Water treatment using nano-materials can have a significant impact due to its surface properties. Coagulation techniques were studied by using 3 mL/L of 0.5% of different coagulants (polyacrylamide, poly aluminum chloride (PAC), ferric chloride, aluminum sulfate, and nanocellulose). Results indicated that the turbidity removal efficiency were 91.6%, 93.04%, 95.2%, 95.4%, and 99.4%, respectively. Treatment of water samples collected from the Ismailia Canal, the Damietta branch of the Nile Delta, and a wastewater treatment plant located in Cairo (Egypt) using nanocellulose fibers was studied. For the Ismailia Canal sample, the removal of turbidity, chemical oxygen demand (COD), biological oxygen demand (BOD), and phosphorous were 96%, 83.3%, 100%, and 100%, respectively. For the Damietta branch sample, the removal of turbidity, COD, BOD, and phosphorous were 87.5%, 81.3%, 88.9%, and 99.1%, respectively. For the wastewater treatment plant sample, the removal of turbidity, COD, BOD, and phosphorous were 86.4%, 91.96%, 92.86%, and 91.74%, respectively. Nanocellulose-nano zero-valent iron composite (NC-nZVI) was investigated for phosphorous removal at different operating conditions. Results showed phosphorous removal efficiencies of 91 and 100% for initial phosphate concentrations of 10 and 1 mg PO43– P/L, respectively. Different isothermal analyses were performed for monolayer and multilayer adsorption processes.
Integrated Efficiency of Using Nanocellulose-Nano Zero Valent Iron Composite in Water Treatment
Jian-Hui Wang,a,b Mohamed S. Mahmoud,c,* and Ahmed S. Mahmoud d
Water treatment using nano-materials can have a significant impact due to its surface properties. Coagulation techniques were studied by using 3 mL/L of 0.5% of different coagulants (polyacrylamide, poly aluminum chloride (PAC), ferric chloride, aluminum sulfate, and nanocellulose). Results indicated that the turbidity removal efficiency were 91.6%, 93.04%, 95.2%, 95.4%, and 99.4%, respectively. Treatment of water samples collected from the Ismailia Canal, the Damietta branch of the Nile Delta, and a wastewater treatment plant located in Cairo (Egypt) using nanocellulose fibers was studied. For the Ismailia Canal sample, the removal of turbidity, chemical oxygen demand (COD), biological oxygen demand (BOD), and phosphorous were 96%, 83.3%, 100%, and 100%, respectively. For the Damietta branch sample, the removal of turbidity, COD, BOD, and phosphorous were 87.5%, 81.3%, 88.9%, and 99.1%, respectively. For the wastewater treatment plant sample, the removal of turbidity, COD, BOD, and phosphorous were 86.4%, 91.96%, 92.86%, and 91.74%, respectively. Nanocellulose-nano zero-valent iron composite (NC-nZVI) was investigated for phosphorous removal at different operating conditions. Results showed phosphorous removal efficiencies of 91 and 100% for initial phosphate concentrations of 10 and 1 mg PO43-– P/L, respectively. Different isothermal analyses were performed for monolayer and multilayer adsorption processes.
Keywords: Nanocellulose fibers; Nano zero-valent iron; Water pollutants; Flocculants; Climate change; Wastewater management
Contact information: a: National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing 400067, China; b: Chongqing South-to-Thais Environmental Protection Technology Research Institute Co., Ltd., Chongqing 400069, China; c: Sanitary and Environmental Engineering Institute (SEI), Housing and Building National Research Center (HBRC), P. O. Box 1770, Cairo, Egypt; d: Scientific Research Development Unit, Egyptian Russian University (ERU), Badr, Egypt; *Corresponding author: firstname.lastname@example.org
Growth and rapid urbanization present the need to search for new technologies that keep water sources safe without any kind of pollution (Abdel-Gawad et al. 2016; Mostafa et al. 2017; Su et al. 2019). The main causes of freshwater pollution can be linked directly to the continued release of coarse toxic industrial waste and effluents. Water sources have different characteristics in terms of water quality. The important factors that affect water quality are organic, inorganic, and biological contaminants (Su et al. 2020; Abdelghany et al. 2021). Hence, the removal of these pollutants that feed into water systems is a task of concern. Dissolved oxygen (DO), pH, turbidity (NTU), chemical oxygen demand (COD), biological oxygen demand (BOD), phosphorous, and total dissolved salts (TDS) are the most influencing parameters in water quality (Cumbal and SenGupta 2005; Bezbaruah et al. 2011; Almeelbi and Bezbaruah 2012; Diallo et al. 2013; Mahmoud et al. 2021a). The deviation of these parameter concentrations out of the normal ranges causes water eutrophication, the proliferation of algae, and several diseases to human and aquatic bodies. Water treatment systems depend on different technologies, mainly, adsorption, coagulation, precipitation, and disinfection (Fan et al. 2018; Farag et al. 2018). Various materials are used in water treatment including coagulants and polymers (Toth 1971; Jayaraman et al. 2007; Hill 1910). The effective methodology with low costs, availability, and eco-friendly characteristics is a criterion in sustainable measurements.
Phosphorus represents organic phosphates, orthophosphates, and polyphosphates (Khan et al. 1997). The main cause of eutrophication is the increase in phosphorus concentrations. The source of phosphorous could be from phosphate rocks as well as from some solid wastes (Koble and Corrigan 1952; Knight et al. 2013). Eutrophication, besides its environmental impact, has some economic merits as a fertilizer (Yuvakkumar et al. 2011; Mahmoud et al. 2018).
Cellulose is one of the most abundant biodegradable polymers. It has a high effective hydroxyl group ratio. Cellulose consists of repeated β-D-glucopyranose units. Various techniques have been used to prepare nanocellulose fibers, namely cellulose nanocrystals and nanofibrillated cellulose. Plant cellulose is mainly composed of amorphous chains and crystalline domains. Nanocellulose is produced by acid hydrolysis (such as sulfuric, hydrochloric, and phosphoric acids) of the cellulose fibers. Nanocellulose obtained from plants is 5 to 70 nm in width and 100 to 250 nm in length. The type of acids used can affect the colloidal stability of nanocellulose. Nanocellulose can be used as catalytic degradation and disinfection as well as high/ active surface area and high aspect ratio as good flocculants (Mahmoud et al. 2019a,b,c). The high mechanical strength of nanocellulose increases stiffness and acid/base resistance, and these attributes give it the possibility for use in different operating conditions. Also, nanocellulose has high surface free energy that can decrease bio-fouling. The adjusting of the medium pH increases the separation of nanocellulose from its colloidal behavior. Many studies have considered the effectiveness of nanocellulose effectiveness for wastewater treatment, including dyes and metal sorption and also the adjacent material in filters and membranes in water treatment systems (Mahmoud et al. 2017a,b).
Nanocatalytic materials, such as zero-valence metal, semiconductor materials, and bimetallic nanoparticles, are used in wastewater and water treatment due to their high reactivity and surface area (Meda et al. 2007). Several studies have been conducted to study the effect of using magnetic nanocomposites, such as nanocellulose-nano zero-valent iron (NC-nZVI) in the removal of inorganic cations and anions, as well as organic compounds, as shown in Fig. 1 (Almeelbi and Bezbaruah 2012; Mahmoud and Mahmoud 2021b).
Fig. 1. Contaminants removal behavior by nanocellulose-nano zero-valent iron composite
This paper focused on the use of nanocellulose as a flocculent agent for the treatment of contaminants in water. Nanocellulose was compared with other agents, analyzing nanocellulose removal efficiency of water contaminants and the integrated behavior of NC-nZVI, on phosphorous removal under different operating conditions. Also, the adsorption mechanisms were estimated by applying nonlinear adsorption isotherm models. Finally, regression analysis was employed to detect the response surface relations between the operating variables and removal efficiency.
The materials used in this work included ferric chloride hexahydrate (FeCl3.6H2O, 98.5% pure, Arabic laboratory equipment Company), sodium borohydride (NaBH4, 99% pure, Win lab Company), ethanol (C2H5OH 95%, World Co. for sub & med industries), potassium orthophosphate (KH2PO4, 99% pure, ADWIC), sodium hydroxide (NaOH, 99% pure, Oxford co.), sulfuric acid (H2SO4, 95-97%, Honeywell), stannous chloride (TiCl2, 99.5% pure, Loba Chem), phenolphthalein, ammonium molybdate (99.9% pure, P.O.C.H., Polska, Poland), ammonium persulphate extra pure, 95.5% pure, Oxford), office paper (source of cellulose).
Preparation of nanocellulose
Office paper cellulose was pretreated using 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO), periodate–chlorite, and 2,3-epoxypropyl-trimethylammonium chloride. Using the sulfuric acid hydrolysis method, nanocellulose fibers were prepared with high colloidal stability because of the presence of sulfate ester groups on their surface.
Preparation of nZVI
Synthesis of nZVI was done using ferric chloride dissolved in ethanol 4:1 (v/v) and sodium borohydride black. Solid particles of nZVI were formed as in Eq. 1 (Bezbaruah et al. 2011). To prevent the rapid oxidation of nZVI, washing with absolute ethanol was completed. Finally, the synthesized nZVI was dried overnight at 50 °C (Cumbal and SenGupta 2005).
2FeCl3 + 6NaBH4 + 18H2O 2Fe0 + 21H2 + 6B (OH)3 + 6NaCl (1)
The prepared NC-nZVI sample was investigated using a Philips Quanta 250 FEG device manufactured by Philips Electronics Company, USA. This was utilized for performing the scanning electron microscopy (SEM) analysis. The SEM instrument operates at a magnification of 80,000x and a voltage of 20 KV. FTIR was analyzed before treatments using FT/IR-6100typeA, S/N A009061020 with a standard light source and TGS detector. The FTIR resolution was 8 cm-1, using a 10000 Hz filter. The SEM and FTIR instruments were located at the National Research Center (NRC). Particle size distribution analysis was conducted for dried samples by using Microvision (particle size measurement) located at CID Company for pharmaceutical industries, Egypt using µ u-tech production, and model VGA-410 France.
Sample collection sites
Samples were collected from contaminated sites in plastic bottles. All analyses were carried out within 8 h of collection at Housing and Building National Research Center (HBRC) laboratories (Cairo, Egypt) (Bezbaruah et al. 2011). Three raw water samples were collected. These came from Ismailia Canal, located east of the Delta, at latitude 30°06’41” N and longitude 31°16’22” E, from the Damietta branch at latitude 30°36’15” N and longitude 31°15’39” E, and from a wastewater treatment plant after the primary screens (WWTP) which is located at Helwan Governorate, Egypt.
Batch adsorption studies
The removal efficiency was studied using a batch technique. The concentration of parameters was measured according to (APHA 2017). The sorption percentage was calculated using Eq. 2 and uptake was calculated using Eq. 3.
Sorption (%) = (Co − Ce/Co) × 100 (2)
where Co is the initial concentration (mg/L) and Ce is the equilibrium concentration (mg/L).
qe (mg/g) = ((Co − Ce) V)/ m (3)
where Qe is the equilibrium adsorption capacity (mg/g), V is the volume of solution (L), and m is the dry weight of the adsorbent (g).
Table 1. Nonlinear Equations of Isotherm Models
Isothermal studies were performed for the monolayer and multilayer adsorption process using nonlinear equations including the Freundlich, Langmuir, Redlich–Peterson, Hill, Sips, Khan, Toth, Koble–Corrigan, and Jovanovich equations, as shown in Table 1.
Statistical analysis: Response surface methodology
A linear regression analysis was employed to estimate the relation between removal efficiency and operating conditions (pH, dose, contact time, stirring rate, and concentration) on phosphate removal efficiencies as presented in the general equation, Eq. 4. The coefficient of determination statistical measure (R2 value) was used to evaluate the accuracy of the model. The t-test was also used to assess the statistical significance by looking at the p values,
where Y(PO43-) is the predicted response of removal efficiency (%).
RESULTS AND DISCUSSION
Treatment of wastewater with NTU 125 and total suspended solids (TSS) 625 (mg/L) was done using different coagulating agents. Measuring turbidity and total suspended solids (TSS) after treatment was done using a jar test mixing rate of 100 rpm for 5 min, 25 rpm for 15 min, and settling for 10 min. Different doses (0.5, 1, 1.5, 2.0, 2.5, and 3.0 mL/L) of 5g/L from each stalk PAC (poly aluminum chloride), polyacrylamide, ferric chloride, aluminum sulfate, and nanocellulose (NC), as shown in Fig. 2.
Fig. 2. Effect of different flocculants agents on A) TSS Removal and B) Turbidity removals
Nanocellulose Removal Efficiency of Water Contaminants
Three raw water samples collected from the Ismailia Canal, the Damietta branch, and a wastewater treatment plant were treated using nanocellulose concentration of 5 g/L. These are described in Table 2. The treatment process was carried out within a pH range of 6.7 to 7.4, 100 rpm for 5 min, 25 rpm for 15 min, and settling for 10 min. Results of the treatment of the Ismailia Canal specimen showed turbidity, COD, BOD, phosphorous, and oil and grease removal efficiency of 96, 83.3,100, 100, and 98.68%, respectively. Results of the treatment of the Damietta branch showed turbidity, COD, BOD, phosphorous, and oil and grease removal efficiencies of 87.5, 81.25, 88.9, 99.11, and 96.38%, respectively. Results of the treatment of the WWTP showed turbidity, COD, BOD, phosphorous, and oil and grease removal efficiencies of 86.36, 91.96, 92.86, 91.74, and 97.18%, respectively.
Table 2. Effect of Nanocellulose on Treatment of Water Samples
Integrated Behavior of NC-nZVI, on Phosphorous Removal
Characterization of NC-nZVI
Fourier-transform infrared spectroscopy (FTIR) characterization
Shimadzu S 201 PC spectrophotometer – Tokyo, Japan was used for infrared spectroscopy. The sample was prepared as a disc (2 mg sample + 200 mg spectroscopy KBr). The surface of the NC-nZVI composite had high ratios of OH– groups that can combine easily with other active functional sulfate esters, carboxyl, amine, and aldehyde groups, as shown in Table 3 and Fig. 3.
Table 3. Indicators of FTIR Observed Bands for NC Sample
Fig. 3. FT-IR of NC-nZVI powder sample
Scanning electron microscope characterization
The obtained SEM results indicated the formation of Nanocellulose-Nano Zero Valent Iron Composite (NC-nZVI) as fiber with a size ranged between 18 and 26 nm, as shown in Fig. 4.
Fig. 4. SEM of NC-nZVI
Fig. 5. Particle size distribution of NC-nZVI
Particle size distribution:
Particle size distribution was tested for NC-nZVI from 0 to 30 µm, as shown in Fig. 5. The obtained results indicated that 94% of the prepared NC-nZVI sample was within 50 nm.
Point of Zero Charge (PZC)
The Point of Zero Charge (PZC) was investigated by preparation of 0.1 M KCl, then about 20 mL was adjusted to pH values 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12 by using 1 N H2SO4 or 1 N NaOH (pHi) and placed in a 100 mL Erlenmeyer flask. About 0.1 g of NC-nZVI was added into the prepared flasks and left 24 h at 23 ºC. The final pH measurements were determined (pHf). Averaged values of pH changes after nZVI were obtained from 5 measurements, and all standard deviation values were within ±0.1. The PZC of nZVI was calculated by plotting the relation between ΔpH values (final pH − initial pHi) and initial pH values (pHi). The result indicated that the PZC of NC-nZVI was about 7.8, as shown in Fig. 6.
Fig. 6. Point of Zero Charge of the NC-nZVI sample
Effect of Operating Conditions
Effect of pH
The effect of pH was studied at pH 3.5, 4.5, 5.5, 7.5, 8.5, and 9.5 for phosphorous removal by using NC-nZVI. An initial phosphorous concentration of 5 mg/L was used. When the stirring rate was 50 rpm, using 0.2 g/L NC-nZVI with a contact time of 15 min, the removal efficiency was 96, 94, 94, 63, 22, and 22%, respectively for the studied pH values as shown in Fig. 7a. At pH values below the point of zero charge (PZC) of NC-nZVI, the highest efficiency was at pH 3.5 and it decreased significantly at pH higher than 7.3. The PZC for nanoscale zero-valent iron is around 7.7 (Redlich and Peterson 1959). Equations 5 through 9 indicate that the reactivity of NC-nZVI increased below PZC and the efficiency of NC-nZVI decreases in the presence of iron oxide (Ross and Schatz 2014, Mahmoud et al 2021c).
Fe0 + 2H2O → 2Fe2+ + H2 + 2OH– (5)
Fe0 + O2 + 2H2O → 2Fe2+ + 4OH– (6)
6Fe2+ + O2 + 6H2O → 2Fe3O4 [magnetite] [s] + 12H+ (7)
Fe–OH → Fe–O− + H+ (8)
Fe–OH + OH− → Fe–O− + H2O (9)
Depending on the electrostatic repulsion phenomenon, the aggregations increased at PZC and decreased up and down. Also, the accumulation of sorbent materials affect the reactivity due to the decrease in the surface area (Ross and Schatz 2014).
Effect of contact time
The effect of contact time on the phosphorous removal was studied at 5, 15, 30, 60, and 120 min. An initial phosphorous concentration of 5 mg/L diluted from prepared solution (500 mg/L po43--p) was used along with 0.1 g/L from NC-nZVI at a stirring rate of 50 rpm. The removal efficiency was 65, 69, 72, 75, and 73% for the studied contact times, respectively, as shown in Fig. 7b.
Effect of adsorbent dose
The effect of the adsorbent dose was studied at 0.1, 0.2, and 0.3 g for phosphorous removal by using NC-nZVI. An initial phosphorous concentration of 5 mg/L was used. At medium pH 3.5 and stirring rate 50 rpm with a contact time of 15 min, the removal efficiency was 69, 94, and 100%, respectively for the studied NC-nZVI doses as shown in Fig. 7c.
Effect of stirring rate
The effect of the stirring rate on the phosphorous removal was studied at 50, 100, 150, 200, 250, 300, and 350 rpm using an orbital shaker GFL 3018, Prague, Czech. An initial phosphorous concentration of 5 mg/L was used. Using 0.2 g/L of NC-nZVI at medium pH 3.5 with a contact time of 15 min, the removal efficiency was 96, 98, 98, 98, 98, 98, and 98%, respectively for the studied stirring rates as shown in Fig. 7d.
Fig. 7. Effect of operating conditions: A) Effect of pH, B) Effect of contact time, C) Effect of dose, and D) Effect of stirring rate
Effect of the initial phosphorous concentration
The effect of the initial phosphorous concentrations was studied at concentrations 10, 9, 7, 5, 3, and 1 mg/L using NC-nZVI. Using 0.2 g/L of NC-nZVI at medium pH 3.5 and stirring rate 50 rpm with a contact time of 15 min, the removal efficiency was 91, 93.6, 96, 98, 99, and 100%, respectively for the studied phosphorous concentrations as shown in Fig. 8 (Toth 1971; Xi et al. 2010).
Fig. 8. Effect of initial concentration
At room temperature, nonlinear relations between isothermal models were considered to describe the removal mechanism, as in Fig. 9. The studied isotherms models were the Redlich-Peterson model, Hill model, Sips model, Khan model, Toth model, Koble-Corrigan model, Javanovic model, Freundlich model, and Langmuir model. The results showed that the NC-nZVI composite was well described by the Sips model (∑ errors: 7.932), as shown in Table 4. The Sips model describes a heterogeneous adsorption isotherm process, which combines Langmuir and Freundlich models. This model tends to approximate the Freundlich model at low concentration and to solve the Freundlich limitation at high concentration through applying the Langmuir adsorption model in the prediction of monolayer adsorption showing the maximum uptake is 105.3 mg (PO43-)/g (NC-nZVI).
Table 4. Nonlinear Adsorption Isotherm for Phosphate Removal Using NC-nZVI
Fig. 9. Adsorption isotherm models for phosphorus removal using NC-nZVI composite. The curve labeled “Qe” corresponds to the experimental data.
Response Surface Methodology (RSM)
Table 5 describes the positive linear effect of the independent variable “pH”, and “dose” on phosphate removal was observed to be significant (p< 0.05). However, an insignificant effect (p> 0.05) was determined for the linear terms of “time”, “stirring rate” and “initial concentrations”. The coefficient of determination between measured data and simulated results (R2) and adjusted R2 existed in Table 5. The significant result of the linear RSM model agrees with the obtained ANN model (Fig. 11) – nonlinear feed-forward backpropagation neural networks – to describe the most significant operating parameters (p-value equal 0.00 for the effect of dose and pH) for phosphate removal using NC-nZVI. By applying Eq. 4, the removal equation appears. The removal equation can be used to control the removal percent by minimizing or maximizing the operating variables using all obtained results not restricted to the optimum conditions,
Y = 92.646 -10.956 x1 + 221.112 x2+ 0.010 x3+ 0.013 x4 – 0.813 x5 (10)
where Y is the predicted response of different wastewater contaminants removal efficiency (%); x1is pH (3.5 to 9.5); x2 is adsorbent dose (0.1 to 0.3 g); x3 is contact time (5 to 120 min); x4 is stirring rate (50 to 400 rpm); x5 is concentration (1 to 10 mg/L); β0 is the model intercept; β1, β2, β3, β4, and β5 are the linear coefficients of x1, x2, x3, x4 and x5, respectively.