Clogging effects on a polyurethane-based permeable pavement under controlled laboratory settings

Abstract

[Abstract] Permeable pavements are a well-established green solution for mitigating urban runoff, but their implementation in cities has been limited due to their low load-bearing capacity. Previous studies of a new polyurethane-based mixture, named Polyurethane Bound Permeable Mixture (PBPM), reported good resistance to heavy loads such buses and trucks. Nevertheless, PBPM remains susceptible to clogging caused by sediment accumulation transported by runoff. Consequently, this study investigated three mixtures under various clogging conditions: two PBPM mixtures with aggregate sizes of 8 mm (PBPM8) and 5 mm (PBPM5), and one bitumen-based mixture with an aggregate size of 8 mm (PA8) as control. Laboratory experiments were conducted using a rainfall simulator and real sediments to evaluate the impact of sediment particle size, sediment load, and rainfall intensity on the hydraulic conductivity (Kv). Three experiments were conducted: Experiment 1 determined the combination of rain intensity and sediment particle size distribution (PSD) that caused maximum clogging; Experiment 2 assessed Kv reduction with increasing sediment loads (applied in multiple steps) at a fixed rainfall intensity; and Experiment 3 examined Kv changes under different combinations of sediment loads (applied in one step) and rainfall intensities. PBPM exhibited superior clogging resistance, maintaining ∼40% of its initial Kv at 2000 g/m², outperforming PA8 and other bitumen-based mixtures. Clogging was exacerbated by shorter rains and specific sediment size distributions, whereas lower-intensity rainfall yielded inconsistent effects. Overall, Kv decreased proportionally with increasing sediment loads. These findings demonstrate that clogging severity is governed by rainfall characteristics (duration and intensity) and sediment properties (size, load, and application method); however, comparisons with previous research suggest that porosity is a greater influence than aggregate size. This study provides a framework for developing representative laboratory-scale clogging protocols and optimizing permeable pavement mixture designs.