Laboratory analysis on the surface runoff pollution reduction performance of permeable pavements

Jia Liu; Hexiang Yan; Ziyuan Liao; Kui Zhang; Arthur R Schmidt; Tao Tao

doi:10.1016/j.scitotenv.2019.07.028

Laboratory analysis on the surface runoff pollution reduction performance of permeable pavements

Sci Total Environ. 2019 Nov 15:691:1-8. doi: 10.1016/j.scitotenv.2019.07.028. Epub 2019 Jul 4.

Authors

Jia Liu¹, Hexiang Yan², Ziyuan Liao², Kui Zhang², Arthur R Schmidt³, Tao Tao⁴

Affiliations

¹ College of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, PR China; Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
² College of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, PR China.
³ Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
⁴ College of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, PR China. Electronic address: taotao@tongji.edu.cn.

PMID: 31306873
DOI: 10.1016/j.scitotenv.2019.07.028

Abstract

Permeable pavements are used to address the water quality impacts of urbanization. However, few quantitative relations are available on their pollutant removal performance with respect to varying conditions, especially for different components of a permeable pavement. Individually, the water quality performance of the surface pavement layer and gravel layer of a permeable pavement under various conditions was determined in laboratory-scale pavement cells. Our aim was to reveal the manner in which different factors influence the ability of these two layers to remove total suspended solids (TSS), nutrients, including nitrate (NO_x-N), ammonia (NH₄-N) and phosphorous (TP), chemical oxygen demand (COD), and heavy metals (copper (Cu), lead (Pb), cadmium (Cd), and zinc (Zn)), and to provide quantitative understanding of these influences. The removal efficiencies of most stormwater runoff pollutants showed a significant variation with changing rainfall intensity. NH₄-N, NO_x-N, TP, and TSS removal exhibited statistically negative linear relationship with rainfall intensity. TSS removal was negatively correlated with TSS concentration for the gravel layer, whereas no obvious trend was observed for the surface pavement layer. The statistical results obtained demonstrate that TSS, NH₄-N, NO_x-N, TP, and COD were removed mainly by the surface pavement layer. A smaller gravel gradation was more effective for removing most pollutants, except for NO_x-N and COD. Positive linear relationships were observed between the gravel layer thickness and pollutant (TSS, TP, NH₄-N, Cu, and Cd) removal. More importantly, a simple mathematical model was developed to predict the overall performance of the permeable pavement system. By comparing with the overall measured performance, a good performance was achieved, illustrating its promising application in the design of permeable pavements.

Keywords: Gravel layer; Mathematical model; Permeable pavement design; Stormwater runoff pollutants; Surface pavement layer.