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Article

Application of a 2k–p Fractional Experimental Design in Coagulation-Flocculation Processes in the Treatment of Wastewater from a Slaughterhouse

by
Javier Carpintero
1,*,
Jennifer Villa-Dominguez
1,
María José Tavera-Quiroz
2,
Humberto Carlos Tavera-Quiroz
3,
Bartosz Kaźmierczak
4,
Jonathan Fábregas-Villegas
5 and
Fausto A. Canales
1
1
Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, Barranquilla 080002, Colombia
2
Department of Agroindustrial Engineering, Faculty of Engineering, DESINPA, Universidad de Sucre, Cra. 28 #5-267, Puerta Roja, Sincelejo 700001, Colombia
3
Departamento de Ingeniería Ambiental, Universidad de Córdoba, Cra. 6 #No. 77-305, Montería 230002, Colombia
4
Department of Water Supply and Sewerage Systems, Faculty of Environmental Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
5
Grupo Interdisciplinario de Investigación en Mineralurgia, Energía y Medio Ambiente (GIIMA), Faculty of Engineering, Universidad Autónoma del Caribe, Barranquilla 080020, Colombia
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(16), 10402; https://doi.org/10.3390/su141610402
Submission received: 1 July 2022 / Revised: 12 August 2022 / Accepted: 16 August 2022 / Published: 21 August 2022
(This article belongs to the Special Issue Sustainability in Water and Wastewater Treatment Technologies)

Abstract

:
Determining the optimal dose of coagulant required to perform flocculation is critical in most water treatment plants’ planning and operation. This study implemented a 2k–p fractional factorial design of experiments to identify the factors influencing the color decrease of wastewater from a slaughterhouse. The variables assessed were the velocity gradient, residence time, primary coagulant dosage, chlorine dosage, and coagulation adjuvant dosage. The results indicate that the primary coagulant dose and the velocity gradient significantly affect the samples’ color and that the other factors can be run at a low technical-economic level to start up the water treatment plant. The fractional factorial design allowed reducing the number of experimental points without affecting the minimum information required to identify which factors are significant in reducing the color of a wastewater sample.

1. Introduction

The pollutants in wastewater negatively affect the ecological balance in the environment [1,2]. Livestock processing facilities generate wastewater with usually high concentrations of organic matter [3], and they are pollution sources in terms of the volume of water used in the process and the concentration of pollutants [4]. In this sense, the recycling of wastewater from slaughterhouses has been investigated to improve the productivity of processing plants of livestock [5,6], considering that the products of this wastewater treatment can be used for washing pens from recycled water, recovery of nutrients, or generation of energy from biomass, among others [7]. Wastewater treatment from this sector usually employs chemical [8] and electrochemical [9,10] processes, unlike other key industries (dairy [11], bakery [12]) where biological processes are frequently employed.
For wastewater treatment plants based on chemical processes, coagulation and flocculation are used to destabilize the dispersed particles in the water and regroup them in small masses of higher density called flocs to remove color, turbidity [13,14], and algae [15]. The ASTM D2035-13 standard suggests an experimental procedure for systematically evaluating treatments for removing colloidal, suspended, dissolved, or non-precipitable material in water, using coagulation, flocculation, and precipitation by gravity settling [16]. Although this procedure is focused on varying each experimental factor in turn while leaving the other factors fixed, this type of approach can be improved [17] if all of them are modified simultaneously to appreciate and decide which of all these factors are significant in wastewater treatment [18,19] taking into account experimental variability. The design of experiments (DOE) has proven to be a technique that allows verifying which factors and their interactions can substantially influence one or multiple response variables, considering the cause-and-effect relationship between the observed system and the impact on its results [20]. The fractional factorial design reduces the number of experimental runs without affecting the minimum information required to identify those significant factors in reducing the color of a wastewater sample. This research paper uses this statistical tool to identify significant causes in the response variable with minimal information based on a few experimental runs [18]. For the design of wastewater treatment plants that involve coagulation-flocculation processes, this approach provides an alternative for the management of several variables or factors that are modeled heuristically through regulations or standards and also in the decisions that must be taken concerning those factors that have a lesser incidence on the objective of reducing the color and managed at a moderate or low technical-economic level [16]. Regarding applying fractional factorial design to solve water quality research problems, Jiang et al. [21] have used this technique to degrade volatile fatty acids in anaerobic digestion processes, using trace elements as experimental factors. Traces of six of these elements were employed to measure their individual and combined effect on the fatty acids studied. Thus, an experimental design 26−2 was modeled to reduce the number of treatments or combinations between these factors to measure the main effects and interactions on the response variable. Stewardson et al. [22] demonstrated the usefulness of fractional experimental design for the parameter adjustment of genetic algorithms. This document highlights the importance of this type of design of experiments to save time when the research problems are extensive due to the number of factors to be considered, without losing quality in the response obtained from the effective and efficient use of this statistical technique of experimentation.
The main objective of this study is to analyze a 2k–p fractional factorial experimental design in a jar test to study five experimental factors and to choose which of these factors should be considered in the initial stages of sizing water treatment equipment, more specifically, flocculators. This statistical tool might serve in designing the processes to reduce the coloration of a wastewater sample from a slaughterhouse. This paper contributes to the literature on the optimal sizing of wastewater treatment plants, the improvement of their operating processes, and their efficient resource consumption. With color as the response variable, this research hypothesizes that the 2k–p fractional experimental design is a practical statistical tool for making decisions about factors or operating conditions that may favor the removal of pollution and contaminants from wastewater.

2. Materials and Methods

Figure 1 presents the assembly of the two-station portable flocculation equipment used in the experiment. This equipment’s characteristics follow those of the jar test [23,24], allowing the operator to program the agitation speed and the contact time of the water and the chemicals in the mixing volumes so that up to two experimental treatments can be conducted simultaneously. Generally, the jar test results for the removal of colloidal-sized particles can be scaled to full-size wastewater treatment plants [25,26]. Based on DOE, this research evaluates how five factors (velocity gradient, residence time, pre-chlorination, concentration of primary coagulant, and concentration of coagulation aid) influence the reduction of the physical parameter of the color of a wastewater sample from a slaughterhouse.

2.1. Case Study

This study used wastewater collected from an oxidation pond of a small refrigerating and processing facility in Monteria, Colombia. The facility aims to recover and reuse 30% to 40% of the discharged wastewater and employ it for irrigation activities and cleaning livestock pens. This application provides an eco-friendly alternative to improve efficiency in managing water resources while reducing costs in billing for drinking water and discharge through wastewater recovery.
The slaughterhouse includes a wastewater treatment system based on three lagoons (anaerobic, facultative, and maturation lagoon). The system’s volume is approximately 21,000 m3 and has a hydraulic retention time of 70 days. Even though the natural processes of self-purification through the symbiotic relationships between algae and organisms remove part of the organic load, as seen in Table 1, the sewerage company where the plant is located considered that the effluent required additional treatment, mainly because of the reddish color of this same.
Therefore, the wastewater treatment plant was expanded according to the diagram in Figure 2, where water loaded with organic material is pumped into a high-rate, rectangular cross-sectional sedimentation tank, where with the help of the factors studied in the experiment design, the suspended solid material is precipitated and then given final disposal in the form of sludge to landfills. The clarified water is conveyed through multimedia filters and an activated carbon bed to remove the remaining solids. Once the water passes through these stages, it is placed in a chemical oxidation reactor tank where it is in contact with sodium hypochlorite to remove the dissolved organic load and microorganisms (coliforms and pathogens). Finally, the reclaimed water goes into an automated storage tank of approximately 100 m3, from where it is employed according to the consumption needs. The main objective of the coagulation in this site’s wastewater treatment plant is to reduce the reddish color of effluent from the livestock processing activities. Therefore, according to wastewater disposal and reuse regulations, the experimental design evaluates the color variable to identify which experimentation route provides adequate wastewater in terms of this factor [27,28].
The color was measured in units of platinum cobalt color scale (Pt-Co), and the value of the initial wastewater sample was 6920 Pt-Co. The measurement method was the SM 2120 B [29], and the equipment selected to perform this test was a HACH DR 890 colorimeter. Table 1 shows other wastewater characteristics before and after the treatment in the system schematized in Figure 2.

2.2. Sewage Treatment System

Figure 2 shows a schematic representation of the wastewater treatment system used in the slaughterhouse under study. This process consists of taking residual water at the outlet of the oxidation lagoon at a rate of 500 m3/day to subject it to a physicochemical polishing that improves its quality, allowing its recycling for washing pens and other industrial activities of the facility. The residual water is conveyed to a high-rate settler with a capacity of 40.3 m3, where the suspended solids precipitate by coagulation and flocculation, reducing the water’s organic load and its reddish color. Subsequently, the water is pumped through a multimedia filter and a bed of activated carbon to retain remaining solids, and from there, the water passes through a chemical oxidation reactor whereby the action of an oxidizing agent the dissolved organic load is removed as well as microorganisms (coliforms and pathogens). Finally, this water reaches a storage tank from where it is consumed according to the needs of the process. The area occupied by this wastewater treatment plant in the slaughterhouse is 98 m2.

2.3. Experimental Factors Studied

This study analyzed five factors that can contribute to the decrease in the color of wastewater from a slaughterhouse. The factors selected to perform the experiment design were the concentration of primary coagulant, coagulation adjuvant, pre-chlorination, velocity gradient, and residence time. The chosen factors were studied because they are controllable, and the literature has shown that they might directly influence the oxidization and organic load remotion processes that address the issue of the reddish appearance of the wastewater from the slaughterhouse. It is worth mentioning that this research did not consider temperature and pH for practical reasons. In the case of temperature, this factor was not assessed because the tropical climate and the operational resources of the treatment plant would make it difficult to control this variable in actual conditions, and the ambient air temperature remains relatively constant during the year. Regarding the pH, the value measured in the wastewater effluent from the slaughterhouse entering the treatment plant is 6, and in the case of the primary coagulant ferric chloride, it operates in an optimal pH range between 4 and 12 [30]. Considering that reuse purpose and that the wastewater has a pH within the adequate range for the coagulant, it was decided to leave it fixed in this study. Before explaining the experimental design, we describe how these selected five factors might help reduce the wastewater’s color.

2.3.1. Residence Time

The residence time is related to the duration of the coagulation process in a mixing volume [31]. Excessive mixing time promotes breaking the connections between the primary coagulant and the colloidal particles present in the wastewater [32], thus affecting factors of interest in the design of industrial equipment for large-scale flocculation, such as agitators, sedimentation tank volumes, among other components related to the flocculation efficiency of the wastewater treatment plant. Therefore, the destabilization of the particles as a function of the residence time is a critical factor in understanding the coagulation mechanism in either fast or slow mixing in a water treatment plant [33]. In this investigation, the lower and upper-level times of 1 and 3 min, respectively, were established based on the process’s fast and slow mixing times reported in the literature [31,34].

2.3.2. Velocity Gradient

This factor sets the mixing intensity while dispersing the coagulant in a mixing chamber. This factor is of interest in designing industrial wastewater treatment equipment, such as flocculators, because it considers the power delivered to the fluid per volume unit. Concerning the dynamic viscosity that it possesses [35,36], the expression is:
G = 2 × π × s × T V × μ   ,
where:
  • G: Velocity gradient ( s 1 ) ,
  • s: Rotor speed measured in revolutions per second (rev/s),
  • T: Input torque on the rotor (N∙m),
  • V: Fluid volume (m3),
  • μ: Dynamic viscosity of the fluid (Pa∙s).
This study evaluates two levels of experimentation regarding the agitation speed: The low level is set at 30 rpm and the high level at 100 rpm. The latter intends to avoid floc breakdown by liquefaction associated with high agitation speeds [37,38].

2.3.3. Primary Coagulant Concentration

Primary coagulants serve in water clarification processes [39,40]. The inorganic compound ferric chloride (FeCl3) was selected as the primary coagulant for this study due to its availability and high efficiency in removing organic compounds. The tendency of iron salts to form polymeric species when dissolved in water allows the formation of positively charged, high surface area amorphous structures [39,41]. Colloidal particles of organic matter suspended in water tend to be highly stable due to the negative charges distributed on their surface. Coagulation with iron salts is appropriate to destabilize the colloids of organic matter. Their injection into effluents produces neutralization of charges, making the small colloids agglomerate into larger particles until they form flocs consisting of iron cations and bound organic anions [42]. This study set the lower level of this factor at 100 ppm and the upper level at 600 ppm, aiming to propose a technical-economic alternative that avoids excessive dosing of chemical products, consequently reducing wastewater treatment costs.

2.3.4. Pre-Chlorination

This factor refers to verifying if the dosage of an oxidizing agent, such as sodium hypochlorite (NaOCl), in the volume of the mixture can reduce the color coming from the organic load of the wastewater. Previous studies have found that pre-chlorination is a reliable strategy for removing organic material, such as algae, followed by a coagulation-flocculation process [43,44]. Natural organic matter reacts with chlorine to produce halogenated byproducts in water treatment [45]. In this sense, this factor is studied with two levels of experimentation: The lower level with 0 ppm and the upper level with a value of 5 ppm. The lower level at 0 ppm refers to the absence of pre-chlorination in the coagulation process analyzed in this jar test to know if this stage improves the color of the wastewater sample studied. This way, it will be possible to validate if this factor significantly reduces the water’s color to be analyzed.

2.3.5. Coagulation Adjuvant

Using flocculants facilitates the formation of flocs to attract suspended particles mechanically. These chemical substances improve the precipitation of organic substances dissolved in the water to be treated [46,47]. This research worked with the synthetic polyelectrolyte PolyDADMAC [48,49], and Figure 3 shows its molecular structure. This high cationic charge density polymer provides a more favorable flocculation environment. This chemical component has been extensively used in studies about coagulation and flocculation in wastewater treatment [49,50]. The two levels employed in this experiment to assess the effect of PolyDADMAC on the reduction of color in the wastewater are 1 ppm (lower level) and 5 ppm (upper level).

2.4. Experimental Design Planning

This study uses a jar test to evaluate the main effects of five factors on the coagulation and flocculation behavior of wastewater from a slaughterhouse. It is possible to significantly reduce the number of experimental points while losing a minimum of valuable information by implementing a 2k–p fractional factorial experimental design [21,51]. Therefore, a 25–1 factorial design is proposed to work with half of the treatments of the complete experimental design. In this 2k–p study, k = 5 because there is an interest in studying five factors to reduce the color of wastewater. Moreover, p = 1 because the number of experimental runs will be halved. Table 2 describes the experimental factors with their respective levels of experimentation for this study. This type of design of experiments allows knowing the impact of various factors on a response variable while using a minimum number of runs and blocks of experimentation to quickly and efficiently obtain the cause-effect relationship between the variables evaluated. Assuming that the main effects are more important than the interactions of two factors, it is convenient to use fractional factorial designs with high resolution [18]. The resolution of the experimental design of this study is of type V since the main effects are estimated concerning the alias of triple and higher-order interactions. The experimental runs included four repetitions at the center of each factor to increase the degrees of freedom of the experimental design error up to 19, and the design did not include replications (one block only–BL). The statistical package used was Statgraphics Centurion XVI. With these considerations, the wastewater volume employed for the study was 20 L.

3. Results

Table 3 presents the worksheet developed for a 25−1 factorial design without replications and four repetitions at the center, displayed in lines related to runs 17 to 20. The last column of the table shows the response of the color variable for each assessed combination.
Table 4 presents the analysis of variance (ANOVA) of the main effects examined in a jar test through a factorial design of experiments with a confidence level of 95%. These results suggest that the concentration of the primary coagulant and the velocity gradient are the factors that significantly affect the decrease in the color of the residual water, according to the results obtained in their respective p-value tests. The residence time, pre-chlorination, and coagulation adjuvant factors do not significantly affect the color of the wastewater sample analyzed in the jar test.
Figure 4 displays the contour plot of the response surface for the jar test in terms of the color variations of the wastewater. The color range is between 2700 and 6000 Pt-Co units based on the experimental limits of the primary coagulant and the velocity gradient.
Figure 5 shows the main effects of the factors on the color variable in the wastewater sample from the slaughterhouse. According to the wastewater color trends, as the levels of each factor change from the lowest to the highest level, while the other factors remain constant, the primary coagulant concentration is the variable with the most significant impact on the color decrease. Similarly, increasing the velocity gradient decreases the color of the water sample. The results related to the variation of the residence time and the coagulation adjuvant show no significant incidence in the color of the wastewater.
Figure 6 refers to the normal probability graph of the effects of the factors analyzed in the jar test. In this plot, the standardized effects are ordered from smallest to largest and plotted against quartiles of a normal distribution. In this case, the residence time, coagulation adjuvant, and pre-chlorination factors are aligned to the process noise since they go in the same direction as the straight line of this graph. On the other hand, the coagulant velocity and concentration gradient factors correspond to signals that significantly affect the color of the wastewater sample studied in the jar test.
Figure 7 presents the graph of residuals versus predicted values of the jar test experiment design. This chart displays residuals against predicted values with a horizontal line at zero. It is observed that the residuals vary randomly around the line. The lack of a pattern or trend in this graph suggests that there is no influence of time or any other external factor during the experimental runs.
In correspondence with the symbols proposed for each factor referenced in Table 4, the fitting model according to the results from the 20 experimental runs conducted for this work is:
color = 9428.75 41.44 × A 30.92 × B 9.13 × C 44.33 × D + 38.03 × E
In this case, the adjusted correlation coefficient is 75%, which suggests that this mathematical function relates the main effects to the color of the wastewater at a moderate level.

4. Discussion

Various advanced statistical tools are currently used to intensify and improve industrial wastewater treatment processes [52]. On jar tests for the sizing of wastewater treatment plants, in the use of a statistical tool to detect those variables that commonly demand resources for their operation, such as the consumption of chemicals (coagulants and flocculants) and energy (electric motors to drive agitators) that, not being significant in the response, can operate at a low level of consumption without affecting the purpose of the equipment that recycles wastewater. With these results, optimization strategies can subsequently be established on those physical-chemical parameters of interest in the wastewater, considering the experimental modification of those factors that are statistically representative.
The concentration of primary coagulants is a factor of interest in designing large-scale flocculation systems [53]. According to Figure 5, as the coagulant concentration in the jar test increases, its color tends to decrease. This behavior occurs because higher coagulant concentrations within the volume of the mixture affect the stability of the colloidal organic matter due to the surface phenomena present in the wastewater during coagulation [54]. According to Oriekhova and Stoll, the optimal concentration of primary coagulant depends on the suspended particle’s surface charge, size, and water composition. Their findings indicate that using high concentrations of the primary coagulant generates polymers of considerable size to precipitate by gravity and, therefore, clarify water samples with polystyrene latex particles [55]. The results indicate that implementing the 2k–p factorial experimental design for the jar test allowed identifying the factors that significantly influence color removal from wastewater. The use of DOE techniques facilitates the identification of significant variables, allowing for their optimization, while the other elements involved in the operation process are dimensioned at cost-effective technical-economic levels. This observation is in line with the findings by De Paula et al., who applied DOE techniques to estimate concentration ranges of coagulants, such as aluminum sulfate, ferric chloride, and Moringa oleifera extract (MO), for wastewater treatment in the concrete industry [56]. In this study, the efficiency in the removal of turbidity from wastewater was compared and the results reported in a standardized Pareto diagram show that increasing the concentration of the primary coagulant, whether it is a natural derivative or a traditional chemical coagulant, improves the final quality of the water subjected to the coagulation process. These results coincide with what is reported in Figure 6, which shows that a higher concentration of primary coagulant corresponds with a higher effect on the color removal in the wastewater sample from the slaughterhouse.
The velocity gradient has been analyzed as a criterion for improving the efficiency of flocculation systems [57,58]. According to Figure 6, this study suggests that as the level of the velocity gradient factor increases, the color of the analyzed wastewater decreases. The hydrodynamic effect of mechanical agitation favors the contact of the primary coagulant with the residual water, a necessary condition for the visible formation of flocs [59,60]. Rossini et al. developed statistical optimization strategies based on the influence of rapid mixing for coagulation-flocculation processes in wastewater treatment plants. This research concluded that rapid mixing strongly influences the reduction of wastewater turbidity when coagulation and flocculation are operated with high values of rapid mixing [61]. These results differ from the findings detected in the present study, which may be justified by the type of wastewater treated.
A recent investigation on the phosphate removal efficiency from anaerobic sludge found that coagulant dosage, agitation speed, and residence time significantly impact the elimination of the pollutant [62]. These findings indicate that DOE techniques, such as those used in the present study, might be applied similarly and simultaneously to assess the removal efficiency of different pollutants in wastewater. Unlike the results of this research, in other types of residual water, such as those reported in the textile industry by Keerthi y Vani, the residence time was found to be a significant factor for the application of statistical techniques, such as the response surface methodology, to reduce the color of wastewater from the textile industry [63].
Table 3 shows an increase in the magnitude of the color in those experimental treatments where the concentration gradient and coagulant concentration factors were evaluated at their low levels. This trend is mainly observed in runs 1, 2, 9, and 10 of Table 3. These results confirm the main effects shown in Figure 5, where steeper slopes denote the significant factors. The contour plot in Figure 4 shows a tendency for the color of the water sample to increase if these factors decrease in the coagulation process.
Colombian legislation regulates the discharge of water contaminated by livestock activities [27]. This study used statistical techniques to identify the factors that improve wastewater coagulation from slaughterhouses. Therefore, these experimental techniques can reduce efforts in designing, selecting components, and adjusting technologies that treat wastewater of this nature.
PolyDADMAC polyelectrolyte as a coagulation adjuvant improves the color removal of wastewater from the palm oil extraction industry if the clarification is combined with the primary coagulant ferric chloride [50]. Although the present investigation was carried out with the hypothesis that the combination of ferric chloride and PolyDADMAC reduce the color of wastewater from slaughterhouses, the results of Table 3 and Figure 5 and Figure 6 show that adding this polyelectrolyte to the clarification process does not significantly affect color removal and conversely, suggesting the dosage of this coagulation adjuvant in the coagulation process makes water treatment more expensive. Coagulation is one of the most critical processes in wastewater treatment to reduce the organic load that contributes to color and COD, among other parameters. The experimental runs indicate that the color decreases because of the formation of ferric hydroxide precipitates in the aqueous solution and by the adsorption of ferric precipitates on the surface of the organic load that precipitates. This tendency can be related to the supersaturation in the solution concerning the ferric hydroxide under the chemical conditions considered in the experimental design. The results from this statistical application suggest that wastewater from slaughterhouses can be treated without a coagulation adjuvant or a pre-chlorination stage and even with a minimum dosage of these factors, given its little effect on reducing the sample’s reddish color.

5. Conclusions

A 25−1 fractional factorial experimental design with four repetitions at the center was conducted to evaluate the effects of five factors in the coagulation-flocculation process, for the design of a treatment plant for wastewater from a slaughterhouse, through a jar test. The fractional factorial design allowed reducing the number of experimental points without affecting the minimum information required to identify which factors are significant in reducing the color of a wastewater sample, which makes this DOE technique an appealing option in budget and time-constrained assessments, especially regarding well-known water treatment processes. It was observed that the dose of primary coagulant and the velocity gradient are the two factors that have a statistically significant effect on the color of the residual water. In this sense, operating these factors at higher levels could reduce the color of the wastewater while the rest of the factors, such as residence time, pre-chlorination, and coagulation adjuvant, can be sized at low technical-economic levels. From this study, it is suggested to use statistical experimentation techniques to optimize this process so that, from the economic point of view, the dose of primary coagulant can provide feasibility for the assembly and operation of this water treatment plant. The results of this research apply to color removal, but it is possible that the parameters evaluated and determined to be irrelevant for color could be significant for other response variables related to contaminants or type of industry.

Author Contributions

Conceptualization, J.C. and F.A.C.; methodology, J.C., J.F.-V., F.A.C. and J.V.-D.; software, J.C.; validation, F.A.C., B.K., H.C.T.-Q. and M.J.T.-Q.; formal analysis, J.C. and F.A.C.; resources, J.V.-D., M.J.T.-Q. and H.C.T.-Q.; data curation, J.V.-D.; writing—original draft preparation, J.C., B.K. and F.A.C.; writing—review and editing, J.C. and F.A.C.; supervision, F.A.C. and J.F.-V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The main data associated with this research paper is available at: https://bit.ly/3Ahmy8k (accessed on 10 June 2022).

Acknowledgments

The Authors would like to thank Ernesto Jaramillo and Andrés Carpintero for their collaboration in executing experimental procedures on jar testing equipment.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Experimental design benches.
Figure 1. Experimental design benches.
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Figure 2. Schematic of the wastewater treatment system.
Figure 2. Schematic of the wastewater treatment system.
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Figure 3. Molecular structure of PolyDADMAC.
Figure 3. Molecular structure of PolyDADMAC.
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Figure 4. Contour diagram for the response of the color variable.
Figure 4. Contour diagram for the response of the color variable.
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Figure 5. Main effects graph for color in the wastewater system.
Figure 5. Main effects graph for color in the wastewater system.
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Figure 6. Normal probability plot for this study.
Figure 6. Normal probability plot for this study.
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Figure 7. Residuals versus predicted plot.
Figure 7. Residuals versus predicted plot.
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Table 1. Average water quality parameters measured at the wastewater treatment plant.
Table 1. Average water quality parameters measured at the wastewater treatment plant.
Before the TreatmentAfter the Treatment
ParameterRaw Wastewater, ppmOutput from Maturation Lagoon, ppmParameterSampling Point at the Oxidation Reactor, ppm
DBO52690646DBO572
DQO4201813DQO178
SST2070233
Grease and oils61721
DETERGENTS3.42.61
Table 2. Experimental factor and its levels of experimentation.
Table 2. Experimental factor and its levels of experimentation.
FactorUnitsLow Level (−1)Intermediate Level (0)High Level (+1)
A: Residence timeminutes123
B: Velocity gradientrpm3065100
C: Coagulant concentrationppm100350600
D: Pre-chlorinationppm02.55
E: Coagulation adjuvantppm135
Table 3. Experimental design worksheet and color variable response.
Table 3. Experimental design worksheet and color variable response.
RunBLABCDEColor (Pt-Co)
11−1−1−1−1+18460
21+1−1−1−1−17740
31−1+1−1−1−15640
41+1+1−1−1+14325
51−1−1+1−1−11400
61+1−1+1−1+13840
71−1+1+1−1+11340
81+1+1+1−1−1640
91−1−1−1+1−17260
101+1−1−1+1+16875
111−1+1−1+1+14320
121+1+1−1+1−16140
131−1−1+1+1+13460
141+1−1+1+1−12120
151−1+1+1+1−1950
161+1+1+1+1+1487
171000006560
181000001420
191000005700
201000004200
Table 4. ANOVA of the experimental design.
Table 4. ANOVA of the experimental design.
SourceSum of SquaresDegrees of
Freedom
Mean SquareF-Ratiop-Value
A: Residence time27,473.1127,473.10.020.9014
B: Velocity gradient1.87337 × 10711.87337 × 10710.850.0053
C: Coagulant concentration8.33706 × 10718.33706 × 10748.280.0000
D: Pre-chlorination196,471.01196,471.00.110.7409
E: Coagulation adjuvant92,568.1192,568.10.050.8203
Total Error2.41754 × 107141.72681 × 106
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Carpintero, J.; Villa-Dominguez, J.; Tavera-Quiroz, M.J.; Tavera-Quiroz, H.C.; Kaźmierczak, B.; Fábregas-Villegas, J.; Canales, F.A. Application of a 2k–p Fractional Experimental Design in Coagulation-Flocculation Processes in the Treatment of Wastewater from a Slaughterhouse. Sustainability 2022, 14, 10402. https://doi.org/10.3390/su141610402

AMA Style

Carpintero J, Villa-Dominguez J, Tavera-Quiroz MJ, Tavera-Quiroz HC, Kaźmierczak B, Fábregas-Villegas J, Canales FA. Application of a 2k–p Fractional Experimental Design in Coagulation-Flocculation Processes in the Treatment of Wastewater from a Slaughterhouse. Sustainability. 2022; 14(16):10402. https://doi.org/10.3390/su141610402

Chicago/Turabian Style

Carpintero, Javier, Jennifer Villa-Dominguez, María José Tavera-Quiroz, Humberto Carlos Tavera-Quiroz, Bartosz Kaźmierczak, Jonathan Fábregas-Villegas, and Fausto A. Canales. 2022. "Application of a 2k–p Fractional Experimental Design in Coagulation-Flocculation Processes in the Treatment of Wastewater from a Slaughterhouse" Sustainability 14, no. 16: 10402. https://doi.org/10.3390/su141610402

APA Style

Carpintero, J., Villa-Dominguez, J., Tavera-Quiroz, M. J., Tavera-Quiroz, H. C., Kaźmierczak, B., Fábregas-Villegas, J., & Canales, F. A. (2022). Application of a 2k–p Fractional Experimental Design in Coagulation-Flocculation Processes in the Treatment of Wastewater from a Slaughterhouse. Sustainability, 14(16), 10402. https://doi.org/10.3390/su141610402

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