River water was treated by continuous electrocoagulation (EC) for acetaminophen (AP), natural organic matter (NOM measured as UV254), and removal of elements. HRT at 40 min with 0.5 mg/L AP exhibited the best removal efficiency for NOM (55.9%) and AP (53.4%) removal. Except for aluminium, other elements in river water were removed completely. The EC sludge (floating and settled) XRD spectrum showed peaks from AP were reduced, and the few peaks left were from aluminium hydroxide formed by EC. Several bonds in functional groups of AP and NOM were significantly deformed. FESEM images revealed that the sludge was highly porous material as needed for adsorption. EDAX showed that floating sludge had slightly higher carbon compared with settled sludge whereas nitrogen was higher in settled sludge. Other element concentrations in both sludges were similar, proving that water treatment was due to electro-floatation, adsorption, and sweep flocs. Single-factor ANOVA showed significant variance at HRT for NOM (F4.066 = 92.67, p = <0.05) and AP (F4.066 = 20.59, p = <0.05) removal. Variance was significant between treatments at different drug concentrations for NOM (F3.478 = 88.53, p = <0.05) and AP (F3.478 = 529.85, p = <0.05) removal. NOM removal correlated well with AP removal during continuous electrocoagulation.

  • Continuous electrocoagulation with Al electrodes was effective for removal of acetaminophen and NOM from river water.

  • Continuous mode operation was influenced by HRT and acetaminophen at 2 mg/L.

  • Analysis of floating and settled sludge revealed that EC treatment was due to combination of electrofloatation, adsorption, and sweep flocs.

  • NOM can be used as a robust parameter to monitor removal of organic micropollutants

Graphical Abstract

Graphical Abstract
Graphical Abstract

Safe drinking water availability to communities is increasingly becoming challenging, not because of scarcity of technologies but mainly due to diverse pollutant presence in water resources. Both conventional pollutants (colour, turbidity, metals, nutrients, and NOM) and emerging pollutants (pharmaceuticals, industrial chemicals, etc.) render water resources unfit for human use without a significant degree of treatment. Even though water treatment technologies are well developed to address these challenges, the scope remains for improving process efficiency with smaller footprint, lower energy demand (overall from the production of chemicals to waste disposal from water works), and ease of retrofitting. From this perspective, the elimination of NOM and new age contaminants from water is increasingly gaining the attention of the scientific community worldwide.

Several technologies have been researched for effective water treatment and it might be long before many of these can be considered fully ready for implementation in the field. However, one process that can be used for potable water treatment is electrocoagulation (EC) as it offers multiple advantages such as ease of implementation, smaller footprint, non-selective removal of pollutants, low operating cost, lower chemical consumption, easy operation, short operating times, cost-effectiveness, and minimal sludge generation (Garcia-Segura et al. 2017; Lynn et al. 2019). EC can be considered as an alternative treatment over conventional chemical coagulation for drinking water treatment. EC comprises dissolution of the anode and reduction of the cathode by electrolysis, producing metallic ions, metal hydroxides, and metal oxides, respectively, that lead to water treatment. During anodic oxidation, metal ions are released into the solution to be treated and eliminate pollutants by charge neutralization, adsorption, and sweep flocs (Garcia-Segura et al. 2017; Ezechi et al. 2020).

To realize EC's potential for removal of conventional and new age pollutants further research is required. Several reports are available in the literature that highlight the advantages of EC for water treatment and some of these studies have explored the longevity of process efficiency, electrode behaviour etc. at field scale. For instance, Bandaru et al. (2020) studied the longevity and effectiveness of Fe electrodes for groundwater treatment contaminated with arsenic for two years. McBeath et al. (2020) studied the applicability of EC to produce drinking water for remotely located small communities and concluded that an iron-based EC system was effective for NOM removal.

The present study focused on understanding the removal of acetaminophen (AP) (less studied with EC, and one of the most commonly consumed drugs), and NOM from river water using continuous EC. AP is increasingly being detected in natural water bodies (Vo et al. 2019). Major sources of AP are water contaminated with human waste, and domestic and industrial wastewater (Vo et al. 2019). It is reported that long-term exposure to AP may lead to chronic diseases like cancer, endocrine disruption, and the development of drug resistance (Fisher & Curry 2019). NOM in potable water leads to aesthetic issues such as odour, colour, and taste, in addition to its reactions with disinfectant chemicals forming harmful contaminants. NOM in water brings challenges during treatment such as the generation of disinfection by-products, in addition to it serving as a carrier of pesticides, radionuclides, and organometallic complexes (Serrano et al. 2015; Santschi et al. 2017). High concentration of NOM can also be a major factor for fouling in water systems (Zhou et al. 2018; Wongcharee et al. 2019).

The present work aimed to find the efficacy of EC in continuous mode with Al electrodes to remove AP and NOM from river water. The influence of process parameters like residence time and AP dosage on the treatment of river water by a bench-scale continuous flow EC reactor was examined. Data were statistically analysed by correlation–regression, single-factor ANOVA, and pseudo-order kinetic models. EC sludge was analysed using XRD, FTIR, FESEM, and EDAX to understand the dominant reactions involved in water treatment.

Water sampling

The river water was taken daily from a water works situated in an academic institute campus, where water comes from the Jumar River. As AP was not identified in the river water, a stock solution of AP was made (Sigma Aldrich purity 99.9%) in one litre of river water. The working solution for continuous EC experiments was prepared as per the requirement by diluting the stock solution.

Experimental setup and continuous mode EC

EC experimental runs were conducted in a plexiglass vessel in continuous mode with a working volume of 1 L in the laboratory (Figure 1). The setup comprised a continuous flow EC reactor, feed pump, raw water storage unit, sedimentation unit, and a DC power unit (make: APLAB, India). A magnetic stirrer was utilized for agitation at 250 rpm for mixing reactor contents. Based on an earlier batch mode study, the best parameters were used for continuous mode operation such as Al–Al electrode, inter-electrode distance 2 cm, electrode dimension 6.3 cm × 7.9 cm, and 9 V (Kumari & Kumar 2021). Parameters that were tested for continuous EC runs were HRT and drug concentration. The pH was not adjusted nor were any additional electrolytes like NaCl added to the EC system. River water was continuously supplied to the reactor with a peristaltic pump (make: Cole-Parmer) at flow rates resulting in HRT of 10, 20, 30, and 40 min in the EC unit. Drug concentration influence was assessed at best HRT by dosing AP at 0.5, 1, 2, 5, and 10 mg/L. Outflow from the EC reactor was collected in a sedimentation unit (glass beaker), and from there water samples were drawn and filtered (0.45 μm) for physico-chemical analyses. For EC sludge analysis, samples (floating and settled sludge) from the sedimentation unit were collected and dried up at 105 °C in a hot air oven.

Figure 1

Schematic of continuous EC system for river water treatment.

Figure 1

Schematic of continuous EC system for river water treatment.

Close modal

Water and sludge analyses

Physico-chemical parameters of river water were determined using the protocols mentioned in the Standard Methods (APHA 2005). The pH was monitored using a benchtop meter (make: Cole-Parmer). NOM (measured at UV254) was estimated after filtering the collected EC samples using UV-Vis spectrophotometer (make: Shimadzu). AP concentration was determined from filtered samples using a UV-Vis spectrophotometer at 243 nm (Yanyan et al. 2017). To determine the surface characteristics, morphology, and chemical composition of sludge, field emission scanning electron microscopy (FESEM) was used, and energy dispersive X-ray spectroscopy (EDAX) SEM was used to learn the elemental composition (make: Jeol, Japan; JSM-6390LV). XRD analysis was conducted to determine the crystallinity of EC sludges at 40 kV and 30 mA with Cu Kα X-radiation (λ = 1.5418 Å), (make: Rigaku, Japan) at a scan range of 20° to 90° with a scan speed of 1° per min. Fourier Transform Infrared (FTIR) spectroscopy was applied in the range 4,000–450 cm−1 in transmission mode (make: Shimadzu, Japan) for EC sludge characterization.

Data analyses and statistical tests

EC experiments were conducted until attainment of steady-state conditions resulting in minimum variations in the treated water quality. Multiple runs for a single experiment were carried out and for data interpretation the average value of the last three stable readings were used. The removal efficiency was calculated using Equation (1):
(1)
where Ci and C0 are initial and final pollutant concentrations in the river water. Correlation–regression analyses on AP and NOM elimination were performed to know the association between their respective removal. Graphs, tables, and statistical analysis were made from the data processed on MS Excel, and Sigma Plot. Single-factor ANOVA was performed between treatments (HRT and AP concentration) to determine the statistical significance, and if significance was found then Tukey's post hoc analysis was carried out to determine the difference between groups within the treatment.

Reaction kinetics

The best kinetic model was determined using correlation–regression coefficient data (R2). Kinetics of the EC reaction for AP removal was performed for several concentrations tested. To the EC data, two pseudo kinetic models were applied to find the reactions' kinetic constants (Wu et al. 2019). The Lagergren model pseudo-first-order equation was used as shown below:
(2)
The expression used for the pseudo-second-order model is shown below:
(3)
where qt and qe (mg · g−1) reflect the quantities of AP sorbed on EC reaction contents at time t and steady-state, t is EC time, k1 (min−1) is the pseudo-first-order reaction rate constant, and k2 (min·g·mg−1) is the pseudo-second-order rate constant.

River water quality

The river Jumar is a non-perennial river that receives a significant discharge of solid and liquid waste. Monsoon in the study area is from June to September, which results in somewhat better river water quality. The present study was conducted from the water sampled during the dry season (January to May) and during this period water quality remains poor. River water had high COD, NOM, and some elements that are of concern (Table 1).

Table 1

Physico-chemical characteristics of river water before and after EC treatment

Sl. no.ParametersRaw water (n = 3, mean ± SD)EC treated water (n = 3, mean ± SD)BIS 10500*
pH 7.01 ± 0.1 7.4 ± 0.01 6.5–8.5 
EC (mS/cm) 0.35 ± 0.01 0.29 ± 0.01 – 
Turbidity (NTU) 55 ± 20 5 ± 1 
NOM (UV254 absorbance) 0.20 0.09 – 
Total hardness (mg/L as CaCO3200 ± 26 170 ± 18 200 
Total alkalinity (mg/L as CaCO3230 ± 14 190 ± 23 200 
COD (mg/L) 240 ± 3 105 ± 5 – 
Al (mg/L) 0.32 ± 0.12 0.54 0.2 
As (mg/L) 0.08 ± 0.004 n.d. 0.01 
10 Fe (mg/L) 0.10 ± 0.006 0.01 0.3 
11 Se (mg/L) 0.03 ± 0.003 n.d. 0.01 
12 Zn (mg/L) 0.01 ± 0.001 n.d. 15 
Sl. no.ParametersRaw water (n = 3, mean ± SD)EC treated water (n = 3, mean ± SD)BIS 10500*
pH 7.01 ± 0.1 7.4 ± 0.01 6.5–8.5 
EC (mS/cm) 0.35 ± 0.01 0.29 ± 0.01 – 
Turbidity (NTU) 55 ± 20 5 ± 1 
NOM (UV254 absorbance) 0.20 0.09 – 
Total hardness (mg/L as CaCO3200 ± 26 170 ± 18 200 
Total alkalinity (mg/L as CaCO3230 ± 14 190 ± 23 200 
COD (mg/L) 240 ± 3 105 ± 5 – 
Al (mg/L) 0.32 ± 0.12 0.54 0.2 
As (mg/L) 0.08 ± 0.004 n.d. 0.01 
10 Fe (mg/L) 0.10 ± 0.006 0.01 0.3 
11 Se (mg/L) 0.03 ± 0.003 n.d. 0.01 
12 Zn (mg/L) 0.01 ± 0.001 n.d. 15 

n.d. – not detected.

*Acceptable drinking water standards in India.

**EC treatment conditions: Al–Al electrodes, inter-electrode distance 2 cm, 9 V, HRT 40 min, AP – 1 mg/L.

Effect of HRT on continuous EC

Among all the parameters that influence the EC efficiency in continuous mode, HRT plays an important role. HRT is one of the main parameters that distinguish continuous mode systems from batch mode. For instance, in batch mode following the generation of coagulants, hydroxide ions, and hydrogen gas bubbles, reactions such as adsorption, sweep flocs, and flotation occur that lead to the elimination of a variety of contaminants from water during EC. We hypothesized that following electrolysis of electrodes in the EC reactor there will be the presence of coagulants and other conditions necessary for water treatment, and the system can be operated in continuous mode where the reaction mixture forms and following the sedimentation step could lead to treatment efficiency similar to that of batch mode. Four different HRT were assessed to validate the hypothesis.

The pH increased marginally at all the HRT in the range of 0.2 to 0.5 units. Final pH ranged from 7.4 to 7.7 at different HRT (Figure S1a, Supplementary Information). The pH increase is a sign that the EC process was effective in continuous flow mode. The pH increases, when compared with batch systems, were lower, which can be explained by the continuous flow of water and lower electrical conductivity of the bulk solution. In this case, electrical conductivity was not adjusted to aid better conductance of electrical charge. COD removal was 27.1%, 36.6%, 55.3% and 65.6% at 10 min, 20 min, 30 min and 40 min HRT, respectively (Figure S1b). Data shows that for considerable COD removal, higher HRT was required, also indicating the need for subsequent water treatment steps such as filtration.

NOM removal was 17.5% at 10 min, 20.4% at 20 min, 44.7% at 30 min, and 58% at 40 min HRT (Figure 2). A substantial difference in NOM removal could be observed when the HRT was >20 min, which along with COD indicates the recalcitrant nature of organic pollutants present in the river water. Similar results of NOM removal (∼60%) from surface water using EC with steel electrodes have been reported earlier (Lynn et al. 2019). These authors noted that a higher concentration of NOM in surface water also results in higher removal of NOM with EC. AP removal was 31.8% at 10 min, 37.1% at 20 min, 42.4% at 30 min, and 46.8% at 40 min HRT (Figure 2). In general, 40 min HRT was effective for removal of COD, NOM, and AP and at this HRT, sludge volume was 25 cm3. Such a trend with HRT is because as the flow rate increases, the reaction time of coagulants with solutes decreases, resulting in lower treatment efficiency. Consequently, the rate and extent of formation of Al–AP complexes reduce, and at high HRT more metals come into bulk solution and coagulant concentration gradually increases, leading to better removal of contaminants from water. This fact can be validated by theoretical estimation of coagulant released into the bulk solution in EC treatment using Faraday's law. The amount of coagulant released was 2.4 mg/L (10 min HRT), 4.6 mg/L (20 min HRT), 7.0 mg/L (30 min HRT) and 9.4 mg/L (40 min HRT). Preliminary cost analysis of continuous mode EC at different HRT was calculated following the literature (Thakur & Mondal 2017). Based on the experimental conditions applied, the operational cost was estimated (electrode consumption + energy demand) at US$ 0.03/m3 (10 min HRT), US$ 0.05/m3 (20 min HRT), US$ 0.08/m3 (30 min HRT), and US$ 0.10/m3 (40 min HRT) for river water treatment.

Figure 2

Mean (n = 3, ±SD) variations in (a) NOM and (b) acetaminophen elimination with continuous electrocoagulation for river water treatment at different HRT. (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V.)

Figure 2

Mean (n = 3, ±SD) variations in (a) NOM and (b) acetaminophen elimination with continuous electrocoagulation for river water treatment at different HRT. (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V.)

Close modal

Effect of AP concentration on continuous EC

Continuous EC was performed further at 40 min HRT, which produced the best conditions for river water treatment, and for removal of AP different concentrations were tested in the range of 0.5 to 10 mg/L. The pH increased from the initial value across all the concentrations tested and the increase ranged between 0.3 and 0.9 units (Figure S2). The COD removal achieved at the end of EC treatment was 56.8%, 55.9%, 53.1%, 52.1%, and 46.6% at 0.5, 1, 2, 5 and 10 mg/L, respectively. The COD removal achieved in continuous EC mode was similar to earlier reported work in batch mode (Kumari & Kumar 2021). NOM removal was 55.9% at 0.5 mg/L, 48.7% at 1 mg/L, 47.9% at 2 mg/L, 39.4% at 5 mg/L and 23.9% at 10 mg/L (Figure 3(a)). AP removal was 53.4% at 0.5 mg/L, 45.7% at 1 mg/L, 35.9% at 2 mg/L, 33.5% at 5 mg/L and 29.6% at 10 mg/L (Figure 3(b)). Both NOM and AP removal at different concentrations increased rapidly until 30 min of treatment and afterward the removal was gradual until attaining a steady state. The removal efficiency of NOM and AP was reduced with an increase in drug concentration. Comparable results of the influence of initial concentration on performance efficiency have been reported earlier for boron elimination from water by continuous mode EC with Al electrode (Ezechi et al. 2020).

Figure 3

Mean (n = 3, ±SD) variations in (a) NOM and (b) acetaminophen elimination with continuous electrocoagulation for river water treatment at different acetaminophen concentrations. (EC conditions: Al–Al, 2 cm electrode distance, 9 V, HRT 40 min.)

Figure 3

Mean (n = 3, ±SD) variations in (a) NOM and (b) acetaminophen elimination with continuous electrocoagulation for river water treatment at different acetaminophen concentrations. (EC conditions: Al–Al, 2 cm electrode distance, 9 V, HRT 40 min.)

Close modal

NOM, AP, and element removal by continuous EC

Elemental analysis of supernatant samples showed that initially Al, As, Se, Fe, and Zn were present in the river water (Table 1). Except for Al, the other elements were removed from the river water as the EC treatment time increased and concentrations were within the prescribed water standards. Al concentration increased slightly with time, which is expected due to oxidation of the anode. Other studies have also reported that the key element based on the electrode used will lead to an increase in the water, and this implies that there will be additional treatment steps such as filtration that will be needed before the water can be used (Heffron et al. 2016). Al present after EC treatment can be effectively removed by adding polymers such as polyelectrolyte followed by conventional sand and activated-carbon-based filtration units.

To understand the mechanism of removal of AP, NOM, and elements from river water with continuous EC, sludge samples both which settled and floated were analysed. Sludge floating could be linked with the evolution of H2 gas at the cathode during EC (Singh et al. 2013; Mahesh et al. 2016). A gentle stirring with a glass rod led to degassing and the floating sludge settled quickly. For comparison, both floating and settled EC sludge were analysed individually, to determine whether there were any differences in their composition.

To determine the crystallinity, sludge samples were subjected to XRD spectrum scanning at 2θ from 10° to 70° (Figure 4(a)). XRD spectra revealed that several peaks of AP were considerably reduced as seen from the sludge samples. The XRD spectrum of shallow peaks exhibited the amorphous nature of the EC sludge. The peaks after treatment in settled as well as floating sludge were at 2θ = 29°, 31°, 36°, 39°, 43°, 45°, and 48° and were due to the presence of aluminium hydroxide flocs (ICDD database) in the EC sludge (Thakur & Mondal 2017; Kumari & Kumar 2021). Aluminium generated from the anode during the EC process undergoes rapid hydrolysis to produce numerous monomeric, dimeric, trimeric, and polymeric forms of Al with OH ions (Mouedhen et al. 2008).

Figure 4

(a) XRD and (b) FTIR spectrum of acetaminophen (control) and sludge from EC treatment from the base of the reactor (settled) and top of the reactor (floating). (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V, HRT 40 min, acetaminophen 1 mg/L.)

Figure 4

(a) XRD and (b) FTIR spectrum of acetaminophen (control) and sludge from EC treatment from the base of the reactor (settled) and top of the reactor (floating). (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V, HRT 40 min, acetaminophen 1 mg/L.)

Close modal

The FTIR spectrum showed significant changes due to chemical bond disruptions in AP following the reactions of EC products and impurities present in the river water (Figure 4(b)). Both settled and floating sludge showed similar peak profiles following EC treatment, however, settled sludge had lower transmission compared with floating sludge. Peaks at 3,595 cm−1 and at 3,311 cm−1 for AP were completely deformed signifying removal of the phenolic group in AP and NOM which could be attributed to a combination of dominant reactions of EC such as charge neutralization, complexation, flotation and adsorption on Al(OH)3 flocs (Ghernaout et al. 2014; Garcia-Segura et al. 2017). Peaks in the 1,800 to 2,900 cm−1 range signifying carboxylic acid and derivates (O-H bond) from drug and NOM were completely deformed. Most peaks from 500 to 2,000 cm−1 and the few new peaks in this range highlighted oxidized nitrogen species presence (1,589 cm−1 – N = O) and (1,286 cm−1 – N-O) post-treatment. The main reaction can be seen from the slight peak in both sludges at 1,439 cm−1 that indicated the formation of an H-bond between drug tested and Al(OH)3 flocs (Quesada et al. 2019; Kumari & Kumar 2021). The peak at 1,233 cm−1 was due to C = O bond deformation following treatment, strengthening the reasoning of adsorption as the dominant process on aluminium hydroxide flocs as the main reaction for removal.

The textural surface properties of EC-process-generated sludge were investigated by FESEM (Figure 5). It can be observed that on the sludge surface several pores could be seen which could allow transfer of AP and NOM leading to its adsorption on aluminium hydroxide flocs. Both floating and settled sludge exhibited good surface characteristics typical of adsorbed species on EC-reaction-linked products. The elemental composition of settled sludge and floating sludge produced from the EC treatment of river water is presented in Table 2. EDAX results highlighted the presence of organic and inorganic contaminants in the EC sludge. Top layer sludge contained a slightly higher concentration of C compared with settled sludge whereas N showed an opposite result. Other elements in both top and settled sludge were at almost the same levels indicating that the removal of COD and micropollutants occurred through a combination of electro-floatation, and electrocoagulation. Top layer sludge or scum formation was due to floatation as a lesser density of flocs was generated by gases that evolved during the EC treatment. The sludge contained a significant amount of carbon and nitrogen, which was expected as the river water, due to severe pollution, had high COD and NOM. Similar results following EDAX analysis on EC sludge (floating and settled sludge) produced from pulp and paper mill wastewater treatment in continuous mode with Fe as electrodes have been reported earlier (Mahesh et al. 2016).

Table 2

EDAX characteristics of sludge from continuous electrocoagulation (floating and settled sludge) for river water treatment

Sl. no.ElementsFloating sludge (weight %)Settled sludge (weight %)
Al 1.2 1.3 
62.6 55.5 
19.9 24.5 
8.5 9.2 
0.05 0.2 
Ca 0.4 0.4 
Mg 0.2 0.2 
Cl 0.3 0.1 
Sl. no.ElementsFloating sludge (weight %)Settled sludge (weight %)
Al 1.2 1.3 
62.6 55.5 
19.9 24.5 
8.5 9.2 
0.05 0.2 
Ca 0.4 0.4 
Mg 0.2 0.2 
Cl 0.3 0.1 
Figure 5

FESEM analysis of (a) settled sludge and (b) top sludge from EC following river water treatment. (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V, HRT 40 min, acetaminophen 1 mg/L.)

Figure 5

FESEM analysis of (a) settled sludge and (b) top sludge from EC following river water treatment. (EC conditions: electrodes Al–Al, 2 cm electrode distance, 9 V, HRT 40 min, acetaminophen 1 mg/L.)

Close modal

EC works mainly through charge neutralization, complexation, flotation and adsorption, and the bulk solution pH governs the domination of one reaction over another (Bernal et al. 2017; Kumari & Kumar 2021). EC solution pH in the present study was >7.0 and at this pH the dominant mechanisms for removal of AP, NOM and metals were amorphous Al(OH)3 formation and subsequent reactions (Kumari & Kumar 2021). That this is the mechanism can be substantiated from the predominance zone diagram of Al species in the aqueous medium and the data from XRD, FTIR, FESEM, and EDAX analysis of the EC sludge, which agrees with the literature (Singh et al. 2013; Kim et al. 2014; Garcia-Segura et al. 2017).

Correlation between NOM and acetaminophen removal

The present study checked whether NOM removal can be correlated to monitor the removal of AP. Correlation plots between NOM and AP at different concentrations revealed that there was a significant relationship (Figure S3). Significant positive correlation existed between NOM and AP elimination from bulk solution at all the concentrations tested. The key values of the correlation–regression analysis are: 0.5 mg/L (r = 0.89, R2= 0.79, n = 3, p = <0.05), 1.0 mg/L (r = 0.99, R2= 0.99, n = 3, p = <0.05), 2.0 mg/L (r = 0.92, R2= 0.85, n = 3, p = <0.05), 5.0 mg/L (r = 0.99, R2= 0.99, n = 3, p = <0.05), and 10.0 mg/L (r = 0.84, R2= 0.71, n = 3, p = <0.05). Earlier studies showed that NOM can be used as a good parameter to follow the removal of other emerging contaminants (Wert et al. 2009; Kumari & Kumar 2021).

In addition to the above finding, it must be stated that NOM removal is complicated from natural waters during treatment as it exhibits both spatial and temporal variations across sites and within sites as well (Sillanpää et al. 2018). For instance, NOM monitored during the study period for three months from the river Jumar showed that it exhibited daily fluctuations (Figure S4). Due to these facts, the efficient removal of NOM from potable water sources is necessary and there is a need for technologies that can be easy to implement in existing water treatment plants. EC can be a suitable process for application in large water treatment plants or as a treatment solution for smaller communities as a decentralized system.

Continuous EC reaction kinetics and statistical analyses

Data from continuous EC at different AP concentrations were fitted in the pseudo-first-order and pseudo-second-order models. AP removal data exhibited a weak fit in the pseudo-first-order model whereas it was an excellent fit in the pseudo-second-order model. Based on the coefficient of determination (r2) values and qcalculated values, it was indicated that the pseudo-second-order reaction model was an excellent fit for the data (Table 3, Figure S5). Earlier work on EC has also reported the pseudo-second-order model to predict the reaction kinetics, which implies that adsorption (chemisorption) is the dominant pathway for pollutant removal during water treatment (Khatibikamal et al. 2010; Wu et al. 2019).

Table 3

Pseudo-second-order model kinetic constants for acetaminophen removal following EC treatment of river water

Acetaminophen concentrationqexperimental (mg/g)qcalculated (mg/g)k2 (min·g·mg−1)R2
0.5 mg/L 7.26 7.35 0.039 0.941 
1.0 mg/L 12.21 12.09 0.027 0.968 
2.0 mg/L 19.71 19.72 0.013 0.933 
5.0 mg/L 45.21 44.84 0.006 0.938 
10.0 mg/L 79.63 79.37 0.003 0.951 
Acetaminophen concentrationqexperimental (mg/g)qcalculated (mg/g)k2 (min·g·mg−1)R2
0.5 mg/L 7.26 7.35 0.039 0.941 
1.0 mg/L 12.21 12.09 0.027 0.968 
2.0 mg/L 19.71 19.72 0.013 0.933 
5.0 mg/L 45.21 44.84 0.006 0.938 
10.0 mg/L 79.63 79.37 0.003 0.951 

AP and NOM removal data from EC was tested using single-factor ANOVA to determine the statistical significance at different drug concentrations and HRT. There was statistically significant variance between treatments with different drug concentrations for NOM (F3.478 = 88.53, p = <0.05) and AP (F3.478 = 529.85, p = <0.05). Pairwise comparisons of means using the post hoc test showed that NOM removal was significant at all the concentrations tested except for treatment between 1 and 2 mg/L whereas for AP removal pairwise comparisons pointed that there was a significant difference between all the concentrations tested. Variance between means of different groups was statistically significant at the HRT tested for NOM (F4.066 = 92.67, p = <0.05) and AP (F4.066 = 20.59, p = <0.05) removal. Pairwise comparisons of means at different HRT tested with the post hoc test showed that for NOM removal the HRT needed was higher than 30 min and for AP removal the higher than 20 min was required.

Table 1 presents some key water quality parameters before and after continuous EC treatment. EC was able to show considerable water treatment in a single step, and the data shows that there will be a requirement of a further treatment step (filtration) before the water can meet drinking water standards. Residual Al post-EC treatment was present at 0.54 mg/L, which is greater than the drinking water standards, and it is not uncommon to find such residual coagulant concentration in EC. Additional steps such as addition of coagulant aids followed by filtration treatment will be able to remove the residual Al and other water quality parameters as has been reported (Heffron et al. 2016). This study showed that EC in continuous mode has potential for integration in existing water treatment plants. However, long-term studies are needed on the operational costs (including sludge disposal), longevity of electrodes (effect of polarity reversal), limiting electrode passivation, regenerating electrodes post-treatment for continuous application and Al-rich sludge disposal options.

A continuous EC process was tested for river water treatment for removal of AP, NOM, and other elements. A continuous EC reactor followed by a sedimentation unit was efficient for elimination of NOM and micropollutants from water. HRT and drug concentration were important process-performance-influencing parameters. HRT at 30 and 40 min was good to treat river water, whereas drug removal was effective up to 1 mg/L. Sludge analysis showed that the removal of NOM and micropollutants was due to the collective effect of electro-floatation, adsorption, and sweep flocs (mainly due to aluminium hydroxide flocs). The sludge formed during the process is separated into two: floating sludge and settled sludge, due to density differences. The reaction kinetics followed pseudo-second-order indicating adsorption as the key mechanism for water treatment. Continuous EC output was assessed through single-factor ANOVA and the results were significant. NOM removal showed a good correlation with AP removal, which indicated its potential as a surrogate to monitor the treatment of organic micropollutants. Further studies at the pilot scale will help to assess the process's performance, longevity, and stability in the long run. Present results appear promising to explore further the integration of EC into existing water treatment plants.

The authors thank Birla Institute of Technology, Mesra, Ranchi, for the facilities provided for this research work. The support of the central instrumentation facility at Birla Institute of Technology, Mesra, is also acknowledged. The first author acknowledges the institute fellowship and TEQIP-III assistance for her PhD program.

All relevant data are included in the paper or its Supplementary Information.

APHA, AWWA, WEF
2005
Standard Methods for the Examination of Water and Wastewater
, 21st edn.
APHA/AWWA/WEF
,
Washington, DC, USA
.
Fisher
E. S.
&
Curry
S. C.
2019
Evaluation and treatment of acetaminophen toxicity
.
Adv. Pharmacol.
85
,
263
272
.
Ghernaout
D.
,
Irki
S.
&
Boucherit
A.
2014
Removal of Cu2+ and Cd2+, and humic acid and phenol by electrocoagulation using iron electrodes
.
Desalin. Water Treat.
52
,
3256
3270
.
Khatibikamal
V.
,
Torabian
A.
,
Janpoor
F.
&
Hoshyaripour
G.
2010
Fluoride removal from industrial wastewater using electrocoagulation and its adsorption kinetics
.
J. Hazard Mater.
179
,
276
280
.
Mahesh
S.
,
Garg
K. K.
,
Srivastava
V. C.
,
Mishra
I. M.
,
Prasad
B.
&
Mall
I. D.
2016
Continuous electrocoagulation treatment of pulp and paper mill wastewater: operating cost and sludge study
.
RSC Adv.
6
,
16223
16233
.
McBeath
S. T.
,
Mohseni
M.
&
Wilkinson
D. P.
2020
Pilot-scale iron electrocoagulation treatment for natural organic matter removal
.
Environ. Tech.
41
,
577
585
.
Mouedhen
G.
,
Feki
M.
,
De Petris Wery
M.
&
Ayedi
H. F.
2008
Behavior of aluminum electrodes in electrocoagulation process
.
J. Hazard. Mater.
150
,
124
135
.
Quesada
H. B.
,
Cusioli
L. F.
,
Bezerra
C. d. O.
,
Baptista
A. T. A.
,
Nishi
L.
,
Gomes
R. G.
&
Bergamasco
R.
2019
Acetaminophen adsorption using a low-cost adsorbent prepared from modified residues of Moringa oleifera Lam. seed husks
.
J. Chem. Technol. Biotechnol.
94
,
3147
3157
.
Serrano
M.
,
Montesinos
I.
,
Cardador
M. J.
,
Silva
M.
&
Gallego
M.
2015
Seasonal evaluation of the presence of 46 disinfection by-products throughout a drinking water treatment plant
.
Sci. Total Environ.
517
,
246
258
.
Sillanpää
M.
,
Ncibi
M. C.
,
Matilainen
A.
&
Vepsäläinen
M.
2018
Removal of natural organic matter in drinking water treatment by coagulation: a comprehensive review
.
Chemosphere
190
,
54
71
.
Vo
H. N. P.
,
Le
G. K.
,
Hong Nguyen
T. M.
,
Bui
X. T.
,
Nguyen
K. H.
,
Rene
E. R.
,
Vo
T. D. H.
,
Thanh Cao
N.-D.
&
Mohan
R.
2019
Acetaminophen micropollutant: historical and current occurrences, toxicity, removal strategies and transformation pathways in different environments
.
Chemosphere
236
,
124391
.
Wert
E. C.
,
Rosario-Ortiz
F. L.
&
Snyder
S. A.
2009
Using ultraviolet absorbance and color to assess pharmaceutical oxidation during ozonation of wastewater
.
Environ. Sci. Technol.
43
,
4858
4863
.
Zhou
Z.
,
Yang
Y.
,
Li
X.
,
Li
P.
,
Zhang
T.
,
Lv
X.
,
Liu
L.
,
Dong
J.
&
Zheng
D.
2018
Optimized removal of natural organic matter by ultrasound-assisted coagulation of recycling drinking water treatment sludge
.
Ultrason. Sonochem.
48
,
171
180
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Supplementary data