Influence of rubber particle inputs on nitrogen removal efficiency of bioretention systems

Bioretention systems effectively capture rubber particles and other microplastics in stormwater runoff. However, it is uncertain whether long-term particle accumulation affects pollutant removal efficacy. This study investigated the impact of various concentrations of ethylene-propylene-diene-monomer (EPDM) particles (0, 50, 100, and 400 mg/L) on bioretention system nitrogen removal performance. The input of EPDM during short-duration (2 h) rainfall favored the removal of nitrogen, and the total nitrogen effluent concentration of the bioretention system with EPDM was reduced by 0.59-1.52 mg/L compared with that of the system without EPDM. In addition, the input of EPDM reduced the negative effects of drought. During long-duration (24 h) rainfall, higher concentrations of EPDM led to lower nitrate-nitrogen concentrations in the effluent. The bioretention system with EPDM required less time for nitrate-nitrogen removal to reach 50% than that without EPDM input. Microbial community analysis showed that EPDM increased the relative total abundance of denitrifying bacteria (such as <i>Dechloromonas</i>, <i>Zoogloea</i>, <i>Ramlibacter</i>, and <i>Aeromonas</i>) by 7.25-10.26%, which improved the denitrification capacity of the system.

Authors

Institutions

Publication Details

Journal
Water Science & Technology
Published
2024-11-05
DOI
https://doi.org/10.2166/wst.2024.363
Citations
2
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
0.27

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Influence of rubber particle inputs on nitrogen removal efficiency of bioretention systems

Jiaqing Xiong, Jiajia Zhou, Qianhe Xia, Tuanping Hu et al.
2 citations
Water Science & Technology
Microplastics and Plastic Pollution
0.27
article

Influence of rubber particle inputs on nitrogen removal efficiency of bioretention systems

Jiaqing Xiong, Jiajia Zhou, Qianhe Xia, Tuanping Hu, Wenyi Li
article en
2 citations

Abstract

Bioretention systems effectively capture rubber particles and other microplastics in stormwater runoff. However, it is uncertain whether long-term particle accumulation affects pollutant removal efficacy. This study investigated the impact of various concentrations of ethylene-propylene-diene-monomer (EPDM) particles (0, 50, 100, and 400 mg/L) on bioretention system nitrogen removal performance. The input of EPDM during short-duration (2 h) rainfall favored the removal of nitrogen, and the total nitrogen effluent concentration of the bioretention system with EPDM was reduced by 0.59-1.52 mg/L compared with that of the system without EPDM. In addition, the input of EPDM reduced the negative effects of drought. During long-duration (24 h) rainfall, higher concentrations of EPDM led to lower nitrate-nitrogen concentrations in the effluent. The bioretention system with EPDM required less time for nitrate-nitrogen removal to reach 50% than that without EPDM input. Microbial community analysis showed that EPDM increased the relative total abundance of denitrifying bacteria (such as <i>Dechloromonas</i>, <i>Zoogloea</i>, <i>Ramlibacter</i>, and <i>Aeromonas</i>) by 7.25-10.26%, which improved the denitrification capacity of the system.

Water Science & TechnologyVol. 90(10)
Xi'an University of Architecture and Technology (CN), Jiaxing Vocational Technical College (CN)
National Natural Science Foundation of China, Xi'an University of Architecture and Technology
Clean water and sanitation
Openalex Percentile: Top 52%
Microplastics and Plastic Pollution
0.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.