Alum Dose Research Articles

Turbidity Removal Efficiency of Tannin Based Flocculants Derived from Different Agricultural Waste

Tannin-based flocculants have been investigated, produced, and commercialized as a promising product in water supply and wastewater treatment. This study compared turbidity removal efficiency of tannin-based flocculants produced from different agricultural waste. Tannin was extracted using ultrasonic method (ethanol 50%, 2 h, 500 kHz) and modified according to Mannich reaction using HCHO and NH4Cl. The coagulation and flocculation efficiencies were determined using Jar-tests on artificial wastewater with initial turbidity of 200 NTU. The results showed that at pH 7 and alum dosage of 5 ppm, turbidity removal efficiency of flocculants derived from longan pericarp, mimosa bark, green tea waste, and green banana peel were 93%, 92.7%, 92%, and 89.8%, respectively; corresponding to flocculant dosages of 10 ppm, 12 ppm, 8 ppm and 8 ppm. Production efficiency for green tea waste (9.4%), mimosa bark (7.1%), longan pericarp (4.6%) were much higher than that for green banana peel (0.5%). Based on the turbidity removal and production efficiencies as well as the optimal dosages of tannin-based flocculants, green tea waste was found to be the most potential material of all four agricultural waste to produce tannin-based flocculants.

Optimizing natural organic matter removal at the Koka water treatment plant, Ethiopia, using soil–alum composite material

ABSTRACT Conventional water treatment methods often fail to remove natural organic matter (NOM), leading to the formation of harmful disinfection by-products in chlorinated water. This study aimed to develop a synergistic, local soil–aluminum sulfate (alum) composite material to enhance NOM removal from real water samples. Locally derived soil (Chalaltu) samples were collected from selected locations and subjected to thermal treatment at elevated temperatures. The thermally treated soil was then combined with alum at varying mixing percentages to create the composite material. The synthesized composite materials were thoroughly characterized using X-ray diffraction, X-ray fluorescence, scanning electron microscopy, Fourier transform infrared, and Brunauer–Emmett–Teller techniques. The alum-treated soil, obtained through thermal treatment at 500 °C with a mixing ratio of 50%, a dosage of 25 mg/L, and a settling time of 25 min, exhibited impressive removal efficiencies. The composite material increased removal efficiency by 1.5 times for both UV254 absorbance (91.1%) and dissolved organic carbon (90%), while reducing the alum dose by 58% compared to the existing Koka water treatment plant process. Reducing alum usage could lead to cost savings and alleviate concerns about its association with Alzheimer's disease. This technique is essential within the context of water treatment technology.

Enhancing activated sludge dewatering performance: Impact of alum dosage on dehydration characteristics and microstructure

Sludge flocs encapsulate a significant amount of bound water, resulting in poor dewatering efficiency. To address this issue, the addition of alum (KAl(SO4)2·12H2O) has emerged as an effective strategy for enhancing sludge dewatering performance. This research specifically investigates the effects of various alum dosages on the dewatering characteristics of sludge. The introduction of alum alters internal temperature, pH levels, and intracellular osmotic pressure, which facilitates the release of trapped water within the flocs. Additionally, alum accelerates sludge sedimentation and promotes the agglomeration of smaller particles into larger ones, further improving dewatering efficiency. However, determining the optimal alum dosage for sludge conditioning is essential, as excessive amounts can lead to a decrease in dewatering performance.

Reduction of organic matter and disinfection by products formation at surface water treatment plants in Egypt

ABSTRACT Although the removal of colloidal particles continues to be an important reason for using coagulation, currently a newer approach, the removal of organic matter to reduce the formation of disinfection byproducts (DBPs) such as trihalomethanes (THMs) are suspected carcinogens. Inefficient removal of total organic carbon (TOC) leads to the formation of carcinogenic THMs. This motivates the research efforts to find a way to reduce them in potable water. The first objective of this research is monitoring the water quality (raw and produced) for selected three water treatment plants within Giza Governorate to reveal the most polluted site (high TOC in the raw water and THMs in the treated water) in the study areas. The second objective of this study is enhancing coagulation to reduce TOC and THMs from surface water treating. In this study, two different coagulants aluminum sulfate (alum), and ferric chloride were tested under different conditions of pH and coagulant concentration to determine their effectiveness for removal of TOC, THMs and turbidity. Optimum values for the mentioned conditions were used to achieve the maximum reduction for TOC and THMs in Al-Ayat drinking water treatment plant (DWTP) which recorded the highest concentration of TOC and THMs. Ferric chloride as a coagulant achieved the maximum removal percentage % of TOC, THMs and turbidity as 79%, 82% and 94%, respectively, at ferric chloride dose 100 mg/L, while alum as a coagulant recorded the maximum removal percentage % of TOC, THMs and turbidity as 46%, 52% and 91%, respectively, at alum dose 100 mg/L. The results indicated that ferric chloride as a coagulant has the highest efficiency reduction of TOC, THMs and turbidity if compared to alum with the same dose added.

Changes in DOM and alum doses for two rivers of contrasting catchments after intense wildfires

ABSTRACT The dynamics of dissolved organic matter (DOM) in two river waters were investigated after their catchments had been severely burnt in the 2019/2020 Australian wildfires. Shortly after these wildfires, dissolved organic carbon (DOC) concentrations were recorded at high levels (∼19 and 30 mg/L) and these became much lower (up to ∼80% less) in the following winter when river flows had increased. Satellite imagery-based data indicated up to 95% of catchment areas burnt and up to ∼50% subsequent vegetation recoveries after 2 years. Shifts in burn index values for the burnt areas coincided with DOC concentration variations. The specific colour of waters increased up to 40% as daily river flows increased, indicating higher input of humic content from the burnt catchments. Chlorophyll a was detected at the highest levels in the waters soon after the fires when river flows were lowest. Enhanced alum doses were predicted using two feed-forward models; one based on DOC and turbidity data and the other based on UV@254 nm, colour, and turbidity. The doses predicted using the two models showed high correlations (r > 0.9) and were highest for waters directly after the fires. These models were developed for diverse source waters including those impacted by extreme climate events.

Using a novel bio-based cationic flocculant for food industry wastewater treatment

Wastewater from the food industry is considered harmful to human health and aquatic life, as well as polluting water and soil. This research is centered around finding an affordable and easy physicochemical method for dealing with waste generated by the food industry. To accomplish this goal, a new bio-based flocculant called 4-benzyl-4-(2-oleamidoethylamino-2-oxoethyl) morpholin-4-ium chloride was created using sustainable sources, specifically crude olive pomace oil. Its chemical structure was confirmed using various spectroscopic techniques such as FTIR, 1H-NMR, mass spectra, and 13C-NMR. This new bio-based cationic flocculant was combined with alum to act as a coagulant in the waste treatment process. Also, a study was conducted to determine the optimal conditions for the coagulation-flocculation process parameters, namely, pH and alum dosage, on COD and removal efficiency. The results showed that the optimal conditions for flocculation were achieved at pH 5.8, with 680 mg/L alum and 10 mg/L of commercial flocculant dose compared to only 5 mg/L of a new bio-based cationic flocculant. A comparison was made between the new bio-cationic flocculant and a commercial CTAB one for treating wastewater in the food industry. The study found that the new bio-based cationic flocculant was more effective in reducing the chemical oxygen demand, achieving a reduction of 61.3% compared to 54.6% for using a commercial cationic flocculant. Furthermore, using a new bio-based cationic flocculant costs only 0.49 $/g, which is less than the present cationic flocculant, which costs 0.93 $/g. The adoption of this new flocculant provides a sustainable alternative to existing industrial wastewater treatment processes

Optimization of calcined eggshell as an effective coagulant for treating colloidal particles in complex effluents in the CPCP industry: mechanistic insights, scale-up design, and comparative analysis with alum

Highly turbid industrial effluent poses significant challenges to environmental sustainability. In this study, we investigated the optimal aggregation kinetics for the removal of colloidal and turbid particles in Cosmetics and Personal Care Products (CPCP) industrial effluent using calcined eggshell (CES) and industrial-grade aluminum sulfate as flocculants. The effluent characteristics were determined following ASTM specifications, and process optimization was carried out using a response surface design approach. The optimal operating conditions at a settling time of 3 min were found to be pH 8, 0.2 g/L dosage of CES, pH 10, and 0.3 g/L of alum dosage. The flocculation efficiencies of CES and alum were found to be 80% and 78%, respectively, demonstrating the effectiveness of both flocculants in removing colloidal particles and reducing turbidity in CPCP effluent. Mechanistic studies revealed that CES achieved particle removal through enmeshment and inter-particle bridging with a significant aggregation rate (1.3 × 10−7) and a lower floc breakup tendency (2.8 × 10−14) compared to alum-sweep flocculation. The hydrodynamics at a velocity gradient of 269s−1 ≤ G ≤ 29s−1 indicated spontaneous agglomeration within a flocculation period of ≤10 min, indicating rapid and efficient particle removal. The findings of this study justify the use of CES as a sustainable and effective option for the removal of colloid/turbid particles from CPCP effluent. The optimized operating conditions and mechanistic insights into the flocculation process contribute to establishing an optimized sedimentation geometry, with specified aspect ratio, detention time, hypothetical settling, and sludge depth for CES, ensuring the favorable stability of the finished CPCP effluent before discharge.

Climate-Driven Increases in Source Water Natural Organic Matter: Implications for the Sustainability of Drinking Water Treatment.

This study presents an updated analysis spanning over two decades (1999-2023) of climate, water quality, and operational data from two drinking water facilities in Atlantic Canada that previously experienced gradual increases in the natural organic matter (NOM) concentration and brownification. The goal was to assess the impact of recent extreme weather events on acute NOM concentration increases and drinking water treatment processes. In 2023, a dry spring combined with a warm and wet summer caused NOM in the water supplies to increase by >67% (as measured by color). To mitigate increased NOM concentration, the alum dose nearly doubled in 2023 compared to that in 2022. Disinfection byproducts were elevated following the event but remained within the compliance levels. From 1999 to 2023, the two plants responded to gradual climate change impacts and brownification, with alum dose increases of between 4.1 and 8.3 times. Equivalent CO2 emissions were estimated for alum usage, which increased by 3 to 7-fold in 2023 compared to when the plants were commissioned decades prior. The plants were not only adversely impacted by climate change but also contributed to the global CO2 burden. Thus, a paradigm shift toward sustainable alternatives for NOM removal is required in the water sector, and climate change adaptation and mitigation principles are urgently needed.

Effect of dual flocculant by unmodified manihot esculenta starch and aluminium sulphate on the removal of chemical oxygen demand optimized by response surface methodology

Abstract Applying inorganic metal salt-based aluminium sulphate (Al2(SO4)3) or alum in wastewater treatment has gained many concerns regarding the impact on health and environmental implications. Due to the negative consequences, incorporating inorganic and natural flocculants in the coagulation-flocculation process is the alternative way to reduce undesirable effects. In this study, an evaluation performance of Manihot esculenta (ME) starch and alum as a dual flocculant was conducted to remove chemical oxygen demand (COD) in the optimum weight ratio of alum/starch = 0.06. The optimization of coagulation-flocculation by the optimal (custom) design, response surface methodology (RSM) presented that applying a dual flocculant improved the COD removal efficiency by up to 93% compared to a single coagulant (alum) of 85%. Besides the performance of COD removal increased, the dosage of the chemical coagulant was reduced by up to 64% at the optimum condition of 18 mg/L alum dosage, 307 mg/L starch dosage, pH 9, and 27 mins settling time. The analysis of variance (ANOVA) indicated that the quadratic model was significantly developed with a p-value < 0.05. The results were justified by a high coefficient of determination (R2 alum = 0.9641) and (R2 dual flocculants = 0.9335) using single and dual flocculants, respectively. The findings supported ME starch as an alternative approach in minimizing chemical coagulants in wastewater treatment.

IoT-Enabled Water Quality Monitoring and Alum Dose Determining System

The water treatment process involves a series of physical, chemical, and biological techniques and methods designed to remove contaminants, impurities, and undesirable substances from raw or untreated water to make it safe, clean, and usable. Adverse weather conditions, such as rainy seasons and floods, present significant challenges, and difficulties to the water treatment process. Alum is mainly used for reducing the turbidity of the water in the treatment process. In Sri Lanka, all water treatment plants use the Jar Test to determine the Alum dosage manually. They conduct Jar Tests to measure raw water quality in their laboratories. The Alum addition valve is set to a pre-determined quantity and the value is decided based on the experience of the technicians. Since there is no specific formula, the presence of an experienced technician is required to determine alum dosage using the Jar test. Thus, this study intends to propose an automated system for determining the optimum Alum quantity to be added to a given raw water sample. This is achieved by designing an Internet of Things (IoT)-enabled sensing device for measuring the water quality, which feeds data to a Machine Learning Model trained to predict the Alum quantity to be added. The task of the Machine learning model is to identify the pattern of raw water parameters and Alum dosage. By doing this, a could be provided a guideline for determining alum dosage instead of a manual Jar test and removed the necessity of experienced technician support always. A user-friendly web interface will allow the operators to customize the parameters according to the requirement and display a detailed analysis report. The predetermined quantity of Alum is transmitted to the output Alum adding value, to enhance its performance as an automated control rather than doing the addition process manually. This is a conceptual study on how to determine the Alum dosage using Raw water parameters and past experiment results.

Polymeric Flocculation as a Sustainable Solution for Heavy Metal Removal from Leachate in Barka Landfill, Oman

Purpose: This study investigates the effectiveness of polymeric flocculation in removing heavy metals from leachate through filtration, sedimentation, and precipitation, aiming to separate and eliminate particulate matter. to separate and remove particulate matter. Method: This study investigated the use of alum and chitosan to remove heavy metals from leachate. The addition of a polymeric flocculant, chitosan, promoted the formation of stable flocs, which effectively removed heavy metals. Chitosan, a natural biopolymer, was found to be a promising alternative to synthetic polymers. Main Findings: The experimental results demonstrated that alum outperformed chitosan in terms of removing heavy metals. Under optimal conditions, an alum dosage of 6 mg/l at a pH of 6.23 resulted in copper and magnesium removal efficiencies of 84% and 92%, respectively. In contrast, the optimal chitosan dosage was 8 mg/l at a pH of 7.5, with copper and magnesium removal efficiencies of 43.1% and 91.8%, respectively. Implications: Leachate treatment reduces heavy metals and organic compounds, controls odors, and generates foam indicating the presence of gases like carbon dioxide and methane. These gases can be harnessed for clean energy production and green hydrogen development. harnessed for clean energy production and green hydrogen development. Novelty: This study is the first to scientifically analyze leachate treatment at the Barka landfill. Chitosan, a natural polymer, effectively removes suspended matter and heavy metals, reducing their concentrations. removes suspended matter and heavy metals, reducing their concentrations.

Evaluation of Anticoagulant Effect of Alum in Rats

Potassium aluminium sulfate, KAl(SO4)2, also called Alum, is an acidic white chemical substance. The role of alum in bleeding and clotting is not fully understood. Objective: To determine the effects of alum on clotting time, D-dimer levels, fasting blood glucose level, and lipid profile. Methods: The study was conducted on 24 male Wistar rats, which were randomly divided into six groups. Four groups were given different concentrations of alum solutions. The remaining two groups received warfarin, and distilled water, which are control, and placebo groups, respectively. Blood tests such as fasting blood sugar (FBS), D-dimers, clotting time, and lipid profile were performed. Results: The study found that the administration of alum prolonged the time it took for blood to coagulate. Alum showed a dose dependent increase in clotting time when compared to the warfarin-control group and group 4 (100 mg/kg alum dose) showed the most significant effect. Similarly, in the case of D-dimers, a dose dependent decrease in the level of D-dimers was seen and the most significant effect was found for high concentration. The plasma blood glucose and lipid level of animals treated with alum did not show any significant effect as compared to placebo. Conclusions: The efficacy of alum as an anticoagulant drug was investigated, and it was found to significantly prolong clotting time while simultaneously reducing the level of D-dimers. Furthermore, it was deemed safe and showed no effects on fasting plasma glucose and lipid profile. The safety profile of alum was assessed to be favorable, thus highlighting its potential as an anticoagulant drug of the future

Effect of coagulation-sedimentation pretreatment on methane production from Indonesian palm oil mill effluent and kinetics

The current study purposed to investigate the influence of coagulation-sedimentation (CS) pretreatment on methane production from Indonesian palm oil mill effluent (POME). In the CS pretreatment, the coagulation process was conducted for 2 h at various alum doses (2, 4, 6, and 8 g/L), followed by the sedimentation process for 24 h to separate sludges from supernatants. Then, supernatants were used as methane feedstocks. The CS pretreatment with an alum dose of 6 g/L generated the highest reduction in chemical oxygen demand (COD) of 70.02 %. The anaerobic digestion (AD) of supernatant resulting from CS pretreatment with an alum dose of 6 g/L generated 8-fold higher methane production than the AD of raw POME. In kinetic analyses, the modified Gompertz model had a higher accuracy (R2 of 0.9938) in predicting methane yield evolution than the first-order model and the Cone model (R2 of 0.9449 and 0.9923).

Machine learning facilitated the conceptual design of an alum dosing system for phosphorus removal in a wastewater treatment plant

Wastewater treatment plants (WWTPs) face challenges in controlling total phosphorus (TP), given more stringent regulations on TP discharging. In particular, WWTPs that operate at a small scale lack resources for real-time monitoring of effluent quality. This study aimed to develop a conceptual alum dosing system for reducing TP concentration, leveraging machine learning (ML) techniques and data from a full-scale WWTP containing incomplete TP information. The proposed system comprises two ML models in series: an Alert model based on LightGBM with an accuracy of 0.92, and a Dosage model employing a voting algorithm through combining three ML algorithms (LightGBM, SGD, and SVC) with an accuracy of 0.76. The proposed system has demonstrated the potential to ensure that 88.1% of the effluent remains below the TP discharge limit, which outperforms traditional dosing methods and could reduce overdosing from 61.3 to 12.1%. Furthermore, the SHapley Additive exPlanations (SHAP) analysis revealed that incorporating the output features from the previous cycle and utilizing the results of the Alert model as the input features for dosage prediction could be an effective method for data with limited information. The findings of this study have practical applications in improving the efficiency and effectiveness of TP control in small-scale WWTPs, providing a valuable solution for complying with stringent regulations and enhancing environmental sustainability.

Use of Paci and Alum to Reduce Tss Levels in People's Rubber Soaking Liquid Waste

The coagulants used are PACl and alum because, in addition to their low price, PACl and alum are also proven to reduce turbidity and TSS levels in wastewater. This study aimed to determine the effect of PACl and alum on reducing TSS levels in people's rubber bath waste. This type of research is classified as an actual experiment, utilizing a pretest and posttest design with a control group. Integrated sampling was the sampling technique used in this study. Statistical analysis is performed using the normality test, and if the data is normally distributed, it is continued with the one-way ANOVA test. The normality test results showed average distributed TSS level data. They continued the Anova test (p = 0.005 < ɑ = 0.05), which found a difference between PACl and alum coagulant in reducing TSS levels in people's rubber immersion liquid waste. A PACl dose of 1200 mg/L lowered TSS levels by 46%. While the alum dose of 3000 mg/LL has not been able to reduce TSS levels, The variation in the dose of PACl and alum coagulants should be reduced again to be optimal for reducing TSS levels in liquid waste. To meet the quality standards of rubber immersion waste by reducing TSS levels, liquid waste with acidic or alkaline properties needs a neutralization process by adding lime.

Optimizing dialysis water treatment based on medical planning requirements

This paper introduces a new approach to improving hemodialysis and peritoneal dialysis processes. This maintains compatibility between the water treatment unit and active dialysis machines. Identification of different deviations in the patient’s requirements to classify the suitable flow rate (FR) of the pure water can be created through an Adaptive Neuro-Fuzzy Inference System (ANFIS). Four types of categories are classified: quarter load, half load, three-quarter load, and full load. This includes two main steps: identifying the dialysis categories with patients and measuring the suitable FR for each category. The effective FR of water was computed to indicate how the number of pumps rose as the number of patients treated within the dialysis unit increased. The introduced prediction method was tested against artificial neural networks to predict alum doses (ANN-AD) method, artificial intelligence as a combinatorial optimization strategy (AN-COS) using peach-palm waste in a solid-state fermentation environment, expert system applications (ESA) in chronic kidney disease management (MDSSs), prescription optimization for automated peritoneal dialysis (BCPH). In this work, pumping system parameter estimation was utilized to assess the performance of the introduced systems based on input voltage, input current, rotor speed, and electromagnetic torque waveforms of the pumping drive. This method uses the ANFIS algorithm to construct a high-performance pumping system to evaluate and predict the flow rate of dialysis machines based on input–output estimates. The flow rate values for each patient in critical care units can be controlled by the presented algorithm according to the time of dialysis. A good predictive model based on integrating the experience and decision making of medical planners was implemented. The proposed method not only improves accuracy but also saves time in the dialysis unit. The presented fuzzy classifier uses the ratio of the number of predicted true positives and false positives to the total number of anticipated positives. The simulation results show that the proposed technique can be successfully used to classify the suitable FR of the water according to the hemodialysis load. One of the advantages of the presented technique is the ability to predict the value of FR in real time with reliability, low computational complexity, and a high accuracy of 98.01%, which simplifies the dialysis process for many patients while at the same time leading to improved performance of hemodialysis. The presented method can be implanted in online FR estimation and analysis hardware for hemodialysis, is easy to calculate and run in real time, minimizes hemodialysis costs, and saves run time.

Effect of comparison ratio of additives on changes in pH levels, TSS, Fe, and Mn metals in the acid mine water treatment process at KPL BB 13 PT bukit asam, tbk.

Mining activities with an open system at PT Bukit Asam Tbk. have the potential to produce acid mine drainage due to contamination by rocks with sulfur content. Acid mine drainage treatment is carried out by the active method in the Mud Settling Pond (KPL). Addition of alum (Al2(SO4)3) and quicklime (CaO) to increase pH levels and reduce water turbidity. Management is carried out to meet environmental quality standards, namely with a pH value of 6-9, a maximum TSS value of 400, and for Mn and Fe a maximum of 4 and 7 mg/L, respectively. Jar Tests were conducted on samples from KPL BB-13 with mixed doses of alum and quicklime used were 0.02 and 0.10 grams; 0.03 and 0.12 grams; 0.04 and 0.14 grams; 0.05 and 0.16; 0.06 and 0.18; and 0.7 and 0.20. The best test results are at a mixed dose of 0.02 grams of alum and 0.10 grams of quicklime to obtain a pH value of 7 (neutral), besides that TSS and Fe metal levels have decreased. Mn metal also decreased, but did not meet environmental quality standards. Increased doses for field scale under actual conditions of observation required alum as much as 1.00 g/s and quicklime as much as 5.0052 g/s. The evaluation results show that the acid mine drainage treatment carried out by the company is more effective and efficient than the dose of laboratory test results.

Sustainable Water Management with Design and Economic Evaluation of Recycling Greywater at Abu Dhabi University—A Case Study on Decentralization

Wastewater can be segregated as greywater and blackwater separately. The greywater generated in malls, restaurants, and university buildings is generally dilute, while it will later become concentrated when it is merged into the main sewage collection line. It would be more economical and environmentally friendly if the greywater is treated locally using a modular wastewater treatment facility that produces treated water amenable for other uses such as irrigation or horticulture. The objective of this article is to study the economic feasibility and design a decentralized plant that produces fresh water from greywater generated at the Abu Dhabi university campus located in the United Arab Emirates. The proposed unit will consist of a compact design of filtration, chemical treatment and disinfection processes that would generate treated wastewater that can be used for horticulture in and around the local campus or can be stored and supplied for irrigation purposes. Several parameters such as total suspended solids, biological oxygen demand, and chemical oxygen demand are measured and monitored throughout the entire process and are regulated by appropriate operations performed for each unit. This study shows that decentralization of greywater treatment is not only economical but also essential for the management of fresh water, which in turn assures environmental sustainability. By using coagulation, flocculation and chlorination with a 30 mg/L alum dosage, 0.6 mg/L of polyacrylamide and 0.12 mg/L of sodium hypochlorite, respectively, greywater is treated to meet the water specification for reusing it for horticulture. Further, a modular plant with an investment of USD 8 M is proved to process 90,000 tons of greywater with a 34% discounted rate of return.

Microplastic removal in batch and dynamic coagulation-flocculation-sedimentation systems is controlled by floc size

Most studies examining the removal of microplastics (MPs) during controlled bench-scale trials have applied high coagulant dosages, which are characteristic of sweep flocculation. As such the impact of other typical operating conditions remains largely unknown. The use of bench-scale jar testing is ubiquitous in the literature, however the hydrodynamics of a batch-type approach bear little resemblance to full-scale treatment processes. In this study, a range of microplastics sizes and types were employed to assess their removal via conventional jar tests as well as to compare results to a continuous-flow bench-scale system. Jar tests were performed to identify pH values and alum dosages that are optimal for MP reduction when considering a range of coagulation conditions. The production of large and readily settling aluminum hydroxide (Al(OH)3) floc represented the dominant condition driving MPs removal. However, total MP removal was observed to be lower during continuous-flow trials when compared to jar tests, suggesting that direct extrapolation of results from jar tests may overpredict performance observed at full-scale. Irrespective of microplastic type and size, strong correlations were observed between MP concentration and turbidity reduction, indicating that turbidity may potentially serve as a very useful surrogate. Significant correlations were observed when comparing both floc size, especially 90th percentile floc diameter, and concentration of floc >100 μm to the reduction of MPs.

A multi-analytical approach to investigate DOM dynamics and alum dose control in enhanced coagulation process using wide-ranging surface waters

In this study, enhanced coagulation (EnC) − as a recommended water treatment process for disinfection by-product control − was investigated using jar testing, multi-analytical techniques, and a wide range of surface water sources. In addition to commonly used dissolved organic matter (DOM) concentration indices, DOM characteristics using UV–Vis spectroscopy, fluorescence EEM (fEEM) data, high-performance size exclusion chromatography (HPSEC), as well as turbidity, zeta potential and chlorophyll-a were studied. The results showed similar removal trends for the DOC, A254 and fluorescent DOM (fDOMs) signals with increasing alum dosing. Absorbance at ∼230 nm and fEEM data near Peak C in raw waters showed the highest correlations with enhanced dose. A decrease in weight-average apparent molecular weight following EnC, and a higher coagulability of DOM fractions with higher molecular weight, was noticed. The optimum zeta potential window was found to be −13 to +4 mV for EnC. Charge neutralization is suggested as the dominant mechanism for the EnC process. In addition to providing comprehensive information on the DOM dynamics during the EnC process, this study helps assess the potential of different water quality analysis techniques for EnC process monitoring and alum dose control, particularly using a field-deployable fDOM probe, offering potential for online, real-time applications.