Response surface methodological (RSM) approach for optimizing the removal of trihalomethanes (THMs) and its precursor’s by surfactant modified magnetic nanoadsorbents (sMNP) - An endeavor to diminish probable cancer risk

Abstract

Response surface methodology (RSM) approach was used for optimization of the process parameters and identifying the optimal conditions for the removal of both trihalomethanes (THMs) and natural organic matter (NOM) in drinking water supplies. Co-precipitation process was employed for the synthesis of magnetic nano-adsorbent (sMNP), and were characterized by field emission scanning electron microscopy (SEM), trans-emission electron microscopy (TEM), BET (Brunauer-Emmett-Teller), energy dispersive X-ray (EDX) and zeta potential. Box-Behnken experimental design combined with response surface and optimization was used to predict THM and NOM in drinking water supplies. Variables were concentration of sMNP (0.1 g to 5 g), pH (4–10) and reaction time (5 min to 90 min). Statistical analysis of variance (ANOVA) was carried out to identify the adequacy of the developed model, and revealed good agreement between the experimental data and proposed model. The experimentally derived RSM model was validated using t-test and a range of statistical parameters. The observed R2 value, adj. R2, pred. R2 and “F-values” indicates that the developed THM and NOM models are significant. Risk analysis study revealed that under the RSM optimized conditions, a marked reduction in the cancer risk of THMs was observed for both the groups studied. Therefore, the study observed that the developed process and models can be efficiently applied for the removal of both THM and NOM from drinking water supplies.

Ultrasound-Assisted Extraction Optimization of Proanthocyanidins from Kiwi (Actinidia chinensis) Leaves and Evaluation of Its Antioxidant Activity

“…Three-dimensional response surface and contour plots ( Figure 4 ) were used to illustrate the interactive effects between four independent variables and the extraction yield of PAs [ 51 ]. The PAs ( z -axis) were plotted against two independent variables while keeping the rest of the variables at a fixed level.…”

“…Moreover, Caco-2 was more sensitive to PAs compared to HepG-2. Kumari and Gupta [ 51 ] reported a marked reduction in probable cancer under RSM optimized conditions. In addition, the mechanistic and preclinical studies demonstrated that the capacity of PAs to modulate the several factors related to colorectal cancer is based on its polymerization degree [ 56 ].…”

Statistical Optimization of Biodiesel Production from Salmon Oil via Enzymatic Transesterification: Investigation of the Effects of Various Operational Parameters

“…The main objective of response surface methodology is to optimize the response as per the needs of the study. Response surface methodology reduces the number of experiments needed to determine the optimal parameters for the process [30,31]. In the present study, the transesterification process was optimized using response surface methodology to maximize the biodiesel yield, and the influence of the main reaction parameters, including enzyme concentration, oil/alcohol molar ratio, temperature, and time, was investigated.…”

Optimization of Strontium Removal Process From Contaminated Water Using Zeolite Nanocomposites

“…Response surface methodology (Bingöl 2011;Kumari and Gupta 2019;Abdulgader et al 2020) is used to recognize the optimum combination of the factors and their interactions with minimum effort, which is not possible in the traditional statistical analysis. Levels for different factors are assigned in Table 1.…”