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Efficient Dye Removal from Real Textile Wastewater Using Orange Seed Powder as Suitable Bio-Adsorbent and Membrane Technology

Miguel A. D. Flores Alarcón
Claudia Revilla Pacheco
Kiara Garcia Bustos
Kevin Tejada Meza
Felix Terán-Hilares
David. A. Pacheco Tanaka
Gilberto J. Colina Andrade
1 and
Ruly Terán-Hilares
Laboratorio de Bioprocesos, Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María—UCSM, Urb. San José s/n—Umacollo, Arequipa 04000, Peru
Laboratorio de Investigación Agroindustrial, Universidad Nacional José María Arguedas, Av. 28 de Julio N° 1103, Talavera—Santa Rosa, Andahuaylas 03701, Peru
Author to whom correspondence should be addressed.
Water 2022, 14(24), 4104;
Submission received: 13 November 2022 / Revised: 5 December 2022 / Accepted: 13 December 2022 / Published: 16 December 2022
(This article belongs to the Section Wastewater Treatment and Reuse)


Textile wastewater is widely produced and its discharge without treatment contributes to environmental pollution. The adsorption process is a suitable and eco-friendly process due to its low initial cost, no formation of degradation products, operation simplicity, insensitivity to toxic compounds, and the possibility of removal from greatly diluted solutions. Orange seed (OS) powder, from which lipids were removed by hexane extraction, was evaluated as a bio-adsorbent to remove dyes from real textile wastewater. In the screening step, pH was a more significant variable (p-value < 0.05) than bio-adsorbent dosage, temperature, stirring speed, and process time. Moreover, under optimized conditions (pH = 2.6, 0.58 g/L from OS powder and 26 °C), more than 95% of the dye was removed from real textile wastewater. Additionally, the dye removal percentage was reduced by only 4% when the volume of textile wastewater was increased from 0.05 L to 10 L. Then, 96% turbidity was removed using a 3 µm tubular ceramic membrane at a pH of 11. Furthermore, the permeate flux through the membrane was kept constant for longer than was observed at low pH (<11). Therefore, the proposed process is an interesting option, due to the fact that orange seeds are currently not valorized and, combined with the membrane process, this could prove a suitable option for the treatment of real textile wastewater.

Graphical Abstract

1. Introduction

The textile industry is one of the world’s major polluters [1]. Moreover, it is well-known as one of the most complex manufacturing industries, with high water, energy, and chemical resource consumption releasing a large number of hazardous effluents [2]. Therefore, the treatment of textile effluents is essential to protect the ecosystem and enable further recycling of the treated effluent for irrigation purposes, reuse in textile manufacturing processes, or cleaning activities [1].
Around 10,000 different kinds of dyes have been produced and are available on the market today with an estimated annual production of 700,000 tons [3]. Textile wastewater contains various chemicals (e.g., azo dyes, anthraquinone dyes, derivatives of indigo, xanthene dyes, phthalocyanine dyes, nitrated and nitrosated dyes, diphenylmethane and triphenylmethane dyes, and cyanines), and inorganic compounds such as metals [4]. Around 15–50% of the azo-type dyes do not bind to the fabric during the dyeing process and are released in many developing countries into wastewater which is used for irrigation in agriculture. This is also very damaging for soil microbial communities, germination, and plant growth [5]. The toxicity of dyes has also aroused public concern, since most of them are resistant to biodegradation, and they could trigger a high risk of developing neoplastic diseases [6]. The high color intensity, the concentration of recalcitrant organics, turbidity, salinity, pH level, and metal content, make textile wastewater a heavily polluted effluent of low biodegradability, which needs to be treated [7].
Textile wastewater has a complex composition which requires the development of new efficient methods in order to remove its pollutants. This represents a current challenge in this field. The relevance of this topic is reflected in the number of publications in the SCOPUS database, which have increased by 63% in 2021, when searching the terms “dye AND removal AND industry”. Some reported methods correspond to adsorption, ion exchange, chemical oxidation photocatalysis, microbiological degradation, and membrane filtration [8,9].
Among these, adsorption processes have received considerable attention in dye removal from wastewater, due to their low initial cost, feasibility, flexibility, operation simplicity, insensitivity to toxic compounds, the possibility of removal from greatly diluted solutions, and the possibility of using bio-adsorbents from agro-industrial residues [10]. The adsorbents obtained from agro-industrial residues are widely available around the world and have several advantages, such as low cost, renewability, and environmental friendliness [11]. These residues, in nature or modified by humans, have been utilized to remove inorganic pollutants such as heavy metals (Hg, Pb, Ni, Cu) [12,13], and organic pollutants from wastewater [14], mainly due to high porosity and large specific surface area. Although, agro-industrial residues have been extensively studied, they have usually been evaluated using pure dyes and at a lab scale, without the presence of interferents that can influence the dye removal.
Oranges are the world’s most popular fruits and, according to the USDA Foreign Agricultural Service, the global orange production for 2021/22 is estimated to be 1.8 million tons more than the previous year (49.0 million). After processing, orange residues (peel, pulp, seeds, orange leaves) are not used, even though, their composition is rich in soluble sugars, protein, cellulose, hemicellulose, pectin, ash, and essential oils [15,16]. The valorization is usually focused on peel and pulp for the production of pectin, essential oil, bio-oil charcoal, and animal feed products. The seeds have been scarcely studied, which means they might have interesting applications, since seeds of other fruits were effectively used as an adsorbent, e.g., pomegranate seeds for methylene blue dye [17], jackfruit seeds for cadmium [18], date seeds for methyl violet [19].
The adsorption process could be combined with other processes, such as separation by membranes. Membrane technology is one of the best methods in terms of novelty, efficiency, and purity for obtaining desired water quality for water reuse [20]. Membranes have been used in dye and wash baths to remove colloidal dyes [21]. Ultrafiltration (UF) membranes have been generally applied to recover high molecular weight substances, auxiliary chemicals, and reactive dyes [22,23], and nanofiltration (NF) membranes have been used to separate organic compounds, divalent salts, and hydrolyzed reactive dyes present in wastewater [22]. Nadeem et al. [23] studied combinations of UF and NF membranes as a novel treatment method for textile wastewater. In UF + NF, the achieved color, COD, and conductivity removal were close to 99.0% in treated wastewater effluents.
In the present study, adsorption and membrane technologies were evaluated for the treatment of real textile wastewater. The adsorbent was obtained from orange seeds, where the lipids were removed by hexane and their influence parameters for dye adsorption were evaluated and optimized. Then, the bio-adsorbent loaded with dye was removed by microfiltration using inorganic membranes.

2. Material and Methods

2.1. Textile Wastewater

Textile wastewater (TW), mainly generated from alpaca wool processing, was collected from a local textile company in Arequipa, Perú. The samples were stored under refrigeration until use. The dye’s adsorption was calculated from the absorbance difference using an OMEGA spectrophotometer. Chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and detergents (SAAM) analysis were carried out according to APHA standard methodology [24]. Turbidity was determined by a HACH TL-2300 turbidimeter. Conductivity, total dissolved solids (TDS), and salinity were obtained using a HANNA HI9829 multiparameter (Hanna Instruments, Inc., Smithfield, RI, USA).

2.2. Bio-Adsorbent Obtention from Orange Seeds

Sweet orange seeds (SOS) were collected and obtained from a local market in the city of Arequipa. Seeds were washed with distilled water, dried (at 60 °C) and ground using a hand mill. The obtained powder was submitted to fat extraction for 6 h in a Soxhlet using n-hexane [25], and the resulting powder was named a “bio-adsorbent”. The protein content in the bio-adsorbent was determined by the Kjeldahl method (A.O.A.C., 1984), and fat, ash, and crude fiber content were determined gravimetrically according to Peruvian Technical Standards (NTP, 2001).

2.3. Evaluation of More Influential Variables through the Screening Step

The influence of variables on dye removal by bio-adsorption was evaluated using a 2(5−1) fractional factorial design with 16 experiments, which was established using Design-Expert software 12.0 (stat-Ease, Inc., Minneapolis, MN, USA). The ranges for variables were pH (2–6), bio-adsorbent dosage (0.5–2.5 g/L), stirring speed (80–160 rpm), temperature (25–35 °C), and time (60–120 min). All of the experiments were carried out using 0.05 L textile wastewater in Erlenmeyer flasks at a controlled temperature. After the process, the obtained sample was centrifuged, and the absorbance was measured at 536 nm (maximal absorbance wavelength) and determined at pH 2, 4, 6, and 9. The significant variables (p-value < 0.05) were established at a 95% confidence level. Finally, the identified variables were considered for subsequent optimization processes.

2.4. Dye Removal Optimization Using a Response Surface Methodology

The variable optimization on dye adsorption was calculated using a Box–Behnken design based on 12 experiments and 3 central points. The variable range considered in the optimization process was the same as that of the screening step and the dye adsorption (%) was considered as a response. All the experiments were carried out using 0.05 L TW in Erlenmeyer flasks, and the process was carried out for 30 min at 120 rpm. Samples were collected immediately after the addition of the bio-adsorbent and after 30 min of the process for its respective absorbance analysis at 536 nm.
Design-Expert software 12.0 (StatEase®, Minneapolis, USA) was used in order to compose and evaluate an empirical model that better describes the response variable (% of dye removal) as a pH function, the dosage of the bio-adsorbent, and temperature. An ANOVA test was also performed, aiming to evaluate the significance of the model, variables, and lack of fit. The process optimization was carried out using the numerical optimization feature of the software, based on the desirability function. The optimization process goal was to maximize the dye adsorption (% removal), which was calculated using the following Equation (1):
D y e   r e m o v a l   ( % ) = ( 1 A B S 30 min A B S 0 ) 100
where ABS0min and ABS30min correspond to absorbance measured after 0 and 30 min of treatment at 536 nm, respectively.

2.5. Dye Adsorption under Optimized Conditions Using 10 L of TW

The optimized conditions established in the previous section for 0.05 L were enlarged to 10 L volume. The process was performed in a jacketed glass reactor and the temperature was controlled by recirculating water through the reactor jacket. Samples were collected periodically during 80 min; these were also centrifuged in order to analyze the absorbance at 536 nm. Moreover, COD, TN, TP, and detergents (MBAS) were also analyzed.
A pseudo-second-order kinetic model was considered for this analysis and the rate constant was calculated using Equation (3) which is derived from Equation (2), where qe is the amount of the dye adsorbed at equilibrium (UA536nm/g of bio-adsorbent), k2 is the equilibrium rate constant of the pseudo-second-order model (g/UA536nm. min), and h (Equation (4)) is the initial sorption rate,
d q t d t = k 2 ( q e q t ) 2
t q t = 1 k 2 q e 2 + t q e
h = k 2 q e 2

2.6. Bio-Adsorbent Removal by Membranes

The TW containing the bio-adsorbent was initially filtered through a sieve (N° 100 (0.149 µm) mesh) to remove larger particles. Then, residual particles of bio-adsorbent were removed by microfiltration using tubular ceramic (Al2O3) membranes (150 mm height × 10 mm diameter) purchased from Inopor® (Scheßlitz, Germany). Membranes of 3 µm, 600, and 200 nm were evaluated based on the turbidity of the recovered water. The microfiltration process was performed using a peristaltic pump for 30 min in each case, and every 1 min the volume permeate was collected and the permeate flux (mL/min) was calculated. Then, the membrane with the best performance was selected, and the pH effect (pH 3, 3.7, and 11) on the permeate flux was evaluated. Before each test, the membrane was washed with distilled water, then with an alkali solution (NaOH), and finally with distilled water again. Tests were performed for 40 min to reduce the fouling and, at minute 20, the membrane was backwashed with distilled water.

3. Results and Discussion

3.1. Orange Seeds and Textile Wastewater Composition

The OS in nature contains around 46% fat, 41% carbohydrates, 9.4% protein, and 2.2% ashes. After fat extraction, the powder obtained was mainly composed of carbohydrates (72.9%), protein (17.5%), ashes (4.0%), fat (1.9%), and humidity (3.7%). The obtained composition is comparable to that of the dehulled orange seed flour (dry weight) reported by Akpata et al. [16]. The hexane removes other biologically active substances which are soluble in this solvent, increasing the porosity of the seeds [11]. In addition to this, the bio-adsorbent has low ash content which, together with the high organic content, allows the presence of a porous structure with hydrophilic character in order to allow the filling of the pores with water containing the dye [26]. Therefore, these properties turn orange seeds, without dehulling, into an interesting option for dye adsorption from textile wastewater. Moreover, the use of orange seed powder for dye removal from real textile wastewater has not been reported, yet. Since the composition of the real sample is complex, it was difficult to individually study the adsorption of all the components in the water and their influence on dye adsorption, therefore it was decided to study the adsorption on the real sample directly.
The composition of textile wastewater varies greatly, depending on the industry and the type of fiber or wool it processes, the fabric produced, the chemicals applied, the season, and fashion trends [27]. In this case, alpaca wool is mainly processed by the company where TW was obtained, but cotton is also processed. The textile wastewater (Table 1) showed a purple tonality with maximal absorbance wavelength at 530–536 nm. The COD value was around 159 mg O2/L, which is in accordance with the study performed by Kehinde et al. [28]. The anionic detergent content expressed in methylene blue active substances (MBAS) was very low.

3.2. Variable Identification Using Fractionated Experimental Design

Bio-adsorbents are very useful for removing organic pollutants such as dyes due to the presence of functional groups and hydrophilic or hydrophobic structures on the surface which have less or more affinity to adhere dyes, depending on other factors such as temperature, pH, the dose of bio-adsorbent, etc. Using this method, the most influential variables on textile dye adsorption using OS powder as a bio-adsorbent were identified through a fractionated factorial design 2(5−1) and the results are shown in Table 2. As observed, in run 9 (pH = 2), more than 97% dye adsorption was achieved, compared to the process at pH 6 (runs 5 and 6). The highest dye adsorption at low pH could be associated with the presence of protonated groups (pKa of OS = 3.74) making the surface positive and attracting the dyes in textile wastewater (probably anionic dyes). In the case of this study, the attraction capacity of the bio-adsorbent was improved at low pH. In addition, the adsorbent based in agro-industrial residues at low pH showed a positively charged surface, as previously reported for watermelon seeds [30]. Although several bio-adsorbents have been developed, to be used for pure dye removal [31,32], for real textile wastewater, which is a complex system (organic compounds, mixture of dyes), this has not been reported, yet. Other compounds present, that are different from dyes, could also act as interferents, and they compete with dyes for active sites of the bio-adsorbent.
According to the ANOVA, test (data not shown), the pH was the most significant variable and it strongly affects the adsorption capacity of the bio-adsorbent. This variable showed the opposite effect, implying that a pH reduction in the process improves the dye adsorption capacity. Concerning the other variables evaluated, adsorbent loading and temperature have some significance compared to speed and time (Figure 1). However, as the adsorption changes with time until equilibrium and the amount of sorbent used is reached, this value will be determined in future studies.

3.3. Optimization of Dye Removal Using a Response Surface Methodology

The pH variable, bio-adsorbent loading, and temperature were optimized using the Box–Behnken method and the results are shown in Table 3. As expected, higher dye adsorption was observed at a high concentration of bio-adsorbent and low pH; under this condition, 96% of the dye was removed (run 2) at 25 °C. Adsorbents based on waste biomass (bio-adsorbents) are being used for the removal of various compounds such as dyes and other particulates from real wastewater, due to their high effectiveness, easy availability, and cheapness, but orange seed has not yet been reported to be used for this purpose.
pH is a fundamental variable in dye adsorption, since the charge of the dye will depend on the pKa and pH of the dye and the adsorbent. The positively charged surface allows the interaction with anionic dye molecules [33]. Therefore, an increase in the pH of the textile wastewater decreases dye adsorption [34]. Another relevant factor is the dosage of bio-adsorbent. This will increase when more adsorbent is used, but it will depend on the maximum capacity and the equilibrium at the given pH. As it is an adsorption mechanism, dye adsorption from textile wastewater decreases when there is a temperature rise, as reported by Asgher et al. [31]. However, as the composition of the sample is complex, the interference of other compounds could change this tendency.
A quadratic empirical model (Equation (5)) was composed, and Table 4 shows the results of the ANOVA test. As shown in the table, the model (Equation (5)) has a fairly high R-squared, of 0.98. This was also confirmed by the p-value of the model (<0.0001), F-value (85.14), and non-significant lack of fit test (p-value > 0.05) at the 95% confidence level. Moreover, all three independent variables have a great influence on dye adsorption.
Equation (5) models the behavior of the experimental design factors predicting dye adsorption from TW for given levels. As observed, pH is the most influential variable. In addition, the dosage of bio-adsorbent and temperature have a high and similar impact, compared to their coefficients:
Y = 88.3 − 18X1 + 14.9X2 − 10.2X3 + 8.5X1X2 − 7.9X1X3 + 6.9X2X3 − 17.4X12 − 16.4X22 + 6.2X32
where Y is the response variable “dye adsorption from TW (%)”. X1, X2, and X3 correspond to current pH values, the dosage of bio-adsorbent, and temperature, respectively.
The interaction of two variables is shown in contour plots (Figure 2). As observed, in Figure 2A, dye adsorption is more than 80% as pH decreases and there is a rise in the bio-adsorbent dosage, driving the enhancement of dye adsorption when the temperature decreases, and the TW pH is low (Figure 2B). The same phenomenon is observed in Figure 2C where the bio-adsorbent dose is increased while the temperature is low, improving the dye adsorption rate to almost 90% in 30 min.
The variables were optimized, aiming to maximize the dye adsorption from textile wastewater. A validation experiment was also performed in the optimized conditions (pH = 2.6, dosage of bio-adsorbent = 0.58 g/L, and temperature = 26 °C). Under optimized conditions, 100.3 ± 3.3% (average ± 95% confidence level interval) of dye removal was predicted by the quadratic model, which was confirmed experimentally at 95.9 ± 0.7% (average ± standard deviation). Therefore, the dye adsorption of orange seeds was comparable to that from olive waste bio-adsorbent, where 84.7% of RR198 dye removal yield was achieved under optimized conditions (pH = 2, bio-adsorbent dosage = 3 g/L, and volume of wastewater = 50 mL; the temperature was not reported [34].

3.4. Textile Wastewater Treatment in a 10 L Reactor

The established condition at a small scale (50 mL) was scaled up to 10 L, and the results are shown in Figure 3. In Figure 3A, the highest dye adsorption from TW occurs in the first 30 min, achieving 92% removal. After 28 min, the adsorption reaches equilibrium, which shows that the bio-adsorbent is saturated. This is the first report about complex mixture dye removal present in textile wastewater using orange seed bio-adsorbent at a volume of 10 L; previous studies are limited to low volume work and pure dyes [35,36]. Because of this, more studies are required, aiming to discover the isotherm, thermodynamic properties, and mechanisms involved in the process.
The adequate fit of the data to pseudo-second-order kinetics (Figure 3B) was corroborated by the R2 (0.99) obtained, which was higher than pseudo-first-order kinetics (R2 = 0.92). Using equation (2), K2 of 3.26 g/UA536nm. min was calculated. Although the value was expressed in UA536nm this is a referential point, since the composition of the real textile wastewater is complex, and even contains a mixture of dyes. Figure 3B is associated with the film diffusion (external mass transfer), and the second linear part to the intra-particle diffusion (into the porous structure of the adsorbent), since the active adsorption sites are filled and the probability of the dye finding an empty site is reduced until equilibrium is reached.

3.5. Bio-Adsorbent Removal by Ultrafiltration and pH Effect

The water containing the bio-adsorbent was submitted to microfiltration using ceramic tubular membranes with three different pore sizes (200, 600 nm, and 3 µm) and the results are shown in Figure 4. As shown in Figure 4A, the 3 µm membrane reaches a 0.70 mL/(min·cm2) flux, which is the maximal flux across the four membranes, and it decreases to 0.28 mL/(min·cm2) after a 20 min process. The reduction in the flux is due to fouling by the retention of small particulates of the wastewater or residual bio-adsorbent; the retention on the surface of the membrane contributes to COD reduction, total suspended solids, dyes, and turbidity in the permeate, as reported for ceramic membranes [37,38]. In this study, more than 96% of turbidity from textile wastewater containing the orange seed bio-adsorbent was removed by all the membranes (3 µm, 600 nm, and 200 nm). This result is in accordance with findings previously reported by Luogo et al. [39], where the turbidity changed from 206 NTU to 10.3 NTU in the MF permeate and 1.01 NTU in the UF permeate. Likewise, by employing ceramic membranes with almost three times smaller pore sizes (1.76, 1.21, and 1.31 µm), 99% turbidity removal from domestic wastewater was reached [38]. Therefore, considering the non-significant difference in the turbidity removal by the evaluated membranes, and the better membrane performance of the 3 µm pore size, additional experiments were performed, aiming to evaluate the effect of pH on the filtration process.
In Figure 4B, the permeate flux, as well as the pH effect (3, 7 and 11) can be observed. As previously noted, experiments were carried out over 40 min, and in the first 20 min a backwashing process was performed, aiming to recover the flux through the membrane. The initial flux in all cases was about 0.72 mL/min·cm2, but during the filtration progress at pH 3 and 7, the flux dropped quickly, and the backwashing performed was not enough to recover the initial flux. This occurred even though, when textile wastewater containing OS bio-adsorbent feed is at pH 11, the membrane presented a maximum 0.72 mL/(min·cm2) flow rate, which is constant and still quite high, compared to the membranes with other pore sizes previously tested; in addition, it was not necessary to backwash the membrane.
The high pH of the solution enhances the flux across the membrane, but this decreases in the rejection of the feed involving a high pass of salts and dyes with a small molecular weight. Similar results were reported by Guo et al. [40], where four solutions of anionic dyes were tested at different pH levels showing that the flux across a ceramic membrane increases as the pH is near 12. Additionally, a reduction in flow rate can be due to particles with similar sizes than the pore, a single particle with exactly the same size as the pore, and a particle or a group of particles that are deposited in the pore, causing the pore to block completely or partially. In addition, the cake formation (layer of particles) on the membrane surface increases the feeding rejection over time [41]. However, it was observed that, at pH 11, the adherence of particles and residues of dyes is easily removed with distilled water and does not reduce the flux significantly, aiming to avoid backwashing, and setting the treated-TW feed at alkaline conditions as flux, with better yield over time.

3.6. Characteristic of the Wastewater after the Sequential Treatment

The characteristics of crude TW before and after adsorption and membrane treatments are summarized in Table 5. As observed, the textile wastewater absorbance unit (UA560nm) measured at 560 nm (wavelength of maximum absorption, Figure 5) decreased from 1.191 to 0.032, which represents more than 97% dye removal by adsorption using the bio-adsorbent. For the chemical oxygen demand (COD), no changes were observed, but the COD content was in accordance with that previously reported, i.e., between 150 and 12,000 mg O2/L [1,42]. After the membrane treatment, there was a slight increase in COD; however, comparing the values to those for the treatment after biosorption, these differences are not statistically significant (p-value > 0.05). Salinity, conductivity, and TDS have a slight increase due to natural bio-adsorbent characteristics; these could also be explained by the partial dissociation of surface groups and the possible interaction between the adsorbent and the constituents of the wastewater [43,44].
After the contact with the bio-adsorbent, 31.8% turbidity removal was achieved; however, after membrane filtration, there was a greater removal (95.7%) because of the separation of the largest particles in the pores of the membrane. Similar removal percentages are reported in synthetic textile wastewater (98.5%) with moringa seed powder after contact and centrifugation [45]. The turbidity removal of real textile wastewater with Strychnos potatorum seed powder reached values between 50–84% [46]. Indeed, some components of textile wastewater were reduced by the effect of the bio-adsorbent and membrane (3 µm) treatment. Parameters such as salinity, TDS, conductivity, total nitrogen, and phosphorous were constant. Therefore, an additional treatment is required in order to remove total nitrogen from wastewater, e.g., biological processes such as microalgae cultivation [47], or activated sludge–biofilm coupled with symbiotic algae [48].

4. Conclusions

An adsorption process using fat-free orange seed powder successfully removed the dyes from textile wastewater. Using optimized conditions, it was possible to adsorb more than 92% of dye in less than 30 min, using 50 mL of real wastewater in an Erlenmeyer flask and 10 L in a glass reactor. Therefore, orange seed as a bio-adsorption treatment is a promising low-cost, renewable material to remove dyes from real textile wastewater at a large scale. The adsorption of dye depends mainly on the pH of the solution and the kinetics of adsorption follow pseudo-second-order kinetics. Moreover, combined with membrane technology, it is possible to almost eliminate the residual turbidity of the wastewater, which will depend on the pore size of the membrane and the pH.

Author Contributions

Conceptualization, R.T.-H. and M.A.D.F.A.; methodology, R.T.-H. and K.G.B.; validation, R.T.-H., K.T.M. and D.A.P.T.; formal analysis, D.A.P.T. and G.J.C.A.; investigation, M.A.D.F.A., F.T.-H., K.G.B. and C.R.P.; data curation, R.T.-H., D.A.P.T. and G.J.C.A.; writing—original draft preparation, R.T.-H., D.A.P.T. and F.T.-H.; writing—review and editing, M.A.D.F.A., R.T.-H. and G.J.C.A.; project administration, R.T.-H.; funding acquisition, R.T.-H. All authors have read and agreed to the published version of the manuscript.


This research was funded by the Universidad Católica de Santa María (UCSM) grant number 28048-R-2021 And the APC was funded by Universidad Católica de Santa María (UCSM).


The author would like to thank the Universidad Católica de Santa María (UCSM).

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Standardized effects for dye removal from textile wastewater (%) by OS bio-adsorbent.
Figure 1. Standardized effects for dye removal from textile wastewater (%) by OS bio-adsorbent.
Water 14 04104 g001
Figure 2. Response surface for dye bio-adsorption by orange seed powder. (A) pH and bio-adsorbent dose. (B) pH and temperature. (C) bio-adsorbent dose and temperature. In each case, the third variable was kept at its center point value.
Figure 2. Response surface for dye bio-adsorption by orange seed powder. (A) pH and bio-adsorbent dose. (B) pH and temperature. (C) bio-adsorbent dose and temperature. In each case, the third variable was kept at its center point value.
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Figure 3. (A) Dye removal percentage and (B) dye adsorption kinetics from TW by orange seed (OS) powder bio-adsorbent in a 10 L reactor.
Figure 3. (A) Dye removal percentage and (B) dye adsorption kinetics from TW by orange seed (OS) powder bio-adsorbent in a 10 L reactor.
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Figure 4. (A) Comparison of membrane filtration flux of OS bio-adsorbent from treated TW using tubular ceramic (Al2O3) membrane with pore sizes of 200 and 600 nm, and 3 µm. (B) Flux variation with pH (3, 7, and 11) across the 3 µm pore size membrane and after backwashing (20 min) with distilled water.
Figure 4. (A) Comparison of membrane filtration flux of OS bio-adsorbent from treated TW using tubular ceramic (Al2O3) membrane with pore sizes of 200 and 600 nm, and 3 µm. (B) Flux variation with pH (3, 7, and 11) across the 3 µm pore size membrane and after backwashing (20 min) with distilled water.
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Figure 5. Absorption spectrum of the untreated textile wastewater at different pH’s: pH 9 (a), pH 6 (b), pH 4 (c) and pH 2 (d). Spectrum of textile wastewater treated with orange seed bio-adsorbent (e).
Figure 5. Absorption spectrum of the untreated textile wastewater at different pH’s: pH 9 (a), pH 6 (b), pH 4 (c) and pH 2 (d). Spectrum of textile wastewater treated with orange seed bio-adsorbent (e).
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Table 1. Main parameters of TW and comparison with reported values.
Table 1. Main parameters of TW and comparison with reported values.
ParametersThis StudyKehinde et al. [28]Avlonitis et al. [29]
COD (mg O2/L)159150–30,000100
Total phosphorous (mg P/L)2--
Total nitrogen (mg N/L)653--
Detergents (mg MBAS/L)<0.061--
Salinity (PSU)2.19--
Total dissolved solids (mg/L)20482900–3100-
Turbidity (NTU)7–15--
Conductivity (µS/cm)4096-1000
Table 2. Design matrix for 2(5 − 1) fractional factorial design and dye adsorption from textile wastewater measured.
Table 2. Design matrix for 2(5 − 1) fractional factorial design and dye adsorption from textile wastewater measured.
RunVariablesDye Adsorption
Stirring Speed
Table 3. Box–Behnken design for optimization of dye adsorption from TW by OS bio-adsorbent after 30 min of treatment.
Table 3. Box–Behnken design for optimization of dye adsorption from TW by OS bio-adsorbent after 30 min of treatment.
RunVariablesDye Adsorption
pHBio-Adsorbent Dosage
Table 4. ANOVA for quadratic model composed for dye adsorption from textile wastewater by orange seed powder as bio-adsorbent.
Table 4. ANOVA for quadratic model composed for dye adsorption from textile wastewater by orange seed powder as bio-adsorbent.
SourceSum of SquaresdfMean SquareF-Valuep-Value
Model8170.989907.8985.14<0.0001 *
A—pH2598.8412598.84243.73<0.0001 *
B—Dosage1773.4011773.40166.32<0.0001 *
C—Temperature829.061829.0677.750.0003 *
AB287.131287.1326.930.0035 *
AC254.721254.7223.890.0045 *
BC190.161190.1617.830.0083 *
A21113.8711113.87104.460.0002 *
B2995.361995.3693.350.0002 *
C2143.251143.2513.430.0145 *
Lack of fit51.35317.1217.420.0548
Pure error1.9720.9828
Note(s): * Significant at 95% of confidence level.
Table 5. Comparison of the composition of crude textile wastewater (TW), bio-adsorbent treated TW, and microfiltration (3 µm) treated TW.
Table 5. Comparison of the composition of crude textile wastewater (TW), bio-adsorbent treated TW, and microfiltration (3 µm) treated TW.
AnalysisCrude TWTW after Treatment with Bio-AdsorbentTreated TW after Microfiltration
(3 µm)
Absorbance unit (AU560nm)
Chemical oxygen demand (mg O2/L)159.3 ± 16.5163.7 ± 16.6165.4 ± 16.6
Total phosphorus (mg P/L)2.35 ± 0.194.07 ± 0.334.71 ± 0.38
Total nitrogen (mg N/L)653.7 ± 16.3306.5 ± 7.7411.3 ± 10.3
Detergents (mg MBAS/L)<0.0610.366 ± 0.090.398 ± 0.1
Salinity (PSU)2.192.322.24
TDS (ppm)204821732104
Turbidity (NTU)15.410.50.66
Conductivity (µS/cm)409643454204
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Flores Alarcón, M.A.D.; Revilla Pacheco, C.; Garcia Bustos, K.; Tejada Meza, K.; Terán-Hilares, F.; Pacheco Tanaka, D.A.; Colina Andrade, G.J.; Terán-Hilares, R. Efficient Dye Removal from Real Textile Wastewater Using Orange Seed Powder as Suitable Bio-Adsorbent and Membrane Technology. Water 2022, 14, 4104.

AMA Style

Flores Alarcón MAD, Revilla Pacheco C, Garcia Bustos K, Tejada Meza K, Terán-Hilares F, Pacheco Tanaka DA, Colina Andrade GJ, Terán-Hilares R. Efficient Dye Removal from Real Textile Wastewater Using Orange Seed Powder as Suitable Bio-Adsorbent and Membrane Technology. Water. 2022; 14(24):4104.

Chicago/Turabian Style

Flores Alarcón, Miguel A. D., Claudia Revilla Pacheco, Kiara Garcia Bustos, Kevin Tejada Meza, Felix Terán-Hilares, David. A. Pacheco Tanaka, Gilberto J. Colina Andrade, and Ruly Terán-Hilares. 2022. "Efficient Dye Removal from Real Textile Wastewater Using Orange Seed Powder as Suitable Bio-Adsorbent and Membrane Technology" Water 14, no. 24: 4104.

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