1. Introduction
Over the past century, natural surfaces have been converted into impermeable finishes such as pavements, parking lots, and roofs. These changes in land use associated with urbanization have had significant effects on the hydrologic response of drainage basins, as reported by various researchers [
1,
2,
3,
4,
5]. Consequently, the quantity and frequency of floods in streams have been magnified [
5]. According to Chithra et al. [
2], increases in impervious cover not only alter the urban hydrology but also degrade the aquatic ecosystem. In the event of rainfall, pollutants such as sediment, pesticides, and petroleum products, to name a few, are accumulated and rapidly transported by surface runoff to nearby water bodies. The authors note that this situation is compounded by the urban heat island (UHI) effect. This refers to the phenomenon where atmospheric and surface temperatures in urban areas are higher than in rural areas.
In spite of pervasive changes to urban hydrology, city planners and stormwater engineers have addressed the necessity of strategic planning for urban growth in order to alleviate the negative impacts of urbanization on natural resources [
1,
5]. Stormwater management measures commonly referred to as low impact development (LID), sustainable drainage systems (SUDs), or stormwater best management practices (BMPs) [
6] have shown promise in mitigating the effects of urbanization and land development [
7,
8,
9]. The underlying principle of these measures is to maintain the hydrology of an urban watershed in order to approach its natural condition before it was developed [
8,
10]. According to Coffman [
10], reducing the amount of impervious surfaces of a developed site is one LID design principle that can restore the hydrologic function of a watershed.
Permeable paving is one LID measure that can be used as an alternative to conventionally impervious surfaces (such as low-traffic roadways, path walks, and car parks [
8,
11]), which generally catch two-thirds of rainfall in an urban watershed [
12]. Unlike traditional pavement surfaces like concrete and asphalt, permeable pavements have voids in their structure that are specifically designed to promote infiltration and storage of stormwater through the paving layers [
6,
12].
A number of studies have indicated the capacity of various permeable pavement materials in the attenuation of runoff rate and volume. Booth and Leavitt [
13] evaluated the degree of surface runoff reduction of four permeable pavement types including Grasspave
2®, Gravelpave
2®, Turfstone
® and UNI Eco-Stone
®. Based on their monitoring, they found that the permeable stalls showed virtually no surface runoff compared to the control asphalt pavement which generated a runoff nearly equal to the maximum rainfall intensity. In a laboratory test conducted by Sañudo-Fontaneda et al. [
14], interlocking concrete block pavement (ICBP) models also showed a residual runoff of 0.5–10%.
Runoff from street surfaces generally contains a large volume of contaminants [
15]. LID pavements have been identified as being effective in filtering pollutants like suspended solids (SS) and heavy metals by trapping them within the voids of pavement layers as shown in the literature [
16,
17,
18,
19]. With the promising filtration capacity of permeable pavement comes a great concern of its susceptibility to clogging [
11]. As pollutants are trapped in the voids, the hydrologic efficiency of LID pavement may be reduced. The permeability loss due to particle clogging can be very dramatic: some field tests report a 92% reduction in infiltration rates after two months of testing [
20]. Some authors [
21] have observed significant infiltration reductions from 290 mm/min to 19 mm/min after approximately two years of operation.
Many field and laboratory investigations have been made regarding the clogging dynamics of permeable pavements. The long-term performance associated with particle clogging is typically influenced by a wide range of factors and local conditions, including pavement type and design [
22,
23,
24]. Laboratory assessments conducted by Andrés-Valeri et al. [
22] indicated that porous concrete pavement showed less clogging potential than porous asphalt pavement due to its higher infiltration capacity and recovery from clogging. In another laboratory study [
23] it was observed that particle clogging occurred on the surface for porous asphalt and on the geotextile for Hydrapave
® after 12 years of stormwater simulation, whereas Permapave
® showed no clogging even after 26 years. Martin et al. [
24] investigated the clogging behavior of porous asphalt, with aggregate gradation considered. They found that the clogging rate can be estimated as a function of the gradation of aggregates and clogging materials.
The properties of clogging particles are also considered to have an influence on the permeability degradation of permeable pavement [
25,
26,
27,
28]. Coughlin et al. [
26] evaluated the clogging effect of sand and sodium montmorillonite (clay) in pervious concrete and concluded that clay causes ten times more infiltration reduction. Regarding clogging with sand, the experiments carried out by Deo et al. [
27] showed that permeability reduction was more severe with finer gradation than coarser gradation of clogging materials. Their test results along with pore size analysis revealed that there is a certain ratio of pore size to particle size that yields the highest clogging degree.
In addition to particle-related clogging, porous pavement may be clogged as a result of permanent deformation [
29]. Deformation-related clogging is the reduction in void content caused by cumulative rutting from traffic loads. Pore size may also be reduced due to binder breakdown [
30]. Because of the exposure to air of porous mixtures, the binder ages faster, resulting in a loss of cohesion which contributes to a reduction in pore size. The present study aims to understand the hydraulic behavior of permeable pavement, specifically that of pervious concrete. Pervious concrete is a type of permeable pavement composed of coarse aggregates only and no fines. Furthermore, the present study aims to investigate two factors that influence the clogging processes of pervious concrete: aggregate size, and clogging particle size and gradation. To accomplish this, laboratory experiments were carried out in order to evaluate the permeability characteristics of pervious concrete pavement. Permeability values were assessed in two scenarios, which were newly built and clogged condition. The scenarios considered three different aggregate sizes and four different clogging particle sizes.
3. Results
The initial permeability (
ko) of the new PC specimen was determined using the constant head concept as described in the previous section. For all specimens, the discharge velocity was measured at four different hydraulic gradients to verify the flow condition mentioned in the previous section.
Figure 4 shows the results of the initial permeability tests conducted for A1, B1, and C1. With regard to the plot, it can be seen that the assumption of non-laminar flow in pervious concrete does hold true, since the values of
v and
i reflect a nonlinear relationship. A regression analysis was performed on these data and revealed a good fit with the modified Darcy’s law equation (Equation (3)). Curve fitting parameters
k and
n were obtained, and the results are presented in
Table 5. The values of
n appear to be less than 1.0, which indicates signs of turbulence. This is in good agreement with the results of several studies [
33,
34,
35,
36]. Furthermore, based on the initial permeability values measured, it can be concluded that particle gradation affects the infiltration ability of PC specimens. In this study, the specimen with the largest nominal maximum aggregate size had the fastest discharge velocity for all head differences, whereas the specimen with the smallest NMAS had the slowest discharge velocity. It can be seen that an increase in aggregate size corresponded to an increase in the permeability coefficient. This can be attributed to the pore structure of the material since pervious concrete specimens have pore sizes that are proportional to their aggregate sizes. As presented in
Table 2, larger aggregate sizes yielded larger representative pore sizes.
The reduced permeability was monitored for the entire duration of the clogging simulations. Permeability measurements were carried out with every incremental addition of clogging particles for different PC mixtures. The normalized permeability after each cycle was calculated using Equation (4), where
kc is the measured permeability for the current clogging cycle and
ko is the initial permeability:
Following the measurement of reduced permeability due to particle-clogging, the specimens were de-clogged by pressure washing in an attempt to eliminate the trapped sand. The permeability at
i = 1.0 was measured to establish the initial permeability for the subsequent clogging experiment. As shown in
Figure 5, the permeability was restored to its original value. The average values of
k for four test cases per specimen are summarized in
Table 6.
Figure 6 shows the permeability reduction in PC specimens A, B, and C after different clogging cases. Three single-sized clogging particles (CP 1, CP 2, and CP 3) having mean diameters (D
50) of 0.7, 0.5, and 0.3 mm, respectively, were used to investigate which road dust size is critical to a particular gradation of pervious concrete pavement. The critical particle size was assessed depending on the degree of permeability loss measured before the terminal stage was reached (i.e., the stage at which one of the conditions discussed in the previous section was met). Furthermore, one non-uniformly graded sand (CP 4) having mean diameter of 0.4 mm was used to assess the effect of clogging particle gradation to clogging behavior.
From
Figure 6a, it can be observed that the permeability of sample A was reduced to a maximum of 34%, which was caused by CP 2. Clogging particles CP 1 and CP 3 both reduced the permeability by only 14%, with CP 1 having a higher clogging rate than CP 3. For this specimen, A1 was observed to have a relatively large clogging particle size compared to pore size, which inhibited more particles from entering through the voids. A3 was observed to have a relatively small particle size compared to pore size, which resulted in the passage of most particles through the end of the specimen. When considering the slope of the curves for A1, A2, and A3, it can be seen that the slope is at a maximum for A1 until midway through the clogging simulation. This suggests that the surface pores were easily blocked by large particles but only until the addition of a total of 12.5 g. After that, further addition of particles did not show more permeability reduction because sand could no longer penetrate the pores. A2 was found to have reached further sand addition and showed the most severe degree of clogging. This implies that CP 2 has the highest potential of being trapped and retained in the pores, among the three CP.
From
Figure 6b, it may be noted that B1, B2, and B3 reveal reductions in permeability of 6%, 26%, and 67%, respectively. B1 and B2 were barely clogged due to their relatively small pore sizes, compared with the large particle sizes which resulted in unsuccessful clogging of a majority of the particles. B3 exhibited the highest clogging effect. However, the rate of clogging was so gradual that it took 60 g of sand to reach the terminal stage. CP 3 was found to be successfully trapped in pores, based on its consistent clogging rate.
From
Figure 6c, it can be concluded that the permeability of C3 was reduced by twice as much as for C1 and C2, which had permeability losses of 35% and 31%, respectively. For specimen C, CP 1 and CP 2 were also observed to be relatively large with regard to penetration of the pores. CP 3 was found to have a gradation that could successfully clog sample C, exhibiting the highest clogging rate (maximum slope) and resulting in a 61% permeability loss. CP 3 was considered to be critical for both samples B and C, but due to the difference in NMAS and corresponding pore size, a lesser amount of sand was needed to clog sample C than B.
From the results of the clogging simulations, it was found that for all aggregate sizes there were clogging particle sizes that seemed too big and too small which failed to effectively reduce the pore sizes of pervious concrete. It was found that clogging particles between those sizes were successfully trapped in the pores, yielding the highest permeability losses. Among these successful clogging sizes, the smallest is considered to be the size that causes the most severe permeability reduction, because the terminal permeability of clogged pervious concrete will be governed by the permeability of the clogging material. For this reason, clogging is considered to be significantly influenced by the minimum particle size that can be trapped in (and not flushed from) the pores. Based on these observations, the effective diameters of the critical clogging particles for sample A (NMAS = 10), sample B (NMAS = 8), and sample C (NMAS = 5) are 0.5, 0.3 and 0.3 mm, respectively. It should be noted that sample A has the highest pore size and sample C has the smallest pore size (see
Table 2). This may imply that the critical particle size varies with NMAS as well as representative pore size of pavement material.
The degree of clogging due to non-uniform sand (CP 4) was also assessed for the three PC mixtures. CP 4 represents the gradation of actual road dust that was collected from Seoul, Korea. Based on
Figure 6, permeability loss due to graded sand ranged from 80–90%. This is relatively high compared to the degree of clogging caused by the single-sized sands which amounted to a maximum of 67% permeability reduction and an average of 32%. Unlike the single-sized clogging particles, CP 4 contained particles of a wide range of sizes. The larger sands filled surface pores easily and the smaller sands were deposited in tinier voids, causing a much greater pore size reduction.
Based on the results of A4, B4, and C4, it can be seen that there is a decrease in the amount of particles needed to reach the terminal stage of clogging when there is a decrease in the aggregate size. This indicates that particle clogging occurs faster for pervious concrete mixtures with smaller NMAS. As mentioned in the previous section, specimens with larger aggregates have bigger pores, and require more particles to fully clog the voids. This may suggest that increasing the nominal maximum aggregate size of pervious concrete can be effective in delaying the permeability reduction caused by particle clogging.