2,4-Dichlorophenoxyl acetic acid (2,4-D) and glyphosate are used extensively as a herbicide in vicinity of Antalya, Turkey. Laboratory batch experiments were conducted to investigate the sorption isotherm and sorption-desorption characteristics of 2,4-D and glyphosate. Results indicated that degree of sorption of glyphosate was approximately 50 times higher than 2,4-D (K d 5 34.43 vs. 0.66 L/ Kg). The sorption of 2,4-D and glyphosate was described by linear and rate-limited processes for soil. Organic carbon content was most likely responsible for sorption behaviour of 2,4-D and glyphosate. The rapid desorption can be attributed to soft carbon fraction (humic/fluvic acid and lipids) whereas slower desorption can be responsible by hard carbon fraction (black carbon, kerogen) of soils that led to chemically nonideal behaviour (hysteresis). Sorption of 2,4-D was low due to most likely deactivation of organic carbon surfaces by excess carbonate fraction, whereas strong binding of glyphosate onto organic carbon causing high sorption behaviour.

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Within the scope of the study, the effectiveness of the experimental conditions was tested by performing a multi‐response Taguchi experimental design for the optimization of the minimum cost remediation performance with Tween 80, Methyl beta cyclodextrine (MCD) and Sodium dodecyl sulfate (SDS) from tetrachloroethylene (PCE) contaminated porous media. Tween 80, MCD and SDS were extensively used in cosmetic industry as emulsifier. Both time of remediation and cost of remediation were studied as two separate response variables in three replicate experiments conducted according to the Taguchi L9 orthogonal experimental design. In the multi‐response Taguchi analysis, the sensitivity analysis was performed by systematically changing the weights determined for two separate response variables in the calculation of total loss of quality (TNQLj). Optimum experimental conditions were determined with the help of the calculated multi‐response signal/noise (S/N) ratios (MRSN). The results show that the type of Flushing Agent is the most important factor in optimizing the remediation time and remediation cost for the removal of dense non‐aqueous phase liquid (DNAPL) PCE mass. Flushing rate is considered to be the least contributing factor. Furthermore, the results of the analysis of variance (ANOVA) showed that all parameters used in the system had a significant effect on the experimental results and the Taguchi method could explain 97.15% of the Remediation Time and 92.03% of the Remediation Cost. Afterwards, the data obtained from the experiments performed according to the experimental design were modelled using Artificial Neural Network (ANN) to estimate the remediation performance and remediation cost without performing new experiments.

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