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Appl. Sci. 2020, 10, 8687 4 of 18 experiments (on axes, distance of ±α from center of rotation, α = ±1.682), k = 6 (experiments in the center of variation field, for the independent estimation of “pure” experimental error variance, data reproducibility) [30–33]. Y = b0 + ni=1 biXi + ni,j=1 bjiXiXj, (2) where Y is the response function (removal degree, [%]); Xi or Xj is the coded selected variable in the SD treatment system (n = 20); i, j = 1 or 2; b0, bi, bj, bij are the model coefficients. The model coefficients are estimated using statistics for the processing of the experimental results obtained in the central points of the central composite rotatable design, according to the equations presented in previous reports [30,31]. In the active central composite rotatable (23) design, a basic value zi0 and a variation step ∆zi0 of each independent variable zi (flowrate, rotational speed, or operating time) were established. The coded value of zi, denoted as Xi, was determined with Equation (3) [30,31,33]: Xi = (zi − zi0)/∆zi0. (3) The upper level is coded with 1, the lower level with −1, and the basic level with 0. There are other possible values of the variable level (αi = ±1.682) [27–29]. The model validation was carried out by an appropriate analysis of variance, consisting of: (i) the calculation of the F constant and its comparison with the statistical value; (ii) the calculation of the multiple correlation coefficient in order to establish the correlation between the dependent variable (Y) and the three independent variables (Xi) as a whole; (iii) the determination of the coefficient’s significance using the Student test, for a certain significance level (p = 0.05) and degrees of freedom (ν1 = n − 1 and ν2 = k − 1) [30,31,33]; (iv) the application of the Fisher test to calculate the Fc value and to compare it with the statistical value; and (v) the calculation of deviation (A) between the calculated values with the proposed model and the experimental data, which must be between +10% and −10% for a good data agreement. The optimal values of independent variables are determined using the classical optimization by the analysis of first- and second-order derivatives systems [30]. 3. Results The studied textile wastewaters were produced in a NE Romanian textile company that manufactures cotton fabrics colored from yellow to red during the period time of this study. The main textile wastewater (WW) characteristics treated in the SD system and their maximum admissible values are presented in Table 1. Quality Indicators pH Colour, [HU] (A436 ) Suspended solids Turbidity, [FTU] Fixed residues COD, [mg O2/L] CBO5, [mg O2/L] Synthetic detergents Measured Value [mg/L] 7.12–7.89 865–4450 (1.200–2.620) 382–930 180–815 3580–4020 560–655 320 1.70–2.50 M.A.C. * [mg/L] 6.50–8.50 50 35 (60) - 1000 125 25 0.50 Quality Indicators Total p Extractible substances Total n Ammonia Sulfates Chlorides Phenol index Total heavy metal ions Measured Value, [mg/L] 5.70–6.45 25.50–31.80 8.30–10.00 2.0–2.75 780–850 95–150 2.60–3.50 <4 M.A.C. * [mg/L] 1 20 10 2 600 70 0.30 <2 (max 5) Table 1. The principal characteristics of the studied textile wastewater. * M.A.C.—maximum admissible concentration, according to the Romanian Government Decision No. 352/2005: Technical Norms for Treated Wastewater Discharged in Natural Water Resources (NTPA 001). As shown in Table 1, some physical-chemical quality indicators of the tested WW are exceeding the maximum admissible limits, especially color (more than 17–89 timefolds), suspended solids (more than 11–26 timefolds), turbidity (more than 36–80 times considering a reference value ofPDF Image | Textile Wastewater Treatment on a Spinning Disc Reactor
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