BioRTC model enables exploration of real time control strategies for stormwater biofilters.

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

Photo-electrochemical oxidation flow system for stormwater herbicides removal: Operational conditions and energy consumption analysis.

Photoelectrochemical oxidation (PECO) is a promising advanced technology for treating micropollutants in stormwater. However, it is important to understand its operation prior to practical validation. In this study, we introduced a flow PECO system designed to evaluate its potential for full-scale applications in herbicides degradation, providing valuable insights for future large-scale implementations. The PECO flow reactor demonstrated the ability to treat a larger volume of stormwater (675 mL, approximately 10 times more than previous batch experiments) with effective removal rates of 92 % for diuron and 22 % for atrazine over 6 h of operation at 2 V. To address the large volume issue in stormwater treatment, a multiple module parallel application design is being considered to increase the treatment capacity of the PECO flow reactor. During the flow reactor operations, flow rate was found to have a notable impact on removal performance, particularly for diuron. At a flow rate of 610 mL min-1, approximately 90 % removal of diuron was achieved, while at 29 mL min-1, the removal efficiency decreased to 60 %. While light intensity had minimal effect on diuron degradation (all settings achieved over 90 % removal), it enhanced atrazine degradation from 9 % to 31 % with an increase in intensity from 63 mW cm-2 to 144 mW cm-2. Remarkably, the PECO flow system exhibited excellent removal performance (>90 % removal) for diuron even at extremely high initial pollutant concentrations (240 µg L-1), demonstrating its capacity to handle varying contaminant loads in stormwater. Energy consumption analysis revealed that flow rate as the primary factor influenced the specific energy consumption rate. Higher flow rate (e.g., 610 mL min-1) were preferable in flow reactor due to its well-balanced performance between removal and energy consumption. These findings confirm that the PECO flow system offers an efficient and promising approach for stormwater treatment applications.

Impact of electrochemically generated iron on the performance of an anaerobic wastewater treatment process.

Anaerobic treatment of domestic wastewater has the advantages of lower biomass yield, lower energy demand and higher energy recover over the conventional aerobic treatment process. However, the anaerobic process has the inherent issues of excessive phosphate and sulfide in effluent and superfluous H2S and CO2 in biogas. An electrochemical method allowing for in-situ generation of Fe2+ in the anode and hydroxide ion (OH-) and H2 in the cathode was proposed to overcome the challenges simultaneously. The effect of electrochemically generated iron (e­iron) on the performance of anaerobic wastewater treatment process was explored with four different dosages in this work. The results showed that compared to control, the experimental system displayed an increase of 13.4-28.4 % in COD removal efficiency, 12.0-21.3 % in CH4 production rate, 79.8-98.5 % in dissolved sulfide reduction, 26.0-96.0 % in phosphate removal efficiency, depending on the e­iron dosage between 40 and 200 mg Fe/L. Dosing of the e­iron significantly upgraded the quality of produced biogas, showing a much lower CO2 and H2S contents in biogas in experimental reactor than that in control reactor. The results thus demonstrated that e­iron can significantly improve the performance of anaerobic wastewater treatment process, bringing multiple benefits with the increase of its dosage regarding effluent and biogas quality.

Water Sensitive Urban Design (WSUD) Spatial Prioritisation through Global Sensitivity Analysis for Effective Urban Pluvial Flood Mitigation.

Water Sensitive Urban Design (WSUD) has attracted growing attention as a sustainable approach for mitigating pluvial flooding (also known as flash flooding), which is expected to increase in frequency and intensity under the impacts of climate change and urbanisation. However, spatial planning of WSUD is not an easy task, not only due to the complex urban environment, but also the fact that not all locations in the catchment are equally effective for flood mitigation. In this study, we developed a new WSUD spatial prioritisation framework that applies global sensitivity analysis (GSA) to identify priority subcatchments where WSUD implementation will be most effective for flood mitigation. For the first time, the complex impact of WSUD locations on catchment flood volume can be assessed, and the GSA in hydrological modelling is adopted for applications in WSUD spatial planning. The framework uses a spatial WSUD planning model, the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), to generate a grid-based spatial representation of catchment, and an urban drainage model, the U.S. EPA Storm Water Management Model (SWMM), to simulate catchment flooding. The effective imperviousness of all subcatchments was varied simultaneously in the GSA to mimic the effect of WSUD implementation and future developments. Priority subcatchments were identified based on their influence on catchment flooding computed through the GSA. The method was tested for an urbanised catchment in Sydney, Australia. We found that high priority subcatchments were clustering in the upstream and midstream of the main drainage network, with a few distributed close to the catchment outlets. Rainfall frequency, subcatchment characteristics, and pipe network configuration were found to be important factors determining the influence of changes in different subcatchments on catchment flooding. The effectiveness of the framework in identifying influential subcatchments was validated by comparing the effect of removing 6% of the Sydney catchment's effective impervious area under four WSUD spatial distribution scenarios. Our results showed that WSUD implementation in high priority subcatchments consistently achieved the largest flood volume reduction (3.5-31.3% for 1% AEP to 50% AEP storms), followed by medium priority subcatchments (3.1-21.3%) and catchment-wide implementation (2.9-22.1%) under most design storms. Overall, we have demonstrated that the proposed method can be useful for maximising WSUD flood mitigation potential through identifying and targeting the most effective locations.

Nitrification potential of daily-watered biofiltration designs for high ammonium wastewater treatment.

The vegetated biofiltration systems (VBS), also known as bioretentions or rain gardens, are well-established technology for treatment of urban stormwater and recently greywater, offering multiple benefits to urban environments. However, the impact of high ammonium strength wastewater (60 mg/L) on the nitrification process in these systems is not well understood. Hence, a laboratory-based column study was conducted to uncover dominant nitrification mechanisms, based on the learnings from similar onsite wastewater treatment systems. The experimental columns tested the effect of contact time (filter media depth, 150 mm, 300 mm and 700 mm), media oxygenation (active and passive) and alkalinity/pH (marble chips 5 % weight), as well as optimal operational conditions (inflow loading, concentrations, and dissolved oxygen (DO)). All nitrogen species (NH4+, NO3-, NO2-), chemical oxygen demand (COD) and physical parameters (DO, pH, electrical conductivity) were monitored across seven events over thirteen weeks. The results show that dosing with 30 and 60 mg/L of NH4+ resulted in 700 mm sand column depth to perform almost complete nitrification of NH4+ to NO3- (< 90 %), while 300 mm designs achieved partial nitrification of NH4+ to NO2-, likely due to limited contact time and inefficient nitrite oxidizing bacteria activity. Nitrification potential of all designs further supported that appropriate aerobic contact time is necessary for effective nitrification. Inflow concentration of NH4+ and DO did not significantly impact nitrification performance, while reducing daily volume loading reduced NO3- and NO2- leaching. Active and passive aeration and alkalinity buffering did not positively affect ammonium removal. While there is a potential to apply both nitrification-denitrification and anammox processes to future VBS design, further understanding of aeration and alkalinity on microbially driven nitrification processes is needed.

Electrochemical iron production to enhance anaerobic membrane treatment of wastewater.

Although iron salts such as iron(III) chloride (FeCl3) have widespread application in wastewater treatment, safety concerns limit their use, due to the corrosive nature of concentrated solutions. This study demonstrates that local, electrochemical generation of iron is a viable alternative to the use of iron salts. Three laboratory systems with anaerobic membrane processes were set up to treat real wastewater; two systems used the production of either in-situ or ex-situ electrochemical iron (as Fe2+ and Fe2+(Fe3+)2O4, respectively), while the other system served as a control. These systems were operated for over one year to assess the impact of electrochemically produced iron on system performance. The results showed that dosing of electrochemical iron significantly reduced sulfide concentration in effluent and hydrogen sulfide content in biogas, and mitigated organics-based membrane fouling, all of which are critical issues inherently related to sustainability of anaerobic wastewater treatment. The electrochemical iron strategy can generate multiple benefits for wastewater management including increased removal efficiencies for total and volatile suspended solids, chemical oxygen demand and phosphorus. The rate of methane production also increased with electrochemically produced iron. Economic analysis revealed the viability of electrochemical iron with total cost reduced by one quarter to a third compared with using FeCl3. These benefits indicate that electrochemical iron dosing can greatly enhance the overall operation and performance of anaerobic membrane processes, and this particularly facilitates wastewater management in a decentralized scenario.

Photo-electrochemical oxidation herbicides removal in stormwater: Degradation mechanism and pathway investigation.

Although advanced oxidation processes (AOPs) such as photoelectrochemical oxidation (PECO), electrochemical oxidation (ECO) and photocatalytic oxidation (PCO), have shown potential for wastewater treatment, their application in urban stormwater has rarely been studied. This paper explored their major degradation mechanisms and possible degradation pathways of herbicides for stormwater applications (with treatment difficulty compared with wastewater). PECO and ECO showed excellent removal performance for diuron (100 %) and moderate for atrazine (around 35 %) under a relatively low potential (2 V). Superoxide radical (·O2-) has been found to be the dominant reactive species. Besides, there is evidence to indicate that hydroxyl radical (·OH) and free chlorine (·Cl) also support the degradation reactions. Up to 11 possible intermediate products have been identified during both diuron and atrazine degradation processes under PECO operation. Based on the proposed possible degradation pathways, the intermediates presented during PECO are species with further oxidation. As evidenced by the undetected species of more oxidized intermediates for ECO and PCO, some further degradation steps are missing, which demonstrate their lower oxidation capacity leading to incomplete decomposition of stormwater herbicides. Thus, PECO has a great potential to be developed into a passive stormwater degradation system due to its strong oxidation potential.

Machine learning approaches for predicting the performance of stormwater biofilters in heavy metal removal and risk mitigation.

The increasing amount of data on biofilter treatment performance over the past decade has made it possible to use data-driven approaches to explore the relationships between biofilter performance and a range of input variables. The knowledge gap lies in lack of models to predict the biofilter performance considering both design and operational variables, especially for heavy metals. In this study, we tested three machine learning (ML) approaches, namely multilinear regression (MLR), artificial neural network (NN), and random forest (RF), to predict biofilter outflow concentrations of heavy metals (Cd, Cr, Cu, Fe, Ni, Pb and Zn) using a range of design and operational factors as input variables. The results show that RF performed relatively better than other two models, with median Nash-Sutcliffe Efficiency (NSE) values of 0.995, 0.317, 0.762, 0.636, 0.726, 0.896 and 0.656 for Cd, Cr, Cu, Fe, Ni, Pb and Zn, respectively during model training. However, all the models were less accurate during model validation, with the better performance found for Cd (average NSE=0.964), Zn (0.530) and Ni (0.393) and poorer performance observed for Cu (0.219), Pb (0.058), Fe (-0.054) and Cr (-0.062). Infiltration rate (IR) and inflow concentration (Cin) were sensitive to all pollutants' removal in biofilters. The ratio of system size to catchment size was also found to be important for Zn, Ni and Cd, while ponding depth was an important variable for Cd. Based on thousands of hypothetical design and operational scenarios (generated using raw data), the best ML models were used to predict the biofilter outflow concentrations and estimate the risk quotient (RQ) values with regards to reuse of treated stormwater for various purposes. Results suggest that biofilters were able to reduce health risks associated with heavy metals in stormwater and therefore produce reliable water fit for reuses such as irrigation, swimming, and toilet flushing. Modelling results showed that biofiltration did not meet the requirements for drinking when Cd contamination exists. Explorative analysis also demonstrated how the key operational and design variables can be optimised to further reduce the health risks that can be fit for drinking purposes (i.e., RQ value <1).

A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks.

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA's probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor's inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

Stormwater herbicides removal with a solar-driven advanced oxidation process: A feasibility investigation.

The solar driven advanced oxidation process (AOP) has the potential to be developed as a passive stormwater post-treatment method. Despite its widespread studies in wastewater treatment, the applicability of the process for micropollutant removal in stormwater (which has very different chemical properties from wastewater) is still unknown. This paper investigated the feasibility of three different AOP processes for the degradation of two herbicides (diuron and atrazine) in pre-treated stormwater: (i) photoelectrochemical oxidation (PECO), (ii) electrochemical oxidation (ECO), and (iii) photocatalytic oxidation (PCO). The durability of different anode materials, the effects of catalyst loading, and solar photo- and thermal impacts under different applied voltages were studied. Boron-doped diamond (BDD) was found to be the most durable anode material compared to carbon fiber and titanium foil for long-term operation. Due to the very low electroconductivity of stormwater, a high voltage was required, causing severe oxidation of the carbon fiber material. PECO achieved the best degradation results compared to ECO and PCO, with over 90% degradation of both herbicides in 2 h under 5 V, following a first-order decay process (with a half-life value of 0.40 h for diuron and 0.58 h for atrazine). The voltage increase had a positive impact on the oxidation processes, with 5 V found to be the optimal applied voltage, while catalyst loading had a negligible effect. Interestingly, the solar thermal effect plays a dominant role in enhancing the performance of the PECO process, which indicates the potential of integrating a photovoltaic chamber with a PECO system to harness both the light and heat of solar energy for stormwater treatment.

The impact of stormwater biofilter design and operational variables on nutrient removal - a statistical modelling approach.

Biofiltration systems can help mitigate the impact of urban runoff as they can treat, retain and attenuate stormwater. It is important to select the optimal design characteristics of biofilters (e.g., vegetation, filter media depth) to ensure high treatment performance. Operational conditions (e.g., infiltration rate) can also lead to significant changes in biofilter treatment performance over time. The impact of specific operational conditions on water quality treatment performance of stormwater biofilters is still not well understood. Furthermore, despite the importance of design characteristics and operational conditions on biofilter treatment performance, there is a lack of models that can be used to determine the optimal design and operation. In this paper, we developed a series of statistical models to predict the Total Phosphorus (TP) and Total Nitrogen (TN) removal performance of stormwater biofilters using various numbers of design characteristics and operational conditions. These statistical models were tested using data collected from four extensive laboratory-scale biofilter column studies. It was found that all models performed relatively well with a Nash-Sutcliffe Efficiency (NSE) of 0.42 - 0.61 for TP and 0.37 - 0.63 for TN. The most important design characteristics were filter media type and depth for TP treatment, and vegetation type and submerged zone depth for TN treatment. In addition, infiltration rate and inflow concentrations were the operational conditions that greatly influence outflow TP and TN concentrations from stormwater biofilters. As such, these variables need to be carefully considered when designing and operating stormwater biofilters. Sensitivity analysis results indicate that the model was quite sensitive to all regression coefficients and intercepts. Additional modelling exercises show that the model could be further simplified by reducing the number of cross-correlated parameters. These models can be used by practitioners for not just optimising the design, but also operating biofilters using real-time monitoring and control to achieve optimum performance.

The effect of intermittent drying and wetting stormwater cycles on the nutrient removal performances of two vegetated biofiltration designs.

Vegetated biofiltration systems (biofilters) are now a well-established technology for treatment of urban stormwater, typically showing high nutrient uptake. However, the impact of high temporal variability of rainfall events (further exacerbated by climate change) on nitrogen and phosphorus removal processes, within different biofiltration designs, is still unknown. Hence, a laboratory-based study was conducted to uncover mechanisms behind nutrient removal in biofilters across different drying and wetting regimes. Two sets of experimental columns were based on (1) the standard biofiltration design (unsaturated zone only), and (2) combination of unsaturated and saturated (submerged) zone (SZ) with additional carbon source. Columns were watered with synthetic stormwater according to three drying and wetting schemes, exploring 1, 2, 3, 4 and 7-week drying. Hydraulic performance, soil moisture and pollutant removal were monitored. The results show that hydraulic conductivity of SZ design experiences less change over time compared to standard design, due to slower media drying, crack formation and lower plant die-off. Varied drying lengths challenged both designs differently, with 2-week drying resulting in significant drop of performance across most pollutants in standard design (except ammonia), while SZ design was able to retain high performance for up to four weeks of drying, sustaining microbial and plant uptake. Increased oxygenation of SZ columns during short-term drying was beneficial for ammonia and phosphorus removal. While SZ design showed better performance and quicker recovery for nitrogen removal, in regions with inter-rain event shorter than two weeks, the standard design (no saturated zone, no carbon source) can achieve similar if not better results.

Effective treatment of greywater via green wall biofiltration and electrochemical disinfection.

Low energy and cost solutions are needed to combat raising water needs in urbanised areas and produce high quality recycled water. In this study, we investigated key processes that drive a unique greywater treatment train consisting of a passive green wall biofiltration system followed by disinfection using a Boron-doped diamond (BDD) electrode with a solid polymer electrolyte (SPE). In both systems, the treatment was performed without any additional chemicals and pollutants of concern were monitored for process evaluation. The green wall system removed over 90% of turbidity, apparent colour, chemical oxygen demand, total organic carbon, and biological oxygen demand, and 1 log of E. coli and total coliforms, mostly through biological processes. The green wall effluent met several proposed greywater reuse guidelines, except for E. coli and total coliform treatment (below 10 MPN/100 mL). Further disinfection of treated greywater (contained 28 mg/L Cl¯ and electrical conductivity (EC) of 181.3 µS/cm) by electrolysis at current density 25 mA/cm2 inactivated over 3.5 logs of both E. coli and total coliforms, in 10 - 15 min of electrolysis, resulting in recycled water with less than 2 MPN/100 mL. A synergistic effect between electrochemically-generated free chlorines and reactive oxygen species contributed to the inactivation process. Although the treated water contained diluted chloride and had low EC, estimated energy consumption was just 0.63 - 0.83 kWh/m3. This is the first study to show the effectiveness of a low energy and a low cost greywater treatment train that combines green urban infrastructure with BDD electrochemical treatment process with SPE, offering a reliable and an environmentally-friendly method for greywater reuse.

A spatial planning-support system for generating decentralised urban stormwater management schemes.

Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices.

An in situ assembled WO3-TiO2 vertical heterojunction for enhanced Z-scheme photocatalytic activity.

The face-to-face contact of a vertical heterojunction is beneficial to charge interaction in photocatalysis. However, constructing a vertical heterojunction with uncompromised redox ability still remains a challenge. Herein, we report the successful synthesis of a WO3-TiO2 vertical heterojunction via establishing an internal electric field across the interface. Experimental investigation and computational simulations reveal that strong electric coupling occurs at the WO3-TiO2 interface forming an internal electric field. The internal electric field induces a Z-scheme charge-carrier transfer through the heterojunction under light irradiation, which leads to effective charge separation and maintains high reaction potentials of charge-carriers. The improved photocatalytic activity of the WO3-TiO2 heterojunction is proved by enhanced generation of reactive oxygen species and accelerated Escherichia coli (E. coli) disinfection. This study provides new insights into understanding and designing Z-scheme heterogeneous photocatalysts.

Green wall height and design optimisation for effective greywater pollution treatment and reuse.

Green walls that effectively treat greywater have the potential to become a part of the solution for the issues of water scarcity and pollution control in our cities. To develop reliable and efficient designs of such systems, the following two research questions were addressed: what would be the optimal design of a green wall for greywater treatment, and how tall should the system be to assure adequate treatment. This paper reports on (i) a long-term pollutant removal comparison study of two typical green wall configurations: pot and block designs, and (ii) a short-term profile study exploring pollutant retention at different heights of a three-level green wall, across different plant species. Removal of suspended solids (TSS), nitrogen (TN), phosphorus (TP), chemical oxygen demand (COD) and Escherichia coli was tested, as well as various physical parameters. Pot and block designs were found to exhibit similar pollutant removal performance for standard and high inflow concentrations, while the block design was more resistant to drying. However, due to its multiple practical advantages, pot designs are favoured. The greatest removal was achieved within the top green wall level for all studied pollutants, while subsequent levels facilitated further removal of TSS, COD, and TN. Interestingly, colour, pH, and EC increased after each green wall level, which must be taken into account to determine the maximum height of these systems. The optimal size of the system was found to be dependent on plant species choice. The results were used to create practical recommendations for the effective design of greywater treatment green walls.

Seasonal operation of dual-mode biofilters: The influence of plant species on stormwater and greywater treatment.

The use of stormwater biofilters (also known as bioretention systems and raingardens), in tropical and semi-arid areas is hindered by seasonal rainfall patterns which cause extended dry periods. These periods can result in plant die-off, long-term damage to system health and leaching of pollutants when stormwater inflows resume. Using an additional polluted water source during dry periods could minimise system stress and eliminate the need to irrigate biofilters with potable water during dry spells. As such, the presented laboratory study tested the seasonal operation of biofilters, by switching from stormwater treatment in wet months to greywater treatment in dry months. Forty-five single planted biofilter columns, incorporating sedges, grasses, understory ornamentals and vines, were subjected to four months of stormwater inflows, followed by three months of greywater inflows. We also investigated the impact of including a carbon source in the saturated zone on treatment performance. The results showed plant species selection to be critical for nitrogen and phosphorus removal, with consistently effective species such as Carex appressa and Canna x generalis able to maintain low outflow concentrations (e.g. total nitrogen of 0.2-0.3 mg/L and 0.3-0.6 mg/L, respectively) across both water sources. Low outflow phosphorus concentrations were associated with plant species that had high filterable reactive phosphorus removal across both water sources. Similarly, higher removal of ammonia and oxidised nitrogen was associated with lower overall nitrogen concentrations. In contrast, high removal of total suspended sediment (>94%), biochemical oxygen demand (>98%) and some heavy metals (e.g. lead >98% and copper >93%) was reported across all designs. The results suggest that with the careful selection of plant species, biofilters can be operated seasonally as a feasible and practical solution to maintaining system health during extended dry periods.

Quantifying the benefits of stormwater harvesting for pollution mitigation.

Stormwater harvesting (SWH) provides multiple benefits to urban water management. Other than providing water for human use, it also reduces the volume of polluted stormwater discharge to the environment. There are currently no methods available to quantify the additional environmental benefits, which could encourage greater uptake of the practice. This paper investigates a number of factors (climate and catchment characteristics, pollutant reduction targets, etc.) that could impact upon the benefits of SWH for pollution reduction through sensitivity analyses. A method was developed and tested for quantification of the pollution mitigation benefits by SWH under different scenarios. A novel indicator, Impervious Area Offset (IAO), was proposed to reflect the additional impervious area that can be left untreated to achieve the equivalent pollution load reduction targets due to the introduction of SWH. Results indicate significant correlations (p < 0.01) between IAO values and extraction rate (proportion of total annual runoff removed due to the harvesting system and water use substitution), system type, and pollutant reduction targets. The proposed linear empirical relationships between IAO values and extraction rate for different types of system configurations and pollution reduction targets were well represented by observed linear regression (average R2 = 0.98 for all tested scenarios). Empirical relationships were validated successfully against different scenarios, with differences between predicted IAO and baseline IAO values being only ±4.5% for the majority of the validation scenarios. Using this simple and reliable method to rapidly quantify SWH benefits can further add to the growing business case of adopting SWH practices.

Validation and uncertainty analysis of a stormwater biofilter treatment model for faecal microorganisms.

Stormwater biofilters, also known as rain gardens or bioretention systems, are effective stormwater treatment systems. This paper presents the validation, sensitivity and uncertainty analyses of a model for microbial removal in stormwater biofilters. The model, previously developed based on a rather limited laboratory study, was fully validated using the data collected in extensive laboratory experiments and field tests. The lab-scale and field-scale systems used for validation were of various designs (e.g., system size, plant type, media type), and have been operated under a wide range of operational conditions (e.g., length of antecedent dry period, and the inflow volume and concentration). For each tested biofilter design, the predicted E. coli concentrations in biofilters' outflow showed relatively good agreement with the measured ones: e.g., Nash-Sutcliffe Efficiency (Ec) ranged from 0.50 to 0.60 for the laboratory tests, and Ec = 0.55 for the field system. The results from sensitivity analysis confirmed the significance of adsorption and desorption processes, and also revealed the impact of temperature on microbial die-off (which was not fully represented in the model development stage). Finally, parameter transferability from one system to another with similar design was examined, achieving generally promising Ec values (0.04-0.56 with the best-fit parameter set for the other system; maximum value: 0.46-0.63) and acceptable uncertainties (intersection between prediction uncertainty band and observation: 50%-97%). Most importantly, the prediction of E. coli outflow concentrations from the field system was reasonably good when laboratory-determined parameter values were adopted: with the best-fit parameter set for the lab-scale system, Ec = 0.39; maximum Ec = 0.55; intersection between prediction and observation = 83%. These results suggested that the very rare biofilter model for microbial removal could provide reliable prediction for large scale field systems, by simply calibrating parameters with limited laboratory-scale experiments.

Salmonella from a Microtidal Estuary Are Capable of Invading Human Intestinal Cell Lines.

Faecal contamination poses health risks for the recreational users of urban estuaries. However, our understanding of the potential pathogenicity of faecal microbes in these environments is limited. To this end, a study was conducted to understand the spatial and seasonal distribution of Salmonella in water and sediments of the Yarra River estuary, Melbourne, Australia. Among 210 samples in total, culturable Salmonella were recovered from 27%, 17%, and 19% of water, bank, and bed sediment samples, respectively. The combined detection increased from 15% in winter to 32% in summer (p < 0.05) indicating seasonal variation as potential part of public health risk assessments. Further, pathogenic potential of the Salmonella isolates was characterised via the quantification of attachment and invasion capacity using human epithelial colorectal cell line Caco-2 on a subset of isolates (n = 62). While all of these isolates could attach and invade Caco-2 cells, 52% and 13% of these showed greater attachment and invasiveness, respectively, than the corresponding mean values for S. Typhimurium ATCC14028 control. Isolates from winter were on average more invasive (seven out of eight isolates with the highest invasiveness recovered from the colder sampling period) than the isolates from summer, and Salmonella collected during summer showed lower invasion (p < 0.05) compared with the control. Similar low invasion compared with the same control was observed for isolates recovered from bank sediment (p < 0.05). While the higher prevalence in summer may imply higher risks during these peak recreational periods, it is essential that this information is used in combination with quantitative microbial risk assessments to fully understand the health risks posed by Salmonella in microtidal estuaries.