A study on the hydraulic and pollutant removal performance of bioretention systems using plants and oyster shells.

Abstract

Bioretention systems are commonly employed in urban stormwater runoff treatments because of the synergistic effects of plants, fillers, and microorganisms. Conventional bioretention systems often face challenges posed by stringent plant requirements and the risk of media failure. Therefore, this study selected drought and flood-tolerant Chlorophytum comosum 'Green' (spider plant) and porous oyster shells fillers to establish modified bioretention systems. The systems operated continuously for 197 days to investigate their comprehensive performance under varying pollutant loads. Results indicated that the C. comosum-oyster shell system (with 20% oyster shell particles) exhibited significantly higher permeability coefficients and retention rates than the systems without plants or oyster shells (p < 0.05). During the low-load influent stage, the system achieved removal rates exceeding 90% for ammonia nitrogen (NH 4 + -N), nitrate nitrogen (NO 3 - -N), and total nitrogen (TN). Furthermore, its chemical oxygen demand (COD) removal performance excelled that of conventional bioretention systems under all influent loading conditions. A significant positive correlation was observed between the total biomass of C. comosum and the nitrogen removal efficiency of the system (p < 0.05). The synergistic effect of plants and oyster shells notably increased the relative abundance of functional microbial communities involved in nitrogen and phosphorus transformation, including Nitrospira, Thauera, and Bacillus. Taken together, the combined application of C. comosum and oyster shell fillers can simultaneously enhance the hydraulic characteristics and pollutant removal performance of bioretention systems, providing new insights into urban runoff pollution control and sustainable water resource management.

Keywords

Identifiers

DOI

10.1016/j.jenvman.2026.129130

PubMed

41762506

Journal

Journal of environmental management

Year

2026