The occurrence of micropollutants (MPs) in various streams of municipal wastewater treatment plants (WWTPs), and their fate and removal processes are discussed. The fate of MPs in WWTPs largely depends on adsorption on suspended particulates, primary and secondary sludge and dissolved organic carbon, and removal occurs due to coagulation-flocculation, and biodegradation. The log Kow (>2.5) and pKa are the dominant properties of the MPs, and the concentration, organic fraction, and surface charge of suspended particulates dictate the extent of adsorption of MPs. Most of the conventional WWTPs do not remove complex MPs by biodegradation or biotransformation effectively (kbio ≤0.0042 L/gss/h), and the removal varies widely for different compounds, as well as for the same substance, due to operational conditions such as aerobic, anaerobic, anoxic, sludge retention time (SRT), pH, redox potential, and temperature. Membrane bioreactor performs better for moderately biodegradable compounds due to the diverse nature of microorganisms as well as greater adaptability due to longer SRT. Ozone and UV-based advanced oxidation processes, membrane filtration can be used for tertiary treatment due to their high rate as well as easy implementation. Various partition coefficients and rate constants values for different MPs are also provided for design and application.

Investigation of the reversible esterification reaction between oleic acid and methanol to produce methyl oleate (biodiesel) catalyzed by Amberlyst 15 ion‐exchange resin was carried out in a simulated moving bed reactor (SMBR). SMBR performance was described both experimentally and numerically using a mathematical model under various operating conditions. The model predicted the experimental outcome reasonably well. An improved yield (56 %) and purity (42 %) of biodiesel could be achieved in an SMBR compared to a fixed‐bed reactor (31 % yield and 22 % purity) by selecting appropriate operating conditions. The effects of various process parameters such as switching time as well as feed and eluent flow rate on SMBR behaviour were also investigated systematically.

In this work, adsorption equilibrium constants, dispersion coefficients, and kinetic parameters were determined for the reversible esterification reaction of oleic acid with methanol, producing methyl oleate (biodiesel) and water. The reaction was carried out at room temperature in the presence of Amberlyst 15 resin, which acts both as an adsorbent and catalyst in an HPLC column, which served as a packed bed reactor. A quasi‐homogenous kinetic model coupled with a linear adsorption isotherm was explored. The elution profiles of the reactant and products were experimentally monitored and then compared with a mathematical model. The adsorption and kinetic parameters were determined by minimizing the error between the experimentally obtained elution curves and the model‐predicted values using the genetic algorithm optimization technique. Further experiments were conducted under varying conditions to establish the validity of the obtained model parameters. It was also found that the system is not affected by internal and external mass transfer resistances. The mathematical model predicted the experimental outcome quite accurately.

In this work, multi-objective optimisation study was performed to determine the performance improvement in a simulated moving bed reactor (SMBR) for biodiesel synthesis. The selection of the operating parameters such as switching time, liquid flow rates in various sections, as well as the length and number of columns is not straightforward in an SMBR. In most cases, conflicting requirements and constraints influence the optimal selection of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified and verified experimentally for multiple-column SMBR system. In this article, a few multi-objective optimisation problems were carried out for both existing set-up as well as at the design stage. A non-dominated sorting genetic algorithm (NSGA) was used as the optimisation tool for the optimisation study. Due to conflicting effect of process parameters, the multi-objective optimisation study resulted in non-dominated Pareto optimal solutions. It was shown that significant increase in yield and purity of biodiesel in SMBR was possible both for operating and at design stage.