Optimizing Three Kinds of Coagulants Using Plackett-Burman and Response Surface Methodology for Phosphorus Removal from Domestic Sewage

Abstract

This study compounds three types of coagulants (AlCl 3 , FeCl 3 , Fe 2 (SO 4) 3) with promising effects on TP removal of domestic sewage. The optimum conditions for TP removal using 1 compounded coagulants are determined by Plackett-Burman (P-B) design, steepest ascent, and Box-Behnken design. The adequacy of the quadratic regression model is evaluated by analysis of variance (ANOVA). Results show that initial pH, AlCl 3 , and Fe 2 (SO 4) 3 are the significant factors for TP removal. F-test, P-value (Prob>F), coefficients R 2 , coefficient of variation, and adequate precision analysis demonstrated the goodness of fit for the regression model. The optimized conditions for TP removal determined by the response surface methodology are initial pH 5.2, AlCl 3 45 mg/L, and Fe 2 (SO 4) 3 51 mg/L, respectively. The experimental TP removal efficiency (82.89%) agrees with the predicted response value (81.99%), thereby validating the feasibility of the model. Compared to single coagulants (AlCl 3 , FeCl 3 , Fe 2 (SO 4) 3), the compounded coagulants demonstrate 3.29%, 7.59%, and 15.19% higher for TP removal; and 10.1%, 3.0%, and 10.3%

Simultaneous Improvement of Lincomycin a Production and Reduction of Lincomycin B Levels in Streptomyces Lincolnensis Using a Combined Medium Optimization Approach

“…Plackett-Burman design to improve lincomycin A production in S. lincolnensis fermentation PBD was developed using Design-Expert software (Wang et al 2019). The design matrix selected for the screening of signi cant variables for lincomycin A and lincomycin B production (Table 2).…”

“…For example, Plackett-Burman design (PBD), the steepest ascent method, and Box-Behnken Design (BBD) have all been successfully applied for determining the components or variables that have signi cant effects on the production of primary or secondary metabolites and have statistically optimized metabolic production (Di et al 2017;Wang et al 2019). By optimizing media components, the yield of lincomycin A was increased from 1 g/L to 3.5 g/L (Luthra et al 2019).…”

Numerical Simulation and Optimization of Screening Process for Vibrating Flip-Flow Screen Based on Discrete Element Method–Finite Element Method–Multi-Body Dynamics Coupling Method

“…The analysis included the screening efficiency (η) and material velocity (v) with various parameters. The experimental plan and results based on the Box-Behnken design [34,35] are shown in Table 5. A total of 43 experiments were conducted, including 5 central replicates for error testing and rationality assessment.…”

Simultaneous improvement of lincomycin A production and reduction of lincomycin B levels in Streptomyces lincolnensis using a combined medium optimization approach

“…PBD was developed using Design-Expert software (Wang et al 2019). The design matrix selected for the screening of significant variables for lincomycin A and lincomycin B production (Table 2).…”

“…For example, Plackett-Burman design (PBD), the steepest ascent method, and Box-Behnken Design (BBD) have all been successfully applied for determining the components or variables that have significant effects on the production of primary or secondary metabolites and have statistically optimized metabolic production (Di et al 2017;Wang et al 2019). By optimizing media components, the yield of lincomycin A was increased from 1 g/L to 3.5 g/L (Luthra et al 2019).…”