# Bioremediation of Hydrocarbon-Polluted Soil: Evaluation of Different Operative Parameters
## 4 Discussion  
Many studies used the Design of Experiment (DOE) to assess the bioremediation process [5, 11, 39, 48, 49, 50]; however, the idea of testing the influence of categorical factors throughout different levels received scarce attention. In previous studies, the classical factorial models as the response surfaces methodology (RSM) or Taguchi DOE were used to evaluate bioremediation runs. Despite these methods demonstrated to be suitable for optimization, they may present limitations when the levels of the factor analyzed are constituted by categories. The categorical factor using one-way ANOVA is widely applied since it manages categorical factors. However, this method fails when more than one factor is included in the experimental array and neglects the interaction effects. The categorical multifactor implemented in the present research strikes an accurate balance between statistical robustness analysis and resource savings for the concept of avoiding analytical measurement of various parameters, usually required for the other DOE models. Instead of that, categories or labels built from the combination of interest predetermined variables should be useful especially in the early stages of bioremediation projects, where the effects of multiple ideas are tested at the same time. Furthermore, as can be noted in both tests, the DOE implemented can distinguish interactions between the factors Treatments and Time in agreement with the reported by [PERSON] et al. [35]. This particularity should be useful to evaluate the hierarchical evolution of the Treatments candidates among the different levels of time contributing to addressing the decision-making process facing the stages of the project development and the technology scale-up. Specifically, in test M, the Treatment M1 (8 WC%-120 C/N) had the lowest TPH concentration at each level of time after the first 15 days. Likewise, after 71 days M3 (12 WC%-120 C/N) was ranked second with lower TPH concentration, suggesting not only the best degradation of the treatments with the less C/N ratio but also the influence of water content in the first period of the run. These findings are consistent with the previous ones modelled by [PERSON] et al. [11] using an RSM model, confirming the accurateness of the evaluation method adopted. As commented in the results section, after the third month, the TPH concentration decreasing was negligible for all treatments. This could represent a crucial issue to estimate the times for the in situ exploitation of the technology. In test B, in all treatments, the TPH concentration decreased until 240 days, with removal percentages between 40% and 60%, values similar to the ones achieved by other authors [1, 5, 26]. The treatments order rank was B5, B6, B2, B1, B4, B3. Specifically, Treatment B5 (beef manure) was the one that reported the lowest TPH concentrations at 240 days, keeping this trend after 60 days. The means obtained for B5 presented marked statistical differences with the rest of the treatment, being the one with the mean lower limit interval under 7.0 g\(\cdot\)kg\({}^{-1}\). In contrast, B3 (sawdust) presented the worst TPH removal, keeping this trend after the 60 days, being the only treatment with the mean interval over 8.0 g\(\cdot\)kg\({}^{-1}\). Despite the rank order, the TPH means of B6, B2 and B1 do not present significative differences for a 95% confidence level. Furthermore, the differences between the levels in the factor Time evidence the evolution in the degradation process. Regarding this issue, the kinetic evaluation derived from experimental runs at the laboratory scale is useful to estimate the time to obtain the pollutant removal [26, 51].