This study reviews the available and most commonly used methods of gas deodorization. Comparing various methods of odor removal, undoubtedly biological methods of pollution degradation have an advantage over others—chemical and physical. This advantage is manifestedmainly in ecological and economic terms. The possibility of using biological methods to remove H₂S and NH₃, as the most common emitted by the municipal sector companies, was analyzed in terms of their removal efficiency. The method of bio-purification of air in biotrickling filters is more advantageous than the others, due to the high effectiveness of VOCs and odors degradation, lack of secondary pollutants, and economic aspects—it is a method competitive to the commonly used air purification method in biofilters.

This study investigates chromium removal onto modified maghemite nanoparticles in batch experiments based on a central composite design. The effect of modified maghemite nanoparticles on the adsorptive removal of chromium was quantitatively elucidated by fitting the experimental data using artificial neural network (ANN) and adaptive neuro-fuzzy interference system (ANFIS) modeling approaches. The ANN and ANFIS models, relating the inputs, i.e., pH, adsorbent dose, and initial chromium concentration to the output, i.e., chromium removal efficiency (RE), were developed by comparing the predicted value with that of the experimental values. The RE of chromium ranged from 49.58% to 92.72% under the influence of varying pH (i.e., 2.6–9.4) and adsorbent dose, i.e., 0.8 g/L to 9.2 g/L. The developed ANN model fits the experimental data exceptionally well with correlation coefficients of 1.000 and 0.997 for training and testing, respectively. In addition, the Pearson’s Chi-square measure (χ²) of 0.0004 and 0.0673 for the ANN and ANFIS models, respectively, indicated the superiority of ANN over ANFIS. However, a small discrepancy in the predictability of the ANFIS model was observed owing to the fuzzy rule-based complexity and overtraining of data. Thus, the developed models can be used for the online prediction of RE onto synthesized maghemite nanoparticles with different sets of input parameters and it can also predict the operational errors in the system.

The potential implementation of Envifer^®, a commercial product containing potassium ferrate (40.1% K₂FeO₄), for the purification of highly contaminated tannery wastewater from leather dyeing processes was proposed. The employment of the Taguchi method for optimization of experiments allowed the discoloration (98.4%), chemical oxygen demand (77.2%), total organic carbon (75.7%), and suspended solids (96.9%) values to be lowered using 1.200 g/L K₂FeO₄ at pH 3 within 9 min. The application of the central composite design (CCD) and the response surface methodology (RSM) with the use of 1.400 g/L K₂FeO₄ at pH 4.5 diminished the discoloration, the chemical oxygen demand, the total organic carbon, and suspended solids within 9 min. The Taguchi method is suitable for the initial implementation, while the RSM is superior for the extended optimization of wastewater treatment processes.