Reduction of Escherichia coli, Enterococcus faecalis and Pseudomonas aeruginosa in stormwater bioretention: Effect of drying, temperature and submerged zone

Søberg, Laila C.; Viklander, Maria; Blecken, Godecke-Tobias; Hedström, Annelie

doi:10.1016/j.hydroa.2019.100025

Cited by 11 publications

(5 citation statements)

References 40 publications

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“…Bioretention system, also known as rain garden, biofiltration or biofilter, is a typical low impact development (LID) facility to purify runoff through the combined action of plants, soil media and microorganisms [1,2]. It has been proved to be effective for the removal of most pollutants in runoff, such as heavy metals [3,4], suspended sediment [5][6][7], grease [8], pathogenic bacteria [9,10], etc. However, many previous studies indicated that bioretention systems have a low and unstable nitrogen removal rate [11,12], especially of NO 3 − .…”

Section: Introductionmentioning

confidence: 99%

Importance of the Submerged Zone during Dry Periods to Nitrogen Removal in a Bioretention System

Qin

Wang

et al. 2020

Water

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Adding a submerged zone (SZ) is deemed to promote denitrification during dry periods and thus improve NO3− removal efficiency of a bioretention system. However, few studies had investigated the variation of nitrogen concentration in the SZ during dry periods and evaluated the effect of the variation on nitrogen removal of the bioretention system. Based on the experiment in a mesocosm bioretetion system with SZ, this study investigated the variation of nitrogen concentration of the system under 17 consecutive cycles of wet and dry alternation with varied rainfall amount, influent nitrogen concentration and antecedent dry periods (ADP). The results indicated that (1) during the dry periods, NH4+ concentrations in SZ showed an exponential decline trend, decreasing by 50% in 12.9 ± 7.3 h; while NO3− concentrations showed an inverse S-shape declining trend, decreasing by 50% in 18.8 ± 6.4 h; (2) during the wet periods, NO3− concentration in the effluent showed an S-shape upward trend; and at the early stage of the wet periods, the concentration was relatively low and significantly correlated with ADP, while the corresponding volume of the effluent was significantly correlated with the SZ depth; (3) in the whole experiment, the contribution of nitrogen decrease in SZ during dry periods to NH4+ and NO3− removal accounted for 12% and 92%, respectively; and the decrease of NO3− in SZ during the dry period was correlated with the influent concentration in the wet period and the length of the dry period.

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Section: Introductionmentioning

confidence: 99%

Importance of the Submerged Zone during Dry Periods to Nitrogen Removal in a Bioretention System

Qin

Wang

et al. 2020

Water

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“…We also observe an average increase in the concentrations of TC and E. coli, for configuration c. Stott et al (2017) noted less microbial retention in systems with saturated zones. On the other hand, Søberg et al (2019) found a reduction in the concentration of bacteria in the saturated zone; however, the increase in temperatures also increased the outflow concentrations. For this study, there is no conclusion due to the possibility of sample contamination.…”

Section: Water Quality Resultsmentioning

confidence: 85%

Evaluating low impact development practices potentials for increasing flood resilience and stormwater reuse through lab-controlled bioretention systems

Macedo

Oliveira

et al. 2021

Water Science and Technology

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Low Impact Development practices (LID) as alternative measures of urban drainage can be used within the approach of resources recycling and co-management. This study evaluates the potential contribution of a bioretention system to flood control, non-potable water demands (NPD) and resources co-management. Bioretention setups were tested experimentally under variable conditions to identify operational key-factors to multiple purposes. Additionally, the efficiencies obtained for laboratory scale were extrapolated for household and watershed scale, quantifying the indicators of water demand reduction (WDR), energy demand reduction (EDR) and carbon emission reduction (CER) for hybrid systems with LID. The laboratory results indicated that the use of a bioretention with a submerged zone can improve the quality of the water recovered for reuse, while maintaining the efficiency of runoff retention and peak flow attenuation. Comparing the bioretention effluent quality with the Brazilian standards for stormwater reuse, the parameters color, turbidity, E. coli and metals were above the limits, indicating the necessity of a better treatment to solids particles and disinfection. Expanding the analysis to watershed scale, the bioretention helped to reduce NPD demands up to 45%, leading to a reduction in energy demand and carbon emission from the centralized water supply system.

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“…Among them, the internal water storage area is a field relatively rarely studied at present, but setting the internal water storage area has been proven to significantly reduce the volume of runoff, effectively maintain the intensity of microbial activity, improve the denitrification reaction rate [86], and enhance the adsorption of harmful microorganisms in the system by enhancing the formation of biofilms, thus reducing the outflow concentration of harmful microorganisms [87]. System blockage is also an important problem to pay attention to.…”

Section: Operational Efficiency Prediction and Planning Of Bioretenti...mentioning

confidence: 99%

Research on Operation Efficiency Prediction and Optimization of Biological Retention System Based on GA-BP Neural Network Model

et al. 2023

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Bioretention systems are an important measure in sandy city construction to remove pollutants. This study collected all the operating data samples of bioretention ponds currently in operation in China and used the Mantel test and Redundancy Analysis (RDA) to optimize the main factors that affect the changes in pollutant-removal efficiency. Genetic Algorithms (GA) were used to optimize the Back Propagation (BP) neural network model, and a predictive index system was established to predict the efficiency of removing typical pollutants (ammonia nitrogen and nitrite nitrogen) by bioretention ponds. The operating efficiency of bioretention ponds was evaluated and predicted based on the GA-BP neural network model. The results indicated that the highest positive correlation with the operating efficiency of the bioretention system was X3 (rainfall duration), with a correlation coeffi-cient of 0.79, while the highest negative correlation was with X7 (percentage of strong percolating soil) and X12 (the proportion of mineral fillers), with correlation coefficients of −0.89. The overall regression coefficients of the GA-BP model for predicting the efficiency of removing typical pollu-tants (ammonia nitrogen and nitrite nitrogen) were 0.9397 and 0.9303, respectively, indicating high accuracy and representativeness. The overall regression index of the model is 0.9298, and the overall predicted removal rates of typical pollutants in the blank area are 78.72%, 70.31%, and 86.92%, re-spectively. The model can provide a basis and reference for the construction and planning of bio-retention ponds in areas lacking them.

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Reduction of Escherichia coli, Enterococcus faecalis and Pseudomonas aeruginosa in stormwater bioretention: Effect of drying, temperature and submerged zone

Cited by 11 publications

References 40 publications

Importance of the Submerged Zone during Dry Periods to Nitrogen Removal in a Bioretention System

Importance of the Submerged Zone during Dry Periods to Nitrogen Removal in a Bioretention System

Evaluating low impact development practices potentials for increasing flood resilience and stormwater reuse through lab-controlled bioretention systems

Research on Operation Efficiency Prediction and Optimization of Biological Retention System Based on GA-BP Neural Network Model

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