Performance of Hydromedia Pervious Concrete Pavement ... · PP systems consist of three basic...
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Performance of Hydromedia Pervious Concrete Pavement Subjected to Urban Traffic Loads in Ontario by Adam Crookes A thesis submitted in conformity with the requirements for the degree of Master of Applied Science Department of Civil Engineering University of Toronto © Copyright by Adam Crookes 2015
Transcript of Performance of Hydromedia Pervious Concrete Pavement ... · PP systems consist of three basic...
Performance of Hydromedia Pervious Concrete Pavement Subjected to Urban Traffic Loads in Ontario
by
Adam Crookes
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Civil Engineering University of Toronto
© Copyright by Adam Crookes 2015
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Performance of Hydromedia Pervious Concrete Pavement
Subjected to Urban Traffic Loads in Ontario
Adam Crookes
Master of Applied Science
Department of Civil Engineering
University of Toronto
2015
Abstract
Flooding and poor surface water quality are common in dense urban areas, and the challenge of
managing stormwater requires a new approach. This study evaluates the hydrologic and water
quality performance of a zero exfiltration Hydromedia Pervious Concrete parking lot in St.
Catharines, Ontario. Hydromedia is a type of permeable pavement, and is considered to be part of
a low impact development approach. Hydromedia showed a much improved hydrologic response
compared to conventional asphalt, with both volume and peak discharge reductions, as well as lag
times to peak for every event observed. Residual concentrations in Hydromedia effluent were
below relevant guidelines for the majority of pollutants, however high early age pH, and elevated
levels of aluminum, chromium, and mercury were detected in the effluent. The LSSC is an
excellent site for further research, and long term monitoring would help to evaluate the
effectiveness of zero exfiltration systems in Ontario.
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Acknowledgments
Thank you to Dr. Jennifer Drake for the opportunity to conduct this research, and for her time,
patience, and valuable feedback throughout the process. Further thanks to field assistants,
including Paul Martin, Michael Mousa, and Kevin Lam. Funding was provided by the Ontario
Centres of Excellence, Connect Canada, and Lafarge Canada. In kind support was provided by
Lafarge Canada, the City of St. Catharines, and Good Harbour Laboratories. Special thanks to Dirk
Hughes and Dianne Allan-Zwart at the City of St. Catharines for all their assistance at the Lake
Street Service Centre. Last but certainly not least, I would like to thank John and Jill Crookes for
always being there and working so hard to provide me the opportunity to pursue education and
research.
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Table of Contents
Acknowledgments .......................................................................................................................... iii
Table of Contents ........................................................................................................................... iv
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
List of Appendices ........................................................................................................................ xii
Chapter 1 Introduction .................................................................................................................... 1
1.1 Background ......................................................................................................................... 1
1.2 Research Objectives ............................................................................................................ 3
1.3 Thesis Structure .................................................................................................................. 4
Chapter 2 Literature Review ........................................................................................................... 5
2.1 Investigations of Permeable Pavement Performance .......................................................... 5
2.1.1 Field Studies ............................................................................................................ 5
2.1.1.1 Water Quantity Performance Monitoring Methods .................................. 7
2.1.1.2 Water Quality Performance Monitoring Methods .................................... 8
2.1.1.3 Surface Infiltration Performance Monitoring Methods .......................... 10
2.1.2 Laboratory Studies ................................................................................................ 10
2.2 Permeable Pavement Water Quality Effects ..................................................................... 11
2.2.1 Suspended Solids .................................................................................................. 12
2.2.2 pH and Alkalinity .................................................................................................. 13
2.2.3 Heavy Metals ........................................................................................................ 14
2.2.4 Nutrients ................................................................................................................ 15
2.2.5 Hydrocarbons ........................................................................................................ 16
2.2.6 Road Salts ............................................................................................................. 17
2.3 Permeable Pavement Water Quantity Effects ................................................................... 18
2.3.1 Full and Partial Exfiltration Systems .................................................................... 19
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2.3.1.1 High Permeability Native Soils .............................................................. 19
2.3.1.2 Low Permeability Native Soils ............................................................... 20
2.3.2 Zero Exfiltration Systems ..................................................................................... 21
2.4 Barriers to Implementation of Permeable Pavements ....................................................... 22
2.4.1 Permeable Pavement Economics .......................................................................... 22
2.4.2 Maintenance .......................................................................................................... 23
Chapter 3 Methodology ................................................................................................................ 26
3.1 Study Site .......................................................................................................................... 26
3.2 Field Scale Methodology .................................................................................................. 31
3.2.1 Infiltration Capacity Measurement ....................................................................... 31
3.2.2 Hydromedia Effluent Outflow and Rainfall ......................................................... 32
3.2.2.1 Flow Measurement Apparatus ................................................................ 32
3.2.2.2 Flow Measurement Calibration .............................................................. 35
3.2.2.3 Rainfall Measurement............................................................................. 37
3.2.2.4 Hydrologic Data Analysis ...................................................................... 37
3.2.3 Water Quality ........................................................................................................ 40
3.2.3.1 Sample Collection and Analysis ............................................................. 40
3.2.4 Data Analysis ........................................................................................................ 42
3.3 Laboratory Scale Methodology ......................................................................................... 44
3.3.1 Test Specimen Preparation and Storage ............................................................... 44
3.3.2 pH Experiment ...................................................................................................... 46
3.3.3 Total Phosphorus Experiment ............................................................................... 47
Chapter 4 Hydrology ..................................................................................................................... 48
4.1 Infiltration Capacity .......................................................................................................... 48
4.2 Weir Box Calibration ........................................................................................................ 50
4.3 Hydromedia Effluent Discharge and Rainfall ................................................................... 51
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4.3.1 Observations ......................................................................................................... 51
4.3.2 Single Event Comparison to Pre-Development Conditions .................................. 56
4.3.3 Regression Analysis Results ................................................................................. 57
4.3.4 Summary ............................................................................................................... 61
Chapter 5 Water Quality ............................................................................................................... 62
5.1 Total Suspended Solids ..................................................................................................... 62
5.2 pH and Alkalinity .............................................................................................................. 66
5.2.1 Field Results .......................................................................................................... 66
5.2.2 Laboratory Scale Results ...................................................................................... 69
5.3 Oil and Grease ................................................................................................................... 71
5.4 Nutrients ............................................................................................................................ 72
5.4.1 Nitrogen ................................................................................................................ 73
5.4.2 Phosphorus ............................................................................................................ 75
5.4.2.1 Field Results ........................................................................................... 75
5.4.2.2 Laboratory Scale Results ........................................................................ 76
5.5 Heavy Metals .................................................................................................................... 78
5.5.1 Arsenic .................................................................................................................. 78
5.5.2 Aluminum ............................................................................................................. 80
5.5.3 Barium ................................................................................................................... 81
5.5.4 Chromium ............................................................................................................. 82
5.5.5 Copper ................................................................................................................... 84
5.5.6 Iron ........................................................................................................................ 85
5.5.7 Mercury ................................................................................................................. 86
5.5.8 Molybdenum ......................................................................................................... 88
5.5.9 Zinc ....................................................................................................................... 89
Chapter 6 Conclusions and Recommendations ............................................................................. 90
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References ..................................................................................................................................... 96
viii
List of Tables
Table 1: Permeable Pavement Field Studies ................................................................................... 6
Table 2: EPA SWMM Model Parameters (Pre-development Condtions) .................................... 39
Table 3. Water quality parameters and minimum detection limits ............................................... 42
Table 4: Specimen ID numbers and storage details ...................................................................... 45
Table 5: Weir Box Calibrations Results Summary ....................................................................... 50
Table 6: Summary of rainfall events and effluent discharge ........................................................ 52
Table 7: Summary of Regression Analysis Correlations .............................................................. 60
Table 8: Descriptive statistics for TSS concentration of Hydromedia effluent ............................ 62
Table 9: Descriptive statistics for pH of Hydromedia effluent ..................................................... 66
Table 10: Descriptive statistics for alkalinity of Hydromedia effluent ......................................... 68
Table 11: Descriptive statistics for TP of Hydromedia effluent ................................................... 75
Table 12. Descriptive statistics for arsenic concentration of Hydromedia effluent ...................... 79
Table 13. Descriptive statistics for aluminum concentration of Hydromedia effluent ................. 80
Table 14. Descriptive statistics for barium concentration of Hydromedia effluent ...................... 81
Table 15. Descriptive statistics for chromium concentration of Hydromedia effluent ................. 83
Table 16. Descriptive statistics for molybdenum concentration of Hydromedia effluent ............ 88
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List of Figures
Figure 1: Types of Permeable Pavement Systems .......................................................................... 2
Figure 2: Weir box schematic ......................................................................................................... 7
Figure 3. Lake Street Service Centre Study Site Location ........................................................... 26
Figure 4. Lake St. Service Centre Test Parking Lot Schematic (Plan View) ............................... 27
Figure 5. Lake Street Service Centre Permeable Pavement Subgrade ......................................... 28
Figure 6: Plan View of Study Site (Image Date: 2010) ................................................................ 29
Figure 7. Photo of Hydromedia sampling catch basin - looking down into catch basin (April 28,
2014) ............................................................................................................................................. 30
Figure 8. Photo of infiltration testing on Hydromedia surface. Test being conducted to left and
infiltration ring temporarily sealed to surface on right. (June 30, 2014) ...................................... 31
Figure 9. Photos of weir box prior to installation. Front view to left, rear view to right. (June 26,
2014) ............................................................................................................................................. 33
Figure 10. Photo of weir box in catch basin - looking down into the catch basin (August 27, 2014)
....................................................................................................................................................... 34
Figure 11. Painted weir box with legs attached prior to installation (July 4, 2014) ..................... 34
Figure 12: Weir calibration apparatus at Good Harbour Laboratories (January 14, 2015) .......... 36
Figure 13: Weir box connected to hose, discharging to basin (January 14, 2015) ....................... 37
Figure 14. Photo of grab sample collection point at outlet from asphalt cell to swale. (April 28,
2014) ............................................................................................................................................. 40
Figure 15. Photo of glass Hydromedia effluent sampler .............................................................. 41
Figure 16: Four of eight Hydromedia Test Specimens (November 10, 2014) ............................. 44
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Figure 17: Inverted Hydromedia specimen showing small drainage holes .................................. 45
Figure 18: Determining pH of Hydromedia Test Specimen Effluent (November 10, 2014) ....... 46
Figure 19: Hydromedia infiltration capacity and approximate test locations (June 30, 2014) ..... 48
Figure 20: Ponding on Hydromedia surface near clogged test location during heavy rainfall
(October 3, 2014) .......................................................................................................................... 49
Figure 21: Weir box calibration results ........................................................................................ 50
Figure 22: Hydromedia Effluent Hydrograph and Rainfall from 42 mm Event (July 7 - July 9,
2014) ............................................................................................................................................. 54
Figure 23: Hydromedia Effluent Hydrograph and Rainfall from 16.5 mm Event (Oct 3 – Oct 4,
2014) ............................................................................................................................................. 55
Figure 24: Hydromedia Effluent Hydrograph and Rainfall from 6.5 mm Event (Sept 13 - Sept 14,
2014) ............................................................................................................................................. 56
Figure 25: July 7, 2014 Pre-Development Modelling Results ...................................................... 57
Figure 26: Hydromedia Effluent Volume Regression Results (diagonal line shows perfect fit – for
reference only) .............................................................................................................................. 58
Figure 27: Hydromedia Effluent Peak Discharge Regression Model (diagonal line shows perfect
fit – for reference only) ................................................................................................................. 59
Figure 28. TSS concentration results (October 3, 2014) .............................................................. 64
Figure 29. Photo of composite samples from October 3, 2014 event. Asphalt runoff on top row,
Hydromedia effluent on bottom row, in chronological order from left to right. .......................... 65
Figure 30: pH results (October 3, 2014) ....................................................................................... 68
Figure 31: Laboratory pH results of Hydromedia test specimens ................................................ 69
Figure 32. Total oil and grease results (October 3, 2014) ............................................................ 72
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Figure 33. TKN results (October 3, 2014) .................................................................................... 73
Figure 34. TP results (October 3, 2014) ....................................................................................... 76
Figure 35. Laboratory TP results of Hydromedia test specimens (175 mL water per flush)........ 77
Figure 36: Laboratory TP results of Hydromedia test specimens (3.9 L water per flush) ........... 77
Figure 37: Arsenic Results (October 3, 2015) .............................................................................. 79
Figure 38. Aluminum results (October 3, 2014) ........................................................................... 81
Figure 39. Barium results (October 3, 2014) ................................................................................ 82
Figure 40. Chromium results (October 3, 2014) ........................................................................... 83
Figure 41: Copper results (October 3, 2014) ................................................................................ 85
Figure 42. Iron results (October 3, 2014) ..................................................................................... 86
Figure 43. Mercury results (October 3, 2014) .............................................................................. 87
Figure 44. Zinc results (October 3, 2014) ..................................................................................... 89
Figure 45: Diagnostic Plots for Hydromedia Effluent Volume .................................................. 108
Figure 46: Diagnostic Plots for Peak Hydromedia Discharge .................................................... 109
Figure 47: Diagnostic Plots for Peak Hydromedia Discharge Omitting July 7 Outlier .............. 110
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List of Appendices
Appendix A – Weir Box Design Drawing .................................................................................. 101
Appendix B – Lamotte Smart 3 Colorimeter TP Test Procedure ............................................... 103
Appendix C – Regression Analysis Diagnostic Plots ................................................................. 107
Appendix D – Laboratory Water Quality Analysis Reports ....................................................... 111
Appendix E –Water Quality Data – Living City Campus at Kortright ....................................... 122
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Chapter 1 Introduction
Introduction
1.1 Background
Management of stormwater has a direct impact on surface water quality and flooding. This is
particularly true in urban areas, where a large portion of the surface has been covered with
impermeable surfaces including roads, parking lots, and buildings. Impermeable surfaces prevent
the natural infiltration of stormwater into the ground. In 2012, the Niagara Peninsula Conservation
Authority (NPCA) evaluated surface water quality of all the subwatersheds falling under their
jurisdiction. Water quality in the majority of subwatersheds received a “poor” grade, indicating
that surface waters are contaminated (NPCA, 2012). In Toronto, Ontario’s largest city, the Toronto
and Region Conservation Authority (TRCA) gave stormwater management across the watershed
a failing grade, and stated that “significant action is required” (TRCA & GGT, 2011).
The traditional approach to stormwater management is to promote rapid drainage of stormwater to
conveyance systems, and provide some quantity and quality control with end of pipe controls. Poor
surface water quality and stormwater management grades in southern Ontario show that the
traditional approach is not effective. Low Impact Development (LID) is an alternative approach,
which can mitigate some of the negative impacts associated with urbanization discussed above,
including surface water quality and flooding (TRCA, 2012). The LID approach aims to manage
stormwater at the source. Permeable pavements (PP) are one type of LID practice, and they are
meant to replace conventional impermeable paving systems, providing a hard, trafficable surface,
where stormwater can still infiltrate into the ground. PP’s are particularly attractive in dense urban
areas, where there is simply no room for other types of stormwater best management practices
(BMP’s) (Fach & Geiger, 2005). They provide quantity control by infiltrating stormwater and
attenuating discharge, and quality control by acting as a filter to remove contaminants.
PP systems consist of three basic elements, including the permeable surface, a clear stone sub base
to promote infiltration, and some form of subgrade drainage. All PP systems can be classified as
either full, partial, or zero exfiltration systems, based on the amount of water that is able to
exfiltrate to the native soil (Drake et al., 2013). Figure 1 shows the differences between these
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systems. A zero exfiltration system has an impermeable liner and subdrains to prevent water from
reaching the native soil, a partial exfiltration system has subdrains which collect some of the
infiltrated water, and a full exfiltration system has no subdrains or liners. Full exfiltration systems
are best suited to sites with high permeability native soils, while partial exfiltration systems are
best suited to sites with low permeability soils. Zero-exfiltration systems are uncommon, although
they are the only option in dense urban environments with poorly draining soils, areas with
contaminated soils, and groundwater sensitive areas. Most research has focused on partial
exfiltration systems, so the infiltrated water collected in subdrains can be measured to monitor
outflow rates, and sampled for effluent water quality analysis.
Figure 1: Types of Permeable Pavement Systems
The three most common types of PP surface materials are permeable interlocking concrete pavers
(PICP), pervious concrete (PC), and porous asphalt (PA). While different in structure and design
requirements, they all serve the same purpose of providing a hard, trafficable surface, yet still
allowing stormwater to infiltrate.
Implementation of PPs in Ontario is not widespread, in part due to concerns over long term
performance. Limited research has been conducted related to the water quantity and quality
performance of PP’s in Ontario. One study site is located in Vaughan, just north of Toronto, and
the performance of three types of PP is monitored there. Monitoring over the first five years at this
site has shown promising results for the use of PP’s in Ontario, but the site is located in a
conservation area with low traffic loads, and no immediate urban surroundings (Drake et al., 2012).
Environmental performance of PP has not been demonstrated in an urban environment in Ontario.
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1.2 Research Objectives
The objective of this thesis is to assess the water quantity and quality performance of a zero
exfiltration, Low-Compactibility Pervious Concrete (Hydromedia) parking lot. The project is
primarily a field study, monitoring the performance of a Hydromedia parking lot in the City of St.
Catharines. This research is considered to be a short term study, with a monitoring period of only
five months. It serves as exploratory work to investigate if the parking lot in St. Catharines is
suitable for a long term study. The objectives of this research are:
1. Assess the current infiltration capacity of the Hydromedia and determine if maintenance is
required;
2. Evaluate the hydrologic performance of the Hydromedia parking lot, including volume and
peak flow reductions, and lag times;
3. Evaluate the water quality of Hydromedia effluent and identify pollutants which may be of
concern to surface water quality; and
4. Develop recommendations for potential improvements to the design and operation of
Hydromedia and zero exfiltration systems, and identify opportunities for further research.
Hydromedia is a low compaction PC produced by Lafarge, which aims to address observed
problems of earlier PC mix designs through improved workability and durability. A high initial
infiltration capacity is achieved by combining a carefully designed aggregate matrix with sufficient
cement paste to coat each stone individually. A bond forms between each aggregate piece while
leaving a large void structure. This research serves to demonstrate if Hydromedia is suitable for
use in urban areas of Ontario, from a hydrologic and surface water quality perspective.
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1.3 Thesis Structure
This thesis is comprised of six chapters. Descriptions of each chapter are provided below:
Chapter 1 – Introduction
Presents background information, research objectives, and a description of the thesis structure.
Chapter 2 – Literature Review
Provides a detailed literature review to discuss the methods and findings of other PP studies, and
to identify gaps in the research.
Chapter 3 - Methodology
Describes the research site, and the field and laboratory methods implemented to collect and
analyze data.
Chapter 4 – Hydrology
Presents the results which describe the hydrology of the PP parking lot, and a discussion comparing
the performance of Hydromedia to a conventional asphalt parking lot.
Chapter 5 – Water Quality
Presents the results of water quality analysis of both Hydromedia effluent, and asphalt surface
runoff. Results and discussion of the analysis of several common pollutants and water quality
parameters is included to evaluate Hydromedia effluent and its potential impacts on watercourses.
Water quality results are compared to observations of Hydromedia performance made at another
site in Ontario.
Chapter 6 – Conclusions and Recommendations
Discusses the primary conclusions of this research, as well as recommendations for additional
research into improving the performance of Hydromedia, both in a general sense for Hydromedia,
and specifically at the St. Catharines research site.
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Chapter 2 Literature Review
This chapter presents the findings of a review of literature related to PP performance. Section 2.1
presents a review of several studies and the methodologies implemented for monitoring the
performance of PPs. Results and conclusions of these studies in regard to water quantity and
quality performance are discussed in Sections 2.3 and 2.4. The chapter concludes with a review of
the literature related to implementation of PPs in urban development, including economics and
maintenance requirements.
Literature Review
2.1 Investigations of Permeable Pavement Performance
There are generally two approaches taken when investigating PP performance, large scale field
studies, and laboratory scale experiments. Large scale field studies make up the majority of the
material reviewed for this chapter, because this is primarily a field scale project, but some relevant
laboratory scale experiments are also discussed. Topics of interest to this study include the
performance of PPs in terms of water quantity and quality effects, and long term infiltration
capacity.
2.1.1 Field Studies
Numerous field studies have been conducted to evaluate the performance of PPs. Most of the
research focuses around parking lots which have been designed to allow for performance
monitoring. Most studies occur early in the life of the parking lot, and do not provide observations
of long term performance over the entire life cycle of the pavements. Table 1 lists the PP field
studies reviewed to prepare this chapter, along with the location and age of the subject site(s) at
the end of each investigation, the type(s) of PP investigated, and the parameters being studied.
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Table 1: Permeable Pavement Field Studies
Paper Location Subject
Site(s) Age
Permeable
Pavement
Type(s)*
Performance Indicators Investigated
Quantity Quality Surface
Infiltration
Bean et al., 2007 4 sites in NC 1-2 years CBP, CGP,
PC
X X
Beecham et al., 2012 Adelaide,
Australia
Unknown CBP X
Booth & Leavitt, 1999 Renton,
Wash.
1 year PGP, CGP,
CBP
X X
Brattebo & Booth,
2003
Renton,
Wash.
6 years PGP, CGP,
CBP
X X
Brown & Borst, 2014a Edison, NJ 3 years PC, CBP, PA X
Brown et al., 2012 Nashville,
NC
17 months PC X X
Borst & Brown, 2014b Edison, NJ 3 years PC, CBP, PA X
Collins et al., 2008 Kinston, NC 1.5 years CBP, CGP,
PC
X X
Collins et al., 2010 Kinston, NC 1.5 years CBP, CGP,
PC
X X
Drake & Bradford,
2013
4 sites in
Ontario
2- 12 years CBP, PC, PA X
Drake et al., 2012 Vaughan,
ON
2 years CBP, PC X X X
Drake et al., 2014 Vaughan,
ON
4 years CBP, PC X X X
Fassman &
Blackbourn, 2010
Auckland,
NZ
2 years CBP X X
Haselbach & Werner,
2015
Pullman,
WA
2 to 4
years
PC X
Henderson & Tighe,
2011
5 sites in
Canada
8 – 31
months
PC X
Houle et al., 2010 Durham, NH 2 years PA, PC X
Hunt et al., 2002 Kinston &
Wilmington,
NC
2 years PGP, CGP, PC X
Jaber, 2015 Fort Worth,
TX
1 year PGP, CBP X X
Pratt et al., 1989 Nottingham,
UK
< 1 year CBP X X
Roseen et al., 2009 Durham, NH 2 years PA X
Roseen et al., 2012 Durham, NH 4 years PA X X X
Rushton, 2001 Tampa, FL 2 years Unknown X X
Sansalone & Teng,
2004
Baton
Rouge, LA
1 year PC X X
Sanudo-Fontaneda et
al., 2014
Santander,
Spain
1 year CGP, PGP,
PC, PA, CBP
X X
Wardynski et al., 2014 Boone, NC 1 year CBP X X X
Welker et al., 2012 Philadelphia,
PA
1 year PC, PA X
* PGP: plastic grid paver, CGP: concrete grid paver, PC: pervious concrete, CBP: concrete block pavers, PA: porous asphalt
7
All of the studies listed in Table 1 were conducted on PP parking lots, with the exception of
Fassman & Blackbourn (2010), and Sansalone & Teng (2004), which were both implemented on
road systems.
2.1.1.1 Water Quantity Performance Monitoring Methods
Monitoring of water quantity performance has been carried out by measuring the flowrate of
effluent collected in subdrains (Drake et al., 2012; Roseen et al., 2012; Sansalone & Teng, 2004;
Wardynski et al., 2014), collecting and measuring surface runoff (Hunt et al., 2002; Pratt et al.,
1989), or both (Bean et al., 2007; Brattebo & Booth, 2003; Collins et al., 2008; Collins et al., 2010;
Fassman & Blackbourn, 2010). The measured flow from either the subdrains or surface runoff can
be compared to measured rainfall to determine volume and peak flow reductions, as well as lag
time and flow attenuation. Flow measurements are most commonly carried out using either a
tipping bucket (Drake et al., 2012; Brattebo & Booth, 2003; Booth & Leavitt, 1999; Pratt et al.,
1989), or a V-notch weir (Bean et al., 2007; Collins et al., 2008; Collins et al., 2010; Hatt et al.,
2009; Hunt et al., 2002; Fassman & Blackbourn, 2010; Wardynski et al., 2014). V-notch weirs are
well suited for measuring a wide range of flows, while tipping buckets can provide more accurate
measurement of low flows.
Figure 2 shows a schematic of a typical weir system. Milburn & Burney (1988) experimented with
V-notch weir box designs to measure subsurface flows and note that a partially contracted weir
should satisfy the following conditions:
Figure 2: Weir box schematic
𝐻
𝑃 ≤ 1.2
𝐻
𝐵 ≤ 0.4
0.05 < 𝐻 < 0.6 𝑚
𝑃 ≥ 0.1 𝑚
𝐵 ≥ 0.6 𝑚
8
It was observed that the nappe tends to cling to the weir crest at heads below 30 mm, and weirs
are less accurate, and therefore not recommended at these low heads (Milburn & Burney, 1988).
Equation 1 applies for a partially contracted V-notch weir (Chin, 2013):
𝑸 = 𝟖
𝟏𝟓 𝑪𝒅 √𝟐𝒈 𝐭𝐚𝐧
𝜽
𝟐 𝑯
𝟓
𝟐 Equation 1
Where: Q: Flow rate (m3/s)
Cd: Drag coefficient (typically 0.58)
g: gravity (9.8 m/s2)
ϴ: V-notch weir angle (degrees)
H: head above weir crest (m)
For Equation 1 to be valid, ϴ should be between 20 and 100 degrees, and H should be greater than
5 cm (Chin, 2013). For other circumstances, a calibration experiment should be conducted to
determine relation between head above the weir crest and the flow rate. A drop of about 15 cm
over the crest of the weir is required to establish free flowing conditions, and the head should be
measured a distance of at least 3 times the maximum head upstream of the weir (Adkins, 2006).
2.1.1.2 Water Quality Performance Monitoring Methods
Analysis of the quality of PP effluent is an important consideration during the evaluation of PPs
as a stormwater management practice. Depending on the type of PP system, effluent will exit the
system either by exfiltration into the native soil, through subdrains, or by both exfiltration and
through subdrains. To determine the potential impact of the effluent on receiving water courses,
subsurface samples are collected and analyzed for common urban stormwater pollutants. The most
common approach is to install subdrains in either partial or zero exfiltration systems, and obtain
samples of water collected in the drains (Drake et al., 2012; Drake et al., 2014; Brattebo & Booth,
2003; Booth & Leavitt, 1999; Roseen et al., 2012; Bean et al., 2007; Collins et al., 2008; Collins
et al., 2012; Pratt et al. 1989; Fassman & Blackbourn, 2010; Sansalone & Teng, 2004; Sanudo-
Fontaneda et al., 2014; Jaber, 2015).
Pollutant concentrations of PP effluent are commonly compared to the concentrations measured
in surface runoff of a conventional asphalt reference parking lot. Drake et al., 2013, conducted a
comprehensive review of PP research, and found that most studies report pollutant reductions in
terms of event mean concentrations (EMCs), and occasionally include pollutant load reductions.
Pollutant load is a more valuable indicator of water quality, because it makes it possible to
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determine impact on surface water quality. Determination of EMC requires the collection of flow-
weighted composite samples throughout the duration of a storm event and any subsequent
drainage. Roseen et al. (2012) used automated samplers to collect composite samples, four for the
first flush of an event, and twenty for the recession limb of the outflow hydrograph. Removal
efficiency of a PP system is determined using Equation 2 (Drake et al., 2014):
𝑹𝑬𝒊 = 𝟏 − 𝑬𝑴𝑪𝑷𝑷
𝑬𝑴𝑪𝑨𝑺𝑯 Equation 2
Where: RE: removal efficiency
i: event 1, 2, 3, … , n
Pollutant loads can be determined using Equations 3 through 5 (Drake et al., 2014):
𝑳 = 𝑽𝒊𝑬𝑴𝑪𝒊
𝑨 Equation 3
𝑴 = ∑ 𝑳𝒊𝒏𝒊=𝟏 Equation 4
𝑺𝑶𝑳 = 𝟏 − ∑ 𝑳𝑷𝑷
𝒏𝒊=𝟏
∑ 𝑳𝑨𝑺𝑯𝒏𝒊=𝟏
Equation 5
Where: L: pollutant load normalized by area
V: event volume
A: pavement area
M: total pollutant mass
SOL: summation of pollutant loads
A host of contaminants can be measured, but the focus tends to be on total suspended solids (TSS),
pH, heavy metals, nutrients (nitrogen and phosphorus), and hydrocarbons (oil and grease).
Removal efficiency is typically reported in the literature rather than residual pollutant
concentrations in PP effluent, and pollutant loads are not reported in most research (Drake et al.,
2013). Reporting of only removal efficiencies does not always provide a good indicator of PP
performance. If the pollutant concentration in asphalt runoff for a study was very high, a good
removal efficiency does not necessarily mean that the PP effluent has an acceptably low pollutant
concentration to protect aquatic life. Water quality benefits of PPs and other LID systems on a
watershed scale have not been investigated (Roy et al., 2008). Most studies focus only on the water
quality of PP effluent, not the receiving waters where the PP effluent is discharged. Research tends
10
to focus on only the lot level scale because the performance of PP is constantly questioned, and
often needs to be demonstrated many times for every new municipality where the technology may
be applied.
2.1.1.3 Surface Infiltration Performance Monitoring Methods
PP’s remove particulate matter from stormwater, which eventually clogs the void spaces in the
pavement surface. Loss of infiltration capacity due to clogging is considered a failure of the PP
system when it can no longer infiltrate all of the stormwater that falls on it (Drake et al., 2013).
Several studies have measured infiltration capacity of PPs (Drake et al., 2012; Henderson & Tighe,
2011; Brown & Borst, 2014a; Drake & Bradford, 2013; Roseen et al., 2012; Collins et al., 2008;
Haselbach & Werner, 2015). The two most recent standard test methods for measuring the
infiltration rate of PP’s are ASTM C1701 (ASTM, 2009) and ASTM C1781 (ASTM, 2013). Both
standards use similar methods, ASTM C1701 was published for use on pervious concrete, and
ASTM C1781 contains some modifications for use with PICP (Brown & Borst, 2014a). A
cylindrical infiltration ring is temporarily sealed to the PP surface, a known volume of water is
poured inside the ring, and the time for the water to infiltrate is recorded (ASTM, 2009).
Brown and Borst (2014) used a modified version of ASTM C1701 to evaluate surface infiltration
testing methods on a parking lot with PC, PICP, and PA. Testing was performed at random and
fixed locations (Brown & Borst, 2014a). The study concluded that surface infiltration testing
programs for PP parking lots should focus on areas of the parking lot which are subject to run on
(Brown & Borst, 2014a). These areas are more likely to become clogged (Haselbach & Werner,
2015), and low measured infiltration rates would indicate that maintenance is required.
2.1.2 Laboratory Studies
Laboratory scale studies are not completely representative of environmental conditions that are
encountered over the life cycle of a PP, including temperature and rainfall variations, freeze-thaw
cycles, traffic, and highly variable pollutant loads. However, they allow for more controlled
conditions to be established, to eliminate the high degree of variability in a natural environment.
Pratt et al. (1999) examined the removal of mineral oil in a PP structure under laboratory
conditions. The experimental setup consisted of a column with PICP underlain by gravel and a
geotextile, with no native soil beneath. A dripper applied oil to the PP surface at a concentration
11
100 times the average load expected in an urban environment, and the surface was irrigated with
simulated rainfall, which infiltrated and drained freely through the bottom of the column where it
was collected for measurement of oil concentration. The pavement surface was seeded with
varying amounts of microbes and fertilizer, to test their effect on oil biodegradation. By performing
this study under laboratory conditions, Pratt et al. (1999) were able to isolate the addition of
microbes and fertilizer, and determine their effect on mineral oil removal. Newman et al. (2002)
expanded on the work of Pratt et al. (1999) by modified the column size and varying nutrient and
microbe doses.
Fach & Geiger (2005) examined the effect of different subbase aggregate materials on heavy metal
removal using several PP columns which were identical other than different types of aggregate.
They used a solution containing heavy metals as simulated rainfall, rather than applying the
contaminant directly to the surface. Applying simulated rainfall rather than relying on natural
conditions may allow for the duration of experiments to be reduced, because higher pollutant loads
and rainfall volumes are possible.
Syrrakou & Pinder (2014) studied evaporation rates under controlled laboratory conditions. They
added water to a freely draining column of PC and aggregate, and measured the change in mass of
the column over time. Freely draining conditions represent a PP system in well-draining native
soils, or with underdrains. Thomle (2010) studied pH of PC effluent by applying water to the
surface of laboratory prepared PC specimens and collecting water samples of the effluent.
2.2 Permeable Pavement Water Quality Effects
This section presents the water quality analysis results and conclusions of the studies reviewed for
this chapter. The discussion is split into subsections by the contaminants which are of concern in
urban stormwater management. Surface deposition of pollutants in urban environments originates
from several sources including vehicle traffic, the atmosphere, leaf litter, animal waste, and road
salt (Drake et al., 2013). Typical surface runoff from an urban watershed contains the highest
contaminant concentrations in the first flush, just as runoff begins shortly after the start of a storm
(Lee & Bang, 2000). Runoff from high density residential watersheds typically contains the highest
pollutant concentrations in a city (Lee & Bang, 2000). The primary pollutant removal mechanism
for a PP system is mechanical filtration (Drake et al., 2013). Sorption, and biological processes
within the aggregate subbase provide additional treatment to remove some dissolved contaminants
12
(Mothershill et al., 2000). Antecedent moisture conditions and the influence of groundwater can
have considerable effects on water quality in PP systems (Brown et al., 2012). Long term
improvements to water quality from PP systems have not been demonstrated, including the
possibility of remobilization of pollutants captured within the PP (Drake et al., 2014).
2.2.1 Suspended Solids
Total suspended solids (TSS) concentration is a measure of the amount of solid particulate matter
suspended in water. The Ontario Ministry of Environment and Climate Change (MOECC) uses
TSS removal as the sole stormwater quality criterion for evaluation of BMP’s. MOECC specifies
three levels of protection, each with a different TSS removal requirement. “Enhanced” protection
corresponds to a TSS removal of 80%, “normal” protection is 70%, and “basic” is 60% (MOECC,
2003). The required level of protection should be selected in order to “maintain or enhance existing
aquatic habitat”, and therefore depends on nature of the habitat in the receiving waterbody
(MOECC, 2003). In southern Ontario, conservation authorities typically specify the required level
of protection. NPCA provides stormwater quality criteria for the Niagara region, including the City
of St. Catharines. NPCA follows the MOECC criteria, but requires a normal level (70% TSS
removal) of protection at minimum (AECOM, 2010).
PP removes suspended solids through mechanical filtration, and all recent studies report TSS
removal of more than 50% in PP effluent compared to asphalt runoff (Drake et al., 2013). Roseen
et al. (2012) reported reductions in TSS concentrations of PP effluent, with only one sample having
TSS concentration above minimum detection limits, during the most intense storm recorded for
the entire study. Pratt et al. (1989) observed that TSS concentrations in PP effluent were about 20
mg/L for a zero exfiltration system. A study which consisted of a PC parking lot in a treatment
train process with a bioretention cell found a TSS removal efficiency of 64% compared to asphalt
runoff (Brown et al., 2012). Jaber (2015) observed a TSS removal efficiency of 65% for two types
of PP.
In Ontario, Drake et al. (2012) found that mean and median TSS concentrations and pollutant loads
were significantly lower in PP effluent than in asphalt runoff. Additional monitoring at the same
study site indicated that TSS concentrations in PP effluent were reduced by at least 80% relative
to asphalt runoff (Drake et al., 2014). This result demonstrates that PPs are capable of producing
13
effluent which meets an enhanced level of protection, according to MOECC criteria. While the
results of all these studies vary, it was been well documented that PP's remove TSS.
2.2.2 pH and Alkalinity
PP effluent is typically basic, especially PC pavements. On a road with PICP, underdrain effluent
was found to have a higher mean pH than asphalt, 7.6 for PP effluent and 6.99 for asphalt runoff
(Fassman & Blackbourn, 2010). Roseen et al., 2012 observed a buffering effect, with a more
neutral median pH of 7.1 in PA effluent as compared to a median of 6.1 in asphalt runoff.
Sansalone & Teng (2004) observed higher pH in PC effluent from a highway (about 8.0),
compared to influent pH (about 6.5 to 7.5). Jaber (2015) observed high pH in PP effluent, and a
decrease over time, trending towards stabilization as the PP aged.
The basic pH observed in PP effluent is likely due to calcium carbonate and magnesium carbonate
in the paving surface and subbase aggregates, especially for PC (Collins et al., 2010). Thomle
(2010) observed a decline in the pH of PC effluent with time under laboratory conditions over the
first year in the life of prepared PC specimens. The decline was attributed to carbonation due to
exposure to carbon dioxide in the ambient air. Carbonation replaces calcium hydroxide with
calcium carbonate, which buffers to a lower pH.
An increase in pH of watercourses due to discharge of basic PP effluent could have negative
impacts on aquatic life and habitat (Drake et al., 2012), but a higher pH increases precipitation of
metals, which improves heavy metal removal in PP effluent (Bean et al., 2007). Considering the
reduced total volume of PP effluent compared to asphalt runoff, the potential negative impacts of
high pH may be justified by a reduction in heavy metal concentrations, particularly as the PP ages
and pH of effluent decreases and stabilizes.
Drake et al. (2012) observed that PC effluent was highly alkaline during the first year of monitoring
after construction of a PP parking lot, but that it decreased with time. This indicates that less
calcium carbonate and other species which buffer pH are present in the effluent. The potential
impact on receiving waters of high pH effluent early in the life of some PP's, or measures to
mitigate these impacts, have not been investigated.
14
2.2.3 Heavy Metals
Common sources of heavy metals in urban environments are from vehicles, and exhaust (Fach &
Geiger, 2005). MOECC has PWQO’s for most heavy metals, for the protection of aquatic life
(MOECC, 1994). Recent studies show a reduction of heavy metal concentrations in PP effluent
compared to asphalt runoff by more than 50% (Drake et al., 2013). Metals can be in either
dissolved or particulate form in infiltrated stormwater. Mechanical filtration occurs through
interception and sedimentation of solid particles, therefore metals are removed most easily from
PP effluent when in particulate form. PP effluent typically has increased pH, which encourages
the precipitation of metals into particulate form (Bean et al., 2007, Sansalone & Teng, 2004), and
improves the removal efficiency for heavy metals in PP systems.
Fach & Geiger (2005) studied the effect of various PP surfacing materials and aggregate subbase
materials on the removal of heavy metals under controlled laboratory conditions. When excluding
an aggregate subbase, they observed that PICP with a crushed brick infill was more effective at
removing heavy metals than PICP with infiltration pores (Fach & Geiger, 2005). However, over
the entire pavement structure including subbase, removal efficiency of heavy metals was the same,
at over 99% (Fach & Geiger, 2005). Drake et al. (2014) observed lower removal efficiencies of
heavy metals, 65 to 93% for Cu, Fe, Mn, and Zn loadings. PP effluent can also contain heavy metal
contaminants which are not present in asphalt runoff, such as Al in PC effluent (Drake et al., 2014).
This indicates leaching of metals from the PP. Brattebo & Booth (2004) noted especially high
removal efficiencies in the median/mean concentrations of Cu and Zn, noting that asphalt
concentrations always had measureable Cu and Zn concentrations, while Cu and Zn concentrations
were below detectable limits in 72% and 22% of samples, respectively. Roseen et al. (2012) also
noted reduction in the concentration of heavy metals due to PP.
Sansalone & Teng (2004) studied the effect of an iron oxide coated engineered medium as a
subbase in a PC system on a highway, and found that it improved the retention of heavy metals
due to a higher surface area of the medium. However, it was noted that the iron oxide coating
dissolved under anaerobic conditions, and therefore increased iron concentrations in PP effluent
(Sansalone & Teng, 2004). This result demonstrates the potential for remobilization of heavy
metals which are captured in a PP system as the conditions and chemistry of the system change,
however, understanding of the potential for remobilization as PP's age is poor.
15
2.2.4 Nutrients
Nutrients are common contaminants in stormwater and consist of various species of nitrogen and
phosphorus. Excess nutrients from runoff contribute to eutrophication in lake and streams. The
interim PWQO for total phosphorus is 0.03 mg/L (MOECC, 1994). Guidelines for nitrogen include
the PWQO of 0.02 mg/L for unionized ammonia (MOECC, 1994), and the CWQG of 3 mg/L and
45 mg/L for nitrite and nitrate species, respectively (Health Canada, 2014). Study results vary, but
generally there is a reduction of both total nitrogen (TN) and total phosphorus (TP), but increased
concentration of some nitrogen and phosphorus species.
Roseen et al. (2012) observed no significant change of nutrient concentrations when comparing
PP effluent to asphalt runoff. Bean et al. (2007) showed a decrease in ammonia based nitrogen and
TN concentrations, but an increase in nitrate. The increase of nitrate is attributed to nitrification
by biological processes under aerobic conditions within the PP structure (Bean et al., 2007).
Collins et al. (2010) also observed a decrease in ammonia and TN (mostly a reduction of ammonia
concentration), and an increase in nitrate. As with Bean et al. (2007), the increase in nitrate was
attributed to conversion of ammonia to nitrate in an aerobic environment. Jaber (2015) observed
the same increases in nitrate and reductions in other nitrogen species.
As with other studies, Drake et al. (2014) observed a reduction in ammonia species and TN
concentrations, amounting to a reduction of mean TN concentration in PP effluent of 47%, but an
increase in nitrate concentrations. Among three PP types, median TN concentrations of effluent
were between 0.8 to 1.1 mg/L, while the median concentration for asphalt runoff was 1.3 mg/L.
The remaining nitrogen in PP effluent was found to be primarily organic nitrogen and nitrates. The
primary removal mechanism of nitrogen in PP is filtration of particulate nitrogen, the remaining
nitrogen species can only be transformed, primarily to nitrate (Drake et al., 2014).
Due to its high solubility (Pitt et al., 1996), nitrate is unlikely to be retained within a PP structure.
Roseen et al. (2012) observed no reduction in nitrate concentrations, which was attributed to the
absence of vegetation in the PP system being studied. The addition of a sand layer within the PP
structure has been found to reduce nitrate concentrations, because there is a greater surface area
for biological activity to take place (Collins et al., 2010). Denitrification of nitrate to nitrogen gas
can only occur under anaerobic conditions (Drake et al., 2014).
16
Brown et al. (2012) observed a significant increase in several nitrogen and phosphorus species in
effluent from a treatment train process consisting of a PC parking lot with a bioretention cell, when
compared to asphalt runoff. The increase was attributed to a seasonally high groundwater table at
the bioretention cell, which added to the nutrient load. Groundwater inflow into the bioretention
cell caused higher nutrient concentrations in the effluent, despite the installation of an impermeable
liner (Brown et al., 2012). Nitrate is extremely soluble in water, and is the most common
contaminant in groundwater (Pitt et al., 1996). The potential exists for migration of nitrate up into
the PP subbase. Subsurface LID systems like PP’s are not suitable where groundwater is present
due to the possible mobilization of additional pollutants, particularly nutrients, unless an
impermeable liner can be used to prevent migration of groundwater into the subgrade.
Removal of phosphorus from stormwater is difficult (Roseen et al., 2012). It is removed in PP
effluent through filtration and geochemical sorption (Drake at al., 2014). Roseen et al. (2012)
observed no significant reduction of total phosphorus in PP effluent. Brown et al. (2012) reported
that mean/median TP concentrations were nearly double in PP effluent when compared to asphalt,
although this site also had a bioretention cell and was influenced by groundwater. Jaber (2015)
observed increased TP and orthophosphate concentrations in PP effluent. Drake et al. (2012) noted
that PC effluent contained high levels of phosphates during the first year of monitoring after
construction of a PP parking lot, although they decreased with time, indicating there may be some
phosphate leaching from the PC. Additional monitoring at the same study site indicated that
phosphate concentrations remained high in PC effluent, and that use of PICP resulted in a higher
removal efficiency of TP (81%) than PC (9%).
2.2.5 Hydrocarbons
Hydrocarbons are common pollutants in urban environments. Common sources of hydrocarbons
on paving surfaces are fuels, exhaust, tire particles and oils (Rushton, 2001). They are removed
primarily through biological processes:
“Microorganisms convert hydrocarbons to CO2 and water in the presence of moisture, given
sufficient nutrients, oxygen, and time.” (Atlas, 1981 as referenced in Newman et al., 2002).
PPs are capable of producing the above conditions necessary for hydrocarbon removal, and are
therefore capable of treating stormwater for hydrocarbons, given enough time and a supply of
17
nutrients. Other studies report that nutrients are present in infiltrated stormwater (See Section
2.2.4), so time and bacterial growth should be the only limiting factor in hydrocarbon removal.
Total oil and grease and mineral oil and grease are commonly used indicators of hydrocarbon
concentration. Total oil and grease provides a measure of all hexane extractable materials,
including animal fats and oils, and petroleum hydrocarbons (Pawlak et al., 2008). Mineral oil and
grease excludes most natural oils and greases, which provides a measure of primarily petroleum
hydrocarbons such as heavy fuels and oils (Pawlak et al., 2008). Mineral oil and grease is a
component of total oil and grease, and thus the concentration of mineral oil and grease is always
smaller.
Under controlled laboratory conditions with the addition of microbes and fertilizers (nutrients) to
a PP test cell, Pratt et al. (1999) observed an average removal efficiency of mineral oil of 97.6%.
In a later study under similar conditions, Newman et al. (2002) demonstrated that the addition of
microbes was unnecessary for mineral oil removal. The native microbial population was sufficient.
However, the addition of fertilizers was necessary to facilitate adequate microbiological growth
(Newman et al., 2002). The use of slow release fertilizers was recommended in order to control
nutrient concentrations in PP effluent (Pratt et al., 1999). However, some studies have shown
adequate hydrocarbon removal under field conditions without the addition of fertilizers, likely due
to the presence of nutrients in the environment.
Most studies where hydrocarbons are measured report concentrations below detectable limits
(Drake et al., 2013). In a LID parking lot system with impervious and pervious pavements and
swales, it was found that concentrations of polycyclic aromatic hydrocarbons (PAHs) were
significantly lower in PP outflows, and some values were near toxic levels for impervious
pavement (Rushton, 2001). Drake et al. (2014) observed almost no oil and grease in PP effluent.
7% of PP effluent samples had detectable oil and grease concentrations and 84% of asphalt runoff
samples had detectable oil and grease concentrations, and PAHs were rarely detected in PP effluent
(Drake et al., 2014). Hydrocarbon removal in PP's has been well documented.
2.2.6 Road Salts
In cold climates, the use of de-icing salts on pavement surfaces during winter conditions introduces
other contaminants to runoff, including sodium and chloride. They are used even though chloride
18
is known to have a harmful effect on the environment and aquatic life (Borst & Brown, 2014b).
Most PP studies do not report salt concentrations, because many are located in warm climates
where salts are not contaminants of concern in stormwater runoff. The studies that do report
chloride concentrations show zero removal of chloride due to PPs. For example, Roseen et al.
(2012) reported no removal for chloride. PPs cannot be expected to remove chloride, because it is
highly soluble.
PPs do however alter the timing of the discharge of chloride. Drake et al. (2012) reported that
chloride concentrations of PP effluent were seasonally “muted”. During the winter, it was observed
that PP effluent had much lower chloride concentrations than snowmelt from asphalt, but in the
summer, chloride concentrations of PP effluent were higher than asphalt runoff, although still
relatively low. Borst & Brown (2014b) observed high chloride concentrations during the first
rainfall after a snow fall event, and decreasing concentrations with each rainfall after the previous
snow event. This indicates that transport of chloride is slowed by the PP system, and flushed out
over an extended period with each rainfall following road salt application. PP’s with high
infiltration rates, such as PC, tend to have higher initial chloride concentrations after the snowfall
event, because they release water (and chloride) more quickly (Borst & Brown, 2014b). The
potential impact on receiving waters of the relatively slow release of salts has not been determined.
Dissolved salts are very mobile, and studies have shown increasing chloride and sodium
concentrations with depth in groundwater systems (Pitt et al., 1996; Borst & Brown, 2014b). The
transportation of salts in infiltration stormwater controls such as PP are poorly understood (Borst
& Brown, 2014b), but are of particular concern in cold regions where de-icing salts are used.
Migration of salts into groundwater systems could have negative implications on groundwater fed
drinking water systems, and this impact has not been quantified for PP's.
2.3 Permeable Pavement Water Quantity Effects
Some of the key factors in the evaluation of a stormwater management control are the effect of the
control on the magnitude of peak outflows, total outflow volumes, and time to peak flows. Control
of these three parameters (often called quantity control) is critical to establish more natural
hydrologic conditions within a watershed. Quantity control is often regulated for new
developments. For example, NPCA requires control of peak flows such that post-development
19
peak flows do not exceed pre-development flows for storms up to a return period of 100 years
(AECOM, 2010).
In this section, the observations and conclusions related to quantity control of PPs is discussed for
the literature reviewed for the chapter. The quantity control effectiveness of a PP varies, and
depends on several factors, especially the permeability of native soils, type and condition of PP
surface, and the design of the parking lot itself (e.g. impermeable liners, subdrains). Most PP
research sites are partial exfiltration systems, in part because underdrains are required to collect
PP effluent to conduct water quality analysis, so this section focuses mostly on partial exfiltration.
Full exfiltration systems are typically only used on sites with high permeability native soils. Only
one zero exfiltration system was reviewed for this chapter.
2.3.1 Full and Partial Exfiltration Systems
For full and partial exfiltration systems, the permeability of the native soils may have an effect on
quantity control for a PP system. Low permeability soils include silts and clays and high
permeability soils are sands and gravels which are likely to drain freely. Reported outflows are
measured in the underdrains of the PP or partial exfiltration parking lots, or surface runoff can also
be collected and measured in full and partial exfiltration systems. The quantity control benefits of
PP's are well established for full and partial exfiltration systems.
2.3.1.1 High Permeability Native Soils
Studies of PP systems with high permeability native soils all show significant runoff reductions.
Booth & Leavitt (1999) observed almost no surface runoff during the first year of monitoring at a
PP parking lot. After an additional five years of monitoring, Brattebo & Booth (2003) observed
surface runoff to be a maximum of 3% of total rainfall volume for any storm event. At another
site, Hunt et al. (2002) observed runoff only for very intense storms in excess of 43 mm/hr. It was
concluded that runoff from a full exfiltration PP with high permeability native soils is dependent
on rainfall intensity, not on rainfall volume (Hunt et al., 2002).
Bean et al. (2007) studied four PP sites in North Carolina and observed very high runoff reductions
over high permeability native soils. For example, at one site 48 storm events were monitored, and
only 11 produced any surface runoff at all (Bean et al., 2007). It was concluded that events which
20
produced runoff likely had rainfall intensities greater than the infiltration capacity of the PP (Bean
et al., 2007).
In an LID treatment train system with PPs and a bioretention cell, peak flow reductions for a PP
underdrain of nearly 100% percent were observed, despite the influence of a high groundwater
table (Brown et al., 2012). This demonstrates that PPs can be part of a robust stormwater
management system which uses multiple LID strategies. This study recommended that it may be
possible to direct surface runoff from surrounding areas to PP parking lots, because they are
capable of infiltrating more rainfall than would ever fall directly on the parking lot (Brown et al.,
2012).
Wardynski et al. (2013) investigated the effect of elevated underdrains in a partial exfiltration
system over sandy loam soils. They determined that volume reductions of nearly 100% could be
achieved by ripping native soils, and elevating underdrains by 15 to 30 cm above the native soil.
2.3.1.2 Low Permeability Native Soils
Even with low permeability native soils, and limited exfiltration, studies commonly demonstrate
the quantity control benefits of PPs. Drake et al. (2012) observed significant reductions in PP
outflows compared to asphalt runoff. Total outflow volume was reduced by 43%, average peak
flows were reduced by 91%, and the average attenuation of a storm event was 14 hours (Drake et
al., 2012). Storm events under 7 mm produced no outflow at all (Drake et al., 2012). For a highway
system, Sansalone & Teng (2004) also found that a partial infiltration system provides volume
control, peak flow control, and lag time to peak flows.
Collins et al. (2008) observed large surface runoff reductions of at least 98% for PP and the mean
volume reduction for PC was 44% for total rainfall depth. Total PP outflow volume was
occasionally higher than asphalt runoff volume, likely due to the influence of groundwater (Collins
et al., 2008). For PP parking lots in areas with seasonally high groundwater tables, impermeable
liners may be necessary. The study recommended raising the elevation of underdrains, to allow for
more infiltration, and storage of stormwater within the aggregate base. It was also observed that
the aggregate medium type had an effect on total outflow, and the use of sand instead of gravel
increased retention of stormwater in the system (Collins et al., 2008).
21
Fassman & Blackbourn (2010) studied quantity control of PP on a road, and only observed surface
runoff occurring for events with rainfall intensities greater than 16 mm/hr. Runoff at relatively low
rainfall intensity was attributed to the road having a steep 6% slope. Outflows from underdrains
were approximately the same as modelled pre-development flows for 75% of all measured events
(any event less than 20 mm) (Fassman & Blackbourn, 2010). Storms with a total depth less than 7
mm had no outflow at all from the PP underdrains (Fassman & Blackbourn, 2010). It was noted
that even if the antecedent dry period was short and the subgrade was wet, PP still attenuated runoff
due to the longer tortuous flow path through the subgrade (Fassman & Blackbourn, 2010).
Tyner et al. (2009) further demonstrated significant increases in exfiltration rates for clay soils
when the native soil was treated during construction by ripping, adding boreholes, or trenching.
All these studies demonstrate that even with less than ideal conditions due to low permeability
soils, PPs can still be an effective stormwater management practice for quantity control.
2.3.2 Zero Exfiltration Systems
Zero exfiltration PP systems feature an impermeable membrane between the gravel aggregate layer
and native soil, to prevent any infiltration of stormwater into the native soil, or groundwater into
the PP aggregate. Rainfall volume reduction is still possible due to evaporation. Under laboratory
conditions, Syrrakou & Pinder (2014) found that the evaporation rate from PP columns began at
about 0.02 mm/h, and decreased non-linearly with time, as the water evaporated. Evaporation rates
in an actually parking lot, may be higher or lower at times, due to different temperature conditions,
and exposure to sunlight.
Zero-exfiltration systems are not common in modern PP designs, and therefore very few studies
have been conducted utilizing these systems. The environmental performance of a zero exfiltration
system is poorer than full or partial-exfiltration systems, but they may be advantageous for research
purposes, because it is likely that more infiltrated stormwater will be collected in underdrains for
sampling purposes, and the effects of native soil permeability can be eliminated to evaluate other
aspects of the PP system. They may be implemented in areas with elevated groundwater tables, to
prevent migration of groundwater into the PP sub base. Despite having no exfiltration, Pratt et al.
(1989) still observed an average peak flow reduction of 70% for individual storm events. The use
of aggregates with higher surface areas resulted in higher runoff reductions (Pratt et al., 1989). The
22
hydrologic performance of zero-exfiltration systems is poorly understood, because so few studies
have been conducted on these systems.
2.4 Barriers to Implementation of Permeable Pavements
Current literature demonstrates that PPs are capable of providing significant stormwater
management benefits, including improvements to water quality and positive hydrologic impacts.
However, traditional asphalt surfaced parking lots are still much more common for new
developments. One reason for the lack of adoption of PPs is uncertainty of developers, the public,
and government. Some of the more obvious areas of uncertainty include economics, infiltration
capacity, and maintenance requirements. This section presents findings of studies which have
attempted to address these barriers to implementation.
There are additional concerns specifically associated with implementation of PPs in cold climates.
Developers have been reluctant to implement LID due to concerns over frozen filter media, high
chloride loading, and dormant biological functions (Roseen et al., 2009).
2.4.1 Permeable Pavement Economics
Economics often drive decision making when it comes to implementation of new technologies.
The economic costs and benefits of PPs are not well understood. Currently the initial capital costs
to surface a parking lot with PP are higher than the costs to surface with asphalt (Booth and Leavitt,
2003). Hunt et al. (2002) estimated that the cost to construct a PP parking lot is 25% higher than a
traditional asphalt lot. The cost of PP may be less than asphalt if the costs of drainage systems and
connections to sewer systems are considered (Booth and Leavitt, 2003), but no detailed estimates
have been published to demonstrate this.
In addition to the initial construction costs, the ultimate costs of pavements to a property owner
are determined by the service life length of the pavement, and the maintenance costs. The service
life of PP (or any system) ends when it fails to function as intended. PPs can fail by loss of
infiltration capacity, loss of structural integrity, and loss of pollutant removal capacity or
remobilization of pollutants (Drake et al., 2013). Current literature has not adequately
demonstrated the service life that can be expected from PPs in regards to infiltration capacity and
pollutant removal capacity, because long term studies have not been carried out, or are not yet
complete (See Table 1). However, early results show that PPs can maintain adequate infiltration
23
capacity when they are well designed and maintained. Loss of structural integrity has become less
of a concern, even for poured PPs, because mix designs have improved (Roseen et al., 2012).
Winter durability under freeze-thaw conditions is good for PPs, because the pavement and subbase
are designed to be free draining and hold very little moisture, and are therefore less susceptible to
frost effects (Tyner et al., 2009, Roseen et al., 2012). When designed accordingly, PPs are even
capable of supporting occasional heavy loads, such as emergency fire fighting vehicles used at
airports (Knapton & Cook, 2003).
After identifying the perceived requirement of maintenance costs of LID as a barrier to
implementation, Houle et al. (2013) compared the maintenance costs of several LID options to
traditional stormwater management systems such as wet and dry ponds. PA was found to have
lower annual maintenance costs than traditional stormwater management systems, and
preventative maintenance was less expensive than reactive maintenance (Houle et al., 2013). The
maintenance cost in terms of TSS load reduction was also low for PA (Houle et al., 2013). This
study suggests that PPs can perform better than traditional stormwater management systems for
lower maintenance costs, but additional research is needed to determine long term costs, and costs
of other types of PPs.
2.4.2 Maintenance
Maintenance of PPs is carried out to remove fines embedded in the surface of the pavement, in an
effort to improve infiltration capacity of the pavement. Property owners often do not maintain PP
parking lots, and the surface may become clogged. This helps reinforce the thought that PPs cannot
maintain surface infiltration capacity over the service life of the pavement (Drake et al., 2013).
Poor understanding of the economic cost of maintenance has been addressed in the previous
section. However, the maintenance methods, and the effectiveness of that maintenance have been
addressed in the literature, as discussed in this section.
In order to determine how often maintenance is required for PP parking lots, the surface infiltration
capacity must be determined. The most common methods for measuring infiltration rates of PPs
are ASTM C1701 and ASTM C1781, or some modified version of these methods. Drake et al.
(2012) observed a median reduction of surface infiltration capacity over two years from 70 to 87%
for PICP, and a median of 43% for PC. Despite these reductions, the PPs were still capable of
infiltrating all stormwater (no surface runoff). PC still had a very high infiltration capacity after
24
two years of 1,072 cm/hr (Drake et al., 2012). After 1.5 years of service, Roseen et al. (2008) still
observed very high infiltration rates for PP surfaces, usually greater than 150 cm/hr. Large
variations in surface infiltration measurements are typical (Brown & Borst, 2014a), so multiple
measurements are necessary to determine when maintenance is required. Haselbach & Werner
(2015) observed that PC maintained more than sufficient infiltration capacity after 2 to 4 years of
operation with little to no maintenance, and that only areas subject to additional run on tended to
clog.
Recommendations regarding frequency of maintenance are varied. The Interlocking Concrete
Paving Institute recommends performing maintenance when infiltration rates are below 250 mm/hr
(Drake & Bradford, 2013). Hunt et al. (2002) recommended performing maintenance every 9 to
12 months. Frequency of maintenance depends on several factors, including the initial
permeability of the PP, the amount of debris transported from surrounding areas (e.g. leaf litter,
soil), and materials used for winter maintenance (Henderson & Tighe, 2011). In cold climates,
maintenance prior to every freeze-thaw season is recommended to reduce raveling of PC
pavements (Henderson & Tighe, 2011). Less maintenance is required for poured PP products than
for paving stones, although maintenance may not be able to effectively remove fine material which
becomes embedded within the PP pores (Drake & Bradford, 2013). Sansalone & Teng (2004)
observed that most particulate material is trapped near the surface of PC, where it may be easier
to remove. Research completed to date does not demonstrate that maintenance can provide
sufficient infiltration capacity in the long term for PICP (Drake et al., 2013), but early results from
short term studies are promising. The effectiveness of maintenance for poured products such as
PC has not been sufficiently demonstrated.
There are several techniques which have been implemented to maintain PPs and restore infiltration
capacity. These include vacuuming, sweeping, power washing, and washing with hoses of various
nozzle diameters (Henderson & Tighe, 2011). Studies which have assessed maintenance
techniques each provide different observations as to which technique is the most effective. In a
detailed study involving five sites across Canada, Henderson & Tighe (2011) suggested that using
a hose with a large diameter nozzle to wash PPs was the most effective method to restore
infiltration capacity. They noted that power washing may actually reduce infiltration capacity by
forcing fines deeper into the PP (Henderson & Tighe, 2011). Hunt et al. (2002) observed acceptable
25
restoration of infiltration capacity by performing annual sweeping. Drake & Bradford (2013)
observed vacuum sweeping to be the most effective maintenance method.
Cold climates with below freezing temperatures and snow and ice conditions introduce additional
maintenance requirements for any paved surface. For PPs, traditional winter maintenance such as
sanding, salting, and ploughing, may not be suitable. In particular, applying sand is not suitable
for PP surfaces because the particles may be forced down into pores and spaces in PPs, reducing
the infiltration capacity (Drake et al., 2013). In a comparison of winter maintenance requirements
between PPs and traditional asphalt, Houle et al. (2010) observed that PA required an average of
75% less salt to maintain a safe surface. When ice buildup requiring salting on asphalt due to thaw
and refreezing was an issue, no additional salt was required on PPs, because the melt water
infiltrated through the surface, rather than ponding as on asphalt (Houle et al., 2010).
Very little difference has been reported between summer and winter infiltration capacity of PPs,
because frozen PP tends to thaw before or during an event (Roseen et al., 2009). PP likely thaws
quickly because it holds very little moisture, and therefore has low heat capacity. PPs have been
shown to remain capable of infiltrating all precipitation during winter conditions, and produce
essentially no runoff (Roseen et al., 2012). There has not been a great deal of winter maintenance
research conducted for PPs, but the literature suggests that less maintenance may be required than
for asphalt, due to less sanding and salting.
26
Chapter 3 Methodology
METHODOLOGY
3.1 Study Site
The study site is located at 383 Lake Street, in St. Catharines, Ontario, Canada (Figure 3 and
Figure 6). Note that the aerial imagery from Figure 6 was taken prior to construction of the PP
parking lot. The property is owned by the City of St. Catharines, and is the site of the Lake Street
Service Centre (LSSC). Among other things, LSCC functions as a maintenance and storage facility
for city equipment, storage for road salt and sand, and office space for city staff. The parking lot
is used primarily as space for city staff to park their personal vehicles, and receives no regular
heavy vehicle traffic from city equipment. There are 156 parking spaces, including 25 Hydromedia
spaces, and 55 asphalt spaces. The lot is typically filled to near capacity during working hours,
particularly near the east end of the lot, closest to the office entrance. Lake Street is a major road
within the city, and the surrounding area is urbanized.
Figure 3. Lake Street Service Centre Study Site Location
27
Considerations were included in the design of the Lake Street lot to allow for monitoring and
sampling of stormwater flows. Construction was completed in 2011, but no major monitoring had
been conducted prior to the beginning of this project in summer 2014, when Lafarge initiated the
study in partnership with the City and the University of Toronto (U of T). The parking lot consists
of four different cells, each with a different type of pavement, including three PP products (Porous
asphalt, Hydromedia, Eco-Optiloc paving stones), and conventional asphalt (Figure 4). The scope
of this study only includes monitoring of Hydromedia and asphalt pavements.
Figure 4. Lake St. Service Centre Test Parking Lot Schematic (Plan View)
The pavement structure of the Hydromedia section of the parking lot is similar to other PP designs
(Figure 5). The design includes a 150 mm thick layer of Hydromedia overlying 350 mm of 19 mm
nominal size clear stone aggregate. The clear stone layer is freely draining to allow infiltrated
stormwater to pass through the void space. At the centre of each PP section, and along the
downstream edge, subdrains are located within trenches at the bottom of the clear stone layer.
Subdrains are 100 mm diameter perforated pipe within a geotextile sock, and they collect water as
the clear stone layer saturates.
28
Figure 5. Lake Street Service Centre Permeable Pavement Subgrade Design
When the parking lot was originally constructed in 2011, the concrete delivered to site was not
mixed as specified. This caused poor bonding of the concrete aggregate matrix, and a large amount
of cement migrated down into the clear stone aggregate, and possibly out through the subdrains.
The poorly bonded concrete was ripped up, and a new layer of Hydromedia was poured to
specification. Residual cement in the clear stone layer and underdrains was not removed prior to
placement of the new concrete surface.
Beneath the pavement structure and subdrains, an impermeable high density poly-ethylene
(HDPE) liner was installed to prevent exfiltration of water into the native subsoil. Therefore the
LSSC lot is classified as a zero exfiltration system. Monitoring studies of zero exfiltration systems
are not common in the literature, as the purpose of a PP parking is most often to infiltrate as much
stormwater into the native soil as possible. The City of St. Catharines selected a zero exfiltration
system at this site to ensure that the subdrains would generate sufficient volume of water for
sampling. The liner also hydraulically isolates each pavement cell, preventing migration of water
from one cell to another within the subsurface.
29
Figure 6: Plan View of Study Site (Image Date: 2010)
30
The Hydromedia and asphalt cells of the parking lot each have a design area of 580 m2. Like the
other PP cells, all stormwater that infiltrates through the Hydromedia surface collects within the
PP or clear stone layer, and subsequently exits through the subdrains. Water collected in the
subdrains is referred to in this thesis as Hydromedia effluent. Effluent is conveyed to a sampling
catch basin (Figure 4). The catch basin entrance is 0.6 m by 0.6 m. Effluent which collects in the
catch basin then passes through an outlet and is discharged to the municipal storm sewer system
(Figure 7). Surface runoff from the Hydromedia cell has not been observed to date by city staff or
U of T personnel (all stormwater is infiltrated), but any potential surface runoff passes through a
concrete outlet to a swale.
Figure 7. Photo of Hydromedia sampling catch basin - looking down into catch basin (April
28, 2014)
The outlet to the storm sewer is fitted with a restrictor valve which can limit the flow rate of effluent
leaving the system. When the valve is closed, or partially closed, effluent backs up and is stored
within the void space in the clear stone layer. The restrictor valve could be used to reduce peak
flows and slowly release effluent, but it has been left open for the duration of this study, and
effluent has been allowed to flow freely.
31
3.2 Field Scale Methodology
This section describes the methods used to study the performance of the LSSC parking lot in the
field, at full scale. Additional experimentation to assess water quality performance was conducted
under laboratory conditions, and is described in Section 3.3.
3.2.1 Infiltration Capacity Measurement
Measurement of surface infiltration capacity was carried out on June 30, 2014, using a modified
version of ASTM C1701. The procedure involved temporarily sealing a metal cylinder to the
pavement surface, and measuring the time required for a known volume of water to infiltrate
through the surface at a constant head (Figure 8). A total of eighteen measurements were made,
spread over the entire Hydromedia cell area. Eight measurements were made within the parking
spaces, and ten measurements were made in the centre driving lanes.
Figure 8. Photo of infiltration testing on Hydromedia surface. Test being conducted to left
and infiltration ring temporarily sealed to surface on right. (June 30, 2014)
Two tests were performed at each location. The first test was a prewetting test, where 3.6 kg of
water was poured into the infiltration ring while maintaining a constant head of 10 to 15 mm above
the pavement surface. The time required for all water to infiltrate was recorded. The second test
was used to determine the infiltration rate, and was similar to the prewetting test, only with a larger
volume of water. If the prewetting test took less than 30 seconds, 18 kg of water was used. If the
32
prewetting test took 30 seconds or longer, 3.6 kg of water was used. Measurement locations were
considered to “fail” where the first test took longer than 30 minutes, or where the second test took
longer than 90 minutes. A failed test indicates that the pores within the pavement have become
clogged at that location. These practices were established by Drake et al., 2012. For this project,
failed tests were conservatively assigned an infiltration capacity of zero.
Infiltration capacity was determined for each test location using Equation 6 (ASTM, 2009):
𝑰 = 𝒌𝑴
𝑫𝟐𝒕 Equation 6
Where: I: surface infiltration rate (mm/h)
k: 4,583,666,000 𝑚𝑚3.𝑠
𝑘𝑔.ℎ
M: mass of water (kg)
D: inner diameter of infiltration ring (mm)
t: drainage time (s)
The mass of water was determined volumetrically, assuming a density of water of 1,000 kg/m3.
This test is not intended to simulate rainfall, but to compare with other PP studies, and to simulate
a situation where surface ponding occurs. The average and median surface infiltration rate over
the surface of the Hydromedia cell was compared to design rainfall intensities from local intensity-
duration-frequency curves for the city of St. Catharines. All rainfall is expected to infiltrate if the
measured infiltration rate is greater than the expected rainfall intensity. If the rainfall intensity is
greater than the infiltration rate, there is a high probability of surface ponding or runoff.
3.2.2 Hydromedia Effluent Outflow and Rainfall
3.2.2.1 Flow Measurement Apparatus
A V-notch weir system was selected to measure the flow rate of Hydromedia effluent. V-notch
weirs allow measurement of a wide range of flow rates, which was ideal because prediction of
outflows from a zero exfiltration system was difficult, given the lack of literature available on zero
exfiltration systems. V-notch weirs have also been successfully implemented in several other PP
studies (Bean et al., 2007; Collins et al., 2008; Collins et al., 2010; Hatt et al., 2009; Hunt et al.,
2002; Fassman & Blackbourn, 2010). The only practical location to measure outflow was in the
sampling catch basin, at the effluent outlet. This meant that the design and sizing of the weir system
was constrained by the size of the sampling catch basin.
33
The flow measurement system was designed and constructed as a weir box (Figure 9). The box
itself was constructed of ½” plywood, measuring 500 mm long, 400 mm wide, and 450 mm deep.
At the rear of the box, a 100 mm diameter hole allows the weir box to be connected to the
Hydromedia effluent outlet in the catch basin. Three baffles dissipate the energy of the flow as it
enters the box to reduce turbulence. A 30o sharp crested V-notch weir made of stainless steel is
fastened at the front of the box. The maximum head over the weir was designed to be 0.15 m, and
the weir was designed to have a 0.15 m deep permanent pool. The inside of the box was painted
with marine paint to reduce rotting of the wood, since the box is designed to hold a permanent
pool, and the wood on the inside of the box is partially submerged at all times. A detailed design
drawing of the weir box is included in Appendix A.
Figure 9. Photos of weir box prior to installation. Front view to left, rear view to right. (June
26, 2014)
The weir box was installed in the sampling catch basin on July 4, 2014, and continuous monitoring
of effluent outflow began at this time (Figure 10). The weir box was removed on November 20,
2014, at the end of the monitoring period. Installation of the weir box was difficult due to the small
space inside the catch basin. A rubber pipe collar extension was sealed to the effluent outlet pipe
using marine caulking, to direct all flow from the pipe into the weir box. Four wood legs were
attached to the sides of box (Figure 11), and the box was lowered down into the catch basin. The
weir box was connected to the effluent outlet pipe using the rubber collar.
34
Figure 10. Photo of weir box looking down into the catch basin (August 27, 2014)
Figure 11. Painted weir box with legs attached prior to installation (July 4, 2014)
Water level over the weir was measured at five minute intervals using two HOBO U20 water level
loggers with a measurement accuracy of ± 3 mm. One logger is located immediately after the
baffles in a perforated pipe, and one is in the open air to measure barometric pressure (Figure 10).
35
3.2.2.2 Flow Measurement Calibration
Due to schedule constraints, the weir box was not calibrated prior to installation. With no
calibration available to relate head over the weir to flow rate, the flow rate was initially
approximated using Equation 1. This equation only provides an accurate estimate of flow rate if
the head over the weir is greater than 5 cm, and when the upstream distance where the head is
measured is at least 3 times the head (Adkins, 2006). In this weir box, the head is measured 26 cm
upstream of the weir. Therefore, Equation 1 was only expected to provide a reliable approximation
of flow when the head was between 5 and 8.7 cm.
The weir box was removed from the catch basin on November 20, 2014, and transported to the U
of T. On January 14, 2015, the weir box was taken to Good Harbour Laboratories, in Mississauga,
Ontario, to conduct the calibration. The laboratory is equipped to deliver water at flow rates at
least as high as any flow observed during the entire monitoring period at the LSSC. The purpose
of the calibration was to develop as accurate a relationship as possible between the head measured
in the weir box and flow rate.
The experimental apparatus consisted of a pump connected to a large reservoir, with a hose
delivering water to the weir box inlet (Figure 12). The reservoir was large enough that the head in
the tank was essentially constant, and the pump was able to deliver a consistent flow rate to the
weir box. Flow rate from the pump was measured using an electromagnetic flow meter between
the pump and weir box. Head in the weir box was measured with a ruler, and water discharged
over the weir was collected in a basin and drained (Figure 13).
36
Figure 12: Weir calibration apparatus at Good Harbour Laboratories (January 14, 2015)
The calibration procedure was carried out as follows:
1. Maintain constant head in reservoir.
2. Pump water from reservoir through pipe and hose to weir box inlet.
3. Allow sufficient time for steady state conditions to be reached in weir box.
4. Once steady state is reached, record head over weir using ruler.
5. Record flow rate using Toshiba electromagnetic flow meter.
6. Repeat 1 through 5, while adjusting pump valve to achieve different flow rates which cover
entire range of weir box heads.
37
Figure 13: Weir box connected to hose, discharging to basin (January 14, 2015)
3.2.2.3 Rainfall Measurement
Rainfall was measured at a weather station located at 190 Linwell Road, approximately 800 m
north of the LSSC parking lot. The station records rainfall depth at five minute intervals, to an
accuracy of 0.25 mm. Rainfall depth and intensity were used to determine expected asphalt runoff
volume and discharge rate. For each rainfall event, expected asphalt runoff volume and peak
discharge were compared to Hydromedia effluent outflow. A rainfall event was defined as any
measured rainfall preceded and followed by a minimum dry period of 18 hours. This minimum
dry period was selected because every effluent discharge event required at least an 18 hour dry
period before the discharge decreased to zero.
3.2.2.4 Hydrologic Data Analysis
Asphalt runoff was not measured at this site, so asphalt runoff was approximated using the rational
method. Expected asphalt runoff rate was determined according to Equation 7:
𝑸𝑨𝒊= 𝑪𝒊𝒊𝑨 Equation 7
Where: QAi: expected asphalt runoff rate (m3/s)
ii: measured rainfall intensity (m/s)
38
A: drainage area (m2)
C: runoff coefficient (0.95 for asphalt)
Expected asphalt runoff volume was then determined from the expected asphalt runoff rate:
𝑽𝑨 = ∑ 𝑸𝑨𝒊 × 𝒕𝒊𝒏𝒊=𝟏 Equation 8
Where: VA: expected asphalt volume (m3)
ti: length of each rainfall interval time (s)
i: event 1, 2, 3, …, n
For high flow rates (above a weir head of 3.6 cm), the discharge rate of Hydromedia effluent was
determined using the measurements of head over the weir, and 𝑸 = 𝟖
𝟏𝟓 𝑪𝒅 √𝟐𝒈 𝐭𝐚𝐧
𝜽
𝟐 𝑯
𝟓
𝟐
Equation 1 with a discharge coefficient (Cd) of 0.58. Effluent volume was then
determined similarly as expected asphalt runoff volume:
𝑽𝑯 = ∑ 𝑸𝑯𝒊 × 𝒕𝒊𝒏𝒊=𝟏 Equation 9
Where: VH: effluent volume (m3)
QHi: measured effluent discharge rate at each time interval (m3/s)
ti: length of each time interval (s)
i: time interval 1, 2, 3, …, n
For low flow rates (below a weir head of 3.6 cm), the volume and flow rate were both increased
by a factor 1.28, to account for inaccuracy of flow measurement due to limitations of the weir at
low head. A factor of 1.28 was selected because the test results at heads less than 3.6 cm showed
an under prediction error of 28%. Note that the discharge at these low heads is very small, less
than 5.4 L/min.
Volume reductions for each flow event, and for all the storm events combined was determined
using the following:
𝑽𝑹 = 𝟏 − 𝑽𝑯
𝑽𝑨 Equation 10
Where: VR: volume reduction ratio
39
Peak discharge reductions were calculated for each flow event:
𝑸𝑹 = 𝟏 − 𝑸𝑯𝒑
𝑸𝑨𝒑
Equation 11
Where: QR: peak discharge reduction ratio
QHp: peak effluent discharge rate (m3/s)
QAp: peak effluent discharge rate (m3/s)
The lag time from peak to peak was determined for each flow event as the difference in time from
the most intense recorded rainfall, to the peak effluent discharge rate. This represents the difference
in time between the occurrence of the estimated peak asphalt surface runoff and the peak discharge
of Hydromedia effluent.
Pre-development runoff conditions were determined using a simple model developed in EPA
SWMM 5.1. The model consisted of only one sub catchment connected to a free outfall, with the
same area and geometry as the LSSC parking lot. Rainfall data from the largest single event
observed during the monitoring period (July 7, 2014) was used to run the model simulation. The
sub catchment parameters are shown in Table 2.
Table 2: EPA SWMM Model Parameters (Pre-development Conditions)
Parameter Value Parameter Value
Area (m2) 580 Depression storage for impervious (mm) 1.5**
Width (m) 25 Depression storage for pervious (mm) 5.1**
Slope (%) 1 Impervious area with no depression storage 25%*
Impervious Area (%) 5* Suction head (mm) 290***
Manning’s n for
impervious
0.011** Hydraulic conductivity (mm/hr) 1***
Manning’s n for pervious 0.24** Initial moisture deficit (assumed at wilting
point)
0.228***
* (Gironas et al., 2009), ** (Rossman, 2010), *** (Chin, 2013)
The parameters were selected assuming the predevelopment conditions were similar to that of
pasture land with dense grass, and that the native soil was composed of silty clay, since the surficial
materials in this area of St. Catharines consist of Halton Till (Feenstra, 1972). Peak runoff rates
predicted by the model for the July 7 event were compared to measured Hydromedia effluent peak
outflow to assess the hydrologic performance of the Hydromedia parking lot.
40
Multiple linear regression analysis was conducted using the statistical software package R 3.1.2
(R Core Team, 2014). Two separate response variables were considered, Hydromedia effluent
depth, and Hydromedia effluent peak discharge. Predictor variables considered in the analysis were
rainfall depth and peak rainfall intensity. All data was square root transformed such that residuals
were normally distributed. A forward analysis procedure was conducted to determine which
predictor variables were significant for each response variable (α < 0.05).
3.2.3 Water Quality
3.2.3.1 Sample Collection and Analysis
Grab samples were collected by U of T or City of St. Catharines personnel. Sampling began on
July 3, 2014 and the final sample was collected on December 17, 2014. A total of seven asphalt
runoff samples were collected, and fifteen Hydromedia effluent samples. Asphalt surface runoff
samples were collected at the outlet from the traditional asphalt cell to the swale (Figure 14).
Asphalt samples were collected before coming into contact with the swale. Obtaining grab samples
of asphalt runoff for each storm was difficult. Asphalt runoff occurs very rapidly after a storm
begins, and it stops shortly after the storm ends. Due to the flashy nature of asphalt runoff, U of T
or city personnel needed to be on site to collect a sample as the rain was falling. This was often
not possible due to the unpredictable nature of rainfall, and many storms occurring during non-
working hours. Fewer samples of asphalt runoff were collected compared to Hydromedia effluent
due to these difficulties.
Figure 14. Photo of grab sample collection point at outlet from asphalt cell to swale. (April
28, 2014)
41
All grab samples of Hydromedia effluent were collected in the sampling catch basin. One grab
sample of Hydromedia effluent was collected from the outlet pipe on July 4, 2014 before the
installation of the weir box. Two effluent samples were collected from the pool in the weir box on
July 8 and August 5, 2014, by lowering a metal sampler on a rope down into the weir box pool.
Collection from the outlet pipe was not possible because the sampler was too large and could not
fit between the baffles and outlet pipe. After August 5, 2014, all remaining effluent grab samples
were obtained by sampling directly from the outlet pipe, prior to the effluent contacting the weir
box. A smaller glass sampler was used which could be lowered between the baffles and outlet pipe
(Figure 15).
Figure 15. Photo of glass Hydromedia effluent sampler
For most events, only one sample of effluent or asphalt runoff was collected, or one sample each
of effluent and runoff. On October 3, 2014, four samples of asphalt runoff and six samples of
Hydromedia effluent were collected. Sampling times were spread out over the course of the event,
to observe variations in pollutant concentrations with time.
Immediately after collection, all samples were stored in a refrigerator at the LSSC. Samples were
then transported to Niagara Analytical Laboratories Inc. (NAL), typically on the day they were
42
collected, or the following day. The only exception was samples collected on October 3, 2014,
which were transported to NAL on October 6. All water quality testing of field samples was
conducted at NAL. Samples were analyzed for the parameters listed in Table 3. Minimum
detection limits for each parameter are also listed in Table 3.
Table 3. Water quality parameters and minimum detection limits
Parameter Minimum Detection Limit (mg/L)
pH N/A
Alkalinity as CaCO3 1
Total Suspended Solids 1
Total Oil and Grease 1
Mineral Oil and Grease 1
Total Kjeldahl Nitrogen 0.5
Total Phosphorus 0.02
Phosphate 0.06
Aluminum 0.01
Antimony 0.0001
Arsenic 0.0001
Barium 0.001
Cadmium 0.005
Chromium 0.002
Cobalt 0.005
Copper 0.002
Iron 0.005
Lead 0.02
Manganese 0.001
Mercury 0.00002
Molybdenum 0.01
Nickel 0.01
Selenium 0.001
Silver 0.005
Tin 0.05
Zinc 0.005
3.2.4 Data Analysis
Event mean concentrations (EMC’s) were determined for asphalt runoff and Hydromedia effluent
for the October 3, 2014 flow event. EMC was determined using a weighted average considering
the surface runoff and effluent flow data. For all other events, the grab sample collected was
considered to be representative of the EMC. Where possible, EMC’s for each pollutant are
compared between asphalt runoff and Hydromedia effluent by determining the removal efficiency:
43
𝑹𝑬𝒊 = 𝟏 − 𝑬𝑴𝑪𝑯𝒊
𝑬𝑴𝑪𝑨𝒊
Equation 12
Where: RE: removal efficiency
EMCH: event mean concentration for Hydromedia effluent (mg/L)
EMCA: event mean concentration for asphalt runoff (mg/L)
i: event 1, 2, 3, …, n
Descriptive statistics were calculated for Hydromedia effluent when no more than one of the fifteen
effluent samples had a concentration below the MDL. These included mean, median, minimum,
maximum, and variance for all applicable contaminants. Results were compared to relevant
guidelines for Ontario to assess performance of the Hydromedia. Provincial Water Quality
Objectives (PWQO) for the protection of aquatic life (MOECC, 1994) are the most relevant
guidelines, and when those were not available for a particular contaminant, Canadian Water
Quality Guidelines for drinking water (Health Canada, 2014) were considered.
Water quality data was obtained from a nearby study site, located at the Kortright Centre for
Conservation in Vaughan, Ontario. The study began in 2010, and is being conducted by TRCA.
The parking lot at this site contains a Hydromedia section, which was constructed in 2010, one
year before the LSSC parking lot. The Kortright lot was designed as a partial exfiltration system,
and has a more sophisticated monitoring program than at LSSC, including automated samplers.
Water quality data from 2010 to 2012 had already been published (Drake et. al., 2012; Drake et.
al. 2014). Additional unpublished data from 2013 to 2014 was provided by TRCA for comparative
analysis. Descriptive statistics for the Kortright data were calculated for all applicable pollutants,
and compared with descriptive statistics for pollutants at the LSSC. Statistics were calculated
separately from 2010 to 2012 and from 2013 to 2014, because pollutant concentrations from 2010
to 2012 are from the first three years of the parking lot life. Concentrations of several pollutants
tend to be higher early in the pavement life. No monitoring was conducted in the first three years
after construction at LSSC, so the water quality statistics obtained from this study are more directly
comparable to the Kortright statistics from 2013 to 2014.
44
3.3 Laboratory Scale Methodology
Mid way through the monitoring period at LSSC, additional questions arose regarding the water
quality as initial results from the analysis of samples of Hydromedia effluent became available.
These included unexpected high results for pH, and unexpectedly low total phosphorous
concentration (compared to observations at Kortright). Additional testing was added to the study
methodology in an attempt to address these questions. The methods for this testing are described
in this section.
3.3.1 Test Specimen Preparation and Storage
On November 6, 2014, eight specimens of Hydromedia pervious concrete were cast at the Lafarge
Innovation and Training Centre, in Toronto. Specimens were cast in 150 mm diameter cylindrical
plastic moulds, with thicknesses ranging from about 200 to 250 mm (Figure 16). After an initial
curing period of 24 hours, concrete specimens were transported to U of T and placed in a moisture
curing room. The plastic moulds were not removed, and five small holes were drilled into the
bottom of each specimen, to allow water to drain in future experiments (Figure 17).
Figure 16: Four of eight Hydromedia Test Specimens (November 10, 2014)
45
The eight specimens were to be used for laboratory experiments with duplicate tests for each
experiment, for a total of four pairs. Specimens were numbered as shown in Table 4. All specimens
were stored in the moisture curing room until December 11, 2014. On December 11, specimens 4-
A and 4-B were removed from the curing room and placed outdoors so that they would be exposed
to weather. On January 12, specimens 3-A and 3-B were permanently moved to the laboratory and
exposed to room temperature conditions.
Table 4: Specimen ID numbers and storage details
Specimen ID Storage details
1-A Curing room only
1-B Curing room only
4-A 35 days curing room, followed by outdoors
4-B 35 days curing room, followed by outdoors
7-A 67 days curing room, followed by lab
7-B 67 days curing room, followed by lab
28-A Curing room only
28-B Curing room only
Figure 17: Inverted Hydromedia specimen showing small drainage holes
46
3.3.2 pH Experiment
Water samples of effluent from Hydromedia test specimens were collected by pouring deionized
water onto the specimen surface, and collecting the effluent after draining through the concrete
and out the holes at the bottom of the cylinder. For all pH tests, a volume of 175 mL of deionized
water was applied to each test specimen. The 175 mL volume was meant to represent a depth of
approximately 10 mm of rainfall, although it was applied in one dose, not over a period of time
like natural rainfall. The pH of effluent samples was determined immediately after sample
collection using a calibrated pH meter manufactured by Canlab (Model No. 607). A photo of one
of the pH tests is shown in Figure 18.
Figure 18: Determining pH of Hydromedia Test Specimen Effluent (November 10, 2014)
Experiments were conducted after 1 day of curing, 4 days, 7 days, 28 days, and on a monthly basis
after 28 days. The first number of the specimen ID’s reflect the curing age in days when an
experiment was first conducted. For example, specimens 4-A and 4-B both received their first dose
of deionized water after 4 days.
47
3.3.3 Total Phosphorus Experiment
Two different experiments were conducted for TP testing. The purpose of the experiments was to
determine the TP levels in effluent from early age Hydromedia, and to determine if there was any
decrease in TP due to curing age. The first experiment was conducted on water samples from
specimen 1-A. These were the same samples used for pH testing described in the previous section
(with a dose volume of 175 mL), although they were stored in glass sample jars in a refrigerator
until the test was conducted on December 18. All four samples were analyzed using a Lamotte
Smart 3 Colorimeter, according to the Low Range TP Test Procedure (See Appendix B).
The second experiment was conducted to determine if TP concentration decreased with application
of larger volumes of water, to simulate the effect of extended exposure of Hydromedia to rainfall.
Four samples were collected by applying 3.9 L of deionized water to the specimen surface and
collecting the effluent. Four 3.9 L doses totaled to 15.6 L of water, which was meant to represent
the approximate volume of an entire year of precipitation for St. Catharines. The first effluent
sample was collected on January 12, 2015, and the remaining samples were collected over a period
of four days, with a drying period of about 24 hours between each experiment. All four samples
were stored in glass sample jars in a refrigerator until they were analyzed for TP on January 24,
2015, again using a Lamotte Smart 3 Colorimeter.
48
Chapter 4 Hydrology
This chapter presents the water quantity results from the monitoring study and analysis. It includes
discussion of surface infiltration capacity, calibration results for the Hydromedia effluent discharge
monitoring equipment, and rainfall and effluent discharge results, analysis, and discussion. Results
are discussed in the context of hydrologic performance of the LSSC Hydromedia parking lot.
HYDROLOGY
4.1 Infiltration Capacity
The mean and median infiltration capacity of the Hydromedia were determined to be 1,280 and
1,490 cm/h, respectively. Only one measurement was considered a fail. The maximum infiltration
capacity was 2,480 cm/h. Measured infiltration capacities at the Kortright Centre were comparable
after three years, with a mean of 1,356 cm/h and a median of 1,072 cm/h (Drake et al., 2012).
Figure 19 shows the approximate location of each infiltration capacity test on the Hydromedia
cell, and the range of results. It shows a high degree of variability in infiltration capacity over the
surface of the parking lot. It is difficult to notice any spatial trends due to this variability, however
the infiltration capacity is lowest near the edges of the Hydromedia cell, in the centre driving lanes.
Four of the five lowest infiltration capacities were measured in the driving lanes (locations 11, 12,
17, and 18), including three locations below 250 cm/hr.
Figure 19: Hydromedia infiltration capacity and approximate test locations (June 30, 2014)
The lower infiltration capacity at the ends of the Hydromedia cell were likely caused by localized
clogging of the PP void space with debris from vehicle traffic in the centre lanes. High traffic areas
49
experience more rapid clogging. Debris from off site can become attached to vehicles and fall off
in the parking lot, or be transported to the LSSC parking lot by other means such as wind (Brattebo
& Booth, 2003). Higher vehicle traffic in the driving lanes of the parking lot may force debris
deeper into the pores causing the Hydromedia to clog more quickly. Some temporary ponding was
observed during heavy rainfall on October 3, 2014 near the failed test location 18 (Figure 20).
However, the ponding did not persist, and no surface runoff was observed. Ponded water runs to
an area where there is sufficient capacity, and is infiltrated.
Figure 20: Ponding on Hydromedia surface near clogged test location during heavy rainfall
(October 3, 2014)
While the infiltration capacity inevitably reduces over the life of the parking lot, and at different
rates in different areas, it should be noted that the infiltration capacity remains very high compared
to rainfall intensity. The largest storm over the monitoring period had an average rainfall intensity
of 18 mm/h, over a duration of 75 minutes, and peak rainfall intensity of 69 mm/h. Local intensity-
duration frequency curves from Environment Canada (2011) indicate this corresponds to a 2-year
return period. Excluding the location of the failed measurement, the lowest measured infiltration
capacity of the Hydromedia was 60 cm/h. Therefore, the infiltration capacity of Hydromedia under
these conditions after three years is more than 30 times greater than the average intensity, and more
50
than 8 times greater than the peak intensity of the observed 2-year event. No ponding of
stormwater, and no direct surface runoff would be expected from the Hydromedia cell surface.
4.2 Weir Box Calibration
Results from calibration of the weir box are shown in Figure 21 below.
Figure 21: Weir box calibration results
The error between measured and calculated discharge is summarized in Table 5.
Table 5: Weir Box Calibrations Results Summary
Measured Discharge (L/min) Calculated Discharge (L/min) Error (L/min) Error %
187.8 192.0 4.2 2.2
163.2 161.5 -1.7 1.0
130.2 129.1 -1.1 0.8
99.9 101.0 1.1 1.0
64.7 64.5 -0.2 0.3
45.8 46.4 +0.6 1.3
26.5 26.6 +0.1 0.2
11.0 10.5 -0.5 3.9
3.0 2.2 -0.8 28.2
The results show an excellent fit (R2 > 0.99) using the standard weir equation (Equation 1) with
a discharge coefficient of 0.58. Therefore, data collected from the water level loggers has been
0
50
100
150
200
250
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
Dis
char
ge (
L/m
in)
Head Over Weir (m)
Measured
Calculated
51
used to determine discharge from the parking lot using the following relationship derived from
Equation 13:
𝑸 = 𝟐𝟐, 𝟎𝟐𝟖. 𝟐 𝑯𝟓
𝟐 Equation 13
Where: Q: Flow rate (L/min)
H: head above weir crest (m)
Note that at low head (H < 3.6 cm), the nappe begins to cling to the weir face, and Equation 13
provides a less accurate model of discharge of Hydromedia effluent. At a head of 2.5 cm, the
lowest head recorded during the experiment, the nappe began to cling. At this low head, Equation
13 predicts 2.2 L/min, while a discharge of 3.0 L/min was measured, an under prediction of 28%.
This demonstrates that at low head, calculated discharge volumes are lower than actual discharge.
For large events, this error is negligible, since most of the volume is discharged at higher head.
For small events, the error may be significant, so the discharge has been adjusted as described in
Section 3.2.2.4.
4.3 Hydromedia Effluent Discharge and Rainfall
4.3.1 Observations
A total of thirty four rainfall events were recorded over the monitoring period (Table 6). All peak
discharge and volume reductions are relative to the expected asphalt surface runoff, since this
could not be directly measured. Events in Table 6 have been categorized as large (more than 20
mm of rainfall), medium (10-20 mm of rainfall), and small (less than 10 mm of rainfall). Drainage
of Hydromedia effluent showed a total volume reduction of 44% from July to November. On a
single event basis, runoff volume reductions ranged from 17 to 100%. These observations only
include monitoring results from summer. Volume reduction may be less during cold weather, and
these results are not directly comparable to Kortright, where volume reduction was reported as
43% for year round monitoring (Drake et al., 2012). Collins et al. (2008) reported a mean volume
reduction of 44%, however this was relative to rainfall depth, not asphalt surface runoff volume,
so the volume reduction was actually higher than observed at LSSC.
52
Table 6: Summary of rainfall events and effluent discharge
Event
size
Event date
Rainfall
Asphalt surface
runoff
Effluent
discharge
Peak
discharge
reduction
(%)
Volume
reduction
(%)
Depth
(mm)
Peak
(mm/h)
Depth
(mm)
Peak
(L/min)
Depth
(mm)
Peak
(L/min)
Lar
ge
(20
mm
+) 07/07/2014 41.75 69 39.7 633.2 31.8 173.3 73 20
27/07/2014 36.25 48 34.4 440.5 28.6 67.9 85 17
05/09/2014 44.00 57 41.8 523.1 30.8 116.9 78 26
Med
ium
(10
-20
mm
) 04/08/2014 12.00 48 11.4 440.5 2.4 6.0 99 79
03/10/2014 16.50 18 15.7 165.2 9.8 14.2 91 38
06/10/2014 13.50 15 12.8 137.7 8.3 19.4 86 35
31/10/2014 11.50 21 10.9 192.7 7.4 4.8 98 33
16/11/2014* 11.75 <3 11.2 <27.5 6.8 8.5 21 39
Sm
all
(Les
s th
an 1
0 m
m)
13/07/2014 4.00 21 3.8 192.7 0.1 0.3 100 97
15/07/2014 4.75 12 4.5 110.1 1.2 1.8 98 74
16/07/2014 1.00 3 1.0 27.5 0 0 100 100
19/07/2014 5.75 6 5.5 55.1 1.2 1.6 97 78
21/07/2014 2.50 15 2.4 137.7 0 0 100 100
26/07/2014 0.50 3 0.5 27.5 0 0 100 100
29/07/2014 1.00 3 1.0 27.5 0 0 100 100
01/08/2014 0.50 <3 0.5 <27.5 0 0 100 100
03/08/2014 0.75 <3 0.75 <27.5 0 0 100 100
12/08/2014 8.75 18 8.3 165.2 0.9 1.4 99 90
16/08/2014 4.25 18 4.0 165.2 0 0 100 100
01/09/2014 2.75 6 2.6 55.1 0 0 100 100
10/09/2014 2.75 6 2.6 55.1 0.2 0.2 100 94
13/09/2014 6.50 9 6.2 82.6 2.8 4.8 94 55
15/09/2014 1.00 <3 1.0 <27.5 0 0 100 100
21/09/2014 3.75 15 3.6 137.7 0.1 0.4 100 90
13/10/2014 2.25 6 2.1 55.1 0 0 100 100
14/10/2014 1.25 3 1.2 27.5 0 0 100 100
18/10/2014 1.75 <3 1.7 <27.5 0 0 100 100
20/10/2014 6.50 3 6.2 27.5 3.2 3.4 88 48
27/10/2014 0.50 <3 0.5 <27.5 0 0 100 100
28/10/2014 0.75 3 0.75 27.5 0 0 100 100
04/11/2014 3.75 <3 3.6 <27.5 0.9 0.6 96 74
06/11/2014 3.50 6 3.3 55.1 2.2 1.1 98 33
08/11/2014 0.25 <3 0.25 <27.5 0 0 100 100
19/11/2014 2.50 3 2.4 27.5 0 0.1 100 100
* Sub-zero temperatures recorded
Three large events were recorded, with rainfall depths of 36, 42, and 44 mm. These events make
up 47% of the total rainfall volume over the monitoring period. Volume reductions were lowest
for large events, ranging from 17 to 26%, with an average of 21%. Five medium events, accounting
for 25% of the total rainfall volume were recorded, with rainfall depths from 11.5 to 16.5 mm.
Volume reductions for medium events ranged from 33 to 79%, with an average of 45%. All
medium and large events produced measureable Hydromedia effluent discharge. Twenty six small
53
events were recorded, with rainfall depths from 0.25 to 8.75 mm, making up 28% of the total
rainfall volume. Small events showed the highest volume reductions, from 33 to 100%, with an
average of 90%. Sixteen small events with depths from 0.25 to 4.25 mm had no measureable
Hydromedia effluent discharge, and all events less than 3 mm had no measureable discharge
(100% volume reduction). Both Drake et al (2012) and Fassman & Blackbourn (2010) observed
no discharge for events less than 7 mm, but they were partial exfiltration systems over poorly
draining soils. Larger volume reductions would be expected at LSSC if exfiltration was allowed
to occur.
Volume reduction observations show distinct hydrologic responses based on the size of the storm.
As expected, larger events tend to have small volume reductions, while small events have high
volume reductions. Since the subdrain is not elevated, the ability of the parking lot to store water
is primarily dependent on the surface area of the clear stone aggregate (Pratt et al., 1989). Lower
volume reductions occur for larger events because the particle surface area of the Hydromedia and
clear stone layer becomes completely wetted, and water begins to saturate the void spaces. Unlike
a full or partial exfiltration system with no liner, the pooled water cannot pass through the HDPE
liner into the native soil, and is eventually collected in the subdrain. However, zero-exfiltration
systems still provide hydrologic benefits after discharge begins. The tortuous flow path of
infiltrated stormwater through the clear stone layer attenuates the flow, spreading it out over an
extended period of time. This reduces the peak discharge and also results in a lag in the time to
peak.
Peak discharge reductions also varied based on rainfall depth. Large storms had peak discharge
reductions ranging from 73 to 85%, with a mean of 79%. Peak discharge reductions for medium
events ranged between 21 to 99%, with a mean of 94%. The low peak discharge reduction of 21%
on November 16, 2014 was not included in the calculation of the mean due to below freezing
temperatures recorded during the event. Precipitation was in the form of snowfall, and rapid
melting or movement of snow may have caused the very low peak discharge reduction. All medium
events during above freezing conditions had peak discharge reductions of at least 86%. Based on
this observation, it is expected that the winter hydrologic response at the LSSC lot will be very
different than spring-summer-fall response. Small events had peak discharge reductions from 88
to 100%, with a mean of 95%. Pratt et al. (1989) observed similar peak flow reductions for a zero-
exfiltration PP system, with a mean reduction of 70%.
54
Figure 22 presents a typical hydrologic response to a large rainfall event (42 mm). There are three
distinct periods of rainfall during this particular event, each accompanied by an increase in effluent
discharge. It has been treated as one event because effluent was still flowing from the previous
period of rainfall as the next period began. The volume reduction for this event was only 20%.
Figure 22: Hydromedia Effluent Hydrograph and Rainfall from 42 mm Event (July 7 -
July 9, 2014)
The peak discharge reduction for the high peak on July 8 was 73%, and each separate peak was
delayed from the peak rainfall intensity by 3.2, 1.3, and 0.3 hours. Even for large events where the
volume reduction was relatively small, peak discharge reduction was still a minimum of 73%,
indicating the flow of stormwater is being attenuated over a longer period of time.
Figure 23 shows the hydrologic response from a medium size event, with a total rainfall depth of
16.5 mm. For this event, there were two distinct periods of rainfall, the first during the afternoon
on October 3, and the second in the early morning on October 4. Discharge of Hydromedia effluent
did not begin until after the first period of rainfall was completed, approximately three hours after
rainfall began. The peak discharge reduction for this event was 91%. The lag time from peak
rainfall intensity to the first peak discharge was 1.25 hours, and the lag time for the second peak
was 1.67 hours. The parking lot was still draining when the second period of rainfall began, and
0
20
40
60
80
100
120
140
160
180
200
0
10
20
30
40
50
60
70
80
07
/07
/20
14
08
/07
/20
14
09
/07
/20
14
Hyd
rom
edia
Eff
luen
t D
isch
arge
(L/
min
)
Rai
nfa
ll in
ten
sity
(m
m/h
r)
Rainfall
Discharge
55
the system responded with an increase in effluent discharge to a second peak. The second peak
discharge (14.2 L/min) was higher than the first (8.9 L/min), even though the second peak rainfall
intensity (6 mm/hr) was less than the first (18 mm/hr).
Figure 23: Hydromedia Effluent Hydrograph and Rainfall from 16.5 mm Event (Oct 3 – Oct
4, 2014)
Figure 24 shows the hydrologic response from a small event with a rainfall depth of 6.5 mm.
Every small event recorded had very low flows, such that the head above the weir was less than
3.6 cm. Estimated discharge is shown in Figure 24. Similar to the medium size event, discharge of
Hydromedia effluent did not occur until rainfall had stopped. The lag time to peak for this event
was 3.75 hours. The peak discharge and volume reductions were 94% and 55%, respectively.
0
2
4
6
8
10
12
14
16
18
20
0
2
4
6
8
10
12
14
16
18
20
Hyd
rom
edia
Eff
luen
t D
isch
arge
(L/
min
)
Rai
nfa
ll in
ten
sity
(m
m/h
r)
Rainfall
Discharge
56
Figure 24: Hydromedia Effluent Hydrograph and Rainfall from 6.5 mm Event (Sept 13 -
Sept 14, 2014)
4.3.2 Single Event Comparison to Pre-Development Conditions
The third period of rainfall for the July 7 event had an average intensity of 18 mm/hr over a duration
of 75 minutes (Figure 22). As discussed in Section 4.1, local intensity-duration-frequency curves
from Environment Canada (2011) indicate this event had a return period of about 2 years. The
peak discharge of Hydromedia effluent was 173 L/min. This event was selected to assess pre and
post-development peak outflows because it was the most intense rainfall event recorded. Model
inputs for pre-development conditions are included earlier in Table 2 in Section 3.2.2.4. Output
results for the EPA SWMM 5.0 model of pre-development conditions estimate a peak flow of
183.6 L/min, as shown in Figure 25.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0
1
2
3
4
5
6
7
8
9
10
Hyd
rom
edia
Eff
luen
t D
isch
arge
(L/
min
)
Rai
nfa
ll in
ten
sity
(m
m/h
r)Rainfall
Discharge
57
Figure 25: July 7, 2014 Pre-Development Modelling Results
The NPCA requires control of post-development flows of the 2, 5, 10, and 100 year storms to pre-
development levels (AECOM, 2010). The observed peak discharge of Hydromedia effluent is less
than the predicted pre-development peak flow, therefore the LSSC parking lot meets the NPCA
criteria for water quantity control, for this particular storm. Meeting the quantity control
requirements for this storm does not necessarily mean that the parking lot would meet requirements
for any other storm, particularly more intense storms. However, this result does demonstrate that
zero-exfiltration systems are at least capable of meeting some of the NPCA requirements.
Additionally, it would be possible to further reduce the peak discharge from the parking lot by
partially closing the catch basin valve, allowing the effluent to back up and be temporarily detained
in the sub base layer.
4.3.3 Regression Analysis Results
Linear regression analysis results show that Hydromedia effluent volume on an event basis is most
strongly correlated to the depth of rainfall, followed by peak rainfall intensity. Effluent volume
was positively correlated to rainfall depth (p < 0.001), and negatively correlated to rainfall intensity
(p < 0.05). Equation 14 describes the regression model for depth of Hydromedia effluent:
0
25
50
75
100
125
150
175
200
0
10
20
30
40
50
60
70
80
14
:30
15
:30
16
:30
17
:30
18
:30
Dis
char
ge (
L/m
in)
Rai
nfa
ll in
ten
sity
(m
m/h
r)Rainfall
Hydromedia
Surface Runoff
58
𝐃𝐇𝐌 = (−𝟏. 𝟏𝟔 + 𝟏. 𝟐𝟕√𝑫𝑹 − 𝟎. 𝟏𝟗√𝑷𝑹)𝟐 Equation 14
Where:
DHM: depth of Hydromedia effluent (mm)
DR: depth of rainfall (mm)
PR: peak rainfall intensity (mm/hr)
The regression model fits the observed data well (R2 = 0.96), with normally distributed residuals.
Figure 26 shows the predicted results versus actual observations. DHM cannot be negative due to
the square root transform. The model is simple, but makes intuitive sense. Events with very low
rainfall depths will have very low discharge. Higher rainfall depths result in higher effluent
discharge volumes. The negative correlation to peak rainfall can be explained by the fact that in
general, events with lower rainfall depth tend to have higher peak rainfall intensities. Lower
rainfall depths from these short duration, intense storms, would likely result in less effluent
discharge volume, simply because there is likely to be less rainfall volume.
Figure 26: Hydromedia Effluent Volume Regression Results (diagonal line shows perfect fit
– for reference only)
Regression analysis results show that the peak discharge of Hydromedia effluent exhibits a
considerably more complicated relationship than effluent volume. The regression model which
included all events with non-zero discharge indicated that peak discharge is correlated negatively
to peak rainfall intensity (p < 0.001), positively to the product of peak rainfall intensity and rainfall
depth (p < 0.001), and not correlated to rainfall depth. Equation 15 describes the regression model
for peak discharge of Hydromedia effluent.
0
10
20
30
40
0 10 20 30 40
Pre
dic
ted
Eff
luen
t D
epth
Observed Effluent Depth (mm)
59
𝐏𝐇𝐌 = (𝟐. 𝟒𝟏 − 𝟏. 𝟐𝟎√𝑷𝑹 + 𝟎. 𝟑𝟔𝟐√𝑷𝑹 × 𝑫𝑹)𝟐 Equation 15
Where:
PHM: peak discharge of Hydromedia effluent (L/min)
The regression model fits the observed data well (R2 = 0.96), however, the July 7 storm (the most
intense storm observed) was an outlier in this model, and the residual error distribution showed
some skewness, therefore confidence in the significance of the model coefficients is poor. The
regression analysis was repeated with the outlier removed. Neither of these models are good
predictors of peak discharge for the most intense recorded event, which is the most important for
engineering design. Equation 16 describes the peak discharge model without considering the
outlier:
𝐏𝐇𝐌 = (−𝟎. 𝟎𝟗 + 𝟎. 𝟗𝟖√𝑫𝑹 − 𝟎. 𝟕𝟓√𝑷𝑹 + 𝟎. 𝟏𝟗√𝑷𝑹 × 𝑫𝑹)𝟐 Equation 16
There is no basis to remove the outlier, other than for the purpose of the regression analysis, so the
models should not be used to predict high flows. More hydrologic data would be required to
develop more robust models, but the regression analysis still provides insight into which predictor
variables are significant to determine effluent volume and peak discharge. Figure 27 shows the
predicted results versus actual observations for Equation 16.
Figure 27: Hydromedia Effluent Peak Discharge Regression Model (diagonal line shows
perfect fit – for reference only)
0
50
100
150
0 50 100 150
Pre
dic
ted
Pea
k D
isch
arge
Observed Peak Discharge (L/min)
60
The product of PR and DR, and a lone PR term as a significant predictor of PHM can be explained
as follows. An event with high PR and DR would have a high PHM. The negative correlation to
the lone PR term is due to the typical shorter duration of high intensity storms. Very short events
with high intensity would not immediately produce high peak discharge because the clear stone
sub base would not yet be saturated. This is already expressed in the product of PR and DR, but is
exaggerated due to the large number of small events. Explanatory variable correlations are
summarized in Table 7. Diagnostic plots for assessing the statistical assumptions of the regression
analysis are included in Appendix C.
Table 7: Summary of Regression Analysis Correlations
Response Variable (Hydromedia
effluent)
Explanatory Variables (Rainfall) Correlation
Depth Peak
Intensity
Depth * Intensity R2
Hydromedia Effluent Volume + (p<0.001) - (p<0.05) None (p>0.05) 0.96
Hydromedia Effluent Peak
Discharge
None - (p<0.001) + (p<0.001) 0.96
Hydromedia Effluent Peak
Discharge (excluding highest
discharge outlier)
+ (p<0.05) - (p<0.01) + (p<0.01) 0.97
The regression models could likely be strengthened by considering events of different sizes (small,
medium, large) separately, and developing unique relationships for each set of events. However,
this analysis is not possible without further data collection due to the limited number of medium
and large size events which occurred over the monitoring period. As a result, confidence in this
model is not strong, particularly when extrapolating beyond the range of values which occurred
during the monitoring period. The model is completely empirically based, and does not have any
wide ranging application outside of the LSSC parking lot, even for zero-exfiltration systems.
Collins et al. (2008) found similar correlations to those discussed above. They determined that PP
peak discharge was positively correlated to both rainfall depth and rainfall intensity, with rainfall
intensity being the best predictor of peak PP discharge for most PP types. PP peak discharge
depends on both rainfall intensity and depth because a larger rainfall depth saturates the voids in
the pavement structure, and water can then exit through subdrains more easily (Collins et al., 2008).
The voids would not necessarily become saturated during a high intensity, lower depth rainfall
61
event. PP effluent total volume was most dependent on rainfall depth, not rainfall intensity (Collins
et al., 2008).
4.3.4 Summary
The Hydromedia parking lot met the NPCA criteria for control of the observed 2-year storm. It
provided substantial peak flow and volume reductions for all recorded events. This is the first
example of the hydrologic benefits of a zero exfiltration system in Ontario. Overall, the
Hydromedia parking lot is an effective management practice for the LSSC, and could be used to
meet NPCA criteria for quantity with minor modifications. Without making any changes to the
existing parking lot, additional control of effluent discharge could be achieved by partially closing
the valve to limit the flow which leaves the catch basin. Flow would back up into the subsurface
and be temporarily stored with a slow release. Sufficient storage capacity exists within the
aggregate layer such that the 100 year storm could be controlled to pre-development flows. A 100
year, 24 hour design storm has a depth of about 96 mm for St. Catharines, which would require
approximately 240 mm of clear stone for storage, while the LSSC has 350 mm.
Quantity control would be further improved if infiltration of stormwater into native soils was
allowed for in the original design of the parking lot, but this is not practical since the parking lot
is complete. Alternatively, the PP parking lot could be integrated as part of a treatment train
process with additional stormwater controls, such as downstream bioswales.
62
Chapter 5 Water Quality
This chapter presents the results of the water quality analysis conducted on all collected samples,
and includes a discussion regarding what these results mean in terms of overall water quality of
the Hydromedia effluent. The chapter is divided into sections based on the water quality parameter
being discussed. Detailed laboratory test reports from NAL are included in Appendix D.
WATER QUALITY
5.1 Total Suspended Solids
TSS concentration is an often used indicator of overall stormwater quality, because it provides an
indication of the concentration of all solid pollutants. NPCA requires a minimum TSS removal
efficiency of 70%, but no maximum concentration is specified (AECOM, 2010). An insufficient
number of asphalt runoff samples were collected to reliably determine the overall removal
efficiency to compare with the NPCA criteria of 70% removal. Instead, the data was compared
with the water quality results from a study conducted by TRCA and Drake et al. (2012) for a
pervious concrete parking lot at the Living City Campus at Kortright, in Ontario. Additional water
quality data from the Kortright parking lot collected between 2013 and 2014 was provided by
TRCA for comparative analysis. Data from Kortright is included in Appendix E. Both parking lots
are approximately the same age, and are surfaced with Hydromedia. Statistics for TSS
concentration are shown for both the LSSC and Kortright parking lots in Table 8. It should be
noted that concentrations at Kortright are reported as EMC’s, while water quality data at LSSC are
from grab samples.
Table 8: Descriptive statistics for TSS concentration of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L) Mean
RE (%) Mean Median Low High Variance
LSSC 15 6 3 < 1 43 102 N/A
Kortright (2010 to 2012)* 43 17.5 6.9 <2.5 101 474.2 79
Kortright (2013 to 2014) 15 6.4 5.9 <2.5 13.6 9.4 92 * Drake et al., 2012
TSS concentrations at the Kortright lot have been split into two periods in Table 8, because
pollutant removal performance has changed with the age of the parking lot. Concentrations were
higher early in the life of the parking lot, from 2010 to 2012. As the Kortright lot aged (2013-
63
2014), TSS concentrations in the PC effluent have decreased. The TSS results at the LSSC are
more comparable to the results from 2013 to 2014 at Kortright, with a similar level of performance.
From 2010 to 2012, the TSS concentrations at Kortright were higher than those observed during
the 2014 monitoring program at the LSSC. The observations indicate that pervious concrete
parking lots perform better in terms of TSS removal as they age. This is likely caused by washing
of fines for the PC and aggregate base early on in the life of the parking lot, as well as material
clogging the pores of the PC. Clogged pores in the PC reduce the porosity of the pavement, smaller
void spaces allow for improved filtration of stormwater.
Average RE at Kortright was 92% from 2013 to 2014. Unlike the LSSC, Kortright is not located
in an urban setting, therefore TSS pollutant loadings are expected to be lower at Kortright. Since
the mean and median residual concentrations are similar at Kortright (2013-2014) and the LSSC
(2014), and the loading is expected to be greater at the LSSC, it can be inferred that the removal
efficiency is likely at least as high as that seen at Kortright, because removal efficiency values are
dependent on influent concentrations. Therefore, it is expected that the LSSC PC parking lot
provides an enhanced level of protection, according to MOECC (2003) criteria for stormwater
BMP’s. The International Stormwater BMP Database reported a median effluent TSS EMC of
13.2 mg/L among all PP sites being monitored (Geosyntec & Wright, 2012). Over 23,000 EMC
observations were considered to determine this median EMC. The lower median concentration of
3 mg/L observed at the LSSC indicates that the lot is performing well in terms of TSS removal,
compared to the other PPs in the BMP database. This is the second site in Ontario where TSS
concentrations were observed to be well below the median from the BMP database.
The highest measured concentration of 43 mg/L at the LSSC is representative of the first flush
from the event on October 3, 2014. This sample was collected immediately after the Hydromedia
effluent began to flow. Other than this first flush sample, all Hydromedia effluent samples had
TSS concentrations less than 10 mg/L. For comparison, no asphalt runoff sample had a TSS
concentration lower than 18 mg/L, and the highest measured concentration was 277 mg/L. The
first flush may contain solids that have settled in the aggregate base layer as well as the underdrains
of the PP system, and become resuspended. Figure 28 shows the change in TSS concentration
with time throughout this event for both asphalt runoff and Hydromedia effluent. Both show a
trend of decreasing concentration with time.
64
While it is not practical to determine TSS removal efficiencies for each event due to limited data
availability for asphalt runoff concentrations, it is possible to determine pollutant removal
efficiency for the event on October 3, 2014, using EMC’s for the collected composite samples.
Note that Figure 28 shows rainfall beginning slightly after the first asphalt runoff sample was
taken. This difference is likely due to the weather station being located approximately 800 m from
the LSSC, or very light rainfall at the beginning of the event.
Figure 28. TSS concentration results (October 3, 2014)
RE for this event was 90%, based on EMCs, which corresponds to an enhanced level of protection
according to MOECC (2003) criteria. It should be noted that this is only RE from one event. While
it can be inferred from the Kortright data that the LSSC PC lot provides and enhanced level of
protection, additional asphalt surface runoff data from other events would be required to confirm
RE performance of the Hydromedia parking lot. However the results do provide an indication that
Hydromedia is functioning as intended by removing most of the suspended solids. Suspended
solids are removed within the PP through filtration, and also likely sedimentation due to reduced
65
velocity of the water as it flows through the tortuous path within the Hydromedia and the clear
stone aggregate.
The difference in TSS concentration between asphalt runoff and Hydromedia effluent is apparent,
even just with visual observation. Figure 29 shows samples collected during the October 3 event.
It is clear that asphalt runoff contains a great deal more suspended solids than the Hydromedia
effluent.
Figure 29. Photo of composite samples from October 3, 2014 event. Asphalt runoff on top
row, Hydromedia effluent on bottom row, in chronological order from left to right.
Overall, the results demonstrate that the LSSC Hydromedia performed well in terms of TSS
control. TSS concentrations were low, even within an urban environment, and with a zero-
exfiltration PP system. This first flush of TSS from the PP system has a higher TSS concentration,
and it then quickly decreases to below 10 mg/L. The results indicate that PC parking lots are
feasible for use as stormwater BMP’s, even when designed as lined, zero-exfiltration systems for
implementation in urban areas of Ontario. Additional composite sampling of both asphalt runoff
and Hydromedia effluent for additional events would be required to confirm that the parking lot is
capable of consistently providing an enhanced level of protection.
66
5.2 pH and Alkalinity
In section 5.2.1, field test results of pH and alkalinity are both discussed because they both have
an effect on the acidity of the stormwater. Additional experimentation was conducted at the
laboratory scale to analyze pH, which is discussed in section 5.2.2.
5.2.1 Field Results
PP effluent typically has a basic pH, particularly cementitious pavements. Results at LSSC also
show that the Hydromedia effluent is basic. Statistics for pH are shown in Table 9.
Table 9: Descriptive statistics for pH of Hydromedia effluent
Dataset # of samples Mean Median Low High Variance
LSSC 15 8.73 8.74 8.20 9.88 0.19
Kortright (2010-2012)* 43 9.15 8.81 8.08 11.80 0.731
Kortright (2013-2014) 15 8.23 8.29 7.33 8.49 0.073 * Drake et al., 2012
MOECC established the PWQO for pH to range from 6.5-8.5, to protect aquatic life and to
maintain an acceptable pH in waters for recreational use (MOECC, 1994). Eight of the fifteen
collected samples of Hydromedia effluent had a pH greater than 8.5. Two samples had pH greater
than 9. Even if these results were discounted, the newly determined mean and median pH would
both exceed 8.5. These results indicate that Hydromedia effluent from the LSSC does not meet the
PWQO for pH the majority of the time. PC effluent is expected to be basic, however, some of the
results are considerably higher than what would be considered typical for a three year old parking
lot in Ontario. This is particularly true for the two highest pH measurements of 9.45 and 9.88.
PC pavement effluent typically has a very high pH early on, and it decreases with time. For
example, at the Kortright Centre lot, pH of PC effluent was below 8.5 approximately one year after
the lot had been constructed. The reduction in pH can been seen in Table 9, where the pH from
2010-2012 is higher than the pH from 2013-2014. The highest pH results at Kortright were
observed during the first year. No samples had pH above the PWQO of 8.5 from 2013-2014.
Comparing the results from LSSC to those at Kortright, it is clear that the pH has decreased more
slowly at the LSSC. The mean and median pH at LSSC are both much higher than that observed
at Kortright from 2013-2014, and both are above the PWQO of 8.5.
67
The high pH results at LSSC are not expected to be typical of PC parking lot effluent in Ontario.
After some discussion with City of St. Catharines staff, it was discovered that there were some
issues during construction of the lot which may have been influencing the pH. It is understood that
a problem with the concrete mix resulted in poor bonding of the aggregate matrix, which caused
much of the paste to be washed down into the clear stone sub base and subdrains. This concrete
was not satisfactory and was ripped up. A new Hydromedia pavement surface was poured, but the
residual paste remaining in the clear stone and subdrains may be affecting the pH results today, as
the alkalies in the cement paste slowly leach out of the system.
Another potential reason for higher pH of Hydromedia effluent at LSSC may be the impermeable
liner. As discussed earlier, PC effluent pH decreases due to carbonation. The liner at LSSC would
prevent carbon dioxide from the native soil from reaching the base of the pavement, therefore
reducing the rate of carbonation, and slowing the reduction of pH. Due to these unexpected high
pH results, and the possibility of a previous construction issue affecting results, a laboratory
experiment was conducted to determine pH from prepared Hydromedia samples. Results from this
experiment are described in section 5.2.2.
Composite samples of Hydromedia effluent from the October 3, 2014 event show a small change
in pH over the course of the event (Figure 30). The results ranged from 8.37 to 8.80 and showed
a small increase in pH over the first hour after the Hydromedia effluent began to flow.
Figure 30 also shows that the pH of Hydromedia effluent is much higher than that of asphalt
runoff. Test results from other asphalt runoff samples confirm this, with a mean and median pH of
7.03 and 7.10, respectively, for all collected asphalt runoff samples, compared to 8.73 and 8.74 for
Hydromedia effluent samples.
68
Figure 30: pH results (October 3, 2014)
Alkalinity of the Hydromedia effluent samples was relatively low, considering the basic pH of all
the samples. Statistics for alkalinity are shown in Table 10. Results from the Kortright Centre by
Drake et al. (2012) are also shown for comparison.
Table 10: Descriptive statistics for alkalinity of Hydromedia effluent
Dataset # of
samples
Alkalinity as CaCO3 (mg/L)
Mean Median Low High Variance
LSSC 15 16 13 10 33 43.2
Kortright (2010 to 2012)* 43 166.5 153 93.2 421 4349
Kortright (2013 to 2014) 15 122.8 116 70.9 206 1151 * Drake et al., 2012
The alkalinity concentration observed at the LSSC was much lower than what was observed at the
Kortright Centre. This is likely due to the composition of the aggregates in the clear stone layer.
The aggregates at Kortright probably contain more calcium carbonate, which would increase the
alkalinity of the effluent. It was not possible to confirm this by collecting an aggregate sample at
either parking lot. Lower alkalinity reduces the ability of the PP system to buffer pH, but this is
69
not a concern because the pH of the influent is not highly acidic, and effluent was shown to be
basic.
5.2.2 Laboratory Scale Results
Observations of effluent pH for eight different concrete cylinders at various curing ages are shown
in Figure 31. Note that the pH results at a specimen age of 28 days were adjusted for a temperature
error on the pH meter. The sample numbers provided in the legend indicate the age in days when
the specimens were first flushed with water (e.g. sample 4-A and 4-B were both flushed for the
first time at an age of four days). The average pH and trend line shown on the figure only include
effluent from samples which had been stored in the curing room. The results show a steady
decrease in pH over the course of the experiment. Flushing of the specimens with water showed
no clear effect the pH of the effluent. For example, specimens 1-A and 1-B received the highest
volume of flush water over the first 28 days, and yet they had the highest pH of all test specimens.
The range of pH results for each flush trial is due to the random path the flush water takes through
the Hydromedia pores.
Figure 31: Laboratory pH results of Hydromedia test specimens
9.5
10
10.5
11
11.5
12
12.5
13
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
Effl
uen
t p
H
Sample Age (years)
1-A
1-B
4-A
4-B
7-A
7-B
28-A
28-B
Average
Linear (Average)
70
The pH results from this experiment show a similar rate of decline in pH to that observed in the
longer duration Thomle (2010) study, which also monitored pH through infiltration tests of
laboratory specimens over a period of one year. Thomle (2010) observed a rate of pH decline of
2.01/year over the first year, compared to a predicted 1.60/year observed in this experiment.
Thomle (2010) observed an initial pH of about 12, compared to about 12.7 in this study. This
difference might be attributed to differences in flush water temperature (colder temperatures
typically result in higher pH), or perhaps the composition or structure of the PC itself. The Thomle
(2010) study also used completely open cylinder bottoms, while this experiment had five small
drain holes at the bottom of each cylinder, which may have restricted the flow of water and allowed
for more contact with the Hydromedia surface.
Extrapolation of the results of this study indicates that it would take two years for the pH of the
effluent from laboratory PC specimens to decrease below 8.5, assuming the observed trend
continues. However, these results cannot be applied directly to field conditions, because an actual
PC parking lot may have a higher exposure to carbon dioxide in the natural environment than under
laboratory conditions, and the aggregate or native soil below the concrete surface could also have
a buffering effect on the pH of parking lot effluent. Furthermore, the use of deionized water for
flushing the PC samples is considered to be a worst case scenario, since the lack of minerals in the
water promotes dissociation of calcium hydroxide, which causes higher pH (Thomle, 2010). The
increase of pH in real stormwater would not be as high when infiltrating through PC due to the
natural presence of ions in the water.
Specimens 4-A and 4-B were placed outside after one month, to determine the effect of exposure
to weather on pH. Specimens 7-A and 7-B were flushed with a much larger volume of water after
about 36 days. Both exposure to weather, and flushing with additional water appeared to decrease
the pH of the effluent for this experiment. Results from these cylinders after changing exposure
conditions were not used to calculate the average pH, and were not used to determine the rate of
change in pH due to age. Note that low pH results at 0.17 years for Specimens 4-A and 4-B
occurred at below freezing temperatures of the concrete specimens, which suggests that the pH of
effluent from a full scale parking lot may be lower in the winter. It is clear from these changes to
exposure conditions that exposure to weather, and flushing with additional water, cause the pH of
Hydromedia effluent to decline more quickly. Therefore, a new Hydromedia parking lot under
71
normal environmental conditions would likely produce effluent with lower pH than these
laboratory results.
It can take more than a year for the effluent from a PP parking lot to reach pH levels below the
PWQO. The experiment should continue with regular monthly testing to determine the amount of
time required for the pH to decrease to an acceptable level (under 8.5). This information would
allow designers of PPs to understand how long it should be expected for pH to drop to acceptable
levels, and to account for the impact of high pH effluent. The experiment will also show whether
exposure to rain and snow increases the rate at which pH of the effluent decreases, or whether
concrete age is the only factor which affects pH.
5.3 Oil and Grease
Both total oil and grease, and mineral oil and grease were analyzed for all water samples. 50% of
Hydromedia effluent samples had total oil and grease concentrations below minimum detection
limits (1 mg/L), and 79% had mineral oil and grease concentrations less than the minimum
detection limit (1 mg/L). In comparison, all of the asphalt runoff samples had both total and mineral
oil and grease concentrations above minimum detection limits. The higher number of Hydromedia
effluent samples below minimum detection limits indicates good removal of oil and grease.
The highest total oil and grease concentration in asphalt surface runoff was 8 mg/L, compared to
only 4 mg/L for Hydromedia effluent. Similarly, the highest mineral oil and grease concentration
in asphalt surface runoff was 2 mg/L, compared to only 1 mg/L for Hydromedia effluent. These
results demonstrate that the parking is removing almost all of the oil and grease.
Total oil and grease concentration results are shown with time during the October 3, 2014 event
for Hydromedia effluent and asphalt runoff in Figure 32. Asphalt runoff concentrations showed a
decrease with time, starting with the highest concentration during the first flush. Hydromedia
effluent showed no indication of any first flush, and the total oil and grease concentration remained
low throughout the event. Concentrations shown on Figure 32 as 0 mg/L were below the minimum
detection limit of 1 mg/L. Removal of hydrocarbons contained in oil and grease requires oxygen,
time, and a sufficient supply of nutrients and bacteria. Very low total oil and grease concentrations
in Hydromedia effluent indicate that the conditions within the PP system are suitable for removal
of hydrocarbons.
72
Figure 32. Total oil and grease results (October 3, 2014)
5.4 Nutrients
Nitrogen and phosphorus are nutrients of concern in stormwater management because they
promote algae growth in natural waters, which can lead to eutrophication. While the largest
nutrient source in watersheds tends to be from rural agriculture, nutrient sources from construction
runoff, combined sewer overflows, and lawn and garden activities, remain a concern in urban
environments. Field results of TKN concentrations are discussed in section 5.4.1. Field results of
TP concentrations are discussed in section 5.4.2.1, along with additional laboratory scale results
in section 5.4.2.2.
73
5.4.1 Nitrogen
Observations of TKN concentrations of Hydromedia effluent show somewhat inconsistent results.
47% of Hydromedia effluent samples had TKN concentrations below minimum detection limits
(less than 0.5 mg/L), whereas all of the asphalt runoff samples had detectable TKN concentrations.
While the high number of non-detects suggests that nitrogen was effectively removed, this was not
always the case. Two Hydromedia effluent samples, one on July 7th, and another on October 3rd,
had relatively high nitrogen concentrations of 36 mg/L, and 6 mg/L, respectively. The 36 mg/L
sample exceeds even the highest measured concentration for asphalt surface runoff of 11.5 mg/L,
however this high result for Hydromedia effluent could be discounted due to probable
contamination of the sample from the paint and wood used in the weir box construction. The
sample was collected from the weir box pool, which may have leached nitrogen from the weir box
materials. However, the 6 mg/L TKN observation cannot be discounted, since it was sampled
directly from the effluent pipe. The sample was taken during the October 3, 2014 event, and was
not associated with a first flush. Figure 33 shows TKN results from October 3. Note that samples
shown with a concentration of 0 mg/L are below the minimum detection limit of 0.5 mg/L. The
peak in TKN concentration of the Hydromedia effluent occurred nearly three hours after effluent
began to flow. It is unclear what caused this peak concentration.
Figure 33. TKN results (October 3, 2014)
74
As expected, asphalt runoff TKN concentrations showed an initial first flush of nitrogen followed
by a decline. The concentration was higher in the asphalt runoff than the Hydromedia effluent,
particularly in the first flush, because the particulate nitrogen was washed from the parking lot
surface. Hydromedia effluent concentrations did not show this predictable pattern of much higher
first flush concentration followed by lower concentrations, although there was a decline over the
first two hours of the flow event, until the nitrogen spike of 6 mg/L occurred.
There are no PWQO’s, Canadian Environmental Quality Guidelines (CEQG’s), or CWQG for TN.
Instead, guidelines are provided for other nitrogen species including ammonia (NH3), nitrate
(NO3- ), and nitrite (NO2
-). The PWQO for unionized ammonia is 0.020 mg/L (MOECC, 1994).
The CWQG for nitrite is 3 mg/L, and 45 mg/L for nitrate (Health Canada, 2014). Organic nitrogen
makes up the majority of the remainder of nitrogen present in water, but no guideline is provided
for organic nitrogen. Only TN was measured as part of this study, so it is not possible to determine
which nitrogen species are present. However, it is most likely that nitrate makes up the majority
of the TN present in the Hydromedia effluent samples, since particulate organic nitrogen would be
filtered out, and nitrification within the pavement structure transforms ammonia and nitrite to
nitrate. It is not possible to determine if the samples exceed the PWQO for ammonia with only
TKN results.
The TKN concentrations observed at the LSSC lot were lower than those observed at the Kortright
Centre for both asphalt runoff and the pervious concrete. The maximum asphalt runoff
concentration at Kortright was 5.75 mg/L (Drake et al., 2012), compared to 11.5 mg/L at the LSSC.
The maximum Hydromedia effluent concentration at Kortright was 0.9 mg/L (Drake et al., 2012),
compared to 6 mg/L at the LSSC. These differences show that the nitrogen loading is higher at the
LSSC.
Overall, nitrogen removal with the PP lot at the LSSC shows some inconsistency, but generally
the residual concentrations of TKN indicate acceptable nitrogen levels in the Hydromedia effluent.
Removal of nitrogen was not complete, but it is expected that in most cases the residual nitrogen
concentrations in the Hydromedia effluent will be acceptable. Additional water quality analysis
would need to be conducted to confirm concentrations of different nitrogen species, including
ammonia, nitrite, and nitrate.
75
5.4.2 Phosphorus
5.4.2.1 Field Results
Residual TP concentrations in Hydromedia effluent were low. Descriptive statistics for LSSC were
not calculated for TP because 80% of the samples had concentrations below the minimum
detection limit of 0.02 mg/L. TP concentrations were variable in the asphalt runoff, with 2 of 7
samples below the minimum detection limit, but a maximum concentration of 0.45 mg/L. For
comparison, the maximum concentration in Hydromedia effluent was more than 10 times less, at
0.04 mg/L.
The large difference in TP between Hydromedia effluent and asphalt runoff, along with the lack
of variability in Hydromedia effluent concentrations, indicates that the parking lot is effectively
removing phosphorus. Such a low concentration of phosphorus is unusual in stormwater, because
removal of phosphorus from stormwater is challenging (Roseen et al., 2012). Table 11 shows
descriptive statistics for TP of PC effluent at the Kortright Centre.
Table 11: Descriptive statistics for TP of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L)
Mean Median Low High Variance
Kortright (2010 to 2012)* 43 0.130 0.110 0.023 0.655 0.010
Kortright (2013 to 2014) 15 0.102 0.041 0.022 0.96 0.053 * Drake et al., 2012
The study at Kortright noted elevated levels of phosphates in pervious concrete effluent, which
does not appear to be the case at LSSC. This difference could be attributed to leaching of
phosphates, since the parking lot at Kortright was newer than at LSSC, or the phosphate could be
from another source, such as the clear stone aggregate or native soils. The mean TP concentration
in asphalt runoff at Kortright was 0.27 mg/L, which is comparable to the concentrations in asphalt
runoff observed at the LSSC.
An interim PWQO of 0.03 mg/L has been set for TP (MOECC, 1994). Four of seven asphalt runoff
samples exceeded the PWQO, compared to only 7% of Hydromedia effluent samples. The single
Hydromedia effluent sample which exceeded the PWQO for TP occurred during the first flush of
the October 3, 2014 event. TP results from October 3 are shown below (Figure 34). Note that
samples shown with a concentration of 0 mg/L are below the minimum detection limit of
0.02 mg/L. Both asphalt runoff and Hydromedia effluent showed signs of a first flush followed by
76
lower concentrations. Asphalt concentrations were much higher, and the first flush was much more
pronounced than in Hydromedia effluent.
Figure 34. TP results (October 3, 2014)
In summary, the field results from the LSSC lot indicate good phosphorus removal performance,
despite other studies which indicate phosphorus removal in stormwater is difficult. The field results
do not suggest that any significant phosphorus is being leached from the PC. Residual phosphorus
concentrations in the Hydromedia effluent were generally acceptable.
5.4.2.2 Laboratory Scale Results
Observations of TP concentration for a single Hydromedia test specimen are shown in Figure 35.
All test results are from test specimen 1-A, and the samples analyzed were the same samples as
used for pH testing. Over the first 28 days, TP concentrations showed no decrease. These TP
concentrations are very high compared to the field results discussed in section 5.4.2.1. The
concentrations ranged from 2.94 to 4.45 mg/L, with a mean and median of 3.91 and 4.12,
77
respectively. The maximum concentration from the laboratory scale testing was more than 100
times higher than the maximum concentration observed during field testing at the LSSC.
Figure 35. Laboratory TP results of Hydromedia test specimens (175 mL water per flush)
TP concentrations from the laboratory scale testing were very high compared to the field test
results, and mean concentration exceeded the PWQO by 130 times. These results confirm that
Hydromedia leaches phosphorus at an early age, but show no indication of any decrease with time,
or any trend at all. There is no other potential source of phosphorus such as the native soil or clear
stone aggregate in this experiment, and deionized water was used, therefore the phosphorus must
be coming from a component of the pervious concrete. Additional testing with much larger
volumes of flush water were conducted on Specimens 7-A and 7-B in an attempt to observe a
decrease in TP concentration. Results are shown in Figure 36.
Figure 36: Laboratory TP results of Hydromedia test specimens (3.9 L water per flush)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 5 10 15 20 25 30Tota
l Ph
osp
ho
rus
(mg/
L as
PO
4)
Specimen Age (days)
0
0.05
0.1
0.15
0.2
0.25
0.3
0 3.9 7.8 11.7 15.6
Effl
uen
t To
tal P
ho
sph
oro
us
(mg/
L as
PO
4)
Cummulative Flush Volume (L)
78
Results from the larger volume flush test (Figure 36) showed much lower TP concentrations than
the results from the smaller volume flush test (Figure 35). The mean was 0.17 mg/L, compared to
3.91 mg/L. Despite this reduction in TP concentration of the Hydromedia effluent, the
concentration of each sample was still well above the PWQO of 0.03 mg/L, with a minimum
concentration of 0.08 mg/L. Furthermore, it is not clear if the lower TP concentrations observed in
this experiment are a result of less phosphorus remaining in the Hydromedia due to flushing, or
whether the larger volume of 3.9 L simply reduces contact of the water with the PC surface area,
limiting the opportunity for phosphorus to dissolve. 3.9 L was meant to simulate the depth of four
months of precipitation, but dosing the PC specimens with such a large volume over a short period
of time may not provide an accurate representation of TP concentrations that would be observed
under realistic rainfall conditions.
Long term experimentation, with realistic rainfall and ambient conditions would be required to
determine the time required to reduce TP concentrations of newly placed Hydromedia to
acceptable levels. However, after more than three years of curing and exposure to weather, the
Hydromedia effluent from the LSSC lot shows very low phosphorus concentrations. These levels
are generally well below the PWQO, and are considered acceptable.
5.5 Heavy Metals
Heavy metals are common in stormwater and PP effluent, particularly in urban areas. This section
discusses field results for a variety of different metals. Not all of the metals which were analyzed
are discussed here, just those with notable results. The nine subsections each contain discussion of
a different metal.
5.5.1 Arsenic
Arsenic was present above the minimum detection limit of 0.0001 mg/L in all Hydromedia effluent
and asphalt runoff samples. Three samples of asphalt runoff had concentrations below minimum
detection limits, but those samples had elevated minimum detection limits (up to either 0.02 mg/L
or 0.005 mg/L) due to high bromide or chloride levels in the samples. As a result, the arsenic
concentration results for asphalt runoff are censored. Descriptive statistics for arsenic
concentrations in Hydromedia effluent are shown below (Table 12).
79
Table 12. Descriptive statistics for arsenic concentration of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L)
Mean Median Low High Variance
LSSC 15 0.0006 0.0006 0.0004 0.0010 0.00000
Kortright (2010-2012)* 30 0.0058 0.0040 <0.0010 0.0244 40.072
Kortright (2013-2014) 15 0.0014 0.0015 <0.0010 0.0021 0.00022 * Drake et al., 2012
The high concentration in asphalt runoff could not be determined due to the elevated minimum
detection limits, but the lowest arsenic concentration observed was 0.0002 mg/L in asphalt runoff.
A PWQO of 0.1 mg/L has been established for arsenic, and an interim PWQO objective of 0.005
mg/L was established for enhanced protection of waters (MOECC, 1994). Despite censoring of
the results due to elevated MDLs, it can still be concluded that all the asphalt runoff and
Hydromedia effluent samples had arsenic concentrations below the PWQO. It is not possible to
determine if all asphalt runoff concentrations were below the interim PWQO of 0.005 mg/L. It is
not clear if arsenic is actually being removed by the PP, because the concentrations are so low.
However, it is evident that arsenic is not a contaminant of concern at the LSSC, and the
concentration of every Hydromedia effluent sample was below the interim PWQO. Change in
arsenic concentrations with time are shown for the October 3, 2014 event below (Figure 37). All
concentrations were below the interim PWQO for this event.
Figure 37: Arsenic Results (October 3, 2015)
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Arsenic concentrations at Kortright were higher than those observed at LSSC. The higher
concentrations observed at Kortright are likely a result of natural arsenic occurring with the
aggregates and native soils at that site. There is no contribution of arsenic from native soils at
LSSC due to the impermeable liner. The low levels of arsenic observed at LSSC are also assumed
to be from naturally occurring arsenic in the aggregates of the clear stone base.
5.5.2 Aluminum
Aluminum concentrations in all collected water samples exceeded the minimum detection limit of
0.01 mg/L. Descriptive statistics for aluminum concentrations in Hydromedia effluent are shown
below (Table 13).
Table 13. Descriptive statistics for aluminum concentration of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L)
Mean Median Low High Variance
LSSC 15 0.07 0.06 0.04 0.16 0.0010
Kortright (2010-2012)* 43 0.517 0.486 0.0477 1.260 0.103
Kortright (2013-2014) 15 0.253 0.162 0.0653 0.848 0.057 * Drake et al., 2012
Residual aluminum concentrations in PC effluent observed at LSSC were consistently lower than
those observed at Kortright, and showed much less variation. The highest concentrations at
Kortright are more similar to the high concentrations observed in asphalt runoff at LSSC.
PWQO’s for aluminum change depending on the pH of the water. For pH between 6.5 and 9.0,
which includes most of the collected water samples, the PWQO for aluminum is 0.075 mg/L
(MOECC, 1994). 33% of the Hydromedia effluent samples had concentrations which exceeded
the PWQO, compared to 86% percent of asphalt runoff samples. While removal was not complete,
it is apparent that the parking lot is filtering out aluminum. Change in aluminum concentrations
with time are shown for the October 3, 2014 event below (Figure 38).
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Figure 38. Aluminum results (October 3, 2014)
Aluminum concentrations in asphalt runoff show a clear first flush with a high aluminum
concentration above the PWQO, while Hydromedia effluent concentrations remain almost
constant throughout the event, and do not exceed the PWQO. Removal efficiency for this event
based on EMC was 73%.
5.5.3 Barium
Barium concentrations in all collected water samples exceeded the minimum detection limit of
0.001 mg/L. Descriptive statistics for barium concentrations in Hydromedia effluent are shown
below (Table 14).
Table 14. Descriptive statistics for barium concentration of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L)
Mean Median Low High Variance
LSSC 15 0.036 0.027 0.021 0.080 0.0004
Kortright (2010-2012)* 43 0.036 0.0265 0.0141 0.158 0.0009
Kortright (2013-2014) 15 0.0682 0.0488 0.0278 0.303 0.0045 * Drake et al., 2012
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The CWQG for barium is 1.0 mg/L (Health Canada, 2014). All samples of asphalt runoff and
Hydromedia effluent had concentrations well below this guideline, therefore barium is not a
contaminant of concern at the LSSC. Residual barium concentrations in PC effluent were very
similar at LSSC and Kortright, particularly from 2010-2012 at Kortright. Barium concentrations
increased with age at Kortright, but are still well below the CWQG. Change in barium
concentrations over the course of the October 3, 2014 event are shown below (Figure 39).
Figure 39. Barium results (October 3, 2014)
The concentrations during this event are all well below the CWQG, but it can be observed that
asphalt runoff concentrations again exhibit a first flush, while Hydromedia effluent concentrations
are consistent throughout the event. Asphalt runoff concentrations were initially higher than
Hydromedia effluent concentrations, but were actually lower by the end of the event. This could
be an indication that barium is dissolving from the Hydromedia or clear stone aggregate, but it is
not a concern since the concentrations are so low compared to the CWQG.
5.5.4 Chromium
Chromium was detected in all water samples except for one Hydromedia effluent sample which
was below the minimum detection limit of 0.002 mg/L. Descriptive statistics for chromium
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concentrations in Hydromedia effluent at LSSC are shown below (Table 15). Descriptive statistics
are not shown for chromium concentrations at Kortright, because the majority of samples were
below the MDL at that site of 0.005 mg/L. Detectable levels of chromium were observed in the
first year following construction of the parking lot, but were all below the MDL about one year
after construction of the parking lot.
Table 15. Descriptive statistics for chromium concentration of Hydromedia effluent
Mean Median Low High Variance
LSSC (mg/L) 0.019 0.021 <0.002 0.029 0.00005
Residual chromium concentrations were much higher at LSSC than was observed at Kortright. The
PWQO for chromium changes dependent on the valence of the chromium species. The PWQO
objectives are either 0.0089 mg/L for trivalent chromium or 0.001 mg/L for hexavalent chromium,
which is much more toxic (MOECC, 1994). Chromium valence was not determined in the analysis
for this project, but every Hydromedia effluent sample exceeded the PWQO in either case, except
for possibly the sample below the MDL. Therefore the residual concentration of chromium in
Hydromedia effluent is not acceptable. Change in chromium concentrations over the course of the
October 3, 2014 event are shown below (Figure 40).
Figure 40. Chromium results (October 3, 2014)
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These results show unique behavior compared to other contaminants, where the residual pollutant
concentrations are higher in Hydromedia effluent than asphalt runoff. While the asphalt runoff
showed typical behavior of a first flush and declining concentrations, Hydromedia effluent
concentrations actually increase throughout the event. Chromium does occur naturally in the
environment, but these residual concentrations are well above the PWQO. The steel industry is
prominent in this area of Ontario, but it is unlikely that the primary source of chromium is
atmospheric deposition, because chromium concentrations were lower is asphalt runoff than
Hydromedia effluent. This behavior suggest that chromium is being leached out of the PP system,
either from the concrete or the aggregate sub base.
Beecham et al. (2012) also observed high chromium concentrations (mean of 0.03 mg/L), but these
were present in both asphalt runoff and PP effluent, so the chromium was likely present in the
environment, and not a result of the PP. Welker et al. (2012) measured average chromium
concentrations in the pore water of PA and PC parking lots, and observed that all concentrations
were below a MDL of 0.0022 mg/L. These two studies, along with the observations at Kortright
and the LSSC indicate that there is a wide range of variation in chromium concentrations amongst
different study locations. At LSSC, the chromium concentration is high, and the source is likely
either the Hydromedia, or the subbase aggregate.
5.5.5 Copper
Copper was detected above the minimum detection limit of 0.002 mg/L in only 13% of
Hydromedia effluent samples, compared to 86% of asphalt runoff samples. The PWQO for copper
is 0.005 mg/L (MOECC, 1994). 7% of Hydromedia effluent samples exceeded the PWQO,
compared to 86% of asphalt runoff samples. This suggests near complete removal of copper due
to the PP system. Figure 41 shows copper concentrations over the course of the October 3 event.
Concentrations shown as 0 mg/L were below the minimum detection limit. Concentrations were
much higher in asphalt runoff than Hydromedia effluent over the entire event, and show high initial
concentrations during the first flush. All asphalt runoff concentrations during the event were above
the PWQO. Only one Hydromedia effluent sample had a detectable concentration, and it was still
well below the PWQO.
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Figure 41: Copper results (October 3, 2014)
5.5.6 Iron
Iron was detected above the minimum detection limit of 0.005 mg/L in 57% of Hydromedia
effluent samples, compared to 86% of asphalt runoff samples. Descriptive statistics for iron were
not calculated due to the high number of non-detects. 7% of Hydromedia effluent samples and
71% of asphalt runoff samples exceeded the PWQO of 0.3 mg/L for iron (MOECC, 1994). Change
in iron concentrations over the course of the October 3, 2014 event are shown below (Figure 42).
Concentrations shown as 0 mg/L are below the minimum detection limit of 0.005 mg/L.
86
Figure 42. Iron results (October 3, 2014)
Hydromedia effluent concentrations are much lower than asphalt runoff, and asphalt runoff shows
the typical first flush with high concentrations, followed by a decline. The Hydromedia effluent
concentrations are consistently low. These results, along with the above comparison to the PWQO
indicate that Hydromedia effluent generally contains acceptable residual concentrations of iron.
5.5.7 Mercury
Mercury was detected above the minimum detection limit of 0.02 μg/L in 79% of Hydromedia
effluent samples, and in all of the asphalt runoff samples. Samples were not analyzed for mercury
at Kortright. The PWQO for mercury is 0.2 μg/L (MOECC, 1994). Eight out of fifteen Hydromedia
effluent samples had mercury concentrations above the PWQO, and five of seven asphalt runoff
samples exceeded the PWQO. Six of the eight Hydromedia samples which exceeded the PWQO
were collected on October 3, 2014. Change in mercury concentrations over the course of the
October 3 event are shown below (Figure 43).
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Figure 43. Mercury results (October 3, 2014)
Mercury concentrations for Hydromedia effluent were higher on October 3 than for any other
measured event, with an EMC of 0.00203 mg/L. This is ten times higher than the PWQO. Other
than a spike in the asphalt runoff concentration to 0.00717 mg/L, the asphalt runoff concentrations
were slightly lower, but not very different from Hydromedia effluent concentrations. The EMC for
asphalt runoff was 0.00141 mg/L. These observations indicate that Hydromedia is not very
effective at removing mercury to acceptable levels. Due to the potential toxicity of mercury, this
contaminant may be of considerable concern.
None of the other studies reviewed analyzed mercury as a pollutant, so no comparisons can be
made. Eckley & Branfireun (2008) determined mercury levels in rainwater and urban stormwater
runoff in Toronto. They found mercury EMC’s in rainwater from 0.0072 to 0.0372 μg/L, with a
mean of 0.0211 μg/L. Mercury EMC’s in surface runoff from a parking lot ranged from 0.0075 to
0.0352 μg/L, with a mean of 0.0184 μg/L. The concentrations in both rainwater and runoff were
very similar, indicating that most of the mercury pollutant came from atmospheric deposition.
88
Mercury concentrations were considerably lower in runoff from a mixed land use area, ranging
from 0.0050 to 0.0114 μg/L, with a mean of 0.0072 μg/L. The majority of mercury was in
particulate form in both rainwater and stormwater runoff.
The concentrations of mercury at the LSSC were generally much higher (two orders or magnitude
in some cases) than those observed in the Eckley & Branfireun (2008) study for both asphalt runoff
and Hydromedia effluent. At the LSSC, rainwater samples were not analyzed for water quality, so
the source of this mercury is unknown. Particulate mercury concentrations tend to be highest on
very small particles (< 63μm) (Eckley & Branfireun, 2008). Hydromedia may not be able to
effectively remove such small particles, as supported by the observations at LSSC.
5.5.8 Molybdenum
Molybdenum is of interest because it was generally not present in asphalt runoff, but almost always
present in Hydromedia effluent. Only one out of seven asphalt runoff samples contained
molybdenum above the minimum detection limit of 0.01 mg/L, while fourteen of fifteen
Hydromedia effluent samples had concentrations above the minimum detection limit. Descriptive
statistics for molybdenum concentrations in Hydromedia effluent are shown below (Table 16).
Table 16. Descriptive statistics for molybdenum concentration of Hydromedia effluent
Dataset # of
samples
Concentration (mg/L)
Mean Median Low High Variance
LSSC 15 0.020 0.020 0.005 0.040 0.00008
Kortright (2010-2012)* 43 0.0070 0.0062 0.0017 0.00194 0.000015
Kortright (2013-2014) 15 0.0036 0.0023 0.0009 0.00118 0.000008 * Drake et al., 2012
These results suggest that molybdenum is present in Hydromedia or the clear stone aggregates and
it is leaching into the effluent. Concentrations at LSSC were much higher than those observed at
Kortright. The higher concentrations are likely due to the presence of more molybdenum in the
local construction materials around St. Catharines. The PWQO for molybdenum is 0.04 mg/L
(MOECC, 1994). None of the asphalt runoff or Hydromedia effluent samples had concentrations
which exceeded the PWQO, therefore this level of molybdenum leaching is acceptable. However,
for a newer parking lot, higher molybdenum concentrations which exceed the PWQO are possible,
because the Hydromedia may contain more molybdenum shortly after construction.
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5.5.9 Zinc
Zinc was detected above the minimum detection limit of 0.005 mg/L in six of seven asphalt runoff
samples, but only two of fifteen of Hydromedia effluent samples. The PWQO for zinc is 0.03 mg/L
(MOECC, 1994). One Hydromedia effluent sample concentration exceeded the PWQO, compared
to six asphalt runoff samples. Change in zinc concentrations over the course of the October 3, 2014
event are shown below (Figure 44). All Hydromedia effluent concentrations were below the
minimum detection limit, and are shown as 0 mg/L on the figure.
Figure 44. Zinc results (October 3, 2014)
Hydromedia effluent concentrations are much lower than asphalt runoff, and asphalt runoff shows
the typical first flush with high concentrations, followed by a decline. The Hydromedia effluent
concentrations are consistently low. These results, along with the above comparison to the PWQO
indicate that Hydromedia performs very well at removing zinc, and almost no residual zinc would
be expected in the effluent.
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Chapter 6 Conclusions and Recommendations
This thesis documents the first research into the hydrologic and water quality performance of a
zero-exfiltration Hydromedia parking lot in Ontario, and the first detailed study on any
Hydromedia parking lot in an urbanized environment in Ontario. Overall, the performance of the
three year old parking lot at the LSSC in St. Catharines was overwhelmingly positive. Both
hydrologic and water quality benefits were demonstrated for every rainfall event observed from
July to November 2014, and for most pollutants and water quality indicators. This chapter
summarizes the benefits observed and the environmental implications, as well as some areas for
improvement and recommendations for further research. Conclusions are discussed in the context
of each objective described in Chapter 1.
Conclusions and Recommendations
Objective 1: Assess the current infiltration capacity of the Hydromedia and determine if
maintenance is required.
Mean and median surface infiltration capacity of Hydromedia at LSSC were determined to be
1,280 and 1,490 cm/h, respectively, in accordance with ASTM C1701. Three years after
construction, the infiltration capacity is more than sufficient to infiltrate any peak rainfall intensity
that would be expected. The lowest infiltration capacities were observed in the centre driving lanes,
particularly at the entrance and exit to the parking lot cell. Clogging was only observed at one test
location, and surface ponding was occasionally observed at that location. All other areas of the
Hydromedia surface showed sufficient infiltration capacity.
These high results indicate that maintenance to partially restore infiltration capacity is not
necessary at this time, and may not be beneficial, since maintenance on PC has not been
demonstrated to be effective. No maintenance to restore infiltration has been carried out at LSSC,
and yet the Hydromedia is still performing adequately. This demonstrates that under these
conditions, with landscaping designed to minimize sources of debris, winter maintenance
programs which do not include sanding or salting, and with limited back and forth traffic typical
of office parking lots, maintenance is not required early in the life of a Hydromedia parking lot.
Continued monitoring of infiltration capacity, especially in the areas of the lot prone to surface
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clogging, would help to determine the frequency of maintenance that is required, if any is required
at all. Annual monitoring of infiltration capacity at LSSC would provide this information.
With a mean infiltration capacity greater than 1,000 cm/hr after three years of service, gradual loss
of infiltration capacity may not be a problem over the design life of the Hydromedia. As the voids
become partially clogged, the capacity is still much higher than required to infiltrate all rainfall. If
the rate of decline in capacity is slow enough, there may still be sufficient capacity at the end of
the pavement’s structural life. Further, such a high infiltration capacity means that additional run
on from adjacent areas, such as asphalt parking lots, could be directed to a Hydromedia surface
and infiltrated, although this would likely increase the rate of infiltration capacity decline. The use
of both traditional asphalt and PC may reduce the higher capital cost associated with PC
installation. Additional research to determine the rate of decline would provide the information to
determine how much run on can be directed towards a Hydromedia surface.
Objective 2: Evaluate the hydrologic performance of the Hydromedia parking lot, including
volume and peak flows reductions, and lag times.
Hydrologic performance of the Hydromedia parking lot was improved compared to estimates of
asphalt surface runoff for every observed rainfall event. Overall, the volume reduction was
determined to be 44%. On a single event basis, runoff volume reductions ranged from 17 to 100%.
A total of thirty four rainfall events were recorded, and sixteen produced no measureable discharge
of Hydromedia effluent. Events less than 3 mm produced no discharge. Large events greater than
20 mm had the smallest volume reductions. These smaller volume reductions for larger events are
a result of the impermeable liner preventing exfiltration of stormwater to the native soil.
Despite having lower volume reductions, large events still showed large peak flow reductions, and
a lag time from peak rainfall intensity to peak discharge of Hydromedia effluent. Large events had
the smallest peak reductions, but were still high with a minimum of 73% for the most intense
rainfall event. Smaller events had larger volume and peak flow reductions. Regardless of the size
of the event, all events showed a more desirable hydrologic response from Hydromedia effluent
discharge than the estimated asphalt surface runoff response. The zero exfiltration Hydromedia lot
reduced discharge volumes, and attenuated flow by releasing stormwater over a long period for all
observed events.
92
The PP system provided adequate peak flow control for the most intense rainfall event observed,
with a return period of approximately 2 years. Observed peak discharge of Hydromedia effluent
was less than the predicted surface runoff peak flow from modelled pre-development conditions,
which satisfies the stormwater quantity control requirements of NPCA. Hydromedia discharge
volume was greater than the pre-development volume, because exfiltration cannot occur within
the system. Peak discharge rates could be further reduced by either restricting the outflow valve in
the catch basin at LSSC, or more generally for PP parking lots, elevating the subdrains to allow
for internal storage of water (especially for partial exfiltration systems).
Multiple linear regression analysis of hydrologic data showed that effluent discharge volume was
most strongly correlated to rainfall depth, but also correlated to peak rainfall intensity. Peak
discharge exhibits a more complicated relationship, which is correlated to peak rainfall intensity,
rainfall depth, as well as the product of rainfall depth and rainfall intensity. The strongest single
predictor of peak effluent discharge was rainfall depth. Insufficient hydrologic data was collected
to produce a reliable regression model for either effluent volume or peak discharge, but the
regression analysis points to rainfall depth as the most significant single predictor of both effluent
volume and peak discharge. With additional data collection, it may be possible to produce a simple,
reliable regression model to predict peak discharge and volume of Hydromedia for zero exfiltration
systems, based only on rainfall depth and peak rainfall intensity. Zero exfiltration systems are not
ideal from an environmental performance perspective, but may be the only feasible alternative in
dense urban areas with poorly draining soils. Such a model would be an extremely useful tool for
municipal designers of PC parking lots in urban areas, and would help to address the
implementation barrier of lack of understanding surrounding PP design methods.
Objective 3: Evaluate the water quality of Hydromedia effluent and identify pollutants which
may be of concern to surface water quality.
Overall, the water quality of Hydromedia effluent was improved compared to asphalt surface
runoff for many water quality parameters including TSS, oil and grease, TN, TP, and several metals
including copper, iron, and zinc. Most water quality parameters were consistently below relevant
PWQO’s and CWQG’s in Hydromedia effluent samples, with a few exceptions, including pH,
aluminum, chromium, and mercury.
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Mean and median pH of effluent were both 8.7, just above the PWQO of 8.5, however these results
were slightly skewed by two high pH observations above 9.4 early in the monitoring period. A
mean pH of 8.7 is higher than would be expected for a three year old Hydromedia parking lot, and
was higher than the pH observed at the Kortright Centre at a similar age. While the pH at LSSC
was just above the guideline after three years, the impact is manageable considering the reduced
discharge volume compared to asphalt. However, high pH of early age Hydromedia effluent should
be addressed. Laboratory results on prepared Hydromedia specimens show pH above 12 early in
the life of the pavement. Discharge of large volumes of stormwater at a pH of 12 could have
harmful effects on aquatic life in receiving water bodies. Further research should be conducted to
assess the impact of discharge of high pH water on aquatic life, and if necessary, development of
methods to mitigate the impacts or reduce the pH should be investigated. Laboratory testing of pH
should continue to determine the time required for pH of early age Hydromedia effluent to decrease
below the PWQO.
Aluminum concentrations in Hydromedia effluent were below those observed in asphalt runoff,
and much lower at LSSC than those observed at Kortright. However, 33% of Hydromedia effluent
samples were above the PWQO. The impact of elevated levels of aluminum should be evaluated,
considering the aluminum concentrations were above the PWQO at both sites in Ontario.
Chromium was detected in all but one Hydromedia effluent sample, and was above the PWQO for
chromium in all those samples. Residual concentrations were higher in Hydromedia effluent than
asphalt surface runoff, which suggests that chromium may be dissolving out of the Hydromedia,
or was previously captured in the Hydromedia or aggregate subbase and is now being released.
With residual levels in the effluent well above the PWQO, further investigation is required to
determine the source of chromium. High levels of chromium in PC effluent were not observed at
Kortright, so it may be from locally sourced materials.
High residual mercury concentrations above the PWQO were detected in both Hydromedia
effluent and asphalt surface runoff. This suggests that mercury is present in the environment at
LSSC, and that Hydromedia does not effectively remove mercury from stormwater. High
concentrations of mercury are not common in the environment, but levels appear to be high at
LSSC. Additional sampling of asphalt surface runoff and Hydromedia effluent should be
conducted to confirm this observation, as well as sampling of rainfall and surface sediments at
94
LSSC to verify that mercury concentrations are high in the environment. Additional treatment with
other stormwater BMP’s may be necessary at sites where mercury concentrations are high.
Assessment of the impact of the discharge of pollutants is difficult to assess when only grab
samples are collected, because pollutant loads cannot be determined. In some cases, while the
residual concentration of a pollutant in Hydromedia effluent may be above guidelines, the actual
impact on surface water quality may be acceptable, especially when considering volume reductions
(and therefore pollutant load reductions) associated with PP. For contaminants with residual
concentrations above the guidelines, automated sampling and determination of pollutant loadings
is required to determine the impact on surface water quality, which has not been carried out for
this project.
Chloride concentrations were not analyzed as part of this project, because the monitoring period
occurred over the summer, and chloride concentrations are highest in stormwater during the winter,
due to application of deicing salts. Chloride concentrations of Hydromedia effluent for a zero-
exfiltration system have not been investigated in Ontario. Zero-exfiltration systems may actually
be desirable where deicing salts are applied, because chloride is highly mobile and could migrate
into groundwater. However, the impact of chloride on surface waters would be greater for zero-
exfiltration systems. Year round monitoring of chloride concentrations would help to assess this
impact.
Objective 4: Develop recommendations for potential improvements to the design and operation
of Hydromedia and zero exfiltration systems, and identify opportunities for further research.
The LSSC is a unique site in Ontario, because it is a zero exfiltration system with three types of
PP, and has been designed such that a monitoring program could be implemented. Further, no
water quality or hydrologic monitoring has been conducted on a porous asphalt site in Ontario.
These unique properties, along with urban surroundings, make the LSSC an ideal site for a long
term evaluation of PP performance in Ontario. While a zero exfiltration system may not be ideal
from a volume reduction performance perspective, it provides a worst-case scenario, and
eliminates the variability of local native soils. Demonstrating adequate long-term performance of
PP’s at LSSC would provide proof that PP’s can be effective BMP’s in almost all urban areas of
Ontario.
95
Continued research would be required to demonstrate adequate long term performance. This would
include the permanent installation of flow monitoring equipment in the catch basin of all three PP
cells, and at the outlet of the asphalt cell to measure surface runoff. In addition to monitoring flows,
automated sampling equipment could be installed to collect flow weighted samples, and ultimately
determine pollutant loads and the impact on local watercourses.
While this project has focused primarily on developing a better understanding of the hydrologic
and water quality performance of Hydromedia, other barriers must be overcome before widespread
adoption of PP’s, and LID in general, becomes reality. Poor understanding of life cycle costs of
PP compared to conventional pavement and stormwater management systems is the most
significant barrier. It is widely understood that the initial cost of PP is higher, but very little
research has been conducted to determine if PP or conventional asphalt are more economical over
the entire life cycle of the infrastructure.
In summary, this study demonstrated that Hydromedia provides hydrologic benefits for all rainfall
events, and water quality benefits for most pollutants. Further consideration should be given to
elevated early pH of effluent, and poor removal of chromium and mercury. Continued monitoring
should be conducted to demonstrate sufficient long term infiltration capacity (or maintenance
requirements), and long term hydrologic and water quality performance. The LSSC is an ideal site
to monitor long term performance of three types of PP, and to determine the suitability of PP as a
stormwater BMP in Ontario.
96
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101
Appendix A – Weir Box Design Drawing
102
103
Appendix B – Lamotte Smart 3 Colorimeter TP Test Procedure
104
105
106
107
Appendix C – Regression Analysis Diagnostic Plots
108
Figure 45: Diagnostic Plots for Hydromedia Effluent Volume
1 2 3 4 5
-1.0
-0.5
0.0
0.5
Fitted values
Resid
uals
Residuals vs Fitted
7
18
16
-2 -1 0 1 2
-2-1
01
2
Theoretical QuantilesS
tandard
ized r
esid
uals
Normal Q-Q
7
18
16
1 2 3 4 5
0.0
0.5
1.0
1.5
Fitted values
Sta
ndard
ized r
esid
uals
Scale-Location
718
16
0.0 0.1 0.2 0.3
-2-1
01
2
Leverage
Sta
ndard
ized r
esid
uals
Cook's distance1
0.5
0.5
1
Residuals vs Leverage
19
18
6
lm(SQDEPTHHM ~ SQDEPTHRAIN + SQPEAKRAIN)
109
Figure 46: Diagnostic Plots for Peak Hydromedia Discharge
110
Figure 47: Diagnostic Plots for Peak Hydromedia Discharge Omitting July 7 Outlier
0 2 4 6 8 10
-1.0
-0.5
0.0
0.5
1.0
Fitted values
Resid
uals
Residuals vs Fitted
13
7
17
-2 -1 0 1 2
-10
12
Theoretical Quantiles
Sta
ndard
ized r
esid
uals
Normal Q-Q
13
7
17
0 2 4 6 8 10
0.0
0.5
1.0
1.5
Fitted values
Sta
ndard
ized r
esid
uals
Scale-Location
13
7
17
0.0 0.1 0.2 0.3 0.4 0.5 0.6
-2-1
01
2
Leverage
Sta
ndard
ized r
esid
uals
Cook's distance
1
0.5
0.5
1
Residuals vs Leverage
8
13
17
lm(SQPEAKHM ~ SQDEPTHRAIN + SQPEAKRAIN + I(SQDEPTHRAIN * SQPEAKRAIN))
111
Appendix D – Laboratory Water Quality Analysis Reports
112
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 1
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 04-Jul-14
Toronto, ON M5S 1A4 #Rec'd: 2 x Aqueous Sets
Phone: 416-946-0164 Complete: 18-Jul-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-1-1 987-1-2 Niagara In-Lab Lab Test Analyst
Test AP-07032014 HM-07042014 Storm Sewer QA/QC Blank Date
Parameter 03-Jul-14 (pm) 04-Jul-14 9pm) Criteria %Recov
pH (SI) 5.89 9.45 no criteria set ~ ~ 04-Jul-14 BJ
Alkalinity as CaC03 15 10 no criteria set 94% <1 16-Jul-14 LJ
Total Suspended Solids 78 7 0 98% <1 16-Jul-14 LJ
Total Oil+Grease 2 1 0 94% <1 15-Jul-14 LJ
Mineral Oil+Grease 2 1 0 100% <1 16-Jul-14 LJ
Total Kjeldahl Nitrogen 3.3 < 0.5 0 93% <0.5 17-Jul-14 FB
Total Phosphorus < 0.02 < 0.02 0 97% <0.02 07-Jul-14 LJ
Phosphate < 0.06 < 0.06 0 calculation < 0.06 10-Jul-14 SJ
Aluminum 0.04 0.11 0 103% <0.01 11-Jul-14 A.S.
Antimony 0.001 0.003 0 104% <0.0001 11-Jul-14 R.F.
Arsenic 0.0002 0.0010 0 112% <0.0001 11-Jul-14 R.F.
Barium 0.042 0.080 0 104% <0.001 11-Jul-14 A.S.
Cadmium < 0.005 < 0.005 0 114% <0.005 11-Jul-14 R.F.
Chromium 0.020 < 0.002 0 102% <0.002 11-Jul-14 R.F.
Cobalt < 0.005 < 0.005 0 103% <0.005 11-Jul-14 A.S.
Copper < 0.002 0.034 0 106% <0.002 11-Jul-14 A.S.
Iron < 0.005 0.38 0 106% <0.005 11-Jul-14 R.F.
Lead < 0.02 < 0.02 0 107% <0.02 11-Jul-14 R.F.
Manganese < 0.001 0.121 0 103% <0.001 11-Jul-14 A.S.
Mercury 0.00006 0.00003 0 102% <0.00002 11-Jul-14 R.F.
Molybdenum 0.03 < 0.01 0 102% <0.01 11-Jul-14 A.S.
Nickel < 0.01 < 0.01 0 102% <0.01 11-Jul-14 R.F.
Selenium 0.003 < 0.001 0 120% <0.001 11-Jul-14 R.F.
Silver < 0.005 < 0.005 0 105% <0.005 11-Jul-14 A.S.
Tin < 0.05 < 0.05 0 100% <0.05 11-Jul-14 A.S.
Zinc < 0.005 0.128 0 102% <0.005 11-Jul-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 17-Jul-14
113
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 2
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 04-Jul-14
Toronto, ON M5S 1A4 #Rec'd: 2 x Aqueous Sets
Phone: 416-946-0164 Complete: 24-Jul-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-2-1 Niagara In-Lab Lab Test Analyst
Test Pervious Concrete Storm Sewer QA/QC Blank Date
Parameter HM-07-07-2014 0900hrs Criteria %Recov
pH (SI) 8.74 no criteria set ~ ~ 08-Jul-14 FB
Alkalinity as CaC03 10 no criteria set 94% < 1 16-Jul-14 LJ
Total Suspended Solids 3 0 98% 16-Jul-14 LJ
Total Oil+Grease 4 0 98% <1 23-Jul-14 FB
Mineral Oil+Grease 1 0 93% 23-Jul-14 FB
Total Kjeldahl Nitrogen 36.0 0 87% <0.5 22-Jul-14 LJ/FB
Total Phosphorus 0.03 0 109% <0.02 09-Jul-14 LJ
Phosphate 0.09 0 calculation < 0.06 10-Jul-14 SJ
Aluminum 0.08 0 103% <0.01 11-Jul-14 A.S.
Antimony 0.0009 0 104% <0.0001 11-Jul-14 R.F.
Arsenic 0.0008 0 112% <0.0001 11-Jul-14 R.F.
Barium 0.080 0 104% <0.001 11-Jul-14 A.S.
Cadmium < 0.005 0 114% <0.005 11-Jul-14 R.F.
Chromium 0.029 0 102% <0.002 11-Jul-14 R.F.
Cobalt < 0.005 0 103% <0.005 11-Jul-14 A.S.
Copper < 0.002 0 106% <0.002 11-Jul-14 A.S.
Iron 0.01 0 106% <0.005 11-Jul-14 R.F.
Lead < 0.02 0 107% <0.02 11-Jul-14 R.F.
Manganese < 0.001 0 103% <0.001 11-Jul-14 A.S.
Mercury < 0.00002 0 102% <0.00002 11-Jul-14 R.F.
Molybdenum 0.03 0 102% <0.01 11-Jul-14 A.S.
Nickel < 0.01 0 102% <0.01 11-Jul-14 R.F.
Selenium 0.005 0 120% <0.001 11-Jul-14 R.F.
Silver < 0.005 0 105% <0.005 11-Jul-14 A.S.
Tin < 0.05 0 100% <0.05 11-Jul-14 A.S.
Zinc < 0.005 0 102% <0.005 11-Jul-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 24-Jul-14
114
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 3
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 28-Jul-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Sets
Phone: 416-946-0164 Complete: 12-Aug-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-3-1 Niagara In-Lab Lab Test Analyst
Test Concrete, HM07282014 Storm Sewer QA/QC Blank Date
Parameter 28-July-14 8:35 Criteria %Recov
pH (SI) 9.88 no criteria set ~ ~ 28-Jul-14 FB
Alkalinity as CaC03 15 no criteria set 96% < 1 11-Aug-14 LJ
Total Suspended Solids 9 0 99% <1 05-Aug-14 LJ
Total Oil+Grease <1 0 99% <1 07-Aug-14 FB
Mineral Oil+Grease <1 0 93% <1 07-Aug-14 FB
Total Kjeldahl Nitrogen 1.5 0 99% <0.5 07-Aug-14 BJ/FB
Total Phosphorus <0.02 0 100% <0.02 30-Jul-14 LJ
Phosphate <0.06 0 calc. < 0.06 12-Aug-14 SJ
Aluminum 0.07 0 99% <0.01 05-Aug-14 AS
Antimony 0.0009 0 98% <0.0001 06-Aug-14 AS
Arsenic 0.0006 0 94% <0.0001 06-Aug-14 AS
Barium 0.032 0 99% <0.001 05-Aug-14 AS
Cadmium < 0.005 0 100% <0.005 05-Aug-14 AS
Chromium 0.015 0 100% <0.002 05-Aug-14 AS
Cobalt < 0.005 0 100% <0.005 05-Aug-14 AS
Copper < 0.002 0 98% <0.002 05-Aug-14 AS
Iron 0.007 0 99% <0.005 05-Aug-14 AS
Lead < 0.02 0 98% <0.02 05-Aug-14 AS
Manganese < 0.001 0 104% <0.001 05-Aug-14 AS
Mercury 0.00002 0 102% <0.00002 01-Aug-14 AS
Molybdenum 0.01 0 96% <0.01 05-Aug-14 AS
Nickel < 0.01 0 98% <0.01 05-Aug-14 AS
Selenium < 0.005 0 100% <0.005 06-Aug-14 AS
Silver < 0.005 0 92% <0.005 05-Aug-14 AS
Tin < 0.05 0 95% <0.05 05-Aug-14 AS
Zinc < 0.005 0 99% <0.005 05-Aug-14 AS
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 12-Aug-14
115
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 4
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 05-Aug-14
Toronto, ON M5S 1A4 #Rec'd: 2 x Aqueous Sets
Phone: 416-946-0164 Complete: 21-Aug-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-4-1 987-4-2 Niagara In-Lab Lab Test Analyst
Test HM08052014 AP08052014 Storm Sewer QA/QC Blank Date
Parameter 05-Aug-14 10:29 05-Aug-14 10:47 Criteria %Recov
pH (SI) 8.82 8.11 no criteria set ~ ~ 05-Aug-14 COC
Alkalinity as CaC03 18 16 no criteria set 0.96 < 1 11-Aug-14 LJ
Total Suspended Solids 6 18 0 0.96 < 1 11-Aug-14 LJ
Total Oil+Grease < 1 3 0 98% < 1 07-Aug-14 FB
Mineral Oil+Grease < 1 2 0 93% < 1 07-Aug-14 FB
Total Kjeldahl Nitrogen < 0.5 2.7 0 100% < 0.5 20-Aug-14 FB
Total Phosphorus < 0.02 < 0.02 0 103% < 0.02 07-Aug-14 LJ
Phosphate < 0.06 <0.06 0 calc. < 0.06 20-Aug-14 FB
Aluminum 0.09 0.28 0 97% < 0.01 08-Aug-14 AS
Antimony 0.0012 0.0012 0 100% < 0.0001 11-Aug-14 AS
Arsenic 0.0004 0.0006 0 97% < 0.0001 11-Aug-14 AS
Barium 0.053 0.034 0 97% < 0.001 08-Aug-14 AS
Cadmium < 0.005 < 0.005 0 99% < 0.005 08-Aug-14 AS
Chromium 0.026 0.003 0 98% < 0.002 08-Aug-14 AS
Cobalt < 0.005 < 0.005 0 100% < 0.005 08-Aug-14 AS
Copper 0.004 0.013 0 99% < 0.002 08-Aug-14 AS
Iron 0.044 0.396 0 98% < 0.005 08-Aug-14 AS
Lead < 0.02 < 0.02 0 97% < 0.02 08-Aug-14 AS
Manganese 0.003 0.040 0 98% < 0.001 08-Aug-14 AS
Mercury 0.00017 0.00012 0 97% < 0.00002 11-Aug-14 AS
Molybdenum 0.04 < 0.01 0 98% < 0.01 08-Aug-14 AS
Nickel < 0.01 < 0.01 0 98% < 0.01 08-Aug-14 AS
Selenium 0.003 < 0.001 0 100% < 0.001 11-Aug-14 AS
Silver < 0.005 < 0.005 0 96% < 0.005 08-Aug-14 MK
Tin < 0.05 < 0.05 0 94% < 0.05 08-Aug-14 AS
Zinc 0.025 0.049 0 97% < 0.005 08-Aug-14 AS
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 20-Aug-14
116
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 5
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 05-Sep-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Set
Phone: 416-946-0164 Complete: 22-Sep-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-5-1 Niagara In-Lab Lab Test Analyst
Test HM-09052014 Storm Sewer QA/QC Blank Date
Parameter Pervious Concrete 12:25pm Criteria %Recov
pH (SI) 8.46 no criteria set ~ ~ 05-Sep-14 FB
Alkalinity as CaC03 22 no criteria set 100% < 1 09-Sep-14 LJ
Total Suspended Solids 4 0 92% < 1 10-Sep-14 LJ
Total Oil+Grease 1 0 98% < 1 11-Sep-14 FB
Mineral Oil+Grease 1 0 93% < 1 11-Sep-14 FB
Total Kjeldahl Nitrogen < 0.5 0 100% < 0.5 22-Sep-14 FB
Total Phosphorus < 0.02 0 110% < 0.02 08-Sep-14 LJ
Phosphate < 0.06 0 calc. < 0.06 22-Sep-14 FB
Aluminum 0.10 0 96% < 0.01 12-Sep-14 DL
Antimony 0.0007 0 97% < 0.0001 12-Sep-14 DL
Arsenic 0.0007 0 94% < 0.0001 12-Sep-14 DL
Barium 0.034 0 96% < 0.001 12-Sep-14 DL
Cadmium < 0.005 0 100% < 0.005 12-Sep-14 A.S.
Chromium 0.02 0 99% < 0.002 12-Sep-14 A.S.
Cobalt < 0.005 0 99% < 0.005 12-Sep-14 A.S.
Copper < 0.002 0 99% < 0.002 12-Sep-14 A.S.
Iron 0.014 0 98% < 0.005 12-Sep-14 A.S.
Lead < 0.02 0 96% < 0.02 12-Sep-14 A.S.
Manganese < 0.001 0 99% < 0.001 12-Sep-14 A.S.
Mercury < 0.00002 0 103% < 0.00002 12-Sep-14 A.S.
Molybdenum 0.03 0 97% < 0.01 12-Sep-14 A.S.
Nickel < 0.01 0 101% < 0.01 12-Sep-14 A.S.
Selenium 0.004 0 97% < 0.001 12-Sep-14 A.S.
Silver < 0.005 0 97% < 0.005 12-Sep-14 A.S.
Tin < 0.05 0 95% < 0.05 12-Sep-14 A.S.
Zinc < 0.005 0 98% < 0.005 12-Sep-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 22-Sep-14
117
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 6
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 16-Sep-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Set
Phone: 416-946-0164 Complete: 26-Sep-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, LJ
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-6-1 Niagara In-Lab Lab Test Analyst
Test AP09152014 Storm Sewer QA/QC Blank Date
Parameter 22:25 Criteria %Recov
pH (SI) 6.63 no criteria set ~ ~ 16-Sep-14 LJ
Alkalinity as CaC03 18 no criteria set 94% < 1 24-Sep-14 LJ
Total Suspended Solids 92 0 92% < 1 17-Sep-14 LJ
Total Oil+Grease 6 0 90% < 1 22-Sep-14 LJ
Mineral Oil+Grease 2 0 99% < 1 22-Sep-14 LJ
Total Kjeldahl Nitrogen 4.2 0 100% < 0.5 22-Sep-14 FB
Total Phosphorus 0.24 0 111% < 0.02 17-Sep-14 LJ
Phosphate 0.73 0 ~ < 0.06 22-Sep-14 FB
Aluminum 0.85 0 99% < 0.01 19-Sep-14 A.S.
Antimony 0.0012 0 94% < 0.0001 19-Sep-14 A.S.
Arsenic 0.0007 0 94% < 0.0001 19-Sep-14 A.S.
Barium 0.041 0 100% < 0.001 19-Sep-14 A.S.
Cadmium 1.05 0 105% < 0.005 19-Sep-14 A.S.
Chromium 0.005 0 103% < 0.002 19-Sep-14 A.S.
Cobalt < 0.005 0 105% < 0.005 19-Sep-14 A.S.
Copper 0.033 0 102% < 0.002 19-Sep-14 A.S.
Iron 1.63 0 105% < 0.005 19-Sep-14 A.S.
Lead < 0.02 0 101% < 0.02 19-Sep-14 A.S.
Manganese 0.089 0 104% < 0.001 19-Sep-14 A.S.
Mercury 0.120 0 102% < 0.00002 19-Sep-14 M.K.
Molybdenum < 0.01 0 99% < 0.01 19-Sep-14 A.S.
Nickel < 0.01 0 104% < 0.01 19-Sep-14 A.S.
Selenium < 0.001 0 100% < 0.001 19-Sep-14 A.S.
Silver 0.014 0 96% < 0.005 19-Sep-14 A.S.
Tin < 0.05 0 96% < 0.05 19-Sep-14 A.S.
Zinc 0.084 0 101% < 0.005 19-Sep-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 25-Sep-14
118
NIA
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NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 8
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 08-Oct-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Set
Phone: 416-946-0164 Complete: 22-Oct-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB
SubLab: Cad
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-8-1 Niagara In-Lab Lab Test Analyst
Test HM-10082014 Storm Sewer QA/QC Blank Date
Parameter 8-Oct-14 @ 8:30 am Criteria %Recov
pH (SI) 8.86 no criteria set ~ ~ 08-Oct-14 BJ
Alkalinity as CaC03 12 no criteria set 98% < 1 21-Oct-14 FB
Total Suspended Solids 1 0 98% < 1 09-Oct-14 FB
Total Oil+Grease < 1 0 98% < 1 22-Oct-14 FB
Mineral Oil+Grease < 1 0 93% < 1 22-Oct-14 FB
Total Kjeldahl Nitrogen < 0.5 0 96% < 0.5 10-Oct-14 BJ
Total Phosphorus < 0.02 0 93% < 0.02 21-Oct-14 FB
Phosphate < 0.06 0 calculation < 0.06 21-Oct-14 FB
Aluminum 0.04 0 97% < 0.01 10-Oct-14 A.S.
Antimony 0.0005 0 101% < 0.0001 10-Oct-14 A.S.
Arsenic 0.0005 0 99% < 0.0001 10-Oct-14 A.S.
Barium 0.022 0 100% < 0.001 10-Oct-14 A.S.
Cadmium < 0.005 0 97% < 0.005 10-Oct-14 A.S.
Chromium 0.02 0 100% < 0.002 10-Oct-14 A.S.
Cobalt 0.006 0 95% < 0.005 10-Oct-14 A.S.
Copper < 0.002 0 95% < 0.002 10-Oct-14 A.S.
Iron < 0.005 0 98% < 0.005 10-Oct-14 A.S.
Lead < 0.02 0 99% < 0.02 10-Oct-14 A.S.
Manganese < 0.001 0 96% < 0.001 10-Oct-14 A.S.
Mercury < 0.00002 0 98% < 0.00002 10-Oct-14 A.S.
Molybdenum 0.02 0 100% < 0.01 10-Oct-14 A.S.
Nickel < 0.01 0 99% < 0.01 10-Oct-14 A.S.
Selenium 0.003 0 96% < 0.001 10-Oct-14 A.S.
Silver < 0.005 0 101% < 0.005 10-Oct-14 A.S.
Tin < 0.05 0 95% < 0.05 10-Oct-14 A.S.
Zinc < 0.005 0 100% < 0.005 10-Oct-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 22-Oct-14
120
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 9
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 25-Nov-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Set
Phone: 416-946-0164 Complete: 02-Dec-14
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, HT
SubLab: Cad
Note: This analysis was invoiced in advance.
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-9-1 Niagara In-Lab Lab Test Analyst
Test HM-11242014 Storm Sewer QA/QC Blank Date
Parameter 24-Nov-14 @ 16:15 hrs. Criteria %Recov
pH (SI) 8.25 no criteria set ~ ~ 25-Nov-14 FB
Alkalinity as CaC03 25 no criteria set 90% < 1 02-Dec-14 HT
Total Suspended Solids 2 0 98% < 1 28-Nov-14 FB
Total Oil+Grease 1 0 100% < 1 27-Nov-14 FB
Mineral Oil+Grease < 1 0 93% < 1 27-Nov-14 FB
Total Kjeldahl Nitrogen < 0.5 0 98% < 0.5 01-Dec-14 BJ
Total Phosphorus < 0.02 0 95% < 0.02 25-Nov-14 FB
Phosphate < 0.06 0 Calculation < 0.06 25-Nov-14 FB
Aluminum 0.07 0 103% < 0.01 28-Nov-14 AS
Antimony 0.0001 0 105% < 0.0001 28-Nov-14 AS
Arsenic 0.0004 0 105% < 0.0001 28-Nov-14 AS
Barium 0.031 0 97% < 0.001 28-Nov-14 AS
Cadmium < 0.005 0 105% < 0.005 28-Nov-14 AS
Chromium 0.012 0 105% < 0.002 28-Nov-14 AS
Cobalt < 0.005 0 105% < 0.005 28-Nov-14 AS
Copper < 0.002 0 104% < 0.002 28-Nov-14 AS
Iron 0.007 0 114% < 0.005 28-Nov-14 AS
Lead < 0.02 0 104% < 0.02 28-Nov-14 AS
Manganese < 0.001 0 105% < 0.001 28-Nov-14 AS
Mercury 0.00044 0 109% < 0.00002 28-Nov-14 MK
Molybdenum 0.02 0 100% < 0.01 28-Nov-14 AS
Nickel < 0.01 0 105% < 0.01 28-Nov-14 AS
Selenium 0.002 0 104% < 0.001 28-Nov-14 AS
Silver < 0.005 0 96% < 0.005 28-Nov-14 AS
Tin < 0.05 0 96% < 0.05 28-Nov-14 AS
Zinc < 0.005 0 103% < 0.005 28-Nov-14 AS
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 02-Dec-14
121
NIAGARA ANALYTICAL LABORATORIES INC.(Lettermail) P.O. Box 205, Niagara Falls, ON L2E 6T3
(Shipping Address) 5805 Progress St., Niagara Falls, ON L2G 0C1ph: 905-374-LABS, fx: 905-356-9672, email: [email protected]
Client: University of Toronto Client#: 987 Job#: 10
Attn: Mr. Adam Crookes; Civil Engineering Analyze: TKN,TP,PO4,pH,O+G,TSS, Alk & Metals
Address: Faculty of Applied Science & Engineering as per Niagara Storm Sewer Bylaw
Galbraith Building, 35 St.George St. Rm.GB-416 Date In: 17-Dec-14
Toronto, ON M5S 1A4 #Rec'd: 1 x Aqueous Set
Phone: 416-946-0164 Complete: 08-Jan-15
Email Report Locked: [email protected] Chemist: BIJ TECHS: FB, HT
SubLab: Cad
Note: This analysis was invoiced in advance.
CERTIFICATE OF ANALYSIS FOR: Select Tests listed within Niagara Sewer-Use Bylaw (storm sewer criteria)-Reg. 27-2014
UNITS OF MEASURE: mg/L (ppm) unless noted othewise
TEST RESULTS
987-10-1 Niagara In-Lab Lab Test Analyst
Test HM-12172014 Storm Sewer QA/QC Blank Date
Parameter 17-Dec-14 @ 9:00 am Criteria %Recov
pH (SI) 8.20 no criteria set ~ ~ 17-Dec-14 FB
Alkalinity as CaC03 33 no criteria set 96% < 1 08-Jan-15 FB
Total Suspended Solids 3 0 96% < 1 18-Dec-14 FB
Total Oil+Grease < 1 0 98% < 1 07-Jan-15 FB
Mineral Oil+Grease < 1 0 88% < 1 07-Jan-15 FB
Total Kjeldahl Nitrogen 0.9 0 102% < 0.5 07-Jan-15 FB
Total Phosphorus < 0.02 0 110% < 0.02 17-Dec-14 FB
Phosphate < 0.06 0 110% < 0.06 17-Dec-14 FB
Aluminum 0.16 0 102% <0.01 19-Dec-14 A.S.
Antimony 0.0002 0 84% <0.0001 22-Dec-14 A.S.
Arsenic 0.0004 0 86% <0.0001 22-Dec-14 A.S.
Barium 0.045 0 99% <0.001 19-Dec-14 A.S.
Cadmium < 0.005 0 109% <0.005 19-Dec-14 A.S.
Chromium 0.014 0 107% <0.002 19-Dec-14 A.S.
Cobalt < 0.005 0 110% <0.005 19-Dec-14 A.S.
Copper < 0.002 0 105% <0.002 19-Dec-14 A.S.
Iron 0.060 0 124% <0.005 19-Dec-14 A.S.
Lead < 0.02 0 112% <0.02 19-Dec-14 A.S.
Manganese 0.001 0 109% <0.001 19-Dec-14 A.S.
Mercury 0.00012 0 97% <0.00002 19-Dec-14 M.K.
Molybdenum 0.02 0 100% <0.01 19-Dec-14 A.S.
Nickel < 0.01 0 110% <0.01 19-Dec-14 A.S.
Selenium 0.001 0 80% <0.001 22-Dec-14 A.S.
Silver < 0.005 0 86% <0.005 19-Dec-14 A.S.
Tin < 0.05 0 89% <0.05 19-Dec-14 A.S.
Zinc < 0.005 0 106% <0.005 19-Dec-14 A.S.
Stephne A. Johnson; CEA Brian I. Johnson; B.Sc., C.Chem.
Managing Director Technical Director
All work herein has been performed with Good Laboratory Practice, QA/QC procedure, in accordance
with published analytical methodology as set forth in the latest edition of "Standard Methods and in
accordance with the reference test methods as originally clarified to your organization a time of quotation.
Test results transcribed within this report relate only to the items tested or calibrated, where relevant and
meet test report and supplemental test report requirements of ISO 17025: 2005. This document is confidential
in nature and is intended only for the named recipient(s). If this document is received in err by anyone
beyond the named recipient (via mail, fax or email), return it immediately to the sender. All lab reports
are securely retained (in hard copy and electronic version) for a minimum of 5 years. Utilization of these
lab results however rising, shall be deemed to imply your agreement that our total liability for these
analyses is limited only to the quoted cost of each test and not beyond. Authorization Date: 08-Jan-15
122
Appendix E –Water Quality Data – Living City Campus at Kortright
123
Parameter TSS pH Alkalinity TP Arsenic Aluminum Barium Molybdenum
Units mg/L none mg/L CaCO3 mg/L ug/L ug/L ug/L ug/L
Detection Limit 2.5 2.5 0.005 1 1 0.5 0.5
16/06/2010 30.4 9.14 197 0.3 671 45.8 48.5
22/06/2010 29.5 9.1 161 0.235 761 36.9 31.3
24/06/2010 22.2 9.67 202 0.24 1010 32.5 19.8
16/09/2010 13.3 9.07 184 0.173 540 32.7 19.4
28/09/2010 12.5 9.62 185 0.175 725 22.8 9.44
05/10/2010 4.1 9.76 172 0.123 632 14.6 9.34
14/10/2010 4.8 9.6 164 0.136 566 15.8 10.1
23/10/2010 3.9 9.34 153 0.11 364 25.7 15.1
26/10/2010 4.5 9.41 152 0.089 386 20.4 12.1
16/11/2010 5 9.96 155 0.145 390 14.1 12.7
22/11/2010 1.25 9.46 126 0.091 294 19.1 12.1
25/11/2010 4.4 9.59 151 0.095 284 17.2 11.9
30/11/2010 10.5 9.92 169 0.117 504 16.3 7.21
01 JAN 2011 41 10.7 253 0.655 577 27.1 12.3
18 FEB 2011 18.8 9.51 181 0.175 486 78.8 7.34
04 - 05 MAR 2011 101 10.9 387 0.196 726 64 11.5
10 MAR 2011 68.8 11.8 421 0.195 24.4 1040 28.3 7.2
16 MAR 2011 47.7 10.6 233 0.13 22 727 19.1 3.4
21 MAR 2011 34.3 9.73 156 0.195 12.7 1260 26.5 2.6
31 MAR 2011 6.6 8.62 114 0.115 4.6 324 51.8 6.2
4 APR 2011 57.3 10.5 249 0.28 15.8 983 20.7 6
10 APR 2011 26.1 8.9 129 0.175 7.4 768 36.6 5.8
16 APR 2011 78.2 10 238 0.263 18.7 1140 22.8 8.5
11 JUN 2011 17.5 9.63 158 0.192 7.2 1020 22 1.7
22 JUN 2011 10.6 9.16 138 0.142 6 592 18.5 4.7
25 JUL 2011 7 8.62 149 0.069 4.8 622 32.2 7
31 JUL 2011 4.7 8.81 197 0.194 4.2 1060 44.9 6.6
6 AUG 2011 8.3 8.67 175 0.16 4.1 984 37.6 6.2
14 AUG 2011 6 8.45 125 0.087 4.2 408 19 4.3
21 AUG 2011 6.2 8.54 153 0.14 3.4 811 31.4 3.6
24 AUG 2011 6.8 8.54 146 0.093 3.8 510 26.5 7
19 OCT 2011 6.1 8.49 109 0.049 2.7 189 21.4 3.6
25 OCT 2011 3 8.47 109 0.051 2.2 243 22.6 2.5
16 NOV 2011 5.4 8.61 131 0.088 2.1 378 29.2 4.5
24 NOV 2011 36.4 8.7 125 0.099 1.7 462 34.5 2.5
15 DEC 2011 3.2 8.58 109 0.058 1.7 804 22.3 4
124
Parameter TSS pH Alkalinity TP Arsenic Aluminum Barium Molybdenum
Units mg/L none mg/L CaCO3 mg/L ug/L ug/L ug/L ug/L
Detection Limit 2.5 2.5 0.005 1 1 0.5 0.5
12 JAN 2012 5.7 8.64 119 0.059 1.3 181 23.7 3.6
26 JAN 2012 3.8 8.22 109 0.053 1.2 163 25.9 2.8
31 JAN 2012 3.6 8.29 93.2 0.054 1.3 161 21.6 2.4
22 FEB 2012 10.3 8.08 97.8 0.048 1.1 105 158 3.4
29 FEB 2012 1.25 8.09 108 0.043 1.3 47.7 145 4.8
2 MAR 2012 3.9 8.2 130 0.05 1.6 129 89.4 4.2
25 APRIL 2012 6.9 8.43 203 0.056 2.1 131 44.8 11.3
30 APRIL 2012 4 8.52 207 0.06 2.3 145 37.4 10
4 JUNE 2012 12 8.46 170 0.074 2.6 270 30.3 7.1
4 DEC 2012 5.4 8.25 129 0.023 0.5 80.4 53.1 3.3
30 JAN 2013 9.8 8.27 108 0.047 1.1 114 74.4 1.8
27 Feb 2013 4.9 8 104 0.057 1.2 65.3 303 8.5
11 Mar 2013 7.5 8.43 161 0.041 2 192 51.1 1.8
24 Apr 2013 3.6 8.47 206 0.058 2.1 366 45.8 2.3
1 Jun 2013 3.2 8.44 159 0.065 1.8 848 32.3 0.9
11 Jun 2013 7.8 8.29 143 0.056 1.8 287 34.9 1.9
28 Jun 2013 5.2 8.31 130 0.027 1.5 195 41 2.7
1 Aug 2013 1.25 8.22 94 0.022 1.2 84.3 48.4 2.5
17-Oct-13 2.6 8.29 120 0.022 0.5 115 51.8 5.9
28-Mar-14 5.9 7.33 116 0.053 1.7 96.1 126 1.9
07-Jun-14 6.5 8.49 141 0.039 1.7 808 52.3 4.6
27-Jul-14 9.5 8.29 70.9 0.029 1.7 195 27.8 1.8
12-Aug-14 4 8.17 90.4 0.024 1.2 119 50.7 3.6
02-Sep-14 13.6 8.24 84.1 0.023 1.2 162 34.1 1.8
03-Oct-14 9.2 8.21 114 0.96 0.5 155 48.8 11.8
