Optimizing Process Parameters on the Remediation Efforts for the Mass Removal of DNAPL Entrapped in a Porous Media

  • Mutala Mohammed
  • Ismail Ozbay
  • Gokce Akyol
  • Nihat Hakan AkyolEmail author
  • Yıldız Sahin
  • Bilge Ozbay
  • Sevgi Turkkan
  • Tuna Karatas


In the present study, the Taguchi design (TD) and the Box-Behnken design (BBD) were used to determine the effect of surfactant concentration, flushing velocity, and dense non-aqueous-phase liquid–trichloroethylene (DNAPL TCE) mass on the time of remediation for the removal of DNAPL zones, which is one of the main persistent sources of groundwater pollution. In the Taguchi approach, the performance of the response variable is measured based on the signal-to-noise (S/N) ratio whereas estimation of the full quadratic model of the parameters is allowed in the Box-Behnken design. The mean experimental values ranged between 3.97–8.31 and 4.01–9.70 for BBD and TD, respectively. Surfactant concentration was identified as the most significant parameter contributing to remediation efficiency in both design techniques. Minimum remediation effort was determined as 5.99 at obtained optimal conditions of surfactant concentration (2.5%), flushing rate (6 cm/h), and DNAPL TCE mass (365 mg) using BBD. In the case of TD, the optimal conditions were determined at a surfactant concentration of 10%, 2 cm/h flushing rate, and 365 mg DNAPL TCE mass. Analysis of variance (ANOVA) revealed a good relationship between the predicted and experimental values with 1.96% and 0.31% of the total variation that was not explained by the model using TD and BBD, respectively. Consequently, from this comparative study, it was concluded that BBD was a more suitable alternative to TD for the evaluation of remediation of DNAPL-contaminated sites.


Optimization Remediation Groundwater pollution Taguchi Box-Behnken design 



This study was funded by TUBİTAK 115Y117. The authors would like to show their appreciation to Dr. Mutala Mohammed for his immense contribution to the optimization analysis.


  1. Akyol, N. H. (2018). Surfactant-enhanced permanganate oxidation on mass-flux reduction and mass removal relationship for pool-dominated TCE source zones in heterogeneous porous media. Water, Air, and Soil Pollution, 229, 285.CrossRefGoogle Scholar
  2. Akyol, N. H., & Turkkan, S. (2018). Effect of cyclodextrin-enhanced dissolution on mass removal and mass-flux reduction relationships for non-uniformly organic liquid distribution in heterogeneous porous media. Water, Air, & Soil Pollution, 229, 30.CrossRefGoogle Scholar
  3. Akyol, N. H., Lee, A. R., & Brusseau, M. L. (2013). Impact of enhanced-flushing reagents and organic liquid distribution on mass removal and mass discharge reduction. Water, Air, and Soil Pollution, 224, 1731.CrossRefGoogle Scholar
  4. Anwar, M., Rasul, M. G., & Ashwath, N. (2018). Production optimization and quality assessment of papaya (Carica papaya) biodiesel with response surface methodology. Energy Conversion and Management, 156, 103–112.CrossRefGoogle Scholar
  5. Arslan, A., Topkaya, E., Bingol, D., & Veli, S. (2018). Removal of anionic surfactant sodium dodecyl sulfate from aqueous solutions by O3/UV/H2O2 advanced oxidation process: process optimization with response surface methodology approach. Sustainable Environment Research, 28(2), 65–71.CrossRefGoogle Scholar
  6. Betiku, E., & Taiwo, A. E. (2015). Modeling and optimization of bioethanol production from breadfruit starch hydrolyzate vis-a-vis response surface methodology and artificial neural network. Renewable Energy, 74, 87–94.CrossRefGoogle Scholar
  7. Bezerra, M. A., Santelli, R. E., Oliveiraa, E. P., Villar, L. S., & Escaleiraa, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta, 76, 965–977.CrossRefGoogle Scholar
  8. Boving, T. B., & Brusseau, M. L. (2000). Solubilization and removal of residual trichloroethene from porous media: comparison of several solubilization agents. Journal of Contaminant Hydrology, 42, 51–67.CrossRefGoogle Scholar
  9. Carroll, K. C., & Brusseau, M. L. (2009). Dissolution, cyclodextrin-enhanced solubilization, and mass removal of an ideal multicomponent organic liquid. Journal of Contaminant Hydrology, 106(1–2), 62–72.CrossRefGoogle Scholar
  10. DiFilippo, E. L., & Brusseau, M. L. (2008). Relationship between mass flux reduction and source zone mass removal: analysis of field data. Journal of Contaminant Hydrology, 98(1–2), 22–35.CrossRefGoogle Scholar
  11. Difilippo, E. L., Carroll, K. C., & Brusseau, M. L. (2010). Impact of organic-liquid distribution and flow-field heterogeneity on reductions in mass flux. Journal of Contaminant Hydrology, 115, 14–25.CrossRefGoogle Scholar
  12. Esfandiar, N., Nasernejad, B., & Ebadi, T. (2014). Removal of Mn(II) from groundwater by sugarcane bagasse and activated carbon (a comparative study): application of response surface methodology (RSM). Journal of Industrial and Engineering Chemistry, 20, 3726–3736.CrossRefGoogle Scholar
  13. Harvell, J.R. (2012) Solubilization of multi-component immiscible liquids in homogeneous systems: a comparison of different flushing agents using a 2-D flow-cell. The University of Alabama M.S Thesis at Geological Science Department.Google Scholar
  14. Ido, A. L., Luna, M. D. G., Capareda, S. C., Maglinao, A. L., Jr., & Nam, H. (2018). Application of central composite design in the optimization of lipid yield from Scenedesmus obliquus microalgae by ultrasonic-assisted solvent extraction. Energy, 157, 949–956.CrossRefGoogle Scholar
  15. Khodaei, K., Nassery, H. R., Asadi, M. M., Mohammadzadeh, H., & Mahmoodlu, M. G. (2017). BTEX biodegradation in contaminated groundwater using a novel strain (Pseudomonas sp. BTEX-30). International Biodeterioration & Biodegradation, 116, 2134–2242.CrossRefGoogle Scholar
  16. Kilavuz, S. A., & Akyol, N. H. (2018). TCE Kaynak Zonların Yerinde Kimyasal Yıkama ile Islahı: Tween 80 ve SDS ile Yıkama Performansı. Dokuz Eylul Üniversity-Faculty of Engineering. Journal of Science and Engineering, 20(58), 197–208.Google Scholar
  17. Mahal, M. K., Murao, A., Johnson, G. R., Russo, A., & Brusseau, M. L. (2010). Non-ideal behavior during complete dissolution of organic immiscible liquid: 2. Ideal porous media. Water, Air, and Soil Pollution, 213, 191–197.CrossRefGoogle Scholar
  18. Martínez-Villafane, J. F., & Montero-Ocampo, C. (2010). Optimisation of energy consumption in arsenic electro-removal from groundwater by the Taguchi method. Separation and Purification Technology, 70, 302–305.CrossRefGoogle Scholar
  19. McCray, J. E., & Brusseau, M. L. (1999). Cyclodextrin-enhanced in situ flushing of multiple-component immiscible organic liquid contamination at the field scale: analysis of dissolution behavior. Environmental Science & Technology, 33(1), 89–95.CrossRefGoogle Scholar
  20. Moosavi, V., Vafakhah, M., Shirmohammadi, B., & Ranjbar, M. (2014). Optimization of wavelet-ANFIS and wavelet-ANN hybrid models by Taguchi method for groundwater level forecasting. Arabian Journal for Science and Engineering, 39, 1785–1796.CrossRefGoogle Scholar
  21. Mutala, M., Ismail, O., Aykan, K., & Augustine, D. (2018). Effect of waste matrix for the optimization of moisture content and calorific value of bio-dried material using Taguchi DOE. Drying Technology. Scholar
  22. Özdemir, U., Özbay, B., Özbay, İ., & Veli, S. (2014). Application of Taguchi L32 orthogonal array design to optimize copper biosorption by using Sphagnum moss. Ecotoxicology and Environmental Safety, 107, 229–235.CrossRefGoogle Scholar
  23. Prasad, K. S., Rao, S., & Rao, N. (2012). Application of design of experiments to plasma arc welding process: a review. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 34, 75–81.Google Scholar
  24. Rosa, J. L., Robin, A., Silva, M. B., Baldan, C. A., & Peres, M. P. (2009). Electrodeposition of copper on titanium wires: Taguchi experimental design approach. Journal of Materials Processing Technology, 209, 1181–1188.CrossRefGoogle Scholar
  25. Russo, A., Mahal, M. K., & Brusseau, M. L. (2009). Nonideal behavior during complete dissolution of organic immiscible liquid: 1. Natural porous media. Journal of Hazardous Materials, 172, 208–213.CrossRefGoogle Scholar
  26. Taguchi, G., Chowdhury, S., & Wu, Y. (2005). Taguchi’s quality engineering handbook. Livonia: ASI Consulting Group, LLC.Google Scholar
  27. Tarley, C. R. T., Silveira, G., dos Santos, W. N. L., Matos, G. D., da Silva, E. G. P., Marcos Almeida Bezerra, M. A., Miró, M., & Ferreira, S. L. C. (2009). Chemometric tools in electroanalytical chemistry: methods for optimization based on factorial design and response surface methodology. Microchemical Journal, 92, 58–67.CrossRefGoogle Scholar
  28. Tick, G. R., & Rincon, E. (2009). Effect of enhanced solubilization agents on dissolution and mass flux from uniformly distributed immiscible liquid trichloroethylene (TCE) in homogeneous porous media. Water, Air, and Soil Pollution, 204, 315–332.CrossRefGoogle Scholar
  29. Tick, G. R., Lourenso, F., Wood, A. L., & Brusseau, M. L. (2003). Pilot-scale demonstration of cyclodextrin as a solubility-enhancement agent for the remediation of a tetrachloroethene-contaminated aquifer. Environmental Science & Technology, 37, 5829–5834.CrossRefGoogle Scholar
  30. Tick, G. R., Harvell, J. R., & Murgulet, D. (2015). Intermediate-scale investigation of enhanced-solubilization agents on the dissolution and removal of a multicomponent dense non-aqueous phase liquid (DNAPL) source. Water, Air, and Soil Pollution, 226, 371.CrossRefGoogle Scholar
  31. Wantala, K., Khongkasem, E., Khlongkarnpanich, N., Sthiannopkao, S., & Kim, K. W. (2012). Optimization of As(V) adsorption on Fe-RH-MCM-41-immobilized GAC using Box–Behnken design: effects of pH, loadings, and initial concentrations. Applied Geochemistry, 27, 1027–1034.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mutala Mohammed
    • 1
    • 2
  • Ismail Ozbay
    • 2
  • Gokce Akyol
    • 3
    • 4
  • Nihat Hakan Akyol
    • 5
    Email author
  • Yıldız Sahin
    • 4
  • Bilge Ozbay
    • 2
  • Sevgi Turkkan
    • 5
  • Tuna Karatas
    • 6
  1. 1.CSIR-Institute of Industrial ResearchLegonGhana
  2. 2.Department of Environmental EngineeringKocaeli UniversityKocaeliTurkey
  3. 3.Degirmendere Ali Ozbay Vocational SchoolKocaeli UniversityKocaeliTurkey
  4. 4.Department of Industrial EngineeringKocaeli UniversityKocaeliTurkey
  5. 5.Department of Geological EngineeringKocaeli UniversityKocaeliTurkey
  6. 6.Faculty of ScienceCharles UniversityPrague 2Czech Republic

Personalised recommendations