Porous pavements are commonly used stormwater management systems. However, the understanding of their long-term capacity to retain heavy metals is limited. This study aims to investigate the long-term removal of heavy metals in three different porous pavements – Porous Asphalt (PA), Hydrapave (HP) and Permapave (PP) over accelerated laboratory experiments representing 26 years with varying hydrological conditions (drying/wetting periods and flow rates). A treatment model that simulates adsorption and desorption processes was developed for the first time to predict the long-term heavy metal removal by porous pavements. Unsurprisingly, all tested porous pavements performed better in removing metals that tend to attach to solid particles (e.g. Pb, Al, Fe) than more soluble ones (e.g. Cu, Zn, and Mn). There was a general increase of heavy metal concentrations at the outlet of the pavements over time as a result of a decrease in adsorption capacity of the systems, especially after the occurrence of clogging; the soluble heavy metals removal decreased with a reduction in flow rates which was speculated to be due to more time being available for desorption of metals and breakdown of accumulated sediments. The proposed model simulated the trend, fluctuations and peaks of heavy metal concentrations reasonably well, achieving the Nash-Sutcliffe coefficient (NSE) values of 0.53–0.68 during model calibration. The model was most promising in predicting Al and Cu release from porous pavements (50%–91% of the observed data within the 90% uncertainty bands, NSE = 0.44–0.74), followed by Fe and Pb (27–77% observations within the bands, NSE = 0.20–0.69). Further improvements of the model are needed for it to be applicable for Zn and Mn.

多孔路面是常用的雨水管理系统。但是，对于它们保留重金属的长期能力的理解是有限的。这项研究的目的是在经过长达26年的不同水文条件（干燥/湿润时间）的加速实验室实验中，研究长期去除三种不同多孔路面-多孔沥青（PA），Hydrapave（HP）和Permapave（PP）中的重金属的方法。和流量）。首次开发了一种模拟吸附和解吸过程的处理模型，以预测多孔路面对重金属的长期去除。不出所料，所有测试的多孔路面去除倾向于附着到固体颗粒（金属表现较好例如铅，铝，铁）比更可溶的人（例如铜，锌和锰）。随着时间的推移，由于系统的吸附能力下降，特别是在发生堵塞之后，人行道出口处的重金属浓度总体上会增加。可溶性重金属的去除随着流速的降低而降低，这被认为是由于有更多的时间可用于金属的解吸和沉积物的分解。所提出的模型对重金属浓度的趋势，波动和峰值进行了较好的模拟，在模型校准期间，Nash-Sutcliffe系数（NSE）值达到0.53-0.68。该模型在预测铝和铜从多孔路面中的释放（在90％不确定带内，观测数据的50％–91％，NSE = 0.44-0.74）中最有前景时，其次是Fe和Pb（在27％至77％的观测范围内）乐队，NSE = 0.20–0.69）。需要对该模型进行进一步的改进，以使其适用于Zn和Mn。