DOE method allows researchers to optimize endocrine disrupter removal from wastewater
by Hubert Cabana and J. Peter Jones, Department of Chemical Engineering, University of Sherbrooke, Quebec, Canada
An endocrine disrupting chemical (EDC) is a synthetic chemical that either mimics or blocks hormones and disrupts the body’s normal functions when absorbed into the body. EDCs can pass through wastewater treatment systems that are not currently designed to remove them. A team of researchers recently performed a designed experiment to evaluate potential methods for removing three common endocrine disrupters. The researchers treated solutions containing the EDCs nonlyphenol (NP), bisphenol A (BPA) and triclosan (TCS) with an enzyme preparation from the white rot fungus Coriolopsis polyzona.
Click here for more information about the potential risk posed by EDCs.
Study Designed to Advance EDC Removal Methods
Figure 1. Effect of temperature and (Ο) pH 3, (⟨) pH 4 and (◊) pH 5 on the degradation of BPA after a 4-hour treatment with 10 U/L of laccase of C. polyzona.Click to enlarge
The two goals of this study were to evaluate the effectiveness of the removal of NP, BPA and TCS with WRF enzymes and to assess the transformation mechanisms by identifying the metabolites that were produced. The researchers also wanted to be sure that the elimination of the EDCs did not produce metabolites with estrogenic activity. The researchers were well aware that the effectiveness of the removal of the EDCs could be affected by factors such as temperature and pH. This meant that accurate assessment of the effectiveness of the enzymes in removing EDCs required determining the effect of these factors and evaluating EDC removal with the factors optimized.
The conventional approach to optimizing the factors would be to run a series of experiments while varying a single factor. The problem with this approach is that it does not detect interactions between factors or second order effects. As a result, the researchers decided to use the design of experiments (DOE) method that varies the values of all variables in parallel so it uncovers not just the main effects of each variable but also the interactions between the variables. This approach makes it possible to identify the optimal values for all variables in combination. It also requires far fewer experimental runs than the one-factor-at-a-time (OFAT) approach.
Designing experiments and analyzing the results using DOE can be time consuming and error prone when manual methods are used. General-purpose statistical tools can do the job but tend to be unintuitive and limited in their choice of experimental designs and results analysis techniques. The researchers chose to use Design-Expert® DOE software from Stat-Ease, Inc. (Minneapolis, MN), because it provideed a wide range of experimental designs and statistical methods to analyze the results.
The researchers decided to look at the following factors:
A. Temperature (20 C vs. 40 C vs. 50 C)
B. pH (3 vs. 4 vs. 5)
Design-Expert software generated a full-factorial experiment with 9 runs for each substance to be removed. Each combination was replicated three times in a randomized run plan. The researchers mixed 5 mg/L of each NP, BPA or TCS, 5 U/L catalase from Aspergillus niger, crude enzyme preparation from C. polyzona, citric acid/di-sodium hydrogen phosphate buffer, and 1% v/v methanol. NP, BPA and TCS were extracted from the mixture and analyzed on a high-performance liquid chromatography system. The estrogenic activity of the treated system was compared to the system before treatment. Mass spectroscopy was used to identify high molecular weight metabolites. The results of the experiment were entered into Design-Expert, and the software analyzed the statistical results.
DOE Results Identify Optimal EDC Removal Conditions
Figure 2. 3-D graph view of the effect of temperature and pH on the degradation of BPA.
A statistical analysis of variance (ANOVA) of the model highlights the significant impact of temperature and pH on the enzymatic transformation of NP, BPA and TCS. This analysis was used to determine the best conditions for enzymatic transformation of the three EDCs. The results showed that 50 C was the best temperature for the removal of NP and TCS, while the results for 40 C and 50 C were not significantly different in the case of BPA. A pH of 5 gave the best results for all three compounds studied. These results can be explained by the higher stability produced by a higher pH and the higher catalytic activity resulting from a higher temperature.
The coefficient of determination (R2) value provides a measure of how much variability in the observed response values can be attributed to the experimental factors and their interactions. The R2 values of 0.995 for NP, 0.996 for BPA, and 0.994 for TCS suggests that the fitted linear-plus interactions models can explain 99.5%, 99.6% and 99.4% respectively of the total variation. The F-values were 426.0 for NP, 622.5 for BPA and 361.3 for TCS. Those values together with a p value of 0.001 for all eliminations indicated that the present models are statistically significant and can predict the experimental results well.
The ANOVA analysis highlighted the significant influence of temperature and pH on the degradation of NP, BPA and TCS. A temperature of 50 C is optimal for the degradation of NP and TCS, and a temperature of 40 C and 50 C showed the same impact on the degradation of BPA. A pH of 5 is optimal for the laccase-mediated degradation of these phenolic compounds. These results are in agreement with a combination of stability produced by a higher pH and catalytic activity resulting from a higher temperature. Figure 1 shows the impact of the parameters on the laccase-catalyzed elimination of BPA as a function of pH and temperature after a 4-hour batch treatment. Figure 2 is a 3-D representation of this information.
The half-life of laccase activity was estimated to be 4 hours, 6 hours and 16 hours at 3, 4 and 5 pH respectively and a temperature of 40 C. Eliminating NP and BPA was directly associated with the disappearance of estrogen activity. Mass spectrometry analysis showed that the enzymatic treatment produced high molecular weight metabolites through a radical polymerization mechanism of NP, BPA and TCS.
The researchers believed that DOE played a critical role in their study by exploring the entire design space and helping them to identify the optimal conditions for removing the EDCs, which may lead to industrial-scale methods for removing EDCs as part of the wastewater treatment process.
For more information, contact J. Peter Jones, Department of Chemical Engineering, University of Sherbrooke, at Peter.Jones@USherbrooke.ca or by phone at 819-821-8000 x62165.
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