A systematic approach for the comparative assessment of stormwater pollutant removal potentials

Scholes, Lian N. L.; Revitt, D. Mike; Ellis, John B.

doi:10.1016/j.jenvman.2007.03.003

Cited by 88 publications

(66 citation statements)

References 7 publications

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“…The Australian MUSIC model (Wong et al, 2001) was an early methodology which attempted to utilise operating processes as a basis for selecting SUDS according to their pollutant mitigation performance. This unit operating process (UOP) approach has since been fully developed to provide a full consideration of process mechanisms as a basis for identifying appropriate SUDS for treatment and control of different pollutant types (Scholes et al, 2008). The fundamental UOPs considered in the modelling approach include adsorption, settling, degradation, filtration, plant uptake, volatilisation and photolysis mechanisms.…”

Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

“…The fundamental UOPs considered in the modelling approach include adsorption, settling, degradation, filtration, plant uptake, volatilisation and photolysis mechanisms. The adopted UOP approach is similar to that followed in the US Environmental Protection Agency (EPA) SUSTAIN model (Shoemaker et al, 2009), and generates ranked preference listings of SUDS in terms of their relative performance in removing different pollutants (Scholes et al, 2008). In their paper, Scholes et al, (2008) successfully compare the theoretically derived SUDS orders of preference with field data for TSS and subject the approach to a sensitivity analysis, reporting that the results of both exercises provide an initial validation of the procedure.…”

Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

“…The adopted UOP approach is similar to that followed in the US Environmental Protection Agency (EPA) SUSTAIN model (Shoemaker et al, 2009), and generates ranked preference listings of SUDS in terms of their relative performance in removing different pollutants (Scholes et al, 2008). In their paper, Scholes et al, (2008) successfully compare the theoretically derived SUDS orders of preference with field data for TSS and subject the approach to a sensitivity analysis, reporting that the results of both exercises provide an initial validation of the procedure. Figure 2 illustrates the generated order of preference (with rank 1 being best), based on consideration of the physico-biochemical processes involved, by which different types of SUDS are able to remove total suspended solids and organic pollutants (i.e.…”

Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

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An impact assessment methodology for urban surface runoff quality following best practice treatment

Ellis

Revitt

Lundy

2012

Science of The Total Environment

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Copyright and moral rights to this thesis/research project are retained by the author and/or other copyright owners. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non-commercial, research or study without prior permission and without charge. Any use of the thesis/research project for private study or research must be properly acknowledged with reference to the work's full bibliographic details.This thesis/research project may not be reproduced in any format or medium, or extensive quotations taken from it, or its content changed in any way, without first obtaining permission in writing from the copyright holder(s).If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Middlesex University via the following email address:eprints@mdx.ac.ukThe item will be removed from the repository while any claim is being investigated. Abstract The paper develops an easy to apply desk-based semi-quantitative approach for the assessment of residual receiving water quality risks associated with urban surface runoff following its conveyance through best practice sustainable drainage systems (SUDS). The innovative procedure utilises an integrated geographical information system (GIS)-based pollution index approach based on surface area impermeability, runoff concentrations/loadings and individual SUDS treatment performance potential to evaluate the level of risk mitigation achievable by SUDS drainage infrastructure. The residual impact is assessed through comparison of the determined pollution index with regulatory receiving water quality standards and objectives. The methodology provides an original theoretically based procedure which complements the current acute risk assessment approaches being widely applied within pluvial flood risk management.

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Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

Section: Suds Pollution Mitigation Index (Pmi) Assessmentmentioning

confidence: 99%

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An impact assessment methodology for urban surface runoff quality following best practice treatment

Ellis

Revitt

Lundy

2012

Science of The Total Environment

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“…Common mitigation measures such as detention basins focus on peak discharge reduction and present limited success in runoff volume reduction or water quality improvement [2,21]. Moreover, if the basin is located inappropriately, it may aggravate flooding [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Green Infrastructure Design for Stormwater Runoff and Water Quality: Empirical Evidence from Large Watershed-Scale Community Developments

Yang

2013

Water

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Green infrastructure (GI) design is advocated as a new paradigm for stormwater management, whereas current knowledge of GI design is mostly based on isolated design strategies used at small-scale sites. This study presents empirical findings from two watershed-scale community projects (89.4 km 2 and 55.7 km 2 ) in suburban Houston, Texas. The GI development integrates a suite of on-site, infiltration-based stormwater management designs, and an adjacent community development follows conventional drainage design. Parcel data were used to estimate the site impervious cover area. Observed streamflow and water quality data (i.e., NO 3 -N, NH 3 -N, and TP) were correlated with the site imperviousness. Results show that, as of 2009, the impervious cover percentage in the GI site (32.3%) is more than twice that of the conventional site (13.7%). However, the GI site's precipitation-streamflow ratio maintains a steady, low range, whereas this ratio fluctuates substantially in the conventional site, suggesting a "flashy" stream condition. Furthermore, in the conventional site, annual nutrient loadings are significantly correlated with its impervious cover percentage (p < 0.01), whereas in the GI site there is little correlation. The study concludes that integrated GI design can be effective in stormwater runoff reduction and water quality enhancement at watershed-scale community development.

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“…However when dealing with MP, this assessment is affected by a general lack of information regarding the performance of stormwater BMPs (examples provided in DiBlasi et al, 2009;Hatt et a., 2009). Scholes et al (2008) and Revitt et al (2008) proposed a method to assess the relative treatment efficiency of a specific BMP based on the inherent properties of a substance, which are usually among the sparse data available for several MP. This approach provides qualitative results as to which BMP is the most appropriate to remove a specific substance, although the potential removal efficiency is not quantified.…”

Section: Introductionmentioning

confidence: 99%

Modelling the fate of organic micropollutants in stormwater ponds

Vezzaro

Eriksson

Ledin

et al. 2011

Science of The Total Environment

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Urban water managers need to estimate the potential removal of organic micropollutants (MP) in stormwater treatment systems to support MP pollution control strategies. This study documents how the potential removal of organic MP in stormwater treatment systems can be quantified by using multimedia models. The fate of four different MP in a stormwater retention pond was simulated by applying two steady-state multimedia fate models (EPI Suite and SimpleBox) commonly applied in chemical risk assessment and a dynamic multimedia fate model (Stormwater Treatment Unit Model for Micro Pollutants -STUMP). The four simulated organic stormwater MP (iodopropynyl butylcarbamate -IPBC, benzene, glyphosate and pyrene) were selected according to their different urban sources and environmental fate. This ensures that the results can be extended to other relevant stormwater pollutants. All three models use substance inherent properties to calculate MP fate but differ in their ability to represent the small physical scale and high temporal variability of stormwater treatment systems. Therefore the three models generate different results. A Global Sensitivity Analysis (GSA) highlighted that settling/resuspension of particulate matter was the most sensitive process for the dynamic model. The uncertainty of the estimated MP fluxes can be reduced by calibrating the dynamic model against total suspended solids data. This reduction in uncertainty was more significant for the substances with strong tendency to sorb, i.e. glyphosate and pyrene and less significant for substances with a smaller tendency to sorb, i.e. IPBC and benzene. The results provide support to the elaboration of MP pollution control strategies by limiting the need for extensive and complex monitoring campaigns targeting the wide range of specific organic MP found in stormwater runoff.Please cite the published version of this article as: . Modelling the fate of organic micropollutants in stormwater ponds.

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A systematic approach for the comparative assessment of stormwater pollutant removal potentials

Cited by 88 publications

References 7 publications

An impact assessment methodology for urban surface runoff quality following best practice treatment

An impact assessment methodology for urban surface runoff quality following best practice treatment

Green Infrastructure Design for Stormwater Runoff and Water Quality: Empirical Evidence from Large Watershed-Scale Community Developments

Modelling the fate of organic micropollutants in stormwater ponds

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