ORCID Profile
0000-0003-0956-2977
Current Organisation
University of New South Wales
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Water Resources Engineering | Civil Engineering | Water Quality Engineering | Environmental Technologies |
Urban and Industrial Water Management | Urban Water Evaluation (incl. Water Quality) | Water and Waste Services not elsewhere classified | Water Services and Utilities
Publisher: Elsevier BV
Date: 07-2021
Publisher: Royal Society of Chemistry (RSC)
Date: 2023
DOI: 10.1039/D3EW00347G
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 10-2018
DOI: 10.1016/J.WATRES.2018.05.038
Abstract: Porous pavements are commonly used stormwater management systems. However, the understanding of their long-term capacity to retain heavy metals is limited. This study aims to investigate the long-term removal of heavy metals in three different porous pavements - Porous Asphalt (PA), Hydrapave (HP) and Permapave (PP) over accelerated laboratory experiments representing 26 years with varying hydrological conditions (drying/wetting periods and flow rates). A treatment model that simulates adsorption and desorption processes was developed for the first time to predict the long-term heavy metal removal by porous pavements. Unsurprisingly, all tested porous pavements performed better in removing metals that tend to attach to solid particles (e.g. Pb, Al, Fe) than more soluble ones (e.g. Cu, Zn, and Mn). There was a general increase of heavy metal concentrations at the outlet of the pavements over time as a result of a decrease in adsorption capacity of the systems, especially after the occurrence of clogging the soluble heavy metals removal decreased with a reduction in flow rates which was speculated to be due to more time being available for desorption of metals and breakdown of accumulated sediments. The proposed model simulated the trend, fluctuations and peaks of heavy metal concentrations reasonably well, achieving the Nash-Sutcliffe coefficient (NSE) values of 0.53-0.68 during model calibration. The model was most promising in predicting Al and Cu release from porous pavements (50%-91% of the observed data within the 90% uncertainty bands, NSE = 0.44-0.74), followed by Fe and Pb (27-77% observations within the bands, NSE = 0.20-0.69). Further improvements of the model are needed for it to be applicable for Zn and Mn.
Publisher: Elsevier BV
Date: 06-2019
DOI: 10.1016/J.COPBIO.2019.04.005
Abstract: Biotreatment technologies offer many advantages for passive stormwater treatment before harvesting, but performance can be variable and sensitive to system design, construction, operation and maintenance. While there is substantial research underpinning pollutant removal, hydraulic function, internal processes and optimal design, specific focus upon stormwater harvesting is relatively limited. Recent advances in system design include testing media amendments for targeted pollutant removal, enhanced pathogen removal using antimicrobial plants, and broadening technology application. However, the production of reliable fit-for-purpose water requires the development of robust validation methodologies to meet public safety expectations. While foundation studies exist, more needs to be done to extend the validation framework, monitor and control system performance and operation in real-time, and apply standards and regulatory checks.
Publisher: Springer International Publishing
Date: 09-2019
Publisher: Springer International Publishing
Date: 09-2018
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.WATRES.2017.10.001
Abstract: The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective s ling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted s les, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different s ling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective s ling strategies. Results indicate that the random s ling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed s ling strategies were better for estimating the SMC of E. coli. The differences in taking one, two or three random s les were small (up to 20% for TSS, and 10% for TN and E. coli), indicating that there is little benefit in investing in collection of more than one s le per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R
Publisher: Elsevier BV
Date: 02-2016
DOI: 10.1016/J.WATRES.2015.11.046
Abstract: Biofiltration systems, also known as bioretentions or rain-gardens, are widely used for treatment of stormwater. In order to design them well, it is important to improve models that can predict their performance. This paper presents a rare model that can simulate removal of a wide range of micro-pollutants from stormwater by biofilters. The model is based on (1) a bucket approach for water flow simulation, and (2) advection/dispersion transport equations for pollutant transport and fate. The latter includes chemical non-equilibrium two-site model of sorption, first-order decay, and volatilization, thus is a compromise between the limited availability of data (on stormwater micro-pollutants) and the required complexity to accurately describe the nature of the phenomenon. The model was calibrated and independently validated on two field data series collected for different organic micro-pollutants at two biofilters of different design. This included data on triazines (atrazine, prometryn, and simazine), glyphosate, and chloroform during six simulated stormwater events. The data included variable and challenging biofilter operational conditions e.g. variable inflow volumes, dry and wet period dynamics, and inflow pollutant concentrations. The model was able to simulate water flow well, with slight discrepancies being observed only during long dry periods when, presumably, soil cracking occurred. In general, the agreement between simulated and measured pollutographs was good. As with flows, the long dry periods posed a problem for water quality simulation (e.g. simazine and prometryn were difficult to model in low inflow events that followed prolonged dry periods). However, it was encouraging that pollutant transport and fate parameters estimated by the model calibration were in agreement with available literature data. This suggests that the model could probably be adopted for assessment of biofilter performance of other stormwater micro-pollutants (PAHs, phenols, phthalates, etc.). The model, therefore, could be applied in practice for sizing of biofilter systems and their validation monitoring, when used for stormwater harvesting.
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.WATRES.2019.115395
Abstract: 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 R
Publisher: Elsevier BV
Date: 05-2017
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.WATRES.2022.118774
Abstract: Green walls can provide an aesthetic approach to treat domestic greywater in urban landscapes. However, the widespread adoption of green walls for greywater treatment depends on its performance to remove the emerging contaminants from greywater such as xenobiotic organic compounds (XOCs). In this study, the performance of five lightweight green wall media types (zeolite, perlite, date seeds, coffee grinds, and coco coir) was evaluated for the removal of six XOCs representing a range of hydrophilic to hydrophobic organic micropollutants in domestic greywater (acetaminophen, diethyltoluamide, bisphenol A, oxybenzone, triclosan, nonylphenol). The adsorption affinity of targeted XOCs on different green wall media types, the role of contact time on XOCs removal, and the impact of background pollutants in greywater matrix on the adsorption of XOCs were analysed. Results indicate that removal of XOCs was higher using carbonaceous waste materials (date seeds, coffee grinds, and coco coir) as compared to natural minerals (zeolite and perlite). Moreover, the adsorption of XOCs increased with the increase in pollutant hydrophobicity. All XOCs showed highest removal using coco coir with fast adsorption kinetics, achieving 90% of the removal in 30 min. The only exception was acetaminophen that showed best removal using zeolite but exhibited slow adsorption kinetics with 90% of the removal attained in 24 h. The initial adsorption kinetics (<30 min) of XOCs in greywater were adversely affected by the presence of background pollutants, indicating the need of higher residence time of greywater in green wall system for better removal of XOCs. Based on the findings of this batch study, it is recommended to design a green wall system with more than 30 min of greywater residence time using a mixture of coco coir and zeolite for effective removal of XOCs from domestic greywater.
Publisher: Elsevier BV
Date: 03-2018
Publisher: Elsevier BV
Date: 05-2023
Publisher: Royal Society of Chemistry (RSC)
Date: 2020
DOI: 10.1039/C9EW00926D
Abstract: A model was developed to simulate the clogging of a field-scale stormwater harvesting system with high flow filters over 2.5-year.
Publisher: Elsevier BV
Date: 09-2015
DOI: 10.1016/J.WATRES.2015.05.043
Abstract: Real time monitoring of suitable surrogate parameters are critical to the validation of any water treatment processes, and is of particularly high importance for validation of natural stormwater treatment systems. In this study, potential surrogates for herbicide removal in stormwater biofilters (also known as stormwater bio-retention or rain-gardens) were assessed using field challenge tests and matched laboratory column experiments. Differential UV absorbance at 254mn (ΔUVA254), total phosphorus (ΔTP), dissolved phosphorus (ΔDP), total nitrogen (ΔTN), ammonia (ΔNH3), nitrate and nitrite (ΔNO3+NO2), dissolved organic carbon (ΔDOC) and total suspended solids (ΔTSS) were compared with glyphosate, atrazine, simazine and prometryn removal rates. The influence of different challenge conditions on the performance of each surrogate was studied. Differential TP was significantly and linearly related to glyphosate reduction (R(2) = 0.75-0.98, P < 0.01), while ΔTP and ΔUVA254 were linearly correlated (R(2) = 0.44-0.84, P < 0.05) to the reduction of triazines (atrazine, simazine and prometryn) in both field and laboratory tests. The performance of ΔTP and ΔUVA254 as surrogates for herbicides were reliable under normal and challenge dry conditions, but weaker correlations were observed under challenge wet conditions. Of those tested, ΔTP is the most promising surrogate for glyphosate removal and ΔUVA254 is a suitable surrogate for triazines removal in stormwater biofilters.
Publisher: Wiley
Date: 12-2021
DOI: 10.1002/HYP.14423
Abstract: For effective water quality management and policy development, spatial variability in the mean concentrations and dynamics of riverine water quality needs to be understood. Using water chemistry (calcium, electrical conductivity, nitrate‐nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus and total suspended solids) data for up to 578 locations across the Australian continent, we assessed the impact of climate zones (arid, Mediterranean, temperate, subtropical, tropical) on (i) inter‐annual mean concentration and (ii) water chemistry dynamics as represented by constituent export regimes (ratio of the coefficients of variation of concentration and discharge) and export patterns (slope of the concentration‐discharge relationship). We found that inter‐annual mean concentrations vary significantly by climate zones and that spatial variability in water chemistry generally exceeds temporal variability. However, export regimes and patterns are generally consistent across climate zones. This suggests that intrinsic properties of in idual constituents rather than catchment properties determine export regimes and patterns. The spatially consistent water chemistry dynamics highlights the potential to predict riverine water quality across the Australian continent, which can support national riverine water quality management and policy development.
Publisher: MDPI AG
Date: 20-12-2021
DOI: 10.3390/SU132414057
Abstract: Ecosystem services are essential for cities and are key factors in achieving many of the Sustainable Development Goals (SDGs). Such services are best delivered through green infrastructure, which works in resourceful, multifunctional, synergistic, and environmentally sensitive ways to deliver ecosystem services and provide alternative cleaner pathways for the delivery of multiple urban services. It is unclear if current research supports the necessary linkages between ecosystem services, cities, and green infrastructure in order to achieve the SDGs. To answer this question, we conducted a systematic review analysing 3392 studies on the SDGs from the WoS database. The contents of 66 of those with relevance to ecosystem services and urban research were reviewed in depth. We applied network-analytic methods to map the relationships of different knowledge clusters of SDGs research (1) across time, (2) across disciplines, and (3) in relation to ecosystem services and cities. The results of our analysis show that research on the SDGs have developed stronger networks from 2010–2018, but this research has not been sustained. Further, whilst research on cities now occupies a central place in the SDGs literature, research on ecosystem services only shows tentative links to both green-infrastructure research and SDGs research. Such literature on urban green infrastructure remains peripheral to the central challenge of sustainable urban transitions. We conclude that when it comes to the SDGs, research articles typically consider urban services independently of green infrastructure. Further, it suggests that green infrastructure is not generally considered as a sustainable alternative to conventional urban infrastructures. To address this serious shortcoming, we recommend transdisciplinary approaches to link urban ecosystem and urban green infrastructure research to the 2030 global sustainability agenda.
Publisher: Elsevier BV
Date: 07-2019
DOI: 10.1016/J.JENVMAN.2019.04.009
Abstract: Pollution build-up and wash-off processes are often included in urban stormwater quality models. However, these models are often unreliable and have poor performance at large scales and in complicated catchments. This study tried to improve stormwater quality models by adopting the genetic programming (GP) approach to generate new build-up algorithms for three different pollutants (total suspend solids - TSS, total phosphorus - TP and total nitrogen - TN). This was followed by testing of the new models (also traditional build-up and wash-off models as benchmark) using data collected from different catchments in Australia and the USA. The GP approach informed new sets of build-up algorithms with the inclusion of not just the typical antecedent dry weather period (ADWP), but also other less 'traditional' variables - previous rainfall depth for TSS and maximum air temperatures for TP and TN simulation. The traditional models had relatively poor performance (Nash-Sutcliffe coefficient, E < 0.0), except for TP at Gilby Road (GR) (E = 0.21 in calibration and 0.43 in validation). Improved performance was observed using the models with new build-up algorithms informed by GP. Taking TP at GR for ex le, the best performing model had E of 0.46 in calibration and 0.54 in validation. The best performing models for TSS, TP, and TN are often different, suggesting that specific models shall be used for different pollutants. Insights into further improvements possible for stormwater quality models were given. It is recommended that in addition to the typical build-up and wash-off process, new generations of stormwater quality models should be able to account for the non-conventional pollutant sources (e.g. cross-connections, septic tank leakage, illegal discharges) through stochastic approaches. Emission inventories with information like intensity-frequency-duration (IFD) of pollutant loads from each type of non-conventional source are suggested to be built for stochastic modelling.
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.JENVMAN.2019.06.006
Abstract: To support sustainable urban planning and the design of water pollution mitigation strategies, the spatial and temporal trends of water quality in urban streams needs to be further understood. This study analyses over ten years of surface water quality data from 53 upstream catchments (20 of them predominated by a single type of land use) and two lowland sites across Greater Melbourne, Australia. We evaluated the impact of various catchment characteristics, especially urban land uses, on spatial and temporal urban water quality trends. Here, we focused on common urban pollutants: total suspended solids (TSS), total phosphorous (TP), total nitrogen (TN), zinc (Zn), copper (Cu) and nickel (Ni). Site median nutrient and heavy metal concentrations were negatively correlated with the catchment's elevation and its average annual rainfall. Further analysis shows that such trends were driven by the geographical pattern of Melbourne - i.e. low-laying sites tend to have less rainfall and be more urbanised. Only median concentrations of heavy metals (Zn and Cu) were correlated to catchment imperviousness. Further characterising of the urban environment was done into specific land uses (residential, industrial and commercial), yet median concentrations of all pollutants were not significantly correlated with land uses. This is because simple metrics, such as land use proportions, do not adequately reflect the significant variability in pollution sources that can exist even within the same land use type. Indeed, our temporal analysis found that the water quality difference between catchments with similar land uses is likely caused by their site-specific pollutant sources (construction and illegal discharge) and environmental management actions (wastewater management actions) regardless of similarities in land use. A 3-stage urbanisation cycle (development, operation and renewal) is suggested to further explain the urban water quality variance, but more data from small areas of an urban catchment is required to directly understand the unique impact of each urbanisation stage on water quality.
Publisher: Elsevier BV
Date: 02-2016
DOI: 10.1016/J.SCITOTENV.2015.11.150
Abstract: Stormwater harvesting biofilters need to be validated if the treatment is to be relied upon. Currently, full-scale challenge tests (FCTs), performed in the field, are required for their validation. This is impractical for stormwater biofilters because of their size and flow capacity. Hence, for these natural treatment systems, new tools are required as alternatives to FCT. This study describes a novel in-situ method that consists of a thin stainless steel column which can be inserted into constructed biofilters in a non-destructive manner. The in-situ columns (ISCs) were tested using a controlled field-scale biofilter where FCT is possible. Fluorescein was initially used for testing through a series of continuous applications. The results from the ISC were compared to FCT conducted under similar operational conditions. Excellent agreement was obtained for the series of continuous fluorescein experiments, demonstrating that the ISC was able to reproduce FCT results even after extended drying periods (Nash-Sutcliffe coefficient between the two data sets was 0.83-0.88), with similar plateaus, flush peaks, slopes and treatment capacities. The ISCs were then tested for three herbicides: atrazine, simazine and prometryn. While the ISC herbicide data and the FCT data typically matched well, some differences observed were linked to the different climatic conditions during the ISC (winter) and FCT tests (summer). The work showed that ISC is a promising tool to study the field performance of biofilters and could be a potential alternative to full scale challenge tests for validation of stormwater biofilters when taking into account the same inherent boundary conditions.
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.CHEMOSPHERE.2018.09.038
Abstract: Preliminary laboratory work has shown that electrochemical oxidation (ECO) is a promising technology for disinfection of harvested stormwater. This paper focuses on understanding how stormwater chemistry (e.g. pH, chloride, bicarbonate, ammonia and total organic carbon - that can vary substantially between sites) impacts the disinfection performance of ECO. Real stormwater s les from four different urban catchments were collected and tested for ECO performance in disinfecting stormwater pathogens using a boron doped diamond anode under the current density of 4.2 mA/cm
Publisher: American Geophysical Union (AGU)
Date: 12-2022
DOI: 10.1029/2022WR032365
Abstract: The state and dynamics of river chemistry are influenced by both anthropogenic and natural catchment characteristics. However, understanding key controls on catchment mean concentrations and export patterns comprehensively across a wide range of climate zones is still lacking, as most of this research is focused on temperate regions. In this study, we investigate the catchment controls on mean concentrations and export patterns (concentration – discharge relationship, C–Q slope) of river chemistry, using a long‐term data set of up to 507 sites spanning five climate zones (i.e., arid, Mediterranean, temperate, subtropical, tropical) across the Australian continent. We use Bayesian model averaging (BMA) and hierarchical modeling (BHM) approaches to predict the mean concentrations and export patterns and compare the relative importance of 26 catchment characteristics (e.g., topography, climate, land use, land cover, soil properties and hydrology). Our results demonstrate that mean concentrations result from the interaction of catchment indicators and anthropogenic factors (i.e., land use, topography and soil), while export patterns are influenced by topography. We also found that incorporating the effects of climate zones in a BHM framework improved the predictability of both mean concentrations and C–Q slopes, suggesting the importance of climatic controls on hydrological and biogeochemical processes. Our study provides insights into the contrasting effects of catchment controls across different climate zones. Investigating those controls can inform sustainable water quality management strategies that consider the potential changes in river chemistry state and export behavior.
Publisher: Royal Society of Chemistry (RSC)
Date: 2023
DOI: 10.1039/D3EW00160A
Abstract: Urban stormwater is a source of persistent, mobile and toxic substances, however the risk for water resources is unknown.
Publisher: Informa UK Limited
Date: 20-08-2018
Start Date: 02-2021
End Date: 02-2025
Amount: $425,952.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2022
End Date: 12-2025
Amount: $450,000.00
Funder: Australian Research Council
View Funded Activity