Evaluation of effective parameters in washing of PAH-contaminated soils using response surface methodology approach

Gitipour, Saeid; Mohebban, Ali; Ghasemi, Soroush; Abdollahinejad, M.; Abdollahinejad, Behnaz

doi:10.1007/s13762-019-02368-6

Cited by 9 publications

(12 citation statements)

References 37 publications

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“…Moreover, increasing the temperature would lead to a rise in diameter of micelles, that would enhance solubilization. This is consistent with the findings of other studies that had found this parameter important in soil washing [26,51]. Among the different washing solutions, the improvement in the results for SDS was more dramatic.…”

Section: Temperaturesupporting

confidence: 92%

“…Compared to using single surfactant, it is believed that using a mixture of different surfactants, can cause synergism to happen [15]. The synergistic solubilization of HOCs in anionic/nonionic mixed surfactant has been observed in various research [25][26][27][28]. This synergism is because the mixed anionic/nonionic surfactants generally show smaller CMCs, higher cloud point and lower Krafft point [29].…”

Section: Introductionmentioning

confidence: 99%

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Applicability of an anionic-nonionic surfactant in p-cresol contaminated soil washing: Finding the optimal mixing ratio

Mohebban

Yaghoobzadeh

Gitipour

et al. 2020

J Environ Health Sci Engineer

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In this study, the parameters influencing p-cresol removal efficiency in soil washing method were investigated. Primarily, extraction efficiencies of three Tween series surfactants (Tween 20, Tween 60, Tween 80) with 10 mM concentration were compared. Tween 80 showed the best results since its value (55%) was 4% and 13% higher than that of Tween 60 and Tween 20. The impact of mixed surfactant on extraction rate was examined by employing a mixture of Tween 80 and one anionic surfactant (sodium dodecyl sulfate) with different molar ratio as the main washing solution. The results denoted that the molar ratio of 3:2 (SDS:Tween80) could enhance the extraction rate up to 38% compared to using SDS and Tween 80 alone. Regarding the initial p-cresol concentration in the collected sample, the cleanup level (390 mg/kg) could only be achieved using the mixed-surfactant. Thus, the minimum required surfactant concentrations to hit the target level was calculated to be 3.54 g/L of Tween 80 and 2.105 g/ L of SDS (molar ratio of 0.27 SDS:Tween80). Studying the role of surfactant concentration indicated that its increment from 10 mM to 20 mM, which is way above all the reagents' critical micelle concentration (CMC), does not affect the removal rate considerably. The same results were obtained comparing the effect of washing time in three different levels (30 min, 60 min and 90 min). However, temperature showed to be a more significant parameter as it could enhance the results up to 20% (for SDS).

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Section: Temperaturesupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Applicability of an anionic-nonionic surfactant in p-cresol contaminated soil washing: Finding the optimal mixing ratio

Mohebban

Yaghoobzadeh

Gitipour

et al. 2020

J Environ Health Sci Engineer

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“…e three factors studied varied within a predetermined range, and the output (i.e., removal rate) was evaluated to compare the removal process of each PAH, so as to obtain the model of the total removal rate of PAHs and finally obtain the optimal conditions related to the parameters studied. In addition, the established secondary model for removing PAHs also has a high correlation coefficient [46]. Ramalhosa and others established a microwave-assisted extraction (MAE)-liquid chromatographyphotodiodearray (LC-PDA) combined fluorescence detection method and used response surface methodology to find the optimal extraction parameters.…”

Section: E Response Surface Methodmentioning

confidence: 99%

Research Progress of Polycyclic Aromatic Hydrocarbons Pretreatment Methods and Application of Computer Simulation Technology for Prediction and Degradation of Electrochemical Concentration Detection

Chang

2022

Journal of Chemistry

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Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds that are composed of aromatic rings containing only carbon and hydrogen atoms. They are one of the widespread environmental pollutants in the world. In recent years, many scholars have focused on the inhibition, formation mechanism, content of active components, and biodegradation effect of polycyclic aromatic hydrocarbons. They summarized the research progress of pretreatment methods for detection, but rarely discussed the experimental dataset for comprehensive analysis of pollution sources and the impact of different pretreatment technologies on the extraction of different substrates. What is more, computer simulation has not been mentioned. In this study, the pollution sources of polycyclic aromatic hydrocarbons (PAHs) are reviewed, and the related applications of various pretreatment methods such as gel permeation chromatography (GPC) are summarized. Finally, the computer simulation of the response surface method is introduced. The concentration of polycyclic aromatic hydrocarbons is tested or predicted by combining the neural network with the alternating trilinear decomposition (ATLD) algorithm, artificial population algorithm (ABC), and hierarchical genetic algorithm (HGA). Its future development trend is discussed and prospected, which provides a reference for solving the pollution problem. We look forward to providing help for the follow-up research of scholars in this field.

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“…With a reasonable number of design points and reliable curvature estimates, CCD is an ideal method for assigning operational individual variables to an evaluation range in order to obtain a reasonable amount of information for testing lack-of-fit . Gitipour et al . investigated effective parameters in washing of contaminated soils by polycyclic aromatic hydrocarbons (PAHs) using a response surface methodology.…”

Section: Introductionmentioning

confidence: 99%

Response Surface Methodology for the Optimization of Zn-Contaminated Soil Remediation by Soil Washing with Water-Soluble Chitosan

Niu

Shen

et al. 2022

ACS Omega

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Soil washing is an important method for the remediation of contaminated soil. This research presents the optimization of soil washing conditions in the remediation of Zn-contaminated soils with water-soluble chitosan (WSCS). Response surface methodology (RSM) was used to optimized the washing conditions after single factor experiments. The central composite design (CCD) with three factors and five levels was applied to the optimization of the removal efficiency of Zn from soils, and WSCS concentration, pH value, and washing time were evaluated variables in the washing process. Results indicated that the pH value (p < 0.0001) was the most significant factor which mainly affected the distribution and content of metal species in aqueous solution, ion exchange and adsorption/desorption behavior of metals, solubility of chelating agent, as well as readsorption of metal complexes. The optimal conditions for the Zn removal from soils were WSCS concentration of 1.5%, pH of 3.3, and washing time of 72 min. The removal efficiency could reach 65.4% under the optimized conditions, which was close to the predicted value of 68.3% by the response surface method. Therefore, it could be found that the response surface methodology was an effective method to determine the optimal conditions for the removal of metals from contaminated soils by soil washing.

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Evaluation of effective parameters in washing of PAH-contaminated soils using response surface methodology approach

Cited by 9 publications

References 37 publications

Applicability of an anionic-nonionic surfactant in p-cresol contaminated soil washing: Finding the optimal mixing ratio

Applicability of an anionic-nonionic surfactant in p-cresol contaminated soil washing: Finding the optimal mixing ratio

Research Progress of Polycyclic Aromatic Hydrocarbons Pretreatment Methods and Application of Computer Simulation Technology for Prediction and Degradation of Electrochemical Concentration Detection

Response Surface Methodology for the Optimization of Zn-Contaminated Soil Remediation by Soil Washing with Water-Soluble Chitosan

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