Determining Urban Storm Water BMP Effectiveness

Strecker, Eric; Quigley, Marcus; Urbonas, Ben; Jones, Jonathan E.; Clary, Jane

doi:10.1061/(asce)0733-9496(2001)127:3(144)

Cited by 208 publications

(86 citation statements)

References 3 publications

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“…Of particular interest, the "concentration gradient" variable may, at least partially, explain the mechanism associated with "irreducible concentrations" reported in previous studies (Schueler, 1996;Strecker et al, 2001). Significance of the "antecedent dry period" variable is consistent with a study which also predicted a positive correlation with flow rate using bench-scale studies with VF wetland cells (Farahbakhshazad and Morrison, 2003).…”

Section: Physical-process Modelsupporting

confidence: 74%

Variability in adsorptive phosphorus removal by structural stormwater best management practices

Rosenquist

Hession

Eick

et al. 2010

Ecological Engineering

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a b s t r a c tVarious best management practices (BMPs) utilizing sorption processes (SP) have demonstrated effectiveness for phosphorus (P) management in stormwater. However, the widespread use of these BMPs in urban areas has been limited by large land requirements and limited P removal capacity. Central to this study is the development of the urban wetland filter (UWF), a concept intended to overcome these limitations and provide a low-cost, easily implemented BMP that can meet urban P-management goals. Performance variation along with finite sorption capacity has limited the reliability of SP as a primary removal strategy. However, if variability were better understood and capacity made renewable, sorption of P to substrates could provide the option of a more rapid and (with less required retention time) more space-efficient sustainable removal strategy than biological uptake. The goal of this study was to identify and model major sources of variability in P removal by sorption, enabling better prediction and optimization of sorption performance and ultimately the development of a small-footprint stormwater BMP with efficient P removal ability. Experiments were conducted in bench-scale reactors with an iron-oxide sand substrate. Results included a physical-process model developed by considering the thermodynamic and kinetic properties of SP. Significant sources of variability included, by order of importance, magnitude of a solution/substrate concentration gradient, length of the "antecedent dry period" between loadings, and pH. Most importantly, results indicate the critical importance of a thermodynamic gradient between solution P and previously adsorbed P to achieve continued removal.

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Section: Physical-process Modelsupporting

confidence: 74%

Variability in adsorptive phosphorus removal by structural stormwater best management practices

Rosenquist

Hession

Eick

et al. 2010

Ecological Engineering

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“…( Figure 3a), but more plausibly the removal rates are instead explained by the differences observed in Campylobacter spp. inflow concentrations before and after the dry weather period (Figure 3b) [35]. Cryptosporidium oocyst removal rates decreased by 1.2 log after the dry period.…”

Section: Effect Of Dry Weather Periodsmentioning

confidence: 95%

Stormwater Biofilters as Barriers against Campylobacter jejuni, Cryptosporidium Oocysts and Adenoviruses; Results from a Laboratory Trial

Chandrasena

Deletić

Lintern

et al. 2017

Water

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Biofilters are a widely used stormwater treatment technology. However; other than some evidence regarding non-pathogenic indicator microorganisms; there are significant knowledge gaps in the capacity of stormwater biofilters to remove actual pathogens and how this removal is impacted by biofilter design elements and operational conditions. In this study; we explored the capacity of stormwater biofilters to remove three reference pathogens (Campylobacter spp.; adenovirus and Cryptosporidium oocysts) and compared these to commonly used indicator microorganisms (E. coli; FRNA coliphages and Clostridium perfringens). Two different biofilter designs; each having a submerged zone (SZ); were tested under extended dry weather periods (up to 4 weeks) and different event volumes (the equivalent of 1-2 pore volumes) in a laboratory trial. These systems were able to consistently reduce the concentrations of all tested reference pathogens (average log reduction in Campylobacter spp. = 0.7; adenovirus = 1.0 and Cryptosporidium oocysts = 1.7) and two of the indicators (average log reduction in E. coli = 1.2 and C. perfringens = 2.1). However; none of the tested indicators consistently mimicked the removal performance of their corresponding reference pathogens after extended dry weather periods and during larger simulated storm events. This indicates that the behaviour of these pathogens in stormwater biofilters are not adequately represented by their corresponding indicator microorganisms and that to optimise biofilter designs for pathogen removal it is critical to further study pathogen removal processes in these systems.

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“…These include: Event Mean Concentration (EM-Equation (1)), Average Concentration Removal Efficiency (Avg.CRE-Equation (2)), and Efficiency Ratio (E-Equation (3)) [17][18][19]. The value of CRE as an effective metric has been reduced as a reliable metric since minor variation (˘1 mg/L) observed in the analytical variability has significant influence on the metric at low influent concentrations, and so ER has been used as the primary metric in this study [19,20].…”

Section: Performance Metricsmentioning

confidence: 99%

Field Evaluation of the Nutrient Removal Performance of a Gross Pollutant Trap (GPT) in Australia

Nichols

Lucke

2016

Sustainability

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Field testing of a proprietary stormwater treatment device (GPT) was undertaken over a one year period at a commercial site located in Sippy Downs, Queensland. The focus of the study was primarily on evaluating the effectiveness of the GPT device in removing pollution in the form of nutrients (Total Suspended Solids, Total Nitrogen, Total Phosphorus) from stormwater runoff. Water quality analysis was performed on water samples taken from the inflow and outflow of the GPT during 15 natural rainfall events. A new testing protocol was developed to ensure a comprehensive investigation of the stormwater treatment performance of the GPT. Pollution treatment Efficiency Ratios (ER) calculated for the GPT were found to be 49.2% for TSS, 26.6% for TN and 40.6% for TP. Although the nutrient removal rates of the GPT observed in the study were below those specified by Queensland regulations, the results are considered notable for a stormwater treatment device that was not specifically designed to remove nutrients from stormwater.

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Determining Urban Storm Water BMP Effectiveness

Cited by 208 publications

References 3 publications

Variability in adsorptive phosphorus removal by structural stormwater best management practices

Variability in adsorptive phosphorus removal by structural stormwater best management practices

Stormwater Biofilters as Barriers against Campylobacter jejuni, Cryptosporidium Oocysts and Adenoviruses; Results from a Laboratory Trial

Field Evaluation of the Nutrient Removal Performance of a Gross Pollutant Trap (GPT) in Australia

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