Hydrological interactions between surface water and groundwater in ancient manmade village tank cascade systems (VTCSs) in the dry zone of Sri Lanka.

Sri Lanka, a tropical island, confronts climate-driven water scarcity and is of great concern to building climate-resilient water management to achieve UN SDGs 6 and 13. This study explores the dynamic interaction between surface water (SW) and groundwater (GW) in the dry zone of Sri Lanka, employing a multi-tracer of dual stable isotopes (18O and 2H) and chloride. Two basins, Mahakanadarawa (MK) basin with numerous village tanks and tank cascade systems (VTCSs/TCSs) and Kawudulla (KW) basin serving as a control with a lack of tanks, were selected in this study. Results show that the presence or absence of TCSs emerges as a pivotal factor influencing regional water dynamics. Water quality (TDS and Cl-) in natural waters between the two basins was significantly different (ANOVA: p < 0.05) in both seasons. Statistically uniform dissolved mineral content in tanks and shallow groundwater in the MK basin contrasted with significant regional deviation in the KW basin. ANOVA and Tukey tests showed significant seasonal differences (p < 0.05) in mean values of ẟ2H and ẟ18O compositions of shallow groundwater and tank water within the MK basin, while non-significance in the KW basin. Isotopic mass balance calculations revealed that tank water mixing in the shallow groundwater (fT: mixed Tank water mass fraction) ranged from 0.9 % to 77.8 % across the MK basin depending on the regional soil characteristics. Lack of tank-aquifer interconnection observed in the shallow soil in rock knob plain results in groundwater depletion while enhanced interconnections within alluvial sediment regions encourage stable and pollution-resistant shallow groundwater bodies. The consistency of the groundwater flow system in TCS regions throughout the year ensures a stable water supply, highlighting the vital synergy between TCSs and regional groundwaters in these arid regions. These results shed insights for policymakers and water managers to implement effective conservation strategies for rehabilitation and restoring these ancient VTCSs/TCSs.

Chemical characteristics and water stability evaluation of groundwater in the CKDu Zone of Sri Lanka.

Groundwater is the main source of drinking water for the rural population in the chronic kidney disease of unknown etiology (CKDu) zone of the North Central Province (NCP) in Sri Lanka. In this study, a total of 334 groundwater samples (311 dug wells, 21 tube wells and 2 springs) during the wet season from two aquifers in the NCP were collected, and investigated their chemical characteristics and evaluate their water quality, including groundwater chemistry, main ion sources, the corrosion and scaling potential of groundwater. The results showed that the two hydrochemical types of groundwater in the NCP were mainly of the Ca-HCO3, Na·Ca-HCO3 types, with the main HCO3-, Na+ and Ca2+ ions in both types of groundwater originating from silicate and evaporite salt dissolution and influenced by alternating cation adsorption, while the presence of NO3- was mainly anthropogenic. Evaluation of water stability using namely Langelier saturation index (LSI), Ryznar stability index (RSI), Puckorius scaling index (PSI) and Larson-Skold index (LS), indicated that most groundwater presents corrosion potential and has corrosion behavior tendency of metals to some degrees. The water quality of Polonnaruwa was better than that of Anuradhapura in the NCP, and when the groundwater was worse than the "good" grade, which must be properly treated before it is used as drinking water.

Imperative assessment on the current status of rubber wastewater treatment: Research development and future perspectives.

The environment has been significantly impacted by the rubber industry through the release of large quantities of wastewater during various industrial processes. Therefore, it is crucial to treat the wastewater from the rubber industry before discharging it into natural water bodies. With the understanding that alarmingly depleting freshwater sources need to be preserved for future generations, this paper reviews the status of the rubber industry and the pollution caused by them, focusing mainly on water pollution. The review pays special attention to the recent advancements in wastewater treatment techniques for rubber industry wastewater categorizing them into pre-treatment, secondary, and tertiary treatment processes while discussing the advantages and disadvantages. Through a comprehensive analysis of existing literature, it was determined that organic content and NH4+ are the most frequently focused water quality parameters, and despite some treatment methods demonstrating superior performance, many of the methods still face limitations and require further research to improve systems to handle high organic loading on the treatment systems and to implement them in industrial scale. The paper also explores the potential of utilizing untreated or treated wastewater and byproducts of wastewater treatment in contributing towards achieving several United Nations sustainable development goals (UN-SDGs); SDG 6, SDG 7, SDG 9, and SDG 12.

Fluorescence characteristics and source analysis of DOM in groundwater during the wet season in the CKDu zone of North Central Province, Sri Lanka.

The dissolved organic matter (DOM) should be purified for safe drinking water due to disinfection by-products (DBPs) produced by disinfectants reaction with DOM. Current research on groundwater in the chronic kidney disease with unknown etiology (CKDu) zone of the North Central Province (NCP) in Sri Lanka has focused mainly on aquatic chemistry, with limited attention paid to the spatial distribution, compositional sources and factors of DOM. Therefore, the structure, composition, source and spatial distribution of the DOM of two kinds of groundwater samples collected from dug well and tube well in the NCP during the wet season were determined, compared and analyzed by analytical tools such as parallel factor analysis (PARAFAC). Results show that the average concentrations of TOC in these two groundwater samples are generally higher than 5.0 mg/L, and the concentration of TOC in the groundwater of the shallow weathered aquifer is higher than that of the deep hard rock aquifer, while its distribution of the two aquifers are on contrary. The DOM in the dug well has three types and four components, including humus-like component C1 (33.36%) and C2 (38.60%), protein-like component C3 (13.09%) and heterogeneous organic component C4 (14.95%). In the tube well, two types and two components of the DOM are determined, including humus-like component CⅠ (69.80%) widely existing in natural water and soluble microbial by-product CⅡ (30.20%) produced by microbial community activities. In the dug well, DOM is mainly exogenous input, the higher ion concentration in water affected the fluorescence intensity of humus and protein components. And in the tube well, DOM has obvious endogenous characteristics, and higher pH value may inhibit the production of protein like fluorescent substances to a certain extent.

Post-treatment of matured landfill leachate: Synthesis and evaluation of chitosan biomaterial based derivatives as adsorbents.

Matured landfill leachate is complex in nature, hence, a single conventional treatment unit is insufficient to remove the contaminants of the leachate to achieve the discharge standards. Furthermore, high levels of organic matter, colour compounds, and iron-based materials form a dark black/brown colour in leachate which is not removed by the biological treatment units. Hence, an Anoxic-Oxic Membrane Bioreactor coupled with a tertiary adsorption unit composed of crosslinked-protonated chitosan was tested for effective removal of the colour of the permeate. Several operational parameters such a pH, contact time, and adsorbent dosage on the adsorptive removal of colour were quantified using sorption-desorption experiments. Furthermore, the biosorbent was characterized using FTIR, SEM, XRD, BET-specific surface area, and pHZPC. Response Surface analysis confirmed the optimization of operational parameters conducted through traditional batch experiments. Langmuir isotherm model fitted with equilibrium data (R2 = 0.979) indicating a monolayer homogeneous adsorption. Kinetic data followed the Pseudo-Second-Order model (R2 = 0.9861), showing that the adsorbent material has abundant active sites. The percentage removal values show that the colour removal increases with time of contact and dosage of adsorbent, but removal is mainly influenced by the solution pH levels. The experimental results manifested a colour removal efficiency of 96 ± 3.8% obtained at optimum conditions (pH = 2, adsorbent dosage = 20 g/L, contact time = 48 h) along with an adsorption capacity of 123.8 Pt-Co/g suggesting that the studied adsorbent can be used as an environmentally friendly biosorbent in a tertiary unit for colour removal in a treatment system which is used to treat matured landfill leachate.

Treatment of mature landfill leachate in tropical climate using membrane bioreactors with different configurations.

This study describes the collection of landfill leachate from seven sites in different climatic zones of Sri Lanka and characterizes the landfills through the analyses of leachate quality. Membrane bioreactors (MBRs) with different configurations were employed to treat some of those leachates. An aerobic MBR (AMBR) system was operated in three Phases. In the first Phase, an AMBR alone, in the second Phase an anaerobic reactor followed by an anoxic reactor and an AMBR and in the third Phase an anoxic reactor followed by an AMBR were operated. In Phases I and II, the sludge retention time (SRT) and the hydraulic retention time (HRT) were kept at infinite (as no intentional wasting of sludge was made) and 96 h; in Phase III, the SRT was varied from 60, 30, 20 to 10 days and under each SRT, the HRT was varied from 96, 48, 24 and 12 h. The optimum operating conditions for the configuration used in Phase III was established through extensive experiments which had a SRT. The three MBR configurations removed more than 93%, 64.8% and 59% of BOD5, COD and total nitrogen respectively. They also removed large amounts of slowly biodegradable substances and nitrogenous compounds other than NH4+, NO3- and NO2-. Relationships between SRT and MLSS as well as SRT and fouling rate of membrane have been found. The study illustrates the capabilities of MBR in treating landfill leachate.

Biosorption of heavy metals: Transferability between batch and column studies.

The design of an industrial water treatment system using sorption is based on laboratory column tests. To verify the applicability of a column sorption system at industrial scale, it is necessary to determine the system's breakthrough time (BT) in a laboratory setting. In a laboratory column set-up, BT is referred to as the time taken by the adsorbate to appear at column outlet for the first time. This is when the mass transfer zone (MTZ), where the equilibrium sorption occurs, reaches the end of the sorbent bed. However, such laboratory set-up requires significant resources including laboratory space, time and multiple trials, which is the opposite to the batch experimental approach that is commonly used to assess efficiency of sorbents. This study identified batch sorption parameters that can be used to determine BT for a column sorption setting for three toxic heavy metals commonly found in industrial wastewater, namely, Pb2+, Cd2+ and Cu2+. The study conducted a comprehensive evaluation of the relationships between column BT and its key influential factors, namely, equilibrium sorption capacity (qe), pseudo second-order kinetic rate constant (k2) and initial sorption rate (h). The results revealed that BT can be better estimated using h compared to qe and k2. As such, a batch experiment which is more resource efficient could be undertaken for an initial estimation of the experimental BT of a column system. Moreover, a simulation model developed to replicate column sorption could demonstrate the behaviour of the breakthrough curve, which is a key to the selection and assessment of the performance of a sorbent in an adsorbent column. The estimation errors in qe and k2 were found to influence the simulation outcomes. Hence, it is necessary to further investigate the other factors that can potentially influence sorption behaviour.

Occurrence of Pharmaceutically Active Compounds and Potential Ecological Risks in Wastewater from Hospitals and Receiving Waters in Sri Lanka.

The presence of pharmaceutically active compounds (PACs) in the environment and their associated hazards is a major global health concern; however, data on these compounds are scarce in developing nations. In the present study, the existence of 39 non-antimicrobial PACs and six of their metabolites in wastewater from hospitals and adjacent surface waters in Sri Lanka was investigated from 2016 to 2018. The highest amounts of the measured chemicals, including the highest concentrations of atorvastatin (14,620 ng/L) and two metabolites, mefenamic acid (12,120 ng/L) and o-desmethyl tramadol (8700 ng/L), were detected in wastewater from the largest facility. Mefenamic acid, gemfibrozil, losartan, cetirizine, carbamazepine, and phenytoin were detected in all the samples. The removal rates in wastewater treatment were 100% for zolpidem, norsertaline, quetiapine, chlorpromazine, and alprazolam. There was substantial variation in removal rates of PACs among facilities, and the overall data suggest that treatment processes in facilities were ineffective and that some PAC concentrations in the effluents were increased. The estimated risk quotients revealed that 14 PACs detected in water samples could pose low to high ecological risk to various aquatic organisms. Compounds such as ibuprofen, tramadol, and chlorpromazine detected in untreated and treated wastewater at these facilities pose a high risk to several aquatic organisms. Our study provides novel monitoring data for non-antimicrobial PAC abundance and the associated potential ecological risk related to hospitals and urban surface waters in Sri Lanka and further offers valuable information on pre-COVID-19 era PAC distribution in the country. Environ Toxicol Chem 2022;41:298-311. © 2021 SETAC.

Integrated mathematical model to simulate the performance of a membrane bioreactor.

Membrane bioreactor technology includes the integration of biological wastewater treatment and physical separation by membrane filtration. When analyzing the system performance, efficiency of biological processes, physical separation and membrane fouling must be taken into consideration. Over the years, mathematical modelling of wastewater treatment has evolved and is being used extensively to optimize the performance of treatment systems. A Number of attempts have been made towards the development of mathematical models for membrane bioreactors and most of these models have not considered the effect of soluble microbial products on membrane fouling. Also the effect of periodic membrane cleaning was neglected. In this study, an integrated mathematical model was developed for the membrane bioreactor. A biological model based on activated sludge processes (extended with biopolymer kinetics) and a physical model with cake layer kinetics and membrane fouling have been combined. In order to overcome the drawbacks of previous attempts of modelling, the influence of soluble microbial products and extracellular polymeric substances are considered in the model integration. Further, the physical processes of the sludge removal and membrane cleaning which have strong influence on membrane fouling are considered in the model. "AQUASIM", a computer program for the identification and simulation of aquatic systems, was used for solving the processes. Calibrated and validated model enables the prediction of the system performance and membrane fouling under different operating conditions.

Evaluation of Performance of Existing RO Drinking Water Stations in the North Central Province, Sri Lanka.

Reverse osmosis (RO) drinking water stations have been introduced to provide safe drinking water for areas with prevailing chronic kidney disease with unknown (CKDu) etiology in the dry zone of Sri Lanka. In this investigation, RO drinking water stations established by community-based organizations (CBO) in the North Central Province (NCP) were examined. Water samples were collected from source, permeate, and concentrate in each station to determine water quality and performance. Furthermore, the operators of the systems were interviewed to evaluate operational and maintenance practices to identify major issues related to the RO systems. Results show that the majority (>93%) of RO systems had higher salt rejection rates (>92%), while water recovery varied from 19.4% to 64%. The removal efficiencies of hardness and alkalinity were averaged at 95.8% and 86.6%, respectively. Most dominant ions such as Ca2+, Mg2+, K+, Na+, Ba2+, Sr2+ Cl-, F-, and SO42- showed higher rejections at averaged values of 93.5%, 97.4%, 86.6%, 90.8%, 95.4%, 96.3%, 95.7%, 96.6%, and 99.0%, respectively. Low recovery rates, lower fluoride levels in product water, and membrane fouling were the main challenges. Lack of knowledge and training were the major issues that could shorten the lifespan of RO systems.

A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters.

Stormwater runoff pollution has become a key environmental issue in urban areas. Reliable estimation of stormwater pollutant discharge is important for implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop water quality models, deterministic approaches have proven inappropriate as they do not address the variability in stormwater quality. Due to the random nature of rainfall characteristics and the differences in catchment characteristics, it is difficult to generate the runoff pollutographs to a desired level of certainty. Bayesian hierarchical modelling is an effective tool for developing complex models with a large number of sources of variability. A Bayesian model does not look for a single value of the model parameters, but rather determines a distribution of the model parameters from which all inference is drawn. This study introduces a Bayesian hierarchical linear regression model to describe a catchment specific runoff pollutograph incorporating the associated uncertainties in the model parameters. The model incorporates catchment and rainfall characteristics including the effective impervious area, time of concentration, rain duration, average rainfall intensity and the antecedent dry period as the contributors to random effects.

The association between antimicrobials and the antimicrobial-resistant phenotypes and resistance genes of Escherichia coli isolated from hospital wastewaters and adjacent surface waters in Sri Lanka.

The presence of antimicrobials, antimicrobial-resistant bacteria (ARB), and the associated antimicrobial resistance genes (ARGs) in the environment is a global health concern. In this study, the concentrations of 25 antimicrobials, the resistance of Escherichia coli (E. coli) strains in response to the selection pressure imposed by 15 antimicrobials, and enrichment of 20 ARGs in E. coli isolated from hospital wastewaters and surface waters were investigated from 2016 to 2018. In hospital wastewaters, clarithromycin was detected at the highest concentration followed by sulfamethoxazole and sulfapyridine. Approximately 80% of the E. coli isolates were resistant, while 14% of the isolates exhibited intermediate resistance against the tested antimicrobial agents. Approximately 61% of the examined isolates were categorized as multidrug-resistant bacteria. The overall abundance of phenotypes that were resistant toward drugs was in the following order: ß-lactams, tetracycline, quinolones, sulfamethoxazole/trimethoprim, aminoglycosides, and chloramphenicol. The data showed that the E. coli isolates frequently harbored blaTEM, blaCTX-M, tetA, qnrS, and sul2. These results indicated that personal care products were significantly associated with the presence of several resistant phenotypes and resistance genes, implying their role in co-association with multidrug resistance. Statistical analysis also indicated a disparity specific to the site, treatment, and year in the data describing the prevalence of ARB and ARGs and their release into downstream waters. This study provides novel insights into the abundance of antimicrobial, ARB and ARGs in Sri Lanka, and could further offer invaluable information that can be integrated into global antimicrobial resistance databases.

Comparison of an integrated short-cut biological nitrogen removal process with magnetic coagulation treating swine wastewater and food waste digestate.

An integration of two processes, magnetic coagulation (MC) and short-cut biological nitrogen removal (SBNR), coupled with a sequencing batch membrane bioreactor (SMBR) controlled by an automatic real-time control strategy (RTC), was developed to treat different characteristics of high strength wastewater. The treatment efficiency and microbial community-diversity of the proposed method was evaluated and investigated using swine wastewater and food waste (FW) digestate. The MC showed high removal of TSS (89.1 ± 1.5%, 92.21 ± 1.8%), turbidity (90.58 ± 2.1%, 95.1 ± 2.1%), TP (88.5 ± 1.9%, 92.1 ± 1.5%), phosphate (87.76 ± 1.6%, 91.22 ± 1.5%), and SMBR achieved stable and excellent removal of COD (96.05 ± 0.2%, 97.39 ± 0.2%), TN (97.30 ± 0.3%, 97.44 ± 0.3%) andNH4+-N (99.07 ± 0.2%, 98.54 ± 0.2%) for swine wastewater and FW digestate, respectively. The effluent COD andNH4+-N concentrations were found to meet their discharge standards. The microbial community comparison showed similar diversity and richness, and genus Diaphorobacter and Thaurea were dominant in denitritation, and Nitrosomonas was dominant in nitritation treating both swine wastewater and FW digestate.

Profiles of antibiotic resistome and microbial community in groundwater of CKDu prevalence zones in Sri Lanka.

The chronic kidney disease of unknown etiology (CKDu) prevalent in certain regions of Sri Lanka poses a serious threat to human health. Previous epidemiological studies focused on the search of causative agents for CKDu etiology from the viewpoint of groundwater composition, but how CKDu prevalence affected the groundwater microbial composition, especially the antibiotic resistome, has never been illuminated. This study investigated the response of microbial community and antibiotic resistome to CKDu prevalence in the groundwater through the high throughput sequencing and qPCR (HT-qPCR), respectively. Results showed that CKDu prevalence significantly influenced the distribution of antibiotic resistome and microbial community composition. The mexF dominated in all the groundwater samples and could be considered as an intrinsic ARG, and the ß-lactamase cphA was specially enriched and closely associated with the antibiotics used for CKDu patients. The Acinetobacter was a potential human pathogen common in the groundwater of CKDu affected regions, while CKDu prevalence specially enriched the Aeromonas. Statistical analysis indicated that CKDu prevalence impacted antibiotic resistome through the microbial community as a whole, and MGEs contributed to the occurrence of mexF, while the enrichment of cphA could be attributed to the increase of Aeromonas.

New conceptualisation of first flush phenomena in urban catchments.

First flush is an important phenomenon commonlyused in stormwater treatment system design where only the highly concentrated initial part of the runoff hydrograph is subject to treatment. Despite the existing methods for estimating the first flush, a robust quantitative definition is difficult to find. This paper discusses a novel approach, where a new parameter is introduced to analyse the variability in the discharge of pollutants at different times throughout a runoff event and thereby enable the identification of first flush. It was found that due to variability in rainfall, the first flush runoff volume varies from event to event. Therefore, a static estimate of the first flush is not applicable for a runoff event. The Monte Carlo simulation undertaken strengthened the analysis by providing credible limits to the outcomes. Accordingly, an interval estimation was obtained in which the first flush runoff can vary, and it was found that most commonly, the first flush can exist through the initial 30%-50% of the runoff. Therefore, in order to treat the stormwater runoff with minimum risk of discharging high loads of pollutants to the receiving water environment, at least the initial 30% of the runoff should be subject to treatment. This understanding provides a fundamental basis for the design of robust stormwater treatment systems.

Catchment based estimation of pollutant event mean concentration (EMC) and implications for first flush assessment.

The Event Mean Concentration (EMC) is considered as a key analytical parameter for assessing the quality of stormwater. The conventional estimation methods to determine EMC do not necessarily address the variability associated with the hydrologic characteristics. Accordingly, this study was conducted to identify the potential hydrologic variables that can influence EMC and thereby to create a mathematical model to determine EMC using the hydrologic variables while incorporating the catchment as an influential factor. This paper introduces an innovative approach to estimate EMC of a runoff event using a stepwise multiple linear regression model. The model incorporates hydrologic variables together with their two-way interaction terms. The catchment was included in the model as a dummy variable. This allows identifying the variability of EMC between catchments. Model can reasonably predict the EMC with an overall prediction error of 0.811. The regression coefficients of the model specify that, maximum rainfall intensity is the most influential variable having a coefficient of 1.008, followed by the average intensity with a coefficient -0.586. The interaction term of rainfall depth and the antecedent dry period indicates that for a relatively small rainfall event (<5 mm), an optimum value of antecedent dry period exists that maximises the EMC. Subsequently, EMC was employed to define the first flush runoff as an alternative approach to the conventional approaches for determining the first flush. The dynamic mean concentration (DMCt), was introduced as a parameter for estimating the first flush using EMC. The maximum accumulated runoff volume such that, DMCt≥EMC was defined as the first flush runoff. It was found that residential catchments generate more intense first flush compared to catchments with totally impervious surface areas and thereby a significant pollutant load is transported within a small initial fraction of the runoff.f.

Fouling of ion exchange membranes used in the electrodialysis reversal advanced water treatment: A review.

Electrodialysis self-reversal (EDR) technology has attracted in the treatment of water for domestic and industrial uses. The self-reversal consists of a frequent reversal of the direction of current between the EDR-cell electrodes to combat fouling of ion exchange membranes (IEMs). Irrespective of the EDR self-cleaning processes, the role of natural organic matter and their complexing ability with metal ions on IEMs fouling is partially understood. The objective of this review is to identify the research gaps present in the elucidation of IEM fouling routes. The common IEMs' foulants are identified, and several fouling mechanisms are briefly discussed. The effectiveness of self-cleaning mechanisms to reduce IEMs fouling is also be discussed. Dissolved organic carbon (DOC) possesses high chelation which forms metal complexes with di and trivalent cations found in water. The role of ternary complexes, e.g. M2+/3+-DOC and membrane surface, on membrane fouling via surface bridging, are also addressed. Finally, mitigation methods of IEMs membrane fouling are also discussed.

Mathematical modelling of the influence of physico-chemical properties on heavy metal adsorption by biosorbents.

Adsorption rate is a critical parameter in the design of effective biosorbent treatment systems for heavy metals removal. Though numerous studies have identified the physico-chemical properties of biosorbents that exert influence on the adsorption rate, such influence has not been mathematically defined, limiting the effective design of adsorption systems. This study quantifies the influence of biosorbent physico-chemical properties including, specific surface area, surface functional groups, pore size, pore volume and zeta potential on the adsorption rate in relation to three divalent metal cations. Mathematical equations were developed to predict the influence of physico-chemical properties on pseudo second order kinetic constant and thereby predict the adsorption rate. Tea factory waste and coconut shell biochar were mixed in different weight percentages to vary the physico-chemical properties under consideration. Four different initial metal ion concentrations were used. Relationship between pseudo second order kinetic constant at each concentration with physico-chemical properties was quantified using regression analysis. The experimental analysis revealed that among the physico-chemical properties, acidic surface functional groups had the most profound influence on sorption mechanisms. Reliability and accuracy of the predictive models were significantly improved when separate models were developed for two ranges of initial metal ion concentrations. The outcomes of this study will contribute to the effective design and optimization of biosorbent mixtures with the capacity to remove Pb2+, Cu2+ and Cd2+ in wastewater.

Taxonomy of influential factors for predicting pollutant first flush in urban stormwater runoff.

Pollutant first flush in urban stormwater runoff is an important phenomenon influenced by a range of rainfall and catchment related variables. Even though numerous studies have been undertaken to mathematically define the first flush and the influential variables of first flush, limited research have been carried out to rank such variables in terms of their level of importance in generating first flush. Identifying the degree of importance of the variables is critical for accurate predictions of first flush occurrence and understanding the main drivers of first flush. This research study undertook a comprehensive analysis of the variables influencing the predictions of first flush occurrence and their relative importance. The study results are expected to contribute to more accurate predictions of first flush by affording greater importance to the highly ranked factors and their impacts. The study outcomes confirmed that total rainfall depth was the most important variable influencing the prediction of first flush events while the maximum intensity was the second. Rain duration, runoff depth, runoff peak and average intensity were the next four most important variables. Antecedent dry period and effective impervious area fraction had relatively low ranking while the time of concentration and the event mean concentration were found to be the least important variables. Furthermore, the study outcomes highlight that the use of a combination of variables and due consideration of their interactions can yield better results than considering their individual roles.

Quantifying the influence of surface physico-chemical properties of biosorbents on heavy metal adsorption.

Heavy metals present in industrial wastewater contribute to human and ecosystem health risk when discharged without proper treatment. Low-cost biosorbents with high metal-binding capacity are increasingly being utilized for the removal of heavy metals. Inherent physico-chemical properties of biosorbents significantly influence their adsorption capacity. Studies quantifying the influence exerted by these properties on adsorption capacity are scarce. This study quantifies the influence and relative importance of selected physico-chemical properties on the adsorption capacity of three divalent heavy metals; Cu2+, Cd2+ and Pb2+ using multivariate analysis. Twenty one biosorbent mixtures were created, systematically varying their physico-chemical properties using tea factory waste and coconut shell biochar. Their adsorption capacities were measured using batch sorption studies. The influence of physico-chemical properties on the adsorption capacity is comparable for all three metal cations. Regression models were developed to quantify the influence of physico-chemical parameters on the adsorption capacity based on regression coefficients. All models were found to have high reliability with R2 values above 0.98. Acidic surface functional groups were found to act as the key property that governs the adsorption capacity of Pb2+, Cu2+ and Cd2+. Carboxylic groups played a major role in the adsorption of Cu2+ and Pb2+, while lactonic groups were more important in providing binding sites to Cd2+. SSA failed to demonstrate a significant impact on the adsorption capacity of these three metals on its own when the biosorbent had a low surface functional group density.