.018 0.02 1.3 0.02

Nitrate nitrogen mg/L 0.34 – 1.6 0.81 0.74 0.76 0.34 0.9 0.4

Total kjeldahl nitrogen mg/L 0.08 – 0.65 0.23 0.20 0.19 0.15 1.8 0.23

Organic nitrogen mg/L <MDL – 0.45 0.17 - 0.16 0.11 1.1 0.6

Total nitrogen mg/L 0.5 – 1.9 1.1 1.0 1.0 0.4 0.9 0.4

Phosphate phosphorus mg/L 0.0058 – 0.09 0.028 0.022 0.023 0.02 1.6 0.03

Total phosphorus mg/L 0.012 – 0.12 0.042 0.034 0.030 0.03 1.3 0.04

Metals

Aluminum μg/L 44 – 1 100 320 224 205 307 1.9 0.96

Antimony μg/L 0.5 – 0.9 0.65 0.64 0.6 0.13 0.4 0.20

Arsenic μg/L 0.6 – 6.6 2.4 1.8 1.6 1.9 1.3 0.80

Barium μg/L 25 – 555 133 78 52 160 1.7 1.20

Boron μg/L 5 - 42 19 16 18 11 0.8 0.56

Calcium mg/L 13 – 148 57 40 31 49 0.9 0.85

Copper μg/L 1.1 – 17.7 5.4 4.1 3.3 4.5 1.6 0.83

Iron μg/L 70 – 950 300 206 145 286 1.4 0.95

Lead μg/L 1.3 – 13.5 5.8 4.4 3.9 4.1 0.6 0.71

Magnesium μg/L 2.9 – 46 17 11 8.7 15 0.9 0.89

Manganese mg/L 4.3 – 51 21 16 14 16 0.9 0.74

Molybdenum μg/L 0.25 – 11 3.4 2.2 1.9 3.0 1.2 0.90

Nickel μg/L 0.89 – 6.8 2.8 2.2 2.4 2.0 0.8 0.72

Potassium mg/L 9.5 – 66 32 27 21 20 0.7 0.62

Strontium μg/L 1 420 – 33 400 314 5 594 176 338 0.8 1.08

Uranium μg/L 0.25 – 2.3 1.2 0.98 0.8 0.74 0.5 0.62

Vanadium μg/L 0.25 – 12.6 3.0 1.5 1 3.5 1.7 1.18

Zinc μg/L 11.5 – 49.7 27 25 24 13 0.5 0.46

Microbiology

Fecal streptococcus c/100mL 24 - 250 91 77 78 63 2.0 0.7

Pseudomonas aeruginosa c/100mL 2 -1 100 208 46 40 374 2.1 1.8

Table H-3: EO winter descriptive statistics

Pollutant Units Range GM

General Chemistry

161

Alkalinity mg/L 58 – 150 101 97 100 29 0.26 0.3

Chloride mg/L 11 – 1 460 543 269 456 452 0.58 0.8

Conductivity uS/cm 291 – 4 500 1 943 1420 1 780 1 317 0.44 0.7

Hardness mg/L 73 – 720 302 234 270 211 0.76 0.7

pH - 7.8 – 9.4 8.2 8.2 8.2 0.38 1.9 0.05

Solids, dissolved mg/L 189 – 3 190 1 173 857 1 030 854 0.89 0.7

Solids, suspended mg/L 2.5 – 45 12 9.0 8.7 11 1.75 0.9

Solids, total mg/L 196 – 3 190 1 185 870 1 040 854 0.87 0.7

Sodium mg/L 20 - 668 318 167 291 249 0.026 0.8

Nutrients

Ammonia + ammonium nitrogen mg/L 0.01 – 0.16 0.042 0.031 0.025 0.038 2.1 0.9

Nitrite + nitrate nitrogen mg/L 0.34 – 1.95 0.74 0.66 0.655 0.40 2.2 0.6

Nitrite nitrogen mg/L <MDL – 0.065 0.015 0.011 0.0095 0.015 2.3 1.0

Nitrate nitrogen mg/L 0.34 – 1.9 0.72 0.65 0.6455 0.40 2.2 0.6

Total kjeldahl nitrogen mg/L 0.06 – 0.52 0.19 0.16 0.15 0.12 1.5 0.6

Organic nitrogen mg/L <MDL – 0.36 0.15 0.12 0.126 0.096 1.1 0.7

Total nitrogen mg/L 0.42 – 2.19 0.92 0.84 0.825 0.45 1.6 0.5

Phosphate phosphorus mg/L 0.0034 – 0.12 0.020 0.013 0.0116 0.025 3.7 1.3

Total phosphorus mg/L <MDL – 0.185 0.040 0.028 0.027 0.043 2.7 1.1

Metals

Aluminum μg/L 45 – 1 460 281 167 123 362 2.5 1.3

Antimony μg/L 0.5 - 0.8 0.61 0.60 0.6 0.10 0.75 0.2

Arsenic μg/L 0.7 – 3.5 1.7 1.5 1.5 0.87 0.70 0.5

Barium μg/L 39 – 483 157 110 90 149 1.4 1.0

Boron μg/L 14 – 54 29 27 27 13 0.75 0.5

Calcium mg/L 20 – 203 84 65 75 58 0.77 0.7

Copper μg/L 2.4 - 11 5.5 5.0 4.8 2.8 0.84 0.5

Iron μg/L 30 – 1 200 253 144 110 304 2.1 1.2

Lead μg/L 0.6 – 13.6 3.1 2.0 1.75 3.4 2.2 1.1

Magnesium μg/L 5.4 – 52 23 18 18 16 0.75 0.7

Manganese mg/L 2.6 – 84 18 12 12 20 2.5 1.1

Molybdenum μg/L 0.8 – 8.6 3.4 2.6 2.1 2.5 0.87 0.7

Potassium mg/L 11.4 – 53.2 26 23 26 14 0.59 0.5

Strontium μg/L 3 720 – 40 400 12518 8 676 6 280 11 951 1.4 1.0

Uranium μg/L 0.5 – 1.9 1.1 1.0 1.0 0.52 0.22 0.5

Vanadium μg/L 0.25 – 9.7 2.4 1.3 1.3 2.7 1.7 1.1

Zinc μg/L 0.4 - 56 16 12 14 12 2.3 0.7

Microbiology

Fecal streptococcus c/100mL 2 - 590 154 35 34 231 1.4 1.5

Pseudomonas aeruginosa c/100mL 0 – 1 200 128 - 1.5 377 3.2 3.0

Table H-4: PC winter descriptive statistics

Pollutant Units Range GM

General Chemistry

162

Alkalinity mg/L 93 – 421 186 167 156 95 1.3 0.5

Chloride mg/L 9.8 – 1 150 359 197 200 344 1.1 1.0

Conductivity uS/cm 334 – 4 360 1730 1 355 1330 1130 0.7 0.7

Hardness mg/L 34 – 260 107 87 68 80 1.4 0.8

pH - 8.1 – 12 9.3 9.2 8.6 1.2 0.8 0.1

Solids, dissolved mg/L 217 – 2 260 958 778 815 589 0.7 0.6

Solids, suspended mg/L 1.3 – 101 28 13 10 30 1.2 1.1

Solids, total mg/L 220 - 2 360 986 802 841 600 0.7 0.6

Sodium mg/L 20 - 780 276 151 194 250 0.7 0.9

Nutrients

Ammonia + ammonium nitrogen mg/L <MDL – 0.17 0.17 0.39 0.056 0.043 0.05 1.1

Nitrite + nitrate nitrogen mg/L 0.26 – 1.6 1.6 0.50 0.58 0.45 0.4 1.9

Nitrite nitrogen mg/L <MDL – 0.053 0.053 0.018 0.02 0.018 0.02 0.5

Nitrate nitrogen mg/L 0.22 – 1.63 0.55 0.47 0.42 0.38 1.9 0.7

Total kjeldahl nitrogen mg/L 0.05 – 0.9 0.9 0.28 0.39 0.22 0.3 0.5

Organic nitrogen mg/L <MDL – 0.8 0.33 0.21 0.18 0.25 0.5 0.8

Total nitrogen mg/L 0.41 – 1.87 0.96 0.87 0.89 0.47 0.9 0.5

Phosphate phosphorus mg/L 0.011 – 0.219 0.22 0.043 0.058 0.043 0.05 2.0

Total phosphorus mg/L 0.043 – 0.66 0.66 0.11 0.15 0.12 0.1 2.5

Metals

Aluminum μg/L 48 – 1 260 521 353 486 401 0.4 0.77

Antimony μg/L 0.25 – 1 0.60 0.57 0.55 0.19 1.0 0.32

Arsenic μg/L 1.1 – 24.4 7.5 3.9 2.2 8.4 1.1 1.12

Barium μg/L 19 – 158 50 39 28 41 1.8 0.83

Boron μg/L 12 – 82 36 28 28 24 0.6 0.67

Calcium mg/L 9.4 – 55 24 20 15 16 1.3 0.68

Copper μg/L 1.8 – 57 15 8.4 8.8 15 1.4 1.04

Iron μg/L 30 – 970 387 252 310 315 0.6 0.81

Lead μg/L 0.6 – 12 4.2 2.8 1.8 3.7 0.9 0.89

Magnesium μg/L 2.4 – 31 12 8.9 7.7 9.9 1.4 0.85

Manganese mg/L 2.7 – 61 21 15 16 18 1.2 0.83

Molybdenum μg/L 0.75 – 12 5.8 4.8 4.8 3.4 0.7 0.59

Nickel μg/L 1.2 – 8.4 3.6 3.0 3.2 2.1 0.8 0.60

Potassium mg/L 41 – 255 102 83 65 74 1.3 0.7

Strontium μg/L 738 – 18 600 276 2 785 194 250 0.7 0.9

Uranium μg/L 0.25 – 1.6 0.75 0.63 0.6 0.44 0.77 0.6

Vanadium μg/L 5.3 – 24.6 6.0 3.2 2.9 5.6 0.42 0.9

Zinc μg/L 18 – 789 12 11 10 6.5 0.72 0.5

Microbiology

Fecal streptococcus c/100mL 2 - 270 50 21 16 84 2.8 1.7

APPENDIX I: TEMPERATURE DATA AND ANALYSIS

Water temperature of the stormwater within the AP underdrain and asphalt collection pipes was

monitored continuously at 5 minute intervals by Onset Smart temperature sensors. Continuous

163

temperature measurements were compiled into a time series plot. The thermal effect of outflow was

characterized by rapid thermal spikes in the data. For each event, the thermal spike was identified in

ASH and AP data and the maximum or minimum temperature recorded during outflow was extracted.

Temperature data was analyzed for the entire study period and for the winter (November – February)

and summer (April – September) seasons.

Water temperature spikes in the ASH and AP collection pipes are described in Table I-1 and extremely

warm and cool thermal events are summarized in Table I-2. During the summer, mean temperature

spikes from the AP effluent were 2.9 °C cooler than those from ASH runoff. Even more significantly,

the AP had 24 fewer thermal events than the ASH pavement and eliminated outflow greater than 29 °C.

During the winter, mean temperature spikes from the AP effluent were 2.7 °C warmer than those from

ASH runoff. Overall, the AP pavement eliminated almost half of the thermal events by capturing

stormwater and preventing outflow.

Table I-1: Water temperature spikes descriptive statistics (°C)

Statistic Overall Summer Winter

ASH AP ASH AP ASH AP

n 121 64 54 30 48 23

Range 0 – 32.6 1.6 – 29 6.8 – 32.8 3.7 -29 0 -11.7 1.6 -13.1

12.8 14.4 22.3 20.9 2.7 5.4

11.2 14.6 23.3 22.5 1.2 4.9

Table I-2: Summary of extreme thermal events

Temperature (°C) ASH AP

> 30 8 0

25 – 30 11 8

< 1 23 0