Stormwater-quality performance of lined permeable pavement systems

Journal of Environmental Management 251 (2019) 109510

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Research article

Stormwater-quality performance of lined permeable pavement systems ∗

T

William R. Selbig , Nicolas Buer, Mari E. Danz U.S. Geological Survey, Upper Midwest Water Science Center, 8505 Research Way, Middleton, WI, 53562, USA

A R T I C LE I N FO

A B S T R A C T

Keywords: Permeable pavement Stormwater Water quality Nutrients Metals Sediment

Three permeable pavements were evaluated for their ability to improve the quality of stormwater runoff over a 22-month period in Madison, Wisconsin. Using a lined system with no internal water storage, permeable interlocking concrete pavers (PICP), pervious concrete (PC), and porous asphalt (PA) were able to significantly remove sediment and sediment-bound pollutant loads from runoff originating from an asphalt parking lot five times larger than the receiving permeable pavement area. Reductions in total suspended solids were similar for all three surfaces at approximately 60 percent. Clogging occurred after approximately one year, primarily due to winter sand application that led to high sediment load in spring runoff. Winter road salt application resulted in high chloride load that was initially attenuated in all three permeable pavements but later released during subsequent spring runoff events. Total phosphorus load was reduced by nearly 20 percent for PICP and PA, and 43 percent for PC. These values were likely tempered by the export of dissolved phosphorus observed in PICP and PA, but not PC. Average removal efficiencies for metals were 40, 42, and 49 percent in PA, PICP, and PC, respectively. A median pH of 10.2 in PC effluent could explain elevated removal efficiency of phosphorus and select metals in PC over PICP and PA (median = 7.5 and 7.8, respectfully) through enhanced precipitation. Elevated pH values in PC may also have led to higher removal efficiencies for select metals than PICP or PA. The environmental benefits as well as potential unintended consequences of stormwater practices like permeable pavement that utilize infiltration as a form of treatment warrant consideration in management of urban runoff.

1. Introduction

design incorporates an impermeable barrier, such as a geosynthetic material or clay, placed below the aggregate subbase to prevent exfiltration (Eisenberg et al., 2015; Smith, 2017). Field evaluation of the hydraulic and stormwater-quality performance of non-lined systems is well documented; however, fewer studies have described the function of lined systems (Støvring et al., 2018). Many of the site-specific design characteristics of permeable pavement are dependent not only on structural factors but also management goals related to the quantity and quality of stormwater (Eisenberg et al., 2015). For lined systems, volume reduction is limited to minor storage and evaporation losses. A study of permeable pavements in New Jersey found cumulative volumetric losses caused by evaporation over a 2year period were estimated to be about 5 percent of cumulative rainfall (Brown and Borst, 2015a). In some cases, lined permeable pavements have been shown to reduce a modest amount of runoff volume, although not to the extent of non-lined systems. Støvring et al. (2018) found total volume reduction of four different types of permeable pavement surfaces and three types of subbase aggregates with an impermeable liner to range from 3 to 27 percent. Alyaseri and Zhou (2016), compared runoff between pre- and post-construction of permeable pavement with underlying clay soils in St. Louis, MO, where

Permeable pavement is a form of green infrastructure designed to treat and manage stormwater near its source (Eisenberg et al., 2015). Although permeable pavement has been in use for decades, quantifying the stormwater quality benefits of various forms of permeable pavement is ongoing with recent advancements in design, construction, and maintenance. Permeable pavement is generally constructed as a full- or partial-infiltration system that allows filtered runoff to infiltrate into native soils and drain excess water through an underdrain (Drake et al., 2014b; Eisenberg et al., 2015). Field tests on the performance of this scenario have shown dramatic reductions in pollutant concentration and load because much of the water filtering through the permeable pavement exfiltrates into underlying soils thereby producing zero effluent for most runoff events (Brattebo and Booth, 2003; Bean et al., 2007; Roseen et al., 2012; Drake et al., 2014a; Braswell et al., 2018; Shafique et al., 2018). While this scenario would result in a 100 percent removal efficiency, it does not properly assess the pollutant removal capabilities of the permeable pavement and underlying aggregate subbase. Additionally, full- or partial-infiltration designs may not be suitable for sites with shallow bedrock or groundwater. An alternative ∗

Corresponding author. E-mail addresses: [email protected] (W.R. Selbig), [email protected] (N. Buer), [email protected] (M.E. Danz).

https://doi.org/10.1016/j.jenvman.2019.109510 Received 5 June 2019; Received in revised form 27 August 2019; Accepted 1 September 2019 0301-4797/ Published by Elsevier Ltd.

Journal of Environmental Management 251 (2019) 109510

W.R. Selbig, et al.

Fig. 1. Aerial photograph of permeable pavement research facility in Madison, Wisconsin showing schematic of drainage area and orientation of permeable pavements (adapted from Selbig and Buer, 2018).

pollutants, particularly chloride, phosphorus, and nitrate (Drake et al., 2014a; Brown and Borst, 2015b; Winston et al., 2016b). Additional information is needed to fully understand the physical and chemical processes of permeable pavement systems and their impact to water quality. In response, the U.S. Geological Survey led a study to better understand the hydraulic and stormwater-quality performance of lined permeable pavement in a field setting. The objective of this paper is to compare stormwater quality of effluent from three lined permeable pavements with untreated parking lot runoff. Data from the study would be used to amend or revise water-quality criteria specified in the WDNR technical standard for permeable pavement (Wisconsin Department of Natural Resources, 2016). The study evaluated three variations of permeable pavement: permeable interlocking concrete pavers, pervious concrete, and porous asphalt. The permeable pavements were selected based on the overall prevalence of use by consumers and interest from industry representatives on the performance of their product. The first two years of the study had contributing drainage area that was approximately nine times larger than the receiving permeable pavement area. Results of that phase of the study are detailed in Selbig and Buer (2018). In 2016, the contributing drainage area was reduced to five times the receiving permeable pavement area. Results of the 2016-2018 portion of the study are described herein. This study supports an ongoing effort to identify existing and new methods to mitigate urban nonpoint stormwater as well as provide high-resolution data critical to understanding the urban component of the hydrologic cycle.

measured runoff reductions varied from 13 percent for porous asphalt (PA) to 46 percent for permeable interlocking concrete pavers (PICP). Although the hydraulic capacity of permeable pavement can vary depending on many site-specific characteristics such as age and maintenance practices, much of the volume reduction capabilities of permeable pavements can be attributed to the size of the contributing drainage area. In general, the recommended ratio of impervious area to permeable pavement area is less than two (Eisenberg et al., 2015; Minnesota Pollution Control Agency, 2017), but in some cases can be much higher. The Wisconsin Department of Natural Resources (WDNR) suggest a drainage ratio less than or equal to three for drainage from roads and five for drainage from other impervious surfaces such as parking lots, rooftops, and driveways (Wisconsin Department of Natural Resources, 2016). Winston et al. (2016b) reported a reduction in stormwater volume by 16 and 32 percent from two permeable pavement systems receiving runoff from catchments 7.2 and 2.2 times larger than the receiving permeable pavement area, respectively. Selbig and Buer (2018) observed PICP and pervious concrete (PC) clogged in approximately one year when receiving runoff from an asphalt parking lot 9.3 times larger than the receiving permeable pavement area. Larger contributing drainage areas can only be used if the permeable pavement is receiving runoff from sources with minor amounts of total suspended solids such as roofs (e.g. Steuer et al., 1997), or if runoff from the impervious surface first undergoes some form of pretreatment to remove sediment. Permeable pavement has also been shown to improve the quality of stormwater through the combined filtering effect of both the permeable pavement and underlying aggregate. Several studies report high sediment removal rates (Roseen et al., 2012, 2014; Barrett, 2008) which can be related to particle size in water (Brown et al., 2009). Because of their strong association to particulate matter, total metals, total phosphorus, and hydrocarbons are also sequestered in permeable pavements (Roseen et al., 2012; Gilbert and Clausen, 2006; Balades et al., 1995). The primary mechanism behind removal of sediment and sedimentassociated pollutants is filtration and sedimentation, with most of the sediment accumulation occurring within the top few inches of the permeable pavement before reaching the underlying aggregate base (Brown et al., 2009; Lucke and Beecham, 2011; Winston et al., 2016a; Selbig and Buer, 2018). Despite the high efficiency in sediment removal, many studies report little to no treatment of dissolved-phase

2. Materials and methods The monitoring period was from September 2016 through July 2018. Discharge was measured and water-quality samples were collected at points representing untreated runoff from the parking lot, runoff that filtered through each permeable pavement, and runoff that cascaded across each permeable pavement as overflow. Hydrologic data were continuously recorded at 1-min increments during periods of runoff and hourly during interevent periods. The experimental methods used for the present study follow those established in Selbig and Buer (2018) and are briefly described herein.

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Fig. 2. Conceptual diagram showing cross-sectional profile of PA, PC, and PICP test surfaces and aggregate base. Blue arrows indicate flow of infiltrated runoff from the underdrain toward the monitoring chamber (courtesy of County Materials Corporation, Inc.). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

the 0.64 cm joints between the PICP at the surface. The void space of each permeable pavement varied from approximately 20 percent for PA and PC to approximately 10 percent for PICP. Impermeable concrete walls were placed around the perimeter of each permeable pavement (subgrade) to prevent lateral exfiltration into underlying soils or crosscontamination between pavements. Similarly, rubberized berms were used at the surface to prevent exchange of surface flow between permeable pavements above grade. Overflow runoff that cascaded across each permeable pavement during periods of heavy rainfall was collected via surface grate and routed by dedicated PVC pipe towards the monitoring vault.

2.1. Site description In 2014, a permeable pavement test site was constructed adjacent to a curbed asphalt parking lot in Madison, Wisconsin (Fig. 1). The parking lot was frequently used by city employees and visitors of a nearby dog park. Asphalt berms were used to define a runoff drainage area comprised of parking spaces and driving lanes that naturally drain towards the test site. The parking lot was approximately 25 years old at the time of the study and in poor condition. Vehicles were restricted to the parking lot only and prohibited from accessing the permeable pavements. Maintenance of the parking lot consisted of snow and ice removal by use of plows with occasional application of sand and salt during winter months. In the fall, leaf litter from the few trees surrounding the site would accumulate on the permeable pavements. During winter, snow accumulation that exceeded approximately 5 cm was removed from the permeable pavements by a hand-operated snow thrower. Sand or salt was not applied on the permeable pavements. The test site was split into three individual plots. A conceptual diagram profiling each of the permeable pavements is shown in Fig. 2. Each 46.5 m2 plot had a depth of approximately 0.5 m with an impermeable membrane lining the sloped base (approximately 2 percent) to prevent exfiltration into underlying soils. A 0.15 m diameter polyvinyl chloride (PVC) underdrain was placed upon the impermeable membrane in each cell to collect and route filtered stormwater towards a monitoring vault. The placement of the underdrain was chosen to minimize internal water storage thereby limiting removal of solids through settling. As such, measurements of water-quality and hydraulic performance are representative of only the combined effect for the permeable pavement and aggregate base. Overlying the underdrain were various gradations of washed aggregate used to support the PA, PC, and PICP surfaces and create void spaces to promote rapid infiltration of stormwater runoff. A number 9 stone (American Society of Testing and Materials, 2002) was used to fill

2.2. Project history Phase I of this study (August 2014–September 2016) tested the water-quality and hydraulic performance of permeable pavement with a drainage ratio of approximately 9:1, far greater than conventional guidelines. Results of Phase I of the study are detailed in Selbig and Buer (2018). Phase II of the study (September 2016–July 2018) tested the water-quality performance of permeable pavement with a smaller drainage ratio of 5:1, the current ratio allowed by the Wisconsin Department of Natural Resources for runoff to permeable pavement from parking lots (Wisconsin Department of Natural Resources, 2016). Except for PC, the PICP and PA surfaces were not new at the beginning of Phase II. The PICP surface was replaced two months prior (July 2016) and therefore exposed to 14 runoff events before evaluation of the 5:1 drainage ratio began. The original PA surface from Phase I of the study continued to be monitored in Phase II until it was removed in July 2017, at which point monitoring was suspended until a new PA surface was installed in June 2018. This 11-month gap was not included when evaluating the water-quality performance of PA.

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2.3. Measurement of infiltration rate

Table 1 Constituents analyzed in influent and effluent runoff at the permeable pavement test site, Madison, WI. [MDL, minimum detection limit; mg/L, milligrams per liter; μg/L, micrograms per liter; col/100 mL, colonies per 100 mL; USEPA, U.S. Environmental Protection Agency (U.S. Environmental Protection Agency, 1993; 2003); SM, Standard Methods (2017)].

Infiltration rates were measured using a modified version of the ASTM standard test method C1701/1701M (American Society of Testing and Materials, 2009). This method measures the time required to infiltrate a known volume of water through a ring of known area sealed to the permeable pavement. Details of the device used to measure infiltration rate are found in Selbig and Buer (2018). Infiltration tests were done at each permeable pavement approximately once per month except in the winter (typically December through March). Each test location consisted of a three by three matrix spaced evenly across the 7.6 by 6.1 m permeable pavement plot. Each monthly test was done in the exact same manner and in the exact same location. 2.4. Measurement of stormwater quantity Stormwater runoff from the parking lot concentrated to a single point where it was routed to a flow splitter equipped with pre-rated flume and attached stilling well (Fig. 1). A submersible pressure transducer measured the changing water level in the flume that was then used to compute instantaneous discharge by use of standard flume equations. Water passing through the flume emptied into a concrete structure that split the volume of runoff from the parking lot into three portions to PA, PC, and PICP. This configuration is unique as it allows for the direct measurement of the quantity and quality of runoff delivered from the parking lot to each permeable pavement. Once delivered to the permeable pavement, stormwater would either filter through or bypass as overflow where it was collected and conveyed separately to a concrete monitoring vault by use of dedicated 15 cm PVC pipes. Each pipe emptied into a fiberglass box equipped with a 15 cm H-flume for measurement of overflow, or 20 cm H-flume for measurement of underdrain discharge. A submersible pressure transducer measured the changing water levels in the H-flumes that were then used to compute instantaneous discharge using standard flume equations.

Constituent

Units

MDL

Method

Total Suspended Solids (TSS) Total Phosphorus (TP) Dissolved Phosphorus (DP) Chloride (Cl) Escherichia Coli (E. coli) Calcium (Ca) Magnesium (Mg) Aluminum (Al) Cadmium (Cd) Chromium (Cr) Cobalt (Co) Copper (Cu) Iron (Fe) Lead (Pb) Manganese (Mn) Nickel (Ni) Vanadium (V) Zinc (Zn) Arsenic (As)

mg/L mg/L mg/L mg/L col/100 mL mg/L mg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L μg/L

2.0 0.005 0.005 1.0 100 0.1 0.1 10.0 1.0 1.0 1.0 5.0 0.1 3.0 1.0 2.0 1.0 5.0 5.0

SM 2540D USEPA 365.1 USEPA 365.1 SM 4500-CL-E SM 9223 BMPN USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7 USEPA 200.7

overflow from each permeable pavement, EMCs for missed storm events were estimated based on regression-based relations with log-transformed, paired influent and effluent EMCs from measured events. The number of samples measured and estimated for each sample collection point as well as metrics describing the goodness of fit are detailed in Carvin and Selbig (2019). Most EMCs in runoff measured in the overflow for each permeable pavement were estimated. This was primarily due to the low volume of water passing the point of measurement which precluded sample collection. As a result, the estimated EMCs associated with these events, in general, had a minor contribution to the cumulative load. Estimates of EMCs for metals were not done because of the small sample size. Summary statistics for censored concentration data (below detection limits) were estimated by use of the Kaplan-Meier method (Helsel, 2005).

2.5. Measurement of stormwater quality Refrigerated, automated samplers were used to collect water samples from parking lot influent and underdrain and overflow effluent. Sample collection was activated by a rise in water level in the flumes during a precipitation or snowmelt event. All flow-weighted discrete samples collected throughout the duration of an event hydrograph were combined into a single, composite sample, resulting in an event mean concentration (EMC) that represented a minimum of 80 percent of the storm hydrograph. Water-quality samples were collected generally within 24 h after runoff cessation. A Teflon churn splitter was used to composite and split samples into smaller plastic sample containers to be delivered to the analytical laboratory. A portion of the composite sample was processed through a 0.45 μm cellulose acetate membrane filter for analyses of dissolved constituents. All processed samples were kept in a refrigerator at 4 °C until delivered to the Wisconsin State Laboratory of Hygiene. Samples were analyzed for determination of constituent concentrations listed in Table 1. Because of the extended period of time without a PA surface as well as funding limitations, samples collected from PA overflow effluent were precluded from determination of metals concentration.

2.6.2. Computation of pollutant load The water-quality performance of PA, PC, and PICP was based on a calculated pollutant removal efficiency. The removal efficiency was based on comparisons of cumulative influent and effluent pollutant load for sampled events during the Phase II study period. Storm event loads at each monitoring location were computed by multiplying the EMC by event runoff volumes. Except for cadmium and arsenic, a value of onehalf the limit of detection was used for censored concentrations to compute an event load. Cadmium and arsenic were below detectable limits for all reported samples and not included in the computation of load. The EMC of pollutants influent to each permeable pavement were assumed to be the same; however, load calculations applied a flowproportional adjustment based on the ratio of underdrain and overflow effluent volume measured at each permeable pavement to the total influent volume from the parking lot (eq. (1)).

Ladj = Li*[Vu/o/V] i

(1)

where. 2.6. Statistical analyses Ladj is the adjusted load delivered to each permeable pavement, in grams; Li is the load measured from the parking lot, in grams; Vu/o is the volume measured at the underdrain or overflow, in cubic feet; Vi is the volume measured from the parking lot, in cubic feet.

2.6.1. Estimating concentrations for missed samples When possible, samples were collected and analyzed from all surfaces for the same event; however, for some storm events, samples were not collected at one or more points of measurement due to equipment failure, laboratory error, or insufficient sample volume. To better evaluate the cumulative pollutant load in both the underdrain and 4

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complete system (summation of underdrain and overflow), all three permeable pavements were able to reduce TSS loads from the parking lot by approximately 60 percent. Median concentrations of TP measured in the underdrain for PICP and PA were slightly lower than the parking lot resulting in similar load reductions of 25 and 34 percent, respectively (Table 3). PC showed a greater ability to filter TP than the other permeable pavements with a median concentration one-half the value of the parking lot (Table 2) which resulted in the largest reduction in load at 61 percent (Table 3). Median concentrations of TP measured in the overflow were nearly the same or slightly higher than the parking lot resulting in a much lower reduction in load than the underdrain; only PICP and PC reductions in the overflow were significant (p < 0.10). This, in turn, reduced the overall removal efficiency of TP to approximately 20 percent for PICP and PA, and nearly twice that (43 percent) for PC. However, PA failed to meet significance (p > 0.10). While all three permeable pavements showed some ability to filter the particulate form of phosphorus, DP was generally left untreated. Median concentrations of DP measured in both the underdrain and overflow of each permeable pavement was equal to or higher than the parking lot (Table 2). Only PC showed moderate reductions in DP load in the underdrain at 46 percent (Table 3) while both PICP and PA showed an export. Load of DP measured in the overflow was similarly higher than the parking lot for PICP and PC and only slightly lower for PA. Despite the export of DP in the overflow, PC was still able to effectively remove 28 percent of the load when combined with the underdrain, whereas PICP and PA still showed minor export (Table 3). Median concentrations of chloride in the underdrain were slightly higher than the parking lot except for PICP, which was slightly lower (Table 2). Concentrations of chloride were seasonally influenced with the highest concentrations occurring in winter and spring. High concentrations of chloride were likely due to application of road salt in the parking lot as a deicing agent during winter months. The range of concentrations measured in all three permeable pavements spanned several orders of magnitude with values occasionally exceeding the U.S. Environmental Protection Agency (U.S. EPA) chronic toxicity criterion of 230 mg/L, and in at least one instance, the acute toxicity criterion of 860 mg/L (Table 2) (U.S. Environmental Protection Agency, 2012). Concentrations of chloride were generally greater in the underdrain than the parking lot for all three permeable pavements with PA having the highest occurrence followed by PC and PICP. This translated into an export of chloride load in the PA underdrain while PC and PICP showed minor reductions; however, PICP failed to meet significance (p > 0.10). Median concentrations of chloride in the overflow of each permeable pavement were lower than the parking lot resulting in a similar load reduction of approximately 60 percent. When combined with loads measured in the underdrain, overall removal efficiencies ranged from 10 to 33 percent with PA the lowest and PICP the highest (Table 3). All three permeable pavements had the ability to effectively reduce concentrations of E. coli. Reductions were most pronounced in PC with a median underdrain concentration approximately one-sixth that measured from the parking lot. PC was the only permeable pavement with median E. coli concentrations that did not exceed the U.S. EPA chronic toxicity criterion of 126 cols/100 ml (Table 2). Median concentrations measured in PC overflow were greater than the parking lot while concentrations measured in PA and PICP overflow were lower. Removal efficiencies for E. coli load were nearly identical for PA and PC with more than 90 percent occurring in the underdrain. Even after accounting for the overflow, removal efficiencies remained high at nearly 80 percent (Table 3). Removal efficiencies in the underdrain of PICP were approximately one-half that observed for PA and PC at 50 percent. This decreased ability to reduce load of E. coli was also noted in the overflow and, and when combined with the underdrain, resulted in a total removal efficiency of 36 percent.

Load data were tested for normality by use of the Shapiro-Wilk test (Helsel and Hirsch, 2002). Generally, the data followed a log-normal distribution in which the statistically significant differences between paired influent and effluent loads were evaluated by use of paired ttests (Helsel and Hirsch, 2002). All other load data were evaluated by use of the nonparametric Wilcoxon signed-rank test (Helsel and Hirsch, 2002). All statistical tests were first done using an upper-tailed test in which the null hypothesis assumed that the influent and effluent loads were not different. If the null was rejected, tests were repeated to determine if the influent load was statistically greater or less than the effluent load. All tests used a 90 percent confidence level (α = 0.10) unless otherwise noted. Because water was not allowed to exfiltrate into native soils, the percent change, herein referred to as removal efficiency, between the sum of paired influent and effluent loads represents the pollutant removal capabilities (or lack thereof) of only the permeable pavement and aggregate base. Removal efficiencies were computed for the underdrain and overflow separately to better understand the filtering capacity of the permeable pavement and aggregate base independent of what may have bypassed as overflow. Removal efficiencies for each permeable pavement, as a complete system, were also determined by combining the underdrain and overflow loads. 2.7. Quality assurance and quality control Field and sample-processing equipment blanks were collected to evaluate the integrity of the water-quality sampling process, identify if sample contamination existed and, if so, to identify possible sources. Quality-assurance results are available in the supplemental online material. Concentrations were within acceptable limits for all constituents. Calcium was above detection in four out of five samples; however, because the concentrations were an order of magnitude lower than those measured in water-quality samples, it was considered insignificant to the overall integrity of the water-quality sampling process. 3. Results During the 22-month study period, 95 runoff events were measured from the parking lot, 84 of which were sampled for water-quality. Although most runoff events were a result of precipitation, some were the result of snowmelt or a combination of precipitation and snowmelt. A complete list of concentrations, loads, and measured weather parameters can be found in in Carvin and Selbig (2019). 3.1. Solids, phosphorus, chloride, and bacteria Median concentrations of total suspended solids (TSS), total phosphorus (TP), and Escherichia coli (E. coli) measured in the PICP, PC, and PA underdrain effluent were lower than those originating from the parking lot (Table 2). Because concentrations were not normally distributed, a comparison of medians was more representative of the central tendency. Conversely, median underdrain concentrations of chloride (with exception of PICP) and dissolved phosphorus (DP) were equal to or higher than those measured from the parking lot. Each permeable pavement was effective at removing sediment from parking lot runoff based on median TSS concentrations measured in the underdrains that were appreciably less than what was measured in parking lot influent. PC had the lowest residual concentration of TSS measured in the underdrain at 18 mg/L compared to 26 mg/L in PA and 50 mg/L in PICP (Table 2). Differences in TSS concentrations measured in the underdrain effluent resulted in PC having the largest reduction in TSS load at 79 percent, followed by PA at 77 percent, and PICP at 61 percent (Table 3). Median concentrations in the overflow for each permeable pavement were similarly lower than the parking lot, but greater than what was measured from the underdrains. This translated into smaller, but still significant, reductions in TSS load (Table 3). As a 5

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Table 2 Summary statistics of event mean concentrations measured at the parking lot, underdrain and overflow monitoring points in the PICP, PC, and PA test plots [n/a, data not available; < , less than; Min, minimum; Max, maximum; COV, coefficient of variation; mg/L, milligrams per liter; cols/100 ml, colonies per 100 mL; PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt; U.S. EPA, U.S. Environmental Protection Agency]. U.S EPA Aquatic Life Criteriaa

Pollutant

Chronic

Acute

TSS (mg/L)

–

–

TP (mg/L)

0.033b

–

DP (mg/L)

–

–

Chloride (mg/L)

230

860

E. Coli (cols/100 mL)

126c

–

a b c

Pavement aype

Parking Lot PICP PC PA Parkinb Lot PICP PC PA Parking Lot PICP PC PA Parking Lot PICP PC PA Parkinc Lot PICP PC PA

Underdrain

Overflow

Min

Max

Median

Mean

COV

Min

Max

Median

Mean

COV

5 6 1 8 0.06 0.06 0.03 0.08 0.02 0.04 0.02 0.04 1.4 1.1 1.7 1.5 <1 <1 <1 <1

764 287 246 346 1.52 0.45 0.26 0.57 0.52 0.34 0.23 0.41 4260 6460 8020 14,000 241,960 32,550 8820 5693

76 50 18 26 0.20 0.18 0.10 0.18 0.06 0.09 0.06 0.10 4.3 4.1 4.8 5.1 199 147 31 161

120 34 28 37 0.26 0.20 0.11 0.21 0.09 0.11 0.07 0.12 69.8 112.1 126.7 320.1 8245 2492 404 1314

1.17 1.02 1.23 1.34 0.80 0.49 0.45 0.54 0.93 0.60 0.57 0.63 6.62 6.33 6.88 6.18 3.96 2.15 3.05 1.34

n/a 4 6 10 n/a 0.06 0.08 0.03 n/a 0.03 0.03 0.03 n/a 1.2 < 0.5 1.2 n/a <1 <1 <1

n/a 315 311 353 n/a 1.52 0.64 2.01 n/a 0.40 0.32 0.39 n/a 224 856 4520 n/a 57,940 15,000 46,213

n/a 38 44 61 n/a 0.19 0.19 0.25 n/a 0.09 0.07 0.07 n/a 2.9 3.6 4.2 n/a 172 219 133

n/a 55 63 85 n/a 0.23 0.21 0.29 n/a 0.11 0.09 0.10 n/a 8.4 19.8 118.8 n/a 2539 2335 2957

n/a 0.97 0.96 0.86 n/a 0.76 0.48 0.96 n/a 0.66 0.64 0.70 n/a 2.94 4.72 5.40 n/a 3.13 1.68 2.67

U.S. Environmental Protection Agency, 2012 Recommended aggregate for ecoregion VII. Based on geometric mean for freshwater.

levels and maximum concentrations for these two metals, as well as zinc, that exceeded the acute toxicity criterion (Table 4). Comparison of underdrain removal efficiencies show, in general, each permeable pavement was able to filter and retain some of the load for all measured metals delivered by the parking lot with aluminum and vanadium having the lowest percent removal and zinc the highest (Table 5). Larger reductions for most metals were observed in PC than PICP and PA. Overflow removal efficiencies were similar in PICP and PC suggesting processes that are similar, but independent, of the permeable pavement. Contrary to the underdrain, removal efficiencies for zinc were lowest in overflow for PC and PICP, which showed a

3.2. Metals Mean and median residual concentrations of all metals measured in both the underdrain (all three permeable pavements) and overflow (PICP and PC) of all three permeable pavements were lower than the parking lot (Table 4). Overflow effluent was not sampled in PA. Cadmium and arsenic were not detected in any of the parking lot, underdrain, or overflow samples. Although PICP, PC, and PA were able to sequester some portion of all 14 metals tested, two metals (aluminum and lead) had median underdrain concentrations that exceeded the U.S. Environmental Protection Agency aquatic health criterion at chronic

Table 3 Cumulative pollutant loads with calculated removal efficiencies between paired influent and effluent loads at the underdrain, overflow, and total (when loads measured in both the underdrain and overflow effluent were combined) monitoring points in the PICP, PC, and PA test plots. Positive removal efficiencies indicate pollutant export. All values are reported as grams except E. coli which is reported as colonies. [InfluentAdj, parking lot influent load adjusted for the volume of runoff measured at the underdrain and overflow monitoring points; PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt]. Pollutant

PICP TSS TP DP Chloride E. coli PC TSS TP DP Chloride E. coli PA TSS TP DP Chloride E. coli a

InfluentAdj Load

Effluent Load

Removal Efficiency

Underdrain

Overflow

Total

Underdrain

Overflow

Total

Underdrain

Overflow

Total

45,494 89 33 45,420 1.5E+10

13,509 25 7 1153 7.6E+09

59,003 114 40 46,573 2.3E+10

17,519 66 35 30,994 7.5E+09

6265 24 11 389 7.0E+09

23,783 90 46 31,383 1.4E+10

−61% −25% 4% −32%a −50%

−54% −5% 65% −66% −9%

−60% −21% 15% −33%a −36%

35,534 71 29 54,975 9.2E+09

20,155 40 11 2863 9.3E+09

55,688 110 40 57,838 1.8E+10

7360 28 15 42,784 5.5E+08

11,861 36 13 1292 3.5E+09

19,222 63 29 44,076 4.0E+09

−79% −61% −46% −22% −94%

−41% −11% 21% −55% −63%a

−65% −43% −28% −24% −78%

19,632 38 13 44,700 1.2E+10

23,411 44 18 40,972 9.9E+09

43,043 82 31 85,673 2.2E+10

4532 25 15 58,448 1.0E+09

13,659 41 17 18,817 3.6E+09

18,190 66 32 77,265 4.6E+09

−77% −34% 16% 31% −91%

−42% −6%a −4% −54%a −64%

−58% −19%a 4% −10% −79%

Failed to meet significance at the 90 percent confidence level. 6

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Table 4 Summary statistics of event mean concentrations for select metals measured at the parking lot, underdrain and overflow monitoring points in the PICP, PC, and PA test plots. [PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt; –, no data; nd, no detection; n/a, data not available; < , less than; Min, minimum; Max, maximum; COV, coefficient of variation; μg/L, micrograms per liter; mg/L, milligrams per liter; U.S. EPA, U.S. Environmental Protection Agency]. Metal

USEPA Aquatic Life Criteriaa Chronic

Acute

Calcium (mg/L)

–

–

Magnesium (mg/L)

–

–

Aluminumb (μg/L)

0.63–3200

1 - 4800

Cadmium (μg/L)

1.8

0.72

Chromiumb (μg/L)

–

–

Cobalt (μg/L)

–

–

Copper (μg/L)

–c

–c

Iron (μg/L)

1000

–

Lead (μg/L)

2.5

65

Manganese (μg/L)

–

–

Nickel (μg/L)

52

470

Vanadium (μg/L)

120d

–

Zinc (μg/L)

120

120

Arsenic (μg/L)

150

340

a b c d

Pavement Type

Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA Parking PICP PC PA

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Lot

Underdrain

Overflow

n

Min

Max

Mean

Median

COV

n

Min

Max

Mean

Median

COV

25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10 25 23 21 10

5.1 6.9 4.9 5.6 1.7 1.4 0.4 1.3 79 364 124 226 nd nd nd nd < 1.0 < 1.0 < 1.0 < 1.0 < 1.0 < 1.0 < 1.0 < 1.0 < 5.0 < 5.0 < 5.0 < 5.0 0.1 0.5 0.2 0.4 < 3.0 < 3.0 < 3.0 < 3.0 11 19 6 15 < 2.0 < 2.0 < 2.0 < 2.0 1.1 1.7 1.1 1.7 12.3 8.9 < 5.0 8.3 nd nd nd nd

99.9 27.4 39.7 29.6 47.6 23.0 21.0 15.1 5660 5520 3130 6030 nd nd nd nd 15.8 8.3 6.1 10.7 7.2 6.4 2.7 6.7 54.1 25.7 18.9 31.8 11.3 8.6 4.8 9.6 36.5 14.7 9.7 18.6 565 316 161 374 15.0 8.5 4.6 9.3 23.0 18.2 11.6 19.4 349 130 74 148 nd nd nd nd

21.7 12.4 12.5 10.3 11.2 4.8 2.8 4.1 1360 1330 970 1235 nd nd nd nd 4.3 2.4 2.5 1.8 2.0 1.4 0.8 1.2 15.7 9.8 6.1 9.5 2.8 2.2 1.3 1.9 9.4 3.9 1.9 2.9 146 84 43 75 4.3 2.4 1.1 1.2 6.5 5.6 5.8 5.1 97 43 22 32 nd nd nd nd

13.5 10.7 10.5 8.5 6.4 2.8 1.6 2.3 1060 1040 859 499 nd nd nd nd 3.2 1.8 2.5 1.0 1.8 1.4 1.0 1.0 12.9 9.1 6.8 7.5 2.0 1.6 1.1 0.8 5.7 3.4 3.0 3.0 107 61 31 36 3.8 2.3 2.0 2.0 5.3 4.9 5.1 3.4 55 31 16 17 nd nd nd nd

1.0 0.4 0.6 0.6 1.0 1.0 1.5 1.0 0.9 0.8 0.6 1.4 nd nd nd nd 0.9 0.8 0.5 1.9 1.0 1.1 1.2 2.0 0.8 0.6 0.9 1.0 1.0 0.8 0.8 1.4 1.0 1.2 1.6 2.2 0.9 0.8 0.8 1.4 1.0 1.0 1.6 3.2 0.9 0.6 0.4 1.0 0.9 0.8 0.9 1.2 nd nd nd nd

n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 – n/a 12 17 –

n/a 4.3 5.2 – n/a 1.2 19.4 – n/a 167 87 – n/a nd nd – n/a < 1.0 < 1.0 – n/a < 1.0 < 1.0 – n/a < 5.0 < 5.0 – n/a 0.3 0.1 – n/a < 3.0 < 3.0 – n/a 14 7 – n/a < 2.0 < 2.0 – n/a 1.3 1.3 – n/a 25 17 – n/a nd nd –

n/a 37.4 39.6 – n/a 1.3 19.5 – n/a 2620 2560 – n/a nd nd – n/a 8.3 8.1 – n/a 4.0 4.7 – n/a 27.1 28.0 – n/a 5.6 5.6 – n/a 16.6 17.2 – n/a 292 295 – n/a 8.0 9.6 – n/a 11.9 12.3 – n/a 258 281 – n/a nd nd –

n/a 12.5 14.0 – n/a 5.8 6.5 – n/a 792 963 – n/a nd nd – n/a 2.4 2.8 – n/a 1.0 1.3 – n/a 8.4 9.0 – n/a 1.6 1.9 – n/a 3.4 5.0 – n/a 88 96 – n/a 2.4 2.9 – n/a 4.0 4.6 – n/a 84 86 – n/a nd nd –

n/a 7.6 9.2 – n/a 2.8 3.2 – n/a 544 603 – n/a nd nd – n/a 1.5 1.4 – n/a 1.0 1.0 – n/a 7.7 7.8 – n/a 0.9 1.1 – n/a 3.0 3.0 – n/a 52 59 – n/a 2.1 2.4 – n/a 2.6 2.9 – n/a 52 49 – n/a nd nd –

n/a 0.8 0.8 – n/a 1.0 1.0 – n/a 0.9 0.8 – n/a nd nd – n/a 1.1 0.9 – n/a 1.6 1.3 – n/a 1.0 1.0 – n/a 1.0 0.9 – n/a 2.2 1.3 – n/a 0.9 0.9 – n/a 1.3 1.2 – n/a 0.8 0.7 – n/a 0.9 0.8 – n/a nd nd –

U.S. Environmental Protection Agency, 2012 Values reported from lab are for total chromium and do not speciate between Cr III and Cr VI. Values will be different under differing water chemistry conditions. Environment Canada, 2016

respectively.

minor export of zinc but failed to meet significance (p > 0.10). The combined effect of underdrain and overflow load resulted in total removal efficiencies that ranged from 7 percent for aluminum in PA (based on underdrain removal only) to 78 percent for nickel in PC. When averaged across all metals, total removal efficiencies were similar for all three surfaces at 40, 42, and 49 percent for PA, PICP, and PC, 7

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Table 5 Cumulative pollutant load of metals with calculated removal efficiencies between paired influent and effluent loads at the underdrain, overflow, and combined (total) monitoring points in the PICP, PC, and PA test plots. Positive removal efficiencies indicate pollutant export. [PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt; InfluentAdj, parking lot influent load adjusted for the volume of runoff measured at the underdrain and overflow monitoring points; g, grams; –, no data available; nd, no detection]. Metal (g)

PICP Calcium Magnesium Aluminum Cadmium Chromium Cobalt Copper Iron Lead Manganese Nickel Vanadium Zinc Arsenic PC Calcium Magnesium Aluminum Cadmium Chromium Cobalt Copper Iron Lead Manganese Nickel Vanadium Zinc Arsenic PA Calcium Magnesium Aluminum Cadmium Chromium Cobalt Copper Iron Lead Manganese Nickel Vanadium Zinc Arsenic

a

InfluentAdj Load

Effluent Load

Removal Efficiency

Underdrain

Overflow

Total

Underdrain

Overflow

Total

Underdrain

Overflow

Total

3185 1587 201 nd 0.6 0.3 2.2 0.4 1.4 21 0.6 0.9 14 nd

851 427 53 nd 0.2 0.1 0.6 0.1 0.3 6.8 0.2 0.3 3.3 nd

4035 2014 254 nd 0.8 0.4 2.8 0.5 1.7 28.2 0.9 1.2 17.8 nd

1457 531 179 nd 0.3 0.2 1.2 0.3 0.6 11.4 0.3 0.7 5.5 nd

540 214 35 nd 0.1 0.1 0.4 0.1 0.2 4.0 0.1 0.2 3.4 nd

1998 744 214 nd 0.4 0.3 1.6 0.4 0.7 15.4 0.4 0.9 8.8 nd Mean

−54% −67% −11%a – −47% −26% −47% −29% −59% −46% −49% −22%a −62% – −43%

−36% −50% −34% – −41% −41% −32% −42% −44% −42% −46% −30% 2%a – −36%

−50% −63% −16%a – −46% −30% −44% −32% −57% −45% −49% −24% −50% – −42%

Mean

−47% −84% −30% nd −46% −52% −61% −54% −73% −72% −79% −17%a −81% – −58%

−33% −47% −30% nd −39% −33% −33% −35% −38% −37% −78% −29% −12%a – −37%

−41% −68% −30% nd −43% −43% −49% −46% −59% −56% −78% −22%a −52% – −49%

Mean

−41% −62% −7%a – −51% −18% −32% −27% −54% −49% −66% −10%a −64% – −40%

– – – – – – – – – – – – – – –

– – – – – – – – – – – – – – –

2357 1169 147 nd 0.4 0.2 1.6 0.3 1.1 15.5 0.5 0.6 10.6 nd

1208 586 81 nd 0.2 0.1 0.9 0.2 0.4 9.4 0.3 0.4 4.8 nd

1770 898 109 nd 0.4 0.2 1.3 0.2 0.7 13.0 0.4 0.5 7.7 nd

– – – – – – – – – – – – – –

4127 2068 257 nd 0.8 0.4 2.9 0.5 1.8 28.6 0.9 1.2 18.3 nd

1208 586 81 nd 0.2 0.1 0.9 0.2 0.4 9.4 0.3 0.4 4.8 nd

1260 182 103 nd 0.2 0.1 0.6 0.1 0.3 4.4 0.1 0.5 2.0 nd

717 225 75 nd 0.1 0.1 0.6 0.1 0.2 4.8 0.1 0.3 1.7 nd

1183 477 76 nd 0.2 0.1 0.8 0.1 0.4 8.1 0.1 0.4 6.8 nd

– – – – – – – – – – – – – –

2443 659 179 nd 0.5 0.2 1.5 0.3 0.7 12.5 0.2 0.9 8.8 nd

717 225 75 nd 0.1 0.1 0.6 0.1 0.2 4.8 0.1 0.3 1.7 nd

Failed to meet significance at the 90 percent confidence level.

4. Discussion

other studies. Median concentrations of TSS from the parking lot (76 mg/L) were larger than a value of 58 mg/L for typical urban runoff (Pitt and Maestre, 2005), and much larger than a value of 12 mg/L reported by Winston et al. (2016a). Mean TSS concentrations were even higher than median values at 120 mg/L (Table 2). Elevated mean and median TSS concentrations were likely influenced by the poor condition of the parking lot as well as large amounts of residual sediment applied for vehicle traction during the winter. Of the 83 runoff events sampled from the parking lot, 22 had concentrations of TSS that were equal to or higher than the mean value of 120 mg/L. Of those, 16 were collected during the winter or spring (Carvin and Selbig, 2019). This seasonal application of sediment was then available for wash-off during subsequent spring precipitation events. A Pearson correlation test was done to identify which climatic parameters (depth, intensity, storm duration, and antecedent dry days)

4.1. Seasonal influence on sediment delivery and the effect of drainage ratio Removal efficiencies for TSS load in Table 3 are lower than those reported in other studies (e.g. Drake et al., 2014a). However, these other studies tend to measure only runoff that filtered through the permeable pavement and underlying aggregate without accounting for runoff that may have by-passed as overflow. Other studies (e.g. Bean et al., 2007) may also have had experimental designs that allow for exfiltration of filtered runoff into underlying soils resulting in zero effluent. While this scenario would effectively reduce pollutant loads by 100 percent (zero runoff), it does not properly assess the pollutant removal capabilities of permeable pavement. Additionally, the parking lot in this study contributed appreciably higher concentrations of TSS than 8

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Fig. 3. Cumulative sediment mass delivered from the parking lot as influent to and retained in the PICP, PC, and PA test plots as well as average infiltration rates measured periodically over the study period [PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt; cm/hr, centimeters per hour].

similar for PICP, PC, and PA, the ability to effectively filter sediment in the permeable pavement and underlying aggregate base was lower for PICP than PC or PA. Selbig and Buer (2018) concluded, in the absence of surface cleaning, permeable pavements with higher sediment removal efficiencies are likely to clog more rapidly than those with lower removal efficiencies. However, despite differences in TSS removal efficiencies reported for underdrain effluent for PICP and PC in Table 3, the total mass of sediment retained for each of these permeable pavements was nearly the same at approximately 35 and 36 kg, respectively. The rate of clogging in PICP and PC, as determined by a decline in measured average infiltration rates, was also generally the same over a 9-month period from September 2016 through May 2017 (Fig. 3). Although both PICP and PC were able to maintain an average infiltration rate of approximately 100 in/hr after this period, they were 82 and 76 percent lower, respectively, than their ability to infiltrate runoff when new. With a drainage ratio of 5:1, the PICP and PC surfaces were essentially clogged after approximately one year. Selbig and Buer (2018) similarly noted with a drainage ratio of nearly 10:1, both PICP and PC were clogged after the same amount of elapsed time. This indicates factors other than contributing area may influence the rate at which permeable pavement becomes clogged. Because the hydraulic capacity of permeable pavement can vary depending on many site-specific characteristics such as age and maintenance practices, the proper contributing drainage area is often based on professional judgement. The Wisconsin Department of Natural Resources suggests a drainage ratio less than or equal to three for roads and five for other impervious surfaces such as parking lots, rooftops, and driveways (Wisconsin Department of Natural Resources, 2016). These guidelines were established to minimize the surface clogging of permeable pavement and extend the ability of permeable pavement to

might influence the concentration of TSS from the parking lot by season. Only 60-min precipitation intensity indicated a significant positive correlation (0.51, p < 0.10) to concentrations of TSS in the spring. A similar conclusion was made by Winston et al. (2016a) when evaluating TSS concentrations from an asphalt parking lot in Ohio. This correlation was not replicated in summer, where, despite having higher precipitation intensities, concentrations of TSS from the parking lot were generally lower than in spring. Results of the Pearson correlation test also showed summer concentrations of TSS from the parking lot to be positively correlated to the number of dry days between runoff events (0.44, p < 0.10). These results indicate heavy spring showers were able to wash the large amount of sediment accumulated over the winter onto the permeable pavements, subjecting them to a high rate of loading. Use of pretreatment structures or timely source controls, such as street cleaning, could limit this effect. By summer, the parking lot may become more source limited with elapsed time between runoff events influencing sediment delivery. This seasonal influx of sediment is further illustrated in cumulative loading curves for each permeable pavement (Fig. 3). Sharp increases in sediment load tend to occur primarily between December and May. More than 25 percent of the total sediment load delivered from the parking lot to the PICP and PC surfaces occurred between the months of December 2016 and March 2017, and an additional 25 percent of the total sediment load delivered from the parking lot occurred after only a few runoff events in early May 2018. This was likely influenced by sand applied to the parking lot after a late winter snow storm on April 18, 2018. The seasonal influence of sediment load to PA was less obvious because of an extended period where the permeable pavement was vacant. While Table 3 shows total removal efficiencies for TSS load were 9

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the TP load delivered from the parking lot, PC demonstrated a greater effect than PICP or PA (Table 3). This was likely due to elevated concentrations of DP measured in the PICP and PA underdrain effluent that resulted in an overall export. This was counter to findings by Drake et al. (2014b) who reported higher TP concentrations in PC effluent than PICP but with a similar explanation as to why. The soluble nature of DP makes removal by permeable pavement difficult, whereas particulate-bound phosphorus would most likely have been sequestered in the void spaces of the permeable pavement and underlying aggregate. Additionally, DP leached from leaves and grass clippings that may have fallen onto the permeable pavement would have contributed to higher concentrations measured in the underdrain but would not have been accounted for at the parking lot influent monitoring point. It is unclear why PC demonstrated a greater ability to filter TP and DP. Brown and Borst (2015b) suggest precipitation of phosphate with metal cations at elevated levels of pH may have resulted in significant reductions of total and dissolved phosphorus. This conclusion was based on evidence by Song et al. (2001) who showed increasing precipitation of phosphate with calcium as pH levels exceeded 10.5. Other stormwater treatment practices have similarly been shown to reduce phosphorus by binding with iron at low pH (Erickson et al., 2007). The effect of pH on phosphorus retention may help explain differences in removal efficiencies between PICP, PC, and PA. The median value of pH in PC was 10.2. Appreciably lower median values were measured in both PICP and PA at 7.5 and 7.8, respectively. Additional research is needed to understand the efficacy of phosphorus removal by use of different additives to filter media and whether these additives are suitable for permeable pavements.

infiltrate runoff throughout several years. The American Society of Civil Engineers recommends the ratio of contributing drainage area to receiving permeable pavement area, in general, be 2:5 (Eisenberg et al., 2015). Other guidance documents adopt a more conservative approach by recommending a contributing drainage area that is typically less than twice the surface area of the permeable pavement (Minnesota Pollution Control Agency, 2017). Evidence from this study indicates a contributing drainage area much less than 5:1 would be necessary to extend the infiltrative capacity of the permeable pavements beyond one year (assuming no surface cleaning). Consideration of variables such as age, condition, slope, materials, or other factors that contribute to sediment delivery from impervious surfaces warrant careful assessment when determining the appropriate amount of contributing area. Additionally, efforts to prevent sediment from accumulating on impervious surfaces, such as street cleaning, as well as regular maintenance of PICP, PC, and PA, will help extend the infiltrative capacity of permeable pavement. 4.2. Estimates of surface clogging capacity and the relevance to drainage ratio The water-quality performance of permeable pavements is influenced by the progressive clogging of surfaces by sediment transported in runoff. The surface clogging capacity, defined as the capacity of the permeable pavement surface to accumulate pollutants (in mass per unit area) to the point where void spaces are full, is a parameter used to estimate when surface infiltration can no longer occur (Wisconsin Department of Natural Resources, 2016). Surface clogging capacity is independent of the contributing drainage area; however, both can have an impact on how quickly a permeable pavement will lose its ability to infiltrate runoff. An initial clogging capacity for PICP and PC was calculated by summing the mass of sediment retained in each permeable pavement after installation until a period when the surface was considered to be clogged. The resulting mass was then divided by the surface area of the permeable pavement. A second clogging capacity was similarly calculated by summing the mass of sediment retained in the permeable pavement for the period after restorative maintenance to when the surface was again considered to be clogged. After initial installation, PC showed a greater ability to filter sediment from runoff before clogging with a measured clogging capacity of 0.40 kg/m2 compared to 0.30 kg/m2 for PICP. After restorative maintenance, PC showed a decline in clogging capacity at 0.27 kg/m2 while PICP showed minor improvement at 0.34 kg/m2. From Table 3, the removal efficiency of sediment (TSS) for PICP was lower than both PC and PA. This is supported by a lower clogging capacity for PICP than PC. Previous studies have shown most of the sediment captured by PICP to be within the top 2.54 cm of the surface (Selbig and Buer, 2018; Winston et al., 2016b; Lucke and Beecham, 2011; Dierkes et al., 2002). Although the ability to capture and retain sediment was lower in PICP than PC or PA, the shallow penetration of sediment into the aggregate between PICP joints made for easy removal by maintenance practices, thereby restoring the clogging capacity to a level similar to when new. A decrease in the clogging capacity for PC after maintenance indicates less of an ability to restore the infiltrative capacity due to deeper penetrating sediment that goes beyond the reach of maintenance practices. Field measured clogging capacities for both PICP and PC are reasonably close to a clogging capacity of 0.30 kg/m2 recommended by the Wisconsin Department of Natural Resources in the design of permeable pavement (Wisconsin Department of Natural Resources, 2016). This indicates over time PICP may have a more consistent clogging capacity resulting in a greater ability to filter sediment while requiring less intensive and easier maintenance than PC.

4.4. Chloride Like DP, chloride is difficult to remove from stormwater runoff due to its soluble nature. From Table 3, total removal efficiencies for all three permeable pavements indicate slight reductions in chloride load; however, results from the nonparametric Wilcoxon signed-rank test for paired samples (Helsel and Hirsch, 2002) show residual chloride load in underdrain effluent to be significantly greater than the parking lot influent for PC and PA (p < 0.10), and no difference for PICP. The discrepancy between statistical comparison and computation of removal efficiencies can be explained by closer examination of individual runoff events. A single winter runoff event on January 10, 2017 produced more than 85 percent of the cumulative chloride load delivered to each permeable pavement (Fig. 4). Chloride load measured in the underdrain effluent for this event was also the highest event load observed over the 22-month monitoring period but was lower than the corresponding influent load resulting in a net reduction. The January 10 event substantially influenced resulting removal efficiencies based on the overall cumulative load, whereas the nonparametric statistical evaluation was not affected by such outliers. Seasonally high contributions of chloride can have a lasting effect on residual underdrain concentrations over time. Selbig and Buer (2018) observed a cycle of elevated chloride concentrations and load associated with early snowmelt and spring runoff followed by gradual dilution from subsequent storms; however, due to a limited number of data points representing winter runoff, the study was unable to confirm if this cycle would be repeated with continued application of chloridebased deicing agents. Fig. 4 confirms this pattern by highlighting two distinct peaks of chloride concentration over the 22-month monitoring period in parking lot influent as well as underdrain effluent in all three permeable pavements. Each peak occurs during the months of December through April, a period when chloride in deicers was likely concentrated in parking lot runoff during snowmelt events. Concentrations of chloride steadily decline over time with subsequent runoff events (Fig. 4). Concentrations of chloride in underdrain effluent for all three permeable pavements exceeded both the chronic and acute toxicity thresholds for freshwater life of 230 and 860 mg/L,

4.3. Phosphorus Although all three permeable pavements removed some portion of 10

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Fig. 4. Seasonal trends of chloride concentration in parking lot influent and PICP, PC, and PA underdrain effluent with denotations of USEPA aquatic toxicity thresholds (U.S. Environmental Protection Agency, 2012) [PICP, permeable interlocking concrete paver; PC, pervious concrete; PA, porous asphalt; mg/L, milligrams per liter; U.S. EPA, U.S. Environmental Protection Agency].

permeable pavement that utilize infiltration as a form of treatment warrant consideration in management of urban runoff.

respectively, on more occasions than the parking lot influent. Because the permeable pavement surfaces were not treated with sand or salt during winter months, the source of chloride could only come from parking lot runoff. Therefore, the frequency of toxicity exceedance is likely due to early attenuation of chloride with later release. Borst and Brown (2013), after identifying a similar behavior when testing the release of chloride from PA, PC, and PICP surfaces, were able to develop a power regression to predict decreasing concentrations with cumulative rainfall since previous snowmelt event. The differences in release rate were proportional to the measured surface infiltration rates (Borst and Brown, 2013). Permeable pavement appears to provide little treatment for dissolved ions and may pose a risk to groundwater resources through exfiltration of chloride-enriched runoff rather than be sequestered in the permeable pavement or aggregate base (Pitt et al., 1999). Despite the lack of sequestration, permeable pavement may still provide some water-quality benefit in cold-weather climates where road salt is the primary form of treatment for snow and ice. Drake et al. (2014b) suggest permeable pavements can provide temporary storage and create opportunities for dilution of sodium and chloride in outflows. Kazemi et al. (2018) observed significant increases in the salinity of water collected in reservoirs of permeable pavements but noted the increase could be beneficial for irrigation purposes because increases in calcium and magnesium from underlying aggregates can reduce the sodium absorption ratio. Others have suggested up to 77 percent less road salt is required for permeable pavement, compared to impervious asphalt surfaces, to prevent snow and ice buildup and maintain traction (Houle et al., 2009; Roseen et al., 2014). The environmental benefits as well as potential unintended consequences of stormwater practices like

4.5. Metals Concentrations of metals in both the parking lot influent and underdrain effluent exhibited relatively low variability as evidenced by coefficients of variation (Table 4). This could indicate sources of metals were relatively consistent such as detritus from automotive vehicles, erosion of the parking lot surface, and atmospheric deposition. In general, median concentrations of select metals (aluminum, copper, iron, manganese, lead, and zinc) for both parking lot influent and underdrain effluent were similar to those reported from previous studies (e.g. Brattebo and Booth, 2003; Bean et al., 2007; Roseen et al., 2012; Drake et al., 2014a; Drake et al., 2014b) with some notable differences. Median concentrations of aluminum were much higher than previously reported, both in parking lot influent and PICP and PC underdrain effluent. Zinc was similarly higher than previous studies, but not to the same degree as aluminum. The abundance of these metals may be the result of atmospheric deposition from a nearby metal recycling facility located approximately 0.25 km away from the study site. Fugitive dust from the recycling facility could have been deposited onto the permeable pavements creating elevated concentrations in the underdrain that would not have been accounted for in the parking lot. However, because the facility recycled both ferrous and non-ferrous metals, median concentrations of other metals besides aluminum and zinc would also have been expected to be higher than those reported in previous studies. In contrast, iron was up to three orders of magnitude lower than reported by Drake et al. (2014a, 2014b) and Winston et al. (2016a). 11

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with subsequent runoff events until slowly diminishing by mid to late summer. Export of DP was most evident in the underdrain effluent of PICP and PA. Vegetation deposited on the permeable pavement could have elevated underdrain effluent concentrations unaccounted for in the influent. In contrast, PC showed some reduction in both TP and DP. A higher pH in PC may have improved the removal efficiency through chemical precipitation. Elevated pH values may also have led to higher removal efficiencies by precipitating select metals in PC more than PICP or PA. Additional research linking the chemical composition of PC, as well as PICP and PA, and subsequent adsorption, precipitation, and transformation of pollutants is needed. Permeable pavement systems with an impermeable liner can reduce the mass of pollutants typically found in parking lot runoff; however, there is evidence showing the potential for dissolved pollutants to pass through permeable pavements and reach nearby receiving waters or underlying native soils in unlined systems. The environmental benefits as well as unintended consequences of stormwater practices like permeable pavement that utilize infiltration as a form of treatment warrant consideration in management of urban runoff.

PC had greater removal efficiencies measured in the underdrain than PICP or PA for all but three metals (calcium, chromium, and vanadium) (Table 5). Like phosphorus, elevated levels of pH in PC could have promoted metal precipitation. Genç-Furhman et al. (2016) found enhanced cadmium, copper, nickel, and zinc removal was observed when pH was approximately 8 but increasing the pH above this point had no additional effect. With a median pH of 10.2, PC would have been more likely to precipitate these metals than PICP or PA which had median pH values of 7.5 and 7.8, respectively. From Table 5, removal of copper, nickel, and zinc was indeed greater in PC than PICP or PA. Genç-Furhman et al. (2016) also noted higher values of pH (> 7) decreased the removal of chromium, which was again supported by underdrain removal efficiencies in Table 5. The effect of permeable pavements on the pH of filtered runoff could potentially be beneficial in areas prone to acidic rainfall (Kazemi and Hill, 2015). Additional research is needed to better understand the link between pH and chemical precipitation of select metals in permeable pavement. Regardless of origin, all three permeable pavements were able to significantly reduce the load of metals in both underdrain and overflow effluent. The only exception was a minor, but still significant (p < 0.10), export of zinc in the PICP overflow. Total removal efficiencies (combination of underdrain and overflow) for all metals were similar between PICP and PC averaging 42 and 49 percent, respectively. Average metals removal for PA was similar to the other surfaces at 40 percent but was a reflection of the permeable pavement only and not the overflow. Compared to previous studies, removal efficiencies reported in Table 5 tend to be appreciably lower for select metals. Borris et al. (2016) observed that heavy metals released from street sediments after leaching with synthetic stormwater were predominantly found in the particulate fraction, with a much smaller proportion found in the dissolved phase. In contrast, Sansalone and Buchberger (1997) determined zinc, cadmium, and copper in stormwater runoff were primarily in the dissolved form while lead, iron, and aluminum are mainly particulate-bound. Metals with a higher proportion in the dissolved fraction would be more difficult to remove than those that are particulate-bound. Because dissolved metals were not measured as part of this study, it's difficult to assess whether this was a contributing factor to resulting removal efficiencies.

Acknowledgements The authors would like to thank Roger Bannerman of the Wisconsin Department of Natural Resources, Bob Roehrig and Jennifer Schaff of County Materials Corporation, John McCarthy of Graef Engineering, Chris Homburg of Homburg Construction, and Greg Fries and Tim Troester of the city of Madison. The authors also would like to thank Oldcastle Inc., Unilock, County Materials Corporation, Rock Roads, and Homburg Construction for donating materials and labor to install the permeable interlocking pavers, porous asphalt, and pervious concrete. The Wisconsin Department of Natural Resources, Wisconsin Department of Transportation, County Materials Corporation, and Interlocking Concrete Pavement Institute provided financial support. Without the cooperation and effort of these individuals, agencies, and companies, this study would not have been possible. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Appendix A. Supplementary data

5. Conclusions Supplementary data to this article can be found online at https:// doi.org/10.1016/j.jenvman.2019.109510.

Analysis of stormwater-quantity and -quality data over a 22-month period indicates that using a lined system without exfiltration to native soils, PICP, PC, and PA were capable of significantly removing sediment and sediment-bound pollutants from runoff originating from an asphalt parking lot. Although the filtering capability of PC was generally more pronounced than PICP or PA, after accounting for concentrations and load in overflow, removal efficiencies for TSS were approximately 60 percent for all three permeable pavements. Retention of TSS eventually lead to clogging with most sediment delivery occurring during spring. Reducing the contributing drainage area from 9:1 to 5:1 did not translate into an extension in lifespan before becoming clogged. The rate of clogging was similar for PICP and PC, calculated to be 0.30 and 0.40 kg/m2, respectively. After restorative maintenance, PICP showed the ability to sustain these rates while PC dropped appreciably. Therefore, establishing a proper contributing drainage area would benefit from consideration of the condition, cleanliness, and anticipated loading potential of impervious surfaces rather than on the contributing area. Pollutants in the dissolved fraction are less likely to be retained in void spaces of permeable pavements and underlying aggregate bases. Export of chloride and dissolved phosphorus were evident in all but PC. Application of deicing agents in winter led to concentrations of chloride that at times exceeded the acute toxicity criterion for aquatic health. Although all three permeable pavements showed some attenuation of these concentration outliers, chloride continued to remain elevated

References Alyaseri, I., Zhou, J., 2016. Stormwater volume reductionin combined sewer using permeable pavement: city of St. Louis. J. Environ. Eng. 142 (4), 9. https://doi.org/10. 1061/(ASCE)EE.1943-7870.0001056. American Society of Testing and Materials, 2002. ASTM C33–02a—standard specification for concrete aggregates: west Conshohocken, Pa. American Society of Testing and Materials International. https://www.astm.org/DATABASE.CART/HISTORICAL/ C33-02.htm, Accessed date: 16 November 2017. American Society of Testing and Materials, 2009. ASTM C1701/C1701M—standard test method for infiltration rate of in place pervious concrete: west Conshohocken, Pa. American Society of Testing and Materials International. https://www.astm.org/ Standards/C1701.htm, Accessed date: 17 November 2018. Balades, J.-D., Legret, M., Madiec, H., 1995. Permeable pavements—Pollution management tools. Water Sci. Technol. 32 (1), 49–56. https://doi.org/10.1016/02731223(95)00537-w. Barrett, M.E., 2008. Effects of a permeable friction course on highway runoff. J. Irrig. Drain. Eng. 134 (5), 646–651. https://doi.org/10.1061/(ASCE)0733-9437(2008) 134:5(646). Bean, E.Z., Hunt, W.F., Bidelspach, D.A., 2007. Evaluation of four permeable pavement sites in eastern North Carolina for runoff reduction and water quality impacts. J. Irrig. Drain. Eng. 133 (6), 583–592. https://doi.org/10.1061/(asce)0733-9437(2007) 133:6(583) , Accessed date: 16 November 2017. Borris, M., Österlund, H., Marsalek, J., Viklander, M., 2016. Contribution of coarse particles from road surfaces to dissolved and particulate-bound heavy metal loads in runoff: a laboratory leaching study with synthetic stormwater. Sci. Total Environ. 573, 212–221. https://doi.org/10.1016/j.scitotenv.2016.08.062. Borst, M., Brown, R.A., 2013. Chloride released from three permeable pavement surfaces after winter salt application. J. Am. Water Resour. Assoc. 50 (1), 29–41. https://doi.

12

Journal of Environmental Management 251 (2019) 109510

W.R. Selbig, et al.

criteria for permeable pavement: Minnesota Pollution Control Agency web page. https://stormwater.pca.state.mn.us/index.php/Design_criteria_for_permeable_ pavement, Accessed date: 26 June 2017. Pitt, Robert, Clark, Shirley, Field, Richard, 1999. Groundwater contamination potential from stormwater infiltration practices. Urban Water 1 (3), 217–236. https://doi.org/ 10.1016/s1462-0758(99)00014-x, Accessed date: 17 November 2018. Pitt, R.E., Maestre, A., 2005. Stormwater quality as described in the national stormwater quality database (NSQD). In: Proceedings of the 10th International Conference on Urban Drainage, Copenhagen, Denmark, August 21-26, 2005, pp. 8. http://unix.eng. ua.edu/∼rpitt/Publications/Stormwater%20Characteristics/MS4%20Pitt%20and %20Maestre%2010ICUD%202005.pdf, Accessed date: 19 July 2019. Roseen, R.M., Ballestero, T.P., Houle, J.J., Briggs, J.F., Houle, K.M., 2012. Water quality and hydrologic performance of a porous asphalt pavement as a storm-water treatment strategy in a cold climate. J. Environ. Eng. 138 (1), 81–89. https://doi.org/10. 1061/(asce)ee.19437870.0000459, Accessed date: 17 November 2017. Roseen, R.M., Ballestero, T.P., Houle, K.M., Heath, Douglas, Houle, J.J., 2014. Assessment of winter maintenance of porous asphalt and its function for chloride source control. J. Transport. Eng. 140 (2), 8. https://doi.org/10.1061/(ASCE)TE.1943-5436. 0000618, Accessed date: 17 November 2017. Sansalone, J.J., Buchberger, S.G., 1997. Partitioning and first flush of metals in urban roadway storm water. J. Environ. Eng. 123 (2), 134–143. https://doi.org/10.1061/ (ASCE)0733-9372(1997)123:2(134). Selbig, W.R., Buer, N., 2018. Hydraulic, water-quality, and temperature performance of three types of permeable pavement under high sediment loading conditions. U.S. Geological Survey Scientific Investigations Report 2018-5037 44. https://doi.org/10. 3133/sir20185037. Shafique, M., Kim, R., Kyung-Ho, K., 2018. Rainfall runoff mitigation by retrofitted permeable pavement in an urban area. Sustainability 10 (4), 10. 1231. https://doi. org/10.3390/su10041231. Smith, D.R., 2017. Permeable Interlocking Concrete Pavements: Design, Specifications, Construction, Maintenance, fifth ed. Interlocking Concrete Pavement Institute, Chantilly, VA, pp. 126. Song, Y., Hahn, H.H., Hoffman, E., 2001. The effects of pH and Ca/P ratios on the precipitation of calcium phosphate. In: Second International Conference on Recovery of Phosphate from Sewage and Animal Wastes (Noordwijkerhout, Netherlands). Steuer, J.J., Selbig, W.R., Hornewer, N.J., Prey, J., 1997. Sources of contamination in an urban basin in marquette, Michigan and an analysis of concentrations, loads, and data quality. USGS Water Resources Investigation 97–4242, 25. https://doi.org/10. 3133/wri974242. Støvring, J., Dam, T., Bergen Jensen, M., 2018. Hydraulic performance of lined permeable pavement systems in the built environment. Water 10 (587), 15. https://doi.org/10. 3390/w10050587. U.S. Environmental Protection Agency, 1993. Methods for the determination of inorganic substances in environmental samples: Environmental Monitoring Systems Laboratory. pp. 18 EPA 600/R–93/100. U.S. Environmental Protection Agency, 2003. Guidelines establishing test procedures for the analysis of pollutants; analytical methods for biological pollutants in ambient water. final rule: Federal Register 68 (139), 13. accessed January 26, 2017. https:// www.federalregister.gov/d/03-18155. U.S. Environmental Protection Agency, 2012. National recommended water quality criteria—aquatic life criteria table. https://www.epa.gov/wqc/national-recommendedwater-quality-criteria-aquatic-life-criteria-table, Accessed date: 27 April 2017. Winston, R.J., Davidson-Bennet, K.M., Buccier, K.M., Hunt, W.F., 2016a. Seasonal variability in stormwater quality treatment of permeable pavements situated over heavy clay and in a cold climate: water, Air. Soil Pollution 227, 21–140. https://doi. org/10.1007/s11270-016-2839-6, Accessed date: 17 November 2017. Winston, R.J., Al-Rubaei, A.M., Blecken, G.T., Vicklander, M., Hunt, W.F., 2016b. Maintenance measures for preservation and recovery of permeable pavement surface infiltration rate—the effects of street sweeping, vacuum cleaning, high pressure washing, and milling. J. Environ. Manag. 169, 132–144. https://doi.org/10.1016/j. jenvman.2015.12.026, Accessed date: 17 November 2017. Wisconsin Department of Natural Resources, 2016. Stormwater post-construction technical standards for permeable pavement (1008). http://dnr.wi.gov/topic/ Stormwater/standards/postconst_standards.html, Accessed date: 26 April 2019.

org/10.1111/jawr.12132. Brattebo, B.O., Booth, D.B., 2003. Long-term stormwater quantity and quality performance of permeable pavement systems. Water Res. 37 (18), 4369–4376. https://doi. org/10.1016/S0043-1354(03)00410-X, Accessed date: 17 November 2017. Braswell, A.S., Anderson, A.R., Hunt, W.F., 2018. Hydrologic and water quality evaluation of a permeable pavement and biofiltration device in series. Water 10 (1), 21. 33. https://doi.org/10.3390/w10010033. Brown, C., Chu, A., van Duin, B., Valeo, C., 2009. Characteristics of sediment removal in two types of permeable pavement. Water Qual. Res. J. Can. 44 (1), 59–70. https:// doi.org/10.2166/wqrj.2009.007. Brown, R.A., Borst, Michael, 2015a. Quantifying evaporation in a permeable pavement system. Hydrol. Process. 29 (9), 2100–2111. https://doi.org/10.1002/hyp.10359. Brown, R.A., Borst, Michael, 2015b. Nutrient infiltrate concentrations from three permeable pavement types. J. Environ. Manag. 164, 74–85. http://doi.org/10.1016/ j. jenvman.2015.08.038. Carvin, R.B., Selbig, W.R., 2019. Stormwater-quality data for lined permeable pavement systems in Madison, WI, from September 2016 through July 2018. U.S. Geological Survey data release. https://doi.org/10.5066/P9IQHJ06. Dierkes, Carsten, Kuhlmann, Lothar, Kandasamy, Jaya, Angelis, George, 2002. Pollution retention capability and maintenance of permeable pavements in International Conference on Urban Drainage. In: 9th, Portland, Oreg., 2002, Proceedings: Reston, Va. American Society of Civil Engineers, pp. 13. https://doi.org/10.1061/ 40644(2002)40, Accessed date: 17 November 2017. Drake, Jennifer, Bradford, Andrea, Van Seters, Tim, 2014a. Stormwater quality of springsummer-fall effluent from three partial-infiltration permeable pavement systems and conventional asphalt pavement. J. Environ. Manag. 139, 69–79. https://doi.org/10. 1016/j.jenvman.2013.11.056, Accessed date: 17 November 2017. Drake, Jennifer, Bradford, Andrea, Van Seters, Tim, 2014b. Winter effluent quality from partial-infiltration permeable pavement systems. J. Environ. Eng. 140 (11), 13. https://doi.org/10.1061/(ASCE)EE.1943-7870.0000854, Accessed date: 17 November 2017. Eisenberg, Bethany, Lindow, K.C., Smith, D.R. (Eds.), 2015. Permeable Pavements: Reston, Va. American Society of Civil Engineers, pp. 249. Environment Canada, 2016. Canadian environmental protection act, 1999, federal environmental quality guidelines – vanadium. http://www.ec.gc.ca/ese-ees/default. asp?lang=En&n=48D3A655-1#toc7, Accessed date: 4 April 2019. Erickson, A.J., Gulliver, J.S., Weiss, P.T., 2007. Enhanced sand filtration for storm water phosphorus removal. J. Environ. Eng. 133 (5), 485–497. https://doi.org/10.1061/ (asce)0733-9372(2007)133:5(485). Genç-Furhman, H., Mikkelsen, P.S., Ledin, A., 2016. Simultaneous removal of As, Cd, Cr, Cu, Ni, and Zn from stormwater using high-efficiency industrial sorbents: effect of pH, contact time and humic acid. Sci. Total Environ. 566–567, 76–85. https://doi. org/10.1016/j.scitotenv.2016.04.210. Gilbert, J.K., Clausen, J.C., 2006. Stormwater runoff quality and quantity from asphalt, paver, and crushed stone driveways in Connecticut. Water Res. 40 (4), 826–832. https://doi.org/10.1016/j.watres.2005.12.006. Houle, K.M., Roseen, R.M., Ballestero, T.P., 2009. Examinations of pervious concrete and porous asphalt pavements performance for stormwater management in northern climates. In: Proceedings of the World Environmental and Water Resources Congress, Kansas City, Missouri, . https://doi.org/10.1061/41036(342)111. Helsel, D.R., 2005. Nondetects and Data Analysis—Statistics for Censored Environmental Data. John Wiley and Sons, New York, pp. 250. Helsel, D.R., Hirsch, R.M., 2002. Statistical methods in water resources: U.S. Geological Survey techniques of water resources investigations. book 4, chap. A3. https://pubs. usgs.gov/twri/twri4a3/, Accessed date: 17 November 2018 522. Kazemi, F., Hill, K., 2015. Effect of permeable pavement basecourse aggregates on stormwater quality for irrigation reuse. Ecol. Eng. 77, 189–195. https://doi.org/10. 1016/j.ecoleng.2015.01.020. Kazemi, F., Golzarian, M.R., Myers, B., 2018. Potential of combined Water Sensitive Urban Design systems for salinity treatment in urban environments. J. Environ. Manag. 209, 169–175. https://doi.org/10.1016/j.jenvman.2017.12.046. Lucke, Terry, Beecham, Simon, 2011. Field investigation of clogging in a permeable pavement system. Build. Res. Inf. 39 (6), 603–615. https://doi.org/10.1080/09613218. 2011.602182. Minnesota Pollution Control Agency, 2017. Minnesota stormwater manual—design

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